A Methodology for Environmental Assessment – Norwegian ......Asplan Viak AS has been lead partner...

A Methodology for Environmental Assessment – Norwegian High Speed Railway Project Phase 2

Final report rev. 1

Jernbaneverket March 2011

A Methodology for Environmental Assessment – Norwegian High Speed Railway Project Phase 2 2

JERNBANEVERKET Asplan Viak AS



PREFACE

Asplan Viak As with partners MiSA, Verkehrswissenschaftliches Institut Stuttgart GmbH (VWI Stuttgart) and Brekke & Strand Akustikk AS have been engaged by The Norwegian Rail Administration to carry out the project ”Environmental analyses” as part of Phase 2 of the High Speed Rail Assessment in Norway.

Asplan Viak AS has been lead partner with responsibility for the project management and coordination of different subjects, both within this specific assignment and with the other studies which are part of Phase 2.

Asplan Viak has been responsible for developing an assessment methodology for the following subjects:

• Subject 1 - Landscape analyses • Subject 2 - Environmental intervention effects • Subject 3 - Effects on noise

Part of Subject 3 – effects on noise - has been carried out in collaboration with Brekke and Strand Akustikk AS, represented by Dr. ing Arild Brekke.

VWI Stuttgart has been responsible for the other part of Subject 3 which concerns developing a methodology for assessing effects on energy consumption. VWI’s representative has been Dr.ing. Harry Dobeschinsky.

MiSA, represented by PhD Håvard Bergsdal, has been responsible for developing a methodology for Subject 4 – Assessment of climate related environmental effects.

Sandvika, Norway, 1th of March 2011

Siv. ing Randi Birgitte Svånå

Project Manager



TABLE OF CONTENTS

Summary ..............................................................................................................................13

1 Introduction ................................................................................................................21

1.1 Background ............................................................................................................21

1.2 Challenges .............................................................................................................21

1.3 Methodology ..........................................................................................................22

Subject 1 and 2: Landscape and intervention effects ...........................................................25

2 Method for assessing landscape and environmental intervention effects ...................25

2.1 Purpose and functionality of method ......................................................................25

2.2 General approach to method development .............................................................25

2.3 State of the art ........................................................................................................26

2.4 General description of method developed for this study .........................................31

3 Coverage of topics .....................................................................................................32

3.1 Landscape .............................................................................................................32

3.1.1 Landscape regions, description and categorisation of landscape ........................32

3.1.2 Mapped and classified landscape data ...............................................................33

3.1.3 Other datasets which are relevant as a basis for the analysis .............................34

3.2 Environmental intervention effects ..........................................................................35

3.2.1 Natural environment ...........................................................................................35

3.2.2 Water resources .................................................................................................35

3.3 Other topics ............................................................................................................36

4 Value classification of topic and area .........................................................................36

4.1 General approach ..................................................................................................36

4.2 Value ratings - landscape .......................................................................................37

4.2.1 Existing value ratings for landscape data ............................................................37

4.2.2 Derived value ratings for landscape data ............................................................37

4.3 Value classifications – environmental intervention ..................................................38

4.3.1 Existing value ratings for the natural environment theme ....................................38

4.3.2 Derived value classification for the natural environment theme ...........................39



4.3.3 Value classification for water resources ..............................................................39

5 Magnitude of effect and conflict potential ...................................................................40

5.1 General approach ..................................................................................................40

5.1.1 Magnitude of effect and conflict potential - landscape .........................................40

5.1.2 Magnitude of effect and conflict potential - natural environment ..........................41

5.1.3 Magnitude of effect and conflict potential - water resources ................................42

5.2 Overall measure of conflict potential .......................................................................42

5.2.1 Proposed approach to assessing conflict potential ..............................................42

5.2.2 Ranking of alternative concepts ..........................................................................43

6 Establishing data models ...........................................................................................44

6.1 Data capture ..........................................................................................................44

6.2 List of themes and coverage ..................................................................................46

6.2.1 Themes with national data coverage...................................................................46

6.2.2 Data coverage at county level .............................................................................47

6.2.3 Municipal coverage of relevant themes ...............................................................50

6.3 Models for analysis of impact .................................................................................51

Subject 3: Effects on energy and noise ...............................................................................55

7 Energy .......................................................................................................................55

7.1 Introduction ............................................................................................................55

7.2 Basic information for energy consumption calculations ..........................................55

7.2.1 Basic information on vehicle dynamics ...............................................................55

7.2.2 Calculation of energy consumption .....................................................................57

7.2.3 General assumptions ..........................................................................................58

7.2.4 Technical train data ............................................................................................60

7.2.5 Efficiency degree of the tractive system ..............................................................71

7.2.6 Infrastructure scenarios ......................................................................................72

7.3 Specific energy consumption of trains ....................................................................75

7.3.1 Passenger load factor effects..............................................................................75

7.3.2 Track gradient effects .........................................................................................76



7.3.3 Permitted track speed impact and train comparison ............................................77

7.3.4 Tunnel impact on specific energy consumption ...................................................78

7.3.5 Effects of intermediate stops ...............................................................................80

7.4 Infrastructure design effects ...................................................................................84

7.4.1 “Steep and straight” vs. “flat with a detour”..........................................................84

7.4.2 Running into inclines at Vmax ...............................................................................86

7.4.3 Continuous vs. intermittent inclines .....................................................................87

7.5 Effects of traffic operations on energy consumption ...............................................89

7.5.1 Economical driving: coasting before stops ..........................................................89

7.5.2 Alignment of crossing and passing loops ............................................................90

7.5.3 Effects of train crossing locations and power supply characteristics on energy consumption .....................................................................................................................92

7.6 Conclusion .............................................................................................................94

8 Noise .........................................................................................................................97

8.1 Introduction ............................................................................................................97

8.2 Rolling stock ...........................................................................................................98

8.2.1 EU requirement for noise from rolling stock ........................................................98

8.2.2 Noise sources in rolling stock..............................................................................98

8.2.3 Train suppliers and noise data of the current high speed trains ..........................99

8.2.4 Future trends in development of high speed trains............................................ 100

8.3 Track systems ...................................................................................................... 100

8.3.1 State of the art for track systems ...................................................................... 100

8.3.2 Track system for the calculations in project Phase 3 ......................................... 101

8.4 Noise calculations ................................................................................................ 103

8.4.1 Noise limits in regulations ................................................................................. 103

8.4.2 Norwegian calculation method for conventional trains and speeds ................... 103

8.4.3 Corrections for high speed trains ...................................................................... 104

8.4.4 Calculation tools ............................................................................................... 105

8.4.5 Preliminary guidelines for planning of high speed railway lines ......................... 106



8.4.6 Calculation method for project Phase 3 ............................................................ 108

8.5 Vibration ............................................................................................................... 109

8.5.1 Vibration limits in regulations ............................................................................ 109

8.5.2 Calculation method for conventional speeds ..................................................... 109


8.5.4 Vibration calculation in project Phase 3 ............................................................ 111

8.6 Ground borne noise.............................................................................................. 112

8.6.1 Ground borne noise limits in regulations ........................................................... 112

8.6.2 Calculation for conventional trains and speeds ................................................. 112


8.6.4 Calculation method for project Phase 3 ............................................................ 114

8.7 Conclusions ......................................................................................................... 114

Subject 4: Climate related environmental effects ............................................................... 117

9 Introduction .............................................................................................................. 117

9.1 Background to the study ....................................................................................... 117

9.2 Lessons from previous assessments of HSR ....................................................... 118

9.2.1 Review of studies .............................................................................................. 118

9.2.2 General conclusions regarding transferability and adaptation to NHSRA .......... 122

9.3 Introduction to life-cycle assessment (LCA) .......................................................... 125

9.3.1 Development of methods .................................................................................. 125

9.3.2 General framework ........................................................................................... 126

10 Goal and scope........................................................................................................ 129

10.1 Scope of this report .............................................................................................. 129

10.1.1 Goal and scope definition ................................................................................. 129

10.1.2 Inventory analysis, sources and structure ......................................................... 134

10.1.3 Impact assessment ........................................................................................... 134

10.2 Structure and organisation for transport system modelling ................................... 135

10.3 Tracking emissions in component-based inventories............................................ 137

10.4 Connection to other project groups and planning for Phase 3 .............................. 139



10.4.1 Connection to other project groups ................................................................... 139

10.4.2 Information need from physical corridor planning, Phase 3 ............................... 141

10.5 Emissions distribution ........................................................................................... 142

10.5.1 Assessment time and temporal distribution of emissions .................................. 142

10.5.2 Spatial distribution, national and total emissions ............................................... 144

10.5.3 Alternative transport modes .............................................................................. 144

10.6 Lifetime of infrastructure components ................................................................... 145

11 Component based LCI approach for infrastructure ................................................... 147

11.1 Inventory data sources ......................................................................................... 147

11.1.1 Electricity mixes ................................................................................................ 148

11.2 Railway infrastructure ........................................................................................... 153

11.2.1 Open track section ............................................................................................ 155

11.2.2 Tunnel section .................................................................................................. 155

11.2.3 Bridge section ................................................................................................... 155

11.2.4 Material and energy use ................................................................................... 155

11.2.5 Single track corridors ........................................................................................ 156

11.2.6 Maintenance and operation of railway infrastructure ......................................... 157

11.3 Road infrastructure ............................................................................................... 157

11.3.1 Open road section ............................................................................................ 158

11.3.2 Tunnel section .................................................................................................. 158

11.3.3 Bridge section ................................................................................................... 159

11.3.4 Maintenance and operation of road infrastructure ............................................. 159

11.3.5 Norwegian road composition ............................................................................ 160

11.4 Air infrastructure ................................................................................................... 160

11.4.1 Airport infrastructure ......................................................................................... 161

11.4.2 Maintenance and operation of airport facilities .................................................. 162

11.4.3 Demolition......................................................................................................... 162

11.4.4 Allocation for airport infrastructure .................................................................... 162

12 Component based LCI for manufacturing and operation of transport vehicles ......... 163



12.1 Railway rolling stock and operation ...................................................................... 163

12.1.1 HSR rolling stock manufacturing and maintenance ........................................... 163

12.1.2 Rail operation ................................................................................................... 164

12.2 Road rolling stock and operation .......................................................................... 167

12.2.1 Passenger cars ................................................................................................. 167

12.2.2 Bus services ..................................................................................................... 174

12.2.3 Road freight ...................................................................................................... 175

12.3 Air flying stock and operation ............................................................................... 176

12.3.1 Flying stock ....................................................................................................... 176

12.3.2 Operation .......................................................................................................... 176

12.3.3 Maintenance ..................................................................................................... 179

13 Main findings ........................................................................................................... 179

13.1 Lessons from other studies .................................................................................. 179

13.2 Solution: component-based emissions inventory .................................................. 180

13.3 Phase 3 ................................................................................................................ 181

References ......................................................................................................................... 183

Appendix A: Legislation and regulations relevant to landscape, environment and water .... 195

A 1 Landscape ................................................................................................................ 195

A 1.2 Den europeiske landskapskonvensjonen ........................................................... 195

A 1.3 Stortingsmelding nr. 26 (2006-2007) .................................................................. 195

A 1.4 Stortingsproposisjon nr. 1S (2009-2010) ............................................................ 195

A 1.5 Naturmangfoldloven (Lov 19. juni 2009 om forvaltning av naturens mangfold.) .. 195

A 1.6 Plan- og bygningsloven (Lov 2008-06-27 nr. 71: Lov om planlegging og byggesaksbehandling.) ............................................................................................... 195

A 1.7 Kulturminneloven ............................................................................................... 196

A 2 Natural environment ................................................................................................. 196

A 2.1 Internasjonale konvensjoner som omhandler biologisk mangfold ....................... 196

A 2.2 Stortingsmelding nr. 42 (2000-2001) Biologisk mangfold – sektoransvar og samordning ................................................................................................................. 197

A 2.3 St.meld. nr. 24 (2003 – 2004) Nasjonal transportplan 2006–2015 ...................... 197

A 2.4 Stortingsmelding nr. 26 (2006-2007) .................................................................. 197

A 2.5 Naturmangfoldloven (Lov 19. juni 2009 om forvaltning av naturens mangfold.) .. 198



A 2.6 Plan- og bygningsloven (Lov 2008-06-27 nr. 71: Lov om planlegging og byggesaksbehandling.) ............................................................................................... 198

A 3 Water resources ....................................................................................................... 198

A 3.1 Vannrammedirektivet ......................................................................................... 198

A 3.2 Vannforvaltningsforskriften ................................................................................. 198

A 3.3 Lov om vassdrag og grunnvann ......................................................................... 198

A 3.4 Lov om vern mot forurensninger og avfall med tilhørende forskrifter .................. 199

A 3.5 Plan- og bygningsloven med tilhørende forskrifter .............................................. 199

A 3.6 Naturmangfoldloven ........................................................................................... 200

A 3.7. Forskrift om vannforsyning og drikkevann (Drikkevannsforskriften) ................... 200

Appendix B Energy ............................................................................................................. 201

B1 Specific energy consumption values .......................................................................... 201

B2 Running into inclines at Vmax ...................................................................................... 208

Appendix C : Noise from rolling stock. State of the art. ....................................................... 211

C1. Noise sources .......................................................................................................... 211

C2. Suspension systems ................................................................................................ 216

Appendix D: Track systems. State of the art concerning noise and vibration ...................... 218

D1. Ballasted track .......................................................................................................... 218

D2. Slab track ................................................................................................................. 219

Appendix E: Vibration calculation and remedial actions. State of the art ............................. 221

E1. Mostly used calculation method in Norway ............................................................... 221

E2. Remedial actions ...................................................................................................... 222

Appendix F: Ground borne noise calculation and remedial actions. State of the art ............ 224

F1. Calculation of ground borne noise ............................................................................ 224

F2. Remedial actions ...................................................................................................... 225



SUMMARY

Background

The Norwegian Rail Administration has been given a mandate from the Ministry of Transport and Communication to assess the feasibility of high-speed railway lines in southern Norway (NHSRA). The deadline for the assessment and the Rail Administration’s recommendations to the Ministry is February 1st 2012. The assessment shall include recommendations regarding which long-term strategies shall form the basis of the development of long distance passenger train transport in the southern part of Norway.

The assessment will be carried out according to three predefined phases, and this report has been developed in response to the contract regarding environmental analyses in Phase 2. The contract for the environmental aspects is one of six, and the other contracts for Phase 2 deal with market analyses, railway specific planning and development, financial and socio-economic assessments, different organisational, contractual and commercial issues, as well as technical and safety evaluations.

This report describes a method and the premises for environmental analysis regarding:

• Subject 1: Landscape analyses • Subject 2: Environmental intervention effects • Subject 3: Effects on noise and energy consumption • Subject 4: Assessment of climate related environmental effects

A summary of the approach adopted for each subject is provided below.

Subject 1 and 2: Landscape and intervention effects

Introduction

The purpose of this study has been to develop a methodology for analysing landscape and environmental effects of alternative rail solutions during Phase 3. The methodology should enable a comparison of effects within and between alternative concepts at an early stage of decision-making, and provide an evidence base for an initial filtering of alternatives.

Methodological approach

A review of some of the most widely used methods and models for impact assessment and landscape analysis in Norway, as well as a selection of international approaches, was used to identify ‘tried and tested’ concepts which could be adapted for high level analysis at a large geographical scale. As a result, the proposed methodology is based on a combination of value and sensitivity analysis (Kolbenstvedt et al. 2000) and a simplified impact assessment methodology applied by the Norwegian Public Roads Administration for evaluating strategic infrastructure concepts (Statens vegvesen 2008, 2010).

In brief, the methodology will consist of:

1. Mapping the characteristics of an area under each topic 2. Ascribing value/ importance/ sensitivity to the characteristics of the area



3. Describing the magnitude and potential conflict of proposals on these characteristics 4. Deriving an overall measure of potential conflict

The main focus will be on identifying areas of conflicting interests within the proposed high speed railway corridors. A GIS model will be built to aid the visualisation and analysis. The model will be based on ILARIS, AREALIS and Topographic Position Index.

In brief, the model building will constitute the following steps:

1. Data capture (collecting and verifying databases) 2. Extracting databases with existing value ratings for further analysis 3. Deriving databases and analysis of databases for exploring vulnerability. Identifying

methods for analysing impact. 4. Stage 1: Overall assessment of main corridors. Identifying “knock out areas” and data

gaps/ uncertainty. Establishing the need for further data capture from regional/local authorities.

5. Stage 2: Detailed analysis within corridors for evaluation of alternative railway lines. Implementing models from point 3.

Topic delimitation

For the purpose of this study, the landscape topic has been defined in terms of visual characteristics, including visibility, visual barriers and visual experience. This reflects the scope of work set out by Jernbaneverket and the way in which landscape assessment is usually undertaken for transport infrastructure initiatives in Norway. It is furthermore driven by the time restraints for undertaking the assessment in Phase 3.

It is proposed that the delimitation of the natural environment topic should reflect the definition used in Handbook 140 (Statens vegvesen 2006).

The analysis of water resources will cover a combination of user interests in the watercourse, changes in hydrology and water quality in the catchment. This reflects both the goals of the EU Water Framework Directive and the delimitation of water resources described in Handbook 140 (Statens vegvesen 2006).

Some of the data sets, including national parks, wilderness areas (INON), protected watercourses and potential world heritage sites, provide important information to both the assessment of landscape and environmental intervention effects. These data sources may therefore be used during both assessments, and the potential for double counting will need to be addressed in Phase 3.

Value classifications

Based on the literature review and the need for a method which enables a high level assessment of strategic alternatives, it is proposed to adopt a simplified approach to value ratings similar to that used by the Norwegian Public Roads Administration for strategic infrastructure concepts (Statens vegvesen 2008, 2010). This implies that most of the data included in the assessment will be data with existing value classifications (e.g. national, regional, local), and that they are ascribed a ‘high’ value rating during the analysis unless otherwise specified.



Conflict potential

Conflict potential will be assessed for each alternative rail concept as a combination of potential effects and their magnitude within the physical corridors, and the value/sensitivity of the affected areas and their characteristics.

Conflict scores will be based on professional judgement and described qualitatively. An overall measure of conflict will be derived for individual sections of the railway and/or for each topic, supported by a written justification.

Ranking of alternative concepts

In order to facilitate an initial sifting of high speed rail concepts, it is proposed that the alternatives are ranked according to their overall conflict potential. The ranking will be based on professional judgement supported by a written statement to ensure transparency and accountability.

Testing and refinement of methodology in Phase 3

The assessment of landscape and environmental intervention effects at a large geographical scale presents considerable challenges with regards methodology and data. The validity, reliability and coverage of data vary greatly for the different themes and geographical regions. In addition, the methodology has been developed in absence of the reference alternative which has yet to be defined by Jernbaneverket. As a result, certain assumptions will need to be revisited, and the proposed methodology for assessing landscape and environmental intervention will need to be tested, adjusted and refined in Phase 3.



Subject 3: Effects on energy and noise

Energy

The purpose of this study was to conduct an analysis of high-speed railways and trains in order to identify typical levels of energy consumption as well as to determine preferable train designs. To accomplish this, technical data was collected on international, high-speed trains. More than 50 infrastructure scenarios were developed, and different operations programs were tested. Using VWI’s software tool PULZUFA, the specific energy consumptions (measured in [Wh/seat-km]) for the different situations were estimated and compared with each other.

Rolling stock

One finding from the analysis is that two of the trains studied exhibit a significantly lower specific energy consumption than the others: the German ICE 3—in service since the year 2000—and the French AGV, which will shortly be put into service in Italy. From the characteristics of these trains, conclusions can be drawn regarding the requirements for energy-efficient and state-of-the-art high-speed trains as well as the future development of high-speed trains and their characteristics.

Three major factors can be pointed out that have a positive effect on the energy efficiency of trains:

1) The aerodynamic design of the train: a small cross section, in combination with an aerodynamic design of the front and favourable materials for the train’s surface. Especially at high speeds, energy consumption depends largely on the quality of aerodynamic design.

2) EMU trains: distribution of the tractive system components along the train increases performance and creates more passenger space.

3) The use of power converters with IGBT technology increases the efficiency degree of the train’s tractive system.

As for the future development of high-speed trains, more incremental improvements are expected than huge advances. This can be noted from the comparison of the specific energy consumptions of the ICE 3 and the AGV. Although these trains were introduced into service almost a decade apart, they both exhibit similar levels of specific energy consumption.

One reason behind these incremental improvements may be due to the restriction that the railway infrastructure has on the trains. Although high-speed trains have the potential to increase their energy efficiency via innovation in aerodynamics, lightweight construction, and technical component improvement, this potential is limited by the conditions of railway infrastructure with its long service life.

Infrastructure

More detailed analysis of the infrastructure design revealed that tunnels considerably affect the amount of energy consumed. The specific energy consumption in tunnels increases as the tunnel length or the quotient between a train’s and the tunnel’s cross section increases.



In contrast, the effect of different designs of track incline arrangements was found to be comparatively small.

Regarding the design of crossing loops on single-track lines, favourable layouts have been found. While there is no significant effect on flat terrain, on inclines the crossing loop should be built either in the form of a rhomboid, or in the form of a trapezoid with the siding reserved for the train travelling uphill.

For the possibility and the extent of energy recovery, the railway power supply system plays an important role. If power supply sections are interconnected and power supply stations are be connected to the public power supply network, energy recovered from using regenerative brakes can be used in the most flexible way.

Operation

With regards to train operations, economical driving, i.e. letting a train coast down to a certain speed instead of braking right away, was found to be energy-efficient only to a certain extent. If the coasting phase lasts for too long, the average train speed will decrease to levels unfitting of high-speed railway operations.

Concluding comment

The values for the specific energy consumption derived from the basic infrastructure scenarios serve well as input values to estimate the energy consumption of trains on potential railway lines. Combined with corrective factors and findings regarding the infrastructure design and traffic operations, they may lead to an early-stage energy consumption assessment for a set of possible railway alignments. However, in order to provide more detail and accuracy to the analysis, both the infrastructure and rolling stock need to be defined and modelled in greater detail as the characteristics of and even more importantly the interaction between the rolling stock and infrastructure significantly affect the overall energy consumption.

Noise

The Technical Specifications for Interoperability (TSI) for noise from high speed trains is lower than the measured values from recent high speed trains. It is expected that the new generation of high speed trains will meet the TSI limit for noise reach the noise limit. Up to a speed of around 300 km/h the noise from the contact rail /wheel is the dominating source. For higher speeds the aerodynamic noise is the dominating source, and the noise level increases strongly with increasing speed. The pantograph then is a dominating source. This noise is difficult to shield.

Slab track gives more noise than ballasted track, typically a 2 – 4 dB increase is found. Because of strong requirements to settlement of the slab which require stiffening of the ground, it is expected that slab track give less transmission of vibration to dwellings in soft clay conditions. However the soft ground in many areas in Norway may be a reason for choosing ballasted track.



It is recommended that the Nord 2000 method is used for the noise calculations. Input noise data from high speed trains will have to be measured. Measurements in Norway and Sweden are suggested in Phase 3. Calculations can be made for ballasted track and slab track for comparison.

Calculated vibration values will be very uncertain. It is necessary to collect more measured data from highs speed trains on clay. Measurements in Norway and Sweden are suggested in Phase 3. It is probable that the embankment must be stiffened in order to prevent problems with critical speed. Probably lime – cement piles must be established in places with soft clay.

Strict requirements on rail deflection imply that it will probably not be possible to reach the ground borne noise limit in many dwellings above blasted tunnels. For slab track in bored tunnels floating slab must be used when there are dwellings near to the tunnels.

Concerning calculations in Phase 3 a method in which contour lines representing the limit values for noise, vibration and ground borne noise are drawn on the maps for the corridors, is suggested. On the basis of GIS data the number of dwellings and people involved then can be calculated.



Subject 4: Climate related effects

Lessons from other studies

In a review of published studies for high-speed rail in Europe, the following summarises the main conclusions that were made:

• Comprehensive system boundaries are required for proper evaluation of HSR in the Norwegian context, with regards to infrastructure, rolling stock and operations

• Comparison with alternative transport modes requires that same or similar system boundaries are used for all modes

• Emissions from electricity production may be highly significant, even at low fractions of fossils in the electricity mix

• Scandinavian HSR concepts use relatively clean electricity for operation, implying that infrastructure development contributes the larger share of the greenhouse gas emissions per passenger

• Occupancy of seats on HSR corridors, and the degree of use of HSR infrastructure, controls the greenhouse gas emissions per passenger in Norway. Energy use per seat may be modelled with good detail, but energy use per passenger in HSR depends on corridor-specific factors

• Completed studies assume very different settings for the most important variables, leading to diverging results for seemingly same assessment

Solution: component-based emissions inventory

Model implementation

Based on the lessons drawn from reviewed studies, it is found that an emissions model for the various corridor alternatives to be assessed in Phase 3 needs to allow multiple infrastructure compositions, market situations and energy supply scenarios. It is proposed to solve this by a component-based emissions inventory, established through use of standardised life-cycle assessment methods.

The following approach is used to ensure a flexible yet transparent model:

• Use of a commonly accepted model approach: life-cycle assessment • Consistent use of database values for emissions: ecoinvent for all background

processes • Norwegian-based emissions modelling for construction of rail and road, given the

high importance for infrastructure to the total emissions estimate for HSR • Unit process detail implemented in a software for LCA: SimaPro • Parameter options for wide scenario analysis • Equivalent coverage for all competing transport modes, to properly reflect the effect

of market transfer from car, bus and air transport for all HSR concepts

Inputs from the complementing work groups in NHSRA will be implemented in the emissions model in Phase 3, together with the alignment proposals from physical planning for corridor alternatives.



Environmental assessment time

Relevant environmental assessment guidelines propose a 60 year assessment time. Some major components have technical lifetimes up to 100 years. If HSR concepts are developed for Norway, they should have an impact for the national transport system for a long time into the future. It is therefore proposed an environmental assessment time up to 100 years, although market information may not be made for the entire period.

Emissions in construction are evaluated separate, to appear in the period up to first year of operation. Maintenance inputs, operational requirement and rolling stock manufacture emissions are annualised based on technical lifetime estimates.

Spatial and temporal distribution of emissions

Emissions from infrastructure, rolling stock and operation of rail, road and air transport systems are split between national emission and emissions appearing abroad. This allows easy estimation of the effect on national greenhouse gas emissions with and without development of HSR concepts.

Scenario considerations are systematically incorporated into the model, for all transport modes through the assessment period.

Norwegian inventory sources selected to describe rail and road infrastructure

Inventories for the transport infrastructure components are compiled from various sources. The main sources for road and rail infrastructure systems are found in reports for the Norwegian transport authorities (road: Statens Vegvesen; rail: Jernbaneverket). These projects have been carried our specifically to evaluate the environmental profile of infrastructure components in the Norwegian context, and are therefore considered the most relevant source for inventories to describe the relevant infrastructure for the task here.

Phase 3

This subject forms the premises for evaluation of corridors for different HSR concepts. It fulfills the goal and scope phase of life-cycle assessment, and partly also the inventory stage. Several links to the complementing working groups in the assessment project are identified, where data gaps will be filled by input for specific HSR concepts in Phase 3. The data gaps are identified and listed throughout the report, and summarised in a separate section.

Main factors are expected to be within the market modelling and physical planning, although identified also in the other groups. Energy modelling is a separate task within the environmental work package and is discussed elsewhere in this report.

A systems analysis such as the Norwegian HSR assessment relies on multiple mutually dependent factors, and it is therefore expected that several iterations must be made for each of the corridors. Concluding results regarding the climate-related environmental performance of high-speed rail in Norway may not be drawn before venturing into Phase 3.



1 INTRODUCTION

1.1 Background

The Norwegian Rail Administration has been given a mandate from the Ministry of Transport and Communication to assess the feasibility of high-speed railway lines in southern Norway (NHSRA). The deadline for the assessment and the Rail Administration’s recommendations to the Ministry is February 1st 2012. The assessment shall include recommendations regarding which long-term strategies shall form the basis of the development of long distance passenger train transport in the southern part of Norway.

The assessment will be carried out according to three predefined phases, and this report has been developed in response to the contract for environmental analyses for Phase 2. The contract for the environmental aspects is one of six, and the other contracts deal with market analyses, railway specific planning and development, financial and socio-economic assessments, different organisational, contractual and commercial issues, as well as technical and safety evaluations.

This report describes a method and the premises for environmental analysis regarding:

• Subject 1: Landscape analyses • Subject 2: Environmental intervention effects • Subject 3: Effects on noise and energy consumption • Subject 4: Assessment of climate related environmental effects

1.2 Challenges

There have been several challenges in developing such a method. The following aspects are emphasised:

1. High level analysis at a large geographical scale within a limited time frame 2. Development of a baseline for analysis and coordination between contractors

High level analysis at a large geographical scale within a limited time frame

The main challenge has been to develop a method for high level analysis at a large geographical scale. In addition, this method shall be applied in connection with the physical planning of corridors within the time frame of Phase 3, which will be between 6 to 9 months.

The methodology will be used for a feasibility study prior to any formal planning required by the Department of Finance and the Norwegian Planning and Building Act. The alternatives which perform best as a result of the analyses in Phase 3 may subsequently be included in a Konseptvalgutredning - a high level consideration of strategic rail concepts. The assessment therefore has to be of such a quality and level of detail that it provides a baseline for decisions regarding any further planning. If a decision is made to proceed to the formal planning stage, an assessment of environmental effects would need to be compatible with the requirements of the Department of Finance and the Norwegian Planning and Building Act.



Development of a common baseline for analysis and coordination between contractors

In Phase 2, studies have been carried out within the following work packages (WP):

WP 1. Market analysis (Atkins) WP 2. Planning & development (WSP) WP 3. Financial and socio-economic assessment (Atkins) WP 4. Commercial & contractual strategies (PWC) WP 5. Technical & security analysis (Pöyry Infra) WP 6. Environmental analysis (Asplan Viak)

In order to develop a methodology (Phase 2) and to undertake the environmental analysis (Phase 3) for WP 6, it is necessary to develop a basis for the analysis regarding the premises for market analysis, technical concepts for infrastructure and rolling stock.

For both phases there is therefore a need for coordination and input from the other studies listed above. The coordination in Phase 2 has been achieved through regular project meetings arranged by Jernbaneverket, and to some extent through individual meetings between the contractors.

1.3 Methodology

This report has been prepared in response to Jernbaneverket’s invitation to tender dated 25th of June 2010 and subsequent negotiations concerning contract and scope of work.

Within the framework provided by Jernbaneverket and the approach adopted to the challenges described above, premises have been derived for the physical planning and a methodology for analysing each of the environmental subjects. Recommendations for a methodological approach for each subject are outlined in the following chapters.

The environmental subjects vary greatly in terms of their scope and character, and it has not been part of the assignment to recommend a methodology for collating all the assessments. The following should nevertheless be highlighted:

• A holistic approach is proposed for assessing climate impacts, which includes the consideration of effects on other transport modes such as road and air transport. Assumptions have been made regarding alternative development scenarios for road and air transport in line with internationally recognised methods.

• Achieving a similarly holistic approach to the assessment of the other topics (in particular noise, landscape, water resources and the natural environment) would have required information about the physical effects of infrastructure for road and air transport. As this information is not available, the assessment methodology has been developed with the aim of differentiating between the different high speed rail concepts, thereby facilitating a comparison within and between corridors.



Based on the above, it would not be appropriate to attempt collating the outcomes of the different assessments. Furthermore, the recognised approach to impact assessment in Norway is to assess energy use, climate and noise in monetary terms, whereas the other topics are assessed qualitatively.

Finally, it is important to note that the methodologies proposed for assessing the various environmental subjects covered in this report will need to be tested once planning of the actual corridors starts. Adjustments and refinements may therefore be necessary in Phase 3, and the proposed methodologies in this report should therefore not be regarded as definitive.



SUBJECT 1 AND 2: LANDSCAPE AND INTERVENTION EFFECTS

2 METHOD FOR ASSESSING LANDSCAPE AND ENVIRONMENTAL INTERVENTION EFFECTS

2.1 Purpose and functionality of method

The purpose of this task has been to develop a methodology and set of parameters which can be used for analysing landscape and environmental effects of alternative rail corridors during the physical/ corridor planning stage in Phase 3. The methodology should enable an analysis and comparison of the landscape and environmental effects of alternative solutions within and between alternative corridors in Phase 3, including:

• Analysis of the baseline/ today’s situation. • Identification of appropriate areas for high-speed railway lines as well as unsuitable

areas. • Illustration/identification of how routes and profiles of the high speed railway lines can

be adjusted to the landscape and the natural environment in the various corridors. • Identification of possible impacts such as landscape fragmentation, loss of habitat,

barriers, noise and changes in hydrology in water and marshland. • Illustration/identification of how the railway lines and profiles can be adapted to the

environment and the plant and animal life in the study area. • Identification of barrier effects caused by the use of tunnels compared to using open

lines. • Ultimately to identify the best fitting high-speed railway lines in respect to landscape

and environmental intervention effects. The analyses in Phase 3 will be used to identify potential conflicts between the railway concepts and landscape and environmental interests at an early stage of decision-making, and provide an evidence base for an initial filtering of alternatives.

2.2 General approach to method development

The approach to developing this method has been to:

• Review existing methods for analysis and assessment of landscape and environmental intervention effects, and to

• Identify aspects of existing methods which could be adapted for high level analysis at a large geographical scale.

This has enabled the use of ‘tried and tested’ concepts and methodologies whilst at the same time providing the necessary flexibility to adapt and further develop existing approaches for use at an overarching level.

The methodology has furthermore been developed in such a way that it will enable analyses according to Norwegian legislation and regulations for landscape, the environment and water resources1.

1 An overview of the relevant Norwegian legislation and regulations is provided in Appendix F.



2.3 State of the art

A brief review has been carried out of some of the most widely used methods for impact assessment and landscape analysis in Norway, as well as a selection of international methods, in order to give a description of the “state of the art” and determine whether aspects of existing methods could enable an evaluation and comparison of high speed rail solutions at the required level of detail.

A list of methods reviewed is provided below, followed by a brief summary and conclusion regarding the applicability and transferability of underlying concepts to the current study. The list of literature is not intended to be comprehensive, and the review was severely restricted by the time and resources available. A more comprehensive review of available methods, models and experiences from comparative analyses in other countries would undoubtedly have resulted in other valuable contributions.

Methods included in the literature review:

• Handbook 140 for environmental assessment - Håndbok 140, Statens vegvesen 2006 (Statens vegvesen 2006)

• Landscape analysis, methodology for the evaluation of landscape character and landscape value - Landskapsanalyse, Fremgangsmåte for vurdering av landskapskarakter og landskapsverdi, Direktoratet for naturforvaltning og Riksantikvaren (2010)

• National referencing system for landscape - Nasjonalt Referansesystem for landskap, Oscar Pushmann 2005 (Pushmann 2005)

• Value and sensitivity analysis - Verdi- og sårbarhetsanalyser - Chapt. 1C in Kolbenstvedt et al. (2000).

• Evaluation of strategic concepts, non-monetised effects - Konseptvalgutredning, vurdering av ikke-prissatte virkninger. E18 Langangen – Grimstad, Statens vegvesen Region Sør (Statens vegvesen 2008) og Grenland 2010, Statens vegvesen Region Sør (Statens vegvesen 2010).

• UK Transport Analysis Guidance – WebTAG Unit 3.3.6: The Environment Capital Approach (Department for Transport 2003)

• ILARIS Intrinsic Landscape Aestethic Resource Information System http://www.esri.com/news/arcnews/winter0506articles/winter0506gifs/ilaris-datamodel.pdf

• AREALIS http://www.ngu.no/kart/arealis/ • Landscape Capacity Evaluation and Visual Impacts Simulation - a GIS Approach

http://proceedings.esri.com/library/userconf/europroc97/7planning/p2/p2.htm • Topographic Position Index

http://www.jennessent.com/downloads/tpi-poster-tnc_18x22.pdf

“Handbook 140 for environmental assessment” (Håndbok 140, Statens vegvesen 2006) is arguably the most widespread impact assessment methodology used in Norway, and can be described as a set of tools for assessing both monetised and non-monetised impacts, including landscape/ townscape; local environment/sports and recreation (friluftsliv); biodiversity/flora/fauna (naturmiljø); cultural heritage and natural resources. For non-monetised impacts, it sets out a process of ascribing value (verdi) to the areas which might be affected, magnitude of effect (omfang), and finally an impact score (konsekvens) on a 9-point scale from very large positive (++++) to very large negative (- - - -). Criteria for ascribing

http://www.esri.com/news/arcnews/winter0506articles/winter0506gifs/ilaris-datamodel.pdf

http://www.ngu.no/kart/arealis/

http://proceedings.esri.com/library/userconf/europroc97/7planning/p2/p2.htm




value and magnitude are defined for each topic, and impact scores are derived according to a pre-defined process for collating value and magnitude (konsekvensviften).

Conclusion: The methodology set out in Handbook 140 is primarily designed for project level assessments, and is not directly applicable to a high level assessment of strategic alternatives.

“Landscape analysis; a methodology for the evaluation of landscape character and landscape value” (Direktoratet for naturforvaltning og Riksantikvaren (DN / RA) 2010) is an in-depth approach for analysing landscapes but does not represent a complete methodology for assessing landscape impacts. The DN / RA 2010 report is due to be complemented by two guidance documents for handling the landscape theme in environmental impact assessment of wind power, however these guidance documents are not yet available.

Conclusion: The approach to landscape analysis developed by DN / RA is too detailed for this early stage of planning where an overarching analysis is required.

The national referencing system for landscape (Pushmann 2005) constitutes a map and description of 45 landscape regions (landskapsregioner) covering the whole of Norway. The landscape regions are defined by a set of common components and characteristics as well as distinctive regional qualities, problem areas or trends. The landscape character is described in terms of spatial and visual landscape components. The 45 landscape regions are divided into 444 sub-regions, which are mapped but not described.

Conclusion: This important knowledge base of landscape regions comprises a readily accessible description of landscape characteristics at an overarching/strategic level.

Value and sensitivity analysis (Kolbenstvedt et al. 2000). A method for assessing an area in terms of its environmental value and vulnerability to impacts. The method provides a basis for identifying areas which:

1. Could be developed with little or no conflicts of interest (road infrastructure or other developments) and

2. Should not be developed.

Conclusion: Value and sensitivity analysis is well suited for early stage planning where it can help to identify areas of conflicting interests and minimise conflicts later in the planning process. Value and sensitivity analysis does not represent a complete impact assessment methodology.

Evaluation of strategic concepts, non-monetised effects (Statens vegvesen 2008, 2010). The methodology used in these two studies is in essence a simplified version of the project level method described in Handbook 140 (Statens vegvesen 2006), adapted for assessing impacts at a more strategic, overarching level of planning. The assessment is as a result less detailed than a formal environmental impact assessment, and identifies instead the conflict potential of strategic road alternatives for non-monetised impacts. Alternatives are scored for each impact topic which forms the basis for an overall scoring of alternatives.

Conclusion: This is an interesting example of how a traditional environmental impact assessment methodology (Handbook 140) could be adapted to enable a high level



assessment. Some of the simplifications and underlying assumptions would require further scrutiny but it could provide a good starting point for the current methodology.

UK Transport Analysis Guidance – WebTAG unit 3.3.6: The Environment Capital Approach (Department for Transport 2003). A methodology developed by the UK Department for Transport (DfT) for appraising impacts of both projects and strategic transport options on Landscape, Heritage of Historic Resources, Biodiversity and Water Environment. This methodology is based on a qualitative 'environmental capital' style approach, in contrast to the more quantitative methodologies developed for e.g. noise, air quality and greenhouse gases. The impacts of a strategic proposal on landscape can be assessed by applying the following three stage approach:

1. Describe the key characteristics of the landscape being impacted by the proposal, using judgement to identify key characteristics

2. Appraise the environmental capital of the landscape, by assessing the importance of the key characteristics; why and who they are important to; and their inter-relationships with other environmental attributes

3. Describe how the strategy will impact on the landscape. In the absence of detailed information, it may only be possible to say whether an option has a positive, neutral, or negative impact on the environmental capital of the landscape.

Conclusion: This methodology provides a broad framework which can be applied to a high level assessment of strategic alternatives.

ILARIS is a model for landscape analysis, developed by landscape architects Grant, Jones & Jones in the USA. The model was developed in connection with a landscape analysis of the Pudget sound on the west coast of the USA, and was awarded the ASLA prize in 2006. The method forms the basis for a GIS model, but is also interesting as a model for mapping landscape and for the delimitation of the landscape theme. The description of the method is relatively similar to that of “Landscape analysis” (Direktoratet for naturforvaltning og Riksantikvaren 2010), but it is based on a consideration of models. It also describes a methodology for aggregating topics to form a landscape map, and the implementation of more advanced geographical relationships (visibility) in the landscape analysis.

Conclusion: The model cannot be directly applied to the current study, but is interesting as a concept and provides inspiration for building a GIS model for the current methodology. The method is also interesting for its holistic approach to landscape and for using catchment areas and ecology to facilitate a better understanding of environmental management across different themes. This also ‘solves’ some of the problems associated with defining landscape areas in areas where there is no available maps/data. Thematically the model is not particularly relevant, and here the Norwegian models will be more applicable e.g. AREALIS, Landscape analysis (Direktoratet for naturforvaltning og Riksantikvaren 2010), NIJOS’ referencing system etc.



Figure 2-1. Illustration of the ILARIS model

AREALIS is a program for spatial documentation, and has been incorporated into Norge Digitalt. It consists of a catalogue and description of many of the datasets which will be relevant to the analysis of landscape and intervention effects. AREALIS is built up thematically according to the model illustrated below.

Conclusion: The relevant models will be central in the subsequent work and will be presented in further detail in the construction of the GIS model. The data models in AREALIS have a relatively complex structure, due to the fact that there has been developed a separate data structure based on the SOSI standard, as well as defined collaboration agreements and responsibilities between different governmental, regional and local bodies. The geographical coverage and data quality varies. There will therefore be a need to identify geographical coverage for the different topics to be included in the current methodology and develop models which can ‘replace’ or supplement information in areas with insufficient coverage.



Data Structure

‘Norge Digitalt’ (‘Norway Digital – AREALIS)

Figure 2-2. Illustration of the data structure used in ‘Norge Digitalt’ (AREALIS)

(Link: Thematic data in 'Norge Digitalt')

Landscape Capacity Evaluation and Visual Impacts Simulation - a GIS Approach. This model was developed at the Technical University of Lisbon (Centro de Valorização de Recursos Minerais (CVRM), Instituto Superior Técnico) in connection with urban development in Lisbon. The model describes the landscape’s visual capacity based on the landscape value and its sensitivity to further development. The model also describes visual sensitivity according to a scale of ‘intervisibility’, in other words how visible different areas are in a given landscape. The illustration below shows a simplified diagram of the model which is used.

Figure 2-3. Model of a scenic landscape capacity evaluation

http://www.statkart.no/Norge_digitalt/Norsk/Temadata/



Conclusion: This model is developed for a particular situation, and for a particular landscape, and is therefore not directly applicable to the current study. Technically however, it adopts a number of approaches which would be interesting to consider.

Topographic Position Index is a simple description of landscape form based on two scales, main forms and minor forms, which is similar to the classification used in NIJOS. However, this method is described as a GIS model and is simple to use as a classification tool. Topographic Position Index is simpler to use than Hammond’s more detailed method developed in New Zealand in the 1950’s, which operates with over 20 different landforms. However, Hammond’s approach could be a good alternative to TPI for the purpose of this study. The TPI model is based on Andrew Weiss, The Nature Conservancy, Northwest Division, Seattle.

Conclusion: Both the underlying methodology and the model developed by Weiss are applicable to the development of the current methodology, and can be used for describing the value and sensitivity of a landscape, plus areas that are potentially important for biodiversity. In addition it can be used to describe the features of different catchment areas.

ASPECTS OF EXISTING METHODS WHICH COULD BE ADAPTED FOR THIS STUDY

Based on the literature review summarised above, it was concluded that the following methodologies provided a good starting point for the development of a method for the current study:

• The approach to value and sensitivity Kolbenstvedt et al. (2000) • The simplified Handbook 140 approach used for the Evaluation of strategic concepts,

non-monetised effects (Statens vegvesen 2008, 2010) • The three stage approach for assessing impacts of strategic transport proposals

provided by WebTAG unit 3.3.6 (Department for Transport 2003) • ILARIS, AREALIS as inspiration, TPI for model and method

2.4 General description of method developed for this study

In brief, it is proposed that the methodology will consist of the following stages:

1. To map the characteristics of an area under each topic (topic coverage is outlined in Chapter 3)

2. To ascribe a value/ importance/ sensitivity to the characteristics of the area (described in Chapter 4)

3. To describe the magnitude and potential conflict of proposals on these characteristics (described in Chapter 5.1)

4. To derive an overall measure of potential conflict (described in Chapter 5.2)

A GIS model will be built to aid visualisation and analysis. This model will be based on available databases and information which is relevant to finding suitable and unsuitable corridors for a high speed railway, and provide the basis for an initial sifting of alternatives.



The databases are variable in terms of value classifications, and whereas some information sources contain data which are already classified in terms of value/importance, other data are unclassified. This is particularly relevant for the landscape topic.

The proposed topic coverage and relevant information sources for mapping the characteristics of the areas (Stage 1) is outlined in Chapter 3, followed by a description of a simplified approach to value classifications (Stage 2) in Chapter 4. The proposed approach to assessing magnitude of impact and potential conflict (Stage 3) is outlined in Chapter 5, along with proposals for how an overall measure of potential conflict (Stage 4) can be derived. Issues related to data capture and building a GIS model are described in Chapter 6.

3 COVERAGE OF TOPICS

3.1 Landscape

The landscape analysis will focus on the visual characteristics of the landscape, including visibility, visual barriers and visual experience (not to be confused with journey ambience, which is not considered relevant at this early stage of planning).

This delimitation of the landscape topic reflects the scope of the invitation to tender and the way in which landscape assessment is usually undertaken for transport infrastructure initiatives in Norway. It is furthermore driven by the time restraints for undertaking the assessment in Phase 3.

Some of the data sets, including national parks, wilderness areas (INON), protected watercourses and potential world heritage sites provide important information to both the assessment of landscape and environmental intervention effects. These data sources may therefore be used during both assessments.

3.1.1 Landscape regions, description and categorisation of landscape

The National Referencing System for Landscape categorises the landscape in Norway into 45 regions based on their overarching and unifying characteristics (Pushmann 2005). These landscape regions provide an overarching description of the landscape and may be used as the focus for the assessment in Phase 3. The data for landscape regions will be obtained from “Norge Digitalt” and are produced by the Norwegian Institute for Forestry and Landscape (NIJOS).

The assessment of alternative railway concepts will be based on professional judgement and knowledge about the landscape components described below, supplemented by a GIS-based analysis of slope/ topography and terrain.

Table 3-1. Landscape components for the 45 landscape regions in Norway, (Pushmann 2005)

Landscape components Primary landscape form (most important for the distinctive visual character) Minor landscape forms (gives locally distinctive character, both geological deposits and rock formations)



Lakes and watercourses (of great importance to the diversity of landscape types) Vegetation (broad vegetation classifications) Agricultural land Buildings and technical facilities/ land use Landscape character

3.1.2 Mapped and classified landscape data

Landscape characteristics which are relevant for describing and assessing visual characteristics, and for which there are available datasets with existing value ratings, are briefly described below.

Valuable landscapes of culture heritage value

Cultural landscapes reflect the natural conditions of an area, social conditions and the history, and contribute to the regional identity of an area. Data will be obtained from the ‘National register of valuable cultural landscapes’, from Arealis, which includes ‘Valuable cultural landscapes in Norway’ (‘Verdifulle kulturlandskap i Norge’, DN 1994) and information about regionally and locally important cultural landscapes. Areas are classified in terms of national, regional or local value.

Urban environment / townscape

The Directorate for Cultural Heritage has made a register of 230 town areas of national and cultural importance. The Directorate has also mapped areas of wooden houses of cultural heritage value (‘trehusbebyggelse’). Cultural heritage gives landscape context and influences how the landscape is perceived and experienced.

Protected areas

The Natural Diversity Law from 2009 (Naturmangfoldloven, Lov 19. juni 2009 om forvaltning av naturens mangfold) is the most central / important legislation within nature conservation in Norway. The law encompasses the management of species, area protection, non-native species, selected habitats and habitats for ‘prioritised species’ (prioriterte arter). The Natural Diversity Law sets out five categories of protected areas, which have value both for the natural environment and the landscape character:

• National parks (Nasjonalparker) § 35 • Areas of protected landscape (Landskapsvernområder) § 36 • Nature reserves (Naturreservater) § 37 • Protected biotopes (Biotopvernområder) § 38 • Protected marine areas (Marine verneområder) § 39

Protected watercourses

A conservation plan for watercourses was adopted by the Norwegian Parliament in 1973, 1980, 1986 and 1993, and supplemented in 2005. The conservation plan encompasses watercourses and catchment areas. Its intention is primarily to secure watercourses against development. The criteria for conservation are to secure variation with regards protection



interests, size, geographical distribution and the prioritisation of centrally located watercourses. Protected watercourses must be managed in line with guidelines from the Directorate for Nature Conservation (Direktoratet for Naturforvaltning) and the Directorate for Cultural Heritage (Riksantikvaren) who have the responsibility for ensuring that the protected resources are not diminished by heavy technical interventions or land use. Water, the nature associated with watercourses and their ‘unspoiled’ nature are considered important for the experience value of landscapes.

Wilderness areas (Inngrepsfrie naturområder/ INON-områder)

Wilderness areas are defined by the Directorate for Nature Conservation (Direktoratet for naturforvaltning) as all areas located further than 1 km from major infrastructure developments and technical plants, increasing in value at a distance of more than 1, 3 and 5 km respectively. The ‘unspoiled’ nature of natural areas is considered important for the landscape experience.

Other landscape data with value ratings

Certain regions have developed value ratings for their landscapes, e.g. ‘Beautiful landscapes in Rogaland’ (“Vakre landskap i Rogaland”).

3.1.3 Other datasets which are relevant as a basis for the analysis

The following datasets are also regarded as relevant to the landscape analysis at this level of planning and will be included in the model as a basis for the assessment. As opposed to the datasets listed under Chapter 3.1.2, the following are not classified in terms of value.

Aquatic areas (lakes, watercourses, fjords and more)

Aquatic areas are defined as the sea, lakes and watercourses with a permanent flow of water. Aquatic areas have value both as a natural environment, recreational areas and as a landscape characteristic.

Densely populated areas and buildings

Data on houses and buildings might be included for areas from which the railway line will be visible. This topic would also be relevant for the local environment and outdoor recreation theme, se Chapter 3.3.

Protected / important outdoor recreation areas

Outdoor recreational areas which are protected through the Planning and Building Act (plan- og bygningsloven) and through the Outdoor Recreation Law (friluftsloven), or areas which are described as locally or regionally important.

Data may be included for areas from which the railway line will be visible. This topic would also be relevant for the local environment and outdoor recreation theme, se Chapter 3.3.

Recreation areas near densely populated areas

Natural areas less than 2 km from densely populated areas provide recreational facilities and walks of 10-15 km. This information would need to be derived from other data sources, and



may be used for areas where there is not sufficient information to undertake the analysis. (Please note that this approach would exclude the potential recreational value of cultural landscapes.)

3.2 Environmental intervention effects

3.2.1 Natural environment

It is proposed that the delimitation of the natural environment topic should reflect the definition used in Handbook 140 (Statens vegvesen 2006). The following data classifications will be relevant. Most of these are already classified in terms of value rating, unless otherwise stated.

Prioritised habitats: A, B and C localities as described in the Directorate for Nature Conservation’s handbook 13 (Direktoratet for naturforvaltning 2007). Prioritised habitats are habitats which are particularly rich in species, rare, threatened, have an important ecological function, used by species on the Red List of Threatened Species (rødlistearter) or which for other reasons are particularly important for biodiversity.

Protected areas: Includes national parks, nature reserves, landscape preservation areas and proposed areas of protection.

Wilderness areas (Inngrepsfrie naturområder/ INON-områder): Areas >1km from areas of larger intervention/ developments. May include important habitats and species which are sensitive to technical infrastructure development.

Game areas: Areas with weighting 4-5, in other words game areas of national – international value according to the Directorate for Nature Conservation’s handbook 11 (Direktoratet for naturforvaltning 2000).

Species: Categories VU (vulnerable), EN (endangered) and CR (critically endangered), Norwegian Red List of Threatened Species 2010 (Kålås et al. 2006).

Protected watercourses: Primarily protected against hydropower development, but the conservation value should also be taken into account in relation to other interventions (www.nve.no) including infrastructure developments.

River deltas: Up-to-date database covering an extremely threatened habitat. Includes little - medium affected deltas over 0,25 km2 (www.elvedelta.no). These data are rated on a three point scale (little – moderately – severely affected) according to level of intervention.

Vegetation: Norut mapping standard, satellite based. May be used where the habitat mapping is deficient. Information for this theme will usually be covered by ‘prioritised habitats’. These data are not classified in terms of value rating.

3.2.2 Water resources

The analysis of water resources will cover a combination of user interests in the watercourse, changes in hydrology and water quality in the catchment. This reflects both the goals of the

http://www.nve.no/

http://www.elvedelta.no/



EU Water Framework Directive and the delimitation of water resources described in Handbook 140 (Statens vegvesen 2006). Relevant data and databases are:

Catchment and hydrology databases: “Vann-Nett” and “Regine” (www.nve.no; www.vannportalen.no) which describes borders for catchment, catchment size and runoff data from the catchment.

Water quality databases: “Vannmiljø” (www.vannportalen.no) which describes historical water quality data. Relevant water quality data will be phosphorus and possibly nitrogen. Historical water quality data will be linked to “good ecological condition” in the watercourse due to the Water Framework Directive. The gap between historical data and good ecological condition will be linked to user interest.

User interest databases: VREG (www.mattilsynet.no) which describes sources for drinking water (surface water and groundwater) to more than 20 households (50 persons). Fishing interest and special water habitats may be found in Naturbase (www.naturbase.no).

3.3 Other topics

Compared to the environmental impact assessment methodology set out in Handbook 140 (Statens vegvesen 2006) the scope of topics which JBV has requested be included in the analysis of alternative rail solutions is relatively limited. For example, it would appear relevant to also include topics such as natural resources (agriculture, forestry and minerals), the local environment, outdoor recreation (friluftsliv), cultural heritage and the cultural environment.

It should also be considered whether other environmental and social interests within the following topics should be included in the methodology:

• Noise barriers – landscape • Noise – local environment

4 VALUE CLASSIFICATION OF TOPIC AND AREA

4.1 General approach

The methods in the literature review vary in their approach to value ratings, from the very detailed approach of attributing individual value scores outlined in ‘Handbook 140’ to the highly simplified approach in the ‘Evaluation of strategic concepts, non-monetised effects’. For example, Handbook 140 (Statens vegvesen 2006) defines landscape value in terms of the following:

• Typical/common landscapes in the region – medium value • Landscapes which are rare nationally – high value • Areas with lower visual value than surrounding areas – low value

In the ‘Evaluation of strategic concepts’ (Statens vegvesen 2008, 2010), all the data included in the assessment are attributed a ‘high’ value score, implying that the value rating is partly implicit in the selection of which data to include. The value classification in ‘Landscape Analysis’ (Direktoratet for naturforvaltning og Riksantikvaren 2010) involves a prioritisation of

http://www.nve.no/

http://www.vannportalen.no/


http://www.mattilsynet.no/

http://www.naturbase.no/



the landscape in relation to other landscape areas in a larger geographical perspective, linking value to rarity and representativeness.

For the current study it is proposed to adopt a similar approach to value ratings as that used in the ‘Evaluation of strategic concepts’ study (Statens vegvesen 2008, 2010). This means that all the datasets included in the assessment which have existing value ratings will by definition be assigned a ‘high’ value, unless otherwise is stated. Although this implies a broad simplification of value classification during the assessment in Phase 3, the original databases with more detailed value descriptions (e.g. the distinction of international, national, regional or local importance) will still be accessible and could enable analysis at a greater level of detail should this be required at a later stage.

The selection of which data to be included in the assessment will be based on whether they are relevant for identifying potential conflicts and whether they will facilitate a comparison of alternative rail solutions. For some topics there may be needed to derive simplified value ratings to enable an assessment of areas with insufficient coverage in existing datasets. A proposed approach to deriving value ratings is proposed for individual themes below.

4.2 Value ratings - landscape

4.2.1 Existing value ratings for landscape data

Datasets which are relevant for describing and assessing the landscape theme and which have existing value classifications are described in Chapter 3.1.2. These will be used as the basis for defining areas of particular landscape value.

Some of the datasets described in Chapter 3.1.2 are classified in terms of local, regional and national value. Others have a protected status of are defined as worthy of preservation. In line with the simplified approach proposed adopted for the purpose of the current methodology outlined in Chapter 4.1, all these will be attributed a ‘high’ value score in the assessment.

4.2.2 Derived value ratings for landscape data

For areas without existing value classifications, an assessment will be required to derive the value rating of the area and its sensitivity to interventions. This will be done using a combination of sources which together describe the nature of the area and topographical features, in line with the approach outlined in the ‘Value and sensitivity analysis’ (Kolbenstvedt et al. 2000). Some examples of how this might be done for a selection of topics are provided below.

Aquatic areas (lakes, watercourses, fjords and more): Lakes and shorelines within the 100-metre belt will be defined as being of value for the landscape theme.

Vegetation and cultivated land: will be used to describe land cover and to assess vulnerability of the landscape



Terrain: On the basis of a terrain model, there will be developed a classification of the major and minor forms of the landscape.

Figure 4-1. Illustration of a modelled example for describing the macro landscape

Urban settlements and recreational areas: Areas where people live and spend time could be incorporated into the sensitivity analysis for landscape in terms of exposure to high speed railway lines. Cultural heritage: Areas or elements with particular importance for the landscape.

4.3 Value classifications – environmental intervention

4.3.1 Existing value ratings for the natural environment theme

As a basis for ascribing valuing ratings to the natural environment, there will be used datasets with existing value classifications (see Chapter 3.2). In a similar vein to the landscape theme, some of the datasets are classified in terms of local, regional or national value, and in the case of game areas, international value. Others have a protected status or are defined as worthy of preservation. In line with the simplified approach outlined in Chapter 4.1, the proposed approach to value classification for a selection of the datasets described in Chapter 3.2 is provided below.



Prioritised habitats: For the purpose of the analysis in Phase 3, A and B localities (Direktoratet for naturforvaltning 2007) will be ascribed a ‘high’ value score, whereas C localities (locally important areas) will be considered of ‘medium’ value.

Protected areas: National parks, nature reserves, landscape preservation areas and proposed protected areas will all be attributed a ‘high’ value score.

Natural areas free of intervention (INON): All areas with a distance >1km from large interventions / developments will be attributed a ‘high’ value score.

Game areas: Game areas of national – international value (weighting 4-5) will be attributed a ‘high’ value score.

Species: Species in all categories (VU, EN, CR) and species on the Norwegian Red List of Threatened Species (Kålås et al. 2010) will be attributed a ‘high’ value score.

River deltas: Deltas over 0,25 km2 that are classified as ‘little affected’ will be regarded as ‘high’ value in the assessment. Deltas classified as ‘moderately affected’ will be attributed a ‘medium’ value score.

Protected watercourses: All protected watercourses will be assigned a ‘high’ value score.

4.3.2 Derived value classification for the natural environment theme

Where there is lacking or insufficient habitat information, it will be possible to identify potentially important habitat areas based on other sources of information e.g. combining vegetation satellite images (Norut) with data on geology, topography, hydrology etc. This would require the selection of mapping units, in other words biodiverse or rare/ threatened habitats. Wetlands (moorland/marsh, deltas etc) may also be relevant, as may delta under 0,25 km2 which are not included in either the river delta database or the ‘naturbase’ database.

4.3.3 Value classification for water resources

The value rating for water resources will be based on the following criteria: • Water quality and hydrology status • Water recipient goal • User interests for the water recipient

Chemical/ecological/hydrological status will be classified due to existing historical water quality and hydrology data in databases such as “Vannmiljø” (see 3.2.2), and Guideline 01:2009 “Klassifisering av miljøtilstand i vann (Direktoratsgruppa for gjennomføringen av vanndirektivet; www.vannportalen.no)”. Water quality status is divided into 5 classes; ”Very good” or High status”, ”Good”, ”Moderate”, ”Bad” or ”Very Bad”. The water quality status of the actual recipient will be compared to the water quality goal for the recipient. According to the Water Framework Directive, the water quality goal can be set as “Good” if an actual water quality goal does not exist (if lower status: abatement measures shall be implemented).




The gap between status and goal - together with user interests, will be the basis for the value classification of the water recipient. A minor gap between water recipient goal and status, and major user interests, will lead to high rating of the water resources. In contrast, a major gap between goal and status combined with minor user interests will lead to a low value rating of the water resources. Only major user interests such as ‘drinking water’ and ‘fishing interests’ will be mapped. Drinking water will be mapped from the databases VREG and fishing interests (mainly salmon, eel) from “Naturbase”.

5 MAGNITUDE OF EFFECT AND CONFLICT POTENTIAL

5.1 General approach

Magnitude of effect is an expression of the scale and importance of (positive or negative) changes caused by an intervention, and should be assessed against the baseline scenario (the 0 – alternative). In the case of the analysis to be undertaken in Phase 3, the 0-alternative represents today’s situation including expected changes/developments if the initiative were not to take place.

We propose initially to provide a general description and assessment of the potential magnitude of effects of the alternative rail concepts (A, B, C and D) on the landscape, natural environment and water resources. This will include an assessment of land take, topographical intervention, proximity, severance/ barrier effects (visual and physical), changes in water levels plus noise and vibration.

The assessment of magnitude will focus on characteristics of ‘high’ value (see Chapter 4). In order to assess the magnitude of impact from the GIS model, parameters will be defined in terms of distance from the corridor and/or land take.

The conflict potential will then be assessed for each alternative concept as a combination of potential effects and their magnitude within the physical corridors, and the value/sensitivity of the affected areas and their characteristics. There is thus a correlation between the geographical boundary of the assessment and the land take required for each alternative concept. The assessment of conflict will be based on professional judgement and described qualitatively.

5.1.1 Magnitude of effect and conflict potential - landscape

A high speed railway has a stiff horizontal and vertical curvature, and there is limited opportunity to adapt the railway line to the undulating and varied landscape which characterises much of Norway.

It is proposed that the assessment of magnitude and conflict potential for the landscape theme is primarily based on the following considerations.



Landscape region: Based on knowledge about the landscape region’s sensitivity to the intervention, professional judgement of the alternative concepts will be based on the parameters in the sensitivity analysis. The result of this analysis will be documented.

Land take: Corresponds to the geographical boundary for the assessment of magnitude and conflict potential. Land take will be calculated for the areas or topics that are classified in terms of their value rating, such as cultural landscape, densely populated areas, recreational areas and aquatic areas.

Visibility/ visual impact: Visual impact can be assessed by the use of visibility mapping. Visibility will be assessed based on:

• Proximity: Proximity will be assessed if the high speed rail line passes within a defined distance to populated areas. Proximity to densely built up areas can also give rise to visual barrier effects.

• Severance/ barrier effects: The high speed railway may cause visual barriers if it crosses densely populated areas, recreational areas or shorelines.

5.1.2 Magnitude of effect and conflict potential - natural environment

The value of natural environments is connected to their biology or landscape ecology, biodiversity and the presence of individual species and their habitats. In order to assess the magnitude of effects which an action/intervention will have on the natural environment, it is important to consider a range of issues such as land take, noise, pollution, changes in hydrology, microclimate, biotope fragmentation and barrier effects.

Land take must be assessed for all natural environments which have been given a value rating. Wilderness areas are per definition reduced at a distance < 1km from a development. The importance of natural environments cannot necessarily be related to the size of land area they occupy – habitats, species, protected areas and game areas which cover relatively small areas geographically may still represent important natural environments. E.g. if a railway line were to cross a watercourse, this may result in little direct land take but nevertheless cause significant adverse effects on biodiversity, landscape ecology etc. In such instances it might be necessary to base the assessment on e.g. the number of adversely affected species rather than the area of land take.

Proximity, area of influence: The high speed railway line can indirectly affect different aspects of the natural environment. For example, wilderness areas are reduced at a distance < 1 km from a development. For other characteristics of the natural environment the area of influence may be in the order of magnitude of 100 – 200 meters. In addition to land take, the assessment might therefore also need to include the number of affected localities/ species.

Biotope fragmentation and barrier effects involve a fragmentation of habitats for both flora and fauna, and can lead to physical barriers which preclude migration and sever ecological corridors. Barriers can have adverse effects on e.g. organisms with low dispersal abilities, leading to the isolation of populations, and game which is dependent on large geographical areas and being able to move between different habitats (grazing areas, breeding grounds etc.). In addition to land take, the assessment might therefore also need to include the number of affected localities/ species and migration routes.



5.1.3 Magnitude of effect and conflict potential - water resources

The assessment of magnitude of effect for water resources will be based on a combination of direct land take and an assessment of downstream effects. The conflict potential will be based on the magnitude combined with a list of activities which will affect the hydrology or water quality. The list of relevant activities will vary for each watercourse, and will be selected on the basis of user interests.

In brief, the assessment of magnitude of effect and conflict potential for water resources will be carried out according to the following steps:

• Area coverage for the water resource subject mapped (includes influence area; that is downstream water recipient)

• Identification of conflict potential: o Possibly hydrological changes for surface water and groundwater

Surface water: Possibly hydrological changes in downstream water recipient for the construction and operation phase

• Hydro morphological barriers for special water habitats (e.g. fish)

• Hydrological changes that may cause changes in vegetation type, access of drinking water for wild life etc.

Groundwater: Possibly hydrological changes in groundwater level in a predefined distance from the railway track for the construction and operation phase

• Hydrological changes that may cause changes in vegetation type, access of drinking water for wild life etc.

o Possibly water quality changes in downstream recipient due to the construction phase Runoff from construction areas Runoff from tunnel – and track construction (explosive residues,

particle erosion etc.) • Assessment of conflict potential (combination of bullet point 1 and 2)

5.2 Overall measure of conflict potential

5.2.1 Proposed approach to assessing conflict potential

The overarching nature of the assessment means that it will not be possible to ascribe detailed impact scores in line with the ‘value– magnitude – impact’ process outlined in Handbook 140 (Statens vegvesen 2006). It is therefore proposed to adopt a simplified approach, similar to that used in the ‘Evaluation of strategic concepts’ study (Statens vegvesen 2008, 2010) where an overall measure of conflict is derived.

The direct land take required by each alternative concept will be used as the basis for identifying potential conflict for each topic (landscape, natural environment, water). The assessment will be undertaken using professional judgement supported by a written statement with a justification of the conflict potential score.

It is proposed that conflict potential is derived for individual sections of the railway and/or for each topic e.g. in the case of landscape, for each landscape region.



5.2.2 Ranking of alternative concepts

In order to facilitate an initial sifting of the alternative concepts, it is proposed that the alternative rail concepts are ranked according to their overall conflict potential.

It is proposed that the ranking within each topic (landscape, natural environment, water) and their subcomponents is used as the basis for a collective ranking of the concepts. Examples of how the alternative concepts could be ranked are provided below, based on the approach used in the ‘Evaluation of strategic concepts’ study (Statens vegvesen 2008, 2010). (Under the assumption that the 0-alternative will lead to least changes and incur the least land take, the 0-alternative will tend to emerge as the ‘best’ alternative.)

The ranking must be carefully documented in order to ensure transparency and accountability, and to compensate for the implicit weighting which is inherent in the process. The ranking will be undertaken using professional judgement and supported by a written statement.

Table 5-1. Example of ranking alternative concepts for the landscape theme

Concept

Landscape region (vulnerability)

Valuable culture landscapes

Protected watercourses

Overall ranking

O-alternative 1 1 1 1 Alternative 1 1 1 2 2 Alternative 2 2 1 2 3

Table 5-2. Example of ranking alternative concepts according to collective theme scores

Concept

Landscape

Natural environment

Water resources

Overall ranking

O-alternative 1 1 1 1 Alternative 1 1 1 2 2 Alternative 2 2 1 2 3



6 ESTABLISHING DATA MODELS

6.1 Data capture

‘Norge Digitalt’ (ND – Digital Norway) is the result of collaboration between national, regional and local institutions and contains map-based information on several themes. These are highly interesting and necessary in planning activities, both for visualisation and thematic mapping. Data models from ‘Norge Digitalt’ are described and documented here: Thematic data in 'Norge Digitalt'.

A rather broad list of themes and documentation was compiled initially, before a decision was made to concentrate on a selection of data models and methods.

On the basis of discussions about ‘Norge Digitalt’ and subsequent discussion with data owners, combined with previous experience, deficiencies and “data gaps” have been identified in the databases. For the purpose of developing the current methodology, much of the data does not have the right resolution, and derivations have to be made from databases (in other words, new themes which are more relevant for this study need to be made by combining existing data).

Contact has been made to the following institutions; The Norwegian Directorate for Nature Management (Direktoratet for naturforvaltning - DN), Norway’s Geological Survey (Norges Geologiske Undersøkelser - NGU), The Norwegian Water Resources and Energy Directorate (Norges Vassdrags- og Energidirektorat - NVE) and the regional environmental administration in Vestfold. A broad range of databases are described in chapter 6.2.

As previously outlined, ND (Norge Digitalt) will be used as the main source of data. Much of the data in ND and other available data are compiled by the regional governments, based on information from the municipalities which have the main responsibility for collecting and mapping data in Norway. Little focus has been placed on local sources of information in this description, but in practice local information sources will have an important role for checking and verifying the final databases that are used for the analysis in Phase 3.

A lot of the available data is not standardised within ND’s system, but is still of great relevance to this project. Several databases from the different counties and municipalities therefore have to be collected and combined into a holistic database for the relevant regions.

The validity and reliability of data will vary greatly for the different themes, and hence the amount of work required for collecting and verifying data will vary from county to county. It is therefore proposed to establish a contact-net for each region (county), in order to ensure efficient data collection and to enable a discussion and documentation of the validity and reliability of different data layers.





Three examples (screen dumps) of different themes based on data from ND, regional data and municipalities:

Figure 6-1. Map example of local data

Figure 6-2. Map example of regional data

Figure 6-3. Map example of national data

This example shows the so called “Green-poster” from a municipality in Norway. “Green – poster” is a method for registering and classifying areas of particular importance in relation to nature, landscape and recreation. Since most municipalities now use internet-based map-viewers, it is relatively easy to get an overview of areas of importance within the different municipalities. The problem with these maps however, are that each municipality often has its own system for ascribing value, which makes it difficult to identify significantly valuable areas at a regional or national level. In terms of ensuring a certain level of accuracy, they will nevertheless be an important source of information.

This example shows regional data from Rogaland. This county has made a regional plan for recreation, sports, nature and cultural heritage. In this work they have also classified different areas according to national, regional and local interests. In this case we can therefore use the data model directly into our database.

Unfortunately there are few regions with this level of coverage.

This example shows national data from The Directorate for Nature Management for the county of Vestfold – both game grazing areas and pathways. The grazing areas are common and not evaluated, whereas the pathways are somewhat more vulnerable.



In order to illustrate the range of challenges involved in building a GIS model for this assessment, models for two different regions are outlined below:

Vestfold County: Vestfold has a lot of good databases with good coverage for the region. A lot of these data are specified within the different municipalities, and therefore evaluated from a local perspective. For example, two different municipalities with very different regional and national interests both have landscape which is described as “outstanding”. Our challenge will therefore be to find indicators that can qualify different areas as national, regional or local significant.

Rogaland County: In this county there has been a process called “Finken” – A regional plan for Recreation, Sports, Nature and Culture. As part of this process, objects and areas have been assigned value ratings according to whether they represent national, regional or local interests, and there is full data coverage for all the relevant themes. For each theme there have also been established regional units with a responsibility to maintain the quality of data.

Other Counties: For other counties, challenges can be expected in obtaining any data at all. The quality and coverage of data will vary greatly, and in these cases regional/local contacts and own local knowledge have to be used to identify and collect databases.

6.2 List of themes and coverage

6.2.1 Themes with national data coverage

Table 6-1. National data coverage

Theme Description Wilderness areas Areas with a certain distance to major

technical installations Cultural heritage, protected by law Cultural heritage which is protected by law

(automatisk fredete kulturminner), due to significance or age

River deltas All river deltas larger than 0,25 km2, classified

Older buildings All buildings built before 1900 Preserved areas (national parks etc.) Areas preserved or planned to be preserved

by the Nature Conservation Act. Secured areas for recreation activity Areas that are secured for public access by

national governments (NOT areas that are secured by regional authorities or municipalities). Does not include areas accessed by “Allemannsretten”

Protected watersheds These are watersheds protected by law. Also include riverside/shoreline, 100 meters from waterfront

Restricted areas due to RPRO These are areas from Østfold along the coastline to Telemark, restricted by national guidelines for planning and building in coastal areas

Landscape regions of Norway These are descriptions and classification of



different landscape regions in Norway Land cover (Ar50) Land cover due to built up areas, forest,

farmland, moors and open areas. The basis for these data is production and production potential for forestry and farming

Watersheds A classification and hierarchy of watersheds in Norway on a scale of 1:50 000

Water environment Consists of Water Location and River Network, relating to Watersheds. Contains data from monitoring of biodiversity and Chemical data.

Land slide, rock slide, snow slide National coverage 1:250 000 Bed rock National coverage 1:250 000 Ground water National coverage Drinking water All drinking water reservoirs/ national

coverage Quaternary register National coverage 1:250 000 Satellite imagery National coverage, land sat 30m Terrain National coverage, 10m resolution height

database

6.2.2 Data coverage at county level

• Wildlife • Biodiversity • Other types of natural heritage: These are areas of importance for nature conservation,

but which are not classified under wildlife or biodiversity. These can be geological phenomena or areas of significance that are more widely defined than the specific locations described for wildlife and biodiversity.

• Recreation areas: These are areas of special importance for recreation that are not secured by national governments.

• Landscape areas: Areas of particular landscape value. These can both be based on regional and local registrations and value ratings.

• Others: For a lot of areas and especially within municipalities, there will be several themes and documents.

• The main source for getting overviews on a county level, different web-viewers are named and described. Some of the solutions mentioned are based on inter-municipality cooperation, but this list is not complete. Table 6-2. Regional data coverage

County Theme Coverage and description Vestfold Wildlife Good cover,

Biodiversity Locally good. Other types of natural heritage

Good, fully covered

Recreation areas 8 municipalities, local valuation

Landscape areas 4 municipalities, local valuation



Other

Main source “12-K”, an internet map-service for 12 municipalities in Vestfold (Good)

Buskerud Wildlife Good cover Biodiversity Locally good Other types of natural heritage

Poor

Recreation areas Poor Landscape areas Poor Other Poor Main source Not found

Telemark Wildlife Poor Biodiversity Locally good, but…. Other types of natural heritage

Poor

Recreation areas Porsgrunn and Skien (local valuation) Coast area national and regional valuation

Landscape areas Porsgrunn, Skien (Local evaluation) and the Telemark Channel (Not evaluated)

Other Several significant themes due to Hardangervidda, Blefjell and Coastal areas. Several themes of good evaluation for our work are found from different municipalities.

Main source “Grenlandskart” an internet map-service for 4 municipalities in Telemark (Average)

Aust-agder Wildlife Good Biodiversity Good Other types of natural heritage

Poor

Recreation areas Medium Landscape areas Poor Others Main source Regional coverage. County

Office Web-site Vest-agder Wildlife Good

Biodiversity Good Other types of natural heritage

Poor

Recreation areas Medium Landscape areas Poor Others Main source Not found

Rogaland Wildlife Good




Good

Recreation areas Good, national and regional valuation

Landscape areas Good, national and regional valuation

Others Very good cover for several themes; heather, limnology etc.

Main source “Temakart- Rogaland” (very good!)

Hordaland Wildlife Good Biodiversity Good Other types of natural heritage

Good

Recreation areas Good, national and regional valuation

Landscape areas Good, but not valued Others A broad specter of significant

data. Main source “Kart i vest” (Very good!)

Hedmark Wildlife Good Biodiversity Good Other types of natural heritage

Poor

Recreation areas Poor Landscape areas Poor Others Hedmark has not established

regional data, except for areas of special interest- shoreline of Mjøsa and FDP’s for mountain areas. Further information:

Main source “InnlandsGIS” (average, give very little new information compared with ND)

Oppland Wildlife Good Biodiversity Good Other types of natural heritage

Poor

Recreation areas Poor Landscape areas Poor Others Oppland has not established

regional data, except for areas of special interest- shoreline of Mjøsa and FDP’s for mountain areas.

Main source “InnlandsGIS” (average, give very little new information compared with ND)

Akershus Wildlife Good




Good

Recreation areas “Marka”-border, no other classification.

Landscape areas Landscapes of national and regional significance

Others Also data from regional environmental program, basically registration of cultural landscapes.

Main source “temakart I Akershus” (Average)

Østfold Wildlife Good Biodiversity Good Other types of natural heritage

Poor, but good for coastal areas and Glomma (vann-portalen)

Recreation areas “Turkart Østfold” has a lot of information on paths and points of interest (POI). “Østfold-landscape” also has a valuation of landscapes for recreation.

Landscape areas “Østfold”-landscape, a registration of different landscapes in Østfold.

Others Main source “FellesGIS” (Good)

Sør-Trøndelag Wildlife Good Biodiversity Locally good Other types of natural heritage

Good

Recreation areas Poor Landscape areas Poor Others Main source “GISLink” (Good)

6.2.3 Municipal coverage of relevant themes

We have through this project identified inconsistencies, gaps and other deficiencies in databases both on a national and county level. For some areas it will be possible to retrieve datasets from municipalities which have carried out their own registrations/value classifications. This will be considered once the municipalities affected by the alternative railway concepts are identified in Phase 3.



6.3 Models for analysis of impact

Following the identification and derivation of the necessary databases for the relevant themes, models for analysing the impact and conflict potential for the alternative railway corridors will be established. The process of model building is illustrated in Figure 6-4. In brief, the process will constitute the following steps:

1. Data capture (collecting and verifying databases) 2. Extracting databases with existing value ratings for further analysis 3. Deriving databases and analysis of databases for exploring vulnerability. Identifying

methods for analysing impact. 4. Stage 1: Overall assessment of main corridors. Identifying ”knock out areas” and data

gaps/ uncertainty. Establishing the need for further data capture from regional/local authorities.

5. Stage 2: Detailed analysis within corridors for evaluation of alternative railway lines. Implementing models from point 3.

The process outlined in Figure 6-4 is based on the assumption that for the stage 2 a detailed description of the alternative railway lines will be available.

The assessments will be based on the analysis of a number of issues, for example:

• Visual impact on landscape by view shed analysis. • Effects on hydrological aspects, by using different tools for hydrological analysis as

watershed and basin analysis. • Proximity to for example reindeer, which are very sensitive to human activity. • Barrier effects by analysing chances in accessibility between different layers, for

example living areas for different species. • For landscape there will also be of great significance to identify vulnerability of a

landscape. o Slope-analysis o Visual fragileness (Open areas, waters, exposes areas etc.) o Landform-analysis o Degree of technical impact

A definitive list of issues for the analysis will be developed in Phase 3.

An example of combined slope and landform analysis in order to identify the vulnerability of a landscape to intervention is provided in Figure 6-5. A similar approach could also be used to identify potentially important areas for biodiversity.

Figure 6-4. Illustration of model building process



Figure 6-5. Example of combined slope and landform analysis, describing vulnerability to intervention



SUBJECT 3: EFFECTS ON ENERGY AND NOISE

7 ENERGY

7.1 Introduction

This chapter focuses on the energy consumption of rolling stock operating on high-speed infrastructure. The analysis specifically aims at mapping and evaluating the infrastructure and operation factors that have an effect on energy consumption. Therefore, different high-speed trains are compared with each other in order to identify typical levels of energy consumption as well as to determine preferable train designs.

The results are an assessment of existing high-speed trains with regard to their energy consumption. The report also includes remarks on the construction of timetables, the operating conditions of high-speed lines, railway infrastructure and the power supply system.

To this end, existing high-speed trains’ technical data is modelled with VWI’s software tool PULZUFA, which allows for the simulation and calculation of the vehicle dynamics and energy consumption on a given infrastructure. From the simulations done with PULZUFA, typical energy consumption values are derived that take into account different characteristics of railway infrastructure and operations, such as gradients, tunnels and intermediate stops

7.2 Basic information for energy consumption calculations

7.2.1 Basic information on vehicle dynamics

As a part of the field of railway vehicle dynamics, energy consumption calculations draw on vehicle and infrastructure specifications, their interdependencies and functions describing their interactions.

From the electric power supply system, electric energy is drawn and converted to allow for train movement. However, some of the energy is dissipated in the process. Between the train’s pantograph and the wheels, energy is lost due to inefficiencies in the tractive system (cf. section 7.2.5).

Moreover, a moving train constantly works against resistances. Electric power drawn from the power grid is converted into a tractive force by the train’s tractive system. The fundamental equation of vehicle dynamics states that

𝐹𝑇 = 𝑊𝑡𝑜𝑡𝑎𝑙

with FT being the tractive effort and Wtotal the total resistance. Note that both variables can assume positive, as well as negative values. In this case, i.e. when a train is braking or running downhill (or doing both at once), electric energy can be recovered if all prerequisites are given.

The train resistance Wtotal as a “sum of all forces opposed to the driving movement” (Steimel 2008, p. 23), can be divided into four categories:



- Train running resistance (wr) - Acceleration resistance (wa) - Grade resistance (wg) - Curve resistance (wc)

The specific resistance opposed to a train’s movement in [N/kN] is thus given as

𝑤𝑡𝑜𝑡𝑎𝑙 = 𝑤𝑟 + 𝑤𝑎 + 𝑤𝑔 + 𝑤𝑐

Multiplying the specific resistance with the train’s weight yields the total resistance in [N].

Train running resistance

Three components add up to the running resistance of a train:

- Normal resistance, which depends on friction, deformation energy dissipated between wheels and track and the train’s mass

- Impulse resistance, which results from air streaming through the train’s interior - Aerodynamic resistance, which depends on the train’s speed, the cross section of

the train and the outside form and material properties of the train’s surface.

Commonly, the specific running resistance in [N/kN] is expressed by a formula depending solely on train speed, where the three components are represented by coefficients a, b and c, that are sought out empirically:

𝑤𝑟 = 𝑎 + 𝑏 𝑉 + 𝑐 𝑉2

with a representing the normal resistance, bV for impulse resistance and cV² representing aerodynamic resistance. The dimensions of the coefficients are the following:

a [N / kN]

b [kN h / kN km]

c [N h² / kN km²]

Acceleration resistance

Due to the inertia of a train’s mass, acceleration resistance is encountered every time the train’s speed changes. For calculation of acceleration resistance wa in [N/kN], the following formula is used:

𝑤𝑎 = 1000 𝑎 𝜚𝑔

a is the current acceleration, g is the acceleration of gravity (9.81 m/s²), and ρ is a coefficient representing an allowance for rotating mass.

Grade resistance

On sloped tracks, trains running uphill work against the grade resistance resulting from the track gradient and the train weight. For railway lines, where the track slope is limited to small angles no larger than 2° (which equals 35 ‰), the specific grade resistance (measured in [N/kN]) is given as



𝑤𝑠 = 𝑖

where i is the track gradient in [‰] (cf. Filipović 1992, p.30)

Curve Resistance

Specific curve resistance can be estimated using Röckl’s formula, which for standard gauge railways is given as the follows where R stands for the radius of the curve in metres (Wende 2003, pp. 107f.):

𝑤𝑐 =650

𝑅 − 55

Even under the assumption of a very low radius of 1.000 m – at least in terms of high-speed railways – the specific curve resistance does not rise above 0.688 N/kN, which gives a total curve resistance of 2.7 kN for a train of 400 t. In terms of energy consumption, curve resistance may thus be neglected for high-speed railways.

7.2.2 Calculation of energy consumption

The work exerted against all resistances opposing train movement yields the mechanical energy consumption. Taking into account the efficiency degree of the tractive system η, the electric energy consumed can be calculated.

Additionally, auxiliary energy needed for tractive system components as well as for passenger comfort such as heating, air-conditioning, lighting, etc. is considered. As the power need of these auxiliary systems can be assumed to be constant over time, auxiliary power is multiplied with travel time and yields auxiliary energy consumption.

Thus, the electric energy consumption of a train Eel over a distance s can be described as:

𝐸𝑒𝑙 = �1𝜂

𝑚 𝑔 𝑤𝑡𝑜𝑡𝑎𝑙 d𝑠 + 𝐸𝑒𝑙,𝑎𝑢𝑥

In the study at hand, energy consumption was calculated by means of the in-house software tool PULZUFA. Table 7-1 lists all the parameters needed as input to the software calculations and the analysis.



Table 7-1. Input to energy consumption calculations and analysis

Train specific data Infrastructure data Operational data

Maximum speed Inclines Location of stops

Maximum acceleration Tunnels

Maximum deceleration Speed restrictions

Tractive power Curves (neglected)

Length

Total mass (deadweight)

Mass on driven axles

Resistance coefficients a, b and c

Mass factor ρ

Wheelbase

Energy recovery from braking

Power for auxiliary needs

Passenger seats

7.2.3 General assumptions

Interoperability

By means of the Interoperability Regulations (Samtrafikkforskriften), European directives concerning the technical specifications of the interoperability for high-speed railways have been implemented in Norwegian law. [JBV, General technology strategy, p. 9]

Accordingly, a future Norwegian high-speed railway system will adhere to these rules that cover not only the subsystems of the infrastructure and rolling stock, but subsystems such as energy, signalling and traffic operations as well.

In the context of the study conducted, especially the rules applying to infrastructure and rolling stock prove to be of importance, as the limits defined by the TSI (Technical Specifications for Interoperability) limit the extent of the study.

Static vehicle gauge

The dimensions of the cross section along the entire train—the vehicle gauge—are limited according to 2008/232/EG, section 4.2.3.1 by the reference profile defined in Annex C of the Conventional Rail Rolling Stock Freight Wagon TSI (2006/861/EG, annex C.3.1).



Figure 7-1. Reference profile for the static vehicle gauge (cf. 2006/861/EG, Figure C14)

The static vehicle gauge, i.e. the profile of the unmoved train, must not exceed the dimensions shown in Figure 7-1. Amongst others, this means that trains’ widths are limited to 3.15 m.

Railway gauge

A railway’s gauge influences the running resistance encountered by a train running on the track. Commonly, railway infrastructure organisations decide or have decided on the gauge of a railway network, and the trains are accommodated to the track. The normal gauge of 1435 mm is assumed for all trains according to the existing Norwegian railway network.

Track gradients

The maximum sizes of rising and falling gradients are defined by the TSI for the infrastructure of the high speed railway system (2008/217/EG) in Section 4.2.5. The steepest permitted gradient lies at 35 ‰. However, the slope of the moving average profile over 10 km must not exceed 25 ‰, and the maximum length of a slope at 35 ‰ is limited to 6 km.

Acceleration and deceleration

Due to passenger comfort needs, an upper limit for the maximum acceleration and deceleration is set for all trains. The values of maximum acceleration and deceleration shown below in each train’s data sheet are limited to these values in the calculation runs:

• Maximum acceleration: 1.0 m/s²

• Maximum deceleration: 0.8 m/s²



Passenger weight

For the calculation of the effects of different load factors on a train’s energy consumption, the resistance factors as well as the tractive and braking effort functions need to be adjusted subject to an average passenger’s weight and any belongings that they may bring onboard with them. Therefore, it is assumed that the average person weighs 75 kg and that on average, 5 extra kg per passenger are also brought onboard the train. In total, 80 kg per person is used in the calculations.

7.2.4 Technical train data

The following sections present the technical data of the trains that are used in this energy study. The data for these trains was collected based on sources already available to VWI, through internet and publication research, by contacting other transportation research institutes and universities, and by contacting the manufacturer and operators of the trains directly. Where no information was publicly or legally available, VWI used data from similar trains and knowledge gained from experience to estimate the missing data.

The resistance coefficients shown in the following tables are based on the dead weight of the train. For calculations with loaded trains, these resistance coefficients were changed appropriately.

ICE 3

In service since the year 2000, the ICE 3 (Class 403), Table 7-2, is currently the fastest passenger train on Germany’s high-speed rail network. Built as an electric multiple unit (EMU) with half of its cars being powered, it can reach a top speed of 330 km/h.

Passenger service with interoperable ICE 3 trains extends to Switzerland, France, the Netherlands and Belgium. Only recently, the first ICE 3 to have crossed the English Channel was displayed at St. Pancras Station in London.

Accommodating to German transport demands, ICE 3 trains are commonly operated in couplings of two units, adding up to a total length of 400 m with seating capacity for more than 800 passengers.

From the year 2011 on, ICE 3 trains will gradually be succeeded by Siemens’ Velaro D (Class 407).

Table 7-2. ICE 3 data sheet

Maximum speed 330 km/h

Maximum acceleration 1.5 m/s²

Maximum deceleration 1.0 m/s²

Power 8,000 kW

Length 200 m

Total mass (deadweight) 448 t



Mass on driven axles 224 t

Constant resistance coefficient 0.7799

Linear resistance coefficient 0.0000079183

Quadratic resistance coefficient 0.0001110267

Mass factor ρ 1.0422

Wheelbase 2.5 m

Energy recovery from braking Yes

Power for auxiliary needs 530 kW

Passenger seats 441

The following diagram, Figure 7-2, shows the tractive effort, braking effort, and running resistances of the ICE 3 with respect to the velocity of the train.

Figure 7-2. ICE 3 characteristics

ICE T

In order to offer high quality passenger services on conventional railway lines, starting in 1999, Germany’s Deutsche Bahn put the ICE T (Class 411) into service. This tilting body EMU consists of seven cars, three of which are motorised. The tilting ability of the train allows for the train to travel at higher velocities in curves.

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0

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0 50 100 150 200 250 300 350

[kN]

Speed [km/h]

Tractive effort Braking effort Running resistance



The ICE T has a maximum speed of 230 km/h, a maximum acceleration of 1.5 m/s², and a total deadweight of approximately 399 metric tons. Other important characteristics of this train are shown in Table 7-3. The diagram in Figure 7-3 depicts the tractive effort, braking effort, and running resistances diagrams of the ICE T.

Table 7-3. ICE T data sheet




Power 4,000 kW

Length 184 m

Total mass (deadweight) 399.2 t






Wheelbase 2.5 m



Passenger seats 382



Figure 7-3. ICE T characteristics

TGV POS

The TGV POS is a train used mostly in eastern France and southern Germany and has a maximum speed of 320 km/h. Unlike the ICE 3 and ICE T, this train is not an EMU. Important technical data for this train is shown in Table 7-4. The tractive, braking, and running resistance characteristics are shown in the diagram in Figure 7-4 .

Table 7-4. TGV POS data sheet




Power 9,280 kW

Length 200 m







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0

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0 50 100 150 200 250 300 350

[kN]

Speed [km/h]




Wheelbase 2.5 m



Passenger seats 380

Figure 7-4. TGV POS characteristics

Talgo 250

The Talgo 250 is a Spanish high-speed train and can reach a maximum velocity of 250 km/h. In Spain, it is also known as the RENFE Alvia 130. The train has passive tilting capabilities with a maximum body tilt of 3.5 degrees.

The Talgo 250 is powered by a power car at each end of the train. Due to this, most of the mass of the Talgo 250 is located on the ends, and not spread out evenly over the length of the train.

The Talgo 250 is equipped with variable-gauge axles to accommodate both the normal gauge and Iberian broad-gauge. A specialty of this train is that it is possible to change the gauge while the train is travelling, using dedicated gauge changing facilities (Talgo, 2010a).

For the study at hand, only the normal gauge was assumed for the train.

The technical data used for this train is listed in table 7-5.

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Table 7-5. Talgo 250 data sheet




Power 4,800 kW

Length 180 m






Mass factor ρ 1.04

Wheelbase 2.8 m (bogies on tractive units)



Passenger seats 299

The tractive effort diagram as well as the braking effort diagram and running resistances of the Talgo 250 are shown in the diagram in Figure 7-5.



Figure 7-5. Talgo 250 characteristics

Talgo 350

Similar to the Talgo 250, the Talgo 350 is a train made up of non-powered passenger wagons and a power car at the front and back of the train. However, the Talgo 350 can reach a maximum speed of 330 km/h. The number of passenger cars is variable with a maximum of 12 cars. The Talgo 350 has passive tilting capabilities and has a maximum body tilt of 2.7 degrees (Talgo 2010b).

The technical details of this train are shown in Table 7-6. The tractive effort, braking effort, and running resistances diagram is shown in the diagram in Figure 7-6.

Table 7-6. Talgo 350 data sheet




Power 8,000 kW

Length 200 m




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0 50 100 150 200 250 300 350

[kN]

Speed [km/h]






Mass factor ρ 1.04

Wheelbase 2.65 m (bogies on tractive units)



Passenger seats 365

Figure 7-6. Talgo 350 characteristics

AGV

The AGV is high-speed train that is in production, but not yet in operation. Its commercial service is planned to begin in 2011, and it will fully comply with TSI. It is an EMU with a maximum speed of 360 km/h. The AGV is available in configurations of 7, 8, 10, 11, and 14 cars for greater capacity flexibility.

For this analysis, the AGV 11 with 11 wagons and a length of 200 m was used. The deadweight of this train is 410 metric tons and it has a passenger seating capacity of 460 seats. The pertinent technical details of this train are given in Table 7-7 and diagram in Figure 7-7.

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[kN]

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Table 7-7. AGV data sheet




Power 8,400 kW

Length 200 m


Mass on driven axles 217.5 t




Mass factor ρ 1.05

Wheelbase 2.5 m



Passenger seats 460



Figure 7-7. AGV characteristics

SJ X2

The SJ X2, also referred to as X2000, is a tilting train used in Sweden. As seen in Table 7-8, the maximum speed of the train is 200 km/h, which makes it the slowest of the trains presented in this study. Other important technical data for the SJ X2 is listed below and the tractive effort, braking effort, and running resistances diagrams are presented in Figure 7-8.

Table 7-8. SJ X2 data sheet




Power 3,260 kW

Length 165 m





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0 50 100 150 200 250 300 350

[kN]

Speed [km/h]

Braking effort Running resistance Tractive effort





Wheelbase 2.5 m



Passenger seats 309

Figure 7-8. SJ X2 characteristics

Shinkansen N700 Series

The Japanese Shinkansen N700 Series was jointly developed by JR (Japan Railway) Central and JR West and was inaugurated in 2007. Due to passive tilting capabilities, it is able to travel in curves at a speed of 270 km/h. With its larger width of 3.36 m, the Shinkansen N700 Series is able to accommodate more passengers. However, its greater width makes it non-compliable with the TSI regulation limiting the train width to 3.15 m.

Due to this fact, the Japanese Shinkansen N700 Series is not included in this energy consumption analysis. If it had been included in the energy analysis, it would not have been possible to correctly compare its results with the results of the other trains.

Gröna Tåget

The Gröna Tåget (Green Train) is a Swedish vehicle research program with the aim “... to develop and maintain the level of competence needed to ensure that future passenger trains running on the Swedish railway network, will be able to meet with the special

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[kN]

Speed [km/h]




technical requirements and business demands brought about by the particularities of Nordic conditions” (www.gronataget.se). These Nordic conditions include cold climates, mixed traffic, and reverse running.

Planned features of the train include mechatronic bogies, an EMU design and a car body width of 3.46 to 3.55 metres for greater passenger capacity.

Gröna Tåget’s program partners include Bombardier Sweden, technical universities such as the KTH Royal Institute of Technology in Stockholm, and railway companies.

As the development of the train is still in a conceptual stage, with only some of the proposed technology having been prototyped and tested, it was not yet optimal to include this train in the study.

Velaro D

The Velaro D is a multiple-unit train and can be seen as the next generation of the ICE 3 and Velaro D trains are planned to be delivered to Germany’s Deutsche Bahn in the third quarter of 2011. The Velaro D is a multi-system train and can thus be used in Belgium, Germany, the French Rhine-Rhone line, and in Switzerland. It is also possible for the Velaro D to be coupled to the ICE 3 currently used in Germany. It uses IGBT power converters and it performs slightly better aerodynamically than the ICE 3.

In this analysis, the Velaro D is expected to perform very similarly to the AGV and it was therefore decided not to include the Velaro D in this study as the results of the two trains are not expected to greatly differ from each other.

7.2.5 Efficiency degree of the tractive system

In order to account for energy losses in the tractive systems between the pantograph and the wheel, the system’s efficiency degree η needs to be considered (cf. section 7.2.2).

For all trains, tractive and braking efficiency is modelled as a function of train speed as well as tractive effort and braking effort respectively, as shown in Figure 7-9.

𝜂 = 𝜂(𝐹𝑇 ,𝑉)

For negative tractive efforts, i.e. when the train is braking, η assumes the reciprocal value, in order to account for energy losses when mechanical energy is converted into electric energy again by means of regenerative braking.

�𝜂(𝐹𝑇 ,𝑉)|𝐹𝑇<0 = � 1𝜂(𝐹𝑇 ,𝑉)�𝐹𝑇≥0

This means that some of the mechanical energy is lost on the way through the train’s tractive system from the wheel to the pantograph when converted into electric energy.

In order to simplify the calculations, the efficiency functions applied only differentiate between two power converter technologies; GTO (gate turn-off thyristor) and IGBT (insulated-gate bipolar transistor) power converters.



Figure 7-9. Efficiency function for power converters with GTO thyristors

As the more modern technology, IGBT power converters can be expected to exceed GTO thyristor power converters’ efficiency by approximately 5 %. Table 7-9 lists the previously-introduced trains introduced according to the power converter technology installed.

Table 7-9. Power converter technology aboard the studied trains

GTO power converters IGBT power converters

ICE 3 (Class 403) AGV

TGV POS Talgo 250

ICE T (Class 411) Talgo 350

SJ X2

7.2.6 Infrastructure scenarios

In this study, some energy consumption calculations are carried out using basic scenarios and some using detailed scenarios. The following sections describe how the basic scenarios are developed, as well as the factors used for creating the detailed scenarios.

Basic infrastructure attributes

To calculate the (specific) energy consumption of a train, different infrastructure scenarios were defined for the train to run on. For this study, three infrastructure attributes are used to construct the basic infrastructure scenarios: track length, constant track gradient, and permitted track speed.

For track length, a length of 500 km is used for all of the basic infrastructure scenarios. For the track gradient, 11 different values are used; these are listed in the following table. Five different values for the permitted track speed were used for the basic scenarios;



these are also listed in Table 7-10. It is important to note that these basic infrastructure scenarios do not include any curves or tunnels. Combining the three infrastructure attributes together results in a sum of 55 different basic infrastructure scenarios.

Table 7-10. Basic infrastructure attributes and their values

Track length [km] Constant track gradient [‰] Permitted track speed [km/h]

500 0 220

±12.5 250

± 20.0 280

± 25.0 300

± 30.0 330

± 35.0

For further analysis, a tunnel was added to the infrastructure. The length of the tunnel was varied and the different amounts of energy depending on the tunnel length were calculated. The different tunnel lengths are shown in Table 7-11. The results of varying the tunnel length are described in a later section.

Table 7-11. Tunnel length used as attributes for detailed test scenarios

Tunnel lengths [km]

0

2

5

10

20

40

Passenger load factors and operations program

For the basic scenarios, a passenger load factor of 67 % was used for all of the seven trains. For the more detailed analyses, different passenger loads were used to examine their influence on the energy consumption of the train.

The operations program used for the basic test scenarios does not include any intermediary stops: the trains start at the beginning of the infrastructure and end at the end with no stops in between. However for the detailed analysis, different numbers of intermediary stops were investigated.

The different load factors and the number of intermediate stops used in the detailed analyses are shown in Table 7-12.



Table 7-12. Passenger load factors and stop quantities used as operational attributes for detailed test scenarios

Passenger load factors [%] Number of intermediate stops

0 0

10 1

20 2

50 5

67 10

100

Calculation of the scenarios

The software PULZUFA was used to calculate the energy consumption for the basic scenarios, namely the seven different trains on each of the 55 different infrastructures, given the passenger load factor of 67 % and no intermediary stops. The compiled results of these energy consumption calculations are found in the appendix of this report.

PULZUFA was also used for the detailed scenarios. These scenarios and their results are described in more detail in the following sections.



7.3 Specific energy consumption of trains

7.3.1 Passenger load factor effects

The trains studied offer different passenger capacities. In order to allow for the comparison of the train specific energy consumptions, the resulting energy consumptions are presented in watt hours per seat-kilometre [Wh/seat-km].

This also allows—under certain assumptions—an extrapolation of results for trains of the same type but with greater lengths and therefore higher seating capacities.

Figure 7-10. Seat load factor effect; ICE 3 at permitted track speed of 330 km/h

Figure 7-10 shows how the amount of specific energy consumption varies depending on the steepness of the track and the percentage of passengers (%pax) in the train; this Figure is based on the ICE 3 train. As can be seen, the different passenger load factors effect energy consumption only marginally on track gradients between -15 ‰ and +15 ‰.

On higher gradients, the effect grows. Compared to an empty ICE 3, a fully loaded train‘s specific energy consumption is about 5 % higher on steep slopes (i.e. 35 ‰). This can be observed for all speeds (220, 250, 280, 300 and 330 km/h). As the test scenarios involve a 500 km run with acceleration and deceleration on inclines, it is unlikely to encounter this spread of values in real-world operations.

As Norwegian load factors cannot be predicted at this stage in the study and the error resulting from assuming a deviant load factor is small, the assumption of an average load factor of 67 % for all trains is made. This leads to an average specific energy consumption that nicely represents energy consumption at different load factors.

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150

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]

Track gradient (‰)

ICE 3 ICE 3; 10% pax ICE 3; 20% paxICE 3; 50% pax ICE 3; 67% pax ICE 3; 100% pax



7.3.2 Track gradient effects

Figure 7-11. ICE 3 specific energy consumption at different permitted track speeds

Table 7-13. ICE 3 specific energy consumption values [Wh/seat-km]

ICE 3 Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 -51.34 -39.65 -26.61 -13.48 7.49 47.31 78.36 96.01 108.60 124.66 138.33

300 -56.28 -44.00 -31.16 -18.06 1.59 41.52 78.36 96.01 108.60 124.66 138.33

280 -59.35 -47.16 -33.96 -21.17 -1.38 37.64 78.36 96.01 108.60 124.66 138.33

250 -63.54 -50.49 -37.78 -24.71 -5.34 32.79 74.09 96.01 108.60 124.66 138.33

220 -66.60 -53.79 -41.07 -27.98 -8.54 28.76 69.55 94.62 108.60 124.66 138.33

Figure 7-11 shows the relationship between the specific energy consumption [Wh/seat-km], permitted track speed, and the track gradient. As Figure 7-11 shows, the specific energy consumption is a near-linear function of the track gradient. The behaviour of specific energy consumption as a function of track gradient is similar for all the trains studied. Figure 7-11 and the corresponding values given in table 7-13 are based on the specifications of the ICE 3 train and shown as an example. Findings for all trains studied are presented in the Appendix B.

In general and as can be expected, as the degree of the constant gradient increases, the amount of energy needed to power the train increases. Also, as the level of permitted speed on the infrastructure increases, the amount of energy needed to power the train increases because the trains can travel faster. However, as the gradient increases, the

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Track gradient [‰]

330 300 280 250 220



specific energy consumptions at different permitted speeds converge. This is because the trains cannot always reach their maximum speeds on the steeper gradients.

The main reason for the near-linearity of specific energy consumption as a function of track gradient is the use of regenerative braking, i.e. energy recuperation and feed-back of electricity into the power grid during deceleration phases.

Figure 7-12. Track gradient effect on average speed, ICE 3 at different permitted track speeds

Figure 7-12 above depicts the relationship the track gradient has on the average train speed for different permitted track speeds. As the (positive) gradient increases, the average speed of the train drops in a linear function of the gradient. Yet, this result must not necessarily be expected when a train is allowed to gather speed before the incline (cf. section 7.4.2). In the simulations, the train always started off from a stand-still and was forced to accelerate during the incline. As a result, the permitted track speed was not always reached.

The Figure 7-12 also shows that the average speed slightly drops on steep downhill runs. This is because the train needs to start decelerating sooner before it comes to a stop. Therefore, the deceleration phase lasts longer, the travel time is longer, and the average speed is lower.

7.3.3 Permitted track speed impact and train comparison

Figure 7-13 shows the effects of the permitted track speed on the specific energy consumption on flat terrain. For the studied trains—with the exception of the ICE T and the SJ X2—specific energy consumption is an almost linear function of the permitted speed (when not running uphill or downhill) and increases with train speed.

As the ICE T’s maximum speed is 230 km/h, only the result of the run at 220 km/h is shown in the following Figure. The same goes for the SJ X2. Note that this train’s

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330 300 280 250 220



maximum speed is 200 km/h; the specific energy consumption nonetheless is shown at a permitted track speed of 220 km/h.

With reference to the trains’ capacities, the amount of energy consumed per seat-km is lowest for the AGV and the ICE 3—the trains with the lowest aerodynamic resistance coefficients (cf. section 7.2.4)—regardless of the trains’ speed.

Figure 7-13. Effect of permitted track speed on specific energy consumption on flat terrain

Notably, the EMU trains (ICE T, ICE 3, AGV= perform better than the trains consisting of power cars with unmotorised intermediate cars (Talgo 250, Talgo 350, TGV POS, SJ X2). This points to two general advantages of EMU train designs that lead to lower values of specific energy consumption:

1) The distribution of the tractive system components leads to a higher ratio of friction mass to total mass compared with power car trains, which allows for better train performance.

2) The distribution and the underfloor or roof-top placement of the components of the tractive system along the length of the train creates more space for passengers to be seated.

7.3.4 Tunnel impact on specific energy consumption

In tunnels, trains encounter a higher aerodynamic resistance than when they are in a normal outside environment. The main influences on the aerodynamic resistance in tunnels are:

a) The ratio between the train’s and the tunnel’s cross section

b) The length of the tunnel

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200 220 240 260 280 300 320 340

Spec

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[Wh/

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-km

]

Permitted track speed [km/h]

ICE 3 TGV POS ICE T 411 AGV Talgo 250 Talgo 350 SJ X2



As the train travels into a tunnel, it acts like a piston moving into a cylinder, working against the air inside the tunnel. A larger tunnel cross section means less aerodynamic resistance, and therefore lower energy consumption. The longer the tunnel is, the harder it is for the train to displace the air by pushing it towards the end of the tunnel. For shorter tunnels (up to 2 km), the aerodynamic resistance ratio quickly increases with the tunnel length. For longer tunnels, the ratio increases more slowly (cf. Gackenholz 1974).

When the aerodynamic resistance ratio according to different tunnel lengths is known, the ratio of overall specific energy consumption between tunnelled and outside track can be calculated.

Figure 7-14. Tunnel factor ftunnel as a function of tunnel length

Figure 7-14 shows the effect of tunnels on the overall specific energy consumption as a ratio between the specific energy consumption inside of and outside of tunnels (ftunnel). Table 7-14 gives the tunnel factors for several different tunnel lengths.

The results are shown for single track tunnels only, in compliance with the European technical specifications for high-speed railway systems.

For tunnel lengths greater than 2 km, ftunnel assumes a near-linear function. For tunnels shorter than 2 km, ftunnel can be approximated with a linear function as well.

Table 7-14. Tunnel factors for flat tracks

Tunnel length [km] 0 0.5 1 1.5 2 5 10 20 40

ftunnel 1.00 1.21 1.41 1.49 1.54 1.59 1.64 1.73 1.88

Figure 7-14 and Table 7-14 are only applicable for flat tunnels, i.e. a track gradient of 0 ‰. As the track gradient varies, so does the ratio between the specific energy consumption outside of and in tunnels. This is because in the simulation model, the tunnel only affects the aerodynamics and therefore the quadratic term of the running resistance formula.

0

1

2

0 5 10 15 20 25 30 35 40

f tunn

el

Tunnel Length [km]



Figure 7-15. Corrective term for tunnel factor ftunnel on rising and falling track gradients

In tunnels on a track gradient other than 0 ‰, the factor ftunnel needs to be multiplied with a corrective term given in Figure 7-15 and Table 7-15 before applying it to the original specific energy consumption value.

Table 7-15. Corrective terms for rising and falling tunnel gradients

Gradient [‰] -35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Corr. term 0.06 0.25 0.44 0.65 0.92 1.00 1.07 1.12 1.16 1.20 1.25

In order to estimate specific energy consumption in a tunnel, the basic specific energy consumption value for flat terrain (cf. table 7-13, and the Appendix B for other trains) is multiplied with the tunnel factor ftunnel for the given tunnel length and with the corrective term from Table 7-15 to account for track gradients.

7.3.5 Effects of intermediate stops

To test the effect of intermediate stops on the specific energy consumption values, further scenarios were defined where evenly spaced stops were added to the basic 500 km scenario with a track gradient of 0 ‰.

Figure 7-16 shows the upper and lower limits for the resulting effect on specific energy consumption at different permitted track speeds if one, two, five, or ten intermediate stops are added to the basic scenario, which has no intermediate stops but one final stop at the end of the infrastructure.

While the values on the far left show the basic scenario of a 500 km train run, where the train accelerates only once and decelerates once, the other scenarios include intermediate stops, leading to a distance between stops of 45 km with 11 stops (10 intermediate stops), which is shown on the right hand side of the Figure.

0

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-40 -30 -20 -10 0 10 20 30 40

Cor

rect

ive

term




As is shown in Figure 7-16, for lower speeds the specific energy consumption rises with stop quantity. At high speeds however, with a rising number of stops, the specific energy consumption declines.

Figure 7-16. Effect of intermediate stops on specific energy consumption (ICE 3, 0 ‰ track gradient)

Obviously, for all permitted track speeds, the average speed of a train can be expected to decrease as the number of intermediate stops increases. Figure 7-17 shows that this effect is stronger for higher permitted track speeds.

Figure 7-17. Effect of intermediate stops on average train speed at permitted track speeds of 220 and 330 km/h

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As the effect of energy consumption decreasing over stop quantity at the upper end of permitted track speeds is somewhat counterintuitive, further explanation is given in the following paragraphs.

The electric energy consumed by the ICE 3 for the whole run (Eel) is made up of four components: energy consumed while accelerating (Eel,acc), while running at constant speed (Eel,const), auxiliary energy (Eel,aux), and energy recovered while braking regeneratively (Eel,dec); all of these are measured in kWh.

Looking at Figure 7-18, where these components are shown for a permitted track speed of 330 km/h, it can be seen that when energy recovery from braking is not taken into consideration, the energy consumption will increase with the quantity of stops.

As the number of intermediate stops increases, the energy consumed while accelerating increases more than the energy consumed while running at constant speed decreases. Once regenerative braking is considered, the amount of energy recovered from the braking phases is enough to compensate for the rising energy consumption from the increased amount of acceleration.

Aerodynamic resistance is higher when trains travel at higher speeds. With the addition of intermediate stops, a train with a maximum permitted speed of 330 km/h will travel for less time at the maximum speed, which leads to a reduction of energy dissipated due to aerodynamic resistance. In comparison, aerodynamic resistance will be reduced less by the addition of intermediate stops for a train travelling with a maximum permitted speed of 220 km/h.

Figure 7-18. Effects of stop quantity for the ICE 3 at a permitted track speed of 330 km/h

1 stop 2 stops 3 stops 6 stops 11 stopsE_el,dec -384 -784 -1 176 -2 351 -4 311E_el,aux 844 868 901 999 1 162E_el,acc 1 030 2 060 3 090 6 181 11 331E_el,const 8 926 8 208 7 458 5 206 1 454E_el 10 416 10 353 10 273 10 034 9 636

-5 000

0

5 000

10 000

15 000

Ener

gy c

onsu

mpt

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[kW

h]

E_el,const E_el,acc E_el,aux E_el,dec E_el



It is of interest, that a study on the energy consumption of the Gröna Tåget concept train (Lukaszewicz & Andersson 2009, p. 19) shows similar results, where at the lowest speed (250 km/h) more energy is consumed with a rising number of intermediate stops, whereas energy consumption decreases with stop quantity at maximum speed.

To reconfirm the findings presented above, the runs were repeated with the TGV POS. As a matter of fact, specific energy consumption of the TGV POS behaves just the same with respect to permitted track speed and stop quantity.

Figure 7-19. Stop quantity factors

Stop quantity factors may be derived to be applied to the values of specific energy consumption from the basic scenarios to model the influence of intermediate stops. These factors are shown in Figure 7-19. For the maximum number of stops shown, dependent on the speed allowed, specific energy consumption lies in a range between 92.5 % and 108 % of the specific energy consumption with just one stop per 500 km.

0,90

0,95

1,00

1,05

1,10

0 2 4 6 8 10 12

Stop

qua

ntity

fact

or


330 300 280 250 220



7.4 Infrastructure design effects

7.4.1 “Steep and straight” vs. “flat with a detour”

When designing a railway line with constant gradient between two points A and B, where B lies at a higher elevation, there are several possibilities:

A straight line running from A to B shows the steepest gradient and shortest track length, while lower gradients can only be achieved by lengthening the track (cf. Figure 7-20, where a is the shortest but steepest connection, and c is the longest with the lowest gradient).

Figure 7-20. Line design between A and B Figure 7-21. Constant gradient of the line betw. A and B

The gradient of the line is given by the relationship between elevation difference (h) and distance (d) as shown in Figure 7-21.

For small angles, as encountered on railway lines (i.e. gradients of up to 35 ‰), the relation between the track lengths of two different connections is inversely proportional to their gradients. In other words: if the length is doubled, half the gradient results. The difference between the track length and the distance as projected onto the x-y-plane can be neglected.

As shown in section 7.3.2, it is to be expected that the specific energy consumption rises as the gradient increases. On the other hand, as downhill runs get steeper, more energy can be recovered because trains need to brake harder. Also, on higher gradients, the average speed is reduced. These aspects lead to the following questions:

Is it better to design a longer line and take a detour, thus lowering a train’s specific energy consumption, than to design a straight but steeper line? How is travel time affected by this choice?

The values for overall energy consumption and travel time between two reference points A and B were calculated at a gradient of 25 ‰. Values calculated at other gradients (12.5 ‰, 25 ‰, 30 ‰, 35 ‰) were then normalised to the reference values at the gradient of 25 ‰. These values are shown in Figure 7-22.



Figure 7-22. Relative energy consumption/recuperation and travel time, ICE 3 at track speed 330 km/h

On the right hand side of the Figure, values for the uphill run are shown. For example, the relative energy consumption at 12.5 ‰ is approximately 1.4 times higher than at the reference gradient of 25 ‰. As can be expected, in the uphill direction the travel time decreases with a rising gradient because the total distance is shortened.

On the left hand side, findings are shown for the downhill run. As on downhill runs, generally energy can be recovered by braking, values for the relative energy recuperation (i.e. energy fed back into the power supply system) are presented.

As demonstrated in Figure 7-22, on both uphill and downhill runs, the shortest routes with the steepest gradients are most energy-efficient: overall energy consumption is lowest on the shortest connection with the steepest incline, and more energy can be recovered by regenerative braking on steeper downhill runs.

Although the average speed is quite reduced on steep uphill runs, the travel time is also shortest on the steepest runs both in uphill and downhill direction.

These findings hold for other trains such as the TGV POS and the ICE T as well. However, the results must be restricted to these given assumptions:

Constant gradient throughout the train run: the train is not able to gather momentum before the incline.

No tunnels on the track: in hilly or mountainous terrain, as a more direct line is chosen, the tunnel ratio may rise. This may well lead to additional energy consumed on steeper lines with more tunnels and to findings different from those presented above.

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7.4.2 Running into inclines at Vmax

While in the previous sections, the trains were simulated starting off from a standstill even on a sloped track, different findings may be expected once the trains are allowed to gather momentum before they reach an incline. When this is the case, less energy is needed to maintain their speed. The question to be answered is whether there is a preferable design for the inclined track. Once the total track distance and the elevation are fixed, is it still more energy-efficient to run over short but steep inclines and use the remainder of the total distance for recovering speed? Or is an alignment preferable where the incline is not as steep but longer?

To assess the effects of these different possibilities in track layout, additional infrastructure scenarios were defined with a fixed average gradient of 6 ‰. The elevation difference between the locations where the train enters and leaves the infrastructure was set at 120 m with a corresponding distance of 20 km.

The track gradient of the single incline was varied with values given at 12.5 ‰, 20 ‰, 25 ‰, 30 ‰ and 35 ‰. This yields corresponding incline lengths of 9.6 km, 6 km, 4.8 km, 4 km and 3.4 km. In each case, the remainder of the total distance is used to recover any speed on flat terrain that may have been lost during the incline.

The calculations were done for three trains (ICE 3, ICE T, and TGV POS), yet only those findings for the ICE 3 are presented below, since they hold for all of the three trains.

Total distance Elevation difference Average gradient

20 km 120 m 6 ‰ Figure 7-23. Uphill, downhill and average specific energy consumption when running into inclines, ICE 3, permitted track speed 330 km/h

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To reconfirm the findings presented in this section, further scenarios were defined in the same way as the scenarios described above, with elevation differences of 120 m and 180 m. These additional findings can be found in the Appendix B

As shown in Figure 7-23, on uphill runs, it is preferable to design short but steep inclines. In contrast, for downhill runs the design of longer inclines with lower track gradients shows to be more energy-efficient. On downhill runs it is preferable to make efficient use of regenerative braking, i.e. prolong the braking phase, so that more time is at hand for energy recovery. On average, i.e. for a train travelling both ways, the effects almost cancel each other out, with a small advantage for longer inclines with a lower gradient.

Compared to the effect of tunnels on energy consumption presented in section 7.3.4, the effect of incline design is only marginal.

Although at first glance the findings may seem contradictory to those of the previous section, it is not. While previously trains had to accelerate and decelerate from and to a standstill on the inclines, here they enter the infrastructure at their maximum speed. Furthermore, in section 7.4.1 the total distance of the train run was varied according to the gradient, whereas here it is held constant.

7.4.3 Continuous vs. intermittent inclines

While the previous section showed that it is energetically advantageous to design long and not so steep inclines when using regenerative brakes, this section discusses whether inclines should be designed continuously or intermittently to allow for the trains to regain speed between stretches of rising track.

To this end, six scenarios were defined with a varying number of intermittent inclines to overcome a height difference set at 600 m. The total distance measures 100 km, so that an average gradient of 6 ‰ is achieved for the whole run. The local track gradients of the intermittent inclines (steps) were set at values rising with the number of steps. Table 7-16 gives an overview of the step numbers studied and their corresponding local gradients.

Table 7-16. Steps and gradients

Number of Steps Gradient of each step

1 6 ‰

2 12.5 ‰

3 20 ‰

4 25 ‰

5 30 ‰

6 35 ‰

The distance left between the intermittent inclines is used to regain speed on flat terrain. The scenarios were simulated with the ICE 3, the ICE T, and the TGV POS trains. To account for trains not only travelling one-way, aggregate results for both uphill and downhill runs are shown in Figure 7-24.



Figure 7-24. Average specific energy consumption (up- and downhill) on intermittent inclines

From Figure 7-24, it can be seen that an optimum of specific energy consumption can be achieved when the total elevation difference is divided into two to three stretches of rising track with gradients between 12.5 ‰ and 20 ‰, although the effect is not expected to raise energy-efficiency drastically.

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7.5 Effects of traffic operations on energy consumption

7.5.1 Economical driving: coasting before stops

In addition to recovering electric energy when a train is braking, energy consumption can be reduced by letting trains coast down to a certain speed before their next stop. That way, the tractive system will neither consume nor generate electric energy. Any energy consumption remaining is then due to auxiliary needs.

To assess the effect of economical driving, an ICE 3 train was run on the basic infrastructure scenarios with intermediate stops at a permitted track speed of 330 km/h. The target speeds at which coasting ends and normal braking begins (coasting end speeds) were set to 100 km/h, 200 km/h, 250 km/h and—as a reference to normal operations—330 km/h.

Figure 7-25. Effect of coasting before stops on specific energy consumption; ICE 3, Vmax = 330 km/h, flat terrain

As Figure 7-25 shows, the specific energy consumption drops as the coasting end speed is reduced, which means that the train is allowed to coast longer until reaching a lower speed. Furthermore, the rate of the reduction in specific energy consumption rises with reduced target speeds.

However, as coasting target speed is reduced, the travel time rises, because the train does not decelerate as much as it would as when the brakes are applied. The gain from a reduction in energy consumption is traded off to a loss in average speed. Figure 7-26 gives an idea of how the average speed of the train is affected by coasting before stops. It is noteworthy that the rate of average speed reduction rises as coasting target speeds get lower.

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Figure 7-26. Effect of coasting before stops on average speed; ICE 3, Vmax = 330 km/h, flat terrain

Effectively, economical driving with coasting before stops seems most promising with a coasting target speed not below 200 km/h for the ICE 3. This amounts to 60 % of the permitted track speed and maximum speed of the train. Although the specific energy consumption may be reduced even further by setting lower coasting target speeds, this comes in at the price of heavily reduced average speeds.

7.5.2 Alignment of crossing and passing loops

Crossing loops

On a single-track railway line, trains running towards each other need to cross paths at some point. This can happen either in train stations or on the running main line when crossing loops are built. To allow for train crossings at high speeds, crossing loops need to be of a certain length so that no train needs to be forced to a full stop.

Crossing loops can be designed in two ways; these are shown below in Figure 7-27 and Figure 7-28.

Figure 7-27 show the trapezoid design. With this design, one train stays on the main track and runs through the crossing and the train moving in the opposite direction is led through the siding. As switches cannot be travelled over at maximum speed, the train moving to the siding is forced to reduce its speed to the maximum allowed speed of the switches. It

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is allowed to regain its speed running through the siding, but it has to brake once more before moving again onto the main track.

Figure 7-28 shows a crossing loop in the rhomboid design. With this design, both trains are required to reduce their speed at the end of the crossing loop when they travel over the switches.

As for the question which design is preferable from an energy consumption point of view, on flat terrain (track gradient = 0 ‰) both designs yield approximately equal results. Table 7-17 shows the specific energy consumption of two ICE 3 trains running through the crossing loop. The runs were simulated for crossing loops with a length of 25 km over a total distance of 250 km.

The speed for travelling over the switches at either end of the crossing loops is restricted to 160 km/h.

Table 7-17. Specific energy consumption in crossing loops on flat terrain

Crossing loop design Specific energy consumption 250 km total distance

Trapezoid 46.83 Wh/seat-km

Rhomboid 46.87 Wh/seat-km

As is expected, the results for crossing loops on flat terrain only differ marginally and the difference may well be neglected.

On sloped terrain, however, differences in energy consumption can be expected, which result from differences in the specific energy consumption for uphill and downhill runs. Moreover, another design possibility needs to be accounted for: on trapezoid crossing loops, it is of importance as to which train runs through the siding, travelling over the switches at reduced speed; the train running uphill or the train running downhill.

As an example for crossing loops on sloped terrain, a track gradient of 20 ‰ and ICE 3 trains are simulated on a 25 km-long crossing loop and a total distance of 250 km.

Figure 7-28. Crossing loop; rhomboid design



Table 7-18. Specific energy consumption in crossing loops on sloped terrain

Crossing loop design Specific energy consumption 250 km total distance

Trapezoid: Train running uphill uses the siding

40.11 Wh/seat-km

Trapezoid: Train running downhill uses the siding

43.14 Wh/seat-km

Rhomboid 39.88 Wh/seat-km

As Table 7-18 shows, the design of a trapezoid crossing loop with the siding reserved for the train running downhill is to be rejected, as it shows the highest specific energy consumption for the two trains. Due to the marginal differences in the energy consumption results of the trapezoid and rhomboid designs, no definitive recommendations can be given as to which is more suitable.

Passing loops

In contrast to crossing loops that enable trains running in opposite directions to pass each other without conflicts, passing loops may be installed to allow one train to overtake another train moving in the same direction but at a lower speed.

Especially on single-track high-speed lines, passing manoeuvres between high-speed trains are unlikely. Train passings are more common with mixed traffic lines, where slow traffic such as freight or regional passenger trains are passed by long-distance, high-speed trains. With mixed traffic, double-track lines are commonly used.

The design of a passing loop on a double-track line resembles that of a trapezoid crossing loop. As previously described for the crossing loops, speed is restricted by the design of the switches. Therefore, the slower trains being passed are not required to reduce speed for moving to the side. Hence, slower trains being passed by high-speed trains on a mixed traffic double-track line are not expected to cause significant changes in energy consumption.

7.5.3 Effects of train crossing locations and power supply characteristics on energy consumption

Normally, the locations of where trains cross each other on the running main line are determined by the timetable. However, if energy consumption is considered in the timetable construction, a number of questions need to be answered regarding the following:

- The characteristics of the railway power supply system - The timetable frequencies of the trains - The number of intermediate stops - The spacing between the intermediate stops



If a railway line’s power supply sections can be interconnected while maintaining electric phase balance, the influence of the train frequencies and intermediate stop characteristics diminishes, and the highest effects on overall energy consumption result from energy loss in the power lines and the railway’s power supply equipment.

However, if the supply sections are not interconnected but closed, an energetically efficient timetable is constructed in such a way that two trains cross while one is running uphill and the other is running downhill. By doing this, the energy recovered from the train running downhill can be re-used by the train running uphill in the same supply section.

In the case that there is no train travelling uphill at the same time as the downhill train, the regained braking energy from the downhill train either has to be converted into thermal energy through braking resistors (which is a total dissipation of braking energy), accumulated in on-board electric capacitators (or similar electric energy storage devices), or fed back into the public power grid via the next power supply station.

The possibility of feeding electric energy back into the public power grid is subject to two conditions:

1) The network operator has to accept the generated surplus electric power, which will only be done when the general demand for electric power is higher than the power supplied from other sources.

2) The power feed-back into the grid does not lead to an asymmetric power load of the three phase system.

Regarding infrastructure and timetable design and for an efficient use of electric energy, it is preferable to let trains running in opposite directions cross on inclines in the same power supply section. However, this means defining the locations of crossing loops solely on the basis of energy consumption considerations, regardless of any other operational or even environmental conditions and restrictions. For instance, an efficient railway alignment in terms of energy recuperation may well affect the circulation times of rolling stock and therefore lead to a higher number of trains needed to service a line.

Given these considerations, it can be said that in order to retain the flexibility of constructing and changing timetables based on transport demand, it is important to have a railway power supply system that allows for electric power feed-back from a single-phase catenary network into the three-phase public power supply network. This calls for every single power supply station along a railway line to be connected to the three-phase public power supply network.

More detailed information on the power supply for electric railways is provided by Biesenack et al. (2006) and Kießling et al. (1998).



7.6 Conclusion

The purpose of this study was to conduct an analysis of high-speed railways and trains in order to identify typical levels of energy consumption as well as to determine preferable train designs. To accomplish this, technical data was collected on international, high-speed trains. More than 50 infrastructure scenarios were developed, and different operations programs were tested. Using VWI’s software tool PULZUFA, the specific energy consumptions (measured in [Wh/seat-km]) for the different situations were estimated and compared with each other.

One finding from the analysis is that two of the trains studied exhibit a significantly lower specific energy consumption than the others: the German ICE 3—in service since the year 2000—and the French AGV, which will shortly be put into service in Italy. From the characteristics of these trains, conclusions can be drawn regarding the requirements for energy-efficient and state-of-the-art high-speed trains as well as the future development of high-speed trains and their characteristics.

Three major factors can be pointed out that have a positive effect on the energy efficiency of trains:

4) The aerodynamic design of the train: a small cross section, in combination with an aerodynamic design of the front and favourable materials for the train’s surface. Especially at high speeds, energy consumption depends largely on the quality of aerodynamic design.

5) EMU trains: distribution of the tractive system components along the train increases performance and creates more passenger space.

6) The use of power converters with IGBT technology increases the efficiency degree of the train’s tractive system.

As for the future development of high-speed trains, more incremental improvements are expected than huge advances. This can be noted from the comparison of the specific energy consumptions of the ICE 3 and the AGV. Although these trains were introduced into service almost a decade apart, they both exhibit similar levels of specific energy consumption.

One reason behind these incremental improvements may be due to the restriction that the railway infrastructure has on the trains. Although high-speed trains have the potential to increase their energy efficiency via innovation in aerodynamics, lightweight construction, and technical component improvement, this potential is limited by the conditions of railway infrastructure with its long service life.

More detailed analysis of the infrastructure design revealed that tunnels considerably affect the amount of energy consumed. The specific energy consumption in tunnels increases as the tunnel length or the quotient between a train’s and the tunnel’s cross section increases. In contrast, the effect of different designs of track incline arrangements was found to be comparatively small.

With regards to train operations, economical driving, i.e. letting a train coast down to a certain speed instead of braking right away, was found to be energy-efficient only to a



certain extent. If the coasting phase lasts for too long, the average train speed will decrease to levels unfitting of high-speed railway operations.

Regarding the design of crossing loops on single-track lines, favourable layouts have been found. While there is no significant effect on flat terrain, on inclines the crossing loop should be built either in the form of a rhomboid, or in the form of a trapezoid with the siding reserved for the train travelling uphill.

For the possibility and the extent of energy recovery, the railway power supply system plays an important role. If power supply sections are interconnected and power supply stations are be connected to the public power supply network, energy recovered from using regenerative brakes can be used in the most flexible way.

The values for the specific energy consumption derived from the basic infrastructure scenarios serve well as input values to estimate the energy consumption of trains on potential railway lines. Combined with corrective factors and findings regarding the infrastructure design and traffic operations, they may lead to an early-stage energy consumption assessment for a set of possible railway alignments. However, in order to provide more detail and accuracy to the analysis, both the infrastructure and rolling stock need to be defined and modelled in greater detail as the characteristics of and even more importantly the interaction between the rolling stock and infrastructure significantly affect the overall energy consumption.



8 NOISE 8.1 Introduction

This report is the Phase 2 report in the Jernbaneverket High speed rail assessment project 2010 – 12 concerning noise and vibration. The report gives

• Results of literature studies on noise and vibration from high speed trains. • Discussion of remedial actions on rolling stock and track considering noise and

vibration from high speed trains. • Methodology on calculation of noise, vibration and ground borne noise which may

be used in Phase 3 of the project.

The High Speed Railway systems (HSRs) defined as "high-speed" in this context is considered to be electrically powered and capable of speeds up to at least 250 km/h.

From a noise perspective the noise characteristics of HSRs vary considerably as speed increases. For that reason it may be beneficial to subdivide the HSRs into 3 sub-categories:

1) “high-speed,” with a maximum speed of about 250 km/h, 2) “very high-speed,” with a maximum speed of 400 km/h 3) “maglev,” magnetically levitated and powered systems representing a potential

speed range of above 400 km/h. For practical purposes only the 1) and 2) is considered feasible for long distance travelling in this analysis. The report is written on a general basis and gives the main topics and conclusions concerning noise, ground borne noise and vibration from high speed trains. The explanations of the three topics are given below.

When a person is standing outside near a railway track, he will hear the noise from the train which is called airborne noise since it is transmitted through the air. In addition he will feel movements in the feet and in the body. This is vibration . The frequency content which can be felt by human beings is low, and is measured up to 80 Hz. The vibration will be transmitted in the ground to nearby buildings, and floors, walls and ceilings are vibrating. The vibration gives pressure differences in the air and noise is radiated. This noise is called ground borne noise. The ground borne noise level is higher in the room than outside because the radiated noise is amplified in the room, and because the vibration in the panels and slabs are amplified. The main frequency content in ground borne noise usually is in octave frequency bands 63 – 250 Hz.



8.2 Rolling stock

8.2.1 EU requirement for noise from rolling stock

It is likely that DIRECTIVE 96/48/EC: “Interoperability of the trans-European high speed rail system”, will be a guideline also for Norwegian HSR. The main requirements are:

– Limiting values LpAeq,T for the stationary noise of rolling stock: 68 dB for train sets – Staring noise for electric trainsets: Class 1/Class 2 = 85/82 dB – Pass-by noise has different limits at different speeds, see table 8-1. Measured 25 m

from centre of track, 3.5 m above ground in a non reflecting environment.

Table 8-1. Limiting values in Directive 96/48/EC. Measured 25 meters from the track

8.2.2 Noise sources in rolling stock

The noise radiated from a railway line is very complex and the noise contribution from the dominant noise sources will depend on the train speed. At very low speeds the traction noise dominates, at higher speeds the rolling noise dominates, and at speeds higher than 200 km/h the aerodynamic noise contributes and increases strongly with the train speed. In appendix A is commented on the important parameters concerning the noise from the rolling stock.

The train speed ve for which the aerodynamic noise equals the rolling noise depend on the track. In the Harmonoise reports from 2001-2003 this speed was assumed to be around ve = 250 km/h. However in later references this speed is higher, more around ve = 300 km/h. In Figure 8-1 is shown the noise level as a function of speed that is used in the calculations of the noise level from a future high speed line between England and Scotland. This is based on the measured noise level of currently operated high speed trains (Gauitier et al. 2007), and the current noise level requirements for new trains from the European Community. (Council Directive 96/48/EC).



Figure 8-1. From British studies of high speed lines. Day time average noise level (L eq,06-18) at 25 meters (HS2 project 2010).

8.2.3 Train suppliers and noise data of the current high speed trains

The list of suppliers of HSRs includes, but not limited to:

Bombardier CNR Tangshan (Chinese CH380) (Bombardier cooperation) Siemens AG Talgo Alstom GE (consider development, not yet confirmed) Kawasaki Heavy Industries

Consortiums including the above manufacturers are also sometimes established with local suppliers.

Results from NOEMIE project compared with TSI values are given in Table 8-2.

Table 8-2. Measured noise levels from different high speed trains compared to the TSI limit.



The measured values in Table 8-2 show that the noise levels are higher than the TSI noise emission limits. Future generations of high speed trains are expected to fulfill the TSI requirements. This is beneficial for the high speed lines in Norway.

8.2.4 Future trends in development of high speed trains

The challenge in predicting noise from future HSRs is embedded in the fact that they are not yet built.

For the same reason, the train manufacturers are restrictive with information on their ongoing development and design targets on the different technical segments, including noise.

However, a summary of the future thoughts on development from the train manufacturers gives some indications on how noise from future train models may evolve versus the TSI.

Some of the more likely technical developments or consequences are:

• Trains will be lighter in weight • Trains will have more optimised aerodynamic properties • Wheel hub motors will lower the weight and lower the height of the noise source

above ground • Modular construction allow better optimisation of size and energy consumption • Improved electronic computer systems for control and management

The impact on the noise and vibration levels will, however, depend upon many factors such as the actual speed, if tracks are dedicated to HSR and the choice of ballast or slab tracks.

Some noise sources, for example the pantograph, although small aerodynamic improvements may be achieved, will remain a significant noise source at high speeds.

The future trends in HSR development will therefore contribute to a lower noise level, supporting the expectation that the noise levels in the TSI can be fulfilled.

However, it seems unlikely that the margin between future noise levels and the TSI levels will be greater than the range of 0 to 3 dB for the trains that would enter service within the next 10 years.

8.3 Track systems

8.3.1 State of the art for track systems

Ballasted track

The combined surface roughness of the rail and wheel surfaces is the main influence parameter on rolling noise generation and differences of noise levels in the order of 8 - 10 dB between track having low and high corrugation level is reported. Efforts therefore should be made to develop solutions that give minimal corrugation of the rail. However the mechanism of rail roughness generation is not fully understood. Why corrugation is developed in one section of a train line and not in another obviously identical section often cannot be



explained. The probability of surface wave generation is higher for lines with only one type of trains and one speed, and in curved tracks having stiff rail pads.

The stiffness of the rail pad is very important for noise radiation from the rail. A soft rail pad gives high vibration in the rail and therefore high noise levels. A stiff rail pad gives lower vibration values and lower noise levels for a given corrugation. However corrugations are more easily developed when the rail pads are stiff, which gives a considerable increase in noise level.

In appendix D is commented on the important parameters concerning the noise from the track.

Slab track

In slab track there is no ballast, and the track is fastened to a concrete slab. The fastening system must give the elasticity in the track which is lost when there is no ballast. In appendix D is shown different types of fastenings systems. The initial costs are reckoned to be higher for slab track than for ballasted track, however the maintenance costs are lower.

The noise from a slab track generally is higher than from a ballasted track, typically a 2 – 4 dB increase is found. One reason is that the sound absorption in the ballast is lost, but the main reason is that in a slab track usually the rail fastening system is softer in order to obtain the elasticity that is lost from the ballast. Therefore the rail vibrates more, and the noise radiation from the rail is higher. The noise radiation from the massive slab can usually be neglected.

8.3.2 Track system for the calculations in project Phase 3

For slab track the requirements for long time settlements are very strict because the possibility for rail height adjustment is limited. This may require considerable stiffening of the ground in clay areas. In addition slab track gives more noise. Based on these two reasons it is expected that most probable ballasted track will be chosen in Norway. In the calculation method for noise in phase 3 ballasted track is foreseen. However this should be clarified before the work in phase 3 starts, the conclusions from the other working groups concerning track form may be different.

The track system in the Norwegian lines is UIC60 rails and monoblock sleepers. There are some advantages concerning noise by using biblock sleepers, but in high speed lines the advantage is smaller. And since monoblock sleepers are used in the ordinary railway lines it is foreseen that this will be chosen in the high speed lines as well.

The relatively soft rail pad which is used in Norway will give considerable higher noise level than a stiffer pad in high speed lines. When the track for the new high speed lines shall be designed in detail the rail pad stiffness must be studied and optimised.

In the measurements of noise from different European highs speed trains in the NOEMIE project a reference track system is provided. The data for different trains are given in table 8-2. The measured data is from a track having a specified roughness values and a specified Track decay rate. (See appendix D) The roughness limit is given in Figure 8-2, and is compared to measured roughness values in different European high speed lines.



Figure 8-2. Rail roughness results from different sites of the NOEMIE project, vs limit proposal. (Fodiman & Gautier 2005).

In most of the European tracks the measured rail roughness is lower than in the reference track. It must be foreseen that the maintenance in the Norwegian high speed lines will keep the rail roughness low and within the TSI specification. The key parameter is the grinding of the rail. It is very important that the grinding process is regularly and with short time intervals so that roughness will not develop. When there are wave patterns in a rail surface it will soon come back after grinding. High speed grinding, in a speed of around 80 km/h, has been successfully used in 16 different high speed lines in Germany and Switzerland (Taubert 2010).



8.4 Noise calculations

8.4.1 Noise limits in regulations

The current Norwegian guidelines for rail traffic noise are based on T-1442, (Miljøverndepartementet 2005) and NS 8175 (Standard Norge 2008). T-1442 is a guideline for noise in community planning. NS 8175 is a standard for acoustic conditions in buildings. . Measurements should be made according to NS 8177 (Standard Norge 2010).

The limits for noise exposure for residences are given in the Table 8-3.

Table 8-3. Requirements in T-1442

Noise from events Noise, energy average

Outdoor noise L5AF ≤ 75 dB Lden ≤ 58 dB

Indoor noise LAmax ≤ 45 dB (bedrooms at night)

LAeq, 24h ≤ 30 dB (all rooms for permanent occupation)

L5AF is the A-weighted level with time constant “FAST” exceeded by 5% of the noise events

Lden (day – evening – night level) is the A-weighted equivalent level with av 5/10 dB penalty for noise at evening/night

LAmax is the maximal A-weighted level

LAeq,24h is the energy average of the noise during 24 hours

It should be noted that the maximal indoor limit at night applies where it is normal that there are more than 10 events per night.

It’s also noteworthy that the calculation of indoor levels is routinely made for all new railways or noise sensitive buildings along railways in Norway.

8.4.2 Norwegian calculation method for conventional trains and speeds

The calculation method is the common Nordic method from 1996. This method does not have limitations on the speed or type of train. Basically the pass-by noise of the train is measured as a basis to create a source description of the train type. This source description is a function of frequency and speed.

The source description is given as a set of train specific values. The method defines the procedure of the reference measurements that form the basis of these values, which makes it possible to add new train types with an appropriate speed interval.

The method calculates an equivalent and maximal level at a distance of 10 meters from the centre line of the track.



These levels are then corrected for:

• The distance to the track • Ground effects • Barrier effects

These corrections are frequency dependent, but since they are independent of the source description, they will be the same for high speed trains as for conventional trains.

Indoor levels

Indoor levels are calculated according to a standard handbook, (Byggforsk handbook 47, Houmb & Hveem 1999), containing a calculation method and a data collection. It is a single number rating method. The starting point is the outdoor level. The façade insulation is calculated by using standard sound insulation values and a spectrum correction factor. The spectrum correction factor is given for different types of railway traffic.

The sound insulation of the façade is calculated according to a procedure similar to NS-EN 12354 (2000). Finally corrections are added for:

• Reverberation time • Exposed façade area • Room volume

8.4.3 Corrections for high speed trains

Railway on the ground

There is no speed limitation on the validity of the Nordic calculation method. The data required for calculation of noise from high speed trains will have to be acquired from testing of the actual train types in question.

It might be that these trains will have noise characteristics that necessitate the use of two different sets of input data, e.g. below and above 250 km/hour because of aerodynamic noise at high speed.

Tunnel openings

Noise from tunnel openings is not expected to be a major problem. An investigation on the noise from tunnel openings has been made on the new line for the Airport express train (Det Norske Veritas 1997). This reference also includes a simple method of calculating noise from the opening of tunnels with ballast track.

Current programs include methods for calculation of noise from tunnel openings using newer methods.

There has been a problem with shock waves from tunnel portals for high speed trains when using a slab track. This problem has not been seen with ballast tracks. It’s also possible to abate the shock wave with slab tracks.



8.4.4 Calculation tools

The current Nordic method for rail traffic noise has input data for trains up to 260 km/h (Swedish train type X2000). This method is implemented in three programs that are widely used in Norway:

CadnaA

Soundplan

NoMeS

The two first programs have facilities for using digital 3D terrain. These two programs also make use of several different noise prediction methods, among others the current Nordic method for railway noise.

The Nordic method for railway traffic noise has been revised under the name Nord 2000 (Jonasson & Storeheier 2001). This work has been strongly connected to the development of the European methods Harmonoise and Imagine. The new, sophisticated method has several improvements. For instance, it takes account for the influence from metrology and has new algorithms for sound diffraction and ground absorption. It also have better provisions for calculating the effect of low barriers close to the track. For high speed trains, a new description of the noise source, distributing the sound power to four different heights above the rail as shown in Figure 8-3, is relevant, having in mind the contribution from aerodynamic noise at higher speeds, as described in chapter 8.2.2 and appendix C. A list of the source heights is given in Table 8-4.

Figure 8-3. Vertical distribution of railway noise sources.



Table 8-4. Source heights in Nord 2000 (From Jonasson & Storeheier 2001).

In Denmark Nord2000 is the demanded method for rail and road traffic noise. In Sweden it is used for calculations of noise from wind turbines. Criticisms, especially from users, include large demands of input data (that partly is not available) and long calculating times. Partly as a consequence from this, a new, simplified common method, KNOSSOS, is the objective of an EU project. To date Nord 2000 is implemented in one commercial program (Soundplan). It will be necessary to acquire input data for calculations for any model to be used for calculation of noise from high speed railways. There are no suitable data available. It is recommended that the most sophisticated model available is taken into use already for Phase 3. This means that our recommendation is that Nord 2000 is chosen as the calculation model for Phase 3, and that acquisition of input data is included as part of the work in this phase. 8.4.5 Preliminary guidelines for planning of high speed railway lines

Norwegian guidelines for planning with regards to noise pose a challenge to the design of high speed railway lines. Estimates have been made in order to find the width of the zone where noise has to be taken into account during planning. Experience has shown that the requirements for maximal levels are usually the most critical. In addition, the equivalent level will also be dependent on the traffic density which is currently unknown.



The underlying assumptions for these calculations are as follows:

• The trains fulfill the noise requirements for the LpAeq,T for class 1 trainsets. • The noise spectra from the high speed trains do not differ significantly from the

spectra of currently running trains on Nordic railways • The trains have a length of less than 300 meters • The indoor level is 27 dB lower than the outdoor free field level, so that an outdoor

maximal level of L5AF ≤ 72 dB ensures an indoor level of LAmax ≤ 45 dB at night. With these assumptions, the width of the area along the tracks where noise has to be analysed further, will be as shown in the Table 8-5. In the table are also shown the width of these zones with three different barrier effects; 5, 10 and 15 dB.

The calculations are for ballasted track. For comparison calculations are also made for slab track . The assumption in the calculation is that noise from slab track is 3 dB higher than for ballasted track.

Table 8-5. Calculated distances to furthest position where noise have to be analysed.

Train speed 250 km/h 300 km/h 320 km/h Noise requirements for class 1 trainsets

87 dB(A) 91 dB(A) 92 dB(A)

BALLASTED TRACK Distance where L5AF ≤ 72 dB is rarely exceeded

200 meters 400 meters 500 meters

5 dB barrier effect 150 meters 250 meters 300 meters 10 dB barrier effect 80 meters 150 meters 150 meters 15 dB barrier effect < 50 meters 50 meters 80 meters SLAB TRACK Distance where L5AF ≤ 72 dB is rarely exceeded

500 meters 800 meters 1000 meters

5 dB barrier effect 250 meters 400 meters 500 meters 10 dB barrier effect 120 meters 200 meters 250 meters 15 dB barrier effect 50 meters 100 meters 120 meters

The distances given above are the outer limits for how far out it may be necessary to analyse noise further. In many cases, residences closer to the track will have acceptable noise levels due to ground effects, natural or constructed noise barriers, local screening etc.

5 dB barrier effect corresponds to a screening that just breaks the line of sight from the receiver to the pantograph. 10 dB barrier effect corresponds to a barrier well over the line of sight between the receiver and the pantograph. 15 dB is the best barrier that can be expected in practice.

There are different possible solutions to reduce the environmental impact in terms of noise exposure. Some of these solutions will consist of barriers or berms along the railway tracks, other solutions will be used on each individual property. These different solutions have different characteristics.

Low barriers along the railway track will have an effect on the rail/wheel noise and rolling noise from the tracks. Such low barriers must be placed very close to the track. At such short distances the height of the barrier is limited because it cannot be in the way of the clearing away of snow. There will be no effect of a low barrier on noise from traction or the pantograph.



High barriers or berms along the track can be designed so that they also give a significant improvement on noise from all sources of noise on the train. This kind of solution could be used in situations where there is a densely built-up area along the track. The effectiveness of such solutions will depend on the geometry on each site.

Local solutions on each residential property may be the best solution in rural areas with few residences. These solutions can be worked out together with the owner of the house. It may take the form of local noise barriers or berms to protect outdoor areas, improved ventilation to avoid the need to open the window towards the railway or improved sound insulation in the façade to secure satisfactory indoor levels.

8.4.6 Calculation method for project Phase 3

For the calculations in Phase 3 it is necessary to establish the following:

• Measure input data for the high speed trains in Nord 2000. It is suggested to measure noise levels from the Gardermobanen airport train and the Swedish X2000 train in highest possible speed. From the measured noise levels and data from the literature the input values for higher speeds is stipulated.

• Establish a methodic for the calculation / stipulation of noise levels along the corridors. It is suggested that simplified calculations are made by using Nord 2000 in the software Soundplan by using digital maps. In the corridors the L5AF = 72 dB contour is drawn in the maps. This is the distance to which the façade insulation in the houses may need to be improved. The actual L5AF value in the contour line may be corrected when better noise data have been established. In built up areas a 15 dB noise barrier is included in the calculations. In rural areas no noise screening is included. On the basis of GIS data the number of dwellings between the track and the L5AF = 72 dB contour line is calculated. In these houses the noise insulation may need to be improved. Cost for the increased sound insulation is calculated on the basis from our experience in other railway projects. The number of people who lives in these houses may also be calculated by using GIS data.

• Correction terms for slab track is found based on the literature and contacts with railway companies. On the basis of this correction term the L5AF = 72 dB contour for slab track is drawn and the number of houses and persons involved are calculated.



8.5 Vibration

8.5.1 Vibration limits in regulations

The Norwegian Standard NS 8176 (Standard Norge 1999) contains a method for measurements and recommended vibration limits in buildings from transportation vibration sources.

Vibration shall be measured in the position in the building which posses the highest vibration values. Normally this is in the middle of the longest floor span. The measured vibration values are weighted with a weighting curve for the human perception of vibration. The maximum weighted vibration values, vw,max , from at least 15 train passages are measured in the building, and the competition of train types shall be as for the total number of train passages during a day and night. From these values a statistical maximum value is calculated, called vw,95. It is 95 % probable that a random chosen train passage will not give higher value than vw,95.

The classification of measured vibration values are given in four classes as shown in Table 8-6.

Table 8-6. Classification of vibration values in dwellings

Class A Class B Class C Class D

v w,95, mm/s 0,1 0,15 0,3 0,6

Class C is the limit value for new dwellings.

For new railway lines the limits value have been given as: “The vibration limit is v w,95 = 0,3 – 0,6 mm/s. The lowest value shall be the goal for the planning”. In praxis this implies that v w,95 = 0,3 mm/s is the limit for the calculations and the remedial actions. Because of the great spread in vibration values in buildings it will be very high costs involved if the planning should be based on v w,95 = 0,3 mm/s as a definite limit.

8.5.2 Calculation method for conventional speeds

The mechanism of transmission of vibration from railway in the soil to adjacent buildings is not fully understood. There are two main mechanisms that may contribute to the transmission of vibration from the track:

- Quasi-static mechanism. The deformation in the ground below each sleeper is moving with the train speed and vibration is induced in the ground.

- Dynamic forces from the train. Main dynamic forces are from rail corrugation, wheel corrugation, flats, and polygonisation (out of roundness), and resonances in bogie / wheel system.

The true mechanism is a combination of these two mentioned.

The Norwegian Geotechnical Institute developed a calculation method when the airport train line Gardermobanen from Oslo to Gardermoen was planned. (Madshus et al.1995; Madshus



& Kaynia 2001). The method is fully empirical and is founded on measured vibration data under various ground conditions. The vibration, v, in the building is calculated from:

v = vT fdistance fspeed ftrack fbuilding

vT is a reference value for the actual train type measured on the actual ground in a distance of D0 = 15 meters running at a reference speed of S0 = 70 km/h. The vibration in the building is calculated from the reference value and correction for distance to the building, the train speed, the track quality and the amplification of vibration in the building. Values for the correction factors are given and commented on in Appendix E.

The highest vibration values are measured from train lines on soft clay. Remedial actions for reduction if vibration is given in appendix E


The correction for high speed trains will depend strongly on the ground condition. Therefore measurements of the speed correction factor should be made from train lines on the actual ground condition in the planning phase. There is not found much data in the literature. However vibration measurements have recently been made in Sweden from the Bombardier Regina 250 train (Grøna Tåget) in speeds from 100 to 250 km/h. (Mirza et al. 2010). The ground was soft clay. The results are shown in Figure 8-4.

Figure 8-4. Measured vibration values in 10 and 20 meter distance from the track. Different speeds.

We have calculated the vibration values in mm/s as given in the table. It can be seen that in 10 meter distance the vibration value more than doubles per doubling of speed. The reason is the increase of the vibration values in the lowest frequency region. However this is not seen in 20 meter distance, and there is no increase in vibration value for speeds higher than 150 km/h. In Mirza et al. (2010) it is explained that in short distances the quasi-static mechanism dominates and that the dynamic forces dominates in bigger distances. We are skeptical to the low measured values in 20 meter distance if the ground is clay. However the

Vibration values in mm/sec:

100 150 200 250

10 meter distance 0,22 0,29 0,5 0,82

20 meter distance 0,05 0,14 0,14 0,14



observed phenomenon that the speed dependence is lower in greater distances is interesting and is very important to study further. If this is correct this is promising for the vibration condition along the new high speed lines in Norway.

A very important phenomenon for high speed lines on soft ground is when the train speed approaches certain critical velocities of wave propagation in the track – ground system. In Ledsgård on the southwest coast of Sweden severe problems with high vibration in the track arised when the trains passed in speeds around 200 km/h (Madshus & Kaynia 2001). It was found that the main reason was that the train speed was higher than the shear wave velocity in the clay. In order to prevent problems of this kind it is necessary to stiffen the clay primarily by using lime – cement piles below the track, see appendix E, Fig E-1. An alternative method is to stiffen the embankment by using concrete slabs.

8.5.4 Vibration calculation in project Phase 3

Calculated vibration levels in dwellings near a new high speed railway line on clay in Norway will be very uncertain values. It is necessary to have more measured data from high speed trains, especially on clay, preferably in Norway. It is suggested to do noise measurements of the Gardermobanen airport train and the Swedish X2000 in order to establish input parameters for the noise calculations. At the same time as the noise measurements is made vibration measurements in different distances from the track should be made in order to get more input to the vibration evaluation. On the basis of the vibration measurement results the distances to the v w,95 = 0,3 mm/s countour line is set up for a high speed line on clay in different speeds.

In addition to vibration measurements on clay measurement should be made on less soft ground as sand and moraine masses in order to be able to set up estimates for the distance to the v w,95 = 0,3 mm/s contour line.

It is probable that the embankment must be stiffened in order to prevent problems with critical speed. There are also strong requirements on settlements of the track. Probably lime – cement piles must be established in places with soft clay. This will reduce the vibration transmission to the dwellings as well.

Concerning the vibration evaluation for the corridors a similar approach as for the noise calculations should be made. However the results will be far more uncertain.

In the corridors the limit value v w,95 = 0,3 mm/s contour line should be drawn in the maps. The basis for the stipulations is the stiffness of the ground and the distances that is set up from the measurements. In built up areas it should be implemented that for the line on clay lime – cement piles are established below the track. On the basis of GIS data the number of dwellings between the track and the v w,95 = 0,3 mm/s contour line is calculated. In these houses the vibration limit is expected to be exceeded. The number of people who lives in these houses should be calculated by using GIS data.



8.6 Ground borne noise

8.6.1 Ground borne noise limits in regulations

The Norwegian Standard NS 8175 gives requirements for ground borne noise from tunnels to dwellings (Standard Norge 2008). The requirements are given in four classes as shown in Table 8-7.

Table 8-7. Requirements for ground borne noise in dwellings from railway tunnels

Class A Class B Class C Class D

LA,max, dB 22 27 32 37

Class C is the limit value for new dwellings and new railway lines.

There is no special regulation for ground borne noise from trains on grade, only for the total noise level in the room, which is the sum of the airborne noise through the façade and the ground borne noise.

8.6.2 Calculation for conventional trains and speeds

For the planning of new railway lines an empirical calculation method have been set up, see appendix F. The highest ground borne levels in conventional railway are measured from freight trains; the calculation method therefore in praxis is valid for freight trains.

The freight trains have cast iron brake blocks and the wheel corrugations determine the ground borne noise. For disk braked passenger trains the combined roughness of wheel and rail determines the ground borne noise levels. From measurements in the Harmonoise project the difference between ground borne levels from freight trains and disk brake passenger trains at the same speed is set to 8 dB.


We do not have Norwegian measurements of ground borne noise from high speed trains. However recent measurements have been made in a tunnel in Sweden for speeds up to 280 km/h. The results are shown in Figure 8-5.

Figure 8-5. Measured vibration velocity on tunnel wall, different train speeds (Odebrant 2010).



From Figure 8-5 it can be seen that the increase in ground borne noise level from a train speed of 80 km/h is as given in Table 8-8:

Table 8-8. Speed correction for ground borne noise from high speed rail

Train speed, km/h Correction, dB

80 0

200 + 5

250 + 7

320 + 9

The value at 320 km/h is stipulated from the shape of the curve.

Calculation model for high speed ballasted track

The empirical calculation method is based on measurements in which the freight trains are the dominating sound source. Disc braked trains give around 8 dB lower ground borne noise levels for the same speed. On the basis of the curve in appendix F and the 8 dB correction for disc braked trains the calculated ground borne levels for the Phase 3 is given in Figure 8-6.

Figure 8-6. Calculated ground borne levels

This curve is a rough stipulation of expected ground borne levels from ballasted track. Efforts should be made to verify the calculation method at a later stage of the high speed rail study.

Concerning remedial actions it will not be possible to reach the ground borne noise limit in many dwellings above tunnels if the strict value for stiffness of ballast mats shall be incorporated. Studies will have to be made to see if soft ballast mats may be used.

2025303540455055

10 20 30 40 60 100

dBA

Distance from rail to foundation, m

Ground borne noise from high speed trains in blasted tunnels, 250 km/h

Max noise level

Speed Correction

200 - 2

250 0

320 + 2



Calculation model for slab track

In bored tunnels the track is slab track in all the projects whish are known, and it is assumed that this will be the case in Norwegian high speed tunnels as well.

Ground borne noise from a bored tunnel is higher than from a blasted tunnel. This because there is reduced cracking in the rock and the concrete in the tunnel is in direct contact with the rock. It is estimated a difference of 5 dB. This means that the calculation model for ballasted track could be used and the calculated results should be increased by 5 dB.

The requirements for maximum rail deflection on slab track is normally not higher than 1.2 – 1.3 mm. This is a very small value and reduces the possibilities for ground borne noise reduction by remedial actions in the track. In many situations it will be necessary to install floating slab track. Remedial actions for ground borne noise reduction of slab track are given in appendix F.

8.6.4 Calculation method for project Phase 3

From the calculation model in Fig. 8-6 it is possible to draw a LA,max = 32 dB contour line on the maps above the tunnels. In built up areas noise reduction in the track should be implemented. The noise reduction will depend on the allowed rail deflection which has to be studied further. For conventional speeds 15 dB noise reduction can be assumed. In this high speed rail study it is suggested that 10 dB noise reduction is assumed and implemented in the calculations because of less allowed rail deflection. For slab track a floating slab is expected to give 15 dB noise reduction. Since the ground borne noise level without remedial actions is 5 dB higher the ground borne noise level including remedial actions are equal for ballasted track and slab track.

Concerning the evaluation for the corridors it is suggested to adopt a similar approach as for the noise- and the vibration calculations. The LA,max = 32 dB contour line should be drawn in the maps. On the basis of GIS data the number of dwellings within the contour lines is calculated. In these houses the ground borne noise limit is expected to be exceeded. The number of people who lives in these houses should be calculated by using GIS data.

8.7 Conclusions

Rolling stock

Up to a speed of around 300 km/h the noise from the contact rail /wheel is the dominating source. For higher speeds the aerodynamic noise is the dominating source, and the noise level increases strongly with increasing speed. The pantograph then is a dominating source. This noise is difficult to shield. In addition it may have a tone component and the noise limit may be lower because of this. It is very important that the noise from the pantograph is reduced as much as possible.

The TSI for noise from highs speed trains is lower than the measured values from recent high speed trains. It is expected that the new generation of high speed trains will reach the noise limit. This is beneficial for the high speed lines in Norway.



Track

Slab track gives higher noise level than ballasted track. The requirements for the settlement of the slab track are very strict and will be expensive to fulfill on clay in Norway. For these reason it is probable that ballasted track will be used on grade. This is assumed in the noise calculations.

It must be foreseen that the maintenance in the Norwegian high speed lines will keep the rail roughness low and within the TSI specification. The key parameter is the grinding of the rail. It is very important that the grinding process is regularly and with short time intervals so that roughness will not develop.

Noise

The recommended method for the calculation of noise from high speed trains is Nord 2000. This is a commercially available method. The input data will have to be acquired from measurements on relevant train types. It is recommended that the scope of Phase 3 includes such measurements.

In the corridors the L5AF = 72 dB contour lines should be drawn in the maps. This is the distance to which the façade insulation in the houses may need to be improved. The actual L5AF value in the contour line may be corrected when better noise data have been established. On the basis of GIS data the number of dwellings between the track and the L5AF = 72 dB contour line is calculated. In these houses the noise insulation may need to be improved. Costs for the increased sound insulation are calculated on the basis from our experience in other railway projects. The number of people who lives in these houses may also be calculated by using GIS data.

Vibration

Calculated vibration levels in dwelling near a new high speed railway line on clay in Norway will be very uncertain values. It is necessary to collect more measured data from highs speed trains on clay, preferably in Norway. It is recommended that the scope of Phase 3 includes such measurements.

It is probable that the embankment must be stiffened in order to prevent problems with critical speed. There are also strong requirements on settlements of the track. Probably lime – cement piles must be established in places with soft clay. This will reduce the vibration transmission to the dwellings as well.

In the corridors in Phase 3 the limit value v w,95 = 0,3 mm/s contour line should be drawn in the maps. In built up areas it should be implemented that for the line on clay lime – cement piles are established below the track. On the basis of GIS data the number of dwellings between the track and the v w,95 = 0,3 mm/s contour line is calculated. In these houses the vibration limit is expected to be exceeded. The number of people who lives in these houses should be calculated by using GIS data.



Ground borne noise

An empirical calculation method which is based on measurements from conventional trains on ballasted track in the Oslo region has been developed. The method is corrected for high speed trains, based on recent Swedish measurements.

Concerning remedial actions it will not be possible to reach the ground borne noise limit in many dwellings above tunnels if the strict value for stiffness of ballast mats shall be incorporated. Studies will have to be made to see if softer ballast mats may be used. This is also valid for slab track in bored tunnels. The strict requirements on rail deflection will imply that floating slab track must be used when there are dwellings near to the tunnels.

In the corridors in Phase 3 the LA,max = 32 dB contour line should be drawn in the maps. In built up areas 10 dB noise reduction in the track is assumed. On the basis of GIS data the number of dwellings within the contour lines is calculated. In these houses the ground borne noise limit is expected to be exceeded. The number of people who lives in these houses should be calculated by using GIS data.



SUBJECT 4: CLIMATE RELATED ENVIRONMENTAL EFFECTS

9 INTRODUCTION

9.1 Background to the study Among the issues to be investigated regarding environmental consequences are emissions of greenhouse gases –the issue in this chapter.

The different work packages in NHSRA are listed below (task leaders indicated), for later reference:

WP 1. Market analysis (Atkins) WP 2. Planning & development (WSP) WP 3. Financial and socio-economic assessment (Atkins) WP 4. Commercial & contractual strategies (PWC) WP 5. Technical & security analysis (Pöyry Infra) WP 6. Environmental issues

This report answers for WP6, the environmental issues from HSR development. Noise, energy and landscape effects are described elsewhere; the aim here is to describe the approach to calculate the temporal distribution of emissions of carbon dioxide equivalents (CO2e), as resulting from development or non-development of high speed rail (HSR) concepts for passenger and freight transport in Norway. The environmental assessment links to national climate targets, and the approach described here therefore separates between emissions occurring in Norway and abroad. The comparison of HSR with alternative transport systems implies that the study must establish emission scenarios for a baseline situation and the situation with development of HSR concepts in Norway.

In order to provide the necessary flexibility for implementation in Phase 3, a component-based inventory is proposed here. The modular approach allows later adjustments and refinements, in composition of corridor development options and technologies for railway infrastructure and rolling stock. The component-based approach is implemented for all modes, road and air as well as rail. The approach is scoped for the goal of just comparison of HSR alternatives against the alternative transport modes.

Final calculation for corridor alternatives, to be made in Phase 3 for four corridors and development options A-D, relies on input from the other work packages. These links are most notably found in connection to WP1 on market analysis and from the physical planning of corridors, but appear also from several of the other work packages. Links to the other WPs are described through the report and summarised in a separate section. WP links are indicated in the text with corresponding numbers [WP Link #].

Previous studies for HSR concepts in Norway and abroad typically cover infrastructure and operation of train sets. Some include manufacture of rolling stock, and maintenance and decommissioning of infrastructure. In effect, any study that aims to include direct and indirect emissions in a consistent manner must accept life-cycle assessment methods and life-cycle thinking. Some of the HSR studies in literature explicitly use LCA as a reference for methodology and environmental information, while others make the connection more implicit.



In this report life-cycle assessment (LCA) methodology is assumed in standards, data sources and modelling tools. Life-cycle assessment provides a structured way to describe system aspects of HSR alternatives.

Life-cycle assessment provides a standardised framework to evaluate and compare alternative products. The product for HSR corridors is the transport service it provides. Environmental performance may be evaluated per single journey, or from a total demand. The aim in NHSRA is to evaluate the greenhouse gas emissions from HSR corridor development and operation, and compare to alternative transport modes such as use of private car, bus services and air transport.

9.2 Lessons from previous assessments of HSR There have been made some previous studies on wide-scale implementation of high-speed rail for Norway and elsewhere. The following presents available studies and discusses the main conclusions made with respect to parameters for the absolute climate-related environmental effects and the relative comparison of high-speed rail to alternative transport systems. A summary is presented in the end of the chapter.

9.2.1 Review of studies

The Bothnia Line (Sweden)

Stripple and Uppenberg (2010) present a life-cycle assessment of a specific railway project, the Bothnia Line in Sweden. The study includes full inventories for most infrastructure components, including stations and elements besides the railway line itself, and also the rolling stock operating on the line. All underlying data and model approach is well documented in a series of reports2, following the structure for environmental product declarations: the EPD system. The Bothnia Line is designed for speeds up to 250 km per hour and therefore not fully a high-speed line. However, the approach and main results are considered to be highly relevant for a high-speed development project in Norway.

The prescribed aim in this report is to define modelling rules for greenhouse gas emissions. One major conclusion from the Bothnia Line study is that the relative importance of track construction, track operation and maintenance, transport work for construction and maintenance operations, operation of trains, and train manufacture differ between various emission-based impacts, including in this set greenhouse gases, acidification, resource depletion, and photochemical oxidants.

A second main finding by Stripple and Uppenberg (2010) is the importance of deforestation for greenhouse gas emissions. Their approach to estimate biogenic CO2 released by deforestation of railway lines is quite crude (Uppenberg et al. 2003), but indicates the potential importance of this process for the total footprint of HSR when developing new corridors. A brief discussion of deforestation effects and release of soil carbon from land use and land use changes (LULUC) is provided later. Greenhouse gas emissions from LULUC are not included in the approach described here, mainly due to missing consensus factors. Documentation for the factor in the Bothnia Line study is not provided, but the importance of LULUC emissions is appreciated and suggested to be a separate issue for Phase 3.

2 All documents available at: www.botniabanan.se

http://www.botniabanan.se/



Most of the underlying model components for the Bothnia study are available, and in many cases materials use data should be transferrable to the Norwegian case. This presents a good library for process data where equivalent information does not exist for Norwegian conditions.

The Swedish White Paper for high-speed rail (SOU 2009:74), concludes that HSR is more energy efficient than air and road transport, and that the relative performance of rail over the alternative transport modes is highly sensitive to the amount of infrastructure investment required for rail lines. The paper provides some experience for the market effect of HSR. In Sweden, most of the replaced transport by the X-2000 HSR line is transport by car (SOU 2009:74).

California, USA

Chester (Chester 2008a; Chester and Horvath 2010), looking at the case for California, has published one of the most comprehensive environmental assessments for HSR. Given the very different contexts with respect to energy supply, and the car fleet fuel-use properties, his conclusions regarding the comparison between road, air and HSR are not transferrable to the Norwegian situation. There are, however, some conclusions from his study that are valuable to the study here – most notably the importance of railway utilisation and seat occupancy.

In the Norwegian context, electricity is relatively low in greenhouse gas intensity, and electricity for operation of trains becomes less important than in many other countries. This puts more importance on emission from development of railway infrastructure. Emissions per passenger from infrastructure development scale with seat and infrastructure utilisation rates. This emphasises transparency in modelling of market situation and load factors, something which has caused friction regarding previous studies for HSR in Norway. It is therefore important to ensure openness in use of these factors, and allow flexibility in the model to investigate different degrees of utilisation, both for seat capacity and train frequency.

ICE, Germany

Rozycki and colleagues (Rozycki et al. 2003) investigated HSR systems for Germany, for the ICE train system. The study included energy for operation, connecting travel, and materials production for major materials in railway infrastructure. The study is not comprehensive in scope, but covers major parts of the infrastructure. On major conclusion was that that traction energy is the dominant cause for primary energy use. The implication is that choice of operating energy controls the environmental footprint of HSR systems. The scope of this report is limited to greenhouse gas emissions, and it has been discussed earlier in this report how the low-carbon electricity market in Norway puts more emphasis on infrastructure components relative to train electricity supply.

A second conclusion made by Rozycki et al is that allocation of infrastructure use between freight and passenger transport, and passenger train frequency, controls the emissions per passenger-km from HSR transport systems. Rozycki concludes that construction completely dominates the emissions, when compared to operation and maintenance of railway infrastructure. This conclusion is shared with Chester and Horvath (2010), but not by Stripple and Uppenberg (2010). The lower importance for infrastructure maintenance found for German and US HSR systems is suspected to be due to system boundaries not completely



covering maintenance inputs, rather than a consequence of conditions somehow being different for these systems. In a recent study for the Norwegian Follo Line (Follobanen;(Korsmo and Bergsdal 2010)), it was found that maintenance and construction emissions are of similar size, supporting the results of Stripple and Uppenberg (2010) for the Bothnia Line.

All studies discussed so far share the conclusion that main materials to consider for greenhouse gas emissions from rail infrastructure development are concrete and steel (Rozycki et al. 2003; Chester and Horvath 2010; Stripple and Uppenberg 2010).

The study by Rozycki et al models both conventional ballasted tracks, as well as non-ballasted slab tracks. They conclude that the slab track does not require higher primary energy use in construction compared to a gravel bed, assuming quite high technical lifetime (60 years) and little maintenance for slab tracks. Data are reported for both slab tracks and gravel beds.

The German ICE study separates bridge sections, tunnel sections and open sections, and concludes that bridges and tunnels have higher specific resource consumption. This means that a meaningful inventory for rail must specify separate inventories for different types of sections, to compose full corridor infrastructure emissions based on input from the physical planning made in Phase 3.

High-speed in the UK

The UK Department of transport (DfT) issued in 2007 a study for the carbon impact of a new rail line, the North-South Line. The study puts most effort into estimation of energy for operation, and less on infrastructure development, specifying only pure material inputs of steel, concrete and ballast. Results from the study indicate that construction emissions are similar for conventional, HSR and Maglev HSR concepts, although with very different energy use patterns for operation of trains. The DfT numbers appear also in later studies in the UK, e.g., a study for general HSR in the UK made by Network Rail (2009). The Network Rail study includes mainly the construction phase for infrastructure, sourcing emission factors from (DfT 2007) and Rozycki et al (2003). One of the findings is that ballastless tracks (i.e., slab tracks) have a slightly higher carbon footprint than the regular gravel bed, about 12 % higher.

The main conclusion is shared in the DfT and Network Rail study: that operating electricity dominates the carbon footprint for HSR in the UK. However, the Network Rail study contains a lot more analysis on the underlying data, and also scenario development for both HSR and conventional rail systems as well as for alternative transport modes, i.e., use of private car and short-haul air, for the 60 year assessment period. Sensitive parameters in the scenario analysis for HSR compared to alternative transport modes are seat utilisation, electricity source (or rather the carbon intensity of electricity), composition and carbon intensity of infrastructure (influenced by material recycling assumptions and physical planning), and market effects on mode and total transport demand. Of these, the largest influence on the carbon footprint of HSR in the UK is made by variation in carbon-intensity in electricity supply and in seat utilisation over the assessment period.



European high-speed rail

The dominance of electricity supply over infrastructure development is found also in results reported by the International Union of Railways (UIC) in a pre-study for the carbon footprint of HSR on European Railways (UIC 2009). The UIC study composes a first comprehensive structure for elements of rail infrastructure; i.e., open sections, bridges and tunnels, and for rolling stock manufacture and operation. The data is structure in a modular form, allowing investigation of different electricity scenarios, composition of infrastructure components, and seat and infrastructure load factors. The study is formatted as a life-cycle assessment study, without referring to LCA standards or guidelines.

Some strong conclusions can be drawn from the study with relevance for the case of HSR in Norway. As mentioned, the UIC study underlines the importance of electricity supply to the total greenhouse gas emissions from rail, even at low fractions of fossils in the total electricity mix. Moreover, the study clearly illustrates the higher carbon intensity in tunnel and bridge sections compared to open sections. The results are presented in a dynamic view, allowing readers to select own assumptions for infrastructure and rolling stock. In these presentations, the importance of market issues for the emissions induced by infrastructure is made very apparent; i.e., the importance of seat occupancy and infrastructure use.

The Vestforsk study, Norway

This review of previous studies made for HSR ends with two recent Norwegian publications. The first is the Vestforsk study (Simonsen 2010c), that presents life-cycle emissions from infrastructure, transport mean and operating energy for a wide selection of transport modes, including regular trains in Norway, various future private car options and air transport.

Given lack of rail studies for the Norwegian context that consider infrastructure as well as operation, it is interesting to see the documentation and comparison between rail and alternative transport modes. The Vestforsk study concludes that greenhouse gas emissions from rail originate more or less solely from infrastructure development, not surprisingly since the electricity is assumed 100 % hydropower. The result does support the findings made in the other studies described – that seat and rail load factors are a controlling factor for the environmental performance of HSR in Norway, in terms of greenhouse gas emissions.

The underlying emissions data in the Vestforsk study is sourced from various publications; mainly using open sources. Infrastructure data for rail is documented in (Simonsen 2010a) and is based on the Ecoinvent database (Spielmann et al. 2007), while energy data is based on data for Norway in 2008. The use of European database information for Norwegian rail infrastructure is a relatively crude approach, given the differences in constructing railway lines in these two areas. While it may be considered sufficient for regular rail on national scale, it is too imprecise for the corridor assessment sought in Phase 3 for NHSRA.

Friends of the Earth Norway

Schlaupitz completed in 2008 an energy and greenhouse gas assessment for HSR in Norway, for Friends of the Earth Norway and NSB (Schlaupitz 2008). The study presents an impressive amount of inventory information for HSR in Norway, based on literature studies for HSR and rail in Europe, and new data from various rail stakeholders.



Schlaupitz presents a detailed discussion of electricity for rail. He concludes that the study should use average values rather than marginal electricity, and states that Norway is a partner in a common European electric grid. The relevant electricity therefore is the European mix. The study scope is rail in a 60 year assessment period, meaning that a future electricity mix should be used. The EU has high ambitions to phase in renewables in the relatively near future, and from this it follows that the electricity used by Schlaupitz has a carbon-intensity at about half of the value today (0.25 kg CO2e/kWh, down from 0.48 in 2000). The study also considers additional scenarios for the electricity future.

The baseline scenario for HSR ends with an about even split between operation of trains and infrastructure for the total greenhouse gas emissions from HSR, where the share for infrastructure increases over time as the carbon-intensity for electricity decreases over time. Future development is also implemented in construction technology, where the carbon intensity for materials is assumed to decrease over time. The value for HSR when implemented is assumed 15% below the original values in literature. Emission factors for materials are sourced from the open German database Gemis and from Swedish inventories for infrastructure (Stripple 2001).

One potentially important conclusion that the Schlaupitz study makes is that a double track line does not increase the greenhouse gas emission from construction by more than 24% compared to a single track line. This is quite surprising and does not fit the conclusions made by other studies, e.g., by Network Rail (2009). In the recent study for the Follo Line (Korsmo and Bergsdal 2010) it was found that for a double track line, the difference between making two separate single-track tunnels and one shared tunnel is not very large. A double track tunnel requires about 50 % more emissions for the life-cycle of the infrastructure than a single track tunnel, considering construction and securing of tunnel, rails and bedding, and technical installations to support train operation.

Schlaupitz further discusses how market issues control the absolute emissions from HSR passenger transport. Given that he finds double track to imply not very much more emissions in infrastructure development, he strongly recommends construction of a double track line to make the most of the infrastructure investment. This will increase the potential to transfer market share from air transport, and reduces the infrastructure load per passenger-km.

The Schlaupitz study is referred in many later studies for rail in Scandinavia, and represents a high-point in evaluation of train transport in terms of structure and scope of the assessment. He covers all main components, including in a systematic way infrastructure construction, maintenance and operation, rolling stock manufacture and energy supply for operation of trains. The findings support use of a component-based inventory approach, to allow inclusion of scenario settings for controlling elements in the emissions model, and also underline the importance of market assumptions for energy use per passenger and the influence of seat occupancy and train frequency for the greenhouse gas emissions from HSR transport.

9.2.2 General conclusions regarding transferability and adaptation to NHSRA

Based on the review of greenhouse gas assessments, some conclusions can be made about transferability and adaptation of data and approach to NHSRA.



General system boundaries

• Most studies are generally not comprehensive in inventory for infrastructure: this is a natural consequence for studies outside Scandinavia, given the relatively higher importance for electricity for operation over construction and maintenance of infrastructure. Very few of the studies explicitly use life-cycle assessment methods; Rozycki et al. (2003), UIC (2009) and Stripple and Uppenberg (2010) are notable exceptions in Europe.

• Studies made for Scandinavian conditions find that infrastructure is a dominant source for greenhouse gas emissions. A meaningful assessment of the climate-related emissions from rail must include construction of infrastructure components, meaning railways, stations, roads, supply lines, and other supporting structures, should be included

• There are studies that include construction of the rolling stock, but results indicate that infrastructure construction is much more important. The life-cycle of rolling stock may therefore be treated in a simpler manner.

• Results show that emissions must cover life-cycle emissions (source-to-wheel) from fuel, electricity, materials and processing, suggesting that LCA literature should be the preferred source for emissions data. Life-cycle assessment provides guidelines for good practice for environmental accounting and benchmarking of transport alternatives.

• Variation in data used to model background processes, i.e., emissions related to production of fuel, electricity and material inputs, may give differences in end results. The emissions information should be structured to accommodate scenarios for production technology.

• Service inputs (including insurance, banking, and other) may be significant for the environmental footprint of the systems that are compared to HSR, both for use of private car and airplanes (Chester and Horvath 2010). They are, however, generally left out of most transport studies. A systematic implementation of service inputs is possible through use of input-output approaches, but requires more resources than what is available in this project.

• Connecting transport is generally considered of little significance (ECON 2008; UIC 2009).

Electricity for operation of trains

• Several of the studies investigate different assumptions for electricity for trains. The electricity assumption is a volatile issue in Norway, and various stakeholders propose different assumptions for relevant supply for a new project such as a Norwegian HSR line (Schlaupitz 2008).

• On a general note, a missing argument in the Norwegian debate is inconsistencies that arise when marginal values are assumed for electricity, but is systematically neglected for all other inputs. It may be relevant to argue that marginal fuel for private cars is petrol made from Fischer-Tropsch synthesis of shale gas, rather than the average petrol that is used in most assessments. Similarly, marginal production of materials such as steel and cement may be very different than the average production technology. Clear guidelines for marginal vs. average analysis can be



found in the LCA literature, summarised for instance in the handbook for LCA issued by the European Platform for LCA3.

• The final model must allow different electricity assumptions and test the importance of the electricity assumption to the final results. It should also reflect how such assumptions affect the systems performance of HSR, including effects on material production.

Model resolution & structure

• The various studies each estimate emissions through different model structures. Seen together, the studies indicate that flexibility and transparency are important to calculate and communicate emission estimates in the best possible way.

• Model resolution must meet demands to separate different types of infrastructure (tunnels, bridges, etc), and accommodate scenario changes. This calls for a component-based emissions model, where core parameters may be changed to fit corridor settings and allow sensitivity analysis for controlling parameters.

• Flexibility in the model should match transparency in calculations. A modular model lets stakeholders investigate different assumptions for market, infrastructure use and future electricity supply. An equivalent resolution in the transport alternatives ensures that options are compared justly, for evaluation of HSR compared to other transport modes, and for more precise estimation of the pay-back time for HSR concepts. .

Energy use per passenger

• Energy use per seat transport must be modelled according to study scope, preferably in line with specific train system properties regarding train system, topography and temporal issues (e.g., Andersson and Lukaszewicz 2006a; Network Rail 2009; Simonsen 2010c).

• Energy use in trains is a separate issue in NHSRA and is treated elsewhere.

Infrastructure composition

• Track system composition is important for the carbon footprint of rail infrastructure (UIC 2009; Stripple and Uppenberg 2010). Development of HSR in Norway is projected to involve a lot of tunnel sections. This has several implications for the modelling of emissions from construction and use of rail infrastructure:

o The model must separate between tunnels, bridge and open sections since they each have different carbon footprints in construction.

o Single-lane sections reduce corridor capacity. The emissions model must in an adequate way split between two- or single-lane railway sections and include the expected effect this will have on usage of railway capacity (measured as trains – or carriages – per day).

Market effects: occupancy and load factors

• Seat utilisation (and freight transport or co-transport) is a controlling factor, and should be discussed in relation to factors applied in other studies and found in the

3 The International Reference Life-cycle Data System Handbook (ILCD Handbook) is available online from the European Platform for LCA: http://lct.jrc.ec.europa.eu/assessment

http://lct.jrc.ec.europa.eu/assessment



complementing market analysis study (WP1). Seat utilisation depends on distance, development of transport needs, as well as the service experienced from high speed rail transport (SOU 2009:74 ; Andersson and Lukaszewicz 2006a; Toutain et al. 2008; Lukaszewicz and Andersson 2009).

• HSR concepts are expected to replace a combination of car, bus and airplane transport – not just airplane transport.

• Market analysis is a separate work package in NHSRA, to be treated in WP1.

Scenarios and temporal issues

• Temporal considerations are important for many factors, most notably for seat utilisation and energy efficiency of transport systems (Andersson and Lukaszewicz 2006a; Nasjonale transportetater 2007; Toutain et al. 2008)

• The various HSR concepts will be operating for an extended period, and the assessment period should cover the lifetime of infrastructure components. This implies an assessment period of up to 100 years (Network Rail 2009, Stripple & Uppenberg 2010).

• A prolonged assessment period requires special consideration for factors that are sensitive to change over time, both in HSR technology as well as for the competing transport modes. Model tools and definitions must be able to systematically handle scenario development for all life-cycle components.

9.3 Introduction to life-cycle assessment (LCA) It is valuable to start with a brief introduction to life-cycle assessment methodology, to aid in the discussion for the component-based emissions inventory made for use in evaluation of corridor alternatives. It is useful to position the methodology used in this assessment to other methods or approaches that are commonly referred to. This includes the GHG protocol (GHG Protocol 2009), PAS2050 (British Standards 2008), ecological footprint (Rees 1992) as well as the ISO standards related to environmental assessment of products or industries (ISO 2000a, 2006a, b, c, 2009).

9.3.1 Development of methods

Life-cycle assessment (LCA) is a method developed to analyse the total environmental impacts of a product or service. As the name indicates it encompasses the entire value chain of the product, from raw material extraction, via manufacturing, use and final disposal (Wenzel et al. 1997; Guinée 2001; Baumann and Tillman 2004; ISO 2006a). This way of analysing environmental impact ensures that emissions reduction efforts are directed toward the most important parts of the life-cycle while monitoring the potential side effects caused by changes in the value chain. Side effects may be unwanted; perhaps an environmental impact is just shifted to another stage in the life-cycle, or perhaps a new type of environmental impact arises. Due to the holistic scope, life-cycle assessment should capture such environmental trade-offs.

LCA has been referred to under many names during its development; evolving from the idea of cumulative resource requirements into a scientific field that involves emission inventory methods (Heijungs and Suh 2002) and modelling of the cause-effect relationships from emissions to environmental damage (de Haes et al. 2002). Some of the first applications



were related to packaging (Nunn 1980) but also included a wide range of other products (Nord 1992).

The methodology has been standardised to some extent the past two decades. The SETAC working groups (Consoli et al. 1993; Barnthouse et al. 1997; de Haes et al. 2002) and other institutions (Nord 1992, 1995) were important is this development. The International Standardization Organization (ISO) first published a set of standards in the late nineties (ISO 1997, 1998, 2000b, c) with revised versions in 2006 (ISO 2006a, b). In addition, new standards describing requirements for environmental product declarations (EPDs) (ISO 2000a) and company- (ISO 2006c) and product (ISO 2009) level carbon footprint analyses have been added. A thorough description of the historical development of LCA may be found in the literature (Ayres 1995; Baumann and Tillman 2004), while interested readers can find recent developments of the method described in Suh et al. (2004) and (Finnveden et al. 2009).

9.3.2 General framework

The general framework described here is based on the ISO standards. The procedure of life-cycle assessment, as outlined in Figure 9-1 below, consists of four main consecutive stages.

The first stage is the goal and scope definition, which should identify a clear question for the analysis to address. The second stage of LCA is collection of inventory data and calculation of life-cycle emissions. The emissions inventory normally covers a list of substances that most often is translated to more easily interpreted units of environmental impact, e.g., CO2-equivalents as indicators for climate change potential. Finally, results are analysed and interpreted.

Figure 9-1. The stages and iterative nature of an LCA (Adapted from ISO 2006a)

As is shown in the figure, the common procedure is that the stages in LCA are iterative. Findings in subsequent phases may lead to redefinition in goal or scope, a new scope most probably alters the emission calculation procedure, and supporting intermediate results may need to be made to strengthen the interpretation of the outcome from impact assessment.

The following sub-chapters will give a brief overview of this procedure, including questions and considerations specific to this assessment.



Goal and Scope definition

The most important stage of an LCA may be said to be the definition of the goal and scope of the study. This is because this will affect all decisions that are made during the consecutive phases of the analysis. The system boundaries (what activities are included or excluded) are determined in this stage based on the question(s) to be answered.

Usually a functional unit (FU) is defined as the comparison metric. The functional unit is a quantitative measure that describes the function(s) the analysed system(s) is intended to fulfil. When the functional unit is defined, a number of so-called reference flows can be used (alone or in combination) to produce the functional unit.

A relevant functional unit for NHSRA is passenger-km transport of transport supplied by a HSR concept. Given an assumed occupancy, seat-km made by the HSR system may be indicated, and this is a reference flow that is used to find the required reference flow of infrastructure and rolling stock inputs. If the HSR concept is not realised, the transport demand will be met by other modes of transport, where reference flows will be vehicle-km by car, or seat-km with airplane.

Inventory analysis methods

The inventory phase of an LCA consists of collecting data on emissions from, and inputs to, relevant processes in the system(s) that are studied. From this system, life-cycle emissions can be calculated by imposing an external final demand on the model. The outcome is a number of emissions that are associated with delivering one functional unit in a life-cycle perspective. Preferably the inventory is structured in such a way that contributions from different life-cycle phases, sub processes, sub-sub processes etc. can be identified and analysed in detail. In addition the inventory should recognise uncertainties and inevitable assumptions that are needed to model the system and structure the inventory in a manner that enables the exploration of how sensitive the conclusions are to these. This is most easily done by parameterising the model. Parameters are also needed for flexible scenario analysis.

There are a few different methods for compiling life-cycle inventories (Suh and Huppes 2005), all with their specific strengths and weaknesses (Suh et al. 2004). Traditional process based LCAs are connected to well-known problems of including all relevant emissions, by typically excluding service based processes (Norris 2002). The bottom-up nature of the method may make it unclear to the practitioner whether all important activities in the system are included. A number of services are also hard to assess using available bottom-up data, even considering the recent developments in generic LCA databases (Ecoinvent Centre 2008).

Parallel to the development of LCA, the field of environmentally extended input-output analysis emerged (Leontief 1970). This approach is top-down, taking as a starting point the national accounts published by statistical offices in combination with sectoral emission statistics. This way all activities in the economy are covered by the method, although at an aggregated level. The procedure of input-output table compilation is described by the UN (United Nations 1999). Economy wide embodied energy of demands for goods and services could now be calculated at an aggregated level using these models (Bullard and Herendeen 1975; Herendeen and Tanaka 1976; Bullard et al. 1978; Herendeen 1978). The method was



picked up by LCA researchers realising the shortcomings of pure process based inventories, and combined in a hybrid LCA-framework (Treloar 1997; Treloar et al. 2000; Suh 2001; Suh et al. 2004). The combination of the approaches allows complete coverage of all emission, while maintaining the specificity needed for many analyses. This comes at the expense of time and data since more or less double inventories must be collected. Full hybrid LCAs are therefore not so commonly undertaken, although examples exist (Strømman et al. 2006). At present input-output analysis, process-based LCA and various versions of hybrid LCA co-exist and are applied to different types of problems. At aggregated (national level) analysis, multi-regional input-output models are most suited (Wiedmann et al. 2009; Peters and Solli 2010), while more specific types of problems may be addressed with other methods such as hybrid LCA (Solli et al. 2006) , process based LCA (Castro et al. 2003; Schmidt et al. 2004; Pettersen 2007), material flow analysis (Bergsdal et al. 2007; Bergsdal 2009), mixed unit input-output analysis (Hawkins et al. 2007), physical input-output analysis (Hubacek and Giljum 2003; Weisz and Duchin 2006) or highly combined methods (Seppälä et al. 2009).

There are several other methods, or at least popular terms, that are used for the holistic assessment of products, companies or services. The GHG protocol (2009) is one such approach. Aimed at calculating the carbon footprint of companies, the GHG protocol is really not a method in itself but more a general classification scheme of emissions, where several methods, including LCA, may be used for the emission calculations. The protocol separates three different scopes of emissions; scope 1 covers direct emission, scope 2 covers indirect emissions from electricity use, while scope 3 is all other indirect emissions. The sum of scopes 1-3 covers all direct and indirect emissions and should therefore correspond to the traditional LCA scope, at least for processes cradle-to-gate.

Another commonly used term is Ecological Footprint (Rees 1992). This term tries to capture environmental impact in one single indicator, an equivalent area. It is mostly developed for climate change, and use and transformation of land areas. It follows this is not a method; it may use e.g. LCA to come to calculate the GHG emissions and land use. There is increasing recognition within the Ecological footprint community that methods such as LCA or input-output analysis are useful to calculate the ecological footprint (Wackernagel 2009).

The standards from ISO related to LCA, such as the standard on EPDs (14025), company level (14064) and product (14067) carbon footprint all use methods similar to those described in the standards specific on LCA (14040, 14044), but with some procedural clarifications specific to global warming or development of product category rules (for EPDs). This is also the case for the British standard PAS2050 (British Standards 2008).

Impact assessment

The impact assessment stage of LCA is the aggregation of the less interpretable list of emissions (may be several thousand types of emissions emitted to different compartments such as air, soil, water etc.) into more understandable categories of environmental impacts. This is usually done by multiplying each emissions type by a factor for the contribution to each of the types environmental impact included in the study. At midpoint level (see Udo de Haes et al. (2002)) the impact is usually expressed in equivalent emissions of a reference substance for a given time frame. For global warming this is usually translated to kg CO2 in a 100 year time frame, while other impacts have other reference substances and may have different time frames.



Interpretation

The ability to interpret the results in a useful manner strongly depends on the structure of the inventory. Hence, interpretation may reveal weaknesses in the previous phases of the analysis and require one or more iterations of the procedure in order to produce meaningful results in line with the intended scope of the study.

Most practitioners appreciate the iterative nature of LCA. Uncertainty is inherent in systems analysis, and so also in LCA. It is typical that first-round results may ask for changes in the scope of the study as the results may not allow the conclusions sought. It may be that important parts of the system are omitted, or that results require that some parts of the system be modelled in more detail. It may also be that stakeholder response demands further modelling, or use of additional impact assessment methods.

Traditionally most practitioners have transferred life-cycle assessment results freely to answer new questions or model new systems. However, due to developments in practice and standards, best practice requires that emission estimates are adjusted to the context in which it is used, for instance to accommodate local electricity, or production technology. Evolution in software for LCA has helped push this development, allowing detailing of inventories and unit process resolution in inventory structure.

Process resolution is a requirement for good modelling, as it allows users to interpret results better. Given that steel is known to be an important input to HSR technology in railway construction, it is highly relevant to know the amounts of recycled material in the database for steel. Unit process resolution in the database, combined with LCA software, allows accommodation of new information, and even adjusting for production technology and composition to the specific supplier.

10 GOAL AND SCOPE

This chapter describes the methodology used in the assessment, including important discussions on system boundary selection, cut-offs and allocation.

10.1 Scope of this report

10.1.1 Goal and scope definition

Goal of the study

The overall scope of the study of climate related environmental effects in Phase 2 is to establish a component-based emissions inventory for high speed rail transport, as well as for alternative transport modes. Inventories should facilitate evaluation of different scenarios with regard to extent of HSR development relative to a reference scenario. The inventory components should accommodate inclusion of the outcome from market studies and other parts of the NHSRA work packages in order to assemble inventories to evaluate specific solutions in Phase 3 with regard to climate gas emissions. The scope includes both passenger and freight transport, and effects on alternative transport systems from various scenarios of HSR development.

Function and functional unit



The functional unit for the HSR assessment is transport service to meet the total transport demand.

Transport demand will depend on the market situation. Specific corridor characteristics, passenger rates and energy consumption for different routes, and infrastructure requirements, are the outcome of other work packages and of specifications in Phase 3 [WP Link no. 1-3, see section 10.4]. Inventories are constructed to accommodate inclusion of this information in Phase 3.

Component-based inventory approach

The component-based inventory approach will provide emissions estimates per delivered transport service as well as for total emissions from a given transport demand and transport system composition in Phase 3.

For full flexibility with regards to the functional unit the component-based inventory is constructed to accommodate the later inclusion of market considerations and other variables. Most notably these parameters include total transport volumes at the different routes [WP Link no.4, see section 10.4] (in terms of passenger-km or tonne-km) and occupancy rates. Similar inventories for road- and air transport are also implemented.

The component-based approach prescribes functional units on the level of transport modes, preferably as seat-km for passenger transport and tonne-km for freight. Seat utilisation rates may then be used in sensitivity analysis, to make the whole-system function of transport service to meet the total transport demand.

Scope of this report

The scope of the report from Phase 2 is to provide the premises for evaluation of corridor alternatives in Phase 3.

A view of the general procedure of LCA is given in Figure 9-1. It is repeated, together with an indication of what is to be concluded in the Phase 2 report, in Figure 10-1 below. The figure indicates that the scope here is what falls under goal & scope phase, and the initial inventory phase. At the completion of Phase 2 there are gaps in the inventory model that must be met with corresponding input from the other work packages in NHSRA. A major component that must be made is the market model, to show the transfer potential for HSR from other modes into HSR for the modelled corridors [WP Link no.5, see section 10.4]. The same information demand is found in market modelling, where market potential is set, among other factors, by cost of development and travel times. This chain of information demand exemplifies the iterative nature of a systems analysis such as the NHSRA.



Figure 10-1. Scope for Norwegian HSR assessment Phase 2 (II) and 3 (III).

Information demand is mapped as “Links” throughout this report, with all input requirements summarised in section 2.3: Connection to other groups. A full LCA model appears as all gaps are filled using corridor specific factors. In the course of this report values are dicussed for some of these parameters that have been used in other studies, to provide a starting point for discussion. Hopefully this will aid in interpretation of results and help compare findings in Phase 3 with the result from other studies.

Technology assumption and pre-existing infrastructure

For considerations regarding time and geography, present technology is used for all processes described by literature and database information, i.e., for energy, fuel and material inputs. Future technology is implemented for transport mode operations, with scenario assumptions for propulsion electricity for trains, and fuel efficiency in air and road transport modes.

In life-cycle assessment terms, this approach implies that present technology is implemented for all background processes (described by database information), and technological development in key variables in the foreground system over time.

Geographically, specific data for Norway will be used as far as possible in the foreground system, while the background system is largely based on European average.

Preexisting structures are included in all comparisons, i.e., these are not considered to be sunken costs but necessary investments for all transport modes. The reasoning is that pre-existing structures exist for all modes, and all modes require large-scale maintenance in the near or present time. Road maintenance and upgrading is a stated priority in Norway, and the same is the situation for most of the national railway grid. Air transport is continuously increasing, and two major Norwegian airports Gardermoen (Oslo) and Flesland (Bergen) are both planning to add new runways and/or terminal buildings. From this it follows that all transport modes will need some updating in the very near future, and definitely within an assessment time of up to 60 years. All infrastructure is therefore included in the assessment.

Land use changes, deforestation and soil carbon

Land use and land use changes (LULUC) generate greenhouse gas emissions through deforestation and release of soil carbon from clearing of land. New HSR corridors require



new areas, and will bring some land use changes. Railways may also cause indirect LULUC emissions, e.g., when line developments leads to drainage of wetlands through change of water ways or other.

The guidance document for environmental product declarations for railways, the PCR issued for the Botnia Line assessment assumes greenhouse gas emissions from clearing of vegetation on the track line, i.e., deforestation. From this, greenhouse gas from deforestation represents about 20% of total climate change effect, soil carbon release not included (Stripple and Uppenberg 2010). Schlaupitz presents a simplistic estimate for greenhouse gas emissions from soil carbon release and deforestation, ending with much lower contributions (Schlaupitz 2008).

Climate change potentials from biogenic materials originate from soil carbon as well as from the standing forest. Emissions from land use changes may be evaluated by use of generic factors, separating between forest, grasslands, croplands and wetlands (Müller-Wenk and Brandão 2010).

LULUC emissions are not covered in this report, as the existing estimates of (Stripple and Uppenberg 2010) and (Schlaupitz 2008) are considered to be to crude, and that they do not separate between types of land use changes. The purpose of including LULUC emissions would be to see differences between the different corridors, resulting from differences in use of tunnelling, alignment solutions through agricultural lands, and different types of vegetation.

LULUC is proposed to be a separate issue for Phase 3, either by adaptation of the factors from (Müller-Wenk and Brandão 2010), or systematic implementation of vegetation and soil carbon in the GIS model made for landscape and environmental interventions (Chapter 6) [WP Link no.6, see section 10.4].

Foreground system

The term foreground system refers to the parts of the emissions model where specific information is collected. This is contrasted by the definition of background system, where literature values are used for instance for the emissions caused by production of cement and steel, and emissions from transport of input materials. An illustration of the distinction between foreground modelling and background database figures in this report is shown in Figure 10-2.

From the definition, the foreground system here for HSR covers

• Energy use and source for rolling stock • Corridor-specific factors for occupancy and load factors for infrastructure use • Composition of infrastructure from major components, and material inputs to

Norwegian HSR for single and double track on open sections, bridges and tunnels, including construction, maintenance, operation and decommissioning

Similarly, foreground systems for road transport are defined to include

• Energy use and source for Norwegian car fleet, composition of fleet with regards to fuel type and efficiency, and national factors for occupancy in cars for long and short trips



• Energy use and source for Norwegian bus and truck fleet, and composition of fleet with regards to efficiency

• National factors for infrastructure use for private cars, bus and freight lines • Composition of infrastructure from major components, and material inputs to

Norwegian roads for conventional sections, bridges and tunnels, including construction, maintenance, operation and decommissioning.

National airlines have a similar foreground system, covering

• Supplier-sourced data for fuel use on national air lines for all corridor options • National numbers for infrastructure use, normalised per passenger

Background system and database

The background system covers all inputs for which specific emissions data is not collected in this project. Adaptations may be made in the background system for some settings, for instance the electricity used to produce inputs, but generally the background model is assumed constant though the assessment time. The use of the background, however, may be changed, for instance by generalised parameterisation of the model with respect to use of materials in construction.

All inputs of energy, fuel, services and materials are modelled using the Ecoinvent 2.2 database (Ecoinvent Centre 2008), with latest updates per May 2010. This is a commercial database developed and maintained by the Swiss Centre for Life-cycle Inventories. Ecoinvent is considered the most extensive database for LCA, and is designed for European/global users. The database contains emission data for over 4 000 processes, covering materials, chemicals, energy, transport, fuels and services.

Model tool

Emission inventories are modelled in SimaPro 7.2 software, developed by PRé Consulting. SimaPro runs on Microsoft Windows OS. SimaPro allows implementation of own data in combination with preinstalled or other databases from proprietary or open sources, both emissions data and environmental impact method factors.

MiSA has previously used SimaPro to make environmental accounts for railway projects for Jernbaneverket, for the Follo rail development project (Oslo-Ski). Emission libraries in SimaPro, particularly when based on the Ecoinvent unit process library, ensure transparency and easy revision in later stages of the HSR project.

Allocation for combined use of infrastructure by passenger and freight transport

In the case of combined use of railway infrastructure for transport of both passenger and freight, allocation rules need to be established to allocate the share of the environmental load of infrastructure construction and operation between the two transport utilities.

Environmental impacts from infrastructure are allocated between the two utilities according to the guidelines provided in the PCR-document for railway passenger and freight transport (PCR: 2009). The guidelines use the term transport work as basis for differentiating between the two transport utilities. Transport work is measured as the amount of gross tonne-



kilometres (gtkm) performed on the infrastructure for the respective transport modes. Freight transport gets the share of gtkm for freight/total gtkm, while passenger transport gets the share of gtkm for passenger transport/total gtkm.

Environmental impacts are then allocated to the freight transport utility by dividing with the number of net tonne-kilometres per year, and by dividing with the number of passenger-kilometres per year.

10.1.2 Inventory analysis, sources and structure

A standard process-based approach is used for the inventory modelling. The national size of the HSR concepts could make input-output based inventory models relevant. However, relevant guidelines propose process-based approaches, and a process-based approach allows use of the inventory components already made in the Follo project. Moreover, input-output data is lacking for the alternative transport modes.

The main inventory for rail and road infrastructure is based on recent life-cycle based studies for infrastructure development in Norway. The main sources are:

• Rail infrastructure: (Korsmo and Bergsdal 2010) • Road infrastructure: (Hammervold 2009)

These two reports form the starting point for the common methodology for greenhouse gas accounts for infrastructure, in a draft proposed by the Secretariat for transport planning in 2010 (Kjerkol et al. 2010). Both reports rely on standard life-cycle assessment methodology, and have been used to generate consistent modules using the same background system, implemented in SimaPro LCA software for the NHSRA project. Further inventory assumptions are described in separate sections for rail, road and air infrastructure and operation later in the report.

10.1.3 Impact assessment

Since the aim of this assessment is to evaluate the climate impacts of alternative scenarios for development of the Norwegian transport system between the large cities, up limit the impact assessment to global warming. For this study the standard 100-yr global warming characterisation factors published by the IPCC will be used (IPCC 2001a).

While the scope here is limited to climate-related impacts, other emissions-related impacts form relevant support for decision-making for HSR concepts in Norway. Noise and energy are treated by other studies within the HSR assessment project, as well as landscape and environmental interventions from land use changes. Additional impacts of relevance for transport planning are, e.g., particulate emissions and other emissions with local health and environmental effects. Emission-related environmental impacts from HSR development besides greenhouse gas emissions may be incorporated in the emissions model presented here, if necessary for Phase 3. Implementation is relatively easy as the required information already exists in the model structure, and sources for emissions data are identified for most parts of the HSR and competing transport systems.

Considering climate-change effects, one issue currently on the rise is the increasing recognition of the limitations of the GWP100 indicator as the only indicator for global climate-change effects. The IPCC GWP100 factor does not cover short lived non-conventional



climate effects such as black carbon, contrails, air induced clouds, aerosols etc. There are also discussions about the universal application of the 100-year timeframe for climate effects. The science within this field is, however, still immature, so this will not be included in this study, but the general framework allows for later inclusion.

It follows that multiplier factors for the potentially larger climate forcing effect of emissions from air transport are not included. Adjustment for larger effect factors for emissions from air transport is prescribed in the (GHG Protocol 2009), where air transport emissions shall be treated by a multiplier of 1.9. Use of SimaPro LCA software ensures simple implementation in the case that higher factors for the effect from emissions from airplanes are considered more relevant.

10.2 Structure and organisation for transport system modelling

Future transport development projects are motivated based on a real or expected increase in transport demand. The transport demand is covered by a combination of the different transport means, and in this case by land transport in the form of rail, road and air transport.

Each transport system has its own characteristics, but they can be described in general terms as consisting of an infrastructure part, a transport mean (rolling or flying stock) and an operation phase, as indicated in Figure 10-2.

Figure 10-2. Transport demand and general description of transport systems.

Structuring transport systems according to these main components allows for evaluation of relative emissions for main components within each system, and for comparison between transport system for total emissions as well as for relative importance of components.

Life-cycle emissions are included for all transport means; to cover manufacture, maintenance and decommissioning of vehicle stock. Operation includes the emissions from operating the transport mean; i.e. fuel combustion for cars and airplanes, electricity production and distribution for electric trains and so on. Infrastructure includes the construction and maintenance of this over its complete lifetime.



Infrastructure for transport means consists of many different structures and components depending on the intended use (capacity, speed etc.) and on topographic conditions. A general structure for a component based description of transport modes with emphasis on infrastructure is shown in Figure 10-3, and discussed below using the example of railway. The structure is divided into system level, section level, component level and production level.

Figure 10-3. Component based structure for transport systems.

System level

At the system level the transport mode consists of infrastructure, transport mean and operation, as described in Figure 10-3.

Section level

A complete railway corridor does not have uniform characteristics for its total length. The section level identifies and separates between various section types. In the case of rail it is separated between open sections, tunnels and bridges. Each section type contains multiple variants differentiating between single track and double track, tunnels for different geological conditions, bridges constructed in different materials, topography etc. A combination of sections and section types makes up a railway corridor.



Component level

On component level each section is described according to its major components, for example railway bed, railway substructure, crossings, tracks, tunnel arches, stabilisation of rock material etc. The component level can be organised with subcomponent level to include various installations or aggregation levels. The lowest subcomponent level is equal to material and energy use.

Production level

Production level links the physical inventory of material and energy use at the component level with its production and accompanying emissions.

The component-based structure facilitates analyses of contribution from individual parts of the system and the accumulation of emissions through the value chain.

Model components and adaptability

The inventories for the different transport modes are constructed modularly to allow for flexibility in modelling various scenarios. Components are defined with the aim to allow routes, capacity and technologies to be modified or substituted and their contribution to the overall impact assessed. Additionally, efforts are made to ensure similar structure for all transport modes for better direct comparisons between transport methods.

10.3 Tracking emissions in component-based inventories

Main arguments and motivation for constructing and organising transport systems in a component based manner is the flexibility in assembling, modifying and evaluating different parts or aspects of the overall system or parts of it. In the same way, results can be presented at various levels, and the emissions contribution can be tracked at various levels. Figure 10-4 shows a schematic outline of results and tracking of important emission sources from the transport systems described in this report.

Figure 10-4 shows a generalised example of how results can be presented and how emissions contributions can be followed from top level to detailed basic processes for material and energy production and processing. The relative size of the areas of the stacked columns does not reflect any real values, but is intended for illustration purposes only. Real values and results will be the scope of Phase 3.



Figure 10-4. Presentation of results and tracking of emission contributions in component- based inventories.

Figure 10-4 uses the railway transport system as example. The structure reflects the general inventory structure presented in Figure 10-3 and is organised accordingly. On top level the transport system, or transport mode, is composed of three main parts; infrastructure, operation and rolling stock. The emissions can be measured per year or accumulated for the chosen calculation period. Considering the case of infrastructure, the total emissions can be calculated per kilometre of each section type, or more specifically for a given corridor with a certain composition of open section line, tunnels and bridges. Each of these section types can again be described in terms of contributions from the physical construction phase, the operation of the infrastructure (not to be confused with operation of the rolling stock), and the maintenance of the infrastructure. Sections are composed of various components and subcomponents (subcomponent level is not included in the figure for simplicity of illustration), and the most critical ones can be identified. On the bottom level is the basic processes describing emissions related to materials and energy production, transport and materials processing.

The component- based inventory approach therefore facilitates tracking main emissions contributions from the top level and down to individual basic processes level.



10.4 Connection to other project groups and planning for Phase 3

10.4.1 Connection to other project groups

There are multiple connection points between the modelling of climate-related environmental impacts and the other work packages in the NHSRA project. Table 10-1 provides an overview of links to other WP groups, including links to information that are not explicitly specified as outcome from the groups, but that might possibly be available.

An important issue is energy use for operation of the HSR fleet, which feeds directly into the GHG model. A second important connection is the train capacity and seat utilisation, where energy use per passenger transport is a direct result of the utilisation of total seat capacity.

Investment in infrastructure is a major controlling factor for the total greenhouse gas emissions from HSR transport. The utilisation of railway capacity is inverse proportional to the resulting emissions per transported seat. Use of railway for transport of goods also helps increase the productivity of the infrastructure.

Greenhouse gas emissions from rail infrastructure will be another important contributor to total climate emissions from potential HSR development. The composition of corridors with respect to section types and the topographical and geological conditions will have a strong influence on infrastructure emissions. The aim of this study is to evaluate greenhouse gas emissions from transport as a result of the level of investment made in rail and HSR in Norway on specified corridors. The GHG account therefore must be made for the baseline situation, as well as for all alternatives involving more investment on rail infrastructure. This implies a GHG account for each scenario for all transport modes affected by the decision of investment, level of investment, and corridors considered. From this it follows that transport demand must be modelled for all transport modes, and include connecting transport.



Table 10-1. Links to input from other WP groups

Section Link no. Description WP source 10.1.1 1 Corridor composition and characteristics WP 2

10.1.1/12.1.2 2 Load factor HSR WP 1

10.1.1/12.1.2 3 Energy consumption HSR WP 6

10.1.1/11.1 4 Transport system composition WP 3

10.1.1 5 Transport potential between transport modes

WP 1

10.1.1 6 Possible link for LULUC evaluation WP 6

10.5.2 7 Possible link for emissions’ origins (location of suppliers)

WP 2,4,5

10.6 8 Assessment period WP 1

11.1 9 Technical corridor specifications WP 2

11.2 10 Corridor technical solution WP 5

11.2 11 Track technical solution (ballast) WP 5

11.2.4 12 Track technical solution and resource requirements

WP 2,5

11.2.5 13 Single-track/double-track composition WP 1,2

11.4.1 14 Connecting traffic for airports WP 1

12.1.1 15 Seat capacity for HSR rolling stock WP 5

12.1.1 16 Maintenance requirements, HSR rolling stock

WP 5

12.1.2 17 Corridor specific energy consumption WP 6

12.1.2 18 Corridor specific energy consumption for rail freight

WP 6

12.2.1 19 Road rolling stock energy scenarios WP 1

12.2.2 20 Bus capacity WP 1

12.2.2 21 Bus load factor WP 1

12.2.3 22 Truck load factor WP 1



10.4.2 Information need from physical corridor planning, Phase 3

The component-based inventory established here for Phase 2 provides the building blocks for evaluation of HSR implementation and associated environmental effects with regards to climate gas emissions. In order to assemble an inventory for Phase 3, some key characteristics for the specific corridors are required from the physical planning. To complement this, there is also need for more detailed specifications describing the technical solutions. Main requirements are summarized in Table 10-2.

Table 10-2. Main requirements from physical planning.

Main requirements Description Total corridor length Total km

Corridor composition Share of open section, tunnel section and bridge section

Number of tracks Single-track or double-track

Other requirements Track support construction Ballast or slab-track (ballastless)

Passing loops Number and length Tunnel dimensions Cross-section area

Tunnel vault With/without Geological conditions (tunnel sections) Rock stabilization and securing

Geological conditions (open sections) Supporting walls, under- and overpasses

Bridge construction Concrete or steel bridges (main material) Vegetation in planned corridor If LULUC considerations are to be included

(see section 10.1)

The main requirements describe absolute needs for evaluation of specific HSR corridors. The other requirements represent important characteristics that have an impact on infrastructure emission levels. Receiving information on these from the physical planning would be of high value when assembling final inventories for evaluation of entire corridors in Phase 3.



10.5 Emissions distribution

10.5.1 Assessment time and temporal distribution of emissions

Estimation of time and place for emissions is of interest when HSR is seen in comparison to national targets for greenhouse gas emissions. National emissions are affected by the level of infrastructure development, and by the degree with which input factors are produced in Norway or abroad. To increase the value of the results from the Norwegian HSR assessment the timing of emissions and whether or not they occur in Norway is estimated.

Timing of emission relates to the assessment time, and the issue therefore is shared between multiple work packages within the Norwegian HSR assessment project. The economic assessment proposes that all costs in construction occur in the first year of operation of the rail system. A similar approach may be used for emissions from construction. To illustrate the alternatives, Figure 10-5 below shows a schematic overview of the way in which timing of emissions may be treated for rail infrastructure construction and operation/maintenance.

On the top (in blue) is seen the emissions as they appear through the construction and operation time. The figure includes emissions from both activities on the track and from production of materials and railway components. The lower part shows three general ways to model the timing of emissions, in order to simplify the modelling approach and comply with the selected assessment time:

a. Based on assessment time All emissions from construction are registered to occur in year 1 of operation. The emissions from maintenance are averaged over the assessment period, with or without consideration of residual value.

b. Based on activity Emissions are modelled to occur at the time in which the activities are undertaken. This implies that emissions from construction are registered to occur in year 1 of operation and maintenance is modelled with temporal resolution.

c. Based on function Emissions from construction and maintenance are averaged over the technical lifetime of each component. This requires a detailed implementation of technical lifetimes.

The economic evaluation will use solution a, subtracting any residual value. Similarly, the HSR investment decision can from an environmental viewpoint be considered as separate from national emissions. Technical lifetimes beyond the assessment time are then treated by subtracting residual environmental investments in the same way as economic costs are treated.

Alternatively, a strict activity-based accounting scheme may be used, where emissions are accounted for at the time that the activity in construction and maintenance is undertaken. This perspective does not include any residual value of investment, shown as alternative b. A third approach is to use a function-oriented accounting scheme, where emissions are distributed over the period of component service time; i.e., averaged over the technical lifetime. This is illustrated as alternative c.



Figure 10-5. Ways to treat the timing of emissions, considering assessment time and lifetime of technical components

Most completed greenhouse gas assessments for rail projects use a combination of alternative a and c, where technical lifetimes are used for most parts of the infrastructure, but the major track foundation components are assumed to have a technical lifetime identical to the assessment time. As previously indicated this study rely on the product category rules (PCR) for railway infrastructure as the general guidelines for life-cycle based emission accounts (PCR 2009). The PCR proposes exactly this solution, where maintenance is included through replacement set by lifetime assumption while tunnels and track beds are set to have a lifetime of 60 years – the same period as the assessment time.

In effect, total estimates end the same whether solution a or c is used as long as no component lives beyond the assessment time. However, there is a difference in temporal distribution. Temporal distribution is not an issue for emission accounts made for function-oriented studies, such as environmental product declarations which is the original aim for PCRs, but they are an issue for large-scale investments with consequences for national emissions.

As a reasonable compromise between the original PCR guidelines and the aim of showing temporal distribution, construction emissions will be considered to occur in year one, with maintenance averaged per year based on the 60 year scope asked for in the PCR documents. The evaluation of climate-related emissions may then be made using any assessment period (25, 40, 60, or 100 years) and still include technical lifetimes assumptions properly. Residuals from the emission investment made in construction are not considered.



Proper evaluation of the investment made therefore requires that an extended timeframe be used to evaluate the greenhouse gas performance of HSR corridors.

10.5.2 Spatial distribution, national and total emissions

The influence of the HSR project on national GHG accounts depends on the degree with which input factors are made in Norway or abroad. Previous studies for railway infrastructure show that infrastructure emissions to a large extent are connected to material and component production, especially concrete and steel. At the planning phase little is known of the actual suppliers selected, and if these are national or international.

All direct emissions in construction and maintenance should be national emissions. Moreover, the same can be assumed for generation of energy inputs, such as fuels and electricity. Transport of input factors to the construction site occurs abroad as well as in Norway, and the distribution between these will require a separate investigation. Many of the main materials in construction could be sourced from national suppliers, such as gravel, steel and concrete. However, a large-scale development of HSR will rely on substantial supply from abroad.

As a simple approach to separate national emissions it is proposed here to separate energy and transport as national emissions. Inputs of bitumen, gravel and rudimentary minerals are also assumed to be sourced nationally, while all other inputs are considered to be produced abroad. The separation between national and emissions abroad can be adjusted if better information is available in Phase 3 [WP Link no.7, see section 10.4]

This described approach overestimates the national share from transport, and underestimates the national share from input of steel and concrete. It is thereby considered a reasonable compromise for the split between national emissions and emissions occurring abroad.

10.5.3 Alternative transport modes

The previous sections discuss temporal and spatial distribution of emissions from HSR development and HSR infrastructure. This study shall also consider other transport modes, including airplane and road. Given the focus on HSR it is not aimed to obtain the same level of resolution for the other modes of transport. This offers a challenge to keep consistent system boundaries for the HSR and other modes.

For HSR it is possible to vary assessment time and treat the temporal distribution of infrastructure emissions in different ways. Infrastructure for the other modes are not modeled with the same flexibility. Rather, infrastructure use and emissions thereof occur as a result of the transport demand for air and road modes, using the technical lifetime and assessment time in the original inventories.

The model base for road and air transport is the commercial Ecoinvent database, v2.2. The Ecoinvent database offers life-cycle emission inventories with unit-process resolution. Full documentation exists, and users may make own model set-ups to consider different assumptions for infrastructure utilisation and lifetime. The general inventories as given in Ecoinvent are used here, and emissions from infrastructure construction appear from a transport demand in person-km.



Spatial resolution is implemented in the same way as for HSR, although infrastructure importance for the total emissions footprint of road and air is much lower than what is seen for HSR and national emissions therefore are dominated by direct emissions from vehicle operation over indirect emissions from infrastructure construction.

10.6 Lifetime of infrastructure components

Assumptions for the technical lifetime of infrastructure and stock should be seen in connection with the timing of emissions and assessment time length, and all three issues are shared between multiple work packages within the Norwegian HSR assessment project. The objective here is to discuss approaches that may be used for the climate-related environmental analysis to be in line with the complementary deliverables within the HSR project and relevant guidelines for environmental accounting guidelines.

Atkins, in charge of the parallel work package on economic evaluation, has published a note on the economic assessment period to use in the Norway HSR (distributed by Ed Zhang, Dec 8th, 2010). The note indicates 25 years as the standard assessment time in Norway, and proposes a complementary period of 40 years to cover more realistically the technical lifetime of rail infrastructure components. The implication is that most of the invested infrastructure is realised within the 40 year period, while longer lived components may be treated by consideration of residual value [WP Link no.8, see section 10.4].

Main guidelines for environmental evaluation of rail infrastructure propose 60 years assessment time, as described in the product category rules (PCR) for rail transport and railway infrastructure (PCR 2009). All activities within this time period, including construction, operations and maintenance, should be accounted for. The railway PCR was developed in the environmental assessment made for the Swedish Bothnia Line. It has already seen the first Norwegian application, in the recently completed emissions budget for the Follo Line part of the Oslo-Ski InterCity network (Korsmo and Bergsdal 2010).

Output from the Follo study was recently used as basis for a draft version of common Norwegian guidelines for greenhouse gas accounts for infrastructure projects, to be applied to rail, road, air transport and harbour development (Kjerkol et al. 2010). Based on experience from projects for the Railway Authority (Jernbaneverket) and Road Authority (Statens Vegvesen), the guidelines propose that the assessment should include the effect of different technical lifetime for components, i.e., 40 years for open road sections and up to 100 years for tunnels.

General guidelines for socio-economic evaluation of rail projects in Norway provide a list of technical lifetimes to be used in the evaluation, summarised in Figure 10-6 below. In the case that the technical life extends beyond the assessment time, remaining life is treated by subtraction of residual value.



Figure 10-6. Technical lifetimes to use in Norwegian socio-economic evaluation of railways (Jernbaneverket 2006).

Previous studies for rail projects use versions of the same approach, with technical lifetime defined for entire infrastructure systems, aggregated components or sub-components. Choice of method to model emissions over time seems mainly to be based on the availability of environmental information to describe infrastructure development; see for instance the component lifetimes summarised in table 10-3.

Table10-3. Technical lifetimes used in previous environmental assessments for high-speed rail

Study Lifetime of components Country

(Network Rail 2009) 10-100 years UK

(Chester 2008b) 4-50 years USA

(Rozycki et al. 2003) 15-100 years Germany

(ADEME 2009) 50-100 years France

(UIC 2009) 25-100 years Europe, general

(Stripple and Uppenberg 2010) 15-60 years Sweden

(Schlaupitz 2008) 20-100 years Norway

(Jernbaneverket 2006) 30-75 years Norway

(Simonsen 2010b, c) 10-40 years Norway

This study rely on the PCR for railway infrastructure (PCR 2009). Technical lifetime is used as basis for demands on maintenance and change of infrastructure components. This is in line with Norwegian guidelines currently in the making.

0102030405060708090

100

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11 COMPONENT BASED LCI APPROACH FOR INFRASTRUCTURE

11.1 Inventory data sources The aim for the Phase 2 report is to establish the necessary inventory components for calculation of greenhouse gas emissions from high-speed rail and alternative modes of transport on major transport corridors in Norway (and to Sweden). This should be done in a flexible manner so that different configurations and scenarios for future development can be analysed and explored within the same framework. The modular structure and consistent use of unit processes provides this flexibility, as described in 10.2.

The emissions model follows the same structure for all transport modes, where infrastructure, vehicles (rolling and flying stock) and operations are separated. The various unit processes can be combined and scaled according to given transport system characteristics and in combination with parameters resulting from other work packages within the high speed rail assessment.

Consistent system boundaries across all technologies or transport modes are crucial for a fair comparison between the alternatives. The same principles are employed for all transport modes. The level of detail in the air inventory is lower than that of high speed rail (mainly due to time restriction within the project, but also related to issues regarding data availability) although the inventory should cover the same range of activities as the other options. Emissions related to air transport is dominated by aircraft operation emissions, and inventory for airport infrastructure is considered sufficient for the purpose of this study.

The market effects with or without high speed rail development will be treated by other work packages within this project, and parameters from these packages will be fed into the emissions model during Phase 3 when the alternatives are compared. The mix of transport modes and the extent of high speed rail development will be modelled and assessed by combining modules and unit processes from the respective inventories to represent the given scenario [WP Link no. 4 and 9, see section 10.4].

Inventories for transport infrastructure are compiled from various sources. Rail and road infrastructure are based on projects and reports that are carried out specifically to evaluate the environmental profile and critical aspects related to infrastructure construction and operation projects. The projects are both carried out by, or in close cooperation, with the relevant transport authorities. These projects are well suited as a foundation for environmental assessment of the respective transport systems. Both studies are structured in a similar manner and infrastructure is assessed with life cycle assessment methodology, which is also the approach in this evaluation of high speed rail. The studies of road and rail infrastructure also facilitate separating between infrastructure types for the same transport mode, i.e. in the sense of describing an infrastructure project as composed of a mix of sections with different characteristics, most notably open sections, tunnels and bridges. An important and valuable common characteristic for the road and rail inventories is that they are based on Norwegian conditions and construction practices.

Road and rail are both land transport with many similar characteristics. Air transport has a very different set of characteristics and consists of a more limited set of subcomponents, mainly the airports with all sub-components such as runways, terminal buildings, other facilities etc. The body of literature applying life cycle assessment methodology for airports is



surprisingly small. The inventory for airport infrastructure is based on international studies and infrastructure operation on Norwegian figures.

Different methodological approaches can assign different relative importance between the components in a transport system. As previously mentioned in 9.3.2 there are methodological differences between process LCA, input-output LCA and hybrid LCA. The most important difference is that process based LCA has cut-offs. For certain parts of the inventory the cut-off may be small, while for others the cut-off may be significant. In particular, it is typically service based activities and high value added activities that are poorly covered by conventional process-based inventories. For transport studies this is evident in the construction (and maintenance) of vehicles, trains and aircraft. For aircraft there is an approximate factor 10 difference between a simple process based inventory (Spielmann et al. 2007) and an input-output based approach for manufacturing of flying stock (Chester 2008a). This difference stems from the fact that the process based inventory only accounts for a (simplified) bill of materials in the aircraft as well as resources into and emissions from the final factory of the plane. For aircraft it is reasonable to assume that several tiers upstream of the aircraft manufacturer (e.g. Airbus or Boeing) will have high value added activities for sub-components, sub-sub components etc. This means a relatively higher share of services compared to material costs. For construction of infrastructure this fraction is smaller; more of the activities within the system are covered by the materials and on-site resource use and emissions.

This study will still use process-based LCA-data, but with the note that certain parts of the inventory may be underestimated.

11.1.1 Electricity mixes

The electricity mix has a potentially strong influence on the results. The model is structured in such a way that the electricity mix can be easily changed at various levels in the analysis. There is an ongoing debate about which electricity mix that should be used in life cycle assessment studies in Norway. It is not considered fruitful to elaborate on that debate here, but the ability to change electricity mix enables easy testing of the sensitivity of the results to the chosen mix(es).

The model here includes the average Norwegian consumption mix for 2007-2009 as well as the average NORDEL (Nordic) mix for 2006-2008. The NORDEL mix including imports is used as the reference electricity mix. Possible supplementary scenarios can include future electricity mixes based on technology (coal power and hydro power respectively) and scenarios for European electricity supply as estimated by the EU financed NEEDS-project (Frischknecht 2009).

This electricity mix will be used for all foreground processes that occurs domestically. For background processes or foreground processes occurring abroad, the European electricity mix in the Ecoinvent database is used as the default.

The following figures document the mixes that have been established for this report (the Norwegian mix and the NORDEL mix) plus the European UCTE mix as described in the Ecoinvent database. For specific technologies (e.g. hydro power, gas power etc.) the



Ecoinvent v2 LCA-database4 (Dones et al. 2007) is used. This also applies to imports from countries outside of NORDEL (for the NORDEL mix) and countries outside Norway (for the Norwegian mix), except Russia where a separate mix based on available statistics5 is constructed for this study. Note that the available statistics for NORDEL only allows 2006-2008 as the most recent 3 yr average, while for Norway the NVE statistics gives numbers for 2007-2009.

NORDEL mix 2006-2008

For the NORDEL mix the most recent statistics6 for NORDEL in 2006-2008 is used to produce an estimate for the average consumption mix in the Nordic countries.

Grid losses and transmission networks are assumed to be the same as in (Dones et al. 2007).

Note that for the case of electricity to rail, the rail-specific transformation and transport losses are applied.

Figure 11-1. NORDEL average consumption mix for the period 2006-2009.

Norwegian mix 2007-2009

For the Norwegian mix the most recent statistics published by NVE7 is used to find the Norwegian production mix for 2007-2009, as well as import and export figures. From this it is possible to construct a consumption mix. Imports are included with country mixes as they are

4 www.ecoinvent.ch 5 http://www.ieej.or.jp/aperc/outlook2006.html 6 https://www.entsoe.eu/index.php?id=65 7 http://www.nve.no/no/Kraftmarked/Sluttbrukermarkedet/Varedeklarasjon1/

http://www.ecoinvent.ch/

http://www.ieej.or.jp/aperc/outlook2006.html

https://www.entsoe.eu/index.php?id=65

http://www.nve.no/no/Kraftmarked/Sluttbrukermarkedet/Varedeklarasjon1/



in the Ecoinvent database (Dones et al. 2007). Figure 11-2 below shows the consumption mix.

Grid losses and transmission networks are assumed to be the same as in the Ecoinvent database.

Figure 11-2. Norwegian average consumption mix for the period 2007-2009.

European UCTE mix

European electricity mix is based on the UCTE mix in the Ecoinvent database. The composition is presented in Figure 11-3. Two third of the UCTE mix is produced with German, French, Italian and Spanish production mixes.

Grid losses and transmission networks are assumed to be the same as in (Dones et al. 2007).



Figure 11-3. European electricity mix 2004 (UCTE).

Electricity scenarios

The electricity production mix is an important parameter for various parts of the different transport systems with respect to climate emissions, most notably for the operation phase of high speed rail. Different electricity production scenarios are included in the inventory. The effect of choices for electricity mix and the sensitivity for results towards the electricity assumption can thus be assessed.

Figure 11-4 presents the range of production scenarios and the associated emissions. Scenarios include a base case scenario using NORDEL mix, an optimistic scenario using Norwegian mix (incl. imports) and a pessimistic scenario towards a European UCTE mix. Electricity from hydro power and coal (assuming Nordic technology) are included to establish a lower and upper boundary, respectively. Please note that the graph is given on a logarithmic scale.



Figure 11-4. Electricity scenarios (medium voltage) and CO2-emission intensities.

The variation in emission intensities is considerable, ranging from 5.7 g CO2-eq per kWh for Norwegian hydro power to 965 g CO2-eq per kWh for coal power. This report uses the NORDEL electricity mix as the default value, with an emission intensity of 166 g CO2-eq per kWh. The large variation underlines the importance and sensitivity to choice of electricity mix. Electricity mixes are given as medium voltage figures.

Electricity use foreground system

Electricity use in the foreground system is determined by the choice of electricity mix described above and in Figure 11-4.

Electricity use in background system

Materials production, processing and transport in the background system is modelled using the Ecoinvent database, and all electricity use is given according to the database processes. The database refers to European conditions and uses mainly the European UCTE mix in Figure 11-3.



11.2 Railway infrastructure Component based inventory for rail infrastructure is based on Norwegian numbers for the projected Follo Line, which is a new double- track line planned for high speed capacity and with a possible connection to a more extensive high speed railway system, both nationally and as a gateway to a transboundary HSR system connecting Norway and Sweden and potentially also the European railway system. This line will be part of the InterCity network and connect Oslo and Ski in the eastern part of Norway, close to the Swedish border. The line is currently in the planning and engineering phase, and an assessment of environmental impacts associated with construction and operation of the line has been carried out. A part of this assessment has included the preparation of an environmental budget, where climate related environmental emissions from infrastructure construction has been one of the key topics (Korsmo and Bergsdal 2010). Other environmental emissions such as ozone depletion, acidification, eutrophication and photochemical oxidant formation were also covered in this assessment, but are not part of the scope in the NHSRA. The inclusion of a range of environmental emissions associated with infrastructure construction was intended as a step towards a methodology for evaluating infrastructure construction and operation projects, and based on life cycle assessment methodology.

Inventory compilation is based on engineering data for the line, and includes both tunnel section and open section. Tunnel sections can be modelled as consisting of two single uni- directional tunnels or as a two-track tunnel. The Follo Line represents a modern railway development dimensioned for efficient operation at higher speeds than most existing railway infrastructure. The dimensioning speed for the Follo Line is 200 km/h. Technical specifications for the corridors in the different alternatives to be evaluated in Phase 3 of the high speed rail assessment are pending, and adjustments might be required for parts of the inventories to be in line with the actual planned corridors [WP Link no. 10, see section 10.4]. The component based inventory is not final and is organised to be flexible and to facilitate adjustments based on more detailed technical specifications for the actual corridor alternatives, i.e. changes in dimensioning or production of various components can be easily incorporated to reflect additional requirements from more detailed engineering data for high speed rail when available.

Assessment of railway development outside the high speed rail assessment project is also facilitated by the inventory. New railway projects for medium and long distances are not likely to be dimensioned for less than 200 km/h.

The reader is referred to the specific report for a more detailed description of the inventory components (Korsmo and Bergsdal 2010). The following describes the organisation and structuring for use in the component based inventory for high speed rail assessment.

Component based inventory for railway infrastructure is structured according to the general outline described in Figure 11-5. The inventory includes open sections, tunnels and bridges. Railway bridges are modelled based on a modified version of road bridges, adapted to railway track and bed.

Figure 11-5 shows the general structure for component based modelling of rail infrastructure. A given railway line, or corridor, is composed of a combination of three main section types; open sections, tunnels and bridges.



Figure 11-5. Component based modelling of rail infrastructure.

Each of these sections is subdivided into modules, including the rail, rail crossings and structures, tunnel structure and technical installations such as lighting, ventilation, signals, etc. At the basic production level the production and use of materials and energy for production and processing of different modules is indicated. Figure 11-5 exemplifies the layout of the component based inventory for the tunnel section and the component “Railway bed” with a selection of the main subcomponents. The inventory structure is adjusted such that the components are calculated on a per unit length of each section.

Tunnelling consists solely of the components of the tunnel itself, excluding the rail sections. This includes blasting, boring and excavating, as well as reinforcing of tunnel walls and installation of tunnel walls and tunnel liner, if necessary.

Railway bed includes the rails, cross-ties, ballast, electric cables, cable ducts and cable support structures. The rail component is assumed to be identical in both tunnel and open sections with the exception of hanging cable supports, which are only necessary for tunnel sections.

Constructions are indicated as a separate component and comprise rail crossings such as under- or overpasses (as bridges or tunnels) and support walls as the main component parts.

Technical installations comprise fans for ventilation of tunnels, emergency lights and equipment, transformers, signalling and communications system including pylons, and power supply system.



Ballastless tracks

Inventories for railway infrastructure construction are implemented assuming conventional technical solutions with use of ballast for the track structure. In recent years the concept of ballastless tracks has been introduced. The International Union of Railways (UIC) has prepared a feasibility study for ballastless tracks in general, and for alternative design solutions (UIC 2002). Ballastless tracks are being explored as an alternative to conventional ballast tracks due to potential improvements within increased capacity, increased speed, reduced maintenance and life cycle costs, and increased safety due to reductions in maintenance operations [WP Link no. 11, see section 10.4].

The inventory for railway construction includes the option of choosing a ballastless track design. The ballastless track component is modelled based on information in (UIC 2002; Rozycki et al. 2003).

11.2.1 Open track section

Open sections consist of blasting and excavation processes to grade the route in addition to the track, over- and underpasses, track and technical installation components. Material use considered includes mainly steel of low, high and reinforcing quality, concrete, copper for cable components, vehicle and diesel use for transport, and gravel for ballast.

11.2.2 Tunnel section

Tunnel section includes the actual tunnelling, track components and other necessary constructions and installations. Construction of emergency evacuation tunnels is also included. The tunnel may be a single tunnel with double tracks, or double tunnels with single tracks.

The materials used in tunnel construction are similar to that of the open track, but with greater quantities of concrete and steel for reinforcement. Additionally, there is use of expanded polystyrene and polyethylene foam for frost protection and plastic pipes for drainage. Due to the excavation of larger quantities of earth and rock in tunnel construction in comparison to open sections, there is also greater quantities of building machine usage and diesel consumption per unit length of construction.

11.2.3 Bridge section

Bridge construction for railway infrastructure is modelled as bridges for road infrastructure, only with a railway bed on top instead of a roadbed. The component based approach facilitates this modification.

Railway bridge structure is modelled as either concrete or steel bridge. The inventory allows the use of each type, and of a combination of both for a given railway corridor.

11.2.4 Material and energy use

The dominant material processes used in the rail infrastructure processes are cast and reinforced concrete, three grades of steel (low, high and structural), copper and aluminium for electricity cable structures. Direct use of electricity and diesel is included for transport of construction materials and excavated materials, and for blasting and ventilation during tunnel construction. All indirect energy use for production of materials is also included.



Material and energy use are affected by topography and geological conditions. Open sections that are designed as below-grade require more excavation and in some case more reinforcements and sheet piling.

Materials used for securing, stabilising and supporting rock material in the tunnel walls depend on geological conditions and are important for the overall material input. Construction materials for this application, like cement and concrete, are important components in the emissions inventory due to their relatively high emission intensities.

Materials and energy use will depend on corridor composition, technical solutions and construction methods [WP Link no. 12, see section 10.4].

11.2.5 Single track corridors

The HSR construction inventory is based on a double-track corridor. Single-track corridors are an alternative for some corridors, or parts of corridors, and can be modelled by adapting the modules in the double-track inventory and scale between single- and double-track [WP Link no. 13, see section 10.4]. Other studies have previously used more or less linear scaling factors (Freeman and Cooper 2007; Network Rail 2010). Single-track lines will require the same components as for double-track, but with varying quantities of components and materials. Some parameters will scale proportionally with choice of single- or double-track, others will scale non-proportionally with the same choice, and some tunnelling parameters will scale with the cross section area.

Metres of rail track and cross-ties scale proportionally for single- and double-track, however with the exception that single-track lines can be expected to include more frequent passing loops to maintain capacity and flexibility. Technical installations, power systems and signalling systems are also considered as proportional to number of tracks. Excavation activities and ballast for the railway bed are considered non-proportional to number of tracks, i.e. railway bed for single track is not considered to be equal to half of a double-track line.

Tunnel sections are represented by single-track tunnels modelled in the inventory (double-track with single-track tunnels). Several aspects of tunnel construction scale with the tunnel cross section area and consequently volume, depending on the length of the tunnel section, rather than directly with the number of tracks. A larger cross section area will reduce energy use for propulsion of the train, but at the expense of more excavation work and material and energy use for construction. Both single- and double- track tunnels are covered by the rail infrastructure inventory, and the inventory organisation allows for modelling tunnels with any cross sectional dimensions. Tunnelling and excavation and the associated use of energy, transport and machinery are parameters depending on the volume of the tunnel. Materials for securing and stabilising rock material, frost protection and construction of tunnel liner are important parameters that scale with the volume and cross section area of the tunnel.

Single-track corridors will have additional challenges regarding flexibility to maintain capacity during maintenance, technical problems or other unexpected incidents resulting in temporary shut-downs.



11.2.6 Maintenance and operation of railway infrastructure

Railway infrastructure maintenance is a complex process that involves the upgrading and replacement of a range of materials and components, each with an individual lifetime. Maintenance is based on the individual replacement need for the components and subcomponents in Figure 11-5.

Timing of replacement of major parts of the infrastructure relative to the assessment period is sensitive, and determination of assessment period decides whether replacement of a major component is included or omitted from the study. The Product Category Rules (PCR) for assessment of environmental performance of rail transport and railway infrastructure establishes 60 years as the calculation period (PCR 2009). In the component based inventory maintenance is added over a 60-year assessment period based on the lifetime and replacement need for individual components and materials. The aggregated maintenance need is then annualised to describe an average annual maintenance activity. The annualised activity facilitates evaluation of assessment periods of varying duration.

Operation of rail infrastructure includes mainly electricity for heating of rail points, operation of signal and telecommunications equipment and ventilation.

11.3 Road infrastructure Component based inventory for road transport infrastructure is based mainly on a report prepared for the Norwegian Public Roads Administration concerning methodology for assessing material and energy use from road construction projects (Hammervold 2009). Approach and methodology is to a large extent identical to the project that is described above for railway infrastructure. Both projects apply life-cycle assessment methodology, rely on the same background inventory database, and use the same software for implementation of the emissions model (i.e., SimaPro).

The objective of the road infrastructure project was to establish methodology for assessing emissions from infrastructure construction and operation projects to supplement the more commonly used approach of only counting and comparing the emission from transitions between transport modes during the operation phase. The road section covered is a four lane development of a pre-existing two-lane road section. Environmental emissions were limited to climate related emissions, but with potential for including other emissions. The project was initiated following a request from the Ministry of Transport and Communications to report changes in climate related emissions caused by large investment projects within the transport sector. Organisation and structuring of the information for use in the high speed assessment is described in the following.

Road infrastructure inventory is structured according to the general outline in Figure 10-3 and similarly to rail infrastructure. The road is modelled and organised according to main section types as in the railway inventory, i.e. open section, tunnels and bridges. The organisation of the road infrastructure inventory is displayed in Figure 11-6.



Figure 11-6. Component based modelling of road infrastructure.

Each section represents a module consisting of the main processes and materials. Figure 11-6 exemplifies the modularity for construction of open section, with the main components being the actual excavation, blasting and moving of rocks and earth, construction of sub-base layer, base layer and the final surface course. The basic production level comprises the manufacturing and production of materials and energy for each component. The inventory structure is adjusted such that components are calculated on a per unit length of each section. Inventories and components can be modelled for various dimensions and characteristics for the individual sections.

11.3.1 Open road section

Open road sections consist of blasting and excavation processes to grade the route and transport and machinery use to move rocks and earth. Open sections also include the components for construction of sub-base layer, base layer and surface course. Main materials include gravel and asphalt materials.

Open road sections are characterised by road dimensions which are based on the predicted average annual daily traffic for the section. Both the thickness of the various layers and the breadth of the road are considered.

Landscape is levelled prior to construction of open sections, and the amount demanded of the blasting or excavation process is dependent on the road dimensions and the local topography. Resulting blasting aggregate is transported and used in the sub-base layer. Hot mix asphalt and gravel are used in the binder, or base course, while asphalt is used on the surface, or wearing course.

Open section is combined with tunnels and bridges to account for the roadway also in tunnels and bridges to describe complete section modules.

11.3.2 Tunnel section

Tunnel section includes among other things the blasting and boring associated with tunnelling, transport and machinery use, construction of tunnel portals and ventilation system. Tunnels can be modelled with different cross sections and characteristics. Main



materials include explosives, reinforcing steel, concrete, steel, polyethylene foam, gravel and asphalt.

Tunnels are characterised by their length and profile. In the various tunnel profiles, the cross-sectional area of the opening varies linearly with arc length.

Open section is used as input to tunnel section to describe the roadway and complete the tunnel section module.

11.3.3 Bridge section

Road bridges are modelled as a bridge structure and roadbed. The inventory for the bridge structure includes both steel and concrete bridges. The bridge section module is completed by adding a roadbed component modelled as open section for the base and surface.

Main building materials considered for the concrete type bridges are concrete, reinforcing steel and asphalt for the road deck. For the steel bridge, these are steel, concrete, reinforcing steel, and asphalt.

Open section is used as input to bridge section to describe the roadway and complete the bridge section module.

11.3.4 Maintenance and operation of road infrastructure

The lifetime of open road elements is assumed to be 40 years, and that of tunnels and bridges to be 100 years. Repaving the road surface is assumed to occur every 10 years, with the exception of last decade of the road’s serviceable lifetime. For every repaving event, an estimated 65% by weight of the original asphalt demand is used.

Recurring operations during the road lifetime are assumed to include lighting along open road and tunnel elements and ventilation in tunnels. Only electricity demand is considered in the operation phase; material demand of light bulbs, fans and motors are not considered.

Uncertainty in use of electricity in the open road sections is assumed in anticipation of advances in lighting technologies in the future. These technologies will likely decrease electricity demand for street lighting and therefore reduce environmental impact.

The electricity demanded for lighting is assumed to be equal to that of an equivalent length of open road.



11.3.5 Norwegian road composition

Modelling use of road infrastructure for transport requires information or assumptions about the composition of section types for Norwegian roads. The road composition is based on characteristics for classified roads (fylkesveger) and information from Statistics Norway (Statistics Norway 2001, 2010). The composition is summarised in Table 11-1.

Table 11-1. Composition of Norwegian classified roads.

Section type Number of kilometres Share Open section 26 366 ~ 96 % Tunnel section 859 ~3 % Bridge section 242 ~1 %

Norwegian classified roads consist mainly of open section roads, but the number of tunnels makes up approximately 3 % of the classified road system, while bridges account for a bit less than 1 %.

11.4 Air infrastructure This chapter considers the appropriate structure of a life cycle inventory for air transport in the context of comparing to alternative transport modes within the high speed rail evaluation project.

Air transport between the large cities is significant. It constitutes a large fraction of passenger transport work between the cities (Denstadli 2006). Between the big cities in Norway and Oslo between 12% (Kristiansand) and 64 % (Stavanger) of travels are done by plane. One hypothesis of a high speed rail development is that it will reduce passenger transport by plane or car and potentially also reduce emissions of greenhouse gases from the transport sector.

Previous studies (Spielmann et al. 2007; Chester 2008a) on air transport have shown construction and operation of infrastructure and construction and maintenance of aircraft to be relatively insignificant compared to emissions in the operation phase. This implies a strong focus on getting high quality operational data and choosing the right parameters for scenario development.

The body of literature on life cycle assessment of air transport is surprisingly small. This may be due to direct emissions dominating impacts, eliminating the need for further investigations. However, some studies have been conducted. The most comprehensive study has been done by Chester (2008a), comparing different transport modes in the US. Chester bases the inventory on a background input-output model of the US economy. This means achieving no cut-offs in the system, at the expense of specificity in sector/process detail. A few other studies have been conducted, although not at a very detailed level. The aircraft manufacturers should be involved in producing better data for future studies.



11.4.1 Airport infrastructure

The infrastructure for air transport systems is limited compared to the alternatives. It consists of the airports with all sub-components such as runways, terminal buildings, other facilities etc. In addition air transport requires transport to and from the airports. This is usually done by car, bus or train and will be covered by the inventories for those transport modes respectively.

The construction of airport infrastructure in the model is split into ground preparations and runway construction and the construction of other facilities such as terminal buildings. Due to the limited literature and data available, existing aggregate data from Ecoinvent (Spielmann et al. 2007) is used, which is based on the construction of the Zürich airport (for area preparations and runway construction). The numbers for Zürich are normalised to 1 air traffic movement/yr and modified to include the project specific electricity mix.

For construction of airport facilities a similar simplistic approach is applied. The data obtained for OSL indicates an area for the terminal of 148,000 m2. The construction of the buildings is modelled using the existing wood hall and steel hall construction processes in Ecoinvent. Data is normalised to 1 traffic movement per year, assuming the OSL (per traffic movement) is a fair estimate for the airports in the large cities.

Parking for 16000 cars (OSL) will be covered by the road construction inventory processes. For simplicity the same amount of parking infrastructure per air traffic movement capacity is assumed.

Data on connecting travels from (Denstadli and Rideng 2010) will be used to make the connection to the road and rail inventories as reproduced in Table 11-2, in combination with parameters from the market study [WP Link no. 14, see section 10.4].

Table 11-2. Transport mode to the airport (in percent), 2009 (Denstadli and Rideng 2010).

Transport mean OSL (Gardermoen)

Large airports

Medium airports

Regional airports

Total

Bus 18 22 14 14 20 Flytoget (Airport rail express)

38 - - - 19

Rail 9 2 - - 5 Total public transport

65 24 14 14 44

Taxi 5 23 21 20 14 Car parked at airport 14 19 24 21 17 Car (driven by others) 12 27 34 34 20 Rental car 2 4 6 6 3 Other 2 3 2 5 2 Total 100 100 100 100 100

The table shows large variations between smaller airports and Norway’s main airport OSL- Gardermoen. Transport by car is the dominating transport mode for all airport types, while the share of public transport is a considerable 65 % for OSL, mainly due to the existence of the airport rail express (Flytoget) and the relatively long distance from Oslo and OSL.



11.4.2 Maintenance and operation of airport facilities

Operation of airport

The operation of airport facilities involves running, lighting and heating of all associated buildings, most notably terminal buildings and other supporting buildings. This includes chemical use for aircraft and runway de-icing. Two simple sources of information on the resource use for operation of the airports are found for Norway; the annual environmental report of Avinor (Avinor 2010) and Oslo airport (OSL) (Oslo lufthavn AS 2010). The Oslo figures are assumed to be representative for Gardermoen airport only, while the Avinor (national average) figures represent all other airports

Maintenance of airport

No information is found for the maintenance of the airport and the literature is also limited on this subject. A number of components and building structures may need regular repair and replacement. Since no data is available regarding the maintenance, the expected lifetime of the terminal building is reduced to 40 years to account for some material replacements and repair.

The runway is modelled for an assumed lifetime of 100 years. Maintenance of runway area is modelled as one additional runway construction during the airport lifetime, equivalent to assuming a 50 year lifetime for the runway area.

11.4.3 Demolition

For the demolition of the airport there is very limited knowledge, since the afterlife of the area is not clear. Data from the Zürich-based assessment (Spielmann et al. 2007) is used. These data only includes excavation of the material and transport away from the site. A lifetime of 100 yrs for the runways and 40 yrs for the terminal buildings is applied.

11.4.4 Allocation for airport infrastructure

Airports serve both passengers as well as freight to some degree. For the specific distances relevant to this study, the level of airborne freight is negligible (SAS, personal communication). Hence, there is no allocation for freight in the model; air freight is assumed to not exist on the given routes.



12 COMPONENT BASED LCI FOR MANUFACTURING AND OPERATION OF TRANSPORT VEHICLES

The rolling, or flying stock for each transport system is separated into a manufacturing phase, an operation phase and a disposal phase.

The manufacturing phase of mass-transit transport modes (buses, trains and airplanes) is structured to be in units of per seat-km or passenger-km travelled. The latter unit is dependent on average load factors of the transport mean in question. Private vehicle manufacture is structured in terms of vehicle-kilometres travelled.

Operational phases include the production and consumption of fuel.

12.1 Railway rolling stock and operation 12.1.1 HSR rolling stock manufacturing and maintenance

The majority of the data found regarding the rolling stock of high speed rail systems were academic literature and feasibility assessments for government projects. An overview of the studied systems is provided in Table 12-1.

Table 12-1. Overview of high speed rolling stock for rail considered in this report.

Country Year Seat Capacity

Service Speed (km/h)

Manufacturing emissions (kg CO2-eq/seat)

Intercity Express (ICE) Germany 380 280 - X-2000 Sweden 320 200 - Train à Grande Vitesse (TGV) Reseau

France 1992-6 377 300 3 459

TGV Duplex 1995-7 545 300 2 380 Eurostar UK-France

UK-Belgium 1993 750 300 3 256

Alta Velocidad Española (AVE)

Spain 2004 404 300 3 552

Shinkansen 700 Series Japan 1998 1323 270 1 618 High speed rail lines (HSL) East and South*

Netherlands Projected - 140-400 -

California High Speed Rail Project*

USA Projected 350 350 -

Alstrom AGV* France Projected 650 360 2 649 * Projection from feasibility assessment

1 Same as X-2000

Sources: (Van Wee et al. 2003; Janic 2005; Andersson and Lukaszewicz 2006b; Chester 2008a; Horvath and Chester 2008; Network Rail 2009)

Construction emissions for the rolling stock for high speed rail systems were fairly similar when compared on a per seat basis, ranging from 1 618 (Shinkansen) to 3 552 (AVE) kg CO2-eq/seat. It should be noted that the AGV, Shinkansen and AVE trains do not have power cars at either end of the train; rather, a distributed traction is used wherein each passenger carriage has a motor underneath the floor.



There was very little detail in the reports used for HSR rolling stock; for the majority of the lines examined, only a single value for the production emissions was provided, without details of the material or energy use in the manufacturing process. Manufacture of rolling stock has a relatively small significance compared to railway infrastructure and operation. For the manufacture of rolling stock for rail the average value 2 819 kg CO2-eq/seat based on the information presented in Table 12-1 is used [WP Link no. 15, see section 10.4].

Maintenance

The lifetime of the rolling stock is assumed to be 25 years (Hveding 2010). Most major components of the train set are changed once during the lifetime. The maintenance of the trains is therefore modelled as one replacement of the entire train over the lifetime of 25 years, which in effect halves the technical lifetime of the train set. The maintenance demand is annualised, and distributed over the lifetime of the train [WP Link no. 16, see section 10.4].

12.1.2 Rail operation

The rail operation covered here includes the total electricity consumption needed for the propulsion of the trains as well as idling and heating up before driving. The energy for operation of trains is modelled through the use of two factors; energy per seat and seat load factor (occupancy).

Energy use

For clarity the system boundary for this process is the electricity line above the train. Losses in distribution (~5%) and transformation (~15%) of the electricity for the train, as well as heating of the track points, are covered in the section on operation of the infrastructure. The figures for Norwegian high speed rail are calculated specifically within this project by a different project partner. This will result in energy consumption estimates for the specific projected corridors in Phase 3 of the assessment [WP Link no. 17, see section 10.4].

There is substantial literature on the calculation of energy for train propulsion (see eg Andersson and Lukaszewicz (2006a) and Vestby (2000)). Specific energy consumption estimates will be provided by project partners for Phase 3, but some generalised estimates based on literature sources are provided for use in figures and discussions, and to place the output from project partners in relation to previous studies. The main resistances that need to be overcome is rolling resistance, air drag and working against gravity. Parameters such as train speed, train length, train shape, the amount (and cross-sectional area) of tunnels, the weight of the train, number of stops, topography, regenerative braking, efficiency of internal electric system etc., all affect the energy use of the train itself. In addition there is some energy consumption connected to heating and idling of the train.

In combination with the amount of seats per train set, this produces an overall estimate of the (net) energy needed to be delivered to the train per seat-km of operation. Several studies give estimates of this specific energy consumption. In addition, there are empirical sources of energy consumption for Norway. The table below shows some of the values given in the literature to indicate the expected range of energy consumption that can be expected from the energy study. Specific energy will be provided by project partners [WP Link no. 3, see section 10.4].



Table 12-2 lists Norwegian average energy consumption for passenger and freight transport. The figure for passenger transport is given per seat-km and per person-km together with a load factor. The number for energy use per person-km includes both energy losses and energy use for rolling stock when not in operation. Energy losses are composed of 15% conversion losses and 5% for the aerial line. Energy use for the non-operation mode is reported as approximately 20%. Assuming the same load and adjusting for losses and non-operation mode, the energy use per seat-km is equivalent for the two studies reporting for conventional Norwegian passenger transport by rail.

Similarly to person transport, Norwegian average figures are provided also for freight transport with and without energy losses and non-operation mode energy use. Energy losses are the same as for passenger transport, while the non-operation energy use is only 1.3%.

Table 12-2. Some selected literature values for specific energy consumption of rail transport.

Type of train Energy consumption [kWh/seat-km]

Occupancy estimated

Reference

Inter City Express (up to 280 km/h)

0.036 46 % (Rozycki et al. 2003)

Grøna toget, high speed

0.036 50-75 % (Lukaszewicz and Andersson 2009)

TGV, France 0.037-0.039 60-88 % (Network Rail 2009) Eurostar 0.041 - (Network Rail 2009) Shinkansen 700, Japan

0.029 - (Network Rail 2009)

Alstom AGV, France (projected)

0.033 - (Network Rail 2009)

AVE, Spain 0.039 - (Network Rail 2009) ICE, Germany - 50 % (Network Rail 2009) High speed, UK (modelled)

- 14-54 % (Network Rail 2009)

High speed 0.037-0.043 40-60 % (Schlaupitz 2008) X 2000, Sweden (up to 200 km/h)

0.0425 40-73 % (SOU 2009:74)

Norwegian average (2007)

0.039 34 % (NSB 2008)

Norwegian average incl. losses (2004)

0.175 [kWh/person-km] - (Toutain et al. 2008)

Norwegian average incl. losses (2004)

0.07 [kWh/tonne-km] - (Toutain et al. 2008)

Cargonet average (2009)

0.06 [kWh/tonne-km] - (Jernbaneverket 2010)

For use in this report a preliminary energy per seat-km equal to the Norwegian average 0.039 kWh/seat-km is used, which is close to the average of the reported values in Table 12-2.

Occupancy rates

Table 12-2 provides an overview of estimated and reported figures for occupancy rates. Specific occupancy rates will be provided for Phase 3 by project partners, but literature



figures are given here for purpose of discussion and to put numbers in context [WP Link no. 2, see section 10.4].

Occupancy rates, or load factor, vary from 34% for Norwegian average to almost 90 % for the French TGV. The Norwegian occupancy figure represents an average for all rail operations, including local traffic. There is reason to believe that the occupancy rate is higher for long distances. The Swedish X 2000 reported occupancy rates of 40% after start-up in 1991, rising to 50% after introducing 2nd class tickets and up to 73% after stronger price differentiation based on demand.

As a preliminary estimate of the occupancy the Norwegian average for 2007 of 34% is used. This includes regional traffic around Oslo and one can expect occupancy rates to be significantly higher on the long distance travels.

Freight transport

It is uncertain whether high speed rail lines may be used for freight to a substantial degree, or if this will cause too many disturbances due to the high differences in speed. However, the introduction of a separate high speed rail infrastructure system is expected to open capacity in the existing network, giving an opportunity to transport more freight on rail instead of on trucks. As for passenger transport, the energy consumption for freight trains is expected to be provided per corridor by partners in the project [WP Link no. 18, see section 10.4].

Domestic freight transport (measured in tkm) is currently dominated by road and sea transport (excl. transport of oil), as shown in Figure 12-1. Rail transport amounts to 7%, compared to 47% and 46% by road and sea, respectively, meaning most land based freight is transported by road (Monsrud 2009).

Figure 12-1. Norwegian domestic freight in tonne-km (Monsrud 2009).



However, these figures also include short-distance transport. For long-distance freight transport the situation is different. Freight transport from Oslo to Trondheim and Stavanger is almost equally shared between road and rail, with slightly more for road-going transport, while more than two third of land based freight is transport by rail from Oslo to Bergen. For even longer distances like Oslo-Bodø and Oslo-Narvik, rail transport dominates by 80-90% share of the freight transport work (Nasjonale transportetater 2008).

12.2 Road rolling stock and operation As a focus was placed on passenger transport in this study, the two types of rolling stock examined in detail were private passenger cars and buses. However, road based freight for long haul transport distances by truck is also included and adapted to Norwegian conditions.

Road transport covers a substantial part of the passenger transport between the large cities. Between 21 and 61 % of all travel were done with cars in 2005 (Denstadli 2006). In addition between 3 and 15% were done by bus transport.

Sources in this chapter include manufacturers’ environmental product declarations (EPD), academic literature and the Ecoinvent database.

12.2.1 Passenger cars

The composition of the Norwegian private passenger car fleet was determined from historic new vehicle purchases data8 as shown in Figure 12-2. A vehicle with median performance from each size class was then selected to represent that class and used to calculate an ‘average car’ using a weighted average of the 2009 sales. The cars generally get heavier as more comfort and safety related equipment become included in the standard package. This is partially offset by the introduction of new technology and materials (IPCC 2007). Also taken into consideration was the composition of the Norwegian private car fleet with regards to the engine type. Although the share of diesel engines in the Norwegian fleet is steadily increasing, as of 2009, the fleet was still dominated by petrol-fuel engines as of 2009, with 70% of the market as shown in Figure 12-3.

8 http://www.ofvas.no/BILSALGET/

http://www.ofvas.no/BILSALGET/



Figure 12-2: Composition of the Norwegian private passenger vehicle fleet by size class in December 2009.

Figure 12-3. Composition of the Norwegian private passenger vehicle fleet by engine type (Statistics Norway9).

9 http://www.ssb.no/emner/10/12/20/klreg/tab-2010-05-11-08.html

http://www.ssb.no/emner/10/12/20/klreg/tab-2010-05-11-08.html



Manufacturing Production impacts for private passenger cars were obtained from manufacturers’ environmental product declarations (EPD). Detailed documentation was obtained particularly from Volkswagen, Mercedes and Ford. The majority of the information found pertains to compact vehicles with manual transmission and internal combustion engines using fossil fuels, although data on a number of hybrid electric, biofuel, natural gas, and fuel cell vehicles were also available. Data were also found that anticipate future manufacturing technology advances, which would thereby reduce overall production emissions. The average studied lifetime for rolling stock ranged from 150 000 to 300 000 km (12-15 years). The majority of the studies found used the CML impact assessment method (CML 2004) to calculate global warming potential. The GHG factors for exhaust components and car related emission profiles are similar to the IPCC 2007 factors used in this project, and have only negligible differences for the climate gas emissions.

The highest contributions to global warming potential from vehicle production were found to be the manufacture of the car body, followed by the engine and chassis (Volkswagen AG ; Mercedes-Benz 2008). The manufacturing process contributes approximately 13% of the total life cycle global warming emissions (Volkswagen AG ; Mercedes-Benz 2006). Energy consumption in the production phase is estimated to represent approximately 13-21% of the total energy consumption over the entire vehicle life cycle (Volkswagen AG ; Mercedes-Benz 2006).

Manufacturing emissions increased nearly linearly with vehicle weight for the passenger cars studied as shown in Figure 12-4. These emissions appeared to be independent of the engine type (diesel versus petrol). Additionally, the making of the vehicle also appeared to have an effect on the production emissions; higher-end makes, such as Mercedes, may include additional features such as electronics and computer systems to the vehicle, adding to the overall manufacturing emissions. While in one case, the manufacturer made a significant improvement in production emissions from one year’s model to the next, generally production emissions remained nearly constant from year to year.

Given the uncertainty of future production technology for cars, it is assumed that for production of vehicles, the same mix of cars as was sold in 2009 forms the basis for all future car production. Hence, further weight increases of cars are not assumed to occur due to emissions restrictions on car sales. However, the option of parameter adjustment for car weight in future scenarios is facilitated in the modeling. The effect of this assumption only has consequences for the emissions in manufacturing of the vehicles. It is assumed that manufacturing has the same emissions per car weight as calculated from a thorough review of published LCA studies on car manufacturing. The average life cycle emissions per kg car to is used to obtain the estimate used in this study.



Figure 12-4. Manufacturing emissions by vehicle weight (MiSA internal review).

Operation Driving emissions, as one might expect, also increase with vehicle weight. Per-kilometre emissions from diesel vehicles were in the range of 60-80% of the petrol driving emissions for vehicles of similar weight. Notable reductions in operational emissions occurred with vehicles fitted with fuel efficiency mechanisms, such as the Mercedes BlueEFFICIENCY and Volkswagen BlueMotion features. Unlike the manufacturing emissions, significant improvements in producer reported driving emissions from year to year (Figure 12-5) were observed. However, large variations were observed in operational emissions within each size class as opposed to with manufacturing, wherein emissions were similar within each size class. Also important is that the producer reported emissions (based on the NEDC) are suspected to under-report actual real-life operational emissions for vehicle operation.



Figure 12-5. Progress of weighted average driving emissions of new sold cars over time. Note the sharp decline from 2006 to 2007, an effect of the introduction of a CO2 tax (Norges Automobil-Forbund).

Basically there are four strategies that can be used to further decrease the emissions from road traffic vehicles (IPCC 2007):

• Reduce weight-, rolling- or air resistance • Increase efficiency of converting fuel into work • Less carbon intensive fuels • Reduce emissions of non-CO2 GHGs from vehicle exhaust and climate control

systems

In the development of scenarios for the future car fleet in Norway, the first two strategies are assumed to be the main strategies for reaching the EU target of 95 g CO2-eq/v-km average by 2020. For the carbon intensity of fuels only a shift toward electric vehicles (fuelled with project specific electricity mix) or plug-in hybrid electric vehicles are considered. This means no biofuels or alternative fossil fuels are considered. The future availability and emissions profile of these fuels is highly uncertain and more research is needed to document the performance of these types of fuels. The majority of emission reductions must come from other measures.

The last reduction strategy is not considered in the scenarios here. The relevance of this simplification is not that high either, given that short lived components (like black carbon) are not included in this study.

Although there are estimates of the current average CO2-emissions and fuel use from the Norwegian passenger car fleet, these are not necessarily applicable to the HSR case as this would involve mostly long distance travels, where the fuel use is lower than average figures, However, in one report Statistics Norway present both average per vehicle emissions figures for 2005 for both diesel and gasoline passenger cars and long distance driving on specific corridors (Toutain et al. 2008). Their 2005 data are used as an estimate of present average



emissions, and the difference in their average and long distance figures is used to arrive at an estimate on how much lower long distance emissions will be in the future, compared to the EU mixed driving targets. Baked into the equation is also a shift from 16% diesel cars in 2005, to a share of about 70% in 2020 (Klima- og forurensingsdepartementet m.fl. 2010). The Statistics Norway fuel use numbers will be used in the model, while emission per fuel will be covered by the Ecoinvent database (Spielmann et al. 2007).

Future target values for average new cars are 95 g/v-km by 2020, and then further reduction to about 90 g/v-km by 2030 (Klima- og forurensingsdepartementet m.fl. 2010). This refers to average emissions for mixed driving. It is mainly long distance driving that is of interest, and this is scaled by the factor obtained from the Statistics Norway study.

Electric vehicles are assumed to have a performance of 0.72 MJ/kg. This is in line with Spielmann et al. (2007), but higher than estimates for the Mitsubishi i-Miev (down to 0.36 MJ/km), the sports car Tesla Roadster (0.63 MJ/km) or the GM EV1 (0.40 kWh/km). The higher number is used under the assumption that future long distance EV will be larger than the present cars. No further future improvement of the performance per km for electric cars is assumed; partially due to the much lower improvement potential, and partially due to an assumption of increasing car size is necessary if it should be used for long distance transport.

Furthermore, a 10 year time lag is assumed between the targets for new cars and actual achieved emissions for the average car. This results in a scenario for future car technologies as shown in Table 12-3. Note that linear scaling is used in the periods between target years.

Table 12-3. GHG emissions estimated for car fleet components on long distance travels (g CO2-eq/v-km).

Vehicle type Present 2030 2040 Post 2040 Average conventional cars

158 (2005) 88 83 83

Plug-in hybrid electric vehicles

Mix of conventional and electric




Electric vehicles 0.72 MJ/v-km 0.72 MJ/v-km 0.72 MJ/v-km 0.72 MJ/v-km

For the modal split between the vehicles, on long distance travels, it is hard to find trustworthy estimates or projections. Future policy and technology development is unpredictable and not decisive for the potential for replacement of the conventional fossil-fuel car fleet. There are some vague targets of having 10% chargeable cars (plug-in hybrids and electric vehicles) by 2020 (Samferdselsdepartementet), but nothingis known about this. Nevertheless, some scenarios are developed for future development of the car fleet. Note that the scenarios may be subject to changes if results from the market study indicate this [WP Link no. 19, see section 10.4].



Table 12-4. Scenarios for the development int the car fleet. Pessimistic/Reference case/Optimistic.

Vehicle type Present 2040 Post 2040 Conventional cars 100/100/100 100/80/30 100/80/30 Plug-in hybrids 0/0/0 0/20/50 0/20/50 Electric vehicles10 0/0/0 0/0/20 0/0/20

Occupancy/ Load factor As for all the other transport modes, the load factor plays an important role. In Norway, the load factor for car transport varies considerably between different types of travel and distances (Vågane 2009). The load factors found by the national travel survey are kept constant through the evaluation period, as shown in Figure 12-6 but the option of changing this parameter is facilitated if market studies indicate that this may change in the future.

Figure 12-6. Load factors for long distance car travels in 2005, passenger per vehicle (Vågane 2009).

10 Requires radical battery improvements for long distance travels



Figure 12-7. Car emissions as a function of weight (MiSA internal review).

End-of-life The end-of life (scrapping) emissions for car production are included in the production figures. The majority of the literature surveyed assumes a very high recycling rate (over 90%) in the end-of-life phase.

12.2.2 Bus services

Manufacturing Information regarding production emissions in the manufacturing process of buses was limited. Data were obtained from a manufacturer environmental product declaration (Volvo 2006), which is the model used for the Ecoinvent process for bus manufacture. As with some of the other processes entered in SimaPro, the Ecoinvent process was adapted to allow flexibility in results comparisons and sensitivity analyses. When documented, the operational lifetime of the buses studied was assumed to be 1 000 000 km.

In the Volvo EPD (2006), the bus manufacturing process was found to contribute nearly 20% to the life cycle impacts of the bus, although nearly 27% (by weight) of the materials used were derived from recycled resources. Approximately 130 MWh of energy is used to produce the Volvo bus, of which 23 MWh is electricity.



Operation As for passenger transport, Statistics Norway has figures for fuel consumption on specific long distance corridors in Norway. Based on the numbers for Oslo-Bergen and Oslo-Trondheim, an average emission of 835 g CO2-eq. per v-km is found. The buses are assumed to have 45 seats and 70% occupancy [WP Link no. 20 and 21, see section 10.4].

Buses are assumed to experience about half of the relative improvement in the future performance per vehicle-km as for long distance travel in conventional cars. A significant share of the improvement in cars is expected from a shift toward more diesel cars. For buses, the fleet is already diesel. This means the 2040 estimate for bus transport is 616 g CO2-eq.per v-km. A linear transition is assumed toward this performance, and a fixed performance post 2040.

The Statistics Norway fuel use numbers will be used in the model, while emission per fuel is covered by the Ecoinvent database (Spielmann et al. 2007).

End-of-life The same inventory as contained in the Ecoinvent database (Spielmann et al. 2007) is used for the end-of-life phase of buses.

12.2.3 Road freight

The roads are also used for freight, and an introduction of a high speed rail line my cause shifts in the freight mode fractions in Norway, either by allowing freight trains to use the high speed rail line, or by freeing up capacity in the existing rail network. For road freight the inventory in Ecoinvent is used with regard to rolling stock manufacturing and amount of infrastructure use. Infrastructure use is linked to tonne-km (tkm) of transport work, and with infrastructure use modelled according to inventory for Norwegian road construction and operation. Fuel use figures are obtained from Statistics Norway (Toutain et al. 2008). The fuel use numbers from Statistics Norway are corridor specific for long distance transport between some Norwegian cities. Average figures for fuel use based on these reported numbers will be used. Figures for large lorries (NO: vogntog) will be used as 89% of all road freight in Norway was performed by large trucks in 2004 (Rideng 2005). For the long haul corridor transport this share might be even larger.

The emission per tonne-km from Statistics Norway are on the lower side of what is reported in Ecoinvent (Spielmann et al. 2007) and also lower than the average macro based numbers reported by Statistics Norway. This difference is assumed to be an effect of the average numbers including a larger fraction of city driving, while the micro based figures from Statistics Norway reflect long haul fuel use. Freight transport has significantly higher CO2- emissions per tkm within city areas. However, the statistical basis of the micro based numbers from Statistics Norway is rather thin on a corridor basis, so the numbers are averaged to produce one number for the emissions per tonne-km long haul freight in Norway. The average utilisation of 58,4% (by weight, 85% by volume/FBV) reported in Toutain et al. (2008) is used. The utilisation is kept as a parameter that can be subject to future changes if indicated by the market studies [WP Link no. 22, see section 10.4]. The base case scenario is however that the utilisation remains constant throughout the assessment period. For combustion of diesel and emissions from diesel production the numbers in Ecoinvent (Spielmann et al. 2007) are used. For freight this results in direct emissions of 44 g CO2-



eq./tonne-km with 100% utilisation and 76 g CO2-eq./tonne-km at the given average utilisation.

The same future improvement in performance per tonne-km is assumed for freight trucks as for buses.

12.3 Air flying stock and operation 12.3.1 Flying stock

For the construction of aircraft limited data is available, probably due to the relatively large importance of operation in aviation. Ecoinvent gives some estimates for the construction of an Airbus aircraft. This includes a (very) simplified bill of materials as well as (detailed) resource use and direct emissions from the manufacturer.

The lifetime performance of the aircraft is assumed to be the same as in Spielmann et.al. (2007).

12.3.2 Operation

For the operation of aircraft there is more data available since this is by far the most important life cycle phase in aviation. Aircraft operation can be split into different modes (Watterson et al. 2004):

• Landing-take-off-cycle (LTO) o Taxi-out o Hold o Take-off roll o Initial climb o Climb-out o Approach o Landing roll o Taxi-in o APU

• Cruise

All of these modes have different characteristics, fuel use patterns, and potentials for future improvements. Several studies give emission estimates for these phases (European Environment Agency 2009), although emissions factors depend on characteristics of each country, flight type or airport. For the LTO cycle it is quite surprising that taxi in and -out represent almost half of the fuel use in the LTO cycle. However, it is not certain this is the case for domestic flights in Norway.

The European Environment Agency (2009) publishes a handbook on how to produce emissions statistics for the various sectors in the economy. They describe 3 different approaches for aviation Tier 1, 2 and 3 methods. This is similar to the method described by the IPCC guidelines for emissions inventories (IPCC 2006).

The fuel use and emissions for each of these phases of a flight should ideally be modelled and subject to scenario development over time. For this assessment a more simplistic approach is chosen. Discussions with the Norwegian airliner SAS indicate that splitting up



the flights into detailed phases is unnecessary if the outcome is total emissions per passenger-km at a given distance. Fuel use estimates from the SAS aviation emissions calculator (SAS group 2010) are preferred instead. These figures are relatively robust; the method is based on a hybrid of the tier 2 and tier 3a methods (Hafstad 2007) and is tested on an annual basis against empirical figures. The difference between the model result and actual fuel consumption is generally less than 2-3% (SAS group, personal communication).

This approach is therefore assumed as the best choice for domestic emissions from aviation. As we move towards the future, scenarios for fuel consumption on new aircrafts will replace the SAS-figures.

Fleet composition assumptions The current fleet between the big cities in Norway is dominated by the Boeing 737. A fleet is constructed, consisting of Boeing 737-500 representing old technology, 737-700 representing the present technology and 737-800W as “new” technology. A “next generation” category is introduced in addition to account for future improvements in fuel efficiency. Table 12-5 shows the present fleet composition.

While the “next generation” category is allowed to be improved in scenario development, the 500s and 700s and 800Ws remain static until they have been phased out in the model. For aircraft technical lifetimes 40 yrs is used, but they are assumed to live only 25 yrs in the operation of Norwegian operators.

Table 12-5. Present fleet composition (2010).

Aircraft technology Share of fleet Time to phase out (yrs) Old 28 % 10 Present 36 % 20 New 36 % 25 Next generation 0 % N/A

For future scenarios of fuel use per seat-km (the “Next generation” category) it is hard to make qualified assumptions. The industry itself has high estimates for their emissions reduction potential, although some of this is due to assumed improvements in routing (applies more to crowded international airspace) and use of biofuels. In addition the improvement is expected from reduced fuel use per km travelled. Biofuels are suggested not to be used in any of the scenarios for air and road transport, as the variation among these and the future of biofuels is highly uncertain11.

Chapman (2007) estimates the improvement potential of aviation to be limited, while the IPCC foresees a significant reduction in the fuel use per seat-km in new aircraft, although the industry total changes slowly due to the long life time of the aircraft (IPCC 2007). The IPCC estimates an average improvement in new aircraft designs of 0.7% per year in the period from 1997 to 2050(IPCC 2001b). A significant portion of the improvements is in aerodynamics, which has lower effect on shorter flights (the LTO has a larger fraction of fuel use) than on longer flights. The 0.7% per year improvement toward 2050 (~45% reduction by 2050 compared to 1997) may therefore be an overestimate for domestic short haul flights.

11 We make the same assumption for cars.



For the fuel use scenarios the Boeing 737-500 represents the basis for new 1997 technology. The IPCC estimate is regarded as an optimistic estimate of the improvements in fuel use per seat-km; some of the potential requires extreme design changes compared to the present aircraft designs. For comparison, an alternative pessimistic scenario is used where fuel efficiency of new aircraft improves by only 10% toward the end of the assessment period compared to present new technology (Boeing 737-800W) and a “realistic” scenario with 20% reduction (own assumption).

Cabin factor The domestic average cabin factor for SAS in Norway was 66% in 2008 (SAS 2009). The cabin factor between the big cities is, however, higher (SAS, personal communication). The exact figures are subject to confidentiality issues, but indications are that present cabin factors are in the range 75-80%. This may also be regarded close to the theoretical average maximum level that can be expected under normal operational conditions for domestic flights between the large cities. Unless otherwise indicated from other work packages in the project, a long term cabin factor of 75% will be used for aviation.

Emissions per seat-km For the three chosen types of aircraft to represent the fleet, distance specific fuel use factors per seat-km are collected from the SAS emissions calculator (SAS group 2010). The factors are presented in Figure 12-8.

Figure 12-8. Example of corridor- and aircraft specific fuel use per seat-km from the SAS emissions calculator.

In general there is a difference between the shortest (great circle) distance and the distances actually travelled. This problem is larger where the airspace is crowded, and for Norway assuming greater circle distances provides high enough accuracy (SAS, personal communication), especially since the fuel use data is verified by empirical data.



For aviation there is also an ongoing debate whether short lived climate effects should be modelled and included in LCA studies. Many studies show the importance of short lived climate components on various time scales (Shine et al. 2007; Berntsen and Fuglestvedt 2008; Fuglestvedt et al. 2008; Fuglestvedt et al. 2010). Contrails and induced clouds strongly affect the short term radiative forcing of aviation activities. In a longer time perspective the effect of CO2 with its long lifetime becomes more important. Ideally these effects should be included in an analysis, but the concept should be employed consistently across all transport modes and for all short lived effects. The methodology for this is still immature, hence short lived components will not be considered.

For aviation emissions it is recorded whether emissions occur in the stratosphere or at ground level, although at a simplistic level. The same emissions splits are used as in (Spielmann et al. 2007). This allows for later inclusion of more advanced evaluation methods.

12.3.3 Maintenance

There is limited information on the environmental impacts of aircraft maintenance, but it is known that substantial resources are put into this due to safety issues. Chester (2008a) estimates about the same emissions from maintenance as for construction of the aircraft over the aircraft life. This is adopted in the model by consuming 1/(aircraft lifetime) of new aircraft per year.

13 MAIN FINDINGS

13.1 Lessons from other studies In a review of published studies for high-speed rail in Europe, the following summarises the main conclusions that were made:

• Comprehensive system boundaries are required for proper evaluation of HSR in the Norwegian context, with regards to infrastructure, rolling stock and operations

• Comparison with alternative transport modes requires that same or similar system boundaries are used for all modes

• Emissions from electricity production may be highly significant, even at low fractions of fossils in the electricity mix

• Scandinavian HSR concepts use relatively clean electricity for operation, implying that infrastructure development contributes the larger share of the greenhouse gas emissions per passenger

• Occupancy of seats on HSR corridors, and the degree of use of HSR infrastructure, controls the greenhouse gas emissions per passenger in Norway. Energy use per seat may be modelled with good detail, but energy use per passenger in HSR depends on corridor-specific factors

• Completed studies assume very different settings for the most important variables, leading to diverging results for seemingly same assessment



13.2 Solution: component-based emissions inventory

Model implementation

Based on the lessons drawn from reviewed studies, it is found that an emissions model for the various corridor alternatives to be assessed in Phase 3 needs to allow multiple infrastructure compositions, market situations and energy supply scenarios. It is proposed to solve this by a component-based emissions inventory, established through use of standardised life-cycle assessment methods.

The following approach is used to ensure a flexible yet transparent model:

• Use of a commonly accepted model approach: life-cycle assessment • Consistent use of database values for emissions: Ecoinvent for all background

processes • Norwegian-based emissions modelling for construction of rail and road, given the

high importance for infrastructure to the total emissions estimate for HSR • Unit process detail implemented in a software for LCA: SimaPro • Parameter options for wide scenario analysis • Equivalent coverage for all competing transport modes, to properly reflect the effect

of market transfer from car, bus and air transport for all HSR concepts

Inputs from the complementing work groups in NHSRA will be implemented in the emissions model in Phase 3, together with the alignment proposals from physical planning for corridor alternatives.

Environmental assessment time

Relevant environmental assessment guidelines propose a 60 year assessment time. Some major components have technical lifetimes up to 100 years. If HSR concepts are developed for Norway, they should have an impact for the national transport system for a long time into the future. An environmental assessment time up to 100 years is therefore proposed, although market information may not be made for the entire period.

Emissions in construction are evaluated separate, to appear in the period up to first year of operation. Maintenance inputs, operational requirement and rolling stock manufacture emissions are annualised based on technical lifetime estimates.

Spatial and temporal distribution of emissions

Emissions from infrastructure, rolling stock and operation of rail, road and air transport systems are split between national emission and emissions appearing abroad. This allows easy estimation of the effect on national greenhouse gas emissions with and without development of HSR concepts.

Scenario considerations are systematically incorporated into the model, for all transport modes through the assessment period.



Norwegian inventory sources selected to describe rail and road infrastructure

Inventories for the transport infrastructure components are compiled from various sources. The main sources for road and rail infrastructure systems are found in reports for the Norwegian transport authorities (road: Statens Vegvesen; rail: Jernbaneverket). These projects have been carried out specifically to evaluate the environmental profile of infrastructure components in the Norwegian context, and are therefore considered the most relevant source for inventories to describe the relevant infrastructure for the task here.

13.3 Phase 3 This chapter forms the premises for evaluation of corridors for different HSR concepts regarding climate related effects. It fulfils the goal and scope phase of life-cycle assessment, and partly also the inventory stage. Several links are identified to the complementing working groups in the assessment project, where data gaps will be filled by input for specific HSR concepts in Phase 3. The data gaps are identified and listed throughout the report, and summarised in a separate section.

Main factors are expected to be within the market modelling and physical planning, although identified also in the other groups. Energy modelling is a separate task within the environmental work package (WP6), and is discussed elsewhere in this report.

A systems analysis such as the Norwegian HSR assessment relies on multiple mutually dependent factors, and it is therefore expected that several iterations must be made for each of the corridors. Concluding results regarding the climate-related environmental performance of high-speed rail in Norway may not be drawn before venturing into Phase 3.



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APPENDIX A: LEGISLATION AND REGULATIONS RELEVANT TO LANDSCAPE, ENVIRONMENT AND WATER

A 1 Landscape

A 1.2 Den europeiske landskapskonvensjonen

Landskapskonvensjonen ble ratifisert i Norge i 2004. Den gir føringer for planlegging og forvaltning av landskap. Hovedmålet er å sikre representative og sjeldne nasjonallandskap, verne og pleie stedskarakter og identitet, samt unngå å forringe rikdommen og mangfoldet av landskapstyper i Europa. Landskapskonvensjonen gjelder alt landskap, også hverdagslandskapet og fremhever landskap som leveområder for mennesker. Landskapet betyr mye for folks livskvalitet og helse og for utvikling av gode livskraftige lokalsamfunn. Landskapet er i beskrevet i konvensjonen både en verdi som skal forvaltes og en ressurs som kan utvikles og gi grunnlag for ny verdiskaping.

A 1.3 Stortingsmelding nr. 26 (2006-2007)

Regjeringens miljøpolitikk og rikets miljøtilstand viser til landskapskonvensjonen og dens formål. En viktig arealpolitisk føring gitt i denne stortingsmeldingen, er at miljøkvaliteter i landskapet skal bevares og styrkes gjennom økt kunnskap om verdier og bevist planlegging og arealpolitikk.

A 1.4 Stortingsproposisjon nr. 1S (2009-2010)

Det overordnete resultatmål for landskap i arealplanleggingen er formulert slik i MDs proposisjoner: helhetlig planlegging og arealforvaltning skal bidra til beærekraftig lokal og regional utvikling og sikre landskaps- natur- og kulturverdier.

A 1.5 Naturmangfoldloven (Lov 19. juni 2009 om forvaltning av naturens mangfold.)

Naturmangfoldloven er den mest sentrale loven innen naturforvaltning. Loven regulerer forvalting av arter, områdevern, fremmede organismer, utvalgte naturtyper, og den tar vare på leveområder for prioriterte arter

Kapittel fem om områdevern fastsetter generelle mål for områdevern og regulerer saksbehandling og erstatning som følge av opprettelse av verneområder. Naturmangfoldloven angir fem vernekategorier for områdevern:

• Nasjonalparker § 35 • Landskapsvernområder § 36 • Naturreservater § 37 • Biotopvernområder § 38 • Marine verneområder § 39

http://www.dirnat.no/naturmangfoldloven/

A 1.6 Plan- og bygningsloven (Lov 2008-06-27 nr. 71: Lov om planlegging og byggesaksbehandling.)



Plan- og bygningsloven inneholder regler for arealplanleggingen i Norge og er derfor sentral i miljøforvaltningen.. Plan- og bygningsloven har som formål å fremme en bærekraftig utvikling til beste for den enkelte, samfunnet og framtidige generasjoner. Loven fremhever kvaliteter i landskapet og vern av verdifulle landskap som en oppgave og et hensyn som planlegging etter loven skal ivareta jf§ 3-1 b. Lovens bestemmelser gir flere virkemidler enn tidligere til å ivareta landskap i planer, gjennom bruk av hensynssoner, arealformål og bestemmelser, og gjennom konsekvensutredninger.

http://www.lovdata.no/all/hl-20080627-071.html

Forskrift om Konsekvensutredninger (2009-06-26 nr 855)

Hovedregelen er at alle regionale planer og alle kommuneplaner med retningslinjer, eller med rammer for fremtidig utbygging, skal konsekvensutredes for å få vurdert planens virkning for miljø og samfunn.

http://www.lovdata.no/for/sf/md/xd-20090626-0855.html

A 1.7 Kulturminneloven

I Kulturminneloven finnes to hovedtyper fredning:

• fredning ved lov (automatisk fredning) • fredning ved vedtak (vedtaksfredning)

Fredet kulturmiljø: Områder fredet av kongen for å bevare områdets historiske verdi. Fredningen skjer etter vedtak med bakgrunn i Kulturminneloven §20, vedtaket må tinglyses

I plan- og bygningsloven oppnås vernestatus gjennom regulering til hensynssone bevaring.

Riksantikvaren har utarbeidet to veiledere til bruk i forvaltningsarbeidet: Kulturminner og kulturmiljøer. Plan- og bygningsloven » Kulturminne og kulturmiljø i konsekvensutgreiingar »

Kulturlandskap: Landbruks- og matdepartementet og Miljøverndepartementet har fra Riksantikvaren, Direktoratet for naturforvaltning og Statens landbruksforvaltning mottatt forslag på 20 utvalgte kulturlandskap i jordbruket som skal sikres en særskilt forvaltning.

http://www.slf.dep.no/iKnowBase/Content/10189/RAPPORT%20DES-08%20-%20TILRÅDING%20TIL%20LMD%20OG%20MD.PDF

A 2 Natural environment

A 2.1 Internasjonale konvensjoner som omhandler biologisk mangfold

Norge har underskrevet flere internasjonale avtaler som har som mål å sikre bedre bevaring av arter og/eller deres leveområder:

http://www.lovdata.no/all/nl-19780609-050.html

http://www.lovdata.no/all/nl-19850614-077.html

http://www.riksantikvaren.no/?module=Files;action=File.getFile;ID=3507

http://www.riksantikvaren.no/?module=Files;action=File.getFile;ID=3506





• Konvensjonen for biologisk mangfold er en global avtale om vern og bærekraftig bruk av alt biologisk mangfold. Den omhandler dessuten rettferdig fordeling av godene ved bruk av genetiske ressurser.

• Bern-konvensjonens formål er å verne om europeiske arter av ville dyr og planter og deres levesteder.

• Bonn-konvensjonen er en global avtale om beskyttelse av trekkende arter av ville dyr som regelmessig krysser nasjonale grenser.

• CITES-konvensjonen er en global avtale der formålet er å regulere den internasjonale handelen med ville dyr og planter som står i fare for å bli utryddet.

• Ramsar konvensjonen er en global avtale med spesiell fokus på våtmarksområder med internasjonal betydning.

http://www.miljostatus.no/Tema/Naturmangfold/Internasjonale-konvensjoner/

A 2.2 Stortingsmelding nr. 42 (2000-2001) Biologisk mangfold – sektoransvar og samordning

Stortingsmelding 42 (2000-2001) gir strategiske mål og nasjonale resultatmål på tvers av sektorer. Stortingsmeldingen slår bl.a. fast at inngrep skal unngås i truede naturtyper, og at viktige økologiske funksjoner skal opprettholdes i hensynskrevende naturtyper. I samferdselsdepartementets kapittel står det at ved etablering og drift av samferdselsanlegg søker samferdselsmyndighetene å unngå nye inngrep i sårbare naturtyper som for eksempel strandsoner og elvedelta, samt andre områder av stor verdi for biologisk mangfold.

A 2.3 St.meld. nr. 24 (2003 – 2004) Nasjonal transportplan 2006–2015

I stortingsmelding 24 (2003 – 2004) står det bl.a.: ”Samferdselsmyndighetene vil søke å unngå inngrep i verneområder, større sammenhengende naturområder og sårbare natur- og kulturmiljøer. Eventuelle skadevirkninger av inngrep skal tillegges økt vekt ved trasevalg, fleksibel utforming av anlegg og avbøtende tiltak. For å sikre ønsket effekt bør avbøtende tiltak langs veg- og jernbanenettet i mange tilfeller inngå i en større plan for en art eller et område”…. ”Ved planlegging av nye anlegg gjennomføres til dels omfattende undersøkelser av biologisk mangfold, ofte som en del av en lovpålagt konsekvensutredning”.

A 2.4 Stortingsmelding nr. 26 (2006-2007)

I stortingsmelding nr 26 er det formulert strategiske mål for Naturens mangfold og friluftsliv. Her står det bl.a.:

”Naturen skal forvaltes slik at arter som finnes naturlig sikres i levedyktige bestander, og slik at variasjonen av naturtyper og landskap opprettholdes og gjør det mulig å sikre det biologiske mangfoldet fortsatte utviklingsmuligheter….

…. Norge har som mål å stanse tapet av biologisk mangfold innen 2010”.

For underområde : ”Bærekraftig bruk og beskyttelse” er det listet opp følgende punkter som nasjonale resultatmål:

• Et representativt utvalg av norsk natur skal vernes for kommende generasjoner. I truede naturtyper skal inngrep unngås,og i hensynskrevende naturtyper skal viktige økologiske funksjoner opprettholdes.

http://www.miljostatus.no/no/Tema/Naturmangfold/Internasjonale-konvensjoner/Konvensjonen-om-biologisk-mangfold/

http://www.miljostatus.no/no/Tema/Naturmangfold/Internasjonale-konvensjoner/Bernkonvensjonen-/

http://www.miljostatus.no/no/Tema/Naturmangfold/Internasjonale-konvensjoner/Bonnkonvensjonen-/

http://www.miljostatus.no/no/Tema/Naturmangfold/Internasjonale-konvensjoner/-CITES---konvensjonen-/

http://www.miljostatus.no/no/Tema/Naturmangfold/Internasjonale-konvensjoner/Ramsarkonvensjonen-/

http://www.miljostatus.no/Tema/Naturmangfold/Internasjonale-konvensjoner/



• Kulturlandskapet skal forvaltes slik at kulturhistoriske og estetiske verdier, opplevelsesverdier, biologisk mangfold og tilgjengelighet opprettholdes.

• Jordressurser som har potensial for matkornproduksjon, skal disponeres slik aten tar hensyn til framtidige generasjoners behov.

A 2.5 Naturmangfoldloven (Lov 19. juni 2009 om forvaltning av naturens mangfold.)

(Se kap.A.1.5.)

A 2.6 Plan- og bygningsloven (Lov 2008-06-27 nr. 71: Lov om planlegging og byggesaksbehandling.)

(Se kap. A 1.6.)

A 3 Water resources

A 3.1 Vannrammedirektivet

EU vedtok i 2000 et direktiv om vannforvaltning for å sikre en felles tilnærming, målsetting, prinsipper og sett av forholdsregler for beskyttelse av overflatevann og grunnvann innenfor EU. Direktivet er en del av EØS-avtalen, og blir i Norge implementert gjennom ”Forskrift om rammer for vannforvaltningen (vannforvaltningsforskriften)” av 15.12.06 med ikrafttredelse fra 1.1.07 (Miljøverndepartementet, 2006) med endringer av 23.12.2009. Hovedhensikten med vanndirektivet er en helhetlig, nedbørfeltorientert vannforvaltning. Det skal settes opp miljømål for vannforekomstene og disse skal oppfylle kravene til ”god økologisk status”. Det skal tas hensyn til egnethet for ulike brukerinteresser i nedbørfeltet. Koordinering av arbeidet med å implementere forskriften er lagt til en vannregion som ledes av én fylkeskommune (fra 01.01.10).

A 3.2 Vannforvaltningsforskriften

Formålet med denne forskriften er å gi rammer for fastsettelse av miljømål som skal sikre en mest mulig helhetlig beskyttelse og bærekraftig bruk av vannforekomstene. Tilstanden i overflatevann skal beskyttes mot forringelse, forbedres og gjenopprettes med sikte på at vannforekomstene skal ha minst god økologisk og god kjemisk tilstand…., og når det gjelder kjemisk tilstand også oppfylle kravene i forurensningsforskriften.

A 3.3 Lov om vassdrag og grunnvann

Denne lov har til formål å sikre en samfunnsmessig forsvarlig bruk og forvaltning av vassdrag og grunnvann. Som vassdrag regnes alt stillestående eller rennende overflatevann med årssikker vannføring, med tilhørende bunn og bredder inntil høyeste vanlige flomvannstand. …. Som vassdrag regnes også vannløp uten årssikker vannføring dersom det atskiller seg tydelig fra omgivelsene.

Ingen må iverksette vassdragstiltak som kan være til nevneverdig skade eller ulempe for … allmenne interesser i vassdraget eller sjøen, uten at det skjer i medhold av ….



Konsesjon fra vassdragsmyndighetene. A vassdragstiltak: vassdragsanlegg og alle andre tiltak i vassdraget som etter sin art er egnet til å påvirke vannføringen, vannstanden, vassdragets leie eller strømmens retning og hastighet eller den fysiske og kjemiske vannkvaliteten på annen måte enn ved forurensning. B vassdragsanlegg: bygning i eller over vassdrag.

Vassdragsmyndigheten kan fastsette kvalitetsmål for vassdrag, bl.a. om vannføring, stoffinnhold og artsforekomst i vassdraget. Kvalitetsmål for forurensende stoffer fastsettes etter forurensningsloven. Langs bredden av vassdrag med årssikker vannføring skal det opprettholdes et begrenset naturlig vegetasjonsbelte som motvirker avrenning og gir levested for planter og dyr.

Vassdragsmyndigheten kan fastsette i forskrift eller ved enkeltvedtak at det ikke trengs konsesjon etter vassdragsloven for tiltak som:

• A må ha tillatelse etter lov om laksefiske og innlandsfisk • B må ha tillatelse etter forurensningsloven (§11) • C Må ha dispensasjon fra vernevedtak etter naturvernloven • D er tillatt i reguleringsplan eller bebyggelsesplan etter PB-loven • E er godkjent med hjemmel i skogbrukslova (§7) eller jordlova (§11)

A 3.4 Lov om vern mot forurensninger og avfall med tilhørende forskrifter

Denne loven har til formål å verne det ytre miljø mot forurensning og å redusere eksisterende forurensning, å redusere mengden avfall og å fremme en bedre behandling av avfall.

Loven skal sikre en forsvarlig miljøkvalitet, slik at forurensninger og avfall ikke fører til helseskade, går ut over trivselen eller skader naturens evne til produksjon og selvfornyelse. Når det er fare for forurensning i strid med loven, eller vedtak i medhold av loven, skal den ansvarlige for forurensningen sørge for tiltak for å hindre at den inntrer. Har forurensningen inntrådt skal han sørge for tiltak for å stanse, fjerne eller begrense virkningen av den. Forurensningsmyndigheten kan etter søknad gi tillatelse til virksomhet som medfører forurensning.

A 3.5 Plan- og bygningsloven med tilhørende forskrifter

Planlegging etter loven skal bidra til å samordne statlige, regionale og kommunale oppgaver og gi grunnlag for vedtak om bruk og vern av ressurser.

I 100-metersbeltet langs sjøen og langs vassdrag skal det tas særlige hensyn til natur- og kulturmiljø, friluftsliv, landskap og andre allmenne interesser. For områder langs vassdrag som har betydning for natur-, kulturmiljø- og friluftsinteresser skal kommunen i kommuneplanens arealdel etter § 11-11 nr. 5 fastsette grense på inntil 100 meter der bestemte angitte tiltak mv ikke skal være tillatt.

I tillegg kan det opprettes hensynssoner rundt drikkevannskilder for beskyttelse av kilden og influensområdet.

§ 20-1 Tiltak som krever søknad og tillatelse:

• A Oppføring, tilbygging, med mer av bygning, konstruksjon eller anlegg



• B vesentlig endring eller reparasjon av tiltak nevnt under A • E riving av tiltak nevnt under A • F oppføring, endring eller reparasjon av bygningstekniske installasjoner • J plassering av midlertidige bygninger, konstruksjoner eller anlegg • K vesentlige terrenginngrep

Se for øvrig A1.6.

A 3.6 Naturmangfoldloven

Se for øvrig F1.5.

A 3.7. Forskrift om vannforsyning og drikkevann (Drikkevannsforskriften)

Forskriften har som formål å sikre vannforsyning av drikkevann i tilfredsstillende mengde og av tilfredsstillende kvalitet, herunder sikre at drikkevannet ikke inneholder helseskadelig forurensning av noe slag og for øvrig er helsemessig betryggende. Det er satt kvalitetskrav til drikkevann. Overskridelse av grenseverdier for kvalitetskrav vil utløse tiltak. Det er delt inn i ulike tiltakstyper (A, B og C) hvorav tiltakstype A krever at det umiddelbart iverksettes tiltak samt at tilsynsmyndigheter varsles.

Drikkevannforskriften er harmonisert med EUs drikkvannsdirektiv.



APPENDIX B ENERGY

B1 Specific energy consumption values

ICE 3

Figure B-1. ICE 3 specific energy consumption

ICE 3 Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 -51.34 -39.65 -26.61 -13.48 7.49 47.31 78.36 96.01 108.60 124.66 138.33

300 -56.28 -44.00 -31.16 -18.06 1.59 41.52 78.36 96.01 108.60 124.66 138.33

280 -59.35 -47.16 -33.96 -21.17 -1.38 37.64 78.36 96.01 108.60 124.66 138.33

250 -63.54 -50.49 -37.78 -24.71 -5.34 32.79 74.09 96.01 108.60 124.66 138.33

220 -66.60 -53.79 -41.07 -27.98 -8.54 28.76 69.55 94.62 108.60 124.66 138.33

Table B-1. ICE 3 specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


330 300 280 250 220



ICE T

Figure B-2. ICE T specific energy consumption

ICE T Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a



250 -63.42 -50.94 -38.57 -25.88 -5.89 33.64 69.71 92.38 111.18 127.48 145.97

220 -64.98 -52.82 -40.00 -27.29 -7.36 31.70 69.71 92.38 111.18 127.48 145.97

Table B-2. ICE T specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


250 220



TGV POS

Figure B-3. TGV POS specific energy consumption

TGV POS Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 -52.69 -39.56 -24.88 -10.39 13.52 57.92 95.93 112.34 125.72 139.79 157.26

300 -57.00 -43.26 -29.08 -14.49 8.49 52.70 95.93 112.34 125.72 139.79 157.26

280 -61.02 -47.03 -32.93 -18.60 2.95 47.41 92.21 112.34 125.72 139.79 157.26

250 -66.57 -52.26 -38.22 -23.90 -2.30 40.55 86.05 112.34 125.72 139.79 157.26

220 -70.61 -56.82 -42.41 -28.42 -6.94 34.85 79.73 107.30 124.34 139.79 157.26

Table B-3. TGV POS specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


330 300 280 250 220



Talgo 250

Figure B-4. Talgo 250 specific energy consumption

Talgo 250 Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]




250 -54.20 -40.67 -26.95 -12.67 7.82 48.26 83.31 101.00 113.86 130.29 147.65

220 -60.15 -46.24 -32.24 -18.36 2.59 41.96 82.22 101.00 113.86 130.29 147.65

Table B-4. Talgo 250 specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


250 220



Talgo 350

Figure B-5 Talgo 350 specific energy consumption

Talgo 350 Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 -33.91 -22.00 -9.93 2.33 22.18 55.99 82.95 95.32 105.99 116.21 127.15

300 -39.81 -27.89 -15.88 -3.86 15.53 49.18 82.95 95.32 105.99 116.21 127.15

280 -43.42 -31.70 -19.71 -7.84 11.33 44.66 78.63 95.32 105.99 116.21 127.15

250 -48.31 -36.64 -24.62 -12.77 5.19 39.04 73.39 94.26 105.99 116.21 127.15

220 -52.49 -40.30 -28.64 -16.76 1.19 34.46 68.86 89.10 103.05 116.21 127.15

Table B-5. Talgo 350 specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


330 300 280 250 220



AGV

Figure B-69. AGV specific energy consumption

AGV Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]

330 -45.28 -34.15 -21.55 -9.41 9.96 43.68 70.49 84.61 95.43 106.99 122.21

300 -49.69 -37.92 -25.89 -13.73 4.01 38.76 70.49 84.61 95.43 106.99 122.21

280 -52.43 -40.59 -28.55 -16.47 1.76 35.47 69.76 84.61 95.43 106.99 122.21

250 -56.16 -43.97 -32.14 -20.05 -1.87 31.36 66.15 84.61 95.43 106.99 122.21

220 -58.66 -46.99 -34.74 -22.97 -4.88 28.06 62.37 83.47 95.43 106.99 122.21

Table B-6. AGV specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


330 300 280 250 220



SJ X2

FigureB-7. SJ X2 specific energy consumption

SJ X2 Track gradient [‰]

-35 -30 -25 -20 -12.5 0 12.5 20 25 30 35

Per

mitt

ed tr

ack

spee

d [k

m/h

]





220 -69.32 -55.67 -41.34 -26.91 -4.06 40.47 81.52 107.79 127.09 144.87 162.20

Table B-7. SJ X2 specific energy consumption values [Wh/seat-km]

-100

-50

0

50

100

150

200

-40 -30 -20 -10 0 10 20 30 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]


220



B2 Running into inclines at Vmax

Elevation difference of 60 m


10 km 60 m 6 ‰

FigureB-8. Energy consumption elevation diff 60 m

0

10

20

30

40

50

60

70

0 5 10 15 20 25 30 35 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]







20 km 120 m 6 ‰


0

10

20

30

40

50

60

70

0 5 10 15 20 25 30 35 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]







30 km 180 m 6 ‰


0

10

20

30

40

50

60

70

0 5 10 15 20 25 30 35 40

Spec

ific

ener

gy c

onsu

mpt

ion

[Wh/

seat

-km

]





APPENDIX C : NOISE FROM ROLLING STOCK. STATE OF THE ART.

C1. Noise sources

General

The noise radiated from a railway line is very complex and the noise contribution from the dominant noise sources will depend on the train speed. In fig. C-1 is shown in which speed intervals the different noise sources are dominant.

Fig. C-1. Relative speed and strength dependence of railway noise sources. (Fodiman 2005).

At very low speeds the traction noise dominates, at higher speeds the rolling noise dominates, and at speeds higher than 200 km/h the aerodynamic noise contributes and increases strongly with the train speed.

Rolling noise

For normal lines in Norway the rolling noise is clearly the dominating noise source. The noise is mainly generated from the irregularities called roughness on the surfaces in the rail and the wheel. The passing of the wheel generates vibration in the rail and in the wheel. The vibration of the surfaces gives pressure fluctuations in the air and sound is radiated. Figure C-2 shows typical contribution from the wheel, the rail and the sleeper on ballasted track. Usually the rail is the main contributor.

Fig. C-2. Typical noise spectrum from railway. From the Harmonoise project. (Fodiman 2005)



The vibration is highest at the resonance frequencies of the wheel, the rail and the sleeper. The most important resonance frequency is the pin-pin resonance in the rail which is the resonance frequency for the rail spanning between the sleepers. This frequency is seen as the maximum value at 1000 Hz in Fig. C-2.

The resonance frequencies in the wheel are normally from 1500 Hz and higher, the wheel therefore is the main sources in the highest frequency region. The resonance frequencies and the noise contribution from the sleepers are in the lowest frequency region below around 400 Hz.

It is the total roughness of the wheel and the rail that is important for the noise radiation. Low noise levels from a railway line are only achieved if the roughness is low in both the wheel and the rail.

The important parameters and remedial actions for the rolling stock concerning rolling noise are listed below. Some values on expected noise reduction are given. These values are for the noise radiation from the wheel. The reduction of the total rolling noise will be less:

- Braking system. The wheel roughness is highly dependent on the braking system. Block braking systems in which there is contact between the rolling tread and the braking material gives much corrugation. This is a big problem in old carriage wagons. Better blocks have been developed, but still the roughness is higher than in disk braked wheels. In high speed trains there is always disk braking systems.

- Number of wheels. The total area for noise radiation increases with the number of wheels. The potential in noise reduction by reducing the number is 1 - 2 dB. A halving of the number of wheels gives 3 dB reduction. However the axle loads will be higher. This may increase the noise from impacts and higher maintenance costs.

- Size of wheel. The resonance frequencies in a small wheel is higher than in a big wheel, the number of frequencies which give audible noise radiation therefore is less. This effect is more important than the effect of the reduced noise radiating area in a small wheel. On the other hand, the contact surface between the wheel and the rail makes a role. When this area is big the shortest wavelength irregularities is not “seen” and the high frequency noise is reduced. A big wheel will give bigger contact area which is beneficial. However totally a small wheel gives less noise.

- Wheel shape. Much research and practical tests have been made in creating low noise wheels. The main effort is to increase the resonance frequencies in the wheel by stiffening in the axial direction. Methods can be to increase the thickness of the web and stiffening of the web by curving the surface. The potential for optimizing the wheel shape can in the order of 3 – 5 dB

- Wheel damping. The vibration response in the wheel, and therefore the noise radiation, is directly dependant on the wheel damping. Different methods have been used in order to increase the wheel damping. The use of constrained layer technique gives good results. This is that a damping material is sandwiched between the web and a stiff plate. Different solutions by using tuned dampers have also been used with success. The potential for noise reduction by damping treatments is up to around 5 dB. In the ICE high speed trains a very god solution for tuned dampers in the wheel are used. The reported noise reduction is even higher than 5 dB. In addition to reduction of rolling noise wheel damping gives considerable reduction of squeal noise.

- Resilient wheels. This is a solution in which there is a rubber element between the tread and the wheel. Resilient wheels are much used in the light suburban trains and in trams. However failure in a resilient wheel in a ICE high speed train was the reason for a tragic



accident in Eschede in Germany. Resilient wheels therefore probably will not be used in high speed trains in the future.

Aerodynamic noise

The aerodynamic noise is mainly created by pressure fluctuations from turbulences. Roughly speaking aerodynamic noise increases with 60 log speed and the rolling noise increases with 30 log speed. The importance of the aerodynamic noise therefore is strongly increasing with increasing speed as seen in Fig. C-3. Moderate deviations from these curves will occur. However the principles that the aerodynamic noise dominates when the speed is very high is well stated.

Fig. C-3. Rolling noise and aerodynamic noise as a function of train speed, v.

The train speed ve for which the aerodynamic noise equals the rolling noise depend on the track. In the Harmonoise reports from 2001-2003 this speed was assumed to be around ve = 250 km/h. However in later references this speed is higher, more around ve = 300 km/h. In Fig. C-4 is shown the noise level as a function of speed that is used in the calculations of

Fig. C-4. From British studies of high speed lines. Day time average noise level (L eq,06-18) at 25 meters. (HS2 project 2010).



the noise level from a future high speed line between England and Scotland. This was based on the measured noise level of currently operated high speed trains (Gautier et al. 2007) and the current noise level requirements for new trains from the European Community (Council Directive 96/48/EC).

The reason to the increase of ve in Fig. C-3 may be because of development of low noise solutions and products on the high speed trains. The rolling stock producers have made considerable amount of work in wind tunnels in order to reduce the aerodynamic noise and the results now have been implemented in the trains.

By using acoustic arrays it is possible to measure which part of the train that is the dominating noise source. In Fig. C-5 is shown measured noise from a train having a speed of 325 Km/h.

Fig. C-5. Measured noise in dBA from a train, speed 325 km/h. (Harmonoise 2002).

The conclusions from the Harmonoise project concerning aerodynamic noise was that the main sources from a high speed train normally is the pantograph and the bogie, particulary the leading bogie. In Fig. C-5 it is not possible to see if the noise from the bogies is rolling noise or aerodynamic noise. Probably both mechanisms contribute. In Fig C-6 it is clearly seen that aerodynamic noise from the front bogie gives higher noise level than the rolling noise because the noise from the latter wheel is much lower.

Fig. C-6. Noise measured from a ICE train, speed 350 km/h (Thompson 2009).

The frequency content in most of the aerodynamic noise sources are below around 500 Hz. Exceptions are tonal noise from vortec sheddings, for instance from tubes in the pantograph. In Norway generally the noise regulations for tonal noise sources are 5 dB lower than for broad band noise. This is because the nuisance for tonal noise is higher and tonal is easier



to detect. Efforts therefore should be made to avoid tonal noise from the high speed trains in Norway.

The most important aerodynamic noise sources and remedial actions are listed below. Some values on expected noise reduction are given. These values are as reduction for the noise radiation from the specific source. The reduction of the total noise will be less:

- Pantograph. The noise from the pantograph is mainly from vortex sheddings behind the tubes and beams. The noise is tonal. The number of pantographs should be as low as possible, and the number of elements and contact strip in each pantograph should be as low as possible. Single arm constructions give reduced noise levels. The cross section of the elements is very important; it is found that elliptical profile is the optimal cross section. The potential for noise reduction is in the order of 10 dB. A conventional and a low noise pantograph are shown in Fig. C-7.

Fig. C-7. (a) Conventional pantograph fitted to early Shinkansen train. (b) prototyp low noise pantograph. (Thompson 2009; Nagawaka 1997).

On the TGV there is a recess for the pantograph so that less of it is in contact with the passing air. However noise was generated in the excess so that there was almost no reduction of the noise.

In the new Chinese train CRH 2 there is noise screening of the pantograph as seen in Fig C-8.

Fig. C-8. Noise screening of the pantograph. From a model of the Chinese train CRH2.



- Front bogie. The bogie is a complicated system, and passing of the air give turbulences and vortex sheddings. The surfaces which meet the air should be as smooth as possible. The potential for noise reduction compared to standard bogies is in the order of 5 dB

- Bogie fairings. In most trains the bogie area is uncovered up to the height of the wheel. In high speed trains bogie covers will reduce the aerodynamic noise from the bogie. The air resistance from this area is considerable reduced as well. Full scale tests on e ETR 500 train gave 3 dB noise reduction and 10 % reduction of running resistance compared to train without fairings (Mancini et al. 2001). Practical aspects as access for maintaining and limited clearance to the wheels makes the solution difficult to implement. However for newly designed stock there are less restrictions than for retrofitting measures.

- Openings between each carriage. Noise is generated in the opening between each carriage. Conventional trains consist of individual carriages resting on two bogies each, articulated trains consist of a fixed position of coaches with consecutive cars resting on shared bogies. Then it is possible to reduce the noise generation from this area. In addition the train weight per length is reduced. However because of fewer axles, the axle loads are higher. This in spite of around 25 % shorter cars in articulated trains.

- Train nose. A long nose is better than a short nose. This because of better aerodynamic shape and because there is a bigger distance to the front bogie. The potential for noise reduction is around 1 – 2 dB. In Shinkansen long nose train gave reduction of chock wave generation in long tunnels.

- Body-shell. The flow around the train creates turbulent boundary layers. The surface should be as smooth as possible. Flush-mounted windows and doors and avoiding of all kinds of cavities gives reduced noise generation. If there are elements along the line which disturbs the turbulence, layer noise is generated. Barriers should be at least 2 meter away from the train surface.

C2. Suspension systems

The suspension system for railway carriages is a based on use of bogies as shown in Fig. C-9.

Fig. C-9. Suspension system for railway carriages. (Railway tech web page: http://www.railway-technical.com/suspen.shtml).

The car body is suspended on bogie through soft spring called the secondary suspension, and for high speed trains these usually are air dampers. In the most advanced system active

http://www.railway-technical.com/suspen.shtml

http://www.railway-technical.com/suspen.shtml



dampers are used. This is that vibration forces are fed in opposite direction of the vibration from the bogie so that the vibration transmission to the car body is cancelled out.

The bogie is suspended on springs on the wheel set called the primary suspension. Usually these are steel springs. The stiffness of the primary suspension is higher than the secondary suspension. A picture of a bogie and the suspension system is shown in Fig. C-10.

Fig. C-10.Example of a bogie. (Railway tech web page: http://www.railway-technical.com/bogie1.shtml).

There are two important resonance frequencies for the suspension system. The lowest are mainly for the car body vibrating on the soft secondary springs. For high speed railway this frequency should be around 1 Hz. This resonance frequency is important for the passenger vibration comfort.

From an environmental noise and vibration view the second resonance frequency is more important. This is the resonance frequency for the bogie vibrating on the primary springs. There are three resonance frequencies. One for the vertical movement (translation) of the bogie and two for rotation (rocking). For high speed trains these resonance frequencies are in the region 5 – 8 Hz. The bogie motion at resonance will give high vibration transmission to the ground. Since the resonance frequency for the secondary suspension is very low, the weight of the car body has less influence on this force. It is important that the primary springs possesses high damping. This will reduce the effect of the bogie resonance frequencies.

http://www.railway-technical.com/bogie1.shtml



APPENDIX D: TRACK SYSTEMS. STATE OF THE ART CONCERNING NOISE AND VIBRATION

D1. Ballasted track

As explained in appendix A the rolling noise is mainly generated from the roughness on the surfaces in the rail and the wheel. The vibration of the surfaces gives pressure fluctuations in the air and sound is radiated. The sound radiation from the rail usually is the most dominating source. This is mainly because vibration in the rail is easily generated.

The combined surface roughness of the rail and wheel surfaces is the main influence parameter on rolling noise generation and differences of noise levels in the order of 8 - 10 dB between track having low and high corrugation level is reported. Efforts therefore should be made to develop solutions that give minimal corrugation. However the mechanism of rail roughness generation is not fully understood. Why corrugation is developed in one section of a train line and not in another obviously identical section often cannot be explained. The probability of generation is higher for lines with only one type of trains and one speed, and in curved tracks having stiff rail pads.

In some cases the high vibration level gives too big forces in the rail fastening system and damage in the fastening system may occur. One case of rail fastening damage is reported from the tunnel Romeriksporten on the Oslo high speed airport train line.

The most important frequency region for noise radiation from the rail is around the lowest resonance frequencies for the rail spanning between the sleepers. The vibration in the rail is increased when the rail pad is softer. In Fig. D-1 is shown the differences in noise from a track with soft and stiff rail pads.

Fig. D-1. Noise radiation and track decay rate. Soft and stiff rail pad. (Fodiman 2005).

The reason why the soft rail pads give more noise is mainly that the vibration reduction from the wheel contact point along the rail is lower. This is tested by hammering on the rail and measurering the vibration transmission along the rail. TDR (track decay rate) is a standardised value for the vibration transmission. When the TDR is low a bigger length of the rail is vibrating which gives higher noise level. The difference between stiff and soft pads increases with increasing train speed. Theoretical calculation reported in the Harmonoise project gave 8 dB higher noise level from a track having very soft rail pads than very stiff pads at a train speed of 315 km/h (Harmonoise 2003).



In Norway normally are used 10 mm relatively soft rail pads of the ”Pandrol studded” type. The noise radiation is higher for a given level of roughness in the rail and the wheel. However, when the rail pad is stiff, wave patterns in the rail surface easier will be the built up. This wave phenomenon is called rail corrugation. High corrugation level give increased vibration in the rail and higher noise levels. The optimum stiffness therefore is not very stiff rail pads. The optimum track is softer rail pads and high track vibration reduction. The latter can be increased by using rail dampers.

The importance of the track parameters and remedial actions concerning noise from ballasted track are listed below:

- Grinding. It is very important that corrugations are avoided. Jernbaneverket have made test of grinding and noise measurements in a project the last couple of years and have found that regulary grinding is vital in order to retain smooth rails. Maintenance grinding at short time intervals reduces the possibility for development of corrugation. When corrugation already have developed in a rail before grinding it will develop faster after grinding than in a rail without corrugation before grinding.

- Rail pad stiffness. Soft rail pads gives higher noise levels especially at high speeds. In the standard Norwegian track today is soft pads. Studies should be made to see if stiffer pads should be used in the high speed lines in order to reduce the noise radiation. In addition soft pads give bigger movements of the rail fasteners and therefore higher possibilities for fatigue.

- Rail pad damping. High material damping in the rail pad may increase the track decay rate. Tests have given reduction in the order of 1 dB.

- Rail dampers. The track decay rate will increase when rail dampers are mounted on the web as shown in fig. D-2. Different products have been tested. Tests made from Jernbaneverket gave 1-2 dB noise reduction.

Fig. D-2. Example of rail dampers. . (Producer S&V, reported 3 – 4 dB noise reduction).

- Type of sleeper. The surface of monoblock sleepers as in Norwegian tracks is smaller than in biblock sleepers, and the vibration loss factor is less. The noise therefore is 2 – 3 dB higher for rolling noise. However for highs speed rail the aerodynamic noise is high in the frequency region in which the noise radiation from the sleepers is important. The sleeper type therefore in not an important parameter for the noise from high speed trains.

- D2. Slab track

In slab track there is no ballast, and the track is fastened to a concrete slab. There are four main solutions for fastening of the rail. The solutions must give the elasticity in the track which is lost when there is no ballast:



- Base plate. The rail and the rail pad are fastened to steel plates, called base plates. The base plates are fastened elastically to the slab. Example: Pandrol Vipa, Vossloh 300,

- Booted sleepers. The rail and the rail pad is fastened to sleepers, and the sleepers are elastically mounted to the slab. Example: Sateba 312, Sonneville, Stedef.

- Embedded rail. The rail is elastically fastened to the slab in continuous support. The system can be based on dry mounting of the system, or on pouring of liquid masses in slots in the slab. Example: Edilon, Ortec, Balfour Beatty.

- Elastic rail fasteners. The rail is fastened to the slab through point fasteners. Example: Pandrol Vanguard.

The noise from a slab track generally is higher than from a ballasted track. The difference is typically 2 – 4 dB. (Thompson). In the German calculation Method for railway noise, Schall 03 2006, the difference is 3 dB. One reason is that the sound absorption in the ballast is lost, but the main reason is that in a slab track usually the rail fastening system is softer in order to obtain the elasticity that is lost from the ballast. Therefore the rail vibrates more, and the noise radiation from the rail is higher. The noise radiation from the massive slab can be neglected.

The possibilities for adjustment of height are limited in a slab track compared to a ballasted track. The Vanguard system and some base plate systems gives up to 35 mm of possible height adjustment, but this is still less than the possibilities in a ballasted track . It therefore is important that the settlement of the ground below the track is very small. We expect that slab track will not be chosen in Norway in areas with soft clay. However for lines on very compact ground and rock slab track may be chosen. In bored tunnels slab track must be used because the use of ballasted track will require bigger diameter on the tunnel boring machine, TBM.

Some tests of low noise slab tracks have been made, and it is possible to reduce the noise down to similar noise levels as from standard ballasted track. The solutions are based on absorbing surfaces on the slab and embedding of the rail. One disadvantage is that the possibilities for height adjustment in embedded rail track are very small.



APPENDIX E: VIBRATION CALCULATION AND REMEDIAL ACTIONS. STATE OF THE ART

E1. Mostly used calculation method in Norway

The mechanism of transmission of vibration from railway in the soil to adjacent buildings is not fully understood. There are many international references on theoretical calculation of vibration. See for instance Krylov et al. (2001). But there is no acknowledged international method that can be used for calculation of vibration from a railway line.

There are two main mechanisms that may contribute to the transmission of vibration from the track:

- Quasi-static mechanism. The deformation in the ground below each sleeper is moving with the train speed and vibration is induced in the ground.

- Dynamic forces from the train. Main dynamic forces are from rail corrugation, wheel corrugation, flats, and polygonization (out of roundness), and resonances in bogie / wheel system.

The true mechanism is a combination of these two mentioned. The quasi-static mechanism is probably the dominating in the lowest frequency region around 10 Hz and lower, and the vibrations from dynamic forces are added to the quasi-static mechanism at higher frequencies.

The highest vibration values are measured from train lines on soft clay. Often there are two dominant frequency peaks in the vibration specter. The lowest is around 8 – 12 Hz and is a kind of a resonance frequency for the embankment and dry clay top layer on the soft clay. The softer the clay is the lower is the resonance frequencies. In areas with very soft clay the frequency may be lower than 8 Hz, down to 5 Hz.

The second top in the vibration specter is for the resonance frequency for the unsprung mass on the total track elasticity, mainly rail pad and ballast. The unsprung mass is wheel, axle and brake disk. For modern tracks in Norway this frequency usually is around 40 Hz. For the old tracks with stiff pads and small ballast layer the frequency is around 63 Hz (1/3 octave band).

The Norwegian Geotechnical Institute developed a calculation method when the airport train line Gardermobanen from Oslo to Gardermoen was planned. (Madshus et al. 1995, Madshus & Kaynia 2001). The method is empirical and is founded on measured vibration data under various ground conditions. The vibration, v, in the building is calculated from:

v = vT fdistance fspeed ftrack fbuilding

vT is a reference value for the actual train type measured on the actual ground in a distance of D0 = 15 meters running at a reference speed of S0 = 70 km/h. The vibration in the building is calculated from the reference value and correction for distance to the building, the train speed, the track quality and the amplification of vibration in the building.

The correction for the distance D is strongly dependant on the ground condition. It is calculated from fdistance = (D/D0)A. We have used the calculation methodology in the



calculation of vibration from new railway line “Dobbeltsporet Skøyen – Asker” and in the upgrading of suburban train lines in the Oslo area. The distance factor fdistance should preferably be determined from vibration measurements in the actual area it varies from A = 0,5 on soft clay to A = 1.5 on compact ground . The amplification factor fB is set to fB = 2 for wooden houses. This is a safe value, measurements very often gives lower results. However a factor of fB =2 must be used because there will be amplification in some single houses. The highest amplification factor is measured in houses on soft ground because the vibration then are low frequency and may “hit” the lowest floor resonances.

The speed factor is an important but difficult factor to establish. fspeed will depend on many factors as the type of ground and for details in the train suspension system, unsprung mass of the wheel set, and the distances between the bogies and between the wheels in the bogie. Measurements we made on a suburban train set for the Kolsåsbanen project gave a linear increase, a doubling of the speed gave 60 % increase of vibration.

E2. Remedial actions

The main action for reducing vibration from the track is to have a stiff high quality embankment. In the new lines Gardermobanen and Skøyen - Asker additional remedial actions have only been found necessary for tracks on clay.

Possible remedial actions are:

- Stone filling below the track. Typical 3 – 4 meters - Lime – cement piles below the track - Lime – cement piles used as a vibration screen besides of the track - Vibration screen of air filled cushions besides of the track

In the new Norwegian projects only lime – cement piles have been used, below the track and as a vibration screen. Stone fillings are impractical to establish, and air cushion have been found to be a too uncertain action.

Lime – cement piles is established by mixing into the clay a combination of cement and lime. The diameter of the piles is 600 m. In the Skøyen – Asker project lime – cement piles was established at Jong. Measurements showed that vibration were reduced in the lowest frequency region, but that in the higher frequency range the vibration increased. In the Kolåsbaneproject finite element calculations were made and it was concluded that it was necessary to use much stiffer piles. Ordinary piles which were used on Jong have a shear stiffness of around 150 kPa whish is reached by mixing in 30 kg/m pile. In the Kolsåsbaneproject piles 140 kg/m have been mixed in, and a stiffness of 625 kPa have been reached. In addition the piles are established in the upper dry clay zone as well by using MDM piles in which water is mixed in. Two examples from the project is shown in Fig. E-1. The distance between the piles in the direction of the track is 1 meter except for the three longest piles on the right were the piles makes a continuous wall.



Figure E-1. Lime – cement piles below the track on Kolsåsbanen

Measurements in the Kolsåsbane project will give valuable data for future planning of new railway lines.

A lime cement screen was established at Lysaker as shown in Fig. E-2.

Figure E-2. Vibration screen of lime – cement piles at Lysaker.

Vibration measurements showed that the vibration had been halved.



APPENDIX F: GROUND BORNE NOISE CALCULATION AND REMEDIAL ACTIONS. STATE OF THE ART

F1. Calculation of ground borne noise

A typical situation is shown in Fig. F-1. Ground borne noise from a tunnel in rock is propagated to a building on rock. In Norway there are regulations for ground borne noise levels from tunnels. There is no special regulation for ground borne noise from trains on grade, only for the total noise level in the room, which is the sum of the airborne and the ground borne noise.

Figure F-1. Railway tunnel in rock below a building.

In the Oslo area many tunnels in rock for railway and subway trains is situated below dwelling areas. In som cases the highest structure borne noise levels in the dwellings are in the order of Lp,max = 50 dBA, In the new building regulations in Norway, the limit for structure borne noise from tunnels is Lp,max = 32 dBA in dwellings.

If the vibration level on the foundation of the house is known it is fairly simple to calculate the structure borne noise levels in the building. This is done by using the well known formulas for sound radiation and if necessary thumb rules or theoretical methods for noise reduction pr floor. The calculations of the vibration transmission in the rock from the rail to the foundation are more complicated and uncertain. The finite element - or boundary element method may be used. However, idealized material models for the rock may be very wrong. The rock is often cracked and non-homogenous, and the results of theoretical calculations therefore are uncertain.

For the planning of the airport train line from Oslo to Gardermoen we have measured ground borne noise from railway main lines and subway trains in many tunnels in the Oslo area. The maximum ground borne noise level was measured in rooms in which the floor was founded directly on the rock. Still more measurements were made for the planning of the tunnels in the Skøyen - Asker line. On the basis of the measurement results an empirical calculation method was made. The highest ground borne noise level were measured from freight trains in their maximum speed of around 80 km/h. Passenger trains in higher speeds, up to 160 km/h gave lower levels



The vibration reduction from the tunnel to the foundation is calculated from geometrical spreading and from vibration dissipation in the rock. At small distances from the track, wheel flats on the freight wagon wheels often give the highest ground borne noise levels. This source is a point source, and the noise theoretical falls with 6 dB pr doubling of the distance. At greater distances the ground borne noise source is more like a line source, and the level falls with 3 dB pr doubling of distance from geometric spreading. In addition the dissipation in cracks and layers contribute to the ground borne noise reduction.

The measurements were made in relatively old tunnels in which the rail pads are stiff, the ballast thickness is often small, and there is no subgrade between the ballast and the rock. The maximum rail deflection is in the order of 0,5 - 0,7 mm. In the new Norwegian tracks the rail pads are relatively soft, and the ballast layer is at least 600 mm. When the tunnels are build, longer augers are used, so that the rock surface becomes like a saw tooth with about 5 meter length between each tooth. It therefore is a considerable thickness of subgrade between the ballast and the rock. We have measured the rail deflection in such a new tunnel. The mean value of rail deflection for all trains in 24 hours was 1.4 mm, the 95 % confidence value was 1,8 mm.

Because the track is softer the ground borne noise from a modern tunnel is considerable lower than from an old tunnel. In the empirical calculation method based on measurements in old tunnel corrections are made for the softer track. Figure F-2 shows calculated noise level on ground floor in a building above a rock tunnel.

Figure F-2. Calculated values for ground borne noise levels from freight trains in ground floor from a modern blasted rock tunnel.

F2. Remedial actions

Ballasted track

The principle for reducing ground borne noise is to introduce elasticity between the rail and the ground / rock. Possible remedial actions are:

2025303540455055

10 20 30 40 60 100

dBA

Distance from rail to foundation, m

Ground borne noise from blasted tunnels

Max noise level



- Ballast mats. Elastic mats underneath the ballast. Thickness: 25 – 85 mm - Under sleeper mats. Elastic mats are glued to the sleepers. Thickness: 20 – 30 mm

Ballast mats are the preferred solution for Jernbaneverket, and in the new Norwegian projects only ballast mats have been used.

The general Jernbaneverket track requirement for ballast mats is identical to the Deutche Bahn requirements, "Technische Lieferbedingungen Unterschottermatten", DB-TL 918 071. The requirements is 120 – 200 km/h: CSTAT > 0,06 N/mm3, from 200 km/h: CSTAT > 0,10 N/mm3. In the planning of the tunnels in the Skøyen – Asker project it was found that it was possible to reach the ground borne noise requirements by using ballast mats of this stiffness. A study was made concerning the experience from the use of softer ballast mats, and it was concluded that considerable softer ballast mats could be used and the requirements for the softest ballast mats was CDYN > 0,02 N/mm3. The maximum rail deflection is calculated to around 3 – 4 mm. The solution for the Jong –Asker tunnels is shown in Fig. F-3.

Figure F-3. Ballast mats in rock tunnel and deep stone – filling. Usually there is not a need for the deep filling.

The ballast mats is calculated to give around 15 dB noise reduction. In some places this was not enough. Full scale tests was made on different methods for increasing the reduction, and it was found that best method was to blast lower and fill in with cracked stones as shown in Figure. F-3. This would increase the reduction with at least 4 dB.

Slab track

There is no lines with slab track in Norway and therefore no Norwegian experience.

The possible solutions are ranked after possible noise reduction:

- Floating slab track. The slab is elastically mounted. Very high reduction may be reached

Ballast mat

Extra cracked stones



- Booted sleepers. The sleepers is elastically mounted in the slab. High noise reduction was reached for the CTRL line under London city with the system Sateba 312 (Greer at al. 2004).

- Base plate system. The rail is mounted on a steel plate, and the steel plate is elastically mounted on the slab. Examples of systems are Pandrol Vipa as in the figure, and Vossloh 300.

- Direct elastic fastening. A system which can give considerable reduction is the Pandrol Vanguard system. The data for Vanguard is competitive with the best booted sleeper and base plate system.

Because the rail is clamped near the rail head it is possible to have quite soft mounting.



Embedded rail systems are not included as a possible solution. The rail is elastically baked into the slab. It is not possible to have satisfactory elasticity in order to reach a high noise reduction.

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