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
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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.
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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
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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
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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
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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 15: Structure of Chapter 4 ...... 42 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 26: Structure of Chapter 5 ...... 63 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 viii
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
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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
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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
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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
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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
GNI Gross national income
GWP Global warming potential
HCFC Hydrochlorofluorocarbons
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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
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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
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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
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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).
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Environmental policy • regulation • law • standards • norms
Environmental impacts • climate change Environmental stress • ozone depletion • use of natural resource • human health effects LCA • emissions • resource depletion • waste • etc.
Environmental problems • air, water, soil pollution • ecosystems degradarion • loss of biodiversity • etc.
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.
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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 km2, 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 3 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;
4
• 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.
5
Chapter 1 INTRODUCTION
BACKGROUND
Chapter 2 • LCA Environmental
• LCIA policy:
methods • Russia • Ecological • Germany Scarcity method
Chapter 3 METHODOLOGY
RESULTS
Chapter 4 Russian German Chapter 5 eco-factors eco-factors
Chapter 6 Case study
Chapter 6
Chapter 7 DISCUSSION
Chapter 8 CONCLUSIONS AND OUTLOOK
Figure 2: Structure of the thesis
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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.
LCA Environmental (2.1.) policy (2.4.)
Goal and scope LCI LCIA Interpretation International National (2.1.1.) (2.1.2.) (2.1.3.) (2.1.4.) (2.4.1.)
LCIA methods Russia (2.2.) (2.4.2.)
Germany (2.4.3.) Charachterization (2.2.1.) Ecological Scarcity method (2.3.) Normalization (2.2.2.)
Development (2.3.1.) Weighting (2.2.3.)
Principals and formula (2.3.2.)
Charachteristics (2.3.3.)
Figure 3: Structure of Chapter 2
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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. 8
Life cycle assessment framework
Goal and scope definition
Direct application: • Product development and improvement; • Strategic planning; Inventory Interpretation • Public policy making; analysis • Marketing; • Other.
Impact assessment
Figure 4: Four phases of a Life Cycle Assessment (ISO, 2006a)
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-
9 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.
• Selection of impact categories, category indicators and characterization models (at the scope level); Mandatory elements • Classification; • Characterization.
• Normalization; • Grouping; Optional elements • Weighting; • Data quality analysis.
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 10 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.
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Example
SO , NO , HCl, Life cycle inventory results 2 x CO2, SF6, CH4,
etc. (kg/FU)
Selection Impact category Global warming
LCI results assigned to GHG (CO , SF , impact category 2 6 CH4, etc. assigned to global
Classification warming)
Characterization Baseline model
model for 100 years of GWP10 IPCC
Characterization
factor GWP100
Characterization GWP100 0
Category indicator kg CO2-eq/ FU mechanism
Infrared radiative forcing is a proxy for
potential effects on Environmental the climate, depending on the Environmental integrated relevance atmospheric heat adsorption caused by emissions and the distribution over time of the heat absorption
Coral reefs, forests, crops, Category endpoint(s) etc.
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)
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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 13 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
Interpretation
Goal and scope definition Evaluation by: • Complete- Identification ness check; of significant • Sensitivity issues check; • Consistency check;
Inventory • Other. analysis checks.
Direct applications • Product development and improvement; Conclusions, limitations and recommendations • Strategic planning; Impact • Public policy assess- making; ment • Marketing; • Other.
Figure 7: The relation between elements within the interpretation phase with the other phases of LCA (ISO, 2006b) 14
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.
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LCI results Midpoint (impact) categories Endpoint (damage) categories Climate change Ozone depletion Human health Human toxicity Respiratory inorganics Ionising radiation
Areas Noise
of
Accidents Ecosystem quality protection Elementary flows Photochemical ozone formation Acidification
Eutrophication Ecotoxicity Land use Natural resources Resource depletion Desiccation, salination
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)
16
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 Ecoindicator99, ReCiPe, EDIP97, EDIP2003, Continent (Europe) 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;
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• 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 18
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).
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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 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)
1∙퐸푃 퐹 2 퐸푐표 − 푓푎푐푡표푟 = 퐾 ∙ ∙ ( ) ∙ 푐 퐹푛 퐹푘
Characterization Normalization Weighting Constant (optional) 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
20 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
1∙퐸푃 444 푘푡 푆푂 2 퐸푃 퐸푃 퐸푐표 − 푓푎푐푡표푟 = 1 ∙ ∙ ( 2) ∙ 1012 = 3 123 922 633 = 3 124 444 푘푡 푆푂2 377 푘푡 푆푂2 푘푡 푆푂2 푘푔 푆푂2
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)
푅푒푔푖표푛 1 2 푅푒푔푖표푛 1 1 ∙ 퐸푃 퐹 퐸푐표 − 푓푎푐푡표푟 = 퐾 ∙ ∙ ( 푅푒푔푖표푛 1) ∙ 푐 퐹푛 퐹푘
Region 1 Region 1 K, c, Fn, EP are the same as in Equation 1. F and Fk are current and critical flows with Region 1 as system boundary.
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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)
푅푒푔푖표푛 1 푅푒푔푖표푛 2 퐸푐표 − 푓푎푐푡표푟 푐표푢푛푡푟푦 = 퐸푐표 − 푓푎푐푡표푟 ∙ 푟1 + 퐸푐표 − 푓푎푐푡표푟 ∙ 푟2 + ⋯ 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.
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difficult LCI result
medium Midpoint
categories
Interpretation
Endpoint
categories Interventions
Total impact in single Ecological
score Scarcity method
easy
low medium high Transparency
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
23 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
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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;
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• 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.
Stockholm POPs Rotterdam Convention Convention UNFCCC
Vienna Convention
CLRTAP Aarhus Convention Basel Convention
1975 1980 1985 1990 1995 2000 2005
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.
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Year, place Protocol Objective 1984, Geneva Protocol on Long-term Financing of the Collection of emissions data for air Cooperative Programme for pollutants, measurement of air and Monitoring and Evaluation of the Long- precipitation quality, modeling of range Transmission of Air Pollutants in atmospheric dispersion Europe (EMEP) 1985, Helsinki Protocol on the Reduction of Sulphur Reduction of the annual emissions of Emissions or their Transboundary sulphur compounds or their Transboundary Fluxes by at least 30 per cent fluxes 1988, Sofia Protocol concerning the Control of Freeze emissions of nitrogen oxides or their Nitrogen Oxides or their transboundary fluxes Transboundary Fluxes 1991, Geneva Protocol concerning the Control of Control and reduce emissions of VOCs in Emissions of Volatile Organic order to reduce their transboundary fluxes Compounds or their Transboundary and the fluxes of the resulting secondary Fluxes photochemical oxidant products 1994, Oslo Protocol on Further Reduction of Control and reduce the sulphur emissions 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 Control, reduce or eliminate discharges, Pollutants (POPs) emissions and losses of persistent organic pollutants 1999, Gothenburg Protocol to Abate Acidification, Control, reduce and set emissions ceilings Eutrophication and Ground-level for four pollutants: sulphur, NOx, VOCs and Ozone 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). 27
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).
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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).
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Russian special environmental authorities
Federal Ministry of Natural Environmental, Special authorities Resources and Industrial Ministry of the subdivisions Environment and Nuclear of Agriculture of Russian Federation (Minprirody) Supervision Service (Rostechnadzor)
The Federal For example, Supervisory Federal Forestry regional Natural Ministries of Resources Agency (Rosleshoz) radiation and Management environmental Service safety
Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet)
Federal Agency for Water Resources (Rosvodresursy)
Federal Agency for Subsoil Management (Rosnedra)
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 30 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.
Protection of air quality and climate change 15% 21% Sewage treatment
4% Waste treatment 8% Protection and soil remediation
9% Saving of biodiversity
43% Others non specified
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).
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Agreement Signature Ratification or Entry into force Acceptance Kyoto Protocol 11.03.1999 18.11.2004 16.02.2005
Montreal Protocol - 10.11.1988 - Protocol on Environmental Protection to the - 01.05.2013 - Antarctic Treaty Framework Convention for the Protection of 4.11. 2003 - 12.08. 2006 the Marine Environment of the Caspian Sea The Basel Convention on the Control of Transboundary Movements of Hazardous 22.03.1990 31.01.1995 - Wastes and Their Disposal Helsinki Convention on the Protection of the 09.04.1992 - 17.01.2000 Marine Environment of the Baltic Sea Area Stockholm Convention on Persistent Organic 22.05.2002 17.08.2011 - Pollutants 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).
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Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB)
Federal Agency Federal Federal Office for Nature The Federal Office Environment for Radiation Conservation for Building and Agency (UBA) Protection (BfS) (BfN) Regional Planning with Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR)
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).
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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).
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Agreement Signature Ratification or Entry into force Acceptance 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 23.10.1989 21.04.1995 - Wastes and Their Disposal Aarhus Protocol 24.06.1998 30.09.2003 -
Gothenburg Protocol 01.12.1999 21.10.2004 - Stockholm Convention on Persistent Organic 23.05.2001 25.04.2002 - Pollutants Table 8: Some of the international environmental agreement signed and accepted by Germany
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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.
Eco-factor (3.1.)
Charachterization Normalization Weighting (3.2.) (3.3.) (3.4.)
Current flow (3.4.1.)
Critical flow (3.4.2.)
Figure 14: Structure of Chapter 3
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. 36
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 Abbreviation Reference unit Source factor
Greenhouse gases Global Warming GWP kg CO2- eq (IPCC, 2007) Potential Ozone depleting Ozone Depletion ODP kg CFC-11- eq (UNEP, 2000) substances Potential
Acidifying Acidification AP kg SO2- eq (Guinée et al., substances Potential 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).
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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)
2 1 ∙ 퐸푃 퐹퐸푈 1 ∙ 퐸푃 4 544 224 025 2 퐸푐표 − 푓푎푐푡표푟퐺푒푟푚푎푛푦 = ∙ ( ) ∙ 푐 = ∙ ( ) ∙ 1012 퐺푒푟푚푎푛푦 퐸푈 939 083 309 4 501 007 793 퐹푛 퐹푘 = 1,09 퐸푃/푘푔
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 38 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).
39
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
퐶푟푖푡푖푐푎푙 푓푙표푤 = 푉 ∙ 푀퐴퐶 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 40 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.
41
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.
Emissions Resources
Energy Air Surface water Sea water Waste consumption (4.1.) (4.2.) (4.3.) (4.4.) (4.5.)
GHG N THP (4.1.1.) (4.2.1.) (4.3.1.)
ODS P Phenols (4.1.2.) (4.2.1.) (4.3.1.)
PM Heavy metals (4.1.3.) (4.2.2.)
Overview (4.6.)
Figure 15: Structure of Chapter 4
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. 42
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
43 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
44
Substance Formula GWP 100 EP/kg
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
Sulphur hexafluoride SF6 22 800 8 373
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 SF CF 17 700 6 500 pentafluoride 5 3 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 45
Substance Formula GWP 100 EP/kg
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 CHF OCF OC F OCHF 1 870 687 1040x) 2 2 2 4 2
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.
4000000 3500000 3000000
2500000
eq - 2000000
Gg CO2 Gg 1500000 GHG emission 1000000 Target 500000 0 1990 1995 2000 2005 2010 2015 2020 2025 Year
Figure 16: GHGs emissions trend in Russia (based on UNFCCC, 2013) 46
4.1.2. Ozone-depleting substances (ODS)
Political targets and situation in Russia 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 47
(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 Maximum level of HCFC in % to base level 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.).
Step of the eco-factor calculation (units) Result Reference year/ source of data 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 Eco-factor (EP/kg) Protocol) 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
48
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.
1400
1200
1000
eq
- 800
11 -
600 t t CFC 400 HCFCs Target 200
0 1989 1994 1999 2004 2009 2014 2019 2024 Year
Figure 17: Russian HCFC consumption trend (based on UNEP, 2013)
4.1.3. Particulate matter (PM)
Political targets and situation in Russia 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 49 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/m3 , 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 Step of the eco-factor calculation (units) Result Reference year/ source of data 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/
50 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. 3500
3000
2500
2000 PM10
kt 1500 PM2,5 PM10 target 1000 PM2,5 target 500
0 1990 1995 2000 2005 2010 2015 Year
Figure 18: PM10 and PM2.5 emissions trend in Russia (based on GAINS)
4.2. Emissions to surface water
Political targets and situation in Russia 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).
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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.
52
Eco-factors for N and P Step of the eco-factor calculation (units) Result Reference year/ source of data 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.
450 400 350 300
250 kt 200 N 150 P 100 50 0 1993 1998 2003 2008 2013 Year
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).
53
9 8 7 6
5
mg/l 4 N 3 P 2 1 0 1993 1998 2003 2008 2013 Year
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).
54
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 Eco-factor (EP/kg) 37 180 33 049 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.
140
120
100
80
t 60 Pb Hg 40
20
0 1993 1995 1997 1999 2001 2003 2005 2007 2009 Year
Figure 21: Trend of lead (Pb) and mercury (Hg) emission in sewage water in Russia (based on “Federal Russian statistic service,” 2013)
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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
Political targets and situation in Russia 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).
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Eco-factors for TPH and phenols Step of the eco-factor calculation (units) Result Reference year/ source of data 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
Political targets and situation in Russia 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. 57
Eco-factor for waste Step of the eco-factor calculation (units) Result Reference year/ source of data
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 %. 4500 4000 3500 3000
2500
mlnt 2000 1500 Waste 1000 Target 500 0 2005 2007 2009 2011 2013 2015 2017 2019 Year
Figure 22: Trend of waste generation in Russia (based on “Federal Russian statistic service,” 2013)
4.5. Energy consumption
Political targets and situation in Russia 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).
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2% 1%
7%
Gas 16% Oil Coal Nuclear power 53% Hydropower
21% Biomass
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.
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Eco-factor for energy consumption Step of the eco-factor calculation (units) Result Reference year/ source of data 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.
60
50
40
30 mtoe 20
10
0 residential public industry transport electricity heat supply buildings organizations systems
Figure 24: Energy Efficiency Potential by sector in Russia (based on World Bank, (2010))
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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
61
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.
1%
GHGs (air) 5% 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)
94% Waste Energy
Figure 25: Overall annual environmental impacts of Russia
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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 Surface water Resources (5.1.) (5.2.) (5.3.)
GHG N Land use Energy (5.1.1.) (5.2.1.) (5.3.1.) (5.3.2.)
NMVOCs P (5.1.2.) (5.2.1.)
NOx PAHs (5.1.3.) (5.2.2.)
NH3
(5.1.4.)
SO2 (5.1.5.)
PM (5.1.6.)
Dioxins (5.1.7.)
Hg, Cd, Pb (5.1.8.)
Overview (5.4.)
Figure 26: Structure of Chapter 5
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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). 2% 6% 5%
CO2 CH4 N2O HFCs+PFCs+SF6
87%
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.
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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 Step of the eco-factor calculation (units) Result Reference year/ source of data
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. Substance Formula GWP 100 EP/kg
Carbon dioxide CO2 1 1,6
Methane CH4 25 41
Dinitrogen oxide N2O 298 485
Sulphur hexafluoride SF6 22 800 37 131 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
65
Substance Formula GWP 100 EP/kg
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
Sulphur hexafluoride SF6 22 800 37 133
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 SF CF 17 700 28 827 pentafluoride 5 3 Fluorinated ethers
HFE-125 CF3OCHF2 14 900 24 267
HFE-134 CHF2OCHF2 6 320 10 293
HFE-143a CH3OCF3 756 1 231 66
Substance Formula GWP 100 EP/kg
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 CHF OCF OC F OCHF 1 870 3 046 1040x) 2 2 2 4 2
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.
67
1400000000
1200000000
1000000000
eq
- 800000000
600000000 GHG MgCO2 Target 400000000
200000000
0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 28: GHGs emissions trend in Germany (based on UNFCCC, 2011)
5.1.2. Non-methane volatile organic compounds (NMVOCs)
Political targets and situation in Germany 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.
12% 17%
Energy 3%
Industrial processes
Solvent use
Transport 68%
Figure 29: NMVOCs emissions by source in Germany in 2010 (based on UBA, 2013b)
68
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 Step of the eco-factor calculation (units) Result Reference year/ source of data 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).
3500
3000
2500
2000
kt NMVOCs 1500 Target
1000
500
0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 30: NMVOCs emissions trend in Germany (based on UBA, 2013b)
69
5.1.3. Nitrogen oxides (NOx)
Political targets and situation in Germany
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 Step of the eco-factor calculation (units) Result Reference year/ source of data Normalization flow (kt/a) 1 329 Current flow (kt/a) 1 329 2010 (BMU, 2013a) Critical flow (kt/a) 960 2020 (UNECE, 1999) Weighting (-) 1,9 Eco-factor (EP/kg) 1 443 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).
70
3500
3000
2500
2000
kt NOx 1500 Target 1000
500
0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 31: NOx emissions trend in Germany (based on BMU, 2013a)
5.1.4. Ammonia (NH3)
Political targets and situation in Germany
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.
71
Eco-factor for NH3 Step of the eco-factor calculation (units) Result Reference year/ source of data Normalization flow (kt/a) 552 Current flow (kt/a) 552 2010 (BMU, 2013a) Critical flow (kt/a) 550 2020 (UNECE, 1999) Weighting (-) 1,0 Eco-factor (EP/kg) 1 822
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).
800
700 600
500
kt 400 NH3 300 Target 200 100
0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 32: NH3 emissions trend in Germany (based on BMU, 2013a)
5.1.5. Sulfur dioxide (SO2) and other acidifying substances
Political targets and situation in Germany 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). 72
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 Step of the eco-factor calculation (units) Result Reference year/ source of data Normalization flow (kt/a) 444 Current flow (kt/a) 444 2010 (BMU, 2013a) Critical flow (kt/a) 377 2020 (UNECE, 1999) Weighting (-) 1,4 Eco-factor (EP/kg) 3 124
Table 28: Eco-factor for SO2 in Germany
Eco-factors for other acidifying substances
Acid producer (in air) Formula Characterization factor Eco-factor (EP/kg SO2-eq) (Guinée et al., 2002)
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 73 decreasing (see Figure 33). To achieve the desirable level, in addition to the actions considered in the f most relevant European directives for the reduction of SO2 in air (for example, LCP and IPPC Directivesg, The Sulphur Contents of Liquid Fuels Directiveh, The Fuels Quality Directivei), there is a need for additional policy instruments to reduce emission of SO2 and others.
6000
5000
4000
kt 3000 SO2 Target 2000
1000
0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 33: SO2 emissions trend in Germany (based on BMU, 2013a)
5.1.6. Particulate matter (PM)
Political targets and situation in Germany 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 74 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 Step of the eco-factor calculation (units) Result Reference year/ source of data PM10 PM2.5 Normalization flow (kt/a) 211 117 Current flow (kt/a) 211 117 2010 (BMU, 2013a). Critical flow (kt/a) 156 87 2020 (UNECE, 1999) Weighting (-) 1,8 1,8 Eco-factor (EP/kg) 8 638 15 621 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).
75
350
300
250
200 PM10
kt 150 Target PM10 PM2.5 100 Target PM2.5 50
0 1995 2000 2005 2010 2015 2020 Year
Figure 34: PM10 and PM2.5 emissions trend in Germany (based on BMU, 2013a)
5.1.7. Dioxins
Political targets and situation in Germany 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.
76
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)
77
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 Step of the eco-factor calculation (units) Result Reference year/ source of data 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. 800 700 600
500
400
g TEQ g Dioxins 300 Target 200 100 0 1990 1995 2000 2005 2010 2015 Year
Figure 35: Dioxins emissions trend in Germany (based on UBA, 2013a)
78
5.1.8. Heavy metals: cadmium (Cd), lead (Pb) and mercury (Hg)
Political targets and situation in Germany 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 Result Reference year/ source calculation (units) 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).
79
2500
2000
1500
t Pb 1000 Pb Target
500
0 1990 1995 2000 2005 2010 2015 Year
Figure 36: Pb emissions to air trend in Germany (based on UBA, 2013c)
35
30
25
20 Cd
t 15 Cd Target Hg 10 Hg Target 5
0 1990 1995 2000 2005 2010 2015 Year
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)
Political targets and situation in Germany 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
80 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 Step of the eco-factor calculation (units) Result Reference year/ source of data 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).
81
1200
1000
800
N
t 600 N target 400 P
200 Ptarget
0 1985 1990 1995 2000 2005 2010 2015 Year
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).
Problems with obtaining financial and/or personal resources
Opposition to the envisaged measures
Problems with obtaining the necessary land
New findings concerning measure impact 24%
Technical obstacles 76%
Cost changes
Substantial delay has been indicated Legal obstacles Substantial delay has not been indicated
0 1000 2000 3000 4000 5000 6000 7000 Number of mentions
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)
Political targets and situation in Germany 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). 82
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 Step of the eco-factor calculation (units) Result Reference year/ source of data Normalization flow (kt/a) 19 Current flow (kt/a) 19 2005 (UBA, 2010a) Critical flow (kt/a) 13 2025 (UBA, 2010a) Weighting (-) 2,2 Eco-factor (EP/kg) 113 047 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).
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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
Political targets and situation in Germany 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 Step of the eco-factor calculation (units) Result Reference year/ source of data
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).
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140
120
100
80 Land use ha/day 60 Target 40
20
0 1996 2001 2006 2011 2016 Year
Figure 40: Land use trend in Germany (based on Statistisches Bundesamt, 2012)
5.3.2. Energy consumption
Political targets and situation in Germany 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).
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Hard coal 19% Nuclear energy Biogenic 18% household 1% waste 3% Photovoltaic 3% Natural gas Water 14% Renewables 5% 20% Biomass
8% Wind Lignite 24% Heating oil, pumped-storage and other 5%
Figure 41: Power production in Germany in 2011 (BMWi, 2012)
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 Step of the eco-factor calculation (units) Result Reference year/ source of data 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
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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).
16000 14000 12000
10000
PJ 8000 6000 Primary energy consumption 4000 Target 2000 0 1990 1995 2000 2005 2010 2015 2020 Year
Figure 42: Primary energy consumption trend in Germany (based on AGEB, 2013)
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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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GHG (air) 4% 5% 3% NMVOCs (air) 6% NOx (air) NH3 (air) 3% SO2 (air) 25% 4% PM10 (air) PM2.5 (air) 6% Dioxins (air) Hg (air)
6% Cd (air) Pb (air) 7% 1% N (surface water) 1% P (surface water) PAHs (surface water) 12% 17% Land use Energy
Figure 43: Overall annual environmental impacts of Germany
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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),
90 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).
Raw material Raw material Frame
extraction processing manufacturing (China) (China) (Germany)
• Bamboo • Preservation • Cutting into cultivation • Drying length
• Bamboo • Cutting • Machining of harvesting bamboo tube
ends • Threading
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.
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Aluminum
recycling (Germany)
Raw material Raw material processing Manufacturing extraction the frame (Germany and (Guinea) (Germany) Guinea)
• Bauxite • Alumina • Cutting processing • Bending • Aluminum • Machining production • Welding
• Finishing
Figure 45: System boundaries of the aluminum bike frame (based on Chang et al., 2012) 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).
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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
93 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 %).
Aluminum frame
100%
90%
80% Emissions to industrial soil 70% Emissions to agricultural soil 60% Emissions to sea water 50% Emissions to fresh water 40% Emissions to air 30% Resources 20%
10%
0% Russia Germany Switzerland
Figure 46: The share of different emissions from the aluminum frame for Switzerland, Germany and Russia
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Bamboo frame
100% 90% 80% Emissions to industrial soil 70% Emissions to agricultural soil 60% Emissions to sea water 50% Emissions to fresh water 40% Emissions to air 30% Resources 20% 10% 0% Russia Germany Switzerland
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 95
EP/FU Aluminum frame Bamboo frame 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 %.
100%
90%
80%
70%
60% Emissions to fresh water 50% Emissions to air 40% Resources 30%
20%
10%
0% Aluminum Frame Bamboo Frame
Figure 48: The share of different emissions excluding emission to sea water from the aluminum and bamboo frame for Russia
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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).
EP/FU Aluminum frame Bamboo frame 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.
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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.
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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 99
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.
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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.
• Endocrine disruptors (Russia, Germany)
Data available for current flow EF Data available for critical flow
• Plant protection products can • Heavy metals emission to soil (Germany) (Germany) be calculated • Biochemical oxygen demand • Nickel emissions to air • GHG (Russia) (Germany) • PM • Arsenic emissions to air • Chemical oxygen demand • N (Germany) (Russia) • … • P • ....
Figure 49: Status for eco-factor calculation in few examples of substances: availability of data for current flow, EF and critical flow calculation
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, 101 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.
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CO2
GHGs CH4
SF6
CFC-11 ODSs Air HCFC-123 NOx
NH3
PM10
Hg
Heavy metalls score result - Pb Surface water N
P
Legend: Overall Overall single TPH Substance Sea water N Group of substances
Land use Environmental Resources media/resources Energy consumption
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 103 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
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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.
40
35
30
factors 25 - Noise 20 Waste 15 Resources
numberofeco 10 Soil Water 5 Air 0
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 105
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
106 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.
4,E+04 4,E+04 3,E+04
3,E+04
factor 2,E+04 -
Eco 2,E+04 1,E+04 5,E+03 0,E+00 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 Normalization flow
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 EP Share in total national impact, % *10-9 impact, % *10-9 Russia (without 60 0,003 % 32 0,002 % emissions to sea water) 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
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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.
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1000000
Logarithmic scale 100000
10000
Russia 1000 Germany
Japan factor, EP/kg - 100
Switzerland Eco
10
1 GHG PM10 Nitrogen to surface water 0,1
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 109
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 110
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.
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1400000000
1200000000
1000000000
800000000
eq -
2 Short- term target Mid- term target
Mg CO 600000000 Long- term target Current flow 400000000
200000000
0 1990 2000 2010 2020 2030 2040 2050 Year
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 Deadline for EF with reference to from 1990 implementation 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
112 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 113 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.
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Substance Current flow Critical flow Assumption EF 2020 (F) 2020 (Fk) for F calculation (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 6,3 kg 2,1 kg - 1,4E+12 water) 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 108 067 582 45% of level 2009 Table 47: Russian set of eco-factors for scenarios 2020 based on trend of emissions and consumptions (scenario 1)
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 100%
Figure 56: Russian national environmental impact for scenario 1
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Substance Current flow Critical flow Assumption EF 2020 ( F) 2020 (Fk) for F calculation (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 6,3 kg 2,1 kg - 1,4E+12 water) Waste 2 437 mln t 2 437 mln t target level 2020 410 323 745 potential to save Energy 14 458 PJ 11 566 PJ 108 067 582 45% of level 2009 Table 48: Russian set of eco-factors for scenarios 2020 based on assumptions of the targets achievement (scenario 2)
8% 5% 5% 5% GHG (air) HCFCs (air) PM10 (air) PM2,5 (air) 20% N (surface water) P (surface water) Pb (surface water) Hg (surface water) THP (see water) Phenols (see water) 46% 11% Waste Energy
Figure 57: Russian national environmental impact for scenario 2
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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.
Current flow Critical flow Assumption EF, EP/ physical unit of Substance ( F) (Fk) for F derivation 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 PAHs (surface 19 kt 13 kt - 1,1E+11 water) 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)
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GHG (air) 9% 8% NMVOCs(air) 3% NOx(air) 6% NH3(air) SO2(air)
5% PM10(air)
1% PM2.5(air) Dioxins (air) Hg(air) 8% 37% Cd(air) Pb(air)
7% N(surface water) P(surface water)
1% PAHs(surface water) 15% 1% Land use Energy
Figure 58: German national environmental impact for scenario 1
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Substance Current flow ( F) Critical flow (Fk) Assumption for F EF, EP/ physical unit of derivation 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 PAHs (surface 13 kt 13 kt target level 2025 76 335 877 863 water) 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)
GHG (air) NMVOCs(air) 8% 8% Nox(air) 8% 8% NH3(air) SO2(air) PM10(air) 8% 8% PM2.5(air) Dioxins (air) Hg(air) 8% 8% Cd(air) Pb(air) N(surface water) 8% 8% P(surface water) PAHs(surface water) 8% 8% Land use 1% 1% Energy
Figure 59: German national environmental impact for scenario 2 119
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 Critical flow Eco-factor (reference year) (reference year) 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 Emissions to surface water 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/ m3 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 120
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.
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CO2 (air) NMVOC (air) 1% 1% NOx (air) 1% 0% 6% SO2 (air) 13% PM2.5 (air) 1% NH3 (air)
4% N (water) 18% 2% P (water) 2% Ni (water) 2% Zn (water) 1% COD (water) 6% 2% Pb (water) Cd (water) 4% Cu (water) 15% 2% PAHs (water) 3% Fresh water consumption
15% Renewable energy Non renewable energy Non hazardous waste Hazardous waste
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.
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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).
Substances/ substance groups, resource assessed Environmental issue Russia Germany
Emissions to air GHGs, HCFCs, PMs GHGs, NMVOCs, NOx, NH3, SO2 and other acidifying substances, PMs, Dioxins, Hg, Cd, Pb Emissions to surface N, P, Pb, Hg N, P, PAHs water 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 123 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.
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Environmental LCA (Russia/ policy making Germany) (Russia/ Germany)
Direct contribution Ecological Scarcity method (Russia / Indirect contribution Germany)
Countries with developed national Other countries Ecological Scarcity method
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
125 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
126 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
127 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).
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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/
129
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
130
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
131
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. 132
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
133
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
134
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
135
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.
136
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
137
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.
138
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.
139