Development of the Ecological Scarcity Method: Application ...

Development of the Ecological Scarcity method:

Application to Russia and Germany

vorgelegt von

Dipl.-Ing.

Marina Grinberg

geb. in Moskau

von der Fakultät III Prozesswissenschaften

der Technischen Universität Berlin

zur Erlangung des akademischen Grades

Doktor der Ingenieurwissenschaften

– Dr.-Ing. –

genehmigte Dissertation

Promotionsausschuss:

Vorsitzender: Prof. Dr.-Ing. Sven-Uwe Geißen

Gutachter: Prof. Dr. rer. nat. Matthias Finkbeiner

Gutachter: Prof. Dr.-Ing. Jens Hesselbach

Tag der wissenschaftlichen Aussprache: 05. Mai 2015

Berlin 2015

iii

Acknowledgment

I would like to express my gratitude to the persons below who made my research successful and

supported me during my doctoral study and staying in Germany.

First of all, I would like express my special appreciation and thanks to my supervisor, Prof. Dr.

Matthias Finkbeiner, for his vital support and assistance, enduring guidance and mentorship he

provided to me. I would especially like to thank my additional supervisors, Dr. Julia Martinez Blanco,

whose help and friendly attitude at every point during my research made it possible to achieve the

goal, and Dr. Robert Ackermann, for his wise advices and ideas that helped to push my research

forward. I would also like to thank Justus Caspers who supported me with German data collection.

I would like to thank defense committee members, Prof. Dr.-Ing. Jens Hesselbach and

Prof. Dr.-Ing. Sven-Uwe Geißen.

I would like to acknowledge DAAD and Siemens for their financial support and assistance, especially

staff members of Desk 522, Rebekka Kammler and Irmgard Kasperek. They have not only made my

accommodation in Germany easier, but they gave me the chance to meet other scholarship holders and

participate in the meetings of the foundation.

I wish to thank my family, especially my parents, my sister, for their endless love, support and

encouragement, and my cousin, Dr. Roman Grinberg, who has believed in me like no other.

I would like to pay my regards to my friends, Anna and Irina, for their friendship and support in any

situation, to my friend and talented artist Kama Jackowska, who helped me with the design of the

thesis, and many others who are not listed here, but are in my heart. At the end, I would like express

appreciation to Tobi, who has supported me a lot.

v

Table of content

Acknowledgment .................................................................................................................................. iii

Table of content ..................................................................................................................................... v

List of figures ...................................................................................................................................... viii

List of tables ........................................................................................................................................... x

List of equations .................................................................................................................................. xii

List of acronyms and abbreviations .................................................................................................. xiii

Summary ............................................................................................................................................. xvi

1. Introduction and goals .................................................................................................................. 1

1.1. Introduction ............................................................................................................................. 1

1.2. Goals of the thesis ................................................................................................................... 4

1.2.1. Structure of the thesis ...................................................................................................... 5

2. Background .................................................................................................................................... 7

2.1. Life cycle assessment .............................................................................................................. 8

2.1.1. Goal and scope definition ................................................................................................ 9

2.1.2. Life cycle inventory analysis ......................................................................................... 10

2.1.3. Life cycle impact assessment ........................................................................................ 10

2.1.4. Interpretation ................................................................................................................. 14

2.2. Elements of LCIA within existing LCIA methods ................................................................ 15

2.2.1. Characterization ............................................................................................................. 15

2.2.2. Normalization ................................................................................................................ 17

2.2.3. Weighting ...................................................................................................................... 17

2.3. Ecological Scarcity method ................................................................................................... 18

2.3.1. Development of the Ecological Scarcity method .......................................................... 18

2.3.2. The basic principle and formula .................................................................................... 20

2.3.3. Characteristics of the Ecological Scarcity method ........................................................ 22

2.4. Environmental policy ............................................................................................................ 24

2.4.1. International agreements for environmental protection ................................................. 24

2.4.2. Environmental policy in Russia..................................................................................... 29

2.4.3. Environmental policy in Germany ................................................................................ 32

3. Methodology for eco-factor calculation for Russia and Germany .......................................... 36

3.1. Eco-factor .............................................................................................................................. 36

3.2. Characterization in the formula for eco-factors calculation .................................................. 37

3.3. Normalization in the formula for eco-factors calculation ..................................................... 38

3.4. Weighting in the formula for eco-factors calculation ............................................................ 38

vi

3.4.1. Current flow .................................................................................................................. 38

3.4.2. Critical flow ................................................................................................................... 39

4. Russian eco-factors ...................................................................................................................... 42

4.1. Emissions to air ..................................................................................................................... 42

4.1.1. CO2 and other greenhouse gases (GHG) ....................................................................... 43

4.1.2. Ozone-depleting substances (ODS) ............................................................................... 47

4.1.3. Particulate matter (PM) ................................................................................................. 49

4.2. Emissions to surface water .................................................................................................... 51

4.2.1. Nitrogen (N) and phosphorus (P) .................................................................................. 52

4.2.2. Heavy metals: lead (Pb) and mercury (Hg) ................................................................... 54

4.3. Emissions to sea water .......................................................................................................... 56

4.3.1. Total petroleum hydrocarbons (TPH) and phenols ....................................................... 56

4.4. Waste ..................................................................................................................................... 57

4.5. Energy consumption .............................................................................................................. 58

4.6. Overview ............................................................................................................................... 61

5. German eco-factors ..................................................................................................................... 63

5.1. Emissions to air ..................................................................................................................... 64

5.1.1. CO2 and other greenhouse gases (GHG) ....................................................................... 64

5.1.2. Non-methane volatile organic compounds (NMVOCs) ................................................ 68

5.1.3. Nitrogen oxides (NOx) ................................................................................................... 70

5.1.4. Ammonia (NH3) ............................................................................................................ 71

5.1.5. Sulfur dioxide (SO2) and other acidifying substances ................................................... 72

5.1.6. Particulate matter (PM) ................................................................................................. 74

5.1.7. Dioxins .......................................................................................................................... 76

5.1.8. Heavy metals: cadmium (Cd), lead (Pb) and mercury (Hg) .......................................... 79

5.2. Emissions to surface water .................................................................................................... 80

5.2.1. Nitrogen (N) and phosphorus (P) .................................................................................. 80

5.2.2. Polycyclic aromatic hydrocarbons (PAHs) ................................................................... 82

5.3. Resources .............................................................................................................................. 84

5.3.1. Land use ........................................................................................................................ 84

5.3.2. Energy consumption ...................................................................................................... 85

5.4. Overview ............................................................................................................................... 88

6. Use of German and Russian eco-factors in a case study: bamboo and aluminum bike frame

……………………………………………………………………………………………………90

6.1. Case study description ........................................................................................................... 90

6.2. Assessment of the case study with the Swiss, German and Russian eco-factors .................. 93

vii

6.2.1. Results for Russia .......................................................................................................... 95

6.2.2. Results for Germany ...................................................................................................... 97

6.3. Outcome ................................................................................................................................ 97

7. Discussion - Evaluation and interpretation of results .............................................................. 99

7.1. Challenges for eco-factor calculation for Russia and Germany ............................................ 99

7.1.1. Challenges for current flow quantification .................................................................... 99

7.1.2. Challenges for critical flow quantification .................................................................. 100

7.1.3. Eco-factors calculation ................................................................................................ 101

7.2. Application .......................................................................................................................... 102

7.2.1. Product level ................................................................................................................ 102

7.2.2. National level .............................................................................................................. 104

7.3. Challenges and opportunities for the comparability of results ............................................ 106

7.3.1. Comparison of sets of eco-factors for different countries ........................................... 106

7.3.2. Comparison of products from different countries ....................................................... 106

7.4. Time and space effects ........................................................................................................ 108

7.4.1. Regional sensitivity ..................................................................................................... 108

7.4.2. Different deadlines for the targets implementation ..................................................... 110

7.5. National environmental impacts for future scenario .......................................................... 113

7.6. Parallel external development of German eco-factors ........................................................ 120

8. Conclusions and outlook ........................................................................................................... 123

8.1. Results of the thesis ............................................................................................................. 123

8.2. Further contribution ............................................................................................................. 124

8.3. Remaining challenges and recommendations for further research ...................................... 126

8.3.1. Review and enhancement of data for eco-factors calculation ..................................... 126

8.3.2. Consideration of different regions within the country ................................................. 126

8.3.3. Implementation in real case studies ............................................................................. 127

8.3.4. Comparability of results .............................................................................................. 127

8.3.5. Development on company level .................................................................................. 127

8.3.6. Update of eco-factor sets ............................................................................................. 128

References .......................................................................................................................................... 129

viii

List of figures

Figure 1: The relation between environmental policy, life cycle assessment and effects on the

environment ............................................................................................................................................. 2

Figure 2: Structure of the thesis ............................................................................................................. 6

Figure 3: Structure of Chapter 2 ............................................................................................................. 7

Figure 4: Four phases of a Life Cycle Assessment (ISO, 2006a) .......................................................... 9

Figure 5: Mandatory and optional elements of life cycle impact assessment (based on ISO, 2006b) 10

Figure 6: Mandatory elements of LCIA and the concept of category indicators with example for

climate change (based on ISO, 2006b; Montero, Antón, Torrellas, Ruijs, & Vermeulen, 2011;

Schebek, 2012) ...................................................................................................................................... 12

Figure 7: The relation between elements within the interpretation phase with the other phases of LCA

(ISO, 2006b) .......................................................................................................................................... 14

Figure 8: General structure of the LCIA framework (based on Jolliet et al., 2004; JRC - EC, 2010c;

Rack, Valdivia, & Sonnemann, 2013) ................................................................................................... 16

Figure 9: Degree of transparency and ability to interpret and Ecological Scarcity method (based on

Huppes & Oers, 2011; Itsubo, 2000) ..................................................................................................... 23

Figure 10: Timeline of some of the UN Conventions .......................................................................... 26

Figure 11: The structure and hierarchy of Russian specific environmental authorities ....................... 30

Figure 12: Distribution of the costs for environmental activities in Russia in 2012 (based on “Federal

State Statistic Service,” 2013) ............................................................................................................... 31

Figure 13: Federal agencies operating under the Federal Environment Ministry in Germany ............ 33

Figure 14: Structure of Chapter 3 ......................................................................................................... 36


Figure 16: GHGs emissions trend in Russia (based on UNFCCC, 2013) ............................................ 46

Figure 17: Russian HCFC consumption trend (based on UNEP, 2013) .............................................. 49

Figure 18: PM10 and PM2.5 emissions trend in Russia (based on GAINS) ....................................... 51

Figure 19: Trend of nitrogen (N) and phosphorus (P) emissions through sewage water in Russia

(based on “Federal Russian statistic service,” 2013) ............................................................................. 53

Figure 20: Trend of nitrogen (N) and phosphorus (P) concentration in sewage water in Russia (based

on “Federal Russian statistic service,” 2013) ........................................................................................ 54

Figure 21: Trend of lead (Pb) and mercury (Hg) emission in sewage water in Russia (based on

“Federal Russian statistic service,” 2013) ............................................................................................. 55

Figure 22: Trend of waste generation in Russia (based on “Federal Russian statistic service,” 2013) 58

Figure 23: Russian primary energy consumption by sources (based on ABB,2011) ........................... 59

Figure 24: Energy Efficiency Potential by sector in Russia (based on World Bank, (2010)) .............. 60

Figure 25: Overall annual environmental impacts of Russia ............................................................... 62


Figure 27: Total GHG emission by greenhouse gas in Germany in 2011 (based on UNFCCC, 2011) 64

Figure 28: GHGs emissions trend in Germany (based on UNFCCC, 2011) ........................................ 68

Figure 29: NMVOCs emissions by source in Germany in 2010 (based on UBA, 2013b) ................... 68

Figure 30: NMVOCs emissions trend in Germany (based on UBA, 2013b) ....................................... 69

Figure 31: NOx emissions trend in Germany (based on BMU, 2013a) ................................................ 71

Figure 32: NH3 emissions trend in Germany (based on BMU, 2013a) ................................................ 72

Figure 33: SO2 emissions trend in Germany (based on BMU, 2013a)................................................. 74

Figure 34: PM10 and PM2.5 emissions trend in Germany (based on BMU, 2013a) ........................... 76

Figure 35: Dioxins emissions trend in Germany (based on UBA, 2013a) ........................................... 78

Figure 36: Pb emissions to air trend in Germany (based on UBA, 2013c) .......................................... 80

ix

Figure 37: Cd, Hg emissions to air trend in Germany (based on UBA, 2013c) ................................... 80

Figure 38: N and P emissions to surface water trend in Germany (based on UBA-Federal

Environment Agency, 2010c) ................................................................................................................ 82

Figure 39: Delays in the implementation of measures for 2015 objectives, and reasons for these delays

(BMU, 2013c) ....................................................................................................................................... 82

Figure 40: Land use trend in Germany (based on Statistisches Bundesamt, 2012) ............................. 85

Figure 41: Power production in Germany in 2011 (BMWi, 2012) ...................................................... 86

Figure 42: Primary energy consumption trend in Germany (based on AGEB, 2013) ......................... 87

Figure 43: Overall annual environmental impacts of Germany ........................................................... 89

Figure 44: System boundaries of the bamboo bike frame (based on Chang et al., 2012) .................... 91

Figure 45: System boundaries of the aluminum bike frame (based on Chang et al., 2012) ................. 92

Figure 46: The share of different emissions from the aluminum frame for Switzerland, Germany and

Russia .................................................................................................................................................... 94

Figure 47: The share of different emissions from the bamboo frame for Switzerland, Germany and

Russia .................................................................................................................................................... 95

Figure 48: The share of different emissions excluding emission to sea water from the aluminum and

bamboo frame for Russia ...................................................................................................................... 96

Figure 49: Status for eco-factor calculation in few examples of substances: availability of data for

current flow, EF and critical flow calculation ..................................................................................... 101

Figure 50: Different levels of score aggregation ................................................................................ 103

Figure 51: Number of eco-factors for different countries aggregated per media for the period 1990-

2014 (based on Ahbe et al., 1990; Büsser et al., 2012; Frischknecht & Büsser Knöpfel, 2013;

Frischknecht et al., 2009; Lindfors et al., 1995; Miyazaki et al., 2004) .............................................. 105

Figure 52: Relation between value of eco-factor and normalization flow based on Russian and

German data ........................................................................................................................................ 107

Figure 53: Eco-factors for GHG, PM10 and nitrogen emissions for different reference countries

(Frischknecht & Büsser Knöpfel, 2013; Büsser et al., 2012) .............................................................. 109

Figure 54: The quality of air in cities in Russia in 2010

(http://www.ecogosdoklad.ru/grAir1_2_1.aspx ) ................................................................................ 109

Figure 55: Real trend of GHG emissions and its assumed paces of reduction for years 1990-2050 in

Germany .............................................................................................................................................. 112

Figure 56: Russian national environmental impact for scenario 1 ..................................................... 115

Figure 57: Russian national environmental impact for scenario 2 ..................................................... 116

Figure 58: German national environmental impact for scenario 1 ..................................................... 118

Figure 59: German national environmental impact for scenario 2 ..................................................... 119

Figure 60: Overall annual environmental impact of Germany according to Volkswagen research

initiative (based on Schebek, 2014) .................................................................................................... 122

Figure 61: Possible contribution of the Ecological Scarcity method for Russia and Germany ......... 125

x

List of tables

Table 1: World Development Indicators for Russia and Germany in year 2011 .................................. 3

Table 2: Some of the most frequently used LCIA methods (based on JRC - EC, 2010b) ................... 16

Table 3: Some of the LCIA methods using spatial scale normalization (based on Huppes & van Oers,

2011; JRC- EC, 2010b) ......................................................................................................................... 17

Table 4: Some of the LCIA methods using weighting (based on Huppes & van Oers, 2011) ............. 18

Table 5: Spreading of the Ecological Scarcity method (based on Ahbe et al., 1990; Büsser et al., 2012;

Frischknecht & Büsser Knöpfel, 2013; Doka, 2002; Frischknecht et al., 2009; Lindfors et al., 1995;

Miyazaki et al., 2004) ............................................................................................................................ 20

Table 6: Protocols to the Convention on Long-range Transboundary Air Pollution (www.unece.org)27

Table 7: Some of the international environmental agreement signed or/and accepted by Russia ........ 32

Table 8: Some of the international environmental agreement signed and accepted by Germany ........ 35

Table 9: Characterization factors applied for the study ........................................................................ 37

Table 10: Calculation of the eco-factor for CO2 in Russia ................................................................... 44

Table 11: Eco-factors for other greenhouse gases in Russia ................................................................ 46

Table 12: Commitments of the Russian Federation to reduce the consumption of

hydrochlorofluorocarbons (HCFCs) (Tselikov, 2012) .......................................................................... 48

Table 13: Eco-factor for HCFC group of ODS in Russia ..................................................................... 48

Table 14: Eco-factors for ODS in Russia ............................................................................................. 48

Table 15: Eco-factor for PM10 and PM2.5 in Russia .......................................................................... 50

Table 16: Eco-factors for nitrogen and phosphorus in surface water in Russia ................................... 53

Table 17: Eco-factors for lead and mercury in surface water in Russia ............................................... 55

Table 18: Eco-factors for TPH and phenols in sea water in Russia ..................................................... 57

Table 19: Eco-factor for waste in Russia.............................................................................................. 58

Table 20: Eco-factor for energy consumption in Russia ...................................................................... 60

Table 21: Eco-factors for some energy resources in Russia ................................................................. 60

Table 22: Russian set of eco-factors ..................................................................................................... 61

Table 23: Eco-factor for CO2 in Germany ............................................................................................ 65

Table 24: Eco-factors for further greenhouse gases in Germany ......................................................... 67

Table 25: Eco-factor for NMVOCs in Germany .................................................................................. 69

Table 26: Eco-factor for NOx in Germany ........................................................................................... 70

Table 27: Eco-factor for NH3 in Germany ........................................................................................... 72

Table 28: Eco-factor for SO2 in Germany ............................................................................................ 73

Table 29: Eco-factors for acidifying substances in Germany ............................................................... 73

Table 30: Eco-factor for PM in Germany ............................................................................................. 75

Table 31: Toxic equivalent factors (Van den Berg et al., 2006)........................................................... 77

Table 32: Eco-factor for dioxins in Germany ....................................................................................... 78

Table 33: Eco-factors for emissions of Hg, Cd, Pb to air in Germany ................................................. 79

Table 34: Eco-factors for emissions of nitrogen and phosphorus to surface water in Germany .......... 81

Table 35: Eco-factors for emissions of PAHs to surface water in Germany ........................................ 83

Table 36: Eco-factor for land use in Germany ..................................................................................... 84

Table 37: Eco-factor for primary energy consumption in Germany .................................................... 86

Table 38: Eco-factors for some energy resources in Germany ............................................................. 87

Table 39: German set of eco-factors .................................................................................................... 88

Table 40: Main materials and energy input of bamboo and aluminum frames per functional unit

(Chang et al., 2012) ............................................................................................................................... 92

xi

Table 41: Single-score results for aluminum and bamboo frames for Germany, Russia and

Switzerland per functional unit ............................................................................................................. 93

Table 42: Environmental impacts of environmental issues making main contribution for two bike

frames (Russian eco-factors set) ............................................................................................................ 96

Table 43: Environmental impacts of environmental issues making main contribution for different bike

frames (German eco-factors set) ........................................................................................................... 97

Table 44: Score for the production of the bike’s frames divided with the total annual national impact

for Russia and Germany ...................................................................................................................... 107

Table 45: Base year of the reduction, current flows and critical flows timelines for the considered

substances ............................................................................................................................................ 111

Table 46: Eco-factors for GHG emissions in Germany with respect to different reduction targets

(based on Statistisches Bundesamt, 2012)........................................................................................... 112

Table 47: Russian set of eco-factors for scenarios 2020 based on trend of emissions and consumptions

(scenario 1) .......................................................................................................................................... 115

Table 48: Russian set of eco-factors for scenarios 2020 based on assumptions of the targets

achievement (scenario 2) ..................................................................................................................... 116

Table 49: German set of eco-factors for scenarios 2020 based on trend of emissions and consumptions

(scenario 1) .......................................................................................................................................... 117

Table 50: German set of eco-factors for scenarios 2020 based on assumptions of the targets

achievement (scenario 2) ..................................................................................................................... 119

Table 51: German eco-factor developed by Volkswagen research initiative (based on Schebek, 2014)

............................................................................................................................................................. 121

Table 52: Environmental issues assessed for Russia and Germany ................................................... 123

xii

List of equations

Equation 1: Eco-factor formula (Frischknecht et al., 2009) ................................................................ 20

Equation 2: Example of eco-factor calculation .................................................................................... 21

Equation 3: Calculation of the environmental impact in EP (Miyazaki, 1998) ................................... 21

Equation 4: Regionalized eco-factor calculation (Frischknecht et al., 2009) ...................................... 21

Equation 5: Average eco-factor calculation (Frischknecht et al., 2009) .............................................. 22

Equation 6: Example of calculation of eco-factor with different current and normalization flows

(GHG emissions, Germany) .................................................................................................................. 38

Equation 7: Example of critical flow calculation with the maximum allowable concentration .......... 40

xiii

List of acronyms and abbreviations

AoP Areas of protection

BBSR Federal Institute for Research on Building, Urban Affairs and Spatial Planning (Germany)

BfN Federal Agency for Nature Conservation (Germany)

BfS Federal Office for Radiation Protection (Germany)

BMUB Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety

(Germany)

Cd Cadmium

CF Characterization factor

CFC Chlorofluorocarbon

CLRTAP Convention on Long-range Transboundary Air Pollution

CML Centre for Environmental Studies

CO2 Carbon dioxide

CSD Commission on Sustainable Development

DALY Disability-adjusted life year

EC European Commission

ECER Energy Conservation and Emissions Reduction

EDIP Environmental Design of Industrial Products

EEA European Environment Agency

EPS Environmental Priority Strategies

FAO Food and Agriculture Organization

FU Functional unit

GAINS Greenhouse gas - Air pollution Interactions and Synergies

GDP Gross domestic product

GHG Greenhouse gas emissions

GNI Gross national income

GWP Global warming potential

HCFC Hydrochlorofluorocarbons

xiv

HELCOM Baltic Marine Environment Protection Commission

Hg Mercury

IEA International Energy Agency

IIP Institute for Industrial Productivity

ILCD International Reference Life Cycle Data

IPCC Intergovernmental Panel on Climate Change

JRC Joint Research Centre

LCA Life cycle assessment

LCC Life cycle cost

LCI Life cycle inventory

LCIA Life cycle impact assessment

LGV Large goods vehicles

MAB Mankind and the biosphere

MAC Maximum allowable concentration

MEA Multilateral environmental agreement

N Nitrogen

NGO Non-governmental organization

NH3 Ammonia

NHS National Sustainable Development Strategy (Germany)

NMVOC Non-methane volatile organic compounds

NOx Nitrogen oxides

ODS Ozone-depleting substances

OECD Organisation for Economic Co-operation and Development

OEF Organisational environmental footprint

P Phosphorus

PAH Polycyclic aromatic hydrocarbon

Pb Lead

PEF Product environmental footprint

PM Particulate matter

xv

POP Persistent organic pollutant

SLCA Social life cycle assessment

SO2 Sulfur dioxide

TEQ Toxic equivalence

TPH Total petroleum hydrocarbons

UBA Federal Environmental Agency (Germany)

UN United Nations

UNDP United Nations Development Programme

UNECE United Nations Economic Commission for Europe

UNEP United Nations Environmental Programme

UNFCCC United Nations Framework Convention on Climate Change

UNIDO United Nations Industrial Development Organization

VOC Volatile organic compound

WB World Bank

WBG World Bank Group

WHO World Health Organization

WMO World Meteorological Organization

xvi

Summary

Life cycle assessment (LCA) is an internationally-recognized and powerful tool, which is successfully

used to enhance sustainability through the environmental improvement of products and services,

communication with stakeholders and decision-making support. There are plenty of life cycle impact

assessment (LCIA) methods and methodologies that aim to model numerous environmental

interventions into a complete, robust and comprehensive set of impact categories. However, it is still a

challenge to connect LCA with environmental policy and to find the right balance between a robust

and streamlined LCIA approach that is understandable by non LCA experts, like policy-makers.

The focus of the thesis is on further developing an existing policy-oriented LCIA method, the

Ecological Scarcity method, for Russia and Germany. It has the potential to assess a wide range of

environmental interventions, take into account the specific features and needs of the corresponding

national environmental policy and support decision making in these countries. The application of the

Ecological Scarcity method to Russia and Germany also reveals methodological challenges and

contributes to the improvement of the method.

The thesis provides German and Russian sets of eco-factors, which serve as indicators of the relative

importance of different environmental issues. The data for eco-factors calculation has been obtained

by reviewing publicly available documents that describe the current Russian and German state of the

environment and the targets and goals of the national environmental policy for each of the substances

contributing to environmental issues. Russian eco-factor set includes 5 environmental issues

(emissions to air, surface water, sea water, resource consumption and waste) and 12 substances and

substance groups. German set of eco-factors has 3 categories (emissions air, surface water and

resources) and 16 substances and substance groups. The identified eco-factors have been tested in the

calculation of the national overall environmental score and in the case study of the manufacturing of

two types of bicycle frames, made of aluminum and bamboo. The case study and application at the

national level aim to verify the comprehensiveness, plausibility and applicability of the developed

German and Russian set of eco-factors.

The method allows identifying single-score results for different product options and reveals

environmental hot spots, at the country and product level. However, the thesis shows, there is a need

to improve data availability and quality on the national level, in order to evaluate more environmental

interventions and make the results more comprehensive. Other methodological challenges, meaningful

beyond Russia and Germany case, have been identified, for example, comparability of the results

obtained with the Ecological Scarcity method. Some solutions have been proposed to overcome data

gaps and enhance the wider application of the method.

The Ecological Scarcity method provides valuable input for policy makers and LCA practitioners with

different level of expertise, and sets of eco-factors are now available and ready to be used for Russia

and Germany. It has the potential to support decision making in the two countries, as the result of the

assessment, measured as a single-score, is concise and easier for further communication, it reflects

national environmental priorities of Russia and Germany, transparent, traceable and open for further

update of eco-factors.

Keywords: life cycle impact assessment, Ecological Scarcity method, decision making support,

environmental policy, eco-factors

1

1. Introduction and goals

1.1. Introduction

Population growth and human activities have contributed to environmental problems, such as the

increase of natural resource use and consumption, destruction of natural ecosystems, loss of

biodiversity and long-term pollution of the environment. The global community recognizes the

pressure on ecosystems and limitation of natural resources and the need for sustainable development.

The concept of sustainable development was defined by the United Nations in 1987 in the Report of

the World Commission on Environment and Development (Brundtland Commission) (UN, 1987).

The emissions of pollutants and the consumption of resources contribute to a wide range of

environmental impacts, such as depletion of resources, water and land use, climate change, ozone

depletion, smog creation, acidification, eutrophication, and toxic effects on human health and

ecosystems. For a sustainable development, there is a clear need of methods and tools that assist on

measuring and identifying opportunities for reducing the negative environmental impacts of human

activities. Among the methods currently available, life cycle assessment (LCA) is an important and

comprehensive method to measure and analyze the environmental impacts of product systems through

their entire life cycle (ISO, 2006a). Though LCA is an internationally accepted, standardized,

powerful tool, there are still some challenges (Finkbeiner et al., 2014). One of them is the connection

of the method with environmental policy. This link may have a great contribution because

environmental protection is often regulated at the policy level. At the same time, the results of LCA

are recognized to be helpful from a decision making point of view (European Commission, 2014).

Figure 1 schematically shows the current relation between LCA and environmental policy.

Governments set environmental standards, regulations and prescribe the level of protection, which rely

on the available scientific knowledge and findings. Environmental policy and its implementation

affect the human activities and thus the derived level of environmental stress, associated with

ecosystems pressure, human health and resource consumption. LCA can identify environmental hot

spots and provide a single tool that is able to provide insights into relations and trade-offs between

different environmental problems, impacts and stresses. Moreover, LCA can inform policy makers,

support more effective decision making in companies and promote life cycle thinking, for example, in

the implementation of new strategies and regulations for the prevention of emissions.

There are some initiatives to include life cycle assessment in environmental policy in the European

Union on both organization and product level, e.g. the Organizational (European Commission, 2012a)

and Product (European Commission, 2012b) Environmental Footprints. However, to achieve its goal

this approach still needs to be improved and balanced to avoid misuse and to contribute to sound

public policy making (Finkbeiner, 2013; Galatola & Pant, 2014).

2

Figure 1: The relation between environmental policy, life cycle assessment and effects on the environment

LCA has four steps: goal and scope definition, life cycle inventory analysis (LCI), life cycle impact

assessment (LCIA) and interpretation. During the impact assessment stage, the inventory results are

linked with the environmental impacts categories through specific methods. Some of the existing

impact assessment methods in LCA directly address the environmental policy issue in different ways,

the EDIP (Hauschild & Potting, 2005), the Ecological Scarcity method (Ahbe, Braunschweig, &

Müller-Wenk, 1990; Frischknecht, Steiner, Braunschweig, Egli, & Hildesheimer, 2006; Frischknecht

& Büsser Knöpfel, 2013), the ECER (Wang, Hou, Zhang, & Weng, 2011) and others. The Ecological

Scarcity method is one of the most recently updated methods among the abovementioned. The method

is relatively easy to understand, transparent and traceable. This policy-oriented method takes into

account the country- or region-specific environmental legislation and policy targets (that define the so

called critical flow), along with the current environmental situation in the country (called current

flow). Using both flows, the method weights the importance of each of the environmental impacts

through the distance to target approach (Frischknecht, Steiner, & Jungbluth, 2009). The method brings

different environmental impacts to single-score points, thus these values can be added and compared.

Environmental policy • regulation

• law

• standards

• norms

Environmental stress • use of natural resource

• emissions

• waste

Environmental problems • air, water, soil

pollution

• ecosystems degradarion

• loss of biodiversity

• etc.

Environmental impacts • climate change

• ozone depletion

• human health effects

• resource depletion

• etc.

LCA

3

Although the method was originally developed for Switzerland, it is flexible for adaptation to different

countries. However, so far it has been developed only for a few countries – only a handful of countries

currently have their own set of eco-factors. Therefore, there is a need to develop and promote the

method further, especially among developing countries. Developing countries are one of the target

groups for LCA, that can possibly “benefit the most by adopting life cycle insights in the early stages

of their product development and organizational activities” (Rebitzer et al., 2004). Furthermore,

current policy development for environmental issues and a wider LCA application makes the

Ecological Scarcity method suitable and useful for developed countries as well.

In order to contribute to the need for development and test of the Ecological Scarcity method in new

countries, two were selected for the study, Russia and Germany. These two countries have significant

differences from several perspectives: level of development, geographical, social and economic

characteristics, LCA experience, environmental policy and others. According to the World Bank (WB)

classification, Russia is one of the so called developing countries, while Germany is a developed

countrya. The additional criteria used by the WB for determining the level of development are gross

domestic product (GDP), per capita income, level of industrialization, amount of widespread

infrastructure and general standard of living. Some of the World Bank indicators for Russia and

Germany are presented in Table 1.

Indicator Russia Germany

GNI per capita, Atlas method (current US$)b 10 820 44 670

Population (inhabitants) 142 960 000 81 797 673

GDP (current US$) 1,90E+12 3,6E+12

GDP growth (annual %) 4,3 3,3

Life expectancy at birth, total (years) 69 81

Table 1: World Development Indicators for Russia and Germany in year 2011 c

Russia is the biggest country in the world, the size of its territory is 17 098 242 km2

(Federal State

Statistic Service, 2012). Therefore, the density of population is relatively low and amounts to 8,7

persons per km2. There is a big variety of natural and undisturbed ecosystems in some parts of the

country. There are around 40 national parks and 100 nature reserves that occupy more than 2 % of the

country’s area – this small part of Russia equals the size of Germany (Federal State Statistic Service,

2012). Moreover, Russia has the largest forests on the planet and it is ranked among the five forest-

richest countries. In fact, it has around 22 % of the total world’s forest resources (Federal State

Statistic Service, 2012). Apart from timber, Russia has a huge natural resource base that includes

petroleum, natural gas, coal, ores and other mineral resources. Russia is the largest exporter of natural

resources, with exports figures of 9,1 % of the world natural resources trade (World Trade

Organization, 2010). However, environmental management in Russia is undergoing severe problems

due to persistent environmental degradation, lack of coordination between the institutions with

responsibilities for environmental protection and weak community involvement (OECD, 2006).

German territory is 357 138 km2, population density is 235 persons per km

2, 26-time higher than

Russian density (Statistisches Bundesamt, 2013). German natural resources base is modest if

a Developing countries are defined according to their Gross National Income (GNI) per capita per year.

Countries with a GNI less than 11 905 US$ are defined as developing. b http://data.worldbank.org/indicator/NY.GNP.PCAP.CD

c http://databank.worldbank.org/data/home.aspx

4

compared with Russian one. It includes iron ore, coal, natural gas, lignite, uranium, potash, timber

copper, nickel and others, but in smaller amounts. Germany is ranked among the leading natural

resources exporting and importing countries, with an export share of 2,4 % of the world natural

resources trade and 6 % for imports (World Trade Organization, 2010). There are 14 national parks

and 14 biosphere reserves in Germany (Statistisches Bundesamt, 2013). Human activity has notably

modified the original landscape through deforestation, agriculture, drainage of wetlands, mining, road

construction, urbanization and others. Nevertheless, environmental management in Germany is well

organized and oriented to joint responsibility and public participation.

In terms of LCA experience, the difference is also significant between the two countries. The LCA

methods started to be known in Russia at the end of 1990s when ISO standard series 14040s were

translated into Russian language (Prityjalova, 2007). Nevertheless, in Russia LCA methodology has

not yet received significant development and wide practical application (Ulanova & Starostina, 2012).

In Germany, the first case studies in LCA became publicly available even in the 1970s. Since then,

many German companies have introduced, or plan to introduce, LCA in their environmental

management system (Frankl & Rubik, 1998). The main driving factor for LCA application has been its

cost-saving opportunities (Frankl & Rubik, 1998). In Germany, companies using LCA often use

material balances and energy efficiency analyses and/or balances. Several popular LCA software

packages have been developed in Germany, for example, GaBi, Umberto and GEMIS.

However, there is an important resemblance: the governments play an essential role in environmental

protection both in Russia and Germany. The application of policy-oriented, transparent and accessible

impact assessment methods for LCA can bring significant benefit to the linkage of LCA and

environmental policy in both countries, making the individual political priorities accessible for LCIA.

1.2. Goals of the thesis

Within this context, the goal of the thesis is to develop two sets of national eco-factors under country-

specific political environmental targets, based on the Ecological Scarcity principle, for Russia and

Germany, and test them for the impact assessment of a case study. The sets of national eco-factors can

reveal major differences in LCIA results according to the specific national environmental priorities

and current environmental situation. The thesis aims to contribute to some of the research needs for

LCIA, for example, promotion geographical differentiation for LCIA methods on country level and

improving the decision support function of LCA and LCIA through providing results that are easier to

interpret for non LCA practitioners. The lessons learned can commit to the development of the

Ecological Scarcity method framework and to its further and wider application over the world.

To achieve the main goal, the following sub-goals were formulated and completed:

• Characterize current environmental situation in Germany and Russia for the identification of

the current flows;

• Study national and international agreements in order to define the national environmental

targets for Russia and Germany that are the basis for critical flow definition;

• Calculate the sets of national eco-factors for Germany and Russia for as many substances and

environmental issues as possible according to the available information;

• Identify national hot spots in terms of environmental impacts for Germany and Russia using

the calculated set of eco-factors;

5

• Test the set of eco-factors developed for Russia and Germany with a case study and interpret

the results;

• Point out the strength, limitations and challenges of the Ecological Scarcity method based on

the experience for Germany and Russia;

• Based on the experience of the eco-factors development and application, give

recommendations for further development and application of the method in other countries.

1.2.1. Structure of the thesis

As shown in Figure 2 , the thesis contains 8 chapters.

Chapter 1 has presented the research topic and objectives of the thesis and described the main goal

and research needs.

Chapter 2 includes general information about LCA and its framework according to the ISO 14040/44

(section 2.1). The chapter focuses on several elements of LCIA, characterization, normalization and

weighting (section 2.2). The description and overview of the Ecological Scarcity method is presented

in section 2.3. Regarding the policy orientation of the method, the information about the

environmental policy on international and national levels in Russia and Germany is also described in

section 2.4.

Chapter 3 explains the methodology that was applied to calculate the set of national eco-factors in

accordance to the Ecological Scarcity principles. It includes general information about the main

sources of data, the assumptions and derivations for eco-factors calculation, characterization and mass

flows.

The result of the eco-factors calculation for Russia and Germany are presented in Chapter 4 and

Chapter 5, correspondingly. Russian part has data for 5 environmental issues (emissions to air, surface

water, sea water, resource consumption and waste) and 12 substances and substance groups. German

part includes 3 categories (emissions air, surface water and resources) and 16 substances and

substance groups.

Chapter 6 tests the set of eco-factors developed for Russia and Germany, as well as the reference set

for Switzerland, in a case study with different material options for a bike’s frame.

Chapter 7 contains the discussion of the results from chapters 4, 5 and 6, including limitations and

challenges of the Ecological Scarcity method application.

Chapter 8 summarizes the results with respect to the goal of the thesis and presents relevant

conclusion and recommendation for further research.

6

Figure 2: Structure of the thesis

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 6

Chapter 5

Chapter 6

Chapter 7

Chapter 8

INTRODUCTION

BACKGROUND

• LCA • LCIA

methods • Ecological

Scarcity method

Environmental

policy:

• Russia

• Germany

METHODOLOGY

RESULTS

Russian

eco-factors

German

eco-factors

Case study

DISCUSSION

CONCLUSIONS AND OUTLOOK

7

2. Background

The chapter contains general information about LCA (section 2.1.) and its stages: goal and scope

definition (2.1.1.), inventory analyses (2.1.2.), life cycle impact assessment (2.1.3.) and interpretation

(2.1.4.). Special focus is made in the chapter for LCIA step. Section 2.1.3. briefly describes the

mandatory and optional elements of the life cycle impact assessment. In sub chapter 2.2., three

elements of LCIA, characterization (2.2.1.), normalization (2.2.2.) and weighting (2.2.3.), are

considered with respect to their connection with existing LCIA methods. The Ecological Scarcity

method that is the object of the study in the thesis is described in section 2.3. This section contains

general information about the method development (2.3.1.), its principals (2.3.2.) and features (2.3.3.).

In order to fulfill one of the sub goals formulated in introduction, section 2.4 has information about the

environmental policy on two levels, international (2.4.1.) and national, for Russia (2.4.2.) and

Germany (2.4.3.). The subsection 2.4.1. gives insight to the main organizations and agreements in the

field of environmental policy on international level. The subsections for Russia (2.4.2.) and Germany

(2.4.3.) contain the overview of some main internal authorities and characterize the environmental

policy for these countries.

Figure 3: Structure of Chapter 2

LCA (2.1.)

Goal and scope (2.1.1.)

LCI (2.1.2.)

LCIA (2.1.3.)

LCIA methods (2.2.)

Charachterization (2.2.1.)

Normalization (2.2.2.)

Weighting (2.2.3.)

Ecological Scarcity method (2.3.)

Development (2.3.1.)

Principals and formula (2.3.2.)

Charachteristics (2.3.3.)

Interpretation (2.1.4.)

Environmental policy (2.4.)

International (2.4.1.)

National

Russia (2.4.2.)

Germany

(2.4.3.)

8

2.1. Life cycle assessment

Life cycle assessment (LCA) is a standardized method for assessing the environmental aspects and

potential impacts associated with a system or serviced. ISO 14040 describes the main principles and

framework of LCA, while ISO 14044 details the requirements for conducting an LCA (Finkbeiner,

Inaba, Tan, Christiansen, & Klüppel, 2006; ISO, 2006a). The methodology assesses the whole-of-life

implication of a product from the resources extraction, through production, package, transporting and

use, up to the final disposal (JRC - EC, 2010a). Because LCA studies the whole product system, it

helps to avoid solving an environmental problem by creating others. LCA shows where environmental

impacts take place across the entire product system, seeks to describe these impacts in quantitative

form and interpret them (Baumann & Tillman, 2004; JRC:The European Commission, 2010).

According to the international standards, LCA can assist in diverse aspects: marketing, decision

making on different levels, learning and exploring the product system and possible improvements of

the environmental performance (see Figure 4). Moreover, LCA is a quantitative tool that is widely

used for the development, monitoring and implementation of environmental policy in public and

private sectors (JRC - EC, 2010c). According to the ILCD Handbook (JRC - EC, 2012) industry

started to use LCA in the late 1980s and still the most of the LCA activities are carried out in industry.

It helps to gain better understanding of the supply chains, support the specific product decisions and

compare alternatives with respect to materials or technologies (JRC - EC, 2012). The LCA can also

support decision making in policy, through the communication of industry to authorities, for example,

in the context of stakeholder communication on policy development, or green NGO’s promotion for

policy decision support (JRC - EC, 2012).

There are four phases in an LCA study (see Figure 4). First step is the goal and scope definition, which

aims to specify the purpose of LCA and to define the product system to be assessed. The next phase,

the inventory analysis, includes the data collection, design of the LCA model and calculation of the

resource use and formed emissions. During the third, impact assessment phase, the used resources and

emissions are connected with environmental impact categories through classification and

characterization. The last step in LCA study is the interpretation of the results of the LCI and LCIA

phases. The final results of an LCA are evaluated and interpreted according to the goal of the study.

d System or service are hereafter called product.

9

Life cycle assessment framework

2.1.1. Goal and scope definition

Goal and scope definition phase has an important role, as it defines the purpose of the overall LCA

study. It specifies the questions to answer by the accomplishment of the LCA study. According to ISO

14040, the goal of an LCA states the reasons to carry out the study and its planned application, to

whom and how the results are intended to be communicated.

The scope should be defined the way that the study is appropriate and sufficient to address the goal.

The scope includes: description of the product system, the functional unit (FU), the reference flow, the

system boundaries, the categories and the methods to consider in the LCIA, allocation, assumptions

and limitations, data requirements and level of detail, type of reporting and critical review.

Functional unit should refer to the function of the product. The purpose of the FU is to provide a

reference to relate inputs and outputs in the inventory. That will provide the comparability of LCA

results on a common basis (ISO, 2006a).

System boundaries define the processes that should be included in LCA study. The elements of the

system boundaries should be related with the goal and scope definition. All the assumptions and cut-

Goal and scope

definition

Inventory analysis

Impact assessment

Interpretation

Direct application: • Product development

and improvement; • Strategic planning; • Public policy making; • Marketing; • Other.

Figure 4: Four phases of a Life Cycle Assessment (ISO, 2006a)

10

off criteria should be underlined and well described. The system boundaries should set the criteria that

are specified enough to deliver the robust result of the study and be feasible the same time.

2.1.2. Life cycle inventory analysis

Life cycle inventory (LCI) analysis is intended to create the system model of the product according to

the requirements of the goal and scope definition (Baumann & Tillman, 2004). LCI includes

construction of flow models, data collection for the activities in the product system, calculation with

relation to the FU and allocation of the flows. Data collection includes the data regarding different

inputs, like energy input, raw materials and other physical inputs, products and waste, emissions to air,

water and soil and other environmental aspects (ISO, 2006a). First validation of the data is carried out

in this phase (JRC - EC, 2012).

2.1.3. Life cycle impact assessment

Life cycle impact assessment (LCIA) is the phase of LCA that aims to describe and to evaluate the

environmental consequences caused by a product system (ISO, 2006b). During the LCIA step the LCI

result is linked with the environmental impacts categories and aggregated. This makes the result more

environmentally relevant, understandable and easier for further communication (Baumann & Tillman,

2004). This phase includes the calculation of the potential environmental impacts in each category

such as climate change, resource depletion, land use, human health and others (JRC - EC, 2012).

LCIA phase should be related to the other steps of LCA to consider possible uncertainties related to

the LCI data quality, cut-offs, averaging, aggregation and allocation within the system (ISO, 2006b).

The LCIA consists of mandatory and optional elements that are presented in Figure 5.

Figure 5: Mandatory and optional elements of life cycle impact assessment (based on ISO, 2006b)

According to the ISO 14044, the distinction feature of mandatory elements of LCIA is scientific

comprehensiveness, i.e. the scientific base for mandatory elements should be internationally accepted.

Moreover, the mandatory elements should be technically valid and environmentally relevant. The

value-choices and assumptions during the mandatory steps should be minimized, to exclude the

subjectivity.

The optional elements are mostly based on value-choices and not scientifically based. Thus, the

individual preferences can change the results of the LCIA and affect the result of LCA. ISO 14044

Mandatory elements

• Selection of impact categories, category indicators and characterization models (at the scope level);

• Classification;

• Characterization.

Optional elements

• Normalization;

• Grouping;

• Weighting;

• Data quality analysis.

11

recommends conducting a sensitivity analysis to assess the consequences on the LCIA results carried

out with value-choices, during the interpretation phase. It should be noted that both types of elements

should be consistent with the goal and scope of LCA.

Mandatory elements of LCIA

Mandatory elements of LCIA include selection of impact categories, category indicators and

characterization models, classification and characterization. Figure 6 shows the mandatory elements of

LCIA, with an example for climate change.

Selection of impact categories, category indicators and characterization models

The selection of impact categories, category indicators and characterization models should reflect the

wide-ranging set of environmental issues related to the product system. The selection should be

justified and consistent in terms of the goal and scope of the study. The impact categories should

perform the impacts of inputs and outputs of the product system through the category indicators (ISO,

2006b). Characterization models describe the relationship between results of LCI and category

indicators, thus, reveal the environmental mechanism, the total of environmental processes connected

with the characterization of impact (ISO, 2006b). The characterization models are used to estimate the

characterization factors.

There are some requirements for the impact categories, category indicators and characterization

models stated in ISO 14044: they should be internationally accepted, scientifically and technically

valid, and environmentally relevant, avoid double counting, and consider spatial and temporal

differentiation, fate and transport of the substance depending on the environmental mechanism and the

goal and scope.

12

Category indicator

Figure 6: Mandatory elements of LCIA and the concept of category indicators with example for climate change (based on ISO, 2006b; Montero, Antón, Torrellas, Ruijs, & Vermeulen, 2011; Schebek, 2012)

Impact category

Characterization

model

GWP10

Characterization

factor

kg CO2-eq/ FU

Environmental

relevance

Life cycle inventory results SO2, NOx, HCl,

CO2, SF6, CH4,

etc.

(kg/FU)

LCI results assigned to

impact category

Global warming

GHG (CO2, SF6,

CH4, etc. assigned

to global

warming)

Baseline model

for 100 years of

IPCC

GWP100

0

GWP100

Category endpoint(s)

Coral reefs,

forests, crops,

etc.

Infrared radiative

forcing is a proxy for

potential effects on

the climate,

depending on the

integrated

atmospheric heat

adsorption caused by

emissions and the

distribution over time

of the heat absorption

Envi

ron

men

tal m

ech

anis

m

Sele

ctio

n

Cla

ssif

icat

ion

C

har

acte

riza

tio

n

Example

13

Classification

Classification is the assignment of the inventory results to the chosen impact categories, in other

words, arrangement of the inventory results in accordance to the environmental impact they contribute

to. For instance, CO2, SF6 and etc. emissions are assigned to the impact category climate change (see

Figure 6). Classification should indicate whether the inventory results relate to one or more than one

impact category, including parallel or serial mechanisms (ISO, 2006b).

Characterization

Characterization is the calculation of the category indicators results. It is derived from the

characterization model. Characterization factors express the impact of the elementary flows in terms of

equivalent units, which are measured against a reference substance for each of the impact categories.

The converted results are aggregated within the same impact category. As an example, in Figure 6 the

greenhouse gas emissions (GHG) are aggregated to the global warming impact category. To get the

category indicator result, the emissions are converted with the characterization factors, global warming

potential (GWP), in relation to equivalent units, namely, kg of CO2-equivalents. The characterization

factors are defined with the characterization model of the Intergovernmental Panel on Climate Change

(IPCC). Thus, the aggregated result for the impact category is measured in the equivalent units.

Optional elements of LCIA

The optional elements of LCIA include normalization, grouping, weighting, and additional LCIA data

quality analysis. The application of optional elements should correspond to the goal and scope of

LCA study and be carefully explained in terms of transparency. Transparency is essential for the

optional elements, as they are mostly based on value-choices and may use data from the outside of

LCIA framework.

Normalization

Normalization is the relative calculation of the LCIA results by dividing the category indicator result

by the reference flow for specific spatial or temporal scales, for example, total input and output for a

specific area, baseline scenario, etc. The main aim of the normalization step is to get the idea about the

magnitude of the environmental impacts. With the normalization step it is possible to assess, for

example, how big is the impact caused by the product in relation to the total impact of the region

where the product is produced.

Grouping

Grouping is the combination of impact categories into sets. There are two options within grouping: to

sort or to rank impact categories. Sorting has nominal basis and ranking has value-choices basis. An

example, for the sorting is grouping by global, regional or local impacts, and for the ranking – impacts

with high, medium, low priority.

Weighting

Weighting expresses the relative importance of the different environmental impacts within the study.

Different environmental impacts related to the life cycle of a product can be scaled through the

weighting. Weighting is based only on value-choices, depends on the priorities of different entities,

societies, administrations and etc. Thus, weighting is not scientifically based. Usually, it is used to sum

the different impact categories using the weighting factors.

Additional LCIA data quality analysis

Additional LCIA data quality analysis is used, when there is a need for better understanding of

significance, sensitivity and uncertainty of LCIA results. According to ISO 14044, there are specific

techniques to conduct the additional LCIA data quality analysis: gravity analysis, uncertainty analysis

14

Interpretation

and sensitivity analysis. Gravity analysis is used for identification of the data that have the largest

contribution to the indicator result. Uncertainty analysis shows how the uncertainties in data and

assumptions in calculations influence the LCIA results. Sensitivity analysis reveals how alterations of

data and methodological choices change the results of LCIA.

2.1.4. Interpretation

The interpretation phase of LCA considers the data of inventory analysis and impact assessment

together. Interpretation delivers the result in consistence with the goal and scope of LCA study.

Interpretation can be an understandable, complete and consistent form of the conclusions or

recommendations to the decision makers in conformity with the goal and scope. The relationship of

the interpretation phase to other phases of LCA is shown in Figure 7.

Life Cycle Assessment framework

Inventory analysis

Goal and scope

definition

Impact

assess-

ment

Conclusions, limitations and

recommendations

Identification

of significant

issues

Evaluation by: • Complete-

ness check;

• Sensitivity

check;

• Consistency

check;

• Other.

checks.

Direct

applications

• Product

development

and

improvement;

• Strategic

planning;

• Public policy

making;

• Marketing;

• Other.

Figure 7: The relation between elements within the interpretation phase with the other phases of LCA (ISO, 2006b)

15

2.2. Elements of LCIA within existing LCIA methods

Starting from the early 1990s various LCIA methodologies have been developed (JRC :The European

Commission, 2010). The different LCIA methodologies represent the different ways to take into

account the complexity of the environmental problems from the different points of view and

environmental priorities. LCIA deals with the inventory analysis results and converts the inventory

inputs and outputs into understandable impact indicators within impact categories. The conversion is

done with factors that are calculated with complex environmental modeling based on environmental

and natural science (characterization) and considering geographical (normalization), political, social

and ethical issues as well (weighting) (Menoufi, 2011). All the LCIA elements have already been

briefly described in subchapter 2.1.3. The subchapters below describe the relation of characterization,

normalization and weighting with existing LCIA methods.

2.2.1. Characterization

Two approaches for characterization can take place along the impact pathway of an impact indicator:

midpoint and endpoint. The midpoint approach is also called problem-oriented approach. It defines the

impact category into real environmental processes as climate change, acidification, etc. In midpoint

approach the environmental relevance is linked to the impact categories and does not model to the end

of the environmental pathway, i.e. to the effects on the areas of protection (AoP) (Jolliet et al., 2004).

Endpoint models use cause-effect chains to model the damage to the area of protection, i.e. human

health, ecosystem quality and natural resources. Endpoint modeling is more complicated and uncertain

by itself, since it should take into account the myriad of processes that can damage the AoP (Bare,

Hofstetter, Pennington, & Udo de Haes, 2000).

The midpoint–endpoint LCIA framework defined by UNEP/SETAC Life Cycle Initiative is presented

in Figure 8. The framework was developed to increase the transparency of the linking between LCI

results, midpoint and endpoint categories. LCI results are linked to midpoint indicators via impact

pathways. These pathways are relatively well scientifically established. The link between some

midpoint and endpoint categories can be uncertain due to the current limits of scientific knowledge or

lacking agreements on the pathway mechanism (Jolliet et al., 2004).

For example, the emissions of GHG like carbon dioxide, methane, nitrous oxide, etc. contribute to the

climate change. Midpoint model measures the potential effect of a certain gas on climate change. The

environmental mechanism and impact of each gas is well known and based on internationally accepted

scientific models. Endpoint model, in the case of GHG emissions, evaluates the potential effects of the

emissions on human health and ecosystem quality. Unlike midpoint model, the pathway mechanism

between climate change and DALY (disability-adjusted life year) or species losses, respectively, is

relatively uncertain. However, the endpoint categories are better connected with areas that have to be

preserved and protected. Thus, endpoint approach seems to be more attractive for decision makers that

are not experienced LCA practitioners.

16

Figure 8: General structure of the LCIA framework (based on Jolliet et al., 2004; JRC - EC, 2010c; Rack, Valdivia,

& Sonnemann, 2013)

Comparing the midpoint and endpoint approaches it is possible to conclude that midpoint results are

less uncertain, but endpoint approach is recommended when there is a need to present only the most

relevant indicators, instead of all indicators (Van Hoof, Vieira, Gausman, & Weisbrod, 2013). Though,

the overall score does not replace more detailed scores (Huppes & van Oers, 2011). For practitioners

using midpoint or endpoint methods usually requires almost identical efforts, i.e. building an

appropriate life cycle inventory and using an existing impact method for translation of emissions to

potential environmental impacts. There are some methods that combine both of approaches.

There is a big variety of LCIA midpoint/endpoint methods that have been developed to address

different issues. The choice of the method depends on the goal and scope of LCA study. Some of the

frequently used LCIA methods are listed in Table 2.

Approach Method

Midpoint CML 2002,TRACI, MEEuP

Endpoint Ecoindicator99, EPS 2000

Combined midpoint-endpoint ReCiPe, LIME, Impact 2002+, LUCAS

Table 2: Some of the most frequently used LCIA methods (based on JRC - EC, 2010b)

LCI results

Elementary flows

Midpoint (impact) categories

Climate change

Ozone depletion

Human toxicity

Respiratory inorganics

Ionising radiation

Noise

Accidents

Photochemical ozone formation

Acidification

Eutrophication

Ecotoxicity

Land use

Resource depletion

Desiccation, salination

Endpoint (damage) categories

Human health

Ecosystem quality

Natural resources

Areas o

f pro

tectio

n

17

2.2.2. Normalization

Normalization is an optional element of LCIA that aims to express LCIA indicators in a way that they

can be compared among them (Pennington et al., 2004). As a result of normalization, the indicator

results are divided by a selected reference value. There are two main reasons why normalization is

conducted during LCIA (Goedkoop, Schryver, Oele, Durksz, & de Roest, 2010):

• Identify impact categories that contribute little compared to other impact categories and can be

disregarded in order to reduce the number of issues that need to be evaluated;

• Show the magnitude of the environmental problems produced during the life cycle of the

product.

There are several ways to select a reference value for normalization: system basis ( e.g. an economic

sector), spatial scaling (e.g. national, regional, local), temporal scaling (e.g. per year), as a ratio of one

alternative to another within the same LCA study, and others (Dahlbo et al., 2012; EPA, 2006). The

choice of an appropriate reference value should be based on the goal and scope of the study.

The most common procedure is to determine the overall impact category indicators for a region during

a year (Goedkoop et al., 2010). Some of the existing LCIA methods that use spatial scale as reference

value are presented in Table 3.

Reference value Method

World ReCiPe, EDIP97

Continent (Europe) Ecoindicator99, ReCiPe, EDIP97, EDIP2003, IMPACT 2002+

Country TRACI, Ecological Scarcity method, LUCAS

Table 3: Some of the LCIA methods using spatial scale normalization (based on Huppes & van Oers, 2011; JRC-

EC, 2010b)

Normalization step is used to simplify interpretation of LCIA results and support decision making.

The results of normalization may help to define the relative importance of different impacts by

showing the magnitude of each impact of the product in relation to a reference situation. However,

correct interpretation of normalized LCIA results requires information on, how the chosen reference

system influences the results (Dahlbo et al., 2012).

2.2.3. Weighting

Another simplifying approach for decision makers, who are not LCA practitioners, is the aggregation

of indicators into a single-score by using weighting factors (Van Hoof et al., 2013), see section 2.1.3.

The goal of weighting in LCIA is to simplify the interpretation by using an overall indicator of

environmental impact (Huppes & van Oers, 2011). However, weighting is a controversial issue

(Soares, Toffoletto, & Deschênes, 2006). The weighting step is based on judgment, but not on

scientific basis and can be influenced by the different perspectives of individuals, organizations and

societies, thus the different parties can get different results for the same system (ISO, 2006b).

Moreover, the methods and values can be space and time dependent, thus representative for different

scales, for example, global, regional and local (Huppes & van Oers, 2011). There are several methods

to generate the weighting factors (Huppes & van Oers, 2011):

• Panel: based on the decision of a group of experts or different stakeholders;

18

• Monetization: based on the estimation of the cost of the economic damage incurred in an

impact category or the cost necessary to prevent environmental damage;

• Distance to target: based on target values, usually political targets, for substances related to a

specific impact category.

Table 4 lists some of the LCIA methods using weighting factors described above.

Weighting Method

Panel TRACI, Ecoindicator99

Monetization EPS, LIME, ReCiPe

Distance to target Ecological Scarcity method, EDIP97

Table 4: Some of the LCIA methods using weighting (based on Huppes & van Oers, 2011)

Among the proposed methods, weighting based on distance to target is being used in some popular

LCIA methods, like, the Ecological scarcity method. LCIA methods using the distance to target

approach can be considered in the context of integrated assessment modeling (Pennington et al., 2004)

that combines analyses of environmental challenges and solutions, in terms of environmental policy

context. Targets are assumed from the goals of the environmental policy, and distance is measured

between the current state of the environment and the target. Thus, LCIA methods using distance to

target as a weighting factor to define the significance of each environmental impact are policy oriented

and adjusted to the site-specific (national or regional) context. However, the approach must be used

with caution. Distance to target does not deliver scientific information about the linkage between the

different impact categories and does not take into account the effects between impacts (Soares et al.,

2006). The environmental policy goals used for establishing the weighting values are supposed to have

equal importance (Frischknecht et al., 2009). The approach should be used, when a streamlined

approach is desired.

Compared to the science-based methods with midpoint-endpoint approach, the number of policy-

oriented methods with distance to target approach is limited. There is an ongoing need for research in

the clarification of the base of distance to target methods and the interrelationship between distance to

target weighting and aggregated impact category results (Seppälä & Hämäläinen, 2001). It is

important to reduce the subjectivity and exclude the confusion, which environmental indicators are the

most relevant for decision making.

2.3. Ecological Scarcity method

2.3.1. Development of the Ecological Scarcity method

The Ecological Scarcity method was originally developed in Switzerland. In the publication by

Müller-Wenk (1978) one of the main principles of the method was established, namely single-score

index for ecological accounting. Afterwards, the method was further developed by Braunschweig

(1982). The first version of the Ecological Scarcity method was published in 1990 by Swiss Federal

Office for the Environment (FOEN) (Ahbe et al., 1990). It was used for LCA of products and

processes, for example, different packages, and further updated in 1993 (Braunschweig & Müller-

Wenk, 1993).

In 2008 the Ecological Scarcity method was qualitatively updated another time. The formula was

slightly changed and new impact categories, for example, water scarcity, were introduced by

19

Frischknecht, Steiner, & Jungbluth, (2009). The most recent update of the method with the data

reference year of 2011 was published at the end of 2013. This last update reflects new scientific

outcomes, state of environment and environmental targets, changes in international standardization

and experience collected by practical application (Frischknecht et al., 2009). However, the

methodology remains unchanged.

Apart from Switzerland, the Ecological Scarcity method was established in some other countries (see

Table 5). In the 1990s, it was developed for a number of European countries such as, Sweden,

Norway, Belgium, the Netherlands, Austria and others (Doka, 2002; Frischknecht & Büsser Knöpfel,

2013). Beyond Europe, the Ecological Scarcity method has been broadly used in Japan. Based on the

Ecological Scarcity principle, the JEPIX (Environmental Policy Priorities Index for Japan) method

was developed and published in 2004 (Miyazaki, Siegenthaler, Schoenbaum, & Azuma, 2004). JEPIX

covers different environmental aspects, such as global warming, ozone depletion, water quality, waste

management, noise and others. Due to the publication of a new version of the Swiss Ecological

Scarcity in 2009, the Japanese method was updated with accordance to the introduced formula and

new categories were added by Büsser, Frischknecht, & Kono (2012).

20

Table 5: Spreading of the Ecological Scarcity method (based on Ahbe et al., 1990; Büsser et al., 2012; Frischknecht & Büsser Knöpfel, 2013; Doka, 2002; Frischknecht et al., 2009; Lindfors et al., 1995; Miyazaki et al., 2004)

The Ecological Scarcity approach can be used to establish Ecological Scarcity method valid for other

nations or political entities (Frischknecht & Büsser Knöpfel, 2013). The environmental targets set by

the concerned country and information regarding the current environmental state in the region is the

base for the assessment criteria of the method. It should be underlined that the individual targets are

influenced by technical, social, economic, policy conditions and are not determined only by the

environmental importance of the effect (Huppes & van Oers, 2011). Hence, different countries can

have different relative importance of the same kind of emissions, for example countries with stricter

targets on CO2 may get higher importance for this kind of emissions than countries with softer targets.

2.3.2. The basic principle and formula

The Ecological Scarcity method refers to the group of weighting methods for Life Cycle Impact

Assessment (see section 2.2.3.). The weighting is based on the ratio between the current environmental

situation and environmental protection targets set by the government, so called distance to target

principle. The Ecological Scarcity method is region and time specific (Huppes & van Oers, 2011).The

method converts environmental impacts to the virtual units, eco-points (EP). The elementary flows,

i.e. pollutant or resource, from LCI are multiplied by the specific eco-factor. Eco-factors can be

defined from the Equation 1 (Frischknecht et al., 2009):

Equation 1: Eco-factor formula (Frischknecht et al., 2009)

𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟 = 𝐾 ∙1∙𝐸𝑃

𝐹𝑛∙ (

𝐹

𝐹𝑘)

2∙ 𝑐

K is the characterization factor of the specific pollutant or resource. It is optional and determined only

for those substances that have a defined environmental consequence, for example, global warming.

The characterization factors are taken from existing impact methods.

Fn is the normalization flow. Normalization is used for adjusting the scarcity status to the current

emissions or use of the resource in the region. In most of the cases normalization flow is identical to

current flow.

F and Fk are current and critical flows, respectively. Critical flow is based on the political target for

the specific emissions or resource, while current flow expresses the environmental situation for this

Country Year of development or update

Austria 1996

Belgium 1994

Denmark 1995

Japan 2004, 2012

Netherlands 1993, 1998

Norway 1998

Sweden 1993, 1998

Switzerland 1991, 1997, 1998, 2009, 2013

Characterization

(optional)

Normalization Weighting Constant

21

emissions or resource. The current and critical flows should be measured in the same units, and be

determined with the same system boundaries. The squared ratio of current and critical flow expresses

the weighting on basis of the distance to target. If the current flow is relatively higher than the critical

flow, the square gives the bigger weighting for such substances.

c is a constant (c = 1012

/a), just serves for scaling of eco-factors and has no technical meaning.

EP (eco-point) would be the unit for the result of the formula.

The formula is supposed to be structured according to ISO 14044 by including the following elements:

characterization, normalization, and weighting. However, in ISO 14044, the characterization is

mandatory element (see 2.1.3) and in Equation 1 it is optional.

Equation 2 shows an example of how the eco-factor is calculated for the emissions of sulfur dioxide

(SO2) to air in Germany (see 5.1.5). In the example, normalization flow is equal to current flow (see

section 3.3.). Current flow is 444 kt. It presents current SO2 emissions in Germany and based on

statistical data. The critical flow is target formulated by German authorities for SO2 emissions; it is

equal to 377 kt. The characterization factor for SO2 as a substance of acidifying substances group is 1.

More details regarding the data derivation are in subsection 5.1.5.

Equation 2: Example of eco-factor calculation

𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟 = 1 ∙1∙𝐸𝑃

444 𝑘𝑡 𝑆𝑂2∙ (

444 𝑘𝑡 𝑆𝑂2

377 𝑘𝑡 𝑆𝑂2)

2

∙ 1012 = 3 123 922 633 𝐸𝑃

𝑘𝑡 𝑆𝑂2= 3 124

𝐸𝑃

𝑘𝑔 𝑆𝑂2

For each emissions (e.g. SO2) or resource concerned, the determined quantities (e.g. eco-factor and

elementary flow) are multiplied to produce an EP number, which is then added up to a total. This

procedure is called aggregation (Frischknecht & Büsser Knöpfel, 2013). The eco-factors are expressed

as EP/kg, EP/m3 etc., and work as weighting factors to indicate the importance of environmental

impacts. Environmental impact is measured in physical units (kg, m3, etc.). As a result environmental

impact for different pollutants is expressed in single-score units, eco-points (EP), so the values can be

summed and compared. The Equation 3 corresponds to the core idea of the ecological scarcity method,

since it can be presented in the following form (Miyazaki, 1998):

Equation 3: Calculation of the environmental impact in EP (Miyazaki, 1998)

Environmental Impact in EP= Eco-factor ∙ Elementary flow in Physical units

According to Frischknecht et al. (2009) eco-factors can be regionalized, where required and where

data availability permits, for example, where environmental policy sets targets that vary greatly in

terms of their spatial reference. To define regionalized eco-factors the weighting factor is calculated

on the basis of the current and critical flows of a certain area (see Equation 4).

Equation 4: Regionalized eco-factor calculation (Frischknecht et al., 2009)

𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟𝑅𝑒𝑔𝑖𝑜𝑛 1 = 𝐾 ∙1 ∙ 𝐸𝑃

𝐹𝑛∙ (

𝐹𝑅𝑒𝑔𝑖𝑜𝑛 1

𝐹𝑘𝑅𝑒𝑔𝑖𝑜𝑛 1

)

2

∙ 𝑐

K, c, Fn, EP are the same as in Equation 1. FRegion 1

and FkRegion 1

are current and critical flows

with Region 1 as system boundary.

22

If several regionally specific eco-factors are determined within one country, then these can be used to

calculate the average eco-factor, as shown in Equation 5 (Frischknecht et al., 2009).

Equation 5: Average eco-factor calculation (Frischknecht et al., 2009)

𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟 𝑐𝑜𝑢𝑛𝑡𝑟𝑦 = 𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟𝑅𝑒𝑔𝑖𝑜𝑛 1 ∙ 𝑟1 + 𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟𝑅𝑒𝑔𝑖𝑜𝑛 2 ∙ 𝑟2 + ⋯

r1, r2 are share of the current flow of Region 1 and Region 2 in the current flow of the whole country or

bigger region.

The quadratic function of the weighting factor in Equation 4 gives greater weight to regions where

environmental pressure is higher in Equation 5 (Frischknecht et al., 2009).

2.3.3. Characteristics of the Ecological Scarcity method

The Ecological Scarcity method deals with environmental interventions, midpoint impact categories

and characterization models, although, results of the assessment are measured in single-score, which is

typical for endpoint approaches. Such a combination may adjust the higher transparency compared to

endpoint approach and less complexity for interpretation compared to midpoint approach (see Figure

9). Though, the method is able to present the result of assessment as single-score, it does not use only

the endpoint impact categories, i.e. areas of protection.

23

Figure 9: Degree of transparency and ability to interpret and Ecological Scarcity method (based on Huppes &

Oers, 2011; Itsubo, 2000)

All the assessed impact categories or environmental interventions are measured in the same units, eco-

points. Such results may be easier to understand and interpret for non LCA practitioners, as decision

makers. Moreover, the environmental impacts from different emissions and consumptions can be

added and compared. The aggregated results can be useful for rough comparison of several

alternatives. However, the aggregated result can be handled for management levels, but not, for

example, for product development, when the detailed information is more desirable (Braunschweig,

2013).

Some limitations of the method are related to its nature as a weighting method. Weighting in LCIA is

mainly based on value-choices (see section 2.2.3.). According to the ISO 14044 (ISO, 2006b), it is not

allowed to use weighting for comparative studies intended to be disclosed to the public. Nevertheless,

the method can be useful for internal life cycle assessment studies and operational purposes

(Frischknecht & Büsser Knöpfel, 2013).

The basis for weighting in the Ecological Scarcity method is the relative importance of the emissions

or use of resources according to the targets in the environmental policy. Thus, the Ecological Scarcity

method itself does not consider the harmfulness of the effects of different kind of emissions and

consumptions, i.e. the various goals of environmental policy have equal importance and the actual

weighting across the problems is missing (Huppes & van Oers, 2011). The method assumes that the

targets defined by environmental policy already have a scientific base. It measures the damage degree

of each emission and consumption according to the target set by the government. The method relies on

LCI result

Midpoint categories

Endpoint categories

Total impact in single

score

Inte

rpre

tati

on

ea

sy

med

ium

Inte

rven

tio

ns

low medium high Transparency

Ecological Scarcity method

dif

ficu

lt

24

the principle of the separation of powers: scientist, lawmakers and developers of life cycle assessment

(Frischknecht & Büsser Knöpfel, 2013), that is designed to exclude the influence of the interested

parties. The scientists provide the information about environmental impacts of the emissions, for

example, toxicity of the substances or negative health effects related to certain emission. Lawmakers

develop environmental targets taking into account the scientific knowledge. The developers of life

cycle assessment, i.e. companies, research institutes, adopt assessment criteria (Frischknecht & Büsser

Knöpfel, 2013). Nevertheless, assessing environment with this method is rather from political, than

scientific, point of view. Government environmental targets are the result of a process in which

different stakeholders can participate and not only environmental, but economic and social aspects are

taken into account.

With the Ecological Scarcity method it is theoretically possible to assess a wide range of

consumptions and emissions (Frischknecht & Büsser Knöpfel, 2013). However, if there are gaps in the

environmental legislation, this can lead to incomplete set of eco-factors. Lack of eco-factors limits the

impact assessment: if major aspects for the assessment are not cover the method application need to be

used with caution (Braunschweig, 2013). Lack of data regarding current environmental state has the

same effect. The data used for the calculation of eco-factors should be taken from publicly available

sources. That is intended to make the method transparent and traceable.

The Ecological Scarcity method is country specific. However, the eco-point approach can be used

worldwide, the principle and formula of the method remains unchanged (Frischknecht & Büsser

Knöpfel, 2013). Every country or region can have its own set of eco-factors based on the own

environmental situation and political targets, thus LCA results for different countries or regions cannot

be directly compared.

The method has temporal representativeness, and, as a result, it should be regularly updated in

accordance to relevant changes in environmental policy and situation and to be up-to-date with

scientific knowledge (Frischknecht & Büsser Knöpfel, 2013). Using the set of eco-factors without

updating for current situation can be misleading and not valid after a certain period. The formula is

uncomplicated and stable, so the update is feasible and strongly recommended.

2.4. Environmental policy

Environmental policy refers to the commitment of an organization to the laws, regulations, and other

policy mechanisms concerning environmental issues and sustainability. Environmental issues include

air, water, soil pollution, waste management, biodiversity and ecosystem management, preservation of

natural resources and wildlife (McCormick, 2001). Environmental policy considers also the social

dimension, like quality of life and human health, and an economic dimension, for example resource

management. Generally, environmental policy can be defined as actions toward the prevention of

harmful effects on the environment, natural resources and human health. Environmental policy can be

implemented both on national and international levels. Subchapters below have the information about

international agreements for environmental protection (2.4.1.) and basic information about national,

Russian (2.4.2.) and German (2.4.3.), policy, instruments used by national governments to implement

their environmental policies.

2.4.1. International agreements for environmental protection

Though, the first multilateral environmental treaties have been already agreed in the 19th century, e.g.

Convention on the Rhine, (Stakeholder Forum, 2004), Stockholm Declaration on the Human

25

Environment can be seen as the forerunner of modern international low on the environment (Francioni

& Bakker, 2013). The declaration was adopted within the context of the first United Nations (UN)

conference in 1972 in Stockholm.

The United Nations is an intergovernmental organization that promotes international cooperation.

There are more than 190 countries members of UN. There are several institution and specialized

agencies within the UN that are dealing with the environmental issues and support sustainable

development, United Nations Environmental Programme (UNEP), Commission on Sustainable

Development (CSD), United Nations Industrial Development Organization (UNIDO), World Bank

Group (WBG), World Health Organization (WHO), World Meteorological Organization (WMO),

United Nations Development Programme (UNDP), United Nations Economic Commission for Europe

(UNECE), Food and Agriculture Organization (FAO) and others.

In terms of the international environmental agreements the UNEP plays key role. Since the formation

of UNEP in 1972 the number of international environmental agreements and international treaties,

which are designed to protect the environment or nature, has significantly risen (Stakeholder Forum,

2004). Moreover, according to Ivanova (2005) UNEP performs the anchor role for the global

environment. UNEP does not perform any direct monitoring of its own, like, for example, the WMO

or WHO. It has coordinating function in order to collect, analyze, and integrate data from UN agencies

and such organizations as universities, science institutes, and NGOs, to broader assess of global,

regional and national environmental conditions and trends (Ivanova, 2005) and develop policy

recommendations. As mentioned above, UNEP has played a leading role in establishing the system of

environmental law through the creation of environmental conventions or multilateral environmental

agreements (MEAs). The key areas of the MEAs includes oceans and regional seas, biodiversity,

chemicals and hazardous wastes, energy, climate change and atmosphere, nuclear energy and the

testing of nuclear weapon, freshwater and land (Stakeholder Forum, 2004).

MEAs enter into force after a series of institutional steps. Basically, the phases that an agreement goes

through are (UNEP, 2010):

• Adoption: the ending of text negotiation and the beginning of the process that an international

treaty passes through before enforceability;

• Signature: expresses readiness of country to proceed with the steps needed to fulfill entering

into force procedures. However, for multilateral agreements, this is a necessary but not

sufficient step for the application of the treaty;

• Ratification, acceptance, or approval: action by which a state specifies its assent to being

bound by the treaty after completion of required national constitutional procedures for

ratification or accession or approval depending upon the country’s legal system. A certain

quantity of states must ratify a treaty before it enters into force. Ratification and

acceptance/approval also implies that a country will enact national implementing legislation to

put national effect to the multilateral treaty;

• Entry into force: multilateral treaties enter into force after an established period has elapsed

subsequent to a set number of states ratifying or acceding to the agreement;

• Accession: this is the act by which a state accepts to become a Party to an agreement whose

text has been negotiated, adopted and signed by other countries;

26

• Withdrawal or denouncing: countries can withdraw or denounce themselves from some

international agreements in accordance with the procedure set in that instrument.

Figure 10 shows some of the international environmental agreements under UN bodies including

UNEP that are relevant in the terms of the thesis. The size of the circles reflects the amount of the

parties signed and/or ratified the treaty. Some of them are further described below.

Figure 10: Timeline of some of the UN Conventions

Convention on Long-range Transboundary Air Pollution

The Convention on Long-range Transboundary Air Pollution (CLRTAP) opened for signature in 1979

and entered into force in 1983. The objective of the Convention is to protect the human environment

from the air pollution and to limit, reduce and prevent air pollution including long-range

transboundary air pollution (UNECE, 1979). The Convention has been extended by eight protocols.

The protocols establish specific measures to be taken by Parties to reduce their emissions of air

pollutants. The protocols to the CLRTAP are in the Table 6.

CLRTAP

Basel Convention

Vienna Convention

UNFCCC

Aarhus Convention

Rotterdam Convention

Stockholm POPs Convention

1975 1980 1985 1990 1995 2000 2005

27

Year, place Protocol Objective

1984, Geneva Protocol on Long-term Financing of the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP)

Collection of emissions data for air pollutants, measurement of air and precipitation quality, modeling of atmospheric dispersion

1985, Helsinki Protocol on the Reduction of Sulphur Emissions or their Transboundary Fluxes by at least 30 per cent

Reduction of the annual emissions of sulphur compounds or their Transboundary fluxes

1988, Sofia Protocol concerning the Control of Nitrogen Oxides or their Transboundary Fluxes

Freeze emissions of nitrogen oxides or their transboundary fluxes

1991, Geneva Protocol concerning the Control of Emissions of Volatile Organic Compounds or their Transboundary Fluxes

Control and reduce emissions of VOCs in order to reduce their transboundary fluxes and the fluxes of the resulting secondary photochemical oxidant products

1994, Oslo Protocol on Further Reduction of Sulphur Emissions

Control and reduce the sulphur emissions and to ensure, as far as possible, that depositions of oxidized sulphur compounds in the long term do not exceed critical loads

1998, Aarhus Protocol on Heavy Metals Control and reduce emissions of three particularly harmful metals: cadmium, lead and mercury

1998, Aarhus Protocol on Persistent Organic Pollutants (POPs)

Control, reduce or eliminate discharges, emissions and losses of persistent organic pollutants

1999, Gothenburg Protocol to Abate Acidification, Eutrophication and Ground-level Ozone

Control, reduce and set emissions ceilings for four pollutants: sulphur, NOx, VOCs and ammonia.

Table 6: Protocols to the Convention on Long-range Transboundary Air Pollution (www.unece.org)

Vienna Convention

The Vienna Convention was agreed in 1985 and entered into force in 1988. In terms of universality, it

is one of the most successful treaties of all time, having been ratified by 197 states and the European

Union. The Vienna Convention became the first Convention of any kind to achieve universal

ratification. The convention is a framework for the protection of the ozone layer, the objectives of the

Convention were to promote cooperation in terms of “systematic observations, research and

information exchange on the effects of human activities on the ozone layer and to adopt legislative or

administrative measures against activities likely to have adverse effects on the ozone layer” (UNEP,

1988). Nevertheless, it does not require countries to take concrete reduction responsibilities for the

chemical agents causing ozone depletion. In order to set the concrete actions to control ozone

depleting substances the parties agreed the Montreal Protocol on Substances that Deplete the Ozone

Layer under the Convention.

The Montreal Protocol is a treaty designed to protect the ozone layer by phasing out the production of

numerous substances supposed to be responsible for ozone depletion. The basis for elimination of the

substances is developments in scientific knowledge, taking into account technical and economic

consideration the developmental needs of developing countries (UNEP, 2000). The protocol was

opened for signature in 1987 and entered into force in 1989. Since then, it has been amended seven

times, in 1990 (London), 1991 (Nairobi), 1992 (Copenhagen), 1993 (Bangkok), 1995 (Vienna), 1997

(Montreal), and 1999 (Beijing).

28

Basel Convention

The Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and Their

Disposal is a treaty that was designed to ensure that the management of hazardous wastes and other

wastes including their transboundary movement and disposal is consistent with the protection of

human health and the environment whatever the place of disposal (UNEP, 2011). However, it does not

address the movement of radioactive waste. The Convention is also intended to minimize the amount

and toxicity of wastes. The Convention was opened for signature in 1989, and entered into force in

1992.

UNFCCC

The objective of the United Nations Framework Convention on Climate Change (UNFCCC) is to

achieve stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent

dangerous anthropogenic interference with the climate system. Such a level should be achieved within

a time frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food

production is not threatened and to enable economic development to proceed in a sustainable manner

(UN, 1992b). The UNFCCC was opened for signature in 1992 and entered into force in 1994. In 1997,

the protocol to the United Nations Framework Convention on Climate Change (the Kyoto Protocol)

was concluded and established the obligations for developed countries to reduce their greenhouse gas

emissions (UN, 1998). The protocol entered into force in 2005. There are two commitments periods

for binding the limitations. The first commitment period applies to emissions between 2008 and 2012,

and the second commitment period applies to emissions between 2013 and 2020.

Aarhus Convention

The UNECE Convention on Access to Information, Public Participation in Decision making and

Access to Justice in Environmental Matters (the Aarhus Convention) was adopted in 1998 at the

Fourth Ministerial Conference in the 'Environment for Europe' process. The subject of the convention

affects the relationship between public and governments. The objective of the Aarhus Convention is to

contribute to the protection of the right of every person of present and future generations to live in an

environment adequate to his or her health and well-being (UNECE, 1998a). The three pillars of the

Convention are access to information, public participation in decision making and access to justice in

environmental matters. On the scope the Aarhus Convention is regional (European). Nevertheless, it is

universal, and is open for any country that would like to join.

Rotterdam Convention

The objective of the Rotterdam Convention on the Prior Informed Consent Procedure for Certain

Hazardous Chemicals and Pesticides in International Trade is to promote shared responsibility and

cooperative efforts in the international trade of certain hazardous chemicals in order to protect human

health and the environment from potential harm and to contribute to their environmentally sound use

(UNEP, 2005). The Convention was adopted in 1998 and entered into force in 2004.

Stockholm POPs Convention

The Stockholm Convention on Persistent Organic Pollutants was adopted in 2001 in Stockholm and

entered into force on 17 May 2004. The objective of the convention is to protect human health and the

environment from persistent organic pollutants (POPs). Governments acting alone cannot protect their

citizens or their environment from POPs, because of their long range transport. In response to this

global problem, the Stockholm Convention requires its parties to take measures to eliminate or reduce

the release of POPs into the environment (UNEP, 2009).

29

2.4.2. Environmental policy in Russia

The Russian Federation is a federal semi-presidential republic, comprising 83 federal subjects. There

are three types of authorities involved in environmental policy in Russia: the bodies of general

competence, the special authorities devoted to environment and other authorities that have some of the

functions in the field of environmental issues and regulate coextensive issues like safety and health

safety (Bogolubov, Kichigin, & Sivakov, 2008).

The bodies of general competence include the president, who is a guarantee of the ecological rights of

the Russian population, and the government, which provides united state environmental policy. The

structure and hierarchy of Russian special environmental authorities are presented in Figure 11. The

Ministry of Natural Resources and Environment (Minprirody) is the federal executive authority

performing functions of public policy making and regulation in the field of the natural resources, water

bodies, forests, environmental monitoring and pollution control, radiation and others and

implementation and statutory regulation, including issues of waste management and state

environmental assessment (Government of the Russian Federation, 2008). Besides the above

mentioned functions, the Ministry shall organize and ensure compliance with the obligations arising

from international agreements of the Russian Federation on environmental issues. Thus, the

environmental functions of governmental authorities cover natural resource management and

prevention of environmental quality degradation (OECD, 2006).

30

Figure 11: The structure and hierarchy of Russian specific environmental authorities

As a result of the growing concern regarding the environmental problems and pressure, the

Environmental Doctrine of Russian Federation was published in 2002. The doctrine has identified

specific policy objectives, but the absolute environmental targets were not set. Unfortunately, the

progress in implementing Environmental Doctrine have been slow (OECD, 2006). Several

Russian special environmental authorities

Ministry of Natural Resources and Environment (Minprirody)

The Federal Supervisory

Natural Resources

Management Service

Federal Service for Hydrometeorology

and Environmental

Monitoring (Roshydromet)

Federal Agency for Water Resources

(Rosvodresursy)

Federal Agency for Subsoil

Management (Rosnedra)

Federal Environmental,

Industrial and Nuclear

Supervision Service (Rostechnadzor)

Ministry of Agriculture

Federal Forestry Agency

(Rosleshoz)

Special authorities of the subdivisions

of Russian Federation

For example, regional

Ministries of radiation and

environmental safety

31

implementation challenges were identified, such as poor environmental governance and fragmentation

within the policy making process, lack of appropriate environmental criteria, indicators and

methodologies, missing mechanisms of public participation in environmental assessment, and lack of

environmental skilled professionals (OECD, 2006).

Environmental law is main basis for environmental planning in Russia. This model of environmental

management without time-bound policy targets and wide expert and public participation could hardly

bring serious environmental improvements (OECD, 2006). Another challenge is how to analyze and

monitor the environmental quality. The size and diversity of ecosystems, ranged from polar desert to

temperate rain forest, not balanced allocation of human residence and use of natural resources make

difficult to define what is the overall environmental quality (Henry & Douhovnikoff, 2008).

Though the costs spent on the environmental protection in money equivalent grow every year, the

amount of the costs of environmental protection as a percentage of gross domestic product (GDP)

decreases. According to the official Russian statistic the costs for the environmental protection in 2012

in Russia came to 0,7 % of GDP and, for example, in 2003 the costs were 1,3 % of GDP. The

environmental activities in terms of the budget in 2012 are shown in Figure 12.

Figure 12: Distribution of the costs for environmental activities in Russia in 2012 (based on “Federal State

Statistic Service,” 2013)

Russian environmental policy is still largely guided by the international environmental agenda. Russia

has signed and ratified number of international environmental agreements, such as Kyoto Protocol,

Montreal Protocol, Protocol on Environmental Protection to the Antarctic Treaty, Framework

Convention for the Protection of the Marine Environment of the Caspian Sea, the Basel Convention on

the Control of Transboundary Movements of Hazardous Wastes and Their Disposal, Helsinki

Convention on the Protection of the Marine Environment of the Baltic Sea Area, Gothenburg Protocol,

Stockholm Convention on Persistent Organic Pollutants and other (see Table 7). However Russian

“records on the implementation of the treaties is mixed and it discourages environmental activism”

(Henry & Douhovnikoff, 2008).

21%

43%

9%

8%

4%

15%

Protection of air quality and climatechange

Sewage treatment

Waste treatment

Protection and soil remediation

Saving of biodiversity

Others non specified

32

Agreement Signature Ratification or Acceptance

Entry into force

Kyoto Protocol 11.03.1999 18.11.2004 16.02.2005

Montreal Protocol - 10.11.1988 -

Protocol on Environmental Protection to the Antarctic Treaty

- 01.05.2013 -

Framework Convention for the Protection of the Marine Environment of the Caspian Sea

4.11. 2003 - 12.08. 2006

The Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and Their Disposal

22.03.1990 31.01.1995 -

Helsinki Convention on the Protection of the Marine Environment of the Baltic Sea Area

09.04.1992 - 17.01.2000

Stockholm Convention on Persistent Organic Pollutants

22.05.2002 17.08.2011 -

Table 7: Some of the international environmental agreement signed or/and accepted by Russia

2.4.3. Environmental policy in Germany

The Federal Republic of Germany is a federal parliamentary republic that consists of 16 states. The

environmental protection in Germany is applied at the federal, state and local levels. The main

authority in the field on the federal level is The Federal Ministry for the Environment, Nature

Conservation, Building and Nuclear Safety (BMUB). The ministry is responsible for the development

of regulations, guidelines, and strategies, for promoting ecological clean-up and development, for

international and supranational coordination, global environmental policy, and for promotion of

environmental technologies (Weidner, 1995). In December 2013 the Chancellor issued a decree

transferring responsibility for urban development, housing, rural infrastructure, public building law,

building, the construction industry and federal buildings to the BMUB (BMUB, 2014d).

There are four federal agencies operating under the patronages of the Federal Environment Ministry

(see Figure 13): the Federal Environment Agency, the Federal Agency for Nature Conservation, the

Federal Office for Radiation Protection and the Federal Office for Building and Regional Planning

with the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BMUB,

2014a).

33

Figure 13: Federal agencies operating under the Federal Environment Ministry in Germany

The Federal Environmental Agency (UBA) was established on 22 July 1974. The main tasks of UBA

are the support on the government decisions and research co-ordination, public information,

development of environmental monitoring, planning and information, participation in labeling (Blue

Angel), etc. (Weidner, 1995). Though UBA is considered as a non-executive agency, i.e. it cannot

issue the regulations or perform control functions, it is supposed to be the most important agency in

the environmental policy area in Germany (Weidner, 1995). Some of the reports and studies of UBA

have deep influence on the public discussion and implementation of measures.

The Federal Agency for Nature Conservation (BfN) is the central scientific authority at federal level

for national and international nature conservation and landscape management (BMUB, 2005). The

main tasks of BfN are to advise the Federal Government, to provide support for federal development

programmes, to approve imports and exports of protected animal and plant species, to conduct its own

research and to provide the information about the results of its work (BMUB, 2005). The Federal

Agency for Nature Conservation is also integrated in the UNESCO programme "Mankind and the

Biosphere" (MAB)(BMUB, 2005).

The Federal Office for Radiation Protection (BfS) is in charge to protect humans and the environment

from ionizing and non-ionizing radiation and guaranteeing their safety (BMUB, 2014c). The further

tasks of BfS are the government custody of nuclear fuel, radioactive waste management, safety of

carriage and stocking of nuclear fuels. The BfS works on technical scientific recommendations for

BMUB and supports the elaboration of legislation (BMUB, 2014c).

The Federal Institute for Research on Building, Urban Affairs and Spatial Planning (BBSR) supports

the BMUB in the fields of regional planning, urban development, including building and housing and

international cooperation in these fields (BMUB, 2014b). It also provides the scientific basis for

political decision making (BMUB, 2014b).

Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB)

Federal Environment Agency (UBA)

Federal Agency for Nature

Conservation (BfN)

Federal Office for Radiation

Protection (BfS)

The Federal Office for Building and

Regional Planning with Federal Institute for Research on

Building, Urban Affairs and Spatial

Development (BBSR)

34

On the state level, all 16 federal states in Germany have established a ministry responsible for

environmental matters. The states or “Länder” have the primary responsibility for policy

implementation, but some of them rely more on voluntary approach to comply the environmental

requirements (OECD, 2012). On the local level, there is a possibility of the independent activities in

the field of environmental policy, for example, urban traffic, i.e. establishing environmental zones.

Within these environmental zones there might be used some measures for protection from noise or

traffic bans for certain types of vehicles in order to prevent air pollution.

Apart of the abovementioned organizations, there are some other authorities related with German

environmental policy making, for example, The Federal Ministry of Food and Agriculture (BMEL)

that integrates environmental, climate and energy-related aspects by promoting sustainable agriculture,

and the Federal Ministry for Economic Affairs and Energy (BMWI) that focuses on climate and

environmental sustainability, to promote energy reforms.

Since the 2000s Germany has established ambitious environmental policy framework on the national

level (OECD, 2012). The environmental policy in Germany is cross-cutting task; the environmental

policy framework has been developed in co-operation of the several ministries, e.g., federal ministries

of environment and economy. One of the examples of the co-operation is the Integrated Energy and

Climate program established the target of the 40% reduction of greenhouse gases emissions by the

year 2020 compared with basic year 1990, or the National Sustainable Development Strategy (NHS)

which establishes the targets, goals, indicators and management rules in areas of resource protection,

climate change, air quality, land use, renewable energy, resource efficiency, biological diversity and

others (OECD, 2012).

The budget of the Federal Ministry for the Environment was 1 644 million euro in 2013. However, the

total federal budget amounted 7 397 million euro that comes also from the of other federal ministries,

for example, Ministry of Education and Research that has a task environmental education fundamental

research on environmental protection promoting sustainable development, or Foreign Office, involved

in implementing international agreements and conferences concerning environmental protection

(BMU, 2014). The total federal budget is around 0,3 % of German GDP.

Germany plays proactive role in environmental policy on EU and international levels. Apart of having

signed most of the international agreements in the environmental protection area (see Table 8),

Germany has hosted several UN conferences, for example, convention on climate change in 1999 and

biodiversity in 2008, conference on the Water, Energy & Food security issues in 2011 and launched

together with the European Commission project the Economics of Ecosystems and Biodiversity

(OECD, 2012).

35

Agreement Signature Ratification or Acceptance

Entry into force

Kyoto Protocol 29.04.1998 31.05.2002 16.02.2005

Montreal Protocol - 16.09.1987 -

Convention on Biological Diversity 12.06.1992 21.12.1993 -

The Basel Convention on the Control of Transboundary Movements of Hazardous Wastes and Their Disposal

23.10.1989 21.04.1995 -

Aarhus Protocol 24.06.1998 30.09.2003 -

Gothenburg Protocol 01.12.1999 21.10.2004 -

Stockholm Convention on Persistent Organic Pollutants

23.05.2001 25.04.2002 -

Table 8: Some of the international environmental agreement signed and accepted by Germany

36

3. Methodology for eco-factor calculation for Russia and

Germany

The eco-factors for Russia and Germany, calculated in Chapters 4 and 5, are based on the Ecological

Scarcity principle and formula (see Equation 1). Chapter 3 describes the main elements for eco-factors

calculation, eco-factor itself (3.1.), characterization (3.2.), normalization (3.3.) and weighting (3.4.).

The chapter contains both explanations about the general methodology and the specific methodology

for the thesis. It covers some particular assumptions and counting rules that have been applied to

estimate current and critical flows for Russia and Germany. The structure of the chapter is

schematically showed in Figure 14.


3.1. Eco-factor

Eco-factors are the result of the Equation 1, and they are expressed in eco-points (EP) per physical unit

of environmental pressure (see 2.3.2.). Eco-factors are used to evaluate the environmental impact of

different environmental categories (see 2.3.). There are some principles of the eco-factors

determination according to the Ecological Scarcity principle (Frischknecht & Büsser Knöpfel, 2013)

that have been used in the study and should be underlined.

The eco-factors for the different environmental media are calculated separately, for example, heavy

metals in air and water. The separation is caused by different statuary requirements for different

environmental media (Frischknecht & Büsser Knöpfel, 2013).

If there is a substance that contributes to more than one environmental impact for the same media, for

example, substance HCFC-22 affects global warming and ozone depletion, the substance may be

included in different political targets. In those cases, the eco-factor should be chosen according to the

principle of the highest eco-factor (Frischknecht et al., 2009). Thus, for the evaluation of the

environmental impact in single-score, the environmental impact of the substance in physical units

should be multiplied with the higher eco-factor.

Eco-factor (3.1.)

Charachterization (3.2.)

Normalization (3.3.)

Weighting (3.4.)

Current flow (3.4.1.)

Critical flow (3.4.2.)

37

As it is mentioned in section 2.3.3., the eco-factors must be regularly updated every few years in

accordance with new environmental political targets and scientific findings (Frischknecht & Büsser

Knöpfel, 2013). The update allows evaluating the current environmental situation more objectively,

due to the constantly changing environment. The update can also reveal the overall progress in the

achievement of political environmental targets, and how the relative importance of one or another

environmental issue has changed.

3.2. Characterization in the formula for eco-factors calculation

Characterization is an optional element in the formula for eco-factors calculation (see Equation 1). It is

used for those groups of substances that can be assigned to a specific environmental category (see

example in 2.1.3.). The main function of the characterization is to capture the relative environmental

impact of substances compared to a reference substance, measured with the reference unit

(Frischknecht et al., 2009).

Table 9 lists the characterization factors used in the thesis. There are several requirements that

characterization factors shall fulfill: be based on scientific knowledge and be relevant for the applied

data, e.g. characterization factors based on European models must be investigated if they can be

applied to non-European data (Frischknecht et al., 2009).

Substance group Characterization factor

Abbreviation Reference unit Source

Greenhouse gases Global Warming Potential

GWP kg CO2- eq (IPCC, 2007)

Ozone depleting substances

Ozone Depletion Potential

ODP kg CFC-11- eq (UNEP, 2000)

Acidifying substances

Acidification Potential

AP kg SO2- eq (Guinée et al., 2002)

Table 9: Characterization factors applied for the study

Global worming potential (GWP) is defined as the ratio of the time-integrated radiative forcing from

the instantaneous release of 1 kg of a trace substance relative to that of 1 kg of the reference gas,

carbon dioxide (IPCC, 2007). GWP is expressed as a factor of carbon dioxide (i.e. GWP of CO2 is

standardized to 1). GWP is calculated over a specific time interval, 20, 100 or 500 years. 100 years is

the widely used option in LCIA and accepted in the Kyoto Protocol time horizon (UN, 1998).

As for Ozone depletion potential (ODP), characterization factors refers to the degree of ozone

depletion caused by a substance. To be exact, the ODP is the ratio of the impact on ozone of a

chemical compared to the impact of a similar mass of trichlorofluoromethane (freon-11, CFC-11, or

R-11). Hence, the ODP of CFC-11 is defined as 1. Other chlorofluorocarbons (CFCs) and

hydrochlorofluorocarbons (HCFCs) have ODPs that range from 0, 01 to 1, the halons, up to 10. ODP

is listed in the amendment to the Montreal Protocol (UNEP, 2000).

Acidification potential (AP) is a meter of the acid formation potential (i.e. the ability to form H+ ions).

It is calculated and set against the reference substance, sulphur dioxide (SO2). AP reflects the

maximum acidification potential of a substance. The other acidifying substances are measured in kg

SO2-equivalents. The APs are given by Guinée et al., (2002).

38

3.3. Normalization in the formula for eco-factors calculation

Normalization in the Ecological Scarcity method gives an idea of the magnitude of the result in

relation to a reference situation. In the thesis, normalization flow (used for calculation in Chapter 4

and Chapter 5) has been considered equal to the current flow and represents the national annual levels

of emission and consumption for Russia and Germany. As a priority, the current flow of a country

should be used for normalization (Frischknecht & Büsser Knöpfel, 2013), to show the magnitude of

the environmental problems produced during the life cycle of the product with regard to the actual

country-specific situation.

The normalization flow can differ from the current flow in some cases, for example, if the

environmental policy is guided by the international objectives and not national. For instance, if

German policy regarding a certain emission would be guided only by European Union targets, the

weighting, ratio between current and critical flows (see section 2.3.2.), will reflect the situation in the

European Union, but the reference region is Germany, i.e. the normalization flow is the current flow of

emissions in Germany. For example, for 2020, the EU has made a commitment to reduce overall

greenhouse gas emissions from its 28 Member States by 20 % compared to 1990 level, which was

equal to 5 626 259 741 Mg CO2-eq. The level of emissions in EU 28 in 2012 was 4 544 224 025 Mg

CO2-eq, in Germany the same year it was 939 083 309 Mg CO2-eq. The eco-factor calculation for the

example is shown in the Equation 6.

Equation 6: Example of calculation of eco-factor with different current and normalization flows (GHG

emissions, Germany)

𝐸𝑐𝑜 − 𝑓𝑎𝑐𝑡𝑜𝑟𝐺𝑒𝑟𝑚𝑎𝑛𝑦 =1 ∙ 𝐸𝑃

𝐹𝑛𝐺𝑒𝑟𝑚𝑎𝑛𝑦 ∙ (

𝐹𝐸𝑈

𝐹𝑘𝐸𝑈)

2

∙ 𝑐 =1 ∙ 𝐸𝑃

939 083 309∙ (

4 544 224 025

4 501 007 793)

2

∙ 1012

= 1,09 𝐸𝑃/𝑘𝑔

In the case of Germany, the real target for GHG reduction is not the average of the EU, but 40 %.

Within the thesis this target and actual German flow is used to give the weighting factor for the

problem, i.e. the current and normalization flows are equal. The example shows that in any case

normalization flow should be country specific, even if weighting is defined by international agenda of

the country.

3.4. Weighting in the formula for eco-factors calculation

The weighting in the Ecological Scarcity method is performed on the distance to target basis (see

2.2.3). Weighting is squared ratio of current (F) and critical (Fk) flows (see Equation 1), i.e. national

annual flows for specific emissions or consumption and the limited value for this specific emissions or

consumption over a specific time horizon. The squared ratio makes it feasible to give larger weighting

for substances exceeding current flow (Frischknecht & Büsser Knöpfel, 2013). For example, if the

current emissions is 25 % higher than critical flow, the weighting will be equal 1,57 and for emissions

which has exceeding 50 %, the weighting will be 2,25. Weighting should not have any units; hence the

current and critical flow should be given in the same units (Frischknecht & Büsser Knöpfel, 2013).

3.4.1. Current flow

Current flow is defined with regard to the reduction target, that means that the system boundaries used

to define the current and critical flow should be identical (Frischknecht & Büsser Knöpfel, 2013). In

39

this thesis, two types of sources for the current flow definition are used: national statistics and

statistics by international organizations or programs. For the calculation only publicly available data

has been used. This corresponds to one of the main principles of the Ecological Scarcity method,

transparency and ability to retrace the result. The national statistical reports usually contain some data

regarding environmental issues. The completeness and format of the available data can vary and be

determined by the competent authority, for example state statistics sources. The participation of the

county in some international agreements, for example, Kyoto protocol obliges the country to report to

the responsible organization (in the example UNFCCC) about the progress in the target achievement.

Thus, the reported data by those organizations are used as the current level of emissions in the country.

Regarding the timeframe, in the study the most recently available statistical data have been used. The

preference was given to the national statistical data, if the data were not available or inconsistent to the

international one.

3.4.2. Critical flow

Critical flow is based on political targets defined by competent authorities and accepted at the

governmental level. The target should rely on national or international environmental treaties

supported by the country and should reflect current scientific knowledge and understanding. The target

can be stated for an individual pollutant or resource or for a group of substances, for example, non-

methane volatile organic compounds (NMVOC) or greenhouse gases (GHG).

The critical flow in the thesis has been defined with (see 2.3.):

• Targets corresponding to the precautionary principle (e.g. for GHG in Germany), i.e. reduction

target;

• Targets based on the standards established on the assumption of zero risk for human health

(e.g. particulate matter in Russia), i.e. thresholds.

Reduction target

The precautionary approach was stated as the preferable and recommended by Frischknecht & Büsser

Knöpfel, (2013) for the definition of environmental targets. Moreover, the Rio Declaration on the

Environment and Development (UN, 1992a) proclaims that “lack of full scientific certainty shall not

be used as a reason for postponing cost-effective measures to prevent environmental degradation”.

That means that the environmental pressure should be reduced to avoid possible harmful or adverse

effects, even if there is a lack of scientific knowledge regarding the potential harmfulness of the effect.

With this approach the target are defined by the national authorities, as a percent of the reduction

compare to the base year, and should have the timeframe for fulfillment. After the stated period the

target should be revised and new time framework estimated.

As aforementioned, such targets can be defined by international treaty and/or internal regulations.

International targets are usually designed in such a way that parties have “common but differentiated

responsibilities” that depend on the specific national capacity level to contribute in the reduction of

common environmental problems. The factors defining this national capacity are, for instance GDP,

technological development, scientific knowledge development and others. In some cases, the national

goal can be more strict and ambitious, than the target defined within the international agreement, e.g.

German target for GHG emissions reduction. In such a case the strictest target should be taken into

account for the critical flow consideration, according to Frischknecht & Büsser Knöpfel, (2013).

40

One example of a reduction target driven by national priorities used in the thesis is the target for GHG,

both in Russia and Germany. As well as, German national driven reduction targets for established

indicators for sustainable development (Statistisches Bundesamt, 2012), including environmental ones

related to climate change in addition to GHG, like land use, primary energy consumption. These

environmental issues can be evaluated with the Ecological Scarcity formula, because the reduction

target along with the current state is clearly identified. An example of national targets established due

to international obligations is Germany and the Gothenburg Protocol to Abate Acidification,

Eutrophication and Ground-level Ozone. The protocol aims to cut the emissions level of sulphur

dioxide, NOx, NVOCs and ammonia and define the reduction target for them. Base on the national

ability to reduce the abovementioned emissions the absolute reduction targets have been claimed and

accepted internationally, within the framework of the agreement.

National reduction targets can be more ambitious than international ones and assume larger percent of

reduction than obliged by international protocols. Such targets can be identified internally without

approval from the other parties; however the targets should not be in contradiction with the

international obligation. For example, national targets for GHG in Russia and Germany are stricter

than their obligations according to Kyoto protocol.

Thresholds

In some cases there are not reduction targets available neither at the national or international level, but

the threshold for the emissions or resource consumption is defined. The level of pollution is often

restricted by environmental standards (e.g. sanitary regulations) and legislation (e.g. the

“Environmental Protection Law”). Most standards are defined based on the assumption of zero risk for

human health, based on available scientific knowledge, and apply to the quality of water, air and soil

(OECD, 2006). Most Russian and German standards use the formulation of maximum allowable

concentrations (MACs) as a main parameter of “zero risk”. In spite of science-based, MACs are

political values and can include certain latitude judgment. For example, for highly toxic substances

MACs may be overrated, since they are usually only emitted in accidents at high doses in the

environment and therefore play a minor role for the exposure to the environmental media (Schebek,

2012). In this thesis, MAC is converted to the critical flow, measured in mass units, it should be

multiplying it by the volume (V), where possible (Equation 7).

Equation 7: Example of critical flow calculation with the maximum allowable concentration

𝐶𝑟𝑖𝑡𝑖𝑐𝑎𝑙 𝑓𝑙𝑜𝑤 = 𝑉 ∙ 𝑀𝐴𝐶

where V is the volume of environmental media (in the thesis, water) to which refers the concentration.

An example of national environmental thresholds is MAC for emissions to water. For Russia, the

critical flows for emissions to water are established based on thresholds, due to the absence of

reduction targets or fix limitation expressed in mass units for the corresponding substances. The

thresholds are the allowable concentrations in water bodies for the corresponding substances (N, P,

heavy metals). To translate these thresholds to critical flows, we need to use additional data on the

total mass bodies that we are assessing (water bodies, for the example). However, these data are not

always available. Environmental monitoring data are often measured in concentration but in the total

content of a certain polluting substance. It seems to be inconvenient for eco-factor calculation, as mass

flow data are preferable. The units of eco-factor should be convenient for further application in LCIA,

as it measures in EP per physical unit. For air emissions or emissions to soil, it is even trickier to

convert concentration into mass. To do that a special scientific method or model valid for the

particular country should be applied. The model should provide mass flow data for the specific

41

substance to the environmental media. One examples of such model is the GAINS model that

establishes the level of particulate matter in Russia. However, the amount of the scientific models that

give the information about various emissions on national level is limited.

A fix limitation without timeframe can be considered as a threshold, as well. It means the level of the

emissions should be kept on a certain level without an obligation for the further reduction. An example

of such fix limitation is the level of dioxins emissions to air in Germany, which is limited by Aarhus

Protocol and fixed on the level of year 1990. Thus, the weighting of dioxins emissions is relatively

low due to the significant reduction of the current level of emissions compared to 1990. Nevertheless,

the environmental issue itself is still actual and important.

42

4. Russian eco-factors

The set of Russian eco-factors includes eco-factors for 5 environmental issues (emissions to air,

surface water, sea water, resource consumption and waste) and 12 substances and substance groups

(Figure 15). For each issue and/or subgroup, several substances are assessed. The subchapters (4.1.-

4.5.) contain, for each of the assessed substances, information about political targets and current

situation in Russia, data for eco-factor calculation, like current flow, critical flow and, when needed,

characterization factors. Each subchapter has also information about the emissions trend during last

years and a future forecast, recommendations are provided as well. Finally, in section 4.6., a general

overview of the results in Russia is presented.


4.1. Emissions to air

A high concentration of pollutants in air, such as particulate matters, sulfur dioxide, nitrogen oxides,

carbon monoxide and other specific including, benzo(a)pyrene and formaldehyde, is typical for most

parts of the Russian territory (Ministry of Natural Resources and Environment of the Russian

Federation, 2012). Of course, it has a negative impact on the health of Russian population and natural

ecosystems. Some of these polluting substances also have negative impact on infrastructure, for

example, through corrosion. The main sources of air pollution in Russia are energy sector, transport,

industry and agriculture.

Emissions

Air (4.1.)

GHG (4.1.1.)

ODS (4.1.2.)

PM (4.1.3.)

Surface water (4.2.)

N (4.2.1.)

P (4.2.1.)

Heavy metals (4.2.2.)

Sea water (4.3.)

THP (4.3.1.)

Phenols (4.3.1.)

Resources

Energy consumption

(4.5.)

Waste (4.4.)

Overview (4.6.)

43

According to the Russian hydrometeorology service, in 138 cities of the Russian Federation,

representing around 57 % of Russian urban population, the level of air pollution is characterized as

high and very high. In 2012, cities without high and very high levels of urban air pollution have not

been identified only in 9 subjects of the Russian Federation (Ministry of Natural Resources and

Environment of the Russian Federation, 2012). Apart from the air quality, the global problems of

climate change and ozone depletion are also of great current interest. In the subchapters below,

political target and current situation are described for such emissions, like greenhouse gases (4.1.1.),

ozone depleting substances (4.1.2.) and particulate matter (4.1.3.).

4.1.1. CO2 and other greenhouse gases (GHG)

Political targets and situation in Russia

Global warming is one of the internationally recognized environmental problems. It has been of

particular concern in Russia in the recent decades, due to the fact that a large part of the Russian

territory is located in the polar region. It is particularly threatened by climate change effects, such as

melting of the ice covering the land and polar sea, changes in river flows, as well as transformations in

terrestrial and marine flora and fauna. These kind of effects can be already observed in Russia

(Direction of the President of the Russian Federation on 17th December 2009 N 861-rp, 2009). It does

not only affect environment, but also economic activity, living conditions and human health (Direction

of the President of the Russian Federation on 17th December 2009 N 861-rp, 2009). However, there is

also the opinion that climate change may benefit Russia, because warmer temperatures may increase

productivity of land, and access to the northern regions that are currently covered with ice (World

Bank, 2010). Nevertheless, climate change effect in Russia may also cause negative effects like, new

diseases, infestations, harmful climatic anomalies, and decreases in agricultural productivity, which

offset the advantages of access to more arable land (World Bank, 2010).

Russia officially notified to the United Nations (UNFCC) the ratification of the Kyoto protocol on the

18th November 2004. According to it, the Russian Federation should not exceed the level of emissions

of the base year 1990. Though, on the international level Russia is the fourth world’s largest CO2

emitter (IEA, 2012). This level is, however, far from the unique high level of GHG emissions that

occurred during the soviet period. Therefore, even after years of economic growth, the Russian

Federation is still around 30 % below the emissions limit allowed by the Kyoto protocol. This formal

compliance was the main argument of Russian government to evade additional commitments to

further reduce GHG emissions during the Doha Climate Change Conference in November 2012

(BBC, 2012.). However, in September, 2013 the President of the Russian Federation signed a decree

"On the reduction of greenhouse gas emissions". According to this document, Russia should not

exceed the 75 % of the base year level by 2020 (The presidential decree of the Russian Federation No.

752, 2013).

Characterization

The set of characterization factors for the various GHG emissions included in this section (CO2, CH4,

N2O, CFC, etc.) are the factors included under the so called impact method global warming potential

(GWP100) for 100 years’ time horizon (see 3.2.). The GWP characterization factors were taken from

the report of The Intergovernmental Panel on Climate Change (Solomon et al., 2007).

Current flow

Data used for current flow derives from the official GHG emissions statistic in the UNFCC database

(UNFCCC, 2013). Under the Kyoto Protocol, Russian actual emissions are mandatorily monitored and

44

precisely recorded. In 2011 the total GHG emissions was 2 320 834 383 Mg CO2 equivalents

(UNFCCC, 2013).

Critical flow

Critical flow is calculated as 75 % from the level of the base year 1990 and equals 2 513 958 007 Mg

CO2 equivalent, according to the target stated in 2013 (The presidential decree of the Russian

Federation No. 752, 2013) for 2020.

Eco-factors for CO2 and other greenhouse gases

The eco-factor for CO2 is determined with the main formula for eco-factors calculation (Equation 1) as

it is presented in Table 10. The eco-factors for other GHG gases are calculated in reference to the CO2

eco-factor and multiplying by the aforementioned characterization factors for GWP100 (see Table 11).

Step of the eco-factor calculation (units) Result Reference year/ source of data

Normalization flow (Mg CO2 eq/a) 2 320 834 383

Current flow (Mg CO2 eq/a) 2 320 834 383 2011 (UNFCCC, 2013)

Critical flow (Mg CO2 eq/a) 2 513 958 007

2020 (The presidential decree of the Russian Federation No. 752, 2013)

Weighting (-) 0,85

Eco-factor (EP/kg CO2-eq) 0,37

Table 10: Calculation of the eco-factor for CO2 in Russia

Substance Formula GWP 100 EP/kg

Carbon dioxide CO2 1 0,37

Methane CH4 25 9,2

Dinitrogen oxide N2O 298 109

Sulphur hexafluoride SF6 22 800 8 373

Carbon monoxide CO 1,57 0,58

Chlorofluorocarbons

CFC-11 CCl3F 4 750 1 744

CFC-12 CCl2F2 10 900 4 003

CFC-13 CClF3 14 400 5 288

CFC-113 CCl2FCClF2 6 130 2 251

CFC-114 CClF2CClF2 10 000 3 672

CFC-115 CClF2CF3 7 370 2 706

Halon-1301 CBrF3 7 140 2 622

Halon-1211 CBrClF2 1 890 694

Halon-2402 CBrF2CBrF2 1 640 602

Carbon tetrachloride CCl4 1 400 514

Methyl bromide CH3Br 5 1,84

Methyl chloroform CH3CCl3 146 54

HCFC-22 CHClF2 1 810 665

45


HCFC-123 CHCl2CF3 77 28

HCFC-124 CHClFCF3 609 224

HCFC-141b CH3CCl2F 725 266

HCFC-142b CH3CClF2 2310 848

HCFC-225ca CHCl2CF2CF3 122 45

HCFC-225cb CHClFCF2CClF2 595 219

Hydrofluorocarbons

HFC-23 CHF3 14 800 5 435

HFC-32 CH2F2 675 248

HFC-125 CHF2CF3 3 500 1 285

HFC-134a CH2FCF3 1 430 525

HFC-143a CH3CF3 4 470 1 641

HFC-152a CH3CHF2 124 46

HFC-227ea CF3CHFCF3 3 220 1 182

HFC-236fa CF3CH2CF3 9 810 3 602

HFC-245fa CHF2CH2CF3 1 030 378

HFC-365mfc CH3CF2CH2CF3 794 292

HFC-43-10mee CF3CHFCHFCF2CF3 1 640 602

Perfluorinated compounds


Nitrogen trifluoride NF3 17 200 6 316

PFC-14 CF4 7 390 2 714

PFC-116 C2F6 12 200 4 480

PFC-218 C3F8 8 830 3 243

PFC-318 c-C4F8 10 300 3 782

PFC-3-1-10 C4F10 8 860 3 254

PFC-4-1-12 C5F12 9 160 3 364

PFC-5-1-14 C6F14 9 300 3 415

PFC-9-1-18 C10F18 7 500 2 754

trifluoromethyl sulphur pentafluoride

SF5CF3 17 700 6 500

Fluorinated ethers

HFE-125 CF3OCHF2 14 900 5 472

HFE-134 CHF2OCHF2 6 320 2 321

HFE-143a CH3OCF3 756 278

HCFE-235da2 CF3CHClOCHF2 350 129

HFE-245cb2 CF3CF2OCH3 708 260

HFE-245fa2 CF3CH2OCHF2 659 242

46

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

1990 1995 2000 2005 2010 2015 2020 2025

Gg

CO

2-e

q

Year

GHG emission

Target


HFE-254cb2 CHF2CF2OCH3 359 132

HFE-347mcc3 CF3CF2CF2OCH3 575 211

HFE-347pcf2 CHF2CF2CH2OCHF2 580 213

HFE-356pcc3 CHFCF2OCH2CH3 110 40

HFE-449sl (HFE-7100) C4F9OCH3 297 109

HFE-569sf2 (HFE-7200) C4F9OC2H5 59 22

HFE-43-10pccc124 (H-Galden 1040x)

CHF2OCF2OC2F4OCHF2 1 870 687

HFE-236ca12 (HG-10) CHF2OCF2OCHF2 2 800 1 028

HFE-338pcc13 (HG-01) CHF2OCF2CF2OCHF2 1 500 551

Perfluoropolyethers

PFPMIE CF3OCF(CF3)CF2OF2OCF3 10 300 3 782

Hydrocarbons and other compounds – Direct Effects

Dimethylether CH3OCH3 1 0,37

Methylene chloride CH2Cl2 8,7 3,2

Methyl chloride CH3Cl 13 4,8

Table 11: Eco-factors for other greenhouse gases in Russia

Outlook

The UNFCCC statistical data for GHG emissions for the Russian Federation are used to show the

trend of the GHG emissions for the period 1990-2011. Figure 16 shows the data for this period plus

the target to be achieved by 2020. It shows that the level of 2011 is lower than the “target” level of

2020, thus Russian level of GHG emissions has space to moderately grow. So the target set for 2020 is

not really a reduction target, but a limitation of the ratio of increment. Therefore, this does not mean

that measures to reduce the emissions should be taken anyway. The economic growth in Russia is

currently linked with the increment of GHG emissions. That is the reason why there is currently a

national program (The presidential decree of the Russian Federation No. 752, 2013) aimed to reduce

the GHG emissions, especially in the main contributing sector, the energy sector.

Figure 16: GHGs emissions trend in Russia (based on UNFCCC, 2013)

47

4.1.2. Ozone-depleting substances (ODS)


The Russian Federation took the responsibilities of former USSR in respect of the international

agreements in the field of ozone layer protection. Russia ratified the Vienna Convention for the

protection of the Ozone Layer (1985), Montreal Protocol on Substances that Deplete the Ozone Layer

(1987) and subsequent amendments to these agreements. Ozone-depleting substances (ODS) are the

substances containing chlorine and/or bromine: chlorofluorocarbons (CFC), hydrochlorofluorocarbons

(HCFC), bromofluorocarbons (halons), carbon tetrachloride (CTC), methyl chloroform,

bromomethane and others (Tselikov, 2012).

CFC production in the Russian Federation, according to the obligations under the Montreal Protocol,

should have been stopped by 1996. However, the economic situation in the country and particularly in

the industry made it impossible to fulfill those obligations in time (Tselikov, 2012). Taking into

consideration this situation, the parties of the Vienna Convention and the Montreal Protocol granted

the extension to Russia. As a result, CFC and other ODS production listed in Annexes A and B of the

Montreal Protocol was finally stopped in 2000. Afterwards, the main source of emissions of those

substances became the stocks accumulated by manufacturers. By 2006, all those stocks were run out

(Tselikov, 2012). Enterprises that decided to phase out substances depleting the ozone layer started

using transitional ODS, HCFC listed in Annex C to the Montreal Protocol. HCFC-21, HCFC-22,

HCFC-141b, and HCFC-142b are the most commonly substances used in Russia, for example, in

domestic, commercial and industrial heating, ventilation, and air conditioning equipment, as well as

for manufacturing of insulating boards, plates, panels, and coatings for water, gas, and oil pipelines

(Tselikov, 2012).

The thickness of the ozone layer over the territory of the Russian Federation in the period 2003 - 2012

was 2,3 % below the norm (Ministry of Natural Resources and Environment of the Russian

Federation, 2012) and keeps decreasing. In March 2013 the Russian Cabinet of Ministers introduced

the document Direction № 447-r ( 27th March 2013) - On introducing a bill aimed at ensuring the

protection of the ozone layer of the atmosphere from environmentally harmful changes, (2013) that

aims to make stricter the state control over the circulation of ozone-depleting substances. The

document emphasizes that today there are no clear restrictions on the import and production of ozone-

depleting substances in Russia. Furthermore, the absence of control and sanctions is a serious barrier

for the law enforcement. The report also notes that the absence of a law regulating the turnover of

ODS, makes higher the risk of serious violations of international obligations, which are stated in the

Montreal Protocol. However, it is not yet known when the parliament will consider the document.

Characterization

The intensity of degradation of the ozone layer due to the emissions of ODS can be expressed with the

Ozone Depletion Potential (ODP) (see 3.2.). The ODP of the trichlorofluoromethane (R-11 or CFC-

11) is taken as reference unit and equals to 1. Ozone depleting potentials for different ODS are

determined in accordance to the Montreal Protocol (UNEP, 2006).

Current flow

The annual consumptions of ODS in Russia can be found in the UNEP (Ozone Secretariat) database.

According to it the “calculated levels of consumption means production plus imports minus exports of

controlled substances” (UNEP, 2013). In 2011 the Russian HCFC consumption was 843 t CFC-11-eq.

For other types of ODS the consumption was equal to zero. It is considered that emissions of HCFC

are equal to the current chemical consumption. This estimation is based on the IPCC Guidelines

48

(IPCC, 1996) that defines “that all material consumed has the potential of being emitted eventually”.

Thus, the official UNEP statistic report data about the consumed HCFC, and therefore these data are

used for calculation of the eco-factor.

Critical flow

As internal Russian regulations do not state clear targets for ODS, critical flow was taken from the

obligations in the Montreal Protocol and its amendments (UNEP, 2000), which were ratified by

Russia. Pursuant to the Russian constitution, if the provisions of any environmental regulation

established by an international convention or treaty and those established by the Russian federal or

regional laws are in contradiction, the provisions of the international convention or treaty prevail

(Kings & Spalding, 2012).Commitments of the Russian Federation to reduce the consumption of

hydrochlorofluorocarbons (HCFC) are presented in Table 12. The critical flow was taken as the target

for 2020 which represents a reduction of 99,5 % and equals 19,98 t CFC-11-equivalent.

Year Reduction of HCFC consumptions in % to base level

Maximum level of HCFC consumption in t CFC-11-eq

2010 75,0 % 999,23

2015 90,0 % 399,69

2020 99,5 % 19,98

Table 12: Commitments of the Russian Federation to reduce the consumption of hydrochlorofluorocarbons

(HCFCs) (Tselikov, 2012)

Eco-factor for ODS

The eco-factors are calculated for HCFC. According to the Montreal Protocol, HCFC refer to the CI

group (Group 1 of Annex C of Montreal Protocol) of ODS. HCFC group includes the most commonly

ODS used in Russia (Tselikov, 2012). For the substances included in the CI group, the eco-factors are

calculated using the characterization factors for ODP (see section 3.2.).


Normalization flow (t/a) 843

Current flow (t/a) 843 2011 (UNEP, 2013)

Critical flow (t/a) 19,98 2020 (Tselikov, 2009)

Weighting (-) 1779

Eco-factor (EP/kg CFC-11-eq) 2 110 944 779

Table 13: Eco-factor for HCFC group of ODS in Russia

Group Substance Formula ODP (Montreal Protocol)

Eco-factor (EP/kg)

CI HCFC

HCFC-21 CHFCl2 0,04 84 437 791

HCFC-22 CHF2Cl 0,055 116 101 963

HCFC-123 C2HF3Cl2 0,02 42 218 896

HCFC-141b C2H3FCl2 0,11 232 203 926

HCFC-142b C2H3F2Cl 0,065 137 211 411

Table 14: Eco-factors for ODS in Russia

49

It is important to mention that most of the ODS also contribute to global warming. According to the

principle of the Ecological Scarcity method, the highest of the corresponding eco-factors for the

several impacts affected should be used (see section 2.3.). For example, HCFC-22 has eco-factor equal

to 664,67 EP/kg as a GHG and 116 101 963 EP/kg as an ODS, thus to evaluate environmental impact

of HCFC-22 to air emissions, the highest eco-factor 116 101 963 EP/kg should be used.

Outlook

The trend of HCFCs consumption since 1989 is shown in Figure 17. It is possible to see that the

HCFCs consumption trend has not been stable. Lower consumption rates mostly occurred during the

years of economic stagnation, beginning of 1990s, 2008. To achieve the target level for 2020,

significant reduction is needed. According to the erratic trend that in has been overall increasing, the

achievement of this goal is highly doubtful. Tselikov (2009) lists some possible measures to reduce the

consumption of HCFC in Russia:

• Develop and implement legislative basis for HCFC to prevent the import into the Russian

Federation of obsolete technologies and equipment;

• Synchronize efforts to reduce consumption of HCFC with actions to reduce their production ,

as well as introduction of energy-saving technologies and equipment;

• Promote transition to ozone-friendly substitutes, for example, R600a (isobutene), R290,

carbon dioxide and others.

Figure 17: Russian HCFC consumption trend (based on UNEP, 2013)

4.1.3. Particulate matter (PM)


According to Strukova, Balbus, & Golub (2007), about 6 % of the annual urban deaths in Russia

(88 800 people) are associated with air pollution. One of the most relevant pollutants is particulate

matter (PM), which has been recognized as a substance that can cause morbidity and mortality. The

World Bank statistics provides “the average annual exposure level of the average urban resident to

outdoor particulate matter” (World Bank, 2006). In 2010 Russia had an average concentration of

particulate matter of less than 10 microns in diameter (PM10) of around 15 mcg per m3

(World Bank,

2014a). The particulate matter concentration reflects the state of a country's technology and emissions

0

200

400

600

800

1000

1200

1400

1989 1994 1999 2004 2009 2014 2019 2024

t C

FC-1

1-e

q

Year

HCFCs

Target

50

control (World Bank, 2006). Comparing the concentration rates for different years, there is a general

tendency of reduction of PM10 concentration in Russia. However, the World Bank figures were

calculated with econometric models with a fixed-country effect, and those models take into account

only Russian cities with populations over 100 000. Therefore, it does not reflect the overall situation.

In small cities in Russia, PM can also have high effect, because they are often built closer to industrial

zones and power stations (Strukova et al., 2007), i.e. in small Russian cities the concentration of

particulate matter can be also high, as in cities with populations over 100 000, but due to the formal

rules they are not considered in the model.

Current flow

The PM current flow is estimated with the Greenhouse gas - Air pollution Interactions and Synergies

(GAINS) modele .The GAINS is a scientific tool that estimates current and future emissions based on

activity data, uncontrolled emissions factors, the removal efficiency of emissions control measures and

the extent to which such measures are applied (IIASA, 2011). Its implementation covers the European

part of Russia. The model estimates the current flow of PM10 in Russia in 2010 as 1117,48 kt and

PM2.5, fine particles in the air that are 2.5 microns or less in diameter, 768, 74 kt. Thus, calculation

is based only on these available data.

Critical flow

The emissions of PM in Russia are regulated by the average maximum allowable concentration

(MAC). There is no absolute reduction target in Russian regulation. However, Russian health

standards state the following average annual MACs for particular matter: for PM10 is 40 mcg/m3 and

for PM2.5 is 25 mcg/m3

(Rosminzdrav, 2003). The report of Russian Federal Service for

Hydrometeorology and Environmental Monitoring gives the average concentration for PM10 and

PM2.5, that in 2010 was 15 mgc/m3 and 11 mcg/m

3 , correspondingly (Rosgidromet, 2011). Using the

data for actual and critical concentration is possible to define the weighting for PM. It is considered

that relation between average concentration of PM and MAC is equal to the relation between current

and critical flows of PM measured in mass units. The critical flow in mass units is defined as current

flow (taken from GAIN model) multiplied with MAC and divided by actual concentration.

Eco-factors for PM10 and PM2.5


PM10 PM2.5

Normalization flow (kt/a) 1 117 769

Current flow (kt/a) 1 117 769 2010 (GAINS model (http://gains.iiasa.ac.at/))

Critical flow (kt/a) 2 979 1 748 (Rosgidromet, 2011)

Weighting (-) 0,14 0,19

Eco-factor (EP /kg) 126 252

Table 15: Eco-factor for PM10 and PM2.5 in Russia

Outlook

The Figure 18 shows the PM emissions trend between 1990 and 2010. According to the report of

“Russian Federal Service for Hydrometeorology and Environmental Monitoring” emissions of

particulate matters for the period 2005-2009 decreased by 20,7 % in absolute value and concentration

e http://www.iiasa.ac.at/

http://gains.iiasa.ac.at/

http://www.iiasa.ac.at/

51

by 5,7 %. However, the report also states, that the general characteristics of the trend in air pollution of

the country is not always quite clearly express the direction and especially long-term changes. The

lack of official statistic regarding level of PM emissions and its sources in Russia is one of the reasons

that create difficulties to evaluate the potential of reduction and set the real achievable absolute target.

Moreover, the existence of revised reduction target is one of the conditions that will let Russia ratify

the Gothenburg protocol.

Figure 18: PM10 and PM2.5 emissions trend in Russia (based on GAINS)

4.2. Emissions to surface water


Russia has extraordinary large water resources, which represent almost a quarter of the world

freshwater (OECD, 2008). The total water reserves in rivers in Russia are estimated over 4 000 km3

per year (Khublaryan, 2000). Problems with surface water availability in Russia are caused by the

unevenness of the hydrographic network and density of population across the country (OECD, 2008).

Most of the economic objects and population are concentrated in the European part of Russia. Beyond

the Urals the population rate and density is reduced, but the water resources are higher. This creates

significant anthropogenic pressure on water bodies in the European part, negatively affecting their

quantitative and qualitative characteristics (Vodainfo, 2011). There are about three million rivers in

Russia, according to the State Water registry, but water resources used in Russia are originating only

from three thousands of them (Vodainfo, 2011). Moreover, there are a lot of climate zones in Russia,

with specific seasonality that determines the presence or absence of a sufficient water resource in a

particular period of the year. Supplies of high quality water resources in Russia are accumulated in

mountainous areas, in Lake Baikal, the rivers of Eastern Siberia and the Far East. Thus, fetching water

to other regions of the country is difficult (OECD, 2008). This forces many regions to use water of

poor quality.

Water quality in most Russian surface water bodies fails to meet Russian standards. The main reason

is that the level of pollution exceeds the self-purification abilities of the water bodies in Russia.

Moreover, most of the industrial enterprises in Russia are located near rivers and floodplains and are

also threatening the water quality (Khublaryan, 2000).

0

500

1000

1500

2000

2500

3000

3500

1990 1995 2000 2005 2010 2015

kt

Year

PM10

PM2,5

PM10 target

PM2,5 target

52

Water standards in Russia are regulated by a special document, the SanPin, which was adopted in

1997 and revised in 2001 (Water use. State control on use and protection of water bodies: Collection

of norms (in Russian)., 2010). This document regulates the amount of chemical pollutants in natural

water sources from human activity. SanPin sets hygienic standards of water, determines the physical-

chemical, organoleptic and some other indicators of quality. Surface water quality regulation in Russia

use maximum allowable concentration (MAC) as the main method for water pollution limitation.

MAC is defined as a concentration above which the water is not suitable for water use: i.e. drinking

water supply, recreation and household/industrial purposes (Kovalenko, Makarov, Medvedev, &

Skibenko, 2010). Regulations are based on the principal „zero impact“ on human health and

ecosystems. The standards are strict, however, it has not been defined yet how to meet these standards

from a technical and economical point of view. For instance, compared to the number of parameters

that should be regulated according to the standards, the number of actually monitored parameters is

rather small (OECD, 2008). This is why eco-factors in this work could be calculated only for a few

substances (nitrogen, phosphorus, lead and mercury). Over the last years, Russia has been trying to

improve the system of water quality regulation, but so far it has not been very effective because of

difficulties with the practical implementation (OECD, 2008). The main difficulties are related to the

fact that this process is expensive, site-specific, heavily reliant on science and on monitoring and

almost completely dependent on the ability and political will of regulators to carry it out (OECD,

2008).

The following subchapters provide details and eco-factor calculation for the emissions of nitrogen and

phosphorus (4.2.1.) and heavy metals, like lead and mercury (4.2.2.), in surface water in Russia. The

main sources of emissions in surface water in Russia are sewage water, water from agricultural sector

and pollutants accumulated in the sediments, which are sources of secondary pollution of surface

waters (Russian State Committee on Environmental Protection, 2011). Russian statistics provide

information regarding the mass of the pollutants only for the sewage water that are released to surface

water bodies. In this chapter the eco-factors are calculated based on the available data and general

requirements for surface water quality.

4.2.1. Nitrogen (N) and phosphorus (P)

The presence of high concentrations of nitrogen (N) and phosphorus (P) indicates the pollution of the

water body. P and N are considered the primary drivers of eutrophication in aquatic ecosystems. For

that reason, they are included in the most basic water quality monitoring programs in Russia.

Current flow

Current flow is the amount of N and P in sewage water released to surface water bodies. Current flows

are taken from the official website of Federal Russian statistic service for the year 2009, the amount of

nitrogen was 36 500 t and for phosphorus it was equal to 22 100 t (“Federal Russian statistic service,”

2013).

Critical flow

Critical flows in mass units are calculated by multiplying the volume of sewage water released to

surface water bodies, 47,7 billion m3 , and the maximum allowed concentration (MAC) in surface

water bodies: for N - 40 mg/l and P - 0,05 mg/l (Water use. State control on use and protection of

water bodies: Collection of norms (in Russian)., 2010). The principle of calculation is shown in

subchapter 3.4.

53

Eco-factors for N and P


N P

Normalization flow (t/a) 36 500 22 100

Current flow (t/a) 36 500 22 100 2009 (“Federal Russian statistic service,” 2013)

Critical flow (t/a) 1 908 000 2 385 (Water use. State control on use and protection of water bodies: Collection of norms (in Russian)., 2010)

Weighting (-) 0,00037 86

Eco-factor (EP/kg) 10 3 885 219

Table 16: Eco-factors for nitrogen and phosphorus in surface water in Russia

Outlook

The trend of N and P pollution released to water bodies through sewage water is presented in Figure

19. The figure shows that there is a trend to the reduction in the total amount of phosphorus released to

surface water bodies in recent years. The emission of nitrogen has not stable trend.

Figure 19: Trend of nitrogen (N) and phosphorus (P) emissions through sewage water in Russia (based on

“Federal Russian statistic service,” 2013)

However, it should be noticed that the amount of sewage water has been reduced over the last years.

Thus, the concentration of N and P in sewage water that goes into surface water bodies is actually

increasing. While the current concentration of nitrogen is still below MAC given in SanPin (for N - 40

mg/l and P - 0,05 mg/l), the concentration of phosphorus already exceeds the regulations almost 9

times (see Figure 20).

0

50

100

150

200

250

300

350

400

450

1993 1998 2003 2008 2013

kt

Year

N

P

http://www.lingvo-online.ru/ru/Search/Translate/GlossaryItemExtraInfo?text=%d0%b2%20%d0%bf%d0%be%d1%81%d0%bb%d0%b5%d0%b4%d0%bd%d0%b8%d0%b5%20%d0%b3%d0%be%d0%b4%d1%8b&translation=in%20recent%20years&srcLang=ru&destLang=en

54

Figure 20: Trend of nitrogen (N) and phosphorus (P) concentration in sewage water in Russia (based on

“Federal Russian statistic service,” 2013)

Compared with equivalent EU regulations, Russian standards (based on MACs) for surface water

quality are stricter. Nevertheless, as aforementioned, determining the standards, technical or economic

feasibility of meeting them was not truly considered (OECD, 2008). Russian water quality standards

need to be revised in order to guarantee feasibility and to achieve a balance between “what is desirable

from an environmental point of view and what is feasible from a technical and economic

standpoint”(OECD, 2008) .

4.2.2. Heavy metals: lead (Pb) and mercury (Hg)

Heavy metals can seriously damage human health and wildlife in water bodies, as they are considered

to be the most hazardous among many different toxic compounds in aquatic ecosystems (Semenovich,

2002) and can be accumulated in biota (Amundsen et al., 1997). The assessment of metal pollution is

an important aspect of most Russian water quality monitoring programs. However, there is a mismatch

between the scope of regulation and government resources for regulatory monitoring in Russia

(OECD, 2008). The number of actually monitored parameters is smaller than the number of regulated

parameters. Thought MACs exist for such heavy metals in surface water as arsenic, lead, cadmium,

chrome, copper, nickel, mercury, zinc, etc., the official Russian environmental statistic gives annual

mass load only for a few, that is why eco-factors are calculated only for those two heavy metals in this

subsection.

Current flow

The data for heavy metals in surface water were taken from the official website of Federal Russian

statistic service for the year 2010. The total amounts released to surface water bodies were for lead 9 t

and for mercury 0,02 t (“Federal Russian statistic service,” 2013).

Critical flow

Critical flows are calculated as a multiplication of the volume of sewage water released to surface

water bodies in 2010 (49,2 bln m3) and the maximum allowable concentration: for Pb – 0,01 mg/l and

for Hg - 0,0005 mg/l (Water use. State control on use and protection of water bodies: Collection of

norms (in Russian)., 2010).

0

1

2

3

4

5

6

7

8

9

1993 1998 2003 2008 2013

mg/

l

Year

N

P

55

Eco-factors for Pb and Hg

Step of the eco-factor calculation Result Reference year/ source of data or for data calculation

Pb Hg

Normalization flow (t/a) 9 0,02

Current flow (t/a)

9

0,02

2010 (“Federal Russian statistic service,” 2013)

Critical flow (t) 492 25 (Water use. State control on use and protection of water bodies: Collection of norms (in Russian)., 2010)

Weighting (-) 0,0003 0,0000007


Table 17: Eco-factors for lead and mercury in surface water in Russia

Outlook

Figure 21 shows that the trend of heavy metals, Pb and Hg, emissions released to surface water bodies

has constantly being reduced from year to year. However, the concentration of lead in 2010 still

exceeds in almost 2 times the standards. The concentration of mercury in 2010 was 20 % lower than

MAC. It should take into consideration that the negative environmental impact of heavy metals is

determined by many factors including simultaneous presence of other metals in water. Nevertheless,

as was mentioned above, not all the heavy metals in Russia are regularly monitored. This eliminates

the possibility of making a conclusion regarding the total environmental effect from other heavy

metals in surface water.

Figure 21: Trend of lead (Pb) and mercury (Hg) emission in sewage water in Russia (based on “Federal Russian

statistic service,” 2013)

0

20

40

60

80

100

120

140

1993 1995 1997 1999 2001 2003 2005 2007 2009

t

Year

Pb

Hg

56

4.3. Emissions to sea water

Russia has a unique sea water coastline that equals (excluding Crimea) 37 653 km (CIA, 2014).

According to “Law of the Russian Federation of 01.04.1993 N 4730-1 (ed. From 28.06.2014) "On the

State Border of the Russian Federation" (01 April 1993)” internal sea waters of Russian Federation

include:

• Water ports of Russia;

• Water bays, inlets and estuaries, which are wholly owned by the coast of the Russian

Federation;

• Water bays, inlets, estuaries and seas, which historically belong to the Russian Federation.

Twelve seas of three oceans surround Russia. Seas are located on different tectonic plates and have

different latitudes and climates, different origins, geology, marine basins sizes and shapes of the

bottom topography, as well as the temperature and salinity of sea water, biological productivity, and

other natural features (Dobrovolskii & Zalogin, 1982).

4.3.1. Total petroleum hydrocarbons (TPH) and phenols


All internal (Caspian Sea) and marginal seas (Black Sea, Baltic Sea, White Sea and etc.) of the

Russian Federation suffer serious environmental pressure from human activity, like human

settlements, construction of coastal infrastructure, tourism, industry, shipping and maritime activities,

mining on the shelf, etc. It causes severe damage to marine environment, for instance, destruction of

natural marine ecosystems, and degradation of the water quality. As an example, the degree of water

pollution in Kola Bay of the Barents Sea is evaluated as very high (Ministry of Natural Resources and

Environment of the Russian Federation, 2012). In recent years the control of the quality of marine

water is not sufficient and reduced due to the lack of funding. Furthermore, the monitoring system of

sea and ocean water is fragmented. Each sea is controlled separately (by the local authorities of the

corresponding region) and there is no common average database. The main element of control and

limitation for sea water is MAC. Examining state reports about the environmental situation in Russian

Federation in 2010 (Russian State Committee on Environmental Protection, 2011), it is possible to

identify two polluting substances that are monitored in most of the Russian seas and Pacific Ocean.

These substances are total petroleum hydrocarbons (TPH) and phenols. In Russia, the high level of

hydrocarbons is typical for inland seas, near costal and shelf zones, and the seas where oil production

and transportation take place (Semenovich, 2002).

Current flow

Current flows were calculated as the product of multiplying the measured average concentration of

TPH 0,0725 mg/l and phenols 0,003 mg/l in sea water assumed from State report about environmental

situation in Russian Federation in 2010 (Russian State Committee on Environmental Protection, 2011)

and the volume of the sea water within Russia’s boundaries (2 100 000 m3).

Critical flow

Critical mass balances were calculated as the multiplication of the volume of sea water and the

maximum allowable concentration: for TPH – 0,05 mg/l and phenols - 0,001 mg/l (Water use. State

control on use and protection of water bodies: Collection of norms (in Russian)., 2010).

57

Eco-factors for TPH and phenols


TPH Phenols

Normalization flow (kg/a) 152 6,3

Current flow (kg/a)

152

6,3

2010 (Russian State Committee on

Environmental Protection, 2011)

Critical flow (kg/a) 105 2,1 (Water use. State control on use and

protection of water bodies:

Collection of norms (in Russian).,

2010).

Weighting (-) 2,1 9

Eco-factor (EP/mg) 13 787 1 428 571

Table 18: Eco-factors for TPH and phenols in sea water in Russia

Outlook

It is difficult to give a comprehensive outlook for sea water pollution in Russia. There is a lack of data

for sea water quality and available data have dissimilar structure and vary from year to year. In

overall, the Ministry of Natural Resources and Environment of the Russian Federation, (2012) states

that there has not been any improvement in the water quality characteristic in recent years and water

quality varies from "moderately polluted" to "contaminated". Apart of TPH and phenols, the

concentrations of detergents, heavy metals and pesticides are also very high in Russian sea water and

often exceed the standards. Next steps should be made towards the consistent monitoring of these

emissions in sea water.

4.4. Waste


According to the evaluation of the Ministry of Natural Resources and Environment of the Russian

Federation, the amount of produced waste in Russia is around 4 billion t per year. Almost 40 % of

industrial waste and around 7-10 % of municipal solid waste is recycled (Minprirody, 2012). The

amount of solid waste currently stored at dumps and storages is around 85 bln t and the amount of

toxic waste stored reaches 1,7 bln t (Mamin & Bayaraa, 2009). Annually up to 10 thousand ha of land

are expropriated for landfills, excluding the land spoiled by illegal dumping (Mamin & Bayaraa,

2009). More than 80 % of landfill sites came into existence more than 20 years ago and up to 30 % do

not meet current sanitary standards (IFC, 2012). The State Program of the Russian Federation

"Environmental Protection" for 2012-2020 is aimed to develop a set of activities that will improve the

system of waste treatment, waste treatment technologies, projects for recycling and toxic waste

disposal (Minprirody, 2012), mainly in energy and mining sectors . The specific target is to reduce by

2020 up to 1,6 times the total amount of waste of the base year 2007 (Minprirody, 2012).

Current flow

Current flow was taken from the official website of Federal Russian statistic service for the year 2010

(“Federal Russian statistic service,” 2013), the amount of waste is 3 734,7 mln t.

Critical flow

Critical flow is calculated as a mass flow with response to 1,6 times reduction of the base year 2007

( 3 889, 3 mln t) by the year 2020.

58

Eco-factor for waste


Normalization flow (mln t/a) 3 735

Current flow (mln t/a) 3 735 2010 (“Federal Russian statistic service,” 2013)

Critical flow (mln t/a) 2 437 2020 (Minprirody, 2012).

Weighting (-) 2,3

Eco-factor (EP/kg) 0,6

Table 19: Eco-factor for waste in Russia

Outlook

The amount of waste in Russia grows every year; it can be seen in Figure 22. To achieve the

aforementioned goal by 2020 Russia should focus on sustainable disposal and adopt better waste

recovery. According to the predictions by IFC, (2012), Russia will have the capacity to recover

around 40 – 45 % of waste by 2025. This will also lead to reduction of the demand for new landfill

capacity by 20 - 30 %.

Figure 22: Trend of waste generation in Russia (based on “Federal Russian statistic service,” 2013)

4.5. Energy consumption


Though the Russian Federation has enormous energy resources, energy efficiency is a high priority for

the Energy Strategy of Russia. In fact, Russia is the world’s third largest energy consuming country

(World Bank, 2010). Accordingly, in 2009 it was defined the 56 % reduction target for the year 2030

compared to year 2005 (ABB, 2011). The federal Low on Energy Conversation and Increase of

Energy Efficiency, adopted in 2009 (Federal Law № 261-FZ “On energy saving and energy efficiency

improvements and on Amendments to Certain Legislative Acts of the Russian Federation,” 2009),

created the framework for energy efficiency promotion (ABB, 2011). Gas and oil have the biggest

share in Russia’s primary energy consumption (see Figure 23).

0

500

1000

1500

2000

2500

3000

3500

4000

4500

2005 2007 2009 2011 2013 2015 2017 2019

mln

t

Year

Waste

Target

59

Figure 23: Russian primary energy consumption by sources (based on ABB,2011)

Higher energy efficiency rates in Russia could promote reduction of environmental costs,

improvement of the health and welfare of citizens, through the reduction of CO2, NOx, SOx and

particulate emissions caused by its energy intense consumption (World Bank, 2010). However, the

federal and regional legislation on energy efficiency has not been successful enough, mainly because

they do not address key barriers such, as the lack of information and insufficient access to long-term

funding (World Bank, 2010).

Characterization

ILCD (JRC: The European Commission, 2012) gives characterization factors (CFs) for some energy

sources using for primary energy consumption. CFs are expressed as net calorific value per mass.

Thus, the eco-factors can be calculated for these resources (see Table 21).

Current flow

The total energy consumption in Russian Federation in 2010 was 903,6 million ton oil equivalent (toe)

or 37 832,3 PJ (Ministry of Natural Resources and Environment of the Russian Federation, 2012).

Critical flow

The critical flow is calculated as 56 % reduction target of the consumption in 2009. Energy

consumption per capita in Russia in 2009 was about 4,4 toe / cap (ABB, 2011). Russian population in

2009 was equal 142,7 mln according to the (“Federal Russian statistic service,” 2013). Thus the total

consumption was 26 288,1 PJ.

53%

21%

16%

7%

2% 1%

Gas

Oil

Coal

Nuclear power

Hydropower

Biomass

60

Eco-factor for energy consumption


Normalization flow (PJ) 37 832

Current flow (PJ)

37 832

2010 (Ministry of Natural Resources and Environment of the Russian Federation, 2012)

Critical flow (PJ) 11 567 2030 (Federal Law № 261-FZ “On energy saving and energy efficiency improvements and on Amendments to Certain Legislative Acts of the Russian Federation,” 2009)

Weighting (-) 11

Eco-factor (EP/MJ) 0,28

Table 20: Eco-factor for energy consumption in Russia

Eco-factors for some energy resources

Resource Net calorific value (MJ/kg) EF, EP/kg

Crude oil 42,3 12,0

Hard coal 26,3 7,4

Brown coal 11,9 3,4

Natural gas 44,1 12,5

Uranium 544 284 153 909

Table 21: Eco-factors for some energy resources in Russia

Outlook

According to the World Bank, (2010), Russia will be able to save 45 % of its total primary energy

consumption by 2020 compared to the levels of 2009. By achieving this energy efficiency potential,

Russia can save: 240 billion cubic meters of natural gas, 340 billion kWh of electricity, 89 million

tons of coal, and 43 million tons of crude oil and equivalents in the form of refined petroleum products

(World Bank, 2010). The energy efficiency saving potential in Russia by sectors is presented in

Figure 24.

Figure 24: Energy Efficiency Potential by sector in Russia (based on World Bank, (2010))

0

10

20

30

40

50

60

residentialbuildings

publicorganizations

industry transport electricity heat supplysystems

mto

e

61

World Bank, (2010) lists also the main barriers for improving energy efficiency in Russia. Among

them there is little appreciation of energy efficiency, lack of statistical data and general awareness,

environmental externalities (i.e. energy prices do not include the negative health effects of emissions

released during energy consumption).

4.6. Overview

Set of eco-factors for Russia

The eco-factors calculated in Chapter 4 are brought together in Table 22. There are four group of

substances related to emission to air, GHG, HCFs, PM10 and PM2.5. Nitrogen, phosphorus and heavy

metals, lead and mercury, are the emissions considered to surface water and total petroleum

hydrocarbons and phenols, to sea water. Eco-factors are also given for waste generation and primary

energy consumption.

Substance Weighting Eco-factor Eco-factor's unit

GHG (air) 0,85 0,37 EP/kg CO2-eq.

HCFC (air) 1 779 2 110 944 779 EP/kg CFC-11-eq.

PM10 (air) 0,14 126 EP/kg

PM2,5 (air) 0,19 252 EP/kg

N (surface water) 0,00037 10 EP/kg

P (surface water) 86 3 885 219 EP/kg

Pb (surface water) 0,0003 37 180 EP/kg

Hg (surface water) 0,0000007 33 049 EP/kg

THP (sea water) 2,1 13 787 EP/mg

Phenols (sea water) 9 1 428 571 EP/mg

Waste 2,3 629 EP/t

Energy 11 0,28 EP/MJ

Table 22: Russian set of eco-factors

The eco-factors for waste, energy consumption and air emission, GHG and HCFC, categories are

calculated with critical flows based on reduction targets. It means that a political target in the country

defines the needed reductions in the emissions or use of resources. The eco-factors for the remaining

category, emissions to water are calculated with thresholds. A threshold of a certain emission is the

critical value or the maximum level of this type of emission that has been defined not to be harmful for

human health or ecosystem quality (see 3.4.2.). Using the thresholds, instead of absolute targets, leads

to a need for additional assumptions and data. Both reduction targets and thresholds are based on

national legal requirements.

Emissions to soil and noise, which are defined in the Swiss Eco-Factors 2013 according to the

Ecological Scarcity Method (Frischknecht & Büsser Knöpfel, 2013), have not been included in the set

of Eco-factors for Russia due to the lack of data for these categories in terms of statistical data for

annual emission, that define the current flow, as well as for applicable reduction targets or thresholds.

In the Swiss Eco-Factors 2013 according to the Ecological Scarcity Method (Frischknecht & Büsser

Knöpfel, 2013), it is underlined that the gaps in national legal requirements are very often the reason

for incomplete sets of national eco-factors. Table 22 lists the substances for which the current and

critical flows could be identified and/or calculated from the current publicly available sources (such as

62

Russian national statistics and reports of international organizations regarding the level of emission in

the country).

Environmental hot spots in Russia

Apart from the environmental assessment of a product (see Chapter 6), the set of eco-factors

developed for a country can be also used to assess the environmental hot spots of that country. The

actual flows of all the categories for which an eco-factor could be calculated are multiplied by the

corresponding eco-factor, to get a result in single-score units (see Equation 3). The obtained results for

each substance are then aggregated for all the substances and its share in total result is showed in

Figure 25.

According to the Russian set of eco-factors, HCFC, referring to ozone depleting substances, have the

biggest share of the total impact in the country, around 94 %. This is the result of the highly

demanding reduction target for these substances (99,5 %) and the current state in Russia that is far

from the target. The contribution is so large that the effect of other environmental categories seems

minor in comparison, for example, the emission of phosphorus in surface water has a contribution of

4,5 %, while all other categories have less than 1 % in the total result. Such unevenness between the

shares is explained by the big difference in weighting values for the different substances (see Figure

25). On national level, eco-factor is multiplied with current flow that is identical to normalization

flow, i.e. the normalization does not have any influence on single-score result on national level. Thus,

the share of each substance in overall national result is influenced only by the value of weighting for

each substance.

Figure 25: Overall annual environmental impacts of Russia

94%

5%

1%

GHGs (air)

HCFCs (air)

PM10 (air)

PM2,5 (air)

N (surface water)

P (surface water)

Pb (surface water)

Hg (surface water)

THP (see water)

Phenols (see water)

Waste

Energy

63

5. German eco-factors

The chapter contains information about German eco-factors that include eco-factors for 3 categories

(emissions air, surface water and resources) and 16 substances /substance groups within the categories

(Figure 26). The subchapters (5.1.-5.3.) contain an overview of current state of the emissions and

resources use, political agenda for their reduction, data for eco-factor calculation and its sources and

short outlook regarding the trend. A general overview of total set of eco-factors and environmental hot

spots for Germany are presented in section 5.4.


Emissions

Air (5.1.)

GHG

(5.1.1.)

NMVOCs (5.1.2.)

NOx

(5.1.3.)

NH3

(5.1.4.)

SO2

(5.1.5.)

PM

(5.1.6.)

Dioxins

(5.1.7.)

Hg, Cd, Pb (5.1.8.)

Surface water (5.2.)

N (5.2.1.)

P (5.2.1.)

PAHs

(5.2.2.)

Resources (5.3.)

Land use (5.3.1.)

Energy (5.3.2.)

Overview (5.4.)

64

5.1. Emissions to air

5.1.1. CO2 and other greenhouse gases (GHG)

Political targets and situation in Germany

Germany is one of the European largest emitters of CO2. In 2011, the emission of CO2 in Germany was

0,8 billion t, while the overall EU27 emission was equal to 3,79 billion t. Thus, Germany contributed

with almost 20 % to total European emission (Olivier, Janssens-Maenhout, Muntean, & Peters, 2013).

CO2 is the most contributing gas to total GHG emissions in Germany (see Figure 27). According to

UNFCCC data, about 67 % of GHG emissions in Germany come from the energy sector; 16,5 % from

transport; 7,7 % from industrial process; 7,2 % from agriculture; 1,3 % from waste; and 0,2 % from

other sources (UNFCCC, 2011).

Figure 27: Total GHG emission by greenhouse gas in Germany in 2011 (based on UNFCCC, 2011)

Climate change, caused by the emission of GHG, can have negative impact in Germany. For example,

the increase of the temperature may cause glacier melting in the Alps, bring fatalities caused by

tropical diseases (like leishmaniasis or Lyme disease, that have been already reported in Germany), or

cause droughts in some regions (von Brook, 2014).

In March 2002, Germany ratified the Kyoto Protocol, that sets binding targets for industrialized

countries for reducing GHG emissions. The main aim of the Kyoto Protocol is to contain the emission

of the main anthropogenic GHG in ways that reflect national differences in current GHG emission

level, wealth, and capacity to make the reductions. According to the protocol, Germany had the duty

of mandatorily reduce by 21 % domestic GHG emissions (UNFCCC) and was expected to achieve that

reduction by 2012. However, in 2011 Germany already met the obligation of the protocol; the

reduction on GHG emissions between 1990 and 2011 was around 24 % (IIP, 2013). Nevertheless,

Germany plans to reduce GHG emission beyond this target. The goal of Germany is a 40 % reduction

in domestic GHG emissions by 2020 compared to 1990 level.

87%

5%

6%

2%

CO2

CH4

N2O

HFCs+PFCs+SF6

65

Characterization

The global warming potential (GWP100) for 100 years’ time horizon was chosen as the characterization

factor for the various greenhouse gases considered The factors of the GWP100 were taken from the

report of “The Intergovernmental Panel on Climate Change” (Solomon et al., 2007). The reference

substance is CO2 (see section 3.2.).

Current flow

Data for the current flow derives from the official UNFCCC GHG emissions statistics. GHG

emissions in Germany was 916 495 078 Mg CO2 equivalent in 2011 (UNFCCC, 2011).

Critical flow

The critical flow is taken from the German internal climate target. It is considered as 40 % reduction

(750 158 162 Mg) in domestic greenhouse gas emissions from the 1990 baseline (1 250 263 604 Mg)

by 2020.

Eco-factor for CO2 and other greenhouse gases


Normalization flow (Mg CO2 eq/a) 916 495 078

Current flow (Mg CO2 eq/a) 916 495 078 2011 (UNFCCC, 2011).

Critical flow (Mg CO2 eq/a) 750 158 162 2020 (Statistisches Bundesamt, 2012)

Weighting (-) 1,5

Eco-factor (EP/kg CO2-eq) 1,6

Table 23: Eco-factor for CO2 in Germany

Eco-factors for further greenhouse gases are calculated by the multiplication of the eco-factor for

CO2 –eq with global warming potential characterization factors.


Carbon dioxide CO2 1 1,6

Methane CH4 25 41

Dinitrogen oxide N2O 298 485


Carbon monoxide CO 1,57 2,56

Chlorofluorocarbons

CFC-11 CCl3F 4750 7 736

CFC-12 CCl2F2 10 900 17 752

CFC-13 CClF3 14 400 23 452

CFC-113 CCl2FCClF2 6 130 9 984

CFC-114 CClF2CClF2 10 000 16 286

CFC-115 CClF2CF3 7 370 12 003

Halon-1301 CBrF3 7 140 11 629

Halon-1211 CBrClF2 1 890 3 078

Halon-2402 CBrF2CBrF2 1 640 2 671

Carbon tetrachloride CCl4 1 400 2 280

66


Methyl bromide CH3Br 5 8,14

Methyl chloroform CH3CCl3 146 238

HCFC-22 CHClF2 1 810 2 948

HCFC-123 CHCl2CF3 77 125

HCFC-124 CHClFCF3 609 992

HCFC-141b CH3CCl2F 725 1 181

HCFC-142b CH3CClF2 2 310 3 762

HCFC-225ca CHCl2CF2CF3 122 1989

HCFC-225cb CHClFCF2CClF2 595 969

Hydrofluorocarbons

HFC-23 CHF3 14 800 24 104

HFC-32 CH2F2 675 1 099

HFC-125 CHF2CF3 3 500 5 700

HFC-134a CH2FCF3 1 430 2 329

HFC-143a CH3CF3 4 470 7 280

HFC-152a CH3CHF2 124 202

HFC-227ea CF3CHFCF3 3 220 5 244

HFC-236fa CF3CH2CF3 9 810 15 977

HFC-245fa CHF2CH2CF3 1 030 1 678

HFC-365mfc CH3CF2CH2CF3 794 1 293

HFC-43-10mee CF3CHFCHFCF2CF3 1 640 2 671

Perfluorinated compounds


Nitrogen trifluoride NF3 17 200 28 013

PFC-14 CF4 7 390 12 036

PFC-116 C2F6 12 200 19 869

PFC-218 C3F8 8 830 14 381

PFC-318 c-C4F8 10 300 16 775

PFC-3-1-10 C4F10 8 860 14 430

PFC-4-1-12 C5F12 9 160 14 918

PFC-5-1-14 C6F14 9 300 15 146

PFC-9-1-18 C10F18 7 500 12 215

trifluoromethyl sulphur pentafluoride

SF5CF3 17 700 28 827

Fluorinated ethers

HFE-125 CF3OCHF2 14 900 24 267

HFE-134 CHF2OCHF2 6 320 10 293

HFE-143a CH3OCF3 756 1 231

67


HCFE-235da2 CF3CHCLOCHF2 350 570

HFE-245cb2 CF3CF2OCH3 708 1 153

HFE-245fa2 CF3CH2OCHF2 659 1 073

HFE-254cb2 CHF2CF2OCH3 359 585

HFE-347mcc3 CF3CF2CF2OCH3 575 937

HFE-347pcf2 CHF2CF2CH2OCHF2 580 945

HFE-356pcc3 CHFCF2OCH2CH3 110 179

HFE-449sl (HFE-7100) C4F9OCH3 297 484

HFE-569sf2 (HFE-7200) C4F9OC2H5 59 96

HFE-43-10pccc124 (H-Galden 1040x)

CHF2OCF2OC2F4OCHF2 1 870 3 046

HFE-236ca12 (HG-10) CHF2OCF2OCHF2 2 800 4 560

HFE-338pcc13 (HG-01) CHF2OCF2CF2OCHF2 1 500 2 443

Perfluoropolyethers

PFPMIE CF3OCF(CF3)CF2OF2OCF3 10 300 16 775

Hydrocarbons and other compounds – Direct Effects

Dimethylether CH3OCH3 1 1,6

Methylene chloride CH2Cl2 8,7 14

Methyl chloride CH3Cl 13 21

Table 24: Eco-factors for further greenhouse gases in Germany

Outlook

The trend of GHG emissions in Germany is shown in Figure 28. Though Germany met the Kyoto

target even earlier than expected, in 2012, according to the preliminary calculations of the Federal

Ministry for the Environment (BMUB) and German Environmental Agency (UBA), domestic GHG

emission increased approximately by 1,6 % compare to year 2011 (BMU, 2013b). It is also stated in

the press release of the German Environmental Ministry (BMU, 2013b) that Germany needs some

energy upgrades and sustainable efforts toward sustainable mobility, in order to achieve the ambitious

German internal climate target for 2020. It should be taken into account that a large share of the initial

GHG reduction was achieved due to the industrial shutdowns that occurred between 1990-1995 and in

2009, as a consequence of the economic crises (Statistisches Bundesamt, 2012). Thus, a significant

part of the reduction has relation with the overall economic situation. Apart from the crises, Germany

has started a conversion process, changed the type of industries and sectors and this has also

contributed to the impact reduction.

68

Figure 28: GHGs emissions trend in Germany (based on UNFCCC, 2011)

5.1.2. Non-methane volatile organic compounds (NMVOCs)


Emission of non-methane volatile organic compounds (NMVOCs) has a significant contribution to air

pollution in Germany (Theloke & Friedrich, 2003). NMVOCs advance the formation of photo-

oxidants and some of them have adverse health effects (for example, benzene, 1,3 butadiene) (Theloke

& Friedrich, 2003, EEA - European Environment Agency, 2001). The major sources of anthropogenic

NMVOCs emission are road transport, energy sector and solvent use. More than 60 % of NMVOCs

released in Germany come from solvent use (UBA, 2010b). The NMVOCs emission by source in

2010 is presented Figure 29.

Figure 29: NMVOCs emissions by source in Germany in 2010 (based on UBA, 2013b)

0

200000000

400000000

600000000

800000000

1000000000

1200000000

1400000000

1990 1995 2000 2005 2010 2015 2020

Mg

CO

2-e

q

Year

GHG

Target

17%

3%

68%

12%

Energy

Industrial processes

Solvent use

Transport

69

Current flow

NMVOCs emission measures and targets are not per compound but for the total NMVOCs emissions.

Anyway, quantifying the emissions of total NMVOCs provides an indicator of the emission of the

most hazardous NMVOCs (EEA, 2005). Current flow is represented by the level of NMVOCs

emission in 2010 and is equal to 1 055 kt (UBA, 2013b).

Critical flow

The German national aim is to stabilize the annual emissions around 995 kt of NMVOCs by 2020

(UNECE, 1999).

Eco-factor for NMVOCs


Normalization flow (kt/a) 1 055

Current flow (kt/a) 1 055 2010 (UBA, 2013b)

Critical flow (kt/a) 995 2020 (UNECE, 1999)

Weighting (-) 1,1

Eco-factor (EP/kg) 1 066

Table 25: Eco-factor for NMVOCs in Germany

Outlook

The implementation of the EC Solvent Directive (EC, 1999) in Germany has resulted in a significant

reduction of NMVOCs emission (UBA, 2010b). This reduction since 1990s was achieved with

improvements in the road transport sector ((EEA, 2005), by the promotion of better practices in the

use of solvents and technologies for manufacturing processes (EEA, 2001), and legislative limiting

measures (EEA, 2005). Further reduction for 2020 can still be challenging to achieve due to the

growth of the number of vehicles (World Bank, 2014b) and difficulties in the implementation of

controls on solvent use in industry and in households (EEA, 2005).

Figure 30: NMVOCs emissions trend in Germany (based on UBA, 2013b)

0

500

1000

1500

2000

2500

3000

3500

1990 1995 2000 2005 2010 2015 2020

kt

Year

NMVOCs

Target

70

5.1.3. Nitrogen oxides (NOx)


Nitrogen compounds in the air, and, thus, nitrogen oxides (NOx), are a big concern due to their

contribution to the formation of ground level ozone and secondary fine particulates, and therefore, as a

result of their potential effects on human health, acidification and eutrophication. Because they are

strong oxidizing agents, nitrogen compounds can cause sore to the organs of the respiratory system

and facilitate the irritation of the other air pollutants (UBA, 2009c). Road transport and combustion

processes in the industrial and energy production sectors have the largest share in the total nitrogen

oxides emission in Germany. The transport sector with 49 % has the biggest share in NOx emission

predominantly originating from large goods vehicles (LGV) (UBA, 2009c).

Germany has the national target, under the Gothenburg protocol (UNECE, 1999), to reduce the

emission level of NOx by 39 % in 2020, in comparison to 2005. Besides, German Federal Government

has a program setting out specific measures to further reduce emissions of NOx. This program aims to

achieve compliance with the national emission ceilings (NECs) laid down in Directive 2001/81/EC

(UBA, 2010b).

Current flow

Current flow is the German total emissions of NOx in 2010. They represented 1 329 kt of NOx

according to statistical data (BMU, 2013a).

Critical flow

Critical flow is calculated with the national target of 39% reduction of the emissions level in 2005

(UNECE, 1999), which was 1 573 kt of NOx (BMU, 2013a).. Therefore, the critical flow is 960 t of

NOx.

Eco-factor for NOx



Current flow (kt/a) 1 329 2010 (BMU, 2013a)


Weighting (-) 1,9


Table 26: Eco-factor for NOx in Germany

Outlook

Since 1990, according to UBA statistics, Germany has been reducing the emission of NOx by an

average of 4 % each year. Making the assumption that this trend will be kept till 2020, it is possible to

predict the approximate level of emission over time (see Figure 31). According to this arithmetic

sequence, the reduction target of 39 % by 2020 could be achieved. However, some additional

measures should be carried out to keep the trend (e.g. the implementation of appropriate measures for

the road traffic sector).

71

Figure 31: NOx emissions trend in Germany (based on BMU, 2013a)

5.1.4. Ammonia (NH3)


Ammonia (NH3) plays an important role in chemical processes that take place in the atmosphere and,

other deposition also, in biogeochemical processes that occur in ecosystems like forests, soils, streams,

and coastal waters (Committee On The Environment And Natural Resources, 2000). For instance, by

reacting with sulfuric and nitric acids formed in the atmosphere, ammonia contributes to the

generation of fine particles (Committee On The Environment And Natural Resources, 2000). The

secondary particles formed by ammonia (NH3), can damage human health (Frischknecht et al., 2009)

and cause damage to crops and natural ecosystems. Secondary particles do not come directly from the

source of emissions; they are formed in complicated reactions in the atmosphere. The main source of

ammonia air pollution in Germany is agricultural activities. They are responsible for almost 95 % of

NH3 national emission (UBA, 2010b), mainly due to agricultural processes, like livestock farming and

application of fertilizers (UBA, 2010b).

With the ratification of the Gothenburg protocol, in 1999 (UNECE, 1999), Germany accepted the

compromise not to exceed the emission level of 550 thousand t of ammonia per year (Döhler, Eurich-

Menden, Rößler, Vandre, & Wulf, 2011). By 2020, Germany has the national target to reduce NH3

emission by 5 % in comparison with 2005 levels.

Current flow

Current flow is the flow of ammonia emission in 2010 according to BMU statistic. The level of

emission was 552 thousand t (BMU, 2013a).

Critical flow

The target for 2020 is 5 % reduction of the NH3 level of 2005, that was 579,4 kt (BMU, 2013a). Thus

the critical flow is 550 kt.

0

500

1000

1500

2000

2500

3000

3500

1990 1995 2000 2005 2010 2015 2020

kt

Year

NOx

Target

72

Eco-factor for NH3


Normalization flow (kt/a) 552

Current flow (kt/a) 552 2010 (BMU, 2013a)


Weighting (-) 1,0


Table 27: Eco-factor for NH3 in Germany

Outlook

Without additional measures for the reduction of ammonia emission, Germany will hardly remain

below the required level (see Figure 32). For the reduction of ammonia emissions, a wide range of

measures in animal housing, and storage and distribution of animal manure is available (Döhler et al.,

2011). Furthermore, at the agricultural level, it is necessary the advancement to environmentally

friendly agricultural practices (amended Fertilizer Ordinance of 2007), like low-emission techniques

and control emissions from animals vital activity (UBA, 2009a).

Figure 32: NH3 emissions trend in Germany (based on BMU, 2013a)

5.1.5. Sulfur dioxide (SO2) and other acidifying substances


Acidifying pollution caused by emission of sulfur dioxide and other acidifying substances contributes

to acid deposition, which can lead to changes on the quality of the ecosystems and damage them. For

instance, pollution can cause adverse effects on aquatic ecosystems in rivers and lakes, damage forests

and acidify soils (EEA, 2007). Acidifying pollution can damage manmade environment as well, for

example, destroying buildings and monuments (EEA, 2007). The pollutants react in the atmosphere

and are transformed into particulate matter, which negatively contributes to human health, namely

damage to respiratory system, like lung functions, and eyes irritation (EEA, 2012). Energy

consumption is the main source of SO2 emission in Germany, with a share over 50 % in the total

emission (UBA, 2010b). The Federal Government has a program to reduce the total national emission

of sulfur dioxide and meet the reduction goal of critical loads for acidification (UBA, 2010b).

0

100

200

300

400

500

600

700

800

1990 1995 2000 2005 2010 2015 2020

kt

Year

NH3

Target

73

Characterization

Sulfur dioxide is one of the most important acidifying air pollutants. Therefore, the acidification

potential (AP) of the sulfur dioxide can serve as a reference factor for other acidifying substances.

Accordingly, AP is quantified in SO2-equivalents (Guinée et al., 2002) (see Section 3.2). For instance,

the acidification potential of one kilogram of HCl is equivalent to the potential for 0,88 kg of sulfur

dioxide (see Table 29).

Current flow

Current flow of SO2 is taken from the BMU statistical data for the year 2010. It is equal to 444 kt

(BMU, 2013a).

Critical flow

Critical flow is calculated as a 21 % reduction from the level of 2005 (477,1 kt) by the year 2020. The

21 % reduction is the reduction target for Germany according to the Gothenburg Protocol (UNECE,

1999).

Eco-factor for SO2



Current flow (kt/a) 444 2010 (BMU, 2013a)


Weighting (-) 1,4


Table 28: Eco-factor for SO2 in Germany

Eco-factors for other acidifying substances

Acid producer (in air) Formula Characterization factor (Guinée et al., 2002)

Eco-factor (EP/kg SO2-eq)

Ammonia NH3 1,88 5 873

Hydrogen chloride HCl 0,88 2 749

Hydrogen fluoride HF 1,6 4 998

Hydrogen sulfide H2S 1,88 5 873

Nitric acid HNO3 0,51 1 593

Nitrogen dioxide NO2 0,7 2 187

Nitrogen monoxide NO 1,07 3 343

Nitrogen oxides NOx 0,7 2 187

Phosphoric acid H3PO4 0,98 3 062

Sulfur trioxide SO3 0,8 2 499

Sulphuric acid H2SO4 0,65 2 031

Table 29: Eco-factors for acidifying substances in Germany

Outlook

Germany has achieved significant reduction in SO2 emission since 1990, the reduction of SO2 in 2010

was more than 90 % less compared to the level of 1990. However, the target value of 377 kt has not

been achieved yet. Since 2005 the emission trend of sulfur dioxide has not tendency for significant

74

decreasing (see Figure 33). To achieve the desirable level, in addition to the actions considered in the

most relevant European directives for the reduction of SO2 in air (for example, LCPf and IPPC

Directivesg, The Sulphur Contents of Liquid Fuels Directive

h, The Fuels Quality Directive

i), there is a

need for additional policy instruments to reduce emission of SO2 and others.

Figure 33: SO2 emissions trend in Germany (based on BMU, 2013a)

5.1.6. Particulate matter (PM)


Research studies of the World Health Organization (WHO) have shown that high concentration of

particulate matter in air negatively affects human health, by increasing the occurrence of respiratory

and cardiovascular diseases (UBA, 2014). The most contributing anthropogenic sources of PM in

Germany are industrial processes, road traffic, heating systems, bulk materials processing and

agriculture (UBA, 2009c). Part of the particulate matter in the air is caused by the transformation of

some air pollutants (e.g. NOx, SO2 etc.), the so called secondary PM (UBA, 2009c). Strict limits and

actions to prevent emissions from the source assisted the reduction of air pollution in Germany during

the last 20 years by an 80 % compared to the level of 1990s. Nevertheless, concentrations of PM still

exceed desired values according to BMU (BMU, 2013a).

German government has implemented some strict measures to reduce the level of PM emissions, for

example, by adopting the so called “low emission zone” and by tightening the provisions on small-

scale firing installations (UBA, 2012a). These measures aim to reduce the PM emission in 2020 by

26 % from the base year 2005.

There are two main regulated classes of particulate matter PM10 and PM2.5. The numbers refer to the

size of the particles. Eco-factors are calculated for PM10, PM2.5 separately using the same target for

f Directive 2001/80/EC

g Directive 2008/01/EC

h Directive 1999/32/EC

i Directive 2009/30/EC

0

1000

2000

3000

4000

5000

6000

1990 1995 2000 2005 2010 2015 2020

kt

Year

SO2

Target

http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:31999L0032

http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32009L0030

75

the critical flow. The 26 % reduction target refers to the particulate matters with a size of 2.5

micrometers as it is supposed that PM2.5 has more serious health concern, due to their small size,

these particles can enter into human small bronchi and bronchioles by inhalation. However, PM10 can

cause serious health effects as well. The relatively large surface area of PM10 can carry significant

amounts of toxic species deep into the lungs. These include organic compounds, trace elements and

biogenic species (such as viruses and fungi) (Environmental Agency, 2012). Thus, the reduction target

is applied for PM10 in accordance to precautionary principle and there is no contradiction with other

possible targets for PM10.

Current flow

Current flow is the national emissions of particulate matter for the year 2010 (BMU, 2013a). It is

equal to 211,4 kt for PM10 and 116,9 kt for PM2.5.

Critical flow

Critical flow corresponds to the emission level of 2005 after a 26 % reduction (UNECE, 1999). As

was mentioned above, the target refers to PM 2.5. However, this target has been applied for the other

type of PM, as no other applicable target has been identified.

Eco-factor for PM


PM10 PM2.5


Current flow (kt/a) 211 117 2010 (BMU, 2013a).

Critical flow (kt/a) 156 87 2020 (UNECE, 1999)

Weighting (-) 1,8 1,8


Table 30: Eco-factor for PM in Germany

Outlook

Germany is struggling for complying with the ambitious limit values for particulate matter, especially

in the transport sector (responsible for 16 % of the total PM emission). PM emissions have not

decreased as expected (see Figure 34), despite the strict emissions standards (BMU, 2010). More

efforts should be done in all sectors, “from wood heating, the automotive industry to large power

plants” (UBA, 2014).

76

Figure 34: PM10 and PM2.5 emissions trend in Germany (based on BMU, 2013a)

5.1.7. Dioxins


The term dioxin refers to a group of chlorinated dioxins and furans with similar chemical structure.

Dioxins are undesired byproducts mainly from combustion processes. The major sources of dioxin

emission to air in Germany are metallurgical industry and thermal waste treatment, such as

incineration (UBA, 2010c). Dioxins are persistent organic pollutants, due to their ability to accumulate

in human and animal tissues and in plants, besides they can be transported over long distances.

Germany was one of the first countries that ratified international treaties regarding persistent organic

pollutants, such as the UNECE Convention on Long-range Transboundary Air Pollution (UNECE,

1999) and the Stockholm Convention on Persistent Organic Pollutants (UNEP, 2009). Though

Germany has strict limits for dioxin emissions and significantly reduced its level from waste

incineration plants, they should be reduced further. Dioxins have carcinogenic effect on humans, and

there is still a large part of the population that intakes dioxins in an amount higher than the WHO limit

value (UBA, 2010c).The Joint FAO/WHO Expert Committee on Food Additives experts established a

provisional tolerable monthly intake of 70 picogram/kg per month (WHO, 2014). This level is the

amount of dioxins that can be ingested over lifetime without detectable health effects (WHO, 2014).

Characterization

Toxic equivalent factor (TEF) expresses degree of toxic effect of a dioxin, taking into account that the

mechanism of the toxic effect is the same for all dioxins. The most toxic dioxin, 2,3,7,8 TCDD

(2,3,7,8-tetrachlorodibenzo-p-dioxin), has the reference value 1 (Van den Berg et al., 2006) and the

other dioxins are expressed according to this reference, as a toxic equivalent (TEQ) in relation to

2,3,7,8 TCDD (see Table 31). The present TEF scheme and TEQ methodology are primarily intended

for estimating exposure and risks via oral ingestion (Van den Berg et al., 2006). TEF does not

consider damage model and deals with information that is relevant for the special conditions and

which could not necessarily be extrapolated to others (Payet, 2008). Thus, TEF is used for human risk

assessment of dioxins compounds and could not be directly applied as LCA characterization factor.

That is why eco-factors have not been derived from the Table 31 using the eco-factor calculation for

TEQ.

0

50

100

150

200

250

300

350

1995 2000 2005 2010 2015 2020

kt

Year

PM10

Target PM10

PM2.5

Target PM2.5

77

Compound TEF (WHO 2005)

Chlorinated dibenzo-p-dioxins

2,3,7,8-TCDD 1

1,2,3,7,8-PeCDD 1

1,2,3,4,7,8-HxCDD 0,1

1,2,3,6,7,8-HxCDD 0,1

1,2,3,7,8,9-HxCDD 0,1

1,2,3,4,6,7,8-HpCDD 0,01

OCDD 0,0003

Chlorinated dibenzofurans

2,3,7,8-TCDF 0,1

1,2,3,7,8-PeCDF 0,03

2,3,4,7,8-PeCDF 0,3

1,2,3,4,7,8-HxCDF 0,1

1,2,3,6,7,8-HxCDF 0,1

1,2,3,7,8,9-HxCDF 0,1

2,3,4,6,7,8-HxCDF 0,1

1,2,3,4,6,7,8-HpCDF 0,01

1,2,3,4,7,8,9-HpCDF 0,01

OCDF 0,0003

Non-ortho–substituted PCBs

3,3',4,4'-tetraCB (PCB 77) 0,0001

3,4,4',5-tetraCB (PCB 81) 0,0003

3,3',4,4',5-pentaCB (PCB 126) 0,1

3,3',4,4',5,5'-hexaCB (PCB 169) 0,03

Mono-ortho–substituted PCBs

2,3,3',4,4'-pentaCB (PCB 105) 0,00003

2,3,4,4',5-pentaCB (PCB 114) 0,00003

2,3',4,4',5-pentaCB (PCB 118) 0,00003

2',3,4,4',5-pentaCB (PCB 123) 0,00003

2,3,3',4,4',5-hexaCB (PCB 156) 0,00003

2,3,3',4,4',5'-hexaCB (PCB 157) 0,00003

2,3',4,4',5,5'-hexaCB (PCB 167) 0,00003

2,3,3',4,4',5,5'-heptaCB (PCB 189) 0,00003

Table 31: Toxic equivalent factors (Van den Berg et al., 2006)

78

Current flow

Current flow is the emission of dioxins aggregated in TEQ (toxic equivalence) units for the year 2010

according to UBA statistical data, it was 67,7 g TEQ (UBA, 2013a).

Critical flow

The critical flow is taken in accordance with the obligation of Germany by the Aarhus Protocol on

Persistent Organic Pollutants (UNECE, 1998b). It obliges signing countries to reduce their emissions

of dioxins, furans below their levels in 1990 (UNECE, 1998b). Therefore, the critical flow is

considered as the value in 1990.

Eco-factor for dioxins


Normalization flow (g TEQ/a) 68

Current flow (g TEQ/a) 68 2010 (UBA, 2013a).

Critical flow (g TEQ/a) 747 1990 (UNECE, 1998b)

Weighting (-) 0,008

Eco-factor (EP/kg TEQ) 121 301

Table 32: Eco-factor for dioxins in Germany

Outlook

Due to the Strategy on Dioxins, Furans and Polychlorinated Biphenyls, that includes both short-term

and long-term reduction measures, Germany has achieved more than 90 % reduction of dioxins

emission since the year 1990 (see Figure 35). Thus, the reduction target for dioxins has been largely

fulfilled. However, further measures must be taken as to identify other dioxin sources and to reduce

emissions at the source (UBA, 2013a) and set new more restrictive targets.

Figure 35: Dioxins emissions trend in Germany (based on UBA, 2013a)

0

100

200

300

400

500

600

700

800

1990 1995 2000 2005 2010 2015

g TE

Q

Year

Dioxins

Target

79

5.1.8. Heavy metals: cadmium (Cd), lead (Pb) and mercury (Hg)


Heavy metals in Germany are mostly emitted to the atmosphere as a result of different combustion

processes and industrial activities (such as non-ferrous metal production, stationary fossil fuel

combustion, waste incineration, metals and cement production and etc.). Germany signed in 1998 and

ratified in 2003 the Aarhus Protocol on Heavy Metals (UNECE, 1998c). The main target was the

reduction of three heavy metals: cadmium (Cd), lead (Pb) and mercury (Hg), as they are highly toxic

and chemically stable. The latter means that these substances accumulate in the environment and

organisms and cause damage to ecosystems, and may also have harmful effects on human health. For

example, Cd is identified as a potential carcinogen and may cause lung cancer, Pb has neuro-behavior

effects on fetuses and children, and Hg can cause damage of organs, like liver and kidney, and

neurological damages (EEA, 2013). Germany has the target not to exceed the emission level of these

three metals in 1995 (UNECE, 1998c). As a result of the application of the Aarhus Protocol the

current emission levels for mercury, cadmium and lead have been reduced around 70 %, 50 % and 30

% from the emission level in 1995, respectively.

Current flow

Current flows are the national emissions of mercury (9,4 t), cadmium (5,4 t) and lead (194 t) for the

year 2010 taken from UBA statistic (UBA, 2013c).

Critical flow

Critical flows are the levels of emission in 1995 of cadmium, lead and mercury, three particularly

harmful metals, controlled by the Aarhus protocol (UNECE, 1998c). Germany has to reduce its

emissions for these three metals below their levels in 1995.

Eco-factors for heavy metals

Step of the eco-factor calculation (units)

Result Reference year/ source of data

Mercury (Hg) Cadmium (Cd) Lead (Pb)

Normalization flow(t/a) 9,4 5,4 194

Current flow (t/a) 9,4 5,4 194 2010 (UBA, 2013c)

Critical flow (t/a) 14 11 694 1995 (UNECE, 1998c)

Weighting (-) 0,43 0,22 0,08

Eco-factor (EP/kg) 45 968 018 41 551 246 403 375

Table 33: Eco-factors for emissions of Hg, Cd, Pb to air in Germany

Outlook

Since 1995, Germany has significantly reduced the level of Hg, Cd, Pb emission and it seems this

positive trend will continue (see Figure 36 and Figure 37). In order to promote further reductions, new

stricter targets should be considered. Furthermore, there should be more control and reduction targets

for some other heavy metals (for example nickel) and arsenic (As).

80

Figure 36: Pb emissions to air trend in Germany (based on UBA, 2013c)

Figure 37: Cd, Hg emissions to air trend in Germany (based on UBA, 2013c)

5.2. Emissions to surface water

5.2.1. Nitrogen (N) and phosphorus (P)


High concentration of nutrients in water, like nitrogen and phosphorus, affects the oxygen balance in

the water body and causes eutrophication and acidification. This disrupts natural substance cycles and

ecosystem relationships, and causes biodiversity losses (UBA, 2009b). The main source for

phosphorus and nitrogen emission in Germany is agriculture sector, around 50 % for nitrogen and

70 % for phosphorus (UBA, 2010e). The pollution also comes from water treatment and industrial

facilities, traffic and power stations. Due to innovations and improved management techniques, a

significant progress in reducing substances emission from industrial production plants has been

0

500

1000

1500

2000

2500

1990 1995 2000 2005 2010 2015

t

Year

Pb

Pb Target

0

5

10

15

20

25

30

35

1990 1995 2000 2005 2010 2015

t

Year

Cd

Cd Target

Hg

Hg Target

81

achieved over the past 30 years (UBA, 2010e). Compared with pollutant sources such as industrial

facilities or sewage treatment plants, reduction achievements in agricultural sector have been

comparatively lower. For the period between 1985 and 2005, releases of nitrogen from agriculture

were reduced by 22 % and phosphorous discharges have remained almost unchanged (UBA, 2010e).

With regard to the European Union (EU) Water Framework Directive (WFD) (European Comission,

2000), Germany should achieve “good ecological and chemical conditions of water” by 2015 (UBA,

2009a). The German Working Group on water issues of the Federal States and the Federal

Government represented by the Federal Environment Ministry (LAWA) is responsible for the

implementation of the European Water Framework Directive by setting the target limits and

monitoring nitrogen and phosphorus in surface water.

Current flow

The level available data of nitrogen and phosphorus emission in German surface water for 2005, given

by UBA, is evaluated as around 565 kt for N and 23 kt for P (UBA, 2010d).

Critical flow

Critical flow is calculated trough the limitation for the concentration of these nutrients in surface

waters. Namely, the concentration limit for nitrogen in surface water is 2,5 mg/l. The highest annual

concentration that was measured at LAWA test point was 6 mg/l in German water bodies (UBA,

2010d). For phosphorus, the limit is 0,15mg/l and the highest detected concentration was 0,3 mg/l

(UBA, 2010d). With the assumption that the volume of the surface water bodies is constant, the

critical flow is calculated as the current flow multiplied by the ratio between target concentration and

current concentration. The assumption is based on precautionary principle, as the worst case is

considered.

Eco-factors for N and P


N P

Normalization flow (t/a) 564 775 23 390

Current flow (t/a) 564 775 23 390 2005 (UBA, 2010d)

Critical flow (t/a) 235 323 11 695 2015 (European Comission, 2000)

Weighting (-) 4,0 5,8

Eco-factor (EP/kg) 10 199 171 017

Table 34: Eco-factors for emissions of nitrogen and phosphorus to surface water in Germany

Outlook

To achieve the goal by 2015 there should be measures towards the decrease of nutrient pollution from

diffuse sources, like agriculture, losses from scattered dwellings and atmospheric deposition on water

bodies, that still have big potential of reduction, for instance, agriculture has the largest emission

reduction potential through the improving of the fertilization efficiency (BMU, 2013c). Despite the

efforts made over many years to reduce nutrients inputs into the environment, most of the related

environmental quality objectives and environmental action targets have not been achieved to date (see

Figure 38) (UBA, 2009b).

82

Figure 38: N and P emissions to surface water trend in Germany (based on UBA-Federal Environment Agency,

2010c)

Moreover, the statistical data are also incomplete. At this point only data for 2005 are publicly

available. The experts list the following reasons presented in Figure 39 for the delay of the WFD

implementation. The main reasons are lack of financial and human resources, opposition to envisaged

the measures, problems with obtaining the necessary land (BMU, 2013c).

Figure 39: Delays in the implementation of measures for 2015 objectives, and reasons for these delays (BMU,

2013c)

5.2.2. Polycyclic aromatic hydrocarbons (PAHs)


Polycyclic aromatic hydrocarbons (PAHs) are molecules with several fused aromatic rings. PAHs are

high persistent and some of them can cause carcinogenic and mutagenic effects (UBA, 2002).

0

200

400

600

800

1000

1200

1985 1990 1995 2000 2005 2010 2015

t

Year

N

N target

P

Ptarget

0 1000 2000 3000 4000 5000 6000 7000

Legal obstacles

Cost changes

Technical obstacles

New findings concerning measure impact

Problems with obtaining the necessary land

Opposition to the envisaged measures

Problems with obtaining financial and/or personalresources

Number of mentions

76%

24%

Substantial delay has been indicatedSubstantial delay has not been indicated

83

Therefore, the group of PAHs is included in the list of priority substances of the Water Framework

Directive (UBA, 2010a). Among the PAHs, only anthracene, naphthalene and small amounts of

fluoranthene are produced in Germany (UBA, 2010a). The main sources of water pollution are

municipal wastewater treatment plants, metal industry and energy sector (UBA, 2012b). According to

the UBA-Federal Environment Agency, (2012b) more than 80% of the PAHs input into water bodies

is influenced by atmospheric deposition. Furthermore, PAHs can enter the waters via sewage

treatment plants, diffuse sources, erosion and surface run-off.

There are various regulations in Germany that limits the use of PAHs in specific products and the

emissions to the environment. Two examples are the directives 2004/107/EC relating to polycyclic

aromatic hydrocarbons in ambient air, and the 2001/90/EC relating to restrictions on the marketing

and use of certain dangerous substances and preparations (for instance, creosote). Nevertheless, these

recommendations sometimes contain also a portion of compromise and can have merely preliminary

character (UBA, 2002).

Current flow

There are more than 100 compounds included in the PAHs group. It is hard to differentiate each type

of PAHs for measurements, due to the high number of intra bonds, i.e. one substance can be composed

from different kinds of PAHs. This is the reason why the most important ones are compiled as „PAH

sum”, including 16 PAHs, like highly toxic benzo(a)pyrene, naphthalene, pyrene, indeno(1,2,3-

cd)pyrene, and others (UBA-Federal Environment Agency, 2010a). Current flow is taken from UBA

latest available statistics as average emissions for the period 2003-2005, that was equal to 19,4 kt

(UBA, 2010d).

Critical flow

Critical flow is taken in accordance with the scenario of UBA. The scenario assumes that with the

Implementation of the Federal Immission Control Act (BMU, 2009), aimed to affect the amount of

PAHs that go to water bodies by atmospheric deposition, the reduction potential for the total PAHs

emissions into German water by 2025 will be 32,5 %, compared to the level of 2005 (UBA, 2010a).

Eco-factors for PAHs



Current flow (kt/a) 19 2005 (UBA, 2010a)

Critical flow (kt/a) 13 2025 (UBA, 2010a)

Weighting (-) 2,2


Table 35: Eco-factors for emissions of PAHs to surface water in Germany

Outlook

Due to the complexity of data collection for PAHs emission and delays in data delivery, there is not

any statistic available to define long termed national trend. The only information available is the trend

estimated for PAHs in water of Baltic and North seas, which shows a decreasing trend for some PAHs

(UBA, 2010d).

84

5.3. Resources

Germany, as a highly developed and industrialized country with a large population density, is

particularly dependent on natural resources, like raw materials, energy, water and land area (UBA,

2007). Improving resource efficiency can become a German hallmark (BMU, 2012). Germany has

launched several programs to implement some long-term measures toward resource-efficient

management of natural resources. However, the reduction targets are defined still only for few

resources. The sections below describes the situation for two significant resources for Germany with

existing targets for eco-factor calculation, land use (5.3.1.) and primary energy consumption (5.3.2.).

5.3.1. Land use


Land in Germany is used for different purposes, agriculture, forestry, transport, natural conservation,

resource extraction, transport, settlement and so on. In Germany the biggest increase on land use has

been in the field of settlement and transport. The environmental consequences for these types of land

use are loss of soil natural functions and therefore loss of biodiversity, among others. Moreover,

settlement and transport increase noise and pollution. The goal of the German Government is to limit

and reduce the land use for settlement and transport (Statistisches Bundesamt, 2012).

Current flow

In 2010 the built-up area and transport infrastructure expansion was 87 ha per day (Statistisches

Bundesamt, 2012).

Critical flow

The aim of the Federal Government is to limit the land use up to 30 ha per day by the year 2020

(Statistisches Bundesamt, 2012)

Eco-factor for land use


Normalization flow (ha/day) 87

Current flow (ha/day) 87 2010 (Statistisches Bundesamt, 2012).

Critical flow (ha/day) 30 2020 (Statistisches Bundesamt, 2012).

Weighting (-) 8,4

Eco-factor (EP/ha) 264 840 183

Table 36: Eco-factor for land use in Germany

Outlook

The trend of the land use in Germany is presented in Figure 40. From the figure is easy to see that

there is still big gap between current and desirable state. The conclusion of Indicator Report of 2012

Sustainable Development in Germany stays that: „Continuing the average annual trend of the last few

years would, however, still not be sufficient to reach the proposed reduction goal by 2020”

(Statistisches Bundesamt, 2012).

85

Figure 40: Land use trend in Germany (based on Statistisches Bundesamt, 2012)

5.3.2. Energy consumption


The consumption of energy affects ecological systems, soil, water bodies and ground water through

the depletion of natural energy resources and the emissions of harmful substances, like greenhouse

gases (Statistisches Bundesamt, 2012). In September 2010, the Federal Government adopted the

“Energy Concept” which sets out Germany's energy policy (BMWi; BMU, 2011).The aim of the

Energy Concept is to provide in Germany high level of energy security, and effective environmental

and climate protection through the political objectives for energy system. The concept set the target to

reduce the annual primary energy consumption 20 % by year 2020 in comparison to the level of 2008

(BMWi; BMU, 2011). Besides this, the German government plans to use system of monitoring to keep

on track the progress to target.

The reduction of the primary energy consumption should be achieved with policy measures within

environmental and economic fields. The growth of the proportion of renewable energy is the core to

achieve the target. The current share from different sources in power production is presented in Figure

41. Currently, fossil energy sources and nuclear energy have the largest share of power production in

Germany. Renewable sources, including hydropower, wind power, solar energy and geothermal

energy and biomass have a share of 20 %. To achieve the target of 20 % reduction in primary energy

consumption, the share of renewable energy should increase up to 35 % in primary production, and

along with additional measures for effective reduction in the consumption (Statistisches Bundesamt,

2012).

0

20

40

60

80

100

120

140

1996 2001 2006 2011 2016

ha/

day

Year

Land use

Target

86

8%

5%

3%

3%

1%

BiogenichouseholdwastePhotovoltaic

Water

Biomass

Wind

Characterization

ILCD (JRC: The European Commission, 2012) gives characterization factors (CFs) for some energy

resource. CFs are expressed as net calorific value per mass. Thus, the eco-factors can be calculated for

these resources (see Table 38).

Current flow

The current flow is the primary energy consumption in Germany in 2010, it was equal to 14 217 PJ

(AGEB, 2013).

Critical flow

The critical flow is calculated as a 20 % reduction of the level of primary consumption in 2008 by

2020. The primary consumption in 2008 was 14 380 PJ (AGEB, 2013).

Eco-factor for primary energy consumption


Normalization flow (PJ/a) 14 217

Current flow (PJ/a) 14 217 2010 (AGEB, 2013)

Critical flow (PJ/a) 11 504 2020 (BMWi; BMU, 2011)

Weighting (-) 1,5

Eco-factor (EP/MJ) 0,1

Table 37: Eco-factor for primary energy consumption in Germany

Nuclear energy 18%

Renewables 20%

Heating oil, pumped-storage

and other 5%

Lignite 24%

Natural gas 14%

Hard coal 19%

Figure 41: Power production in Germany in 2011 (BMWi, 2012)

87

Eco-factors for some energy resources

Resource Net calorific value (MJ/kg) EF, EP/kg

Crude oil 42 4,2

Hard coal 26 2,6

Brown coal 12 1,2

Natural gas 44 4,4

Uranium 544 284 54 428,4

Table 38: Eco-factors for some energy resources in Germany

Outlook

During the period of 1990-2010 energy productivity in Germany increased by 37 % (Statistisches

Bundesamt, 2012). However, even with the increase of productivity the primary energy consumption

was reduced only by 6 % (see Figure 42). The increase in energy efficiency has been offset by the

growth of the consumption because of a growing economy. “A continuation of the previous average

pace of development would not be sufficient to achieve the goals set for 2020 for either energy

productivity or primary energy consumption” (Statistisches Bundesamt, 2012).

Figure 42: Primary energy consumption trend in Germany (based on AGEB, 2013)

0

2000

4000

6000

8000

10000

12000

14000

16000

1990 1995 2000 2005 2010 2015 2020

PJ

Year

Primary energy consumption

Target

88

5.4. Overview

Set of eco-factors for Germany

The set of eco-factors for Germany is presented in Table 39. It includes a wide range of emissions to

air, GHGs, NMVOCs, NOx, NH3, SO2, PM10, PM2.5, dioxins and heavy metals, Hg, Cd, Pb. The eco-

factors for emissions to surface water, like N, P and PAH, are also listed in the table, as well as

resource, land and energy use or consumption. Most of the listed substances, except, emissions to

surface water, have been calculated with the critical flow derived from the proper national reduction

target. The eco-factors for nitrogen and phosphorus are defined with the corresponding thresholds. The

targets and thresholds are coordinated with the legal national targets for the corresponding substances

or resource. There are some gaps, for example, waste, noise, emissions to soil, because these issues

due to several internal reasons are not subject to the targets set out in the German legislation.

Substance Weighting Eco-factor Eco-factor's unit

GHG (air) 1,5 1,63 EP/kg CO2-eq.

NMVOCs (air) 1,1 1 066 EP/kg

NOx (air) 1,9 1 443 EP/kg

NH3 (air) 1 1 822 EP/kg

SO2 (air) 1,4 3 125 EP/kg

PM10 (air) 1,8 8 638 EP/kg

PM2.5 (air) 1,8 15 621 EP/kg

Dioxins (air) 0,008 121 301 EP/kg TEQ

Hg (air) 0,4 45 968 018 EP/kg

Cd (air) 0,2 41 551 246 EP/kg

Pb (air) 0,1 403 375 EP/kg

N (surface water) 4,0 10 199 EP/kg

P (surface water) 5,8 171 017 EP/kg

PAHs (surface water) 2,2 113 047 EP/kg

Land use 8,4 264 840 183 EP/ha

Energy 1,5 0,1 EP/MJ

Table 39: German set of eco-factors

Environmental hot spots in Germany

Figure 43 shows German national overall environmental impact based on actual situation and assessed

categories, i.e. the national critical flows are multiplied with the corresponding eco-factor (see

Equation 3). Within the overall impact of Germany, the biggest share is for land use (25 %), and for

nitrogen (17 %) and phosphorus (12 %) emissions to surface water. The lowest environmental impacts

are for emission of dioxins and heavy metals to air. The chart shows that some environmental

categories have higher score in overall result, for example land use. The national current flow of these

substances is higher than the critical flow. As a consequence, the weighting that is a squared ratio

between current and critical flows, of the substances, is high. In general, it is clear that different

substances have different priority for German environmental policy; however, there is no such a

drastic dominating substance as for Russian set.

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Figure 43: Overall annual environmental impacts of Germany

5% 3%

6%

3%

4%

6%

6%

1%

1%

17% 12%

7%

25%

4%

GHG (air)

NMVOCs (air)

NOx (air)

NH3 (air)

SO2 (air)

PM10 (air)

PM2.5 (air)

Dioxins (air)

Hg (air)

Cd (air)

Pb (air)

N (surface water)

P (surface water)

PAHs (surface water)

Land use

Energy

90

6. Use of German and Russian eco-factors in a case study:

bamboo and aluminum bike frame

The chapter presents the use of the set of eco-factors for Germany and Russia (calculated in Chapter 4

and 5, respectively) in a case study. The objective of this chapter is to:

• Use national sets of eco-factors for Germany, Russia and Switzerland, as the benchmark, to

measure the single-score “environmental footprint” of a case study;

• Identify the differences in overall result caused by the individual set of eco-factors of each

country;

• Test the applicability of the method for Russia and Germany.

Bicycle is the most popular transport in the world, in 2007 the production of bicycles was equal to

130 bln units worldwide (Gardner, 2008). Moreover, bicycle is potentially an important way of

sustainable urban transportation system: it does not need fuel during use phase; it is relatively cheap

and good for the health of the users. Russia and Germany have high rates of urban population, more

than 70 % of the total population, according to the World Bank database. The wider use of bikes in the

cities can have positive effects, like reduced air and noise pollution, effective land use, lower health

costs, etc. (Gardner, 2008). In Germany the production of bikes in 2012 was 2 211 thousand units, and

sales in the same year ware equal to 3 966 thousand units (Colibi & Coliped, 2013). For both

categories, Germany is the leader among the European countries (Colibi & Coliped, 2013). The

production of bicycles in Russia in 2010 made up 1 169 thousand units according to United Nations

Statistics Division (UN, 2014). The sales in the Russian Federation ware around 4 300 units in 2012

and will keep growing in 2013-2017 up to 5 410 thousands (BusinesStat, 2014).

The frame is one of the main parts of a bicycle. In this case study, two types of bike frames are

considered, an aluminum alloy frame, popular due to its weight properties, and a frame made of

bamboo, a natural and renewable material. Taking into account the high production and sales rates of

bikes in Russia and Germany, the comparison of different frames may support decision making.

The study framework and data collection were first proposed by Chang, Schau, & Finkbeiner, (2012)

and Chang, Neugebauer, & Finkbeiner, (2013). The most relevant elements of LCA study are briefly

described in section 6.1. Results for the Ecological Scarcity method are shown and discussed in

section 6.2.

6.1. Case study description

The two documents Application of Life Cycle Sustainability Assessment to the bamboo and aluminum

bicycles in surveying social risks of developing countries (Chang, Schau, & Finkbeiner, 2012) and Life

Cycle Sustainability Assessment (LCSA) comparison of modern bikes (Chang, Neugebauer, &

Finkbeiner, 2013) further describe the goal and scope of the case study selected in this chapter. These

previous documents include results for life cycle assessment (LCA), using the impact method ReCiPe,

for life cycle costs (LCC) and for social life cycle assessment (SLCA). This chapter only focuses on

the environmental impact assessment results.

The goals of the study by Chang et al., (2012) are to assess the environmental impacts of the different

life cycle phases (i.e. raw material extraction, raw material processing and frame manufacturing),

91

compare the environmental assessment for the bamboo and aluminum frame bicycles, and contribute

to the future development of LCA, LCC and SLCA. The functional unit used is transporting 15 000

person km which is fulfilled with a reference flow of one bicycle for both materials (Chang et al.,

2012). The system boundaries of the bamboo frame and aluminum frame are presented in Figure 44

and Figure 45, respectively.

For the bamboo frame the raw material is cultivated and harvested at sustainable managed plantations

in China (see Figure 44). The inputs and outputs of the agricultural stage, including for instance

manure and gasoline, are estimated in Chang et al., (2012). The raw material processing stage takes

part also in China and includes preservation, drying and cutting of bamboo into a standard length.

After the raw material processing, the bamboo stems are transported to Germany by truck and ship and

all the processes of the manufacturing of the frame take place in Germany (Chang et al., 2012).

Figure 44: System boundaries of the bamboo bike frame (based on Chang et al., 2012)

According to Figure 45, the raw material stage for the aluminum frame includes the mining of the

bauxite in Guinea. The processed alumina is then exported and the whole frame manufacturing occurs

in Germany. For the manufacturing of the frame, the share of primary alumina is 40 % and recycled

60 %, according to Chang et al. (2012) who reflect the real aluminum production conditions in

Germany.

• Bamboo cultivation

• Bamboo harvesting

• Preservation • Drying • Cutting

• Cutting into length

• Machining of bamboo tube ends

• Threading

Raw material extraction

(China)

Raw material processing

(China)

Frame manufacturing

(Germany)

92

The material and energy inputs of bamboo and aluminum bike frames production are presented in

Table 40.

Item Bamboo frame Aluminum frame

Fertilizer (Manure) 34 kg -

Gasoline 0,0043 l -

Boron solution 0,93 kg -

Bamboo stem 2,0 kg -

Hemp 0,1 kg -

Epoxy resin 0,1 kg -

Bauxite - 4,1 kg

Primary aluminum - 1,0 kg

Secondary aluminum - 1,5 kg

Tap water 0,60 kg 0,71 kg

Energy 68 MJ 71 MJ

Table 40: Main materials and energy input of bamboo and aluminum frames per functional unit (Chang et al.,

2012)

Regarding the environmental impacts, 18 mid-point ReCiPe indicators were adopted by Chang et al.,

(2012). The results of the LCIA showed that the impacts of the life cycle of the aluminum frame are

higher than from the bamboo frame, except for ionizing radiation and terrestrial acidification. The

aluminum frame had larger environmental impacts in categories as freshwater ecotoxicity, freshwater

eutrophication, human toxicity, marine ecotoxicity, water depletion and other. The carbon footprint of

aluminum frame was higher than bamboo frame (Chang et al., 2012).

Aluminum

recycling

(Germany)

• Bauxite

• Alumina processing

• Aluminum production

• Cutting • Bending • Machining • Welding • Finishing

Raw material extraction (Guinea)

Raw material

processing

(Germany and

Guinea)

Manufacturing the frame (Germany)

Figure 45: System boundaries of the aluminum bike frame (based on Chang et al., 2012)

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6.2. Assessment of the case study with the Swiss, German and Russian

eco-factors

The LCI of the case study, described in 6.1. , is assessed here with the Ecological Scarcity method for

Switzerland, Germany and Russia. The LCI is assessed with the sets of national eco-factors to identify

how the use of country specific eco-factors affects the results and how the results reflect the national

level of “scarcity”.

The new sets of determined eco-factors for Russia and Germany were added to the GaBi 6.0 Software

(Schuller et al., 2013), that helped on the calculation of the results. The Swiss Ecological Scarcity

Method Eco-Factors 2006 (Frischknecht et al., 2009) are in the software by default.

The inventory is exactly the same for the three set of eco-factors. Though, the Ecological Scarcity

method considers the possibility to incorporate regionalization (see Equation 4), here the eco-factors

are not adjusted to the countries where the specific processes took place. In order to express the

environmental impact results for different pollutants in single-score units, i.e. eco-points (EP), the

values can be summarize and compared. The elementary flows in physical units should be multiplied

with the corresponding eco-factor (see Equation 3). The single-score results for the bamboo and

aluminum bike frames are presented in Table 41.

Aluminum frame Bamboo frame Difference, %

Germany, EP/FU 838 136 616

Russia, EP/FU 6 533 451 1 069 112 611

Switzerland, EP/FU 41 454 4 694 883

Table 41: Single-score results for aluminum and bamboo frames for Germany, Russia and Switzerland per

functional unit

The aluminum frame has a higher single-score than bamboo frame in the three assessed cases. Some

of the reasons, why aluminum frame can have bigger environmental impacts are explained by Chang

et al.,(2012). For example, the high contribution to some of the environmental impacts (eutrophication,

waste) during the raw material processing stage of aluminum frame production or the assumption that

for bamboo plantation only rainfall is needed.

The single-scores obtained for the same case study in each country are different (see Table 41).

However, it should be underlined that the countries have very different sets of eco-factors and cannot

be directly compared. They cannot be compared due to the differences in national priorities (i.e.

differences in the targets stated) and normalization flows, as well as in the number of environmental

aspects covered. The uncovered environmental aspects have zero impact in the final result. For

example, the emissions to soil were not assessed for Russia, due to the lack of data regarding the state

of the soil and appropriate target. It should be emphasized that each country considers each own set of

impact categories, and thus emissions. Therefore, within the label “emissions to sea water”, for

instance, different substances are taken into account for the three countries. While eco-factors for sea

water in Russia include TPH and phenols, Switzerland considers radioactive emissions to seas and for

Germany no emissions to sea water are considered.

Figure 46 and Figure 47 show the share of different emissionss in the total result for aluminium and

bamboo frame. It is clearly seen that there are one or two dominating categories for the assessed

94

countries with no dependence on the number of eco-factors within the national set. However, the

media with major contrbution in Russia, Germany and Switzerland are different.

In case of aluminium frame the dominating impacts are

• Emissions to see water for Russia (99 %);

• Emissions to air for Germany (99 %);

• Resources consumption for Switzerland (52 %) and emissions to air (44 %).

For bamboo frame the dominating impacts are

• Emissions to see water for Russia (99 %);

• Emissions to air for Germany (93 %);

• Emissions to air for Switzerland (64 %) and emissions to fresh water (23 %).

Figure 46: The share of different emissions from the aluminum frame for Switzerland, Germany and Russia

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Russia Germany Switzerland

Aluminum frame

Emissions to industrial soil

Emissions to agricultural soil

Emissions to sea water

Emissions to fresh water

Emissions to air

Resources

95

Figure 47: The share of different emissions from the bamboo frame for Switzerland, Germany and Russia

The LCA results show that bamboo frame has a lower “environmental score” than aluminum frame.

The same result was obtained by Chang et al. (2012) with the ReCiPe and carbon footprint methods.

In spite of the different comprehensiveness of the eco-factor sets for Switzerland, Germany and

Russia, there are few dominant environmental impacts in all the cases, though the most contributing

substances are not completely similar. The difference in the most contributing substances depends on

national scarcity, because the inventory of the case study is assumed to be constant. In general, the

comprehensiveness of the eco-factor sets also depends on the national environmental conditions and

needs.

6.2.1. Results for Russia

In this case study four environmental media/categories can be assessed with the developed national set

of eco-factors, for the aluminum and bamboo frames: resources, emissions to air, to surface water and

sea water. The share of the environmental categories in the total result is similar for bamboo and

aluminum frames, but the total environmental score is different. Table 42 shows the environmental

impact in single-score for substances and resources from the assessed categories.

EP/FU Aluminum frame Bamboo frame

Resources

Energy 30 1,3

Emissions to air

GHG 9,8 1,2

ODS 0,1 1,2

PM 5,0 0,4

Emissions to water

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Russia Germany Switzerland

Bamboo frame

Emissions to industrial soil

Emissions to agricultural soil

Emissions to sea water


Emissions to air

Resources

96


Phosphorus to fresh water 15 27

Phenols to see water 6 533 392 1 066 662

Table 42: Environmental impacts of environmental issues making main contribution for two bike frames

(Russian eco-factors set)

The results for the two frames are rather different (see Table 42). The score for consumption of energy

is more than 20 times larger and for particulate matter around 12 times larger for the aluminum frame.

However, the emissions of phosphorus and ozone depleting substances have 1,8 and 17 times

correspondingly higher impacts for the bamboo frame .

Phenols emissions to sea water for the two frames have the largest score and leave other

environmental issues in minor contribution. This can be explained by the high eco-factor of phenols

emissions to sea water in Russia, as the current national flow of the emissions is several times higher

than the threshold, the second reason is the high mass of the substance released into the sea, according

to the inventory data compared to the national normalization flow assumed for the eco-factor

calculation (see 4.3.). To see better the contribution of the other substances, the results for the two

types of frames without sea water emissions category are presented in Figure 48. In this case, the

dominating environmental issues are rather different, for aluminum frame the most contributing

category is resources (50 % of total score) and for the bamboo one, emissions to fresh water (87 % of

total score). Emissions to air and fresh water have more or less equal importance for production of

aluminum frame, with around 25 % share of each in total result. For bamboo frame, emissions to air

are equal to 9 % in total result and resources category has only 4 %.

Figure 48: The share of different emissions excluding emission to sea water from the aluminum and bamboo

frame for Russia

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Aluminum Frame Bamboo Frame


Emissions to air

Resources

97

6.2.2. Results for Germany

There are 3 environmental categories assessed with German set of eco-factors, namely, resources,

emissions to air and emissions to surface water. Table 43 presents single-score result in EP for main

resources, emitting substances and substance groups, like energy consumption, land use, greenhouse

gases, SO2, particulate matter, heavy metals and emissions to water (PAHs and phosphorus).


Resources

Energy 21 0,5

Land use - 8,2

Emissions to air

GHG 48 5,1

SO2 324 46

PM 269 26

NOx 91 32

Heavy metals 89 15

Emissions to surface water

PAHs 1,3 0,0

Phosphorus 0,7 1,2

Table 43: Environmental impacts of environmental issues making main contribution for different bike frames

(German eco-factors set)

Aluminum frame has higher score for all the substances, except, phosphorus and land use. SO2 has the

largest contribution for both frames (38 % for aluminum and 34 % for bamboo), NOx has a share of

11 % and 23 %, and PM, around 31 % and 19 %, correspondingly. Phosphorus has higher score for

bamboo frame, the same as in the case of Russia. That means that mass of phosphorus emissions is

rather large for bamboo frame. Land use has 6 % in total score of bamboo frame; however, for the

aluminum frame it is not relevant and has no score in total result.

6.3. Outcome

In spite of the fact that aluminum frame has higher environmental score both for Russia and Germany,

it should be underlined that the ecological performance of the products assessed with the Ecological

Scarcity method is carried out with reference to the political agenda of the specific country

(Frischknecht et al., 2012). Thus, the results for different options can be compared only on the national

level.

Comparing the results of the case study with the results for national overall environmental impact (see

4.6. and 5.4.), it is obvious that environmental priorities on the national level do not directly reflect the

score for the environmental interventions from a particular product. The result of the LCIA depends on

the inputs/outputs included in the inventory and the amounts considered emissions or resource. For

example, HCFCs emissions, that have major share in overall Russian environmental impact, have

mere contribution for the score of the products assessed, because hardly presented in the life cycle of

bike frames. Thus, environmental hot spots on national and product level maybe different.

98

The assessment with Ecological Scarcity method should be reasonable for the specific product, i.e. the

number of eco-factors considered should be high enough to provide the necessary information to

support the right decision, as it is promoted as a decision making tool. Based on the case study, it

seems possible to state with the eco-factor sets for Germany and Russia, which is the product with

lower environmental impact within the options, and define environmental hot spots for each product.

However, it is important to check, if some significant environmental issues for the particular product

are omitted due to the lack of the corresponding eco-factor within the set. For example, in the case of

the bamboo frame, it is important to include land use category, while in the case of aluminum frame

land use does not have such an important relevance.

The case study shows that the Ecological Scarcity method for Russia and Germany, which is

developed in the thesis, can be used for the identification of the environmental hot spots of the

product. The single-score result may be convenient for comparison of alternatives to support internal

decision making among non LCA experts. The method is not suitable for marketing purposes, i.e. to

promote one of the compared alternatives. This is due to the weighting that is the underlying approach

of the method, and it is not allowed to be used to be disclosed to the public (ISO, 2006b). The direct

comparison between the countries is also not possible, due to the methodology based on national

policy. However, the definition of a common normalization flow can solve the problem in the future.

In general, the choice of the method for LCIA should meet the requirements formulated in goal and

scope. Moreover, the developed method can be used for the estimation of the environmental impacts

that are defined as the priority of national environmental policy, for more detailed analysis the method

can be combined with some other methods for LCIA.

99

7. Discussion - Evaluation and interpretation of results

One of the purposes of development of the Ecological Scarcity method for Russia and Germany is to

provide the decision makers in these countries with a manageable method to measure the

environmental performance of a product in compliance with the environmental policy of these

countries. This means also, to go beyond the general compliance with environmental regulation and

move towards an active management. The application and development of the method has distinctive

features that will be discussed within the chapter. The chapter gives the information about challenges

for eco-factor calculation (7.1.), application of the method on different levels (7.2.), comparability of

results (7.3.), some effects that can affect the results (7.4.) and future scenarios to define the possible

consequences of the decision in environmental policy (7.5.).

7.1. Challenges for eco-factor calculation for Russia and Germany

To calculate an eco-factor for an environmental intervention, data regarding the current state and data

regarding desired state of environment are vital. The main challenge for development of the

Ecological Scarcity method for Russia and Germany is data availability, consistency, actuality and

coverage. Moreover, the available data should have the format suitable for eco-factors calculation and

its further use in LCIA.

7.1.1. Challenges for current flow quantification

One of the problems to define the current flow for eco-factors calculation in the thesis is the lack of

broad and harmonized environmental statistic in Russia and Germany. For instance, the data given in

the official annual state report about environmental situation in the Russian Federation (Russian State

Committee on Environmental Protection, 2011) are inconsistent. It is difficult to compare specific data

sets over time or identify trends due to the lack of stability in the set of indicators used and in the

scope of statistical observation that are often changed over the years. In some cases, current

environmental situation is described in statistical data through the long-term trend measured in percent

without reference to a base year, e.g. emissions are 30% higher than in previous year, or through

integrated evaluation of environmental quality, like polluted or highly polluted and etc. Thus, these

kind of data demand additional information or assumptions to estimate current flow, as a mass flow of

pollutant or resource consumed. In this case, for example for emission to sea water, the current flow

was calculated as the product of the detected concentration of the pollutant and the volume of water of

specific water body. Besides, the report often gives information on selected separate objects, for

example separate region, sectors or natural object, like river or lake, of the Russian Federation, and

very often using different indicators and evaluations scope. This creates difficulties for data

aggregation and for the estimation of the average current flow at the national level. In German

statistics more data regarding the present state of the environment are available, than for Russia.

However, some environmental issues are lacking, for example the statistical data for ODS emissions to

air, or measured in physical units, that are not convenient for further calculation of eco-factors.

The quality of the environmental monitoring system and the availability of monitoring data influence

the existence of environmental data on country level. A large country needs enough monitoring

stations to get the full information regarding environmental issues. According to the United Nations

Environment Programme Global Environment Monitoring System (GEMS) there are 53 water

monitoring stations in Russia and 17 in Germany. The water area in Russia is 720 500 km2 and in

Germany, 8 350 km2

(CIA, 2014). Thus, there is 1 monitoring station for 13 594 km2 in Russia and

100

491 km2 in Germany. However, a wider net of monitoring stations is also not a guarantee of

availability of the annual data on the national level. For instance, the assessment of total PAHs

(Polycyclic aromatic hydrocarbons) in German surface water (see 5.2.2.) is a complicated process that

requires using different models along with the monitoring results , for example, MONERIS Model, to

estimate the total emissions in water bodies based on monitoring data from several measuring spots.

This causes delays in data availability. The last report on national statistic of UBA - Federal

Environment Agency - for 2010 delivered data up to 2005 (UBA, 2010a).

The current flows in the thesis are derived from the latest available statistic (mostly for 2010-2011).

Actuality of the data plays an important role for the Ecological Scarcity method as it is based on

distance to target principle. The environmental situation is changing over the years, affecting the value

of the eco-factor. In case, the situation is improving the use of old data can lead to the overestimation

of the eco-factor value and in the case of an increasing of environmental stress – to underestimation.

This is one of the weaknesses of the Ecological Scarcity method, as the number and value of eco-

factors depends not only on the availability, but also on the quality of national environmental statistic.

7.1.2. Challenges for critical flow quantification

Monitoring and a correct evaluation of the results of monitoring are essential not only for the

definition of current flows. They are also a tool to characterize the nature of the environmental

problem, provide information and support policy makers (Selman & Greenhalgh, 2009). Monitoring

data is helpful for the identification of the appropriate actions to reduce negative environmental effects

and setting reduction targets. The establishment of a target is not really feasible without rigorous

review of the current state of the environment. Policy makers need to evaluate the potential reduction

to set the target and/or chose the base year for the reduction. For example, the data for annual GHG

emissions in Russia or for annual emissions of GHG, NMVOCs, NOx, NH3, SO2 and PM in Germany

are well presented and publicly available. For these emissions, it is then feasible to define the eco-

factor and general trend over the years.

To define the eco-factor the critical flow should be set in a specific quantity. Within the thesis several

options are used to define the critical flow, depending on the availability of data. One way is to use

absolute targets that expressed as a percentage and are measured against a deadline, e.g. 99,5 %

reduction of HCFC by 2020 compared to the base year in Russia. Other option is to use the level, fixed

by government, of the emissions without connection with the percentage of the reduction, e.g. not to

exceed the level of dioxins emissions in 1990 in Germany. The third type of data, used for estimation

of critical flows, is MAC (maximum allowable concentration) that refers to the maximum level of

emissions that is not harmful for human and/or ecosystem, e.g. MACs for nitrogen and phosphorus in

surface water. In case of using the maximum allowable concentration to quantify the critical flows

additional assumptions and data are needed, like, for example, volume of the media.

Some environmental issues, e.g. use of plant protection products or waste production in Germany,

could not be included to the national eco-factor set in the thesis, due to the absence of critical flows. In

general, there are several reasons for lacking of critical flows: little environmental relevance for the

country, for example, water scarcity in Russia or emissions to sea in Germany, or lacking of

knowledge, information and resources to define the desired state of the environment, for example, for

emissions to soil.

101

7.1.3. Eco-factors calculation

As it is mentioned above, eco-factors can be calculated only for the substances with both current and

critical flows defined. Figure 49 shows some included and not included substances with lacking

monitoring data, targets or both. For example, there are some statistical data for Germany regarding

the emissions to air of heavy metals, like nickel, and arsenic, however, a reduction target has not been

set yet for this type of emissions. At the other extreme, the example of the biological oxygen demand

(BOD) in surface water, which can be used for water quality assessment. BOD levels are limited by

Russian sanitary norms. However, the absence of current flow data makes it hardly possible to define

eco-factors for BOD in surface water. Endocrine disruptors are an example of substances with a lack

of both current and critical flow data. Greenhouse gases, particulate matters emissions to air, nitrogen

and phosphorus emissions to surface water are examples of substance that have both critical and

current flows that allow to calculate the eco-factors for these substances. In Figure 49 these substances

are situated in the area where current and critical flows are intercepted.

As it is described above, the current and critical flows can be measured as a concentration. It seems to

be inconvenient for eco-factor calculation, as mass flow data are preferable. The units of eco-factor

should be convenient for further application in LCIA, as it measures in EP per physical unit. For air

emissions or emissions to soil, the calculation of the mass flow from a concentration needs to use other

assumptions and numbers of physical parameters, like temperature of emission, chemical composition

and distribution, that can vary a lot depending on the source of the polluting substance and not always

publicly available. To estimate the annual mass flows for water objects, the assumption that the mass

flow is equal to a product of concentration by volume of the water, is applied in the thesis. However,

EF

can

be calculated

• GHG

• PM

• N

• P

• Endocrine disruptors (Russia, Germany)

Figure 49: Status for eco-factor calculation in few examples of substances: availability of data for current flow,

EF and critical flow calculation

Data available for current flow • Plant protection products

(Germany) • Nickel emissions to air

(Germany) • Arsenic emissions to air

(Germany) • …

Data available for critical flow

• Heavy metals emission to soil (Germany)

• Biochemical oxygen demand (Russia)

• Chemical oxygen demand (Russia)

• ....

102

such an approach is quite conservative and may be source of inaccuracy, as it does not take into

account the diluting ability of water body, natural cycle of matter and source of emission, which can

affect the actual mass of emissions truly going to the water body. Moreover, rigorous value of MACs

given by the government, without consideration of its accessibility to real conditions can result a high

weighting of the environmental issue and high eco-factor. For example, the weighting for phosphorus

emission to surface water in Russia is around 86 and it is the second highest weighting value within

the Russian eco-factor set (see Table 22).

Therefore, the lack of data availability and quality are the main obstacles for the eco-factors

calculation. The data for current flow refers to the latest available official statistical environmental

data and express the annual load of the certain emissions or resource used. The critical flows are based

on political statement or combination of political statement and assumption that allow converting the

critical flow into mass units. The data within the thesis derive from different publicly available

sources, national statistics, reports and provisional documents. The quality of such data can be

assumed as reliable and targets - objective. Nevertheless, the use of environmental data from

governments and other governmental organizations does not exclude outdated data or limitation of the

highlighted issues. The problem of lacking data is general for LCA (Reap, Roman, Duncan, & Bras,

2008). Due to the policy specificity of the Ecological Scarcity method, the problem should be solved

by the governments, for example, by improving monitoring systems or using of an adapting

management approach that allows flexibility for the revision of environmental policy goals, which are

based on limited knowledge (Reap et al., 2008).

7.2. Application

The Ecological Scarcity method can support decision making within companies and policy making.

Thus, it can be applied on different levels: for life cycle impact assessment of a product or

identification of environmental hot spots on national level and its trend. Both ways of application have

particular strengths and limitations. Both features are considered and discussed in subchapters below.

7.2.1. Product level

As is it shown in Chapter 6, the Ecological Scarcity method can be used for LCIA of products. With

the method it is possible to identify environmental hot spots and get single-score results for different

product alternatives. The results expressed in single-score, however, can be used only for internal

decision making processes, not for marketing communication purposes. The Ecological Scarcity is a

weighting method and according to ISO 14044, the results obtained through weighting cannot be used

for public assertions (ISO, 2006b).

The result obtained for products, as shown in Chapter 6, is traceable and can be reproduced with the

relevant set of eco-factors and life cycle inventory. Single-score results are convenient for

communication with non LCA experts, to compare different environmental impacts related to the

product, or to assess and compare several alternatives. However, the overall single-score does not

replace a more detailed score. The score can be aggregated for different environmental media (e.g.

emissions to air, emissions to water), group of substances (e.g., GHG, ODS) or given for each

substance separately (see Figure 50). Thus, the results do not lose the transparency, which is the

critical point for some single-score methods, if all the levels of results are provided.

103

Figure 50: Different levels of score aggregation

The Ecological Scarcity method is based on politically and legally defined environmental targets or

goals (Frischknecht & Büsser Knöpfel, 2014). That means that the availability of such goals plays an

important role for comprehensiveness of the method. In theory, with the Ecological Scarcity method it

is possible to assess a quite broad range of environmental interventions. Though, if the critical flow or

other key elements of the formula (Equation 1) are missing, the calculation of the eco-factor becomes

impossible. Thus, some important issues might be omitted through the LCIA of the product. For

example, the Russian eco-factors set does not include the land use category. That can influence the

overall result for bamboo bike frame, even if it seems that land use category can have lesser priority

for Russia than for Germany or Switzerland, due to the territory size and population density.

The comprehensiveness of the result of product assessment depends on comprehensiveness and range

of eco-factors within the set, which depends on the data availability on the country level. With a more

comprehensive set it is possible to assess a broader range of different products and relative

environmental issues for these products. The method can be recommended for LCA, if the set includes

the eco-factors that evaluate the main environmental impacts associated with the product assessed. The

assessment with the method developed for Russia and Germany in the thesis should be used as a

valuation method to estimate screening results for decision makers. The result expresses political,

rather than ecological relevance and based on overall national emission and priorities, without taking

into account, for example sector-specific, features. The results of the assessment may not be specific

enough for strategic decision-making. Nevertheless, the assessment with the method has some positive

Ove

rall

sin

gle

-sco

re r

esu

lt

Air

GHGs

CO2

CH4

SF6

ODSs

CFC-11

HCFC-123

NOx

NH3

PM10

Surface water

Heavy metalls

Hg

Pb

N

P

Sea water

TPH

N

Resources

Land use

Energy consumption

Substance

Group of substances

Environmental

media/resources

Legend:

104

effects, such as the automatically implementation of the governmental environmental priorities to the

product and the avoidance of regulatory measures connected with the failure to comply with the

regulation, like additional taxes or fines.

7.2.2. National level

The method can identify environmental hot spots not only on product, but also on national level (see

4.6. and 5.4.). Thus, these results can support decision making in policy. The result can be assessed

both on quantitative, e.g. the score for each intervention, and qualitative level, e.g. assessment of the

included and not included environmental issues. The Ecological Scarcity approach can benefit in

legislation and environmental monitoring. The authorities can review the environmental targets and

their effects on the priorities, trace the trend of each of the environmental categories with respect to its

target, identify the reasons why some of the substances are not included and take some steps to

improve the situation, for example, establish new monitoring programs or reduction targets.

The consideration of the importance of effects in the Ecological Scarcity includes not only the

environmental relevance of the considered issues, because the goals are defined by the policy they are

influenced also by technical, economic and social factors (Huppes & van Oers, 2011). Technical

factors include technology and innovation development that helps to measure and reduce the negative

environmental impacts, as well as adjust the efficient communication and information exchange for

policy makers. The economic factors include economic growth of the country, system of

environmental taxation, trade issues and others. For example, the countries members of World trade

Organization should follow some of the environmental commitment on the governmental level. Social

factors include population growth, health consciousness, living standards, society attitude, opinions

and awareness regarding some of the environmental issues and others. All abovementioned factors can

somehow affect the policy in one or another country and the value and difficulty of the Ecological

Scarcity method development for these countries.

For example, Russian environmental regulation includes a wide range of limitations at the level of

polluting substance in different environmental media, but environmental monitoring data does not

include all the limited substances. Therefore, it is not possible to estimate the current flow for these

substances. Besides, Russian environmental statistics are incomplete. For most of the environmental

issues the national environmental report gives an integrated evaluation, like the class of water body or

an index that points out the level of pollution, or compares the quality with the previous years, without

mass flow data for these years. This creates difficulties to define the annual level of emissions load.

The decision makers in policy should review the current system of monitoring and reporting and take

some legal steps for its improvement. The improved statistical data can help to estimate the reduction

target and take first steps toward the reduction of the negative impacts.

According to the principles of the Ecological Scarcity method, targets claimed by the government

should be used for eco-factor calculation. The legislative targets are supposed to have validity and be

accepted by decision makers. The level of development of the country has influence on the data

availability as well. The lack of financial and human resources causes delays in environmental

programs development or implementations. Consequentially, the environmental progress has low pace

or is not reported, and the quantitative targets are not formulated. In some other cases, the

environmental issues can become more “fashionable” while others are still scientifically unresolved

(Finkbeiner, 2009), for example, through mass media. It can affect political decisions and social

awareness. The example is the political claim to reduce the level GHG emissions in Russia that was

accepted shortly before the Olympic Games, at the end of 2013, while the formal compliance with

105

Kyoto protocol was the main argument of Russia to escape the additional obligation to reduce GHG

emissions during the Doha Climate Change Conference in November 2012 (BBC, 2012.). Thus, it

should be taken into account, while applying the Ecological Scarcity method, that the set of eco-

factors may have more political than environmental relevance (Miyazaki et al., 2004).

Figure 51 shows the range of environmental impacts included in the sets of eco-factors for different

countries for the period 1990-2014. For each country, the set is individual and includes a different

range of environmental categories and substances. The same product assessed with different sets gets

different scores because of the comprehensiveness of each set and individual national political

priorities. The result of the assessment is valid only for the country which set has been used. The direct

comparison of eco-factor values and single-score results of assessment for products between countries

is not possible (see 6.3.). With a continuous and close cooperation with the environmental authorities

the set of eco-factors could be broadened and advanced, as it was possible for Switzerland and Japan.

For these countries the updated sets of eco-factors include larger amounts of substances within the

environmental media and different environmental aspects, like noise or emissions to soil.

Figure 51: Number of eco-factors for different countries aggregated per media for the period 1990-2014 (based on Ahbe et al., 1990; Büsser et al., 2012; Frischknecht & Büsser Knöpfel, 2013; Frischknecht et al., 2009; Lindfors et al., 1995; Miyazaki et al., 2004)

j

The government alone cannot truly identify what is the ideal state of the environment. The

environmental policy is a bargain process between society, experts, politicians, administrator and

industry (Miyazaki et al., 2004). This should be taken into consideration for the deliberate

development of the Ecological Scarcity method based on the national environmental policy.

j GHGs, ODS, PMs, heavy metals, radioactive emissions, noise, waste are included as substance groups, without

division into individual substances

0

5

10

15

20

25

30

35

40

nu

mb

er

of

eco

-fac

tors

Noise

Waste

Resources

Soil

Water

Air

106

7.3. Challenges and opportunities for the comparability of results

The results of LCIA carried out with the Ecological Scarcity method have potential to not only

identify environmental hot spots of the product, but to compare environmental impacts from different

product alternatives on a uniform basis within one country. The comparability of the results can play

an essential role for the decisions between several options. The comparison can be done on several

levels, product and national. However, comparability on both levels has several peculiarities.

Comparison of the results should be carried out cautiously in order to obtain right conclusions and

effectively support decision making.

For the proper interpretation of the result on the national and product levels, in some cases, it is more

important to get the profile of the environmental score than the score itself. The eco-factors represent

the number of eco-points given per mass unit of the particulate. Eco-factor can indicate the relative

importance that the substance can get through the assessment. For example, environmental impact

from 1 kg of nitrogen emission to surface water in Germany is around three times larger than impact

from 1 kg of SO2 emission to air. Eco-factors itself is a measure of weight of environmental pressures

that converts elementary flows from inventory to environmental impacts in EP units. Thus, both eco-

factor and elementary flow affect the value of resulting environmental impacts.

7.3.1. Comparison of sets of eco-factors for different countries

Among other differences, the sets of eco-factors for Russia and Germany are different in the number

of assessed substances and environmental issues. Russian set has eco-factors for 12 substances or

substance groups within 5 environmental categories (emissions to air, to surface and sea water,

resources, waste). The German eco-factor set contain 16 substances or substance groups within 3

environmental categories (emissions to air, emissions to surface water, resources). Therefore, the

environmental issues assessed are different among the two countries. For example, the environmental

category emissions to air for Germany include a larger number of substances, than in Russia. Other

example, NOx and SO2 are not included for Russia, while emissions to sea water are included in

Russia but not in Germany.

As for the similar environmental issues, the value of single-score cannot be set off directly, because

the results are derived from the individual national legislation and current state of the environment.

Nonetheless, it may be useful to compare the share of the environmental issues within the total

national score of the countries to identify the common hot spots. The similar major hot spots could be

recognized as global environmental problems and can be the base for broader international

collaboration aimed to solve them. For example, the emissions of phosphorus into surface water are

one common environmental hot spot both for Russia and Germany. There are some joint international

programs and policies to address the eutrophication caused by nutrients pollution, including

phosphorus, for example, The Baltic Sea Project or EU’s Common Agricultural Policy (Selman &

Greenhalgh, 2009), however, the problem remains unsolved, and there is a need for the establishment

of strong, coordinated cooperation.

7.3.2. Comparison of products from different countries

There are some obstacles to compare the results obtained with different eco-factor sets. The reasons

are the different issues considered and included in the national eco-factors sets, the individual weight

of each environmental problem and the current pressure in the country. Normalization in the

Ecological Scarcity method “measures the contribution of the unit of quantity to the total current

107

pressure in a region per year” (Frischknecht & Büsser Knöpfel, 2013). Within the thesis,

normalization is defined as equal to the national current flow. The total single score result for a

product resumes the sum up of the environmental impacts from individual interventions in the

inventory. Through the multiplication with eco-factor each individual intervention is normalized with

the corresponding total country level of the emissions for the intervention.

The inventory flows for a product and the current pressure on the country level for a certain substance

are expected to be varied. The difference affects the value of the environmental impact. The larger the

normalization flow when compared with the inventory flow for the product, the smaller the

corresponding result in eco-points (see Figure 52). The relation between eco-factor and normalization

flow can be described with a power function. Aluminum and bamboo frames from the cases study

have different values of single-score results for different countries (see 6.2.). The explanation is that

normalization flows for the countries differ a lot, while the inventory is fixed.

Figure 52: Relation between value of eco-factor and normalization flow based on Russian and German data

To make the results of the assessment comparable for different countries, the environmental impact of

the product can be normalized once again to the overall national environmental score. Table 44 shows

the result of assessment for bike frames for Russia and Germany from subchapter 6.2. and result of its

normalization to the total environmental impact (see 4.6. and 5.4.) of these countries. The share of

environmental impact from production of aluminum frame with Russia as a reference scale is 800

times smaller in the national annual environmental impact than in Germany. The share of

environmental impact from the production of bamboo frame is 245 times less in Russia than in

Germany (Table 44).

Aluminum frame Bamboo frame

EP Share in total national impact, % *10

-9

EP Share in total national impact, % *10

-9

Russia (without emissions to sea water)

60 0,003 % 32 0,002 %

Germany 838 2,536 % 136 0,411 %

Table 44: Score for the production of the bike’s frames divided with the total annual national impact for Russia

and Germany

0,E+00

5,E+03

1,E+04

2,E+04

2,E+04

3,E+04

3,E+04

4,E+04

4,E+04

0,E+00 5,E+02 1,E+03 2,E+03 2,E+03 3,E+03 3,E+03 4,E+03 4,E+03

Eco

-fac

tor

Normalization flow

108

The example of the bike frames shows that the chosen reference system influences the single-score

result for the products. The comparison of the “harmfulness” of the products for different countries

cannot be done simply on the basis of the normalized results. To compare single-score results for

alternative products between the countries they can be normalized to the total national score. Such an

approach can reveal the magnitude of the score of the product measured in EP compared to overall

national score in EP.

However, the conclusions should be drawn with respect to the number of assessed and omitted

environmental issues for each product, as described in section 7.2.1. One option to adjust comparison

of products between countries, can be the use of identical reference values for normalization, for

example European or global. However, if the emissions and resource extraction are located in a

specific area, the use of global reference it is not meaningful. The choice of appropriate reference for

the normalization is important for the interpretation of the LCIA results.

7.4. Time and space effects

The Ecological Scarcity method, how it is defined in section 2.3., is temporally and geographically

specific. Thus, time and space can have relevant effects on the results of the assessment carried out

with the method. The regional sensitivity (7.4.1.) and the effects of different deadlines for target

implementation (7.4.2.) are discussed below.

7.4.1. Regional sensitivity

The eco-factors for one substance are different, depending on the reference country. Figure 53 shows

the eco-factors for GHG emissions, PM emissions to air and nitrogen emissions to surface water for

Russia, Germany, Japan and Switzerland. The differences between countries are caused by distinct

current environmental conditions and particular regulation of the environment quality and value of

normalization flows.

109

Figure 53: Eco-factors for GHG, PM10 and nitrogen emissions for different reference countries (Frischknecht &

Büsser Knöpfel, 2013; Büsser et al., 2012)

The same differences may be identified for each region within a country. The territory of the Russian

Federation is 45 times larger than territory of Japan, 47 times larger than Germany, and 409 times

larger than territory of Switzerland. It is possible that natural and environmental conditions can differ a

lot for a bigger country. Figure 54 shows that the quality of air in different Russian cities is dissimilar.

Thus, the regionalization of eco-factors for air and others emissions can make sense in big countries or

countries with very divergent environmental conditions and regulations.

Figure 54: The quality of air in cities in Russia in 2010 (http://www.ecogosdoklad.ru/grAir1_2_1.aspx )k

k The green bubble stands for low level of pollution, yellow for increased, light red for high and red for very high

0,1

1

10

100

1000

10000

100000

1000000

GHG PM10 Nitrogen to surfacewater

Eco

-fac

tor,

EP

/kg

Russia

Germany

Japan

Switzerland

Logarithmic scale

http://www.ecogosdoklad.ru/grAir1_2_1.aspx

110

Moreover, within a country there may be different ecoregions and a number of natural heritages that

are more sensitive or resistant to environmental stress, like Lake Baikal, Virgin Komi Forests, Natural

system of Wrangler Islands Reserves in Russia, and Messel Pit Fossil Site and Wadden Sea in

Germany. Average standards for environmental quality are not applicable to such objects, as they need

to be overprotected. One option to reflect that major level of protection is to set specific and stricter

targets for those areas. Therefore, any human activity in the protected areas could be assessed with a

specific regionalized set of eco-factors. One example could be the products of Baikalsk Pulp and Paper

Mills from the industrial enterprise located in the south eastern shore of Lake Baikal.

The Ecological Scarcity method embraces the possibility of regionalization (see 2.3.). However, to

calculate regionalized eco-factors, the data for current flow and critical flow should be available. That

means that the region should have developed monitoring system to obtain reliable data regarding the

current environmental state. The reduction target should also be adjusted to the region according to the

level of protection and to its capacity for real reduction. To do this, the region should identify the

relevant substances and environmental interventions and set particular actions, strategies and policy

for their reduction. Regionalization within a country can be applied to areas where environmental

quality differences are observed with respect to the country average. An effort for regionalized eco-

factors is needed and it can be considered as a further step of development for Russian and German

Ecological Scarcity method.

7.4.2. Different deadlines for the targets implementation

The reduction targets typically include a specific deadline for their implementation. The same

substances with short-term and long-term reduction targets can get different eco-factors. Long term

targets usually have a larger distance to target, thus the weighting of the substances in the eco-factor

calculation formula may get a larger value. Most of the national reduction targets, used within the

thesis, have a similar period for the implementation of the reductions, 2015-2030, and data on current

flow are taken from the latest available statistics (see Table 45).

Environmental intervention Base year Current flow Critical flow

Russia

GHGs (air) 1990 2011 2020

HCFCs (air) 1989 2011 2020

PMs (air) * 2010 *

N,P (surface water) * 2009 *

Heavy metals (surface water) * 2010 *

TPH, Phenols (sea water) * 2010 *

Waste 2007 2010 2020

Energy 2009 2010 2030

Germany

GHGs (air) 1990 2011 2020

NMVOCs (air) 2005 2010 2020

NOx (air) 2005 2010 2020

NH3 (air) 2005 2010 2020

SO2 (air) 2005 2010 2020

111

Environmental intervention Base year Current flow Critical flow

PMs (air) 2005 2010 2020

Dioxins ** 2010 1990**

Heavy metals (air) ** 2010 1995**

N,P (surface water) *** 2005 2015

PAHs (surface water) 2005 2005 2025

Land use *** 2010 2020

Energy *** 2010 2020

* Critical flow defined with a threshold that has no deadline for implementation or reference year

** Critical flow should not exceed a certain level of the emission in the past without reference to base year

*** Critical flow should be reduced to a certain level in the future without reference to base year

Table 45: Base year of the reduction, current flows and critical flows timelines for the considered substances

For both Germany and Russia, the current level of some substances is close to what was accepted as

sustainable or target level, for others is not. However, as time goes the current flow and critical flow

are changing. That change will affect the number of eco-factors, for instance, new ones can be

included in the set, derived from future available knowledge and legislation. Also the eco-factor value

can change, depending on new available targets and current level. How it is mentioned above in

7.2.2., environmental policy is affected by different factors. For example, the most discussed by mass

media environmental topics, like climate change or ozone depletion, can get more attention from the

policy makers. As a result, the targets can be more ambitious and be set for longer term of

implementation. That could be one of the reasons why some substances got higher environmental

score compared to others.

To show how the value of the eco-factor can be affected by different deadlines, short-, mid- and long-

term GHG emissions targets in Germany are identified from the literature. Short-term target is 21 %

reduction from base year 1990, according to Kyoto protocol. The time for the implementation of the

target was 2010. As the reference year for the current flow is 2011, this target is not considered in the

thesis. Instead the mid-term target of 40 % reduction from the base year 1990 by the year 2020 is used

for the critical flow definition. However, the “Sustainable Development in Germany: Indicator Report

2012” (Statistisches Bundesamt, 2012) identifies the long-term target of up to 95 % reduction by the

year 2050. The base year for the reduction remains year 1990 for the three cases. Such a big difference

can affect a lot the weighting and in turn the value of the eco-factor for GHG emissions in Germany.

Figure 55 shows the trend of GHG emissions based on statistics and three reduction targets. The graph

follows the assumption that the pace of reduction is linear, i.e. the reduction per year is regular.

According to this, it is possible to estimate the desirable critical level of GHG emissions for the year

2020 considering 95 % reduction long-term target.

112

Figure 55: Real trend of GHG emissions and its assumed paces of reduction for years 1990-2050 in Germany

The results of the eco-factor calculation for GHG emissions in Germany, considering mid-term, long-

term and long-term adjusted to 2020 targets are presented in Table 46. The result shows that without

the adjustment of the long-term target to 2020, the eco-factor for GHG emissions in Germany would

be around 108 times higher. This could lead to the overestimation of the importance of results. The

eco-factor for long-term adjusted target is still higher than the eco-factor for mid-term target, but not

as high as the one without the adjustment.

Target % of reduction from 1990

Deadline for implementation

EF with reference to 2011, EP/Mg CO2-eq

mid-term 40 2020 0,17

long-term 95 2050 24

long-term adjusted 48 2020 0,22

Table 46: Eco-factors for GHG emissions in Germany with respect to different reduction targets (based on

Statistisches Bundesamt, 2012)

In general, it is important to make sure, that the value of the eco-factor is not overestimated or

underestimated due to excessive or too short differences between reference year and the deadline for

the target achievement. If there are several alternatives, the analysis and justification of selected target

for derivation of eco-factor should be carried out. Other option is to calculate several eco-factors for

different targets, how it is done, for example, in Ecological Scarcity Japan (Büsser et al., 2012) or

Swiss version (Frischknecht & Büsser Knöpfel, 2013). However, in this case the users of the method

0

200000000

400000000

600000000

800000000

1000000000

1200000000

1400000000

1990 2000 2010 2020 2030 2040 2050

Mg

CO

2-e

q

Year

Short- term target

Mid- term target

Long- term target

Current flow

113

should be clearly guided, how and when to use one or another eco-factor for assessment. It could help

to avoid incorrect conclusions during the interpretation of results.

7.5. National environmental impacts for future scenario

The Ecological Scarcity method is based on data drawn from the past and the present. However, one

of the main functions of the method is to support decision making, which aims to affect the future. It

can thus be useful to create future scenarios to identify possible consequences of national

environmental policy decisions.

Miyazaki et al., (2004) proposed several ways to identify data for future scenarios with the Ecological

Scarcity method:

• Adjust the level of emissions to the population;

• Adjust emissions to the economic growth indicators, like GDP;

• Make assumptions derived from the political agenda on the future targets and legislation;

• Extrapolation trends based on historical patterns.

For instance, in the Swiss and Japanese versions of the Ecological Scarcity method, the data for future

scenarios have been identified through close collaboration of the method developers with

governmental bodies for setting future targets, and adjustment of the level of emissions to their

population or to European level in the case of Switzerland.

However, it seems that extrapolating emissions trends from historical patterns is more convenient and

simple way to define the scenario for Russia and Germany. The population in Germany and Russia,

according to the Word Bank data, has been decreasing through the last 20 years, though the emissions

trend for some substances has not followed the same direction. Thus, the adjustment according to the

population seems to be not reliable for these countries. Moreover, economy has a strong influence on

the emissions trend, and this is better illustrated by historical patterns. The trend figures in Chapters 4

and 5 (at the outlook sub-sections) show that significant reductions on the level of emissions have

been achieved during years of economic stagnation or crisis. Nevertheless, additional research and use

of specialized models from economics science are needed to accurately predict future economic

situation and its consequences to the level of emissions. Assumptions regarding the future policy

targets, demands close collaboration with the governmental authorities. Future environmental policy

depends, among others, on the progress made and the potential for further reduction.

In this section, possible future scenarios for Russia and Germany are defined by the extrapolation of

emissions trends. Scenario 1 is based on the assumption that current flow will change with accordance

to the average reduction or increase historical trend that is shown in chapters 4 and 5. It is based on

environmental statistics for the past years both for the substances with reduction target and with

threshold as a critical flow. Scenario 2 is based on the assumption that the substances with applicable

reduction target will be reduced up to the level of the target. For those substances with thresholds for

critical flow calculation, it is assumed that current flow changes according to the historical trend,

based on average reduction or increase of emissions. New substances that can be included in the set of

eco-factors and new targets based on available knowledge by 2020 are not considered.

Depending on the defined trend, some environmental issues can get a bigger or smaller share in the

national annual environmental impact. For example, if Russian trend for HCFCs consumption keeps

114

the same, 18 % average annual increasing (see Table 47), it will become the main environmental

problem by 2020 and will have a share of nearly 100 % in the overall national score (see Figure 56).

Hg emission has stronger trend for growth every year 118 %, the difference between critical and

current flow will not achieve such a big value. However, if the actions to achieve the target reduction

are successfully implemented in Russia (see Table 48), the share of these group of ODS substances

will be significantly reduced up to 5 % in total share (see Figure 57). For other environmental issues

that have targets the share will be 5 % as well. That will happen due to the assumption that

normalization flow is equal to current flow and current flow is equal to critical flow, if the target is

achieved. Thus, the value of environmental impact from these environmental interventions on national

level will be equal constant, c, 1012

(see Equation 1). The environmental issues related to water

pollution will get bigger share in the total result, as pollution will keep growing and the issue will

remain far, like phenols, or get further from the sustainable level, like Hg.

115

Substance Current flow (F) 2020

Critical flow (Fk)

Assumption for F calculation

EF 2020 (EP/ physical unit of reference substance)

GHG (air) 1 935 004 046 Mg 2 513 958 007 Mg -2% per year 306,1

HCFCs (air) 3738 t 19,98 t +18 % per year 9,3E+12

PM10 (air) 788 kt 2 979 kt -16 % per year 88 849 978

PM2,5 (air) 542 kt 1748 kt -16% per year 177 523 231

N (surface water) 768 t 1 908 000 t -5 % per year 211

P (surface water) 13 t 2385 t -5 % per year 2 209 912

Pb (surface water) 2,2 t 492 t -13 % per year 9 236 444

Hg (surface water) 49 t 25 t +118 % per year 80 117 007 164

THP (sea water) 152 kg 105 kg - 13 786 848 073

Phenols (sea water)

6,3 kg 2,1 kg - 1,4E+12

Waste 6 083 mln t 2 437 mln t + 5 % per year 1 024 240 662

Energy 14 458 PJ 11 566 PJ potential to save 45% of level 2009

108 067 582

Table 47: Russian set of eco-factors for scenarios 2020 based on trend of emissions and consumptions

(scenario 1)

Figure 56: Russian national environmental impact for scenario 1

100%

GHG (air)

HCFCs (air)

PM10 (air)

PM2,5 (air)

N (surface water)

P (surface water)

Pb (surface water)

Hg (surface water)

THP (see water)

Phenols (see water)

Waste

Energy

116

Substance Current flow ( F) 2020

Critical flow (Fk)

Assumption for F calculation

EF 2020 (EP/ physical unit of reference substance)

GHG (air) 2 513 958 007 Mg 2 513 958 007 Mg target level 2020 397,8

HCFCs (air) 19,98 t 19,98 t target level 2020 50 050 050 050

PM10 (air) 788 kt 2979 kt -16% per year 88 849 978

PM2,5 (air) 542 kt 1748 kt -16% per year 177 523 231

N (surface water) 768 t 1 908 000 t -5% per year 211

P (surface water) 13 t 2 385 t -5% per year 2 209 912

Pb (surface water) 2,2 t 492 t -13% per year 9 236 444

Hg (surface water) 49 t 25 t +118% per year 80 117 007 164

THP (see water) 152 kg 105 kg - 13 786 848 073

Phenols (see water)

6,3 kg 2,1 kg - 1,4E+12

Waste 2 437 mln t 2 437 mln t target level 2020 410 323 745

Energy 14 458 PJ 11 566 PJ potential to save 45% of level 2009

108 067 582

Table 48: Russian set of eco-factors for scenarios 2020 based on assumptions of the targets achievement

(scenario 2)

Figure 57: Russian national environmental impact for scenario 2

5%

5%

20%

11% 46%

5%

8%

GHG (air)

HCFCs (air)

PM10 (air)

PM2,5 (air)

N (surface water)

P (surface water)

Pb (surface water)

Hg (surface water)

THP (see water)

Phenols (see water)

Waste

Energy

117

For Germany, the trend of emissions reduction for different substances also has different rates (see

Table 49). However, all the emissions have a tendency to decrease. The energy consumption and land

use categories have relatively low pace of reduction, 0,42 % and 2 % per year respectively, compare

with some other substances. As a result, the share of the environmental impact for these two resources

will grow by 2020 (see Figure 58). If the targets are achieved (scenario 2), and current flow is equal to

critical flow (see Table 50), these environmental issues will get equal shares in the annual

environmental impacts (see Figure 59), for the same reason described above for Russia. Figure 59

shows that there are more substances than in Russia that have equal shares, and it means that there are

more substances within German eco-factor set with applicable reduction targets rather than thresholds.

Substance Current flow ( F)

Critical flow (Fk)

Assumption for F derivation

EF, EP/ physical unit of reference substance

GHG (air) 837 234 061 Mg 750 158 162 Mg -1 % per year 1 488

NMVOCs (air) 631 kt 995 kt -5 % per year 638 031 839

NOx (air) 883 kt 960 kt -4 % per year 958 005 360

NH3 (air) 499 kt 550 kt -1 % per year 1 650 310 431

SO2 (air) 138 kt 377 kt -11 % per year 974 092 806

PM10 (air) 173 kt 156 kt - 2 % per year 7 061 423 238

PM2.5 (air) 86 kt 87 kt - 3 % per year 11 521 251 019

Dioxins (air) 21 g TEQ 747 g TEQ - 11 % per year 37 820 816

Hg (air) 5,6 t 14 t - 5 % per year 27 557 020 063

Cd (air) 3,2 t 11 t -5 % per year 24 980 465 454

Pb (air) 68 t 693 t - 10 % per year 140 625 106

N (surface water) 359,3 t 235 322 t -14 % per year 6 489

P (surface water) 9,3 t 11 694 t -26 % per year 68 145


19 kt 13 kt - 1,1E+11

Land use 25 946 ha 10 950 ha -2% per year 216 393 711

Energy 13 631 PJ 11 504 PJ -0,42 % per year 102 998 627

Table 49: German set of eco-factors for scenarios 2020 based on trend of emissions and consumptions

(scenario 1)

118

Figure 58: German national environmental impact for scenario 1

8%

3%

6%

5%

1%

8%

7%

1%

1% 15%

37%

9%

GHG (air)

NMVOCs(air)

NOx(air)

NH3(air)

SO2(air)

PM10(air)

PM2.5(air)

Dioxins (air)

Hg(air)

Cd(air)

Pb(air)

N(surface water)

P(surface water)

PAHs(surface water)

Land use

Energy

119

Substance Current flow ( F) Critical flow (Fk) Assumption for F derivation

EF, EP/ physical unit of reference substance

GHG (air) 750 158 162 Mg 750 158 162 Mg target level 2020 1 333

NMVOCs (air) 995 kt 995 kt target level 2020 1 005 025 126

NOx (air) 960 kt 960 kt target level 2020 1 041 666 667

NH3 (air) 550 kt 550 kt target level 2020 1 818 181 818

SO2 (air) 377 kt 377 kt target level 2020 2 652 519 894

PM10 (air) 156 kt 156 kt target level 2020 6 393 861 893

PM2.5 (air) 87 kt 87 kt target level 2020 11 560 693 642

Dioxins (air) 21 g TEQ 747g TEQ - 11 % per year 37 820 816

Hg (air) 5,6 t 14 t - 5 % per year 27 557 020 063

Cd (air) 3,2 t 11 t - 5 % per year 24 980 465 454

Pb (air) 68 t 694 t - 10 % per year 140 625 106

N (surface water) 235 323 t 235 323 t target level 2015 4 249 482

P (surface water) 11 695 t 11 695 t target level 2015 85 508 089


13 kt 13 kt target level 2025 76 335 877 863

Land use 10 950 ha 10 950 ha target level 2020 91 324 200

Energy 11 504 PJ 11 504 PJ target level 2020 86 926 286

Table 50: German set of eco-factors for scenarios 2020 based on assumptions of the targets achievement

(scenario 2)

Figure 59: German national environmental impact for scenario 2

8%

8%

8%

8%

8%

8% 8% 1% 1%

8%

8%

8%

8%

8%

GHG (air)

NMVOCs(air)

Nox(air)

NH3(air)

SO2(air)

PM10(air)

PM2.5(air)

Dioxins (air)

Hg(air)

Cd(air)

Pb(air)

N(surface water)

P(surface water)

PAHs(surface water)

Land use

Energy

120

These future scenarios show how eco-factors value and national priorities can change over the years,

as a result of actions toward the meeting of reduction targets. Underestimation and overestimation of

the possible reduction can influence the eco-factor value of a substance and lead to misinterpretation

of the results for LCIA. Thus, the consideration of historical trend can be useful to evaluate, if the

reduction target is realistic at the present conditions. From another point of view, more ambitious

targets can have positive effect for the government, as the companies applying the method for the

assessment of their products can put more efforts for the reduction of the negative environmental

impacts that the ones defined as a priority for national environmental policy. There is a need to clarify,

if the environmental policy truly identifies the environmental priorities and what kind of the other

factors with environmental relevance that can influence policy decision making.

7.6. Parallel external development of German eco-factors

On the 4th of December 2014 a set of German eco-factors was also presented at the AutoUni, the

institution, part of Volkswagen Group that promotes knowledge exchange between the academia and

industry, based in Wolfsburg, Germany. That set of German eco-factors was a research initiative of

Volkswagen together with UBA, TU Darmstadt and SYRCON, a consulting company. The

development of the eco-factors has been mainly targeted to the assessment of the environmental

impact of Volkswagen vehicle productionl. The eco-factors are presented in Table 51, along with

critical and current flows, and cover the following environmental issues: emissions to air, emissions to

surface water, fresh water consumption, energy efficiency and waste.

Substance (units) Current flow (reference year)

Critical flow (reference year)

Eco-factor

Emissions to air

CO2 (kt/a) 916 769 (2011) 246 486 (2050) 0,015/g

NMVOC (kt/a) 1 006 (2011) 826 1,475/g

NOx (kt/a) 1 288 (2011) 652 3,03/g

SO2 (kt/a) 445 (2011) 324 4,239/g

PM2.5 (kt/a) 111 (2011) 79 17,79/g

NH3 (kt/a) 563 (2011) 426 3,102/g


N (t/a) 564 800 (2005) 515 550 2,125/g

P (t/a) 22 200 8 822 285,2/g

Ni (t/a) 476,8 225 9418/g

Zn (t/a) 2755,4 1764,5 885/g

COD (t/a) 490 800 264 666 7,01/g

Pb (t/a) 263,04 65,75 (2016) 60 846/g

Cd (t/a) 9,23 2,31 (2016) 1 729 728/g

Cu (t/a) 461,2 352,9 3 703/g

PAHs (t/a) 19,16 4,41 985 186/g

Fresh water consumption (bln m3/a) 32 (2007) 37,6 (basis 2007) 22,63/ m

3

Energy efficiency

primary energy consumption (PJ/a) 13 599 (2011) 7 140 (2050) -

Renewable (PJ/a) 1 463 (2011) 2 245 (2050) 0,349/ MJ-eq

l http://www.autouni.de/content/master/de/home/Veranstaltungen/institute/institut-fuer-produktion/veranstaltungen-produktion-archiv2014/oekofaktoren_2014-2.html

http://www.autouni.de/content/master/de/home/Veranstaltungen/institute/institut-fuer-produktion/veranstaltungen-produktion-archiv2014/oekofaktoren_2014-2.html

http://www.autouni.de/content/master/de/home/Veranstaltungen/institute/institut-fuer-produktion/veranstaltungen-produktion-archiv2014/oekofaktoren_2014-2.html

121

Nonrenewable (PJ/a) 12 136 (2011) 4 895 (2050) 0,506/ MJ-eq

Waste creation

Non-hazardous (Mt/a) 136,815 136,815 0,0073/g

Hazardous (Mt/a) 15,728 15,728 0,0636/g

Table 51: German eco-factor developed by Volkswagen research initiative (based on Schebek, 2014)

There are differences between the eco-factor set presented in the thesis and the eco-factor set

developed by Volkswagen research initiative. Some of the identified dissimilarities, according to the

information provided in the overview presented in Schebek (2014), are briefly described below. At

this point of time, further insight about the discrepancies was not possible due to the lack of publicly

available comprehensive report on the calculation and data sources for the Volkswagen set of eco-

factors.

Included issues

The eco-factor set developed in the thesis contains some environmental interventions that are not

included in the set from Volkswagen, namely, emissions of dioxins, lead, mercury and cadmium to air

and land use. In its turn, the set from the thesis does not include eco-factors for some of the emissions

to surface water, fresh water consumption and waste which are considered in the Volkswagen set.

However, they are not calculated based on real targets formulated by German environmental policy,

but on specific assumptions of the authors. For example, Volkswagen research initiative assumes in

some cases (like for non-hazardous and hazardous waste) that the current flow is identical to the

critical flow. Within the thesis this assumption was turned down due to insufficient publicly available

information that proves that German environmental policy supports such statements.

Timeline

The reference year of the current and critical flows for the eco-factors from Volkswagen research

initiative are presented in Table 51. In some cases, the reference years are different from the ones used

in the thesis. For example, the critical flows for GHG emissions and energy consumption are defined

for different deadlines for the implementation of the targets. Eco-factors for CO2 and energy from

Schebek (2014) are calculated with the target year 2050, while in the thesis the target 2020 was used

for them. The choice of a long-term target can lead to the overestimation of the eco-factor compared to

the other eco-factors in the set that have a “shorter” distance to target (see 7.4.2.). The thesis tried to

be consistent in the selection of the targets, and used similar mid-term timeframe for all the issues

included to avoid possible overestimations or underestimations.

Environmental hot spots

Using the data from Table 51, it is possible to define the German environmental hot spots according to

Schebek (2014), as it was done in section 5.4. using the set of eco-factors of the thesis. The overall

annual environmental impact of Germany based on Volkswagen set is presented in Figure 60. The

bigger shares are for PAHs (18%), lead (15%) and cadmium (15%) emitted to water and for GHG

emissions to air (13%). According to the results of the thesis, the main environmental hot spots in

Germany are land use (25%), emissions to surface water: nitrogen (17%), phosphorus (12%), and

PAHs (7%) (see 5.4.). Both research studies indicate that emissions to surface water are environmental

hot spots for Germany, but different substances are identified as the target ones, apart from PAHs. The

differences on the hot spots can be explained by the time and data discrepancies explained above. For

example, land use is not included in Volkswagen research initiative and the eco-factor for GHGs

emissions is calculated with respect to long-term target.

122

Figure 60: Overall annual environmental impact of Germany according to Volkswagen research initiative (based

on Schebek, 2014)

Both researches are based on the same Ecological Scarcity principles and use data of German

environmental statistics and policy. However, the lack of data was addressed with different

assumptions in the two initiatives. In any case, the set of eco-factors should be presented along with

the assumptions considered to obtain the harmonized set of eco-factors for Germany.

13%

1%

4%

2% 2%

2%

1%

6%

4%

2%

3%

15%

15%

2%

18%

1% 0% 6%

1% 1%

CO2 (air)

NMVOC (air)

NOx (air)

SO2 (air)

PM2.5 (air)

NH3 (air)

N (water)

P (water)

Ni (water)

Zn (water)

COD (water)

Pb (water)

Cd (water)

Cu (water)

PAHs (water)

Fresh water consumption

Renewable energy

Non renewable energy

Non hazardous waste

Hazardous waste

123

8. Conclusions and outlook

This chapter summarizes the main conclusions drawn from the results and the case study, the

identified challenges and the recommendations for further research.

8.1. Results of the thesis

The Ecological Scarcity method is a method for LCIA that takes into account national conditions and

can support policy and product decision making. This method assesses the impact caused by a

substance system with reference to the national environmental policy. In the thesis Ecological Scarcity

method was applied for Russia and Germany based on publicly available data for national current

environmental situation and priorities.

Eco-factor sets for Russia and Germany

The eco-factors in the thesis are calculated for the substances with either applicable reduction targets

or thresholds and with comprehensive environmental data characterizing the environmental status. To

do that, the documents describing the environmental national and international agenda of Russia and

Germany are identified and reviewed. As a result of the review the list of substances for which eco-

factors can be calculated is defined. There are five environmental issues (emissions to air, emissions to

surface and sea water, waste and resources) assessed for Russia and three (emissions to air, emissions

to surface water, resources) for Germany (see Table 52).

Environmental issue Substances/ substance groups, resource assessed

Russia Germany

Emissions to air GHGs, HCFCs, PMs GHGs, NMVOCs, NOx, NH3, SO2 and other acidifying substances, PMs, Dioxins, Hg, Cd, Pb


N, P, Pb, Hg N, P, PAHs

Emissions to sea water TPH, Phenols -

Waste Waste to landfills -

Resources Primary energy consumption Land use for settlement and transport, primary energy consumption

Table 52: Environmental issues assessed for Russia and Germany

The thesis contains a detailed description for the environmental issues included for Russia and

Germany, namely, it describes the political targets concerning emissions or resources within the

national eco-factor set, gives information regarding the source of data and applied assumptions for

eco-factor calculation. Such structure makes the obtained results transparent and traceable. The thesis

provides an overview of the historical trend and, in some cases, forecasts based on the given

information for each of the assessed substance, substance group or resource. The outlook discusses

actions that could improve the environmental situation with respect to considered goals of

environmental policy and close gaps in data availability for Russia and Germany.

National hot spots

The national overviews gather together the assessed environmental interventions, based on the

publicly available national and international reports, regulations and statistics in Russia and Germany.

Thus, national overviews represent assessment of the national situation through the set of eco-factors

124

and the current flows. Such an overview is useful for hot spots identification on national level. Thus,

the main hot spots in Russia are ODS emissions to air and phosphorus emissions to surface water. For

Germany the largest share in the total national environmental impact are land use category and

nitrogen and phosphorus emissions to surface water. The information may be useful for the

establishment of further action in the field of the environmental policy making, for example, review

current environmental legislation and establishment of new monitoring programme with respect to the

environmental hot spots and gaps identified with the Ecological Scarcity method.

Case study

The national eco-factor sets are intended for the LCA of products that have a clear national reference

for their production, i.e. it assesses the product and its environmental performance for the specific

country with reference to its conditions and priorities. The case study in the thesis is aimed to test the

obtained national sets of eco-factors and show that it is suitable for the LCIA of a product. The single-

score result can be disaggregated to different issues, like environmental media, substance group or

individual substance, if needed. So well, the two sets of eco-factors based on Ecological Scarcity

principle specific for Russia and Germany are used for the assessment of bicycle frames made of two

different materials, aluminum and bamboo. The case study results show that the Ecological Scarcity

method used during the LCIA can reveal environmental hot spots with connection to national

environmental policy and provide single-score result that can be practical and supporting for decision

making. The case study shows that bamboo frame has less environmental impact than the frame made

of aluminum for most of the substances. Similar results were obtained by Chang et al. (2012).

However, the method should be used with caution, for different reasons, for instance, the results of the

assessment are not appropriate for comparative studies disclosed to the public, due to the weighting

that is used for giving a value to each environmental intervention.

Identification of challenges

Apart of the calculation of eco-factors for Russia and Germany the thesis raises the main challenges

for method development and application identified for the two countries, like current data and policy

gaps, comparability of results, influence of normalization on the value of the single-score results,

regional sensitivity, different time frame and deadlines. Some of the identified problems can be solved

by using additional assumptions described in the thesis, for instance, different deadlines for

environmental target. Nevertheless, some of the remaining challenges should be addressed by future

research described in 8.3.

8.2. Further contribution

The aim of the thesis is not only to develop the Ecological Scarcity method for Russia and Germany,

but also contribute to the further development of the methodology and method’s application to other

countries. Thus, the contribution of the thesis is presented attending to two different dimensions: the

so called direct and indirect contribution (see Figure 61). The direct contribution is the use of the

method and its findings on national level in Russia and Germany for environmental policy making and

LCA purposes. Indirect contribution is understood here as the contribution to the already developed

national Ecological Scarcity methods, e.g. Swiss method, and recommendation for application in other

countries.

125

Figure 61: Possible contribution of the Ecological Scarcity method for Russia and Germany

The main aim of the method in policy making context is to deliver easy to understand LCA results to

compare different options, which can support decision making process, e.g. for a company.

Additionally the method gives information regarding the effectiveness of environmental policies

against the targets, which can be addressed in policy decision making in Russia and Germany. The

Ecological Scarcity method can serve as a link between environmental policy and LCA. The method

can be a starting point to promote further LCA activities in Russia. The relatively easy to understand

single-score results of assessment can help to involve more stakeholders in both countries in

identifying environmental burdens and evaluate the environmental consequences of a product. For

Germany, as a country with wide application of LCA studies, the method can help to avoid possible

discrepancies between the results of LCA and environmental policy and be a tool to respond to the

pressure by the environmental regulation, through the direct implementation of the environmental

policy goals within the method.

The results of the thesis may also have an application beyond Russia and Germany. For example,

previous case studies showed that it can be sensible to use eco-factors that consider the regional

situation (Frischknecht, Steiner, Braunschweig, Egli, & Hildesheimer, 2006), as long as there are more

than one country involved in the life cycle of the product. So far, that was mainly referring to water

scarcity. However, other environmental interventions, apart from using water resources, can have

importance for the products as well. Thus, the data obtained in the thesis for Russia and Germany can

be used for the assessment, for example, with Swiss Ecological Scarcity method, if there is a need to

consider the national scarcity level in these countries for the assessment of a product.

According to Jungbluth et al. (2012) the Swiss Ecological Scarcity method can be used for countries

with similar environmental policy. However, the result of the case study showed that normalization

has a great influence on the values of the eco-factors for different countries. Thus, to use national

Ecological Scarcity method for countries with similar environmental policy (i.e. similar weighting for

the environmental issues) the eco-factors should be recalculated with respect to the difference in

Ecological Scarcity method (Russia /

Germany)

Environmental policy making

(Russia/ Germany)

LCA (Russia/ Germany)

Countries with developed

national Ecological

Scarcity method

Other countries

Direct contribution

Indirect contribution

126

normalization flows. Germany and Switzerland may be claimed to have similar environmental

policies, however, the thesis shows that they have quite different sets of eco-factors. The difference

refers not only to the value of the eco-factors due to different normalization flows, but mostly to the

difference in data availability for assessed issues and its importance for environmental policy in these

countries, for example, limited number of eco-factors for surface water emissions for Germany

compared to Switzerland. Thus, it is possible to apply developed eco-factors for other countries, if the

weighting for the environmental issues is assumed to be equal. However, to identify the truly results, it

is better to rely on own country-specific environmental situation and priorities.

The assumptions and pathways of data collection and calculation described in the thesis may be

helpful for other countries to ease the application of the Ecological Scarcity method, considering

possible short comes, and development of country specific eco-factors.

8.3. Remaining challenges and recommendations for further research

The thesis provides discussion to point out some of the shortcomings of the Ecological Scarcity

method and challenges occurred during its application to Russia and Germany. The identified issues

demand the joint efforts from the government, scientists, LCA practitioners and industry to be solved

in the future.

8.3.1. Review and enhancement of data for eco-factors calculation

The included environmental issues for Russia and Germany are currently limited, due to the restricted

availability or comprehensiveness of data. Data used are derived from publicly available sources and

the environmental policy agenda of Russia and Germany. Thus, statistics gaps or/and shortcomings

within environmental policy directly affect the comprehensiveness of the method and amount of eco-

factors, i.e. the country with “incomplete” environmental policy has a risk to get the “incomplete”

method for LCA. To enhance the comprehensiveness of the method efforts should be made towards:

• Improvement of the data quality and availability, by:

• increasing the monitoring net;

• standardize monitoring data collection and processing;

• working out comprehensive scientific models to define annual mass flows for

relevant emissions to media, like soil, ground water and etc.;

• adjust the reporting and its format.

• Clear definition of environmental policy agenda and influenced factors, by:

• identification the most relevant environmental issues;

• identification factors influencing environmental policy;

• further estimation and review of applicable national reduction targets.

8.3.2. Consideration of different regions within the country

The thesis provides the calculation of eco-factors on the country level. However, in big countries, like

Russia, high variety of environmental conditions occurs. National standards often consider average

quality that is not always applicable for some regions or ecosystems. Regionalization of eco-factors

can address the diversity of environmental conditions and identify where within a country the same

127

process or product has the least environmental impact. However, the regionalization demands clear

additional data regarding environmental situation and regulation at the regional level.

8.3.3. Implementation in real case studies

Within the thesis Russian and German eco-factor sets are tested only for one case study. To further

evaluate usefulness and plausibility of the method it should be applied for the assessment of different

products and sectors. The feedback from decision makers in industry and LCA practitioners can

enhance the method and set effective collaboration between industry and policy makers. For instance,

policy makers may consider environmental issues that would be identified as important for national

industry and put more effort for the gathering of data for that issue on governmental level. Moreover,

the real case study can define if eco-factors calculated with assumptions give plausible result within

the assessment.

8.3.4. Comparability of results

The general ecological scarcity methodology is defined to work out country or regional specific

method for LCIA. The single-score result reflects the priority of national environmental policy and

situation. However, there is still need to define a framework how the results of the assessment made

with different national sets of eco-factors can be compared between themselves. To do this not only

the environmental priorities and situation of the countries should be considered, but also the

geographical and temporal scales should be harmonized. For example, comparison of different

national results for the same production process can define the optimal production chain in

international or global scale.

8.3.5. Development on company level

The Ecological Scarcity method can be used on the company level as well. Up to now, some

companies have already assessed their products with the Swiss Ecological Scarcity method and

concluded that the assessment with the method is able to identify the environmental spots and helps to

identify the measures to improve the performance of their products (Frischknecht & Büsser Knöpfel,

2014). To do this, companies mostly used the national Swiss set of eco-factors. However, the distance

to target approach can be applied on company level as well. Thus, instead of the targets set by the

government, the company can identify relevant environmental issues and set internal targets for the

selected issues. Selected issues can be identified with respect to the specific products and its potential

threat for the environment through the life cycle.

The environmental targets set by the company should be specific for the environmental interventions

that should be included, relevant for the products of the company, measurable, plausible, have the

deadline for implementation. The approach can be especially useful for companies with high

environmental standards and awareness that go beyond the formal compliance with the state

environmental regulation. Some international companies that operate in different countries often have

internal standards that are equal or stricter than regulation of the country where it is operating. Such

companies can define their own reduction targets for the collected environmental interventions and

calculate their own set of eco-factors. Therefore, they can implement the harmonized internal

approach to assess the environmental performance of their products on every production site. The

targets defined within the company can be independent from governmental ones that can be affected

apart of environmental relevance by different factors or missing. The normalization reference should

be also defined by the company itself. The reference system can include direct and indirect emissions

128

of the company or local, regional, country level where the product is produced depending on the

capability for reduction.

The result of the assessment of products performance with internal set of eco-factors should not be

misused for marketing purposes, but to support internal decision making. The set should be also

updated to have relevance and to track the environmental performance of the product through the time,

for example improvements or newly assessed environmental issues.

8.3.6. Update of eco-factor sets

Eco-factors for Russia and Germany, as well as for other countries, should be regularly updated in the

future to reflect up-to-date environmental situation and include new political requirements and

scientific findings. All the above mentioned factors can influence the value and the number of eco-

factors. Thus, to obtain the appropriate result the method should be updated. A recommended time for

updating would be 5 years. This period would cover some statistic data delays and would be optimal

for governments to revise new political targets. Moreover, the experience of Switzerland, that updates

eco-factors every 5 years, shows that some of the existing data gaps can be closed over this time

(Frischknecht & Büsser Knöpfel, 2013).

129

References

ABB. (2011). Russia Energy efficiency report (pp. 1–6).

AGEB. (2013). Evaluation Tables on the Energy Balance for the Federal Republic of Germany 1990

to 2012. Last updated : July 2013.

Ahbe, S., Braunschweig, A., & Müller-Wenk, R. (1990). Methodik für Ökobilanzen auf der Basis

ökologischer Optimierung. Bern.

Amundsen, P. A., Staldvik, F. J., Lukin, A. A., Kashulin, N. A., Popova, O. A., & Reshetnikov, Y. S.

(1997). Heavy metal contamination in freshwater fish from the border region between Norway

and Russia. The Science of the Total Environment, 201(3), 211–24. Retrieved from

http://www.ncbi.nlm.nih.gov/pubmed/9241871

Bare, J. C., Hofstetter, P., Pennington, D. W., & Udo de Haes, H. A. (2000). Midpoints versus

Endpoints : The Sacrifices and Benefits. The International Journal of Life Cycle Assessment,

5(6), 319–326.

Baumann, H., & Tillman, A.-M. (2004). The Hitch Hiker’s Guide to LCA. Lund, Sweden:

Studentlitteratur AB.

BBC. (2012). The Kyoto Protocol is extended despite the efforts of Russia. Retrieved from

http://www.bbc.co.uk/russian/international/2012/12/121208_kyoto_protocol_extension.shtml

BMU. (2009). Act on the Prevention of Harmful Effects on the Environment Caused by Air Pollution ,

Noise , Vibration and Similar Phenomena ( Federal Immission Control Act - BImSchG ).

BMU. (2010). New EU Directive on Ambient Air Quality transposed into German law. Retrieved from

www.bmub.bund.de/N46311-1

BMU. (2012). German Resource Efficiency Programme ( ProgRess ).

BMU. (2013a). Emissionen ausgewählter Luftschadstoffe nach Quellkategorien Stickstoffoxide, (2).

BMU. (2013b). Press Release No. 013/13: Greenhouse gas emissions up by 1,6 percent in year 2012.

Retrieved from www.bmub.bund.de/N49862

BMU. (2013c). Water Framework Directive. Implementation of WFD programmes of measures –

interim results 2012.

BMU. (2014). Government billions for environmental protection. Retrieved from

www.bmub.bund.de/P163-1/

BMUB. (2005). Federal Agency for Nature Conservation. Retrieved from www.bmub.bund.de/P190-

1/

BMUB. (2014a). Federal Authorities. Retrieved from www.bmub.bund.de/P188-1/

BMUB. (2014b). Federal Institute for Research on Building, Urban Affairs and Spatial Planning

(BBSR). Retrieved from www.bmub.bund.de/P3149-1/

130

BMUB. (2014c). Federal Office for Radiation Protection (BfS). Retrieved from

www.bmub.bund.de/P191-1/

BMUB. (2014d). Tasks and structure. Retrieved from www.bmub.bund.de/P84-1/

BMWi. (2012). Germany ’s new energy policy.

BMWi; BMU. (2011). Energy Concept (Vol. 2010).

Bogolubov, S., Kichigin, N., & Sivakov, D. (2008). Ecological law. Moscow: Prospekt.

Braunschweig, A. (1982). Ökologische Buchhaltung für eine Stadt. Chur: Rüegger Verlag.

Braunschweig, A. (2013). Using Ecological Scarcity in Companies based on the experience of

McDonald ’ s ( CH ) and other companies. In 54th Swiss LCA Discussion Forum “Ecological

Scarcity 2013.” Bern.

Braunschweig, A., & Müller-Wenk, R. (1993). Ökobilanzen für Unternehmungen – eine Wegleitung

für die Praxis. Bern: Verlag Paul Haupt.

BusinesStat. (2014). Analysis of the market for bicycles in Russia in the years 2009-2013, 2014-2018

forecast period (in Russian).

Büsser, S., Frischknecht, R., & Kono, J. (2012). Ecological Scarcity Japan. Report, Uster.

Chang, Y.-J., Neugebauer, S., & Finkbeiner, M. (2013). Life Cycle Sustainability Assessment (LCSA)

comparison of modern bikes. In The 6th International Conference on Life Cycle Management,

August 25-28, Gothenburg, Sweden.

Chang, Y.-J., Schau, E. M., & Finkbeiner, M. (2012). Application of Life Cycle Sustainability

Assessment to the bamboo and aluminum bicycles in surveying social risks of developing

countries. 2nd World Sustainability Forum.

CIA. (2014). The World Factbook. Retrieved from https://www.cia.gov/library/publications/the-

world-factbook/index.html

Colibi & Coliped. (2013). European Bicycle Market. Industry & Market Profile (2012 statistics).

Committee On The Environment And Natural Resources. (2000). Atmospheric Ammonia: Sources and

Fate A Review of Ongoing Federal Research and Future Needs.

Dahlbo, H., Koskela, S., Pihkola, H., Nors, M., Federley, M., & Seppälä, J. (2012). Comparison of

different normalised LCIA results and their feasibility in communication. The International

Journal of Life Cycle Assessment, 18(4), 850–860. doi:10.1007/s11367-012-0498-4

Direction № 447-r ( 27th March 2013) - On introducing a bill aimed at ensuring the protection of the

ozone layer of the atmosphere from environmentally harmful changes (in Russian). (2013).

Retrieved from http://government.ru/docs/1040

Direction of the President of the Russian Federation on 17th December 2009 N 861-rp. Climate

Doctrine of the Russian Federation (in Russian) (2009). Retrieved from

http://news.kremlin.ru/acts/6365

131

Dobrovolskii, A. D., & Zalogin, B. S. (1982). The Seas of the USSR (in Russian) (p. 192). Moscow:

Moscow State University.

Döhler, H., Eurich-Menden, B., Rößler, R., Vandre, R., & Wulf, S. (2011). UN ECE-Convention on

long-range transboundary air pollution -Task Force on Reactive Nitrogen: Systematic cost-

benefit analysis of reduction measures for ammonia emissions in agriculture for national cost

estimates. Dessau-Roßlau.

Doka, G. (2002). Synopsis of variations of the BUWAL Ecopoints LCIA method, (December 2002),

3–6. Retrieved from http://www.doka.ch/ECOSCARCITYsurveyDOKA.pdf

EC. (1999). COUNCIL DIRECTIVE 1999/13/EC. Official Journal of the European Communities, (6).

EEA. (2001). Indicator Fact Sheet Signals 2001– Chapter Air Pollution (pp. 1–7).

EEA. (2005). EEA-32 non-methane volatile organic compounds NMVOC emissions, 1–25.

EEA. (2007). EN06 Energy-related emissions of acidifying substances (pp. 1–8). Retrieved from

http://www.eea.europa.eu/data-and-maps/indicators/en06-energy-related-emissions-of-1/en06

EEA. (2012). Air quality in Europe — 2012 report.

EEA. (2013). Air quality in Europe — 2013 report.

Environmental Agency. Technical Guidance Note (Monitoring) M15. Monitoring PM10 and PM2.5

(2012). England.

EPA. (2006). LIFE CYCLE ASSESSMENT: PRINCIPLES AND PRACTICE.

European Comission. Directive 2000/60/EC of the European Parliament and of the Council of 23

October 2000 establishing a framework for Community action in the field of water policy (Water

Framework Directive) (2000).

European Commission. (2012a). Organisation Environmental Footprint ( OEF ) Guide.

European Commission. (2012b). Product Environmental Footprint ( PEF ) Guide.

European Commission. (2014). European Platform on Life Cycle Assessment (LCA). Retrieved

September 16, 2014, from http://ec.europa.eu/environment/ipp/lca.htm

Federal Law № 261-FZ “On energy saving and energy efficiency improvements and on Amendments

to Certain Legislative Acts of the Russian Federation” (2009).

Federal Russian statistic service. (2013). Retrieved from

http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/environment/

Federal State Statistic Service. (2012). Russia and countries of the world.

Federal State Statistic Service. (2013). Retrieved July 14, 2014, from http://www.gks.ru/

Finkbeiner, M. (2009). Carbon footprinting—opportunities and threats. The International Journal of

Life Cycle Assessment, 14(2), 91–94. doi:10.1007/s11367-009-0064-x

132

Finkbeiner, M. (2013). Product environmental footprint—breakthrough or breakdown for policy

implementation of life cycle assessment? The International Journal of Life Cycle Assessment,

19(2), 266–271. doi:10.1007/s11367-013-0678-x

Finkbeiner, M., Ackermann, R., Bach, V., Berger, M., Brankatschk, G., Chang, Y.-J., … Wolf, K.

(2014). Challenges in Life Cycle Assessment: An Overview of Current Gaps and Research

Needs. In W. Klöpffer (Ed.), Background and Future Prospects in Life Cycle Assessment SE - 7

(pp. 207–258). Springer Netherlands. doi:10.1007/978-94-017-8697-3_7

Finkbeiner, M., Inaba, A., Tan, R. B. H., Christiansen, K., & Klüppel, H. (2006). Commentaries The

New International Standards for Life Cycle Assessment : ISO 14040 and ISO 14044, 11(2), 80–

85.

Francioni, F., & Bakker, C. (2013). The Evolution of the Global Environmental System: Trends and

Prospects The Evolution of the Global Environmental System: Trends and Prospects.

Frankl, P., & Rubik, F. (1998). Application Patterns of Life Cycle Assessment in German, Italian,

Swedish and Swiss Companies.Comparative Results and Conclusions.

Frischknecht, R., & Büsser Knöpfel, S. (2013). Swiss Eco-Factors 2013 according to the Ecological

Scarcity Method. Methodological fundamentals and their application in Switzerland. Bern.

Frischknecht, R., & Büsser Knöpfel, S. (2014). Ecological scarcity 2013—new features and its

application in industry and administration—54th LCA forum, Ittigen/Berne, Switzerland,

December 5, 2013. The International Journal of Life Cycle Assessment, 19(6), 1361–1366.

doi:10.1007/s11367-014-0744-z

Frischknecht, R., Büsser, S., Hayashi, K., Kono, J., Makino, N., Shobatake, K., & Hokazono, S.

(2012). Assessment of Rice Cultivation with Ecological Scarcity Japan. In EcoBalance (pp. 4–7).

Frischknecht, R., Steiner, R., Braunschweig, A., Egli, N., & Hildesheimer, G. (2006). Swiss

Ecological Scarcity Method : The New Version 2006.

Frischknecht, R., Steiner, R., & Jungbluth, N. (2009). The Ecological Scarcity Method – Eco-Factors

2006. A method for impact assessment in LCA. Environmental. Federal Office for the

Environment, Bern, (Environmental studies no. 0906.), 188 pp.

Galatola, M., & Pant, R. (2014). Reply to the editorial “Product environmental footprint—

breakthrough or breakdown for policy implementation of life cycle assessment?” written by Prof.

Finkbeiner (Int J Life Cycle Assess 19(2):266–271). The International Journal of Life Cycle

Assessment, 19(6), 1356–1360. doi:10.1007/s11367-014-0740-3

Gardner, G. (2008). Bicycle Production Up Slightly. Worldwatch Institute. Retrieved from

http://www.worldwatch.org/node/5462

Goedkoop, M., Schryver, A. De, Oele, M., Durksz, S., & de Roest, D. (2010). Introduction to LCA

with SimaPro 7.

Government of the Russian Federation. Decree from May 29, 2008 N 404: The Statute on the Ministry

of Natural Resources and Environment of the Russian Federation, Pub. L. No. N 404 (2008).

Guinée, J. ., Gorrée, M., Heijungs, R., Huppes, G., Kleijn, R., de Koning, A., … Weidema, B. (2002).

Handbook on Life Cycle Assessment. Operational Guide to the ISO Standards. Kluwer

Academic Publishers.

133

Hauschild, M., & Potting, J. (2005). Spatial differentiation in Life Cycle impact assessment - The

EDIP2003 methodology. Environmental News, 80.

Henry, L. a., & Douhovnikoff, V. (2008). Environmental Issues in Russia. Annual Review of

Environment and Resources, 33(1), 437–460. doi:10.1146/annurev.environ.33.051007.082437

Huppes, G., & Oers, L. Van. (2011). Evaluation of Weighting Methods for Measuring the EU-27

Overall Environmental Impact. doi:10.2788/88465

Huppes, G., & van Oers, L. (2011). Background Review of Existing Weighting Approaches in Life

Cycle Impact Assessment ( LCIA ) (pp. 60–63). Ispra. doi:10.2788/88828

IEA. (2012). IEA - International Energy Agency, CO2 Emissions From Fuel Combustion, Highlights.

Retrieved from http://www.iea.org/co2highlights/co2highlights.pdf

IFC. (2012). Municipal Solid Waste Management : Opportunities for Russia.

IIASA. (2011). The GAINS model (pp. 1–10).

IIP. (2013). Germany ’ s GHG emissions reductions policies. Retrieved from

http://www.iipnetwork.org/IIPFactSheet_Germany.pdf

IPCC. (1996). The Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC

Guidelines).

IPCC. (2007). Climate Change 2007 - The Physical Science Basis The. Cambridge University Press.

ISO. (2006a). ISO 14040:2006 Environmental Management – Life Cycle Assessment – Principles and

Framework. Geneva, Switzerland.

ISO. (2006b). ISO 14044:2006 Environmental management – Life cycle assessment – Requirements

and guidelines. Geneva, Switzerland.

Itsubo, N. (2000). Screening life cycle impact assessment with weighting methodology based on

simplified damage functions. The International Journal of Life Cycle Assessment, 5(5), 273–280.

doi:10.1007/BF02977579

Ivanova, M. (2005). Can the Anchor Hold ? Rethinking the United Nations Environment Programme

for the 21st Century.

Jolliet, O., Miiller-Wenk, R., Bare, J., Brent, A., Goedkoop, M., Heijungs, R., … Weidema, B. (2004).

The LCIA Midpoint-damage Framework of the UNEP/SETAC Life Cycle Initiative. The

International Journal of Life Cycle Assessment, 9(6), 394–404.

JRC - EC. (2010a). ILCD Handbook . General guide for Life Cycle Assessment - Detailed guidance.

doi:10.2788/38479

JRC - EC. (2010b). ILCD handbook: Analysis of existing Environmental Impact Assessment

methodologies for use in Life Cycle assessment.

JRC - EC. (2010c). ILCD Handbook: Framework and requirements for LCIA models and indicators

First edition. doi:10.2788/38719

134

JRC - EC. (2012). The International Reference Life Cycle Data System (ILCD) Handbook (online

version). doi:10.2788/85727

Jungbluth, N., Büsser, S., Frischknecht, R., Flury, K., & Stucki, M. (2012). Feasibility of

environmental product information based on life cycle thinking and recommendations for

Switzerland. Journal of Cleaner Production, 28, 187–197. doi:10.1016/j.jclepro.2011.07.016

Khublaryan, M. G. (2000). Water Resources for Sustainable Development, with Particular Reference

to Russia. In Encyclopedia of Life Support Systems (EOLSS).

Kings & Spalding. (2012). Overview Russian Environmental Regulation. Retrieved from

http://www.kslaw.com/imageserver/KSPublic/library/publication/RussianEnvironmental.pdf

Kovalenko, L. ., Makarov, A. ., Medvedev, V. ., & Skibenko, V. . (2010). Environmental monitoring

and protection from man-made pollution (2nd ed.). Moscow: MPEI.

Lindfors, L.-G., Christiansen, K., Hoffman, L., Virtanen, Y., Juntilla, V., Hanssen, O.-J., …

Finnveden, G. (1995). Nordic Guildlines on Life-Cycle Assessment.

Mamin, R. ., & Bayaraa, U. (2009). Natural resources, national parks and international

environmental problems (in Russian). Moscow: ACB.

McCormick, J. (2001). Environmental Policy in the European Union. (N. Nugent, W. E. Paterson, &

V. Wright, Eds.). Palgrave Macmillan.

Menoufi, K. A. I. (2011). An overview on Life Cycle Impact Assessment ( LCIA ) methodologies : State

of the art. Universitat de Lleida.

Ministry of Natural Resources and Environment of the Russian Federation. (2012). State report

“About state and protection of the environment in Russian Federation in 2012.”

Minprirody. (2012). State Program of the Russian Federation “Environmental Protection” for 2012-

2020.

Miyazaki, N. (1998). Applying EcoBalance to Management Control:Combining Economic and

Ecological Accounting. In Second Asian-Pacific Interdisciplinary Research in Accounting

Conference (pp. 1–10).

Miyazaki, N., Siegenthaler, C., Schoenbaum, T., & Azuma, K. (2004). Japan Environmental Policy

Priorities Index (JEPIX) – Calculation of Ecofactors for Japan: Method for Environmental

Accounting based on the EcoScarcity Principle. Tokyo.

Montero, J. I., Antón, A., Torrellas, M., Ruijs, M., & Vermeulen, P. (2011). Environmental and

economic profile of present greenhouse production systems in Europe, (September), 1–101.

Müller-Wenk, R. (1978). Die ökologische Buchhaltung: Ein Informations- und Steuerungsinstrument

für umweltkonforme Unternehmenspolitik. Frankfurt: Campus Verlag.

OECD. (2006). Environmental Policy and Regulation in RUSSIA: The Implementation Challenge.

Paris, France.

OECD. (2008). Surface Water Quality Regulation in EECCA Countries: Directions for Reform (pp. 1–

13). Retrieved from http://www.oecd.org/env/outreach/41832129.pdf

135

OECD. (2012). OECD Environmental Performance Reviews: Germany 2012.

doi:10.1787/9789264169302-en

Olivier, J. G. J., Janssens-Maenhout, G., Muntean, M., & Peters, J. A. H. W. (2013). Trends in global

CO2 emissions 2013 report. Hague.

Payet, J. (2008). Similarities and differences between EcoRA and LCA (pp. 1–21).

Pennington, D. W., Potting, J., Finnveden, G., Lindeijer, E., Jolliet, O., Rydberg, T., & Rebitzer, G.

(2004). Life cycle assessment Part 2: Current impact assessment practice. Environment

International, 30(5), 721–39. doi:10.1016/j.envint.2003.12.009

Prityjalova, O. (2007). Evaluation of environmental impact with life cycle assessment (in Russian).

Tyumen State University Herald, 3(Geography), 152–158.

Rack, M., Valdivia, S., & Sonnemann, G. (2013). Life Cycle Impact Assessment—where we are,

trends, and next steps: a late report from a UNEP/SETAC Life Cycle Initiative workshop and a

few updates from recent developments. The International Journal of Life Cycle Assessment,

18(7), 1413–1420. doi:10.1007/s11367-013-0569-1

Reap, J., Roman, F., Duncan, S., & Bras, B. (2008). A survey of unresolved problems in life cycle

assessment. The International Journal of Life Cycle Assessment, 13(5), 374–388.

doi:10.1007/s11367-008-0009-9

Rebitzer, G., Ekvall, T., Frischknecht, R., Hunkeler, D., Norris, G., Rydberg, T., … Pennington, D. W.

(2004). Life cycle assessment part 1: framework, goal and scope definition, inventory analysis,

and applications. Environment International, 30(5), 701–20. doi:10.1016/j.envint.2003.11.005

Rosgidromet. (2011). Yearbook of State Air Pollution in Cities in Russia for 2010.

Rosminzdrav. GN 2.1.6.1338-03 Maximum allowable concentration (MAC) of pollutants in the air of

residential areas (2003).

Russian State Committee on Environmental Protection. (2011). State report about environmental

situation in Russian Federation in 2010. Moscow.

Schebek, L. (2012). Material Flow Analysis and Life Cycle Assessment (pp. 1–35).

Schebek, L. (2014). Methode der Ökologischen Knappheit: Bewertung von Umwelaspekten.

Schuller, O., Hassel, F., Kokborg, M., Thylmann, D., Stoffregen, A., Schöll, S., & Rudolf, M. (2013).

GaBi Database & Modelling Principles 2013.

Selman, M., & Greenhalgh, S. (2009). Eutrophication: Policies, Actions, and strategies to Address

Nutrient Pollution. WRI Policy Note, (3).

Semenovich, I. (2002). Water pollution and its impact on fish and aquatic invertebrates. In Water

Interactions with Energy, Environment, Food, and Agriculture - Volume 1 (Vol. I).

Seppälä, J., & Hämäläinen, R. P. (2001). On the meaning of the distance-to-target weighting method

and normalisation in Life Cycle Impact assessment. The International Journal of Life Cycle

Assessment, 6(4), 211–218. doi:10.1007/BF02979376

136

Soares, S. R., Toffoletto, L., & Deschênes, L. (2006). Development of weighting factors in the context

of LCIA. Journal of Cleaner Production, 14(6-7), 649–660. doi:10.1016/j.jclepro.2005.07.018

Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., … Miller, H. . (2007). IPCC

2007 - Contribution of Working Group I to the Fourth Assessment Report of the

Intergovernmental Panel on Climate Change.

Stakeholder Forum. (2004). International Environmental Governance. A Briefing Paper (pp. 1–10).

Statistisches Bundesamt. (2012). Sustainable Development in Germany: Indicator Report 2012.

Wiesbaden.

Statistisches Bundesamt. (2013). Statistical yearbook Germany. Wiesbaden.

Strukova, E., Balbus, J., & Golub, A. (2007). Saving lives, saving money : regulating particulate

matter air pollution in Russia. Environmental Defense.

The presidential decree of the Russian Federation No. 752 (2013).

Theloke, J., & Friedrich, R. (2003). Development of an improved product based approach for the

calculation of NMVOC emissions from solvent use in Germany and uncertainty analysis. In

Paper presented at the 12th International Emission Inventory Conference “Emission Inventories

- Applying New Technologies,” San Diego, April 29 - May 1, 2003 (pp. 1–14).

Tselikov, V. N. (2009). Estimate of hydrochlorofluorocarbon consumption level in Russia until 2020

and the prospects of hydrofluorocarbons use until 2033 (in Russian). Kholodilnaya Tekhnika,

(11).

Tselikov, V. N. (2012). Ozone-Depleting Substances In Russia: Current Situation And Forecast.

Retrieved from http://apic.ru/en/index.php?doc=106

UBA. (2002). International Pilot Study for the determination of Riverine Inputs of Polycyclic

Aromatic Hydrocarbons (PAHs) to the Maritime Area on the basis of a harmonised

methodology.

UBA. (2007). Environmental Data for Germany. Practicing Sustainability – Protecting Natural.

UBA. (2009a). Data on the Environment.

UBA. (2009b). Integrated Strategy for the Reduction of Nitrogen Emission.

UBA. (2009c). Trends in Air Quality in Germany.

UBA. (2010a). 46/2010 Calculation of Emissions into Rivers in Germany using the MONERIS Model.

UBA. (2010b). Air Quality Control 2010: National Programme of the Federal Republic of Germany

pursuant to Article 6 of Directive 2001/81/EC of 23 October 2001 on national emission ceilings

for certain atmospheric pollutants (NEC Directive).

UBA. (2010c). Background: Dioxins, 1–13.

UBA. (2010d). Wasserwirtschaft in Deutschland. Teil 2 - Gewässergüte.

137

UBA. (2010e). Water Protection in Cooperation with Agriculture.

UBA. (2012a). How good is air quality in Germany? Retrieved from

http://www.umweltbundesamt.de/en/press/pressinformation/how-good-is-air-quality-in-germany

UBA. (2012b). Polycyclic Aromatic Hydrocarbons: Harmful to the Environment! Toxic! Inevitable?.

UBA. (2013a). Dioxine und dioxinähnliche PCB in Umwelt und Nahrungsketten.

UBA. (2013b). Emissionen flüchtiger organischer Verbindungen ohne Methan (NMVOC) nach

Quellkategorien.

UBA. (2013c). National Trend Tables for the German Atmospheric Emission Reporting (Heavy

Metals), 1990-2011.

UBA. (2014). Particulates and nitrogen dioxide still a health burden in 2013. Retrieved from

http://www.umweltbundesamt.de/en/press/pressinformation/particulates-nitrogen-dioxide-still-a-

health-burden

Ulanova, O., & Starostina, V. (2012). Overview of Life Cycle Assessment approach for products and

waste management systems. Modern Problems of Science and Education, (4). Retrieved from

http://www.science-education.ru/104-6799

UN. (1987). Our Common Future. Report of the World Commission on Environment and Development

(The Brundtland Report). Oxford.

UN. (1992a). Report of the United Nations Conference on Environment and Development. Rio de

Janeiro.

UN. (1992b). United Nations Framework Convention on Climate Change. New-York.

UN. (1998). Kyoto Protocol to the United Nations Framework Convention on Climate Change.

UN. (2014). UN data record view: Bicycles and other cycles, not motorized. Retrieved August 28,

2014, from http://data.un.org/Data.aspx?q=bicycle&d=ICS&f=cmID:49921-

0;crID:643&c=2,3,5,6&s=_crEngNameOrderBy:asc,yr:desc,_utEngNameOrderBy:asc&v=1

UNECE. (1979). 1979 Convention on Long-Range Transboundry Air Pollution. Geneva, Switzerland.

UNECE. (1998a). Convention on Access to Ionformation, Public Participation in Decision-Making

and Access to Justice in Environmental Matters.

UNECE. (1998b). Protocol to the 1979 convention on long-range transboundary air pollution on

persistent organic pollutants. Aarhus, Denmark.

UNECE. (1998c). To the 1979 convention on long-range transboundary air pollution on heavy metals.

UNECE. (1999). Protocol to the 1979 Convention on Long-range Transboundary air pollution

(LRTAP Convention) to abate acidification, eutrophication and ground-level ozone. Gothenburg,

Sweden.

UNEP. (2000). The Montreal Protocol on Substances that Deplete the Ozone Layer. Retrieved from

http://www.unep.org/ozone

138

UNEP. (2005). Rotterdam Convention on the Prior Informed Consent Procedure for Certain

Hazardous Chemicals and Pesticides in International Trade. Geneva, Switzerland.

UNEP. (2006). Handbook for the Montreal Protocol on Substances that Deplete the Ozone Layer - 7th

Edition. United Nations Environment Programme.

UNEP. (2009). Stockholm Convention on Persistent Organic Pollutants (POPs).

UNEP. (2010). Auditing the Implementation of Multilateral Environmental Agreemnets (MEAs): A

Primer for Auditors.

UNEP. (2011). Basel Convention On The Control Of Transboundary Movements Of Hazardous

Wastes. Protocol On Liability And Compensation For Damage Resulting From Transboundary

Movements Of Hazardous Wastes And Their Disposal. Texts And Annexes. Geneva, Switzerland.

UNEP. (2013). UNEP Data Access Centre. Retrieved from

http://ozone.unep.org/Data_Reporting/Data_Access/.

UNFCCC. (n.d.). Kyoto Protocol to the United Nations Framework Convention on Climate Change.

Retrieved from http://unfccc.int/essential_background/kyoto_protocol/items/1678.php

UNFCCC. (2011). Summary of GHG Emissions for Germany (pp. 2–5).

UNFCCC. (2013). Summary of GHG Emissions for Russian Federation. Retrieved from

http://unfccc.int/di/DetailedByParty/Event.do?event=go

Van den Berg, M., Birnbaum, L. S., Denison, M., De Vito, M., Farland, W., Feeley, M., … Peterson,

R. E. (2006). The 2005 World Health Organization reevaluation of human and Mammalian toxic

equivalency factors for dioxins and dioxin-like compounds. Toxicological Sciences : An Official

Journal of the Society of Toxicology, 93(2), 223–41. doi:10.1093/toxsci/kfl055

Van Hoof, G., Vieira, M., Gausman, M., & Weisbrod, A. (2013). Indicator selection in life cycle

assessment to enable decision making: issues and solutions. The International Journal of Life

Cycle Assessment, 18(8), 1568–1580. doi:10.1007/s11367-013-0595-z

Vodainfo. (2011). Development of water sector of Russia in 2012-2020. Retrieved March 25, 1014,

from http://www.vodainfo.com/ru/5602.html

Von Brook, A. (2014). Germany - the effects of climate change.

Wang, H., Hou, P., Zhang, H., & Weng, D. (2011). A Novel Weighting Method in LCIA and its

Application in Chinese Policy Context. In M. Finkbeiner (Ed.), Towards Life Cycle

Sustainability Management SE - 7 (pp. 65–72). Springer Netherlands. doi:10.1007/978-94-007-

1899-9_7

Water use. State control on use and protection of water bodies: Collection of norms (in Russian).

(2010). Yekaterinburg: Ural Jur Izdat.

Weidner, H. (1995). 25 years of modern environmental policy in Germany: treading a well-worn path

to the top of the international field.

WHO. (2014). WHO Dioxins and their effects on human health. Fact sheet N°225.

139

World Bank. (2006). World Bank, Development Research Group and Environment Department

Catalog Sources World Development Indicators.

World Bank. (2010). Energy Efficiency in Russia: Untapped Reserves.

World Bank. (2014a). PM10, country level (micrograms per cubic meter). Retrieved March 17, 2014,

from http://data.worldbank.org/indicator/EN.ATM.PM10.MC.M3

World Bank. (2014b). World Development Indicators : Traffic and congestion Road sector energy

consumption Fuel price.

World Trade Organization. (2010). World Trade Report 2010. Trade in natural resources.

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