Energy Recovery

ENERGY RECOVERY

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ENERGY RECOVERY

EDGARD DUBOIS AND

ARTHUR MERCIER EDITORS

Nova Science Publishers, Inc. New York

Copyright © 2009 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com

NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA DuBois, Edgard. Energy recovery / Edgard DuBois and Arthur Mercier. p. cm. Includes index. ISBN 978-1-61728-402-1 (E-Book) 1. Waste products as fuel. I. Mercier, Arthur. II. Title. TP360.D82 2009 662'.87--dc22

2009024627

Published by Nova Science Publishers, Inc. New York

CONTENTS

Preface vii Chapter 1 Biogas Recovery from Landfills 1

Sherien A. Elagroudy and Mostafa A. Warith Chapter 2 Landfill Gas: Generation Models and Energy Recovery 69

Lidia Lombardi Chapter 3 Energy and Material Recovery from Biomass: The Biorefinery

Approach. Concept Overview and Environmental Evaluation 97 Francesco Cherubini and Gerfried Jungmeier

Chapter 4 Pinch Technology for Waste Heat Recovery Applications in Oil Industry 141 Mahmoud Bahy Noureldin

Chapter 5 Treatment of Secondary Sludge for Energy Recovery 187 Chunbao (Charles) Xu and Jody Lancaster

Chapter 6 Energy Recovery from Waste: Comparison of different Technology Combinations 213 Lidia Lombardi and Andrea Corti

Chapter 7 Energy Recovery from Waste Incineration: Linking the Systems of Energy and Waste Management 229 Kristina Holmgren

Chapter 8 Experimental Analysis of a Combined Recovery System 253 R. Herrero Martín

Chapter 9 Energy Recovery Systems from Industrial Plant Waste: Planning of an Industrial Park Located in the South of Italy 289 Silvana Kühtz, Francesca Intini, Sara Bellini and Giovanna Matarrese

Index 311

PREFACE Energy recovery occurs when the energy that is released from a resource recovery

process (i.e., pyrolysis/gasification) is used for another purpose such as to generate steam, fuel or electricity generation. This book examines the energy recovery technologies which use landfill gas to produce energy directly. An overview of a variety of secondary sludge post treatment methods for energy recovery is given, including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. The several routes that energy recovery can follow from waste are looked at as well, of which the most common is waste direct combustion associated with conventional energy recovery in a steam turbine cycle. Energy recovery in air conditioning systems to promote energy saving and improve environmental quality is also explored in this book.

Chapter 1 - Disposal of municipal wastes can produce emissions of most of the important greenhouse gases (GHG). Solid wastes can be disposed of through landfilling, recycling, incineration or waste-to-energy. This chapter will deal with emissions resulting from landfilling of solid waste. The most important gas produced in this source category is methane (CH4). Approximately 5-20 per cent (IPCC 1992) of annual global anthropogenic CH4 produced and released into the atmosphere is a by-product of the anaerobic decomposition of waste. A major source of this type of CH4 production is solid waste disposal to land. In landfills, methanogenic bacteria break down organic matter in the waste to produce CH4. In addition to CH4, solid waste disposal sites can also produce substantial amounts of carbon dioxide (CO2) and non-methane volatile organic compounds (NMVOC).

The gases produced in solid waste disposal sites, particularly CH4, can be a local environmental hazard if precautions are not taken to prevent uncontrolled emissions or migration into surrounding land. Landfill gas is known to be produced both in managed “landfill” and “open dump” sites. Both are considered here as solid waste disposal sites (SWDSs). Gas can migrate from SWDSs either laterally or by venting to atmosphere, causing vegetation damage and unpleasant odors at low concentrations, while at concentrations of 5-15 per cent in air, the gas may form explosive mixtures.

With the recognition of the formation of landfill gas and its associated hazards, and the potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and

Edgard DuBois and Arthur Mercier viii

a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site.

This chapter will describe the processes that result in gas generation from SWDSs and the factors which affect the amount of CH4 produced. It will then describe two methodologies for estimating CH4 emissions from SWDSs. One of these methods is a default base method which all countries can use to estimate CH4 emissions from different types of SWDSs. It is recommended that countries which have adequate data also estimate their emissions using the second method presented. Finally, this section discusses sources of uncertainty associated with any estimates of CH4 emissions from SWDSs, in particular the availability and quality of data required.

Chapter 2 - In this chapter different landfill gas production mathematical models have been analysed, implemented and compared among themselves and with data collected from existing landfills. These models will be presented in the chapter. One of these models has been selected for application to some study cases. The selected model is based on first-order decay equation and considers as basic inputs the years of landfill operation, the amount of municipal solid waste landfilled per year, the municipal solid waste component characterisation and biodegradability. Three different behaviours, in reference to biodegradation rate, have been considered dividing the material categories into rapidly, moderately and slowly biodegradable. The model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system. In particular, reciprocating engines were considered for energy recovery purposes. The landfill gas energy recovery by means of reciprocating engines is a quite widespread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue. For this reason, the selection of an appropriate combination of engines has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions.

Further, in order to investigate the management possibilities to enhance energy recovery, the behaviour of a landfill where leachate is recirculated was observed, recording a more concentrated landfill gas production in a shorter time than in conventional landfills - and reproduced by means of adapting the landfill gas production model. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission.

Chapter 3 - A great fraction of worldwide energy carriers and material products come from fossil fuel refinery. Because of the on-going price increase of fossil resources, the uncertain availability, the environmental concerns and the fact that they are not a renewable resource, the feasibility of their exploitation is predicted to decrease in the near future. Therefore, alternative solutions able to reduce the consumption of fossil fuels should be promoted. Electricity and heat can be provided by a variety of renewable alternatives (wind,

Preface ix

sun, water, biomass), while the fossil resource alternative for production of fuels and chemicals can be just biomass, the only C-rich material source available on the Earth, besides fossils.

The replacement of oil with biomass as raw material for fuel and chemical production leads to the development of “biorefinery”, a relatively young concept in the scientific literature. In biorefinery, almost all the types of biomass feedstock can be converted to different classes of biofuels and chemicals through jointly applied conversion technologies. This chapter describes the emerging biorefinery concept and provides an overview of the most important biomass sources, conversion technologies and platforms (or intermediates). The advantages of biorefinery systems over conventional fossil systems are outlined by means of Life Cycle Assessment (LCA): in the second half of this chapter, a LCA of a biorefinery system based on a lignocellulosic feedstock (e.g. wood industrial residues) and producing bioethanol and methyltetrahydrofuran (MTHF) as transportation biofuels, furan resins, fumaric acid and oxygen as chemicals and hydrogen, biomethane, electricity and heat as further energy carriers, is reported. The biorefinery system is compared with a reference system based on fossil sources. Results focus on greenhouse gas (GHG) and energy balances and estimate the possible GHG and fossil energy savings. System performances are also investigated with calculations of product yields and mass, energy, exergy and C conversion efficiencies. Since the biorefinery system co-produces many high value products, an allocation issue must be addressed. Different allocation procedures (substitution method, and energy, exergy, economic allocation) are therefore used and final results compared. The evaluation of the environmental performances reveals that relevant environmental benefits can be gained with a shift from oil refinery to biorefinery: almost 89% of GHG emissions and 96% of fossil energy demand can be saved.

Chapter 4 - This chapter addresses the problem of waste heat recovery via presenting an introduction to the pinch technology and two industrial applications of heat integration for waste heat recovery in oil and gas business. Pinch technology, after almost three decades of its emanation in the late seventies for a reason or another, is still the most widely used method for energy integration in oil industry.

The chapter comes into two parts; the first part introduces some aspects of Pinch technology in brief. Pinch technology is now well documented in several literatures and the refernces 1 to 4 at the end of this chapter are only few main examples. In this part, authors will show how authors can use pinch technology for energy utility targeting, selection of utility mix and heat exchanger network synthesis using pinch design method [1, 2, 3 and 4]. The second part introduces two important applications for heat integration in oil industry [5]. The first application is showing the effect of heat integration on both energy consumption and GHG emission reduction in an oil-gas separation facility, and in the second application an evolutionary approach to crude distillation pre-heat train design is introduced.

Chapter 5 - Primary and secondary sludges are produced as a result of primary and secondary wastewater treatment in municipal wastewater plant or pulp and paper mills. Sludge disposal has become a worldwide problem for many reasons including rapidly shrinking landfill space, increased environmental awareness, more stringent environmental standards governing the disposal of sludge, and dewatering challenges. Unlike the primary sludge, the secondary sludge as byproduct of the biological treatment is far more difficult to dewater and to be disposed. Secondary sludge waste management issues are a continuing challenge. This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. In this chapter, authors have overviewed a variety of secondary sludge post treatment methods for energy recovery,

Edgard DuBois and Arthur Mercier x

including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. A critical comparison between these methods is presented with respect to their net energy efficiencies. The advantages and drawbacks of each treatment option are also highlighted in this chapter.

Chapter 6 - Energy recovery from waste can follow several routes. The most common one is waste direct combustion associated with conventional energy recovery in a steam turbine cycle. The combustion can be applied directly to Municipal Solid Waste or can be applied to a stream of selected waste obtained by means of mechanical sorting of Municipal Solid Waste, using several technologies for the combustion, the most common of which is mobile grate combustor.

Besides the direct combustion of waste, alternative possibilities for thermal treatment are gasification and pyrolysis. These processes require being fed by a homogeneous combustible fraction obtained by mechanical sorting and supply as output one or more combustible streams, available for energy recovery.

When Municipal Solid Waste mechanical sorting is applied, besides the combustible fraction stream, a humid fraction is also obtained, characterised by a high presence of organic biodegradable fraction. At present the fate for this stream is biological aerobic stabilisation, but another option, to push energy recovery also from this stream, is biological anaerobic digestion, which can be applied through different technologies (wet and dry digestion). Through this process a biogas with elevated content of methane can be produced and supplied to engines for energy recovery.

The above-mentioned technologies can be combined in several schemes to optimise the overall energy recovery. The combination of schemes will be analysed in this chapter in reference to a study case characterised by an average waste material composition. The comparison will be carried out using some indicators of the overall energy recovery for each scheme.

Chapter 7 - Energy recovery from waste incineration has a double function as a waste treatment method and a supplier of electricity and/or heat. Waste incineration thereby links the systems of waste management and energy. This chapter addresses the importance of taking this into consideration when e.g. making investment decisions or designing policy instruments. The design of two policy instruments will be described as examples of the conflicting goals in the two systems. A conflict is also that increased waste incineration can decrease production of combined heat and power in the district heating systems. Since policy instruments in Sweden are dependent on the common legislation of the European Union this will be addressed, together with trading in waste and electricity and how this impacts waste incineration in Sweden. Conflicts between the internal market in the European Union and waste management goals are shown. When making investment decisions, various models are often used as decision support tools. Some models for assessing waste incineration/ management are therefore described together with strengths and weaknesses when dealing with the dual function of waste incineration.

Chapter 8 - The present work is found in the field of energy recovery in air conditioning systems to promote energy saving and improve environmental quality. Experimental research has been carried out whose aim is the characterization of combined recovery equipment, consisting of a ceramic semi-indirect evaporative cooler and a heat pipe device to recover energy at low temperature in air conditioning systems. For characterization purposes, a design of experiment (DOE) and an analysis of variance (ANOVA) were applied with the aim of

Preface xi

better understanding the energy behaviour of the combined device. The combined system built allows a feasible energy exchange between the supply airstream and the return one, improving the operation in air-conditioning systems. It is a new alternative device for use as a recovery system. The configuration chosen (crossed flow) is the most adequate from an operational point of view. The characterization of the system was carried out by employing experimental design methodology. A factorial design was performed by analysing how the factors used affect the characteristics analyzed. The contributions of the single factors and their interactions were presented by carrying out a variance analysis. The superiority of the evaporative cooling device under the operating conditions was clearly shown. An estimation of the energy saved by the combined system was carried out, showing the possibilities of implementing this solution to save energy and also to improve the indoor air quality by means of increasing the ventilation rates.

Chapter 9 - In this chapter, authors compare environmental and technological aspects of some innovative energy recovery systems from industrial waste. The authors present the results of a research study that authors are conducting on an Italian firm that produces polyethylene terephthalate (PET) supports for waterproof membranes from plastic bottles. For this firm (and all of the firms in the same industrial park), the waste represents only an undesired cost rather than a potential energy source. The authors first compared a traditional thermal waste treatment with a molecular dissociator and then with a specific gasifier. All three technologies can be fed with basically every type of waste, and can produce electric and/or thermal energy. In particular, the latter two produce syngas that can be burned after depuration to produce energy. A cost-benefit analysis is then carried out to plan how the whole industrial park can use the industrial waste to produce the energy it needs, with economic and environmental benefits for all.

In: Energy Recovery ISBN: 978-1-60741-065-2 Editors: Edgard DuBois and Arthur Mercier © 2009 Nova Science Publishers, Inc.

Chapter 1

BIOGAS RECOVERY FROM LANDFILLS

1Sherien A. Elagroudy and 2Mostafa A. Warith* 1Civil Engineering Department, Ain Shams University Univeristy,

13 El-Makreezy Street, Manshiett Elbakry, Heliopolis, Cairo, Egypt, 11341 2Ryerson Polytechnic University, Civil Engineering Department,

350 Victoria Street, Toronto, ON, Canada, M5B 2K3,

ABSTRACT

Disposal of municipal wastes can produce emissions of most of the important greenhouse gases (GHG). Solid wastes can be disposed of through landfilling, recycling, incineration or waste-to-energy. This chapter will deal with emissions resulting from landfilling of solid waste. The most important gas produced in this source category is methane (CH4). Approximately 5-20 per cent (IPCC 1992) of annual global anthropogenic CH4 produced and released into the atmosphere is a by-product of the anaerobic decomposition of waste. A major source of this type of CH4 production is solid waste disposal to land. In landfills, methanogenic bacteria break down organic matter in the waste to produce CH4. In addition to CH4, solid waste disposal sites can also produce substantial amounts of carbon dioxide (CO2) and non-methane volatile organic compounds (NMVOC).

The gases produced in solid waste disposal sites, particularly CH4, can be a local environmental hazard if precautions are not taken to prevent uncontrolled emissions or migration into surrounding land. Landfill gas is known to be produced both in managed “landfill” and “open dump” sites. Both are considered here as solid waste disposal sites (SWDSs). Gas can migrate from SWDSs either laterally or by venting to atmosphere, causing vegetation damage and unpleasant odors at low concentrations, while at concentrations of 5-15 per cent in air, the gas may form explosive mixtures.

With the recognition of the formation of landfill gas and its associated hazards, and the potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the

* J. Patrick A. Hettiaratchi, PhD, PEng, Professor of Environmental Engineering, Associate Head of Undergraduate

Studies, Department of Civil Engineering, and Center for Environmental Engineering Research & Education (CEERE), University of Calgary, Calgary, Alberta, Canada, Tel. 403-220-5503; Fax. 403-282-7026, [email protected]

Sherien A. Elagroudy and Mostafa A. Warith 2

landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site.

This chapter will describe the processes that result in gas generation from SWDSs and the factors which affect the amount of CH4 produced. It will then describe two methodologies for estimating CH4 emissions from SWDSs. One of these methods is a default base method which all countries can use to estimate CH4 emissions from different types of SWDSs. It is recommended that countries which have adequate data also estimate their emissions using the second method presented. Finally, this section discusses sources of uncertainty associated with any estimates of CH4 emissions from SWDSs, in particular the availability and quality of data required.

I. INTRODUCTION Throughout Europe and the United States, there is a strong reliance on disposing of waste

in landfills. Furthermore, in many developing countries, conditions for waste disposal are still rudimentary. In 1997, for instance, 99% (around 90,000 tons per day) of Brazil's collected waste was being landfilled or simply dumped. Each person in the United Staes generates about 4.5 pounds of waste per day, which is nearly 1 ton per year. Again, most of this waste is deposited in municipal solid waste (MSW) landfills. As MSW decomposes, it produces a blend of several gases, including methane (about 50%).

Landfilling is the oldest and most widely practiced waste disposal option. Modern landfill sites have developed from uncontrolled dumping sites to be an advanced treatment and disposal option designed and managed as engineering projects. In addition, modern purpose-built landfill sites normally incorporate a system for the extraction of landfill gas (arising from the decomposition of biodegradable wastes), from which energy can be recovered. The types of wastes suitable for landfilling include biodegradable wastes, aqueous liquids in limited amounts, inert wastes, and certain special wastes that would not pose toxic threats. Wastes that are generally considered unsuitable for landfilling include volatile liquids or solvents, wastes that would introduce unacceptable contamination into the leachate, and wastes that would interfere with the biological processes in a landfill site.

More recently, increasing attention has focused on the role of CH4 in global atmospheric change. Methane from SWDSs contributes a significant proportion of annual global CH4 emissions, although the estimation is subject to a great deal of uncertainty. Estimates of global CH4 emissions from SWDSs range from less than 20 to 70 Tg/yr (Bingemer and Crutzen 1987; US EPA 1994), or about 5 per cent to 20 per cent of the total estimated emissions of 375 Tg/yr (IPCC 1996) from anthropogenic sources globally.

There are eight sections in this chapter. Section 2 discusses environmental regulations as they pertain to landfill gas emissions. Regulations addressed in this section include the European Landfill Directive [1999/31/EC], Resource Conservation and Recovery Act (RCRA) solid and hazardous waste management requirements, Clean Air Act (CAA) requirements, and Clean Water Act (CWA) requirements associated with landfill emissions. An overview of the different types of bioreactor landfills as a development to sanitary landfills is provided in Section 3 along with bioreactor features and advantages. Section 4

Biogas Recovery from Landfills 3

provides a broad overview on Landfill gas (LFG) characteristics, composition, LFG production and methods of enhancement, and gas yield. It also discusses gas-generation mechanisms and gas-transport mechanisms and factors affecting both mechanisms.

Gases generated in the landfill will move throughout the mass of waste in addition to movement or migration out of the site. Section 5 focuses on LFG movement and generation and LFG monitoring programs. Landfill gas may form an explosive mixture when it combines with air in certain proportions, LFG hazards including explosion, asphyxiation hazards and odor are also discussed in this section.

Section 6 discusses LFG generation models. Several models are available for estimating the LFG generation rate using site-specific input parameters. These models vary widely, not only in the assumptions that they make, but also in their complexity, and in the amount of data they require. The LandGEM model is one of these models and was developed by the US Environmental Protection Agency to estimate landfill gas emissions and to determine regulatory applicability to CAA requirements. There are other LFG emission models in use by industry that also work very well. The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of CH4 emissions from the landfills is based on First-Order decay (FOD) method. These 2 models are explained in details in this section. LFG regression models using site-specific data are also discussed in this section along with mathematical models.

Section 7 provides an overview of landfill gas energy recovery system. The energy recovery technology is based around the gas collection system and the pre-treatment and power generation technology. Each of those three systems is explained separately in details in this section.

Section 8 covers the Calgary biocell as a full-scale case study that is constructed in Calgary, Canada. It is a unique facility where the three processes, anaerobic bioreactor, aerobic bioreactor and mining are sequentially applied in one cell. The stages of operation of the cell and the LFG data collected over 2 years from the cell are provided in this section.

Anaerobic decomposition of organic solid waste in the landfill environment produces landfill gas (LFG). LFG mainly consists of methane and carbon dioxide, both of which are odorless. Trace constituents of other volatiles, often malodorous or toxic gases, are also found in LFG. LFG can migrate through soil into structures located on or near landfills. Since methane presents a fire or explosive threat, LFG must be controlled to protect property, and public health and safety. Also, many jurisdictions require landfill owners/operators to reduce reactive organic gas emissions to improve regional air quality. Thus, engineered solutions are needed to efficiently and safely monitor, collect, and process landfill gas. As noted, a positive side to LFG control is energy recovery. Today's technology allows a landfill owner/operator to recovery the energy in LFG while reducing gas emissions. Revenue from the sale of LFG or electricity generated using LFG as a fuel can offset costs for landfill environmental compliance and/or closure.

II. REGULATORY CONSIDERATIONS This section discusses environmental regulations as they pertain to landfill gas emissions.

Regulations addressed in this section include the European Landfill Directive [1999/31/EC], Resource Conservation and Recovery Act (RCRA) solid and hazardous waste management requirements, Clean Air Act (CAA) requirements, and Clean Water Act (CWA) requirements


associated with landfill emissions. Many of the regulations discussed below apply to currently operating or recently closed landfills and may not be appropriate for landfills that stopped receiving wastes prior to 1987. It is important that personnel know the regulatory framework under which the LFG control is being done (e.g., Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) remediation, RCRA Corrective Action, etc.) in order to determine which, if any of the following requirements must be met.

The discussion of applicable regulations and legal requirements in this section is only meant to make the reader aware of some of the many requirements that may potentially apply to landfill gas emissions and disposal of condensate. This chapter is not intended to stand in place of any applicable law, regulation, or standard and may not reflect the current standards embodied in law and regulation. Statutes and regulations are the controlling rule of law and should always be consulted to determine how they apply to a particular set of circumstances to assure compliance before action is taken.

Regulations affecting LFG management are addressed under various legislations including:

• Landfill Directive 1999/31/EC • The RCRA which regulates solid and hazardous waste management such as the

landfill itself. • The CAA which regulates air emissions. • The CWA which regulates discharges of water such as LFG condensate and storm

water runoff. A brief summary of these regulations applicable is presented in the following section.

A. U Landfill Directive 1999/31/EC The EU Landfill Directive [1999/31/EC] became law on 16 July 1999 after a protracted

drafting process. It was published in the Official Journal of the European Communities on the 16th July 1999. Member States were required to bring into force the laws, regulations and administrative provisions necessary to comply with the Landfill Directive not later than two years after its entry into force i.e. the 16th July 2001.

The aim of the Directive is "by way of stringent operational and technical requirements on the waste and landfills, to provide for measures, procedures and guidance to prevent, or reduce as far as possible, negative effects on the environment, in particular the pollution of surface water, groundwater, soil and air, and on the global environment, including the greenhouse effect, as well as any resulting risk to human health, from landfilling of waste, during the whole life-cycle of the landfill." (Waste Landfill Directive, 1999)

The Landfill Directive sets requirements for the authorization, design, operation, closure and aftercare of landfills. The reduction of the biodegradable fraction of municipal waste going for landfill disposal is given specific targets in the Landfill Directive. Some wastes may no longer be accepted in landfills and only wastes that fulfill certain acceptance criteria may be disposed of in the appropriate class of landfill. In addition to the Landfill Directive, the


Council Decision 2003/33/EC established the criteria and procedures for the acceptance of waste in landfills (commonly referred to as Waste Acceptance Criteria (WAC)).

The Directive encompasses the requirements of Articles 3 and 4 of 75/442/EEC (The Framework Directive). It also covers the technical requirements for landfills covered by the IPPC Directive (Council Directive 96/61/EC). The Directive has 19 Articles and 3 Annexes covering General Requirements, WAC, and Control and Monitoring. Central to the Directive is the requirement (Article 5) that all Member States shall introduce measures to reduce the quantities of biodegradable material going to landfill, to 35% of 1995 levels by 2016. Up to 4 years' derogation from this is possible for countries currently landfilling more than 80% of wastes. The Directive also requires Member States to set up a national strategy for the implementation of these targets.

B. RCRA Regulations Under RCRA, if LFG is emitted or condensate is treated and/or disposed of, RCRA

requirements may have to be met. Primary RCRA requirements pertaining to LFG emission and condensate disposal are found in the following regulations:

• 40 CFR Part 258 [regulations for LFG emissions from MSW (non-hazardous)

landfills] • 40 CFR Parts 260-261 [regulations for characterization and disposal of condensate] • 40 CFR Part 262 [regulations pertaining to generator requirements] • 40 CFR Part 268 [regulations for land disposal restrictions]

C. CAA Regulations Since passage of the Federal CAA in 1970, many rules and regulations have been

adopted that could potentially affect LFG operations. The applicability of these rules and regulations are governed by specific factors such as the implementation schedule of the rule, size of the facility, the equipment and type of operations conducted at the site, and the emissions from these operations. Personnel need to be familiar with the specific requirements of each regulation prior to deciding whether or not the requirements apply to their project. Potentially applicable CAA regulations include:

• New Source Performance Standards (NSPS) found at 40 CFR Part 60 • National Emission Standards for Hazardous Air Pollutants found at 40 CFR 63 • Title V Operating Permits found at 40 CFR Part 70 • State and local air quality regulations The Environmental Protection Agency (EPA) designed the Title V operating permit

program as a central mechanism to regulate emissions, monitoring data needs, compliance schedules, fee payments, and other conditions associated with the issuance, compliance and enforcement of operating permits. Personnel involved in designing LFG control systems


should ensure that the customer is made aware of calculated LFG emissions and what control devices will be used to control them. This information is important to the customer who is ultimately responsible for determining the need to obtain a Title V operating permit or to revise an existing permit. Any questions regarding the need to obtain an operating permit for the LFG control system should be discussed with the customer and the project team.

D. CWA Regulations Under the CWA, if LFG condensate is disposed of by treatment and effluent discharge to

Waters of the United States, discharge permits may be required and effluent concentrations/limits may be required to meet a state's water quality standards. Effluent analyses required for all discharge permits can include:

• Biochemical Oxygen Demand (BOD) • Chemical Oxygen Demand (COD) • Total Organic Carbon (TOC) • Total Suspended Solids (TSS) • Ammonia • Temperature • pH • Flow Response actions taken under CERCLA are not required to obtain discharge permits.

However, substantive requirements such as numerical discharge limits may still have to be established and met at these sites, especially when condensate is discharged via a point source to Waters of the U.S.

Other analyses may be required if other pollutants are expected to be present. If the condensate is disposed of by indirect discharge through a publicly owned treatment works (POTW), sewer effluent conditions will be imposed by the local POTW as regulated by local ordinances or federal requirements.

III. SANITARY AND BIOREACTOR LANDFILLS

A. Development of Sanitary Landfills In the past, a landfill often represented little more than an open hole or mash where refuse

was dumped. The refuse was often not covered properly, sometimes it was burned for volume reduction, and there was little effort to control storm water runoff and downward migration of water that had come into contact with the refuse (Barlaz 1997). With the implementation of increasingly stringent regulations, landfills have become highly engineered facilities with sophisticated containment systems, environmental monitoring, and improved operational practices.


As a generality, a typical dry landfill has an impermeable bottom liner, the wastes are delivered to the landfill, spread out, compacted and covered at the end of the day with a thin layer of soil, until a planned depth is reached, then the waste is covered with an impermeable cap. The environmental barriers such as landfill liners and covers exclude moisture that is essential to waste biodegradation. Consequently, wastes are contained in a “dry tomb” and remain intact for long periods of time ranging from 30 to 200 years, possibly in excess of the life of the landfill barriers and covers. Liner failure could happen in conventional dry landfill sometime in future, which can cause serious groundwater and surface water contamination (Warith 2003).

Nowadays, siting new landfills has been very difficult and costly not only because landfills can threaten the environment, but also because the public opposition, this often called the NIMBY, or not in my back yard, syndrome. Therefore, the condition appeals to investigators to make efforts to make landfills more economically sound and environmentally friendly (Stessel and Murphy 1992).

Today, the “bioreactor landfill” is one idea that has gained significant attention. A bioreactor landfill is a sanitary landfill that uses enhanced microbiological processes to transform and stabilize the readily and moderately decomposable organic waste constituents within 5 to 10 years of bioreactor process implementation. The bioreactor landfill significantly increases the extent of organic waste decomposition, conversion rates and process effectiveness over what would otherwise occur within the landfill (Pacey et al. 1999). The “bioreactor landfill” provides control and process optimization, primarily through the addition of leachate or other liquid amendments, the addition of sewage sludge or other amendments, temperature control, and nutrient supplementation (Reinhart et al. 2002). Beyond that, bioreactor landfill operation may involve the addition of air. Based on waste biodegradation mechanisms, different kinds of “bioreactor landfills” including anaerobic bioreactors, aerobic bioreactors, and aerobic-anaerobic (hybrid) bioreactors have been constructed and operated worldwide. According to the survey conducted by the Solid Waste Association of North America (SWANA) in 1997, there were over 130 leachate recirculation landfills in USA (Gou and Guzzone 1997; Reinhart et al. 2002).

Generally, there are four advantages for employing bioreactor landfill technology comparing to conventional dry landfills: (1) contain and treat leachate, (2) rapidly recover air space, (3) accelerate waste stabilization and avoid long-term monitoring and maintenance and delay siting of a new landfill, and (4) make more potential benefits from increased methane generation in anaerobic bioreactor landfill. For aerobic bioreactor landfill, there are three other advantages: (1) significant increase in the biodegradation rate of the MSW over anaerobic processes, (2) a reduction in the volume of leachate, and (3) significantly reduced methane generation and “anaerobic” odors. However, Costs for continuous supply of air are excessively high for municipal solid waste treatment (Hanashima, 1999).

B. Bioreactor Landfills There are three types of bioreactor technology: 1. Anaerobic Bioreactor Landfills 2. Aerobic Bioreactor Landfills 3. Aerobic-Anaerobic Bioreactor Landfills


1. Anaerobic bioreactor landfills The Anaerobic Bioreactor seeks to accelerate the degradation of waste by optimizing

conditions for anaerobic bacteria. In landfills, consortia of anaerobic bacteria are responsible for the conversion of organic wastes into organic acids and ultimately into methane and carbon dioxide. Anaerobic conditions develop naturally in nearly all landfills without any intervention. The waste in typical landfills contains between 10 and 25 percent water. It is generally accepted that to optimize anaerobic degradation moisture conditions at or near field capacity, or about 35 to 45 percent moisture, are required. Moisture is typically added in the form of leachate through a variety of delivery systems.

However, the amount of leachate produced at many sites is insufficient to achieve optimal moisture conditions in the waste. Additional sources of moisture such as sewage sludge, storm water, and other non-hazardous liquid wastes may therefore be necessary to augment the leachate available for recirculation. As the moisture content of the waste approaches optimal levels, the rate of waste degradation increases, this in turn leads to an increase in the amount of landfill gas produced. Also observed is an increase in the density of the waste. While the rate of gas production in an anaerobic bioreactor can be twice as high as a normal landfill, the duration of gas production is significantly shorter. Because of this accelerated production, gas collection systems at bioreactor landfills must be capable of handling a higher peak volume but need do so for a shorter period of time. The anaerobic biodegradation of MSW follows three sequenced biochemical reactions involving three different groups of anaerobic bacteria which are: (1) Fermentative and hydrolystic bacteria, (2) Acidogenic bacteria and (3) Methanogenic bacteria. In the anaerobic stage, there are four steps involved in the bacteria groups to convert waste into biogas (CH4, CO2) as end products, and organic acids as intermediate products. The four steps are hydrolysis, acidogenesis, acetogenesis and methanogenesis (Jin, 2005).

Figure 1 shows a cut-away view of an anaerobic bioreactor with elevated levels of ammonium in the leachate. Leachate is removed via pipes from the bottom of the landfill and piped to an on-site biological leachate treatment facility. The treated leachate and other liquids are then reinjected into the landfill. At the same time, gas generated by the decomposing waste rises through the landfill, and is collected by pipes within the waste and on top of the landfill. The landfill gas that is collected is used to generate energy. Groundwater monitoring occurs at monitoring wells situated around the perimeter of the landfill (U.S EPA 2004).

2. Aerobic bioreactor landfills

The Aerobic Bioreactor seeks to accelerate waste degradation by optimizing conditions

for aerobes. Aerobes are organisms that require oxygen for cellular respiration. In aerobic respiration, energy is derived from organic molecules in a process that consumes oxygen and produces carbon dioxide. Aerobes require sufficient water to function just as anaerobes do. However, aerobic organisms can grow more quickly than anaerobes because aerobic respiration is more efficient at generating energy than anaerobic respiration. One consequence of this is that aerobic degradation can proceed faster than anaerobic degradation. Another consequence is that aerobic respiration can generate large amounts of metabolic heat, which requires significant quantities of water. In landfills aerobic activity is promoted through


injection of air or oxygen into the waste mass. It is also possible to apply a vacuum to the waste mass and pull air in through a permeable cap. Liquids are typically added through leachate recirculation, with the need for additional sources of moisture even more acute than for anaerobic reactors. The aerobic process does not generate methane.

Figure 2 shows a cut-away view of an aerobic bioreactor. Leachate is removed from the bottom layer of the landfill and piped to a liquids storage tank. From the tank, the leachate is piped across the top layer, where it is released to filter down through the landfill to be collected again. A blower forces air into the waste mass through vertical or horizontal wells located in the top layer of the landfill. Groundwater monitoring occurs at wells situated around the perimeter of the landfill (U.S EPA 2004).

Figure 1. Anaerobic Bioreactor Landfill (U.S EPA 2004)

Figure 2. Aerobic Bioreactor Landfill (U.S EPA 2004)


3. Aerobic-anaerobic bioreactor landfills The Aerobic-Anaerobic Bioreactor is designed to accelerate waste degradation by

combining attributes of the aerobic and anaerobic bioreactors. The objective of the sequential aerobic-anaerobic treatment is to cause the rapid biodegradation of food and other easily degradable waste in the aerobic stage in order to reduce the production of organic acids in the anaerobic stage resulting in the earlier onset of methanogenesis.

In this system the uppermost lift or layer of waste is aerated, while the lift immediately below it receives liquids. Landfill gas is extracted from each lift below the lift receiving liquids. Horizontal wells that are installed in each lift during landfill construction are used convey the air, liquids, and landfill gas. Figure 3 shows a cut-away view of an aerobic-anaerobic bioreactor.

The principle advantage of the hybrid approach is that it combines the operational simplicity of the anaerobic process with the treatment efficiency of the aerobic process. Added benefits include an expanded potential for destruction of volatile organic compounds in the waste mass.

C. Features Unique to Bioreactor Landfills The bioreactor accelerates the decomposition and stabilization of waste. At a minimum,

leachate is injected into the bioreactor to stimulate the natural biodegradation process. Bioreactors often need other liquids such as stormwater, wastewater, and wastewater treatment plant sludge to supplement leachate to enhance the microbiological process by purposeful control of the moisture content and differs from a landfill that simple recirculates leachate for liquids management. Landfills that simply recirculate leachate may not necessarily operate as optimized bioreactors.

Figure 3. Aerobic-Anaerobic Bioreactor Landfill (U.S EPA 2004)


Moisture content is the single most important factor that promotes the accelerated decomposition. The bioreactor technology relies on maintaining optimal moisture content near field capacity (approximately 35 to 65%) and adds liquids when it is necessary to maintain that percentage. The moisture content, combined with the biological action of naturally occurring microbes decomposes the waste. The microbes can be either aerobic or anaerobic. A side effect of the bioreactor is that it produces landfill gas (LFG) such as methane in an anaerobic unit at an earlier stage in the landfill’s life and at an overall much higher rate of generation than traditional landfills.

D. Potential Advantages of Bioreactor Landfills Decomposition and biological stabilization of the waste in a bioreactor landfill can occur

in a much shorter time frame than occurs in a traditional “dry tomb” landfill providing a potential decrease in long-term environmental risks and landfill operating and post-closure costs. Potential advantages of bioreactors include:

• Decomposition and biological stabilization in years vs. decades in “dry tombs” • Lower waste toxicity and mobility due to both aerobic and anaerobic conditions • Reduced leachate disposal costs • A 15 to 30 percent gain in landfill space due to an increase in density of waste mass • Significant increased LFG generation that, when captured, can be used for energy use

onsite or sold • Reduced post-closure care Research has shown that municipal solid waste can be rapidly degraded and made less

hazardous (due to degradation of organics and the sequestration of inorganics) by enhancing and controlling the moisture within the landfill under aerobic and/or anaerobic conditions. Leachate quality in a bioreactor rapidly improves which leads to reduced leachate disposal costs. Landfill volume may also decrease with the recovered airspace offering landfill operators an extension for the operating life of the landfill.

LFG emitted by a bioreactor landfill consists primarily of methane and carbon dioxide plus lesser amounts of volatile organic chemicals and/or hazardous air pollutants. Research indicates that the operation of a bioreactor may generate LFG earlier in the process and at a higher rate than the traditional landfill. The bioreactor LFG is also generated over a shorter period of time because the LFG emissions decline as the accelerated decomposition process depletes the source waste faster than in a traditional landfill. The net result appears to be that the bioreactor produces more LFG overall than the traditional landfill does.

Some studies indicate that the bioreactor increases the feasibility for cost effective LFG recovery, which in turn would reduce fugitive emissions. This presents an opportunity for beneficial reuse of bioreactor LFG in energy recovery projects. Currently, the use of LFG (in traditional and bioreactor landfills) for energy applications is only about 10 percent of its potential use. The US Department of Energy estimates that if the controlled bioreactor technology were applied to 50 percent of the waste currently being landfilled, it could provide over 270 billion cubic feet of methane a year, which is equivalent to one percent of US electrical needs.


IV. LANDFILL GAS (LFG) This section covers LFG characteristics, composition, LFG production, and gas yield. It

also discusses gas-generation mechanisms and gas-transport mechanisms and factors affecting both mechanisms.

A. Landfill Gas Characteristics Landfill gas is typically a combination of methane, carbon dioxide, and non-

methanogenic organic compounds. Table 1 shows characteristics of some of the typical components of landfill gas.

1. Density and viscosity

The density of LFG depends on the proportion of gas components present. For example, a

mixture of 10 percent hydrogen and 90 percent carbon dioxide, such as might be produced in the first stage of anaerobic decomposition, will be heavier than air, while a mixture of 60 percent methane and 40 percent carbon dioxide, such as might be produced during the methanogenic phase of decomposition, will be slightly lighter than air. Some typical values for density and viscosity at 00C and atmospheric pressure are given in Table 2.

Table 1. Landfill Gas Characteristics

Constituent Relative Specific Gravity

Concentration in Landfill Gas Notes

Air 1 NA Forms explosive mixture with methane

Methane 0.554 40-70% Explosive; LEL 5% in air; UEL 15% in air

Carbon Dioxide 1.529 30-60% Forms weak acid; Asphyxiant

Hydrogen Sulfide 1.19 800 ppm Forms strong acid Toxic: PEL = 10 STEL = 15

Water Vapor 0.62 100% Saturated Forms acids with hydrogen sulfide and carbon dioxide

Benzene 2.8 30 ppm Flammable Toxic: PEL 1.0 ppm STEL 5 ppm

Toluene 3.1 300 ppm Toxic: PEL 100 ppm STEL 150 ppm

Organic Acids GT 2 Traces Odorous Organosulphur Compounds GT 1.5 50 ppm Odorous

Source: US Army Corps of Engineers (2008) LEL = lower explosive limit; UEL = upper explosive limit; STEL = short-term-exposure limit; PEL =

permissible exposure limit.


Table 2. Typical Values for Gas Density and Viscosity at (00C)

Gas Density (kg/m3) Viscosity (Pa*s) Air 1.29 1.71 × 10–5 Methane 0.72 1.03 × 10–5 Carbon Dioxide 1.9 1.39 × 10–5 50% CH4+ 50% CO2 1.35 1.21 × 10–5 60% CH4+ 40% CO2 1.19 1.17 × 10–5

Source: US Army Corps of Engineers (2008)

2. Heat value content During the methanogenic stage, LFG can be expected to have a heating value of 18.6

MJ/m3 under good conditions. This value is about half that of natural gas. The actual heating value of the gas from a landfill is a function of the type age of the waste, the type of landfill cover, and many other factors.

3. Non-methane organic compounds

If a landfill contains a significant amount of municipal solid waste, the gas produced will

consist of approximately 50 percent methane, 50 percent carbon dioxide, and trace amounts of non-methane organic compounds (NMOC). The concentration of NMOC can range from 200 to 15,000 ppm according to research from the EPA. In the EPA study, ethane, toluene, and methylene chloride were found at the highest concentrations in landfill gas with average reported values of 143, 52, and 20 ppm, respectively. The most frequently detected compounds reported were trichloroethene, benzene, and vinyl chloride. During the design phase of a landfill closure, historical records or word of mouth information should be obtained as to the type of wastes that were placed in the landfill and the potential for these wastes to create off-gas emissions.

4. Water vapor

Gas created during the decomposition of organic compounds typically includes between

4 and 7 percent by volume water vapor. The actual water vapor content of LFG will depend on the temperature and pressure within the landfill. Temperatures are typically elevated over ambient during biological decomposition, increasing the evaporation of water into the LFG.

5. Others

Hydrogen is produced during waste decomposition, particularly during the initial

anaerobic conversion of mixed organic acids to acetic acid. Significant amounts of hydrogen are later consumed in the formation of CH4. Hydrogen is flammable between 4 and 74 percent, by volume, in air. The presence of CO2 affects these ranges although little significant change occurs near the lower limit of the range


B. Landfill Gas Composition LFG is the product of microbiological decomposition of land-filled garbage. The

microorganisms turn complex organic compounds in garbage into methane, carbon dioxide, and trace amounts of other compounds. The composition of landfill gas depends on the activity of the bacteria involved, the available substrate and other factors. Landfill gases can be classified into three groups: (1) major components which consist of methane and carbon dioxide; (2) minor components which consist of ammonia, hydrogen, hydrogen sulfide, nitrogen, and carbon monoxide; and (3) trace compounds known as ‘trace gases’, mainly volatile organic compounds (VOC) (Tchobanouglous et al. 1977). Table 3 shows the composition of major and minor compounds in landfill gases, whereas Table 4 shows the concentration of various VOC in landfill gases (Tchobanouglous et al. 1993).

Methane comprises about 50- 55% of LFG, while 40-45% of LFG is carbon dioxide. Methane is the most reduced organic molecule. In other words, no further conversions to simpler organic molecules are possible once methane has been produced. It is produced as an end product of anaerobic metabolism. Methane is a short-lived GHG with an atmospheric lifetime of approximately 12 years compared to over 100 years for carbon dioxide. It is 21 times more potent as a GHG, kilogram for kilogram, than carbon dioxide.

The balance of the input rate and the removal rate determines atmospheric concentrations of GHG. There will be a greater impact by concentrating on methane in the medium-term because it is short lived in the atmosphere and has a high global warming potential (GWP). Some 60 percent of methane emissions come from anthropogenic sources, with around 40 percent from natural sources.

Over 550 trace gases have been identified to date, and doubtless more will yet be discovered. The trace components have chemical or physical properties that differ significantly from the bulk gases. Also, it is known that some of these trace components, when present above threshold concentrations, cause physiological effects and thus have potential health impacts. Just sixty two landfill gas trace substances were then more recently identified within the landfill gas source-term as those from the list of 500, being likely to be present at a significant concentration and to be worthy of further consideration.

Table 3. Typical Composition of Landfill Gas

Component Percent (volume basis) Methane 45 – 65 Carbon dioxide 40 – 60 Nitrogen 2 – 5 Oxygen – 1 Sulfides 0 – 1 Ammonia – 1 Hydrogen 0 – 0.2 Carbon monoxide 0 – 0.2 Trace constituents 0.01 – 0.6

(Source: Tchobanouglous et al., 1993)


C. Landfill Gas Yield Methane yield is defined as the total amount of methane generated per unit weight (dry or

wet) of MSW (El-Fadel et al. 1996a). The methane yield is a function of waste composition. Eleazer et al. (1997) found that the methane yield increased as cellulose and hemicelluose content increased. The methane yield was reviewed by El-Fadel et al. (1996a). There are two approaches for estimating this yield: theoretical and experimental

The Theoretical approach uses the stoichiometric and biodegradability methods to estimate the gas yield. The stoichiometric method is based on several assumptions, such as whether or not complete degradation of waste has occurred; the degradation product only includes CH4 and CO2; the balance of substrates and nutrients is available at all times in all places in the landfill, and no portion of the degraded matter is utilized into cell growth (Ham 1979). The following equation is commonly used to estimate the theoretical landfill gas yield:

.

SHeNHdCOedcba

CHedcbaOHedcbaSNOHC edcba

232

42

483

482

483

482243

24

++⎟⎠⎞

⎜⎝⎛ +++−

+⎟⎠⎞

⎜⎝⎛ −−−+⇒⎟

⎠⎞

⎜⎝⎛ ++−−+

[1]

Table 4. Typical Concentrations of VOCs Compounds in Landfills Gases

Concentration, ppbV (Part per billion per volume) Compound

Median Mean Maximum Acetone 0 6,838 240000 Benzene 932 2057 39000 Chlorobenzene 0 82 1640 Chloroform 0 245 12000 1,1-Dichloroethane 0 2801 36000 Dichloromethane 1150 25694 620000 1,1-Dichloroethene 0 130 4000 Diethylene chloride 0 2835 20000 trans-1,2-Dichloroethane 0 36 850 Ethylene dichloride 0 59 2100 Ethyl benzene 0 7334 87500 Methyl ethyl ketone 0 3092 130000 1, 1, 1-Trichloroethane 0 615 14500 Trichloroethylene 0 2079 32000 Toluene 8125 34907 280000 1, 1, 2, 2-Tetrachloroethane 0 246 16000 Tetrachloroethylene 260 5244 180000 Vinyl chloride 1150 3508 32000 Styrenes 0 1517 87000 Vinyl acetate 0 5663 240000 Xylenes 0 2651 38000

(Source: Tchobanouglous et al., 1993)


Table 5. Methane Yield Based on the Stoichiometric Method

Sources Methane (L/kg dry waste)

Barlaz et al. (1989) 373 carbohydrate 274 protein

Ham et al. (1989) 270 El-Fadel et al. (1996) 220-270 Peer et al. (1993) 230-270

(Source: El-Fadel et al. 1997) Using this method, the estimated yield of the landfill gas is 440 L/kg wet waste with a

composition of 53% methane and 46% CO2 (Ham 1979). El-Fadel et al. (1997) reported, based on the stoichiometric method that the estimated methane yield is in the range of 220-270 L/kg dry waste after complete decomposition. Table 5 summarizes the estimated methane yield based on this method.

In the experimental approach, the landfill gas yield can be obtained from laboratory scale studies. The amount of biogas produced by biodegradation of MSW can be measured in the laboratory. The biodegradation of MSW can be controlled and enhanced by manipulating environmental factors such as pH, temperature, moisture, nutrients, etc. The range of methane yield from lab scale studies varies from no generation to 107 L CH4/kg dry waste.

D. LFG Emission LFG emissions are governed by gas-generation mechanisms and gas-transport

mechanisms. The following paragraphs describe these mechanisms and the major factors influencing gas generation and transport.

1. LFG Generation

1.1. LFG generation mechanisms The three primary causes of LFG generation are volatilization, biological decomposition,

and chemical reactions.

Volatilization Volatilization is due to the change of chemical phase equilibrium that exists within the

landfill. Organic compounds in the landfill volatilize until the equilibrium vapor concentration is reached. This process is accelerated when biological activity increases the temperature of the waste mass. The rate at which compounds volatilize depends on their physical and chemical properties.

Biological decomposition

The rate and composition of landfill gas vary according to the stabilization stages of MSW. Five main stages of degradation of biodegradable wastes have been identified (Kjeldsen et al 2002; Waste Management Paper 26B, 1995; McBean et al 1995). Figure 4


shows the decomposition pathways of the major organic and inorganic components of biodegradable wastes, and Figure 5 shows the process in more detail (Waste Management Paper 26B, 1995). Throughout the process of degradation, because of the heterogeneous nature of waste, all the different stages may be progressing simultaneously until all the waste has reached stage five and stabilization of the landfill has been reached.

Figure 4. Major stages of waste degradation in landfills. Source: Waste Management Paper 26B, 1995.


Figure 5. Details of the stages of waste degradation in landfills. Source: Waste Management Paper 26B, 1995.


Stage I. Hydrolysis/aerobic degradation The hydrolysis/aerobic degradation stage occurs under aerobic (in the presence of

oxygen) conditions. This occurs during the emplacement of the waste and for a period thereafter which depends on the availability of oxygen in the trapped air within the waste. The micro-organisms are of the aerobic type, that is, they require oxygen and they metabolise the available oxygen and a proportion of the organic fraction of the waste to produce simpler hydrocarbons, carbon dioxide, water and heat. The heat generated from the exothermic degradation reaction can raise the temperature of the waste to up to 70–90 °C (McBean et al. 1995; Waste Management Paper 26B 1995). However, compacted waste achieves lower temperatures due to the lower availability of oxygen. Water and carbon dioxide are the main products, with carbon dioxide released as gas or absorbed into water to form carbonic acid, which gives acidity to the leachate.

The aerobic stage lasts for only a matter of days or weeks depending on the availability of oxygen for the process, which in turn depends on the amount of air trapped in the waste, the degree of waste compaction and how quickly the waste is covered.

Stage II. Hydrolysis and fermentation Stage I processes result in a depletion of oxygen in the mass of waste and a change to

anaerobic conditions. Different micro-organisms, and the facultative anaerobes, which can tolerate reduced oxygen conditions, become dominant. Carbohydrates, proteins and lipids are hydrolysed to sugars which are then further decomposed to carbon dioxide, hydrogen, ammonia and organic acids. Proteins decompose via deaminisation to form ammonia and also carboxylic acids and carbon dioxide. The ammonia is derived largely from the deaminisation of proteins, which also form carboxylic acids and carbon dioxide. The derived leachate contains ammoniacal nitrogen in high concentration. The organic acids are mainly acetic acid, but also propionic, butyric, lactic and formic acids and acid derivative products, and their formation depends on the composition of the initial waste material. The temperatures in the landfill drop to between 30 and 50 °C during this stage. Gas concentrations in the waste undergoing stage II decomposition may rise to levels of up to 80% carbon dioxide and 20% hydrogen (Waste Management Paper 26, 1986; Waste Management Paper 26B, 1995).

Stage III. Acetogenesis The organic acids formed in Stage II are converted by acetogen micro-organisms to

acetic acid, acetic acid derivatives, carbon dioxide and hydrogen under anaerobic conditions. Other organisms convert carbohydrates directly to acetic acid in the presence of carbon dioxide and hydrogen. Hydrogen and carbon dioxide levels begin to decrease throughout Stage III. Low hydrogen levels promote the methane-generating micro-organisms, the methanogens, which generate methane and carbon dioxide from the organic acids and their derivatives generated in the earlier stages. The acidic conditions of the acetogenic stage increase the solubility of metal ions and thus increase their concentration in the leachate. In addition, organic acids, chloride ions, ammonium ions and phosphate ions, all in high concentration in the leachate, readily form complexes with metal ions, causing further increases in solubiliation of metal ions. Hydrogen sulphide may also be produced throughout the anaerobic stages as the sulphate compounds in the waste are reduced to hydrogen sulphide by sulphate-reducing micro-organisms (Christensen et al 1996). Metal sulphides may be a


reaction product of the hydrogen sulphide and metal ions in solution. The presence of the organic acids generates a very acidic solution which can have a pH level of 4 or even less (Moss 1997).

Stage IV. Methanogenesis The methanogenesis stage is the main landfill gas generation stage, with the gas

composition of typical landfill gas generated at approximately 60% methane and 40% carbon dioxide. The reactions are relatively slow and take many years for completion. The conditions maintain the anaerobic, oxygen-depleted environment of Stages II and III. Low levels of hydrogen are required to promote organisms, the methanogens, which generate carbon dioxide and methane from the organic acids, and their derivatives such as acetates and formates, generated in the earlier stages. Methane may also form from the direct micro-organism conversion of hydrogen and carbon dioxide to form methane and water. Hydrogen concentrations produced during Stages II and III therefore fall to low levels during this fourth stage. There are two classes of microorganisms which are active in the methanogenic stage, the mesophilic bacteria which are active in the temperature range 30–35 °C and the thermophilic bacteria active in the range 45–65 °C. Therefore, landfill gas can be generated during the methanogenic stage over a temperature range of 30–65 °C, with an optimum temperature range of gas generation between 30 and 45 °C. In fact, most landfill sites fall within this temperature range with an average range for UK landfill sites of between 30 and 35 °C. Where temperatures in the mass of waste drop significantly, for example, to below 15 °C in cold weather in shallow sites, then the rate of biological degradation falls off. The organic acids formed during Stages II and III are degraded by the methanogenic micro-organisms, and as the acid concentration becomes depleted, the pH rises to about pH 7–8 during the methanogenesis stage. Ideal conditions for the methanogenic micro-organisms are a pH range from 6.8 to 7.5, but there is some activity between pH 5 and pH 9. Stage IV is the longest stage of waste degradation, but may not commence until 6 months to several years after the waste is placed in the landfill, depending on the level of water content and water circulation. Significant concentrations of methane are generated after between 3 and 12 months, depending on the development of the anaerobic micro-organisms and waste degradation products. Landfill gas will continue to be generated for periods of between 15 years and 30 years after final deposition of the waste, depending on waste and site characteristics (Landfill Gas Development Guidelines 1996). However, low levels of landfill gas may be generated up to 100 years after waste emplacement.

Stage V. Oxidation The final stage of waste degradation results from the end of the degradation reactions, as

the acids are used up in the production of the landfill gas methane and carbon dioxide. New aerobic micro-organisms slowly replace the anaerobic forms and re-establish aerobic conditions. Aerobic micro-organisms which convert residual methane to carbon dioxide and water may become established.

Figure 6 shows the changes in composition of landfill gas and leachate as the five stages of waste degradation progress with time. Initial formation of hydrogen and carbon dioxide in the hydrolysis/aerobic degradation, hydrolysis and fermentation and acetogenesis stages is followed by the main landfill gas generation stage, the methanogenesis stage. The characteristic landfill gas composition is methane and carbon dioxide with other minor


components and water vapor. The final stages mark the end of the reaction and a return to aerobic conditions. Hydrogen sulphide gas may also form, derived from sulphate-reducing micro-organisms, in wastes with a high concentration of sulphate.

Figure 6. Changes in composition of LFG and leachate during stages of waste decomposition (modified from Pohland and Harper, 1986)

1.2. Factors affecting LFG generation

Solid waste disposal sites are by nature heterogeneous. Microbiological investigations

into site characteristics have shown that there are considerable differences between different SWDSs and even different regions within the same SWDS. This makes it very difficult to extrapolate from observations on single SWDSs to predictions of global CH4 emissions. Nevertheless, a better understanding of the factors thought to most significantly influence the generation of CH4 from land disposal of solid waste can reduce the uncertainty associated with emissions estimates.

1. Site characteristics

Landfill sites with waste depths exceeding 5m tend to develop anaerobic conditions and greater quantities of landfill gas. Shallower sites allow air interchange and lower anaerobic activity, and consequently lower landfill gas production. However, if the site is well capped, anaerobic conditions will be created. Similarly, rapid covering of the waste will reduce the aerobic phase, and since this is the increasing temperature phase, this will tend to keep waste temperatures down. Also, rapid covering of the waste will reduce the chance of rainfall increasing the moisture content of the waste, which in turn reduces the initial rate of biodegradation.

2. Waste characteristics

The major components of municipal solid waste include the biodegradable fraction, that is, the paper and board, food and garden waste, and non-biodegradable components, plastics, glass and textiles. The amount of gas produced will vary depending on the proportion of biodegradable components in the waste. This fraction has been shown to vary depending on a number of factors, for example, higher concentrations of garden waste are produced in spring and autumn, and more industrially developed countries produce more paper. In addition, the bacteria that break down the waste require small amounts of certain minerals such as calcium,


potassium and magnesium and other micronutrients. If these are present the bacteria thrive and gas is produced rapidly. If they are lacking or if substances that inhibit bacterial growth are present, gas production will proceed more slowly and in extreme circumstances may stall completely. In addition, the composition of the organic components, that is, the proportion of cellulose, proteins and lipids, will similarly influence the degradation pathway. The rate at which gas is produced depends on the proportions of each type present in the waste.

Shredding or pulverisation of the waste prior to landfilling results in increased available surface area and consequent increased homogeneity and increased rates of biological degradation. The density or degree of compaction of the waste in the landfill will increase the amount of biodegradable material available for degradation and therefore increase the production of landfill gas per unit volume of void space in the landfill. Too high a degree of compaction, however, may limit the percolation of water through the site, which is necessary for the free flow of nutrients for the micro-organisms.

3. Age of the waste

Landfill gas production begins as soon as waste has been deposited, but anaerobic methane production only occurs when all of the available oxygen has been absorbed. Peak landfill gas production generally occurs about a year after deposit and thereafter gradually declines. Significant gas production is generally completed within about 20 years of deposition, but every site is different. Where gas production is slow, the period of significant gas production may extend for 40 or 50 years. Also, older landfill sites have been shown to contain lower proportions of biodegradable waste than modern sites due to the changing nature of waste over the last few decades.

The pattern of gas production for an entire site is the sum of the performance of all of the individual components of waste. Some will be rapidly enter the gas generation stage, others will be slower, particularly where the period over which waste has been deposited, has been many years. Similarly, the period of significant gas production will vary, and for an entire site most often extends over several decades. Figure 7 below shows an idealised and fairly typical sequence of LFG production, although actual durations will vary greatly site by site.

Figure 7. Variations in Rate of Landfill Gas Production with Time

Source: UK Department of Energy (1992)


4. Temperature Similar to other microbial processes, the biodegradation rate of microorganisms involved

in the MSW decomposition is highly affected by temperature. Methane production increases with an increase in temperature. The optimum temperature for methane production in mesophilic waste decomposition is in the range of 30 to 40ºC, whereas 60 is the optimum temperature for thermophilic waste decomposition (Ham et al. 1989; Barlaz et al. 1990). Hartz et al. (1982) recommended that the optimum temperature for methane generation is in the range of 36 to 41˚C. Ham and Barlaz (1989) concluded that gas production rates at 30, 35, and 40˚C are much higher than rates at 20 and 25˚C.

Anaerobic bacteria produce only small amounts of heat and may not be able to maintain the temperature of a shallow landfill when external temperatures fall so landfill gas generation may show pronounced diurnal or seasonal variations. Likewise, waterlogged landfills may not attain optimum temperatures because the bacteria do not generate sufficient heat to raise the temperature of the excess water. Higher temperatures promote volatilisation and chemical reactions within the waste so the trace gas component of landfill gas tends to increase with higher landfill temperatures.

Chaiampo et al. (1996) have monitored the temperature changes with depth throughout a 20 m deep municipal solid waste landfill in Italy. They showed that the first 1–2m were in the temperature range of 10–15 °C, but the temperature increased to 35–40 °C at the 3–5m depth and to 45–65 °C in the 5–20 m depth region. They equated the temperature regions with the mesophilic bacteria in the 1–5m range and thermophilic bacteria in the deeper layers.

5. Pressure

Atmospheric pressure can have a minor affect on the rate at which landfill gas is released to the atmosphere. It can also influence the operation of gas extraction systems. A decrease in barometric pressure results in a temporary increase in LFG flow and an increase in barometric pressure will cause LFG flow to temporarily decrease. This is because the pressure within the landfill changes at a slower rate than the atmosphere and a pressure gradient temporarily develops between the inside and outside of the landfill until these pressures equalize.

6. Moisture content and movement

Moisture is essential for the activity of all microorganisms in the landfill. The moisture content therefore is one of the most critical factors controlling the biodegradation of MSW.

Many researches have shown that the methane production rate increases by increasing the moisture content of the MSW. Rees (1980) found from existing literature that by increasing the water content from 25% to 60% (wt), the rate of gas production and the percentage of methane in the gas are increased. Baldwin et al. (1998) studied the moisture content in three landfills over 1-6 years and found that wastes with high moisture content are more quickly decomposed. The increase in moisture content affects the limitation of oxygen diffusion from the atmosphere into the landfill, the exchange of substrate, nutrients and microorganisms, and the dilution of inhibitors and improved distribution of enzymes and microorganisms within the landfill (Klink et al. 1982; Christensen et al. 1996). Furthermore, Klink et al. (1982) concluded that moisture movement through the MSW increased the methane production rate from 25% to 50%, compared to no movement of moisture at the same moisture content levels. Compaction of the waste and the presence of layers of poorly permeable material such as clay used for covering


will tend to reduce gas production because they obstruct the passage of moisture. Leachate recirculation back into the waste tends to increase the rate of gas production.

7. Atmospheric conditions

Atmospheric conditions affect the temperature, pressure, and moisture content within a landfill. Landfill covers and liners help to isolate waste from atmospheric conditions by limiting oxygen intrusion, limiting infiltration of precipitation, and buffering the effects of temperature changes.

8. Oxygen concentration

The activity of anaerobic microorganisms is affected by the presence of oxygen. Thus, the absence of free oxygen concentration in the landfill is required in order to grow and degrade the MSW into methane and CO2. In reality, the oxygen that diffuses from the atmosphere into the landfill is consumed by aerobic bacteria in the top layers of the landfill (aerobic zone) (Warith 2003).

If oxygen is present, aerobic biodegradation will proceed rapidly and the resulting gas will comprise mostly carbon dioxide. A few modern engineered landfills are designed to function aerobically. However, in a typical engineered landfill where waste is quickly compacted and covered, aerobic degradation only occurs until the entrained oxygen is used up in newly deposited waste. Where oxygen is not available, the waste is broken down by anaerobic bacteria that produce a “classic” landfill gas, containing roughly equal amounts of methane and carbon dioxide. In uncontrolled “dumps”, where waste is left loose and uncovered, breakdown of the waste may be almost entirely aerobic, and in such cases no methane will be produced.

9. Hydrogen concentration

The fermentative and acidogenic bacteria produce hydrogen during the biodegradation of MSW, while the methanogenic bacteria use the hydrogen as a substrate to produce methane. Low partial pressure of hydrogen is required for the acidogenic processes (hydrogen producing bacteria) and methanogenesis processes.

An increase in the partial pressure of hydrogen causes the generation of propionic and butyric acids with no further conversion, resulting in an accumulation of volatile organic acids which reduce the pH and inhibit the methanogenic bacteria. The conversion of propionic acid requires a hydrogen pressure lower than 9x10-5 atmospheres (Christensen et al. 1989).

10. Precipitation

Precipitation dramatically affects the gas generation process by supplying water to the process and by carrying dissolved O2 into the waste with the water. High rates of precipitation may also flood sections of the landfill, which will obstruct gas flow. The amount of precipitation that reaches the waste is highly dependent on the type of landfill cover system.

11. Density of the waste

The density of waste fills is highly variable. An estimate of waste density is often required for estimating landfill gas generation rates. Several researchers reported density values; Stecker, (1989) reported that MSW density values range from 474 to 711 Kg/m3,


Emcon Associates (1980) stated that MSW density is about 650 Kg/m3, a wider MSW density range of 387 to 1662 Kg/m3 was suggested by Landva et al. (1990).

12. Nutrients and trace metals

Microorganisms in the landfill require various nutrients for their activity, such as nitrogen and phosphorous, as well as traces of heavy metals like zinc, iron, copper, potassium, calcium, cobalt and molybdenite. Rees (1980) and Christensen et al. (1996) found from existing literature that all the necessary nutrients and traces of heavy metals are available in most landfills, but heterogeneous insufficient mixing of the wastes may result in nutrient limited environments. The optimal ratios needed in order to enhance the biodegradation are 100:0.44:0.08 for organic matter expressed as chemical oxygen demand (COD), nitrogen and phosphorous (McCarty 1964).

13. Acidity

The acidity of the landfill site influences the activity of the various microorganisms and therefore determines the rate of biodegradation. The pH of leachate produced from a landfill can have a significant effect on the stabilization of methane production. The pH of a typical landfill site would initially be neutral, followed by acidic phases, Stages II and III, where organic acids are produced from waste degradation by the acetogenic micro-organisms, and the pH falls to as low as 4. The resultant organic acids provide the nutrients for the methanogenic bacteria and as the acids are consumed, the pH rises. The fermentative and acetogenic microorganisms have a wider range of pH compared to methanogenic bacteria. The ideal methanogenic bacteria activity occurs in environmental conditions within a pH range of 6.8 to 8.0 (Warith 2003). Any drop in the pH value below 6.8 will slow down the activity and growth of methanogenic microorganisms. In a well-established methanogenic media, if the methanogenic activity is inhibited by other factors [O2, H2, etc.], the conversion of acetic acid to methane and CO2 decreases and leads to an accumulation of the acids, thereby decreasing the pH which in turn may stop the generation of methane (Christensen et al. 1996).

14. Inhibitors

There are a number of elements or compounds that can inhibit the biodegradation of MSW (methane production) besides O2, H2, pH (acidity) and high concentrations of heavy metals. These inhibitors are carbon dioxide, sulphate, and high concentrations of cations such as sodium, potassium, calcium, magnesium, and ammonium. The CO2 acts as an inhibitor by raising the redox potential which has an effect on the acetic acid conversion to methane (Christensen et al. 1996).

Rees (1980) reported that high sulphate concentrations inhibit the methanogenic bacteria for two reasons: reduction of SO4

2- to S2-, which is toxic; and competition for common substrate between methanogenic and sulphate reducing bacteria.

These cations in low concentrations are required for biodegradation, but in high concentrations they inhibit the methanogenic bacteria. To the author’s knowledge, there have been no studies to evaluate the impact of Chloride on the degradation of MSW.


2. LFG Transport

2.1. LFG transport mechanisms Transport of landfill gas occurs by the two principal mechanisms of diffusion and

advection. Transport conditions both within the landfill and for the subsurface surrounding the landfill must be considered. These transport mechanisms are discussed in the following paragraphs.

Diffusion Molecular diffusion occurs in a system when a concentration difference exists

between two different locations. Diffusive flow of gas is in the direction in which its concentration decreases. The concentration of a volatile constituent in the LFG will almost always be higher than that of the surrounding atmosphere, so the constituent will tend to migrate to the atmosphere. Wind often serves to keep the surface concentration at or near zero, which renews the concentration gradient between the surface and the interior of the landfill and thus promotes the migration of vapors to the surface. Geomembranes in landfill covers will significantly reduce diffusion because the geomembrane prevents gases from diffusing to the atmosphere.

Specific compounds exhibit different diffusion coefficients. Diffusion coefficients are the rate constants for this mode of transport and quantify how fast a particular compound will diffuse. Published diffusion coefficients have been calculated using open paths between one vapor region (concentration) and another. This type of test is not very representative of the conditions found in a landfill. In landfills, gases must travel a tortuous path around all the solids and liquids in its path; thus, the published diffusion coefficients must be used with care.

Advection. Advective flow occurs where a pressure gradient exists. The rate of gas

movement is generally orders of magnitude faster for advection than for diffusion. Gas will flow from higher pressure to lower pressure regions. In a landfill, advective forces result from the production of vapors from biodegradation processes, chemical reactions, compaction, or an active LFG extraction system. Variations in water table elevations can create small pressure gradients that either push gases out (rising tide) or draw gases in (falling tide). Changes in barometric pressure at the surface can also have an impact on the advective flow of gas.

2.2. Factors affecting LFG transport mechanisms

LFG transport is affected by the following factors: Permeability. The permeability of waste has a large influence on gas flow rates and gas

recovery rates. Coarse-grain wastes exhibit large values of gas permeability and more uniform gas flow patterns. By contrast, fine-grained and heterogeneous wastes are characterized by small values of gas permeability and gas flow patterns that are not uniform throughout the waste mass. Permeability of refuse is often reported in Darcys. One Darcy = 9.85×10–9 cm2. Reported values for the apparent permeability of municipal solid waste are in the range of 13 to 20 Darcys. Water competes with air to occupy pore space within the solid matrix and ultimately reduces the effective porosity and ability of vapors to migrate through


the landfill due to a reduction in available air pathways. This reduction will also reduce the rate of gas flow and decrease gas recovery rates.

Geologic Conditions. Geologic conditions must be determined to estimate the potential

for off-site migration of gas. Permeable strata such as sands, gravels, and weathered bedrock provide a potential pathway for off-site migration, especially if these layers are overlain by a layer of low permeability soil. Geologic investigations must be performed to determine the potential for off-site migration. Additional attention must be given to areas where houses and other structures are present to ensure off-site migration will not impact these structures.

Depth to Ground Water. The water table surface acts as a no-flow boundary for gas. As a

result, it is generally used to help estimate the thickness of the zone through which gas can travel. A consistently high ground water table will significantly reduce the potential for off-site migration of gas. The depth to groundwater (as well as seasonal variations) also needs to be evaluated during the design process to evaluate well construction requirements and the potential for water table upwelling (i.e., the upward rise of the water table toward a vacuum well screened in the unsaturated zone).

Man-Made Features. In some instances, underground utilities such as storm and sanitary

sewers or the backfill that surrounds these features may produce short-circuiting of airflow associated with an active landfill gas collection system. As a result, airflow may be concentrated along these features rather than within the landfill. Man-made features also provide a potential pathway for the off-site migration of landfill gas.

Landfill Cover and Liner Systems. The components of many hazardous and solid waste

landfill cover systems consist of a vegetated surface component, a drainage layer, and a low permeability layer composed of one or more of the following: geomembrane, geosynthetic clay liner (GCL), or compacted clay. A geomembrane in the cover system will prevent the intrusion of air into the waste. Therefore, a higher operating vacuum can be applied to the gas collection system without the danger of overdrawing. Thus, the effective radius of influence of each well is increased. Overdrawing occurs when oxygen from the atmosphere is pulled into the landfills interior during the anaerobic phase.

Landfill liner systems consist of various combinations of low permeability layers and leachate collection layers. The low permeability layers are created using natural low permeability geologic formations, compacted clay, geomembranes, and geosynthetic clay liners. Liner systems prevent the migration of LFG to the surrounding areas. Liner systems also prevent gases in the surrounding geologic formations from being pulled into the LFG collection system.

Barometric Pressure. The amount of gas escaping from a landfill’s surface changes as

barometric pressure changes. Gas generation within a landfill will result in a positive pressure gradient from the inside to the outside of the landfill. For a passive LFG collection system, increases in atmospheric pressure will cause a decrease in gas flow from a landfill because the pressure differential between the inside and the outside has decreased. For an active gas collection system, there is a higher probability of atmospheric air intrusion through the landfill cover during periods when the barometric pressure is rising. The amount of air


intrusion will be greatly affected by the type of cover on the landfill. A landfill with a low permeability (geomembrane) cover will be more resistant to air intrusion than a landfill with a soil cover.

E. LFG Production Enhancement Methods The biodegradation of MSW and LFG production in bioreactor landfills can be enhanced

through different methods. In all cases, the purpose is to control and manipulate the influencing factors in a positive manner in order to accelerate the biodegradation of MSW and increase the amount of LFG produced. There are many advantages to enhancing the biodegradation of MSW, including more rapid waste stabilization and increased gas production; lower leachate treatment costs through recirculation to the landfill; reduced length and cost of post closure activities; and greater landfill airspace availability due to increased settlement during the operation rather than the post closure stage, as is the case in conventional landfills (Reinhart et al., 2002).

The technologies used to enhance the biodegradation of MSW are studied by San et al. (2001), Laquidara et al. (1986), Chan et al. (2002), Chiemchaisri et al. (2002), Warith (2003), Bae et al. (1998), Pacey (1989), Klink et al. (1982), Stegmann (1983), and reviewed by Barlaz et al. (1990), Warith et al. (1998), Komilis et al. (1999a), Christensen et al. (1992), Stegmann et al. (1996).

These technologies are leachate recycle, pH buffering, sludge addition, temperature control, reduced waste particle size, improved cell design, daily cover and waste compaction, and pre-treatment of MSW. They will all be discussed in the following sections.

1. Leachate recirculation

Leachate recirculation is the process by which the leachate collected at the base of the landfill is recycled or reintroduced in the landfill in order to control the moisture content.

The advantages and impacts of leachate recirculation on the degradation of MSW were covered by Barlaz et al. (1996), San et al. (2001), Ham et al. (1982, 1989), Baldwin et al. (1998), Warith et al. (1998, 2002, 2003), Reinhart et al. (1996, 2002), and Sponza et al. (2004). The advantages of leachate recirculation lay both in the rapid reduction of the organic content present in the leachate itself which reduces the cost of treatment; and the potential transformation of waste into energy, as it increases the rate of methane production.

Leachate recirculation provides optimum conditions for enhancing biodegradation by increasing the moisture content and movement, and by distributing the nutrients throughout the landfill. Both moisture content and moisture movement are necessary settings for bacteria growth and the establishment of methanogenic conditions. They also provide better contact between insoluble substrates, soluble nutrients and microorganisms (Klink et al., 1982).

Ham et al. (1982) and Baldwin et al. (1998) studied the effect of moisture content on the biodegradation of MSW and concluded that moisture content has a positive effect on gas production. Also, leachate recirculation treats the leachate through the landfill (in situ treatment) because the organic compounds in the leachate are reduced with the recirculation due to the biological activity within the landfill (Sponza et al., 2004).


Klink et al. (1982) found that the reactor with leachate recycle had 25-50% higher methane production as compared to reactors having the same moisture content but without leachate recirculation.

2. pH buffering

The methanogenic bacteria are sensitive to pH and could be inhibited by acidic conditions. This understanding has led to adding buffer to the leachate prior to recycling it back to the bioreactor landfill. Leachate recirculation with a buffering system to control the pH causes a shorter acidogenic stage compared to leachate recirculation without a buffering system (Komilis et al., 1999a).

In a study conducted by Warith (2002), the reactor with buffered and nutrients amended recycled leachate resulted in the greatest reduction of COD concentration over time. Also, a study by San et al. (2001) found that the highest degree of stabilization occurred in a reactor with a four-time per week recirculation and pH control by addition of buffer. Ağdağ et al. (2005) studied the effect of alkalinity addition to leachate recycle on the degradation of MSW in an anaerobic bioreactor. It was observed that lower COD, VFA concentrations and BOD5/COD ratios were obtained in the bioreactors with alkalinity addition in comparison to the bioreactor (control) without alkalinity addition.

Lab scale experiment results recommend the addition of buffer to leachate recycle, especially in the acid generation phase, to maintain the pH at a neutral level. This helps to establish a methanogenic condition.

3. Sludge addition

The effect of sludge addition on the MSW degradation is covered by Pacey (1989), Leuschner (1982) and Warith (2002). They concluded that the addition of sewage sludge has both a positive and a negative effect on the MSW biodegradation and methane generation.

The positive effect of sludge addition occurs if the methanogenic bacteria are already established or the landfill environment is optimum (pH neutral) for methanogenic bacteria (Christensen et al., 1992). This positive effect can be attributed to the following factors: 1) sludge can be a source of nutrients and active methanogenic bacteria, and; 2) sludge increases the moisture content.

The negative effect of sludge addition to fresh waste is attributed to the acid accumulation that is associated with it which decreases the pH and inhibits the methanogenic bacteria (Barlaz et al., 1990).

Rees (1980) and Leuschner (1982) found that the anaerobic digested sewage sludge is an excellent source of microbial inoculum, whereas the septic tank sludge is a poor one. Also, Komilis et al. (1999a) concluded that adding anaerobic digested sludge to MSW produces three times more methane than adding primary sludge.

It appears that the addition of anaerobic digested sludge with buffering enhanced the biodegradation and increased methane generation. Buffering controls the pH of the landfill around neutral, allowing the methanogenic bacteria in the anaerobic sludge to acclimatize to the landfill environment faster than without buffer addition.

The addition of old waste or ashes to new waste could improve biodegradation by diluting the acids produced during the acidogenic stage, thereby enhancing the methane formation stage. The percentage of ash should not exceed 10% in weight (Komilis et al., 1999a).


4. Temperature control The direct effect of temperature on bacteria activity could be manipulated to optimize the

decomposition of MSW in the bioreactor landfill. Thus, it is necessary to realize the temperature constraints on individual microorganisms in order to control the activity of bacteria and enhance waste stabilization.

Baldwin et al. (1998) investigated the effect of temperature on a large scale using two different landfills, one located in Florida and the other in Wisconsin. The Florida landfill (30˚C) had a more rapid decomposition compared to the Wisconsin landfill (22˚C). Kasali et al. (1989) found that by increasing the temperature of MSW with a 60% w/w moisture content from 18.7 to 30˚C caused a 2.6 times increase in the methanogenic rate, while a 7.8 times increase when the temperature rose from 18.7 to 40˚C. The methanogenic rate is inhibited when the temperature is increased to 55˚C. Based on the experimental work, the optimum temperature for enhancing the MSW biodegradation is in the range of 30-40˚C.

5. Reduced waste particle size

Shredding or reducing the particle size of MSW has several advantages, such as providing more landfill space and greater MSW stabilization. The arguments for shredding are: 1) it increases homogeneity and distribution of waste within the landfill, 2) it improves the contact surface area of the waste, 3) it promotes better contact between the organic matter and microorganisms (Christensen et al., 1992).

Ham et al. (1982) found that the shredding of waste increases the rate of decomposition and methane production. Some authors (Buivid et al., 1981) concluded that refuse with 2.5 to 3.5 cm particle sizes produced 32% more methane than refuse with 1 to 1.5 cm particle sizes in a period of 90 days. This is due to the fact that the smaller particle size increases the rate of hydrolysis and acid formation which in turn decreases the pH and postpones the production of methane.

Based on that, if the negative effect of smaller particle sizes in the initial stage of biodegradation can be controlled (by adding buffer or pre-composting), shredding may enhance the biodegradation process, since the hydrolysis is the rate-limiting step (Yildiz et al., 2004; El-Fadel et al., 1996b; Pareek et al., 1999; Naranjo et al., 2004).

Sponza et al. (2005) reported that the shredding of MSW has a positive effect on the rate of biological degradation in anaerobic bioreactors with leachate recycle. They compared three types of reactors. The first reactor was loaded with raw waste, the second with shredded waste, and the third with compacted waste. At the end of the experiments (57 days later), they found that the reactor with waste shredding had the lowest COD and VFA concentrations and the highest methane percentage.

6. Cell design, daily cover and compaction of waste

The enhancement of waste biodegradation in the landfill is also affected by the cell thickness, daily cover and compaction of waste.

The cell thickness has an adverse effect on the biodegradation of waste. Ham et al. (1982) found that the cell with a 2m deep lift produced higher leachate concentrations and took a longer time to stabilize than the cell with a 1.2m deep lift. By doubling the cell depth from 1.2 to 2.4 m, the concentration of leachate and the stabilization time are doubled as well.


Similarly, the daily cover has a negative effect on the biodegradation of waste because it decreases the O2 diffusion into the waste which in turn diminishes the composting rate. If a low permeability soil is used as a daily cover, it could create a barrier and may impact leachate distribution and landfill gas flow into the collection system. A soil cover more permeable than the waste can direct leachate to the sides. Use of alternative covers that do not create such barriers can reduce these effects. On the other hand, positive effects of daily cover soil may be expected if the soil supplies buffer to the landfill (e.g. contain lime) (Christensen et al., 1992).

The cell with soil cover has a higher leachate concentration than the cell without it. Initially, the cell without cover produced a high leachate concentration, but it was followed by a rapid decrease (Ham et al., 1982). It appears that the lack of daily cover enhances the aerobic activity and prevents a long acidogenic stage. The short acidogenic period leads to the rapid establishment of the methanogenic stage. The landfill should utilize thin lifts and the daily cover should not be used immediately.

Likewise, waste compaction has an adverse effect on the biodegradation of waste in the landfill. Ehring et al. (1980) found that cells with low-density waste have shorter periods of high leachate concentration. This means that there is an enhancement in the acidogenic stage. Rees et al. (1982) concluded that by increasing the waste density from 0.2 to 0.47 t/m3, there was a decrease in gas production due to acid accumulation, which in turn decreased the pH and inhibited the methanogenic bacteria.

Waste compaction causes sudden decrease in the void space of the waste which in turn decreases the moisture content dramatically. On the other side, the effect of load caused from subsequent waste layers, which is examined in this thesis, causes a gradual decrease in waste voids in a way that does not affect waste biodegradation.

7. Pre-treatment

The objective of the pre-treatment of MSW is to enhance the acidogenic stage and decrease the accumulation of organic acids. This method is based on the stabilization of part of the waste through aerobic processes which will dilute the organic acids and cause a balance between the acidic phase and the methanogenic bacteria. This method was studied by Ham et al. (1982); Beker (1987); and Stegmann (1983) and was reviewed by Komilis et al. (1999b).

Ham et al. (1982), Beker (1987) and Stegmann (1983) found that by placing fresh waste on top of the composted waste layer caused a shorter acidogenic stage and enhanced the methanogenic stage. This is due to the fact that the composted layer acts as an anaerobic filter which has the ability to treat leachate as it passes through. The composted bottom layer can be prepared by the following procedure: a layer (1.5m-2m) of waste is placed without compaction, so that the easy degradable material can be decomposed aerobically with leachate recycle. The leachate concentration and the temperature of the waste can be used as indicators for the progress of the aerobic process. After one year of the placement, the waste layer is compacted and an additional layer of fresh waste can be added on top (Stegmann, 1983). The author suggested that efforts should be made to reduce the time required for aerobic decomposition of the first layer by injecting air through perforated pipes.


V. LANDFILL GAS BEHAVIOUR

A. LFG Movement and Migration Gases generated in the landfill will move throughout the mass of waste in addition to

movement or migration out of the site. The mechanism of gas movement is via gaseous diffusion and advection or pressure gradient. That is, the gas moves from high to low gas concentration regions or from high to low gas pressure regions (Kjeldsen et al 2002). Movement of gas within the mass of waste is governed by the permeability of the waste, overlying daily or intermittent cover, and the degree of compaction of the waste. Lateral movement of the gases is caused by overlying low permeability layers such as the daily cover and surface and sub-surface accumulations of water. Vertical movement of gas may occur through natural settlement of the waste, between bales of waste if a baling system is used to compact and bale the waste, or through layers of low permeability inert wastes such as construction waste rubble. Where landfill gas extraction is practised to recover the gas for energy use, the gas is collected in gas wells, and piped to the surface (Waste Management Paper 27, 1994).

Fully contained landfill sites where, after completion, the landfill is capped with an impermeable synthetic and natural containment system to prevent migration of landfill gas out of the site and which have gas recovery systems in place, have low gas emission levels (Mosher et al 1999). The capping liner system is also designed to prevent ingress of precipitation. For landfill sites, where landfilling is still in operation and where the waste is only partially covered by an impermeable layer, there are higher emissions of landfill gas. Waste landfills are a source of volatile organic hydrocarbons, both to the site workers and to the surrounding neighbourhood. The contribution of a range of chemicals identified in landfill gas has been shown to be significant contributors to the toxic air pollutants in local neighborhoods adjacent to landfill sites (Scheff et al 2001). Certain chemicals, including chlorinated hydrocarbons, have been identified as being derived from landfill as the major source. Additionally, other work has shown that chlorinated hydrocarbons are found in landfill gas at concentrations which exceed occupational exposure levels (Allen et al 1997). However, it is unlikely that long exposure to such levels would be experienced by landfill site workers and even less likely for members of the public (Allen et al 1997).

Sub-surface gas migration out of the mass of waste into the surrounding environment may occur from older sites, where containment was not practised, or through containment sites, where significant leakage has occurred. In addition, leachate movement out of such sites may cause later degradation to landfill gas. Migration of gas outside the site requires migration pathways such as high-permeability geological strata, through caves, cavities, cracks in the overlying capping layer and through man-made shafts, such as mine shafts and service ducts, etc. Gas may migrate considerable distances from the boundaries of the site through these possible pathways. It has been reported that changes in the major and trace components of landfill gas occur during subsurface migration (Ward et al 1996). For example, reduction in methane concentration occurs due to oxidation, and some alteration of trace landfill gases occurs due to adsorption onto soil particles, oxidation, degradation, condensation and dissolution.


B. Monitoring of LFG The monitoring program for landfill gas at waste landfill sites is recommended to

determine whether landfill gas is causing a hazard to human health or the environment. Monitoring takes place throughout the operation of the plant and for many years during the post-closure period, until emission levels of methane and carbon dioxide are at environmentally insignificant levels, typically below 1.0% by volume of methane and 1.5% by volume of carbon dioxide. Monitoring takes place within the landfill and outside the site boundary. The monitoring program, including the frequency of monitoring, will be dependent on the age of the site, the type of waste and the gas collection and control measures installed. Frequency between measurements will vary from weekly, monthly or even quarterly, depending on site-specific characteristics. More frequent monitoring may be required where migration of gas is suspected. Monitoring techniques for landfill gas include, for example, surface monitoring, sub-surface probes, gas monitoring wells, and boreholes. Surface monitoring with portable instruments is mainly used to detect the presence of gas leaks throughout the site. Sub-surface monitoring using gas probes is used to monitor gas production and migration at depths of between 1 and 10m in the mass of waste and in the surrounding environment. The probes may be left for long periods of time to monitor and map the production of gas from the site throughout site operation and post-closure. The probes are constructed of steel and plastic pipe, consisting of a porous lower section and a gas transfer pipe which transfers the gas to the surface, where the gas sample is taken for analysis. Gas monitoring well and boreholes consist of a porous plastic casing in direct contact with the waste or geological strata. Probes or tubes may be permanently installed. They are installed within the mass of waste and in the surrounding environment.

Gas sample analysis may take the form of portable instruments for gas analysis or laboratory-based analysis. Portable analyzers may be simple devices, such as gas indicator tubes, which produce a color change to indicate a concentration of a particular gas in a sample. The gas is drawn through the tube on-site and an immediate indication of gas concentration is obtained. The method is, however, subject to error. More sophisticated instruments are available, such as infra-red gas analyzers and flame ionization detectors, which would normally be housed in a portable laboratory or at the analytical laboratory. The gas sample is piped directly to the analyzer or else a sample of the gas is taken in suitable sealable containers, such as ‘Teflon’ bags or glass sample tubes and the sample is then transferred to the instrument for analysis. The most accurate and reliable technique for gas analysis is gas chromatography. A sample of the gas is taken in a suitable container to the laboratory for analysis. The gas chromatograph can separate out individual gas components and provide an accurate analysis, even at trace concentrations.

C. LFG Hazards

1. LFG explosion hazard Landfill gas may form an explosive mixture when it combines with air in certain

proportions. The following conditions must be met for landfill gas to pose an explosion hazard:


• Gas production. A landfill must be producing gas, and this gas must contain chemicals that are present at explosive levels.

• Gas migration. The gas must be able to migrate from the landfill. Underground pipes or natural subsurface geology may provide migration pathways for landfill gas. Gas collection and treatment systems reduce the amount of gas that is able to escape from the landfill.

• Gas collection in a confined space. The gas must collect in a confined space to a concentration at which it could potentially explode. A confined space might be a manhole, a subsurface space, a utility room in a home, or a basement. The concentration at which a gas has the potential to explode is defined in terms of its lower and upper explosive limits (LEL and UEL). The concentration level at which gas has the potential to explode is called the explosive limit. The LEL and UEL are measures of the percent of a gas in the air by volume. At concentrations below its LEL and above its UEL, a gas is not explosive. However, an explosion hazard may exist if a gas is present in the air between the LEL and UEL and an ignition source is present.

Methane is the constituent of landfill gas that is likely to pose the greatest explosion

hazard. Methane is explosive between its LEL of 5% by volume and its UEL of 15% by volume. Because methane concentrations within the landfill are typically 50% (much higher than its UEL), methane is unlikely to explode within the landfill boundaries. As methane migrates and is diluted, however, the methane gas mixture may be at explosive levels.

Table 6. Potential Explosion Hazards from Common Landfill Gas Components

Component Potential to pose an explosion hazard

Methane

Methane is highly explosive when mixed with air at a volume between its LEL of 5% and its UEL of 15%. At concentrations below 5% and above 15%, methane is not explosive. At some landfills, methane can be produced at sufficient quantities to collect in the landfill or nearby structures at explosive levels.

Carbon dioxide Carbon dioxide is not flammable or explosive. Nitrogen dioxide Nitrogen dioxide is not flammable or explosive. Oxygen Oxygen is not flammable, but is necessary to support explosions.

Ammonia Ammonia is flammable. Its LEL is 15% and its UEL is 28%. However, ammonia is unlikely to collect at a concentration high enough to pose an explosion hazard.

NMOC

Potential explosion hazards vary by chemical. For example, the LEL of benzene is 1.2% and its UEL is 7.8%. However, benzene and other NMOC alone are unlikely to collect at concentrations high enough to pose explosion hazards.

Hydrogen sulfide Hydrogen sulfide is flammable. Its LEL is 4% and its UEL is 44%. However, in most landfills, hydrogen sulfide is unlikely to collect at a concentration high Enough to pose an explosion hazard.

Source: Cheremisinoff 2003

Also, oxygen is a key component for creating an explosion, but the biological processes that produce methane require an anaerobic, or oxygen-depleted, environment. At the surface of the landfill, enough oxygen is present to support an explosion, but the methane gas usually


diffuses into the ambient air to concentrations below the 5% LEL. In order to pose an explosion hazard, methane must migrate from the landfill and be present between its LEL and UEL.

Other landfill gas constituents (e.g., ammonia, hydrogen sulfide, and NMOC) are flammable. However, because they are unlikely to be present at concentrations above their LELs, they rarely pose explosion hazards as individual gases. For example, benzene (an NMOC that may be found in landfill gas) is explosive between its LEL of 1.2% and UEL of 7.8%. However, benzene concentrations in landfill gas are very unlikely to reach these levels. If benzene were detected in landfill gas at a concentration of 2 ppb (or 0.0000002% of the air by volume), then benzene would have to collect in a closed space at a concentration 6 million times greater than the concentration found in the landfill gas to cause an explosion hazard.

Table 6 provides a summary of the potential explosion hazards posed by the important constituents of landfill gas. Methane is the most likely landfill gas constituent to pose an explosion hazard. Other flammable landfill gas constituents are unlikely to be present at concentrations high enough to pose an explosion hazard. However, the flammable NMOC do contribute to total explosive hazard when combined with methane in a confined space. 2. LFG asphyxiation hazard

Landfill gas poses an asphyxiation hazard only if it collects in an enclosed space (e.g., a basement or utility corridor) at concentrations high enough to displace existing air and create an oxygen-deficient environment. The Occupational Safety and Health Administration (OSHA) defines an oxygen-deficient environment as one that has less than 19.5% oxygen by volume. Ambient air contains approximately 21% oxygen by volume. Health effects associated with oxygen deficient environments are described in Table 7. Any of the gases that make up landfill gas can, either individually or in combination, create an asphyxiation hazard if they are present at levels sufficient to create an oxygen-deficient environment.

Table 7. Health Effects from Oxygen-Deficient Environments

Oxygen Concentration Health Effects 21% Normal ambient air oxygen concentration

17% Deteriorated night vision (not noticeable until a normal oxygen concentration is restored), increased breathing volume, and accelerated heartbeat

14 to 16% Increased breathing volume, accelerated heartbeat, very poor muscular coordination, rapid fatigue, and intermittent respiration

6 to 10% Nausea, vomiting, inability to perform, and unconsciousness

Less than 6% Spasmatic breathing, convulsive movements, and death in minutes

Source: Cheremisinoff 2003 Carbon dioxide, which comprises 40% to 60% of landfill gas, may pose specific

asphyxiation hazard concerns. Because it is denser than air, carbon dioxide that has escaped from a landfill and collected in a confined space, such as a basement or an underground utility corridor, may remain in the area for hours or days after the area has been opened to the air


(e.g., after a manhole cover has been removed or a basement door opened). Carbon dioxide is colorless and odorless and therefore not readily detectable. Carbon dioxide concentrations of 10% or more can cause unconsciousness or death. Lower concentrations may cause headache, sweating, rapid breathing, and increased heartbeat, shortness of breath, dizziness, mental depression, visual disturbances, and shaking. The seriousness of these symptoms depends on the concentration and duration of exposure. The response to carbon dioxide inhalation varies greatly even in healthy normal individuals.

In assessing the public health issues of migrating landfill gas, environmental health professionals should investigate the presence of buried utility lines and storm sewers on or adjacent to the landfill. These structures not only provide a pathway for migrating gases, but also pose a special asphyxiation problem for utility workers who fail to follow confined space entry procedures prescribed by OSHA. On-site or adjacent residences and commercial buildings with basements or insulated (or sealed) crawl spaces should also be investigated for potential asphyxiation hazards.

3. Landfill odors

Landfill odors often prompt complaints from community members. People may also have concerns about health effects associated with these odors and other emissions coming from the landfill. People in communities near landfills are often concerned about odors emitted from landfills. They say that these odors are a source of undesirable health effects or symptoms, such as headaches and nausea. At low-level concentrations—typically associated with landfill gas— it is unclear whether it is the constituent itself or its odors that trigger a response. Typically, these effects fade when the odor can no longer be detected. Landfill gas odors are produced by bacterial or chemical processes and can emanate from both active and closed landfills. These odors can migrate to the surrounding community. Potential sources of landfill odors include sulfides, ammonia, and certain NMOC, if present at concentrations that are high enough. Landfill odors may also be produced by the disposal of certain types of wastes, such as manures and fermented grains. The following are major landfill gases generated:

Sulfides. Hydrogen sulfide, dimethyl sulfide, and mercaptans are the three most common

sulfides responsible for landfill odors. These gases produce a very strong rotten-egg smell—even at very low concentrations. Of these three sulfides, hydrogen sulfide is emitted from landfills at the highest rates and concentrations. Humans are extremely sensitive to hydrogen sulfide odors and can smell such odors at concentrations as low as 0.5 to 1 part per billion (ppb). At levels approaching 50 ppb, people can find the odor offensive. Average concentrations in ambient air range from 0.11 to 0.33 ppb. According to information collected by the Connecticut Department of Health, the concentration of hydrogen sulfide in ambient air around a landfill is usually close to 15 ppb.

Ammonia. Ammonia is another odorous landfill gas that is produced by the

decomposition of organic matter in the landfill. Ammonia is common in the environment and an important compound for maintaining plant and animal life. People are exposed daily to low levels of ammonia in the environment from the natural breakdown of manure and dead plants and animals. Because ammonia is commonly used as a household cleaner, most people are familiar with its distinct smell. Humans are much less sensitive to the odor of ammonia


than they are to sulfide odors. The odor threshold for ammonia is between 28,000 and 50,000 ppb. Landfill gas has been reported to contain between 1,000,000 and 10,000,000 ppb of ammonia, or 0.1% to 1% ammonia by volume. Concentrations in ambient air at or near the landfill site are expected to be much lower.

NMOC. Some NMOC, such as vinyl chloride and hydrocarbons, may also cause odors.

In general, however, NMOC are emitted at very low (trace) concentrations and are unlikely to pose a severe odor problem.

Odor control technologies prevent odor-causing gases from leaving the landfill. Installing a landfill cover will prevent odors from newly deposited waste or from gases produced during bacterial decomposition. Covering a landfill daily with soil can help reduce odors from newly deposited wastes. More extensive covers are installed at landfill closure to prevent moisture from infiltrating the refuse and encouraging bacterial growth and decomposition. Vegetative growth on the landfill cover also reduces odors. Flaring is another technique that can eliminate landfill gas odors by thermally destroying the odor-causing gases. Venting landfill gas through a filter is another technology used to reduce odors. Landfill gas is collected and vented through a filter of bacterial slime. As long as oxygen is present, bacteria will decompose landfill gas under aerobic conditions, producing carbon dioxide and water.

VI. MODELING OF METHANE GAS GENERATION AND EMISSION FROM LANDFILLS

A. General

Several models are available for estimating the LFG generation rate using site-specific

input parameters. These models vary widely, not only in the assumptions that they make, but also in their complexity, and in the amount of data they require. The LandGEM model is one of these models and was developed by the US Environmental Protection Agency to estimate landfill gas emissions and to determine regulatory applicability to CAA requirements. There are other LFG emission models in use by industry that also work very well. The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of CH4 emissions from the landfills is based on First-Order decay (FOD) method. Regardless of what model is used, the accuracy of the inputs drives the results and given the level of uncertainty, it makes estimating landfill emissions very difficult.

Estimates of the amount of landfill gas generated throughout the lifetime of the landfill site are highly variable with estimates of between 39 to 500 m3/tonne (McBean et al 1995). For the estimation of landfill gas throughout the lifetime of a site for the assessment of energy recovery from landfill gas utilization, values of between 150 and 250m3/tonne are typically used (Loening 2003). Annual rates of gas production have been estimated for a typical municipal solid waste landfill at between 6 and 8m3/tonne/year but much higher rates of over 25m3/tonne/year have been recorded (Characterization of 100 UK landfill sites 1995). This allows the potential amount of energy which could be generated from the site, knowing that undiluted landfill gas can have a calorific value of between 15 and 21 MJ/m3, compared to the calorific value of natural gas at about 37 MJ/m3 (Waste Management Paper 27, 1994). The


calorific value of the gas depends on the percentage composition of combustible gases such as methane, and non-combustible gases such as carbon dioxide. The presence of carbon dioxide results in reduced flame temperatures and burning rates, a narrower range of flame stability and thus lower combustion efficiency (Qin et al 2001). The carbon dioxide is also regarded as ‘inert’, in that it does not combust and therefore does not contribute to the energy content of the landfill gas.

B. U.S.E.P.A. Model - Landgem

1. Model description The landfill gas emission model (LandGEM) developed by US EPA provides an

automated estimation tool for estimation of landfill gas emissions from municipal solid waste MSW landfills (http://www.epa.gov/ttn/catc/products.htmlsoftware).

The model is based on a first order decomposition rate equation to estimate annual emissions over a specified time period, described as follows:

ijkti

n

i joCH eMkLQ −

= =⎟⎠⎞

⎜⎝⎛= ∑ ∑ 101

1

1.04

(1) Where,

4CHQ = Annual Methane generation in the year of the calculation (m3/year)

iM = Mass of waste accepted in the year I (Mg)

0L = Potential methane generation capacity of the waste (m3/Mg)

k = Methane generation rate (per year) j = Waste type category (index) i = 1Year n = (year of the calculation)- (initial year of waste acceptance)

ijt = Age of the jth section of waste mass

iM accepted in the ith year (decimal years, e.g., 3.2 years)

1.1. Input Parameters Main Input parameters required for LandGEM are as follows: • Annual Waste acceptance rate during the operation of the landfill (tons/year) • Start year and end year of the landfill operations • Assumed values of methane generation rate (k ) and methane generation potential

( 0L )

• NMOC concentration and methane content in landfill gas


LandGEM is considered a screening tool – the better the input data, the better the estimates. The Input parameters in the model are described below in more details:

Methane generation potential (L0)

The methane generation potential is the total amount of methane that a unit mass of refuse will produce given enough time. It depends upon the composition of the waste. Values of Lo can vary widely and are difficult to estimate for a particular landfill. As per IPCC (1996), the values of Lo may range from less than 100 to over 200m3/Mg.

Methane generation rate (k)

The k value is indicative of the fraction of the waste which undergoes decomposition in the given year to produce methane. The k value for the given mass is actually related to its half life time period of decay:

2/1

2lntk = (2)

Where, half life is the time taken by the degradable organic carbon in the waste to decay

to half of its initial mass. This value is affected by a number of factors including the waste composition, climatic

conditions at the site, characteristics of the disposal site, waste disposal practices etc. The most rapid rates (k = 0.2) are associated with high moisture conditions and rapidly

degradable material such as food waste. The slower decay rates (k = 0.02) are associated with dry site conditions and slowly degradable waste such as wood or paper. IPCC (2006) has provided default k values as dry and wet values for various types of waste depending upon the climatic conditions.

There are two options to use the value of k for estimation of gas potential: Bulk waste option in which single value of k is chosen for the entire waste and Waste composition option in which k value for each component of waste stream is considered for calculations. LandGEM has bulk waste option for k.

C. IPCC-First Order Decay (FOD) Model

1. Model description The Intergovernmental Panel on Climate Change (IPCC) methodology for estimation of

CH4 emissions from the landfills is based on FOD method. This method assumes that the degradable organic carbon (DOC) in the waste decays slowly throughout a few decades, during which CH4 and CO2 are formed. If conditions are constant, the rate of CH4 formation depends solely on the amount of carbon remaining in the waste. Therefore, the CH4 emissions from the waste deposited in a landfill are highest in the first few years after closure and then gradually start reducing.

The FOD model developed by IPCC (2006) has been widely adapted for calculation of methane emissions from the landfills. Same model has been used by United Nations Framework Convention on Climate Change (UNFCCC) in its “Tool to determine methane


emissions avoided from dumping waste at a solid waste disposal site” to award Clean Development Mechanism (CDM) benefits to a particular landfill closure project.

As per the tool, the amount of methane that is generated each year (ySWDSCHBE ,,4), (t

CO2e) is calculated for each year y, using the following equation:

4, , 4

( ),

1

16(1 ) (1 )12

(1 )j j

CH SWDS y CH f

yk k y x

j x jx j

BE f GWP OX F DOC

MCF W DOC e e

j

- - × -

=

= × - × × - × ×

× × × - ×å å (3)

Where:

ySWDSCHBE ,,4 =

Methane emissions avoided during the year y from preventing waste disposal at the solid waste disposal site (SWDS) during the period from the start of the project activity to the end of the year y (tCO2e)

φ = Model correction factor to account for model uncertainties

f = Fraction of methane captured at the SWDS and flared, combusted or used in another manner

4CHGWP = Global Warming Potential (GWP) of methane, valid for the relevant commitment period

OX = Oxidation factor (reflecting the amount of methane from SWDS that is oxidised in the soil or other material covering the waste

F = Fraction of methane in the SWDS gas (volume fraction)

fDOC = Fraction of degradable organic carbon (DOC) that can decompose

MCF = Methane correction factor

xjW , = Amount of organic waste type j prevented from disposal in the

SWDS in the year x (tons)

jDOC = Fraction of degradable organic carbon (by weight) in the waste type j

jk = Decay rate for the waste type j j = Waste type category (index)

x = Year during the crediting period: x runs from the first year of the first crediting period (x = 1) to the year y for which avoided emissions are calculated (x = y)

y = Year for which methane emissions are calculated

1.1. Input Parameters The input parameters used in the FOD model are more or less similar to the LandGEM

model except that IPCC has attempted to make the projections for methane emissions more realistic by incorporating various correction factors to the equation.


The values for correction factors used in the model are mostly default values suggested by IPCC, as mentioned below:

Degradable Organic Carbon ( jDOC )

Degradable organic carbon is the fraction of the organic carbon present in the waste that will degrade under anaerobic conditions. However, only fraction of the DOC is decomposable in nature ( fDOC ). Hence, decomposable degradable organic carbon by mass (

mDDOC )

is:

MCFDOCDOCWDDOC fm ∗∗∗= (4)

Where, W is the mass of the waste deposited in the landfill in the given year and MCF is the methane correction factor for aerobic decomposition of waste.

The relationship between Methane generation potential (0L ) used in LandGEM and

mDDOC , as described in IPCC (2006), is:

1216

0 ∗∗= FDDOCL m (5)

Where, F = CH4 concentration in LFG and 16/12 is the ratio of molecular weight of CH4

and Carbon. MSW contains different types of waste namely food waste, garden waste, paper, wood,

textiles, plastics etc. Different waste types contain different amount of degradable organic carbon (DOC). As per IPCC FOD model, waste composition of MSW is classified into six categories as shown in Table 8.

Decay rate/methane generation rate ( jk )

As already mentioned in the previous section, IPCC has mentioned two alternatives to use the value of k for estimation of gas potential. In this model, the waste composition option is used where degradation of different types of waste is assumed to be independent of each other. IPCC 2006 has recommended default k values for different waste categories dependent upon the location of the landfill site and its climatic conditions as shown in Table 9.

Table 8. IPCC Default DOC Value (In Fraction) For Different Waste Type

Type of Waste DOCj Wood and wood products, A 0.430 Pulp, paper and cardboard, B 0.400 Food, food waste, beverages and tobacco, C 0.150 Textiles, D 0.240 Garden, yard and park waste, E 0.200 Glass, plastic, metal other inert, F 0

Source: IPCC, 2006


Table 9. IPCC Default of K Used in IPCC in IPCC FOD Modeling

Type of Waste K Wood and wood products, A 0.035 Pulp, paper and cardboard, B 0.07 Food, food waste, beverages and tobacco, C 0.40 Textiles, D 0.07 Garden, yard and park waste, E 0.17 Glass, plastic, metal other inert, F 0

Source: IPCC, 2006 D. Regression Models

The EPA Air and Energy Engineering Research Laboratory (AEERL) began a research

program in 1990 with the goal of improving global landfill methane emission estimates. Part of this program was a field study to gather information that was used to develop an empirical model of methane emissions. Twenty-one US landfills with gas recovery systems were included in the study. Site-specific information included average methane recovery rate, landfill size, refuse mass, average age of the refuse, and climate. A correlation analysis showed that refuse mass was positively linearly correlated with landfill depth, volume, area, and well depth. Regression analysis of the methane recovery rate on depth, refuse mass, and volume was significant, but depth was the best predictive variable (R2 = 0.53). Refuse mass was nearly as good (R2 = 0.5). None of the climate variables (precipitation, average temperature, dew point) correlated well with the methane recovery rate. Much of the variability in methane recovery remains unexplained, and is likely due to between-site differences in landfill construction, operation, and refuse composition. A model for global landfill emissions estimation was proposed based on this data. A simple model correlating refuse mass to methane recovery with a zero intercept was developed:

wQmethane 52.4= (6)

Where;

methaneQ = Methane flow rate (m3/min)

w = mass of refuse (Mg)

E- Theoretical Models The theoretical CH4 generation capacity ( 0L ) can be determined by a stoichiometric

method that is based on a gross empirical formula representing the chemical composition of the waste. If a waste contains carbon, hydrogen, oxygen, nitrogen and sulfur (represented by CaHbOcNdSe), its decomposition to gas is shown as:

4 2 2 3 2a b c d eC H O N S vCH wCO xN yNH zH S humus® + + + + + (7)


However, this type of model is of limited use because it provides an estimate of the total amount of gas generated and does not provide information on the rate of generation. It also requires knowledge of the chemical composition of the waste.

F. Other Models El-Fadel et al. (1996b) developed a mathematical model to simulate the biodegradation of

solid waste and biogas generation in a sanitary landfill. The model was based on bio-kinetic equations describing the microbial processes, time dependent transport and generation of gas and heat. The biodegradation process occurred in three stages: hydrolysis, acidogenesis and methanogenesis. They assumed hydrolysis to be the rate limiting step in the biodegradation process and was represented by first order kinetics. Monod kinetics were used to simulate the growth rate of acidogenic and methanogenic biomass. The effect of pH inhibition on the methanogenic growth rate was also included. In El-Fadel et al. (1997) several runs were performed to assess the model sensitivity to the hydrolysis rate constant, the kinetics constant of acidogenic and methanogenic biomass (µ, kd, ks) and initial carbon concentrations (solid, aqueous, acetic acid, acidogenic and methanogenic). They concluded that the hydrolysis rate is the most important parameter in gas generation in landfills. Gas generation showed greater sensitivity to the methanogenic kinetics than to the acidogenic kinetics, and the initial concentrations of acetic acid and methanogenic biomass had a more important impact on gas generation than aqueous and acidogenic biomass.

In El-Fadel et al. (1996c) the model was used to simulate data from the Mountain View controlled landfill. The results of the model showed good agreement with the field data. They concluded that the model could be used to predict the rate and total production of biogases in landfills.

Al-Yousfi et al. (1998) developed a numerical (PITTLEACH) model to predict the leachate quality and quantity and biogas generation from municipal solid waste, for both single pass and leachate recirculation. The model consisted of four phases. In the first phase, the water budget method was used to estimate the net percolation rate of water flow into the waste layer. In the second phase, leachate generation and transport rates were estimated by using the theory of moisture flow through unsaturated porous media. The third step was to simulate the anaerobic process involved in landfill stabilization, including hydrolysis, acid formation and methane fermentation. In the fourth phase, the effect of acids on the pH was modeled. The model was calibrated with experiments done by Pohland et al. (1992) and Yari (1986). The model results were close to the experimental results for both scenarios (single pass and leachate recirculation).

Pareek et al. (1999) developed a mathematical model to predict the methane and carbon dioxide production from landfill reactors operated under sulfate reducing and methane producing conditions. The model was based on biochemical processes responsible for the degradation of solid waste in landfills. These processes were hydrolysis, acidogenesis, methanogenesis and sulfidogenesis. Hydrolysis was assumed to be the rate limiting step in the process and followed first order reaction, whereas the Monod kinetics were applied for the growth of acidogenic and methanogenic bacteria. A multiplicative model was applied to estimate the growth rate of the sulfidogenic bacteria. The values of kinetics required were taken from the literature. The model was calibrated with four experiments run for 700 days.


The simulated methane production was in good agreement with the measured values in all reactors, but the carbon dioxide production was not so accurate in the sulfate reducing reactors for the first 100 days. They concluded that the moisture factor and initial concentration of biomass and acetate were important factors in controlling the microbial growth rates and methane production.

Suk et al. (2000) proposed a numerical model to predict the change in leachate concentration and gas production by microbial activity in landfills. The model included gas and water flows, interphase mass transfer of solids and water phase solutes, microbial growth and death, and aerobic and anaerobic biodegradation. The model was applied to measure gas composition and leachate qualities of the experiments done by Lee (1997). The results of the model matched the experimental data.

Haarstick et al. (2001) developed a mathematical model to simulate the biodegradation of organic wastes (easily and slowly degraded), biogas generation and heat release. The model was based on physical, chemical, thermodynamic and microbial processes occurring in landfills. The biodegradation of organic waste was assumed to follow three biochemical reactions: hydrolysis, acidogenesis and methanogenesis in which Monod kinetics were used for all of them. The specific growth rate was considered to be effected by inhibition terms included substrate limiting, inhibitory substrate, temperature, and pH.

)()()()( 4321max pHfTfsfsf ⋅⋅⋅⋅μ (8) Where;

isi

i

sKssf+

=)(1: Inhibition term for substrate limiting

isi

Ii

sKKsf

+=)(2

: Inhibition term for inhibitory substrate

))((exp)(3 optTTkTf −−= : Inhibition term for influence of temperature

pHpH

pH

IKK

pHf+

=)(4: Inhibition term for influence of pH

The temperature effect is taken into account in the hydrolysis rate constant, and in the

acidogenic and methanogenic bacteria kinetics. The effect of pH on the biodegradation rate is also taken into account by including an inhibition term in the maximum growth rate and expressed as non competitive inhibition. The kinetics required for the model were obtained from the literature. The model was not calibrated with real data.

Naranjo et al. (2004) modified the model of Haarstrick et al. (2001) by assuming the hydrolysis followed first order kinetics. The model was calibrated with experiments. They used the model to simulate the effect of temperature and water content on acetate and methane production. The model showed results similar to the experiments. They concluded that temperature had an impact on the growth and activity of bacteria and that an increase in water content enhanced methane production.


Zacharof et al. (2004) developed a mathematical model to simulate the hydrological and biochemical processes taking place in solid waste landfills. They used a statistical velocity model to represent the water flow through the waste. The waste biodegradation was assumed to follow three steps: hydrolysis, acidogenesis and methanogenesis; and employed a simplified methodology for the rate of biodegradation to reduce the parameter required. The model was used to simulate case studies. Sensitive analysis showed uncertain results. They found the model was sensitive to depth of waste, infiltration rate, waste heterogeneity and biodegradation rate constants. In the end, they concluded that the model could be used as a tool for modeling landfill processes and that further improvements were required to assess the model’s performance.

Yildiz et al. (2004) proposed a mathematical model to simulate the landfill leachate behavior, distribution of moisture through the landfill, and methane production. They assumed that landfills consisted of cells and that each cell consisted of several layers. Also, they considered each layer as a completely mixed reactor having uniformly distributed solid wastes, moisture, gases and microorganisms. The model was based on the governing equations that describe leachate production, solubilization of inorganic and organic matter, degradation of soluble organic matter, the growth of acidogenic and methanogenic microorganisms, and their inhibition by acetic acid, and change in pH over time. The solubilization of inorganic solid waste was assumed to have followed zero order kinetics, whereas the solubilization of organic solid waste was assumed to be a function of the concentration difference in leachate and microbial activity. The growth rate of acidogenic and methanogenic microorganisms were described by the Monod model, and it included an inhibition terms for acetic acid and pH. The model was solved by the fourth order Runge-Kulta method and calibrated with real landfill data from the Keele Valley landfill. The values of the kinetics required for the model were determined by using a trial and error procedure with the data obtained from the landfill. These values were then compared with the literature. There was good agreement between the predicted and observed results from the Keele Valley landfill. They concluded that the model had the potential to be used during the design of the landfills to estimate the quality and quantity of leachate and methane production for different operation conditions.

White et al. (2003, 2004) developed a mathematical model to simulate solid waste biodegradation and gas generation in landfills. The model included biochemical degradation of solid waste, and transport of leachate and gas. The biodegradation part was based on the model proposed by Young (1989) and El-Fadel et al. (1996a) and occurred in three stages: hydrolysis, acidogenesis and methanogenesis. The Monod kinetics were used to simulate the growth rate of biomass in all stages. The moisture content and effect of pH inhibition on the biomass growth rates were included in the model. The required kinetics for the model were obtained from the literature. The model was used to simulate case studies but was not calibrated with real data. They concluded that it could be used for laboratory and field tests to investigate the geotechnical and hydrogeological properties of biodegrading solid waste.


VII. LANDFILL GAS ENERGY SYSTEMS With the recognition of the formation of landfill gas and its associated hazards, and the

potential to utilize the energy content of the gas, the modern landfill site is designed to trap the gases for flaring or use in energy recovery systems, particularly for the landfilling of biodegradable municipal solid waste in non-hazardous waste landfills. The priority for control of the gases is to protect the environment and prevent unacceptable risk to human health, and a landfill gas control system is therefore required. In addition, control mechanisms are required to minimize the risk of migration of the gases out of the site.

Figure 8 shows a schematic diagram of a landfill gas energy recovery project. The energy recovery technology is based around the gas collection system and the pre-treatment and power generation technology. Each of those three systems is explained separately in details.

Figure 8. Schematic diagram of a landfill gas energy recovery scheme. Source: Brown and Maunder 1994.

A. LFG Collection System

Once gases are produced under the landfill surface, they generally move away from the

landfill. Gases tend to expand and fill the available space, so that they move, or "migrate," through the limited pore spaces within the refuse and soils covering the landfill. The natural tendency of landfill gases that are lighter than air, such as methane, is to move upward, usually through the landfill surface. Upward movement of landfill gas can be inhibited by densely compacted waste or landfill cover material (e.g., by daily soil cover and caps). When upward movement is inhibited, the gas tends to migrate horizontally to other areas within the landfill or to areas outside the landfill, where it can resume its upward path. Basically, the gases follow the path of least resistance. Some gases, such as carbon dioxide, are denser than air and will collect in subsurface areas, such as utility corridors. Three main factors influence


the migration of landfill gases: diffusion (concentration), pressure, and permeability. Gases can travel off-site and into neighboring buildings, posing indoor air quality threats such as odors or exposures to inhalation hazards, or even fire and explosion. For these reasons gas control is needed.

There are three types of systems used to control landfill gas migration (Tchobanoglous and O’Leary 1994; McBean et al 1995; Pescod 1991–93; Waste Management Paper 26B, 1995; Waste Management Paper 27, 1994): passive venting; physical barriers; pumping extraction systems.

Passive venting

Passive systems use existing variations in landfill pressure and gas concentrations to vent landfill gas into the atmosphere or a control system. Passive venting systems are only recommended for old sites in the late stages of gas generation where gas generation rates are low, or where inert wastes are landfilled and similarly low or negligible rates of gas generation are found. The passive venting pit consists of a highly permeable vent of gravel material encased in a geotextile fabric to prevent ingress of fine material and reduction of permeability. The gases flow up the highly permeable layer, and vent passively into the atmosphere through a permeable capping layer of sand and granular soil or crushed stone. The vent may also be constructed of granular material but with a central perforated plastic pipe, the pipe venting directly to the atmosphere. Construction of the passive venting system may be as emplacement of the waste proceeds or afterwards by drilling or excavation into the mass of waste. Typically the vents are placed at intervals of between 20 and 50 m and to depths ranging from 50% to 90% of the waste thickness. If groundwater is encountered within the waste, wells end at the groundwater table. Other designs of passive gas venting systems include trenches, which are excavated into or at the boundary of the waste. The trench is lined at the outer edge with a low-permeability barrier and the trench is filled with high-permeability gravel, or perforated pipes are used to vent the migrating gas to the surface (Waste Management Paper 26B, 1995; Waste Management Paper 27, 1994).

Physical barriers

Physical barriers use low-permeability barriers of, for example, flexible polymeric geomembranes, bentonite cement or clay, to contain and restrict the gas migration. Whilst these barriers might form part of a leachate containment system, they are less effective in containing gas. Coefficients of permeability for gas containment are required to be lower than 10−9 m/s. Efficiencies of barriers are improved if they are combined with a means of removing the gas by either passive venting or pumped extraction.

Pumping extraction systems

Pumping extraction systems pump the gas out of the landfill. The gas migrates to gas pits or wells, within the waste, which consist of highly permeable gravel, stones or rubble with a central perforated plastic pipe. The gases pass through the high-permeability vent to a plain imperforated pipe which draws the gases through to the pump. Leachate vapor may also be pumped out with the gas, which has high moisture content, and therefore a leachate condensation trap is required. Figure 9 shows a typical pumping extraction well. The gas pumped to the surface is either flared by self-sustaining combustion or the use of a support


fuel, utilized in an energy recovery system, or if the gas concentrations are sufficiently low, discharged to the atmosphere.

Figure 9. Typical combined leachate and landfill gas collection well. Source: Waste Management Paper 26B, 1995.


B. LFG Pretreatment System A condensate removal system is required, since the gas is at temperatures above ambient

and is saturated with water vapour and organic vapours. As the gas cools the water vapour condenses to form water in the pipe, which reduces the efficiency of gas collection and transport. The condensate system used to remove the water vapour consists of baffled or expansion chambers which cool and condense the water. Condensate systems both below and above ground may be required to de-water the gas. A filter would also be included to remove fine particulate material from the gas flow. The gas is then compressed and possibly passed to a pre-treatment section if a greater degree of clean-up is required, for example, to remove corrosive trace gases and vapor from the gas stream. Such possible pre-treatments may include further filtration, gas chilling to condense certain constituents, absorption and adsorption systems to scrub the gases, and other gas clean-up systems such as membranes and molecular sieves to remove trace contaminants. A large proportion of the landfill gas consists of carbon dioxide which is non-combustible and therefore reduces the overall calorific value of the gas. Therefore, for utilization systems requiring a high specification gas or a high calorific value, then clean-up systems to remove carbon dioxide may be required. Such systems include water scrubbing, absorption on zeolites and membrane separation and are expensive to install and maintain (Brown and Maunder 1994; Stegmann 1996).

C. LFG Utilization System

1. Combustion technologies (Flaring Practices) LFG flaring Combustion is the most common technique for controlling and treating landfill gas.

Combustion technologies such as flares, incinerators, boilers, gas turbines, and internal combustion engines thermally destroy the compounds in landfill gas. Over 98% destruction of organic compounds is typically achieved. Methane is converted to carbon dioxide, resulting in a large greenhouse gas impact reduction. Combustion or flaring is most efficient when the landfill gas contains at least 20% methane by volume. At this methane concentration, the landfill gas will readily form a combustible mixture with ambient air, so that only an ignition source is needed for operation. At landfills with less than 20% methane by volume, supplemental fuel (e.g., natural gas) is required to operate flares, greatly increasing operating costs. When combustion is used, two different types of flares can be chosen: open or enclosed flares.

1.1. Open flame flares

Open flame flares (e.g., candle or pipe flares), the simplest flaring technology, consist of a pipe through which the gas is pumped, a pilot light to spark the gas, and a means to regulate the gas flow. The simplicity of the design and operation of an open flame flare is an advantage of this technology. Disadvantages include inefficient combustion, aesthetic complaints, and monitoring difficulties. Sometimes, open flame flares are partially covered to hide the flame from view and improve monitoring accuracy.


1.2. Enclosed flame flares Enclosed flame flares are more complex and expensive than open flame flares.

Nevertheless, most flares designed today are enclosed, because this design eliminates some of the disadvantages associated with open flame flares. Enclosed flame flares consist of multiple burners enclosed within fire- resistant walls that extend above the flame. Unlike open flame flares, the amount of gas and air entering an enclosed flame flare can be controlled, making combustion more reliable and more efficient.

1.3. Other enclosed combustion technologies

Other enclosed combustion technologies such as boilers, process heaters, gas turbines, and internal combustion engines can be used not only to efficiently destroy organic compounds in landfill gas, but also to generate useful energy or electricity, as described later in this chapter. In addition to flaring, the other options for dealing with landfill gas (once collected) are as follows:

• boilers for making thermal energy • Internal combustion engine for generating electricity • Gas turbine for generating electricity • Fuel cell for generating electricity • Conversion of the methane to methyl alcohol There are limited data comparing emissions from landfill gas flares to energy producing

combustion devices (which includes boilers, turbines and internal combustion engines). According to very limited data in a USEPA 1995 report, carbon monoxide and NOx emissions are highest from internal combustion engines and lowest from boilers. Flares and gas turbines are somewhere in the middle.

Flaring of landfill gas is done either in a candle flare or a shrouded flare. A candle flare is an open air flame. With such, there is no reliable means to monitor for dioxins or other toxic emissions. Shrouded flares involve enclosing the flame in an insulated cylindrical shroud which can be anywhere from 5 to 18 m tall. While dioxins can be tested for in such flares, it is possible that enclosing the flare will keep the post combustion temperature in dioxin-formation range, resulting in increased dioxin emissions. Essentially, this is a loose-loose situation. Most shrouded landfill gas flares have exit temperatures of around 7600C, well above the dioxin formation range (which end around 4000C). In such cases, dioxins will be formed in midair as the exhaust hits the cooler background air after leaving the stack.

Dioxin emissions data are also very sparse. Flares are known to generate more dioxin than internal combustion engines or boiler mufflers. There is high variability in dioxin emissions from landfill gas burners (based on composition of waste dumped and also on the combustion technology - internal combustion engines are much more variable). Burning landfill gas is dirtier than burning natural gas. Whether using an internal combustion engine or a gas turbine, burning landfill gas to produce energy emits more pollution per kilowatt hour than natural gas does.

Some public concerns have been raised about whether the combustion of landfill gas may create toxic chemicals. Combustion can create acid gases such as SO2 and NOx. The generation of dioxins has also been questioned. EPA investigated the issue of dioxin formation and


concluded that the existing data from several landfills did not provide evidence showing significant dioxin formation during landfill gas combustion. Because of the potential imminent health threat from other components of landfill gas, landfill gas destruction in a properly designed and operated control device, such as a flare or energy recovery unit, is preferable to uncontrolled release of landfill gas. Scientists continue to review new information on by- product emissions from landfill gas control devices as it becomes available.

• Boilers

Boilers are among the cheapest options. They produce thermal energy or heat, not electricity. Boilers are generally less sensitive to landfill gas contaminants and therefore require fewer cleanups than other alternatives. Boilers have the lowest NOx and carbon monoxide emissions of the combustion technologies. Landfill gas use in boilers brings in the issue of piping the gas to local industries. While boilers themselves may not require much cleanup of the gas, the pipelines do require some cleanup, since corrosive compounds in the gas (particularly the acids and hydrogen sulfide -- H2S) can damage the pipelines. Among the concerns with this option are the integrity of the pipeline, liability issues, and the economic support of neighboring polluting industries which might use the gas.

• Internal Combustion Engines

Internal combustion engines are the dirtiest technology for burning landfill gas. They emit the most carbon monoxide and NOx and they may be the largest dioxin source of the available technologies.

• Gas Turbines

Gas turbines are somewhere in the middle in terms of carbon monoxide and NOx emissions. There isn't enough data on dioxin emissions from landfill gas turbines to provide an extensive comparison.

• Fuel Cells Fuel cells are the most expensive technology, and they are still largely experimental. EPA

describes fuel cells as "potentially one of the cleanest energy conversion technologies available." In order not to poison the fuel cells, halogenated contaminants must first be removed and destroyed, for example by pyrolysis.

• Conversion of Methane to Methyl Alchol

One option is to convert the methane recovered from landfills into methyl alcohol or methanol. Other novel ideas include converting the carbon dioxide in landfill gas to dry ice for sale to industry.

2. Non-combustion technologies

Non-combustion technologies were developed in the 1990s as an alternative to combustion, which produces compounds that contribute to smog, including nitrogen oxides, sulfur oxides, carbon monoxide, and particulate matter. Non combustion technologies fall into two groups: energy recovery technologies and gas-to-product conversion technologies. Regardless of which non combustion technology is used, the landfill gas must first undergo


pretreatment to remove impurities such as water, NMOC, and carbon dioxide. Numerous pretreatment methods are available to address the impurities of concern for a specific landfill. After pretreatment, the purified landfill gas is treated by non combustion technology options.

Figure 10. Schematic diagram of the Calgary Biocell

2.1. Energy recovery technologies

Energy recovery technologies use landfill gas to produce energy directly. Currently, the phosphoric acid fuel cell (PAFC) is the only commercially available non-combustion energy recovery technology. Other types of fuel cells (molten carbonate, solid oxide, and solid polymer) are still under development. The PAFC system consists of landfill gas collection and pretreatment, a fuel cell processing system, fuel cell stacks, and a power conditioning system. Several chemical reactions occur within this system to create water, electricity, heat, and waste gases. The waste gases are destroyed in a flare.

2.2. Gas to product conversion technologies

Gas-to-product conversion technologies focus on converting landfill gas into commercial products, such as compressed natural gas, methanol, purified carbon dioxide and methane, or liquefied natural gas. The processes used to produce each of these products vary, but each includes landfill gas collection, pretreatment and chemical reactions and/ or purification techniques. Some of the processes use flares to destroy gaseous wastes.

Non-combustion energy recovery systems are not used as widely as combustion based systems. Fuel cells are a promising new technology for producing energy from landfill gas that does not involve combustion. This technology has been demonstrated and in the future may become more economically competitive with other options. One option that does not involve combustion of landfill gas at or near the landfill is purifying the landfill gas to remove constituents other than methane, producing a high British thermal unit (Btu) gas that can be sold as pipeline quality natural gas. Although the high-Btu gas is eventually combusted, it


would not contribute to any emissions near the landfill. Another option is using compressed landfill gas as a vehicle fuel.

Both combustion and non-combustion energy recovery systems have three basic components: (1) a gas collection system; (2) a gas processing, treatment, and conversion system; and (3) a means to transport the gas or final product to the user. Gas is collected from the landfill by the use of active vents. It is then transported to a central point for processing. Processing requirements vary, depending on the gas composition and the intended use, but typically include a series of chemical reactions or filters to remove impurities. For direct use of landfill gas in boilers, minimal treatment is required. For landfill gas injection into a natural gas pipeline, extensive treatment is necessary to remove carbon dioxide. At a minimum, the gas is filtered to remove any particles and water that may be suspended in the gas stream.

VIII. CASE STUDY: CALGARY BIOCELL PROJECT

A. Introduction Although landfill disposal is an integral part of waste management, most people identify

sanitary landfills as a key factor in the mis-management of finite resources and as a source of greenhouse gas emissions. This situation arose because modem landfills have evolved from open dumping of solid waste. Since 1960s, engineers and scientists have attempted to rectify the problems with “open dumps”, targeting groundwater contamination by landfill leachate and waste related aesthetic issues. More recently, attempts have been made to address the landfill gas issues, including the contribution of landfills towards the global carbon budget and potentially global warming. The reactive approach followed by landfill engineers has created collateral problems. For example, the current traditional approach of waste landfilling, namely the dry-tomb landfilling approach, solves the problem of groundwater contamination but is counterproductive because of the slow production and atmospheric release of methane (CH4), and loss of resources (e.g. material and space).

So far, the general approach towards solving the solid waste problem has been mostly piece meal and reactive. Landfills are considered a liability requiring solutions for individual landfill problems. This reactive approach has ignored the positive aspects of solid waste including the inherent resource value of the waste. The pessimistic view of waste is “waste is a liability and requires high level of resources to manage” but the optimistic view of waste is “waste is a resource in the wrong place and wrong time”.

Recent advances in sanitary landfill technology research have indicated that the operation of landfills as bioreactors (Reinhart and Townsend, 1998) could be viable. Waste entombment in a conventional landfill slows down the process of biodegradation by minimizing moisture entry, whereas, bioreactors speed up the biodegradation process by controlled input of moisture (i.e., by leachate recirculation) and increased cycling of nutrients and bacterial populations (Reinhart and Townsend, 1998). The operation of traditional “entombed” landfills for the sole purpose of controlling groundwater contamination is not sustainable, and could be counterproductive because of the slow production and atmospheric release of CH4 and loss of resources (e.g. material and space).


The biocell concept involves the operation of a landfill cell as an anaerobic bioreactor with leachate recirculation to recover the full energy potential of biomass waste. In a second stage, the biocell is operated in the aerobic mode to produce stable organic material, that can be used as low-quality compost or refuse derived fuel (RDF). The input of air and operation of the cell as an aerobic bioreactor (Stessel and Murphy, 1992) enhances waste decomposition to a level where it could be mined in a third stage for compost/RDF and space recovery, thus making the landfill operation sustainable. Instead of operating the “entombed” waste cell as a “long-term storage facility”, the biocell converts the cell into a waste processing facility. The biocell is a novel and holistic approach; with energy recovery, landfill gas emission control, groundwater contamination control, and resource/space recovery as direct benefits. This approach has the potential to revolutionize management of waste in Canada, and in other countries, both developed and developing.

B. The Calgary Biocell: Background and Construction Phase In dry-tomb type sanitary landfills, the preferred landfilling option in the United States,

the underlying principle has been to prevent saturation of the waste in order to reduce the potential for leachate generation and leaking into the sub-surface and groundwater aquifers. In a bioreactor landfill, leachate is re-circulated to maintain high waste moisture content. Data compiled by Rees and Grainger (1982) from lysimeter studies suggest the rate of gas production increases exponentially as the water content of the waste is increased. At the Brogborough landfill in the United Kingdom, addition of water to test cells containing 15,000 tonnes of waste was found to increase the rate of gas production by 8 m3/tonne/yr than that of a control cell (Knox and Gronow, 1995).

There are three different types of bioreactor landfills corresponding to the operational processes involved, aerobic, anaerobic, and hybrid (aerobic-anaerobic) as discussed in Section 2. The primary difference between the aerobic and anaerobic is that, in anaerobic bioreactors, a key objective is to enhance the generation of landfill gas, containing methane and carbon dioxide, under anaerobic conditions, by minimizing oxygen infiltration, whereas, in aerobic bioreactors, the objective is to maintain aerobic conditions by introducing oxygen into the waste mass.

The Calgary biocell is a unique facility where the three processes, anaerobic bioreactor, aerobic bioreactor and mining are sequentially applied in one cell. The Calgary biocell is a full-scale facility, which covers an area of 100 m x 100 m with a waste footprint of 85 m x 85 m and a maximum height of 18 m. The schematic diagram of the biocell is presented in Figure 10. The base of the biocell is 50m x 50m, and it extends 10 m below the ground surface. The shape of the biocell is a pyramidal square frustum increasing sectional area with side slope of 3H : 1V up to ground level. The bottom liner/leachate collection systems are used to minimize groundwater contamination and maximize recovery of leachate. The biocell received 43,000 tonnes of residential (high in organics) and selected commercial wastes, with the resulting feedstock placed in three lifts of 5-6 m each. Collected leachate is re-circulated after ensuring the quality is acceptable. A pipe system was added to re-circulate the collected leachate. Re-circulation of leachate adds the much needed moisture and transfer bacteria from well-inoculated waste to freshly deposited waste, thus accelerating the establishment of microbial community. The biocell is instrumented to gather moisture, temperature and


settlement data. The leachate composition is analyzed on a regular basis. A gas collection system is installed for landfill gas collection and emission control. The produced biogas is collected using this gas collection system comprised of a combination of vertical wells and horizontal trenches. The collected bio-gas is used to produce electrical energy. This gas collection system will also be used to pump air into the waste matrix during the second stage aerobic operation to accelerate biological degradation. A low permeable final biocover was installed to prevent gas escape from the top surface prior to extraction of biogas. Gas/energy recovery has commenced after filling and construction of the final cover.

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Figure 10. Schematic diagram of the Calgary Biocell

The biocell is located at the Shepard landfill owned and operated by the City of Calgary,

Canada. Construction of the biocell started in the summer of 2004. The biocell started receiving domestic municipal solid waste in April 2005. The 1st intermediate cover consisted of a mixture of partly stabilized leaf compost and soil (6:4 wet weight) and was placed in July 2005 over the 1st lift, with a depth of 5 m. Similarly, a 2nd intermediate cover of tree branch mulch was placed in December 2005 over the 2nd lift which was also 5 m in depth. A mixture of stabilized compost and tree mulch (9:1 wet weight) was placed in an area of 10m x 10m in the northwest quadrant. The thickness of both intermediate covers ranged from 30 to 40 cm. The placement of the third and final lift of waste commenced during the third week of January 2006. The materials for the landfill final cover and leachate collection system were selected to facilitate convenient excavation, and to recover, and to reuse all components of the biocell. The biocell reached its final design elevations by April 2006 and was capped initially with a 0.5 m biocover, a granular medium to support methanotrophic bacteria that oxidize methane to carbon dioxoide without producing harmful by-products. The construction was completed in summer 2006 and operation started in September 2006 with gas recovery. The Calgary biocell pilot project used real-time instrumentation to measure settlement during the


construction phase of the biocell. The field data during construction stage was presented in Hunte et al, 2007. According to Hunte et al. (2007) the settlement trend follows the waste filling operation. In addition, based on the load cell data, Hunte et al. (2007) back calculated the average unit weight of waste and also the compression index, two useful parameters of settlement models and found to be consistent with values reported in literature.

C. Operation of the Calgary Biocell The biocell operational plan is illustrated in Figure 11. The operation of each stage is

described below.

Stage of Landfill Timeline Stage I: Anaerobic Bio-Reactor 5 to 7 years Stage II: Enhanced Aerobic Reactor 1 to 2 years Stage III: Mining, Recycling, and Recovery ½ to 1 year Total Expected Life Span of the Biocell 6 to 12 years

Figure 11. Operational Plan of the Calgary Biocell

1. Biocell stage 1: Anaerobic decomposition with gas extraction In a waste cell, the biodegradation rate and landfill gas production depends on

temperature, moisture content, nutrient and organic content in the waste. The higher the organic content, higher will be the gas production. In a conventional dry-tomb sanitary landfill, it may take as long as 50 to 100 years to degrade the majority of biodegradable organics (Crawford and Smith, 1985). In the biocell, such degradation will occur within a ten year time period.

Although the concept of bioreactor landfilling is relatively new, a number of demonstration anaerobic bioreactors are underway in Northern America and Europe (Hettiaratchi, 2006). Crow Wing County Landfill (CWC) located in north central Minnesota was started in 1998 and accepted 50,000 tonnes of waste annually in an area of 5.7 hectares (14.1 acres). Four million gallons of treated and untreated leachate were injected to waste via


horizontal laterals, working face spray; and spray on yard waste composting over intermediate cover (USEPA, 2007). Burlington County bioreactor in northwest New Jersey had full scale leachate and liquid recirculation from 2002 to 2005 in a 4 hectare (10 acre) area accepting about one million tonnes of MSW.

The New River Regional bioreactor was a “research” bioreactor in Union County, north central Florida. It had about one million tonnes of waste in-place in an existing 5.07 hectare (10-acre) area. Leachate was re-circulated into an existing interim capped landfill with an exposed membrane cover. Volume of leachate re-circulated was about 24,600 m3 (6.5 million gallons) to date (USEPA, 2007). Salem County bioreactor in southwest New Jersey is another anaerobic bioreactor with about 2 hectare (5-acre) area. Leachate re-circulated from storage tank and force main to subsurface horizontal injection trenches has been performed since 2000. The rate of moisture addition is about 0.167 m3/tonne (44 gallons/tonne) waste (USEPA, 2007).

Indicators of waste stabilization in these bioreactor landfills include settlement and gas production. The airspace at CWC landfill had been monitored using airspace factor (AUF) calculations. The cell was constructed in 1991 and recirculation began in 1998. Accordingly, the pre- and post-recirculation AUF was 595 kg/m3 (1004 lb/yd3) and 795 kg/m3 (1,341 lb/yd3) respectively. In addition, CWC installed four settlement plates in 2000 and 2001 at the waste level of two of the horizontal laterals. Data indicates that about 20% settlement has occurred within 5 years (USEPA, 2007). Burlington County landfill bioreactor measures quarterly settlement surveys with settlement plates and annual air photography surveys for topographic comparisons. Substantial settlement over the last 4 years of operation was observed increasing the effective density from 500 kg/ m3 (840 lb/yd3) to over 720 kg/ m3 (1,200 lb/yd3) (USEPA, 2007). The New River Regional Landfill measured the settlement with GPS coordinates on the landfill surface with settlement of each nested vertical injection well. The depth of settlement was the greatest at the injection well and declined with radial distance from the well up to 15 m (50 ft) away and then leveled off. The data also showed a distinct linear relationship between total settlement and the amount of moisture added (USEPA 2007). The Salem County bioreactor showed a settlement rate of about 1.5 m (5 ft) per year, which was greater than the rate observed before leachate re-circulation commenced (USEPA 2007). Landfill gas was passively vented at Crow Wing County Landfill and concentrations of methane had been as high as 60%.

At the Calgary biocell, the end of stage 1 will be determined using a combination of settlement and gas generation readings. The gas production rate from October 2006 to September 2008 is shown on Figure 12. The initial gas production rate was low, indicating the microorganism acclimation stage. After leachate recirculation was initiated, the gas production rate increased four-fold to 254 m3/h (150 cfm). Thereafter, the gas production rate decreased gradually and reached a steady state flow rate of 170 m3/h (100 cfm) throughout the winter months. The Calgary Biocell received 43,000 tonnes of waste over a period of about one year. The methane generation potential, calculated from waste composition data, is 120 m3/tonne of solid waste. Hence, in October 2006 the theoretical gas generation rate at the Biocell should be approximately 282 m3/h (166cfm) which is very close to the field measured value of 254 m3/h (150cfm) reported in Figure 12.


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Figure 12. Comparison of Gas Production Data at the Biocell and a Conventional Landfill

For comparison purposes, the Figure 12 includes the cumulative methane generation

curve for a landfill cell containing 43,000 tonnes of waste and operated as a dry-tomb sanitary landfill. The Scholl Canyon model was used to generate this curve using the parameter values; k = 0.023 yr-1 and Lo = 116.7 m3/tonne. The parameter values are those proposed by Environment Canada for a typical sanitary landfill in the province of Alberta. Evidently, the gas production at the biocell is more than 400% higher than that of a dry tomb type sanitary landfill of similar size and configuration located in Calgary, Alberta.

2. Biocell stage 2: Aerobic decomposition

Once methane production decreases to a critical level, the next stage of biocell will initiate, that is to use aerobic degradation to rapidly decompose the remaining organic waste. Since aerobic degradation occurs at a high rate, this stage may take only a year or two to complete.

To convert from anaerobic to aerobic conditions, air has to be introduced to the biocell and maintained to enhance the rate of waste decomposition (Stessel and Murphy, 1992; Hettiaratchi, 2006). The aerobic bioreactor concept was first proposed by Merz and Stone (1962) and there are more than 20 operating aerobic bioreactors in North America. The gas extraction system used during the anaerobic stage will be used to pump air into the landfill to create aerobic conditions, which accelerates and completes biological degradation or organic waste. The recirculation of appropriately adjusted leachate for aerobic degradation is also required for the same reason stated in the first stage of operation. Towards the end of aerobic decomposition, periodic testing of waste from boreholes and the analysis of the leachate would ensure complete biodegradation.

The Calgary biocell is not the first to propose the use of aerobic treatment of waste in a waste cell. Williamson County bioreactor in central Tennessee is one of the existing aerobic


bioreactors. This bioreactor landfill contains about 70,000 tonnes of waste in a cell of area 2.85 hectares (7 acres). Leachate, storm water, and air were injected into vertical risers with force main and header from storage tank that were retro-fitted for the closed landfill. The operation started in June 2000 and approximately 3,785 m3 (one million gallons) of leachate has been re-circulated (USEPA 2007). Two other aerobic landfills are in operation in Georgia (the Columbia County landfill) and in Atlanta (a privately operated bioreactor). For each aerobic landfill system, the air injection comprises of air compressor and piping connected to vertical air injection wells. Leachate collected in holding tanks at each site was pumped back into each aerobic system through a leachate recirculation system installed on top of the intermediate cap. The air injection rates were 56 m3/min and 100 m3/min for the Columbia County Landfill and Atlanta Landfill, respectively (Hudgings and Harper, 1999).

Monthly topographic surveys of Williamson County Landfill bioreactor surface were performed to detect settlement across the site. An initial survey of the landfill bioreactor surface was conducted in January 2000, several months prior to the start-up of the landfill bioreactor as a baseline. Results of settlement as of April 2005 show a 0.53-meter to 1.2-meter drop in the surface elevations since the landfill bioreactor operations began. The comparisons of the April 2005 elevations with the original survey in January 2000 show a 5.1% to 10.7% decrease in waste height over a 59-month period of operation (USEPA 2007). The study conducted in Georgia is interesting since it was conducted after landfills went through anaerobic process first. It was observed that the average settlement was 4.5% and the greatest settlement was 9% at Columbia County Landfill and 10% at Atlanta Landfill. The methane generation was reduced to 50% for the Columbia County Landfill and 50 to 90% for the Atlanta Landfill after aeration started. The operation of each system was also a dynamic process. It was observed in some areas that the decay process would revert back to anaerobic once temperatures decreased and that the air would make its way to other nearby areas, thereby repeating the process. Also, if too much leachate was applied in the aerobic areas, there would be an insufficient amount of oxygen for the bacteria and reverted the decay process back to anaerobic. Conversely, if too little leachate was applied, waste mass temperatures would tend to rise into the thermophillic range (40 to 700C). In several cases, it was also observed that air could provide a cooling effect on the waste mass temperatures above 600C or increase temperatures that were below 200C, provided sufficient moisture was applied (Hudgins, 1998; Hudgins and Harper, 1999).

Partially degraded waste has produced difficulties in post mining attempts. Therefore, before moving to the mining step, it is essential to ensure that most of the organic waste is decomposed before mining commences.

3. Biocell stage 3: Mining for recovery of useful/recyclable products

Mining will ensure recovery of space and various products (Murphy, 1993; Zee et al., 2003). Recycling a biocell involves a series of activities that includes excavation of cell, separating, sorting, and processing of recyclables. Separation of waste based on size can be performed through the use of various types of screens (trammel, vibrating, rotating, and disc). Once recovered, the recyclables can be crushed, bailed or shredded for the convenience of transportation.

Usually, the excavated waste is stockpiled and fed to a shaker with sieves to separate the leftover organic waste. The organics that passes through 1 cm – 5 cm sieve size can be used as compost in agricultural applications or as refuse derived fuel (RDF). The collected non-


biodegradable fraction will be sent to an automatic sorting unit through a feeding belt with a magnetic drum installed on the belt to remove the ferrous metals. The automatic sorting unit will sort through air flotation the light materials such as plastic, and non-degraded packaging wastes from heavier materials such as glass and aluminum based on weight difference. The mixed plastic waste could be shredded into small pieces for further processing.

The majority of the compost-like product resulting from biodegradation is expected to be used as soil conditioner with various agricultural applications. Thermoplastics, such as PETE, PVC, and HDPE, soften when heated and can be recycled and remolded. Cullet, the industrial term for the furnace-ready scrap glass, is one of the most important ingredients of the glass manufacturing process. Cullet requires less energy to melt compared to sand since it already contains additives and can reduce furnace temperature. Recycled paper has many applications in newspaper industry and packaging. Other than these versatile uses, recyclables can be used as feedstock for a number of products, such as plastic lumber park benches or decks made from plastic milk jugs or soda bottles. Also, cardboard containers such as juice boxes and plastics have been used to produce construction materials (El Hagger, 2005).

Even with enhanced biodegradation and recycling processes described above, there will be some residual waste which are non-recoverable, but with high calorific value. These wastes may include plastics, textiles, rubber, waste wood, and a number of other organic waste types. These can be used to produce refuse derived fuel (RDF) and co-incinerated in cement kilns.

D. Summary and Conclusions There are four main problems with landfill operation, namely aesthetic issues,

ground/surface water contamination with leachate, emission of landfill gases, and extensive space requirements. Over the last three decades, the design and operation of sanitary landfills have managed to solve, to a large extent, the first three problems. However, the fourth problem has not been adequately addressed. The biocell is a concept proposed to solve all four problems at the same time. The biocell approach involves sequential operation of a landfill cell to produce methane gas during the first stage of anaerobic degradation, in-situ composting within the cell footprint during aerobic degradation in the second stage and landfill mining for resources and space recovery in a third stage. The resources that can be recovered include compost-like material and recyclables such as plastics, metal, and glass. Non-recovered waste but with high energy content can be used as refuse derived fuel. The practice of this approach will no longer require the need to allocate valuable land for new landfills on an on-going basis and hence will revolutionize the management of municipal solid waste.

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landfill gas at seven U.K. waste disposal sites Environ. Sci. Technol., 31(4), 1054-1061.


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NOTATIONS The following symbols are used in this chapter: (AEERL): Air and Energy Engineering Research Laboratory

ySWDSCHBE ,,4 : Methane emissions avoided during the year y from preventing waste

disposal at the solid waste disposal site during the period from the start of the project activity to the end of the year y (tCO2e)

(BOD): Biochemical Oxygen Demand (CAA): Clean Air Act (CDM): Clean Development Mechanism (CERCLA): Comprehensive Environmental Response, Compensation, and

Liability Act (CH4): Methane (CO2): Carbon dioxide (COD): Chemical Oxygen Demand (CWA): Clean Water Act (CWC): Crow Wing County Landfill (DOC): Degradable Organic Carbon

fDOC : Fraction of degradable organic carbon (DOC) that can decompose

(EPA): Environmental Protection Agency (EU): European Union f : Fraction of methane captured and flared, combusted or used in

another manner F : Fraction of methane in the SWDS gas (volume fraction) (FOD): First Order Decay (GHG): GreenHouse Gases (GWP): Global Warming Potential

4CHGWP : Global Warming Potential (GWP) of methane, valid for the relevant commitment period

(HDPE): High Density Polyethylene (H2S): Hydrogen Sulfide


i : 1Year (IPCC): Intergovernmental Panel on Climate Change k : Methane generation rate (per year)

jk : Decay rate for the waste type j

j : Waste type category (index)

0L : Potential methane generation capacity of the waste (m3/Mg) (LFG): Landfill Gas

iM : Mass of waste accepted in the year I (Mg) MCF: Methane correction factor for aerobic decomposition of waste (MSW): Municipal Solid Waste n : (year of the calculation)- (initial year of waste acceptance) (NIMBY): Not in My Back Yard (NMOC): Non-Methane Organic Compounds (NMVOC): Non-Methane Volatile Organic Compounds. (NSPS): New Source Performance Standards (OSHA): Occupational Safety and Health Administration OX: Oxidation factor (reflecting the amount of methane that is oxidized

in the soil or other material covering the waste (PAFC): Phosphoric Acid Fuel Cell (POTW): Publicly Owned Treatment Works

4CHQ : Annual Methane generation in the year of the calculation (m3/year)

methaneQ : Methane flow rate (m3/min) (RCRA): Resource Conservation and Recovery Act (RDF): Refuse Derived Fuel (SWANA): Solid Waste Association of North America (SWDSs): Solid Waste Disposal Sites

ijt : Age of the jth section of waste mass iM accepted in the ith year

(TOC): Total Organic Carbon (TSS): Total Suspended Solids (UNFCC): United Nations Framework Convention on Climate Change (VOC): Volatile Organic Compounds w : Mass of refuse (Mg) W : Mass of the waste deposited in the landfill (WAC): Waste Acceptance Criteria x : Year during the crediting period: x runs from the first year of the

first crediting period (x = 1) to the year y for which avoided emissions are calculated (x = y)

y : Year for which methane emissions are calculated φ : Model correction factor to account for model uncertainties


Chapter 2

LANDFILL GAS: GENERATION MODELS AND ENERGY RECOVERY

Lidia Lombardi∗ Dipartimento di Energetica “Sergio Stecco”

Università degli Studi di Firenze Via Santa Marta, 3, 50139 Firenze, Italy

ABSTRACT

In this chapter different landfill gas production mathematical models have been analysed, implemented and compared among themselves and with data collected from existing landfills. These models will be presented in the chapter. One of these models has been selected for application to some study cases. The selected model is based on first-order decay equation and considers as basic inputs the years of landfill operation, the amount of municipal solid waste landfilled per year, the municipal solid waste component characterisation and biodegradability. Three different behaviours, in reference to biodegradation rate, have been considered dividing the material categories into rapidly, moderately and slowly biodegradable. The model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system. In particular, reciprocating engines were considered for energy recovery purposes. The landfill gas energy recovery by means of reciprocating engines is a quite widespread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue. For this reason, the selection of an appropriate combination of engines has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions.

Further, in order to investigate the management possibilities to enhance energy recovery, the behaviour of a landfill where leachate is recirculated was observed, recording a more concentrated landfill gas production in a shorter time than in

∗ Tel. +39 055 4796349; Fax +39 055 4796342; [email protected]

Lidia Lombardi 70

conventional landfills - and reproduced by means of adapting the landfill gas production model. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission.

1. INTRODUCTION Energy recovery from landfill gas (LFG) is strongly recommended as a means to reduce

the environmental impact, in terms of Greenhouse Effect (GHE), arising from landfills containing biodegradable wastes (Lombardi et al., 2006). As a matter of fact, biodegradable organic matter contained in Municipal Solid Wastes (MSW) is degraded by anaerobic biological processes in landfills giving place to a LFG, which is approximately composed of 50% methane and 50% carbon dioxide. Hence the LFG has two main features: it is composed of two of the main Greenhouse gases and it has a not negligible heating value (approximately 16.000-17.000 kJ/Nm3).

Simple flare combustion of LFG allows reducing landfill GHE contribution converting methane to carbon dioxide, since Global Warming Potential (GWP) of methane is twenty-one times larger (on mass basis) than GWP of carbon dioxide. When LFG is combusted with energy recovery, both thermal and electric energy can be delivered and landfill GHE is further reduced, considering the avoided emissions from conventional sources of energy, in place of which LFG is exploited.

The proper design of LFG collection and energy recovery system needs to be based on an adequate LFG production estimation during the landfill operation and post-closure phases, this can be done through LFG production modelling.

2. LANDFILL GAS CHARACTERISTICS AND GENERATION MECHANISMS

LFG is composed of a number of gases that are present in large amounts (the principal

gases) and a number of gases that are present in very small amounts (the trace gases). The principal gases are produced from the decomposition of the organic fraction of municipal solid waste (OFMSW) and they include mainly carbon dioxide (CO2) and methane (CH4), but also ammonia (NH3), carbon monoxide (CO), hydrogen (H2) and oxygen (O2) can be present. Trace constituents mainly belong to the VOCs family. The typical percentage composition of LFG is reported in Table 1.

The generation of LFG takes place in different steps. At the beginning, as OFMSW is placed in the landfill, it undergoes microbial decomposition in aerobic conditions, because certain amount of air is trapped within the waste (phase I). When oxygen is depleted, anaerobic conditions begin to develop and after a transition phase (phase II), during which the oxidation/reduction potential decreases, the acid phase (phase III) starts, consisting in

Landfill Gas: Generation Models and Energy Recovery 71

hydrolysis of higher molecular mass compounds into compounds suitable for use by microorganisms as a source of energy and cell carbon, followed by the acidogenesis of the previous formed compounds to produce lower-molecular mass intermediate compounds, as typified mainly by acetic acid (CH3COOH). Carbon dioxide is the principal gas generated in this phase. Small amounts of hydrogen gas will also be produced.

Table 1. Typical composition of LFG (Tchobanoglous et al., 1993)

Component Percent (dry volume basis) Component Percent

(dry volume basis) Methane 45-60 Carbon dioxide 40-60

Sulfides, disulfides, mercaptans, etc. 0-1,0

Nitrogen 2-5 Ammonia 0,1-1,0 Oxygen 0,1-1,0 Hydrogen 0-0,2 Carbon monoxide 0-0,2 Trace constituents 0,01-0,6

The microorganisms involved in this conversion, described collectively as

nonmethanogenic, consist of facultative and obligate anaerobic bacteria. In the following phase – the methane fermentation phase (phase IV) a second group of microorganisms, which convert the acetic acid and the hydrogen to methane and carbon dioxide, becomes more predominant. The microorganisms responsible for this phase are strict anaerobes and are called methanogenic. In this phase both methane and acid formation proceed simultaneously, although the rate of acid formation is considerably reduced. Finally the last phase – the maturation phase (phase V) occurs when almost all the readily available biodegradable organic material has been converted. The rate of LFG generation decreases significantly because most of the available nutrients have been previously removed and the remaining substrates are slowly biodegradable.

The duration of the individual phases in the production of LFG will vary depending on the distribution of the organic components in the landfill, the availability of nutrients, the moisture content of waste, moisture routing through the landfill and the degree of initial compaction.

Figure 1. Generalised phases in the generation of LFG (Tchobanoglous et al., 1993).

Lidia Lombardi 72

3. MATHEMATICAL MODELS FOR LANDFILL GAS PRODUCTION PREDICTION

Mathematical models for LFG production prediction are tools used to estimate, along the

time, gas or methane production from a given amount of waste starting from some input data supplied by the model user.

In technical literature several models have been proposed (EMCON, 1980) (Boyle, 1976) (Ham, 1979) (Halvadakis, 1983) (Findikakis, 1988) (Christensen et al., 1996) (Swarbrick and Lethlean, 1995) (Young, 1995) (Bonori et al., 2001) in order to both estimate the potential amount of LFG that can be produced from a given amount of waste and forecasting the temporal evolution of LFG production.

The models proposed in literature can be classified into: empirical models, stoichiometric models, biochemical models and ecological models.

Empirical models are based on black box approach, correlating input, related to typology of landfilled waste, and output related to LFG production, in reference to collected data from existing landfills and experimental data. These kind of models are very site and data specific.

Stoichiometric models are based on a global stoichiometric reaction, in which the reactant is waste, represented by an empirical chemical formula, and the products include methane and carbon dioxide. Stoichiometric models differ in the selected stoichiometric reaction, in waste components considered and whether they include or not cellular growth. Obtainable results are generally overestimated, since actual biodegradation efficiency is not taken into account.

Biochemical models are based on biodegradable substrate removal equations, using more or less complex kinetics, considering more or less substrates and including or not the parameters influencing the degradation (temperature, moisture, compaction, etc).

Ecological models describes the dynamic coexistence of the different bacterial populations which compete in the waste degradation. Actually these are the only models which are able to highlight nutrients imbalances and substrate characteristics, but their application is quite complex due to the non homogeneous characteristics of landfills and moreover it is too onerous in the frame of LFG collection and recovery.

However, quite often the proposed models are a mixing of different elements, mainly using a stoichiometric sub-model which uses waste composition as input, supplying the amount of biodegradable compounds as output, and a biochemical-kinetic sub-model which supplies the evolution during the time of LFG from biodegradable compounds, on the basis of some parameters as temperature, moisture, etc.

In this chapter the attention is focused on four previously proposed models which are: the Triangular model (Tchobanoglous et al., 1993; Bonori et al., 2001); the Scholl Canyon equation model (Department of the Army U.S., 1995); the LandGEM model (EPA, 2005) and a modified version of first order decay model (Van Zanten and Scheepers 1995).

The Triangular Model In the triangular model, a linear growth of the LFG production rate is assumed until it

reaches a peak after which a linear decrement starts (Tchobanoglous et al., 1993), as shown in


Figure 2. In the original version, LFG production is assumed to start at the end of the first year of full landfill operation and to finish after a finite time tend. The area under the triangle is equal to one half the base (which represents the time during which LFG production lasts) times the altitude (which represents the peak rate of LFG production), therefore, the total amount of LFG produced from an amount Ri of waste placed in landfill at year i is equal to:

iLFGiiendi QttLR max,,,0,0 )(21

⋅−=

(1)

where: L0 = waste potential gas production [m3/t] tend,i = time during which gas production takes place [year] t0,i = time at which LFG production starts for waste placed at year i [year] QLFG,i,max = maximum gas production rate [m3/(t · year)] Ri = amount of waste placed in landfill at year i [t]

LFG

pro

du

ctio

n ra

te [m

/ye

ar]

3

end 0t - tyear

QLFG maxs

Figure 2. Triangular distribution of LFG production rate.

The triangular model, in the original version (Tchobanoglous et al. 1993), considers two different behaviours in biodegradation rate, distinguishing waste components in rapidly biodegradable, which are degraded within five years or less, and slowly biodegradable, which require up to fifty years for degradation. For each of the two categories a triangular LFG production distribution is assumed, characterised by a different peak rate time. The total rate of LFG production from a landfill operated for a given time is obtained graphically – as shown in Figure 3 - by summing the LFG produced from the rapidly and slowly biodegradable portions of waste deposited each year.

In the present chapter, as it will be described later, the Triangular model has been applied considering three different behaviours in biodegradation rate, distinguishing waste components in rapidly, moderately and slowly biodegradable.

Lidia Lombardi 74

Figure 3.. Graphical representation of LFG production over a five-year period from the rapidly and slowly decomposable organic materials in landfill (Tchobanoglous et al., 1993).

Analytically, the LFG production rate in the Triangular model can be described as a function of time as it follows:

iendiitLFG

iendiiiiend

iiiLFGitLFG

iiiii

iiiLFGitLFG

iiitLFG

ttQ

ttttt

ttQQ

ttttt

ttQQ

ttQ

,,,

,max,max,,

max,max,,,,

max,,0,0max,

,0max,,,,

,0,,

,0

,:phase decreasing

,:phase growing

,0

≥=

≤≤−

−=

≤≤−

−=

≤=

(2)

where: QLFG,t,i = LFG production rate at year t for waste placed at year i [m3/(t · year)] tmax,i = time at which LFG production reaches the peak for waste placed at year i [year]

In order to estimate the current emissions from waste placed in all years, Equation 1 and

Equation 2 can be solved for all values of Ri and the results summed:

∑=

=t

yearinitialiitLFGtLFG QQ

,,,

(3)


First Order Decay Model: The Scholl Canyon Equation The Scholl Canyon Model is a model which assumes that LFG generation is a function of

first-order kinetics. This model ignores the first two stages of bacterial activity and is simply based on the observed characteristics of substrate-limited bacterial growth. The LFG production rate is assumed to be at its peak upon initial placement after a negligible lag time –in the original version - during which anaerobic conditions are established and decreases exponentially (first-order decay) as the organic content of the waste is consumed (Department of the Army U.S., 1995). Average annual placement rates are used, and the time measurements are in years. The model equation takes the form:

)(0

kTkcavgLFG eeLRQ −− −⋅⋅= (4)

where: QLFG= LFG generation rate at time T [m3/year] L0= waste potential LFG generation capacity [m3/t] Ravg = average annual acceptance rate of waste [t/year] k = LFG generation rate constant [1/year] c = time since landfill closure [year] (c = 0 for active landfills) T = time since initial waste placement [year]

To allow for variances in annual acceptance rates, the derivative of Equation 4 with

respect to the time can be used to estimate LFG generation from waste landfilled in a single year (Ri) (IPCC, 1996). In this equation, the variable T is replaced with t-i, which represents the number of years the waste has been in the landfill. The resulting equation thus becomes:

)(

0,,itk

iitLFG eRkLQ −−⋅⋅⋅= (5)

QLFG,t,i = the amount of LFG generated in the current year (t) by the waste Ri [m3/year] Ri = amount of waste disposed in year i [t/year] i = the year of waste placement [year] t = current year [year]

In order to estimate the current emissions from waste placed in all years, Equation 5 can

be solved for all values of Ri and the results summed:

∑ ∑= =

−−⋅⋅⋅==t

yearinitiali

t

yearinitiali

itkiitLFGtLFG ekLRQQ

)(0,,,

(6)

Lag time due to the establishment of anaerobic conditions could also be incorporated into

the model by replacing “t” by “t + lag time”. The lag time before which anaerobic conditions are established may range from two-hundred days to several years (Department of the Army U.S., 1995):

Lidia Lombardi 76

)(0,,

lagitkiitLFG ekLRQ −−−⋅⋅⋅= (7)

lag = time to reach anaerobic conditions [year]

Software Application of First Order Decay Model: Landgem U.S. EPA developed LandGEM (Landfill Gas Emissions Model), which is a software for

quantifying LFG emissions, based on the application of Scholl Canyon model in the form of equation (6) (EPA, 2005).

The required inputs for estimating the amount of generated LFG are: design capacity of the landfill; amount of waste in place or the annual acceptance rate; the LFG generation rate constant k and LFG generation potential L0; the number of years of waste acceptance. Default values for k and L0 can be used or site-specific values can be introduced. The software can be operated under the Windows environment. Graphs and reports of estimated gas emissions can be produced.

Modified First Order Model A modified version of the first order decay model assumes that LFG generation is

initially low and then rises to a maximum before declining exponentially. The equation of this model is represented by Equation 8 (Van Zanten and Scheepers, 1995):

)()(,, )1( lagitklagits

oiitLFG ekes

skLRQ −−−−−− ⋅−+

⋅=

(8)

where s = rise phase LFG generation rate constant [1/year]

4. THE ESTIMATION OF K AND L0 IN THE MODELS The tricky parameters for the first order models are the gas generation rate constant (k)

and the waste potential LFG generation capacity (L0). The potential for LFG generation capacity, usually expressed as the volume of gas per

mass of waste, can be estimated based on theoretical prediction, laboratory experiments or actual gas production data. At present, there is no method for determining gas potential that is without fault (Reinhart and Faour, 2005).

Experimental procedure to evaluate the gas potential has been developed (biochemical methane potential - ASTM Method E1196-92), which determines the methane yield of an organic material during its anaerobic decomposition by a mixed microbial flora in a defined medium. Such a procedure has been modified for solid waste (Owens and Chynoweth, 1992), so biochemical methane potential values are available for various waste fractions. Hence on


the basis of waste component characterization, L0 can be calculated as weighted average of biochemical methane potential values.

Actual gas production data have been collected from lysimeters, pilot-scale cells, and full-scale landfills. However, the drawback of utilizing these data is that they reflect gas recovered, not gas generated. Gas recovery efficiency is believed to be far less than 100% and depends on many factors such as the presence and integrity of a cover and the type and quality of the gas collection system. The presence of cracks and fissures will reduce collection efficiency. In addition, these studies rarely last sufficiently long to actually reach the point of total gas production. Further, other data necessary, such as waste mass and actual dates of placement, for determining methane potential may not be available (Reinhart and Faour, 2005).

Theoretical predictions are based on the chemical composition of the waste and would give absolute maximum gas potential. In reality, gas generation would never reach this potential due to the inaccessibility of some waste, the inability to biodegrade all organic wastes, and the likely production of other non-methane carbon compounds other than carbon dioxide. Consequently, theoretical gas potential must be adjusted by a biodegradability factor, also based on various assumptions (Reinhart and Faour, 2005).

The first-order rate constant, k, controls the rate of decline of the first-order model and, consequently, the period of LFG generation predicted by the model. As the value of k increases, the duration of LFG production declines. It would be expected that as conditions within a landfill are optimized with respect to waste degradation (i.e., moisture content, temperature, biodegradability of the waste, etc.), k would increase, assuming that L0 remains the same (Reinhart and Faour, 2005).

In the present chapter both L0 and k have been estimated on theoretical basis, in reference to a component characterization of the waste, specific for the analysed site and reported in Table 2, using a stoichiometric based approach. For each material component the chemical composition, the moisture and the biodegradability coefficients reported in Table 2 have been assumed (Tchobanoglous,1993).

On the basis of component characterisation of waste, chemical composition of each component and biodegradability of each component it is possible to describe the biodegradable fraction, with reference to the unit mass of waste, by the generic formula CaHbOcNdSe. In calculating the biodegradable fraction, it was also considered that not all the biodegradable fraction is available for being converted to LFG according to an efficiency depending on the landfill body temperature as it follows (Tabasaran, 1982):

Biodegradable fraction availability = 0,014 Temp + 0,28 (9)

where Temp is the landfill body temperature expressed in °C. Assuming a landfill body temperature of 35°C the biodegradable fraction availability results 0,77.

The biodegradation process of the organic biodegradable fraction to form the LFG can be described by the global stoichiometric reaction (Tchobanoglous,1993):

SHkNHzCOyCHxOHwSNOHC edcba 23242 ⋅+⋅+⋅+⋅→⋅+

(10)

Table 2. Waste component characterisation for the study case site and assumed values for chemical composition, moisture and biodegradability

Component characterization %

C %SS

H %SS

O %SS

N %SS

S %SS

Inert %SS

Moisture %

Biodegradability %

Organic fraction 17,53% 28,70% 3,10% 29,20% 1,90% 0,60% 36,50% 70,00% 82% Paper and cardboard 32,20% 44,40% 4,40% 40,90% 0,10% 0,30% 9,90% 5,50% 50% Plastics 16,83% 70,50% 11,50% 11,30% 0,90% 0,90% 4,90% 2,00% 0% Textile 6,20% 39,60% 6,50% 25,30% 5,60% 0,70% 22,30% 10,00% 54% Pruning scrap 2,46% 45,50% 8,70% 20,10% 1,80% 0,20% 23,70% 60,00% 60% Wood 6,31% 49,50% 6,00% 42,70% 0,20% 0,10% 1,50% 20,00% 72% Glass and inert 10,61% 0,50% 0,10% 0,40% 0,10% 0,00% 98,90% 2,00% 0% Metals 3,86% 0,50% 0,60% 4,30% 0,10% 0,00% 94,50% 3,00% 0% Sewage sludge 4,00% 47,07% 6,74% 26,43% 5,97% 2,24% 11,54% 70% 57,5%

Table 3. Values assumed for gas generation rate constant, rise phase gas generation rate constant (for modified first order model),

potential gas generation capacity and lag time of materials with different biodegradation velocity

k [1/year] k [1/year] L0 [Nm3/t] L0 [Nm3/t] Lag Time [year] s [1/year] Rapidly biodegradable fractions

Organic fraction Pruning scrap 0,36 13,44 0,3 1,155

Moderately biodegradable fractions Paper and cardboard 0,15 29,54 2 0,346

Slowly biodegradable fractions Textile Wood Sewage sludge

0,07

Calculated as weighted average* 0,139

29,69

Calculated as weighted average* 24,59 5 0,231

* input to LandGEM


Applying the stoichiometric balance to the reaction above it is possible to obtain the stoichiometric coefficients w, x, y, z and k as a function of a, b, c, d, e:

SeHdNHCOedcbaCHedcba

OHedcbaSNOHC edcba

2324

2

82324

82324

42324

++⋅⎟⎠⎞

⎜⎝⎛ +++−

+⋅⎟⎠⎞

⎜⎝⎛ −−−+

→

→⋅⎟⎠⎞

⎜⎝⎛ ++−−

+

(11) Hence, total number of dry kilomoles of LFG will be:

[ 8

23248

2324,

kmoledaededcbaedcbakzyxLFG drykmol ++=+++++−

+−−−+

=+++=

(12)

In order to consider the presence of water vapour in the LFG it has been assumed that the

gas is saturated with water vapour. From the total number of kilomoles it is then possible to calculate the potential gas generation capacity (L0):

][414,22][][33

0 kmolNm

tkmolLFGt

NmL mol ⋅= (13)

Actually, the different components of waste undergo biodegradation according to

different degradation rates. The different behaviours have been considered distinguishing the materials in rapidly, moderately and slowly biodegradable, according to (EMCON, 1980). After a literature review (Nutting, 2001) (US-EPA, 1995) (IGES, 2000) (Metcalf and Eddy (1991) (Baldwin et al., 1998) (Hartz et al., 1982) (Warith and Sharma, 1998) (Lifshits and Galueva, 1997) (McBean et al., 2005) (Christensen et al., 1996), different values for LFG generation rate constant have been assumed for each class of materials with different biodegradation velocity, as reported in Table 3.

Also the potential LFG generation capacities (L0) for each class of material with different biodegradation velocity were calculated separately (calculated values are reported in Table 3) in order to apply the models – when this is allowed by the model itself – in order to proceed with separate calculations and adding up the three contributions of LFG production.

From Equation 11 it is, also, possible to calculate LFG composition, which, in this case, results: CH4 48,23%; CO2 47,95%; NH3 3,39%; H2S 0,42 %. The composition is assumed not to change during the time.

5. APPLICATION OF THE MODELS TO A STUDY CASE The above described models – with the exception of LandGEM – have been implemented

using a calculation worksheet. In reference to Scholl Canyon model, LandGEM and modified first order model the input data consisted in: amount of waste landfilled yearly; potential LFG

Lidia Lombardi 80

generation capacity; LFG generation rate constant. In the case of Scholl Canyon model and modified first order model, calculation have been performed separately for group of waste components with different biodegradation velocity, using values for potential LFG generation capacity and LFG generation rate constant reported in Table 3. Also, for these two models, a lag time was considered, as reported in Table 3.

Concerning the modified first order model, assumed values for the rise phase gas generation rate constant (s) are reported in Table 3 (Youcai et al., 2002).

The LandGEM model does not offer the possibility of considering different velocities of biodegradation for different materials, hence single average values were introduced for potential gas generation capacity and gas generation rate constant, as reported in Table 3. It is not possible to introduce lag time in the software.

The amount of waste landfilled yearly is reported in Table 4. The analysed site is a landfill for non-hazardous waste with an overall capacity of about 3.700.000 m3 located in central Italy. Values until seventh year are real data collected on-site, while values between after eighth year are assumed according to the hypothesis of filling up the site authorised capacity within the ninth year (last year of operation).

Table 4. Amount of waste landfilled yearly in the analysed site

Year Waste [t] Year Waste [t] 1 171.929 7 278.634 2 263.606 8 240.000 3 260.453 9 240.000 4 315.214 10 240.000 5 246.159 11 240.000 6 259.896

The triangular model requires as inputs: amount of waste landfilled yearly; maximum gas

production rate (QLFG,max); time at which gas production starts (t0); time at which the peak rate of gas production occurs (tmax); time at which gas production finishes (tend).

The maximum gas production rate (QLFG,max) was obtained from the total amount of produced LFG i.e. potential gas generation capacity (L0) used for the other models, from equation (1) according to:

0

0max,

2tt

LQend

LFG −=

(14)

Also in this model calculations have been performed separately for group of waste

components with different biodegradation velocity, adding up the results to obtain overall LFG production. Assumed values for start time, peak rate time, end time and maximum LFG production rate for each group of waste components with different biodegradation velocity, are summarised in Table 5.

The results obtained applying the different models, according to the assumed inputs, are shown in Figures 4, 5, 6 and 7. Figure 8 shows the comparison of results obtained from the different applied models.


Table 5. Assumed input parameters for Triangular model

Rapidly biodegradable fractions

Moderately biodegradable fractions

Slowly biodegradable fractions

t0 [year] 0 0 0 tmax [year] 1,92 4,62 9,90 tend [year] 9,63 23,10 49,51 QLFG,max [Nm3/t] 2,78 2,55 1,19

0,0E+00

2,0E+06

4,0E+06

6,0E+06

8,0E+06

1,0E+07

1,2E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81Year

Nm

3

Rapidly biodegradable fractions Moderately biodegradable fractionsSlowly biodegradable fractions

Figure 4. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of Scholl Canyon model.

Results obtained from the different models have been compared with the data of collected LFG at the landfill site during three years of operation, which are reported in Table 6. For the analysed landfill site, the estimation escaped LFG from the landfill surface, is available from a measuring campaign previously carried out, by means of the accumulation chamber method (Cardellini et al., 2003) (Börjesson et al., 2000) (Raco et al., 2005) during the sixth year of operation. The specific carbon dioxide emission resulting from those previous measurements is 350 g/(m2 · day). Assuming a composition of LFG of 50% CH4 and 50% CO2 and an overall landfill surface of about 90.000 m2 (at sixth year), the amount escaped LFG is about 11.713.862 Nm3 in the sixth year. This allows the estimation of the LFG collection efficiency, as shown in Table 6.

Table 6. Collected LFG data, estimated escaped LFG at the studied landfill site

and estimated collection efficiency

Year Collected LFG [Nm3] Escaped LFG [Nm3] Estimated collection efficiency [%] 5 7.500.000 - - 6 7.707.818 11.713.862 40 7 11.500.000 - -

Lidia Lombardi 82

0,0E+00

2,0E+06

4,0E+06

6,0E+06

8,0E+06

1,0E+07

1,2E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81Year

Nm

3

Slowly biodegradable fractions Moderately biodegradable fractionsRapidly biodegradable fractions

Figure 5. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of modified first order model.

0,00E+00

2,00E+06

4,00E+06

6,00E+06

8,00E+06

1,00E+07

1,20E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81

Year

Nm

3

Figure 6. Results of overall LFG production, obtained by the application of LandGEM model.


0,00E+00

2,00E+06

4,00E+06

6,00E+06

8,00E+06

1,00E+07

1,20E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81Year

Nm

3

Rapidly biodegradable fractions Moderately biodegradable fractionsSlowly biodegradable fractions

Figure 7. Results of LFG production, for each group of waste components with different biodegradation velocity, obtained by the application of Triangular model.

0,00E+00

5,00E+06

1,00E+07

1,50E+07

2,00E+07

2,50E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81Year

Nm

3

Scholl Canyon Modified first order Triangular LandGEM

Figure 8. Comparison of results obtained from the different applied models.

Applying the estimated collection efficiency to the model results, it is possible to estimate the collected LFG from the model results and compare it with the collected LFG measured data available for the fifth, sixth and seventh year, as shown in Figure 9.

From a first look at Figure 9, it is evident that the model which fits better the measured data, at least in the years for which data are available, is the Scholl Canyon one. For these reasons the selected model is the Scholl Canyon one.

Lidia Lombardi 84

0,00E+00

5,00E+06

1,00E+07

1,50E+07

2,00E+07

2,50E+07

5 6 7Year

Nm

3

Measured collected landfill gas Scholl Canyon - collectedTriangular - collected Modified first order - collectedLandGEM - collected

Figure 9. Comparison of results obtained from the different applied models with the data of collected LFG.

6. ENERGY RECOVERY The selected Scholl Canyon model has been used to predict the LFG production for the

case-study landfill in order to properly size the energy recovery system along the time. In particular, reciprocating engines were considered for energy recovery purpose. The LFG energy recovery by means of reciprocating engines is a quite wide spread practice in modern landfills, but the energy recovery system definition and sizing, also in reference to its economic convenience, is a crucial and tricky issue.

For this reason, the selection of the engine configuration along the time has been carried out with the aim of obtaining the maximum profits from selling the produced electric energy.

It has been assumed that no LFG collection takes place until the fifth year included, then the assumed collection efficiency coefficient is equal to 40% for the sixth and seventh years, and 60% for the following years (on the basis of the designed improved collection network in the specific plant).

Several sizes of engine have been considered with reference to existing Jenbacher engines (kWe 143, kWe 330, kWe 511, kWe 625, kWe 836, kWe 1048, kWe 1413, kWe 1698). The amount of potential electric energy has been calculated according to:

LFGLFGel VLHVEE ⋅⋅=η (12)

where: EE = electric energy [kW] ηel = engine electric energy conversion efficiency VLFG = LFG flow rate [Nm3/h] LHVLFG = LFG low heating value [kWh/Nm3]


The values of engine maximum LFG flow rate and energy conversion efficiency were retrieved from Jenbacher engine technical forms. Energy conversion efficiency was considered dependant on the engine load (i.e. decreasing when load decreases) according to the indications on Jenbacher engine technical forms.

On the basis of the LFG collected yearly, obtained from the Scholl Canyon model, it is possible to estimate the appropriate size and number of reciprocating engines required every year for the LFG exploitation, considering as constraints the maximum load (i.e. maximum LFG flow rate) for each engine and 90.000 hours as maximum amount of operating hours for each engine (about ten years).

As a matter of fact, during the energy recovery time, different combinations of engine sizes and numbers can be adopted to exploit the LFG: the selection of the final combination, was carried out with the aim of maximising the profits coming from the balance of energy system investment and maintenance costs and electric energy selling earnings.

Assuming the energy recovery to start at the sixth year of landfill operation and to finish in year thirty-eight, a combination of engines which maximises the profit was found, based on the use of one 143 kWe engine, three 625 kWe engines and two 1413 kWe engines, distributed as shown in Figure 10.

0,00E+00

5,00E+06

1,00E+07

1,50E+07

2,00E+07

2,50E+07

3,00E+07

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81

Year

Recovered EE [kWh] Produced LFG [Nm3] Collected LFG [Nm3]

625 kWe625 kWe625 kWe

1413 kWe1413 kWe 143 kWe

143 kWe

Figure 10. Results of produced LFG, collected LFG and recovered electric energy, with the indication of the time during which engines have been used.

The economic evaluation was carried out considering the depreciation annual cost for the engine investment (considering 6,5% interest rate and 10 years investment time), the maintenance costs (assumed 0,03 €/kWh for programmed maintenance plus 3% for non programmed maintenance), the earnings for electric energy (EE) selling assuming a selling price equal to 0,13 €/kWh (considering an engine availability of 88%). Table 7 reports the engine costs. Results in terms of produced EE, overall costs and earnings are reported in Table 8.

Lidia Lombardi 86

The obtained configuration for energy recovery was evaluated also from an environmental point of view, estimating the overall GHE produced, considering the contribution due to the presence of both carbon dioxide and methane in the escaped LFG and considering the contribution due to carbon dioxide (originally present in LFG and obtained from methane combustion) in collected and combusted LFG.

Moreover, it is possible to consider that the amount of electric energy produced by the engines fed with LFG, is no more produced by conventional energy system, this term can be considered as an avoided effect of GHE emissions and then subtracted from the overall balance. Being the specific emission of about 0,551 kg of equivalent CO2/kWh for electric energy production (with reference to the Italian situation (ENEL, 1999)) the overall avoided effect can be calculated. Table 9 summarises the above mentioned contributions.

Table 7. Investment costs and depreciation cost for the selected engines

Engine size Engine cost [€]

Additional cost [€]

Total investment cost [€]

Depreciation [€/year]

kWe 143 252.000 282.500 534.500 74.351 kWe 625 377.000 282.500 659.500 91.740 kWe 1413 689.300 282.500 971.800 135.182

Table 8. Costs and earnings for the LFG energy recovery system

kWe143 kWe625 kWe1413 Produced EE [kWh] 6.513.868 42.315.774 139.652.646 Total produced EE [kWh] 188.678.178 EE selling earnings [€] 846.803 5.501.051 18.154.844 Engine costs + maintenance costs [€] 751.249 2.927.351 2.826.306 Net profit [€] 95.553 2.573.700 15.328.538 Total net profit [€] 17.997.791

Table 9. Contributions to GHE during the landfill life time

GHE from escaped LFG [tCO2eq] 1.221.175 GHE from collected LFG [tCO2eq] 234.839 Total produced GHE [tCO2eq] 1.456.014 Avoided GHE form EE production [tCO2eq] - 103.962 Net produced GHE [tCO2eq] 1.352.052

The simple collection and combustion of LFG (for example by means of flaring) offers

the possibility of reducing GHE with respect to uncontrolled emission of all LFG to atmosphere (in that case the GHE production would be 2.199.035 tCO2eq and the reduction by means of collection and combustion is about 34%). When EE is produced the contribution of avoided GHE allows a further decrease of about 7%. From an energetic point of view, it is possible to calculate an overall energy conversion efficiency, dividing the amount of generated electric energy (Table 8) by the energy content of the LFG (considering the


calculated content of methane) generated in the landfill life time (both collected and non). The value of the overall energy conversion efficiency results about 15%.

In order to highlight the contribution to natural resources conservation, and in particular to saved conventional fossil fuels, the EE production from this renewable source allows to save about 40.599 TEP (ton of equivalent petrol) (assuming an average energy conversion efficiency of 37% for conventional plants).

7. MANAGEMENT OPTION TO IMPROVE ENERGY RECOVERY The Scholl Canyon equation based model has been applied to a second study case in

order to evaluate the possibility of improving energy recovery from LFG by means of leachate recirculation (Corti et al., 2005). The practice of leachate recirculation has been studied in several laboratory cells, pilot cells and real landfills highlighting its beneficial effects on the waste biodegradation process (Reinhart and Townsend, 1998).

In the present chapter, the aim is to highlight the behaviour differences between a landfill where leachate recirculation takes place and a conventional landfill, by means of adapting the Scholl Canyon equation based model previously described.

In order to define the different parameters to be used to describe a conventional landfill and a landfill where leachate is recirculated, the above described model has been applied to simulate the behaviour of an existing reference landfill, where MSW are deposited, in the two periods in which it was operated without leachate recirculation and with leachate recirculation. In order to do this, measured data from a landfill where leachate recirculation takes place were considered and the Scholl Canyon equation based model was built around data and inputs –referred to the analysed landfill - reported in Table 10 and Table 11.

Table 10. Chemical composition of waste component fractions and their humidity,

biodegradability and biodegradation rate category

Material C H O N S Inert Humidity Biode Grada bility

Biode Gradation rate

Organic matter 28,70% 3,10% 29,20% 1,90% 0,60% 36,50% 70,00% 82% Rapid

Paper and cardboard 44,40% 4,40% 40,90% 0,10% 0,30% 9,90% 5,50% 50% Moderate

Plastics 70,50% 11,50% 11,30% 0,90% 0,90% 4,90% 2,00% 0% - Textiles 39,60% 6,50% 25,30% 5,60% 0,70% 22,30% 10,00% 54% Slow Pruning scrap 45,50% 8,70% 20,10% 1,80% 0,20% 23,70% 60,00% 60% Rapid

Wood 49,50% 6,00% 42,70% 0,20% 0,10% 1,50% 20,00% 72% Slow Glass and inert 0,50% 0,10% 0,40% 0,10% 0,00% 98,90% 2,00% 0% -

Metals 0,50% 0,60% 4,30% 0,10% 0,00% 94,50% 3,00% 0% -

Lidia Lombardi 88

Table 11. Waste component characterisation, input parameters for Scholl Canyon model and amount of MSW landfilled yearly in the analysed site

Material Mass composition [%] Lag time [year] K[1/year] Year MWS [t] Organic matter 15,97 0,3 0,69 1 9.883 Paper and cardboard 20,47 1 0,14 2 94.308 Plastics 19,54 - - 3 80.600 Textiles 23,05 5 0,05 4 47.311 Pruning scrap 4,37 0,3 0,69 5 49.598 Wood 4,38 5 0,05 6 36.544 Glass and inert 9,53 - - 7 25.020 Metals 2,69 - - 8 28.413 The application of the previously described Scholl Canyon equation based model,

applying a LFG collection efficiency of 0,75, supplied the results shown in Figure 11, which are compared with the real data collected at the existing reference landfill. As a matter of fact the model fits the real data properly in the period before starting the leachate recirculation (the third year), but it fails after leachate recirculation starts. So, in order to fit the real data after the third year, it is necessary to introduce a proportional coefficient β between reaction rate for a conventional landfill and a landfill with leachate recirculation, defined as reported in Equation 13. It has been assumed that the LFG generation potential remains the same in the case of presence or absence of leachate recirculation.

βLR

CVkk =

(13)

where, kCV = LFG generation rate constant for the conventional landfill [1/year] kLR = LFG generation rate constant for the landfill with leachate recirculation [1/year]

Figure 11. Comparison of model results and collected data for the existing reference landfill.


With a value of β in the range of 2-2,5, it is possible to obtain quite good accordance between real data, after the recirculation beginning, and model results, as shown in Figure 12.

Figure 12. Model results applying different β coefficients.

Further, the modified model has been applied to a hypothetical study case - characterised

by the waste component characterisation and amount of MSW yearly landfilled reported in Table 12 - in order to understand the behaviour differences between a conventional landfill and a landfill with leachate recirculation.

Table 12. Waste component characterisation and yearly landfilled amount

for the hypothetical study case

Material Mass composition [%] Year MSW [t] Organic matter 36,3 1 113.873 Paper and cardboard 21,4 2 111.163 Plastics 12,0 3 107.655 Textiles 5,9 4 104.538 Pruning scrap 3,5 5 101.775 Wood 3,5 6 99.521 Glass and inert 11,0 7 98.865 Metals 6,4

The model results, in terms of produced LFG, are plotted in Figure 13. It is quite

important to note that in the case of landfill with leachate recirculation the 95% of LFG is produced ten years before than in the conventional landfill case. This feature allows the concentration of energy recovery during a smaller period of time.

Lidia Lombardi 90

0,00E+00

2,00E+06

4,00E+06

6,00E+06

8,00E+06

1,00E+07

1,20E+07

1,40E+07

1 6 11 16 21 26 31 36 41 46 51 56

Year

Nm3

Conventional landfill

Landfill with leachate recirculation

Figure 13. Comparison of model results – LFG production - for landfill with leachate recirculation and conventional landfill.

The accelerated biological degradation also strongly contributes to the volume reduction

of the landfilled waste. In order to evaluate the overall waste volume reduction it is necessary to account for both the increasing density of the waste, due to the weight of the upper layers, and the accelerated biodegradation. Assuming that waste density passes from 0,6 to 1 t/m3 in thirty years and then it keeps constant, both in a conventional landfill and landfill with leachate recirculation, and combining this effect with the material loss in LFG, it is possible to estimate the overall volume reduction in the two cases. It was calculated that at the end of the seventh year (last year of operation) in both plants the volume reduction allows further landfilling, but while in the conventional landfill the recovered volume can host about 55.000 t, in the landfill with leachate recirculation about 80.000 t of waste can still be placed. This possibility of higher recovered volumes and higher capacity has been accounted in the following considering as input to the landfill with leachate recirculation the higher amount of waste.

In order to understand the benefits that can derive from leachate recirculation, the two hypothetical plants have been compared from an economic, environmental and energetic point of view.

From an economic point of view, the considered investment costs included: bottom impermeabilisation cost, LFG and leachate collection system costs and capping (Table 13).

In the case of landfill with leachate recirculation a horizontal piping system for both LFG collection and leachate recirculation has been assumed (with a LFG collection efficiency of about 70%), while for the conventional landfill a vertical LFG collection system (with a LFG collection efficiency of about 60%) and a separate conventional leachate draining system were considered.

In order to properly calculate the annual instalment connected to the investments relative to bottom impermebilisation, collection system, capping and flaring it is necessary to consider


the effective utilisation time of the equipment. Table 14 summarises the construction phases and the depreciation times assumed. The interest rate used is 6,5%.

On the basis of the LFG collected yearly in the two considered cases, it is possible to estimate the appropriate size and number of reciprocating engines required every year to use the LFG energy content, assuming to apply LFG collection and energy recovery until about 95% of total LFG is produced. Considering a reciprocating engine average life of ten years, it is possible to calculate the overall number and combination of engines required.

The engine selection has been based on existing models (Jenbacher), using relative large size engine in the high LFG production period and small size engines in the final LFG production. Table 15 summarises the engine number used for each of the considered case.

Table 13. Investment and operation costs for the different considered plants

Equipment Landfill with leachate

recirculation

Conventional landfill with vertical collection system

Bottom impermeabilisation [€] 4.957.803 4.957.803 Collection system (leachate and LFG) [€] 750.000 460.000 Capping [€] 1.816.809 1.816.809

Table 14. Assumed construction phases and the depreciation times

Equipment Construction phases Depreciation time [years] Bottom impermeabilisation All placed at the beginning 8 Capping All placed at the closing time 1 Flare Life time of 1 flare 10 Landfill with leachate recirculation

Collection/recirculation system is placed at three different moments At the beginning After 2 year After 5 years

8 6 3

Collection system

At the beginning After 2 year After 5 years

8 6 3

Conventional landfill with vertical collection system Collection system Collection system is placed at

the beginning Landfill operation time = 8 years

From the electric energy conversion efficiency of the considered engines (143 kW –

34,3%; 625 kW – 38,7; 836 kW – 38,8) it is possible to evaluate the electricity production and assuming an electric energy selling price of about 0,13 €/kWh, it is possible to estimate the gain from electricity sell. The estimation of electricity production also took into account the energy conversion efficiency lowering when energy input is less than nominal size.

Lidia Lombardi 92

Table 15. Number, size and overall investment cost of the reciprocating engines and energy production for each considered case in the operating and post-closure phases

Landfill with leachate

recirculation Conventional landfill with vertical collection system

Considered configurations 4 x 625 kW engines + 1 x 143 kW engines

3 x 625 kW engines + 3 x 143 kW engines

Investment cost [€] 2.246.740 2.469.720 Produced electric energy [GWh] 131 105

Table 16 summarises operation costs, grouping together the costs that last for the same

number of years. Operation cost have been assumed equal for the two different plants considered.

Table 16. Summary of the operation costs

Operation costs [year] [€/year] Personnel, covering soils 8 380.000 Leachate disposal, electricity, water, etc 9 630.000 Mechanical machines, fuels and lubricating oil, machine maintenance 10 275.000

Leachate disposal, environmental and topographic analysis, general maintenance, assurance 49 460.000

Vigilance 58 25.000 From an energy point of view, it is possible to calculate an overall energy conversion

efficiency, dividing the amount of generated electric energy (Table 15) by the energy content of the LFG generated in the landfill life time (assuming an average low heating value of 16.000 kJ/Nm3).

From an environmental point of view, it is possible to calculate the specific GHE production for the different considered cases. Contributions to GHE during operation and post-closure phases come from collected LFG combustion and from uncollected LFG directly emitted to the atmosphere; while after the end of the post-closure phase the residual LFG is all emitted to the atmosphere contributing as well to GHE. These contributions have been calculated for the two cases (landfill with leachate recirculation and conventional landfill). Further, considering that the amount of electric energy produced by the engines fed with LFG, is no more produced by conventional energy system, this term can be considered as an avoided effect of GHE emissions and then subtracted from the overall balance. Being the specific emission of about 0,551 kg of equivalent CO2/kWh for electric energy production (with reference to the Italian situation (ENEL, 1999) the overall avoided effect can be calculated.

Table 17 shows the results in terms of specific disposal cost for disposing one ton of MSW, in the two cases of landfill with leachate recirculation and conventional landfill.

From the economical point of view, it appears that applying the leachate recirculation, even if a slightly higher investment cost for the collection/recirculation system is required, a lower specific disposal cost can be reached in comparison to a conventional landfill. The lower cost is mainly due to the shorter time during which the LFG production exhausts with a


more concentrated energy recovery using a lower number of engines (lower investment), but also to the possibility of higher landfill volume recovery due to the accelerated biodegradation process with a consequent higher amount of disposed waste that corresponds to a higher amount of LFG production.

Table 17. Specific disposal cost for MSW, overall energy

conversion efficiency and specific CO2 emission

Landfill with leachate recirculation

Conventional landfill with vertical collection system

Disposed MSW [t] 817.390 792.518 Total cost [€] 32.980.512 37.679.930 Specific disposal cost [€/tMSW] 40,35 46,28 Overall energy efficiency and environmental impact Overall energy conversion efficiency [%] 25 20 GHE [kgCO2/tMSW] without avoided effects 528 644 GHE [kgCO2/tMSW] with avoided effects 439 571

From the results concerned with overall energy conversion efficiency, a higher value was

obtained for the landfill with leachate recirculation with respect to the conventional landfill. Concerning GHE production the landfill with leachate recirculation allows the reduction

of specific CO2 equivalent emitted per each ton of landfilled waste, thanks to the less LFG emitted directly to the atmosphere after the post-closure phase (without any collection and combustion). When considering avoided effects, since in the landfill with leachate recirculation case a higher energy recovery is possible, a further decrease in CO2 equivalent specific emission is registered.

CONCLUSION Different landfill gas production mathematical models have been analysed, implemented

and compared among themselves and with data collected from existing landfills, selecting one of them for application to some study cases.

The use of landfill gas production models is definitely useful in order to properly design landfill gas collection and energy recovery systems since it supplies an estimation of landfill gas amount during the landfill operation and post-closure phases. The accuracy of the landfill gas production estimation depends in part on the complexity of the model and mainly on the accuracy and specificity of the input data.

The selected model has been used to predict the landfill gas production of a case-study landfill in order to properly size the energy recovery system, with the aim of obtaining the maximum profits from selling the produced electric energy. The obtained configuration for energy recovery was evaluated also from an energetic and environmental point of view, estimating the overall contribution to Greenhouse Effect from escaped landfill gas, collected and combusted landfill gas and recovered electric energy avoided emissions. Energy recovery offers the possibility of decreasing the contribution to Greenhouse Effect, with respect to

Lidia Lombardi 94

simple landfill gas flaring, and the chance to save conventional fuels being a renewable source of energy.

The same selected model was, then, applied to another case-study landfill in order to investigate a management option to enhance energy recovery, consisting in leachate recirculation. The landfill gas production and energy recovery for the conventional landfill and the landfill with leachate recirculation were compared from different points of view: economic evaluation, energy conversion and environmental impact. The economic analysis showed that the specific disposal cost is lower for the landfill with leachate recirculation with respect to the conventional landfill. Moreover, the landfill with leachate recirculation shows better indicator values both for the overall energy conversion efficiency and for Greenhouse Effect specific emission.

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Bonori B., Pasquali G., Bergonzoni M. (2001), “Landfill gas production valued with a mathematical method” in Sardinia 2001 Eighth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

Börjesson G., Danielsson A., Svensson B. H., (2000), "Methane Fluxes from a Swedish Landfill Determined by Geostatistical Treatment of Static Chamber Measurements", in Environmental Science Technology, vol. 34, pp. 4044-4050.

Boyle W.C. (1976), “ Energy recovery from sanitary landfills: a review”. Microbial energy conversion, Schlegel H.G. and Barnes J. Eds.

Cardellini C., Chiodini G., Frondini F., Granieri D., Lewicki J. and Peruzzi L. (2003), “Accumulation chamber measurements of methane fluxes: application to volcanic-geothermal areas and landfills”. Applied Geochemistry, Volume 18, Issue 1, January 2003, Pages 45-54.

Corti A., Lombardi L., Puglierin L. (2005), “Landfill gas production and energy recovery in bioreactor landfill”, Proceedings of SARDINIA 2005, Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

Department of the Army U.S. Army Corps of Engineers Washington (1995). Engineering and Design - Landfill Off-Gas Collection and Treatment Systems, da Environmental Technical Letter, ETL 1110-1-160.

EMCON Associates (1980). “Methane generation and recovery from landfills”. Ann Arbour Science Publisher Inc., Ann Arbour, USA.

ENEL “Rapporto Ambientale 1999” (in Italian). EPA (2005), Landfill Gas Emissions Model (LandGEM) Version 3.02 User's Guide,

EPA/600/R-05/047. Findikakis A.N. et al. (1988), “Modelling gas production in managed sanitary landfills”.

Waste Management and Research, vol. 6, No. 2, pagg 115-124. Halvadakis C.P. (1983), “Methanogenesis in solid waste landfill bioreactors”. PhD Thesys.

Stanford University


Ham R.K. (1979), “Predicting gas generation from landfills”. Waste Age, 11, 50. Hartz K.E., Ham R.K. (1982), “Gas generation rates of landfill samples”. Conservation and

Recycling, 5, 2/3, 133-147. Hartz K.E., Klink R.E., Ham R.K. (1982), “Temperature Effects: Methane generation from

landfill samples.” J. Env. Eng. 108: 629-638. IGES (2000), “Good Practice Guidance and Uncertainty Management in National

Greenhouse Gas Inventories, Institute for Global Environmental Strategies (IGES). IPCC (1996), “Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories”.

Workbook (Volume 2). Lifshits A.and Galueva T. (1997), “Gas production modelling based on the field gas

emissions measurements”, in Sardinia 1997, Sixth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

Lombardi L., Carnevale E., Corti A. (2006) Greenhouse effect reduction and energy recovery from waste landfill”, Energy, Vol. 31, Pag. 3208-3219, Elsevier Science Limited, Oxford (UK).

McBean E., Ritchie S. and Gidda T. (2005), “Landfill gas collection for greenhouse gas credits: an Argentinian case study”, Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

Metcalf and Eddy (1991), “Wastewater engineering: Treatment, disposal, and reuse”. Third Ed. McGraw-Hill, Inc. New York.

Nutting L. (2001), “Evaluating Landfill Gas Potential” Proceedings Training Workshop Sao Paulo, Brazil

Owens. J.M.; and Chynoweth, D.P., 1992. “Biochemical Methane Potential of MSW Components,” International Symposium on Anaerobic Digestion of Solid Waste, Venice, Italy. April 15–17.

Raco B., Scozzari A., Guidi M., Lelli M. and Lippo G., (2005). Comparison of two non invasive methodologies to monitor diffuse biogas emissions from MSW landfills soil: a case study. Sardinia 2005 Tenth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

Reinhart D., Faour A. (2005), First-Order Knetic Gas Generation Model Parameters for Wet Landfills, EPA-600/R-05/072.

Reinhart, D.R., Townsend, T.G., (1998), “Landfill Biorector Design and Operation”, Lewis Publisher.

Swarbrick, G.E. and Lethlean, J.J. (1995), “Physical and bio-chemical modelling of landfill degradation” in Sardinia 1995, Fifth International Waste Management and Landfill Symposium, CISA Environmental Sanitary Engineering Centre, Cagliari, Italy.

T.H. Christensen, R. Cossu, R. Stegmann (1996) “Landfilling of waste: Biogas”, Th. Christensen, E and FN SPON, 237-268.

Tchobanoglous G., Theisen H., Vigil S., (1993), Integrated solid waste management – Engineering principles and management issues. McGraw-Hill, Inc.

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Van Zanten, B., Scheepers, M.J.J. (1995) “Modeling of Landfill Gas Potentials.” in Proceedings of SWANA 18th Annual Landfill Gas Symposium, New Orleans, LA.

Warith M.A. and Sharma R. (1998), “Technical review of methods to enhance biological degradation in sanitary landfills.” Water Qual. Res. J. Canada. 33(3): 417-437.

Young A. (1995), “Mathematical modelling of the methanogenic ecosystem”. Microbiology of Landfill sites, ed. E. Senior, Lewis Publishers, Ann Arbor, pp. 67-89.

Zhao Youcai, Wang Luochun, Hua Renhua, Xu Dimin and Gu Guowei, (2002), A comparison of refuse attenuation in laboratory and field scale lysimeters, Waste Management, Volume 22, Issue 1, 2002, Pages 29-35.


Chapter 3

ENERGY AND MATERIAL RECOVERY FROM BIOMASS: THE BIOREFINERY APPROACH. CONCEPT

OVERVIEW AND ENVIRONMENTAL EVALUATION

Francesco Cherubini∗ and Gerfried Jungmeier Joanneum Research, Institute of Energy Research, Elisabethstraße 5, 8010 Graz, Austria

ABSTRACT

A great fraction of worldwide energy carriers and material products come from fossil fuel refinery. Because of the on-going price increase of fossil resources, the uncertain availability, the environmental concerns and the fact that they are not a renewable resource, the feasibility of their exploitation is predicted to decrease in the near future. Therefore, alternative solutions able to reduce the consumption of fossil fuels should be promoted. Electricity and heat can be provided by a variety of renewable alternatives (wind, sun, water, biomass), while the fossil resource alternative for production of fuels and chemicals can be just biomass, the only C-rich material source available on the Earth, besides fossils.

The replacement of oil with biomass as raw material for fuel and chemical production leads to the development of “biorefinery”, a relatively young concept in the scientific literature. In biorefinery, almost all the types of biomass feedstock can be converted to different classes of biofuels and chemicals through jointly applied conversion technologies. This chapter describes the emerging biorefinery concept and provides an overview of the most important biomass sources, conversion technologies and platforms (or intermediates). The advantages of biorefinery systems over conventional fossil systems are outlined by means of Life Cycle Assessment (LCA): in the second half of this chapter, a LCA of a biorefinery system based on a lignocellulosic feedstock (e.g. wood industrial residues) and producing bioethanol and methyltetrahydrofuran (MTHF) as transportation biofuels, furan resins, fumaric acid and oxygen as chemicals and hydrogen, biomethane, electricity and heat as further energy carriers, is reported. The biorefinery system is compared with a reference system based on fossil sources. Results focus on greenhouse gas (GHG) and energy balances and estimate the possible GHG and fossil energy savings. System performances are also

∗ Corresponding author; tel. +433168761327; fax: +433168761330; e-mail: [email protected]

Francesco Cherubini and Gerfried Jungmeier 98

investigated with calculations of product yields and mass, energy, exergy and C conversion efficiencies. Since the biorefinery system co-produces many high value products, an allocation issue must be addressed. Different allocation procedures (substitution method, and energy, exergy, economic allocation) are therefore used and final results compared. The evaluation of the environmental performances reveals that relevant environmental benefits can be gained with a shift from oil refinery to biorefinery: almost 89% of GHG emissions and 96% of fossil energy demand can be saved.

1. INTRODUCTION Our strong dependence on fossil fuels results on the intensive use and consumption of

petroleum derivatives which, combined with diminishing petroleum resources, causes environmental and political concerns. As a consequence, new renewable sources of energy and chemicals are object of research and development activities. Electricity and heat can be provided by a variety of renewable alternatives (wind, sun, water, biomass and so on), while the fossil resource alternative for production of transportation fuels and chemicals is biomass, the only C-rich material source available on the Earth, besides fossils.

The term “biorefinery” is raising importance in the scientific community and the concept embraces a wide range of technologies able to separate biomass resources (wood, grasses, corn…) into their building blocks (carbohydrates, proteins, fats…) which can be converted to value added products, biofuels and chemicals (see Figure 1). A biorefinery is a facility that integrates biomass conversion processes and equipment to produce transportation biofuels, power, and chemicals from biomass. The biorefinery concept is analogous to today's petroleum refinery, which produces multiple fuels and products from petroleum. The replacement of oil with biomass as raw material will require some changes from the today’s production of goods and service: biological and chemical sciences will play a leading role in the generation of future industries and new synergies of biological, physical, chemical and technical sciences must be elaborated (Kamm et al., 2006a).

A first generation of transportation biofuels and chemicals is today produced from sugars, starches and vegetable oils, giving rise to several issues: these raw materials compete with food for their feedstock and fertile land, their potential availability is limited by soil fertility and per hectare yields and the effective savings of CO2 emissions and fossil energy consumption are limited by the high energy input required for crop cultivation and conversion (Lange, 2007).

PretreatmentBiomass Biomass components

Biomaterials

Conversion technologies Bioenergy

Biochemicals

Figure 1. Simplified scheme of biorefinery: conversion of biomass into bioproducts.

Biorefinery Concept: Energy and Material Recovery from Biomass… 99

These limitations can be partly overcome by the utilization of lignocellulosic materials, such as residues from agriculture, forestry, industry and dedicated crops (Cherubini et al., 2009). The importance of recovering transportation biofuels and chemicals from lignocellulosic biomass feedstocks is evident: they are the most abundant biomass source in the Earth, they can be recovered from residue streams in different sectors, they can be grown in combination with food (e.g. straw and corn stover) or in non-agricultural lands and they have high potential for converting their main components (cellulose, hemicellulose and lignin) into a wide spectrum of biofuels and chemical products (Kamm et al., 2006b; Katzen and Schell, 2006).

Since this is a relatively new concept in the scientific literature, few published papers on environmental performances of biorefinery systems are currently available. This work addresses this aspect: after a definition of the biorefinery concept, a Life Cycle Assessment (LCA) of a biorefinery system based on wood residues is reported.

The chapter starts with a formal definition of biorefinery and a list of criteria that a bioenergy/biomass system has to meet to be a real “biorefinery”. Afterwards, the most important biomass feedstocks, processes and platforms, related to the biorefinery concept, are depicted and a comparison between biomass and oil as raw materials is presented. In order to investigate all the environmental aspects of biorefinery systems, a case study is evaluated by means of Life Cycle Assessment (LCA). The biorefinery system produces bioethanol, furfural derivates, electricity, heat, biomethane, hydrogen and oxygen from wood industrial residues. The biorefinery is compared with a reference system producing the same products from fossil sources. Information concerning product yields and mass, energy, exergy and carbon conversion efficiencies are also reported. Several allocation methods are used to share the environmental burdens of the biorefinery among the co-products and the final results are compared.

2. APPROACHING BIOREFINERY: DEFINITION, CRITERIA AND CHARACTERISTICS

2.1. Background and Current Status

Among the several definition of biorefinery, the most exhaustive was recently performed

by the IEA Bioenergy Task 42 on biorefineries (IEA 2008) (Figure 2):

“Biorefining: the sustainable processing of biomass into a spectrum of marketable products and energy”.

One of the main driving factors for the future development of biorefinery can be seen in the

efficient production of transportation liquid biofuels. The transportation sector is growing steadily and in the same way grows the demand for renewable (bio-)fuels, which can only be provided from biomass. Numerous countries have targets for improving the shares of biofuels in the national transport sector.


Figure 2. Biorefinery recovers energy and materials from biomass sources.

For instance, Europe aims at a share of 5.75% in 2010 and 10% in 2020 of biofuels,

according to the draft directive for renewable energy, while IEA and IPCC expect a significant contribution of biofuels on transportation market in 2030 (10 – 20%) (EBS 2007). The main challenge for biorefinery development is therefore the efficient and cost effective production of transportation biofuels, whereas for the coproduced biomaterials and biochemicals additional economic and environmental benefits might be gained.

The most common biofuels produced today in the world are bioethanol, biodiesel and biogas (or biomethane). Bioethanol production from sugar or corn starch was more than 17 Mtoe in 2005; United States (from corn starch) and Brazil (from sugar cane) are the largest producers (GBEP 2007). Biodiesel, made by combining vegetable oil (from rapeseed, soybean, sunflowers, canola and others) or animal fat with an alcohol and a catalyst through a reaction known as transesterification, is mainly produced in European countries and its total production in 2005 was about 2.5 Mtoe (GBEP 2007). The production of biogas is diffused in all the countries, and in the last few years it has been strong implemented in countries with high feed in tariffs for electricity generation from biogas (especially European countries). In some countries (such as Germany and Sweden), biogas is also used as transportation biofuel, after upgrading to biomethane. For instance, Sweden currently leads the world in automotive biogas production, with a total fleet of approximately 4500 vehicles with 45 % of its fuel supplied by biomethane (Jönsson and Persson, 2003).

Already commercially available biobased products include adhesives, cleaning compounds, detergents, dielectric fluids, dyes, hydraulic fluids, inks, lubricants, packaging materials, paints and coatings, paper and box board, plastic fillers, polymers, solvents, and sorbents.

However, most of these biofuels and biochemicals are produced in single production chains and not with a biorefinery approach, and have raw materials in competition with the food and feed industry. Their exploitation is thereby limited. An alternative can be represented by lignocellulosic materials. In fact, lignocellulosic feedstocks can be supplied either from dedicated crops or as residues from agricultural, forestry and wood industry. This feedstock is made of 3 main components (cellulose, hemicellulose and lignin) which can be refined into different final products using a set of jointly applied technological processes. There is not anymore a competition with the food and feed industry since lignocellulosic biomass can be grown on land which is not suitable for agricultural crops. Moreover, in comparison with conventional starch and oilseed crops that can contribute only with a small fraction (grains and seeds) of the above standing biomass to bioenergy and biochemical


production, biorefineries based on lignocellulosic feedstocks can rely on bigger biomass per hectare yields, since the whole crop is available as feedstock.

Therefore, lignocellulosic raw materials are the most suitable biomass source for providing a large and constant feedstock supply to biorefineries, on condition that sustainable practices and managements are followed. Over the next 10 to 15 years, it is expected that lower cost residue and waste sources of lignocellulosic biomass will provide the first influx of next-generation feedstocks, with cellulosic energy crops expected to begin supplying feedstocks for bioenergy production towards the end of this time frame, then expanding substantially in the years beyond (Worldwatch Institute, 2006).

2.2. Criteria for Biorefinery System In addition to the definition, biorefinery systems should also follow some requisites

which act as guidelines for the future deployment of biorefinery concepts. The criteria which a biomass or bioenergy system has to follow to be named biorefinery are the following:

1. Biomass Refining: a biorefinery, similarly to the upgrading of crude oil that occurs in oil

refinery, is based on feedstock upgrading processes, where raw materials are continuously upgraded and refined. This means that a biorefinery should separate all the biomass feedstock components in order to be individually exploited, leading through a chain of several processes to a high concentration of pure chemical molecules (e.g. ethanol) or a high concentration of molecules having similar functions (e.g. the mixture of C alkanes in FT-fuels).

2. Combustion of residues: a feedstock can not be directly combusted without any previous treatment, since the aim of a biorefinery is to increase the value of the different biomass components as material and energy source. Therefore, the most desirable option is to send combustion for heat and electricity production only the residues and leftovers of the several technological treatments and conversion processes.

3. Value chemicals/materials: a biorefinery should produce at least one value chemical/material product, besides the low-grade and high-volume animal feed and fertilizers, according to the specifications of the first criterion.

4. Fuel-Energy products: as a direct consequence of the second criteria, a biorefinery should produce at least one energy product besides heat and electricity. Therefore, the production of at least one biofuel (liquid, solid or gaseous) is required.

5. Fossil fuel replacement: the products of a biorefinery must be able to replace fossil fuel based products coming from oil refinery, both chemicals and energy carriers. Concerning the chemicals, this objective can be met by producing the same chemical molecule from biomass instead of from fossils (e.g. phenols), or producing a molecule having a different structure but an equivalent function (e.g. succinic acid from biomass vs. maleic anhydride from fossils) or new biobased products able to replace petroleum based products (e.g. synthetic biodegradable plastics from starch). Concerning the fuels, a biorefinery must replace conventional fossil fuels (mainly gasoline, diesel, heavy oil, coal and natural gas) with the production of biofuels coming from biomass upgrading, both liquid (e.g. bioethanol, biodiesel, FT-fuels), gaseous (e.g. synthetic natural gas, hydrogen) and solid (e.g. lignin, charcoal, residues).


6. Energy self-sufficiency: a biorefinery plant should have the aim to run in a sustainable way: all the energy requirements of the several biomass conversion processes should be internally supplied by the production of heat and electricity from combustion of residues. For instance, in a lignocellulosic ethanol plant, lignin, after separation from cellulose and hemicellulose, can be burnt to provide the heat and electricity required by the plant. However, direct external fossil energy inputs are allowed if they ensure economic benefits to the system and do not unduly burden the overall GHG and energy balances.

7. Waste minimization: solid, liquid and gaseous wastes released by a biorefinery should be minimized. This target can be achieved in two ways: using the different biomass components for producing a wide spectrum of multiple products, or setting up “bio-clusters”, where material flow exchanges among different plants are promoted in order to transform a downstream residue of a plant into an upstream raw material for another plant.

2.3. Fossils vs. Biomass as Raw Materials The structure of biorefinery raw materials is totally different from that on which the

current oil refinery is based. Crude oil is a mixture of many different organic hydrocarbon compounds (based on C and H) while biomass is made of different compounds (with a large abundance of O and ashes). The first step of oil refinery is to remove water and impurities, then distill the crude oil into its various fractions as gasoline, diesel fuel, kerosene, lubricating oils and asphalts. Then, these fractions can be chemically changed further into various industrial chemicals and final products.

Unlike petroleum, biomass composition is not homogeneous, because the biomass feedstocks might be made of grains, wood, grasses, biological wastes and so on, and the elemental composition is a mixture of C, H and O (plus other minor components such as N, S and other mineral compounds). This biomass compositional variety is both an advantage and a disadvantage. An advantage is that biorefineries can make more classes of products that can petroleum refineries and can rely on a wider range of raw materials. A disadvantage is that a relatively larger range of processing technologies is needed, and most of these technologies are still at a pre-commercial stage (Dale and Kim, 2006).

In order to be used for production of biofuels and chemicals, biomass needs to be depolymerized and deoxygenated. Deoxygenation is required because the presence of O in biofuels reduces the heat content of molecules and usually gives them high polarity, which hinders blending with existing fossil fuels (Lange, 2007). Chemical applications may require much less deoxygenation, since the presence of O often provides valuable physical and chemical properties to the product.

The main benefits which can be related to an extensive deployment of biorefinery in replace of oil refinery are based on the supply of renewable biomass. In fact, if this is managed with sustainable practices, biomass has a closed carbon cycle: its use release to the atmosphere almost the same amount of CO2 that was captured during the photosynthetic process. Furthermore, unlike fossil resources, biomass resources are locally available for many countries and their provision, together with an implementation and development of biorefinery industries, will create a large number of jobs, especially in rural areas. Therefore, biorefinery technologies should be compact and suitable for local installations.


Another important point concerning biorefinery processing is the fact that environmental impacts and consumption of non renewable resources should be minimized, while complete and efficient biomass use maximized. This ecological perspective requires: analyses of three important agricultural and forestry cycles as carbon (respiration, photosynthesis, and organic matter decomposition), water (precipitation, evaporation, infiltration, and runoff) and nitrogen (N fixation, mineralization, denitrification) and their interdependencies (Gravitis and Suzuki, 1999); system performance evaluations and environmental impact estimations carried out by means of Life Cycle Assessment (Cherubini et al., 2007). Especially soil degradation minimization and biodiversity conservation seems to be two dominating factors to consider in the assessment of biorefinery systems.

With all this, biorefinery represents a change from the traditional refinery based on large exploitation of natural resources and large waste production towards integrated systems in which all resources are used. An example of how the biorefinery of the future will evolve can be found in the history of the existing corn wet-milling industry (Lasure and Min, 2004). Initially the corn wet milling industry produced starch as the major product. As technology developed and the need for higher value products drove the growth of the industry, the product portfolio expanded from various starch derivatives such as glucose and maltose syrups to high fructose corn syrup. Later, fermentation products derived from the starch and glucose such as citric acid, gluconic acid, lactic acid, lysine, threonine and ethanol were added. Many other by-products, such as corn gluten, corn oil, corn fiber and animal feed are now being produced. The final vision is then the development of the technical, commercial and political infrastructure for a biomass refinery (biorefinery), which will be similar to the current oil refinery concept.

3. OVERVIEW OF BIOREFINERY FEEDSTOCKS, PROCESSES AND PLATFORMS

3.1. Biorefinery Feedstocks

The term of feedstock refers to raw materials used in biorefinery, from which biofuels

and biochemicals are produced and recovered by means of a set of jointly applied technological processes.

The biomass of the world is synthesized via the photosynthetic process that converts atmospheric carbon dioxide to sugar. Plants use the sugar to synthesize the complex materials that are biomass. Renewable carbon-based raw materials are produced in agriculture, silviculture and microbial systems.

Although a tremendous variety of biomass resources is available, only four basic chemical structures are of significance for production of biofuels and biochemicals: carbohydrates (sugar, starch, cellulose, hemicellulose), lignin (polyphenols), triglycerides (lipids, vegetable oils and animal fats) and proteins (vegetable and animal polymers made up of amino-acids). The average composition of synthesized biomass in the world is 75% carbohydrates, 20% lignin and 5% other compounds (oils, proteins and so on) (Lichtenthaler, 2006). As a consequence, the main attention of research and development activities should first be focused on efficient access to carbohydrates, and their subsequent conversion to chemical intermediates and corresponding final products.


All the existing types of biomass feedstocks can be divided in five groups: sugar crops, starch crops, oil based materials, grasses, lignocellulosic materials and organic residues and others. In the next sections, each of this group is depicted.

3.1.1. Sugar crops

Concerning sugar crops, they provide sugars in a simple form, i.e. mono- or disaccharides, which can be readily used in conversion processes. Six-carbon, single-molecule “monosaccharide” sugars (C6H12O6) include glucose, galactose and mannose, while the most common 5-carbon sugars (C5H10O5) are xylose and arabinose. The two most important sugar crops are sugar cane and sugar beet which, together with corn (a starch crop), supply almost all the bioethanol that is produced today (Rajagopal and Zilberman, 2007). The drawback of this type of feedstock is that requires dedicated hectares for the production and can compete with the food industry. Chemical structures of glucose and xylose are reported in Figure 3.

Figure 3. Chemical structures of glucose and xylose.

3.1.2. Starch crops

Starch crops provide grains containing starch. Starch (C6H10O5)n is a very large polymer molecule composed of many hundreds or thousands of glucose molecules (polysaccharides), which must be broken down into one or two molecule pieces prior to be fermented to bioethanol or biochemicals. The most widespread starch crops are wheat and corn (Tuck et al., 2006; Wright, 2006). The major drawback of the use of these crops in biorefinery is that they are also used in the food and feed industry and their provision as biorefinery feedstock can have adverse impacts on food supply, soil carbon content (if straws and corn stovers are removed) and land pressure. The chemical structure of starch is illustrated in Figure 4.


Figure 4. Chemical structure of starch (segment).

3.1.3. Oil based materials

Oil based materials are made of triglycerides which typically consist of glycerin and saturated and unsaturated fatty acids (the chain length ranges between C8 and C20). The sources of oils and fats are a variety of vegetable and animal raw materials. Soybean, palm, rapeseed and sunflower oil are the most important in the terms of world wide production (Demibras, 2003; Hill, 2006; Sheehan et al., 2000). Vegetable oils are nowadays used for production of biodiesel by reacting with an alcohol, usually methanol. However, they can also be used as a substrate for chemical reactions thanks to two chemically reactive sites: the double bond in the unsaturated fatty acid chain and the acid group of the fatty acid chain (Biermann et al., 2001). Like sugar and starch crops, oilseed crops are characterized by low yield, high use of agrochemical inputs and competition with food market. In the future, non-edible crops like Jatropha curcas and Pongamia pinnata, which require lower inputs and are suited to marginal lands, may become the most widespread oil crops, especially in dry and semiarid regions (Achten et al., 2007; Rajagopal and Zimermann, 2007). Other sources of oil provision are the food industry, where waste edible oil is mainly generated from commercial services and food processing plants such as restaurants, fast food chains and households (Tsai et al., 2007), and the micro-algae, microscopic single cell aquatic plants with the potential to produce large quantities of lipids. The latter seems to have promising advantages over conventional oil crops because of the possibility to be grown in arid and semi-arid regions with poor soil quality, with a per hectare yield estimated to be many times greater than that of even tropical oilseeds. Moreover, algae can also grow in saline or polluted water, which has few competing uses in agriculture, forestry and industry (Chisti, 2007; Sheehan et al., 1998). A chemical structure of a saturated triglyceride is illustrated in Figure 5.


Figure 5. Chemical structure of triglycerides.

3.1.4. Grasses

Grasses are the raw materials for the so-called green biorefinery. This group includes the large family of green plant materials (green grass from meadows, willow and other natural resources), alfalfa, clover grass, grass silage, immature cereals and plant shoots (Kromus et al., 2006). The main components of green plant materials are carbohydrates, proteins, fibers, fats, amino acids and others. This composition allows to the green biorefinery to produce biogas, lactic acid, amino acids and fibers. An important green raw material source is the green harvesting residue material from agricultural cultivated crops, mainly the green foliage from sugar beet leaves, hemp scrape and leaves.

3.1.5. Lignocellulosic materials

Lignocellulosic materials include dedicated energy crops (such as switchgrass and miscanthus), agricultural residues, forestry wastes, agroindustrial wastes, and other industrial wastes. The importance of lignocellulosic biomass as feedstock for biorefinery is evident: their use allows either the production of valuable biofuels and chemicals able to replace fossil derived products, and the utilization of a wide range of residues of domestic, agricultural and industrial activities.

Among the potential large scale industrial biorefineries, the biorefinery systems based on lignocellulosic feedstocks will most probably achieve the greatest success in terms of market penetrations and product volumes. On the one side the raw material situation is optimum (widespread and easily available), on the other side conversion product have a good position on both the traditional petrochemical and future biobased product market.

All kinds of lignocellulosic biomass are made of three main components: cellulose, hemicellulose and lignin. Cellulose (see Figure 6) has a strong molecular structure made by long chains of glucose molecules (C6 sugars) and is one of the most important raw materials for a variety of industries. Currently, major uses of cellulose are in pulp and paper industry, in medicine and in pharmacy (Kamm et al., 2006b).


Figure 6. Cellulose structure.

In the biorefinery concept, the first treatment which cellulose undergoes is usually acid or enzymatic hydrolysis to glucose, if the feedstock is not pyrolysed or gasified. This sugar monomer is a key chemical that can mainly follow two routes: fermentation or chemical synthesis (Schiweck et al., 1991).

The second main component of lignocellulosic biomass is hemicellulose (see Figure 7), which is relatively easier to breakdown to sugar monomers with chemicals and/or heat than cellulose. It contains a mix of C6 sugars (galactose and mannose) and C5 sugars (xylose and arabinose), which represent a great potential for the production of biofuels or chemicals. Xylose, the most representative sugar in hemicellulose, can mainly undergo three different pathways: hydrogenation to xylitol, acid treatment to furfural and fermentation to bioethanol together with C6 sugars (Kamm et al., 2006b).

Figure 7. Hemicellulose structure.


Figure 8. Fragment of lignin structure.

The third component of lignocellulosic feedstock is lignin, made of phenolic polymers

(see Figure 8). Even if lignin cannot be hydrolyzed to sugars and then fermented, it is useful for other purposes. For instance, it can be used in its polymeric forms as adhesives for wood materials, cement additive and so on, or can be fractionated into low molecular mass compounds (e.g. phenols), completely degraded to gas or liquid bio-oil through gasification or pyrolysis, or burnt as a solid fuel to generate heat and electricity.

Table 1 reports the composition of some lignocellulosic biomass which can constitute the raw materials for biorefinery systems. The abundance of the three main components can vary significantly among the feedstocks. For instance, lignin ranges from 17% in wheat straw up to 28% in softwood.

3.1.6. Organic residues and others

This group refers to the other biomass raw material sources that do not fall into the other categories, i.e. the organic fraction of Municipal Solid Waste (MSW), manure, wild fruits and crops and residues from the food production chain (such as fresh fruit and vegetable). The physical and chemical characteristics of this wide spectrum of biomass resources vary largely. Certain streams such as sewage sludge, manure from dairy and swine farms and residues from food processing are very wet, with moisture contents over 70%. Therefore, these feedstocks are more suited for an anaerobic digestion process to generate biogas, rather than other biofuels or chemicals (Berglund and Börjesson, 2006). Other streams, such as organic MSW, may be more or less contaminated with heavy metals or other elements (Faaij et al., 1997). Clearly, the different properties and characteristic of the biomass wastes require the application of different conversion technologies.


Table 1. Composition of some lignocellulosic feedstocks.

Parameter Unit (dry) Softwood Switchgrass Corn stover Wheat straw

Water % 15 15 15 15 LHV MJ/kg 19.6 18.6 18.51 17.56 Cellulose % 44.55 35.39 38.12 32.64

Glucan (C6) % 44.55 35.39 38.12 32.64 Hemicellulose % 21.9 26.52 25.29 22.63

Xylan (C5) % 6.3 22.44 20.25 19.22 Arabinan (C5) % 1.6 2.73 2.03 2.35 Galactan (C6) % 2.56 0.96 0.74 0.75 Mannan (C6) % 11.43 0.39 0.41 0.31

Lignin % 27.67 18.17 20.24 16.85 Acids % 2.67 2.15 4.84 2.24 Extractives % 2.88 11.46 4.78 12.95 Ash % 0.32 4.28 8.59 10.22 C % 50.26 46.9 46.75 43.88 H % 5.98 5.54 5.49 5.26 O % 42.14 41.96 38.4 38.75 N % 0.03 0.62 0.67 0.63 S % 0.01 0.7 0.1 0.16

Sources: softwood Hammelinck et al., 2005; swithgrass EERE 2008 (biomass sample type: Switchgrass Alamo Whole Plant #94); corn stover EERE 2008 (biomass sample type: Corn Stover Zea Mays Stalks and Leaves w/o cobs #55); wheat straw EERE 2008 (biomass sample type: Wheat Straw (Triticum Aestivum) Thunderbird Whole Plant #154).

3.2. Technological Processes Biomass must be chemically converted for production of biofuels and biochemicals.

Obviously, changes are necessary to convert biomass from a solid to a liquid state. As discussed in the previous section, fundamental is the biomass feedstock composition: it generally has too little hydrogen (which must be added), too much oxygen (which must be rejected), and other undesirable elements (such as nitrogen and sulphur) which also must be rejected (Cherubini and Jungmeier, 2008). The aim of each technological process which acts on raw biomass can be summarized in depolymerising and deoxygenating the biomass components. Especially for producing fuels, deoxygenation is particularly important as the presence of oxygen reduces the heat content of the molecules, while some chemical products may require much less deoxygenation, because the presence of oxygen often provides valuable physical and chemical properties to the compound (Lange, 2007).

In order to convert biomass feedstock into valuable products within a biorefinery approach, several technological processes must be jointly applied in multiple steps. These


technologies can be grouped in 4 main categories: thermochemical, biochemical, mechanical / physical and chemical processes.

3.2.1. Thermochemical processes

There are two main thermochemical processes for converting biomass into energy and chemical products. The first is gasification, which consists in keeping biomass at high temperature (> 700°C) with low oxygen levels to produce syngas, a mixture of H2, CO, CO2 and CH4 (Paisley et al., 1998; Spath and Dayton, 2003). Syngas can be used directly as a fuel or can be a chemical intermediate (platform) for production of fuels (FT-fuels, Dimethyl ether, ethanol, isobutene…) or chemicals (alcohols, organic acids, ammonia, methanol and so on). The second most common thermochemical pathway is pyrolysis, which uses high temperatures (300 – 600°C) in absence of oxygen to convert the feedstock into a liquid pyrolytic oil (or bio-oil), solid charcoal and light gases similar to syngas (Bridgwater and Peacocke, 2000; Guo et al., 2001). Their yields vary with process conditions and for biorefinery purposes the treatment which maximizes the production of liquid bio-oil is the most desirable (flash pyrolysis). The application of bio-oil as a transportation fuel is problematic (see following section) and its use as a chemical source of phenols or levoglucosan is still under development (Helle et al., 2007; Meister, 2002; Zhuang et al., 2001). Together with charcoal, it is generally best suited as a fuel for stationary electric power or thermal energy plants. In addition to gasification and pyrolysis, direct combustion is also included among the thermochemical processes (Gani and Naruse, 2007; Senneca, 2007). This is the most common and oldest form of biomass conversion that involves burning biomass in an oxygen-rich environment mainly for the production of heat. Another less widespread thermochemical process is the biomass hydrothermal upgrading (HTU), which can be conducted at different conditions of temperature and pressure and with or without a catalytic mean (Karagöz et al., 2005; Zhang et al., 2002). The purpose of the HTU process is to convert biomass into the so-called “biocrude”, a liquid fuel with an energy density approaching that of fossil fuels which requires additional treatment before to be used as a transportation biofuel. This technology is still at a research and development stage.

3.2.2. Biochemical processes

Unlike thermochemical processes, biochemical processes occur at lower temperatures and have lower reaction rates. The most common types of biochemical processes are fermentation and anaerobic digestion. The fermentation uses microorganisms and/or enzymes to convert a fermentable substrate into ethanol, the most common fermentation product, but the production of many other chemical compounds (e.g. hydrogen, methanol, succinic acid, among others) is nowadays object of many activities of research and development. Hexoses, mainly glucose, are the most frequent fermentation substrates, while pentoses (sugars from hemicellulose), glycerol and other hydrocarbons have required the development of customized fermentation organisms to enable their conversion to ethanol (Hamelinck et al., 2005; Lynd, 1996). Anaerobic digestion involves bacterial breakdown of biodegradable organic material in the absence of oxygen over a temperature range of about 30 – 65 °C. The main end product of this process is biogas (a gas mixture made of methane, CO2 and other impurities), which can be upgraded up to > 97% methane and used as a surrogate of natural gas (Berglund and Börjesson, 2006; Romano and Zhang, 2008).


3.2.3. Mechanical/physical processes Mechanical/physical processes are processes which do not change the state or the

composition of biomass, but only perform a size reduction or a separation of feedstock components. In a biorefinery pathway, they are usually applied first, because the following biomass utilization requires reduction of the material size within specific ranges, depending on feedstock specie, handling and further conversion processes. Biomass size reduction is a mechanical treatment process that significantly refers to either cutting or commuting processes that significantly change the particles size, shape and bulk density of biomass. Separation processes involve the separation of the substrate into its components, while with extraction methods valuable compounds are extracted and concentrated from a bulk and inhomogeneous substrates (Huang et al., 2008). Lignocellulosic pre-treatment methods, (e.g. the split of lignocellusic biomass into cellulose, hemicellulose and lignin) fall within this category, even if some hemicelluse is also hydrolized to single sugars (Cadoche and Lopez, 1989; Lasser et al., 2002, Sung and Cheng, 2002).

3.2.4. Chemical processes

Chemical processes are those processes which carry a change in the chemical structure of the molecule by reacting with other substances. The most common chemical processes in biomass conversion are hydrolysis and transesterification, but this group also includes the wide class of chemical reactions where a change in the molecular formula occurs. Hydrolysis uses acids, alkalis or enzymes to depolymerise polysaccharides and proteins into their component sugars (e.g. glucose from cellulose) or derivate chemicals (e.g. levulinic acid from glucose) (Lynd, 1996; Sung and Cheng, 2002). Transesterification is the most common method to produce biodiesel today and is a chemical process by which vegetable oils can be converted to methyl or ethyl esters of fatty acids, also called biodiesel. This process implicates the coproduction of glycerine, a chemical compound with diverse commercial uses (Crabbe et al., 2001; Demirabas, 2003; Marchetti et al., 2007). Other important chemical reactions in biorefining are Fisher-Tropsch synthesis, methanisation, steam reforming, catalytic synthesis or reactions, hydrogenation, oxygenation and so on.

3.3. Platforms In biorefinery, the platforms are the intermediates which constitute the link between

feedstock and final products. This concept is similar to the petrochemical industry, where the refinery starts with a massive distillation to separate the crude oil into a large number of intermediates that are further manipulated into the desired products.

Among the several possible alternatives, the chemicals (or mix of chemicals) which are individuated as the most important biorefinery platforms are the following: biogas, syngas, hydrogen, C6 sugars, C5 sugars, levulinic acid, furfural, pyrolytic oil, oil and organic juice.

3.3.1. Biogas

Biogas is a biomass derived gas made of mainly CH4 and CO2. It can be produced either by anaerobic digestion of biological materials or by methanisation of the syngas coming out from gasification. Biogas can be used as such for electricity and heat generation or can be


upgraded to biomethane by removing CO2 and other undesired elements, like H2S (Mozaffarian et al., 2004a; Mozaffarian et al., 2004b). Biomethane can be used as a transportation biofuel, as a stationary biofuel for electricity and heat generation or can be transported through the existing gas infrastructure and substituting natural gas in all its existing applications.

3.3.2. Syngas

Syngas is the product of the gasification process. It is mainly made of CO, H2, CH4 and CO2, but it may also contain different contaminants such as nitrogen, particulates, condensable tars, alkali compounds, H2S, HCl, NH3, HCN and COS. Since these contaminants can lower activity in the FT or other chemical synthesis due to catalyst poisoning, the syngas undergo a cleaning process in which the contaminats are removed and its main components can be tailored to the needs of the following conversion processes, by means of methane reforming (which converts CH4 with steam to CO and H2), water gas shift reaction (adjusts the H2/CO ratio by converting CO with steam to H2 and CO2) and CO2 removal (with an amine). The main products that can be obtained from syngas are: ethanol, methanol, hydrogen, ammonia, FT-fuels, acetic acid, formaldehyde and others (Dybkjaer and Christensen, 2001; Hamelinck et al., 2004; Spath and Dayton, 2003).

3.3.3. Hydrogen

Hydrogen can be produced by syngas after a water shift reaction process (CO + H2O → H2 + CO2), by methane after a steam reforming process (CH4 + H2O → 3 H2 + CO), by alkaline water electrolysis (H2O → H2 + ½ O2) or by fermentation of suitable substrates and microorganisms (Spath and Mann, 2001; Spath and Mann, 2004; Stojic et al., 2003). Hydrogen can be used either as a fuel or as a chemical reducing agent.

3.3.4. C6 sugars

C6 sugars are the most abundant renewable resource available. Glucose is the most important C6 sugar and, in Nature, is present in cellulose, starch or as a free monomer. Other C6 sugars, present in hemicellulose, are arabinose and galactose. Glucose may be used as substrate for producing energy and material product through mainly 3 pathways: a) hydrogenation, leading to sorbitol and 1,2-propylene glycol, b) acid treatment, leading to 5-Hydroxymethylfurfural, levulinic acid and their derivates, c) fermentation, leading to ethanol, other alcohols and organic acids (such as lactic acid, acetic acid, citric acid and others) (Kamm et al., 2006b).

3.3.5. C5 sugars

The most common C5 sugars in biomass feedstocks are xylose and mannose (with xylose having a dominant position). They can be found in the hemicellulose fraction of lignocellulosic raw materials or as free monomers. As in the previous case, there are three main chemical conversion pathways for producing fuels or chemicals from xylose: (a) hydrogenation, producing xylitol, (b) acid treatment producing furfural and its derivates, (c) fermentation, producing bioethanol and other chemicals (Kamm et al., 2006b).


3.3.6. Levulinic acid Levulinic acid (C5H8O3) is formed by acid hydrolysis of C6 sugars and can be easily

converted to chemical derivates, thanks to its high reactivity: since it has both a ketone carbonyl group and an acidic carboxyl group, it can react as a ketone and as a fatty acid.

Figure 9. A possible reaction mechanism of levulinic acid from C6 sugars via HMF (Hayes et al., 2006; Timokhin et al., 1999).

A possible reaction mechanism for the production of levulinic acid from C6 sugars is illustrated in Figure 9. Firstly, cellulose is hydrolyzed to C6 sugars and then levulinic acid is obtained through hydroxymethylfuran (HMF) with an efficiency of 50% (Hayes et al., 2006). Its main derivates are: methyltetrahydrofuran (MTHF, a fuel which can be obtained by dehydratation and hydrogentation), δ-aminolevulinic acid (DALA, a herbicide which can be produced after a chemical synthesis process), diphenolic acids (DA, a polymer constituent coming out from the reaction of levulinic acid with phenols), ethyl levulinate (EL, a fuel produced by the reaction with ethanol) and others (Bozell et al., 2000; Hayes et al., 2006).


3.3.7. Furfural Since there is no synthetic route available for furfural production, this chemical

compound is exclusively produced from lignocellulosic biomass by dehydrating C5 sugars (mainly xylose) which are present in the hemicellulose fraction (see Figure 10). Furfural (C5H4O2), together with its derivates, is an important chemical because is a selective solvent for separating compounds in petroleum refining, gas, oil and diesel fuel. The main furfural derivate is furfuryl alcohol, a basic component for furan resins, but a wide range of products can also be produced through different chemical reactions, such as methylfuran (MF, a pharmaceutical compound), methyltetrahydrofuran (MTHF, a fuel additive), maleic acid (MA, a commodity chemical) and Nylon 6.6 (a polyamide), among others (Kamm et al., 2006b; Vazquez et al., 2007).

Xylose

Furfural

- 3 H2O

Figure 10. Production of xylose from dehydratation of xylose.

3.3.8. Pyrolytic liquid

Pyrolytic liquid is the product of the pyrolysis process applied to biomass feedstocks; in the case of flash pyrolysis, the yield of pyrolytic oil is about 75%. Pyrolytic liquid (or bio-oils) is a multi-component mixture of different size molecules derived from depolymerization and fragmentation of the feedstock. Therefore, the elemental composition of bio-oil and petroleum derived fuel is different, and they cannot be mixed. Pyrolytic liquid has a water content of 20-30%, and an oxygen content of 35-40% (but if only lignin is pyrolysed this value can decrease to 20%); it is highly corrosive and with a lower heating value of 20 MJ/kg (Bridgwater and Peacocke, 2000; Spilae et al., 1998). The 99.7% (dry weight) of pyrolytic oil, is composed of acids, alcohols, aldehydes, esters, ketones, sugars, phenols, guaiacols, syringols, furans, lignin derived phenols and extractible terpene with multi-functional groups. Many of these substances can be extracted, such as phenols, volatile organic acids, levoglucosan and others, but the utilization of pyrolytic oil as a fuel for stationary generation of steam and power remains, to date, the most suitable alternative (Zhang et al., 2007).

3.3.9. Vegetable oil

Vegetable oil can be extracted from nearly any oilseed crop for potential use as biofuels or as a chemical substrate. They are made of triglycerides which typically consist of glycerin and saturated and unsaturated fatty acids. Triglycerides have two chemically reactive sites and thanks to this reactivity, a wide range of products can be produced, such as: biodiesel (giving glycerin as a co-product), dicarboxylic acid (by bio-oxydation), polyamides and polyurethanes (i.e. bio-plastics), among others (Hill, 2006).


3.3.10. Organic juice Organic juice refers to the liquid phase which can be obtained after pressing of fresh

biomass feedstock such as grasses, vegetables, fruits and others. This organic fraction is extremely reach of chemical compounds dispersed in an aqueous solution, mainly organic acids of different size and proteins, which can be extracted and concentrated in order to become value added products.

4. LIFE CYCLE ASSESSMENT OF BIOREFINERY SYSTEMS: A CASE STUDY

4.1. Introduction to LCA

In order to investigate all the environmental aspects of biorefinery systems, an evaluation

by means of Life Cycle Assessment (LCA) of the full production chain, from supply of raw materials to final use of products, is required.

A Life Cycle Assessment study is a tool for evaluating environmental impacts associated with a product, process, or service by identifying energy and materials used and emissions released to the environment; moreover it also allows an identification of opportunities for environmental improvements (Consoli et al., 1993; Lindfors et al., 1995). A typical LCA study consists of the following stages:

1. Goal and scope definition (ISO 14041); 2. Life cycle inventory (LCI) analysis, with compilation of data both about energy and

material flows and on emissions to the environment, throughout the life cycle of the case study (ISO 14041);

3. Assessment of the potential impacts (Life Cycle Impact Assessment, LCIA) associated with the identified forms of resource use and environmental emissions (ISO 14042);

4. Interpretation of the results from the previous phases of the study in relation to the objectives of the study (ISO 14043).

4.2. Goal and Scope Definition

The goal and scope definition is the first part of an LCA, where the purpose, the scope,

the functional unit and the system boundary of the assessment are described. The aim of this work is to analyze a biorefinery system by means of LCA. The

investigated biorefinery is a system where several conversion technologies are jointly applied to produce transportation biofuels, bioenergy and material products. The products of the biorefinery are the following:

1. Transportation biofuels: bioethanol and methyltetrahydrofuran (MTHF); 2. Bioenergy carriers: biomethane, hydrogen, electricity and heat; 3. Biomaterials: furan resins, fumaric acid (FUMA) and oxygen.


Wood industrial residues are used as raw materials and are delivered to the plant in the form of pellets (chemical and elemental composition in Table 1). The results of the biorefinery systems are shown in comparison with a fossil reference system providing the same amount of energy and chemical products from fossil sources. The software tool Gemis is used to model LCA calculations and as database source (Gemis, 2008).

Environmental concerns are focused on energy and greenhouse gas (GHG) balances of biorefinery and fossil reference systems, because reduction of GHG emissions and decrease of fossil fuel consumption are two driving forces of biomass utilization strategies. As a direct consequence of the definition, a biorefinery is characterized by multiple useful outputs (both energy and material products). This fact gives rise to an allocation issue, which was addressed using different allocation methods.

Finally, biorefinery system performances are investigated by means of several indices and indicators such as conversion yields and mass, energy, exergy and C efficiencies.

4.2.1. Biorefinery: scope and system boundaries

Wood industrial residues are the raw materials for this biorefinery system. The feedstock is assumed to be collected from industries, transported to a pellet facility (20 km), where it is dried and pelletized, and transported to the biorefinery plant (100 km). The GHG emissions estimated for collecting, processing and delivery of raw materials to biorefinery gates are equal to 1.94 g CO2-eq./MJpellets, while the primary fossil energy consumption is 8.47 kJ/MJpellets (Gemis, 2008).

FermentationHydrolysisPre-treatment

Combustion

Anaerobic digestion

Acid treatment

Chemical reactions

C5 sugars

C6 sugars

Alkaline water electrolysis

Distillation

O2

H2

Feedstock

Furfural

Lignin & residues

Waste-water

MTHF

Furan resins

FUMA

Fertilizer

Biogas

Oxygen

HydrogenElectricity

Heat

Biomethane

Bioethanol

Legend

ProcessFeedstock

Intermediate

Energy Product

Material Product

Output not exploited

CO2

Upgrading

Figure 11. Process scheme of the investigated biorefinery.

This biorefinery produces bioethanol from fermentation of C6 sugars, furfural from hydrolysis of C5 sugars (which is then chemically converted to fuel additive and other chemicals), electricity and heat from combustion of lignin and residues, hydrogen and oxygen through alkaline water electrolysis and biomethane and fertilizer via anaerobic digestion of wastewaters (Figure 11).


The lignocellulosic feedstock (530 ktonnes/a) is pretreated through an acid catalyzed hydrolysis step which splits the raw material in 2 flows: a solid flow containing cellulose and lignin and a liquid flow containing the hydrolyzed C5 sugars. The pretreatment occurs at temperatures higher than 160°C and with a reaction time of 2-10 minutes (Sun and Cheng, 2002). The liquid flow is made of C5 sugars (xylose and arabinose monomers coming from hemicellulose hydrolysis with an efficiency of 95%) which are treated with a dilute sulfuric acid solution at low temperature for a short period of time. The product output is furfural, obtained with an efficiency of 90% by the following reaction: C5H10O5 → C5H4O2 + 3H2O (Kaylen et al., 2000).

Furfural is then converted to the following products (Kamm et al., 2006b; Vazquez et al., 2007):

Figure 12. Conversion of furfural to MTHF via methylfuran.

• 70% to the fuel additive methyltetrahydrofuran (MTHF) by reduction with H2 via the

intermediate methyl furan, as illustrated in Figure 12 (1st reaction: C5H4O2 + 2H2 → C5H6O + H2O, molar efficiency 80%; 2nd reaction: C5H6O + 2H2 → C5H10O, molar efficiency 95%; both reactions needs a Ni catalyst; overall yield 76%);

• 15% to furan resins, made by polymerization of furfural, furfuryl alcohol or other compounds containing a furan ring;

• 15% to fumaric acid (FUMA) by oxidation (followed by opening of the furan ring) in presence of a V2O5 catalyst (C5H4O2 + 2O2 → C4H4O4 + CO2) (Figure 13).

Figure 13. Conversion of furfural to FUMA via oxidation.


The reactants H2 and O2 are internally produced in the biorefinery system by alkaline water electrolysis; 89% and 22% of the generated H2 and O2 are required in the production of MTHF and FUMA.

The solid fraction coming out from pretreatment step is subjected to a further hydrolysis to hydrolyze the remaining cellulose and other C6 polymers and separate lignin. The conversion efficiencies are the following (Hamelinck et al., 2005):

• from cellulose to glucose 90%, • from galactan to galactose 82%, • from mannan to mannose 89%. About 2% of cellulose is lost during acid recycle activities, while 9% is set aside for

bacteria cultivation; all the C6 sugar monomers are then fermented to bioethanol with the following efficiencies (Hamelinck et al., 2005):

• glucose to ethanol 93%, • galactose and mannose to ethanol 90%. Bioethanol is finally recovered via distillation. Lignin (lower heating value 22.9 MJ/kg) and the unconverted cellulose and hemicelluse

(lower heating value15.63 MJ/kg) are combusted to produce electricity and heat with an efficiency of 26% and 44%, respectively (De Feber and Gielen, 2000). Ashes are delivered to landfill. Since H2 and O2 are required for the chemical conversion of furfural to its derivates, 20% of the total electricity output is destined to water electrolysis, which generates H2 with an energy efficiency of 77% and O2 at a rate of 7.92 g/gH2 (Gemis, 2008). Wastewaters coming from xylose conversion to furfural and C6 sugar fermentation are anaerobically digested to produce biogas. These wastewaters have a total dry matter content of 54.4 ktdry and generate biogas at a rate of 6 GJ/tdry (Berglund and Börjesson, 2006). The produced biogas has a heating value of 24 MJ/m3 and methane content of 60% (Alzate and Toro, 2006). Undesired methane emissions to the atmosphere during digestion and biogas treatments are estimated to be 3.47 mg/MJ and the upgrading of biogas to biomethane (CH4 content greater than 97%), by removing impurities and CO2, needs 5% of the energy content of the biogas (Gemis, 2008).

Fossil energy consumption and GHG emissions related to the supply of auxiliary materials (such as sulphuric acid, lime, urea, sodium hydroxide, potassium chloride, phosphporic acid and sodium sulfite) are calculated using the software tool Gemis, while the quantities come from (Kaylen et al., 2000). Other releases of GHG emissions are the following (Gemis, 2008):

• Emissions from lignin (and biomass residue) combustion in turbine, estimated to be

1.59 g CO2-eq./MJ of heat set free from combustion; • Emissions from combustion of bioethanol in a passenger car, assumed to be 3 g CO2-

eq./km (with a specific consumption of 2.45 MJ/km); • Emissions from combustion of biomethane in its final use (0.67 g CO2-eq./MJ).


Because of a lack in available data, the GHG emissions from MTHF combustion and its specific consumption in cars are assumed to be equal to bioethanol. Since the combustion of these biofuels (e.g. lignin and biomass residues, bioethanol, biomethane and MTHF) releases CO2 which has a biological origin, it is not accounted for as a GHG and the above emission factors are mainly due to N2O and CH4.

This biorefinery plant requires 0.16 MWh of electricity and 0.60 MWh of heat per ton of feedstock for producing bioethanol and furfural (Kaylen et al., 2000), while 7.5 kJ of heat per g water are needed to distil the water required by the electrolysis process (Gemis, 2008). The anaerobic digestion step and following biogas upgrading requires 0.65 GJ of electricity and 0.1 GJ of heat per tonne of dry matter in wastewaters (Berglund and Börjesson, 2006).

4.2.2. Biorefinery material products

All the products produced by biorefinery systems can be grouped in two broad categories: material products and energy products. Energy products are those products which are used for their energy content, providing electricity, heat or transportation service. On the other hand, material products are not used for an energy generation purpose but for their chemical or physical properties. The chemical structure of energy and material products of the investigated biorefinery system are reported in Figure 14.

The market share of products produced from biomass is expected to rise from the current level of 5% to 20% in the short run (Sauer et al., 2007). In fact, these products are favourable from a chemical point of view. Functional groups that must be introduced by costly oxidative process steps into oil are already available in plant materials. It is noteworthy that for many biomass derived chemicals the actual market is small, but an economical production process will create new markets by providing new opportunities for the chemical industry. For example, succinic acid and formic acid could replace the petroleum-derived commodity chemical maleic anhydride. The market for maleic anhydride is huge, whereas the current market for the organic acids mentioned is small.

The material products of the analyzed biorefinery system are fumaric acid, furan resins, O2

and fertilizers. Fumaric acid (HO2CCH=CHCO2H) is a carboxylic acid currently produced from the oxygenation of the fossil derived product benzene. It is mainly used in medicine, in food industry as a food acidulent, in chemical industry and in the manufacture of polyester resins and polyhydric alcohols. Fumaric acid has an annual production of 12 ktonnes but a projected market volume of more than 200 ktonnes (Sauer et al., 2007). The uses are the following: 35% as paper size resins, 22% as food acidulant, 15% in unsaturated polyester resins, 6% in alkyd resins, 5% as plasticizers and 17% miscellaneous (including lubricating oils and oil field fluids, esters, inks, lacquers, carboxylating agent for styrenebutadiene rubber) (CMR, 2008).

Furan resins are made by polymerization or polycondensation of furfural, furfuryl alcohol or other compounds containing a furan ring, or by reaction of these furan compounds with other molecules (not over 50%). The major uses of furan resins are as foundry binders and their production in biorefinery is assumed to play a major role in chemical conversions of furfural. Another chemical product is oxygen in its diatomic form (O2), which can be used in a lot of chemical applications like oxidizing agent. Fertilizers are the residues of the anaerobic digestion step which can partly replace the use of synthetic fertilizers. However, due to a lack of data on its use and fossil fertilizers replacement rate, no benefits from this material output are considered in LCA calculation.


Figure 14. Chemical structures of the bioproducts from the biorefinery: bioethanol, biomethane, MTHF, furfural and fumaric acid

4.2.3. Biorefinery energy products

The energy products of the biorefinery are bioethanol, MTHF, biomethane, hydrogen, electricity and heat. The production of large quantities of biofuels or fuel additives via renewable feedstocks offers perhaps the greatest potential for mass-market penetration of biorefineries.

Bioethanol is one of the most common transportation biofuels currently produced in the world and can replace gasoline in vehicles. Biomethane is obtained from upgrading of biogas by removing CO2 and other undesired elements, like H2S. Biomethane can be used as a transportation biofuel or can be transported through the existing gas infrastructure and substituting natural gas in all its existing applications.

Methyltetrahydrofuran (MTHF) is produced from furfural by reduction to methyl furan, which is then reduced to MTHF (both reductions occur with H2). MTHF is a very important compound because it can be added to gasoline (to be blended at the refinery rather than later in the distribution process) or bioethanol up to 30% by volume without effects on performances and engine modification. Using MTHF as a fuel additive increases the oxygenate level in gasoline without adversely affecting engine performance. MTHF also boasts a high octane rating (87) and a low vapour pressure, thereby reducing fuel evaporation and improving air quality. Although it has a lower LHV than gasoline, it has a higher specific gravity and hence mileage is competitive. Properties of MTHF as fuel are reported in Table 2.

Hydrogen is produced via alkaline water electrolysis and is used as a reducing agent for conversion of furfural to MTHF at the biorefinery plant site. This can be seen as an innovative way to safely store H2 in a transportation biofuel. The remaining H2 fraction is delivered to the market.


Table 2. Selected properties of MTHF as a transportation biofuel.

Property Unit MTHF Boiling point (102 mmHg) °C 20 Boiling point (Atm.) °C 80 Flash point °C 11 Reid vapour pressure psig 5.7 Lower heating value MJ/kg 32 Specific gravity 0.813 Octane rating 80

Electricity and heat are produced by combustion of lignin and process residues. Part of

this electricity and heat production is used to meet the plant energy demand and the rest is delivered to the public grid.

4.2.4. Fossil reference system

LCA environmental performances of the analyzed biorefinery system are compared with those of a fossil reference system based on oil refinery, producing the same amount of energy and chemical products. A comparison between the two systems is illustrated in Figure 15.

Collection

Electric netHeating network

Biorefinery plant

Processing

Transport

Biofuel vehicles

Distribution

Natural decomposition

Extraction & Conveyance

Transport

Power plant

Electric net

Extraction & Conveyance

Transport

Refinery

Distribution

Gasoline vehicles

Products and services (transportation, chemicals, electricity, heat, H2,

methane)

Biorefinery Reference System

Wood residues

Heavy oil GasolineChemicals

Heating plant

Heating network

Distribution

Steam reforming

Distribution

Natural gas Oil

H2

Chemicals and H2

Distribution

Air

Processing

Distribution

O2

Figure 15. Comparison between production chains: biorefinery system vs. fossil reference system.


The biorefinery chain starts at the top with carbon fixation from the atmosphere via photosynthesis, or, as it occurs in this case study, biomass C taken as biomass waste from the forest sector. At the end of the biorefinery chain a certain amount of useful energy and products are supplied. Along the whole process chain, all the energy and material inputs and emissions occurring for planting and harvesting the crop (or collect the raw materials), processing the feedstock into fuels and products, transporting and storing of the feedstock, distributing and final use of the products must be accounted for in a life cycle perspective (Schlamadinger et al., 1997). Particular importance should be given to the numerous co-products which a biorefinery may produce, because they can have relevant implications in the assessment of the overall system.

The fossil reference system is dealt with in a similar way, considering all the material and energy inputs and emissions associated with its life cycle stages: production of the raw fossil fuel, refining, storage, distribution and combustion. If compared in this manner, the differences between the two systems producing the same product/service can be presented.

Table 3 reports the bioproducts produced by the investigated biorefinery and the fossil conventional counterparts that they replace. In the right part of the table the environmental impacts, in terms of GHG emissions and total energy demand, of the fossil derived products are listed: these are the GHG emissions and energy consumption saved by the biofuels and biochemicals of the biorefinery. These values, reported in the right part of the table, have been calculated by means of the LCA software tool Gemis (Gemis, 2008).

Table 3. Table reporting the conventional alternatives of the different products

of the biorefinery and their specific factors for GHG emissions and fossil energy consumptions.

Biorefinery Fossil reference system

Bioproducts Conventional alternative Unit g CO2-eq./unit MJtot./unita

Bioethanol Gasoline km 189 2.36 Electricity Electricity from natural gasb MJ 120 1.96 Heat Heat from oilc MJ 106 1.32 Biomethane Conventional methaned MJ 76 1.31 MTHF Gasoline km 189 2.36 H2 H2 from natural gas MJ 72 1.24 Furan resins Epoxy resins g 6.07 0.13 Fumaric acid Conventional fumaric acid g 1.29 0.05 O2 Conventional O2 (from air) g 0.07 0.001 Fertilizer No benefits

a Mainly fossil energy (> 98%) b Large scale gas-fired combined-cycle (CC) power plant with efficiency of 57% and low NOx burner; it

is assumed that 1/3 of the electric capacity comes from the steam turbine. c Heavy oil boiler for industrial process heat, efficiency 85%. d Including emissions from combustion in natural gas boiler (66.15 g CO2-eq./MJ), efficiency 85%.


The transportation biofuels bioethanol and MTHF replace conventional gasoline as a liquid transportation fuel in passenger cars. It is assumed that the electricity and heat produced by the biorefinery substitute, respectively, electricity produced from natural gas turbine and heat generated from a heavy oil boiler.

Regarding the two remaining biofuels, biomethane (fed to the national grid) replaces conventional natural gas in its applications as a stationary fuel while bio-H2 replaces conventional hydrogen production from steam reforming of natural gas.

Concerning the chemicals, their GHG emissions and fossil energy requirements were been estimated considering their production chains in the current oil refinery. It is assumed that furan resins replace epoxy resins.

Epoxy resins are polymers originated from polymerization of epoxy monomers, and are produced by reaction of epichlorohydrin and bisphenol-A. Epichlorohydrin is a highly reactive epoxide and polymerizes upon treatment with acid or strong base; bisphenol A, commonly abbreviated as BPA, is an organic compound with two phenol functional groups and constitutes a building block of several important polymers and polymer additives. Epoxy resins are used as adhesives (they are one of the few adhesives that can be used on metals), as protective coatings, as materials in electronic circuit boards and for patching holes in concrete pavement. In Figure 16, the chemical structures of BPA, epichlorohydrin and the reaction mechanism leading to epoxy resins, are illustrated.

Figure 16. Reaction between BPA and epichlorohydrin and formation of epoxy resins.


Conventional fumaric acid is currently produced from oxygenation of benzene (C6H6 + 4O2 → C4H4O4 + 2 CO2H2). The chemical properties of fumaric acid can be anticipated from its component functional groups. This weak acid forms a diester, it undergoes additions across the double bond, and it is an excellent dienophile.

The O2 produced by the biorefinery plant (via alkaline water electrolysis) replaces the molecular oxygen (O2) that is currently produced from processing of air, from which O2 is separated. About 100 million tonnes of O2 are extracted from air for industrial uses annually. The most common method to recover O2 is to fractionally-distill liquefied air into its various components, with nitrogen N2 distilling as a vapor while oxygen O2 is left as a liquid (Emsley, 2001).

4.2.5. Functional unit

The functional unit is the foundation of biorefinery systems LCA: it sets the scale for comparison of different technological routes which a biomass feedstock can undergo in order to be converted to biofuels and chemicals. One of the main purposes of the functional unit is to provide a reference to which the input and output data are normalized and the basis by which the final results are shown. For instance, the results of a bioenergy system from dedicated biomass crops should be expressed on a per hectare basis, since the available area for the production of biomass raw materials is the biggest bottleneck for the production of biofuels (Schlamadinger et al., 2005). However, in order to be comparable, biorefinery results have the need to be independent from the kind of biomass feedstock (dedicated crops or residues) and from the conversion processes which act on the biomass raw materials. As a consequence, they cannot be expressed per hectare basis or per unit of output. The most suitable functional unit is then the unit of biomass input which, in this study, is the amount of biomass treated per year by the biorefinery: 530 ktonnes/a. Therefore, all the input flows reported in the following inventory list and the final results of GHG emissions and cumulated primary energy demand are referred to this amount of biomass input.

4.2.6 Allocation

Allocation in LCA is carried out to attribute shares of the total environmental impact to the different products of a system. This concept is extremely important for biorefinery systems, where multiple energy and material products are produced. The question of the most suitable allocation procedure is still an open issue. Scientific LCA publications show benefits and disadvantages of several allocation methods (Curran 2007; Ekval and Finnveden, 2001; Frischknecht 2000; Wang et al., 2004).

The ISO standards suggest to avoid allocation by expanding system boundaries, when possible. This method relies on the expansion of the product system to include the additional functions related to the co-products. This procedure (also called substitution method) has the advantage to avoid allocation issues while has the disadvantage to make the system too complex, especially if multiple co-products are present (like in biorefineries). In fact, this method relies on identification of a main product and the environmental benefits of co-products are assumed as credits, which are subtracted to the total GHG emissions and the remaining emissions are completely assigned to the main product. Furthermore, the identification of one of the output as main product is an arbitrary choice and can be a difficult decision in biorefinery systems, where multiple useful and valuable outputs are produced. Therefore, system expansion is not recommended when an elevated number of high quality outputs is produced; this situation can even lead to a negative value (i.e. below zero) of the


burdens allocated to the main product. Where system expansion cannot be applied and the allocation cannot be avoided, ISO norms suggest that the inputs and outputs of the system should be partitioned between its different products or functions in a way which reflects the underlying physical relationships between them (physical allocation); i.e. they shall reflect the way in which the inputs and outputs are changed by quantitative changes in the products or functions delivered by the system (Curran 2007). Where physical relationship alone cannot be established or used as the basis for allocation, the inputs should be allocated between the products and functions in a way which reflects other relationships between them. If system expansion cannot be applied, input and output data might be allocated between co-products in proportion to thermodynamics parameters (such as energy or exergy content of outputs) or to the economic value of products.

Allocation based on energy content of products can be easily carried out but its application is inconsistent (i.e. lacking of a correct logical relation) and results in misleading conclusions if there are some products which are not used as energy carriers (e.g. chemicals). Allocation based on exergy overcomes this inconsistency but can be problematic to be applied because of the difficulties for estimating the exergy content of substances (especially new bio-based products). Allocation based on economic values focuses on external characteristics of the products and has the disadvantages that do not take into account the environmental perspective and the physical properties of the products, because is based on their “value” in human societies; in addition, market values of products can fluctuate consistently according to the reference year, production chain and geographical location (Ekvall, 2001; Pierru 2007).

In order to do not disregard these issues and provide a sensitivity analysis on how the different allocation procedures affect the final results, all the above mentioned allocation methods are applied to the biorefinery system assessed in this chapter.

Concerning system expansion, the main product is assumed to be bioethanol and the environmental benefits of co-products are assumed as credits, calculated thanks to the fossil reference systems. These credits (i.e. the GHG and fossil energy saved by the co-products) are then subtracted to the total GHG emissions and energy consumption of the whole system; the resulting environmental burdens are completely assigned to the main product.

Allocation methods based on thermodynamics parameters (energy and exergy content) and economic values of the products share the environmental burdens among the different outputs, without identifying a main product.

Concerning allocation based on energy content, for biofuels the following heating values are considered: bioethanol 27 MJ/kg, MTHF 32 MJ/kg, biomethane 34.75 MJ/kg, hydrogen 114 MJ/kg. The energy content of the material products has been estimated by means of the Dulong’s formula (furan resins 21.22 MJ/kg, FUMA 9.08 MJ/kg). Oxygen does not have a heating value. Exergy content of products are collected from a specific database (Ayres et al., 1996).

4.3. Life Cycle Impact Assessment

Life Cycle Impact Assessment (LCIA) stage deals with the evaluation of environmental

impacts of the biorefinery system and fossil reference system over their whole life cycle. The results focus on two types of impact categories: greenhouse gas (GHG) emissions and cumulative primary energy demand.


Table 5 reports the prices of the products for the allocation based on economic values.

Table 5. List of prices of biorefinery products to be used in the allocation procedure based on economic values.

Product Unit Price Transportation (bioethanol)a $/kg 1.34 Transportation (MTHF)a $/kg 1.31 Furan resinsb $/ton 3555 FUMAc $/ton 1278 Electricityd $/GJ 27.78 Heate $/GJ 9.29 Biomethanef $/GJ 9.29

H2g $/GJ 35.09

O2f $/kg 8.93

a Calculated on the basis of gasoline price in the US (1.06 $/L) b New chemical commodity, price in market not available. Estimate on the basis of the price of epoxy

resins c The price is referred to low grade fumaric acid d Average electricity price for households in the US e Price based on energy content of replaced natural gas f Average price natural gas for households in the US g Average estimated price of H2 in future markets (Ducharme et al., 2005) f Average O2 price for laboratories

The first impact category refers to all the GHG emissions released for feedstock production, transport, conversion processes, provision of auxiliary materials and final use of the products. These emissions are accounted for and converted to g CO2-eq. with equivalency factors. The analysis considers three long lived GHGs released by human activities: CO2, CH4 and N2O. Their effect on global warming can be assessed by an index called Global Warming Potential (GWP), which is a measure of how much a given mass of GHG contributes to global warming relative to a reference gas (usually CO2) for which GWP is set to 1. For a 100-year time horizon, GWPs of CO2, CH4 and N2O are, respectively, 1, 25 and 298 g CO2-eq./gemission

(IPCC, 2007). Using this index, one can calculate the equivalent CO2 emission by multiplying the emission of a GHG by its GWP.

Similarly, the cumulative primary energy demand accounts for all the life cycle stages, from feedstock provision to final use of products. The primary energy demand is divided into fossil, renewable and other energy demand. The same impact categories are evaluated for the fossil reference system as well, with the intent to make comparisons and quantify savings.

In order to gain information concerning performances and conversion efficiencies of the biorefinery system, the mass, energy, exergy and carbon efficiencies are carried out through the whole biorefinery conversion chain. The C content of the different feedstock components and final products are estimated and the C balance of the system calculated according to the methodology depicted in (Cherubini and Jungmeier, 2008), while the exergy contents of the molecules are derived from (Ayres et al., 1996).


4.3.1. Results and interpretation The final quantities of products produced are reported in Table 6 (upper part), where the

results of the biorefinery and fossil reference systems are also shown. The biorefinery releases about 36.8 kt CO2-eq./a and requires 10858 TJ/a of primary energy, of which 208 TJ/a fossil energy. On the other hand, the fossil reference system releases 336 kt CO2-eq./a and requires 4772 TJ/a, of which 4736 TJ/a fossil energy.

Table 6. Quantities of final products, GHG emissions and primary energy demand

of biorefinery system and fossil reference system.

Product/service: Product/service:Transportation (bioethanol) 1,082 Mio km Transportation (gasoline) 1,204 Mio kmTransportation (MTHF) 122 Mio kmFuran resins 2.91 kt Epoxy resins (from fossil) 2.91 ktFUMA 3.34 kt FUMA (from fossil) 3.34 ktElectricity 333 TJ Electricity (from natural gas) 333 TJHeat 224 TJ Heat (from oil) 224 TJBiomethane 261 TJ Natural gas 261 TJH2 13.7 TJ H2 (from natural gas) 13.7 TJO2 7.07 kt O2 (conventional, from air) 7.07 ktFertilizer (no benefit) 36.9 ktd ry

Environmental impacts: Environmental impacts (including heat):Total GHG emissions 36.8 kt CO2-eq./a Total GHG emissions 336 kt CO2-eq./aCO2 27.0 kt CO2-eq./a CO2 322 kt CO2-eq./aN2O 9.22 kt CO2-eq./a N2O 7.27 kt CO2-eq./aCH4 0.61 kt CO2-eq./a CH4 7.69 kt CO2-eq./a

Primary energy demand 10,858 TJ/a Primary energy demand 4,772 TJ/aFossil 208 TJ/a Fossil 4,736 TJ/aRenewable (biomass) 10,495 TJ/a Renewable 7 TJ/aOthers 16 TJ/a Others 25 TJ/aGHG and energy savings

Environmental impacts (excluding heat):GHG emissions saved 300 kt CO2-eq./a Total GHG emissions 313 kt CO2-eq./a

0.66 t CO2-eq./tdrywo od CO2 299 kt CO2-eq./aFossil energy saved 4,527 TJ/a N2O 6.76 kt CO2-eq./a

10.05 GJ/tdrywood CH4 7.15 kt CO2-eq./a

GHG emissions saved 276 kt CO2-eq./a Primary energy demand 4,474 TJ/a0.61 t CO2-eq./tdrywo od Fossil 4,440 TJ/a

Fossil energy saved 4,231 TJ/a Renewable 6 TJ/a9.39 GJ/tdrywood Others 24 TJ/a

Fossil Reference SystemBirefinery System

With heat credits

Excluding heat credits

This means that the biorefinery system is able to save 89% of GHG emission and 95.6%

of fossil energy in respect with its fossil reference system, providing the same quantities of products and services. In Figure 17, the GHG emissions of the biorefinery and fossil reference system are compared.

Biorefinery shows a relevant decrease of total GHG, CO2 and CH4 emissions, while it has a slight increase in N2O emissions, because of the biomass (lignin, residues, biofuels) combustion steps.


336322

9 70.61 8

3727

-

50

100

150

200

250

300

350

Biorefinery Fossil reference system

kt C

O2-e

q./a Total GHG

CO2N2OCH4

Figure 17. Comparison between GHGs of biorefinery and fossil reference system.

Going into details, about 33 kt CO2-eq./a are released by feedstock production and biorefinery plant activities, with the following shares:

• 61% of these emissions comes from feedstock provision (e.g. collection of wood

residue, pelleting and transport), • 16% from lignin and process residue combustion for CHP production (i.e. emissions

of CH4 and N2O), • 23% from manufacturing of auxiliary materials such as urea (9%), sulfuric acid,

phosphoric acid (5.7%), sodium hydroxide (5%) and others. In addition to these emissions, distribution and final use of products are responsible for

an emission of 3.8 kt CO2-eq./a (coming from combustion of transportation biofuels in passenger cars (95%) andfrom combustion of biomethane in its final application (5%)).

Table 7. GHG emissions of the fossil reference system.

Fossil reference system

Product/service kt CO2-eq./a %

Transportation (gasoline) 227 67.6%

FUMA (from fossil) 4.31 1.3%

Epoxy resins (from fossil) 17.7 5.2%

Electricity (from natural gas) 39.8 11.8%

Heat (from oil) 23.8 7.1%

Natural gas 21.9 6.5%

H2 (from natural gas) 987 0.3%

O2 (conventional) 509 0.2%

Total GHG emissions 336 100.00%


Manufacture of auxiliary materials

20%Feedstock provision

55%

Biomethane combustion

0.5% Other0.5%

Biofuel combustion in cars10%

Residue combustion

14%

Figure 18. Contributions to the total GHG emissions of the biorefinery system. “Other” includes wastewater treatment, waste disposal (mainly ashes) and uncontrolled CH4 emissions from anaerobic digestion.

Contributions from all the stages to the total GHG emissions of the biorefinery system are

illustrated in Figure 18. More than half of the GHG emissions are due to feedstock provision, i.e. collection, processing and delivery of wood residue pellets.

Concerning the fossil reference system, the total GHG emissions are mainly due to

gasoline (68%), followed by electricity (12%) and then other products. Detailed information concerning the contributors to the total GHG emissions of the fossil reference system are reported in Table 7. The primary energy demand of biorefinery system and fossil reference system has similar contributions than those of GHG emissions.

Results highlight both the importance of generating high quantities of electricity and the benefits deriving from an utilization of the process heat produced for achieving high GHG emission and fossil energy savings. Concerning electricity, the lower the share of electricity sent to alkaline water electrolysis, the higher the savings. In the determination of the magnitude of these savings, a fundamental role is played by the fossil reference system considered. It is assumed that the fossil reference system produces electricity from natural gas but the savings would be larger if, for instance, electricity from coal or oil is displaced. Regarding the heat, fundamental is the possibility to use it in an application located in the surrounded of the biorefinery, maximizing the environmental benefits which can be gained. In the fossil reference system, heat is assumed to be produced from oil and even in this case, environmental savings would be larger if coal-derived heat is replaced. The differences between biorefinery systems with and without process heat utilization are reported in the


lower part of Table 6: GHG and fossil energy savings are about 8% lower if heat is not used to substitute oil-derived heat.

Comparison of the biorefinery with its fossil reference system shows that the biorefinery can reduce GHG emissions of about 299.6 kt CO2-eq./a (0.66 t CO2-eq./tdry wood) and save 4527 TJ/a of fossil energy (10.05 GJ/tdry wood).

Even if the biorefinery system requires more than twice the primary energy demand of the fossil reference system, it is mainly constituted (97%) by renewable energy, i.e. the energy content of biomass feedstock, and the savings of fossil energy are relevant (almost 96%). As a consequence, the provision of biomass with sustainable practices is a crucial point to ensure a renewable energy supply to biorefineries.

Table 8. Conversion yields and mass, carbon, energy and exergy

efficiencies of the biorefinery system.

Ethanol yield per t of feedstock (dry) 0.22 t/tdry Ethanol yield per ton of cellulose 0.49 t/tcell C conversion efficiency from wood to EtOH 22.45% C conversion efficiency from cellulose to EtOH 56.98% Furfural yield per t of feedstock (dry) 0.04 t/tdry Furfural yield per ton of xylan 0.68 t/txylan C conversion efficiency from wood to furfural 5.35% C conversion efficiency from hemicellulose to furfural 74.86% Material products per t of feedstock (tprod/tdry wood)a 2.96% Energy products (net) per GJ of feedstock (GJprod/GJwood)b:

with heat 37.28% without heat 35.12%

C conversion efficiency (from feedstock to products) 29.15% Exergy conversion efficiency:

with heat 44.38% without heat 42.95%

a Only material products included (e.g. furan resins, FUMA, and O2) b Energy feedbacks to the plant subtracted (i.e. only final energy outputs included)

Biorefinery system performances in terms of product yields and mass, energy, exergy and C conversion efficiencies are reported in Table 8. Bioethanol and furfural yields are respectively 0.22 and 0.04 t per tonne of dry feedstock, but the yields increase up to 0.49 t of bioethanol per tonne of cellulose and 0.78 t of furfural per tonne of xylan. The overall C conversion efficiency of the plant from feedstock to products is 29.15% and the exergy conversion efficiency is 44.38%. The material products of the biorefinery (i.e. furan resins, FUMA and O2) constitute 2.96% of the total mass of the dry feedstock, while final net energy products (bioethanol, MTHF, H2, biomethane, electricity and heat) store about 37% of the raw material energy content. Without heat, this energy efficiency decreases to 35%. A comparison can be done with other biomass conversion systems, which have energy efficiencies higher than biorefinery. In fact, production of heat from wood combustion can reach efficiencies higher than 85%, while in CHP application the overall energy efficiency is around 80%. The reason is that a biorefinery system is made of several conversion steps and biomass undergo chemical reactions and changes of state, while the aforementioned


conventional biomass system mainly involve one step (biomass combustion). In particular, energy and C conversion efficiencies of the biorefinery are lowered by the fermentation step, where C6 sugars are converted to bioethanol: C efficiency from cellulose to bioethanol is about 57% while from hemicellulose to furfural (a chemical pathway, without microorganisms) is about 75%. During fermentation almost half of the C in C6 sugars is converted to the useless product CO2, thus lowering the overall efficiency of the process.

4.3.2. Allocation results

The allocation procedures previously described are applied in order to share the environmental burdens of the biorefinery among the different products. The allocation criteria are based on energy content, exergy content and economic value of products. An attempt to avoid allocation through system expansion was also done. Results are reported in Table 9, where the GHG emissions of the biorefinery system are allocated. Concerning the cumulated primary energy demand, allocation can be performed considering the same shares of the total GHG emissions of Table 9.

Table 9. Allocation of the GHG emissions to the biorefinery products using

different allocation methods.

Allocation method

Unit Energy Exergy Economic value System

expansion

Transportation (bioethanol) kt CO2-eq./a 25.1 68.3% 25.7 69.8% 25.4 68.9% -97.6

main produc

t Transportation (MTHF) kt CO2-eq./a 2.82 7.68% 2.98 8.09% 2.36 6.41% 25.6 credits

Furan resins kt CO2-eq./a 0.59 1.60% 0.62 1.69% 2.02 5.48% 4.31 credits FUMA kt CO2-eq./a 0.29 0.79% 0.33 0.90% 0.83 2.26% 17.6 credits Electricity kt CO2-eq./a 3.18 8.64% 2.60 7.07% 1.80 4.90% 39.8 credits Heat kt CO2-eq./a 2.14 5.83% 1.05 2.86% 0.41 1.11% 23.8 credits Biomethane kt CO2-eq./a 2.49 6.78% 3.22 8.75% 0.47 1.29% 21.8 credits H2 kt CO2-eq./a 0.13 0.36% 0.11 0.30% 0.09 0.25% 0.99 credits O2 kt CO2-eq./a - 0.00% 0.01 0.02% 3.45 9.38% 0.51 credits

In Figure 19, the influence of the allocation methods on GHG emissions allocated to

biorefinery products is shown. It can be noticed that, besides system expansion which uses a different approach, all the allocation criteria lead to similar results, especially concerning transportation biofuels (bioethanol and MTHF). Allocation based on energy and exergy content of products show similar results also for the other energy products and chemicals, while allocation based on economic values increases the shares of chemical products, such as furan resins, FUMA and mainly oxygen, while decreasing the environmental burdens assigned to electricity, heat and biomethane.

The specific GHG emission factors for each product according to the allocation procedure are listed in Table 10. In this table, GHG emissions per unit of product, i.e. km driven for biofuels, GJ for electricity and heat, g for chemicals and gaseous biofuels, are reported. For instance, these factors can be applied in a LCA if these products are used as auxiliary materials in a future biobased society. Results of these biomass derived products and services can be compared with those derived from oil refinery (reported in Table 3). For


instance, driving a car fuelled with bioethanol produced from biorefinery (23.23 g CO2-eq./km, energy allocation) instead of gasoline from oil refinery (189 g CO2-eq./km), saves approximately 88% of CO2-eq. emissions .

-

5

10

15

20

25Tr

ansp

orta

tion

(bio

etha

nol)

Tran

spor

tatio

n(M

THF)

Fura

n re

sins

FUM

A

Elec

trici

ty

Hea

t

Biom

etha

ne H2

O2

kt C

O2 -

eq./a

Energy allocation Exergy allocation Economic allocation

Figure 19. mparison among the different allocation methods (data from Table 9).

Table 10. Specific factors of GHG emissions of biorefinery products

according to the different allocation methods used.

Unit Energy Exergy Economic System expansion

Transportation (bioethanol) g CO2-eq./km 23.23 23.74 23.43 -90.20 main product

Transportation (MTHF) g CO2-eq./km 23.23 24.47 19.38 210.23 credits

Furan resins g CO2-eq./g 0.18 0.21 0.69 1.48 credits

FUMA g CO2-eq./g 0.09 0.10 0.25 5.29 credits

Electricity kg CO2-eq./GJ 9.56 7.82 5.42 119.60 credits

Heat kg CO2-eq./GJ 9.56 4.69 1.81 106.00 credits

Biomethane g CO2-eq./g 0.33 0.43 0.06 2.91 credits

H2 g CO2-eq./g 1.09 0.92 0.78 8.23 credits

O2 g CO2-eq./g - 0.001 0.49 0.07 credits


5. CONCLUSION The use of biomass as raw materials for bioenergy and biochemical production is

encouraged by the need for a secure energy supply, a reduction of fossil CO2 emissions and a revitalization of rural areas. Biomass energy and material recovery is maximized if a biorefinery approach is considered, where many technological processes are jointly applied to different kinds of biomass feedstock for producing a wide range of bioproducts. A lot of biorefinery pathways, from feedstock to products, can then be established, according to the different types of feedstock, conversion technologies and products. Biorefinery concept is analogous to today's petroleum refinery, which produces multiple fuels and products from petroleum.

Among the different biomass resources, lignocellulosic materials have great potentials for production of bioenergy and biochemicals in biorefinery, replacing fossil derived products and services. The LCA depicted in this chapter shows that significant GHG and fossil energy savings are achievable if a biorefinery system is compared with a fossil reference system. The investigated biorefinery produces transportation biofuels (bioethanol, MTHF), gaseous biofuels (biomethane and H2), chemicals (furan resins, FUMA and O2), electricity and heat from softwood forest residues, while the fossil reference system produces gasoline as transportation fuel, natural gas, H2 from natural gas, conventional O2 from air processing, conventional FUMA and epoxy resins from oil refinery, electricity from natural gas and heat from heavy oil. The biorefinery releases 36.8 kt CO2-eq./a and requires 10858 TJ/a of primary energy, of which 208 TJ/a fossil energy, while the fossil reference system releases 336 kt CO2-eq./a and requires 4772 TJ/a, of which 4736 TJ/a fossil energy. Therefore, 89% of GHG emissions and 96% of fossil energy can be saved. Even if the biorefinery has higher primary energy demand than the fossil reference system, it is mainly based on renewable energy (i.e. the energy content of the processed feedstock): the provision of biomass with sustainable practices is then a crucial point to ensure a renewable energy supply to biorefineries. Furthermore, more than half of the total GHG emissions of the biorefinery are originated from feedstock provision (collection, processing and delivery), followed by manufacture of auxiliary materials and biomass combustion. Results also show biorefinery system performances in terms of product yields and mass, energy, exergy and C conversion efficiencies. Energy and C efficiencies result affected by the fermentation step, where almost half of the C of the feedstock is loss in the formation of the useless product CO2.

In order to share the environmental impacts of the biorefinery among the different coproducts, several allocation procedures were applied. An attempt to avoid allocation through system expansion was developed and then allocations based on energy content, exergy content and economic value of outputs have been carried out. All the findings are finally compared and the specific GHG emission factors (g CO2-eq./unit) of each product are reported. These factors can be applied in LCA studies of a future biobased society, when biorefinery products will be widely used by customers and as auxiliary materials in production processes.


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Chapter 4

PINCH TECHNOLOGY FOR WASTE HEAT RECOVERY APPLICATIONS IN OIL INDUSTRY

*Mahmoud Bahy Noureldin Consulting Services Department, Saudi Aramco, Dhahran, Saudi Arabia.

Part I: Pinch Technology for Energy Utilities Targeting and HEN Design

Constructing the Composite Curves for Energy Utilties Targeting Targeting using Algebraic and Mathematical Programming Methods Constructing the Grand Composite Curve (GCC) Utility Selection Using Grand Composite Curve (GCC) Understanding and Applying Grand Composite Curve Heat Exchanger Network Synthesis using Pinch Design Method

Part II: Heat Integration Applications in Oil Industry

Oil and Gas Separation Process Crude Atmospheric Distillation Unit

INTRODUCTION In process industries the main source of waste heat is associated with hot utilities; that

include furnaces, steam boilers, gas turbines and diesel engines. Energy efficiency optimization not only keeps operating cost under control and conserve

depleted resources but also reduces GHG emissions. Oil and gas industry consists of very energy intensive processes. Oil and gas separation;

crude atmospheric and vacuum distillation; Naphtha and Diesel hydro-treating and gas oil and Naphtha reforming, are only some examples.

In the oil and gas business, energy cost is a major element in any facility operating cost. It usually comes before maintenance cost and sometimes even labor cost. Implementation of a

* [email protected] Tel: 9663-873-6045, Fax 9663-873-0766

Mahmoud Bahy Noureldin 142

decent level of energy integration in any industrial facility, most of the time, needs capital investment.

This chapter addresses the problem of waste heat recovery via presenting an introduction to the pinch technology and two industrial applications of heat integration for waste heat recovery in oil and gas business. Pinch technology, after almost three decades of its emanation in the late seventies for a reason or another, is still the most widely used method for energy integration in oil industry.

The chapter comes into two parts; the first part introduces some aspects of Pinch technology in brief. Pinch technology is now well documented in several literatures and the references 1 to 4 at the end of this chapter are only few main examples. In this part, I will show how we can use pinch technology for energy utility targeting, selection of utility mix and heat exchanger network synthesis using pinch design method [1, 2, 3 and 4]. The second part introduces two important applications for heat integration in oil industry [5]. The first application is showing the effect of heat integration on both energy consumption and GHG emission reduction in an oil-gas separation facility, and in the second application an evolutionary approach to crude distillation pre-heat train design is introduced.

TARGETING USING GRAPHICAL METHOD Any heat exchanger can be represented as a hot stream that is cooled by a cold stream

and/or cold utility and a cold stream that is heated by a hot stream and/or hot utility with a specified minimum temperature approach between the hot and the cold called ∆Tmin.

The process exhibited below in the graph shows the situation when the two streams do not have a chance of overlap that produce heat integration between the hot and the cold.

Figure 1. Two Non-Overlapping Streams

Pinch Technology for Waste Heat Recovery Applications in Oil Industry 143

PROCESSH CFeed Product

0

20

40

60

80

100

120

0 10 20 30 40 50 60 H

T HOT UTILITY

COLD UTILITY

HEAT RECOVERY

Pinch(MAT)

PROCESSH CFeed Product

0

20

40

60

80

100

120

0 10 20 30 40 50 60 H

T HOT UTILITY

COLD UTILITY

HEAT RECOVERY

Pinch(MAT)

Figure 2. Heat Integration between Hot and Cold

Moving the cold stream to the left on the enthalpy axis without changing its supply and target temperatures until we have a desired small vertical distance between the hot stream and the cold stream we obtain some overlap between the two streams that result in heat integration between the hot and the cold and less hot and cold utilities. As seen depicted in the graph below with shrinkage in the red and blue lines span.

Now we want to represent all the hot streams in the process by one long hot stream and we will call this line the hot composite curve. We will also do the same thing with all the cold streams in the process.

The next step will be drawing the two composite curves/lines on the same page in a Temperature (T)-Enthalpy diagram with two conditions:

1. The cold composite curve should be completely below the hot composite curve, and 2. The vertical distance between the two lines/curves in terms of temperature should be

greater than or equal to a selected minimum approach temperature called global ∆Tmin The resulting graph is depicted below and known as thermal pinch diagram.

Net Heat SinkAbove the Pinch

Net Heat SourceBelow the Pinch

Opportunity for heat recovery

Net Heat SinkAbove the Pinch

Net Heat SourceBelow the Pinch

Opportunity for heat recovery

Figure 3. Composite Curves


Constructing the Composite Curves

1. Draw the hot composite curve and the cold composite curve via developing the following tables.

2. These tables list all the hot and cold streams temperatures in an ascending order with the cumulative enthalpy corresponding to the lowest hot temperature and lowest cold temperature respectively equal to zero.

3. In every temperature interval the cumulative hot load is calculated using the following formula

H= FCp * (Tsupply – Ttarget)

4. In every temperature interval the cumulative cold load is calculated using the following formula

H= FCp * (Ttarget – Tsupply) Hot streams temperature list Cumulative Enthalpy (H) T0=30 H0=0.0 T1=70 H1=800 T2=120 H2=2300 T3=170 H3=2800 Cold streams temperature list Cumulative Enthalpy (H) T0=20 H0=0.0 T1=50 H1=450 T2=90 H2=2650 T3=110 H3=3450 As we mentioned before the cold composite curve shall lie completely below the hot

composite curve and this can be done via dragging the cold composite curve to the right on the enthalpy axis (H). This process shall stop at a vertical distance between the cold and the hot composite curve for a temperature equal to the minimum temperature approach selected earlier.

Table 1. Data for Constructing Composite Curves

Supply Temp

(º C) Target Temp.

(º C) FCp (kW/ ºC)

170 70 10 120 30 20 50 90 40 20 110 15


Temperature (T)- Enthalpy (H) Diagram

T

H

30

20

Hot composite curve

Cold composite curve

Cold composite curve is not completely below the hot composite curve

Figure 4. Temperature (T) Enthalpy (H) Diagram 1

Figure 5. Temperature (T) Enthalpy (H) Diagram 2

Temperature (T)- Enthalpy (H) Diagram

T

H

30

20

Hot composite curve

Cold composite curve

Minimum Heating Utility

Minimum Cooling Utility

Qh=300 kW

Qc=150 kW

Minimum Temperature Approach


TARGETING USING ALGEBRAIC METHOD

Information needed Given a unit with a list of hot streams to be cooled and cold streams to be heated

Table 2. Data for Algebraic Method FCp (kW/ ºC)

Supply Temp

(º C) Target Temp. (º C)

10 520 330 5 380 300

10 300 550 5 320 380

1. Constructing Temperature Iinterval Diagram

1.1. Draw two temperature scales one for the hot streams and another for the cold streams 1.2. Select a reasonable minimum temperature approach between the hot streams and the

cold stream, (for instance, 10 ºC) 1.3. Draw all the hot streams (in the table hot section) to be cooled according to the hot

steam scale as arrows that start at the supply temperatures and end at the target temperatures

1.4. Repeat step 1.3 for all cold streams in the cold section of the table 1.5. Start at the highest temperature of any hot stream in the hot section and draw a

horizontal line that spans across the two sections of the table, the hot and the cold. 1.6. Draw horizontal lines again at the start and the end of any arrow representing the hot

streams in the hot section of the table 1.7. Repeat step 1.6 for any arrow representing cold stream in the cold section (at the start

and the end of any arrow) 1.8. Count the number of segments generated and number them starting at the highest

temperature (they are called temperature intervals) 1.9. Make sure that each temperature interval has now temperature value on both the hot

temperature scale and cold temperature scale. The difference is the desired minimum temperature approach (for instance the 10 ºC used in this example)

These procedures are depicted in the figure below Note: This structure means that within any temperature interval it is thermodynamically

feasible to transfer heat from the hot streams to cold streams. It is also feasible to transfer heat from a hot stream in an interval “x” to any cold stream which lies in an interval below.

Note: The temperature symbol T* ‘(Figure 6) is the interval inlet temperature used later on constructing what is know as grand composite curve for selecting the suitable energy utility mix. To calculate T* we take the average interval inlet temperature of the hot and cold temperature scale.


T tHot Streams Cold StreamsInterval

6

4

3

2

1

5

520

380390

370380

320330

300310

290300

510

550560

∆ T minimum = 10 K

T*

385

375

310

305

295

515

555

Hot Streams:H1; F1Cp1= 10 kW/KH2; F2Cp2= 5 kW/K

Cold Streams:C1; F1Cp1= 10 kW/KC2; F2Cp2= 5 kW/K

C2

C1

H2

H1

Figure 6. The Temperature Interval Diagram

2. Constructing Tables of Exchangeable Heat Loads and Cooling Capacities

2.1. Determining individual heating loads and cooling capacities of all process streams

for all temperature intervals using this formula:

Qnm = F1Cp1* (Ts-Te) in energy units (kW) Ts is the interval start temperature and Te is the interval end temperature “n” is stream number and “m” is the interval number

Example 1: Interval # 1 in the hot section: The interval start temperature is 560 K The interval end temperature is 520 K Q11 (Q for stream #1 in interval #1)= F1Cp1*(560-520) Since there is no H1 stream in this interval, hence, F1Cp1=0.0 Q stream # 1(exchangeable load) in this interval = 0.0*(560-520) = zero

Example 2: Interval # 2 in the hot section: The interval start temperature is 520 K The interval end temperature is 390 K The flow specific heat F1Cp1= 10 kW/K Then, Q stream #1(exchangeable load) in interval #1= 10*(520-390) = 1300 kW


Example 3: Interval # 1 in the cold section: The interval start temperature is 550 K The interval end temperature is 520 K The flow specific heat of this cold stream is F1Cp1= 10 kW/K Then, Q stream #1(cooling capacity) in interval #1= 10*(560-520) = 400 kW

Upon the completion of this step,

2.2 We can now obtain the collective loads (capacities) of the hot (cold) process streams.

These collective loads (capacities) are calculated by summing up the individual loads of the hot process streams that pass through that interval and the collective cooling capacity of the cold streams within the same interval

These calculations for the above problem is shown in the following tables

Table 3. Exchangeable Loads for Process Hot Streams Intervals

Interval Load of H1, kW Load of H2, kW Total Load, kW

1

2

3

4

5

6

0.0*(560-520)= 0.0

10*(520-390)= 1300

10*(390-380)= 100

10*(380-350)= 500

0.0*(330-310)= 0.0

0.0*(310-300)= 0.0

0.0*(560-520)= 0.0

0.0*(520-390)= 0.0

0.0*(390-380)= 0.0

5*(380-330)= 250

5*(330-310)= 100

5*(310-300)= 50

0.0+0.0= 0.0

1300+0.0= 1300

100+0.0= 100

500+250= 750

0.0+ 100= 100

0.0+50= 50

Table 4.Cooling Capacities for Process Cold Stream Intervals

Interval Capacity of C1, kW Capacity of C2, kW Total Load, kW

1

2

3

4

5

6

10*(550-510)= 400

10*(510-380)= 1300

10*(380-370)= 100

10*(370-320)=500

10*(320-300)= 200

0.0*(300-290)= 0.0

0.0*(550-510)= 0.0

0.0*(510-380)= 0.0

5*(380-370)= 50

5*(370-320)= 250

0.0*(320-300)= 0.0

0.0*(300-290)= 0.0

400+0.0= 400

1300+0= 1300

100+50= 150

500+250= 750

200+ 0.0= 200

0.0+0.0= 0


1

Hot Load From Utility Source

“Top Input”

Hot Load From Process Source

“Left Input”

Cooling Capacity From Process Source

“ Right Output”

Residual Hot to Subsequent Interval

“Bottom Output” from first interval

Heat Balance

Top Input+ Left Input- Right Output = Bottom Output

Figure 7. First Interval Heat Balance

Figure 8. Numerical Example of First Interval Heat Balance

1

Numerical Example of First Interval Heat Balance


“Top Input ”= 0.0 kW


“Left Input ”= 0.0 kW


“ Right Output ”=400 kW


“Bottom Output ” from first interval

Heat Balance

Top Input+ Left Input - Right Output = Bottom Output0.0 + 0.0 - 400 = - 400 kW

= - 400 kW

1

Numerical Example of First Interval Heat Balance


“Top Input ”= 0.0 kW


“Left Input ”= 0.0 kW


“ Right Output ”=400 kW


“Bottom Output ” from first interval

Heat Balance

Top Input+ Left Input - Right Output = Bottom Output0.0 + 0.0 - 400 = - 400 kW

= - 400 kW


N

Subsequent Intervals Heat Balance

Hot Load From Above Interval

“Top Input”


“Left Input”


“ Right Output”


“Bottom Output”

Heat Balance

Top Input+ Left Input- Right Output = Bottom Output

Figure 9. Subsequent Intervals Heat Balance

Figure 10. Numerical Example for Subsequent Heat Balance

3

Numerical Example for Subsequent Intervals Heat BalanceFor instance; Interval # 3


“Top Input” = - 400


“Left Input”= 100


“ Right Output”= 150


“Bottom Output” = - 450

Heat BalanceTop Input+ Left Input- Right Output = Bottom Output- 400 + 100 -150 = - 450

3

Numerical Example for Subsequent Intervals Heat BalanceFor instance; Interval # 3


“Top Input” = - 400


“Left Input”= 100


“ Right Output”= 150


“Bottom Output” = - 450

Heat BalanceTop Input+ Left Input- Right Output = Bottom Output- 400 + 100 -150 = - 450


3. Constructing Thermal Cascade Diagrams

This diagram is constructed using the total hot loads and cooling capacities obtained in the previous step for each temperature intervals.[1,2,3]

The temperature intervals are drawn as “rectangular” with two inlets and two outlets. The inlet from the left is the total hot load available in this interval (for instance, 1300

kW in case of interval # 2) The inlet from above is the utility input load, in case of the first interval, or the input

from interval above in case of second, third,……,N intervals. The output from the right is the total cooling capacity of this interval ( for instance, 1300

kW in case of interval #2). The output from the bottom is the difference between the total inputs and the cooling

capacity of the interval The heat balance around each interval will be conducted as above.

The reader is encouraged to do the calaculation for interval number 2 and see that in interval number 2 the hot side input is equal to the cold side output and hence the final output of the interval will be the same as interval number one ,-400 energy unit.

Upon the completion of the heat balance around each interval the following energy deficiency diagram will be produced.

Figure 11. Thermal Cascade Diagram (Un-Balanced)

Thermal Cascade Diagram (Un-Balanced)

Note: During this step the input from Hot Utility to the first interval is equal to zero

0.0

1300

- 550

-450

- 450

- 400

-400

0.0

1300

400

100 150

750 750

100 200

50 06

5

4

3

2

1

- 500


The maximum difference between the available hot loads and cooling capacities from the heat balances of these intervals is – 550 kW. This deficiency in heat will be supplied via an outside hot utility. This value will be the input (from the top of the first interval) and the same heat balance calculation conducted above will be repeated to produce the energy balanced thermal cascade diagram below.

Figure 12. Thermal Cascade Diagram (Balanced)

With the completion of this step, the minimum heating utility and minimum cooling

utility required are 550 kW and 50 kW respectively. TARGETING USING MATHEMATICAL PROGRAMMING METHOD The algebraic method mentioned above can be generalized using optimization techniques.

A very famous approach is the “transshipment model formulation as we mentioned in the first module.

Mathematical programming at a Glance: Let us consider the following constrained problem; Min f(x) s.t. h(x) =0.0 g(x) ≤ 0.0 x є nR Where: f(x) is the objective function h(x) = 0.0 is the set of (m) equations in variables x g(x) ≤ 0.0 is the set of r inequality constraints.

Balanced Thermal Cascade Diagram

0.0

1300

0.0

100

100

150

150

Minimum Heating Utility = 550 units

1300

400

100 150

750 750

100 200

50 06

5

4

3

2

1

Minimum Cooling Utility = 50 units

Pinch Point


In general the number of variables, n, will be greater than the number of equations, m, and the difference between (n-m) is commonly denoted as the number of degrees of freedom of the optimization problem. Any optimization problem can be represented in the above form. If we want to maximize a function this is equivalent to minimizing the negative of that function.

Now for the heating and cooling utilities minimization problem, let us go back to our small problem solved algebraically before using pinch technology and use FCP for cold streams of 19 and 2 kW/ºC resepctively. The new problem can be easily solved using mathematical programming model. We write our objective function not only including heating and cooling utiltities loads but also including heating and colling utilitie costs in dollar value; formulate our model/constraints using the cascade approach; and then solving the optimization problem using any commercial software.

• Objective function

Minimize (5* 610− min

heatingQ + 9* min610 coolingQ− )*3600*8000

• Define the loads of heating and cooling utilities in each temperature interval and the surplus from each interval as we did before in the algebraic method through the development of temperature interval diagram, tables of exchangeable loads and un-balanced thermal cascade diagram.

The model formulation is a heat balance around each temperature interval in the graph below as follows:

0.0

1300 2470

760

100 210

750 1050

100 380

50 0.06

5

4

3

2

1r1

r2

r3

r4

r5

minheatingQ

mincoolingQ

Figure 13. Thermal Cascade diagram for LP model

minheatingQ + 0.0-760 = r1

r1+1300-2470 = r2


r2+100-210 = r3

r3+750-1050 = r4

r4+100-380 = r5

r5+50-0.0 = min

coolingQ Now using any optimization software: Model:

Min = (3* 610− minheatingQ + 5* min610 coolingQ− )*3600*8760;

r1- min

heatingQ = -760;

r2-r1= -1170;

r3-r2= -110;

r4-r3= -300;

r5-r4= -280;

mincoolingQ -r5= 50;

minheatingQ ≥ 0.0;

mincoolingQ ≥0.0;

r1≥0.0;

r2≥0.0;

r3≥0.0;

r4≥0.0;

r5≥0.0;

The targets obtained graphically or algebraically or using mathematical programming,

give an idea about the potential utility needs of any industrial facility. To get a better idea in terms of utility types needed, we need to construct a diagram

known as the grand composite curve (GCC) and use it for defining the kind of utilities we need and how much we need. We can then utilize these findings to compare the current


facility needs with the minimum utility needs calculated before to define the gap needed to be tackled. This step will help us evaluate potential savings upon the heat integration for certain process area.

CONSTRUCTING THE GRAND COMPOSITE CURVE (G.C.C) This curve will be drawn between T* calculated before during the temperature interval

diagram construction which is the average temperature of hot and cold side each interval boundary and the corresponding surplus heat/enthalpy from each interval.

These data are shown below for a generic balanced cascade diagram that can be developed for any application as shown before:

Data Required To Construct The G.C.C

0.0 kW

280 kW

580 kW

690 kW

1860 kW

2620 kW

6

5

4

3

2

1

Thermal Pinch

50 kW

385

375

310

305

295

515

555

T* (K) Enthalpy ( kW)

T* (K)

Enthalpy ( kW)

Figure 14. Data required to drawing Grand Composite Curve (G.C.C.)

Drawing these data as T* versus Enthalpy results in the following diagram that can be used to define different levels of utilities mix that can be used to satisfy the process heating utility requirement for instance, as shown below.


Grande Composite Curve (G.C.C)Should Be Drawn To Scale

T* (K)

Enthalpy ( kW)

700 1400 2100 2800200

300

400

500

600

Total hot utility required is equal to 2620 kW

Hu1

Hu2Hu3

Figure 15. Grand Composite Curve

Multiple Utility Targeting/Selection using Grand Composite Curve (GCC)

Upon maximizing heat recovery in the heat exchanger network, those heating duties and

cooling duties not serviced by heat recovery must be provided by external utilities. The most common utility is steam. It is usually available at several levels. High

temperature heating duties require furnace flue gas or a hot oil circuit. Cold utilities might be refrigeration, cooling water, air cooling, furnace air preheating, boiler feed water preheating, or even steam generation at higher temperatures.

Although the composite curves can be used to set energy targets, they are not a suitable tool for the selection of utilities. The grand composite curve drawn above is a more appropriate tool for understanding the interface between the process and the utility system. The GCC is obtained via drawing the problem table cascade as we shown earlier.

The graph shown above is a typical GCC. It shows the heat flow through the process against temperature. It should be noted that the temperature plotted here is the shifted temperature T* and not the actual temperature. Hot streams are represented by ∆Tmin/2 colder and the cold streams ∆Tmin/2 hotter than they are in the streams problem definition. This method means that an allowance of ∆Tmin is already built into the graph between the hot and the cold for both process and utility streams. In other words, the actual hot utility


temperature will be {T*(obtained from graph)+(∆Tmin/2)} and the actual cold utility temperature will be {T*(obtained from graph)-(∆Tmin/2)}

The point of “zero” heat flow in the GCC is the pinch point. The open “jaws” at the top and the bottom represent QHmin and QCmin respectively.

The grand composite curve (GCC) provides a convenient tool for setting the targets for the multiple utility levels of heating utilities as illustrated above.

The graphs below further illustrate such capability for both heating and cooling utilities.

Figure 16. Grand Composite Curve for Utility Selection-1

The above figure 16(a) shows a situation where HP steam is used for heating and

refrigeration is used for cooling the process. In order to reduce utilities cost, intermediate utilities MP steam and cooling water (CW) can be introduced. The second graph (b) shows the targets for all the utilities. The target for the MP steam is set via simply drawing a horizontal line at the MP steam temperature level starting from the vertical axis until it touches the GCC. The remaining heat duty required is then satisfied by the HP steam. This maximizes the MP steam consumption prior to the remaining heating duty be fulfilled by the HP steam and therefore minimizes the total utilities cost. Similar logic is followed below the pinch to maximize the use of the cooling water prior the use of the refrigeration.

The points where the MP steam and CW levels touch the GCC are called utility pinches since these are caused by utility levels. The graph, 17(C) below, shows a different possibility of utility levels where furnace heating is used instead of HP steam. Considering that furnace


heating is more expensive than MP steam, the use of the MP steam is first maximized. In the temperature range above the MP steam level, the heating duty has to be supplied by the furnace flue gas. The flue gas flowrate is set as shown in the graph via drawing a sloping line starting from the MP steam to theoretical flame temperature Ttft.

If the process pinch temperature is above the flue gas corrosion temperature, the heat available from the flue gas between the MP steam and pinch temperature can be used for process heating. This will reduce the MP steam consumption.

In summary the GCC is one of the basic tools used in pinch technology for the selection of appropriate utility levels and for targeting for a given set of multiple utility levels. The targeting involves setting appropriate loads for the various utility levels by maximizing cheaper utility loads and minimizing the loads on expensive utilities.

Normally, we have a choice of many hot and cold utilities. Using the entropy balance equation for an open system we can conclude and generally recommend to use hot utilities at the lowest possible temperature while we generate it at the highest possible temperature to generate work. And for the cold utilities it is recommended to use it at the highest possible temperature. These recommendations are best explained using the grand composite curve.

MP

CW

Refrigeration

T*

H

T-tft(C)

Figure 17. Grand Composite Curve for Utility Selection-2


Understanding and Applying the Grand Composite Curve The graph below shows that utility pinches are formed according to the number of

utilities used. Each time a utility is used a “utility pinch” is created. It also shows that the GCC right noses, sometimes known as “pockets”, are areas of heat integration/energy recovery and hence does not need any external utilities. These right noses/pockets represent another possibility of heat integration among hot and cold process streams at a minimum approach temperature ∆T higher than that of the ∆Tmin. In such cases an ooprtunity for lost work recovery can exist on the expense of process to process heat integration.

The GCC curve can be used by engineers to select the best match between the utility profile and process combined heat and power requirements profile. For instance, the steam system shown below in figure 19 needs to be integrated with the process demands to minimize low pressure steam flaring and high or medium pressures steam let downs.

In addition, GCC can also helps in selecting steam header pressure levels and loads.

Figure 18. Understanding the Grand Composite Curve

Before closing this part of GCC and its use in selecting process requirements of utilities

mix, I need to mention one important fact here about a rule in pinch technology that is generally accepted by many people in the industrial community.

This rule says that: “do not use cold utility above the pinch” to avoid buying extra heating and cooling utiltities. This rule is absolutely true when we talk only about cost of heating


utilities. However, in some situation we can have a trade off between heating utilities cost and benefits obtained from reducing power import or exporting power to the grid.

With the aid of GCC we might find situations in which it is better from work generation point of view to use cold water above the pinch to produce steam and generate electricity, then using steam turbines exhaust for process heating than literally doing process to process integration using minimum approach temperature ∆T among hot and cold process streams much higher than the originally selected minimum approach temperature ∆T_min.

chemicals

Proc. #1

Proc. #1

Proc. #1

Proc. #2

Proc. #3

Proc. #4

BFWRaw water Make-up Treatment Plant

MP Process Condensate

LP Process Condensate

HP Process Condensate

Process Condensate

HP Boiler

MP Boiler

HP

MP

LP

Vent

Effluent

Deaerator

Vent

Figure 19. Combined Heat and Power System Example

In summary, the Grand Composite Curve can be utilized to help optimize combined heat and power systems (CHP) shown in figure 19, select the load and return temperature of hot oil circuits, best integration between process and furnaces exhaust and process refrigeration levels as well as the synthesis of the multiple-cycle refrigeration systems [1,3].

HEAT EXCHANGERS NETWORK (HEN) SYNTHESIS Upon deciding on process reaction-separation system design, the optimization of major

design variables such as reactor conversion, selectivity, recycle inert concentration, etc., minimization of process waste, minimization of utility waste via heat integration, process modifications for the sake of more heat integration has been explored and the plant utility system is configured, the material and energy balance can now be more or less fixed and hence the hot and cold streams which contribute to the heat exchanger network can be


identified. The task is then becomes to design the heat exchanger network. In a little elaboration define the HEN streams matching, duty of each heat exchanger, inlet and outlet temperatures of each heat exchanger and with given overall heat transfer coeffiecients calculate the surface area of each heat exchanger. In the section below we will be defining the topology, duty and temperatures information of the HEN.

The Pinch Design Method The best design for an energy efficient heat exchange network will often result in a

tradeoff between the equipment and operating cost. This is dependent on the choice of the DTmin for the process. The lower the DTmin chosen, the lower the energy costs, but conversely the higher the heat exchanger capital costs, as lower temperature driving forces in the network will result in the need for greater area. A large DTmin on the other hand will mean increased energy costs due to less overall heat recovery, but the required capital cost will be less. This is true most of the time but not all of the time. Designers may find that a very large DTmin might lead to high levels of heat duties available to be handled by process to process heat exchangers and process to utiltities ones resulting in high surface area needs and consequently both capital cost and energy cost will be increased.

Any way early in this chapter we introduced how to set energy and area targets for the process before considering the HEN design because in the early days of pinch technology this technique was important to help make the trade-off between the HEN capital cost and operating cost quickly and without any heavy calculations. However, nowadays lot of software is available to make a preliminary synthesis of any large size HEN and estimate its capital cost directly and then automatically make the trade-off between the operating cost and the capital cost for the HEN in order to determine the optimal Dtmin for the HEN to be designed.

Now let us first estimate the minimum number of units in a HEN (Nunits ) using the

following formula:[1]

Nunits = S – 1 Where,

S = number of streams (hot and cold) including utilities

It is important to keep in mind that using the above formula for HEN minimum number of units calculation will only be giving an estimate and in some cases designers can come up

with designs which exhibit less number of units due to some perfect matches in temperature range and load among hot and cold process streams.

Having calculated an estimate to HEN minimum number of units we can then use the

composite curves again used before to determine the energy targets for a given value of DTmin to determine another estimate to the minimum heat transfer area required to achieve the desired energy targets ahead of HEN design.


To calculate the HEN estimated surface area from the composite curves, utility streams must be included with the process streams in the composite curves to obtain the balanced composite curves. The resulting balanced composite curves should have no residual demand for utilities.

Then the balanced composite curves are divided into vertical enthalpy intervals to calculate the total minimum area targets assuming constant overall heat transfer coefficient and pure vertical counter current heat transfer using the famous formual in heat transfer Q=U*A*T_L.M.T.D [4]. Nowadays due to widespread use of computer programs for HEN automated design such area targeting calculation is not very beneficial any more in industry.

Now we will start the design of the HEN using the well known pinch design method. A good initialization of this design is to assume that no individual heat exchanger will have a temperature difference smaller than ∆Tmin calculated from the targeting phase and there must be no heat transfer across the pinch by process to process heat transfer or/and inappropriate use of utilities.

These rules are important for the HEN design to achieve the energy target, given that no individual exchanger should have a temperature difference smaller than ∆Tmin. To comply with these two guidelines the design problem needs to be divided at the pinch and using the grid diagram as shown in figure 20.

HEN DESIGN METHOD

Four Streams Problem Example The graph below shows the stream data of a very simple HEN problem drawn on a grid

diagram [1,2,3], where the pinch temperature is shown on both the hot and the cold sides using a minimum approach temperature, ∆T_min=10 ºC

Figure 20. Grid Diagram for HEN Design

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC

The Grid Diagram for the Step -By-Step HEN Design

CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW


The example given in this chapter for the illustration of the pinch design method for heat exchangers network design is very simple. Before going through the design of the network for this simple example in a step-by-step manner, some important rules in pinch design method need to be mentioned to enable the reader solve more complicated problems.

Start at the Pinch The pinch is the most constrained region of the problem. At the pinch, ∆Tmin exists

between all the hot and cold streams. As a result, the number of feasible matches in this region is severely restricted. Quite often there are essential matches to be made. If such matches are not made, the result will be either using a temperature differences smaller than ∆Tmin or we have to buy more utilities due to heat transfer across the pinch.

Since the pinch point divides the problem into two subproblems we are going to solve first the above pinch subproblem. We need to start at the pinch. There are some rules for matches to be both feasible and efficienct for the designated ∆T_min. With feasible we mean that the hot stream shall always have a ∆T_min over the matched cold stream. We will be elaborating more about feasibility later in this section. With efficienct we mean that a hot stream shall be matched above the pinch at the pinch in a way that he/she reaches its target temperature at the pinch. Hence, we reach the target heating utility calculated beforehand. Otherwise we will be needing to buy cold utility above the pinch!! Resulting in more heating and cooling utilities than the ones originally calculated during the energy targeting step.

In order to be able to achive this requirement, during matching above the pinch we have to have enough number of cold streams above the pinch at the pinch to enable each hot stream above the pinch at the pinch reaches its pinch temperature via matching with a cold process stream. Otherwise we end up using cold utility above the pinch. If the number of hot stream above the pinch at the pinch is less than the number of cold streams in such situation we can consider splitting cold streams to enable us keep the following two rules intact above the pinch at the pinch. These rules of the inch design method will be further elaborated in this section.

But for now we need to keep in mind the following two rules for streams matching above the pinch at the pinch:

1. Number of hot streams above the pinch at the pinch shall be less than or equal to

number of cold streams; and 2. Upon matching hot and cold streams, hot stream CP(FCp) should be less than or

equal to the cold stream matched with it (lighter in load) to avoid infeasiibilty in matching at some point and again to avoid using cold utility above the pinch at the pinch that results in consuming more than originally calculated energy target

For streams matching below the pinch at the pinch the reverse is true: 3. Number of cold streams at the pinch shall be less than or equal to number of hot

streams; and 4. Upon matching hot and cold streams, cold stream CP(FCp) should be less than or

equal to the hot stream matched with it (lighter in load) to avoid infeasiibilty in


matching at some point and again to avoid using hot utility below the pinch at the pinch that results in consuming more than originally needed energy target

The CP(FCp) inequality for individual matches

In summary for hot and cold streams matching above the pinch at the pinch; if a hot steam with CP(FCp) greater than a CP(FCp) of a cold stream, moving away from the pinch, the temperature difference must increase. At the pinch the match starts with a temperature difference equal to selected ∆Tmin. The relative slopes (1/FCp) of the temperature-enthalpy profiles of the two streams mean that the temperature differences become smaller while we are moving away from the pinch, which is infeasible. Hence we should not consider such match. On the other hand if we match this hot stream with another cold stream having a greater CP(FCp), in such case the relative slopes (1/FCp) of the temperature-enthalpy profiles now cause the temperature differences to become larger moving away from the pinch, which is feasible. Thus starting with ∆Tmin at the pinch, for temperature difference to increase while moving away from the pinch, we have to have this inequality achieved.

CPH(FCpH) is less than or equal to CPC(FCpC)

(Above the pinch for streams at the pinch)

So a very simple explaination for you to remember:

Above the pinch at the pinch the CP (FCp) of the hot stream shall be less than (lighter in load) or equal the cold stream matched with to enable it reach its pinch target tempetraturte without aid of cold utility above the pinch. Otherwise; the matching will be infeasible and to avoid such infeasibility we have to use cold utility above the pinch to enable the hot stream reach its pinch target temperature.

Below the pinch at the pinch the rules are the opposite. If a cold stream is matched with a hot that has a smaller CP(FCp), in such case steeper slope(1/FCp) will result, then the temperature differences away from the pinch will become smaller which is infeasible. If the same cold stream is matched with a hot stream with a larger CP(FCp) different situation will arise. A less steep slope(1/FCp) will be obtained resulting in temperature differences that become larger away of the pinch which is feasible. Thus starting with ∆Tmin at the pinch, for temperature difference to increase while we are moving away from the pinch we have to have the following inequality achieved

CPH(FCpH) is greater than or equal to CPC(FCpC)

( below the pinch for streams at the pinch) Again a very simple words for you to remember, below the pinch at the pinch the CP

(FCp) of the cold stream shall be less than (lighter in load) or equal to the hot stream matched with to enable it reach its pinch target tempetraturte without aid of hot utility below the pinch. Otherwise; the matching will be infeasible and to avoid infeasibility we have to use hot utility below the pinch to enable the cold stream reach its pinch target temperature that results in both heating and cooling utilities increase than originally obtained in the energy targeting step.


The CP(FCp) table Identification of the essential matches in the pinch region can be clarified using what we

call CP(FCp) table [1,2,3]. In a CP(FCp) table as is shown in the graphs below, the CP(FCp) values of the hot and the cold streams at the pinch are listed in descending order.

It is important to note here that the CP(FCp) inequality constraint applies only when a match is made between two streams that are both at the pinch. Away from the pinch, temperature differences increase and it is no longer essential to obey the CP(FCp) inequalities.

In conclusion there are some essential matches at the pinch or the region of minimum choice (ROMC) that need to be made around the pinch or the ROMC.

The next task is to design a network that exhibit minimum number of units. In other words we need to decide the matched heat loads which minimize the HEN number of units.

The “tick-off” heuristic

Once the matches around the pinch have been chosen to satisfy the criteria for minimum energy, the design should be continued in such a way to keep capital cost to a minimum. One important criterion in the capital cost is the number of units since more heat exchangers mean more skids; instrumentation, control; space; concrete and so on.

Keeping the number of units at a minimum can be achieved using the “tick-off” heuristic [1,2,3]. To tick off a stream, individual units are made as large as possible. In other words the smaller of the two heat duties on the streams being matched shall be taken completely.

Cooling water must not be used above the pinch to avoid unwarranted excessive use of utilities, therefore if there are hot streams above the pinch where the duties are not specified by pinch matches, additional process-to-process matches for more heat recovery shall be explored; even if it leads to more number of units in the network than the estimated minimum.

Same logic is correct for heating utilities application below the pinch. Hot utilitites must not be used below the pinch to avoid unwarranted excessive use of utilities; both heating and cooling. Therefore if there are cold streams below the pinch where the duties are not specified by pinch matches, additional process-to-process matches for more heat recovery shall be identified; even if it leads to more number of units in the network than the estimated minimum.

Streams Splitting Stream splitting is sometimes necessary to overcome the CP(FCp) constraints mentioned

above and/or to avoid using cold utility above the pinch or hot utility below the pinch. Cooling utilities should not be used above the pinch. It means that all hot streams must be

cooled to pinch temperature by heat recovery. If we have a number of hot streams greater than the number of cold streams (Three hot streams and two cold streams for instance) a problem will then arise. Since regardless of the CP(FCp) values of the streams, there will be one of the hot streams that will not be cooled to pinch temperature without some violation of the ∆Tmin constraint. This problem can only be resolved by splitting a cold stream into two


parallel branches. Thus in addition to the CP(FCp) criterion, there is a stream number criterion above the pinch such that

Sh is less than or equal to Sc (above the pinch)

Where:

Sh = number of hot streams at the pinch Sc = number of cold streams at the pinch

If there had been more cold streams than hot streams in the design above the pinch, this

would not have created a problem, since hot utility can be used above the pinch. Let us now consider the sub-problem below the pinch. Here hot utility must not be used

below the pinch. That’ means that all cold streams must be heated to pinch temperature by heat recovery. Again, for below the pinch, if we have the number of cold streams greater than the number of hot streams (3 cold streams and two hot streams, for instance) regardless of the CP(FCp) values, one of the cold streams can not be heated to pinch temperature without some violation of the ∆Tmin constraint.

The problem can be solved by splitting a hot stream into two parallel branches. In such a

case, each cold stream at the pinch will have a partner with which to match and be capable of heating it to pinch temperature. Thus there is also a stream number criterion below the pinch such that

Sh is greater than or equal to Sc (below pinch)

If we have more hot streams than cold streams below the pinch, this would not be a

problem, since cold utility can be used below the pinch. It is instructive to mention here that it is not only the stream number that creates the need

to split streams at the pinch but also the streams CP(FCp) inequality. Sometimes the CP(FCp) inequality criteria for the streams above the pinch “at the pinch”

and below the pinch “at the pinch” can not be met at the pinch without a stream split. It is important to emphasize here the need to satisfy both criteria; the stream population and the CP(FCp) inequality.

The number of hot streams above the pinch at the pinch needs to be less than or equal to

the number of cold streams above the pinch at the pinch. If this is not the case then we need to split a cold stream to achieve this guideline. At the same time, the CP(FCp) of the hot stream above the pinch at the pinch shall be less than or equal to the CP(FCp) of the cold stream above the pinch at the pinch in order to be able to match them in a heat exchanger. If this is not the case the cold stream needs to be split into two.


On the other hand, the number of cold streams below the pinch at the pinch needs to be smaller than or equal to the number of hot streams below the pinch at the pinch. If this is not the case then we need to split a hot stream to achieve this guideline. At the same time, the CP(FCp) of the hot stream below the pinch at the pinch shall be greater than or equal to the CP(FCp) of the cold stream below the pinch at the pinch in order to be able to match them in a heat exchanger. If this is not the case the cold stream needs to be split into two lighter loads cold streams.

Before closing the pinch design method (PDM) general description with its rules and heuristics let us summarize the methodology in a step-by-step fasion.

Briefly, the design procedure known as the pinch design method can be lumped as

follows: • Divide the problem at the pinch into two separate sub-problems • The design for the separate sub-problems is started at the region of minimum choice

known as the pinch point and then moving away • Temperature feasibility requires constraints on the CP(FCp) values to be satisfied for

matches between streams “at the pinch” for the two problems above the pinch and below the pinch

• The loads on individual heat exchangers are determined using the tick-off heuristic to minimize the number of units

• Away from the pinch there is usually more freedom in the choice of matches. In this case the designer can choose on the basis of his/her process knowledge

Having described the pinch design methodology, let us solve the numerical example

mentioned above. The pinch point has divided the problem into two sub-problems one above the pinch and

another below the pinch. The division lies at 310 ºC on the hot streams side and 300 ºC on the cold streams side. The problem minimum approach temperature used is ∆T_min=10 ºC, and the minimum heating and cooling utiltities are 2876 kW and 50 kW, respectively. Using the minimum number of units formula mentioned before we can estimate that the network minum number of units shall be 5 units. Now we will synthesize a feasible HEN that realizes these two design objectives; minimum utiltities consumtion and minimum number of units.

In such situations two pinch points will be arised and three sub-problems will be produced. One sub-problem above the 330 ºC-320 ºC near pinch point; one sub-problem below the 310 ºC-300 ºC pinch point and a third sub-problem in between the two pinch points. Handling situations like that is not difficult but less systematic than one pinch point situation [1]. The impact of such situation in the systematic design of the HEN is generating a HEN design that exhbits more number of units than the estimated minimum number of units HEN originally calculated without considering the near pinch point.


It is instructive to mention here that the hot stream H1 and the cold stream C2 can be called “near” pinch streams and in some commercial software another near pinch vertical line will be drawn at 330 ºC-320 ºC as shown in figure 21 below.

Figure 21. Grid Diagram with near pinch representation

We will start now the design above the pinch at the pinch. Since we have only one

possibility for hot stream matching with cold stream at the pinch, we will check the CP(FCp) matching rule. Since stream H2 has CP(FCp) equal to 5 while the cold stream C1 has a CP(FCp) equal to 20, the CP(FCp) matching rule here rule is satisfied, we do not need to make any split and we can match the hot stream H2 and the cold stream C1 as shown in the graph below, figure 21. Upon matching H2-C1 in a heat exchanger uint we need to tick-off one of the streams to minimize the number of heat exchangers, hence we let the stream with lower heat load ticked-off. In this example it is the hot stream H2. The heat exchganger heat duty/load can now be calculated by simply using Q= FCp (Ts-Tt) formula. This load (Q) in this example is equal to 350 kW. The hot stream H2 has now been cooled down to its pinch target temperature of 310 ºC and the cold stream C1 has been heated up from its pinch temperature at 300 ºC to 317.5 ºC as shown in figure 22. It is also important to note here that in the pinch design method, away from the pinch there is no systematic technique to complete the HEN. The designer can use his/her common sense to complete the design to reach feasible network rendering the exact minimum utilities requirements with minimum number of units.

It is clear in figure 22 above that the hot stream H1 and the cold stream C2 can also have a good match since hot stream H1 can be ticked-off completely, upon such matching with C2 resulting in a HEN with the desired estimated minimum number of units calculated earlier for the this example (5 units). The minimum approach temperature between the two streams is still not violated, greater than or equal to the specified ∆T_min=10 ºC, and is equal to 12.5 ºC.

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Near Pinch


Figure 22. Grid Diagram for H2-C1 matching above the pinch at the pinch

The hot stream H1 has a heat load of 1900 kW and hence the process to process heat

exchange between H1-C1 match shall be 1900 kW which is now the duty of this heat exchanger as shown in figure 23 below.

Figure 23. Grid Diagram for H1-C1 matching away from the pinch

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Q= 350 kW

317.5 ºC

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Q= 350 kW

317.5 ºC

Q= 1900 kW

412.5 ºC


Now to calculate the cold stream C1 outlet temperature from H1-C1 heat exchanger we divide the load/duty of this hea exchanger, 1900 kW, on cold steam C1 CP(FCp) to get the raise in temperature of this stream upon matching it with the hot stream H1. Adding this raise in temperature to the the cold stream C1 inlet temperature to H1-C1 heat exchanger renders the cold stream C1 outlet temperature equal to 412.5 ºC. Upon the completion of defining the matches for the two hot streams H1 and H2 at the pinch cold stream C1, we need now to decide the amount of hot utility needed to allow the cold stream C1 reaches its target temperature, 550 ºC.

Figure 24. Grid Diagram for C1 matching with hot utility away from the pinch

Figure 24 above shows that; the hot utility unit has a heating load/duty of 2750 kW. Bear in mind that in order to reach the minimum heating utiltity target the cold stream C2 should not require more than 2870-2750 kW of heating utility. Otherwise, the network streams matching to realize the minimum heating utility target will not be adequate. To enable the cold stream C2 reaches its target temperature we need a hot utility heater with duty equal to 120 kW as shown in figure 25 below.

Counting the number of units and adding the duties of the two utilities units, we see that the estimated minimum number of units, above the pinch, and minimum heating utiltity requirements are both satisfied. Before we move to the network design below the pinch, it is instructive to note that same result obtained in figure 25 above for the estimated minimum number of units and minimum heating utility equal to 2870 kW, may be obtained again using different HEN structure and process engineers are always encouraged to explore; synthesize and generate more than one HEN structure to study other process objectives satisfaction

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Q= 350 kW

317.5 ºC

Q= 1900 kW

412.5 ºCQ= 2750 kW


Figure 25. Grid Diagram for C2 matching with hot utility away from the pinch Figure 26. Grid Diagram for H2 matching with cold utility below the pinch Now after we completed the network above the pinch we go below the pinch. In this

simple example we have only one hot steam H2 below the pinch. The hot stream H2 needs to be cooled down from 310 ºC to 300 ºC. The amount of load needed to be removed from this stream is equal to 50 kW. Therfore the amount of cooling utility required using cooler will be 50 kW, which is exactly the cooling utility target obtained earlier during the utilities targeting step. Combining the design above the pinch and below the pinch gives us the complete design of the heat exchanger network that satisfy our two objectives of minmum number of units and minimum utitilties consumption at ∆T_min equal to 10 ºC.

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Q= 350 kW

317.5 ºC

Q= 1900 kW

412.5 ºC

Q= 120 kW

Q= 2750 kW

310 ºC

300 ºC

Pinch

380 ºC

520 ºC

380 ºC

330 ºC

300 ºC

300 ºC

320 ºC

550 ºC


CP(kW/ ºC)

H1=10

C2=2

C1=20

H2=5

QH_min = 2870 kW

QC_min = 50 kW

Q= 350 kW

317.5 ºC

Q= 1900 kW

412.5 ºC

Q= 120 kW

Q= 2750 kW

Q= 50 kW


Figure 26 above is showing such complete heat exchanger network that achieves the desired heat recovery level exhibited in minimum heating utility equal to 2870 kW and minimum cooling utility equal to 50 kW. It also consists of the estimated minimum number of units that equal to 5 units, two process to process heat exchangers and three utiltity service units (two heaters and one cooler).

Having introduced the fundamentals of energy integration using pinch techniques, the second part will discuss two industrial applications. In these two application pinch technology has been used for targeting and utility selection. However, because of capital cost and end user preference its strict application has been sacrificed for the sake of easy to operate networks and less capital investment.

PART II. HEAT INTEGRATION APPLICATIONS IN OIL INDUSTRY Environmentally, there are essentially four phenomena associated with atmospheric

emissions. They are urban smog, acid rain, ozone layer destruction and the greenhouse effect or global warming.

The greenhouse gas effect or global warming phenomenon problem arises mainly from the burning of fossil fuels, and its main constituents are carbon dioxide and methane, of which methane has more than ten times the effect of carbon dioxide. The result is that global temperatures increase, leading to melting of the polar ice caps and thus rising sea levels, increased weather disruptions and changes to ocean currents. Atmospheric emissions are mainly formed as by-products of combustion processes. Such combustion processes, to date, remain to be the main source used for energy generation in our societies.

In process industries, the essential sources of energy waste are associated with hot utilities. If the process industries require a furnace or a boiler to provide hot utility, then any excessive use of the hot utility will automatically produce excessive utility waste and consequently excessive generation of atmospheric emissions.

Therefore, energy conservation is one important way of not only saving money and natural resources, but also protecting the environment via minimizing energy-based GHG emissions. Until late last century the preferred method of dealing with the atmospheric emissions were known to be taking the end-of-pipe approach. This approach is myopic view and usually an expensive one.

This view does not tackle the problem at the source where solving could and indeed has proved in many cases to be easier and more cost effective. Nowadays, energy efficiency optimization techniques have become a major tool in NOx, SOx, CO and CO2 emissions minimization from combustion-based processes.

Systematic methods and tools have been developed and are currently utilized to conserve energy; protect energy-based natural resources and last but not least to minimize energy-based emissions and reduce the impact on the environment.

A major concept in the energy efficiency optimization techniques is the concept of “Heat Integration” applied in Pinch Technology and others to enhance waste energy recovery in industrial processes. One way of using this concept is to look first in our plants to satisfy some of their thermal energy needs through letting the hot streams (sources) that are to be


cooled help the cold streams (sinks) that are to be heated to enable both hot and cold process streams reach their heating and cooling targets.

This approach of “Integration” of heat sources and sinks in industrial facilities reduces the need for external hot thermal energy utility that mostly come from fossil materials combustion processes. This methodology in turn attacks, at the source, the main contributor to the atmospheric emissions problem by reducing the heating utility requirement. In this paper a step-by-step modifications are applied to an actual oil and gas separation plant to minimize its environment-footprint via GHG emissions reduction using heat integration. The approach give the process owner the facility to select scheme based upon not only capital but also energy resources sustainability and environmental impact on the world.

Oil and Gas Separation Plant Process Description The un-stabilized crude oil is pumped to the stabilizer unit through a pipeline. The

stabilizer is fed after removing some light ends. These light ends are combined with overheads from the column to the compression system. Light end gases from other stabilizers and low pressure and high pressure production traps, not shown in this graphs but by arrows only, are also directed to the gas compression section.

The fractionation capability provides a well defined split between the light ends and the crude oil. This tight split ensures maximization of stabilized crude and minimization of crude oil quality loss (API Gravity).

Heat input to the stabilizer bottom is provided through reboilers utilizing a heating oil media in a closed loop circulation system. A furnace is used to heat up the return cold heating oil. Light ends from the stabilizer overhead system is used as fuel for the heating oil furnace; flare pilot and purge gas process blanketing.

Net light gases are then compressed, condensed and pumped to the natural gas liquid pipeline.

The stabilized crude flowing from the bottom of the stabilizer column is cooled before going to its final destination partially by heat exchange with the stabilizer bottoms and completely in a final cooling stage using air coolers.

Heat Integration Application in Oil and Gas Separation Facility Pinch Analysis techniques have been applied taking into consideration legitimate process

constraints such as safety and operability to evaluate the possibility of improving heat recovery in the process and consequently reducing energy-based GHG emissions. Major streams in the process have been listed below with its supply temperatures. In this chapter Pinch technology has been used for targeting purposes and HEN synthesis. However the problem solved in this chapter is considering HEN sophistication as the primary dominant objective and energy cost and/or GHG emissions reduction as the secondary one.


Figure 1. Typical Oil and Gas Separation Process Flow Diagram

The design shown above is used as a base case to make comparisons among other design

options regarding energy consumption, capital investment, expressed in terms of number of heat exchangers and its surface area, and the GHG emissions reductions.

Heat integration role is not only to save energy consumption and its environmental impact but also it can save some capital investment.

Table 1.

Stream Name TS

[F] 1 De-gassing Tank Feed 90.0 2 Desalter Feed 109.8 3 Stabilizer Feed 157.5 4 Stabilizer Btms to Reb 165.0 5 Stb Btm Product 195.3 6 Atm Comp 1st stg 265.2 7 HP Comp 1st stg 191.0 8 HP Comp 2nd stg 210.9


In the early days of its application in process plants; people were triggered with its capability in such direction, hence many plants have been reporting successful applications. In many other cases realizing all possible potential in energy consumption collided with excessive needs for capital investment. In case of the oil and gas separation presented in this paper, Figure 2 below shows that for hot and cold streams minimum approach temperature of 17 ºF, the one used in the base case design, minimum heating and minimum cooling utilities consumption due to heat integration are 615 and 24 MM Btu/h respectively. Heating oil media is used to render the desired heating and air is used for the desired cooling. Realizing such results needs significant capital investment and the decision makers are always looking for scenarios to select among it, where they get highest possible impact on energy consumption and GHG emissions reduction with minimum capital investment.

A furnace with about 90 percent efficiency is used to heat up the return hot oil and electricity is taken from the grid to supply for air coolers and others. This furnace will produce about 300 kg of CO2 per hour for each megawatt of heat delivered to the heating oil media used in the process [1].

It is important to note here that even though the hot oil system used in the process can better match the process requirements for heating purposes compared with steam due to the slope of the heat deficit curve, as per the shown grand composite curve in Figure 3.In early design stages it might be much better to consider cogeneration application. Considering a CHP combined heat and power system in oil and gas separation processes can produce the desired electricity for the plant and the low pressure steam produced as a by-product of the cogeneration system in process heating purposes.

In this chapter the HEN design is only considered and not the whole utilities system. According to pinch technology heuristics for defining the minimum number of units, we have 8 streams above the pinch and 3 streams below the pinch, eleven heat exchangers will be required. This number can increase and form a very complex network in order to satisfy the desired energy targets for the oil and gas separation system while the base case design network is using only seven heat exchangers. Enabling the process owners to exercise their best budget allocation in reducing energy consumption and GHG emissions by a little defined increase in the capital investment is shown in the graphs below.

In figure 4 below only one heat exchanger has been added to the base case design to integrate the discharge of the first stage compressor with a branch from the crude stream before the desalter. In addition to the relocation of the stabilizer bottoms feed heat exchanger to make the matching happens before the desalter instead of having it after the desalter. This change requires an increase in the reboiler duty from the base case design of 197 MM Btu/h to 272 MM Btu/h

Such modifications in the base case design due to better integration results in about 85.8 MM Btu/h savings in heating oil duty and about 180 T/d reductions in GHG emissions and of-course savings air cooling duties savings too.

The capital investment is exhibited in the extra heat exchangers surface area increase shown in graph below.


Figure 2. Oil and Gas Separation Utilities Targeting

Figure 3. Oil and Gas Separation GCC


Figure 4. Oil and Gas Separation Design Option # 1

Pushing the envelope for more reduction in both energy consumption and GHG emissions lead us to design option # 2 shown in figure 5 below. In this design option two heat exchangers have been added to the base case design to integrate the discharge of the first and third stage compressors with a branch from the crude stream before the desalter. Again the relocation of the stabilizer bottoms feed heat exchanger has been also implemented and extra duty for the reboiler has been added. In this design option more waste heat has been recovered and consequently more GHG emissions have been reduced as follows; about 124 MM Btu/h savings in heating oil duty and about 260 T/d reductions in GHG emissions and of-course again more savings in air cooling duties.

Further push towards more reduction in heating oil duty and GHG emissions through design modification produces design options three, four and five shown in Figures 6, 7 and 8.

In these three new design options, three heat exchangers have been added to the base case design but with different surface area requirements as shown in the three figures below.

The reduction in heating oil duties are 128.6 MM Btu/h, 139.4 MM Btu/h and 142.9 MM Btu/h; respectively and the reduction in GHG emissions due to such reduction in heating oil duties are 270 t/d, 292 t/d and 300 t/d; respectively too.

It is instructive to note here that the reduction in both heating oil duties and GHG emissions with the increase in number of heat exchanger and associated surface area is happening with steeper change. About 60 % of the reduction in GHG emissions can be attained with 50 % of extra heat exchangers surface area.


Heat Integration in Crude Atmospheric Distillation Unit In crude atmospheric distillation units, feed get separated to different cuts according to

difference in boiling points. Crude feed get heated up from the ambient temperature to the desalting temperature, normally between 126 and 140 ºC. After desalting operation that reduces the crude temperature between 3 to 6 ºC, crude is fed to the pre-flash drum or sometimes even tower to remove some of the light hydrocarbons before the crude goes to the crude furnace.

Petroleum Gas & Light Naphtha

Heavy Naphtha

Kerosene

Light Gas Oil (LGO)

Heavy Gas Oil (HGO)

Atmospheric residue

Preheated Crude oil

Distillation tower

Fired heater

Crude oil feed

~40°C

~25-175°C

~150-260°C

~235-360°C

~330-380°C

~250-280°C

~350-370°C

Figure 9. Crude Atmospheric Distillation Unit

As shown in the generic crude atmospheric distillation; Figure 9 above the products from the crude tower and circulating pump-around that are used as tower inter-coolers are used to aid the products in heating the incoming crude. The incoming crude then is fed to the heater to raise its temperature to the desired flash zone temperature in the atmospheric distillation column.

It is always of high importance in the design of this unit to integrate the cold stream represented by the crude feed stream and products as well as pump-arounds to reduce the heat load the crude heater as much as possible. In this chapter, a real industrial application is introduced and discussed.

Table 2 below, shows data extracted from plant process flow diagrams for the crude as a cold stream and other hot streams. The cold stream is segmented into several streams using its simulation heating curve to avoid in-accuracy for assuming constant specific heat along long temperature range. The same is also practiced for some hot streams as shown in the table, using its simulation cooling curves.


Table 2.

TS TT DH CP Stream Name [C] [C] [MM kCal/hr] [MM kCal/C]

37.46 84.16 16.02 0.343041 84.16 90.42 2.27 0.36262 PreDesalter 90.42 126.7 13.74 0.378721 125 158.9 13.4833 0.397738 PreFlash 158.9 193 14.216 0.41689 188 225.1 14.8257 0.399614 225.1 265 16.64 0.417043 AfterFlash 265 378 64.52 0.570974

TPA 160.5 75 16.02 0.187369 185.1 105 2.27 2.83E-02 105 61 1.12 2.55E-02 Kero 61 40 0.5 2.38E-02 241.2 103.3 13.74 9.96E-02 LDO Prod 103.3 60 3.68 8.50E-02

IPA 253.9 138 13.43 0.115876 318.2 198.4 4.06 3.39E-02 HDO Prod 198.4 60 3.89 2.81E-02

BPA 327.5 225 10.35 0.100976 346.4 259.7 16.65 0.192042 259.7 169.9 15.52 0.172829 RCO 169.9 80 13.23 0.147164

The first step in applying pinch technology is to find for a reasonable minimum approach

temperature the minimum heating utility and minimum cooling utilities required for this crude unit. These targets are shown in Figure 10.

The heating utility which is our main focus in this application is about 48 MM Kcal/h Using pinch design method (PDM) to synthesis the crude pre-heat train, to reach desired

level of waste heat recovery and to minimize the heating load of the crude heater results in the network below in Figure 11. The network exhibits three splits in the cold crude stream. First split happens before the crude desalter, the second after the desalter and before the flash drum and the third after the flash drum up to the crude heater.

As you notice both heating and cooling utilities are considered being of the same important. In most cases in oil refining heating utility is more expensive than cooling water. Therefore, many designer put more emphasis on saving in heating utility since it also reduce emissions than saving on the cold side. Another very important objective in designing new pre-heat train in crude distillation unit is the number of units of the heat exchangers, less sophisticated configuration and the easiness of heat exchanger network operation and maintenance. This need pushes the plant designers to the extreme in considering the easiness of operation to the extent that they design networks that do not give enough attention to decent level of waste heat recovery and GHG emissions reduction compared with their emphasis on capital investment, maintenance and operation of the network.


Figure 10. Crude Atmospheric Distillation Unit Utilities Targeting

This approach is demonstrated here in the schematic pre-heat train design shown below in Figure 12 for the same industrial application in hand. The schematic network shown is only used for topology comparision.

The design exhibits less number of units, no split at all, but much less crude temperature ,265 ºC before the crude heater. This design means that the approach advocating the easiness of operation and minimum number of units results in more energy consumption in the crude heater and consequently more GHG emissions.

It is important to note here that maintenance and easiness of operation of heat exchanger networks in crude oil refining facilities are very legitimate issues. However, it needs to be handled with care and at the end a balanced picture and right trade-off based upon economic should prevail over the argument of we did not do designs like this before, or our operators are not trained to operate such sophisticated network or even we do prefer this one since it has no splits and less potential for fouling and cleaning.


Flash

Desalter

IPA157.9 To Tower

LOD Prod.241.2 C

RCO346.4 C

378 C292.8 C

HDO327.5 C

IPA253.9 C

HDO318.2 C

IPA217.4 C

HDO217 C

199.2 C

0.4

0.2

0.32

0.08

HDO Prod.60 C

150.7 C

37.5 C

0.3

0.46

0.24

RCO150.7 C

TPA160.5 LDO

150.9 C

HDO217.9 C

136.8 C

RCO Prod.80 C

To Colm.75 C

LDO Prod.60 C

133.9 C

133.4 C

133.8 C

134.5 C205.5 C

0.32

0.3

0.38 207 C

204.2 C

205.1 C

322.8 C

238.5 C

292.2 C

308.8 C

Figure 11. Crude Atmospheric Distillation Unit HEN (I)

E-7

E-1E-4E-3E-2

V04-V6\Desalter

E-5 E-6

E-8 E-9

TPA

160.5 C

KERO

185.1 C

LDO

241.2 C 253.9 C

37.5 C 84.5 C 90.8 C 127.0 C

138.8 C 137.1 CRCOBPA

346.4 C327.5 C

225.7 CHDO-2

318.2 C259.9 C

IPA-b

253.9 C

198.4 C169.9 C141.2 C

159

.

C 196

.

C 206 C

199.6 C 225.5 C

265.4 C

378 C

To air and water coolers

IPA

Figure 12. Crude Atmospheric Distillation Unit HEN (II)


Furnace

E-1 E-4E-3E-2

Desalter

E-5

Flash Drum

E-6 E-7

E-9

E-8

160.5 C

84.5 C37.45 C

TPA

75 C75 C

185.1 CKero

90.8 C

105 C

40 C 61C

241.2 CLDO

60 C103.3C

253.9 CIPA-a

134.2 C

127 C 138.8 C 137.1 C

IPA-b253.9C

141.2 C

RCO346.4 C

220 CRCO

80 C145 C318.2 C

HDO

186.3 C

60 C

193.8 C

200 C183.9 C

137.1 C

199.4 C

Flash Vap

276.6 C

275.4 C

275.8 C

378 C

327.5 CBPA

225.7 C

193.7 C

Figure 13. Crude Atmospheric Distillation Unit HEN (III)

The third network shown in figure 13 set the right compromise to some facilities. It is designed differently than the first network since it does not use the pinch design method. However, some sense of systematic technique has been also used here. This network design evolves from the simplest design desired by most of the process owners and plant operators. It has less number of units, no splits, less possibility of fouling and frequent cleaning needs, easy to operate and more importantly less area and capital cost.

The pre-heat train in Figure 13 kept the simple design before the desalter almost as it is and focused only on the heating utility minimization. It tried to push the temperature before the crude heater from 265 ºC in the simple design to about 276 ºC in the new design via better heat recovery in the area after the pre-flash drum only. A systematic technique can be used for that purpose via enumerating all matches possibilities between the crude stream, after the pre-flash drum, and all hot streams available at temperatures higher than its supply temperature. Simulating these possibilities only and then ranking them based upon the impact on the heating utilities requirement but with only one split in the crude stream after the pre-flash drum to avoid increasing fouling, will conclude this step and move the approach to the second step. The second step is to reconcile the selection of the new matches after the pre-flash drum with that before it. The possibilities that can arise can also be ranked based upon the level of simplicity in it.

The point that we are trying to make here in this crude unit pre-heat train design approach is that instead of designing the heat exchanger network using pinch design method to get the best possible waste heat recovery scheme and try an ad hoc approach to simplify the network,


we can start from the simplest possible straight line network shown in this chapter and evolve from it systematically to reach to better networks from waste heat recovery point of view and of-course GHG emissions reduction while keeping the easy to operate, clean to maintain and capital cost objectives satisfied. The details of this new approach and its step-by-step implementation will be published latter elsewhere.

CONCLUSION Pinch technology as a new systematic method for advanced waste heat recovery and heat

integration in industrial facilities emanated in the early seventies during the first oil crisis is still nowadays the most widely used technique for energy integration in oil industry. It has been successfully used to systematically address the problems of energy efficiency optimization and the reduction of energy-based un-desired emissions.

Systematic waste heat recovery in oil and gas industry is very beneficial to plant operating cost reduction. Aggressive waste heat recovery is an essential approach for in-process GHG emissions avoidance. GHG and other energy-based undesired by-products atmospheric emissions, produced during oil and gas separation processes and crude oil distillation can be reduced significantly through proper application of heat integration concepts. Every megawatt of heating utilities obtained from process boilers and/or furnaces that can be saved through efficient waste heat recovery system design and operation means less greenhouse gas and other harmful NOx and Sox emissions.

Improved heat recovery systems designs while can be attained systematically using Pinch Technology, it is important to consider it in a step-by-step approach especially for the heat exchangers network grassroots design modifications and existing plants retrofit to enable the decision makers selects the right scenario that best fit his/her capital investment budget.

REFERENCES

Douglas, J. (1985). Conceptual Design of Chemical Processes, McGraw-Hill, Inc. EL-Halwagi, M. (1996). Pollution Prevention Process Integration, Academic Press, Linnhoff, B. (1993). Pinch Analysis-a state-of-the-art, Trans. IChemE, 71(A5), 503-522 Noureldin, M. B. & Hasan, A. K. (2006). Global energy targets and optimal operating

conditions for waste energy recovery in Bisphenol-A plant, Applied Thermal Engineering 26, 374-381.

Noureldin, M. B. & Swan, J. E. (2004). Computer-Aided design software for energy optimization through interval constraint logic propagation, Proceeding of MDP-8, Cairo University Conference on Mechanical Design and Production, Cairo, Egypt, January.

Noureldin, M. B. (2003). TEM_icons™ 1.2 User’s manual, Report, Department of Materials and Process Engineering, University of Waikato, Hamilton, New Zealand.

Noureldin, M. B., Aseeri, A. S. & Al Qahtani, A. H. (2006). Systematic in-Process Modification Approach for Enhanced Waste Energy Recovery in Gas Plants, AIChE Spring Meeting Orlando, Florida, April 23-27.Smith, R. (1996). Chemical Process Design , McGraw-Hill, Inc.


Chapter 5

TREATMENT OF SECONDARY SLUDGE FOR ENERGY RECOVERY

Chunbao (Charles) Xu* and Jody Lancaster Department of Chemical Engineering, Lakehead University, 955 Oliver Road,

Thunder Bay, Ont., Canada P7B 5E1

ABSTRACT

Primary and secondary sludges are produced as a result of primary and secondary wastewater treatment in municipal wastewater plant or pulp and paper mills. Sludge disposal has become a worldwide problem for many reasons including rapidly shrinking landfill space, increased environmental awareness, more stringent environmental standards governing the disposal of sludge, and dewatering challenges. Unlike the primary sludge, the secondary sludge as byproduct of the biological treatment is far more difficult to dewater and to be disposed. Secondary sludge waste management issues are a continuing challenge. This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. In this chapter, we have overviewed a variety of secondary sludge post treatment methods for energy recovery, including incineration, gasification, pyrolysis, direct liquefaction, supercritical water oxidation (SCWO) and anaerobic digestion. A critical comparison between these methods is presented with respect to their net energy efficiencies. The advantages and drawbacks of each treatment option are also highlighted in this chapter.

1. INTRODUCTION Primary and secondary sludges are produced as a result of primary and secondary

wastewater treatment in municipal or industrial wastewater plants, e.g., pulp and paper mills. For instance, about 40-50 kg of sludge (dry)is generated in the production of 1 tonne of paper at a paper mill in North America (Joyce et al., 1979), and of that approximately 70%is primary sludge and 30% secondary sludge (Elliot and Mahmood, 2007). The primary sludge

* E-mail: [email protected]

Chunbao (Charles) Xu and Jody Lancaster 188

can be relatively easily dewatered for disposal. The secondary sludge consists predominantly of excess biomass produced during the biological process (Ramalho, 1983), and about half of the incoming organic pollution load is converted into secondary sludge, containing 0.5 to 2% solids (Winkler, 1993). Compared with the primary sludge, the secondary sludge is far more difficult to dewater.

The management of municipal and industrial wastewater sludges has been a long-standing challenge for many utilities. For example, Canadian municipalities spend $12–15 billion annually for sewage sludge treatment (Buberoglu and Duguay, 2004). Normally, sludges are disposed by landfilling and incineration (Reid, 1998), which have, however, suffered from their inherent drawback of poor economics due to many reasons including (1) the high cost associated with dewatering the sludge to 20-40% solids or higher so as to meet the requirements of landfilling or incineration, and (2) the significant energy loss in evaporating the sludge-containing water in incineration or combustion of the sludges in a recovery boiler. The sludge disposal/management costs can be as high as 60% of the total wastewater treatment plant operating costs (Canales et al., 1994). In recent years, due to rapidly shrinking landfill space and the secondary pollution issues associated with the conventional sludge disposal approaches as well as the increasingly stringent environmental regulations, the disposal of sludges continues to be one of the major challenges for the municipal wastewater plants and most pulp and paper mills (Mahmood and Elliott, 2006). This together with record high oil prices have contributed to a need to examine methods of converting secondary sludge waste into energy. For instance, the percentage of pulp/paper sludges disposed by landfills has constantly decreased in Europe in recent years, as shown in Fig. 1, dropping 40% in 1990 to 20% in 2002. In the meantime, the percentage of pulp/paper sludge used as a raw material in other industries and other applications (e.g., agriculture as soil improvers, in road construction, land reconstruction) and for energy recovery has steadily increased.

Figure 1. Disposal methods for the pulp and paper residues in Europe (adapted from Monte et al., 2008 and CEPI, 2004)

Treatment of Secondary Sludge for Energy Recovery 189

Comparing with other typical industrial sludges containing 16-35% of total dry solids (Oral et al., 2005; Rato Nunes, et al., 2008), the original secondary sludges from municipal wastewater treatment plant or a pulp and paper mill usually contains a much higher ratio of water (98-99%). A comparison of municipal and pulp and paper secondary sludge characteristics is presented in Table 1. Similarities exist between municipal and pulp and paper waste activated sludge, which would suggest that technologies used in the municipal wastewater sector could be transferred into the pulp and paper industry. General processes and technologies of sludge reduction technologies through process changes (e.g. operational control, and return activated sludge treatment) or through post-treatment (e.g., incineration, carbonization gasification, pyrolysis, supercritical water oxidation (SCWO) and aerobic/anaerobic digestion, etc.) have been recently reviewed by Mahmood & Elliot (2006). While changing/optimizing the sludge producing process would certainly reduce the amount of secondary sludge generation and thus alleviate the issues of sludge waste management, secondary sludge post-treatment technologies and in particular those aimed at energy recovery are the focus of this chapter.

Table 1. Comparison of municipal and pulp and paper activated sludge

(modified from Elliott and Mahmood, 2007)

Municipal Pulp/Paper Total dry solids (TS) (%) 0.8-1.2 1.0-2.0 Volatile solids (%TS) 59-68 65-97 N (%TS) 2.4-5.0 3.3-7.7 P (%TS) 0.5-0.7 0.5-2.8 Fe (g/kg_TS) 0 0.33-2.2 PH 6.5-8.0 6.0-7.6 Heating value (MJ/kg_TS)

19-23 22-25

To evaluate different post-treatment options and in order to provide a means of

comparison, it is advantageous to compare the energy efficiency for each option if possible. A definition of net energy efficiency may be outlined as follows (Xu and Lancaster, 2008). The net energy efficiency or “Energy Output/Input Ratio” can be defined as the ratio of energy content of the objective products to the energy input to produce it, as show in Eq. (1). For simplification of the discussion, several assumptions may be adopted: (1) Since the feedstock used is waste biomass or waste sludge, it can be considered as the feed of “ZERO” energy value, (2) the heat loss of the reactor or process is negligibly small assuming well insulation and (3) the energy consumption by other auxiliary operations (e.g., feedstock preparation and feeding, products separation and recovery, etc.) may be neglected. From the above assumptions, for many hydrothermal treatment processes for the treatment of sludge, the energy input may be approximated by the energy required to dewater/thicken the sludge from its original TS content (e.g. 1-2% for secondary pulp/paper sludge) to a suitable TS content for the process use (e.g 25% TS or above), and to heat the dewatered sludge from room temperature (Trm) to the specified reaction temperature (T).


Energy Output/Input Ratio = Input)(Energy

product) theof (massproduct) theof (HHV ∑ × (1)

The approximate energy efficiency of each process can be estimated by the equation

above, while depending on different requirements and characteristics of each process, the energy input calculation may differ method to method and may be difficult to determine due to shortage of experimental data reported.

The objective of this chapter is to provide an overview of different types of post-treatment methods of secondary sludge, i.e., waste activated sludge (WAS), for energy recovery. Emphasis is put on the discussion on the energy efficiency for each process, while advantages and disadvantages of each process are also highlighted. An outline of the many post-treatment options and their primary energy products can be summarized in Figure 2. A description of each treatment method including incineration, gasification, pyrolysis, direct liquefaction, super critical water oxidation and anaerobic digestion follows.

Figure 2. Outline of treatment options of secondary sludge for energy production

2. SECONDARY SLUDGE TREATMENT METHODS

Secondary sludge can be treated by employing a variety of post-treatment technologies

such as heat treatment, chemical oxidation and sludge digestion whose processes have been overviewed recently by Mahmood & Elliot (2006).

2.1. Incineration Incineration technology is the controlled combustion of waste with the recovery of heat

to produce steam that in turn produces power through steam turbines (Kumar, 2000). A general flow diagram of the incineration process is depicted in Figure 3. It shows that the sludge is fed into the boiler, which could be rotary kiln, fixed bed furnace or, common in the


paper industry, a fluidized-bed incinerator (Latva-Somppi et al., 1997). The incinerator yields products of steam and byproducts of ash and flue gas. Ash can be disposed directly into the nearest landfill or it can be used as the raw materials of light-weight aggregate and constructional brick in the building industry (Liaw et al., 1998; Monte et al., 2008). The flue gas requires treatment through air pollution control before discharge through the stack. However, specifically designed fluidized-bed combustors produce fewer pollutants through the flue gas (Kumar, 2000). For power generation the steam is directed through steam turbines, which work to produce power through the electric generator. Alternatively steam can be used locally for process steam reducing the mill’s dependence on costly fossil fuels for steam production (Monte et al., 2008). Typical fluidized bed operating temperature is between 700-900oC (Latva-Somppi et al., 1997). While depending on specific waste regulations in Europe 850oC must be achieved for at least 2 seconds, and if hazardous waste with a content of more than 1% of halogenated organic substances, the temperature is raised to 1100oC for 2 seconds in order to reduce the formation of the toxic compounds such as polychlorinated dibenzodioxins (PCDDs) (Monte et al., 2008). Efficient heat and mass transfer in the fluidized bed enables the endothermic fuel drying and devolatilization to occur simultaneously with exothermic combustion of char and volatiles (Latva-Somppi et al., 1997). Incineration of residues (both rejects and sludge), combined with power and steam generation, is one of the most commonly applied disposal methods in Europe (Monte et al., 2008). Sludge incineration is widely practiced on a full-scale basis in many highly populated urban areas such as in Japan and Germany (Stark et al., 2006). A recent review by Monte et al. (2008) cited eleven European pulp mills which burn some portion of pulp sludge in combination with other biomass. Oral et al. (2005a/b) described a three-stage retrofit of an incinerator in the Czech Republic and concluded that the thermal treatment through incineration of sludge for energy recovery is favorable both economically and environmentally.

Figure 3. General flow diagram of incineration (modified from Kumar, 2000)


In a sludge incineration process, water in the sludge is completely evaporated and the organic matter in the sludge is effectively oxidized at high temperatures to CO2 and H2O, as shown in the following two reactions:

Evaporation: H2O (l) → H2O (g) Oxidation and combustion: sludge solids/organics + O2 → CO2 + H2O + ash + heat Since the water evaporation reaction is highly endothermic, in order to sustain the

combustion for sludge with a low TS content, dewatering of the original sludge must be conducted or additional fuels (bark, wood waste and oil, etc.) shall be added (Monte et al., 2008). Monte et al. (2008) illustrated that self-supporting incineration (combustion) can be attained for feedstock containing approximately > 25% combustible/organic content and an ash content of 0-60%, where additional fuels are not necessary. Evaporation, oxidation and combustion occur simultaneously. The energy required for evaporation can be estimated using an equation from Kim and Parker (2008):

Qdrying = Mws ×W × [(Cp,water × ΔT) + ΔHvap] + [Mws × (1-W)] × Cp,sludge × ΔT (2)

Where Mws is unit mass of wet sludge using a basis of 1kg, W is the water fraction in

sludge, ΔHvap is latent heat for vaporization of water (2090 kJ/kg), Cp,water is heat capacity of water (4.186 kJ/kg/oC), Cp,sludge is heat capacity of solids in sludge (1.95 kJ/kg/oC) and ΔT is temperature difference between initial temperature of 25oC and the temperature of drying of 105oC. This results in an approximate energy input for drying of 2198 kJ/kg. Further energy input is required to raise the temperature of the sludge from drying temperature of 105oC to an average reactor temperature of 800oC. The further energy input can be estimated at 2753 kJ per kg of the sludge with 10% total solids (TS). An estimated energy consumption of the evaporation energy input plus the energy required for heating the feedstock to the reactor temperature is thus approximately 5000 kJ/kg. Approximately 30% of the solids remain in the ash (Fytili and Zabaniotou, 2008), therefore 70% is combusted. Energy output of the incinerator may be estimated given the steam generation data for the incinerator.

2.2. Pyrolysis Pyrolysis is a thermal decomposition process in the absent of oxygen to convert biomass

or waste materials into solid charcoal, water, water-soluble organics (pyroligneous acids, including methanol and acetic acid); water-insoluble organics grouped under the term of “tar” or “bio-oil”, and non-condensable gases (H2, CH4, CO, CO2).

The chemistry of pyrolysis mainly associates with degradation of carbohydrate polymers (cellulose and hemi-cellulose) and conversion of carbohydrate components, which may be illustrated in Figure 4.

When heated at a temperature higher than 300°C, the carbohydrate polymers de-polymerize into short chains of sugars, accompanied by slow dehydration and subsequent reactions to form unsaturated polymer intermediates that may be eventually condensed to form char (Lomax et al., 1991). When heated at a higher heating rate to a higher temperature, the de-polymerization reactions will liberate volatile products as oil or tar. Cleavage of C-C


bond will occur at a high temperature, leading to formation of gas products (mainly CO, CO2, H2 and CH4). Accordingly, pyrolysis process can be tuned to produce char, oil and/or gas by properly selection of the operating conditions of temperature, heating rate and reaction time. If the purpose is to maximize the oil yield then a high heating rate and short gas residence time would be required, while for high char production, a low temperature and low heating rate would be preferred. High yield of bio-oil up to about 70-75% (Agblevor et al., 1995) can be produced in fast pyrolysis processes (with very short residence time and elevated reactor temperature of ~500°C or higher). The commonly used reactors for fast pyrolysis include bubbling fluidized bed, circulating fluidized bed, ablative, entrained flow, rotating cone reactors, and vacuum reactors (Mohan et al., 2006). A significant amount of char and equal amounts of oil and gas products can be obtained in slow pyrolysis processes (operating at a low temperature for a long residence time). The char produced typically has a higher heating value of ~ 30 MJ/kg, which can be used as a valuable fuel for generating heat and electricity, or can be turned into activated carbon by activation. Pyrolysis oils are normally composed of a variety of organic oxygenates and polymeric carbohydrate and lignin fragments derived from the thermal cracking of cellulose, hemi-cellulose and lignin components of the biomass (Mohan et al., 2006; Tsai et al., 2007). The physical properties of wood fast-pyrolysis oil are compared with those of a petroleum-based heavy fuel oil in Table 2 (Czernik and Bridgewater, 2004). As shown in this Table, pyrolysis oil contains a high concentration of water (15-30%), and is highly acidic (corrosive) and unstable liquid with a lower caloric value of 16-19 MJ/kg compared with 40 MJ/kg for the petroleum-based heavy oil. Pyrolysis oil is a potential liquid fuel for turbines and boilers, or it can also be applied to produce chemicals directly, or be upgraded to high-quality fuels by hydro-cracking or catalytic cracking (Vitolo et al., 1999).

Figure 4. Chemistry of biomass pyrolysis (Lange, 2007)

Pyrolysis has long been recognised more advantageous over conventional incineration processes for the treatment of sewage-sludge with respect to fuel economy, energy recovery, and the control of heavy-metal emissions (Lewis, 1975). However, process efficiency is affected by sludge moisture content, such that co-pyrolysis with other wastes has been recommended in order to increase the dry-solids content of the sludge (Olexseyr, 1975). The process normally needs additional treatment to remove excess water. Higher water content feedstocks cause increases in the production of hydrogen and methane, but these do not compensate for the losses of carbon monoxide and thermal efficiency (Carre, et al., 1989). Water reduction is accomplished by dewatering to about 25% DS followed by thermal drying to 95% DS.


Table 2. Typical properties of pyrolysis bio-oil and of a petroleum-based heavy fuel oil (Czernik and Bridgewater, 2004).

Physical property Bio-oil Heavy fuel oil

Moisture content (wt %) 15-30 0.1

pH 2.5 -

Specific gravity 1.2 0.94

Elemental composition (wt %)

C 54-58 85

H 5.5-7.0 11

O 35-40 1.0

N 0-0.2 0.3

ash 0-0.2 0.1

HHV (MJ/kg) 16-19 40

Viscosity (at 50 oC, cP) 40-100 180

Low temperature pyrolysis with reactor temperature <500oC has also been widely

adopted for the treatment of sewage sludge in order to promote the oil yields and to minimize heavy metal evaporation. For a pyrolysis temperature maintained between 500 and 600°C, heavy metals in the sludge (except mercury and cadmium) could be safely retained within the solid chars (Kistler and Widmedz, 1987; Karayildirim et al., 2006). Cadmium has a lower evaporation temperature than most other metals and is dispersed into the gas phase at about 60°C, but can be condensed in gas-cleaning and scrubbing equipment with relative ease, while mercury can be completely evaporated at temperatures above 350°C and is difficult to eliminate from the gas stream (Furness et al., 2000). As an extension of standard pyrolysis, an oil-from-sludge (OFS) process has been developed with the system arranged to maximise the production of high quality oil, which can be used as a fuel (Bridle and Hertle, 1998). In the OFS process, pre-dried sludge (25% DS) is heated to 450°C for a heating period of about 30 minutes under anoxic conditions and at a pressure just above atmospheric, until about 50% of the sludge is evaporated. The vapours are then contacted with residual tar to catalyze the formation of high caloric value hydrocarbons. The process can produce 200-300 litres of oil per tonne of dried sludge. In comparison with incineration and anaerobic digestion, 95-98% of the energy in the dried sludge is recovered in the various products, and the net energy efficiency could be greater. However, the energy input for pyrolysis, including energy consumption for thickening, drying, and heating of the sludge feedstock to necessitate the pyrolysis process, is still fairly high. While the data of energy consumption for thickening of the sludge is unavailable, the energy consumption required to dry thickened waste activated sludge (TWAS) containing about 10% TS to a dry sludge at 105°C is about 2220 kJ/kg-ws, according to Kim and Parker (2008). This is a significant portion of the energy consumption for pyrolysis. Kim and Parker (2008) also found the energy consumption for increase of


temperature of the dry sludge from 105oC to reach target reactor temperature of 500oC to be about 770 kJ per kg, while the energy consumed during pyrolysis they assumed to be 300 kJ/kg. Thus, the total energy consumption for pyrolysis at 500oC is 3290 kJ/kg. Energy outputs for pyrolysis include the amounts and heating values of the oil, gas and char products, which is not easy to estimate. Using data from Kim and Parker (2008), the average yields of oil, gas and char were used as 25%, 10% and 65%, respectively, based on dry sludge (or 2.5%, 1% and 6.5% yield of oil, gas and char, respectively, based on TWAS). Average calorific values in kJ/kg of oil, gas and char were used and are 22,500, 1400, and 16,500 respectively. The total energy output is thus estimated to be 1649 kJ/kg. The net energy efficiency, calculated using Eq.1 is determined to be about 0.5, suggesting that pyrolysis is still an energy inefficient process. This conclusion may be supported by the work of Fytili and Zabaniotou (2008), which shows that pyrolysis is a rather endothermic process, of a magnitude of 100 kJ per kg of dry sludge.

2.3. Gasification Gasification is a thermo-chemical process during which carbonaceous content of coal,

biomass or lignocellulosic wastes is converted to a combustible gas at a high temperature (as high as 900-1400°C) into combustible gases (e.g. H2, CO, CO4, and CH4) in the presence of air, O2 or steam (Fytili and Zabaniotou, 2008). Gasification technology has been widely used around the world for the production of a fuel gas (or producer gas) from coal biomass. Typical producer gas from an air-blown gasification process has the following compositions: 9 vol% H2, 14 vol% CO, 20 vol% CO2, 7 vol% CH4, and 50 vol% N2, with a calorific value of 5.4 MJ/Nm3 (Furness et al., 2000). As a comparison, an O2-blown gasification process produces a gas of the following compositions: 32 vol% H2, 48 vol% CO, 15 vol% CO2, 2 vol% CH4, and 3 vol% N2, with an increased calorific value of 10.4 MJ/Nm3 (Furness et al., 2000).

Biomass gasification technology has received increased interest in the last decade since it offers several advantages over direct combustion, such as reduced CO2 emission, compact equipment with small footprint, accurate combustion control, and high thermal efficiency (Rezaiyan and Cheremisinoff, 2005). Gasification technology if integrated with combined cycle gas turbine system has an overall thermal efficiency of 70-80% and an electrical efficiency as high as 50%, offering better perspectives for power generation from biomass (IEA Bioenergy Executive Committee, 2007). It has been shown that biomass gasification plants can be as economical as conventional coal-fired power plants (Badin and Kirschner, 1998). Gasification, in particular larger scale circulating fluidized bed (CFB) concepts, also offers excellent possibilities for co-firing schemes. The gas product of gasification, also known as producer gas or syngas, can be mainly used for steam or heat generation as the fuel gas, for hydrogen and substitute natural gas production, for fuel cell feed, and for the synthesis of liquid fuels such as methanol and F-T liquid through various gas-to-liquid catalytic conversion processes (Dry, 1999). Gasification of biomass has been achieved with various types of gasifiers, ranging from fixed-bed to fluidized-bed and entrained bed gasifiers, whose advantages and disadvantages are as summarized by Rampling and Gill (1993) in Table 3. As revealed in the Table, the major technical challenge for biomass (as well as for sludge) gasification is associated with ash slagging and the formation and removal of tar (high


molecular-weight hydrocarbons rich in benzene, toluene and xylene). The presence of tar in the producer gas is undesirable not only because it is an indicator of low gasification efficiency, but also due to the fact that it increases the difficulty of syngas cleanup by fouling and plugging the pipes and tubes of some equipment (Rezaiyan and Cheremisinoff, 2005). It is thus necessary to develop technical approaches to eliminate tar. Tar removal can be achieved either by primary method taking place insider the gasifier or by secondary treatments outside the gasifier (e.g., hot gas cleanup). As a primary method, choosing the proper configuration of a gasifier can reduce tar formation. Brandt and Larsen (2000) produced a significantly low tar formation by employing a novel two-stage gasifier composed of a pyrolysis unit and a gasification unit with a charcoal bed. Nunes et al. (2007) also observed a reduction in tar formation when the producer gas went through a second-stage bed packed with char in a downdraft fixed-bed gasifier. Addition of catalysts, such as char, alkali/alkaline earth metal-based catalysts (e.g. Na, K, and Ca) and transitional metal-based catalyst (e.g., Ni and Fe), proved to be an effective means to reduce tar formation by converting tar into combustible gases through steam reforming, CO2 reforming, thermal cracking, hydro-reforming/hydro-cracking, and water-gas reactions (Kimura et al, 2006). As the secondary method for tar removal, hot gas cleanup has attracted increasing attention in recent years due to the development of integrated gasification combined cycle (IGCC) and integrated gasification fuel cell (IGFC) technologies. Hot gas cleanup, i.e., catalytic destruction of tarry products and NH3 (a contaminant species in the producer gas) at a high temperature is needed to further increase the overall power generation efficiency of IGCC and IGFC. The most common catalysts for the decomposition of tar and NH3 are dolomite (a calcium magnesium ore, CaMg(CO3)2) and Ni-, Mo-, or Ru-based catalysts (Dayton, 2002), as well as inexpensive Fe catalysts (such as chars from low rank coals with inherent Fe and Ca cations and limonite iron ore) (Ohtsuka et al., 2004; Xu et al., 2005).

Recent developments in biomass gasification including some non-conventional gasification processes are under investigation, such as plasma gasification and supercritical water gasification. Plasma gasification is a gasification process that decomposes biomass into basic components, such as hydrogen, carbon monoxide, and carbon dioxide in an oxygen-starved environment, with the assistance of a plasma torch heating the biomass feedstock to a temperature of 3000°C or higher (Rezaiyan and Cheremisinoff, 2005). This plasma technique has high destruction and reduction efficiencies, and it has great application potential for a wide range of hazardous waste treatment, including both organic and inorganic compounds.

Recently, supercritical water (SCW), highly compressed water at above its critical temperature of 374°C and critical pressure of 22 MPa, has been chosen as an ideal gasification medium for biomass or lignocellulosic waste conversion primarily because of its special properties such as liquid-like density and gas-like diffusivity. More importantly, SCW has strong solubility for organic compounds, accompanied with its high reactivity (Akiya and Savage, 2002). A wide range of biomass including some model compounds and lignocellulosic wastes have been successfully gasified in supercritical water (Xu and Antal, 1998; Yoshida et al., 2004; Hao et al, 2005; Williams and Onwudili, 2006). Compared to conventional gasification processes, supercritical water gasification (SCWG) has higher gasification efficiency, hydrogen yield and less tar formation (Xu and Antal, 1998). In addition, supercritical water gasification can utilize the wet biomass and wastes directly, eliminating the energy- and capital-intensive drying process. Thus, SCWG is particularly suitable for gasifying biomass with high moisture content and some waste streams such as sewage sludge (Xu and Antal, 1998). A recent study by Izumizaki et al. (2005) summarized


experiments where hydrogen was produced from paper sludge in supercritical water in the presence of ruthenium (IV) dioxide, RuO2. The reaction conditions were 100 mg paper sludge, 20 mg catalyst, temperature of 450oC for 2 hours. The major components of gases produced were hydrogen, methane and carbon dioxide in molar ratios of 27%, 27% and 45%, respectively. One of the author’s research group has recently started an extensive study on catalytic gasification of pulp/paper secondary sludge in SCW for hydrogen production. To the best of the authors’ knowledge, to date there is no other investigation worldwide that is focused on the use of pulp/paper secondary sludge as feedstock for hydrogen generation.

Table 3. Comparison of different types of gasifiers (Rampling and Gill, 1993).

Energy requirement in different stages of a typical gasification process is outlined in

Figure 5, including the location of energy inputs and outputs. According to Ptasinkski et al. (2007), gasification of raw sludge is not very energy

efficient because the raw sludge contains a substantial amount of water (at as high as 98-99 wt%), and hence the optimal reaction conditions are difficult to achieve. In order to improve the gasification efficiency, the moisture content of the sludge must be greatly reduced or dried


prior to being fed to a gasifier. According to Kim and Parker (2008), the energy consumption required to dry thickened waste activated sludge (TWAS) containing about 10% TS to a dry sludge at 105°C is about 2220 kJ/kg-ws. It may be possible to use the enthalpy of the producer gas for drying the sludge and biomass feedstock for the gasification. However, the gasification of pulp/paper secondary sludge is a relatively new method and hence not very well documented so far, except for several reports on gasification of a mix of municipal sewage sludge and coal and other domestic waste (Dinkel et al., 1991; Baumgartel, 1993). For dry sludge, the gasification technology has shown to be an energy efficient process. For instance, Hamilton (1998) reported that gasification of dried sewage sludge thermally with the Lurgi-Rhurgas process based on a circulating fluidized bed produced 0.7 m3 of fuel gas per kg of dry sludge (DS), and the calorific value of the gas was as high as 22.7 MJ/m3, i.e., a total energy output of about 16 MJ//kg-DS. With dry sludge used, the total process can thus be energetically self-sustaining (Furness et al., 2000).

Figure 5. Energy requirement in different stages of a typical gasification process (modified from Furness et al., 2000)

2.4. Direct Liquefaction

Due to the skyrocketed oil price and the increased concerns over greenhouse gas

emissions, there is a worldwide resurgence of interest in the production of liquid oil products (e.g., bio-oils and bio-crude) from biomass through liquefaction. Fast pyrolysis, as described


in the preceding section, is so far the only industrially realized technology for bio-oil production (with a liquid yield of 50-70%) (Onay and Kockar, 2006; Maschio et al., 1992). However, the oil product in fast pyrolysis (i.e., bio-oil) consists of a high content of water (20-25%) and oxygen, and hence a low heating value (<20 MJ/kg, about only half of that of crude oil), and the oil is highly corrosive due to its low pH value, as given in Table 2. Without further upgrading, the pyrolysis oil is not regarded as an ideal liquid fuel for heat and power generation. The main purpose of liquefaction is to produce oil products of increased H/C ratios and decreased O/C ratios, and hence a high caloric value relative to those present in the feedstock. Liquefaction can be accomplished indirectly or directly. For indirect liquefaction, biomass is converted into liquid products through first gasification to syngas followed by catalytic conversion (Dry, 1999). Direct liquefaction of biomass feedstocks into liquid oils has attracted more intensive interest, due to its simpler technical route and better conversion economy and efficiency relative to the indirect liquefaction processes. In a typical direct liquefaction process, biomass is converted to liquid products directly but through a complex sequence of processes involving solvolysis, depolymerization, decarboxylation, dehydration and hydrogenolysis/hydrogenation (when hydrogen is present in liquefaction). Direct liquefaction is a low-temperature, high-pressure conversion in the liquid phase, usually with a high hydrogen partial pressure and a catalyst to enhance the rate of reaction (Furness et al., 2000). Yields of the products depend on temperature, residence time, initial biomass concentration, catalysts and liquefaction atmosphere (inert, N2 or reducing, H2). The effects on the liquefaction product yields were investigated.

Research on direct liquefaction has been widely performed in the 1980’s for the purpose of alternative energy production (Kranich, 1984; Beckman and Elliot, 1985; Boocock and Sherman, 1985). For instance, in an early study on liquefaction of sewage sludge, conducted by Kranich (1984), sewage sludges were converted to oils in a reaction medium of water or oil at 295-450°C with the presence of a reducing gas (hydrogen) and catalysts of Na2CO3, NiCO3 and Na2MnO4. The organic conversion rates varied from 45% to 99% and the oil yields were from 35% to 63% in the reaction medium of oil. However, the oil yields were found very low with the water medium (usually less than 20%). Many successful studies on direct liquefaction of biomass in organic solvents such as anthracene oil (Appel et al., 1996; Crofcheck et al., 2005) and alcohols (Miller at al., 1999; Xu and Etcheverry, 2007) have been reported. Hot compressed water and sub-/supercritical water (at temperatures of 200-400°C) are however more advantageous for being used as the solvent in biomass direct liquefaction in that water is likely the most “green” and environmentally benign solvent. Extensive research work has been conducted on direct liquefaction of biomass in sub- and near-critical water. A pioneer work was reported by Appell et al. (1971), where a variety of lignocellulosic materials were efficiently converted to oily products in water at around 350oC in the presence of Co and Na2CO3 as the catalysts. Minowa et al. (1998a, b) obtained heavy oil (HO) (with calorific values of around 30MJ/kg) at a yield of 21-36 wt% from a variety of biomass feedstocks in water at 300oC and around 10 MPa with Na2CO3 as catalyst. Qu et al. (2003) obtained liquid organic products at a total yield of 30-35% by direct liquefaction of Cunninghamia lanceolata in water at 280-360oC for 10-30 min. It has also been demonstrated by Suzuki et al. (1986) that the treatment of sewage sludge by direct liquefaction in water at around 300oC could be a profitable alternative means for sludge disposal. However, the feedstocks tested so far were mainly wood and municipal sewage sludge, and to the best of


the authors’ knowledge, other than the published work by Xu and Lancaster (2008), no work has been reported on treatment of pulp/paper secondary sludge in hot-compressed water or sub-/supercritical water. As a result, liquefaction as a treatment method is still in the research stages but could potentially be an effective approach to recover energy from the secondary sludge waste for production of liquid oil products.

Xu and Lancaster (2008) experimentally treated secondary pulp/paper sludge in hot-compressed or sub-/supercritical water at a temperature of 250-380oC in order to produce liquid oils for energy recovery from the secondary pulp/paper sludge. An outline of a direct liquefaction process for the treatment of sludge is pictured in Figure 6, where sludge is fed into a pressure reactor where liquid products are primarily produced and gas products are collected. Liquid products are a mixture of water-soluble oil (WSO) and heavy oils (HO) and solid residue or char. Filtration is performed on the liquid product mixture in order to separate the liquid oil products from the solid residue, char.

Figure 6. Outline of the direct liquefaction process (adapted from Xu and Lancaster, 2008)

The effects of liquefaction temperature, residence time, initial biomass concentration,

catalysts and liquefaction atmosphere (inert, N2 or reducing, H2) on the liquefaction product yields were investigated. Treatments of secondary pulp/paper sludge in water at 250-380°C for 15-120 min in the presence of N2 atmosphere resulted in yields of water soluble oils (WSOs) at 20 wt% - 45 wt% and yields of heavy oils (HOs) at 15 wt% – 25 wt%, with HHVs of 10-15 MJ/kg and >35 MJ/kg, respectively. For temperatures lower than 350oC, as temperature increased the yield of heavy oil (HO) increased at the expense of the water-soluble oil (WSO) formation, while as temperature increased further to above 350oC, the yield of HO decreased, accompanied by an increase in the yield of WSO. An increased residence time produced a greater yield of HO (reaching as high as 25wt% for 120min) but a lower yield of water-soluble and a reduced yield of total oil. A higher initial biomass


concentration produced a greater yield of HO but a reduced yield of WSO, while resulting in negligible change in the formation of total oil products. The presence of 0.1M K2CO3 dramatically enhanced organic conversion leading to a low yield of char, while the use of the K2CO3 suppressed the formation of both types of oils. The use of the two alkaline earth metals catalysts, i.e., Ca(OH)2 and Ba(OH)2, did not alter biomass conversion significantly, but catalyzed the formation of WSO and produced much higher yields of total oil products. The liquefaction atmosphere (inert or reducing) was found to be another important factor influencing the liquefaction process. As shown in Figure 7, it was demonstrated that the reducing atmosphere (i.e., H2) in the liquefaction process promoted the HO formation while suppressing the WSO formation. With the presence of 0.1M Ca(OH)2 and 2MPa H2, liquefaction of the sludge powder in water at 280oC for 60 min produced a high yield of HO (26 wt%), almost two times as high as that in N2 (13.6 wt%), and it produced total oily products (HO+WSO) at a yield as high as 60 wt%.

20.3

13.6

21.0

26.0

36.9

51.4

35.6

34.2

21.3

21.5

20.6

22.0

5.7

4.8

7.3

6.2

0 20 40 60 80 100

None

Ca(OH)2

None

Ca(OH)2

Yield (wt%, daf)

HO WSO Char Gas

Liquefaction in H2

Liquefaction in N2

280oC, 60 min9.1 wt% biomassInitial gas pressure: 2 MPa

Figure 7. Variation in the product yields with different liquefaction atmospheres (N2 and H2) (adapted from Xu and Lancaster, 2008).

In Xu and Lancaster’s (2008) work, the energy output/input ratios, calculated based on Eq. (1), were all <1.0, suggesting that the liquefaction operation tested, in a batch reactor, was energy inefficient. However, the energy efficiency can be improved by employing a flow-type reactor and installing a heat exchanger to pre-heat the reactor feed stream using the hot product stream as well as by combusting the resulting chars/gases to provide a portion of the heat for the process. Liquefaction of sludge in H2, irrespective as to whether a catalyst was present or not, resulted in significantly improved net energy efficiencies. However, the operation in H2 with the presence of Ca(OH)2 catalyst dramatically enhanced the efficiency to as high as 0.76.


2.5. Supercritical Water Oxidation (SCWO) Supercritical Water Oxidation, SCWO, also referred to as hydrothermal oxidation, is a

process that oxidizes organic solutes in an aqueous medium using oxygen/air or hydrogen peroxide as oxidants, at temperatures and pressures above the critical point of water, i.e., 374oC and 22MPa, respectively (Bermejo et al., 2006). The SCWO process has been under development since the early 1980’s when the well known process of wet oxidation was developed at MIT (Modell, 1982). SCW is a superior reaction medium with a high diffusivity, a low viscosity, and relatively high-density therefore rapid oxidation reactions are expected. Moreover, the low temperature of the SCWO process in comparison to conventional combustion can lead to a greatly reduced NOx and SO2 formation. In addition, water is not only the reaction medium but it participates directly in the reaction through the formation of free radicals (Griffith and Raymond, 2002). Since water is utilized in the reaction there is no requirement to dewater the sludge before processing. Sludge can be processed at 10% solids by weight or even less (Mahmood and Elliott, 2006).

Figure 8 outlines a schematic of a SCWO process. Pressurized sludge (25.5MPa) and pressurized oxygen are fed into the preheater reactor at 25 degrees Celsius. In the preheater the mixture of sludge and oxygen are heated up to approximately 300 to 400oC, to achieve the supercritical state of water. Water at its supercritical state can dissolve organics and hydrolyze even polymers and hence prevent the formation of char (Perry and Green 1999; Fang and Koziński, 2000; Mahmood and Elliot, 2006). The reaction mixture enters the main reactor where the remaining portion of the organics is oxidized in short hydraulic residence time of 5-10 min at the maximum process temperature of around 600oC (Mahmood and Elliott, 2006). After reaction, the effluent is cooled and energy is recovered. According to Svanstrom et al. (2004), about half of the heating value of the sludge can be recovered in the studied process. The solid and liquid products are separated and the wet inorganic solids can be sent to a landfill or spread on dedicated land while the water can be redirected to the wastewater treatment plant.

Figure 8. Schematic of a SCWO system (modified from Mahmood and Elliott, 2006).


The effectiveness of SCWO has been demonstrated at the laboratory and pilot scale with a wide broad range of feedsctocks, such as pig manure (Rulkenes et al., 1989), a variety of biomass slurries including pulp mill sludge (Modell, 1990), and sewage sludge (General Atomics, 1997). It has been demonstrated that complete oxidation of virtually any organic material, including hazardous wastes such as hexachlorobenzene, could be achieved by SCWO. A supercritical water oxidation sludge processing plant has been installed at Harlingen, Texas to process up to 9.8 dry tonnes per day of municipal sludge (Griffith and Raymond, 2002). An environmental assessment was conducted on the Harlingen plant and found large environmental gains from recovery of heat thereby reducing natural gas consumption for heat generation (Svanström et al., 2004). Hydrothermal oxidation, in particular SCWO, is currently being considered by various research and waste management organizations as an alternative treatment option (Stark et al., 2006).

2.6. Anaerobic Digestion Since a large number of the enteric bacteria and viral pathogens presented in untreated

sewage are associated with wastewater solids, many are not completely removed during sewage treatment processes and are merely transferred to wastewater sludge (Farrah and Bitton, 1983). Anaerobic digestion processes are widely recognized as particularly suitable for highly polluted wastewater treatment and for the stabilization of primary and secondary sludges. Anaerobic digestion occurs in the absence of oxygen while in the presence of bacterial activity, producing bio-gas (mainly methane). The methane gas produced can be used to generate power by fueling a biogas engine connected to an electric generator. The digested and separated solids can undergo further processing and potentially be used as a fertilizer or soil conditioner for land application (Kumar, 2000; Gavala et al., 2003), while the treated water may be used for irrigation (Kumar, 2000). Anaerobic digestion of municipal or pulp/paper bio-solids could reduce solid wastes by 30-70% with the benefit of energy recovery through methane production. Generally about half of the organic matter in sludge is susceptible to anaerobic biodegradation into the formation of biogas (Elliot and Mahmood, 2007).

The microbiology of anaerobic digestion is complicated and involves several bacterial groups forming a complex interdependent food web. However, four major steps can be distinguished. In the first hydrolysis step, both solubilization of insoluble particulate matter and biological decomposition of organic polymers to monomer or dimmers take place. Acidogensis and acetogenesis follow in the second and third step while in the fourth and final step methane is produced by menthanogenic archaea (Gavala et al., 2003). Figure 9 outlines a flow diagram of anaerobic digestion of secondary sewage sludge for energy production. Secondary sludge is fed into the hydrolysis tank. In conventional single-stage anaerobic digestion processes, hydrolysis is regarded as the rate-limiting step in the degradation of complex organic compounds, such as sewage sludge. Two-stage systems have been proposed to enhance this process (Ponsá et al., 2008). The first stage digests the solids, and the second stage separates the undigested solids from the liquid to form carbon dioxide, methane and water. There are two typical operating temperatures for anaerobic digesters determined by the desired species of methanogens. For mesophilic processes, the optimum operating temperature is 37oC, while 55oC is desirable for thermophilic processes (Song et al., 2004).


Thermophilic anaerobic digestion is generally more efficient in terms of organic matter removal and methane production than the mesophilic process (Gavala, H.N. et al., 2003).

Figure 9 . Flow diagram of anaerobic digestion for power generation (modified from Kumar, 2000)

Telles et al. (2002) evaluated the performance of a slow rate anaerobic digester in treating

secondary sewage sludge. The digester was fed by secondary sewage sludge without any previous thickening, having a concentration of volatile suspended solids (VSS) of 24-29 gL-1. The operation of anaerobic digestion at room temperature was stable, with no noticeable scum or foaming problems. The COD reduction in these experiments reached 29, 21 and 45% in the sludge. Anaerobic digestion of Kraft waste activated sludge (or secondary sludge) was tested with a pilot-scale digester for sludge reduction and biogas production (Puhakka et al., 1992). With sludge containing 38% lignin, 40% reduction of the sludge and a biogas production of 0.5 m3-biogas/kg sludge removed were achieved. In these tests, 13 g NaOH/kg sludge was added to maintain the optimum pH in the system for the maximum sludge reduction efficiency. Fein et al. (1989) reported that the anaerobic digestion process for the treatment of Kraft mill primary sludge could be significantly more economical than the conventional landfilling. Stahl et al. (2004) also reported a pilot trial using anaerobic digestion to pre-treat wastewater and to digest untreated paper mill effluent, which resulted in a much lower amount of organics entering the activated sludge system, thus substantially reducing the quantity of the secondary sludge from the aerobic treatment operation. Anaerobic digestion has been widely adopted for the treatment of municipal sewage sludge before final disposal


and it is employed worldwide as the oldest and most important process for sewage sludge stabilization and treatment (Ponsá et al., 2008). While anaerobic digestion is commonly practiced in the municipal sector, it has not gained popularity in the pulp and paper industry mainly because of its long sludge residence time requirement of 20-30 days (Elliot and Mahmood, 2007). There is currently no full-scale anaerobic digestion facility in the pulp and paper sector for the digestion of solid residues. Nevertheless, there is recent technological advancement that potentially can make anaerobic digestion of pulp/paper sludge more feasible by the development and establishment of pretreatment of sludge prior to anaerobic digestion to accelerate the hydrolysis of sludge.

3. DISCUSSION AND COMPARISON OF TREATMENT METHODS The operating conditions (temperature, pressure, atmosphere and products, etc.) vary

among the methods discussed in the preceding sections, as summarized in Table 4. For example, incineration, gasification and SCWO methods utilize air or oxygen while the remaining methods are conducted under oxygen depleted or anaerobic conditions. Some direct liquefaction processes employ hydrogen gas to obtain better product yields and results. Incineration, pyrolysis and gasification operate at high temperatures, while these methods differ in the objective products. Incineration aims to produce heat and steam/electricity, pyrolysis targets a high yield of oil, and gasification favors production of gas.

Table 4. Summary of Comparison of Secondary Sludge Treatment Methods

Comparison Parameter

Incineration Pyrolysis Gasification Direct

Liquefaction SCWO Anaerobic Digestion

Preheating/ Drying required

No Yes (25% solids, ~150oC)

Yes No No No

Operating Temp (oC) 850-950 400-800 800-1400 250-400 400-

600

37 (Mesophilic) 55 (Thermophilic)

Operating Pressure Ambient Ambient or

slightly above Ambient 4-20 MPa 22 MPa Ambient

Operating atmosphere Air Oxygen

depleted Air or oxygen

H2 – reducing N2 - inert

Air or oxygen Anaerobic

Primary Energy Products

Steam Oil, Gas and Char Syngas Oil, Gas and

Char Gas Biogas, Methane

The greatest sludge volume reduction (over 90%) can be achieved with the high-

temperature methods including incineration, pyrolysis and gasification, which is advantageous as it effectively reduces the physical amount of sludge for disposal. The major disadvantage for these high-temperature processes is their lower net energy efficiency for the treatment of secondary sludge containing very high content of water (98-99%), resulting from the need of the energy intensive operations of dewatering/thickening and complete evaporation of the water in the sludge.


Other main problems concerning these high-temperature thermal processes include excessive energy to reach high temperatures, need for extensive air pollution equipment and, therefore, high capital costs (Monte et al., 2008). In contrast, the other three treatment methods, i.e., direct liquefaction, SCWO and anaerobic digestion, operate at a relatively lower temperature and more importantly without the need of dewatering /thickening and complete evaporation of the water in the sludge. As a matter of fact, for SCWO and direct liquefaction methods, the water in the sludge is the reaction medium and participates directly in the reaction through the formation of free radicals (Griffith and Raymond, 2002). Accordingly, these methods are more promising for the treatment of secondary sludge from the standpoint of energy recovery. A comparison of advantages and disadvantages of different treatment methods are presented in Table 5.

Table 5. Advantages and disadvantages of sludge treatment methods

(Kumar, 2000; Furness et al., 2000; Karayildirim et al.,2006; Bermejo et al., 2006; Mahmood and Elliot, 2006;Monte et al., 2008)

Treatment Method

Advantages Disadvantages

Incineration - High reduction of sludge volume by about 90%

- Nearly complete elimination of the organic materials

- Possible utilization for the ashes obtained

- Incineration process can be energy deficient - Air pollution problems (NOx and SO2

emissions) - Dewatering/thickening of the sludge is

required - Emission of chlorinated compounds - High cost due to the increasing demand on

the flue gas cleaning Pyrolysis - Non-burning process

- Production of a mixture of gaseous and liquid fuels and a solid inert residue

- Conversion of all sludge biomass fraction into useful energy

- Volume reduction by as much as 90% and production of a sterile carbon char

- Dewatering/thickening of the sludge is required.

- Less technical maturity for its application to paper/pulp sludges

Gasification - Higher efficiency of energy recovery - Reduced environmental emissions - Ability to handle most inorganic compounds

found in sludge - Production of an inert solid waste

- Dewatering and drying of sludge is needed - Not commercially developed for pulp and

paper sludge treatment - Complexity of technology

Direct Liquefaction

- Reaction occurs in aqueous phase, so that no dewatering, thickening and drying of the feedstock is required

- Production of a mixture of high calorific value liquid fuels

- Conversion of all sludge biomass fraction into useful energy

- Not commercially developed

Supercritical Water Oxidation

- Easily controlled by operator - Reaction medium is water, so no

dewatering/drying required - High organic carbon destruction efficiencies

- Corrosion and salt deposition in the equipment which accelerates the deterioration of the reactor

Anaerobic Digestion

- High energy recovery efficiency - Low operating temperature - No dewatering/drying required

- Slow process, long residence times - Cannot accept shock loading and excessive

foaming is often a problem


4. CONCLUSIONS Unlike primary sludge, secondary sludge as a byproduct of biological treatment is far

more difficult to dewater and to be disposed. Secondary sludge waste management issues are a big challenge especially with the implementation of more stringent environmental legislation. Typical post-treatment methods for secondary sludges include incineration, pyrolysis, gasification, direct liquefaction, super critical water oxidation and anaerobic digestion. The operating conditions (temperature, pressure, atmosphere and products, etc.) vary among the methods. For example, incineration, gasification and SCWO methods utilize air or oxygen while the remaining methods are conducted under oxygen depleted or anaerobic conditions. Incineration, pyrolysis and gasification operate at high temperatures, while these methods differ in the objective products. Incineration aims to produce heat and steam/electricity, pyrolysis targets a high yield of oil, and gasification favors production of gas. The greatest sludge volume reduction (over 90%) can be achieved with the high-temperature methods including incineration, pyrolysis and gasification, which is advantageous as it effectively reduces the physical amount of sludge for disposal. The major disadvantage for these high-temperature processes is their lower net energy efficiency for the treatment of secondary sludge containing very high content of water (98-99%), resulting from the need of the energy intensive operations of dewatering/thickening and complete evaporation of the water in the sludge. In contrast, the other three treatment methods, i.e., direct liquefaction, SCWO and anaerobic digestion, operate at a relatively lower temperature and more importantly without the need of dewatering /thickening and complete evaporation of the water in the sludge. Accordingly, these methods are more promising for the treatment of secondary sludge from the standpoint of energy recovery.

ACKNOWLEDGMENTS Part of this work was financially supported by the Natural Science and Engineering

Research Council of Canada (NSERC) through the Discovery Grant awarded to Dr. Charles XU.

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Chapter 6

ENERGY RECOVERY FROM WASTE: COMPARISON OF DIFFERENT TECHNOLOGY COMBINATIONS

1Lidia Lombardi and 2Andrea Corti 1Università degli Studi di Firenze, Via Santa Marta, 3, 50139 Firenze – Italy,

2Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Siena, Via Roma Siena – Italy.

ABSTRACT

Energy recovery from waste can follow several routes. The most common one is waste direct combustion associated with conventional energy recovery in a steam turbine cycle. The combustion can be applied directly to Municipal Solid Waste or can be applied to a stream of selected waste obtained by means of mechanical sorting of Municipal Solid Waste, using several technologies for the combustion, the most common of which is mobile grate combustor.

Besides the direct combustion of waste, alternative possibilities for thermal treatment are gasification and pyrolysis. These processes require being fed by a homogeneous combustible fraction obtained by mechanical sorting and supply as output one or more combustible streams, available for energy recovery.

When Municipal Solid Waste mechanical sorting is applied, besides the combustible fraction stream, a humid fraction is also obtained, characterised by a high presence of organic biodegradable fraction. At present the fate for this stream is biological aerobic stabilisation, but another option, to push energy recovery also from this stream, is biological anaerobic digestion, which can be applied through different technologies (wet and dry digestion). Through this process a biogas with elevated content of methane can be produced and supplied to engines for energy recovery.

The above-mentioned technologies can be combined in several schemes to optimise the overall energy recovery. The combination of schemes will be analysed in this chapter in reference to a study case characterised by an average waste material composition. The comparison will be carried out using some indicators of the overall energy recovery for each scheme.

Lidia Lombardi and Andrea Corti 214

INTRODUCTION The thermal treatment of solid residues was introduced as the most suitable way to reduce

the mass (up to 70–80% reduction) and the volume (up to 90% reduction) of waste and to clear up their potential for putrefaction, with the connected sanitary risks (Tchobanoglous et al.,1993).

Further, according with the growing awareness of conventional fuels availability reduction and along with the increasing costs of traditional energy sources, the solid waste thermal treatment collected attention also in reference to the possibility of associating, to the simple disposal, the energy recovery process. Nowadays, the waste thermal treatment represents an inescapable part of the integrated waste management and treatment system and the challenge for the future lays in the improvement of energy recovery, keeping a high level of plant reliability.

The term “thermal treatment” means a process which takes place at relatively high temperatures involving several different chemical reactions evolving, in the case of waste, from the compounds present in the solid mass.

Whether the oxygen is present or not it is possible to obtain different thermo-chemical processes.

The most common thermo-chemical process applicable to solid materials—and hence waste—is combustion (Tchobanoglous et al., 1993). It takes place in a large excess of oxygen with respect to the stoichiometric ratio, since the aim is the complete oxidation of organic material made of mainly carbon and hydrogen. The combustion is an exothermic process, and since its outputs are combustion gases and bottom ashes—both of which are completely oxidised materials—there is no energy content left.

When oxygen is added in sub stoichiometric ratio to solid materials, partial oxidation reactions of the organic material take place, releasing thermal energy and heating up the system. At increasing temperature, the bonds of long chain molecules of solid materials are broken to obtain smaller molecules in gaseous form. Hence, the process outputs are a gaseous stream (called the syngas), which still has an energy content, carried by partially oxidised compounds and small hydrocarbons, and solid residues which may contain unreacted compounds. Such a process is called gasification (Reed, 1981).

When the solid material undergoes a process that takes place at a relatively high temperature and in complete absence of oxygen, this is called the pyrolysis (Bridgewater et al., 1999). Such a process requires a heat supply from the external environment and its outputs are in general—with different yields depending mainly on the temperature—a gaseous stream (called the syngas), a liquid stream (called the tar) and a solid stream (called the char), with all three having combustible characteristics.

In this chapter the application of the above-mentioned thermo-chemical processes to Municipal Solid Waste (MSW), coupled with appropriate energy recovery systems, is considered from a process analysis point of view, with the aim of comparing the energy recovery potential in the different cases.

Of course, while combustion can be applied to MSW directly, gasification and pyrolysis require a more homogeneous entering material, in terms of size, calorific value and composition. In order to obtain an adequate stream from MSW to be fed to gasification and pyrolysis, a pre-treatment, based on mechanical sorting of MSW, is applied with the aim of

Energy Recovery from Waste: Comparison of different Technology … 215

removing humid and inert fractions and concentrating high energy content materials—as plastic, wood and paper—in a stream which is commonly called combustible fraction (CF) or in some cases—if some law requirements are complied with—can be addressed as Refuse Derived Fuel (RDF).

When MSW mechanical sorting is applied, besides the combustible fraction stream, also a humid fraction (HF) is obtained, characterised by a high presence of organic biodegradable fraction. At present the most common fate for this stream is biological aerobic stabilisation, but another option to push energy recovery also for this stream is biological anaerobic digestion, which can be applied through different technologies (wet and dry digestion). Through this process a biogas with elevated content of methane can be produced and supplied to engines for energy recovery. It is worth noticing that the anaerobic digestion is not an alternative to the aerobic biostabilisation, since an aerobic post-treatment for the anaerobic digestate is always required, in order to reach high levels of stabilisation and sanitary risk avoidance.

According to the considerations above, the energy recovery potentials from MSW were evaluated including not only the thermo-chemical processes but also their integration with anaerobic digestion, considering for each process the appropriate entering stream.

The analysis is reported in reference to a study case in terms of MSW flow rate and composition, as it will be illustrated in the next paragraph.

All the considered processes were analysed by means of thermodynamic and chemical simulation using specific tools, illustrated in the following.

MSW Characteristics and Pre-treatment In order to perform a comparison among the different possibilities for energy recovery

from MSW, a reference study case was assumed, characterised by the features reported in table 1 in terms of MSW material composition, mass flow rate and low heating value (LHV).

With respect to this MSW composition a simplified mechanical sorting process was considered, based on grinding, metals removal by magnetic separator and sieving (figure 1). The process outputs are mainly a combustible fraction—adequate for feeding a thermal treatment—and a humid fraction, characterised by a large presence of organic fraction—appropriate to feed a biological process. The material composition, mass flow rate and LHV of the output stream are reported in table 1.

Figure 1. Schematic of simplified mechanical sorting line.


Table 1. Material composition and mass flow rate for MSW, combustible fraction and humid fraction.

MSW Combustible fraction Humid fraction Paper and cardboard 15,53% 21,59% 2,57% Organic fraction 30,14% 19,84% 54,85% Pruning scrap 8,74% 7,03% 13,02% Plastics 8,63% 11,99% 1,43% Metals 7,07% 5,17% 7,01% Wood 4,46% 5,22% 2,95% Glass 8,44% 5,56% 15,36% Textiles 16,99% 23,61% 2,81% Mass flow rate [kg/h] 14.344 9.536 4.649 LHV [kJ/kg] 10.127 12.201 3.647

On the basis of the assumed elemental composition and moisture content for each single

material fraction (table 2), whose results are coherent with literature values (Tchobanoglous et al., 1993), the overall elemental composition and moisture content of each waste stream (MWS, combustible fraction, humid fraction), were determined and results are reported in table 3.

The elemental composition for each waste stream is required in the chemical and thermodynamic models used for the mathematical simulation of the analysed processes.

Table 2. Assumed elemental composition and moisture

content for each material fraction

Carbon Hydrogen Oxygen Nitrogen Sulphur Inert Moisture Paper and cardboard 33,30% 3,30% 30,68% 0,08% 0,23% 7,43% 25,00% Organic fraction 16,80% 2,24% 13,16% 0,91% 0,14% 1,75% 65,00% Pruning scrap 25,03% 4,79% 11,06% 0,99% 0,11% 13,04% 45,00% Plastics 66,98% 10,93% 10,74% 0,86% 0,86% 4,66% 5,00% Metals 0,44% 0,53% 3,78% 0,09% 0,00% 83,16% 12,00% Wood 39,60% 4,80% 34,16% 0,16% 0,08% 1,20% 20,00% Glass 0,49% 0,10% 0,39% 0,10% 0,00% 96,92% 2,00% Textiles 35,64% 5,85% 22,77% 5,04% 0,63% 20,07% 10,00%

Combustion with Energy Recovery The most common route followed to realise energy recovery from waste is their direct

combustion associated with conventional energy recovery in a steam cycle. This is conventionally addressed as a Waste-to-Energy (WtE) process. The WtE can be applied directly to MSW or can be applied to the combustible fraction obtained by means of mechanical sorting.


Table 3. Calculated elemental composition and moisture content of the considered waste streams

MSW Combustible fraction Humid fraction Carbon 26,10% 30,84% 16,56% Hydrogen 1,76% 2,14% 2,45% Oxygen 0,00% 0,00% 11,57% Nitrogen 1,32% 1,58% 0,81% Sulphur 0,27% 0,34% 0,13% Inert 20,74% 17,91% 24,23% Moisture 49,81% 47,91% 44,24%

MSW direct combustion could be of particular interest when a well developed separate

collection system is applied. This means that the waste fractions that can be recovered are separated up-stream of the waste collection, and the remaining non differentiated residual MSW are characterised by relatively high low heating values (since the humid fraction and inert fractions are preliminarily eliminated).

The simulation of the WtE process was carried out using an in-house developed mathematical code, using the Engineering Equation Solver software (F-Chart Software). The code requires as input the mass flow rate of waste, its elemental composition, the combustion temperature, the steam cycle maximum pressure, maximum temperature and condenser pressure, the temperature levels in the heat recovery steam generator (HRSG) and the estimation of the internal consumption in term of percentage of the produced gross power.

The code calculates the energy and mass balance in the combustion chamber and the volumetric percentage of oxygen in the combustion gases, estimates the thermal energy losses, the bottom and fly ash production, and evaluates the steam production in the HRSG, the steam turbine power output, the net power production and the net efficiency.

The main operating parameters assumed for the simulations are reported in table 4. The WtE process was simulated for both MSW and combustible fraction, considering as input the mass flow rates, previously reported in table 1, and elemental compositions, previously reported in table 3.

Figure 2 shows the simplified schematic of the considered WtE process. The recovery of the heat released in the combustion is assumed to start within the combustion chamber itself, placing evaporator pipes in the wall of the combustion and post-combustion zone. This integrated boiler in the combustion zone represents the most recent technology for WtE and it is able to improve the energy recovery in this kind of plant, with respect to the previous technology which was based on adiabatic (unless the unavoidable thermal losses) combustion. From a modelling point of view, the combustion temperature is imposed, while the amount of heat recovered in the integrated boiler is subtracted – from energy balance in the combustion chamber – to such an extent that the excess combustion air is enough to assure a minimum level of about six percent of oxygen volume in the exhausts.

The main output results from the WtE simulations, are reported in table 5, with reference to the two different feedings of MWS and combustible fraction.


Table 4. Main operating parameters assumed for the waste combustion with energy recovery

Combustion temperature [°C] 1.100 Steam maximum temperature [°C] 400 Steam maximum pressure [bar] 40 Steam cycle condenser pressure [bar] 0,25 Exhausts HRSG entering temperature [°C] 620 Exhausts HRSG exiting temperature [°C] 150 Internal consumption [%] 12

Figure 2. Simplified schematic of the considered WtE process.

Table 5. Main results form the WtE simulations.

MSW Combustible fraction Waste mass flow rate [kg/h] 14.344 9.537 LHV [kJ/kg] 10.127 12.201 Entering thermal power [kW] 40.350 32.322 Gross power output [kW] 10.109 8.356 Net Power output [kW] 8.896 7.376 Exhaust mass flow rate [kg/h] 90.582 68.750 Gross efficiency [%] 25,1 25,8 Internal consumption [%] 12 12 Net efficiency [%] 22,05 22,82 CO2 mass flow rate output [kg/h] 13.841 10.643

Gasification with Energy Recovery The simulation of the gasification process with energy recovery was carried out using the

commercial software Aspen Plus® (Aspen Technology Inc.), considering as input only the combustible fraction, in reference to the elemental composition and mass flow rate reported in table 3.

The simplified schematic of the proposed gasification process with energy recovery is shown in figure 3.


Figure 3. Simplified schematic of the proposed gasification process with energy recovery.

The waste enters the gasification reactor together with the gasification air and a stream of steam, supplied to push the hydrogen production. Once imposed the gasification temperature, the amount of required gasification air is evaluated. The gasification solid residues leave the reactor from the bottom, while the syngas exits from the top. Syngas is cooled down to an assumed temperature – recovering the heat to produce superheated steam - before entering a wet scrubbing for the removal of undesirable compounds. Actually the removal process is simulated only from a thermodynamic point of view, considering the syngas further cooling and its moisture content saturation, at the temperature assumed at the exit. Then the syngas is fed to a boiler together with combustion air, which is evaluated on the basis of the assumed combustion temperature. The energy released in the combustion is in large part recovered in the boiler to produce superheated steam. This steam, together with the amount of steam produced in the first syngas cooler, expands in a steam turbine, down to the condenser pressure, producing power output. The exhausts exiting from the boiler are further cooled down in order to produce the amount of process steam required by the gasification reactor.

Table 6. Main operating parameters assumed for the waste gasification with energy recovery.

Gasification temperature [°C] 875 Gasification pressure [bar] 1 Steam supplied to process gasification [kgH2O/kgC] 0,11 Unreacted carbon [%] 4,60 Syngas temperature at the exit of first cooler [°C] 150 Syngas temperature at the exit of scrubbing [°C] 80 Syngas combustion temperature [°C] 850 Steam maximum temperature [°C] 400 Steam maximum pressure [bar] 40 Steam cycle condenser pressure [bar] 0,25 Temperature of exhausts after last cooling [°C] 150

The main operating parameters assumed for the simulations are reported in table 6. Table 7

shows the simulation main results and the details of calculated syngas characteristics. Table 8 reports the gasification and energy recovery cycle synthetic results. The overall process efficiency is calculated as the ratio between the power output an the energy entering with the waste.


Table 7. Main simulation results and details of calculated syngas characteristics

Cycle main results Syngas characteristics at gasification reactor exit Gasification air mass flow rate [kg/h] 23.112 Temperature [°C] 875 Evaporated water in the scrubbing process [kg/h]

1.080 Mass flow rate [kg/h] 31.197

Syngas mass flow rate after scrubbing process [kg/h]

32.277 LHV [kJ/kg] 2.210

Combustion air mass flow rate [kg/h] 34.700 Compounds Mass fraction Exhausts mass flow rate [kg/h] 66.977 N2 0,59 Steam produced in the first syngas cooler [kg/h]

9.870 CO 0,096

Steam produced in the boiler [kg/h] 18.072 CO2 0,176 Exhausts boiler exiting temperature [°C]

200 H2O 0,124

Turbine power output [kW] 5.345 H2 0,01 Pump consumptions [kW] 72 Other trace compounds 0,004

Table 8. Gasification and energy recovery cycle synthetic results

Combustible fraction Waste mass flow rate [kg/h] 9.537 LHV [kJ/kg] 12.201 Entering thermal power [kW] 32.322 Net Power output [kW] 5.273 Net efficiency [%] 16,31 CO2 mass flow rate output [kg/h] 10.280

Pyrolysis with Energy Recovery The simulation of the pyrolysis process with energy recovery was carried out using the

commercial software Aspen Plus ® (Aspen Technology Inc.), considering as input only the combustible fraction, in reference to the elemental composition and mass flow rate reported in table 3.

The simplified schematic of the proposed pyrolysis process with energy recovery is shown in figure 4.

The waste enters the pyrolysis reactor were the temperature is kept at the assumed value. A syngas is produced and the solid products/residues are discharged from the bottom. In this study the attention was focussed on syngas production, rather than on liquid and solid outputs, since the assumed operating temperature is relatively high. Part of the syngas is burnt to supply the heat required by the pyrolysis reactor. The remaining syngas is burnt with air combustion in a reciprocating engine to produce electric energy. This layout solution was proposed on the basis of the very good LHV obtained for the pyrolysis syngas, which can be accepted by the reciprocating engine. The possibility of using relatively high efficiency


equipment for energy conversion of this syngas open the potential to high energy recovery, with respect to steam cycles proposed previously for the WtE and gasification cases.

Figure 4 – Simplified schematic of the proposed pyrolysis process with energy recovery.

The main operating parameters assumed for the simulations are reported in table 9. Table 10 shows the simulation main results and the details of calculated syngas characteristics. The overall process efficiency is calculated as the ratio between the power output an the energy entering with the waste.

Table 9. Main operating parameters assumed for the waste

pyrolysis with energy recovery.

Pyrolysis temperature [°C] 750 Pyrolysis pressure [bar] 1 Unreacted carbon [%] 4,60 Reciprocating engine efficiency [%] 35

Table 10. Main simulation results and details of calculated syngas characteristics.

Cycle main results Syngas characteristics at pyrolysis reactor exit Heat required by the pyrolysis reactor [MW] 14,5 Temperature [°C] 750

Syngas mass flow rate for heating the reactor [kg/h] 2.640 Mass flow rate [kg/h] 7.533

Syngas mass flow rate to engine [kg/h] 4.893 LHV [kJ/kg] 19.850 Syngas mass flow rate for heating the reactor [%] 35 Compounds Mass fraction

Syngas mass flow rate to engine [%] 65 N2 0,018 Reciprocating engine power output [kW] 9.447 CO 0,778

CO2 0,028 H2O 0,009 H2 0,057 CH4 0,1 NO3

- 0,007

Other trace compounds 0,003


Table 11. Pyrolysis and energy recovery cycle synthetic results

Combustible fraction Waste mass flow rate [kg/h] 9.537 LHV [kJ/kg] 12.201 Entering thermal power [kW] 32.322 Net Power output [kW] 9.447 Net efficiency [%] 29,22 CO2 mass flow rate output [kg/h] 10.280

Anaerobic Digestion Anaerobic digestion is a sequence of biological processes in which different types of

bacteria break down biodegradable material in the absence of oxygen (Mata-Alvarez , 2002). Thus the humid fraction mechanically sorted from MSW (table 1), which contains a large amount of biodegradable fraction, is a good candidate to be processed in such a way. The main product of anaerobic digestion is a biogas with good LHV, that can be supplied to a reciprocating engine to produce electricity, as illustrated in Figure 5.

Figure 5. Simplified schematic of the anaerobic digestion process with energy recovery.

The anaerobic biological process could be simulated in a complete way reproducing the microbial reaction kinetics by mathematical models (Mata-Alvarez , 2002), but this can be particularly onerous especially if we are dealing with solid waste. For this reason a simplified approach was followed in this application, which is based on some simplified assumptions, aimed to evaluate biogas production from anaerobic degradation of humid fraction. Starting from the material composition of the humid fraction and the moisture content assumed in table 2, the amount of Total Solids (TS) was evaluated. From TS, assuming the inert content of table 2, recalculated on dry basis (table 12), the Volatile Solids (VS) content was estimated. Then, assuming a biodegradability coefficient (BC), coherent with literature data (Tchobanoglous et al.,1993), for each material fraction, and a VS removal efficiency (RE), that can be obtained in the anaerobic digestion (Mata-Alvarez , 2002), the amount of the biodegraded material was evaluated. This amount of biodegraded material was characterised – for each material fraction – in term of brutal chemical formula of the type CaHbOcSdNe, on the basis of elemental composition (table 2). Then the general anaerobic stoichiometric reaction (1) was considered:


CaHbOcSdNe + rH2O mCH4 + sCO2 + dH2S + eNH3 (1)

in order to evaluate the amount of the reaction products which build up the biogas and, hence, the biogas production.

Table 12 summarises the calculation procedure steps and table 13 reports the calculation results.

Table 12. Summary of calculation procedure for biogas production estimation.

Humid fraction TS Inert VS BC RE VSREMOVED

Wet % [kg/h] % [kg/h] % TS % TS [kg/h] % VS % [kg/h]

Brutal chemical formula

Paper and cardboard 2,57 120 75,00 90 9,90 99,90 81 50,00 60,00 24 CHO Organic fraction 54,85 2550 35,00 893 5,00 99,95 848 82,00 60,00 417 C18H28O10 Pruning scrap 13,02 605 55,00 333 23,70 99,76 254 60,00 60,00 91 C5H10O2 Plastics 1,43 66 95,00 63 4,90 99,95 60 - 60,00 - - Metals 7,01 326 88,00 287 94,50 99,06 16 - 60,00 - - Wood 2,95 137 80,00 110 1,50 99,99 108 72,00 60,00 47 C2H3O Glass 15,36 714 98,00 700 98,90 99,01 8 - 60,00 - - Textiles 2,81 131 90,00 118 22,30 99,78 91 54,00 60,00 30 CH2O

Table 13. Results of the biogas production modelling.

CH4 CO2 H2S NH3 Produced [kg/h] 210,82 438,34 5,05 7,24 Produced [kmol/h] 13,14 9,96 0,15 0,43 Produced [Nm3/h] 294,34 223,11 3,36 9,63 Volume composition [%] 55,49 42,06 0,63 1,82

The overall biogas production resulted to be about 530 Nm3/h, which correspond to about

0,11 Nm3 of biogas per kg of humid fraction or 0,36 Nm3 per kg of VS, which resulted coherent with literature data (Mata-Alvarez , 2002). Being the biogas LHV of about 19.420 kJ/Nm3 (on the basis of the CH4 volumetric fraction) and assuming an electric conversion efficiency of 0,35 for the reciprocating engine, the power output was calculated and reported in table 14, with the overall efficiency of the process (the ratio between the net power output and the entering power with the humid fraction).

Table 14. Anaerobic digestion with energy recovery cycle synthetic results

Humid fraction Waste mass flow rate [kg/h] 4.650 Waste LHV [kJ/kg] 3.647 Entering thermal power [kW] 4.711 Net Power output [kW] 1.002 Net efficiency [%] 21,27 CO2 mass flow rate output [kg/h] 438


Comparison of Thermal Processes The resulted obtained above are compared in this section in term of several performance

indicators for the different thermo-chemical treatments with energy recovery applied to the considered waste. The compared systems are:

- MSW WtE (MSW-WtE) - combustible fraction WtE (CF-WtE) - combustible fraction gasification with energy recovery (CF-GAS) - combustible fraction pyrolysis with energy recovery (CF-PYR).

Table 15 reports the comparison, assuming a continuous operation of processes for 325

days per year. The calculated performance indicators consist of energy conversion efficiency; energy source savings, expressed in Ton of Oil Equivalent (TOE) per year; specific energy production per unit mass of processed waste; gross CO2 emission/production – overall amount and specific values – due to the waste/syngas combustion; avoided CO2 emissions, due to the avoided use of conventional energy replaced by the amount produced in the energy recovery process, considering a specific emission for conventional processes of about 0,496 kgCO2/kWh (ENEL, 2006); net CO2 emission/production as the difference between the gross and the avoided CO2 emission/production.

Table 15. Comparison of studied processes according to some energy

and environmental performance indicators.

MSW-WtE CF-WtE CF-GAS CF-PYR Waste mass flow rate [kg waste/h] 14.344 9.537 9.537 9.537 LHV [kJ/kg waste] 10.127 12.201 12.201 12.201 Entering power [kW] 40.350 32.322 32.322 32.322 Net power output [kW] 8.896 7.376 5.273 9.447 Efficiency [%] 22 23 16 29 Energy source saving [TOE/year] 16.075 13.311 9.528 17.071 Specific energy production [kWh/kg waste] 0,62 0,77 0,55 0,99 Gross CO2 emission [tCO2/year] 107.960 83.016 80.184 80.184 Avoided CO2 emission [tCO2/year] -34.417 -28.501 -20.400 -36.551 Net CO2 emission [tCO2/year] 73.543 54.515 59.784 43.633 Gross specific CO2 emission [kg CO2/kWh] 1,56 1,44 1,95 1,09

Net specific CO2 emission [kg CO2/kWh] 1,06 0,95 1,45 0,59 Gross specific CO2 production [tCO2/t waste] 0,96 1,12 1,08 1,08

Net specific CO2 production [tCO2/t waste] 0,66 0,73 0,80 0,59 With respect to the results in table 15, in order to have a complete view of the energy

recovery potential, the additional energy consumptions, due to the pre-treatment of the MSW to obtain the combustible fraction, are to be considered in the processes which accept the combustible fraction as input. In order to consider this contribute, an average value in the


range from 29 kWh/tMSW (Lombardi et al., 2007) and 48 kWh/tMSW (Lombardi et al., 2006) – dependant on the type pre-treatment – of about 38,5 kWh/tMSW was assumed. Consequently the performance indicators related to energy are modified as reported in table 16.

Table 16. Energy performance indicators, considering the pre-treatment consumptions.

MSW-WtE CF-WtE CF-GAS CF-PYR

Waste mass flow rate [kg waste/h] 14.344 9.537 9.537 9.537

LHV [kJ/kg waste] 10.127 12.201 12.201 12.201

Entering power [kW] 40.350 32.322 32.322 32.322

Net power output [kW] 8.896 7.367 5.273 9.447 Specific pre-treatment consumptions [kWh/tMSW] - 38,5 38,5 38,5

Pre-treatment consumption [kW] - 552 552 552 Net power output considering pre-treatment consumption [kW] 8.896 6.815 4.721 8.895

Efficiency [%] 22 21 15 28

Results in table 15 and 16 show that the efficiency of WtE applied to MSW or combustible fraction is quite similar, but the amount of recovered energy is higher in MWS WtE. Gasification of combustible fraction with energy recovery of syngas in steam cycle offers a lower efficiency and lower amount of recovered energy with respect to WtE in general. On the contrary, from a theoretical point of view, the combustible fraction pyrolysis, with syngas energy recovery in engine, leads to a higher efficiency with respect to the other considered systems.

Comparison of Integrated Energy Recovery Systems The possibility of combining the thermo-chemical treatments for the combustible fraction

and the biological treatment for the humid fraction gave the possibility of composing four integrated scenarios for the processing of MSW, as shown in figure 6. Scenario I is the direct MSW combustion in WtE. In scenario II, MSW is mechanically sorted: the combustible fraction (CF) is sent to WtE, while the humid fraction (HF) is sent to anaerobic digestion with biogas energy recovery in engine. In scenario III, MSW is mechanically sorted: the combustible fraction (CF) is sent to gasification with syngas energy recovery in a steam cycle, while the humid fraction (HF) is sent to anaerobic digestion with biogas energy recovery in engine. In scenario IV, MSW is mechanically sorted: the combustible fraction (CF) is sent to pyrolysis with syngas energy recovery in engine, while the humid fraction (HF) is sent to anaerobic digestion with biogas energy recovery in engine. Results for the compared scenarios are reported in table 17.


Figure 6. Schematic of the compared integrated waste treatment scenarios.

Table 17 shows that the energy and environmental performances for scenario I and scenario II are quite similar, even if the CO2 emissions are higher in the case of MSW WtE, since a more complete use of the carbon content is performed with respect to the combination of combustion with anaerobic digestion. Again the scenario based on gasification reports lower performances, while the one based on pyrolysis has the best energy and environmental results.

CONCLUSION

From a technological point of view, the market of energy recovery from waste offers

today a wide number of proven technical systems only in reference to processes based on waste direct combustion, i.e. WtE. WtE is the most widespread thermal treatment for waste at the international level. It is a mature technology which has reached a high reliability.

Gasification and pyrolysis processes are far less common and especially applied to particular typologies of wastes, with relatively small plant sizes. They present a significant complication both at plant level and at operating level. Up to now, their reliability, in reference to the continuous operation, is lower with respect to WtE.

From the results reported in this chapter, the gasification process coupled with syngas energy recovery in a steam cycle does not offer a potential in the direction of the efficiency improvement in energy recovery from waste, with respect to the traditional WtE.


Table 17. Comparison of proposed scenarios according to some energy and environmental performance indicators.

Scenario 1 Scenario II Scenario III Scenario IV

MSW WtE CF WtE + HF AD

CF GAS + HF AD

CF PYR + HF AD

Waste mass flow rate [kg waste/h] 14.344 14.344 14.344 14.344

LHV [kJ/kg waste] 10.127 10.127 10.127 10.127 Entering power [kW] 40.350 40.350 40.350 40.350 Net power output [kW] 8.896 8.369 6.275 10.450 Efficiency [%] 22 21 16 26 Energy source saving [TOE/year] 16.075 15.122 11.338 18.882

Specific energy production [kWh/kg waste]

0,62 0,62 0,72 0,53

Gross CO2 emission [tCO2/year] 107.960 84.815 85.852 85.852

Avoided CO2 emission [tCO2/year] -34.417 -32.377 -24.276 -40.400

Net CO2 emission [tCO2/year] 73.543 52.437 61.576 45.425

Gross specific CO2 emission [kg CO2/kWh]

1,56 1,3037 1,75 1,05

Net specific CO2 emission [kg CO2/kWh]

1,06 0,80 1,26 0,56

Gross specific CO2 production [tCO2/t waste]

0,96 0,77 0,78 0,78

Net specific CO2 production [tCO2/t waste]

0,66 0,47 0,56 0,41

On the contrary the pyrolysis process, coupled with syngas energy recovery in a

reciprocating engine, can reach quite high performances in terms of efficiency and energy recovery. However, today the pyrolysis technology is not yet competitive in reference to commercial industrial scale installations for waste treatment, since its application to the biomass sector (small sizes) in still in development.

The possibility of coupling the thermal treatment, for the combustible fraction, with the anaerobic digestion, for the humid fraction, allows keeping efficiency and energy recovery levels similar to the MSW WtE case, with two additional benefits. The first one is related to the lower CO2 production, due to lower carbon transformation in the biological process. The second one is related to the possibility of obtaining incentive pay for the energy produced from anaerobic digestion, since this is acknowledged as a renewable source, while energy from WtE is not, at least in some countries (as in Italy for example).


REFERENCES

Aspen Technology Inc., Aspen Plus ®, www.aspentech.com Bridgewater, A. V., Meier, D. & Radlein, D. (1999). “An overview of fast pyrolysis of

biomass”, Organic Geochemistry, 30, pp. 1479–1493. ENEL, Rapporto Ambientale 2006, www.enel.it Engineering Equation Solver, F-Chart Software, [email protected] Lombardi, L., Corti, A. & Sirini, P. “Analisi di ciclo di vita per la valutazione di scenari di

trattamento di rifiuti urbani”, VIII SIBESA Simposio Italo-Brasiliano di Ingegneria Sanitaria Ambientale, 17-22 Settembre 2006, Fortaleza Brasil. ISBN: 85-7022-148-7

Lombardi, L., Corti, A., Meoni, R. & Iossifidis E. “Comparing different Municipal Solid Waste management scenarios by means of Life Cycle Assessment”. ISWA/NRVD World Congress 2007, Amsterdam, The Netherlands, 24-27 September, 2007.

Mata-Alvarez, J. (2002). Biomethanization of the organic fraction of municipal solid wastes. IWA Publishing.

Reed, T. B. Biomass Gasification: Principles and Technology, Energy Technology Review, No. 67, Noyes Data Corporation, Park Ridge, N.J., 1981. ISBN 0-8155-0852-2.

Tchobanoglous, G., Theisen, H. & Vigil, S. (1993). Integrated solid waste management – Engineering principles and management istsues. McGraw-Hill, Inc.


Chapter 7

ENERGY RECOVERY FROM WASTE INCINERATION: LINKING THE SYSTEMS OF ENERGY AND WASTE MANAGEMENT

Kristina Holmgren∗ Linköping Institute of Technology, Linköping, Sweden

ABSTRACT

Energy recovery from waste incineration has a double function as a waste treatment method and a supplier of electricity and/or heat. Waste incineration thereby links the systems of waste management and energy. This chapter addresses the importance of taking this into consideration when e.g. making investment decisions or designing policy instruments. The design of two policy instruments will be described as examples of the conflicting goals in the two systems. A conflict is also that increased waste incineration can decrease production of combined heat and power in the district heating systems. Since policy instruments in Sweden are dependent on the common legislation of the European Union this will be addressed, together with trading in waste and electricity and how this impacts waste incineration in Sweden. Conflicts between the internal market in the European Union and waste management goals are shown. When making investment decisions, various models are often used as decision support tools. Some models for assessing waste incineration/management are therefore described together with strengths and weaknesses when dealing with the dual function of waste incineration.

INTRODUCTION Energy recovery through waste incineration1 connects two vital systems in modern

society: the waste management system and the energy system. In Sweden, with an extensive

∗ Corresponding author: Tel.: +46 13 286687; fax: +46 13 281788. E-mail address: [email protected] 1 Digestion also has this function, since it is a treatment method for easily biodegradable waste, where the residual

products are a fertilizer and a gas which can be used for electricity and heat production or for transportation after cleaning, but this chapter will address only waste incineration.

Kristina Holmgren 230

district heating (DH) system that supplies just over 40% of the total heating demand of buildings and premises, heat supply from waste incineration has a substantial share of the total DH supply of about 12% (Swedish Energy Agency, 2004). Furthermore, both these systems are the focus of attention due to environmental concerns, and for this reason, changes are being made in both systems. The European Union has common legislation which impacts both systems in the member countries. Apart from the legislation, the countries of the European Union are connected through trade; important in this case are the common electricity market and trading in waste.

The aim of this chapter is to highlight two issues. The first is the dual purpose of waste incineration as a waste treatment method and as a supplier of electricity and/or heat. This chapter will emphasise the importance of taking this into consideration with regard to, e.g. decision making and when designing policy instruments. Two policy instruments that impact both technical systems will be described and the difficulties in handling the double function of waste incineration will be the central issue. These policy instruments are a recently proposed tax on incinerated waste in Sweden and green electricity certificates. Various models are often used as decision support tools in decision making processes, e.g. when municipalities make investment decisions. When designing and using these models, the dilemma of the two functions needs to be faced and the ways in which some models handle this will be described.

Policy instruments in Sweden are highly dependant on legislation in the European Union, the policy instruments that will be described in this chapter are no exception. Therefore, the second issue in focus in this chapter is the connection via common legislation between countries in the EU. The consequences of this will be discussed, with a special emphasis on its impact on waste incineration in Sweden. Furthermore, the countries in the EU are connected via trade, and of special importance for waste incineration in Sweden is naturally the trade in waste, but also in electricity.

The methodology applied to address these issues consists of a literature review and knowledge gained in earlier studies.

DEVELOPMENT OF WASTE INCINERATION IN SWEDEN This section will include a description of the historical development of waste incineration

in Sweden. This information has been collected from a report from the Swedish Association of Waste Management (2005a) and from Hrelja (2006). The current situation with regard to waste incineration in Sweden will also be described, together with its impact on district heating, combined heat and power production and also the material recovery market.

Historical Development Burning waste has been carried on for a long time; it has been done in the open at

landfills or in simple furnaces in order to reduce waste volumes and decrease problems with vermin. This brought inconveniences, such as hazardous emissions to the atmosphere, and in 1903 Sweden’s first waste incineration plant began operations in Stockholm. However, it was

Energy Recovery from Waste Incineration: Linking the Systems … 231

not until the 1960s that waste incineration really began to show some development. The prerequisites for this were the district heating networks that began to appear after the Second World War, when municipalities’ interest in district heating was aroused. In 1948, Sweden’s first district heating network was operational in the city of Karlstad and other cities soon followed. This expansion created opportunities for waste incineration plants, since it provided an outlet for the heat produced, giving the waste a value. In the 1970s, waste began to be seen as a resource rather than a problem; in 1975 a proposition from the government stated that recovery had to increase in the future. The proposition did not state which technology was to be preferred, but incineration was regarded as preferable in bigger cities. As a result of the new view of waste as a resource, a number of plants with central sorting and composting were built. This venture failed since the plants did not work satisfactorily and there was no outlet for the residual product. This served to increase interest in waste incineration. Waste incineration expanded significantly, especially during the 1970s, over the years up until 1985. The number of plants increased from 2 in 1960 to 27 in 1985, and treatment capacity from 100,000 tons annually to 1,800,000 tons. The oil crises of the 1970s led to a growth in interest in waste incineration as an indigenous fuel, in order to decrease oil dependency.2 During the 1980s, researchers began to report widespread diffusion of heavy metals and dioxins in the environment and the effects on humans and animals. Waste incineration was found to be an important cause of this diffusion of hazardous substances in the environment.3 In 1985, a ban on investment in waste incineration was issued by the Swedish Environmental Agency, until the issues of emissions and technology had been solved. The Environmental Agency and the Energy Agency were commissioned to analyse the risks associated with waste incineration and concluded that it was possible to reduce the emissions to acceptable levels through a number of measures, including “cleaner” waste (i.e. more sorting of waste), more efficient combustion, advanced flue gas cleaning equipment, and the safe disposal of residual products. Limits were set for emissions. On the basis of these results, the ban on investment was lifted. Of the existing plants, 20 went through with modernisations while 7 were shut down. However, the debate on dioxins in the municipalities did not end there. Hrelja (2006) shows that in the 1980s the municipality of Skövde chose not to build a waste incineration plant due to lack of confidence in the treatment method. Later, however, Skövde went ahead and built the plant, which was inaugurated in 2005.

Waste Incineration in Sweden Today Today, there are 29 waste incineration facilities in Sweden, both hot water boilers (14)

and combined heat and power plants (15) producing about 8.6 TWh heat and 0.74 TWh electricity (Swedish Association of Waste Management, 2005b). These facilities treat about 1.95 million tons of municipal waste and 1.2 million tons of other waste, mainly from the manufacturing industry. Cleaner fractions of waste can also be incinerated at other facilities and is not included in the figures presented here. Figure 1 shows the waste treatment methods

2 This was only one of a number of measures to decrease oil dependency. 3 There are a number of sources, of which waste incineration is one. Industrial processes can also give raise to

dioxins as can power plants using other fuels. Spontaneous fires at landfills are also a source of dioxins, where the contribution of emissions is hard to estimate.


for municipal waste in Sweden. As can be seen, energy recovery is the treatment method for almost half of the municipal waste today. This development is mainly a result of recent regulations in the waste management system aimed at decreasing landfill; the introduction of a tax on landfill in 2000, at present 46.3 €4/ton (Ministry of Finance, 2005a) and a ban on landfill of combustible waste from 2002 and from 2005 also of organic waste (Ministry of the Environment, 2001).

33%

10%47%

9% 1% MaterialrecoveryBiologicaltreatmentEnergyrecoveryLandfill

Hazardouswaste

Figure 1. Treatment methods of municipal waste in 2004, total amount 4.2 million tons (Swedish Association of Waste Management, 2005b).

Capacity for waste incineration is currently increasing and is forecast to increase from 2.8

Mton in 2002 to 4.9 Mton in 2008, if all planned projects are carried out (Swedish Association of Waste Management, 2004), resulting in a total of 40 waste incineration plants. Despite these investments there will still be a lack of treatment capacity. The fact is that quantities of waste are also increasing, between 1985 and the present by some 2-3% per year. If this trend is not broken, additional waste treatment capacity will also be needed after 2008.

Waste incineration and district heating

The role of waste as a fuel makes it part of the energy system. Therefore, the use of waste

as a fuel is dependent on such factors as the prices of other fuels used, legislation, and policy instruments in the energy system. The value of using the waste is higher when the prices of e.g. fossil fuels or biofuel increase. Energy taxation in Sweden has had a significant effect on what fuels are used in the DH systems, since heat from fossil fuels has been heavily taxed.5 There has been a major shift from an almost total dependency on oil up until 1980 to a diversified supply where renewables represent a substantial proportion. This can be seen in Figure 2. A historical survey of the development of the DH sector can be found in Sjödin (2002).

4 An exchange rate is 1 € = 9.40 SEK is used throughout this chapter (January 2006). 5 The carbon dioxide tax is at present 0.1 €/ton. More details of the energy taxation can be found e.g. in (Holmgren,

2006).


0

10

20

30

40

50

60

1970

1973

1976

1979

1982

1985

1988

1991

1994

1997

2000

2003

Waste heatHeat pumpsElectric boilersBiofuel & peatRefuseCoalNatural gasOil

Figure 2. Development of heat supply to the district heating networks between 1970 and 2003 (Swedish Energy Agency, 2004).

Palm (2004) shows that also institutional factors can connect the waste management

system and the DH system. In the city of Linköping, one reason for the introduction of waste incineration was that the same municipal utility operated both the waste management system and the DH system and saw that with waste incineration they could solve two problems at the same time: both an acceptable waste treatment method and heat production for the DH system. A study by Sahlin et al (2004), which is an overview of the consequences of using waste as fuel in Swedish DH systems, also shows that waste incineration enables DH networks to expand due to the low cost of the heat.

Waste incineration and combined heat and power production

One disadvantage of waste incineration is the low electrical efficiency in the plants.6 This

is due to the many impurities in the fuel; the temperature of the steam in the boiler can not exceed 400ºC without entailing high maintenance costs due to corrosion, as stated e.g. by Korobitsyn et al (1999). Combined heat and power (CHP) production is an efficient way to use resources and is recognized by the European Union as one of the measures needed to meet the demands in the Kyoto protocol (European Union, 2004a). Many utilities have chosen not to invest in electricity production in their waste incineration plants due to difficulties in producing electricity in combination with historically low electricity prices in Sweden.7 However, electricity production at waste incineration plants is forecast to increase, from 0.7 to 1.7 TWh between 2002 and 2010. (Swedish District Heating Association, 2005).

6 The electrical efficiency of waste incineration plants is around 23% at capacity 30 MWe (Elforsk, 2003). By way

of comparison, a natural gas fired CHP plant has an electrical efficiency of 46-49.5% at capacity 150 MWe and biomass fuelled power plants 34% at capacity 80 MWe (Elforsk, 2003).

7 A more detailed explanation of this can be found e.g. in Trygg and Karlsson (2005).


Existing waste-fired CHP plants will increase their electricity production and the total number of waste-fired CHP plants will double over the same period. The reason for the increase in electricity production at waste fired CHP plants is not clarified, but it is reasonable to believe that it is a result of the higher electricity prices anticipated when Swedish electricity prices are harmonized with those in continental Europe; this is further explained in the section on Impact on Waste Incineration of Trade in Electricity. The proposed tax on incinerated waste, which is designed to promote CHP production, is probably also a factor. In the municipalities that have a waste incineration plant, the plant is the base supplier of heat to the DH network, due to the negative operational cost of receiving the waste. This can remove the heat sink for more efficient plants and shorten their annual operational times. How to use the heat sink can in this perspective be seen as a conflict between waste management and the energy system. If waste incineration is chosen as the treatment method, it is vital to recover as much as possible of the energy content of the waste. This heat can occupy much of the heat sink leading to lower electricity production in the DH system, compared to if a plant with higher electrical efficiency were chosen instead of a waste incineration plant. Earlier studies have shown that this can be the case, e.g. for a municipal system (Holmgren and Bartlett, 2004) and an overall study of the DH systems in Sweden (Sahlin et al, 2004). This can of course vary between systems as shown by Holmgren (2006). This study deals with the ”competition” in the DH system in the city of Göteborg, where there is heat from waste incineration, waste heat from industries, and also investment in a natural gas fired CHP plant. There is room in the system for all types of waste heat; the new CHP plant mostly replaces heat boilers in the system.

Waste and Connection to the Material Market Waste management is connected to the material markets through the material recovery

systems. However, the development of the material recovery system is highly dependent on political decision, such as the introduction of the concept of Producer Responsibility. The incentive to material recovery of municipal waste comes mainly from the Ordinance on Producer Responsibility, which includes packaging, cars, car tyres, newspapers, and electric and electronic devices (e.g. Ministry of the Environment, 1994; 1997). For the included fractions, levels of material recycling are stated. Packaging producers have set up companies to handle the collection of packaging. The companies have a deficit in financing this system, which the producers pay. This is different to newspapers, for example, which do not show this deficit in collection; a functioning market existed even before the legislation was introduced. Also, in industry, different metal fractions such as copper and steel have had a functioning market for recycling for a long time – half of the raw material used to produce steel comes from collected scrap.8 The prices of materials naturally influence the attractiveness of material recovery.

8 Personal communication with Åsa Ekdahl, European Confederation of Iron and Steel Industries, 2003.


CONNECTION BETWEEN COUNTRIES IN THE EUROPEAN UNION VIA LEGISLATION AND TRADE AND THE IMPACT

ON THE SWEDISH WASTE INCINCERATION This section will describe the connections between EU countries in terms of common

legislation and trade in waste and electricity. Differences and similarities in waste management and district heating will also be outlined.

European Legislation Affecting Energy and Waste The common legislation in the European Union connects the countries to each other. This

section will describe policies and directives that influence waste incineration. The European Union’s member states are obliged to implement the directives in their national legislation.

The core of the European Union is the internal market which means free mobility of goods, services, people, and capital. This can be in conflict with waste management goals; examples are the principles of proximity and self-sufficiency, meaning that waste should be treated in the proximity of its origin and that member states should be self-reliant as regards treatment capacity. This is stated in the Framework Directive (European Union, 1975) which also defines waste as “any substance or object which the holder disposes of or is required to dispose of” and establishes the fundamental concept of the Polluter Pays Principle. One problem with the Framework Directive is that it does not clearly state when waste ceases to be waste and becomes a secondary material. In the Shipment of Waste Ordinance (European Council, 1993), waste is divided into two categories - for disposal and for recovery - where trading in the former is forbidden, in order to satisfy both the internal market and the proximity and self-sufficiency goals. Environmental concerns may be in conflict with free trade, both in terms of differing cost for waste treatment options due to varying standards and subsidies to the material recovery market. It is important to harmonise standards for waste treatment options in order not to “draw” waste to less controlled plants. The Directive on landfill (European Union, 1999) and the Directive on the incineration of waste (European Union, 2000) have this purpose. The Directive on the incineration of waste sets permitted maximum levels for emissions to the atmosphere and directions for monitoring the emissions. Emissions to water are also regulated, there are directions as to how the combustion process should be controlled, and how to take care of the residual products. It concerns both waste incineration plants and plants that burn both waste and other fuels, and has meant investment costs for the plants in Sweden in order to fulfil these demands. Whereas the directive is specific about emission levels, it is vague on how to classify efficient energy recovery of waste, which is a shortcoming. It says “the heat generated during the incineration and co-incineration process is recovered as far as practicable e.g. through combined heat and power, the generating of process steam or district heating”. The performance of waste incineration plants differs widely, as can be seen from Figure 3, and is detailed further in the section on European differences in waste management and use of district heating. A definition of what an efficient energy recovery of waste is should be introduced. This weak point has been observed by the European Commission, which suggests that the energy efficiency of the plant should decide whether to classify it as a disposal plant or a recovery plant. The use of


resources in other plants that the waste incineration plant could replace should also be taken into consideration (European Commission, 2005). The Landfill Directive specifies operational and technical requirements for landfills. It sets the demands that the pricing for receiving waste should include after-care for at least 30 years. It also dictates lower quantities of biodegradable waste in landfill and the collection of methane emissions. Apart from this, there is a directive on producer responsibility for packaging waste (European Union, 2004b), stipulating levels of material and/or energy recovery for different packaging materials.

The EU’s waste policy is founded on the waste hierarchy, described in the Sixth Environmental Action Programme from the European Commission (2001) and states that first comes waste prevention, then recovery (reuse, material and energy recovery where material recovery, including biological treatment9 is preferred to energy recovery) and finally disposal, where landfill and waste incineration without energy recovery are included. Swedish waste policy is based upon this hierarchy. This does not go undisputed, however; in particular the question of whether energy recovery or material recovery, including biological treatment, is to be preferred, raises issues.

Directives that impact the energy sector include the directive on the common electricity markets (European Union, 2003a), which states that Europe should have free trade in electricity in member states. This will mean higher electricity prices than historically in Sweden, since Sweden will be harmonized with continental Europe which currently has a higher electricity price (e.g. Trygg and Karlsson, 2005). This will further be described in the section on Impact on Waste Incineration of Trade in Electricity. There is a directive promoting CHP (European Union, 2004a), stating that CHP is an effective way to use resources and one measure to meet the demands in the Kyoto protocol. This has probably had an impact on the design of the proposed tax on incinerated waste, which will be explained in the section on Introduction of a tax on incinerated waste in Sweden. Recently, the European Union managed to agree on minimum energy tax levels (European Union, 2003b). There is a directive promoting electricity produced from renewable energy sources (European Union, 2001). Also this is seen as a measure to meet the demands in the Kyoto protocol and strengthening the domestic supply of energy. This has in Sweden led to the implementation of a system of green electricity certificates, which will be explained in the section on Green electricity certificates and waste incineration. Another directive regulates the emission allowance trading (European Union, 2003c). Waste incineration plants are not included in the trading sector, but are affected by the fact that the costs for fossil fuels increase as do electricity prices due to marginal pricing, where the marginal power producer is coal condensing power in the European system, further explained by Trygg and Karlsson (2005).

European Differences in Waste Management and Use of District Heating This section presents some figures with regard to the amount of district heating in

different European countries and waste management methods. Figures for electricity and heat output from waste incineration in different European countries are given. The aim is to

9 Biological treatment includes digestion and composting. When digested, biodegradable waste is degraded without

access to oxygen, resulting in biogas which can be used as fuel for vehicles or for electricity and heat production, and a residual product which can be used as fertilizer. When composted, biodegradable waste is degraded with access to oxygen, and the residual product can be used as a soil amender.


investigate if any unambiguous trends can be seen in this material; is there a correlation between high DH production and/or high market share and high proportion of energy recovery as a waste treatment method? In Sweden this is the case, but what about other European countries?

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Figure 3. Fuels used for DH in the countries surveyed in a report by Euroheat and Power (2003).

Figure 3 shows the amount of fuel used for DH production by some European countries.

It can be seen that the supply differs between countries. Coal is the major fuel used in the Central and Eastern European (CEE) countries and natural gas is also widely used; and the two fuels account for about 85% of the total supply. The CEE countries show a less diversified supply than the old EU member states and a large untapped potential exists for using more heat from waste incineration, renewables, and industrial surplus heat. As regards the proportion of DH produced in CHP plants, this is high in the old member States (64-94%) with the exception of Sweden.10 In the CEE countries, the proportion is lower (35-72%).

Figure 4 shows the total DH production in several European countries together with its share of the heat market. It can be seen that Poland and Germany are the largest producers. The highest market shares exist in some Nordic countries, along with some CEE countries.

Profu (2004) identifies a number of “key-factors” when assessing environmental impact of waste incineration, where one is energy recovery per ton waste. Figure 5 shows the extent to which the useful energy content of the incinerated waste is taken care of in a number of countries. Sweden has the highest energy recovery of the countries surveyed, mainly due to the country’s extensive DH network. The efficiency of using waste as a fuel varies between the countries surveyed. It should be noted, however, that if the data in the diagram were recalculated into oil equivalences, countries would show more similar figures.

10 One reason for this is the historically low electricity prices in Sweden (Sjödin, 2002) and (Trygg and Karlsson,

2005).


Table 1. Treatment methods for municipal waste in European countries 2002 in 000s of tons (Eurostat, 2005)11

Recycling Composting Energy

recovery Incineration, destruction Landfill Total

Belgium 1442 1088 1493 134 594 4761 Czech Republic 175 122 398 3 2097 2845

Denmark 796 555 2008 : 215 3587 Germany 17250 7844 153 11673 11266 52532 Estonia 13 2 0 0 419 553 Greece 375 32 : : 4233 4640 Spain 3811 3914 1567 : 14723 : France 4715 4208 10235 875 12991 33024 Ireland 463 34 : : 1967 2724 Italy 3897 7335 2587 111 18500 29929 Cyprus : : : : 450 500 Latvia 35 24 55 0 657 866 Lithuania : : : : 1000 1000 Luxembourg : : : : : : Hungary 67 47 288 : 3907 4646 Malta : : : : 188 187 Netherlands 2133 2365 3125 : 810 9900 Austria : : 490 : 1500 4634 Poland 116 215 : 36 10142 10509 Portugal 252 135 944 : 3388 4618 Slovenia 87 11 5 0 699 956 Slovakia 37 39 91 65 1192 1524 Finland 659 : 201 0 1512 2372 Sweden 1295 354 1675 : 825 4172 UK 3733 1423 2674 7 27545 33535 Bulgaria : : : : 3188 3945 Romania 170 : : : 6695 8365 Turkey : 383 9 0 24573 33324 Iceland 19 3 7 3 245 293 Norway 507 225 492 482 3061 Switzerland : : : : 80 4900

11 The data in the Recycling, Composting, Energy recovery, Incineration destruction, and Landfill columns are

taken from “Treatment of municipal waste”. The data in the Total column is taken from “Generation of municipal waste”. These were obtained from the Eurostat website. The data differs somewhat in some cases. This is done in order to compare data, to see whether anything has been omitted.


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DH production DH market share

Figure 4. DH production (TWh) and DH market share (%) in the countries surveyed by the report in Euroheat and Power (2003).

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Figure 5. Energy recovery by waste incineration (International Solid Waste Association, 2002; Swedish Association of Waste Management, 2000)

Table 1 shows different waste treatment methods in the European countries. The statistics

are not exhaustive because not all data is available. Nonetheless, some comments can be made. Regarding the correlation between high amount of DH and energy recovery, this can


mainly be seen in Sweden and Denmark. One thing that separates Denmark from Sweden is the high proportion of total electricity production that comes from CHP plants; about 40% in Denmark compared to around 8% in Sweden. The countries in CEE with a high amount of DH and/or large market share (the Baltic countries, Poland, the Czech Republic, Slovakia, and Romania) have not evolved their waste management sector and landfill is still the dominating treatment method. Some countries have a large proportion of heat from waste incineration in the DH systems, but the total amount of DH and/or market share is low, such as France, Norway, Italy and Switzerland. For Germany, the data is contradictory. In Table 1, it would appear that incineration is used mainly as a destruction method but as Figure 3 shows, some of the heat comes from waste. What can be said is that Germany has put a lot of effort into developing their material recycling. In general for Table 1, it can be said that waste treatment differs widely between countries and many still rely heavily on landfill.

Impact on Waste Incineration in Sweden of Waste Trade with Some European Countries

Trading in waste in the European Union is regulated (European Council, 1993) and waste

is divided into different categories: green, yellow and red. Green waste includes e.g. wood chips, logging residues, pellet, tall oil and sorted fractions of plastics, paper and rubber; imports of waste in this category do not have to be registered. Examples of yellow waste are chemically treated used woods, mixed fractions of used wood, paper, rubber and plastics, and municipal solid waste. Red waste is e.g. waste containing or contaminated with polychlorinated biphenyl (PCB) or polychlorinated dibenzo-dioxin. The information on what type of waste the categories include is taken from Ericsson and Nilsson (2004). The authors estimated imports of green waste in 2000 at 760,000 tons. The Swedish Environment Protection Agency must approve imports of yellow and red fractions. Imports of yellow waste increased from 200,000 tons in 1999 to 430,000 tons in 2002 (Olofsson et al 2005). Olofsson et al analyse which factors lie behind Swedish yellow waste imports, mainly intended for use in waste incineration plants with energy recovery. Both factors in the waste management system and the energy system are analysed. Five countries account for almost all imports to Sweden: Denmark, Finland, Germany, Norway, and Holland. The following factors may be significant;

– The infrastructure in Sweden, with DH systems that can utilise the heat, thus raising

energy recovery significantly – Energy taxation on fossil fuels is high12 in Sweden, and this increases the value of heat. – Different types of bio fuel are the most common alternative for the base supply of heat.

This means that clean fractions of waste are suitable to combust in existing plants, since the fuels are similar in composition.

– The quality of the imported waste has been higher than waste from Sweden, but this is starting to level out due to stricter sorting requirements in Sweden.

– Taxes on waste and a ban on landfill are also driving factors. Norway and Denmark both have taxes on waste incineration.

12 The carbon dioxide tax is at present 0.1 €/kg.


All the above factors lead to a difference in gate fees. The authors assume that in the future, the predominant factor to decrease the driving factors for import to Sweden would be the introduction of a waste incineration tax. A change in energy taxation in order to better fit in to the European Union legislation could also have a significant impact. In Sweden, business is divided into different sectors, with differentiated energy tax levels. This may be in conflict with the EU’s rules with regard to state aid, but Sweden has been granted temporary exemption. If the differentiation were changed and the same rules were valid for the whole of the business sector, the value of heat would be lowered, since the high taxes on fossil fuels would be lowered. Instead, it is suggested that there would be taxation on heat for consumers (Ministry of Finance, 2003).

Table 2 shows the gate fees in Sweden for different treatment options for municipal waste. As can be seen, there is great variation between plants.

Table 2. Gate fees for municipal waste, including VAT and taxes

(Swedish Association of Waste Management, 2005b)

Treatment method Landfill Incineration Biological treatment Cost (€/ton) 74-128 32-64 43-106

Impact on Waste Incineration of Trade in Electricity The objective of the directive (European Union, 2003a) on a common internal electricity

market is to open up the electricity market by subjecting it to competition. The reason for this is to increase efficiency in the energy sector. Industrial consumers can choose their supplier from July 1st 2004 and all consumers from July 1st 2007. The European Commission publishes a yearly report about the implementation of the internal market (European Commission, 2004) and that report states that the result of the implementation so far is unsatisfactory. One reason is barriers to cross-border trade, e.g. market structures and the need for additional investments in infrastructure. However, the report states that these problems must be solved. The impact of this directive in Sweden is that electricity prices will increase due to harmonisation with the electricity prices in continental Europe, which are higher than in Sweden. This is further described in Trygg and Karlsson (2005).

Higher electricity prices increases interest in producing electricity in the DH systems, and naturally also interest in electricity production in waste incineration plants. It also effects the cost of heat in the DH networks. A higher electricity price reduces the cost of heat from CHP plants and their possibility to compete with other plants also improves. Waste incineration plants are base suppliers of heat due to their negative operational costs and the need to treat the waste. However, in the DH network of Göteborg (Holmgren, 2006), where the municipal energy utility buys heat from a waste incineration plant13 and also waste heat from industries, the municipal utility had a better negotiation position towards those companies when they invested in a natural gas fired CHP plant assuming electricity prices harmonized with those on the continent.

13 In this case, another company, co-owned by several neighbouring municipalities owned the waste incineration

plant and sold the heat to the utility operating the DH network.


DISCUSSION OF TWO POLICY INSTRUMENTS Two policy instruments will be discussed in this section: the introduction of a tax on

incinerated waste and the green electricity certificate system. The aim here is to show how policy instruments in one system affect the other, and the difficulties in handling the double function of waste incineration as a supplier of heat and/or electricity and as a waste treatment method.

Introduction of a Tax on Incinerated Waste in Sweden A government investigation on a tax on incinerated waste was presented recently

(Ministry of Finance, 2005b), and a proposal of the tax was incorporated in the government budget proposition (Ministry of Finance, 2005c). The proposal is that waste should be incorporated in the existing energy taxation system by taxing the fossil content of the waste, meaning e.g. plastic packaging. However, at the time of writing, the tax has been postponed due to difficulties in measuring the fossil content in municipal waste. Table 3 shows the level of the tax on incinerated waste and how it applies to different energy conversion units.

Table 3. Waste incineration tax as proposed (Ministry of Finance, 2005b)

Energy tax (€/ton waste)

Carbon dioxide tax (€/ton waste)

Total (€/ton waste)

Fossil content 100% Hot water boiler 16 355 371 Condensing power plant 0 0 0 CHP plant14 51-62 51-62 Fossil content: 14% of total weight (assumed value for municipal waste) Hot water boiler 2 45 47 Condensing power plant 0 0 0 CHP plant 0 6.5-8 6.5-8

The design of the tax is in accordance with how existing energy taxation is applied to the

DH sector; with a carbon dioxide tax and an energy tax, which is not applied to electricity production, since electricity is taxed for the consumer (industrial consumers are exempt), heat from hot water boilers is taxed in full, and heat from CHP plants is taxed at deducted levels as is heat to industrial consumers. For a more detailed description of energy taxation, see e.g. Holmgren (2006). It can also be noted that the DH networks are part of the emission allowance trading systems, and the plants included will therefore probable be granted additional deductions of carbon dioxide taxes. However, since waste incineration plants are not included in the trading system, this is not included here.

The description of the assignment to carry out the governmental investigation of this tax includes several goals that should be taken into consideration. How the tax steers according to the waste hierarchy and to make material recovery including biological treatment more


economically competitive is important, but also impacts on the DH networks and the incentive for CHP production from waste incineration. The problem is that the goals that are enumerated conflict.

In the waste incineration tax proposal, resulting from the government investigation, the energy system perspective is the predominant; waste is seen primarily as a fuel, and therefore the main objective is that waste taxation be harmonized with energy taxes on other fuels. The investigation states that the fossil content of waste is subsidized in comparison to fossil fuels and that the value of the subsidization of biomass fuels is lessened if there is no tax on incinerated waste. This is corrected if the tax on incinerated waste is designed in this way, and it also provides the incentive for CHP production in waste incineration plants which has hitherto been lacking. The EU directive on promotion of CHP (European Union, 2004a) has influence over this. When summarizing the proposal, it can be said that the energy perspective has been given first priority and the waste management priority second. The only fraction which will have an increased incentive to material recover is various plastics. This fraction is appropriate for material recycling in an energy efficiency perspective; an earlier study has shown large energy savings when recycled plastic material is used instead of virgin material (Holmgren and Henning, 2004).

Another study has analysed the consequences for a municipal energy utility of investing in waste incineration if a tax on incinerated waste were introduced. (Holmgren and Gebremedhin, 2004). Tax levels of 11 and 42.5 €/ton were analysed, since those were the levels proposed in an earlier government investigation (Ministry of Finance, 2002). The conclusion was that at the tax level of 11 €/ton, the investment was still profitable for the utility, but at the 42.5 €/ton level, the investment was not profitable. Note that in Table 3 these levels are in the proximity of the levels proposed for plants with CHP production and hot water boilers respectively. The prerequisite for the results is naturally that the utility can not raise the gate fee for receiving the waste. The results indicate, however, that at these tax levels, other treatment options begin to be of interest.

Other questions which are raised concern the impact on gate fees of waste incineration plants. Plants with electricity production could maintain lower gate fees than other plants. Would that mean transportation of waste to those plants? This, however, is contradicted by the lack of waste treatment capacity (Swedish Association of Waste Management, 2004), due to waste management regulations. Another issue is to what extent the energy utilities will raise their gate fees to let consumers shoulder the increasing costs. Most existing plants without electricity production can not easily convert to CHP production since they consist of hot water boilers,15 and conversion would virtually mean building a new plant. Of the planned waste incineration plans, all have electricity production16 (Swedish District Heating Association, 2005). One question in a waste management perspective is what will happen in terms of encouraging material recovery and biological treatment, in accordance with the waste hierarchy, since this opportunity to increase incentive was not taken.17

14 Electrical efficiency in the interval 15-28%. 15 Personal contact with Anders Hedenstedt, Swedish Association of Waste Management. 16 Personal contact with Anders Hedenstedt, Swedish Association of Waste Management. 17 Again; except for fractions of plastic waste.


Green Electricity Certificates and Waste Incineration The green electricity certificate system is designed to increase electricity produced by

renewables (Ministry of the Environment, 2003a, b). The certificate system is influenced by the directive on increased electricity from renewables (European Union, 2001). The producers of electricity receive a certificate when they produce electricity in approved conversion units. These are wind power, solar power, geothermal power, tidal power, hydropower in new or small plants (installed after the end of 2002, and also increased power in old plants renovated after April 2003 and hydropower in plants with a maximum capacity of 1.5 MW), biomass, peat, sorted wood waste from demolition waste, and electricity produced from biogas. It is also proposed that animal fat, meaning residual products from the food industry, should receive certificates (Ministry of Finance, 2005c). Consumers will need a quota of certificates in relation to their total electricity consumption, creating a demand for certificates and thus giving them an economic value. The aim is to increase annual electricity production from renewable energy sources by 10 TWh between 2003 and 2010. The system ends in 2010, but a proposal to extend it to 2030 is in place (Ministry of Sustainable Development, 2005).

Electricity produced from municipal waste does not receive certificates in the Swedish certificate system, even if municipal waste is estimated to be of about 80% biological origin. If municipal waste were to be included, it would further increase the incentives for CHP in waste incineration plants since it pays off for every produced MWh of electricity. In the proposed tax on incinerated waste, the main issue is to be classified as a CHP plant, and in order to be so, the quota between electricity and heat needs to be at least 20% (Ministry of Finance, 2005b). The issue of whether municipal waste should receive electricity certificates has been debated since the electricity certificate system was originally designed and in the government investigation on a tax on incinerated waste (Ministry of Finance, 2005d) the question is analysed once again. The conclusion is that the new tax on incinerated waste is enough to steer towards increased CHP in waste incineration plants and if electricity certificates were given for municipal waste, it could steer waste of biological origin towards incineration and that would not comply with Swedish waste management goals.18 Again, the conflict between the goals in waste management and in the energy system can be seen. From an energy system viewpoint, it is logical to implement electricity certificates for municipal waste. It would increase electricity production in waste incineration which is in line with the European directive on promotion of cogeneration (European Union, 2004a). When the tax on incinerated waste is introduced, it is deemed important to remove the subsidies that the fossil part of municipal waste has enjoyed in comparison to fossil fuels. When the electricity certificate system is analysed, it is not important to insert the biological part in the system which benefits biomass fuels. When it comes to green electricity certificates, the government investigation states that the waste management goals are more important than the goals of the energy system.

The directive on electricity from renewables (European Union, 2001) provides scope for interpretation by member states, e.g. as regards which sources should be included in a certificate system. A voluntary certificate system exists in Europe, The Renewable Energy

18 The Swedish goals for biodegradable waste state that at least 35% should be biologically treated by 2010

(Swedish Environmental Protection Agency, 2005).


Certificate System19 (RECS) which in contrast to the Swedish system does include municipal waste. This shows that opinions as to how to classify waste in terms of whether it is a renewable or not differ throughout Europe.

MODELS AS DECISION SUPPORT Various models are often used as decision support tools, e.g. when municipalities make

infrastructural decisions, such as waste treatment capacity and energy utility plants. This section describes some models based on system analysis. The models have been used to assess waste management systems and waste incineration and the common theme is the dilemma of the two purposes waste treatment and production of heat and sometimes electricity, and how to handle this.

System analysis can be a mean to assess complex systems in order to e.g. determine how available resources should be used to satisfy the aim of the system or to evaluate environmental impacts of various measures. A model can be built that should include the essential features of the system. By building a model, understanding and knowledge of the system and the correlation between components in the system is gained.

Models and How to Handle the Double Function of Waste Incineration The method used in earlier studies carried out by the author (Holmgren and Bartlett,

2004; Holmgren and Gebremedhin, 2004; Holmgren, 2006) is energy system modelling, using the MODEST model (Henning 1998; 1999). MODEST is a linear programming model which minimizes the cost of supplying heat and/or power demand during the analysed period. The main purpose of the model is to find suitable investments, but it can also be used to optimize the operation of existing plants. The results from these studies are mainly how waste functions as a fuel in the district heating system, e.g. the impact on other fuels used, the cost of supplying heat with different amounts of waste used as fuel, and the amount of electricity produced in the DH networks. The effects of various policy instruments are also an appropriate issue to assess. The influence of the waste management system in the model is mainly via economic signals as regards the cost of waste as a fuel. Limits on amount of available waste is also set. When analyzing the results, it is vital to be aware that also considerations, more related to the waste management sector, should be included. A study has also been made that has broadened the scope by comparing waste treatment options from an energy efficiency viewpoint (Holmgren and Henning, 2004). Assuming that there is a district heating system that can utilize the heat, which fractions of the waste are suitable to energy recover and which to material recover? Another example of a study with the energy system in focus is Sahlin et al (2004), which analyses the impact on Swedish district heating systems as a whole, using a questionnaire and a simulating energy model named HEATSPOT.

Other methods have the waste management system in focus, as shown e.g. by Sundberg et al (1994). The paper describes the model MIMES/WASTE, which seeks the most cost-

19 More information can be found at www.recs.org (November 2005).


efficient way to treat waste. Another study has linked MIMES/WASTE with an energy system model, MARTES, by using both models in two case studies (Olofsson, 2001).

Life cycle assessment (LCA) is a widely used method for evaluating the environmental impact of products and services (Rydh et al, 2002). How to perform an LCA is laid down in ISO standards. The methodology in short has four steps:

1. Goal and scope definition 2. Inventory analysis, where data is compiled 3. Life cycle assessment involving classification of data to different environmental

impacts;20 characterization, where the data is analysed as to the extent to which they contribute to different impacts; and valuing or weighting. The step of valuing is however in question since it is considered to be subjective.

4. Interpretation of results. One model for assessing waste management options based on LCA methodology is

ORWARE, see e.g. Eriksson et al (2002). This model handles the double functions of waste incineration by compensatory systems, in line with LCA methodology. A compensatory system, e.g. for waste incineration, apart from the function of waste treatment, also means district heating and/or electricity. To assess the robustness of the results, a sensitivity analysis of these compensatory systems is recommended, e.g. if district heating is produced by biomass fuel or oil. Finnveden and Ekvall (1998) compare LCA studies of recycling versus incineration of paper, and show the importance of assumptions made with regard to compensatory systems and also take up the question of biomass; what is made of the saved biomass when recycling paper? This question indicates a need to define how biomass should be regarded; should it be regarded as a scarce resource?

A number of studies have attempted to estimate the potential biomass supply. Ericsson and Nilsson (2006) have assessed the potential in the 15 old EU countries (EU15), 8 newcomers21 and 2 candidate countries22 (ACC10) and also Belarus and Ukraine, and compared it with the EU’s targets for increasing the proportion of the total primary energy supply produced with biomass. Their assessment shows that, subject to certain restrictions on land availability, the potential is up to 11.7 EJ/year in the EU15 and 5.5 EJ/year in the ACC10. These figures can be compared with the fact that total energy supply in the EU15 in 2001 was 62.6 EJ. There are no resource limitations in meeting the EU target of 5.6 EJ/year in the EU15 by 2010, though it will probably not be met due to slow implementation of the renewable energy policy. Berndes et. al. (2003) are reviewing 17 studies on the contribution of biomass in future global energy supply. Both demand-driven studies23 and resource studies24 were reviewed. The resource studies showed large variations in the amount of biomass fuels. The studies with the highest assumptions assumed vast areas of Africa to be given over to energy crop production with exports to the rest of the world. The article

20 Such as greenhouse gases, eutrophication, acidification. 21 Cyprus and Malta are not included. 22 Bulgaria and Romania. 23 The meaning of demand-driven studies is the potential of energy from biomass in competition with other energy

carriers. 24 The meaning of resource-driven studies is the possibility to produce biomass for energy purposes in competition

with other land uses, such as food production.


criticizes the studies for not including other environmental effects of such expansion, such as biodiversity, and social factors are also overlooked. These studies give an indication that biomass utilization could increase substantially; this could, however, lead to environmental and social problems which are not taken into account when, for example, making a study where biomass fuel replaces fossil fuel as a compensatory system for district heating production, hence indicating lower environmental concerns. This is a significant issue, since it has been shown that these assumptions are often crucial for the results in LCA studies.

One drawback of using MODEST when analyzing waste incineration is that few environmental effects have been taken into account. In earlier studies (Holmgren and Bartlett, 2004; Holmgren and Gebrenedhin, 2004; Holmgren, 2006), only carbon dioxide emissions from the analysed DH networks have been calculated. One solution could be to use external costs of environmental effects, and include these costs in the optimization calculations of the D networks. This has been done by Carlsson (2002). In that study, external cost data was obtained from the European Union’s ExternE-project.25 The basic idea behind the concept of external cost is that electricity and heat production give rise to several negative external effects,26 such as climate change, acidification and health impacts. The cost of these effects should be internalized in the price of the energy supply, otherwise a suboptimal consumption of energy occurs from a socio-economic perspective. This can be compared to the step of valuing or weighing in the LCA methodology, since that is essentially also to put a value on environmental effects. However, this step is not really accepted in LCA methodology since it is considered to be subjective and the recommendation is to use it with care.

CONCLUSION The double function of waste incineration, both as a waste treatment method and a

supplier of electricity and/or heat is discussed in this chapter. A positive impact in one of the systems may be negative in the other, and strategies and goals in the two sectors can conflict. The main findings in this chapter are as follows.

– Sweden has extensive DH networks and therefore better possibilities to efficiently

recover the energy content in the waste than countries with a less developed infrastructure. There is a correlation between extensive DH networks and substantial incineration as waste treatment method in Sweden, and the connection is both historical and organisational. This correlation can not be unambiguously shown to exist in any other EU country. In this context, Sweden differs from other Western European countries, since relatively little DH is produced in CHP plants.

– Waste incineration can decrease possibilities for producing CHP in DH networks and this can be seen as a conflict between the need to treat waste in an acceptable way and the goal of more CHP production in the energy system.

– There is a conflict in the European Union between the internal market and waste management policy, for example that waste should be treated close to its origin. This has been solved by prohibiting exports of waste for disposal but not for recovery. A

25 Information about the ExternE project can be found at http://www.externe.info/ 26 Positive external effects, for example on local employment, can also occur.


shortcoming in the directives is that they do not clearly define what an energy efficient waste incineration plant is and hence not when a waste incineration plant should be defined as recovery versus destruction.

– The conflict between waste management goals and energy system goals when designing policy instruments has been shown. When designing the tax on incinerated waste, the energy system perspective was the predominant factor, the main objective being to harmonize taxes on incinerated waste with taxes on other fuels. The incentive for increasing material recovery and biological treatment was set aside, except in the case of plastic waste. In the design of the electricity certificate system, the waste management goals, for example more biological treatment, prohibits waste incineration plants from receiving certificates even if this would increase the incentive to produce CHP, consistent with the goals for the energy system.

– The double function is also addressed when different models for assessing waste incineration are reviewed; the importance of being aware of this and the impacts of different assumptions are discussed. Various models deal with the double function in different ways, and have their own strengths and weaknesses. It is also essential to be aware of the importance of assumptions. A model’s construction and the results from it should be seen as way of gaining knowledge of the system and as a support in decision-making. When actual decisions are to be made, there are other aspects that can be of importance that has not been included in the model.

ACKNOWLEDGMENTS The work was carried out under the auspices of The Energy Systems Programme, which

is financed by the Swedish Foundation for Strategic Research, the Swedish Energy Agency and Swedish Industry. Tekniska Verken i Linköping AB is acknowledged for their financial support. The author is grateful to Maria Saxe, Mats Bladh and Björn Karlsson for valuable comments on the chapter.

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Chapter 8

EXPERIMENTAL ANALYSIS OF A COMBINED RECOVERY SYSTEM

R. Herrero Martín* Departamento de Ingeniería Térmica y de Fluidos

Universidad Politécnica de Cartagena.

ABSTRACT

The present work is found in the field of energy recovery in air conditioning systems to promote energy saving and improve environmental quality. Experimental research has been carried out whose aim is the characterization of combined recovery equipment, consisting of a ceramic semi-indirect evaporative cooler and a heat pipe device to recover energy at low temperature in air conditioning systems. For characterization purposes, a design of experiment (DOE) and an analysis of variance (ANOVA) were applied with the aim of better understanding the energy behaviour of the combined device. The combined system built allows a feasible energy exchange between the supply airstream and the return one, improving the operation in air-conditioning systems. It is a new alternative device for use as a recovery system. The configuration chosen (crossed flow) is the most adequate from an operational point of view. The characterization of the system was carried out by employing experimental design methodology. A factorial design was performed by analysing how the factors used affect the characteristics analyzed. The contributions of the single factors and their interactions were presented by carrying out a variance analysis. The superiority of the evaporative cooling device under the operating conditions was clearly shown. An estimation of the energy saved by the combined system was carried out, showing the possibilities of implementing this solution to save energy and also to improve the indoor air quality by means of increasing the ventilation rates.

Keywords: energy recovery, evaporative cooling, heat pipes.

* Corresponding author: C/ Dr. Fleming, s/n (Campus Muralla), 30202 Cartagena , Murcia (España), Tel. +34-968-

32.59.85, Fax +34-968-32.59.99, E-mail: [email protected]

R. Herrero Martín 254

INTRODUCTION After the 1973 oil crisis and subsequent rise in fuel prices, there was a change in

approach on a world scale, both in political circles as well as among the population who realised their dependency on oil producing countries. As a result of these events, interest has grown in reducing energy demand at all levels, together with a search for more efficient energy equipment. The circumstances currently favouring the use of conventional energy sources not only involve facing up to increased costs as well as the foreseeable exhaustion of sources, but also include the costs involved in environmental protection and the harmful effects on the planet arising from their use (increase in the greenhouse effect due to greater CO2 emissions into the atmosphere or the destruction of the ozone layer due to emissions from coolants used in mechanical compression processes for cooling). Nowadays, energy saving is not an option but rather a priority concern. Using energy efficiently is, in many cases, the most effective and economic alternative for achieving environmental protection.

In HVAC installations, a solution in terms of improving energy efficiency is the use of air conditioner recoverers. The systems used can be considered as heat recoverers when they use, as secondary air, that which is provided by the air-conditioned premises, or just a mixture of this and outdoor air.

This is the target of this work, in which experimental research has been carried out whose aim is the energy study of combined recovery equipment, consisting of an evaporative cooler and a heat pipe device to recover energy at low temperature in air conditioning systems. To characterize the device empirically, an experimental design technique was employed by calculating all the characteristics which are involved in the energy analysis developed.

EVAPORATIVE COOLING SYSTEMS Evaporative cooling offers an alternative for reducing water or air temperature in the

systems that operate using this principle, thus enhancing the performance of the air conditioning installations in which they are used [1]. Traditionally, three different types of evaporative cooling systems were available: Direct Systems, Indirect Systems or a multi-step combination of both systems (Mixed Systems).

In Direct Systems, the water evaporates directly into the supplied air, cooling and increasing the amount of water in this air in an adiabatic heating process; the air supplies heat in order to evaporate the water, so the dry bulb temperature decreases and the humidity increases. The quantity of heat exchanged from the air is equal to the quantity of heat absorbed by the evaporation of water. If the water is recycled inside the device, its temperature is almost the wet bulb temperature of the air used in the process.

In the Indirect evaporative coolers, water evaporation takes place in a secondary airstream which only allows sensible heat exchange with the primary airflow using an interchanger. The heat transfer surface is cooled by contact with this secondary airflow and simultaneously, on the other side of the exchanger, the primary airstream is cooled (involving just sensible heat so humidity is not added). This is the reason why this process is called indirect and is especially used in those applications where humidity addition is not allowed in

Experimental Analysis of a Combined Recovery System 255

the renewed air and the contamination risks are avoided (“useful” airflow does not come into contact with the water that has been cooled evaporatively).

The mixed systems are a combination of direct and indirect systems, using sequential modules in order to improve the performance and increase their utility in wet climates. Other possibilities are heating exchange batteries and classical cooling systems.

As aforementioned, the evaporative systems can be considered as heat recoverers when they use, as secondary air, the air provided by the conditioned premises, or just a mixture of this air and outdoor air. These configurations are called regenerative or recoverable based on the following explanations:

Indirect Regenerative Evaporative System: this is an Indirect Evaporative Cooler

where a percentage of the primary airstream is used as a secondary airstream, which allows an increase in the cooling effect (Figure 1).

Figure 1. Indirect Regenerative Evaporative System.

Indirect Evaporative System with a Returning Air Recovery Configuration: this is an

Indirect Evaporative Cooler where the air that comes from the installation is used as a secondary airstream. This is the configuration which we have used (Figure 2).

Figure 2. Indirect Evaporative System with a Returning Air Recovery Configuration.


As Johnson [2] et al. mentioned, most conventional direct evaporative cooling methods involve collection and recirculation of water to keep the wetting media or misting region saturated. There exists an environment of almost stagnant water in direct contact with the outside air, which aids, if not properly maintained at significant costs, the spread of many liquid phase-born bacterial diseases, most notably Legionnaire’s disease.

Due to this fact, indirect evaporative cooling application has been commonly used, despite the fact that indirect systems have lower efficiency in comparison with direct systems [3]. An evolution from indirect evaporative cooling systems is the semi-indirect evaporative cooling system with porous media. The cooling effect of the impulsed air would thus be the addition of two processes: the heat exchange between the two air flows (supply and return) plus the heat exchange process, via evaporation, between the air supply and the external wall. Depending on the permeability of the wall of the solid porous cooler which separates the two air flows, there is greater or lesser liquid diffusion (water) with evaporation towards the air flow supply from the external pores, in all cases. The absolute humidity of the air supply is the controlling factor in this mass transport process, which is why it has been called semi-indirect. The semi-indirect evaporative cooler works with the following mechanisms:

• Heat and mass transfer in the return air flow. • Spread of mass due to porosity and heat transport through the solid wall. • Evaporation or condensation as well as heat and mass exchange in the air flow

supply.

Figure 3. Evaporative Cooler: heat and mass transfer mechanisms.

All of these features are presented together, thus combining heat and mass transfer,

increasing the cooling effect of the air to be conditioned and achieving optimisation of the thermal process [4] (See Figure 3).


Several prototypes for cooling building using porous ceramic materials as wetting media in indirect evaporative cooling applications as this paper proposes, have been built in recent years such as those by Ibrahim et al [5] or Riffat and Zhu [6] who also combined an indirect evaporative cooler using porous ceramic as the cooling source and a heat pipe as the heat transfer device.

The coolant material chosen yields low thermal resistance, high resistance to corrosion and is also economical and offers high porosity. The geometric dimension and configuration of the ceramic exchanger are shown in Table 1:

Table 1. Geometric dimensions of the evaporative cooler

Internal diameter

(di)

External diameter

(de)

Thickness

(δ)

Section T (ST)

Section L (SL)

Section D (SD)

Pipe Lengt

h

Area (Ao)

15*10-3m 25*10-

3m 5*10-3m 30*10-3m 25*10-3m 29,2*10-3m 0.6 m 2.3

m2

Figure 4. Evaporative Cooler geometric configuration

Table 2.-Geometric configuration of the evaporative cooler

Arrangement Number of columns Number of rows Number of pipes Material

Staggered 7 7 49 Ceramic It is important to point out that this system allows water evaporation in the air supply, but

the ceramic material used has a pore diameter that prevents the exchange of harmful agents through the porous structure, thus avoiding impulsed air contamination from the pollutants carried by the return air. [7]


The following photograph (Figure 5) shows the semi-indirect evaporative cooler and its arrangement above the tank that contains the water used in evaporative cooling.

Figure 5. The Evaporative Cooler device.

HEAT PIPE SYSTEMS

As Vasiliev [8] mentioned, the heat pipe or two-phase thermosyphon device is an

important concept in heat exchangers, which can be used in different branches of industry such as metallurgy, power, oil-refining, glass, etc. There are many articles carried out in the field of work of heating recovery using heat pipes such as the one by Shao et al [9] who presented a low pressure-loss heat recovery device based on heat pipes which was suitable for application in passive stack ventilation where a low pressure loss is essential. Lukitobudi et al. [10] designed, constructed and tested an air-to-air heat exchanger using thermosyphon heat pipes using water as the working fluid for heat recovery in industry, such as bakeries. Noie-Baghban and Majideian [11] designed and constructed a heat pipe heat exchanger for heat recovery in hospital and laboratories. In their research, the characteristic design and heat transfer limitations of single heat pipes for three types of wick and three working fluids were investigated using computer simulation. The experimental results presented agreed with the data obtained through computer simulation. Abd El-Baky and Mohamed [12] investigated the thermal performance and effectiveness of heat pipe heat exchanger for heat recovery in air conditioning applications by measuring the temperature difference of fresh warm and return cold air through the evaporator and condenser side. The heat transfer and enthalpy ratio between heat recovery and conventional air mixing are also targeted. The optimum


effectiveness of heat pipe heat exchanger is calculated and compared with the experimental results.

Numerous investigations have been made to obtain the thermal performance, ensure efficient and reliable operation of heat pipe heat exchangers [13–17]. Soleymez [18] presented a thermoeconomic optimization analysis is presented yielding a simple algebraic formula for estimating the optimum HPHE effectiveness for energy recovery applications. Lin et al [19] also carried out a thermal model for simulating the performance of a heat pipe system for recovering waste heat in the drying cycle in a domestic appliance. Noie [20] presented experimental and theoretical research carried out to investigate the thermal performance of an air-to-air thermosyphon heat exchanger. Many factors affect the thermal performance of thermosyphon heat exchangers including velocity and temperature of input air, type and filling ratio of the working fluid, and pipe material. Several experiments were carried out under different operating conditions by varying the parameters in order to determine and investigate their effect on the thermal performance of the thermosyphon heat exchanger.

The heat pipe recuperator is a super-conducting device comprising of an array of tubes, each of which is sealed at both ends. These tubes are the actual heat pipes. Each heat pipe consists of an envelope (the tube), a wick, and a working fluid.

Heat applied to one end evaporates the working fluid from the wick, the vapour flows to the cold end of the tube where it is condensed and returned by the wick to the hot end for re-evaporation, thus completing the cycle.

The heat pipe device is arranged over a metal bank bench. The following photograph (Figure 6) shows the heat pipe system and its set-up. The heat pipe exchanger built only recovers sensible heat from the airstreams expelled outdoors.

Figure 6. The HP device.


Table 3 presents the main design characteristics of the heat pipe recoverer that has been built. The tube bundle consists of 4 pipes per row, and three rows. The configuration chosen is done taking into account boundary layer limitations. In order to decrease the convection heat transfer resistance between the air and the heat pipes, both in the impulse air area as well as the return air area, fins perpendicular to the heat pipes are located parallel to the air flow, and built of layers of an aluminium-manganese alloy within which the heat pipes are inserted.

Table 3. Design characteristics of the heat pipe device

Maximum heat output (W) 85 Pipe length (m) 0.62 Pipe wall thickness (m) 2.1 × 10−3 Wick type 350, smooth Wick porosity (m2) 5.3 × 10−11 Wick material: Stainless steel Inner radius (m2) 10.6 × 10−3 Working fluid water

EXPERIMENTAL INSTALLATION Experiments were developed in the Air Conditioning Laboratory at the University of

Valladolid, Spain. As mentioned, the system is located in a recovery configuration to condition a room. The recovery system plus the conditioned room takes up approximately 20 square metres.

The systems used to carry out the trials are the following: (Figure 7 -8) • Supply system: this has a fan with a potentiometer to keep the air flows under

control. • Air Handling Unit (A.H.U.): this equipment allows us to simulate the conditions of

the air supplied (temperature and humidity). • Air distributing System: all the measuring instruments are inserted here. • Water distribution System: there is a water pump to which a rotameter is joined. The

system also has a pressure spray system with downward directed nozzles and a water droplet remover to avoid water loss.

• A porous evaporative cooler with energy recovery. (E.C.) • A heat pipe device with energy recovery. (H.P.) • The conditioned room: the dimensions are 2x2x2.5 m, which contains an air to air

reversible heat pump inside to guarantee when needed necessary that the space is properly conditioned.

• Monitoring and Data-Acquisition system: a computer monitors and stores all the results from the measuring instruments.

From the A.H.U. the air goes inside the EC. This main airstream is called the primary

airstream and when this airstream is conditioned in the SIEC it goes to the HP and after passing through this device it enters the room. As was mentioned the system is located in a recovery configuration.


Figure 7. Experimental Installation Schema.

Figure 8. Experimental Facility.

Thus, the air expelled from the room goes through the EC in a cross-flow, until it leaves in the upper part, when it is impulsed into the heat pipe in a cross-flow in relation to the primary airstream, ensuring non-dispersion of Legionella in the expelled air, which might carry aerosols. After passing through the HP, it is impulsed to the exterior heat pump unit, thus obtaining a three-recovering configuration.


The measurement sensors are shown in Figure 9: • T: temperature measuring sensor. (Accuracy: 0.1 C) • HR: relative humidity measuring sensor. (Accuracy: ±2 % RH (0-100% RH))

Figure 9. Measurement Sensors.

EXPERIMENTAL MEASUREMENTS The characterization of the recovery system was carried out following the experimental

design method. A complete factorial design was developed, to analyse the total heat recovered by the system in heating mode and in cooling mode. (See Figure 10)

There were two factors analyzed: • Air Flow The airflow levels correspond to three levels: 300m3/h, 400m3/h and 500m3/h. • Temperature The temperature levels correspond to summer and winter conditions in Valladolid (Spain)

in order to analyze the behaviour of the device in both working modes. The summers levels are: 45ºC (T9), 40ºC (T8), 35ºC (T7), 30ºC (T6) and 25ºC (T5) and the winter levels are: 20ºC (T4), 15ºC (T3), 10ºC (T2) and 5ºC (T1).

From the experimental results, the following characteristics: sensible heat, latent heat and

total heat are evaluated separately to better explain the combined system behaviour.


Figure 10. Experimental Design Schema.

For the evaporative cooler, latent and sensible heat were considered in order to obtain the total heat recovered. The heat pipe exchanger built only recovers sensible heat from the airstreams expelled outdoors. The uncertainty values for the characteristics analyzed are shown in Table 4, where UVi, represent the uncertainty values for each volumetric flow described.

Table 4. Uncertainty values for the characteristics analyzed: sensible,

latent and total heat (GUM procedures with k=2) [21]

Sensible Heat Latent Heat Total Heat Temperature

(ºC) UV1 (%)

UV2 (%)

UV3 (%)

UV1 (%)

UV2 (%)

UV3 (%)

UV1 (%)

UV2 (%)

UV3 (%)

25 4.6 5.5 5.8 4.6 5.5 5.9 6.6 7.8 8.3 30 4.5 6.2 5.7 4.6 6.2 5.7 6.4 8.8 8.0 35 4.5 5.2 6.0 4.5 5.2 6.1 6.3 7.3 8.5 40 4.4 5.1 5.4 4.4 5.1 5.4 6.2 7.2 7.6 45 4.3 5.7 5.5 4.3 5.8 5.6 6.1 8.1 7.8

The characteristics analysis was carried in two stages. Firstly, average values of the

single factors and their interactions are given and afterwards, final conclusions are supported by the variance analysis. The conclusions derived by single factors and interaction values inspection will not be accepted if the ANOVA analysis do not corroborate them.


The results will be presented in the following order:

- Sensible heat combined system analysis evaporative cooler analysis o heat pipes battery analysis

- Latent heat o evaporative cooler analysis

- Total heat o evaporative cooler analysis

SENSIBLE HEAT RECOVERED

Combined System In Figure 11 the average values of sensible heat recovered are plotted against single

factors levels (temperature (T) and airflow (V)), in Figure 12 the mean values of the characteristic are plotted against factor interaction (VxT). The corresponding values are also given. In table 6 the ANOVA is presented. In the ANOVA table column 1 shows the factors analyzed, which are: volumetric flow rate (Vi), temperature and the interaction between the aforementioned factors (VxT). Column 2 represents the degree of freedom (Dof) of the factors analyzed. Column 3 shows the sum of squares (SS) of the factors column 4 gives the associated variance values (V) and in column 5 the contributory percentage is given (%). Furthermore, remarkable conclusions in terms of the most contributory factor are fully addressed.

Factors Mean Values

V1 -1124.22 V2 -1439.77 V3 -1691.29 T1 977.19 T2 577.93 T3 -203.78 T4 -785.89 T5 -1220.62 T6 -1984.62 T7 -2591.93 T8 -3491.74 T9 -4042.37

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Figure 11. Average values of sensible heat recovered are plotted against single factors levels.


Table 5. VxT interaction mean values

Sensible Heat (W) Factors Mean Values Factors Mean Values Factors Mean Values V1T1 1137.10 V2T1 1039.37 V3T1 755.10 V1T2 608.00 V2T2 571.05 V3T2 554.74 V1T3 -79.89 V2T3 -224.62 V3T3 -306.84 V1T4 -784.19 V2T4 -705.10 V3T4 -868.38 V1T5 -972.33 V2T5 -1136.68 V3T5 -1552.84 V1T6 -1751.26 V2T6 -2059.50 V3T6 -2143.11 V1T7 -2125.84 V2T7 -2548.11 V3T7 -3101.84 V1T8 -2988.21 V2T8 -3563.80 V3T8 -3923.21 V1T9 -3161.36 V2T9 -4330.53 V3T9 -4635.21

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V1

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Figure 12. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction )

Table 6-. ANOVA results

Factors DoF SS V % V 2 1453205.1 726602.5 1.9 T 8 73561119.0 9195139.9 96.7 VxT 16 1065784.6 66611.5 1.4 Error 0 0.0 0.0 0.0 Total 26 76080109.0 2926158.0 100.0


Analysis of Results

Temperature This is the most contributory factor with a percentage close to 97% (See Table 6). As in

common heat exchangers, since the heat transfer rate is related to the temperature difference, when the temperature difference between the outdoor and the return airstreams rises, the sensible heat recovered is higher. (See Figure 11).

Furthermore, next to temperature level 3 (T3) a change can be clearly observed, fact which represents a different behaviour of the device from heating mode to cooling mode falling from positive values to negative ones. (See Figure 11)

In Table 7 the average values of sensible heat recovered for the combined system and the single systems are given and in Table 8 the corresponding ANOVA are shown. In Figure 13 the single devices contribution in comparison with combined system contribution is given.

Table 7. Single factors mean values for the combined system

and the single systems separately

Sensible Heat Recovered (W) Combined System Evaporative Cooling System Heat Pipes System

Factors Mean Values Factors Mean values Factors Mean Values

V1 -1124.22 V1 -1104.45 V1 -19.77 V2 -1439.77 V2 -1402.66 V2 -37.10 V3 -1691.29 V3 -1640.12 V3 -36.35 T1 977.19 T1 878.70 T1 98.49 T2 577.93 T2 562.59 T2 59.79 T3 -203.78 T3 -251.93 T3 48.14 T4 -785.89 T4 -765.58 T4 -20.30 T5 -1220.62 T5 -1189.54 T5 -31.07 T6 -1984.62 T6 -1920.03 T6 -64.59 T7 -2591.93 T7 -2503.58 T7 -88.35 T8 -3491.74 T8 -3366.12 T8 -125.62 T9 -4042.37 T9 -3886.21 T9 -156.16

Table 8. ANOVA (combined system and single systems separately)

Sensible Heat Combined System Evaporative Cooler Heat Pipe System Factors DoF SS % SS % SS % V 2 1453205.1 1.9 1296814.6 1.9 1727.2 0.9 T 8 73561119.0 96.7 67024437.0 96.5 181267.1 97.0 VxT 16 1065784.6 1.4 1102928.9 1.6 3956.1 2.1 Error 0 0.0 0.0 0.0 0.0 0.0 0.0 Total 26 76080109.0 100.0 69424180.0 100.0 186950.5 100.0


When analyzing Figure 13, one conclusion is inferred, the dominant recovery system is the evaporative cooler. This factor can be easily explained taking into account its location within the test ring where the heat pipes battery works with lower temperature differences during its operation cycles.

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Combined System Heat Pipes Evaporative Cooler

Figure 13. Evaporative Cooler and Heat Pipes contribution in global recovery.

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Evaporative cooling system

In this subsection a detailed analysis for the evaporative cooling system was carried out. Firstly, the corresponding results for both working modes are shown ( See Figure 14 and 17 and Tables 9-10), and secondly, these results are studied separately for heating mode (See Figure 15 and 18 and Tables 11 and 13 ) and cooling mode (See Figure16 and 19 and Tables 12 and 13).


Table 9. Single factors mean values

Sensible Heat (W) Factors Mean Values Factors Mean Values

V1 -1104.45 T4 -765.58 V2 -1402.66 T5 -1189.54 V3 -1640.12 T6 -1920.03 T1 878.70 T7 -2503.58 T2 562.59 T8 -3366.12 T3 -251.93 T9 -3886.21

Sensible Heat (W) Factors Mean Values V1 174.58 V2 128.80 V3 14.45 T1 878.70 T2 562.59 T3 -251.93 T4 -765.58 -1000

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Figure 15. Heating Mode: Average values of sensible heat recovered are plotted against single factors levels.

Calor Sensible (W) Factores Promedio V1 -2127.67 V2 -2627.83 V3 -2963.79 T5 -1189.54 T6 -1920.03 T7 -2503.58 T8 -3366.12 T9 -3886.21

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Figure 16. Cooling Mode: Average values of sensible heat recovered are plotted against single factors levels.


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V1

V2

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Figure 17. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction)


Sensible Heat (W)

Factors Mean value Factors Mean Value Factors Mean Value

V1T1 1043.36 V2T1 950.02 V3T1 642.72 V1T2 548.83 V2T2 517.52 V3T2 621.41 V1T3 -124.42 V2T3 -266.02 V3T3 -365.35 V1T4 -769.44 V2T4 -686.33 V3T4 -840.98 V1T5 -954.20 V2T5 -1113.31 V3T5 -1501.11 V1T6 -1712.27 V2T6 -1993.26 V3T6 -2054.56 V1T7 -2074.65 V2T7 -2443.92 V3T7 -2992.17 V1T8 -2887.95 V2T8 -3420.28 V3T8 -3790.13 V1T9 -3009.28 V2T9 -4168.39 V3T9 -4480.96

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Temperature factor ( Heating Mode)

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Figure 18. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction in Heating Mode)



Sensible Heat (W)

Factors Mean Value Factors Mean Value Factors Mean

Value V1T1 1043.36 V2T1 950.02 V3T1 642.72 V1T2 548.83 V2T2 517.52 V3T2 621.41 V1T3 ‐124.42 V2T3 ‐266.02 V3T3 ‐365.35 V1T4 ‐769.44 V2T4 ‐686.33 V3T4 ‐840.98

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Sensible Heat (W)

Factors Mean value Factors Mean value Factors Mean value V1T5 -954.20 V2T5 -1113.31 V3T5 -1501.11 V1T6 -1712.27 V2T6 -1993.26 V3T6 -2054.56 V1T7 -2074.65 V2T7 -2443.92 V3T7 -2992.17 V1T8 -2887.95 V2T8 -3420.28 V3T8 -3790.13 V1T9 -3009.28 V2T9 -4168.39 V3T9 -4480.96

Table 13. ANOVA (heating and cooling mode)

Heating Mode Cooling Mode Factors DoFheat DoFcool SS V % SS V % V 2 2 54418,37 27209,19 1,04 1770189,60 885094,80 10,82 T 3 4 5079918,40 1693306,13 97,41 14096108,00 3524027,00 86,16 VxT 6 8 80448,80 13408,13 1,54 494686,21 61835,78 3,02 Error 0 0 0,00 0.00 0,00 0,00 0,00 0,00 Total 11 14 5214785,60 474071,42 100,00 16360984,00 1168641,71 100,00


Analysis of Results All the considerations mentioned for the combined system, are essentially linked to the

evaporative cooler behaviour.

Heating and cooling mode analysis Temperature Factor: • Heating Mode: This is the most contributory factor. Its shows a lineal decreasing trend,

the transition between heating and cooling mode can be clearly appreciated next to temperature level 3, where primary air and secondary air temperatures are very similar.

• Cooling Mode: this is the most contributory factor. Its shows a lineal decreasing trend, although this trend could be considered as increasing trend, due to the fact that more negative values results in a gain in terms of energy recovered in cooling mode. This fact can be easily explained in terms of thermal differences between primary and secondary airstream when temperature factor is increased from T5 to T9.

Furthermore, the cooling mode potential in terms of energy recovery in comparison with

heating mode is clearly shown. Due to the aforementioned fact, a conclusion can be inferred, the behaviour of the analyzed device can be considered as irreversible and thus it should be operated under cooling conditions.

Heat Pipes System In this subsection a detailed analysis for the heat pipes system was carried out. Firstly,

the corresponding results for both working modes are shown ( See Figure 20 and 23 and Tables 14-15 and 18), and secondly, these results are studied separately for heating mode (See Figure 21 and 24 and Tables 16 and 19) and cooling mode (See Figure22 and 25 and Tables 17 and 20).

Table 14-. Single factors mean values

Sensible Heat (W)

Factors Mean Values Factors Mean Values V1 -19.77 T4 -20.30 V2 -37.10 T5 -31.07 V3 -36.35 T6 -64.59 T1 98.49 T7 -88.35 T2 59.79 T8 -125.62 T3 48.14 T9 -156.16


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Sensible Heat (W) Factors

Mean Values

V1 45.67 V2 41.38 V3 52.54 T1 98.49 T2 59.79 T3 48.14 T4 -20.30

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Sensible Heat (W)

Factors Mean Values

V1 -72.13 V2 -99.89 V3 -107.46 T5 -31.07 T6 -64.59 T7 -88.35 T8 -125.62 T9 -156.16

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Sensible Heat (W) Factors Mean Values Factors Mean Values Factors Mean Values V1T1 93.74 V2T1 89.35 V3T1 112.38 V1T2 59.17 V2T2 53.53 V3T2 66.67 V1T3 44.53 V2T3 41.40 V3T3 58.50 V1T4 -14.75 V2T4 -18.77 V3T4 -27.39 V1T5 -18.13 V2T5 -23.36 V3T5 -51.73 V1T6 -38.99 V2T6 -66.24 V3T6 -88.55 V1T7 -51.18 V2T7 -104.19 V3T7 -109.67 V1T8 -100.26 V2T8 -143.52 V3T8 -133.08 V1T9 -152.08 V2T9 -162.14 V3T9 -154.25

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Sensible Heat (W) Factors Mean Values Factors Mean Values Factors Mean Values V1T1 93.74 V2T1 89.35 V3T1 112.38 V1T2 59.17 V2T2 53.53 V3T2 66.67 V1T3 44.53 V2T3 41.40 V3T3 58.50 V1T4 -14.75 V2T4 -18.77 V3T4 -27.39

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Figure 25. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction in Cooling Mode)


Sensible Heat (W)

Factors Mean Values Factors Mean

Values Factors Mean Values

V1T5 -18.13 V2T5 -23.36 V3T5 -51.73 V1T6 -38.99 V2T6 -66.24 V3T6 -88.55 V1T7 -51.18 V2T7 -104.19 V3T7 -109.67 V1T8 -100.26 V2T8 -143.52 V3T8 -133.08 V1T9 -152.08 V2T9 -162.14 V3T9 -154.25

Table 18. ANOVA

Factors DoF SS V %

V 2 1727.23 863.62 0.92 T 8 181267.12 22658.39 96.96

VxT 16 3956.14 247.26 2.12 Error 0 0.0 0.0 0.00 Total 26 186950.49 7190.40 100.00


Table 19. ANOVA (heating mode)

Heating Mode Factors DoFheat SS V % V 2 253.64 126.82 1.12 T 3 22034.72 7344.91 97.20 VxT 6 381.52 63.59 1.68 Error 0 0.00 0.00 0.00 Total 11 22669.87 2060.90 100.00

Table 20. ANOVA (cooling mode)

Cooling Mode

Factors DoFheat SS V % V 2 3460.31 1730.16 10.12 T 4 29148.66 7287.16 85.24 VxT 8 1587.91 198.49 4.64 Error 0 0.00 0.00 0.00 Total 14 34196.88 2442.63 100.00

Analysis of Results

Temperature • Heating Mode: This is the most contributory factor, with a percentage next to 97%.

When the temperature difference between the outdoor and the return airstreams rises, the sensible heat recovered is higher. The transition between cooling and heating modes occurs next to temperature level 4. (See figure 7)

• Cooling Mode: This is again the most contributory factor, since the heat transfer rate is related to the temperature difference, when the temperature difference between the outdoor and the return airstreams rises, the sensible heat recovered is higher.

LATENT HEAT RECOVERED Latent heat is only recovered by the evaporative cooler device. In this subsection a detailed analysis for the evaporative cooling system was carried out.

Firstly, the corresponding results for both working modes are shown ( See Figure 26 and 29 and Tables 21-22 and 25), and secondly, these results are studied separately for heating mode (See Figure 27 and 30 and Tables 23 and 26) and cooling mode (See Figure 28 and 31 and Tables 24 and 26 ).



Latent Heat (W) Factors Mean Values Factors Mean Values

V1 671.29 T4 516.25 V2 672.31 T5 699.80 V3 473.95 T6 827.53 T1 326.35 T7 811.22 T2 321.36 T8 997.64 T3 247.60 T9 704.90

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Latent Heat (W)

Factors Mean Value

V1 381.37 V2 385.66 V3 291.65 T1 326.35 T2 321.36 T3 247.60 T4 516.25

0

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Sensible Heat (W)

Factors Mean Value

V1 903.23 V2 901.63 V3 619.80 T5 699.80 T6 827.53 T7 811.22 T8 997.64 T9 704.90

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Latent Heat (W) Factors Mean Value Factors Mean Value Factors Mean Value V1T1 424.04 V2T1 188.23 V3T1 366.78 V1T2 359.07 V2T2 433.75 V3T2 171.25 V1T3 234.05 V2T3 351.59 V3T3 157.17 V1T4 508.31 V2T4 569.06 V3T4 471.39 V1T5 914.48 V2T5 670.09 V3T5 514.82 V1T6 846.11 V2T6 1021.86 V3T6 614.63 V1T7 946.76 V2T7 942.50 V3T7 544.41 V1T8 1267.68 V2T8 897.48 V3T8 827.77 V1T9 541.11 V2T9 976.24 V3T9 597.35

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Figure 30. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction in Heating mode)


Sensible Heat (W)

Factors Mean Value Factors Mean Value Factors Mean Value

V1T1 93.74 V2T1 89.35 V3T1 112.38 V1T2 59.17 V2T2 53.53 V3T2 66.67 V1T3 44.53 V2T3 41.40 V3T3 58.50 V1T4 -14.75 V2T4 -18.77 V3T4 -27.39

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Figure 31. Average values of sensible heat recovered are plotted against temperature factor. (VxT interaction in Cooling mode)



Sensible Heat (W)

Factors Mean Value Factors Mean Value Factors Mean Value

V1T5 -18.13 V2T5 -23.36 V3T5 -51.73 V1T6 -38.99 V2T6 -66.24 V3T6 -88.55 V1T7 -51.18 V2T7 -104.19 V3T7 -109.67 V1T8 -100.26 V2T8 -143.52 V3T8 -133.08 V1T9 -152.08 V2T9 -162.14 V3T9 -154.25

Table 25. ANOVA

Factors DoF SS V %

V 2 234869.36 117434.68 10.38 T 8 1676654.00 209581.75 74.10 VxT 16 351256.57 21953.54 15.52 Error 0 0.0 0.0 0.00 Total 26 2262779.9 87029.99 100.00


Heating Mode Cooling Mode Factors DoF % DoF % V 2 10.77 2 39.66 T 3 56.58 4 26.23 VxT 6 32.65 8 34.11 Error 0 0.00 0 0.00 Total 11 100.00 14 100.00

Analysis of Results All the factors and interaction with a percentage of contribution in the ANOVA higher

than 15% are considered.

Air Flow • Cooling Mode: This factor presents the highest contributory percentage (39%). A

priori, it is thought that when the airflow rises the latent heat recovered also does, due to the increase in the mass heat coefficient, nevertheless, the convective mass diffusion does not limit mass transport, thus it cannot be considered the controlling resistance. It was observed that when increasing the airflow above 400 m3/h, the humidity addition lowers (in absolute terms), this means that this airflow value can be considered as a maximum, reaching this value the system behaves as a current


indirect evaporative cooler system, diminishing the latent heat recovered. To observe the aforementioned fact (“so called” by-pass effect), a series of charts are provided ( See Tables 27-29). In this tables, in the last column the specific humidity values are provided.

Table 27. Results for 300 m3/h.

T1 (C)

x1 (gwater / kg dry air )

T2 (C)


T1-T2 (C)

x1-x2 (gwater / kg dry air )

5.3 0.0035 8.9 0.0041 -3.6 0.6 9.8 0.0035 11.7 0.0040 -1.9 0.5 13.9 0.0037 13.5 0.0040 0.4 0.3 21.1 0.0081 18.4 0.0088 2.6 0.7 23.3 0.0083 20.0 0.0096 3.3 1.3 29.9 0.0091 24.0 0.0102 5.9 1.2 33.2 0.0087 26.1 0.0100 7.1 1.3 39.3 0.0090 29.4 0.0108 9.9 1.7 44.3 0.0101 34.0 0.0109 10.2 0.7


T1 (C)


T2 (C)


T1-T2 (C)


4.9 0.0035 7.3 0.0037 -2.4 0.2 10.7 0.0032 12.0 0.0037 -1.3 0.4 14.6 0.0036 13.9 0.0039 0.7 0.4 21.5 0.0086 19.9 0.0091 1.6 0.5 23.4 0.0078 20.7 0.0084 2.6 0.6 30.7 0.0094 25.3 0.0105 5.4 1.1 33.8 0.0093 28.2 0.0102 5.6 0.9 39.4 0.0082 31.6 0.0090 7.8 0.8 44.8 0.0099 33.9 0.0109 10.9 1.0


T1 (C)


T2 (C)


T1-T2 (C)


4.2 0.0034 5.4 0.0036 -1.21 0.3 10.1 0.0032 11.4 0.0033 -1.28 0.1 14.3 0.0035 13.5 0.0036 0.76 0.1 19.6 0.0081 18.0 0.0085 1.61 0.4 25.4 0.0076 22.5 0.0080 2.94 0.4 30.1 0.0090 26.1 0.0095 3.95 0.5 34.5 0.0087 28.3 0.0092 6.20 0.5 39.1 0.0088 32.0 0.0094 7.13 0.6 44.5 0.0087 35.7 0.0092 8.79 0.5


Temperature • Both Modes analysis: this is the dominant factor. There are two different trends,

firstly, heating one, form levels 1 to 3, where latent heat decreases and secondly, cooling one from level 4, where latent heat increases.

• Heating Mode: evaporation is governed by the water vapour partial pressure

between the tubes surface and the primary airstream. The specific humidity levels of the dates (See Tables 6-9) are closed, under these conditions, the heat exchanged is mainly sensible heat, within this situation the saturation vapour pressure enables water evaporation, (although temperature rises the corresponding relative humidity is lower). Level 4 presents a different trend in comparison with levels 1 to 3).

• Cooling Mode: The dates present low relative humidity values and high

temperatures, which corresponds to large evaporative capacity, whilst for lower temperature levels (heating mode) the relative humidity levels associated are higher, which corresponds to low evaporation capacity. Even next to saturation, condensation conditions could occur, diminishing the latent heat exchanged.

VxT interaction

• Heating Mode: When analyzing the data in detail, it is observed that T1 for V2

presents an anomalous value, lower than expected, fact which motivates the intersection. Level 4 presents a different behaviour similar to the one observed in cooling mode.

• Cooling Mode: in this case an interaction occurs. When increasing airflow and

temperatures together with lower relative humidity levels, the latent heat recovered rises. As previously discussed, this behaviour is limited by the maximum airflow (V2).

TOTAL HEAT RECOVERED Due to the fact that the combined system mostly reproduces the evaporative cooler device

behaviour (see Figure 32). The results offered corresponds to the evaporative cooler device. The ANOVA also corroborates this fact. (See Table 30).

Evaporative Cooler

In this subsection a detailed analysis for the evaporative cooling system was carried out. Firstly, the corresponding results for both working modes are shown ( See Figure 33 and

36 and Tables 31-33), and secondly, these results are studied separately for heating mode (See Figure 34 and Table 34 ) and cooling mode (See Figure 35 and Table 34).


-4000

-3000

-2000

-1000

0

1000

2000

V1 V2 V3 T1 T2 T3 T4 T5 T6 T7 T8 T9

Single Factors

Tota

l Hea

t Rec

over

ed (W

)(A

vera

ge V

alue

s)

Combined System Heat Pipes Evaporative Cooler

Figure 32 Evaporative Cooler and Heat Pipes contribution to total heat recovered.

Table 30. ANOVA (combined system and single systems separately)

Total Heat Total Evaporative Cooler Heat Pipes Factors DoF SS % SS % SS % V 2 2656919.8 4.41 2446733.6 4.50 1727.23 0.92 T 8 56340888 93.48 50688523 93.16 181267.12 96.96 VxT 16 1275887.2 2.12 1274684.4 2.34 3956.14 2.12 Error 0 0.0 0.00 0.0 0.00 0.0 0.00 Total 26 60273695 100.00 54409941 100.00 186950.49 100.00


Total Heat (W)

Factors Mean Values Factors Mean Values V1 -433.16 T4 -249.33 V2 -730.35 T5 -489.74 V3 -1166.17 T6 -1092.50 T1 1205.05 T7 -1692.36 T2 883.94 T8 -2368.48 T3 -4.33 T9 -3181.31


-3500

-3000

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

V1 V2 V3 T1 T2 T3 T4 T5 T6 T7 T8 T9

Factors Levels

Tota

l Hea

t Rec

over

ed (W

) (A

vera

ge v

alue

s)


Total Heat (W)

Factors Mean value

V1 555.95 V2 514.46 V3 306.10 T1 1205.05 T2 883.94 T3 -4.33 T4 -249.33

-400

-200

0

200

400

600

800

1000

1200

1400

V1 V2 V3 T1 T2 T3 T4

Factors Levels

Tota

l Hea

t Rec

over

ed (W

) (A

vera

ge v

alue

s)


Total HeatW)

Factors Mean Value

V1 -1224.44 V2 -1726.20 V3 -2343.99 T5 -489.74 T6 -1092.50 T7 -1692.36 T8 -2368.48 T9 -3181.31

-3500

-3000

-2500

-2000

-1500

-1000

-500

0

V1 V2 V3 T5 T6 T7 T8 T9

Factors Levels

Tota

l Hea

t Rec

over

ed (W

) (A

vera

ge v

alue

s)




Total Heat(W)

Factors Mean Value Factors Mean value Factors Mean Value

V1T1 1467.40 V2T1 1138.25 V3T1 1009.50 V1T2 907.90 V2T2 951.27 V3T2 792.66 V1T3 109.63 V2T3 85.57 V3T3 -208.18 V1T4 -261.13 V2T4 -117.26 V3T4 -369.60 V1T5 -39.72 V2T5 -443.22 V3T5 -986.29 V1T6 -866.16 V2T6 -971.40 V3T6 -1439.93 V1T7 -1127.89 V2T7 -1501.43 V3T7 -2447.75 V1T8 -1620.28 V2T8 -2522.80 V3T8 -2962.35 V1T9 -2468.17 V2T9 -3192.15 V3T9 -3883.62

-5000

-4000

-3000

-2000

-1000

0

1000

2000

T1 T2 T3 T4 T5 T6 T7 T8 T9

Temperature factor

Tota

l Hea

t Rec

over

ed (W

) (A

vera

ge v

alue

s)

V1

V2V3


Table 33. ANOVA

Factors DoF SS V % V 2 2446733.6 1223366.8 4.50 T 8 50688523 6336065.4 93.16 VxT 16 1274684.4 79667.8 2.34 Error 0 0.0 0.0 0.00 Total 26 54409941 2092690 100.00



Heating Mode Cooling Mode Factors DoFheat DoFcool SS V % SS V % V 2 2 143416.55 71708.28 3.13 3144680.40 1572340.20 18.65 T 3 4 4360719.70 1453573.23 95.20 13361816.00 3340454.00 79.23 VxT 6 8 76221.97 12703.66 1.66 357099.39 44637.42 2.12 Error 0 0 0.00 0.00 0.00 0.00 0.00 0.00 Total 11 14 4580358.20 416396.20 100.00 16863596.00 1204542.60 100.00

Analysis of Results

Airflow Analysis • Cooling Mode: its contribution is higher, around 18%. It is shown that, when the

airflow is increased, the total heat recovered rises, due to the increment of the film coefficients: both the thermal coefficient, which characterises the sensible exchange, as well as the mass coefficient linked to the latent exchange.

Temperature

• Heating Mode: this is the most contributory factor, with a very high percentage of

approximately 95%. This value is increased for the highest temperature differences between both airstreams (supply and return). The behaviour of the system is clearly shown, which goes from the positive values that characterize the heating mode to the negative ones which represent the cooling mode. The transition between these behaviours occurs near the temperature level 3 which corresponds to 15ºC.

• Cooling mode: this is the most contributory factor whose values are approximately 80%. In this factor, the effects produced by the temperature increments are cancelled out by the sensible and latent heat recovered. The rising trend to negative values, the continuity and the linearity that presents the evaporative cooler in this working mode are clearly shown.

SUMMARY In Table 35 the main conclusions from the analysis performed are summarized. The legend to understand the following table is: “x” means no contribution (negligible

contribution in terms of variance analysis), as well as the white squares. The light-grey coloured squares represent a medium contributory percentage, and the ones in dark grey are the most contributory squares, their effects were previously explained.


Table 35. Summary of Results (combined system and single systems separately)

Sensible Heat Evaporative Cooler Heat Pipes

Factors TOTAL Heating Mode

Cooling Mode

Heating Mode

Cooling Mode

V x x Decreasing (-) x Decreasing

(-)

T Decreasing (+/-)

Decreasing (+/-)

Decreasing (-)

Decreasing (+/-)

Decreasing (-)

VxT x x x x x LATENT HEAT

Evaporative Cooler Factors Heating Mode Cooling Mode

V Decreasing (+) By- pass efect T Decreasing (+) Increasing (+)

VxT Corroborates individual factors Interaction Total Heat

RESI H.P Factors TOTAL Heating

Mode Cooling Mode

Heating Mode

Cooling Mode

V x x Decreasing (-) x Decreasing

(-)

T Decreasing (+/-)

Decreasing (+/-)

Decreasing (-)

Decreasing (+/-)

Decreasing (-)

VxT x x x x x • It should be mentioned as a general conclusion that level 4 is a discordant point of

the Heating mode behaviour. • The dominant recovery system is the evaporative cooler in terms of total heat

recovered.

Sensible Heat • Temperature is the most contributory factor in terms of sensible heat. A decreasing

trend is clearly observed from positive values (heating mode) to negative ones (cooling mode).

Latent Heat

• Heating mode: temperature was the most contributory factor. • Cooling mode: an important by-pass effect was found.


Total Heat • Temperature is the most contributory factor. This value is increased for the highest

temperature differences between both airstreams (supply and return).

CONCLUSIONS The combined system built allows a feasible energy exchange between the supply

airstream and the return one, improving the operation in air-conditioning systems. It is a new alternative device for use as a recovery system. The configuration chosen (crossed flow) is the most adequate from an operational point of view.

The characterization of the system was carried out by employing experimental design methodology. A factorial design was performed by analysing how the factors used affect the characteristics analyzed. The contributions of the single factors and their interactions were presented by carrying out a variance analysis. The superiority of the evaporative cooling device under the operating conditions was clearly shown.

An estimation of the energy saved by the combined system was carried out, showing the possibilities of implementing this solution to save energy and also to improve the indoor air quality by means of increasing the ventilation rates.

ACKNOWLEDGMENTS This work was developed thanks to the support of the Spanish Ministry of Education and

Science of Spain which awarded a Ph.D. scholarship with the reference number: AP2003-3730 IME in order to carry out the Ph.D. work entitled: “Waste Energy Recovery using a combined system: SIECHP”.

REFERENCES Watt, J. R. (1986). Evaporative Air Conditioning Handbook, Chapman & Hall, New York. Johnson, D. W., Yavuzturk, C. & Pruis, J. (2003). Analysis of heat and mass transfer

phenomena in hollow fiber membranes used for evaporative cooling. Journal of Membrane Science, vol. 227, Issues 1-2, 15 December, Pages 159-171.

Rey Martínez, F. J., Velasco Gómez, E., Herrero Martín, R., Martínez Gutiérrez, J. & Varela Diez, F. (2003). Comparative Study Of Two Different Evaporative Systems: An Indirect Evaporative Cooler And A Semi-Indirect Ceramic Evaporative Cooler. Energy and Buildings.

Kaviany, M. (1999). Principles of Heat Transfer in Porous Media. Springer-Verlag, New York. ISBN 0-387-94550-4.

Ibrahim, E., Shao, L. & Riffat, S. B. (2003). Performance of porous ceramic evaporators for building cooling application. Energy and Buildings, 35, 941-949.


Riffat, S. B. & Zhu, J. (2004). Mathematical model of indirect evaporative cooler using porous ceramic and heat pipe Applied Thermal Engineering, vol. 24, Issue 4, March, Pages 457-470.

Robert, L. (2003). Minimizing Legionella concentration in cooling water systems, Water Technol Mag.

Vasiliev, L. L. (2005). “Heat pipes in modern heat exchangers”. Applied Thermal Engineering 25, 1-19.

Shao, L., Riffat, S. B. & Gan, G. “Heat recovery with low pressure loss for natural ventilation”. Energy and Buildings, vol. 28, Issue 2, October 1998, Pages 179-184

Lukitobudi, A. R., Akbarzadeh, A., Johnson, P. W. & Hendy, P. (July 1995). “Design, construction and testing of a thermosyphon heat exchanger for medium temperature heat recovery in bakeries” Heat Recovery Systems and CHP, vol. 15, Issue 5,Pages 481-491.

Noie-Baghban, S. H. & Majideian, G. R. (1 October 2000). “Waste heat recovery using heat pipe heat exchanger (HPHE) for surgery rooms in hospitals” Applied Thermal Engineering, vol. 20, Issue 14, Pages 1271-1282

Mostafa, A. Abd El-Baky 1 & Mousa M. Mohamed. (2007). “Heat pipe heat exchanger for heat recovery in air conditioning”. Applied Thermal Engineering, 27, 795-801.

Larson, E. D. Nilsson, L. J. (1991). Electricity use and efficiency in pumping and air handling system, ASHRAE Trans., 97 (part 2), 363-377.

Faghri, A. et al. Heat pipe for hands, Mech. Eng. 111 (6) (1989) 72-75. Liu, G. et al. (1992). The application of heat pipe heat exchanger in exhaust gas heat recovery

system and its thermodynamic analysis, in: 8th International Heat Pipe Conference, Beijing, China, 582–585.

Dube, V., Sauciuc, I. & Akbarzadeh, A. (1996). Design construction and testing of a thermosyphon heat exchanger for medium temperature heat recovery, in: 5th International Heat Pipe Symposium, Melbourne, Australia.

Tan, J. O. & Liu, C. Y. (1990) Predicting the performance of a heat pipe heat exchanger using the NTU method, Int. J. Heat Fluid Fl. 11 (4), 376-379.

Söylemez, M. S. (September 2003). “On the thermoeconomical optimization of heat pipe heat exchanger HPHE for waste heat recovery”. Energy Conversion and Management, vol. 44, Issue 15, Pages 2509-2517

Lin, S., Broadbent, J. & McGlen, R. (January 2005). “Numerical study of heat pipe application in heat recovery systems”Applied Thermal Engineering, vol. 25, Issue 1, Pages 127-133

Noie. S. H. (April 2006). “Investigation of thermal performance of an air-to-air thermosyphon heat exchanger using ε-NTU method”. Applied Thermal Engineering, vol. 26, Issues 5-6, Pages 559-567

International Organization for Standardization. (1995). Guide to the expression of uncertainty in measurement:101, ISO Geneva.


Chapter 9

ENERGY RECOVERY SYSTEMS FROM INDUSTRIAL PLANT WASTE: PLANNING OF AN INDUSTRIAL PARK

LOCATED IN THE SOUTH OF ITALY

Silvana Kühtz∗, Francesca Intini, Sara Bellini and Giovanna Matarrese

Università della Basilicata, Facoltà di Ingegneria DIFA – via Lazzazzera, 75100 Matera, Italy

ABSTRACT

In this chapter, we compare environmental and technological aspects of some innovative energy recovery systems from industrial waste. We present the results of a research study that we are conducting on an Italian firm that produces polyethylene terephthalate (PET) supports for waterproof membranes from plastic bottles. For this firm (and all of the firms in the same industrial park), the waste represents only an undesired cost rather than a potential energy source. We first compared a traditional thermal waste treatment with a molecular dissociator and then with a specific gasifier. All three technologies can be fed with basically every type of waste, and can produce electric and/or thermal energy. In particular, the latter two produce syngas that can be burned after depuration to produce energy. A cost-benefit analysis is then carried out to plan how the whole industrial park can use the industrial waste to produce the energy it needs, with economic and environmental benefits for all.

INTRODUCTION The gradual depletion of environmental resources is one of the most complex and

pressing problems facing the world today. Too often in the past people have failed to take into account that the environment is not an inexhaustible resource and that its indiscriminate use

∗ [email protected]

Silvana Kühtz, Francesca Intini, Sara Bellini and Giovanna Matarrese 290

would have led sooner or later to a highly critical situation. Waste management in industrial parks is a particularly relevant issue for the purpose of minimizing the global impact on the environment and introducing an advanced model of industrial ecology.

The plans to set up a dense network of relations within an industrial park, aiming to achieve shared goals of environmental and economic performance, have been carried out through the creation of eco-industrial parks. In this chapter, we are going to analyze various waste disposal methods by identifying their specific skills in the ecological exploitation of waste products and the respective plant/environment interactions.

To this purpose, it is necessary to introduce innovative methods and tools of analysis, design and planning, which take into account the complex relationships between the environmental variables.

Life cycle assessment, combined with cost-benefit analysis, is part of the methodological apparatus developed for an objective environmental assessment aimed at comparing alternative scenarios, and it can be used as a decision support tool for the framing of industrial and environmental policies.

In order to make our analysis more realistic, our comparative assessment of technological and management aspects of the various systems present in the waste to energy sector has referred to the results of a research study we have conducted on an Italian firm that produces polyethylene terephthalate (PETP) support membranes from plastic bottles, and which regards (like all of the firms in the same industrial park) industrial waste only as an undesired cost, whereas it could represent an energy source.

1. A STRATEGY FOR SUSTAINABLE MANAGEMENT OF INDUSTRIAL PARKS

The environmental management of industrial parks was a new topic until some time ago.

The situation has evolved rapidly, thanks to the introduction of regulations and directives concerning this sector, and it has increasingly drawn the attention of public and private institutions which are becoming increasingly aware of the need to promote sustainable development, especially in terms of energy saving and of improving life and work conditions. These notions, that only a few years ago were considered too innovative and as potential obstacles to industrial development, are today topics of wide interest.

1.1. Environmental Qualification of Industrial Parks The issue of the environmental qualification of industrial sites is relatively new, even on

an international level: it is only since the early 1990s that the U.S., together with Asia and Europe, has witnessed the spread of voluntary experimentations aimed at creating industrial areas equipped with tools for minimizing the impact on the environment [1].

Eco-industrial parks (EIP), as theorized by Lowe [2], are networks of manufacturing companies and service firms which are linked by a joint management and commit themselves to improving their own environmental, economic and social performances, by collaborating in dealing with environmental issues and resource use (including energy, water and

Energy Recovery Systems from Industrial Plant Waste: Planning … 291

minerals). This integrated approach pursues collective benefits that are greater than the sum of individual benefits that each company would obtain individually from the optimization of its own performances. The strategies to achieve such a goal require a new design or a revitalisation of infrastructures and of industrial park planning, cleaner production, protection from pollution, energy efficiency and business cooperation.

We distinguish three basic categories of eco-industrial projects:

1. Eco-industrial park or estate (EIP) – an industrial park developed and managed as a real estate development enterprise and seeking high environmental, economic, and social benefits as well as business excellence.

2. By-product exchange (BPX) – a set of companies seeking to utilize each other’s by-products (energy, water, and materials) rather than disposing of them as waste.

3. Eco-industrial network (EIN) – a set of companies collaborating to improve their environmental, social, and economic performance in a region (see Figure 1). We believe these distinctions are important to maintain, although there are various ways

projects can overlap. EIPs and EINs may include by-product exchange programs. One or more EIPs may participate in either a BPX or an EIN [3].

An eco-industrial network may include stand-alone companies, companies in industrial parks, and the park management organizations. EIN members collaborate to enhance their performance and to create shared services and facilities. One form of collaboration is to exchange by-product materials, energy, or water among companies, when feasible.

Hence, the strategic objectives of environmental performance pursued by the EIPs are: • efficient resource use • environmental impact reduction • management of interactions between the environment and surrounding communities. Some of the shared services may be: environmental management systems of a single

production cycle, logistics, by-products exchange, recruitment of other businesses, external promotion, management of green areas, etc.

Figure 1. Eco-industrial network.


1.2. Principles of Industrial Ecology Eco-Industrial Parks take up the principles developed by industrial ecology, which is the

study of material and energy flows, with the aim to reduce significantly resource use and pollution. Indeed it proposes to apply to industrial systems and to their transformation-production cycles the same rules and principles governing the functioning of non-human biological systems that are the ecosystems, characterised by symbiotic relationships and by the absence of the idea of waste: each waste product is put back into the system, to produce energy or as a raw material, in order to start a process essential to maintain a global balance.

According to Allenby’s scheme [4], traditional industry follows a linear process: the consumption of energy and materials to produce goods and services generates a significant amount of waste (Figure 2). Such a system could operate in a sustainable manner only if the resources fed and the space to dispose of the waste are unlimited.

Figure 2. Traditional industry.

An ecological system, by contrast, is characterised by the right combination between dynamic balance and closed loop, Figure 3. In a dynamic balance, energy and waste are constantly recycled and reused by other organisms and processes within the system. In a perfect closed-loop system, only solar energy (or other renewable energy sources) should come from the outside, while all by-products should be constantly reused or recycled. Nevertheless, a total cycle closure cannot be achieved at the level of eco-districts, because at least the final products have to be released outside the system. This model brings about also the mutual dependence between the various parts of the system, along with problems and advantages connected to it.

Figure 3. Ecological system.

Figure 4. Eco-industrial parks.


Therefore the goal to be pursued is a limited use of inputs (virgin resources and materials), a limited amount of waste discharged from the system and, above all, a collaboration between the various components of the industrial ecosystem through the exchange of energy and materials, Figure 4. This model goes beyond the principle of “product stewardship”, as it also takes into account the whole process, along with its waste, and it requires business cooperation, both vertical and horizontal.

There are therefore two possible approaches:

1. the creation of symbiotic production processes with regard to material flow (energy, heat, water, waste, emissions, people, goods…), whose aims of efficiency and effectiveness in the use of materials and energy are the basis of business cooperation;

2. the planning of services and infrastructures within the industrial parks applying the principles of environmental sustainability and closed-loop natural cycles. Consequently, the main requirements for service sharing and for a successful industrial

symbiosis are the following: • complementary needs as far as material/energy are concerned; • physical proximity in order to implement cascade systems of energy and water

supply and to cut transport costs; • presence of a homogeneous service demand in order to obtain economies of scale; • importance of personal relationships between the various enterprises, also by means

of associations. Industrial parks are important tools of economic and social qualification of an area but, at

the same time, they are potential sources of pressure on the environment and on surrounding communities.

1.3. Ecologically Equipped Industrial Areas The notion of industrial park as an eco-friendly place (as well as an area of economic and

urban development) has evolved in time and has led Italy to the construction of the so-called Ecologically Equipped Industrial Areas (in the year 1998). The Italian production system, organised into chains and districts, is characterised by a great flexibility and by the tendency to networking.

But as regards the environmental field, the Italian business sector, whose main feature is a high concentration of small and medium-sized enterprises, encounters a lot of difficulties in implementing preventive measures, due to a lack of culture in such issues.

Joint environmental management, dialogue with local authorities and business participation in the process are key elements in the enhancement of a new territorial governance framing and supporting a sustainable environmental policy on industrial areas. The Ecologically equipped industrial area may be regarded as a forum for environmental dialogue where all the stakeholders involved in its constitution, development and activities


share their experiences, their resources and their goals and perform partnership actions aimed at complying with regulations but, in broader terms, at meeting the environmental needs and expectations of the resident industries and the local communities. Through a joint management of shared infrastructures and services, planned in concert with the resident group of enterprises, it is possible to create economies of scale allowing the environmental issues to be settled with a reduction in cost. The introduction of Ecologically Equipped Industrial Areas should not be viewed by stakeholders (enterprises, local authorities) as an external constraint hindering economic development but rather as a tool for revitalizing the area and increasing the enterprises production system’s competitiveness. The aim of joint environmental management is to provide mutual benefits to industries, public authorities and local populations. The enterprise system is evolving and territories are being provided with policies and tools aimed at their strengthening. Industrial parks as well may take part in this change process, closely meeting businesses and citizens’ needs and becoming one of the most effective strategies toward growing territorial competitiveness from an economic, social and environmental point of view.

The introduction of this new concept of industrial area, provided with technical and organisational tools aiming to minimize and manage jointly the pressures on the environment, responds to the need to replace the so-called end of pipe approach (combating pollution as a last stage of the process) with the precautionary principle preventing pollution. In particular, it is not meant just to supply industries with specific environmental equipment, as it has been so far, but to organize the industrial site so as to help, from an economic and technical point of view, each enterprise in the area achieve their environmental goals, be they prescriptive or voluntary.

1.4. Generation of Industrial Waste in Europe

Manufacturing industry waste comprises many different waste streams arising from a

wide range of industrial processes. Some of the largest waste generating industrial sectors in Western and Central Europe include the production of basic metals, food, beverage and tobacco products, wood and wood products and paper and paper products [5].

It has been estimated that over 33 million tonnes of industrial waste were generated in Europe in 1998. Waste from the manufacturing sector continues to rise, despite national and international declarations to reduce waste from manufacturing industry, to introduce cleaner technologies and other waste minimisation initiatives and to work towards manufacturing practices that are sustainable in the long term.

The manufacturing industry has a central role to play in the prevention and reduction of waste as the products that they manufacture today become the wastes of tomorrow. Manufacturers can achieve innovative solutions:

• considering the impacts of their products throughout its life at the design stage of the product (LCA);

• using manufacturing processes that minimise material and energy usage; • eliminating or reducing where possible the use of substances or materials hazardous

to health or the environment; • manufacturing products in such a way that they last longer and may be recycled or

reused at the end-of-life stage.


EU and government policy across Europe is increasingly driven by the need to influence manufacturing practices in an effort to decrease the environmental impact of products during their manufacture, use and end-of-life.

The EU Strategy for Sustainable development emphasises the strategic target to break the link between economic growth, the use of resources, and the generation of waste.

Therefore natural resources and wastes is one of four key environmental priorities described in the 6th European Action Programme. The objective is to decrease the amount of waste generated and to achieve a relative decoupling between economic growth and generation of waste.

Europe aims to reduce the final amount of waste by 20% by the year 2010 and by 50% by the year 2050.

Figure 5 shows the amounts of manufacturing waste generated in nine Western European (WE) countries and seven Central and Eastern European (CEE) countries [6]. From 1996 to 2002 the generation of waste in the manufacturing sector increased by 15% in WE (from 123 Mtonnes to 141 Mtonnes) and by 42% in CEE (from 60 Mtonnes to 86 Mtonnes).

Due to lack of proper time series data from the large countries UK, France and Spain are missing in the indicator. The three countries are responsible for about half of the manufacturing waste generation in WE. The few data available from the countries indicate a slight decrease in waste generation.

Figure 5. Manufacturing waste generation in Western Europe and Central Eastern Europe in Mtonnes.

Figure 6 depicts generation of manufacturing waste held against the gross value added in

the manufacturing sector in the years 1996 to 2002 in the 13 European countries for which data are available. The gross value added by the manufacturing sector is steadily rising in the period (6%), but not as much as the generation of manufacturing waste (24%).


Figure 6. Manufacturing waste generation in Europe compared to gross value in the manufacturing sector.

This means that overall objective of decoupling waste generation in Europe from

economic development has failed as regards manufacturing waste. The European manufacturing sector is very diverse and the individual countries have had very different trends in the period analysed. The growth at European level can mainly be explained by the massively rising waste amounts in the three countries Italy, Netherlands and Poland, while most other countries have stagnating or even falling waste amounts.

Figure 7 shows the national differences in manufacturing waste generation per capita as well as the temporal trends for 1996-2002 for a range of European countries. In nine countries a declining or steady trend can be observed, while seven countries have increasing amounts of manufacturing waste per capita. The manufacturing waste generation per capita is generally higher in the CEE countries (1000 kg per capita) than WE countries (ca. 700 kg per capita). Finland has a very high manufacturing waste generation per capita. However, Figure 7 does not reveal the reasons for the observed trends and distributions, and establishing causal relations to driving forces are beyond the scope of the indicator framework.

Theoretically, a given level of generation per capita could be explained by two factors:

1. the reliance of a country on the manufacturing sector (measured, e.g., as the share of the sector in the total economy);

2. the resource efficiency of the manufacturing sector and the structure of the manufacturing sector. The above figure shows how important it is to also be aware of the trends inside the

countries since this varies a lot and perhaps shows how the resource efficiency varies and changes within the countries.


Figure 7. Trends in generation of manufacturing waste per capita.

Figure 8 shows the manufacturing waste generated per gross value added1 in the

manufacturing sector.

Figure 8. Trends in manufacturing waste generation per gross value added in the manufacturing sector.

1 In national accounts such as the United Nations System of National Accounts (UNSNA) or the NIPA’s, gross

value added is obtained by deducting intermediate consumption from gross output. Thus gross value added is equal to net output. (http://en.wikipedia.org/wiki/Value_added)


It can be seen that relatively small decoupling is seen in Belgium, Denmark and Germany while the waste intensity in the CEE countries (871 tonnes per million USD) are many times higher than the WE countries (129 tonnes per million USD). Romania, Poland and Slovakia have the highest waste intensity while Iceland, Norway and Denmark have the lowest. There is a falling tendency in five countries while the waste intensity is increasing in five other countries.

Manufacturing waste is typically heterogeneous and with differentiated range of potential impact on the environment. Although different wastes cause different environmental impact potential, there is also a quantitative aspect as more waste means potentially higher pressure on the environment.

The industrial structure, in terms of the prevailing sectors and branches, is an important factor for the amount and the kinds of waste generated, some sectors being the source of large quantities of hazardous waste with high environmental impacts. Waste also represents a loss of resources both in the form of materials and energy. Indeed, quantities of manufacturing waste can be seen as an indicator of the material efficiency of the manufacturing sector.

Excessive quantities of waste result directly from a large industrial production and inefficient production processes. Indirectly it reflects low durability of goods and unsustainable consumption patterns leading to high demand for manufacturing products and thereby potentially high waste quantities. Waste minimisation in manufacturing production processes is an increasingly important objective of manufacturing environmental strategies also in the framework of environmental certification. Different countries and industrial sectors are differently positioned in the process of optimising resource use, factory-level waste minimisation and the adoption of certification instruments.

2. THE MAIN FINAL THERMAL TREATMENTS OF WASTE The thermal treatment which takes out energy from waste includes also combustion and

gasification processes. Combustion and gasification technologies of alternative fuels, like bio-mass, fuels from wastes and from other types of industrial wastes, are gaining importance. The energy conversion technologies are increasingly constrained by environmental regulations on regional, national and international level. So it is necessary to move towards advanced technologies like gasification systems in combined cycles.

Combustion and gasification processes of non-conventional solid fuels increasingly require the integration of different skills, due to the high variability of physicochemical parameters of the initial fuels. The nature of fuels influences choices in the processes and systems. The complicated fluid-dynamic behaviour of multiphase systems is another factor of influence [7]. So, when analysing the thermo treatment processes with energy recovery from solid urban wastes and industrial wastes it is necessary to look for their environmental and energetic performances.

The three technologies analyzed in this chapter are: a waste to energy plant of the latest generation, a molecular dissociator and a gasifier licensed in Italy. The three of them aim to dispose of every kind of waste, at the same time producing electricity and/or thermal energy but in different ways and with different results.


2.1. Waste to Energy Plant – System a Although the traditional waste to energy plant uses a more obsolete technology, studying

it helps to understand evolution and innovations in energy efficiency occurred in the last few years [8].The primary purpose of waste to energy plants, also called incinerators (waste burning plants) with energy recovery, is to burn waste (at 900°–1000°C) and make it biologically and chemically inert, by reducing its volume, with a great advantage that is the production of electricity and thermal energy. The heat produced by the combustion, generates steam which is used for energy production and for the heating [9].

Municipal waste incineration is a controlled combustion process which oxidizes the organic substances contained in waste, producing simple molecules in a gaseous state at standard temperature (gas): organic carbon is oxidized to carbon dioxide (CO2), hydrogen to water (H2O) and sulphur to sulphur dioxide (SO2); generally the inorganic part of the waste is not subject to reactions and becomes a solid waste to be disposed of and/or to be recovered (ash or slag). Also unpleasant chemical transformations take place, such as the creation of nitrogen oxide (NO), hydrochloric acid and hydrofluoric acid, which toxic characteristics.

The cycle of wastes combustion is divided into the following phases: • acceptance and storage; • feeding; • combustion; • cooling of combustion smokes and warmth recovery; • treatment of combustion rests: ashes, smokes, slags, waste waters. Waste combustion phase is performed in furnaces and it involves three phases: drying,

starting and combustion. In order to meet various needs, several kinds of furnaces have been introduced: moving grid, fluid bed and rotary drum. During combustion the smokes come out at a temperature of 1000°C, so it is necessary an intermediate phase of cooling in a combustion section and the extraction of heat from the smokes. But these smokes embed pollution elements. It is possible to treat these smokes. Polluting gas control equipment can be performed by mixing smokes with chemical elements (solids, liquids or gas) able to remove one or more polluting components. Often the absorption process on solids are used, like active carbon.

Another problem of wastes incineration is due to solid residual products and to their impact on the environment. The incinerators produce two kinds of solid wastes: slags discharged by furnaces, and fine particles (flying ash mixed to smoke) seized by smoke treatment. It is difficult to manage them because they embed large quantities of toxic compounds, like heavy metals and organ chlorinated compounds easily released in the environment through percolation.

2.2. Molecule Dissociation – System b The molecular dissociation process includes the thermo chemical conversion of a carbon-

composite into a burning gas [10].


Briefly, the process consists in a chemical splitting up of complex organic molecules into simpler ones through thermal gasification at low temperature (T = 400°–500°C) performed in controlled conditions of warmth and oxygen availability (max. 3–4% of O2) inside a locked cell. Here, carbon chemical links are broken and simpler molecules take origin, thanks to warmth effect during starting phases of fuel use (i.e., methane gas). The process is very slow and the whole cycle lasts 24 hours; furthermore, the reduced turbulence and the flames absence lessen the powder presence in smokes. After breakdown, carbon matrix changes from a solid condition into a gas one, by producing a synthesized gas (syngas) with good combustible characteristics. The synthetic gas after depuration stage can be burnt in the presence of air (T≈1100°C) in a following stage, where there are thermodynamic cycles, like co-generator cycle. The systems can use several thermodynamic cycles, consequently they are more flexible in regulation between heat and electricity production. The remaining waste is composed of ash, inert and non toxic, and it can be disposed of in a dump or used for tiles construction or mixed with asphalt.

2.3. Gasifier Licensed in Italy – System c A gasifier with a new technology was licensed in Italy. It is different from the traditional

gasifier and the molecular dissociation thanks to the gasification reactor and to different conditions of management and control.

Gasification is a chemical decomposition produced by thermal energy. Without a surplus of air and oxygen, gasification produces thermo chemical decomposition of waste’s organic matter and change this matter into syngas [11].

The system which produces the above-mentioned process involves a lot of sections, that can be listed according to their functions:

• materials preparation section: this involves the storage building and machinery

where wastes are treated and stored (raw materials for the plant) in order to make their size suitable for feeding the reactor where the gasification process takes place. These treatments are usually meant to transform the waste into waste fuels (dry and crushed municipal solid waste).

• gasification section: this is the technological heart of the system. Thanks to the technology licensed in Italy, a specific reactor has been designed (with new characteristics), with vertical development, descending flow and best temperature of process at 1200°C. The waste is fed at the top of reactor and by falling down from top to bottom (as a fluid bed) is covered by flames come out from thermic lances which are tangentially in reactor. These lances produce high turbulences which create an immediate gasification. Thermic lances fed by pure methane and oxygen characterize this process which grant high ecological and energetic results. Another peculiarity of this reactor is that it can be fed continuously, wih all the wastes categories independently from their calorific value and chemical composition.

• energy generation section: it is the final step where the syngas is used. Nowadays the groups with endothermic/alternator engine are more used thanks to their high electric (about 38% compared to the fuel input) and global efficiency. Thermal recovery


takes place during the cooling cycle (engine side, smoke side and oil engine side) of the machine. This brings to total efficiency even higher than 80/90%. The temperature of the thermal energy recovery is about 80°C in case of water use, or 6–8 bar of pressure in case of steam production.

The solid wastes of gasification are transformed into glass, thanks to high temperatures,

and are completely inert.

2.4. Comparison among Systems for Waste Disposal with Energy Recovery It is necessary to point out which is the most efficient technology from an environmental

and an energetic point of view. This comparison considers the following aspects: • structure-process; • performance; • environmental impact. From the structural-processing point of view, system a (waste to energy plant described

on paragraph 2.1 and here called system a) reduces waste in ash, by using again combustion smokes to produce electric and/or thermal energy, whereas system b (dissociator, described in paragraph 2.2 and here called system b) and system c (gasifier, described in paragraph 2.3 and here called system c) transform (in different ways) the raw material into a synthetic gas used then as a fuel.

The main body of system a is the furnace of combustion, in system b is the cell and in system c is mono-tube reactor with vertical development, the last two produce syngas. Another important aspect is the very high chimney for system a compared to the chimney a few meters high for system b.

Despite the fact that the final product is the same, there are a lot of differences between b and c systems: the main body of the system, the working temperature, the procedures and the scheme for syngas production.

System b works at about 400°C, in presence of oxygen at 4–5%, so the raw material transformation is exothermic; so it only triggers the reaction with a moderate electric resistance (200-300kW per 100 t/g of waste).

System c has a different mechanism. Its reactor has a variable thermic profile (optimum temperature at 1200°C). The waste falls down in the reactor from top to bottom, and it is burnt by flames generated by thermic lances which are fed with methane and oxygen. This lets the process be controlled, independently from changes of waste calorific value, but with unavoidable economic consequences (262 m3/h of methane and 560 m3/hof oxygen per 3 t/h of input waste are necessary).

System b has a lower self-consumption (less than 2%) and it can treat any kind of waste without a pre-treatment. Furthermore, both the gasification technologies dimensions fill a minimum space, and have a modular process; system a does not present these advantages. The energetic results depend on the choice of the system for the production of electric and/or thermic energy. Analysis results, listed in Figure 9, show how syngas brings higher


efficiencies. Moreover, system b produces very low percentages of inert ashes, about the 3–4%, compared to 30% of toxic wastes produced by system a.

For systems b and c it’s important to emphasize the conversion energetic efficiency, that is 0.98 for the first and 0.68 for the latter, and also the percentage composition of syngas, (see Figure 10).

System c offers a cleaner gas compared to system b, with high concentrations of hydrogen and carbon monoxide, and low percentage of nitrogen and negligible sulphur compounds.

Figure 9. Energy efficiencies (expressed in percent) of system a and b.

Figure 10. Percentage composition of syngas.

Despite the sophisticated instruments for the reduction of smokes, from an environmental point of view, the smokes of system a present organic material deriving from uncompleted combustion or thermic synthesis reaction. Systems b and c generate syngas in good conditions, so they do not give rise to hazardous dioxins and furans. Experimental data demonstrate that emissions to atmosphere generated by the combustion of the synthetised gas of system b and c are lower than emissions produced by system a, especially when it comes to sulphur, nitrogen and chlorine compounds.


3. ENVIRONMENTAL AND ECONOMIC ASSESSMENT METHODS In the industrial areas analysis, the relationship between industry and its local

environment misses a main dimension of sustainable development: the environmental protection, that is the connection between products and pollution phenomena linked to them.

The main purpose of a sustainable development consists in granting a high quality level of life to all people, by taking less natural resources and using them as efficiently as possible. In other words the energetic resources management needs measures and means related to industrial systems eco-efficiency.

The environmental and economic assessment methods let the industries analyse the environmental matters considering not only the production but also the resources that is possible to re-use and save (energy, materials, water, natural resources).

The decision-taking processes in the environmental field depend on the purposes to be attained, as those purposes determine the demands which to answer to, the actions to undertake and the analytical and procedural means to use [12].

A large number of instruments have been created as methodological aid for strategies and techniques of environmental management. The choice of the most appropriate instrument depends first of all on the object to be studied, on the purpose of decision process, the space and time context of the project, the available information about environment impacts, and on the doubts about costs and benefits. Anyway, a unique method to establish the most appropriate instrument does not exist, therefore often multiple instruments with the same technical aids and the same information are used in an integrated way. Life Cycle Assessment and Cost Benefit Analysis (CBA) are the major instruments, which emphasise environmental and socio-economic aspects in order to make the best choice.

3.1. Life Cycle Assessment Life cycle assessment (LCA) is the broadest indicator and an internationally standardized

method (ISO 14040 and ISO 14044). It not only evaluates the impact on climate change, but also other impact categories such as acidification potential, eutrophication potential, ozone depletion potential, and ground level ozone creation. For each of these impact categories, the product or system is evaluated over its complete life span, from the extraction of raw material and manufacturing, to the use of the product by final consumers and end-of-life processes like recycling, energy recovery, and ultimate waste disposal. The ISO standards provide robust and practice-proven requirements for performing transparent LCA calculations. Moreover, one can make use of extensive databases containing life cycle profiles of many goods and services, as well as many of the underlying materials, energy resources, transport systems, etc. Nevertheless, LCA calculations remain very complex [13].

In order to achieve the established purposes in a transparent and comprehensible way, it is necessary to take into consideration and describe the following elements:

• The function unit: measurement of input and output flow of the product system; • The product system: an ensemble of processes linked by flows of matter, energy,

wastes;


• The system’s borders: selection of productive processes and environments; • High quality and reliability of data (data bank, temporal, geographic and

technological coverage). The inventory analyse involves the construction of reality analogical model. First of all

the flow-chart including the product system’s processes is necessary [14]. Consequently, the second step is data collection, that is direct surveys, estimations, medium values or values from literature and data bank. The inventory aim is to get objective data, which, later on, would be processed in order to take useful assessments for an improvement of processes analyse (see Figure 11).

The environmental and energetic allocation could be carried out as: • physical quantity, such as mass, volume and energy; • economic values of the products. The results are estimated and associated under their effects on the environment, such as

greenhouse gas effect or stratospheric ozone deletion. Environmental effects can be on global, regional, local scale: for example GHG effect has global effects, while a noise has local effects.

Figure 11. Inventory analysis.


Nowadays in life cycle analyses the main impact categories are: • greenhouse effect; • stratospheric ozone deletion; • acidification; • eutrophication; • photochemical oxidant formation; • human and environment toxicity; The environmental impacts quantification is performed in the phase of distinction thanks

to scientific models and correspondence’s factors, on an international level (i.e., greenhouse effect follows global warming potential, that is, the equivalent CO2 quantity). To synthesize the analysis and compare it with more productive systems, it is necessary to make the data normal (i.e., to estimate the pro-capite environmental charge) and to carry out a weighing in order to get a single index of impact. In the last phase of LCA, that is the interpretation, the results of inventory analysis are correlated with those ones of impacts analysis, to propose better measures for a reduction of environmental charges.

Life cycle assessment is used for more aims: processes’ improvement, products innovation under new standards of production, assessment of carbon footprint, progress of environmental policy strategies.

On a planning and organizing level it is very hard to reach a production improvement, which consists in choosing the solutions to be applied to productive system and suitable to maximize the global environmental energetic efficiency.

LCA application does not always guarantee a reduction of energy consumption or emissions, but it allows people to evaluate a service or a product in a total way, in order to avoid a wrong interpretation, i.e. an improving intervention that moves a problem from the analysed area to another one.

3.2. Cost Benefit Analysis CBA CBA is one of the most popular method for investment assessment, especially when they

refer to support measures on territory; it chooses the best proposal, or, in case the proposal is only one, it verifies the project costs, that should be lower than the benefits, in order to improve the general social and economic welfare of the project context [15].

CBA is divided into three phases:

1. identification of all positive and negative effects of the project. The negative effects involve: water consumption, wastes production, etc. The positive effects could be: employment, water availability for civil agricultural or industrial use, the creation of a green area or a system for waste water conditioning.

2. quantification of effects from the previous phase. The costs and the benefits of a project are expressed in monetary terms, while the other effects are expressed in their own measure units (jobs number, decibel of produced noise, etc.).


3. interpretation in monetary terms of all the effects measured in quantification phase. There are direct financial costs and benefits (expenses and revenues of project) and indirect economical ones (damages and benefits caused by project to other activities). CBA must pay attention to the beneficiary of project benefits, and to the supporters of

direct and indirect costs. When the best project is chosen an ongoing process is established, and it involves more phases, including identification and assessment which are the most important. Identification means to consider demographic, social, cultural and economic aspect of social groups.

It is important to include stakeholders in decisional process as they could be stimulated through offsetting measures.

To let the changes in life and habits be accepted, it is important to give population a right information about benefits project, and to establish an active cooperation between population and public decision-maker (particularly regarding rural population); furthermore, identification must show eventual project damages on environment, and suggest some ways to reduce them (external effects).

The more the identification reaches a high and complete level of information, the less the decision-makers have the possibility to discuss faults. The identification phase requires a lot of time in order to avoid errors, as they are expensive and resources are very few.

After realizing the project, benefits could be:

(a) transitory – they can be carried out only during project realization; (b) lasting – linked to the entire life of the project. These lasting benefits are direct, when

they give advantages to receivers, and indirect, when they are in favour of the community;

(c) concrete – they can be quantified; (d) intangible – of intangible quantification.

And costs can be divided into:

(a) monetary – supported directly by public administration and related to complete realization of project, its maintenance and management;

(b) social – supported by community. They are primary if they refer to projects’ costs that the community supports by renouncing other alternative projects; or secondary if they refer to external effects on people or things, but they have no influence on the market.

4. CASE STUDY The examined case study is an industry leader in the world for production of polyester

nonwovens with high toughness by continuing thread and flake. The firm produces an industrial fabric that is a supporter for bituminous membranes destined to waterproofing of roads and roofs, as PET bottle after use. This firm is located in the south of Italy within a technological park that is managed by a company that provides services for the firms in the


industrial area, such as electric and thermal energy, technical gas (i.e., steam overheated) and industrial water, with advantageous conditions for the industries, and also sustains the territory industrialization by giving services and utilities similar to the most industrialized areas of the country. Furthermore, it treats the waste of the industrial activities of the industrial area, and also waste coming from activities of regional and extra-regional territories with specific authorization codes (EWC European Waste Catalogue).

The firm in this case study is a partner of the manager company and purchases from it steam, water and electric energy. Before the final discharge, it sends the wastes to the treatment plant [16][17].

The industrial process of nonwovens production is divided into the following phases: • bottle washing and flake production: from plastic bottles PET material is selected and

sent to a washing centre and then to the mill to be reduced into little pieces; at the end bottles are centrifugated to set apart the water, and sent to a washing section. The obtained product is called flake.

• polyester drying-up and extrusion by forming threads set in a random way on a sucked carpet: flakes are heated until they become crystals, then they are dried and extrapolated. After extrusion, the melted polymer gives rise to a film;

• mechanical binding process (needlepunch technology); • glass thread inclusion between the two films and further mechanical binding; • thermo-fixture and longitudinal cut, and consequent selvedge production; • thermal consolidation and product incorporation in resins. To summarize, the analysis of life cycle defines the functional unit as 1 m2 of fixed and

reinforced nonwoven, and considers one year’s time for the system and the process. In the following inventory analysis, data are collected, measure units are converted, and

data refer to their functional unit, as shown in Figure 12. The diagram in Figure 12 summarizes resources, energy consumption, all emissions (to

air, water and ground) and production of waste. Thanks to software, it has been possible to assess the impacts on the environment (i.e.,

CO2eq, CH4, SOX e PM10, COD, BOD and solids). Industrial waste referred to in the considered firm are divided into two categories: • waste products: these are not dumped, but used again in the production cycle or sold

for other purposes (polymer badge, nonmelted selvedges, melted selvedges, felts, roll line starts);

• wastes of various origin (residues of the washing system, iron waste, wood waste, paper, some oils, etc.)

For an economic-environmental assessment, it is necessary to incorporate the system

analysis with a cost/benefit analysis by emphasising emissions and energy savings. If the analysis is extended to the whole area where the firm is located, the processes of all

the productive activities have to be analysed in order to find the the best area for fuel co-production.


Figure 12. Flow diagram of nonwoven production.

To carry out an energy system from wastes in an industrial park, it is necessary: • to verify the area and examine the physicochemical characteristics of the wastes; • to find out the critical elements of the system; • to study the draw-plate for waste treatment after production and their technologies; • to make a hypothesis about the logistics of the waste collection; • to give the system dimensions; • to assess possible environmental effects in the neighbouring area (air quality; impacts

on territory, on noise, on waters, on ground, etc.) • to emphasize relief and reward measures of impacts, both environmental and social; • to study the economic/financial feasibility and analyse the economic new effects in

the industrial area.


The main benefits of this system are to close the waste cycle at local level, and to use energetic and economic benefits from waste use for energy purposes. Furthermore the disposal of wastes at a local level means a reduction of costs, as otherwise transport costs, eco-tax and local duties must be introduced.

CONCLUSION Because of the continuing increase in population, the resources of our natural

environment are limited: most of the materials we use to create products come from natural sources, and several production systems stil require virgin products rather than recycled ones..

To overcome the crisis of waste management, it is necessary to introduce a Zero Waste strategy. This consideration involves rejecting the whole notion of waste, and moves the problem towards the starting point of an industrial eco-system [18].

The traditional industrial system is based on a unique direction: take-transform-dump Materials are taken from the earth’s crust, moved to firm, used to produce finished goods and waste, destined to the disposal or waste to energy plant. Extraction, production, transport, and removal of resources are causes of environmental destruction and global heating.

It is necessary to revise the unidirectional industrial system and form a closed circular one by recycling the resources dumped from community to industries. The economic and social system must know that the circular course of nature is the most efficient, less expensive and more profitable, and avoids the environment’s deterioration.

In the end, it is important to integrate the responsibilities of community, industry and government in order to make a zero wastes strategy feasible.

REFERENCES

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Lowe, E. (1997). Creating by-product resource exchanges: strategies for eco-industrial parks. J.Cleaner Prod., vol. 5, n. 1-2.

Lowe, E. (2001). Eco-industrial Park Handbook for Asian Developing Countries. A Report to Asian Development Bank, Environment Department. Oakland,CA: Indigo Development.

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degli Studi di Catania, Materiale didattico a sostegno del corso di Complementi di Impianti Termotecnica, in Italian.

Arena, U. and Mastellone, L. (1998). Centrali di termovalorizzazione di rifiuti solidi urbani. La Termotecnica, 48 (1), in Italian.

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INDEX

A

absorption, 49, 299 access, 236 accuracy, 37, 49, 93, 181 acetate, 15, 44, 64 acetic acid, 13, 19, 25, 43, 45, 71, 112, 192 acid, ix, 12, 13, 19, 20, 24, 25, 29, 30, 31, 43, 45, 50,

52, 61, 70, 71, 97, 101, 103, 105, 106, 107, 110, 111, 112, 113, 114, 115, 117, 118, 119, 120, 122, 123, 124, 126, 128, 134, 139, 172, 192, 211, 299

acidic, 19, 25, 29, 31, 113, 193 acidification, 246, 247, 303, 305 acidity, 19, 25 activated carbon, 193, 209 activation, 193, 209 acute, 9 additives, 60, 120, 123 adhesives, 100, 108, 123 adiabatic, 217, 254 administration, 306 administrative, 4 adsorption, 32, 49 aerobic, x, 3, 7, 8, 9, 10, 11, 19, 20, 21, 24, 31, 37,

41, 44, 54, 58, 59, 60, 62, 63, 65, 67, 70, 189, 204, 213, 215

aerobic bacteria, 24 aerosols, 261 affect, 242 Africa, 246 age, 13, 33, 42, 62 agent, 112, 119, 120 agents, 257 agricultural, 59, 60, 99, 100, 103, 106, 136, 210, 305 agricultural crop, 100 agricultural residue, 106 agriculture, 99, 103, 105, 139, 188 agroindustrial, 106

aid, 160, 164, 181, 209, 303 air, vii, x, 1, 3, 4, 5, 7, 9, 10, 11, 12, 13, 19, 21, 26,

27, 31, 32, 33, 34, 35, 36, 37, 46, 49, 50, 54, 55, 57, 58, 59, 60, 70, 120, 122, 124, 133, 156, 173, 175, 177, 191, 195, 202, 205, 206, 207, 217, 219, 220, 253, 254, 255, 256, 257, 258, 259, 260, 271, 280, 287, 288, 300, 307, 308

air emissions, 4 air pollutants, 11, 32 air pollution, 191, 206 air quality, xi, 3, 5, 47, 120, 253, 287, 308 Alberta, 1, 58 alcohol, 50, 51, 100, 105, 114, 117, 119, 210 alcohols, 110, 112, 114, 119, 199 aldehydes, 114 alfalfa, 106 algae, 105, 138 alkali, 112, 196, 210 alkaline, 112, 116, 118, 120, 124, 129, 196, 201 alkaline earth metals, 201 alkalinity, 29, 61 alkanes, 101 alternative, viii, x, xi, 31, 51, 97, 98, 100, 114, 122,

199, 203, 213, 215, 240, 253, 254, 287, 290, 298, 306

alternative energy, 199 alternatives, viii, 41, 51, 97, 98, 111, 122 aluminium, 60, 260 ambient air, 35, 36, 37, 49 amendments, 7 amine, 112 amino, 103, 106 amino acids, 106 ammonia, 14, 19, 34, 35, 36, 70, 110, 112, 210, 212 ammonium, 8, 19, 25 Amsterdam, 228 anaerobes, 8, 19, 71 anaerobic, vii, x, 1, 3, 7, 8, 10, 11, 12, 13, 14, 19, 20,

21, 22, 24, 27, 29, 30, 31, 34, 41, 43, 44, 54, 56,

Index 312

57, 58, 59, 60, 61, 65, 70, 71, 75, 76, 108, 110, 111, 116, 119, 129, 138, 187, 189, 190, 194, 203, 204, 205, 206, 207, 208, 209, 211, 213, 215, 222, 225, 226, 227

anaerobic bacteria, 8, 24, 71 anaerobic digesters, 203 anaerobic sludge, 29 analysis of variance, x, 253 animals, 36, 231 anomalous, 281 ANOVA, x, 253, 263, 264, 265, 266, 270, 274, 275,

279, 281, 282, 284, 285 anoxic, 194 anthracene, 199 anthropogenic, vii, 1, 2, 14 API, 173 application, viii, ix, 62, 69, 72, 76, 81, 82, 83, 88, 93,

94, 108, 110, 125, 128, 129, 130, 136, 142, 155, 165, 172, 175, 182, 185, 196, 203, 206, 208, 210, 214, 222, 227, 256, 258, 287, 288, 305

aqueous solution, 115 aquifers, 54 Arabia, 141 archaea, 203 argument, 183 arid, 105 Army, 72, 75, 94 Army Corps of Engineers, 94 ash, 29, 191, 192, 194, 195, 211, 217, 299, 300, 301 Asia, 290 Asian, 61, 309 Aspergillus niger, 139 asphalt, 300 assessment, 37, 103, 115, 122, 134, 136, 203, 211,

246, 249, 251, 290, 303, 305, 306, 307 assignment, 242 assumptions, 3, 15, 37, 77, 189, 222, 246, 248 ASTM, 61, 63, 76 atmosphere, vii, 1, 14, 23, 24, 26, 27, 47, 48, 86, 92,

93, 102, 118, 122, 199, 200, 205, 207, 230, 235, 254, 302

atmospheric pressure, 12, 27 attacks, 173 attention, 72, 230 attractiveness, 234 Australia, 288 Austria, 97, 134, 135, 238 availability, viii, 2, 19, 28, 71, 77, 85, 97, 98, 135,

137, 214, 246, 300, 305 avoidance, 185, 215 awareness, ix, 187, 214

B

bacteria, vii, 1, 8, 14, 20, 21, 23, 24, 25, 28, 29, 30, 31, 37, 43, 44, 54, 55, 59, 71, 118, 203, 222

bacterial, 22, 36, 37, 53, 72, 75, 110, 203, 256 barrier, 31, 47 barriers, 7, 31, 47, 241 base case, 174, 175, 177, 180 batteries, 255 battery, 264, 267 behavior, 45, 63 behaviours, viii, 69, 73, 79, 285 Beijing, 136, 288 Belarus, 246 Belgium, 65, 135, 238, 249, 298 beneficial effect, 87 benefits, ix, xi, 7, 10, 40, 54, 90, 98, 100, 102, 119,

122, 124, 125, 129, 138, 160, 211, 227, 244, 289, 291, 294, 303, 305, 306, 309

benign, 199 benzene, 13, 15, 34, 35, 119, 124, 196 beverages, 41, 42 binding, 307 bioconversion, 137 biodegradability, viii, 15, 69, 77, 78, 87, 222 biodegradable, vii, viii, x, 2, 4, 5, 16, 21, 22, 46, 56,

60, 69, 70, 71, 72, 73, 77, 78, 79, 81, 101, 110, 213, 215, 222, 229, 236, 244

biodegradable wastes, 2, 16, 70 biodegradation, viii, 7, 8, 10, 16, 21, 23, 24, 25, 26,

28, 29, 30, 31, 43, 44, 45, 53, 56, 58, 60, 61, 62, 69, 72, 73, 77, 78, 79, 80, 81, 82, 83, 87, 90, 93, 203

biodiesel, 100, 101, 105, 111, 114, 134, 137, 138, 139

biodiversity, 103, 247 bioethanol, ix, 97, 99, 100, 101, 104, 107, 112, 115,

116, 118, 119, 120, 123, 125, 126, 130, 131, 132, 133

biofuel, 100, 101, 110, 112, 120, 121, 134, 232, 248 biofuels, ix, 97, 98, 99, 100, 101, 102, 103, 106, 107,

108, 109, 114, 115, 119, 120, 122, 123, 124, 125, 127, 128, 131, 133, 138

biogas, x, 8, 16, 43, 44, 55, 61, 66, 95, 100, 106, 108, 110, 111, 118, 119, 120, 134, 203, 204, 213, 215, 222, 223, 225, 236, 244

Biogas, v, 1, 62, 65, 95, 111, 136, 205 biological activity, 16, 28 biological processes, 2, 34, 65, 70, 222 biological systems, 292 biomass, ix, 43, 44, 45, 54, 97, 98, 99, 100, 101, 102,

103, 104, 106, 107, 108, 109, 110, 111, 112, 114, 115, 116, 118, 119, 122, 124, 127, 130, 131, 133,

Index 313

134, 135, 136, 137, 138, 139, 188, 189, 191, 192, 193, 195, 196, 198, 199, 200, 203, 206, 207, 208, 209, 210, 211, 212, 227, 228, 233, 243, 244, 246, 248, 249

biomass growth, 45 biomaterials, 100 bioreactor, 2, 3, 7, 8, 9, 10, 11, 28, 29, 30, 54, 56, 57,

58, 59, 61, 63, 64, 94 Bioreactor, 6, 7, 8, 9, 10, 11, 65 bioreactors, 7, 10, 11, 29, 30, 53, 54, 56, 58, 59, 61,

62, 65, 94 biorefinery, ix, 97, 98, 99, 100, 101, 102, 103, 104,

106, 107, 108, 109, 110, 111, 115, 116, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 136, 137

biotechnology, 137 bisphenol, 123 body temperature, 77 boilers, 49, 50, 51, 53, 141, 185, 193, 231, 234, 242,

243 boiling, 180 bonds, 214 boreholes, 33, 58 bottleneck, 124 Brazil, 2, 95, 100 breakdown, 24, 36, 107, 110, 300 breathing, 35, 36 Brussels, 62, 65, 135, 249 buffer, 29, 30, 31 building blocks, 98 buildings, 36, 47, 230 Bulgaria, 238, 246 burn, 191, 235, 299 burning, 38, 50, 51, 110, 172, 206, 299 butyric, 19, 24 by-products, 55, 103, 172, 185, 291, 292

C

cadmium, 194, 209 calcium, 21, 25, 196, 210 Canada, 1, 3, 54, 55, 58, 63, 65, 96, 135, 137, 187,

207 capital cost, 161, 165, 172, 184, 185, 206 caps, 46 carbohydrate, 192 carbohydrates, 19, 98, 103, 106 carbon, vii, 1, 3, 8, 11, 12, 13, 14, 19, 20, 24, 25, 33,

35, 37, 38, 39, 40, 41, 42, 43, 46, 49, 50, 51, 52, 53, 54, 55, 64, 66, 70, 71, 72, 77, 81, 86, 99, 102, 103, 104, 122, 126, 130, 139, 172, 193, 196, 197, 203, 206, 209, 211, 214, 219, 221, 226, 227, 232, 240, 242, 247, 299, 300, 302, 305

Carbon, 6, 12, 13, 14, 34, 35, 41, 66, 67, 71, 209, 216, 217, 242, 251

carbon dioxide, vii, 1, 3, 8, 11, 12, 13, 14, 19, 20, 24, 25, 33, 35, 37, 38, 43, 46, 49, 51, 52, 53, 54, 70, 71, 72, 77, 81, 86, 103, 172, 196, 197, 203, 232, 240, 242, 247, 299

carbon fixation, 122 carbon monoxide, 14, 50, 51, 70, 193, 196, 302 carbonization, 189 carboxyl, 113 carboxylic, 19, 119 carboxylic acids, 19 cardboard, 41, 42, 60, 78, 87, 88, 89, 216, 223 case study, 3, 95, 99, 115, 122, 134, 252, 306, 307 catalyst, 100, 112, 117, 196, 197, 199, 201, 210 category d, 240 cavities, 32 C-C, 192 CEE, 237, 240, 295, 296, 298 cell, 3, 15, 28, 30, 31, 45, 50, 52, 54, 56, 57, 58, 59,

60, 63, 71, 105, 135, 195, 300, 301 cell growth, 15 cellulose, 15, 22, 99, 100, 102, 103, 106, 107, 111,

112, 113, 117, 118, 130, 135, 192, 193, 209, 210, 212

Cellulose, 106, 107, 109, 210 cellulosic, 101 cement, 47, 60, 108 Central Europe, 294 ceramic, x, 253, 257, 287, 288 CERCLA, 4, 6, 66 cereals, 106 certificate, 242, 244, 248, 251 certification, 298 CH3COOH, 71 CH4, vii, viii, 1, 2, 3, 8, 13, 15, 16, 21, 37, 39, 41,

42, 53, 66, 70, 79, 81, 110, 111, 112, 118, 119, 126, 127, 128, 129, 192, 193, 195, 221, 223, 307

chain molecules, 214 charcoal, 101, 110, 192, 196 chemical composition, 42, 43, 77, 78, 300 chemical industry, 119 chemical oxidation, 190 chemical properties, 16, 102, 109, 124 chemical reactions, 16, 23, 26, 52, 53, 105, 111, 114,

130, 134, 207, 214 chemical structures, 103, 123 chemicals, ix, 11, 32, 34, 50, 97, 98, 99, 101, 102,

106, 107, 108, 110, 111, 112, 116, 119, 123, 124, 125, 131, 133, 136, 193

China, 136, 288 chloride, 13, 15, 19, 37, 118, 209 Chloride, 25

Index 314

chlorinated hydrocarbons, 32 chlorine, 302 CHP, 128, 130, 160, 175, 233, 236, 237, 240, 241,

242, 243, 244, 247, 248, 249, 288 chromatography, 33 chromium, 209 Cincinnati, 209 circulation, 20, 54, 57, 173 citizens, 294 classes, ix, 20, 97, 102 classical, 255 classification, 246 clay, 23, 27, 47 Clean Air Act, 2, 3, 66 Clean Development Mechanism, 40, 66 Clean Water Act, 2, 3, 66 cleaning, 100, 112, 183, 184, 194, 206, 229, 231 cleanup, 51, 196 cleavage, 210 climate change, 247, 303 closed-loop, 292, 293 closure, 3, 4, 11, 13, 28, 33, 37, 39, 40, 70, 75, 92,

93, 292 clusters, 102 Co, 135, 138, 139, 199 CO2, vii, 1, 8, 13, 15, 16, 24, 25, 39, 66, 70, 79, 81,

86, 92, 93, 98, 102, 110, 111, 112, 116, 117, 118, 119, 120, 122, 126, 127, 128, 130, 131, 132, 133, 138, 172, 175, 192, 193, 195, 218, 220, 221, 222, 223, 224, 226, 227, 254, 299, 305

coal, 101, 129, 195, 198, 210, 236 coatings, 100 cobalt, 25 codes, 307 collaboration, 291, 293 collateral, 53 Colorado, 138 Columbia, 59 combustion, vii, x, 38, 47, 49, 50, 51, 52, 53, 70, 86,

92, 93, 101, 102, 110, 116, 118, 119, 121, 122, 127, 128, 130, 133, 135, 138, 172, 173, 188, 190, 192, 195, 202, 213, 214, 216, 217, 218, 219, 220, 224, 225, 226, 231, 235, 298, 299, 301, 302

combustion chamber, 217 combustion characteristics, 135 combustion processes, 172, 173 commodity, 114, 119, 126 common rule, 249 communication, 234, 310 communities, 36, 291, 293, 294 community, 36, 54, 98, 159, 306, 309 community support, 306 compaction, 19, 22, 26, 28, 30, 31, 32, 71, 72

competition, 25, 100, 105, 234, 241, 246 competitiveness, 294 compilation, 115 complex systems, 245 complexity, 3, 37, 93 compliance, 3, 4, 5 components, 12, 14, 17, 21, 22, 27, 32, 33, 51, 53,

55, 62, 65, 71, 72, 73, 79, 80, 81, 82, 83, 99, 100, 101, 102, 106, 108, 109, 111, 112, 124, 126, 192, 193, 196, 197, 245, 293, 299

composition, x, 3, 12, 14, 15, 16, 19, 20, 21, 22, 38, 39, 41, 42, 43, 44, 50, 53, 55, 57, 70, 71, 72, 77, 78, 79, 81, 87, 88, 89, 102, 103, 106, 108, 109, 111, 114, 116, 194, 209, 213, 214, 215, 216, 217, 218, 220, 222, 223, 240, 300, 302

compost, 54, 55, 59, 60 composting, 30, 31, 57, 60, 63, 231, 236 compounds, 13, 14, 16, 19, 25, 26, 49, 51, 64, 71, 72,

77, 100, 102, 103, 108, 110, 111, 112, 114, 115, 117, 119, 191, 196, 206, 212, 214, 219, 220, 221, 299, 302

Comprehensive Environmental Response, Compensation, and Liability Act, 4, 66

concentration, 13, 14, 16, 19, 20, 21, 24, 26, 29, 30, 31, 32, 33, 34, 35, 36, 38, 41, 44, 45, 47, 49, 89, 101, 160, 193, 199, 200, 204, 288, 293

concrete, 123, 165, 306 condensation, 32, 47, 256, 281 conditioning, vii, x, 52, 253, 254, 258, 287, 288, 305 confidence, 231 configuration, viii, xi, 58, 69, 84, 86, 93, 182, 196,

253, 255, 257, 260, 287 conflict, x, 229, 234, 235, 241, 243, 244, 247, 248 Congress, 228 Connecticut, 36 conservation, 87, 103, 172 consolidation, 307 constraints, 30, 85, 152, 153, 165, 167, 174 construction, 10, 27, 32, 42, 55, 60, 65, 91, 155, 188,

248, 288, 293, 300, 304 construction materials, 60 consumers, 241, 242, 243, 303 consumption, viii, ix, 97, 98, 103, 116, 118, 119,

122, 125, 134, 142, 157, 158, 172, 174, 175, 177, 183, 189, 192, 194, 198, 203, 217, 218, 225, 244, 247, 292, 297, 298, 301, 305, 307

consumption patterns, 298 contaminant, 63, 196 contaminants, 49, 51, 112 contamination, 2, 7, 53, 54, 60, 255, 257 context, 247 continuity, 285

Index 315

control, vii, 2, 3, 4, 5, 6, 7, 10, 28, 29, 30, 33, 37, 46, 47, 51, 54, 55, 62, 63, 64, 141, 165, 189, 191, 193, 195, 210, 249, 260, 299, 300

convection, 260 convective, 279 conversion, viii, ix, 7, 8, 13, 20, 24, 25, 51, 52, 53,

70, 71, 84, 85, 86, 87, 91, 92, 93, 94, 97, 98, 99, 101, 102, 103, 104, 106, 108, 110, 111, 112, 115, 116, 118, 120, 124, 126, 130, 133, 135, 137, 139, 160, 192, 195, 196, 199, 201, 209, 221, 223, 224, 242, 243, 244, 298, 299, 302

conversion rate, 7, 199 cooling, xi, 59, 147, 148, 151, 152, 153, 156, 157,

159, 163, 164, 165, 167, 172, 173, 175, 177, 181, 182, 219, 249, 253, 254, 255, 256, 257, 258, 262, 266, 267, 270, 271, 275, 279, 281, 285, 286, 287, 288, 299, 301

Copenhagen, 63, 64, 136, 137, 250 copper, 25, 209, 234 corn, 98, 99, 100, 103, 104, 109 correction factors, 40, 41 correlation, 42, 237, 239, 245, 247 correlation analysis, 42 corridors, 46 corrosion, 158, 233, 257 corrosive, 49, 51, 114, 193, 199 cost-benefit analysis, xi, 289, 290 cost-effective, 208 costs, 3, 11, 28, 49, 85, 86, 90, 91, 92, 153, 161, 188,

206, 214, 233, 235, 236, 241, 243, 247, 248, 254, 256, 293, 303, 305, 306, 309

Council of Ministers, 137 coupling, 227 covering, 5, 21, 23, 40, 46, 67, 92 Cp, 192 CPC, 164 cracking, 193, 196 CRC, 134, 211 critical temperature, 196 Croatia, 250 crop production, 246 crops, 99, 100, 101, 104, 105, 106, 108, 124, 139 cross-border, 241 crude oil, 101, 102, 111, 173, 183, 185, 199 crust, 309 crystals, 307 cultivation, 98, 118 culture, 293 customers, 133 cycles, 103, 221, 267, 292, 293, 298, 300 cycling, 53 Cyprus, 238, 246 Czech Republic, 191, 238, 240

D

dairy, 108 danger, 27 Darcy, 26 data collection, 304 database, 116, 125 death, 35, 36, 44 decay, viii, 3, 37, 39, 59, 69, 72, 75, 76 decibel, 305 decision makers, 175, 185 decision making, 230 decision support tool, x, 229, 230, 245, 290 decisions, x, 229, 230, 245, 248 decomposition, vii, 1, 2, 3, 7, 10, 11, 12, 13, 14, 16,

17, 19, 21, 23, 30, 31, 36, 37, 38, 39, 41, 42, 54, 56, 58, 61, 67, 70, 76, 103, 192, 196, 203, 209, 210, 212, 300

decoupling, 295, 296, 298 deficiency, 151, 152 deficit, 175, 234 definition, viii, 69, 84, 99, 101, 115, 116, 156, 189,

235, 246 degradation, 8, 10, 11, 15, 16, 17, 18, 19, 20, 22, 24,

25, 28, 29, 30, 32, 41, 43, 45, 55, 56, 58, 60, 61, 63, 64, 65, 66, 72, 73, 77, 79, 90, 95, 96, 103, 192, 203, 222

degradation pathway, 22 degradation rate, 79 degrees of freedom, 153 dehydration, 192, 199 delivery, 8, 116, 129, 133 demand, 230, 244, 245, 246, 249 denitrification, 63, 103 Denmark, 136, 238, 240, 250, 298 density, 8, 11, 12, 22, 24, 31, 57, 90, 111, 196, 202 density values, 24 Department of Energy, 11, 22, 65, 135, 251 depolymerization, 114, 199, 210 deposition, 20, 22, 206 depreciation, 85, 86, 91 depression, 36 derivatives, 19, 20, 98, 103 designers, 161, 182 destruction, 10, 49, 51, 172, 196, 206, 208, 210, 238,

240, 248, 254, 309 detergents, 100 developed countries, 21 developing countries, 2 devolatilization, 191 dew, 42 diesel, 101, 102, 114, 141 diesel engines, 141

Index 316

diesel fuel, 102, 114 differentiation, 241 diffusion, 23, 26, 31, 32, 47, 231, 256, 279 diffusivity, 196, 202 digestion, vii, x, 108, 110, 111, 116, 118, 119, 129,

138, 187, 189, 190, 194, 203, 204, 206, 207, 208, 209, 211, 213, 215, 222, 223, 225, 226, 227, 236

dioxin, 50, 51, 240 dioxins, 50, 231, 302 directives, 235, 248, 290 discharges, 4 Discovery, 207 dispersion, 261 dissociation, 299, 300 distillation, ix, 111, 118, 141, 142, 180, 181, 182,

185 distribution, 23, 30, 31, 45, 71, 73, 120, 122, 128,

139, 260 district heating, x, 229, 230, 231, 232, 233, 235, 236,

245, 246, 247, 250, 251 division, 167 dizziness, 36 draft, 100 drainage, 27 dry ice, 51 dry matter, 118, 119 drying, 191, 192, 193, 194, 196, 198, 206, 259, 299,

307 DSM, 252 dumping, 2, 40, 53 durability, 298 duration, 8, 36, 71, 77 duties, 156, 161, 165, 171, 177, 180, 309 dyes, 100

E

earnings, 85, 86 ears, 91 earth, 196, 309 Eastern Europe, 237, 295 ecological, 72, 103, 137, 290, 292, 300 Ecological models, 72 ecology, 290, 292 economic development, 294, 296 economic growth, 295 economic performance, 136, 290, 291 economic welfare, 305 economics, 137, 188, 209 economies of scale, 293, 294 ecosystem, 96, 293 ecosystems, 292 Education, 1

EEA, 309 effluent, 6, 202, 204, 212 egg, 36 Egypt, 1, 185 elaboration, 161 electric energy, viii, 69, 70, 84, 85, 86, 91, 92, 93,

220, 307 electric power, 110 electricity, vii, ix, x, 3, 50, 51, 52, 91, 92, 97, 99,

100, 101, 102, 108, 111, 115, 116, 118, 119, 120, 121, 123, 126, 129, 130, 131, 133, 160, 175, 193, 205, 207, 222, 229, 230, 231, 233, 235, 236, 237, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 298, 299, 300

electrolysis, 112, 116, 118, 119, 120, 124, 129, 138 e-mail, 97 emission, viii, ix, 3, 5, 32, 33, 37, 38, 42, 54, 55, 60,

70, 81, 86, 92, 93, 94, 119, 126, 127, 128, 129, 131, 133, 142, 195, 224, 227, 235, 236, 242, 249

employment, 247, 305 endothermic, 191, 192, 195, 300 energy consumption, ix, 98, 116, 118, 122, 125, 142,

174, 175, 177, 183, 189, 192, 194, 198, 224, 305, 307

energy density, 110 energy efficiency, 93, 118, 130, 172, 173, 185, 189,

190, 194, 201, 205, 207, 235, 243, 245, 254, 291, 299

Energy Efficiency and Renewable Energy, 135 energy recovery, vii, viii, ix, x, xi, 1, 3, 11, 37, 46,

48, 51, 52, 53, 54, 55, 69, 70, 84, 85, 86, 87, 89, 91, 93, 94, 95, 159, 173, 185, 187, 188, 189, 190, 191, 193, 200, 203, 206, 207, 210, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 232, 235, 236, 237, 239, 240, 250, 251, 253, 259, 260, 271, 289, 298, 299, 303

energy supply, 130, 133, 246, 247, 248 engines, viii, x, 49, 50, 51, 69, 84, 85, 86, 91, 92, 93,

141, 213, 215 England, 135 enterprise, 291, 294 Enthalpy, 143, 144, 145, 155 entropy, 158 environment, vii, 2, 3, 4, 7, 20, 29, 32, 33, 34, 35, 36,

46, 76, 110, 115, 172, 173, 196, 208, 231, 250, 256, 289, 290, 291, 293, 294, 298, 299, 303, 304, 305, 306, 307, 309

environmental awareness, ix, 187 environmental conditions, 25 environmental effects, 247, 308 environmental factors, 16

Index 317

environmental impact, viii, 62, 64, 70, 93, 94, 103, 115, 122, 124, 125, 133, 173, 174, 237, 245, 246, 291, 295, 298, 301, 305

environmental influences, 64 environmental issues, 290, 294 environmental policy, 293, 305 environmental protection, 254, 303 Environmental Protection Agency, 3, 5, 37, 66, 244,

252 environmental regulations, 2, 3, 188, 298 environmental resources, 289 environmental standards, ix, 187 environmental sustainability, 293 enzymatic, 107 enzymes, 23, 110, 111 EPA, 2, 5, 8, 9, 10, 13, 38, 42, 50, 51, 63, 66, 72, 76,

79, 94, 95, 209 epoxy, 123, 126, 133 epoxy resins, 123, 126, 133 equilibrium, 16 equipment, 91, 231 EST, 251 esters, 111, 114, 119 estimating, viii, 2, 3, 15, 24, 37, 69, 76, 86, 93, 125,

259 Estonia, 238 ethane, 13, 14, 23, 34, 203 ethanol, 101, 102, 103, 110, 112, 113, 118, 134, 137,

139, 212 Ethanol, 130, 136, 137 Europe, 2, 56, 100, 139, 188, 191, 234, 236, 241,

244, 249, 290, 294, 295, 296 European Commission, 235, 236, 241, 249 European Community, 249 European Environment Agency, 309 European Parliament, 249 European Union, x, 66, 210, 229, 230, 233, 235, 236,

240, 241, 243, 244, 247, 249 Eurostat, 238, 249 eutrophication, 246, 303, 305 evaporation, 13, 103, 120, 192, 194, 205, 207, 254,

256, 259, 281 evolution, 72, 256, 299 exchange rate, 232 exercise, 175 experimental design, xi, 253, 254, 262, 287 exploitation, viii, 85, 97, 100, 103, 290 explosions, 34 exports, 246, 247 exposure, 12, 32, 36, 64 external costs, 247 external environment, 214

extraction, 2, 23, 26, 32, 47, 55, 56, 58, 111, 208, 299, 303

extrusion, 307

F

fabric, 47, 306 factorial, xi, 253, 262, 287 failure, 7 family, 70, 106, 136 FAO, 135 farms, 108 fast food, 105 fat, 100, 244 fatigue, 35 fats, 98, 103, 105, 106, 134 fatty acid, 105, 111, 113, 114 faults, 306 fax, 97, 229 February, 135, 249 fee, 5, 243 feeding, 60, 189, 215, 299, 300 feedstock, ix, 54, 60, 97, 98, 100, 101, 103, 104, 106,

107, 108, 109, 110, 111, 114, 115, 116, 117, 119, 122, 124, 126, 128, 129, 130, 133, 135, 137, 189, 192, 194, 196, 197, 198, 199, 206

fees, 241, 243 feet, 11 fermentation, 19, 20, 43, 64, 71, 103, 107, 110, 112,

116, 118, 131, 133, 139 ferrous metal, 60 ferrous metals, 60 fertility, 98 fertilizer, 116, 203, 229, 236 fertilizers, 101, 119 fiber, 103, 287 fiber membranes, 287 fibers, 106 fillers, 100 film, 285, 307 filters, 53 filtration, 49 financial support, 248 financing, 234 Finland, 238, 240, 296 fire, 3, 47, 50, 195 fires, 231 firms, xi, 289, 290, 306 first generation, 98 fixation, 103, 122 flame, 33, 38, 49, 50, 158 flame ionization detector, 33 flare, 49, 50, 51, 52, 70, 91, 173

Index 318

flexibility, 293 flood, 24 flora, 76 flotation, 60 flow, xi, 22, 23, 24, 26, 27, 31, 42, 43, 45, 47, 49, 57,

65, 67, 84, 85, 102, 117, 147, 148, 156, 157, 181, 190, 191, 193, 201, 203, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 227, 253, 256, 260, 261, 263, 264, 287, 293, 300, 303, 304

flow rate, 26, 42, 57, 67, 84, 85, 215, 216, 217, 218, 220, 221, 222, 223, 224, 225, 227, 264

flue gas, 156, 158, 191, 206, 231 fluid, 258, 259, 260, 298, 299, 300 fluidized bed, 191, 193, 195, 198 flushing, 63 food, 10, 21, 39, 41, 42, 98, 99, 100, 104, 105, 108,

119, 137, 203, 244, 246, 294 food industry, 104, 105, 119, 244 food production, 108, 246 forecasting, 72 forestry, 99, 100, 103, 105, 106 formaldehyde, 112 fossil, viii, ix, 87, 97, 98, 99, 101, 102, 106, 110,

116, 119, 121, 122, 123, 125, 126, 127, 128, 129, 130, 133, 138, 172, 173, 191, 232, 236, 240, 241, 242, 243, 244, 247

fossil fuel, viii, 87, 97, 98, 101, 102, 110, 116, 122, 172, 191, 232, 236, 240, 241, 243, 244, 247

fossil fuels, viii, 87, 97, 98, 101, 102, 110, 172, 191, 232, 236, 240, 241, 243, 244

fouling, 183, 184, 196 fractionation, 173 fragmentation, 114 framing, 290, 293 France, v, 97, 134, 138, 209, 238, 240, 295 free radicals, 202, 206 free trade, 235, 236 freedom, 153, 167, 264 fructose, 103 fruits, 108, 115 fuel, vii, viii, ix, 3, 48, 49, 51, 52, 53, 54, 59, 60, 97,

100, 101, 108, 110, 112, 113, 114, 116, 117, 120, 122, 123, 133, 134, 135, 136, 139, 173, 191, 193, 194, 195, 198, 199, 212, 231, 232, 233, 236, 237, 240, 243, 245, 246, 247, 254, 300, 301, 307

fuel cell, 51, 52, 135, 195 fugitive, 11 fumaric, ix, 97, 115, 117, 119, 120, 122, 124, 126 furan, ix, 97, 114, 115, 117, 119, 120, 123, 125, 130,

131, 133 furnaces, 141, 160, 185, 230, 299

G

G8, 135 garbage, 14 gas chromatograph, 33 gas phase, 194 gas separation, ix, 141, 142, 173, 175, 185 gas turbine, 49, 50, 123, 141, 195, 250 gaseous waste, 52, 102 gases, vii, 1, 2, 14, 26, 27, 32, 35, 36, 37, 38, 45, 46,

47, 49, 50, 52, 60, 70, 110, 173, 192, 195, 196, 197, 201, 214, 217, 246

gasification, vii, x, 108, 110, 111, 112, 135, 138, 187, 189, 190, 195, 196, 197, 198, 199, 205, 207, 208, 209, 211, 212, 213, 214, 218, 219, 220, 221, 224, 225, 226, 298, 300, 301

gasifier, xi, 196, 198, 208, 210, 289, 298, 300, 301 gasoline, 101, 102, 120, 123, 126, 128, 129, 132, 133 GCC, 141, 154, 156, 157, 158, 159, 160, 176 generation, vii, viii, 2, 3, 7, 11, 12, 16, 20, 21, 22, 23,

24, 25, 27, 29, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 50, 54, 57, 58, 59, 62, 63, 64, 67, 70, 71, 75, 76, 77, 78, 79, 80, 88, 94, 95, 98, 100, 101, 111, 114, 119, 138, 156, 160, 172, 189, 191, 192, 195, 197, 199, 203, 204, 210, 211, 248, 295, 296, 297, 298, 300

Geneva, 288 geology, 34 Geomembranes, 26 Georgia, 59, 66 geothermal, 94, 244 Germany, 100, 191, 237, 238, 240, 298 GHG, vii, ix, 1, 14, 67, 97, 102, 116, 118, 119, 122,

123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 138, 141, 142, 172, 173, 174, 175, 177, 180, 182, 183, 185, 304

glass, 21, 33, 60, 258, 301, 307 global warming, 14, 53, 126, 172, 305 Global Warming, 40, 67, 70, 126 Glucan, 109 glucose, 103, 104, 106, 107, 110, 111, 118, 136, 212 glycerin, 105, 114 glycerine, 111 glycerol, 110 glycol, 112 goals, x, 229, 235, 242, 244, 247, 248, 290, 294 goods and services, 251, 292, 303 governance, 293 government, 231, 242, 243, 244, 295, 309 government budget, 242 government policy, 295 GPS, 57 grain, 26

Index 319

grains, 36, 100, 102, 104 graph, 142, 143, 153, 156, 157, 159, 162, 168, 177 grass, 106 grasses, 98, 102, 104, 115 grassroots, 185 gravity, 120, 121, 194 Greece, 238 greenhouse, vii, ix, 1, 4, 49, 53, 95, 97, 116, 125,

134, 137, 138, 172, 185, 198, 246, 249, 254, 304, 305

Greenhouse, viii, 69, 70, 93, 94, 95, 135 greenhouse gas, vii, ix, 1, 49, 53, 95, 97, 116, 125,

134, 138, 172, 185, 198, 246, 249, 304 greenhouse gas (GHG), ix, 97, 116, 125 greenhouse gases, vii, 1, 246 groundwater, 4, 7, 27, 47, 53, 54 grouping, 92 groups, 8, 14, 51, 104, 114, 119, 123, 124, 203, 300,

306 growth, 15, 22, 25, 28, 37, 43, 44, 45, 72, 75, 103,

231, 295, 296 growth rate, 43, 44, 45 guidance, 4 guidelines, 101, 136, 162

H

H1, 144, 147, 168, 169, 170 H2, 25, 70, 110, 112, 117, 118, 120, 122, 123, 126,

128, 130, 131, 132, 133, 144, 168, 169, 170, 171, 192, 193, 195, 199, 200, 201, 205, 220, 221

halogenated, 51, 191 handling, 8, 111, 230, 242, 288 hands, 288 harmful effects, 254 harvesting, 106, 122 hazardous substances, 231 hazardous wastes, 203 hazards, vii, 1, 3, 34, 35, 36, 46, 47 HDPE, 60, 67 headache, 36 health, vii, 2, 4, 14, 33, 36, 46, 51, 247, 294 health effects, 36 heart, 300 heartbeat, 35, 36 heat capacity, 192 Heat Exchangers, 160 heat loss, 189 heat release, 44, 217 heat storage, 249 heat transfer, 161, 162, 163, 254, 257, 258, 260, 266,

275

heating, x, 13, 70, 84, 92, 114, 118, 121, 125, 147, 152, 153, 155, 156, 157, 158, 159, 160, 163, 164, 165, 166, 167, 170, 171, 172, 173, 175, 177, 180, 181, 182, 184, 185, 192, 194, 196, 199, 202, 214, 215, 217, 221, 229, 230, 231, 232, 233, 235, 236, 245, 246, 247, 249, 250, 251, 254, 255, 258, 262, 266, 267, 270, 271, 275, 279, 281, 285, 286, 299, 309

heating oil, 173, 175, 177, 180 heating rate, 192 heavy metals, 25, 108, 194, 231, 299 heavy oil, 101, 123, 133, 193, 199, 200 height, 54, 59 hemicellulose, 99, 100, 102, 103, 106, 107, 110, 111,

112, 114, 117, 130, 131 hemicellulose hydrolysis, 117 hemp, 106 herbicide, 113 heterogeneity, 45, 66 heterogeneous, 17, 21, 25, 26, 298 heuristic, 165, 167 hexachlorobenzene, 203 high pressure, 173 high temperature, 110, 192, 193, 195, 196, 205, 206,

207, 214, 281, 301 hips, 240 holistic, 54, 134 holistic approach, 54, 134 Holland, 240 homogeneity, 22, 30 horizon, 126 hospital, 258 hospitals, 288 host, 90 hot water, 137, 231, 242, 243 House, 139 household, 36 households, 105, 126 human, vii, 2, 4, 33, 46, 125, 126, 305 humanity, 134 humidity, 87, 254, 256, 260, 262, 279, 281 Hungary, 238 hybrid, 7, 10, 54 hydraulic fluids, 100 hydro, 19, 32, 37, 110, 141, 180, 193, 194, 196, 212,

214 hydrocarbons, 19, 32, 37, 110, 180, 194, 196, 214 hydrochloric acid, 299 hydrofluoric acid, 299 hydrogen, ix, 12, 13, 14, 19, 20, 24, 34, 35, 36, 42,

51, 70, 71, 97, 99, 101, 109, 110, 111, 112, 115, 116, 120, 123, 125, 193, 195, 196, 199, 202, 205, 212, 214, 219, 299, 302

Index 320

hydrogen gas, 71, 205 hydrogen peroxide, 202 hydrogen sulfide, 12, 14, 34, 35, 36, 51 hydrogenation, 107, 111, 112, 199 hydrological, 45 hydrolysis, 8, 19, 20, 30, 43, 44, 45, 71, 107, 111,

113, 116, 117, 118, 136, 137, 203, 205, 209 hydrolyzed, 108, 113, 117 hydropower, 244 hydrothermal, 110, 137, 189, 202 Hydrothermal, 203 hydroxide, 118, 128 hypothesis, 80, 308

I

ice, 51 identification, 115, 124, 305, 306 IEA, 99, 100, 136, 195, 209 imbalances, 72 implementation, 5, 6, 7, 102, 185, 207, 236, 241, 246 imports, 240 impurities, 52, 53, 102, 110, 118, 233 in situ, 28 incentive, 227, 234, 243, 248 incentives, 244 incineration, vii, x, 1, 187, 188, 189, 190, 191, 192,

193, 194, 205, 207, 210, 229, 230, 231, 232, 233, 235, 236, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 299

inclusion, 307 indication, 33, 85, 247 indicators, x, 31, 116, 213 indices, 116 indigenous, 231 industrial, ix, xi, 60, 97, 99, 102, 106, 116, 122, 124,

138, 142, 154, 159, 172, 173, 181, 183, 185, 187, 188, 189, 210, 227, 237, 242, 289, 290, 291, 292, 293, 294, 298, 303, 305, 306, 307, 308, 309

industrial application, ix, 142, 172, 181, 183 industrial chemicals, 102 industrial production, 298 industrial sectors, 294, 298 industrial wastes, 106, 298 industrialization, 307 industry, ix, 3, 37, 51, 60, 99, 100, 103, 104, 105,

106, 111, 119, 141, 142, 162, 185, 189, 191, 205, 210, 231, 234, 244, 250, 258, 292, 294, 303, 306, 309

inequality, 152, 164, 165, 166 inert, 2, 32, 38, 41, 42, 47, 78, 87, 88, 89, 160, 199,

200, 205, 206, 215, 217, 222, 299, 300, 301, 302 influence, 234, 235, 243, 245

infrastructure, 103, 112, 120, 240, 241, 247 inhalation, 36, 47 inhibition, 43, 44, 45 inhibitors, 23, 25 inhibitory, 44 injection, 9, 53, 57, 59 innovation, 64, 134, 305 inoculum, 29 inorganic, 17, 45, 196, 202, 206, 299 input, 72, 78, 79, 81, 88, 90, 91, 93 inspection, 263 institutions, 290 instruments, x, 33, 229, 230, 232, 242, 245, 248,

250, 260, 298, 302, 303 insulation, 189 intangible, 306 integrated waste management, 214 integration, ix, 142, 143, 155, 159, 160, 172, 173,

174, 175, 177, 185, 215, 250, 298 integrity, 51, 77 interaction, 263, 264, 265, 269, 270, 273, 274, 277,

278, 279, 281, 284 interactions, xi, 253, 263, 287, 290, 291 interest, 231, 241, 243 interface, 156 Intergovernmental Panel on Climate Change (IPCC),

3, 37, 39, 136 internal combustion, 49, 50 International Organization for Standardization, 288 interphase, 44 interpretation, 244 interval, 144, 146, 147, 148, 151, 152, 153, 155, 185,

243 intervention, 8, 305 investment, x, 85, 86, 90, 92, 142, 172, 174, 175,

177, 182, 185, 229, 230, 231, 234, 235, 243, 305 ionization, 33 ions, 19 IPCC, vii, 1, 2, 39, 40, 41, 42, 67, 75, 95, 100, 126,

136 IPPC, 5 Ireland, 238 iron, 25, 196, 210, 212, 307 irrigation, 203 ISO, 115, 124, 135, 136, 246, 288, 303, 310 Israel, 211 Italy, v, 23, 61, 62, 63, 69, 80, 94, 95, 137, 213, 227,

238, 240, 289, 293, 296, 298, 300, 306

J

Japan, 191 Jatropha, 105, 134

Index 321

jobs, 102, 305 jurisdictions, 3

K

kerosene, 102 ketones, 114 kinase, 139 kinetic equations, 43 kinetic model, 136 kinetics, 43, 44, 45, 72, 75, 222 knowledge, 230, 245, 248 Kyoto protocol, 233, 236

L

labor, 141 lack of confidence, 231 lactic acid, 103, 106, 112 land, vii, 1, 5, 14, 21, 60, 98, 100, 104, 188, 202,

203, 246 land disposal, 5, 21 land use, 246 landfill gas, vii, viii, 1, 2, 3, 4, 8, 10, 11, 12, 13, 14,

15, 16, 20, 21, 22, 23, 24, 26, 27, 31, 32, 33, 34, 35, 36, 37, 38, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 60, 61, 62, 63, 64, 65, 69, 70, 93, 94

landfill management, 62 landfills, vii, viii, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 17, 18,

23, 24, 25, 26, 27, 28, 30, 32, 34, 36, 37, 38, 39, 42, 43, 44, 45, 46, 49, 51, 53, 54, 57, 59, 60, 61, 62, 63, 64, 65, 66, 69, 70, 72, 75, 77, 84, 87, 93, 94, 95, 96, 188, 230, 231, 236

large-scale, 64 Latvia, 238 law, 4, 215, 250 laws, 4 LCA, ix, 97, 115, 116, 119, 121, 122, 124, 131, 133,

134, 135, 139, 246, 247, 294, 303, 305, 310 leachate, viii, 2, 7, 8, 9, 10, 11, 19, 20, 21, 25, 27, 28,

29, 30, 31, 32, 43, 44, 45, 47, 48, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 69, 87, 88, 89, 90, 91, 92, 93, 94

leachate recirculation, viii, 7, 9, 28, 29, 43, 53, 54, 57, 59, 61, 62, 63, 64, 65, 70, 87, 88, 89, 90, 91, 92, 93, 94

lead, 241, 247 leakage, 32 leaks, 33 Legionella, 261, 288 legislation, x, 207, 229, 230, 232, 234, 235, 241

life cycle, 115, 122, 125, 126, 134, 135, 303, 305, 307

Life Cycle Assessment, (LCA)ix, 97, 99, 103, 115, 138, 228, 303

life-cycle, 4, 134 lifetime, 14, 37 lignin, 99, 100, 101, 102, 103, 106, 108, 111, 114,

116, 117, 118, 119, 121, 127, 128, 135, 137, 193, 204, 210

limitation, 23 limitations, 99, 246, 258, 260 limiting oxygen, 24 linear, 57, 72, 245, 292 linear programming, 245 links, x, 229, 300 lipids, 19, 22, 103, 105 liquefaction, vii, x, 187, 190, 198, 199, 200, 201,

205, 206, 207, 208, 210, 211, 212 liquefied natural gas, 52 liquid fuels, 135, 195, 206 liquid phase, 115, 199, 256 liquids, 2, 8, 9, 10, 11, 26, 136, 299 Lithuania, 238 local authorities, 293 logging, 240 logistics, 291, 308 London, 61, 62, 63, 64, 65, 139, 208 long period, 7, 33 losses, 193, 217 lover, 106 low-density, 31 low-level, 36 low-permeability, 47 low-temperature, 199, 211 lubricants, 100 lubricating oil, 92, 102, 119 Luxembourg, 238 lysimeter, 54, 65 lysine, 103

M

machinery, 300 machines, 92 Madison, 65 magnesium, 22, 25, 196 magnetic, 60, 215 maintenance, 7, 85, 86, 92, 141, 182, 183, 233, 306 Malta, 238, 246 maltose, 103 management, viii, ix, x, 2, 3, 4, 10, 53, 54, 60, 61,

62, 64, 65, 69, 94, 95, 136, 187, 188, 189, 203, 207, 208, 211, 228, 229, 232, 233, 234, 235, 236,

Index 322

240, 243, 244, 245, 246, 247, 248, 249, 251, 252, 290, 291, 293, 300, 303, 306, 309

manganese, 260 man-made, 32 manufacturing, 60, 128, 231, 290, 294, 295, 296,

297, 298, 303, 309 manufacturing companies, 290 manure, 36, 108, 203 market, x, 100, 105, 106, 119, 120, 125, 126, 135,

226, 229, 230, 234, 235, 237, 239, 240, 241, 247, 249, 252, 306

market penetration, 106, 120 market share, 119, 237, 239, 240 market structure, 241 market value, 125 markets, 119, 126, 138, 234, 236 Maryland, 62, 64 mass transfer, 44, 191, 256, 287 mathematical programming, 153, 154 matrix, 26, 55, 300 maturation, 71 measurement, 262, 288, 303 measures, 4, 5, 33, 34, 57, 231, 233, 245, 293, 303,

305, 306, 308 media, 25, 43, 173, 175, 256, 257 medicine, 106, 119 Mediterranean, 210 megawatt, 175, 185 melt, 60 melting, 172 membranes, xi, 49, 289, 290, 306 mercaptans, 36, 71 mercury, 194, 209 metabolic, 8 metabolism, 14 metal ions, 19 metallurgy, 258 metals, 25, 60, 123, 194, 201, 215, 231, 294 methane, vii, x, 1, 2, 3, 7, 8, 9, 11, 12, 13, 14, 15, 16,

19, 20, 22, 23, 24, 25, 28, 29, 30, 32, 33, 34, 35, 38, 39, 40, 41, 42, 43, 44, 45, 46, 49, 50, 51, 52, 53, 54, 55, 57, 58, 59, 60, 61, 62, 63, 64, 66, 67, 68, 70, 71, 72, 76, 77, 86, 87, 94, 110, 112, 118, 172, 193, 197, 203, 213, 215, 236, 300, 301

methanogenesis, 8, 10, 20, 24, 43, 44, 45 methanol, 51, 52, 105, 110, 112, 192, 195 methodology, 230, 246, 247 methylene, 13 methylene chloride, 13 microalgae, 134 microbes, 11 microbial, 23, 29, 43, 44, 45, 54, 61, 70, 76, 103, 222 Microbial, 61, 65, 94, 138

microbial community, 54 micronutrients, 22 microorganisms, 14, 19, 20, 21, 22, 23, 24, 25, 28,

30, 45, 71, 110, 112, 131 migration, vii, viii, 1, 2, 3, 6, 26, 27, 32, 33, 34, 46,

47, 65 milk, 60 mineralization, 103 minerals, 21, 291 mining, 3, 54, 59, 60, 64, 66 Ministry of Education, 287 Minnesota, 56 misleading, 125 missions, 51, 133, 138, 172, 226, 247, 254 MIT, 202 mixing, 25, 72, 258, 299 mobility, 11, 235 modeling, 45, 64, 66, 139 models, viii, x, 3, 37, 56, 69, 72, 76, 79, 80, 81, 83,

84, 91, 93, 216, 222, 229, 230, 245, 246, 248, 305 modern society, 229 modules, 255 moisture, 7, 8, 9, 10, 11, 16, 21, 23, 24, 28, 29, 30,

31, 37, 39, 43, 44, 45, 47, 53, 54, 56, 57, 59, 63, 71, 72, 77, 78, 108, 193, 196, 197, 216, 217, 219, 222

moisture content, 8, 10, 11, 21, 23, 24, 28, 29, 30, 31, 45, 47, 54, 56, 63, 71, 77, 108, 193, 196, 197, 216, 217, 219, 222

molar ratio, 197 molar ratios, 197 molecular mass, 71, 108 molecular oxygen, 124 molecular structure, 106 molecular weight, 41 molecules, 8, 14, 101, 102, 104, 106, 109, 114, 119,

126, 214, 299, 300 money, 172 monitoring, 235 monomer, 107, 112, 203 monomers, 107, 112, 117, 118, 123 monosaccharide, 104 movement, 3, 23, 26, 28, 32, 46, 63 MSW, 2, 5, 7, 8, 15, 16, 23, 24, 25, 28, 29, 30, 31,

38, 41, 57, 61, 67, 70, 87, 88, 89, 92, 93, 95, 108, 214, 215, 216, 217, 218, 222, 224, 225, 226, 227

municipal sewage, 198, 199, 204, 208 municipal solid waste, (MSW)vii, viii, 2, 7, 11, 13,

21, 23, 26, 37, 38, 43, 46, 55, 60, 61, 62, 63, 64, 65, 66, 69, 70, 209, 212, 228, 240, 251, 300

myopic, 172

Index 323

N

natural, 10, 13, 14, 27, 32, 34, 36, 37, 46, 49, 50, 52, 53, 87, 101, 103, 106, 110, 112, 120, 122, 123, 126, 128, 129, 133, 135, 172, 173, 195, 203, 233, 234, 237, 241, 288, 293, 295, 303, 309

natural environment, 309 natural gas, 13, 37, 49, 50, 52, 53, 101, 110, 112,

120, 122, 123, 126, 128, 129, 133, 135, 173, 195, 203, 233, 234, 237, 241

natural resources, 87, 103, 106, 172, 295, 303 nausea, 36 needs, 230, 244 negotiation, 241 Netherlands, 135, 228, 238, 296 network, ix, 84, 142, 156, 160, 161, 163, 165, 167,

168, 170, 171, 172, 175, 182, 183, 184, 185, 231, 234, 237, 241, 250, 290, 291

networking, 293 New Jersey, 57, 63 New Orleans, 96 New York, 62, 64, 65, 95, 138, 287 New Zealand, 185 newspaper industry, 60 newspapers, 234 Ni, 117, 196, 209 nickel, 209, 210 NIPA, 297 nitrogen, 14, 19, 25, 42, 51, 103, 109, 112, 124, 299,

302 nitrogen oxides, 51 noise, 304, 305, 308 non invasive, 95 non toxic, 300 non-hazardous, vii, 2, 5, 8, 46, 80 non-human, 292 normal, 8, 35, 36, 305 norms, 125 North America, 7, 58, 67, 187 Norway, 238, 240, 298 NTU, 288 nutrient, 7, 25, 56 nutrients, 15, 16, 22, 23, 25, 28, 29, 53, 71, 72

O

obligate, 71 observations, 21 obsolete, 299 occupational, 32 octane, 120 odors, vii, 1, 7, 36, 37, 47

OFS, 194 oil, ix, 92, 97, 98, 99, 100, 101, 102, 103, 104, 105,

108, 110, 111, 114, 119, 121, 122, 123, 128, 129, 131, 133, 136, 138, 139, 141, 142, 156, 160, 173, 175, 177, 180, 182, 183, 185, 187, 188, 192, 194, 198, 199, 200, 205, 207, 208, 209, 210, 212, 231, 232, 237, 240, 246, 254, 258, 301

oil production, 199 oil refining, 182, 183 oils, 103, 105, 114, 134, 138, 193, 198, 199, 200,

212, 307 oilseed, 100, 105, 114 oligomers, 210 onion, 138 operator, 3, 206 opposition, 7 optimization, 7, 141, 152, 153, 154, 160, 172, 173,

185, 247, 259, 288, 291 organ, 299 organic, vii, x, 1, 3, 7, 8, 10, 11, 12, 13, 14, 17, 19,

20, 22, 24, 25, 28, 30, 31, 32, 36, 39, 40, 41, 44, 45, 49, 50, 54, 56, 58, 59, 60, 61, 62, 63, 64, 66, 70, 71, 74, 75, 76, 77, 102, 103, 104, 108, 110, 111, 112, 114, 115, 119, 123, 138, 139, 188, 191, 192, 193, 196, 199, 201, 202, 203, 206, 207, 209, 213, 214, 215, 228, 232, 299, 300, 302

organic chemicals, 11 organic compounds, vii, 1, 10, 12, 13, 14, 28, 49, 50,

61, 196, 203 organic matter, vii, 1, 25, 30, 36, 45, 62, 70, 103,

192, 203, 204, 209, 300 organic polymers, 203 organic solvent, 199 organic solvents, 199 organism, 20 output, 72, 236 oxidants, 202 oxidation, vii, x, 32, 70, 117, 187, 189, 190, 192,

202, 203, 207, 208, 209, 210, 211, 214 oxidative, 119 oxide, 52, 299 oxides, 51 oxygen, ix, 8, 19, 20, 22, 23, 24, 25, 27, 34, 35, 37,

42, 54, 59, 70, 97, 99, 109, 110, 114, 115, 116, 119, 124, 131, 192, 196, 199, 202, 203, 205, 207, 214, 217, 222, 236, 300, 301

Oxygen, 6, 14, 24, 34, 35, 66, 71, 125, 135, 205, 216, 217

oxygenation, 111, 119, 124 ozone, 172, 254, 303, 304, 305

Index 324

P

packaging, 60, 100, 234, 236, 242, 249, 250 PAFC, 52, 67 paints, 100 Pap, 211 parameter, 43, 45, 58 Paris, 138, 209 Parliament, 249 particles, 32, 53, 111, 299 particulate matter, 51, 203 partnership, 294 passenger, 118, 123, 128 passive, 27, 47, 258 pathogens, 203 pathways, 17, 27, 32, 34, 107, 112, 133 peat, 244 per capita, 296, 297 percolation, 22, 43, 299 performance indicator, 224, 225, 227 periodic, 58 permeability, 26, 27, 28, 31, 32, 47, 256 permit, 5 personal relations, 293 personal relationship, 293 perspective, 234, 243, 247, 248, 250 PET, xi, 289, 306, 307 petrochemical, 106, 111 petroleum, 98, 101, 102, 114, 119, 133, 139, 193,

194 Petroleum, 138 petroleum products, 139 pH, 6, 16, 20, 24, 25, 28, 29, 30, 31, 43, 44, 45, 194,

199, 204, 211 pharmaceutical, 114 phenol, 123 phenolic, 108 Philadelphia, 63 phosphate, 19 phosphoric acid fuel cell, 52 phosphorous, 25 photochemical, 305 photosynthesis, 103, 122 photosynthetic, 102, 103 physical properties, 14, 119, 125, 193 physicochemical, 298, 308 physiological, 14 pig, 203 pilot study, 251 pipelines, 51 planning, 290, 291, 293, 305

plants, 36, 87, 90, 91, 92, 102, 105, 110, 173, 175, 185, 187, 188, 195, 231, 232, 233, 235, 236, 237, 240, 241, 242, 243, 244, 245, 247, 248, 252, 299

plasma, 196 plastic, xi, 33, 41, 42, 47, 60, 100, 215, 242, 243,

248, 289, 290, 307 plastics, 21, 41, 60, 101, 114, 240, 243 platforms, ix, 97, 99, 111 play, 98, 119, 294 poison, 51 poisoning, 112 Poland, 237, 238, 240, 296, 298 polar ice, 172 polar ice caps, 172 polarity, 102 policy instruments, x, 229, 230, 232, 242, 245, 248,

250 politics, 250 pollutants, 6, 66, 191, 257 pollution, 4, 50, 188, 191, 206, 210, 291, 292, 294,

299, 303 polyamides, 114 polychlorinated dibenzodioxins (PCDDs), 191 polycondensation, 119 polyester, 119, 306, 307 polyethylene terephthalate, xi, 289, 290 polymer, 52, 104, 113, 123, 192, 307 polymer molecule, 104 polymerization, 117, 119, 123, 192 polymers, 100, 103, 108, 118, 123, 192, 202, 203 polyphenols, 103 polysaccharides, 104, 111 polyurethanes, 114 poor, 29, 35, 105, 188 population, 166, 254, 306, 309 pore, 26, 46, 257 porosity, 26, 256, 257, 260 porous, 33, 43, 256, 257, 260, 287, 288 porous media, 43, 256 portfolio, 103 Portugal, 134, 238 potassium, 22, 25, 118 potential energy, xi, 289 powder, 201, 212, 300 power, x, 3, 46, 52, 63, 64, 98, 110, 114, 122, 136,

159, 160, 175, 190, 195, 199, 203, 204, 208, 217, 218, 219, 220, 221, 222, 223, 224, 225, 227, 229, 230, 231, 233, 235, 236, 242, 244, 245, 251, 258

power generation, 3, 46, 63, 64, 191, 195, 199, 204 power plant, 122, 195, 208, 231, 233, 242 power plants, 195, 231, 233 precipitation, 24, 32, 42, 103 prediction, 62, 72, 76, 134

Index 325

preference, 172 pressure, 12, 13, 23, 24, 26, 27, 32, 47, 104, 110,

120, 121, 159, 173, 175, 194, 196, 199, 200, 205, 207, 217, 218, 219, 221, 258, 260, 281, 288, 293, 298, 301

prevention, 236, 249, 294 preventive, 293 prices, ix, 126, 138, 187, 188, 232, 233, 234, 236,

237, 241, 254 private, 290 probability, 27 process gas, 219 producers, 100, 234, 237, 244 product market, 106 profit, 85, 86 profits, viii, 69, 84, 85, 93 program, 5, 33, 42, 138, 208 programming, 152, 245 propagation, 185 property, 3, 194 propionic acid, 24 proposition, 231, 242 propylene, 112 protection, 254, 291, 303 protective coating, 123 protein, 16 proteins, 19, 22, 98, 103, 106, 111, 115 Proteins, 19 protocol, 233, 236 public administration, 306 public health, 3, 36 pulp mill, 191, 203, 210 pumping, 47, 288 purification, 52 PVC, 60 pyramidal, 54 pyrolysis, vii, x, 51, 108, 110, 114, 134, 135, 136,

138, 139, 187, 189, 190, 192, 193, 194, 196, 198, 205, 207, 208, 209, 210, 212, 213, 214, 220, 221, 224, 225, 226, 227, 228

Q

quality loss, 173 questionnaire, 245

R

radial distance, 57 radius, 27, 260 rain, 172 rainfall, 21

random, 307 range, 2, 13, 16, 20, 23, 24, 25, 26, 30, 32, 36, 38,

39, 50, 59, 75, 89, 98, 102, 106, 110, 114, 133, 158, 161, 181, 196, 203, 225, 294, 296, 298

raw material, ix, 97, 98, 99, 100, 101, 102, 103, 105, 106, 108, 112, 115, 116, 117, 122, 124, 130, 133, 188, 191, 234, 292, 300, 301, 303

raw materials, 98, 99, 100, 101, 102, 103, 105, 106, 108, 112, 115, 116, 122, 124, 133, 191, 300

RCRA, 2, 3, 4, 5, 67 reactant, 72 reactants, 118 reaction mechanism, 113, 123 reaction medium, 199, 202, 206 reaction rate, 88, 110 reaction temperature, 189 reactive sites, 105, 114 reactivity, 113, 114, 196 real estate, 291 reality, 24, 77, 304 recognition, vii, 1, 46 reconcile, 184 reconstruction, 188 recovery, vii, viii, ix, x, 3, 11, 26, 32, 42, 46, 52, 54,

55, 59, 60, 65, 69, 70, 72, 77, 84, 85, 86, 87, 89, 91, 93, 94, 95, 133, 142, 156, 159, 161, 165, 166, 172, 174, 182, 184, 185, 188, 189, 190, 203, 213, 214, 215, 216, 217, 225, 226, 227, 229, 230, 231, 232, 234, 235, 236, 237, 238, 239, 240, 242, 243, 247, 248, 250, 251, 253, 254, 258, 260, 262, 267, 286, 287, 288, 299, 300

recovery technology, 3, 46 recyclables, 59, 60 recycling, vii, 1, 29, 60, 135, 207, 234, 240, 243,

246, 249, 303, 309 redox, 25 reduction, 70, 86, 90, 93, 95 reference system, ix, 97, 99, 116, 121, 122, 125, 126,

127, 128, 129, 130, 133 refineries, 102, 139 refining, 114, 122, 135, 182, 183, 258 refrigeration, 156, 157, 160 regression, 3 regular, 55 regulation, 4, 5, 300 regulations, 4, 5, 6, 191, 232, 243, 290, 294 regulatory framework, 4 relationship, 41, 57, 125, 303 relationships, 125, 290, 292, 293 reliability, 214, 226, 304 remediation, 4 renewable energy, 100, 130, 133, 236, 244, 246, 249,

292

Index 326

renewable resource, viii, 97, 103, 112 replacement rate, 119 research and development, 98, 103, 110 residential, 54 residues, ix, 97, 99, 100, 101, 102, 104, 106, 108,

116, 119, 121, 124, 127, 133, 135, 188, 191, 205, 208, 210, 211, 214, 219, 220, 240, 307

resins, ix, 97, 114, 115, 117, 119, 122, 123, 125, 128, 130, 131, 132, 133, 307

resistance, 46, 257, 260, 279, 301 Resource Conservation and Recovery Act, 2, 3, 67 resources, viii, 53, 60, 87, 97, 98, 102, 103, 106, 108,

133, 141, 172, 173, 233, 236, 245, 249, 289, 292, 293, 294, 295, 298, 303, 306, 307, 309

respiration, 8, 35, 103 responsibility, 236, 250 restaurants, 105 restructuring, 249 rice, 212 rice husk, 212 risk, vii, 2, 4, 46, 215 risks, 11, 214, 231, 255 robustness, 246 Romania, 238, 240, 246, 298 Rome, 135, 137 room temperature, 189, 204 routing, 71 rubber, 60, 119, 240 rule of law, 4 runoff, 4, 6, 103 rural, 102, 133, 306 rural areas, 102, 133 rural population, 306 Russian, 139 ruthenium, 197

S

safety, 3, 174 saline, 105 salt, 206 sample, 33, 109 sand, 47, 60 satisfaction, 171 saturation, 54, 219, 281 Saudi Arabia, 141 savings, ix, 97, 98, 126, 129, 130, 133, 155, 177,

224, 243, 307 schema, 249 scholarship, 287 scientific community, 98 SCW, 196, 202 sea level, 172

search, 254 seasonal variations, 23, 27 Second World War, 231 sediment, 61 seeds, 100 selecting, 93, 146, 159 selectivity, 160 self, 235 semiarid, 105 semi-arid, 105 sensitivity, 43, 125, 246 sensors, 262 separation, ix, 49, 102, 111, 136, 141, 142, 160, 173,

175, 185, 189 septic tank, 29 services, 105, 127, 131, 133, 235, 246, 251, 291,

292, 293, 294, 303, 306 sewage, 7, 8, 29, 61, 108, 188, 193, 194, 196, 198,

199, 203, 204, 208, 209, 210, 211, 212 shape, 54, 111 shares, 99, 124, 128, 131, 237 sharing, 293 shock, 206 short period, 117 short run, 119 shortage, 190 shortness of breath, 36 Short-term, 12, 210 shoulder, 243 Siemens, 207 signals, 245 simulation, 61, 64, 181, 215, 216, 217, 218, 219,

220, 221, 249, 258 simulations, 217, 218, 219, 221 sites, vii, 1, 2, 6, 8, 20, 21, 22, 32, 33, 37, 47, 61, 64,

96, 105, 114, 290 skills, 290, 298 slag, 299 Slovakia, 238, 240, 298 Slovenia, 238 sludge, vii, ix, 7, 8, 10, 28, 29, 61, 78, 108, 138, 187,

188, 189, 190, 192, 193, 194, 195, 196, 197, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212

smog, 51, 172 smoke, 299, 301 SO2, 50, 202, 206, 299 social benefits, 291 social factors, 247 social group, 306 social performance, 290 social problems, 247 sodium, 25, 118, 128

Index 327

sodium hydroxide, 118, 128 software, 76, 80, 116, 118, 122, 135, 153, 154, 161,

168, 185, 217, 218, 220, 307 soil, 3, 4, 7, 27, 28, 31, 32, 37, 40, 46, 47, 55, 60, 67,

95, 98, 103, 104, 105, 188, 203, 210, 236 soil particles, 32 soils, 46, 92, 210 solar, 244, 292 solar energy, 292 solid matrix, 26 solid waste, vii, viii, 1, 2, 3, 7, 11, 13, 21, 23, 26, 27,

37, 38, 40, 43, 45, 46, 53, 55, 57, 60, 61, 62, 63, 64, 65, 66, 69, 70, 76, 94, 95, 203, 206, 209, 212, 214, 222, 228, 240, 251, 299, 301

solubility, 19, 196 solvent, 114, 199, 208, 209 solvents, 2, 100, 210 sorbents, 100 sorbitol, 112 sorting, x, 59, 60, 213, 214, 215, 216, 231, 240 Southampton, 64 soybean, 100 Spain, 238, 260, 262, 287, 295 species, 138, 196, 203 specific gravity, 120 specific heat, 147, 148, 181 specificity, 93 spectrum, 99, 102, 108 speed, 53 stability, 38 stabilization, 7, 10, 11, 16, 25, 28, 29, 30, 31, 43, 57,

62, 64, 65, 66, 203, 205 stabilize, 7, 30, 173 stages, 3, 16, 17, 18, 19, 20, 21, 43, 45, 47, 75, 115,

122, 126, 129, 175, 197, 198, 200, 263 stakeholders, 293, 306 standards, ix, 4, 6, 124, 187, 235, 246, 303, 305 Standards, 5, 67 starch, 100, 101, 103, 104, 105, 112, 212 starches, 98 state aid, 241 statistics, 239 steady state, 57 steel, 33, 234, 260 sterile, 206 Stochastic, 66 storage, 9, 54, 57, 59, 122, 249, 299, 300 stormwater, 10 strategies, 116, 247, 291, 294, 298, 303, 305, 309 streams, x, 99, 108, 142, 143, 144, 146, 147, 148,

153, 156, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 170, 173, 174, 175, 181, 184, 196, 211, 213, 217, 294

subjective, 246, 247 subsidies, 235, 244 subsidization, 243 substances, 14, 22, 111, 114, 125, 191, 294, 299 substitution, ix, 98, 124 substrates, 15, 28, 71, 72, 110, 111, 112 sucrose, 138 sugar, 100, 103, 104, 105, 106, 107, 112, 118, 137,

210 sugar beet, 104, 106 sugar cane, 100, 104, 137 sugars, 19, 98, 104, 106, 107, 108, 110, 111, 112,

113, 114, 116, 117, 131, 137, 192 sulfate, 43 Sulfide, 12, 67 sulfur, 42, 51 sulfur oxides, 51 sulfuric acid, 117, 128 sulphate, 19, 21, 25 sulphur, 109, 299, 302 summer, 55, 262 Sun, 117, 139 sunflower, 105 supercritical, vii, x, 187, 189, 196, 199, 200, 202,

203, 208, 209, 210, 211, 212 superheated steam, 219 superiority, xi, 253, 287 supervision, 249 supplemental, 49 suppliers, 241 supply, x, xi, 7, 101, 102, 104, 115, 118, 143, 146,

174, 175, 184, 213, 214, 220, 230, 232, 233, 236, 237, 240, 246, 247, 248, 249, 250, 253, 256, 257, 285, 287, 293, 294

surface area, 22, 30, 161, 162, 174, 177, 180 surface component, 27 surface water, 4, 7, 60 surgery, 288 surplus, 153, 155, 237, 300 sustainability, 134, 173, 293 sustainable development, 290, 303 Sweden, x, 100, 229, 230, 231, 232, 233, 235, 236,

237, 238, 240, 241, 242, 247, 248, 250, 251, 252 Switzerland, 238, 240 symbiosis, 293 symbiotic, 292, 293 symbols, 66 symptoms, 36 syndrome, 7 synthesis, ix, 107, 111, 112, 113, 136, 139, 142, 160,

161, 174, 182, 195, 302 system analysis, 245, 264, 307

Index 328

systems, x, 93, 229, 230, 232, 233, 234, 240, 241, 242, 245, 246, 247, 250, 251

T

Taiwan, 139 tanks, 59 tar, 192, 194, 195, 196, 208, 209, 214 tar removal, 196, 209 targets, 4, 5, 99, 154, 156, 157, 161, 162, 173, 175,

181, 185, 205, 207, 246 tariffs, 100 taxation, 232, 240, 241, 242, 243, 249, 251 taxes, 240, 241, 242, 243, 248, 250 technological advancement, 205 technology, 231 Teflon, 33 TEM, 185 temporal, 72, 296, 304 Tennessee, 58 territorial, 293 territory, 305, 307, 308 Texas, 203 textiles, 21, 41, 60 thermal decomposition, 192 thermal efficiency, 193, 195 thermal energy, xi, 50, 51, 110, 173, 214, 217, 289,

298, 299, 300, 301, 307 thermal resistance, 257 thermal treatment, x, 191, 213, 214, 215, 226, 227,

298 thermodynamic, 44, 215, 216, 219, 288, 300 thermodynamic cycle, 300 thermodynamics, 125, 134 Thermophilic, 204, 205 threat, 3, 51 threats, 2, 47 threonine, 103 threshold, 14, 37 time, viii, 69, 72, 73, 74, 75, 76, 78, 79, 80, 84, 85,

86, 87, 88, 89, 91, 92, 230, 233, 234, 242 time frame, 11, 101 time series, 295 tobacco, 41, 42, 294 TOC, 6, 67 Tokyo, 138 toluene, 13, 196 topographic, 57, 59, 92 topology, 161, 183 total energy, 122, 195, 198, 246 total product, 43, 100 toughness, 306 toxic, 2, 3, 25, 32, 50, 191, 299, 302

toxic gases, 3 toxicity, 11, 305 TPA, 181 trade, 160, 161, 183, 230, 235, 236, 241, 248 trade-off, 161, 183 trading, x, 229, 230, 235, 236, 242, 249 trans, 15 transesterification, 100, 111 transfer, 33, 54, 146, 161, 162, 163, 254, 257, 258,

260, 266, 275 transformation, 28, 227, 292, 301 transformations, 299 transition, 70, 271, 275, 285 transparent, 303 transport, 3, 12, 16, 26, 43, 45, 49, 53, 62, 65, 99,

126, 128, 139, 256, 279, 293, 303, 309 transport costs, 293, 309 transportation, ix, 59, 97, 98, 99, 100, 110, 112, 115,

119, 120, 121, 123, 128, 131, 133, 136, 229, 243 transshipment, 152 traps, 173 travel, 26, 27, 47 treatment methods, vii, ix, 111, 187, 190, 206, 207,

231, 239 trees, 136 trend, 232 trial, 45, 204 trial and error, 45 triggers, 301 triglyceride, 105 triglycerides, 103, 105, 106, 114 Triglycerides, 114 turbulence, 300 Turkey, 238 typology, 72

U

Ukraine, 246 uncertainty, viii, 2, 21, 37, 66, 263, 288 UNFCCC, 39 uniform, 26 United Kingdom, 54 United Nations, 39, 67, 135, 297 United States, 2, 6, 54, 64, 100 urban areas, 191 urea, 118, 128 US Army Corps of Engineers, 12, 13, 65 USEPA, 50, 57, 59, 65

Index 329

V

vacuum, 9, 27, 141, 193 values, viii, 12, 13, 24, 26, 37, 38, 39, 41, 43, 45, 56,

58, 70, 74, 75, 76, 78, 79, 80, 85, 94, 122, 125, 126, 131, 165, 166, 167, 195, 199, 216, 217, 224, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 304

vapor, 13, 16, 21, 26, 47, 49, 124 variability, 42, 50, 298 variables, 42, 152, 153, 160, 290 variance, x, 253, 263, 264, 285, 287 variation, 241 VAT, 241 vegetable oil, 98, 100, 103, 111 vegetables, 115 vegetation, vii, 1 vehicles, 100, 120, 236 velocity, 45, 78, 79, 80, 81, 82, 83, 259 ventilation, xi, 253, 258, 287, 288 Victoria, 1, 137 vinyl chloride, 13, 37 viscosity, 12, 202 vision, 35, 103 voids, 31 volatilization, 16 vomiting, 35

W

waste disposal, vii, 1, 2, 21, 39, 40, 61, 66, 129, 290, 303

waste disposal sites, vii, 1, 21, 61 waste imports, 240 waste incineration, x, 229, 230, 231, 232, 233, 235,

236, 237, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 250, 251, 299

waste management, ix, x, 2, 3, 4, 53, 65, 95, 187, 189, 203, 207, 214, 229, 232, 233, 234, 235, 236, 240, 243, 244, 245, 246, 247, 248, 249, 251, 252, 309

waste products, 290, 307 waste treatment, x, xi, 64, 196, 226, 227, 229, 230,

231, 232, 233, 235, 237, 239, 242, 243, 245, 246, 247, 289, 308

wastes, vii, 1, 2, 4, 7, 8, 13, 16, 21, 23, 25, 26, 32, 44, 47, 60, 61, 65, 70, 102, 108, 193, 195, 196, 203, 294, 295, 298, 299, 300, 301, 302, 305, 307, 308, 309

wastewater, ix, 10, 129, 138, 187, 188, 189, 202, 203, 204, 211

wastewater treatment, ix, 10, 129, 187, 188, 189, 202, 203, 211

wastewaters, 116, 118, 119 water evaporation, 192, 254, 257, 281 water gas shift reaction, 112 water quality, 6 water quality standards, 6 water table, 26, 27 water vapor, 13, 21 water vapour, 49, 79, 281 water-soluble, 192, 200 web, 134, 203 wells, 8, 9, 10, 32, 33, 47, 55, 59 Western Europe, 247, 295 wetting, 256, 257 wheat, 104, 108, 109, 210 wind, viii, 97, 98, 244 winter, 57, 262 Wisconsin, 30, 65 wood, ix, 39, 41, 42, 60, 97, 98, 99, 100, 102, 108,

128, 129, 130, 137, 192, 193, 199, 208, 209, 210, 215, 240, 244, 294, 307

wood products, 41, 42, 294 wood waste, 192, 244, 307 woods, 240 word of mouth, 13 work, 231, 248 workers, 32, 36 World Bank, 138 World Health Organization, 64 writing, 242

X

Xylan, 109 xylene, 196

Y

yield, 3, 12, 15, 16, 62, 76, 105, 114, 117, 130, 193, 195, 196, 199, 200, 205, 207

Z

zeolites, 49, 212 zinc, 25, 209

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