oEPA
United States
Environmental Protection
Agency
EPA/600/R-15/325 I April 2016
www.epa.gov/research
Life Cycle Assessment of Cookstove Fuels
in India and China
Office of Research and Development
National Risk Management Research Laboratory
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EPA/600/R-15/325
April 2016
FINAL REPORT
LIFE CYCLE ASSESSMENT OF
COOKSTOVE FUELS IN INDIA AND
CHINA
Sarah Cashman, Molly Rodgers, Melissa Huff, Rebe Feraldi, and
Ben Morelli
Eastern Research Group, Inc.
Lexington, MA 02421
Contract No. EP-D-11-006
Work Assignment No. 5-10
Prepared for
Susan A. Thorneloe
U.S. Environmental Protection Agency
Office of Research and Development
National Risk Management Research Laboratory
Air Pollution Prevention and Control Division
Research Triangle Park, NC 27711
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NOTICE
The U.S. Environmental Protection Agency through its Office of Research and Development
funded and managed the study described here under Contract EP-D-11-006 to Eastern Research
Group, Inc. This report has been subjected to the Agency's peer and administrative review and has
been approved for publication as an EPA document.
1
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ABSTRACT
Over half of the population in both China and India use traditional cookstoves that emit harmful
air pollutants resulting in over a million annual premature deaths. Reducing pollution from
cookstoves is a key priority as emissions from traditional cookstoves and open fires with solid
fuels is a major health concern. Past studies have focused on the impacts of replacing "dirtier"
stoves with "cleaner" stoves; however, less research is available on the full supply chain of the
fuels used in the stoves. Use of traditional cookstoves fuels such as firewood and coal, combined
with rapid rates of urbanization and industrialization, have contributed to resource depletion,
deforestation, desertification, and biodiversity loss. The U.S. Environmental Protection Agency
(U.S. EPA) is conducting research to provide data and tools that inform decisions regarding
clean cookstoves and fuels for these countries. A life cycle assessment (LCA) was conducted to
compare the environmental footprint of current and possible fuels used for cooking in China and
India. This report provides the life-cycle inventory (LCI) environmental tradeoffs for cooking
fuels on the basis of 1 gigajoule (GJ) of delivered cooking energy. The fuels evaluated include
natural gas; liquefied petroleum gas (LPG); coal; kerosene; biomass (crop residue, dung,
charcoal, firewood, wood pellets); biogas; sugarcane ethanol; and dimethyl ether (DME). The
study also assessed electric stoves that utilize a diverse set of fuel types upstream. Current fuel
mix profiles are compared to scenarios of projected differences in and/or cleaner cooking fuels.
Results are reported for a suite of relevant life cycle impact assessment (LCIA) indicators: global
climate change, energy demand, fossil depletion, water consumption, particulate matter
formation, acidification, eutrophication and photochemical smog formation. Traditional fuels
demonstrate notably poor relative performance in particulate matter formation, photochemical
oxidant formation, freshwater eutrophication, and black carbon emissions. Most fuels
demonstrate trade-offs between impact categories. Stove efficiency is found to be a crucial
variable determining environmental performance across all impact categories. The study shows
that electricity and many of the processed fuels, while yielding emission reductions in homes at
the point of use, transfer many of those emissions upstream into the processing and distribution
life cycle stage. The data presented in this report will be part of an EPA tool that provides users
access to data and facilitates analyses to evaluate differences in fuels and other parameters that
affect selection of future cookstove fuels. The tool will provide information on the LCA
environmental tradeoffs that affect the environmental performance of cookstove fuels. The tool
will also link to a Global Alliance for Clean Cookstoves' tool - the Fuel Analysis, Comparison
and Integration Tool (FACIT) - providing information on environmental, economic and social
impacts associated with several types of fuels used in cookstoves.
ii
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FOREWARD
The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the
Nation's land, air, and water resources. Under a mandate of national environmental laws, the
Agency strives to formulate and implement actions leading to a compatible balance between
human activities and the ability of natural systems to support and nurture life. To meet this
mandate, EPA's research program is providing data and technical support for solving
environmental problems today and building a science knowledge base necessary to manage our
ecological resources wisely, understand how pollutants affect our health, and prevent or reduce
environmental risks in the future.
The National Risk Management Research Laboratory (NRMRL) within the Office of Research
and Development (ORD) is the Agency's center for investigation of technological and
management approaches for preventing and reducing risks from pollution that threaten human
health and the environment. The focus of the Laboratory's research program is on methods and
their cost-effectiveness for prevention and control of pollution to air, land, water, and subsurface
resources; protection of water quality in public water systems; remediation of contaminated
sites, sediments and ground water; prevention and control of indoor air pollution; and restoration
of ecosystems. NRMRL collaborates with both public and private sector partners to foster
technologies that reduce the cost of compliance and to anticipate emerging problems. NRMRL's
research provides solutions to environmental problems by: developing and promoting
technologies that protect and improve the environment; advancing scientific and engineering
information to support regulatory and policy decisions; and providing the technical support and
information transfer to ensure implementation of environmental regulations and strategies at the
national, state, and community levels.
This publication was produced in support of ORD's Air, Climate, and Energy FY16-19 Strategic
Research Action Plan. EPA, along with other federal partners, is working in collaboration with
the Global Alliance for Clean Cookstoves to conduct research and provide tools to inform
decisions about clean cookstoves and fuels in developing countries. This study scope includes a
Life Cycle Assessment (LCA) comparing the environmental footprint of current and potential
fuels and fuel mixes used for cooking within China and India. Study results will allow
researchers and policy-makers to quantify sustainability-related metrics from a systems
perspective.
Cynthia Sonich-Mullin, Director
National Risk Management Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
111
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TABLE OF CONTENTS
Page
NOTICE i
ABSTRACT ii
FOREWORD iii
ACRONYMS AND ABBREVIATIONS xvii
ES.l Executive Summary 1
ES.1.1 Introduction 1
ES.2.1 Methodology 1
ES.3.1 Key Findings 4
ES.4.1 Report Organization Summary 11
1. Goal and Scope Definition 1-1
1.1 Goal 1-1
1.2 Scope of the Study 1-2
1.2.1 Functional Unit 1-2
1.2.2 Geographical Scope 1-2
1.2.3 Transparency 1-2
1.2.4 Fuel Systems Studied 1-3
1.2.5 System Boundary 1-6
1.2.6 Scenario Development 1-11
1.2.7 Data Sources Summary 1-20
1.2.8 Data Requirements 1-20
1.2.9 Life Cycle Impact Assessment Methodology and Impact
Categories 1-21
2. Process Descriptions and Methodology 2-1
2.1 Overview 2-1
2.2 Life Cycle Inventory Data for Current and Potential Fuels Used in India
and China 2-1
2.2.1 Processed Fuel Heating Values 2-1
2.2.2 Electricity 2-2
2.2.3 Liquefied Petroleum Gas 2-3
2.2.4 Kerosene 2-4
2.2.5 Coal 2-4
2.2.6 Firewood 2-5
2.2.7 Crop Residues 2-5
2.2.8 Biomass Pellets 2-5
2.2.9 Charcoal from Wood 2-6
2.2.10 Dung 2-6
2.2.11 Ethanol 2-6
2.2.12 Biogas 2-6
2.2.13 Natural Gas 2-7
iv
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TABLE OF CONTENTS (Continued)
Page
2.2.14 Dimethyl Ether 2-7
2.3 Allocation Methodology 2-7
2.4 Biogenic Carbon Accounting 2-8
2.5 Non-Renewable Wood Fuel Calculations 2-8
2.6 Black Carbon and Short-Lived Climate Pollutants Calculations 2-9
2.7 LCA Model Framework 2-10
3. Life Cycle Assessment Results for India 3-1
3.1 Results for India by Cooking Fuel Type 3-1
3.1.1 Global Climate Change Potential 3-1
3.1.2 Cumulative Energy Demand 3-2
3.1.3 Fossil Depletion 3-4
3.1.4 Water Depletion 3-5
3.1.5 Particulate Matter Formation Potential 3-6
3.1.6 Photochemical Oxidant Formation Potential 3-6
3.1.7 Freshwater Eutrophication Potential 3-7
3.1.8 Terrestrial Acidification Potential 3-8
3.1.9 Ozone Depletion Potential 3-9
3.1.10 Black Carbon and Short-Lived Climate Pollutants 3-11
3.2 Results for India by Baseline and Potential Scenarios 3-11
3.2.1 Global Climate Change Potential 3-12
3.2.2 Cumulative Energy Demand 3-13
3.2.3 Fossil Depletion 3-14
3.2.4 Water Depletion 3-15
3.2.5 Particulate Matter Formation 3-16
3.2.6 Photochemical Oxidant Formation Potential 3-17
3.2.7 Freshwater Eutrophi cation Potential 3-18
3.2.8 Terrestrial Acidification Potential 3-19
3.2.9 Ozone Depletion Potential 3-20
3.2.10 Black Carbon and Short-Lived Climate Pollutants 3-21
3.2.11 Relative Impacts of Current and Cleaner Electrical Grid Scenarios
in India 3-22
3.3 Summary Tables for Fuel and Fuel Scenarios in India 3-23
4. Life Cycle Assessment Results for China 4-1
4.1 Results for China by Cooking Fuel Type 4-1
4.1.1 Global Climate Change Potential 4-1
4.1.2 Cumulative Energy Demand 4-2
4.1.3 Fossil Depletion 4-4
4.1.4 Water Depletion 4-5
4.1.5 Particulate Matter Formation Potential 4-6
4.1.6 Photochemical Oxidant Formation Potential 4-6
4.1.7 Freshwater Eutrophi cation Potential 4-8
4.1.8 Terrestrial Acidification Potential 4-9
v
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TABLE OF CONTENTS (Continued)
Page
4.1.9 Ozone Depletion Potential 4-10
4.1.10 Black Carbon and Short-Lived Climate Pollutants 4-11
4.2 Results for China by Baseline and Potential Scenarios 4-12
4.2.1 Global Climate Change Potential 4-12
4.2.2 Cumulative Energy Demand 4-13
4.2.3 Fossil Depletion 4-14
4.2.4 Water Depletion 4-15
4.2.5 Particulate Matter Formation Potential 4-16
4.2.6 Photochemical Oxidant Formation Potential 4-17
4.2.7 Freshwater Eutrophication Potential 4-18
4.2.8 Terrestrial Acidification Potential 4-19
4.2.9 Ozone Depletion Potential 4-20
4.2.10 Black Carbon and Short-Lived Climate Pollutants 4-21
4.2.11 Relative Impacts of Current and Cleaner Electrical Grid Scenarios
in China 4-22
4.3 Summary Tables for Fuel and Fuel Scenarios in China 4-23
5. Conclusions and Next Steps 5-1
5.1 Key Takeaways 5-1
5.2 Next Steps 5-4
6. References 6-1
APPENDIX A: DETAILED LCI UNIT PROCESS TABLES A-l
APPENDIX B: DETAILED LCA RESULTS TABLES B-l
vi
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LIST OF TABLES
Page
Table ES-1. Average Emission Factors during Cooking (in kg/MJ) of Key Pollutants by
Cookstove Fuel Category for India ES-5
Table ES-2. Average Emission Factors during Cooking (in kg/MJ) of Key Pollutants by
Cookstove Fuel Category for China ES-5
Table ES-3. Description of Bin Cut-offs for Summary Impact Results ES-6
Table ES-4. Summary Impact Results by Cooking Fuel for India ES-7
Table ES-5. Summary Impact Results by Cooking Fuel for China ES-8
Table 1-1. Current Fuels Used for Cooking in China and India 1-3
Table 1-2. Current Electricity Grid Mix in India 1-4
Table 1-3. Current Electricity Grid for China 1-4
Table 1-4. Full and Abbreviated Scenario Names for India 1-12
Table 1-5. Cooking Fuel Mix Scenarios Evaluated for India 1-13
Table 1-6. Thermal Efficiencies Modeled for Indian Cookstoves 1-15
Table 1-7. Full and Abbreviated Scenario Names for China 1-16
Table 1-8. Cooking Fuel Mix Scenarios Evaluated for China 1-17
Table 1-9. Thermal Efficiencies Modeled for Chinese Cookstoves 1-20
Table 1-10. Environmental Impact Category Descriptions and Units 1-23
Table 2-1. Heating Values of Cooking Fuels in India 2-2
Table 2-2. Heating Values of Cooking Fuels in China 2-2
Table 2-3. Current and Cleaner Electricity Grids for India 2-2
Table 2-4. Current and Cleaner Electricity Grids for China 2-3
Table 2-5. Characterization Factors for BC eq 2-10
Table 3-1. Ranked Performance of Fuels by Impact Category in India 3-24
Table 3-2. Ranked Performance of Fuel Scenarios by Impact Category in India 3-26
vii
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LIST OF TABLES (Continued)
Page
Table 4-1. Ranked Performance of Fuels by Impact Category in China 4-24
Table 4-2. Ranked Performance of Fuel Scenarios by Impact Category in China 4-26
APPENDIX A TABLES
Table A-l. Code Key for LCI Tables A-l
Table A-2. Data Quality Index Methodology [1] A-l
Table A-3. Data Quality Indicator Descriptions [1] A-3
Table A-4. Biogas; Production from Dung; At Anaerobic Digester (IN) A-4
Table A-5. Charcoal; Production from Wood; At Earth Mound Kiln (IN) A-5
Table A-6. Electricity; Average Production; At Consumer; Production Mix (IN) A-6
Table A-7. Hard Coal; Extraction; At Open Cast Mine (IN) A-7
Table A-8. LPG; Production from Natural Gas; at Plant; Production Mix (IN) A-9
Table A-9. LPG from Crude Oil; Petroleum Refining; At Plant; Production Mix (IN) A-10
Table A-10. Molasses; Production from Sugarcane; At Plant (IN) A-13
Table A-l 1. Sugarcane; Production; At Farm (IN) A-14
Table A-12. Ethanol; Production from Sugarcane Molasses; At Plant (IN) A-16
Table A-13. Biomass Pellet Production, At Consumer (IN) A-17
Table A-14. Crude Oil; Extraction; At Plant; Production Mix (IN) A-18
Table A-l5. Natural Gas; Extraction; At Plant; Production Mix (IN) A-20
Table A-16. Bottling; LPG from Crude Oil; At Plant (IN) A-21
Table A-17. Bottling; LPG from Natural Gas; At Plant (IN) A-22
Table A-18. Heat from Biomass Pellets; Pellet Stove; At Consumer (IN) A-23
Table A-19. Heat from Sugarcane Ethanol; Alcohol Stove; At Consumer (IN) A-24
Table A-20. Heat from Biogas; Biogas Stove; At Consumer (IN) A-25
Table A-21. Heat from Charcoal; Metal Stove; At Consumer (IN) A-26
viii
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LIST OF TABLES (Continued)
Page
Table A-22. Heat from Hard Coal; Metal Stove; At Consumer (IN) A-27
Table A-23. Heat from Firewood; Traditional Mud Stove; At Consumer (IN) A-28
Table A-24. Heat from Natural Gas LPG; LPG Stove; At Consumer (IN) A-29
Table A-25. Heat from Crop Residue; Traditional Mud Stove; At Consumer (IN) A-30
Table A-26. Heat from Dung Cake; Traditional Mud Stove; At Consumer (IN) A-31
Table A-27. Heat from Crude Oil LPG; LPG Stove; At Consumer (IN) A-32
Table A-28. Heat from Kerosene; Kerosene Pressure Stove; At Consumer (IN) A-33
Table A-29. Biomass Pellets, At Consumer, National Mix (CN) A-34
Table A-30. Bottling, DME from Coal Gas, At Plant (CN) A-35
Table A-31. Bottling, LPG from Crude Oil, At Plant (CN) A-36
Table A-32. Bottling, LPG from Natural Gas, At Plant (CN) A-37
Table A-33. Brush Wood, At Consumer (CN) A-38
Table A-34. Coal Briquette, At Consumer (CN) A-39
Table A-35. Coal Gas, At Consumer (CN) A-39
Table A-36. Coal Powder, At Consumer (CN) A-40
Table A-37. Fuel Wood, At Consumer (CN) A-41
Table A-38. Kerosene, At Consumer (CN) A-42
Table A-39. LPG At Consumer (CN) A-42
Table A-40. Maize Residue, At Consumer (CN) A-43
Table A-41. Natural Gas, At Consumer (CN) A-43
Table A-42. Rice Straw, At Consumer (CN) A-44
Table A-43. Wheat Residue, At Consumer (CN) A-44
Table A-44. Heat from Biomass Pellets; Pellet Stove; At Consumer A-45
Table A-45. Heat from Biomass; Cookstove; At Consumer; National Mix (CN) A-46
ix
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LIST OF TABLES (Continued)
Page
Table A-46. Heat from Brush Wood; Brick Stove With Flue; At Consumer (CN) A-47
Table A-47. Heat from Brush Wood; India Metal Stove Without Flue; At Consumer (CN)... A-49
Table A-48. Heat from Coal Briquette; Metal Stove with Flue; At Consumer (CN) A-50
Table A-49. Heat from Coal Briquette; Metal Stove without Flue; At Consumer (CN) A-52
Table A-50. Heat from Coal Gas; Traditional Gas Stove without Flue; At Consumer (CN)... A-55
Table A-51. Heat from Coal Powder; Brick Stove with Flue; At Consumer (CN) A-57
Table A-52. Heat from Coal Powder; Metal Stove with Flue; At Consumer (CN) A-59
Table A-53. Heat from Coal Powder; Metal Stove without Flue; At Consumer (CN) A-61
Table A-54. Heat from DME; Traditional Gas Stove without Flue; At Consumer (CN) A-63
Table A-55. Heat from Fuel Wood; Brick Stove with Flue; At Consumer (CN) A-65
Table A-56. Heat from Fuel Wood; Improved Brick Stove with Flue; At Consumer (CN) .... A-67
Table A-57. Heat from Fuel Wood; Improved Brick Stove without Flue; At Consumer
(CN) A-68
Table A-58. Heat from Honeycomb Coal Briquette; Improved Metal Stove without Flue;
At Consumer (CN) A-69
Table A-59. Heat from Honeycomb Coal Briquette; Metal Stove with Flue; At Consumer
(CN) A-71
Table A-60. Heat from Honeycomb Coal Briquette; Metal Stove without Flue; At
Consumer (CN) A-73
Table A-61. Heat from Kerosene; Pressure Stove without Flue; At Consumer (CN) A-75
Table A-62. Heat from LPG; Infrared Gas Stove without Flue; At Consumer (CN) A-77
Table A-63. Heat from LPG; Traditional Gas Stove without Flue; At Consumer (CN) A-79
Table A-64. Heat from Maize Residue; Brick Stove with Flue; At Consumer (CN) A-81
Table A-65. Heat from Maize Residue; Improved Brick Stove with Flue; At Consumer
(CN) A-83
Table A-66. Heat from Natural Gas; Traditional Gas Stove without Flue; At Consumer
(CN) A-85
X
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LIST OF TABLES (Continued)
Page
Table A-67. Heat from Rice Straw; Improved Brick Stove with Flue; At Consumer (CN) A-87
Table A-68. Heat from Shanxi Coal Powder; Metal Stove with Flue; At Consumer (CN) A-89
Table A-69. Heat from Shanxi Honeycomb Coal Briquette; Metal Stove with Flue; At
Consumer (CN) A-91
Table A-70. Heat from Washed Coal Powder; Metal Stove with Flue; At Consumer (CN).... A-93
Table A-71. Heat from Wheat Residue; At Improved Brick Stove with Flue; At
Consumer (CN) A-95
Table A-72. Heat from Wheat Residue; Brick Stove with Flue; At Consumer (CN) A-97
APPENDIX B TABLES
Table B-l. Detailed Results for Global Climate Change Potential by Cooking Fuel Type
in India B-l
Table B-2. Detailed Results for Cumulative Energy Demand by Cooking Fuel Type in
India B-2
Table B-3. Detailed Results for Fossil Depletion by Cooking Fuel Type in India B-2
Table B-4. Detailed Results for Water Depletion by Cooking Fuel Type in India B-3
Table B-5. Detailed Results for Particulate Matter Formation by Cooking Fuel Type in
India B-3
Table B-6. Detailed Results for Photochemical Oxidant Formation by Cooking Fuel Type
in India B-4
Table B-7. Detailed Results for Freshwater Eutrophication by Cooking Fuel Type in
India B-4
Table B-8. Detailed Results for Terrestrial Acidification by Cooking Fuel Type in India B-5
Table B-9. Detailed Results for Ozone Depletion by Cooking Fuel Type in India B-5
Table B-10. Detailed Results for Black Carbon by Cooking Fuel Type in India B-6
Table B-l 1. Detailed Results for Global Climate Change by Cooking Fuel Type in China B-6
Table B-12. Detailed Results for Cumulative Energy Demand by Cooking Fuel Type in
China B-7
xi
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LIST OF TABLES (Continued)
Page
Table B-13. Detailed Results for Fossil Depletion by Cooking Fuel Type in China B-7
Table B-14. Detailed Results for Water Depletion by Cooking Fuel Type in China B-8
Table B-15. Detailed Results for Particulate Matter Formation by Cooking Fuel Type in
China B-8
Table B-16. Detailed Results for Photochemical Oxidant Formation by Cooking Fuel
Type in China B-9
Table B-17. Detailed Results for Freshwater Eutrophication by Cooking Fuel Type in
China B-9
Table B- 18. Detailed Results for Terrestrial Acidification by Cooking Fuel Type in
China B-10
Table B-19. Detailed Results for Ozone Depletion by Cooking Fuel Type in China B-10
Table B-20. Detailed Results for Black Carbon by Cooking Fuel Type in China B-l 1
Table B-21. Detailed Results for Global Climate Change Potential by Baseline and
Potential Scenarios in India B-l 1
Table B-22. Detailed Results for Cumulative Energy Demand by Baseline and Potential
Scenarios in India B-12
Table B-23. Detailed Results for Fossil Depletion by Baseline and Potential Scenarios in
India B-13
Table B-24. Detailed Results for Water Depletion by Baseline and Potential Scenarios in
India B-13
Table B-25. Detailed Results for Particulate Matter Formation by Baseline and Potential
Scenarios in India B-14
Table B-26. Detailed Results for Photochemical Oxidant Formation by Baseline and
Potential Scenarios in India B-15
Table B-27. Detailed Results for Freshwater Eutrophi cation by Baseline and Potential
Scenarios in India B-15
Table B-28. Detailed Results for Terrestrial Acidification by Baseline and Potential
Scenarios in India B-16
Table B-29. Detailed Results for Ozone Depletion by Baseline and Potential Scenarios in
India B-17
xii
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LIST OF TABLES (Continued)
Page
Table B-30. Detailed Results for Black Carbon & Short-Lived Climate Pollutants by
Baseline and Potential Scenarios in India B-17
Table B-31. Detailed Results for Global Climate Change Potential by Baseline and
Potential Scenarios in China B-18
Table B-32. Detailed Results for Cumulative Energy Demand by Baseline and Potential
Scenarios in China B-19
Table B-33. Detailed Results for Fossil Depletion by Baseline and Potential Scenarios in
China B-19
Table B-34. Detailed Results for Water Depletion by Baseline and Potential Scenarios in
China B-20
Table B-35. Detailed Results for Particulate Matter Formation by Baseline and Potential
Scenarios in China B-20
Table B-36. Detailed Results for Photochemical Oxidant Formation by Baseline and
Potential Scenarios in China B-21
Table B-37. Detailed Results for Freshwater Eutrophication by Baseline and Potential
Scenarios in China B-21
Table B-38. Detailed Results for Terrestrial Acidification by Baseline and Potential
Scenarios in China B-22
Table B-39. Detailed Results for Ozone Depletion by Baseline and Potential Scenarios in
China B-22
Table B-40. Detailed Results for Black Carbon & Short-Lived Climate Pollutants by
Baseline and Potential Scenarios in China B-23
xiii
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LIST OF FIGURES
Page
Figure ES-1. Current Cooking Fuel Mix in India and China ES-2
Figure 1-1. Study Boundaries of the Baseline Scenario for India 1-8
Figure 1-2. Study Boundaries of the Baseline Scenario for China 1-9
Figure 3-1. Cookstove Fuel Global Climate Change Potential for India 3-2
Figure 3-2. Cookstove Fuel Cumulative Energy Demand for India 3-3
Figure 3-3. Cookstove Fuel Fossil Depletion for India 3-4
Figure 3-4. Cookstove Fuel Water Depletion for India 3-5
Figure 3-5. Cookstove Fuel Particulate Matter Formation Potential for India 3-6
Figure 3-6. Cookstove Fuel Photochemical Oxidant Formation Potential for India 3-7
Figure 3-7. Cookstove Fuel Freshwater Eutrophication for India 3-8
Figure 3-8. Cookstove Fuel Terrestrial Acidification for India 3-9
Figure 3-9. Cookstove Fuel Ozone Depletion Potential Impacts for India 3-10
Figure 3-10. Cookstove Fuel Black Carbon and Short-Lived Climate Pollutant Impacts
for India 3-11
Figure 3-11. Global Climate Change Potential Impacts for Current and Future Fuel Mix
Scenarios in India 3-12
Figure 3-12. Cumulative Energy Demand for Current and Future Fuel Mix Scenarios in
India 3-13
Figure 3-13. Fossil Depletion for Current and Future Fuel Mix Scenarios in India 3-14
Figure 3-14. Water Depletion for Current and Future Fuel Mix Scenarios in India 3-15
Figure 3-15. Particulate Matter Formation Potential for Current and Future Fuel Mix
Scenarios in India 3-16
Figure 3-16. Photochemical Oxidant Formation Potential for Current and Future Fuel
Mix Scenarios in India 3-17
xiv
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LIST OF FIGURES (Continued)
Page
Figure 3-17. Freshwater Eutrophication Potential for Current and Future Fuel Mix
Scenarios in India 3-18
Figure 3-18. Terrestrial Acidification Potential for Current and Future Fuel Mix
Scenarios in India 3-19
Figure 3-19. Ozone Depletion Potential for Current and Future Fuel Mix Scenarios in
India 3-20
Figure 3-20. Black Carbon and Short-Lived Climate Pollutant Impacts for Current and
Future Fuel Mix Scenarios in India 3-21
Figure 3-21. Relative Global Climate Change, Cumulate Energy Demand, Fossil
Depletion, Water Depletion, and Particulate Matter Formation Impacts of Study
Electricity Grids in India 3-22
Figure 3-22. Relative Photochemical Oxidant Formation, Eutrophi cation, Acidification,
Ozone Depletion, and Black Carbon Impacts of Study Electricity Grids in India 3-23
Figure 4-1. Global Climate Change Potential Impacts of Cooking Fuels per GJ of
Delivered Heat for China 4-2
Figure 4-2. Cookstove Fuel Cumulative Energy Demand Impacts for China 4-3
Figure 4-3. Cookstove Fuel Fossil Depletion Impacts for China 4-4
Figure 4-4. Cookstove Fuel Water Depletion Impacts for China 4-5
Figure 4-5. Cookstove Fuel Particulate Matter Formation Potential Impacts for China 4-6
Figure 4-6. Cookstove Fuel Photochemical Oxidant Formation Potential Impacts for
China 4-7
Figure 4-7. Cookstove Fuel Freshwater Eutrophication Potential Impacts for China 4-8
Figure 4-8. Cookstove Fuel Terrestrial Acidification Potential Impacts for China 4-9
Figure 4-9. Cookstove Fuel Ozone Depletion Potential Impacts for China 4-10
Figure 4-10. Cookstove Fuel Black Carbon and Short-Lived Climate Pollutant Impacts
for China 4-11
Figure 4-11. Global Climate Change Potential Impacts for Current and Future Fuel Mix
Scenarios in China 4-12
XV
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LIST OF FIGURES (Continued)
Page
Figure 4-12. Cumulative Energy Demand for Current and Future Fuel Mix Scenarios in
China 4-13
Figure 4-13. Fossil Depletion for Current and Future Fuel Mix Scenarios in China 4-14
Figure 4-14. Water Depletion Impacts for Current and Future Fuel Mix Scenarios in
China 4-15
Figure 4-15. Particulate Matter Formation Potential for Current and Future Fuel Mix
Scenarios in China 4-16
Figure 4-16. Photochemical Oxidant Formation Potential for Current and Future Fuel
Mix Scenarios in China 4-17
Figure 4-17. Freshwater Eutrophication Potential for Current and Future Fuel Mix
Scenarios in China 4-18
Figure 4-18. Terrestrial Acidification Potential for Current and Future Fuel Mix
Scenarios in China 4-19
Figure 4-19. Ozone Depletion Potential for Current and Future Fuel Mix Scenarios in
China 4-20
Figure 4-20. Black Carbon and Short-Lived Climate Pollutant Impacts for Current and
Future Fuel Mix Scenarios in China 4-21
Figure 4-21. Relative Global Climate Change, Cumulative Energy Demand, Fossil
Depletion, Water Depletion, and Particulate Matter Formation Impacts of Study
Electricity Grids in China 4-22
Figure 4-22. Relative Photochemical Oxidant Formation, Eutrophi cation, Acidification,
Ozone Depletion, and Black Carbon Impacts of Study Electricity Grids in China 4-23
xvi
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Acronyms and Abbreviations
AD
Anaerobic Digester
nh3
Ammonia
Ag
Agricultural
NMVOC
Non-Methane Volatile
AGB
Above Ground Biomass
Organic Carbon
BC
Black Carbon
NOx
Nitrogen Oxides
BGB
Below Ground Biomass
OC
Organic Carbon
BrC
Brown Carbon
ONGC
Oil and Natural Gas
CAP
Criteria Air Pollutants
Corporation
CED
Cumulative Energy Demand
P
Phosphorous
CFC
Chi orofluorocarb ons
PM2.5
Particulate Matter, <2.5
ch4
Methane
micrometers
CN
China
PM10
Particulate Matter, <10
CO
Carbon Monoxide
micrometers
co2
Carbon Dioxide
PV
Photovoltaics
co3
Carbonate
QAPP
Quality Assurance Project
DME
Dimethyl ether
Plan
EC
Elemental Carbon
SLCPs
Short-Lived Climate
FAO
Food and Agriculture
Pollutants
Organization
so2
Sulfur Dioxide
GACC
Global Alliance for Clean
SOx
Sulfur Oxides
Cookstoves
US EPA
United States Environmental
GCCP
Global Climate Change
Protection Agency
Potential
USD A
United States Department of
GHG
Greenhouse Gas
Agriculture
GJ
Gigajoule
US LCI
United States Life Cycle
GSF
Gold Standard Foundation
Inventory
GWP
Global Warming Potential
VOC
Volatile Organic Carbon
HAPs
Hazardous Air Pollutants
HCFC
Hy drochl orofluorocarb on
HHV
Higher Heating Value
IEA
International Energy
Association
IN
India
IOCL
Indian Oil Corporation
Limited
IPCC
Inter-Governmental Panel on
Climate Change
LBNL
Lawrence Berkeley National
Laboratory
LCA
Life Cycle Assessment
LCI
Life Cycle Inventory
LCIA
Life Cycle Inventory
Assessment
ISO
International Standards
Organization
LPG
Liquefied Petroleum Gas
NG
Natural Gas
xvii
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Executive Summary
ES.l Executive Summary
ES.1.1 Introduction
The use of traditional cookstoves in developing countries affects millions of lives on a daily
basis with far-reaching health and environmental impacts. In both China and India, approximately
half of each country's population (totaling more than 2.6 billion people) currently use traditional
cookstove fuels (e.g., wood, crop residues, dung cake and coal). Over a million annual premature
deaths in China and India are attributed to criteria air pollutants (CAPs) and hazardous air
pollutants (HAPs) from these cooking fuels. Consumption of these traditional cookstove fuels,
combined with rapid rates of urbanization and industrialization, has furthered the countries'
resource depletion, deforestation, desertification, and biodiversity loss. The U.S. Environmental
Protection Agency (U.S. EPA) is working in collaboration with the Global Alliance for Clean
Cookstoves (the Alliance) and other international partners to conduct research and provide tools
to inform decisions about clean cookstoves in these countries. This study scope includes a Life
Cycle Assessment (LCA) comparing the environmental footprint of current and potential fuels and
fuel mixes used for cooking within China and India. LCA is a tool used to quantify sustainability-
related metrics from a systems perspective.
The term "clean cooking fuel" is commonly understood to represent fuels that produce less
damaging emissions at the point of use. Table ES-1 and Table ES-2 provide a range of emission
factors at the point of use for cooking fuel types typically considered "clean" as compared to
cookstove fuel types with greater emissions during combustion. However, assessing only point of
use emissions may neglect important impacts across the full life cycle of the fuel. There may be
increased emissions at the point of production, processing or distribution of the fuel. Conducting
an LCA of cooking fuels allows a more holistic analysis of changes in cookstove fuel mixes, which
may lead to increases or decreases in environmental releases both locally and globally. The first
goal of this study is, therefore, to determine the life cycle environmental burdens associated with
a suite of current fuels used for cooking within China and India. The study then leverages the
individual fuel profiles developed to assess the environmental impacts from the current cookstove
fuel mix in each country as well as projected future cookstove fuel mix scenarios.
This study focuses on delivering information to stakeholders involved in making decisions
related to optimizing cookstove fuel production, processing, distribution and use. Audiences that
may benefit from the information developed through this research include, but are not limited to,
local and national governments in China and India, donors and investors (e.g., strategic planners),
and researchers (e.g., sustainability scientists).
ES.2.1 Methodology
This LCA investigates current fuels and fuels with market potential for cookstoves in India
and China. The current India and China fuel mix for cooking, including potential fuels considered
but not currently utilized in measurable quantities in these two countries, is illustrated in Figure
ES-1. The environmental impacts of the fuels per country listed in Figure ES-1 are covered in this
analysis.
ES-1
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Executive Summary
India
(Current) Hard Coal.
_ 1.9%
Crop
Residue.
Firewood
19.0",,
Kerosene. 3.20%
Electricity,
0.4% '
Sugarcane
Ethanol,
0%*
Biogas from Cattle
Dung, 0.40%
Biomass Charcoal from Wood.
Pellets, (!",,* 0.40%
Source: Dalberg 2013; Venkataraman et al. 2010
China
(Current)
Natural
DME**, Gas. 2.4%
0%*
Crop
Residue
12.0%
Biomass
Pellets,
0%*
Firewood
14.7%
Kerosene
0.3%
Electricity, J
10.6%
Source: Dalberg 2014; NBS China 2008
"These fuels are not currently used at measurable quantities in the investigated countries, but are considered as potential future
fuels for cooking.
"DME = dimethyl ether, a gaseous fuel type from coal gasification. LPG = liquefied petroleum gas.
Figure ES-1. Current Cooking Fuel Mix in India and China
The following life cycle stages are analyzed for each fuel system:
• Production of the cookstove fuel feedstock, including all stages from extraction or
acquisition of the fuel feedstock from nature through production into a form ready
for processing into cooking fuel (e.g., cultivation and harvesting of sugarcane,
extracting crude oil from wells).
• Processing of the fuel into a form ready to be used in a cookstove.
• Distribution of fuels from the production site to the processing location and on to
a retail location or directly to the consumer. Distribution also includes bottling for
fuels stored in cylinders.
• Use of the fuel via combustion of the fuel or use of electricity in a cookstove,
including disposal of any combustion wastes or residues (e.g., ash).
Cookstove production and distribution, human energy expended during collection of fuels,
and the production, preparation, consumption, and disposal of food and food wastes are outside
the boundaries of this project. A previous LCA examining production of fuel-efficient cookstoves
found that the use phase significantly dominates life cycle greenhouse gas (GHG) emissions
regardless of the combusted cooking fuel type utilized (Wilson 2016); therefore, it is reasonable
to exclude processes associated with stove production and distribution from the study scope.
Results of the LCA are expressed in terms of a common reference unit, or functional unit.
As this analysis is a comparison of different fuels used to provide cooking energy, an energy
ES-2
-------
Executive Summary
functional unit is a proper basis of comparison. Therefore, the LCA results are based on useful
energy delivered for cooking: 1 GJ of useful energy delivered to the pot for cooking.
This study investigates bio-based and fossil-based cooking fuels as well as electricity (a
mix of fuel types) currently used at a measurable level of capacity in India or China, as
depicted in Figure ES-1. Cooking fuels not currently used, or used in only small quantities but
with future market potential in these two countries, are also assessed. The current fuel use
percentages are varied to show possible future cooking fuel mix scenarios for each country.
These cooking fuel scenarios were chosen through review of public sources discussing possible
changes in the fuels used within these countries, including the effect of policies that have been
or could be put in place to increase future use of specific fuels. Eight cooking fuel mix scenarios
were considered for India and for China (displayed in Table 1-5 and Table 1-8 of Chapter 1).
The scenarios focus on a feasible increase of cleaner burning fuels and a decrease of traditional
fuels, such as unprocessed biomass and dung cake, including:
• Increases in electricity used for cooking (used by induction cookstoves) in urban
areas,
• Increases in electricity using a cleaner electricity grid (e.g. grid decrease in coal
contribution and increase in contribution from natural gas, nuclear, hydropower,
and other renewable fuel sources such as wind power),
• Increases of liquefied petroleum gas (LPG) use in urban and/or rural areas, and
• Increases of other cleaner burning fuels such as biomass pellets, dimethyl ether
(DME), ethanol, and biogas, currently used in smaller amounts in each country.
These increases were based on the current urban or rural population that could possibly use
the fuels in each country. No increases/decreases greater than 20% were considered for long-term
changes to the use of cooking fuel. The cleaner electricity grid focuses on a decrease in coal use,
which currently accounts for over 70% of generated electricity in each country, while increasing
use of cleaner generation from hydropower, nuclear, natural gas, and wind.
Environmental impacts are presented and analyzed by life cycle stage - feedstock
production, fuel processing, distribution and use - to identify those stages responsible for the
largest impacts and therefore presenting the greatest opportunity for improvements. The
environmental analysis was conducted in accordance with the following voluntary international
standards for LCAs:
• International Standards Organization (ISO) 14040: 2006, Environmental
management - Life cycle assessment - Principles and framework (ISO 2010a); and
• ISO 14044: 2006, Environmental management - Life cycle assessment -
Requirements and guidelines (ISO 2010b).
The majority of life cycle inventory (LCI) data were extracted from existing studies in
publicly available academic literature. An LCI is an accounting of the material, energy, and water
inputs and the product, waste, emission, and water outputs for a particular product or process
ES-3
-------
Executive Summary
(Baumann and Tillman 2004). Detailed unit process LCI data were entered into the United States
Department of Agriculture (USDA) and U.S. EPA US Federal LCA Digital Commons LCI Unit
Process Templates (USDA and U.S. EPA 2015) and imported into OpenLCA software
(GreenDelta 2015) to calculate the life impact assessment results (LCIA). LCIA is the process
of translating emissions data contained in an LCI into environmental loads, which help users to
interpret cumulative environmental impacts of the studied system (Baumann and Tillman 2004).
The following ten impact assessment indicators are covered in this analysis:
1. Global Climate Change Potential (GCCP)
2. Cumulative Energy Demand (CED)
3. Fossil Depletion
4. Water Depletion
5. Particulate Matter Formation Potential
6. Photochemical Oxidant Formation Potential
7. Freshwater Eutrophication Potential
8. Terrestrial Acidification Potential
9. Ozone Depletion Potential
10. Black Carbon (BC) and Short-Lived Climate Pollutants
This suite of indicators addresses global, regional, and local impact categories of
relevance to the cookstove sector, such as energy demand driving depletion of bio-based and
fossil-fuel-resources, greenhouse gases (GHG) and black carbon emissions causing both short-term
and long-term climate effects. Of particular concern are those impact categories that directly
impact human health. These include emissions resulting in black carbon, particulate matter
formation, and photochemical oxidant formation, all of which can lead to eye irritation,
respiratory disease, increased risks of infection, and cancer (Goedkoop et al. 2008). Table 1-10
in Section 2 provides a description of each impact category along with the relevant units used to
report results. Results for each impact category are calculated using the ReCipe impact
assessment methodology (Goedkoop et al. 2008). Section 1.2.9 describes the methodology in
greater detail.
ES.3.1 Key Findings
Although this analysis is focused on the comparison of current and potential future fuel
mix scenarios, results by life cycle stage for individual fuel use in each country are also provided.
Investigating the impact of individual fuels provides insight into the differences in results observed
between each of the cookstove fuel mix scenarios. Table ES-1 and Table ES-2 depict the average
emissions factors for key pollutants across four broad cooking fuel types for India and China,
respectively. Emission values that contribute to the averages can be found in Appendix A in Tables
A-18 to A-28 and Tables A-44 to A-72 for India and China, respectively. These tables provide
context for the level of magnitude differences in emissions values between broad cooking fuel type
categories. Liquid and gas cookstove fuels typically have the lowest emission factors at point of
use and are generally considered "clean cooking fuels". Processed biomass fuels also lead to
relatively lower air emissions during cooking compared to coal and unprocessed biomass.
ES-4
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Executive Summary
Table ES-1. Average Emission Factors during Cooking (in kg/MJ) of Key Pollutants by
Cookstove Fuel Category for India
Cooking Fuel Category*
Processed
Emission
Fossil Solid
Liquid/Gas
Solid
Biomass
Unprocessed
Biomass
Carbon dioxide
0.86
0.12
0.29
0.89
Carbon monoxide
0.027
0.0012
0.029
0.041
Methane
0.0026
2.5E-05
8.8E-04
0.0042
Nitrogen oxides
5.5E-04
4.2E-05
1.5E-04
6.4E-04
Sulfur dioxide
0.0015
7.6E-05
3.5E-05
2.3E-04
Dinitrogen monoxide
4.4E-08
2.3E-04
8.0E-06
8.7E-05
Particulates, > 2.5 urn, and < lOum
0.017
7.8E-05
3.6-04
0.013
NMVOC**
0.0058
3.1E-04
0.011
0.0086
*Fossil-solid fuel includes only coal; Liquid/gas fuel values are a direct average of point-of-use
emissions forbiogas, ethanol, LPG (from natural gas and crude oil), and kerosene; Processed solid
biomass is a direct average of point-of-use emissions for charcoal and biomass pellets; and
unprocessed biomass is a direct average of point-of-use emissions for dung cake, firewood, and
crop residues.
Note: The table does not distinguish between biogenic and fossil emissions.
Sources: MacCarty 2009, Jetter et al., 2012, Singh et al. 2014.
**NMVOC = non-methane volatile organic carbon
Table ES-2. Average Emission Factors during Cooking (in kg/MJ) of Key Pollutants by
Cookstove Fuel Category for China
Cooking Fuel Category*
Emission
Fossil Solid
Liquid/Gas
Processed
Solid
Biomass
Unprocessed
Biomass
Carbon dioxide
0.58
0.13
0.26
0.69
Carbon monoxide
0.022
3.7E-04
9.0E-04
0.040
Methane
1.4E-03
2.0E-05
1.0E-04
0.0019
Nitrogen oxides
3.5E-04
8.8E-05
6.0E-05
4.2E-04
Particulates, < 2.5 um
8.0E-04
9.9E-06
9.0E-05
2.3E-03
* Fossil-solid fuel includes all coal types; Liquid/gas fuel values are a direct average of point-
of-use emissions for LPG, kerosene, DME, and natural gas; Processed solid biomass includes
biomass pellets; and unprocessed biomass is a direct average of point-of-use emissions for
firewood and crop residues.
Note: The table does not distinguish between biogenic and fossil emissions.
Sources: Zhang et al. 2000, Tsai et al. 2003, Jetter et al. 2012.
Tables describing summary impact results are included below. Color gradient coding is provided
to indicate the relative magnitude of results for each indicator across the fuels evaluated. Six bins
are defined to aid in quantifying the variation in impact scores that exist between the studied fuels.
Definitions of these bins are provided in Table ES-3.
ES-5
-------
Executive Summary
Table ES-3. Description of Bin Cut-offs for Summary Impact Results
Bin Description
Bin Color
Values > 5 times the median
Values between 2 and 5 times the median
Values between 1 and 2 times the median
Values between 0.5 and 1 times the median
Values between 0.1 and 0.5 times the median
Values <0.1 times the median
Table ES-4 depicts the environmental impact results by cooking fuel type for India, while Table
ES-5 shows the equivalent results for China. For an example of interpreting the tables, in Table
ES-4, the color coding indicates that biogas from dung generally has lower environmental impact
compared to other fuels. The exclusive presence of dark and medium green indicates that all of the
impact scores for this fuel are less than one half the median reported value for each
impact category. Unprocessed dung cake shows tradeoffs (i.e., comparatively low results for
fossil depletion, water depletion, and ozone depletion, but relatively high results for cumulative
energy demand, particulate matter, photochemical oxidants, eutrophication, and black carbon
compared to other fuels). While the colors applied show quantitative thresholds between
different results' ranges, they should not be interpreted as indicators of statistically significant
differences between cooking fuel types.
ES-6
-------
Executive Summary
Table ES-4. Summary Impact Results by Cooking Fuel for India
Per GJ Delivered Heat for Cooking
Global
Climate
Change
Potential
Cumulative
Energy
Demand
Fossil
Depletion
Water
Depletion
Particulate
Matter
Formation
Potential
Photochemical
Oxidant
Formation
Potential
Freshwater Terrestrial
Eutrophication Acidification
Potential Potential
Ozone
Depletion
Black
Carbon &
Short Lived
Climate
Pollutants
kg
C02eq
MJ
kg oil
eq
m3
kg
PMlOeq
kg NMVOC
eq
kgP eq
kg S02 eq
kg CFC-
11 eq
kg BC eq
Unprocessed
solid
biomass
Firewood
539
7,716
0.0064
0.049
4.72
6.02
0.16
0.40
2.6E-09
1.04
Crop
residue
132
9,670
0.0076
0.058
11.3
8.75
0.19
0.62
3.1E-09
2.42
Dung
cake
191
12,859
0.15
1.19
23.6
18.7
3.82
0.75
6.2E-08
5.01
Processed
solid
biomass
Charcoal
from
wood
572
10,209
0.12
0.63
19.5
10.5
0.28
0.21
4.5E-09
4.27
Biomass
pellets
134
2,039
6.25
35.6
0.21
0.24
0.0034
0.29
3.2E-07
0.020
Liquid/gas
Ethanol
from
sugarcane
95.7
6,507
18.3
88.6
0.17
0.34
0.037
0.50
6.3E-06
-0.0054
Biogas
from dung
10.5
1,820
0
1.04
0.077
0.11
0
0.11
0
0.0068
LPG from
natural
gas
292
1,391
36.1
26.7
0.12
0.62
0.0021
0.31
2.3E-06
5.5E-04
LPG from
crude oil
303
2,106
53.7
31.7
0.16
0.76
0.0029
0.33
2.0E-06
0.014
Kerosene
181
2,584
65.7
36.3
0.31
1.16
0.0033
0.40
2.4E-06
0.045
Other
Hard coal
963
13,778
243
16.6
19.3
7.86
0.0021
1.87
8.2E-07
3.91
Electricity
415
5,443
91.4
515
1.69
2.01
0.0034
4.00
1.4E-06
-0.019
All-Fuel Median 241 5,975 12.3 21.7 1.00 1.59 0.0034 0.40 5.7E-07 0.032
Sources: Compilation of results reported in Appendix B, Tables B1-B10. Individual source documents reported in Appendix B.
*PM10 = particulate matter up to 10 micrometers in size, CFC = Chlorofluorocarbon, NMVOC = non-methane volatile organic carbon, C02 = carbon dioxide,
S02 = sulfur dioxide, P = Phosphorus
ES-7
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Executive Summary
Table ES-5. Summary Impact Results by Cooking Fuel for China
Per GJ Delivered Heat for Cooking
Black
Carbon &
Global
Particulate
Photochemical
Short
Climate
Cumulative
Matter
Oxidant
Freshwater
Terrestrial
Lived
Change
Energy
Fossil
Water
Formation
Formation
Eutrophication
Acidification
Ozone
Climate
Potential
Demand
Depletion
Depletion
Potential
Potential
Potential
Potential
Depletion
Pollutants
kg
C02eq
MJ
kg oil eq
m3
kg
PMlOeq
kg NMVOC
eq
kgP eq
kg S02 eq
kg CFC-
11 eq
kg BC eq
Unprocessed
solid biomass
Firewood
281
6,538
0.0025
0.019
1.49
1.81
0.061
0.29
9.9E-10
0.30
Crop
residue
54.7
7,905
0.015
0.12
3.40
2.52
0.38
0.30
6.2E-09
0.69
Processed
Biomass
solid biomass
pellets
118
2,369
8.12
49.2
0.21
0.26
0.020
0.39
2.3E-07
0.011
LPG
188
2,784
64.4
57.1
0.20
0.40
0.0080
0.68
2.9E-05
-0.018
Kerosene
207
2,943
67.7
72.3
0.23
0.42
0.010
0.87
3.8E-05
-0.032
Liquid/gas
Natural
gas
213
2,049
48.6
5.77
0.057
0.23
6.8E-04
0.17
3.4E-05
-0.0022
DME
345
6,395
111
27.5
0.75
2.01
0.063
1.18
2.3E-05
0.054
Coal mix
1,014
10,506
179
44.5
1.81
2.33
0.11
3.72
6.4E-06
0.043
Other
Electricity
496
6,060
95.6
524
1.33
1.87
0.063
4.27
2.3E-06
-0.12
All-fuel Median 213 6,060 64 45 0.75 1.81 0.06 0.68 6.37E-06 0.011
Sources: Compilation of results reported in Appendix B, Tables B11-B20. Individual source documents reported in Appendix B.
ES-8
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Executive Summary
It is challenging to pin down a precise definition of what is considered a "clean" cooking
fuel. As Table ES-4 and Table ES-5 clearly demonstrate, the majority of cooking fuels exhibit
some trade-offs between impact categories. Biogas from dung is the only possible exception. Even
for biogas from dung, a designation cannot be made in absolute terms on the basis of this research
and any "clean" designations or comments regarding either favorable or unfavorable
environmental performance should be understood to be relative to the selection of studied fuels
within each country. In general, when this study refers to a fuel's favorable environmental
performance, this should be understood to indicate that its impact scores in the referenced impact
category were less than half of the median impact score. Conversely, if the study refers to a fuel
having poor or unfavorable environmental performance, this indicates that the impact score is
greater than two times the median impact score. Any deviations to these general interpretations are
clearly expressed in the body of this report, and only apply to the example they are immediately
referencing. These limitations should be kept closely in mind when interpreting the results as
presented throughout the remainder of this report.
Overall, the efficiency of fuel and stove combinations was found to be a key parameter
driving impact results in both countries. Fuels that can be used in stoves with higher efficiencies
(e.g., LPG, kerosene, biogas, ethanol, natural gas, electricity and biomass pellets) had generally
lower environmental impacts compared to low efficiency stoves burning traditional fuels (e.g.,
firewood, dung cake, crop residues, and coal).
In India, biogas consistently emerged as a low-impact fuel with all of its impact scores
being less than 50% of the all-fuel median in each category. None of the other fuels exhibit such
consistent environmentally preferable performance. Results for dung cake, firewood, charcoal, and
hard coal are often found on the lower end of environmental performance. All four of these fuels
have at least five of their ten impact scores that are over two times the median value associated
with the respective impact category. Biomass pellets as well as kerosene and LPG tend towards
favorable environmental performance with each fuel having six or more impact scores that are
better than the impact category median. Ethanol from sugarcane produces low impact scores in
GCCP, and the three major human health related impact categories (particulate matter formation,
photochemical oxidant formation and black carbon); however, higher water depletion impacts
were seen for this fuel since irrigation is required during cane production. This could be a particular
challenge in India, which is currently a water-stressed nation. The traditional fuels had particularly
high impacts for particulate matter formation and black carbon emissions.
In China, natural gas, biomass pellets, and LPG generally showed favorable environmental
performance relative to other fuels. Each of these fuels have impact scores that are better than the
median in eight or more of the ten impact categories. Coal has the lowest aggregate environmental
performance with five of its ten impact scores being over two times the median value for each
impact category. Since electricity generation in both China and India is dominated by coal, the
electricity impacts are influenced by coal production and combustion impacts. Water impacts were
also significant for electricity due to the contribution of hydroelectric power to the grid mix.
Establishment of dams for hydropower leads to notable evaporative losses.
Although many of the fuels used for cooking in India and China are considered "clean"
cookstove fuels, based on the reduced amount of emissions released at the point of use in the home,
the LCA reveals that for many of these fuels, lower emissions at point of use are offset by impacts
at the point of fuel production or processing. During the production or processing step, emissions
ES-9
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Executive Summary
may be released due to a thermal and/or chemical change to the feedstock, or from combustion of
fuels (or generation of electricity) required to process the feedstock. Even though the immediate
emission exposure risks to the person cooking are alleviated, emissions will still be released on a
regional or global basis at the location of production or processing. For example, use of electric
cookstoves ensures persons in the household are no longer exposed to direct emissions of the
particulates in wood smoke from traditional cookstoves. However, since over 70% of electricity
in India and China is generated from coal, there is a tradeoff between avoided wood smoke
emissions at point of use and emissions released from combustion of coal at the power plant, which
contribute to a variety of local, regional, and global environmental impacts. These tradeoffs are
best exemplified in the results by cooking fuel type reported in Sections 3.1 and 4.1. Given that
this study considers the full life cycle of cooking fuels rather than only point-of-use emissions,
usage of the term "clean" in this report diverges from this common usage, and should be considered
more comprehensive.
Given the magnitude of impacts resulting from the use of cookstoves on both the
environment and human health (e.g., photochemical smog, particulate matter emissions, and black
carbon impacts are all associated with a range of human health issues) it is important to consider
how future changes in cookstove fuel mix scenarios might affect these impacts. As previously
noted, eight potential fuel use scenarios were evaluated to explore how impacts in each of the ten
studied environmental impact categories may change in the future for shifts in the national mix of
cooking fuels.
Trends and observations about similarities and differences in LCA results for both India
and China include the following:
• Processed biomass energy sources such as biogas from dung in India and biomass
pellets in China perform well across many of the LCA results categories in
comparison to both traditional and fossil fuels. Scenarios where these fuels partially
displace traditional biomass show some promise of reducing point of use emissions
in the home that can be harmful to human health without significant tradeoffs such
as increased global climate change potential or water depletion.
• The production and use of coal requires the most energy and has the greatest
amount of GCCP impact. Therefore, any reduction of coal, either as a direct fuel
input for cookstoves or within the electricity grid, will result in a better
environmental footprint for cooking fuel use within either country.
• Increased use of LPG in the future could also result in lower impacts for most LCA
results categories in both countries. However, this is only true for certain scenarios
where LPG replaces the worst performing fuels such as dung in India and coal in
China.
• While increasing use of electric cookstoves will not decrease GCCP, CED, and
fossil depletion impacts in India due to the large share of electricity that is generated
from coal, replacing use of coal cookstoves with electric cookstoves in China does
result in reductions in these impact categories largely because the efficiency of the
electric cookstove is so much higher than the efficiency of the coal cookstoves used
ES-10
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Executive Summary
in the home, and because some portion of the grid electricity is derived from
cleaner, non-fossil sources such as hydropower.
• Finally, a large portion of CED and GCCP originates from the use phase of the life
cycle of the cooking fuels. The evaluated fuels have a range of heating values;
however, when cooking, the amount of useful energy delivered to the cookstove
depends not only on the energy content of the fuel, but also on the cookstove
efficiency. If the cookstove has a low efficiency, more fuel must be used to provide
a given amount of cooking energy. If more fuel is required due to the use of a low
efficiency stove, the benefits of using a fuel with a low environmental profile could
be offset.
This research built a framework model for examining the life cycle impacts of cookstove
fuels in developing countries. This framework model can serve as the basis for further
understanding the quantifiable tradeoffs between fuel choices to help spur initiatives to change
cooking fuel use patterns. The model can be continually improved upon as it is enhanced with
additional sensitivity and uncertainty analyses, and as more current data on cookstove fuel impacts
becomes publicly available.
ES.4.1 Report Organization Summary
The remainder of this report is organized as follows:
• Chapter 1: Goal and Scope Definition - Discusses the overall study goal and
scope, boundaries, and describes the LCA categories addressed in the study;
• Chapter 2: Process Descriptions and Methodology - Describes details of the
LCA methodology, including allocation, data sources, and description of the fuels
addressed in the study;
• Chapter 3: Life Cycle Assessment Results for India ~ Provides an analysis of
all environmental results for all individual fuels, as well as all fuel mix scenarios
for India;
• Chapter 4: Life Cycle Assessment Results for China ~ Provides an analysis of
all environmental results for all individual fuels, as well as all fuel mix scenarios
for China;
• Chapter 5: Conclusions and Next Steps - Describes the main LCA conclusions
for each country and discusses recommendations for future work;
• Chapter 6: References ~ Lists references used in this LCA;
• Appendix A: Detailed LCI Tables - Presents supporting LCI data and
information, including detailed tables of all energy and emissions data for all fuels
at each life cycle phase with associated citations; and
• Appendix B: Detailed LCA Result Tables - Presents LCA tables for each
individual fuel and all scenarios.
ES-ll
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Goal and Scope Definition
1. Goal and Scope Definition
1.1 Goal
The overall goal of this study is to conduct a transparent LCA for the U.S. Environmental
Protection Agency (U.S. EPA), in coordination with the Global Alliance for Clean Cookstoves
(the Alliance), to facilitate the comparison of the current fuel mix used and possible future changes
to the fuel mix used for cooking within India and China. The output of this effort will improve the
understanding of the comparative life cycle environmental impacts and benefits that can be
affected by choice of cookstove fuels. The current mix of the most common cookstove fuels for
each country, as well as eight possible fuel mix changes for China and for India, are evaluated.
The main study goals are to:
1. Determine the environmental burdens associated with current individual fuels used for
cooking within India and China on a life cycle basis using publicly available data
sources; and
2. Calculate the environmental impacts associated with use of the current and projected
cooking fuel mixes used in India and China.
The environmental impacts for each fuel are reported by life cycle stage: feedstock
production, fuel processing, distribution, and use in a cookstove including combustion and disposal
of residuals. For each of the two countries, the environmental impacts are calculated for the current
mix of cooking fuels used and compared to a number of possible projected changes (scenarios) in
the fuel mix profile.
The primary intended use of this study report is to provide comparative data to inform
policy decisions based on a more holistic analysis of changes in cooking fuels and stoves and the
associated changes in environmental releases both locally and globally. Environmental issues
surrounding cooking fuels are identified, along with opportunities to address these issues based on
the choices of cooking fuels. The study also identifies areas, such as cooking fuel types or life
cycle stages, where changes in the mix of fuels would be most beneficial in terms of reduced
energy use, water consumption or impacts associated with environmental emissions (e.g.,
emissions released to air, water, and land).
The study is conducted in accordance with the following voluntary international standards
for LCAs:
• ISO 14040: 2006, Environmental management - Life cycle assessment - Principles
and framework (ISO 2010a); and
• ISO 14044: 2006, Environmental management - Life cycle assessment -
Requirements and guidelines (ISO 2010b).
Audiences that may benefit from information developed through this research include,
but are not limited to local and national governments in China and India, donors and
investors (e.g., strategic planners), and researchers (e.g., sustainability scientists).
l-l
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Goal and Scope Definition
1.2 Scope of the Study
This section discusses the overall scope of the study necessary to accomplish the stated
goals. The LCA components covered include the functional unit, fuel systems studied, study
boundaries, scenario development, impact assessment methodology and data quality requirements.
1.2.1 Functional Unit
To provide a basis for comparison of different products, a common reference unit must be
defined. The reference unit is based upon the end function of the products, so that comparisons of
different products are made on a uniform basis. This common basis, or functional unit, is used to
normalize the inputs and outputs of the LCA. Results of the LCA are then expressed in terms of
this functional unit. As this analysis is a comparison of different fuels used to provide energy for
cooking, a functional unit of cooking energy delivered is a proper basis of comparison. For this
reason, the functional unit of this LCA is based on useful energy delivered: 1,000 megajoules (MJ)
(or 1 GJ) of useful energy delivered to the pot for cooking. Useful energy refers to energy that
goes into work and is not lost (e.g., through transmission or distribution or heat losses at the
cookstove).
1.2.2 Geographical Scope
The geographic scope of this analysis is fuels used in cookstoves in India and China. India
and China were selected because they are both Phase 1 Alliance countries, and fuel literature and
LCI data are available. Phase 1 countries are those for which the Alliance has mobilized resources
to grow the global market for clean cookstoves between 2012 and 2014. The Alliance selected
Phase 1 countries as top priorities for clean cookstoves based on the size of the impacted
population, the maturity of the market in each country, the magnitude of need, and the strength of
the partner (including government).
In both China and India, approximately half of each country's population currently uses
traditional cookstove fuels (i.e., coal and wood), and over a million annual premature deaths are
attributed to CAPs and HAPs released from combustion of these fuels. Consumption of traditional
cookstove fuels, combined with rapid rates of urbanization and industrialization, has contributed
to the countries' resource depletion, deforestation, desertification, and biodiversity loss. According
to the United Nations Convention to Combat Desertification, nearly 40% of the Asian continent is
arid, semi-arid, and dry sub-humid land, with 27% of China's land being desertified. Deserts are
expanding in both China and India (UNCCD 2015).
1.2.3 Transparency
The methods, standards, tools, and data upon which this study is based are all clearly
communicated in the report body or in the appendices. Raw life cycle inventory data are included
in Appendix A. Appendix B reports model output by impact category for each of the studied
scenarios. Using this information in combination with the freely available OpenLCA software tool
(GreenDelta 2015) will allow interested parties to recreate results using the reported methods.
Reporting of results both according to fuels and scenarios allows users the flexibility to explore
alternative scenarios that are not explicitly covered in this report. Reference material that was used
as source data for the LCA models is clearly documented in the Appendix A tables, and an effort
was made to prioritize the use of publicly available information from literature.
1-2
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Goal and Scope Definition
1.2.4 Fuel Systems Studied
This LCA considers the main cooking fuels currently used in India and China. Electricity,
which is generated from a mix of sources in each country, is also included. Table 1-1 lists the fuels
commonly used for cooking in these countries. The environmental impacts for each individual
fuel, as well as the current mix of cooking fuels used in each country, are calculated in this analysis.
This study also considers eight possible fuel mix changes for both China and India, representing
potential shifts to increased use of cleaner-burning fuels, as discussed in Section 1.2.6.
Table 1-1. Current Fuels Used for Cooking in China and India
Fuels Used for Cooking*
China
India
Fuel
(%)
(%)
Liquefied Petroleum Gas
31.10
25.20
Coal
28.90
1.90
Biomass
26.70
57.90
Electricity
10.60
0.40
Kerosene
0.30
3.20
Dung
0.00
10.60
All other Fuels
2.40
0.40
Total
100.00
100.00
Source: China: Dalberg 2014, NBS China 2008; India: Dalberg
2013, Venkataraman et al. 2010.
*Percentages based on fraction of population using fuel for
cooking.
Brief profiles for the primary cooking fuels used in India and China are provided below.
Typical emission profiles at point of cooking fuel use were previously presented in Table ES-1
and Table ES-2. More details on the fuels themselves, including fuel heating values and stove
thermal efficiencies by cooking fuel type, are presented in Section 2.2, while the fuel mix scenarios
are described in Section 1.2.6.
India Electricity Grid: A breakdown of fuels contributing to India's national grid mix is
depicted in Table 1-2. As of 2012, coal-fired electricity generation constitutes the majority of
India's electrical grid at over 70% (Table 1-2). Hydropower and gas each comprise approximately
10% of the grid. Indian power plants together consume approximately 530 million metric tons
(tonnes) of coal per year. Indian distribution losses are high at approximately 37% of generation.
Distribution losses refer to the loss of electricity in the grid, which occurs between the generating
plant and the point of consumption.
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Goal and Scope Definition
Table 1-2. Current Electricity Grid Mix in India
2011 Electricitv Production*
India
Production Type
(%)
Coal and Peat
71.10
Hydroelectric
11.20
Natural Gas
8.30
Nuclear
2.90
Wind
2.50
Oil
2.00
Biomass
1.70
Solar Photovoltaic
0.20
Waste
0.09
Total Production
100.00
Distribution Losses**
37.00%
Source: International Energy Agency (IEA) 2012.
*Percentages based on total Gigawatt hours electricity
produced from each fuel.
**Calculation: (DS-FC)/DS x 100, where DS = domestic
supply and FC = final consumption.
China Electricity Grid: The composition of the Chinese electricity fuel mix as of 2011 is
listed in Table 1-3. The electricity generation in China is comprised of nearly 80% coal and peat
with hydroelectric following at approximately 15% (Table 1-3). The remaining five percent of
China's electricity grid is generated from a mix of natural gas, nuclear, oil, biomass, and
renewables. Chinese power plants annually consume a total of about 2 billion tonnes combined of
bituminous coal (84%) and coke oven gas (10%), with less significant amounts of coking coal and
blast furnace gas. Distribution losses in the Chinese system amount to 22% of generated electricity.
Table 1-3. Current Electricity Grid for China
2011 Electricitv Production*
China
Production Type
(%)
Coal and Peat
79.00
Hydroelectric
14.80
Natural Gas
1.80
Nuclear
1.80
Wind
1.50
Biomass
0.70
Oil
0.20
Industrial Waste
0.20
Solar Photovoltaic
0.10
Total Production
100.00
Distribution Losses**
22.00%
Source: IE A 2011b.
*Percentages based on total Gigawatt hours electricity
produced from each fuel.
**Calculation: (DS-FC)/DS x 100, where DS = domestic
supply and FC = final consumption.
1-4
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Goal and Scope Definition
Liquefied Petroleum Gas is a clean burning gas, which is a co-product of the production
of natural gas (NG) and crude oil (hereafter referred to as "LPG from oil")) (GACC 2015). Both
India and China currently use substantial quantities of LPG, with the fuel comprising 25% and
31% of each country's current cooking fuel mix, respectively. Urban consumers have considerably
better access to LPG than do their rural counterparts.
Coal is a black solid fossil fuel that is often used in countries where stoves serve a dual
function of cooking and heating, such as China (GACC 2015). Twenty-nine percent of Chinese
cooking is currently done with stoves using various coal products. The use of coal in India is much
more limited, where it comprises only 1.9% of the current combustible fuel cooking mix. As
mentioned above, coal is the predominant fuel used for electricity generation in both countries.
Biomass includes various types of plant-derived fuels and is one of the largest energy
resources used for cooking in both China (26.7%) and India (57.9%). In China, a significant
portion of biomass cooking fuel is agricultural residues (e.g., rice straw and husk) (Jingjing et al.
2001). The majority of biomass cooking fuel in India is manually gathered firewood (e.g., acacia,
eucalyptus, sheesham, mango, etc.) (Singh et al. 2014a). Most biomass cooking fuel types (e.g.,
crop residues and firewood) currently used for cooking in India and China are unprocessed, with
the exception of biomass pellets and charcoal from wood. For charcoal, small local markets in
India carbonize wood in traditional earth mound kilns to increase the fuel's energy density and
ease of distribution (since charcoal is less bulky than the energy equivalent amount of firewood).
Non-carbonized processed fuels like biomass pellets, a densified form of traditional biomass, are
increasingly being used in developing countries.
Kerosene is a liquid product derived from crude oil. Kerosene is predominantly used for
cooking in urban households where it causes a high number of accidents each year due to its
flammability. Kerosene is used more widely in India, where it constitutes 3.2% of the current fuel
mix, compared to China, where it is only 0.3% of all cooking fuel. None of the study scenarios
anticipate expansion of kerosene use in coming years.
Dung, or animal waste, usually from cows, is used as an inexpensive fuel in rural areas.
While dung represents a renewable energy source, burning solid dung inside may lead to high
levels of harmful air emissions of particulate matter and volatile organic compounds (VOCs).
Dung is sparingly used as a cooking fuel in China; however, as a result of its wide availability in
rural India, dung accounts for 10.6% of total cooking fuel use in India. A number of the scenarios
for India explore the effect on life cycle environmental impacts if dung use is replaced by
alternative, cleaner burning fuels (Table 1-5).
Natural Gas is a gaseous clean burning fossil fuel that accounts for a small percentage of
China's current cooking fuel mix (2.4%). Piped natural gas is only available for urban customers
with access, unlike LPG which can be distributed to rural communities in cylinders. None of the
studied scenarios explore the potential expansion of natural gas use as a cooking fuel in
either country because natural gas comprises only a small portion of the cooking fuel mix
and its expansion is limited by accessibility issues. Inclusion of additional scenarios with
expansion of piped natural gas for cooking will be evaluated in a future study that builds
upon this study as discussed in Section 5.2.
1-5
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Goal and Scope Definition
Ethanol is a liquid fuel produced through the distillation of various agricultural products.
Ethanol is not currently understood to be used as a cooking fuel in either China or India. The use
of ethanol is explored in one of the study scenarios for India, due to the rapid expansion of global
ethanol production and its high thermal efficiency when used as a cooking fuel.
DME is a gaseous fuel that is a product of the coal gasification process. DME does not
currently comprise an appreciable portion of the cooking fuel mix in either country. The use of
DME is considered in fuel use scenarios for China, as it is derived from coal, which is widely
available in China, and the environmental, human health, and thermal performance of DME are
improved compared to an energy-equivalent amount of coal. Because hard coal only makes up
1.9% of cooking fuel consumption in India, DME was not considered as a cooking fuel option for
India.
1.2.5 System Boundary
This LCA focuses on a variety of current and potential future fuels for cookstoves in China
and India, as detailed above in Table 1-1 and below in Table 1-5 and Table 1-8. The following life
cycle stages are included for each fuel system:
• Production of the cookstove fuel feedstock, including all stages from extraction or
acquisition of the fuel feedstock from nature through production into a form ready
for processing into cooking fuel (e.g., cultivation and harvesting of sugarcane,
extracting crude oil from wells).
• Processing of the fuel into a form ready to be used in a cookstove.
• Distribution of fuels from the production site to the processing location and on to
a retail location or directly to the consumer. Distribution also includes bottling for
fuels stored in cylinders (e.g., LPG).
• Use of the fuel via combustion of the fuel or use of electricity in a cookstove,
including disposal of any combustion wastes or residues (e.g., ash).
Figure 1-1 provides the study boundaries for the baseline scenario for India and Figure 1-2
illustrates the study boundaries for the baseline scenario for China.
Fuel production and processing consists of all necessary steps, beginning at resource
extraction, which are required to make the fuel ready for use in a cookstove. For ethanol produced
from sugarcane, the fuel production stage includes impacts for growing and harvesting the
sugarcane, while the processing stage includes the steps to convert the harvested cane into ethanol.
Specific processing steps included in the analysis are described in greater detail for individual fuels
in Section 2.2. In the case of electricity, power generation as well as transmission and distribution
losses are incorporated in the system boundaries. Additionally, transportation requirements
between all life cycle stages within the boundaries of this study are accounted for. Cookstove
production and distribution, human energy expended during collection of fuels, and the production,
preparation, consumption, and disposal of food and food wastes are outside the boundaries of this
project. The rationale for excluding these stages is discussed in the next section (Section 1.2.5.1).
1-6
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Goal and Scope Definition
The use phase is modeled to reflect the combustion of the cooking fuels and fugitive
emissions during use. The types and quantities of air emissions associated with fuel use depend on
the fuel's elemental composition (e.g., average fixed carbon, ash content, and volatile matter) and
the cookstove technology or technology mix (e.g., thermal efficiency) for each country, which
affects the quantity of the fuel that must be consumed to deliver 1 GJ of cooking energy. At the
fuel end-of-life, solid residues from the combustion of cookstove fuels (bottom ash and carbon
char) are disposed. The major components of these wastes are determined by the type of fuel
combusted, but biomass fuel combustion typically results in ash containing silica, alumina,
calcium oxides, sodium, magnesium, and potassium. The disposal of these wastes is generally
modeled assuming land application. In land application, the wastes in question are spread out over
a landscape, often as an agricultural amendment, to ultimately be assimilated by the environment
through physical, chemical, and biological processes.
1-7
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Goal and Scope Definition
t N
I Food Production, |
| Preparation, and |
| Consumption j
Elementary Inputs from Nature
•Water
•Raw Materials
Intermediate Inputs
•Treated Water
•Energy
•Economic Goods
t ^
Cookstove
Production
Fuels for India
Electrical Grid
Hydropower
Natural Gas
Biomass
Wind & Solar PV
T
Cookstove Fuels
UnDrocessed Solid Biomass Mix
1. Firewood
2. Crop Residues
3. Dung Cake
Fuel Production
Generation of
Electricity
^ Lie
luid and Gas Fuels
1.
LPG
2.
Kerosene
3.
Biogas from Dung
4.
Ethanol from
Sugarcane
1
1. Coal Briquettes
Processed Solid Biomass
1. Biomass Pellets
2. Charcoal from Wood
Distribution
Transport
Distribution
Transport
Distribution Losses
Disposal of
Cookstove
Residues
Distribution to
Consumer
(e.g. Bottling)
Use of
Electricity/Fuel
in Cookstoves
1 GJ Useful
Energy
Within Study Boundary
— — Outside Study Boundary
"Human energy expenditures are
not included.
Elementary Outputs to Nature
•Water
•Airborne Emissions
•Waterborne Emissions
Intermediate Outputs
•Waste water to be Treated
•Economic Goods
•Solid Waste to be Managed
, —jr—%
I I
I Food Wastes ¦
Figure 1-1. Study Boundaries of the Baseline Scenario for India
1-8
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Goal and Scope Definition
Food Production,
Preparation, and
Consumption
T
Elementary Inputs from Nature
•Water
•Raw Materials
Intermediate Inputs
•Treated Water
•Energy
•Economic Goods
Cookstove
Production
Fuels for China
Electrical Grid
Hydropower
Natural Gas
Wind & Solar PV
Cookstove Fuels
Unprocessed Solid Biomass Mix
1. Firewood
2. Crop Residues
Processed Solid Biomass
1. Biomass Pellets
1. LPG
2. Kerosene
3. Natural Gas
. DME
Fuel Production
Generation of
Electricity
Coal Mix
1. Coal Powder
2. Coal Briquettes
3. Honeycomb Coal
Briquettes
Distribution
Transport
Distribution
Transport
Distribution Losses
Disposal of
Cookstove
Residues
Distribution to
Consumer
(e.g. Bottling)
Use of
Electricity/Fuel
in Cookstoves
1 GJ Useful
Energy
Within Study Boundary
— — Outside Study Boundary
*Fluman energy expenditures are
not included.
Elementary Outputs to Nature
•Water
•Airborne Emissions
•Waterborne Emissions
Intermediate Outputs
•Waste water to be Treated
•Economic Goods
•Solid Waste to be Managed
Food Wastes ¦
Figure 1-2. Study Boundaries of the Baseline Scenario for China
1-9
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Goal and Scope Definition
In addition to benchmarking the current fuel use for cookstoves in these two countries, a
goal of this study is to consider scenarios for changes in the mix of cooking fuels used or changes
in availability and utilization of cleaner burning fuels. Eight potential fuel mix scenarios affecting
the life cycle environmental profile of cookstove fuel use in each country's market are evaluated.
The details of these scenarios are described in Section 1.2.6.
1.2.5.1 System Components Excluded
The following components of each system are not included in this study.
Cookstove Production and Distribution. The focus of this study is the life cycle of fuels
used within all types of cookstoves in the country; therefore, all burdens associated with production
and distribution of the cookstoves themselves are excluded from the analysis. A previous LCA
examining production of fuel-efficient cookstoves found that the use phase significantly dominates
life cycle GHG emissions regardless of the combusted cooking fuel type utilized (Wilson 2016).
Therefore, the overall life cycle impacts of the stove relative to the fuel are assumed to be
negligible.
Human Energy Expended During the Collection or Use of Fuels. This analysis does
not include human biological energy or emissions. Shifts in the mix of fuels may decrease the
overall human energy and emissions expended during the distribution phase in some cases (e.g.,
shifting to fuels with higher energy density that are easier to transport, or that do not require
consumer transport, such as electricity). Such affects would be associated with a high degree of
uncertainty, and their benefits and burdens would be better captured by qualitative or analytical
methods apart from LCA.
Food and Food Wastes. The focus of this study is the life cycle of fuels used to cook the
food in the country; therefore, all burdens associated with production, preparation, storage,
consumption, and disposal of the food being prepared using the fuels are excluded from the
analysis.
Capital Equipment and Infrastructure. The energy and wastes associated with the
manufacture of capital equipment and infrastructure are excluded from this analysis, including
equipment to manufacture buildings, motor vehicles, and industrial machinery, as well as roads
and electricity distribution infrastructure used to distribute fuels throughout the supply chain and
to end users. In general, these types of capital equipment and infrastructure are used to produce
and deliver large quantities of product output over a useful life of many years. Thus, energy and
emissions associated with the production of these facilities and equipment generally become
negligible when allocated over the total amount of output or service over their useful lives
(Berglund 2006).
Stove Stacking. The transition from one cooking system to another does not always occur
instantaneously. In communities that are undergoing transitions to a new cooking fuel type, field
observations indicate that very often individual homes will initially use a mixture of new and
traditional cooking systems. This phenomenon, known as 'stove-stacking,' allows households to
take advantage of the differences that exist between the stove-fuel combinations that they employ.
While this would ultimately affect the pace of change and the attendant shift in environmental
impacts, it represents a dynamic force operating at a household level (Hiemstra-van der Horst and
1-10
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Goal and Scope Definition
Hovorka 2008) that lies outside of the study scope. This study focuses on scenarios encompassing
the national cooking fuel mix, which could include households using a mixture of fuels, although
this was not explicitly considered when developing the cooking fuel scenarios.
1.2.6 Scenario Development
As shown in Table 1-1, the baseline scenarios examine the most common fuels currently
used for cooking in India and China. However, initiatives to decrease citizens' exposure to indoor
air pollution are encouraging use of cleaner burning fuels such as biomass pellets or liquid and gas
fuels such as biogas, ethanol, and/or DME. Study scenarios were constructed based on insights
derived from the literature, as well as common opinions and logic regarding fuels that have been
traditionally considered to be "clean" or "dirty." The goal in creating these scenarios is to propose
reasonable scenarios that might be expected to yield environmental and human health benefits to
facilitate analyzing the performance of these scenarios from a life cycle perspective.
Increases in cleaner fuels were set at reasonable amounts or based on the current urban or
rural population that could possibly use the fuels in each country. No increases/decreases greater
than 20% were considered for long-term changes to the use of cooking fuel. Such reasonable
thresholds were set in the absence of detailed technological and economic feasibility studies
centered on the practical potential of future fuel scenarios. This section provides an introduction
to the current and potential future scenarios that are examined as a part of this analysis. Scenarios
for each country are described separately in the following two sections.
Fuel choice depends on geographic location, market and technology access, and socio-
economic parameters such as prosperity, education, and agro climatic conditions. Also, cooking
habits and taste considerations influence fuel choice, generally towards more traditional fuels
(Mainali et al. 2012). Access to some fuels may be limited, especially in remote rural areas.
Conversely, access to unprocessed fuels like biomass and dung is more limited in urban areas. This
includes access to electricity and LPG networks. LPG is distributed through pipelines in urban
centers where infrastructure exists. Where pipelines do not exist, LPG cylinders are available.
However, this fuel is less common in rural areas because of limited market access and high costs.
Although electricity is a possible source of cooking energy, electric cookstoves are not primary
fuel sources even in major cities (Mainali et al. 2012).
For each country and fuel source, the current average stove thermal efficiency per fuel type
is applied to the analysis. For China, this constitutes a weighted average of traditional and
improved stove efficiencies presented below in Table 1-9. A specific exploration of the benefits
of increasing thermal efficiency within a fuel type is an area for future research, as the work
considered within this study is focused on fuels. A more detailed analysis of the effect of stove
efficiency on LCIA results will be evaluated in a future study.
1.2.6.1 India Cooking Fuels
Table 1-5 presents the baseline current mix of cookstove fuels used, as well as eight
additional scenarios modeled in this LCA as potentially more sustainable cookstove fuel mixes
that could be used within India. The name of each scenario is abbreviated to facilitate presentation
and discussion of the results. The abbreviated names are presented in Table 1-4.
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Goal and Scope Definition
Table 1-4. Full and Abbreviated Scenario Names for India
Scenario
Brief Scenario Name
Full Scenario Name
Current
Current Cookstove Fuel Use
(1)
Increase Urban Electric
Increase of Electrical Use in Urban
(2)
Increase Urban LPG
Increase of LPG in Urban
(3)
LPG Replaces Biomass
Increase in LPG/ Decrease in Biomass in both Urban and Rural
(4)
Increase Clean Electric
Cleaner Electrical Grid with Increase in Urban
(5)
LPG Replaces Rural Biomass
Increase in LPG/ Decrease in Biomass & Dung in Rural
(6)
Increase Biomass Pellets
Increased Biomass Pellets/Decreased Biomass & Dung
(7)
Ethanol Replaces Biomass
Increased Ethanol/Decreased Biomass & Dung
(8)
Biogas Replaces Biomass
Increased Biogas/Decreased Biomass & Dung
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Goal and Scope Definition
Table 1-5. Cooking Fuel Mix Scenarios Evaluated for India
Fuels:
Current
Increase
Urban
Electric
Increase
Urban
LPG
LPG
Replaces
Biomass
Increase
Clean
Electric
LPG
Replaces
Rural
Biomass
Increase
Biomass
Pellets
Ethanol
Replaces
Biomass
Biogas
Replaces
Biomass
Scenario
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Hard Coal
1.90%
1.90%
1.90%
1.90%
1.90%
1.90%
1.90%
1.90%
1.90%
LPG from Natural Gas*
5.29%
5.29%
7.39%
9.49%
5.29%
9.49%
5.29%
5.29%
5.29%
LPG from Crude Oil*
19.91%
19.91%
27.81%
35.71%
19.91%
35.71%
19.91%
19.91%
19.91%
Kerosene
3.20%
3.20%
3.20%
3.20%
3.20%
3.20%
3.20%
3.20%
3.20%
Electricity
0.40%
10.40%
0.40%
0.40%
10.40%
0.40%
0.40%
0.40%
0.40%
Sugarcane Ethanol
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
10.00%
0.00%
Biogas from Cattle Dung
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
10.40%
Charcoal from Wood
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
0.40%
Biomass Pellets
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
10.00%
0.00%
0.00%
Firewood
49.00%
40.72%
40.72%
32.22%
40.72%
36.47%
44.97%
44.97%
44.97%
Crop Residue
8.90%
7.19%
7.19%
5.69%
7.19%
6.44%
7.94%
7.94%
7.94%
Dung Cake
10.60%
10.60%
10.60%
10.60%
10.60%
5.60%
5.60%
5.60%
5.60%
TOTAL
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
* LPG split between natural gas and crude oil based on statistics from the Government of India Ministry of Petroleum and Natural Gas Economics and Statistics
Division 2014.
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Goal and Scope Definition
Current Baseline Scenario
The current baseline scenario for India is based on 2014 data from the Alliance as presented
previously in Table 1-1. Approximately 70% of India's nearly 1.3 billion people lived in rural
areas in 2010, while the remaining 30% lived in urban areas (World Bank 2014). Nearly 70% of
these people, mostly those in rural areas, still rely on solid fuel feedstock for their cooking needs,
with their attendant human and environmental impacts. The current fuel mix in India is dominated
by the use of biomass, which constitutes 58% of all fuels used. It is assumed that 49% of this 58%
is firewood while the remaining 8.9% consists of crop residue. Dung and coal complete the sources
of solid fuel providing 10.6% and 2.3% of the fuel mix, respectively. LPG is also used extensively
at the national level, at just over 25% of households. Kerosene is used in much more limited
quantities (3.2% of the fuel mix). Unlike China, electricity is only very sparsely used for cooking
in India.
Potential Future Scenarios
A variety of social and environmental issues have spurred interest in shifting the
composition of the national cooking fuel mix in India. The emission of GHGs from direct
combustion of fuels in household stoves can be significant due to the large percentage of the
population engaging in such activities and the lack of any form of emission controls on residential
cookstoves. Emissions of particulate matter have a particularly detrimental effect on human health.
For these and additional reasons, including the significant amount of time required for rural
individuals, mainly women, to gather firewood or dung, this research proposes eight scenarios that
explore the benefits and burdens associated with a variety of shifts in the cooking fuel mixture.
Greater reliance on electricity is explored as it moves combustion out of the home, thereby
decreasing human health impacts at the point-of-use. Increased use of LPG is explored due to its
high stove thermal efficiencies, clean emissions profile, and user convenience (Dalberg 2013).
Biomass pellets provide an attractive option as they leverage existing resources in a more efficient
manner. Biogas also offers the opportunity to utilize an existing resource, dung, more effectively
by boosting cookstove thermal efficiency. Sugarcane ethanol as a cooking fuel is explored due to
the industries presence in India and interest on the part of the government to expand production
(Tsiropolous et al. 2014). A move towards higher stove efficiencies is common to the majority of
study scenarios. Stoves with higher thermal efficiencies not only require less fuel to deliver the
same amount of useful cooking energy, but also often produce fewer undesirable products of
incomplete combustion. Table 1-6 displays the average thermal efficiencies modeled for the stoves
used for various cooking fuels for the Indian context. The study scenarios for India are outlined
above in Table 1-5 and are described below.
1. Increase Urban Electric: This scenario explores the effects of increasing the use of
electricity as a cooking fuel. The use of electricity is assumed to increase from its
current level of 0.4% to a high of 10.4%. The use of both firewood and crop residue
are decreased to adjust for the additional electricity use. Firewood use decreases by a
little over eight percent of the total fuel mix while the share of crop residue in the fuel
mixture decreases by 1.71%. In this scenario the composition of the fuel mix that is
used to generate electricity stays consistent with that in the current scenario (Table 1-2).
Electric stoves are assumed to have the highest thermal efficiency of any of the
cookstoves considered.
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Goal and Scope Definition
2. Increase Urban LPG: In this scenario the use of LPG is increased from 25.2% to
35.2% of the national cooking fuel mix. The majority of the additional LPG is modeled
as produced from crude oil (79%), while the remainder is produced from natural gas.
Traditional sources of biomass, firewood and crop residue, are reduced corresponding
to the increase in LPG.
3. LPG Replaces Biomass: This scenario proposes an even more dramatic increase in
the use of LPG, to supply 45.2% of India's cooking energy needs. The share of biomass
fuels (firewood and crop residues) in the fuel mix is decreased to approximately 38%.
4. Increase Clean Electric: This scenario is the same as the baseline electric scenario
except that the scenario assumes that a cleaner electricity grid mix is used. The details
of the cleaner grid are presented in Table 2-3.
5. LPG Replaces Rural Biomass: As in the previous scenario (3), LPG use is increased
to 45.2% of the cookstove fuel mix. In this scenario a share of the displaced demand
comes from dung, which is reduced to 5.6% of the fuel mix. Firewood accounts for
36% of the fuel mix. Crop residue is decreased from a high of 8.9% in the current
scenario to 6.44% in this scenario.
6. Increase Biomass Pellets: This scenario targets the increased thermal efficiency of
biomass when it is utilized in pelletized form. Pelletized biomass increases from zero
to 10% of the Indian cooking fuel market. Traditional firewood, crop residue, and dung
cake are all displaced by the increased use of pelletized biomass.
7. Ethanol Replaces Biomass: This scenario introduces the use of ethanol as a cooking
fuel within the Indian context. In this scenario, ethanol distilled from sugarcane is
assumed to provide energy for 10% of India's cooking needs. The use of dung is
decreased by nearly half. Reduced use of firewood represents the remainder of
displaced demand.
8. Biogas Replaces Biomass: The final scenario introduces the use of biogas which is
produced in anaerobic digesters using animal dung as a feedstock. Biogas use increases
from 0.4% of the fuel mix to 10.4% in this scenario. As in the previous scenario, the
increase in biogas displaces use of solid dung and firewood.
Table 1-6. Thermal Efficiencies Modeled for Indian Cookstoves
Fuels:
Stove Thermal Efficiency
Source
Hard Coal
15.50%
LPG from NG
57.00%
Singh et al. 2014a
LPG from Oil
57.00%
Kerosene
47.00%
Electricity
67.00%
Berick 2006
Sugarcane Ethanol
53.00%
MacCarty 2009
Biogas from Cattle Dung
55.00%
Singh et al. 2014a
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Goal and Scope Definition
Table 1-6. Thermal Efficiencies Modeled for Indian Cookstoves
Fuels:
Stove Thermal Efficiency
Source
Charcoal from Wood
17.50%
Singh et al. 2014a
Biomass Pellets
53.00%
Jetter et al. 2012
Firewood
13.50%
Crop Residue
11.00%
Singh et al. 2014a
Dung Cake
8.50%
Note: Stove thermal efficiencies modeled are based on the average mix of stove technologies currently in use in
India and are not representative of specific stoves.
1.2.6.2 China Cooking Fuels
Table 1-8 presents the baseline current mix of cookstove fuels used, as well as eight
additional scenarios modeled in this LCA as potentially more sustainable cookstove fuel mixes
that could be used within China. The rationale for the scenario fuel mixes is described in the
Potential Futures Scenarios subsection. The name of each scenario has been abbreviated to
facilitate presentation and discussion of the results. The abbreviated names are presented in Table
1-7.
Table 1-7. Full and Abbreviated Scenario Names for China
Scenario
Brief Scenario Name
Full Scenario Name
Current
Current Cookstove Fuel Use
(1)
Increase Electric
Increase of Electrical Use in Urban
(2)
LPG Replaces Biomass
Increase in LPG/ Decrease in Biomass in both Urban and
Rural
(3)
LPG Replaces Coal
Increase in LPG/ Decrease in Coal in Rural
(4)
Increase Clean Electric
Cleaner Electrical Grid with Increase in Urban
(5)
Increase Biomass Pellets
Increase Biomass Pellets/ Decrease Biomass & Coal
(6)
Increase DME
Increase DME/ Decrease Biomass & Coal
(7)
Coal Swap
Increase Coal Briquettes/ Decrease Coal Powder
(8)
Ag Replaces Wood
Increase Agricultural (Ag) Residues/ Decrease Fuel & Brush
Wood
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Goal and Scope Definition
Table 1-8. Cooking Fuel Mix Scenarios Evaluated for China
Fuels:
Current
Increase
Electric
LPG Replaces
Biomass
LPG Replaces
Coal
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal Swap
Ag Replaces
Wood
Scenario
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
Coal Mix
28.90%
8.90%
28.90%
8.90%
8.90%
18.90%
18.90%
28.90%
28.90%
Biomass Mix
26.70%
26.70%
6.70%
26.70%
26.70%
16.70%
16.70%
26.70%
26.70%
LPG
31.10%
31.10%
51.10%
51.10%
31.10%
31.10%
31.10%
31.10%
31.10%
Kerosene
0.30%
0.30%
0.30%
0.30%
0.30%
0.30%
0.30%
0.30%
0.30%
Electricity
10.60%
30.60%
10.60%
10.60%
30.60%
10.60%
10.60%
10.60%
10.60%
Natural Gas
2.40%
2.40%
2.40%
2.40%
2.40%
2.40%
2.40%
2.40%
2.40%
Biomass Pellets
0.00%
0.00%
0.00%
0.00%
0.00%
20.00%
0.00%
0.00%
0.00%
DME
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
20.00%
0.00%
0.00%
TOTAL
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
100.00%
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Goal and Scope Definition
Current Baseline Scenario
The current fuel mix scenario for China is based on 2014 data from the Alliance as
presented previously in Table 1-1. Approximately 47% of China's 1.4 billion people lived in rural
areas in 2013, and the remaining 53% lived in urban areas (NBS China 2008). More than half of
these people, mostly those in rural areas, still rely on solid fuel feedstock for their cooking needs,
with their attendant human and environmental impacts. The current fuel mix in China is dominated
by the use of three fuels: LPG, coal, and biomass. Each of these fuels comprise slightly less than
one third of total fuel use. Nearly 11% of the population uses electricity as a cooking fuel. Small
percentages of the population use kerosene or natural gas.
Potential Future Scenarios
A variety of social and environmental reasons exist for shifting the composition of national
cooking fuel mixes in China. The emission of GHGs from direct combustion of fuels in household
stoves can be significant due to the large percentage of the population engaging in such activities
and the lack of any form of emission controls on residential cookstoves. Lack of emission controls
on cookstoves also contributes to the exposure of individuals in the home to particulate matter,
which is detrimental to both human and environmental health. For these and additional reasons,
including the significant amount of time that rural individuals, mainly women, spend gathering
biomass or dung, this research proposes eight scenarios that explore the benefits and burdens
associated with a variety of shifts in the cooking fuel mixture.
Greater reliance on electricity is explored as it moves combustion out of the home, thereby
decreasing human health impacts at the point-of-use. Increased use of LPG is explored due to its
high stove thermal efficiencies, clean emissions profile, and user convenience (Dalberg 2013).
Biomass pellets provide an attractive option as they leverage existing resources in a more efficient
manner. Similarly, the increased use and production of coal briquettes allows the Chinese to
continue utilizing their extensive coal resources in a way that is more efficient and protective of
human health (Zhang et al. 2000). DME also leverages China's coal supplies. DME production
has been expanding rapidly in recent years (Yang and Jackson 2012), and it provides the
opportunity to produce electricity as a by-product (Larson 2004). A move towards higher stove
efficiencies is common to the majority of study scenarios. Table 1-9 depicts the traditional and
improved thermal efficiencies modeled for the stoves used for various cooking fuels for the
Chinese context. The study scenarios, illustrated in Table 1-8, are described below.
1. Increase Electric: This scenario explores the effects of increasing the use of electricity
as a cooking fuel. The use of electricity is assumed to increase from its current level of
10.6%) to a high of 30.6%>. Coal use is assumed to decrease by a corresponding amount,
while the rest of the fuels stay fixed at the levels present in the baseline scenario. In
this scenario the composition of the fuel mix that is used to generate electricity stays
consistent with the composition in the current fuel mix scenario.
2. LPG Replaces Biomass: This scenario also proposes an increase in the use of LPG,
however instead of replacing coal, LPG is used in place of solid biomass fuels. A
portion of this replacement is assumed to happen in both rural and urban locations.
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Goal and Scope Definition
3. LPG Replaces Coal: The impacts of increasing the use of LPG by 20% are explored
in this scenario. The level of LPG use is assumed to increase from 31.1% to 51.1% as
a fraction of the fuel mix. The shift in LPG use acts as a substitute for coal in the current
scenario, which decreases from 28.9% to 8.9% of the fuel mix.
4. Increase Clean Electric: Like scenario (1), this scenario proposes a 20% increase in
the use of electricity as a cooking fuel. Again, the increased use of electricity is
assumed to replace the burning of solid coal. The only difference between the scenarios
is that the increased electricity use in this scenario is modeled based on a cleaner grid
mix. A detailed comparison of the current and cleaner grid mix for China is presented
in Chapter 2 (Table 2-4).
5. Increase Biomass Pellets: This scenario leverages the increased thermal efficiency
that is realized when traditional biomass sources are converted into a pelletized form
(Table 1-9). Pelletized biomass is assumed to compose 20% of the cooking fuel mix in
this scenario. The use of both non-pelletized biomass and coal is each decreased by
10%) each (in the total fuel mix).
6. Increase DME: The use of DME is increased from a low of zero percent in the current
fuel mixture to a high of 20% in this scenario. As in scenario (5), the increase substitutes
for equal shares of traditional biomass and coal use.
7. Coal Swap: This scenario explores the environmental effect of changing the form of a
fuel rather than substituting a different fuel. As shown in Table 1-9, a cookstove is able
to extract much more useful energy from a given quantity of coal when it is consumed
in briquettes versus a powdered form. Because the form of coal used (e.g., powder,
briquette, honeycomb briquette) is not specified in Table 1-8, the percent breakdown
by fuels remains the same for the baseline scenario and scenario (7); however, results
for the two scenarios (presented in Chapter 4) show differences related to the change
in the form of coal used.
8. Ag Replaces Wood: In this scenario one form of biomass, agricultural residues, is
substituted for another, fuel and brush wood. The total amount of biomass in the fuel
mixture remains constant however. Unlike other scenarios where the increased fuel is
used in a stove with higher efficiency, the increased use of agricultural residues to
replace fuel wood leads to a decrease in stove thermal efficiency.
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Goal and Scope Definition
Table 1-9. Thermal Efficiencies Modeled for Chinese Cookstoves
Fuels:
Stove Thermal Efficiency
Traditional Improved
Source
Coal Mix
22.3%
23.3%
Zhang et al. 2000
Coal Powder
14.3%
17.3%
Coal Briquettes
37.1%
27.2%
Honeycomb Coal Briquettes
23.4%
31.4%
Biomass Mix
15.2%
16.7%
Fuel & Brush Wood
19.2%
16.3%
Ag Residues
10.3%
17.2%
LPG
45.2%
42.1%
Kerosene
44.8%
45.9%
Singh et al. 2014a
Electricity
67.0%
Barick 2006
Natural Gas
53.7%
60.9%
Zhang et al. 2000
Biomass Pellets
53.0%
Jetteret al. 2012
DME*
46.0%
Zhang et al. 2000
*Coal gas stove efficiency is used as a proxy forDME stove efficiency. Note: Stove thermal efficiencies modeled
are based on the average mix of stove technologies currently in use in China and are generally not representative of
specific stoves.
1.2.7 Data Sources Summary
The majority of LCI data were extracted from existing studies in publicly available
academic literature. Table A-3 through Table A-72 in Appendix A contain detailed LCI inventory
data for the life cycle stages modeled for each fuel system. Each table cites the sources for the data
used. The data were constructed and data quality was scored according to the procedures
established in the project Quality Assurance Project Plan (QAPP) "Quality Assurance Project
Plan for Comparative Life Cycle Assessment of Cooking Fuel Options in China and India",
approved August 25, 2014.
1.2.8 Data Requirements
ISO standards 14040 and 14044 detail various aspects of data quality and data quality
analysis. These ISO Standards state: "descriptions of data quality are important to understand the
reliability of the study results and properly interpret the outcome of the study (ISO 2010a, 2010b)."
These ISO Standards list three critical data quality criteria: time-related coverage, geographical
coverage, and technology coverage. The following subsections discuss these three critical data
quality criteria and the typical specifications associated with high quality data. Appendix A, Table
A-2, adapted from Weidema and Wesnaes (1996), discusses all data quality criteria evaluated (the
three critical criteria identified by the ISO Standards along with additional criteria identified by
U.S. EPA).
The geographic scope of this study is fuel used in China or India, However, some fuels or
upstream inputs to fuel production/processing are imported from other regions of the world. High
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Goal and Scope Definition
quality data and information for geography-dependent processes (e.g., energy production) were
obtained from country-specific articles and databases. Data for technology-based processes are
based on the most recent average country-specific technology mix (e.g., the current production
methods China employs for mining and processing coal). It is more difficult to evaluate data
quality for future technologies not yet in use or that currently have a small market share. When
more specific information was not available, data quality for future technological processes was
based on current technological processes used in the same country. For example, for a scenario
with increased use of natural gas to produce electricity in China, the future natural gas production
is modeled assuming China will produce natural gas in the future using the same methods it
currently employs.
High quality temporal data are typically temporal data that are less than six years from the
reference year (2013 for this project), with the highest quality temporal data less than three years
from the reference year. A difference of six years meets the top two data scores for temporal
correlation as identified in Appendix A (Table A-2). In some cases, this goal was met, while in
many cases the available data sources do not meet the temporal data quality goals. Projected
scenarios are modeled with the same temporal parameters (e.g., electricity grid fuel mix) as
scenarios that exist in today's operating landscape. In this way, differences in environmental
results for fuel mix scenarios are focused on material and process differences for the fuels (and
associated stove efficiencies) rather than influence from other factors not directly related to the
change in fuel mix.
The data quality scores assigned to each unit process are recorded in Table A-4 through
Table A-72.
1.2.9 Life Cycle Impact Assessment Methodology and Impact Categories
The full inventory of atmospheric and waterborne emissions generated in an LCA study is
lengthy and diverse, making it difficult to interpret system differences in individual emissions in a
concise and meaningful manner. Life Cycle Impact Assessment helps with interpretation of the
emissions inventory. LCIA is defined in ISO 14044 Section 3.4 as the "phase of life cycle
assessment aimed at understanding and evaluating the magnitude and significance of the potential
environmental impacts for a product system throughout the life cycle of the product (ISO 2010b)."
In the LCIA phase, the inventory of emissions is first classified into categories in which the
emissions may contribute to impacts on human health or the environment. Within each impact
category, the emissions are then normalized to a common reporting basis, using characterization
factors that express the impact of each substance relative to a reference substance.
Characterization factors have been defined to quantify the impact potential of LCI results.
There are two main methods to developing LCIA characterization factors. The 'midpoint' method
links LCI results to categories of commonly defined environmental concerns like eutrophication
potential and global climate change potential. The 'endpoint' method further models the causality
chain of environmental stressors to link LCI results to environmental damages (e.g., final impacts
to human and ecosystem health). ISO standards allow the use of either method in the LCIA
characterization step. Overall, indicators closer to the inventory result (midpoint indicators) have
a higher level of scientific consensus, as less of the environmental mechanism is modeled.
Conversely, endpoint and damage-oriented characterization models inevitably include more
aggregation, or more assumptions (e.g., about fate and transport, exposures/ingestion, etc.). To
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Goal and Scope Definition
reduce uncertainty in communication of results, this LCA focuses on indicators at the midpoint
level.
1.2.9.1 Scope of Impact Assessment
This study addresses global, regional, and local impact categories of relevance to the
cookstove sector, such as air emissions leading to human health issues, energy demand driving
depletion of bio-based and fossil-fuel-resources, and GHG and BC emissions causing both short-
term and long-term climate effects. For most of the impact categories examined, the ReCiPe
impact assessment method is utilized to represent global conditions (Goedkoop et al. 2008).
Characterization factors, which are developed on the basis of established impact pathways, form
the basis of impact assessment methods such as ReCiPe. An impact pathway is a series of
quantifiable relationships that can be used to link LCI emissions to units of environmental impact
(e.g. kg CCh-eq for GCCP). Characterization factors in ReCiPe were originally developed for
global or European conditions and are not specific to China or India. Currently, no established
LCIA method exists for the China or India scope. For the category of GCCP, a global impact,
contributing elementary flows are characterized using factors reported by the Intergovernmental
Panel on Climate Change (IPCC) in 2013 with a 100 year time horizon (IPCC 2013).
Considerations for biogenic carbon accounting are covered in Section 2.4 and Section 2.5. BC and
co-emitted species are characterized to BC - equivalents (eq) based on a novel method recently
released by the Gold Standard Foundation (GSF) (GSF 2015). A detailed discussion of the BC
methodology is presented in Section 2.6. In addition, some inventory results are incorporated in
the results reported in the analysis as:
• Cumulative energy demand: this indicator is not an impact assessment, but rather
is a cumulative inventory of non-renewable energy extracted and renewable energy
utilized. The energy demand includes processing energy, transportation energy, and
feedstock energy.
• Water depletion: this indicator is not an impact and is assessed only as an inventory
item. It represents consumptive use of water.
A summary of the LCI and LCIA categories and methods used in this study are presented
in Table 1-10. While this study focuses on environmental impacts and does not include impact
categories which focus exclusively on human health, a number of included emission types are
closely associated with both environmental and human health impacts. These include emissions
leading to black carbon, particulate matter formation, and photochemical oxidant formation, all of
which can lead to eye irritation, respiratory disease, increased risks of infection, and cancer.
Linking these emissions definitively to human health impacts would introduce a higher level of
uncertainty to the study results. Human health impacts are dependent not only on emission
quantities, but also on the fate and transport of the emitted substances and the concentrations and
pathways by which organisms are exposed to these substances. These detailed types of exposure
information are not tracked in an LCI, requiring additional assumptions about the environmental
mechanism to be made by the developer of the LCIA methodology. So while human health impacts
are not explicitly estimated by this study, pertinent impact categories related to known human
health impacts of cookstove use are included in the analysis. The results of this study could inform
a more detailed assessment of the human health impacts from exposure to direct or indirect
emissions from the cookstove fuel life cycle.
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Goal and Scope Definition
Table 1-10. Environmental Impact Category Descriptions and Units
Impact/Inventory
Category
Description
Unit
Global Climate
Change Potential
The global climate change potential impact category represents the heat
trapping capacity of GHGs over a 100 year time horizon. All GHGs are
characterized as kg CO2 equivalents according to the IPCC 2013 5th
Assessment Report global wanning potentials.
kg C02 eq
Cumulative
Energy Demand
The cumulative energy demand indicator accounts for the total usage of
non-renewable fuels (natural gas, petroleum, coal, and nuclear) and
renewable fuels (such as biomass and hydro). Energy is tracked based on
the heating value of the fuel utilized from point of extraction, with all
energy values summed together and reported on a MJ basis.
MJ
Water Depletion
Water depletion results, in aligmnent with the ReCiPe impact assessment
method, are based on the volume of fresh water inputs to the life cycle of
the assessed fuels. Water may be used in the product, evaporated or
returned to the same or different water body or to land. If the water is
returned to the same water body, it is assumed the water is returned at a
degraded quality. Water consumption includes evaporative losses from
establishment of hydroelectric dams.
m3
Black Carbon and
Short-Lived
Climate Pollutants
BC, formed by incomplete combustion of fossil and bio-based fuels, is
the carbon component of particulate matter (PM) 2.5 that most strongly
absorbs light and thus has potential short-term (e.g., 20-year) radiative
forcing effects (e.g., potential to contribute to climate wanning). Organic
carbon (OC) is also a carbon component of PM and possesses light-
scattering properties typically resulting in climate cooling effects. PM
from the cookstove sector is typically released with criteria pollutants,
such as carbon monoxide (CO), nitrogen oxides (NOx), and sulfur oxides
(SOx), which may result in additional wanning impacts or exert a cooling
effect on climate. This indicator characterizes all PM and co-emitted
pollutants to BC equivalents depending on the relative magnitude of
short-tenn wanning or cooling impacts. The BC method is based on the
novel GSF method (GSF 2015).
kg BC eq
Particulate Matter
Formation
Potential
Particulate matter fonnation results in many negative health impacts such
as effects on breathing and respiratory systems, damage to lung tissue,
cancer, and premature death. Primary pollutants (including PM2.5) and
secondary pollutants (e.g., SOx and NOx) leading to particulate matter
fonnation are characterized here as kg PM10 eq based on the ReCiPe
impact assessment method.
kg PM10 eq
Terrestrial
Acidification
Potential
Tenestrial acidification potential quantifies the acidifying effect of
substances on their enviromnent. Important emissions leading to
tenestrial acidification include SO2, NOx, and NH3. Results are
characterized as kg SO2 eq according to the ReCiPe impact assessment
method.
kg SO2 eq
Freshwater
Eutrophication
Potential
Freshwater eutrophication assesses the potential impacts from excessive
load of macro-nutrients to the enviromnent and eventual deposition in
freshwater. Pollutants covered in this category are all P based (e.g.
phosphate, phosphoric acid, phosphorus), with results characterized as kg
P eq based on the ReCiPe impact assessment method.
kgP eq
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Goal and Scope Definition
Table 1-10. Environmental Impact Category Descriptions and Units
Impact/Inventory
Category
Description
Unit
Photochemical
Oxidant (Smog)
Formation
The photochemical oxidant formation (e.g. smog formation) potential
results determine the formation of reactive substances that cause harm to
human health and vegetation. Results are characterized here to kg of
NMVOC eq according to the ReCiPe impact assessment method. Some
key emissions leading to photochemical oxidant formation include CO,
methane (CH4), NOx, NMVOCs, and SOx.
kg NMVOC
Ozone Depletion
Potential
Measures stratospheric ozone depletion. Important contributing emissions
include CFC compounds and halons. It is likely that ozone depletion is of
lower importance for cookstoves fuels compared to other impact
categories. There will be differences between stove options as fossil fuels
generate ozone depleting emissions within their supply-chain that are
absent in the biomass options. However, the ozone depletion category has
become less critical following the regulation of the worst offending ozone
depleting chemicals.
kg CFC-11 eq
Fossil
Depletion
Fossil depletion captures the consumption of fossil fuels, primarily
coal, natural gas, and crude oil. All fuels are normalized to kg oil eq
based on the heating value of the fossil fuel and according to the ReCiPe
impact assessment method.
kg oil eq
1-24
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Process Descriptions and Methodology
2. Process Descriptions and Methodology
2.1 Overview
This section provides descriptions of fuel production for each cooking fuel analyzed for
use in India and China. It also discusses the methodology used for allocations performed for a
number of fuels in this analysis. Discussions of the impact assessment considerations for biogenic
carbon accounting, non-renewable forestry calculations and the BC indicator are also provided.
Finally, a high level discussion of the model framework built for this project is provided at the end
of this section.
2.2 Life Cycle Inventory Data for Current and Potential Fuels Used in India and China
No new unit process datasets were produced for this LCA analysis. LCI unit process data
were either acquired or adapted from publicly available sources. Table A-4 through Table A-72 in
Appendix A provide detailed LCI values, data quality scores and citations for each value used in
the modeling for each fuel. The level of granularity available for each cooking fuel type is
dependent on the level of detail reported in the utilized literature sources. For India, cookstove
modeling assumptions are largely based on work conducted by Singh and colleagues (2014) for
all cookstove fuels except sugarcane ethanol and biomass pellets. Sugarcane ethanol production in
India is derived from a study by Tsiropoulos and colleagues (2014), with combustion impacts
calculated from laboratory tests by Aprevecho Research Center (Barick 2006, MacCarty 2009).
For the Chinese cookstove fuels, fuel modeling data are primarily from work by Zhang and
colleagues (2000). Combustion emissions of volatile organic compounds (VOCs) for Chinese fuels
were further speculated based on research by Tsai et al. (2003). For both China and India, biomass
pellet production is from work by Jungbluth and colleagues (2007a), while combustion of the
pellets is modeled based on emission and stove efficiency profiles from Jetter, et al (2012).
Documentation of the processed cookstove fuel heating values is provided in the next section,
followed by a discussion on the supply chain for each fuel. Upstream processes such as transport
and ancillary material inputs are modeled using information from the National Renewable Energy
Laboratory's (NREL's) US Life Cycle Inventory (US LCI) Database and ecoinvent v2.2. The US
LCI is a publicly available LCI source specific to US conditions (NREL 2012) and ecoinvent v2.2
is a private Swiss LCI database with data for many global unit processes (Ecoinvent Centre 2010).
Where possible, these upstream databases are adapted to the geographic scope of interest, i.e., by
linking process electricity requirements to the country-specific grid mix.
2.2.1 Processed Fuel Heating Values
The higher heating values (HHVs) employed in the LCA model for India and China are
shown in Table 2-1 and Table 2-2, respectively. Associated cookstove thermal efficiencies for
each country and fuel combination were previously provided in Table 1-6 and Table 1-9 for India
and China, respectively.
2-1
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Process Descriptions and Methodology
Table 2-1. Heating Values of Cooking Fuels in India
Cooking Fuel Type
HHV (MJ/kg)
Source
Firewood
15.8
Singh et al. 2014a
Crop Residue
14.6
Singh et al. 2014a
Dung Cake
13.3
Singh et al. 2014a
Charcoal Briquettes from Wood
27.9
Singh et al. 2014a
Biomass Pellets
17.9
Singh et al. 2014a & Jetter et al. 2012
Ethanol from Sugarcane
28.3
MacCarty 2009
Biogas from Dung
18.2
Singh et al. 2014a
LPG
53.4
Singh et al. 2014a
Kerosene
49.0
Singh et al. 2014a
Hard Coal
16.3
Singh et al. 2014a
Table 2-2. Heating Values of Cooking Fuels in China
Cooking Fuel Type
HHV (MJ/kg)
Source
Firewood
15.3
Zhang et al 2000
Crop residue
14.0-14.5
Zhang et al 2000
Biomass Pellets
15.9
Jungbluth et al. 2007a
LPG
49.0
Zhang et al. 2000
Kerosene
49.0
Singh et al. 2014a
Natural Gas
51.3
Zhang et al. 2000
DME
28.4
Zhang et al. 2000
Hard Coal
13.9
Zhang et al. 2000
2.2.2 Electricity
The electricity mix is based on the average electricity mix from the IEA for India (2012)
and for China (201 lb). The electricity modules include estimates of distribution losses, which are
substantial for both countries: 22% for China and 37% for India. The mix of fuels in the electrical
grid is presented in Table 2-3 for India, and in Table 2-4 for China. These tables also provide the
electrical grid fuel mix projections used to model a cleaner future electricity grid in each country.
The cleaner electricity grid focuses on a decrease of coal use, which is currently used at a rate of
over 70% to produce electricity in each country, while increasing cleaner fuels such as
hydropower, nuclear, natural gas, photovoltaics (PV), and wind. The electric stove thermal
efficiency modeled for both countries is 67% (Barick 2006).
Table 2-3. Current and Cleaner Electricity Grids for India
Fuels:
Current India Electrical Grid
Cleaner India Electrical Grid
Coal
71.07%
59.07%
Oil
2.01%
2.01%
Natural Gas
8.33%
14.33%
Biofuels
1.72%
1.72%
Nuclear
2.92%
4.92%
Hydro
11.16%
14.16%
Solar PV
0.19%
0.19%
Wind
2.51%
3.51%
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Process Descriptions and Methodology
Table 2-3. Current and Cleaner Electricity Grids for India
Fuels:
Current India Electrical Grid
Cleaner India Electrical Grid 1
Waste
0.09%
0.09%
TOTAL
100.00%
100.00%
Sources: IEA 2012.
Table 2-4. Current and Cleaner Electricity Grids for China
Fuels:
Current China Electrical Grid
Cleaner China Electrical Grid
Coal
79.0%
59.0%
Oil
0.20%
0.20%
Natural Gas
1.80%
7.80%
Biomass
0.70%
0.70%
Nuclear
1.80%
3.80%
Hydro
14.8%
24.8%
Solar PV
0.10%
0.10%
Wind
1.50%
3.50%
Waste
0.20%
0.20%
TOTAL
100.00%
100.00%
Source: IEA 2011b.
2.2.3 Liquefied Petroleum Gas
In India, 21% of LPG is assumed to be produced from natural gas and 79% from crude oil
(MPNG 2014). For India LPG from NG, natural gas extraction is based on drilling, metering,
testing and servicing of oil wells and production data of Oil and Natural Gas Corporation (ONGC),
the largest oil company in India. Eighty-four percent of natural gas in India comes from offshore
sources and 16% is from onshore sources. LPG production is based on the scenario of an LPG
production line of ONGC Uran Gas fractionating plant located near Mumbai, India. Natural gas is
transported to the gas fractionating plant by pipeline (500 km from onshore, 250 km from
offshore). Processing requirements are allocated to the outputs from LPG production on a direct
mass basis. The bottling stage is modeled based on the per-day production scenario of Indian Oil
Corporation Limited (IOCL) Barkhola bottling plant located in Assam, India. This plant is one of
the recent state-of-the art bottling plants commissioned by IOCL and is considered representative
of bottling plants in India. LPG is bottled in steel cylinders (Singh et al 2014a). Incoming transport
of natural gas to the bottling plant is 60% by rail (1000 km) and 40% by heavy duty vehicle (500
km). The bottled LPG is then transported 750 km by heavy duty diesel vehicle to the distributor
and 100 km by light duty diesel vehicle from the distributor to retail.
For the 79% of LPG produced from crude oil, the India model considers only the domestic
production of refined petroleum fuels. The exclusion of overseas crude oil is not expected to impact
findings significantly because only the extraction stage is impacted (not the refining stage), and
Indian companies engage in extraction of crude oil following globally accepted practices and
operational standards -equivalent to overseas oil companies (Singh et al. 2014a). Onshore crude
oil is 30% of refinery inputs, and is transported 1000 km by rail to the refinery; offshore crude oil
makes up 70% of the inputs and is first transported 500 km to the port, then 60% is transported
2-3
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Process Descriptions and Methodology
1000 km by rail to refineries and 40% is transported 500 km to refineries by heavy duty diesel
vehicle (Singh et al. 2014a). Mass allocation is used to partition petroleum refining burdens to
different refinery products. Once the LPG reaches the bottling plant, the supply chain is equivalent
to that modeled for the NG LPG supply chain.
LPG production for China is based on two Swiss refineries for the year 2000. Electricity
grid mix and rail transport are adapted to the China geographic scope. The bottling stage is
simulated based on the model created for India.
2.2.4 Kerosene
For the India kerosene model, only the domestic production of petroleum refining products
is considered. The exclusion of overseas crude oil is not expected to impact findings significantly
because only the extraction stage is affected (not the refining stage), and Indian companies engage
in extraction of crude oil following globally accepted practices and operational standards
equivalent to overseas oil companies. Onshore crude oil (30% of refinery inputs) is transported
1000 km by rail to the refinery; offshore crude oil (70% of the inputs) is first transported 500 km
to the port, then 60% is transported 1000 km by rail to refineries and 40% is transported 500 km
to refineries by heavy duty diesel vehicle. Mass allocation is used to partition petroleum refining
burdens to different refinery products. Thirty percent of kerosene is assumed to be transported
1000 km by rail, while the remaining 70% travels the same distance by way of heavy duty diesel
vehicle. All kerosene is transported in a light duty diesel vehicle 100 km from the distributor to
retail. The kerosene pressure stove efficiency is 47%. Similar to LPG, the bottling stage is
simulated based on the per-day production scenario of the IOCL Barkhola bottling plant located
in Assam, India. Kerosene is bottled in steel cylinders (Singh et al. 2014a).
For China, production of petroleum products is adapted to the China geographic scope
using a refinery dataset in ecoinvent (Ecoinvent Centre 2010). The data set includes all flows of
materials and energy for throughput of one kilogram of crude oil in the refinery. The multi- output
process 'crude oil, in refinery' delivers the co-products gasoline, bitumen, diesel, light fuel oil,
heavy fuel oil, kerosene, naphtha, propane/ butane, refinery gas, secondary sulfur, and electricity.
The impacts of processing are allocated to the different products on a mass basis. Electricity grid
mix and rail transport are adapted to the China geographic scope. The bottling stage is simulated
based on the per-day production scenario of the IOCL Barkhola bottling plant located in Assam,
India. Kerosene is bottled in steel cylinders. Incoming transport to the bottling plant is 60% rail
(1000 km) and 40% heavy duty vehicle (500 km). All bottled kerosene is modeled as being
transported 750 km by heavy duty diesel vehicle to the distributor where it travels a further 100
km by light duty diesel vehicle from the distributor to retail. Kerosene is combusted in wick and
pressure stoves.
2.2.5 Coal
In India, coal for cookstove use is modeled as produced in an open cast surface mine.
Surface mines account for over 80% of total coal production in India, and almost 100% of the coal
grades used for cooking. The consumption of coal for cooking is primarily in areas near coal mines,
with an average transport distance of 100 km (rail). Coal is combusted in a metal stove. The coal
ash remaining after combustion, as well as the mining overburden, is assumed to be disposed in
landfills.
2-4
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Process Descriptions and Methodology
In China, coal is used in a variety of forms, including unprocessed, washed and dried,
powdered, formed into briquettes, or formed into honeycomb briquettes. Coal is combusted in
metal and brick stoves (both traditional and improved) which have efficiencies assumed to range
from 14% - 37% depending on the fuel/stove technology combination (Zhang et al. 2000). The
coal ash remaining after combustion, as well as the mining overburden, is assumed to be disposed
in landfills. The process also includes estimated emissions due to leaching from coal heaps into
groundwater at storage sites.
2.2.6 Firewood
Typical tree species used for firewood in India are acacia, eucalyptus, sheesham and
mango. Forty-one percent of firewood cooking fuel in India is estimated to be non-renewable,
based on trends in forest land area, renewable biomass generation on forest land, and demand for
cooking firewood as discussed in Section 2.5 (FAO 2010, Drigo 2014). Firewood is assumed to
be collected manually and combusted in a traditional mud stove. The remaining ash is modeled as
land applied.
In China, cooking fuel wood is harvested from mature trees or large branches (e.g.,
eucalyptus, acacia, oak, pine, poplar, willows, etc.), obtained manually from local forest and sun-
dried. Brush wood, or thin branches of brush which normally grow faster than trees, that is obtained
locally is also assumed to be sun-dried and held in a large storage room for a minimum of four
weeks prior to use. About 43% of firewood from China is estimated to be non-renewable, based
on trends in forest area, renewable biomass generation on forest land, and demand for firewood
for cooking. Fuel wood and brush wood are assumed to be collected manually and combusted in
traditional and improved brick and metals stoves. The remaining ash is modeled as land applied.
2.2.7 Crop Residues
In India, residues from crops such as rice, wheat, cotton, maize, millet, sugarcane, jute,
rapeseed, mustard, and groundnut are burned by households. Crop residues are modeled as
manually collected, air dried but not further processed, and combusted in traditional mud stoves.
In China, residues from maize, wheat, and rice are modeled as manually collected and combusted
in traditional and improved brick and metal stoves. In both countries, the ash remaining after stove
use is assumed to be land applied.
2.2.8 Biomass Pellets
For pellets, biomass species mixes are specific to each country. It is assumed that biomass
species (85% firewood, 15% crop residues) typical for use in India are manually collected from
local areas and pelletized via motorized machinery operated with electricity by small-scale
manufacturers. Approximately 41% of the wood input (85% of total biomass pellet composition)
is calculated to be non-renewable, which equates to approximately 35% of feedstock being non-
renewable. Manual collection and small-scale mechanized pelletization are also assumed for
China. In China, approximately 43% of the wood and brush inputs (56% of national biomass
market mix) are estimated to be non-renewable, which equates to approximately 24% of
feedstock being non-renewable. The processing energy and distribution transport are adapted
from Austria and central Europe. Electricity is required for pelletization and is modeled using
representative grids for the Indian and Chinese geographic scopes, respectively (IEA
2011b, 2012). Some
2-5
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Process Descriptions and Methodology
incoming transport to pelletization (rail and truck) is included. The model for emissions from
biomass pellet combustion is based on laboratory testing results.
2.2.9 Charcoal from Wood
In India, charcoal is produced from wood in a traditional earth mound kiln. The charcoal
yield from the kiln is modeled as 30%, and the combustion residuals are land applied. As with
other wood fuels in India, 41% of the wood the charcoal is derived from is assumed to be non-
renewable. The firewood is assumed to be collected and brought to the charcoal kiln manually.
Charcoal is modeled as combusted in a metal stove. Charcoal is an informal manufacturing sector
in India, and it is assumed charcoal is used for cooking only by those living near charcoal kilns.
No notable use of wood based charcoal was found for cooking in China (Singh et al. 2014a).
2.2.10 Dung
The dung of stall fed cattle and buffaloes is converted into dung cake primarily by women
who mix the manually collected dung with residual feed (e.g., straw, wood chips). Dung cake is
combusted in a traditional mud stove with a low thermal efficiency. The remaining ash after
combustion is modeled as land applied. Dung cake is a significant fuel source for cooking only in
India.
2.2.11 Ethanol
Ethanol production and processing is modeled based on the data provided by Tsiropoulos
and colleagues (2014). In India, sugarcane cultivation practices are almost exclusively manual,
with the exception of plowing, which is modeled as partially mechanized in some states. Pre- and
post-harvest burning of straw is not practiced in most of India. Sugarcane is transported 12 km by
truck to the sugarcane mill. The output products of the conventional sugar mill are sugar, molasses,
and electricity from surplus bagasse. Conventional mills represent 75% of the sugar production in
India. Bagasse provides all necessary energy requirements at the mill as well as surplus electricity,
which is considered a useful co-product to replace grid electricity in India. Sugarcane ethanol is
then produced from the molasses. This study considers a weighted average of ethanol distilleries
as standalone distilleries and as adjacent to sugar refineries. Molasses is transported on average 75
km to the ethanol plant. Sugarcane ethanol production energy is also provided by bagasse. The
model is based on a hydrous ethanol yield (for 95% ethanol by volume) of 84.7 liters/tonne of cane
and an ethanol density of 0.789 kg/L. All ethanol is assumed to be transported 750 km by heavy
duty vehicle to the distributor and 100 km by light duty vehicle from the distributor to retail.
Sugarcane ethanol combustion emissions are based on laboratory testing, rather than field results
(e.g., actual measurements from cookstoves in use within India). Sugarcane ethanol is not
considered as a cooking fuel in China, as sugarcane production is less prevalent in China than it is
in India based on Food and Agricultural Organization (FAO) statistics from 2012.
2.2.12 Biogas
This study considers a two cubic meter household type fixed dome anaerobic digester (AD)
operating in continuous feeding mode for 350 days/year and 10 years operational life (UN 2007).
The AD is loaded with 19.3 kg/day of fresh dung mixed with small quantities of water to produce
1.31 rnVday of biogas (Singh et al. 2014a). Leakage is the source of fuel production emissions.
Approximately one percent of biogas (methane) generated is assumed to leak from the system
2-6
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Process Descriptions and Methodology
(Afrane 2011, Boijesson 2006). Digested slurry is a useful co-product and is stored for application
in land farming. The AD is located at the home where the fuel is used (distributed through piping
running from the digester to the home).
2.2.13 Natural Gas
Natural gas extraction is based on Russian production data and long-distance pipeline
transport of natural gas to China. Energy requirements for operation of the gas pipeline network
are adapted from an Italian company data set in ecoinvent for delivery of natural gas to consumers
via pipelines (Ecoinvent Centre 2010). The total leakage rate, modeled as 1.4% for long-distance
pipeline transport, is based on European data (Ecoinvent Centre 2010). The electricity grid mix
and rail transport are adapted to the China geographic scope. Piped natural gas is not a major
cookstove fuel in India.
2.2.14 Dimethyl Ether
DME is modeled as produced from coal gas and delivered to rural China via a long-distance
pipeline network followed by bottling close to end consumers (see Larson 2004 for description of
DME production and distribution process). The process technology, coal gas produced from coke
oven gas, is adapted from ecoinvent for the Chinese geographic scope. Transport of the coal gas
from plant to rural consumer is via high pressure network. DME is assumed to be burned in a
standard multiple-burner gas range; the combustion profile for this fuel/cookstove technology
combination reflects use of only one burner, and is based on laboratory testing results. The fuel is
available in bottles and remains in gaseous form under normal atmospheric conditions. DME is
considered as a cooking fuel only for China, since coal (the fuel DME is derived from) is not
widely used for cooking in China. While DME is not currently used as a cooking fuel type in
China, the production technology is well understood (Larson 2004). Pursuit of DME as a cooking
fuel in India is considered unlikely due to the current low prevalence of coal as heat source for
cooking.
2.3 Allocation Methodology
For processes that produce more than one useful output, allocation is required. No single
allocation method is suitable for every scenario. The method used for handling product allocation
will vary from one system to another but the choice of allocation is not arbitrary. ISO 14044,
Section 4.3.4.2 states that "the inventory is based on material balances between input and output.
Allocation procedures should therefore approximate as much as possible such fundamental
input/output relationships and characteristics (ISO 2010b)." In this analysis, the baseline method
used for modeling multi-output product processes with one primary product and one or more
unavoidable co-products is the "cut-off approach. Under this approach, all burdens are assigned
to the primary product. The cut-off method is outlined in detail in the 1993 EPA Life Cycle
Assessment: Inventory Guidelines and Principles document (Baumann and Tillman 2004).
Processes in the cookstove fuel life cycle requiring allocation include crop residues and
other products generating co-products. For instance, production of sugarcane ethanol may result
in a net production of electricity from the combusted bagasse. For crop residues, burdens begin at
collection of the biomass from the field; all cultivation burdens are assigned to the primary crop.
For co-produced electricity from ethanol production, credits associated with exporting electricity
2-7
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Process Descriptions and Methodology
are considered outside the system boundaries. The digested slurry from the biogas production in
the AD may also be used as a fertilizer for supporting household crop production. The benefits
realized from increased nutrients available from the land applied digested slurry are not captured
in the impact assessment in this work. Multiple allocation methods exist and may have a significant
influence on results. The Next Steps Section of this study (Section 5) describes potential allocation
sensitivity analyses anticipated to be conducted for the above mentioned multi-output product
systems in the next phase of the research.
2.4 Biogenic Carbon Accounting
In biomass fuel systems, CO2 is removed from the atmosphere and incorporated into the
plant material that is harvested from the forest or field. This (biogenic) carbon is stored in the
material throughout the life of the product until that fuel is combusted or degrades, at which point
the carbon is released back into the environment. Combustion and degradation releases are
predominantly in the form of CO2 and CH4. This study, in alignment with the IPCC methodology,
assumes a net zero impact for biogenic carbon that is removed from the atmosphere in the form of
CO2 and later returned to the atmosphere, e.g., as CO2 emissions from the combustion of biomass
cookstove fuels. That is, if the carbon removed from the atmosphere is returned to the atmosphere
in the same form, the net impact GWP is zero. Impacts associated with the emission of biogenic
carbon in the form of CH4 are included since CH4 was not removed from the atmosphere and its
global warming potential (GWP) is 28 times that of CO2 when applying the IPCC 2013 100a LCIA
method. The one exception to this is the CO2 emissions from non-renewable wood fuel in China
and India associated with deforestation and, therefore, long-term reduction of global CO2 sinks.
The method used to calculate the non-renewable portion of wood for cooking fuel is described in
the next section.
2.5 Non-Renewable Wood Fuel Calculations
In the GHG analysis, the carbon dioxide emissions for the portion of the biomass fuel from
unsustainable use of wood fuel are considered non-renewable, and, therefore incorporated into the
overall GCCP results. The calculations for the renewable and non-renewable supply of wood for
cooking fuel use were based on a multi-step approach outlined by Singh and colleagues (2014).
First, the biomass stock in m3 for each country (from FAO 2010 Table 10) was multiplied by the
regional factor for tonnes of above-ground biomass (AGB) per m3 (from FAO 2010 Table 2.18)
to calculate the tonnes of AGB. The amount of below-ground biomass (BGB) was calculated by
multiplying the tonnes of AGB by the regional factor for BGB/AGB (from FAO 2010 Table 2.18).
The amount of dead wood was then calculated using the regional factor for dead-to-live biomass
ratio (from FAO 2010 Table 2.18) applied to the total AGB and BGB. Next, the average annual
increase or decrease in forest land for each country was calculated based on the carbon stocks in
living forest biomass reported for each country in 2000 and 2010 (from FAO 2010 Table 11). The
annual firewood supply potential for each country was then calculated as the total weight of AGB
and dead wood multiplied by country-specific factors for the percent accessibility to forests (from
the Yale WISDOM Database (Drigo 2014)) and the country-specific average annual change in
forest land.
The annual demand for firewood cooking fuel (tonnes) for each country was calculated
based on the country-specific cooking energy demand per household multiplied by the number of
households using wood for cooking fuel, divided by the cooking energy per kg of firewood
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Process Descriptions and Methodology
(calculated as the lower heating value of firewood multiplied by stove efficiency). For India, 11.0
MJ of cooking energy are consumed per household per day (Habib et al. 2004), with 105 million
rural households and 16 million urban households using wood for cooking fuel (Singh et al. 2014).
In China, 13.6 MJ of cooking energy are consumed per household per day (Zhou et al. 2007), with
over 131 million rural households and over nine million urban households using wood for cooking
according to World Bank statistics. Finally, the renewable percentage of cooking firewood was
calculated as the annual firewood supply potential divided by the total annual demand for cooking
firewood. The percentage of annual firewood demand that cannot be met by the annual firewood
supply potential was considered non-renewable.
2.6 Black Carbon and Short-Lived Climate Pollutants Calculations
This section summarizes key physical parameters considered in the approach to include the
differences in potential amounts of BC, organic carbon (OC), and other co-emitted species
produced from use of the investigated cookstove/fuel technologies. BC and co-emitted species are
formed by combustion of fossil and bio-based fuels (e.g., diesel, coal, crop residues).
Per the Gold Standard Framework method (GSF 2015), fuel production, transport, and
consumption life cycle phases are included in the inventory and impact assessment. An inventory
of BC and OC is based on the quantity of particulate matter (less than or equal to 2.5 microns of
aerodynamic diameter-PM2.5) released for each inventory step in the cookstove fuel/technology
life cycle. In many cases, LCI data sources do not specify the type of PM emissions (e.g., outputs
are reported as 'particulate matter' or 'particulate matter, unspecified'). For upstream process
inventories where PM emission speciation is not provided, no BC and/or OC emission factors are
applied. However, co-emitted species emission factors for these processes are included. In the
foreground cookstove fuel combustion, BC and OC emission factors based on quantity of PM
released (e.g., per fraction reported as PM2.5) are applied. Where no size distinctions between PM
emissions have been made in LCI data sources, all PM emissions from fuel combustion are
assumed to be of the fine particle variety, e.g., of less than or equal to 2.5 microns in size.1
Carbon in PM2.5 emissions takes the following forms: 1) organic carbon; 2) Elemental
carbon (EC), which usually includes soot; and 3) carbonate ion (C03"2). Methods which measure
light absorption in PM2.5 assume that the light absorbing component is BC and partitioning of EC
and OC is somewhat arbitrary. Though some components of OC may be light-absorbing (e.g.,
brown carbon or BrC), most researchers presume that OC possess light-scattering properties (e.g.,
producing climate cooling effects). Because there is high uncertainty and lack of consensus on the
ratio BrC class of OC compounds for each fraction of OC, analyzing impacts of BrC in OC is
excluded in this analysis and instead focus is placed on the EC or soot portion and the OC portions
of the PM2.5 emissions. In other words, BC emissions may be estimated by assuming that only
the EC portion of the PM2.5 emissions contributes to BC release and subsequent positive radiative
forcing, while OC emissions are assumed to contribute to negative radiative forcing. This approach
requires estimating the PM2.5 emission amount and source-specific EC-to-PM2.5 and then the
BC-to-OC ratio for each of the fuel/stove technologies being investigated in the study.
1 Per Bay Area Air Quality Management District (2008) "Secondary PM and combustion soot tend to be fine
particles (PM 2.5), whereas fugitive dust is mostly coarse particles".
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Process Descriptions and Methodology
Potential climate forcing impacts resulting from BC/OC and co-emitted species include
direct, albedo, and other indirect effects. Overall, most estimates indicate BC yielding a net
warming effect on climate but co-emitted species can have some offsetting effects, as discussed
below. Species co-emitted with BC/OC such as carbon monoxide (CO), NMVOCs, nitrogen
oxides (NOx), and sulfur dioxide (SO2) are pre-cursors to the formation of sulfate and/or organic
aerosols in the atmosphere. These aerosols affect reflectivity and other cloud properties and have
a cooling affect.
BC and other short lived climate pollutants (SLCPs) such as the aforementioned co-emitted
species are distinguished from other climate-forcing emissions (e.g., GHGs) in that their
atmospheric lifetime is not as long-lived, so potential impacts are estimated on a shorter time-scale
and can be very geographic and seasonally dependent (unlike long-lived, well-mixed GHGs).
However, short-lived forcing effects of BC are substantial compared to effects of long-lived GHGs
from the same sources, even when the forcing is integrated over 100 years. The GCCP of BC and
co-emitted species included in this approach are calculated using GWP 20-year BC eq. factors
from IPCC 2013 as summarized in Table 2-5.
Table 2-5. Characterization Factors for BC eq
Included in GSF 2015
GWP(20) per IPCC 2013
BC eq
BC
2421
1
Wanning Effects
NOx
16.7
0.00690
CO
5.9
0.002
NMVOC
14
0.006
Cooling Effects
oc
-244
-0.1
S04 (-2)
-141
-0.058
Sources: IPCC 2013 and GSF 2015.
2.7 LCA Model Framework
All LCI unit processes developed for this work (summarized in Appendix A) were input
into the US Federal LCA Digital Commons Life Cycle Inventory Unit Process Templates (in MS
Excel format) (USDA and U.S. EPA 2015). To build the life cycle model, the unit processes were
imported into the open-source OpenLCA software (Version 1.4.2, GreenDelta 2015) directly from
the US Federal LCA Digital Commons Life Cycle Inventory Unit Process Templates using an
OpenLCA plug-in. The OpenLCA model was reviewed to ensure that all inputs and outputs,
quantities, units, and metadata were correctly imported. Associated metadata for each unit process
was recorded in the unit process templates and imported into OpenLCA along with the model
values.
Once all necessary data were imported into the OpenLCA software and reviewed, system
models were created for each fuel and country combination. The models were reviewed to ensure
that each elementary flow (e.g., environmental emissions, consumption of natural resources, and
energy demand) was characterized under each impact category for which a characterization factor
was available. The draft final system models were also reviewed prior to calculating results to
make certain all connections to upstream processes and weight factors were valid. LCIA results
2-10
-------
Process Descriptions and Methodology
were then calculated by generating a contribution analysis for the selected fuel product system
based on the defined functional unit of 1 GJ of delivered heat for cooking.
2-11
-------
Life Cycle Assessment Results for India
3. Life Cycle Assessment Results for India
This section presents cookstove fuel LCA results for India first by individual cooking fuel
type, followed by fuel mix scenario.
3.1 Results for India by Cooking Fuel Type
The following ten sections provide the results analysis of the LCI and LCIA categories for
the individual fuels used within India. Results are provided in graphical format in this section and
companion tables for each figure are provided in APPENDIX B: DETAILED LCA RESULTS
TABLES. The impact scores depicted here are based on LCI data catalogued in APPENDIX A:
DETAILED LCI UNIT PROCESS TABLES.
3.1.1 Global Climate Change Potential
Figure 3-1 displays the GCCP results for India for each cookstove fuel included in this
study. Fossil fuel GCCP impacts are dominated by combustion emissions in the cookstove use
stage. Coal has the highest impacts, since it is derived from non-renewable carbon and the thermal
efficiency of coal stoves (15.5%) is relatively low compared to stoves for the other fossil fuel
options (e.g., LPG stove efficiency is 57%). Electricity in India is derived from a mix of coal and
petroleum fuels as well as some other sources such as hydropower, which is the primary reason its
impacts fall between coal usage and fuels derived from crude oil or natural gas. For consistency
with other fuels, fuel combustion emissions associated with electricity generation are shown in the
use stage here, although emissions will not occur at the household level. For electric stoves,
emissions instead occur at the point of combustion in the power plant. Biogas GCCP impacts are
primarily from methane leakage during the production of biogas in an anaerobic digester.
Sugarcane ethanol, dung cake (from animals consuming biomass to produce the dung), and
unprocessed crop residues are derived from renewable biomass that removed CO2 from the
atmosphere during growth; therefore, the CO2 emissions released from combustion of these fuels
is considered carbon neutral. Methane emissions from the animals producing the dung for the dung
cake is also modeled as outside the system boundaries of this work, with these emissions being
allocated to the primary animal product (e.g. dairy). Impacts for these renewable fuels during the
use phase are driven by nitrous oxide and methane emissions during cookstove use. Impacts
associated with fertilizer production and emissions from fertilizer application also play a role in
the sugarcane ethanol overall impacts.
Based on the trend in forest area and the annual generation of biomass per hectare, a little
less than 60% of the firewood required for cooking can be sustainably sourced; therefore, the
combustion emissions for the non-renewable 41% of wood are not considered carbon-neutral. This
adjustment is also applied to other wood fuels (wood-derived charcoal and the wood portion of
biomass pellets). For charcoal, GCCP impacts for carbonization of the wood in the kiln are
comparable in magnitude to the emissions from combustion of the charcoal in a cookstove.
Charcoal kiln impacts are largely driven by the methane emissions during the carbonization
process.
3-1
-------
Life Cycle Assessment Results for India
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use ® TOTAL
1/°00 ' 963
ClO
c
o
o
u
(D
"O
(D
OJ
>
~ai
Q
3
u-
QJ
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900
800
700
600
500
400
300
200
100
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572
292
303
o
415
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6
I
f r
539
134
*
191
132 6
«
S//SS///////
V V Xj" SS. nS . O
dS° *
V 0
cP ^
Figure 3-1. Cookstove Fuel Global Climate Change Potential for India
3.1.2 Cumulative Energy Demand
Figure 3-2 displays the CED results for India for each cookstove fuel included in this study.
Energy demand results are shown here at the point of use of the relevant energy source.
The results here are largely a function of the fuel heating value and thermal efficiency of
the fuel-stove combination. Stoves with higher efficiencies (e.g. LPG, kerosene, biogas, ethanol,
and biomass pellets) have a lower CED overall, because more of the heating value of the fuel is
converted into useful cooking energy and therefore less fuel must be produced, transported, and
burned to deliver the same amount of cooking energy.
A number of observations can be made regarding energy results for the various types of
fuels. For sugarcane ethanol, the feedstock energy results include not only the energy value of the
sugar that is converted to ethanol but also the energy content of the bagasse, which provides the
majority of energy used to process the sugarcane to molasses and then to ethanol. A co-benefit of
ethanol production is the generation of electricity, which may be exported. As discussed in the
Chapter 2 methodology (Section 2.3), this model employs the cut-off allocation methodology;
therefore, a credit is not given here to the sugarcane ethanol for exported electricity, so the energy
demand impacts for ethanol should be considered as the upper bounds for this cooking fuel type.
3-2
-------
Life Cycle Assessment Results for India
For biomass fuels, the biomass pellets have a lower CED than traditional firewood or
unprocessed crop residues. Wood pellets typically have a lower moisture content, greater energy
content, and greater surface area than the traditional solid biomass, which allows the fuel to
combust more efficiently. It is also more common to see improved cookstoves, which have higher
stove thermal efficiencies, used in combination with wood pellets in India. Crop residues have a
comparably lower stove efficiency than traditional firewood in India, leading to relatively higher
cumulative energy demand impacts for crop residue fuels compared to firewood.
For charcoal briquettes from wood, the energy demand impact is relatively high compared
to other fuels due to the lower stove efficiencies for metal charcoal stoves in India and the charcoal
kiln energy impacts. That is, additional energy is consumed when burning firewood at the kiln to
produce charcoal prior to charcoal utilization in a cookstove.
Overall, liquid and gas fuels, as well as processed solid biomass fuels not requiring
additional combustion of solid fuel for processing (e.g., wood pellets), lead to the lowest overall
cumulative energy demand impacts. Hard coal results in the highest overall cumulative energy
demand due to the low coal stove thermal efficiency and the energy required for coal mining and
distribution. Dung cake also has comparably high CED impacts, as it is the fuel type associated
with the least efficient cookstove.
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
16,000
12,859
c
^ 14,000
o
u
x 10,000
"O
a>
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o 12,000 10,209 9'670
6,000
Si
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1 2'000 * 6
5,443
7,716
6,507
I
¦
2,039
1,820
1
•
•>* o° ^ ^
J / *
CP
Figure 3-2. Cookstove Fuel Cumulative Energy Demand for India
3-3
-------
Life Cycle Assessment Results for India
3.1.3 Fossil Depletion
Figure 3-3 displays the fossil depletion results for India for each cookstove fuel included
in this study. All fuels are normalized to kg oil equivalents (eq) based on the heating value of the
fossil fuel relative to oil. The fossil depletion associated with traditional biomass fuels and biogas
is negligible, as these fuels are not derived from fossil fuel, and collection of these fuels is done
manually. While biomass fuels are not derived from fossil fuels, some fossil fuels may be
consumed across the life cycle of these fuels for energy inputs to fuel production and processing,
distribution, and disposal. Fossil depletion for biomass pellets is associated with electricity usage
for pelletization and some transport, while sugarcane ethanol fossil depletion is primarily from
fertilizers during cane production, as well as diesel for farm equipment operation and distribution
of the feedstock and fuel. Fossil depletion impacts are highest for coal, LPG, kerosene and
electricity, as these sources of cooking energy rely on fossil fuels. The greatest impacts are seen
for coal. The combination of coal's lower heating value, measured in MJ/kg, compared to crude
oil or natural gas and the lower coal stove thermal efficiency (15.5%) compared to the more
efficient LPG stoves (57%) means that more coal than LPG must be burned to get the same amount
of cooking energy, leading to the higher fossil depletion for cooking with coal compared to LPG.
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
300
ClO
E 250
o
o
u
O 200
(D
U 150
I—
0>
>
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e?
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0 117 6.25 0.0064 0.0076
. - . . :15
p6 jp J> ^
J? _jF sT
* -o * * S / /./ * 0°" *
J / *
J?
Figure 3-3. Cookstove Fuel Fossil Depletion for India
3-4
-------
Life Cycle Assessment Results for India
3.1.4 Water Depletion
Figure 3-4 displays the water depletion results for India for each cookstove fuel included
in this study. Water depletion results are based on the volume of fresh water inputs over the life
cycle of the assessed fuels. Water may be incorporated in the fuel product, evaporated, or returned
to the same or different water body or to land. If the water is returned to the same water body, it is
assumed the water is returned at a degraded quality, and therefore is considered consumptive use.
Water consumption includes evaporative losses from establishment of hydroelectric dams but does
not include the water passing through the turbine, since that water is not removed from its source.
The hydropower in the electricity mix drives the overall water depletion impacts. In this case, for
simplicity, electricity impacts have been allocated to the use life cycle stage. Water depletion
associated with biomass pellets is also due to electricity usage during pelletization. Water depletion
impacts are also notable for sugarcane ethanol, as irrigation is required for the cane production.
Some water depletion impacts are also seen for the biogas to maintain the digester, but these are
negligible when compared to the evaporative losses from hydropower in the electricity grid. Water
depletion impacts are negligible for the traditional biomass fuels, which are not irrigated. Because
the water content of these fuels comes from the atmosphere as rainfall, the water released back to
the atmosphere when the biomass is dried or combusted is not considered consumptive use.
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
600
ClO
c
C
515
§ 500
o
S 400
x
~o
cu
!jj 300
OJ
o
3 200
Figure 3-4. Cookstove Fuel Water Depletion for India
3-5
-------
Life Cycle Assessment Results for India
3.1.5 Particulate Matter Formation Potential
Figure 3-5 displays the particulate matter formation results for India for each cookstove
fuel included in this study. Traditional biomass fuels and hard coal lead to the greatest particulate
matter formation impacts, with dung cake having the highest overall impacts. Most particulate
matter formation impacts occur during cookstove use at the household with the exception of
charcoal, where the carbonization of the wood in the kiln dominates the overall life cycle impacts.
Advanced liquid fuels as well as biogas and wood pellets have comparably small particulate matter
impacts. Most of the particulate matter impacts for electricity are derived from the coal mix in the
average Indian electrical grid. The particulate matter impacts from fuel combustion for electricity
generation have been allocated to the use phase because even though they do not occur within a
household, they are emitted at the point of combustion in the power generating facility.
I Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
25.0
QlO
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<§ 20.0
19.3
19.5
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ft
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.
1.69
11.3
.
4.72
yU.-L /
¦ ^ .
0.17 °-08 H 0.21
/ / / s ^ /
-------
Life Cycle Assessment Results for India
photochemical formation impacts, with dung cake having the highest overall impacts. For
charcoal, impacts are split between the fuel processing stage (carbonization in a kiln) and the use
stage. Photochemical oxidant impacts for electricity are primarily associated with utilization of
hard coal in the grid mix. Impacts from fuel combustion emissions for electricity generation are
shown in the use stage here for simplicity, although the contributing emissions are not released at
the household level. Photochemical oxidant formation impacts are relatively small for the liquid
fuels, biomass pellets and biogas.
I Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
18.7
c 20
o
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18
16
14
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.
i
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i 1 * I I
6.02
i
1
0.24
o — - — — •
/¦ y y y /¦ y
J// ^/ /// ^
-------
Life Cycle Assessment Results for India
associated with biogas. Application of the digested sludge from the biogas system would lead to
some eutrophi cation impacts, but utilization of this co-product is outside the system boundaries of
this study. The digested sludge impacts are allocated to the product system it serves (e.g. nutrients
for crop production). Impacts from fossil based fuels and biomass pellets are minimal compared
to the traditional fuels.
Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
4.5
g? 4.0
8 3-5
i—
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3.0
+-»
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1 S / / si ¦ / 1 '
f / S # J J ~ /./ /
^*VVV / ^
// ~
J?
-------
Life Cycle Assessment Results for India
I Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
1.00
0.50
0.00
1-
4.50
QlO
.E r 4.00
g 4.00
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/
1
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¦
¦
0.75
0.62
^0.50 o.ll °-21 °'29
U.bz
0.40
^ / >
-------
Life Cycle Assessment Results for India
Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use ® TOTAL
CbO
c
o
o
u
(D
"O
(D
(D
>
(D
Q
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(D
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.
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*
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• / / 1
?// S *
V V lO A oS ..(V
J> xO2, .X?
($0
o
$
Jr
(f
-------
Life Cycle Assessment Results for India
3.1.10 Black Carbon and Short-Lived Climate Pollutants
Figure 3-10 displays the black carbon results for India for each cookstove fuel included in
this study. The highest BC impacts are seen for traditional unprocessed biomass fuels as hard coal,
which tends to have high particulate matter emissions when combusted, and charcoal. For
charcoal, the largest share of particulate matter is seen for fuel processing in the charcoal kiln,
which combusts wood to carbonize the fuel. Utilization of the liquid and gas fuels result in the
lowest overall BC impacts. Some life cycle stages have negative BC equivalent impacts, which is
the case when emissions of SOx and organic carbon, pollutants with net cooling effects on the
climate, are greater than the emissions of BC and other co-emitted pollutants that lead to short
term warming impacts.
Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
c 6.0E+00
o
(3 5.0E+00 3 91
I—
o
5.01
(D
4.0E+00
4.27
~o 3.0E+00 2 42
cN s$0 ($> si?1
-1.0E+00 jC° ^ ^ ;«> # <5^ AO jP c?
# +////
-------
Life Cycle Assessment Results for India
3.2.1 Global Climate Change Potential
Figure 3-11 presents the GCCP results for the current and potential future cookstove fuel
mix scenarios. All of the potential future fuel mix scenarios result in less GCCP, with the 'LPG
Replaces Biomass' and 'Biogas Replaces Biomass' scenarios having the lowest impacts. However,
the difference in climate change potential between the current scenario and the future scenarios is
not large. Firewood contributes the most to global climate change across all scenarios, followed
by LPG from crude oil. Although wood is generally considered a renewable resource, the portion
of greenhouse gas emissions from combustion of the non-renewable portion of wood fuel are not
considered carbon neutral and are therefore counted towards the GCCP. Another fraction of the
GCCP from firewood, as well as from other traditional biomass fuels, is due to formation of
methane and nitrous oxide emissions during fuel combustion in the cookstove.
I Hard Coal
Kerosene
I Biogas from Cattle Dung
I Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
50 100 150 200 250 300
kg C02 eq/GJ Delivered Heat for Cooking
350
400
Figure 3-11. Global Climate Change Potential Impacts for Current and Future Fuel Mix
Scenarios in India
3-12
-------
Life Cycle Assessment Results for India
3.2.2 Cumulative Energy Demand
Figure 3-12 displays the CED results for each scenario in India. Currently, firewood
contributes more than half of total CED while the next largest contributor, dung cake makes up
less than a quarter of total CED. All of the future fuel mix scenarios lead to a decrease in CED,
but the reductions due to the 'Increase Clean Electric' and 'Increase Urban Electric' scenarios are
minimal. The scenarios that are most effective in lowering CED are those that involve replacing a
portion of firewood, crop residue, and dung use with another fuel. Replacement of biomass and
dung with LPG in particular results in considerably less CED than the current cookstove fuel mix
in India. However, even in the scenarios that involve reductions in firewood use, firewood remains
the dominant source of CED.
Hard Coal
Kerosene
Biogas from Cattle Dung
Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000
MJ/GJ Delivered Heat for Cooking
Figure 3-12. Cumulative Energy Demand for Current and Future Fuel Mix Scenarios in
India
3-13
-------
Life Cycle Assessment Results for India
3.2.3 Fossil Depletion
Figure 3-13 depicts the depletion of fossil fuels as a result of the current and future
cookstove fuel mix scenarios. Currently in India, the greatest source of fossil depletion in the
cooking fuel mix is LPG from crude oil, followed by hard coal. Kerosene, LPG from natural gas,
and electricity are other lesser contributors. Use of biomass fuels results in zero or negligible fossil
depletion impacts. While substituting biogas use in cookstoves for a portion of the traditional
biomass used in India today would result in no change in overall fossil depletion, the remaining
potential future scenarios would all result in higher fossil depletion. The highest impacts are seen
for the scenarios where LPG replaces some of the current biomass usage or when use of current
grid mix electricity for cookstoves is increased, since much of electricity in India is generated from
coal combustion. The 'Ethanol Replaces Biomass' scenario also results in slightly higher fossil
depletion since sugarcane farming uses more fossil fuel inputs than gathering and processing
traditional biomass fuels.
¦ Hard Coal ¦ LPG from NG ¦ LPG from Oil
¦ Kerosene ¦ Electricity ¦ Sugarcane Ethanol
¦ Biogas from Cattle Dung ¦ Charcoal from Wood ¦ Biomass Pellets
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
0 5 10 15 20 25 30
kg oil eq/GJ Delivered Heat for Cooking
Figure 3-13. Fossil Depletion for Current and Future Fuel Mix Scenarios in India
3-14
-------
Life Cycle Assessment Results for India
3.2.4 Water Depletion
Figure 3-14 shows that the current mix of cookstove fuels in India has lower water
depletion results compared to the future scenarios investigated in this study. 'Increase Clean
Electric' and 'Increase Urban Electric' scenarios would cause 6.6 and 5.5 times the amount of
water depletion resulting from the current scenario, respectively. Evaporative water loss related to
hydroelectric dams drives the high water depletion impacts associated with increased electricity
usage. The 'Increase Clean Electric' scenario includes a greater percentage of hydroelectric power,
which results in even greater water depletion than the 'Increase Urban Electric' scenario. Water
depletion associated with biomass pellets is also due to electricity usage during pelletization.
Introducing sugarcane ethanol into the fuel mix would also increase water depletion, since
irrigation is required for sugarcane production. In general, replacing traditional biomass fuels that
require little water over their life cycle will cause an increase in water depletion.
¦ Hard Coal
¦ Kerosene
¦ Biogas from Cattle Dung
¦ Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
20 40 60
m3Water/GJ Delivered Heat for Cooking
80
Figure 3-14. Water Depletion for Current and Future Fuel Mix Scenarios in India
3-15
-------
Life Cycle Assessment Results for India
3.2.5 Particulate Matter Formation
As seen in Figure 3-15, current particulate matter formation potential could be reduced if
any of the potential future cookstove fuel mix scenarios were achieved. Even though an increase
in electricity used for cookstoves as modeled in the 'Increase Clean Electric' and 'Increase Urban
Electric' scenarios would reduce particulate matter impacts in homes, the particulate matter
formation associated with electricity generation from coal means that these scenarios would not
greatly reduce life cycle particulate matter impacts. LPG, biogas, biomass pellets, and sugarcane
ethanol produce significantly less particulate matter during combustion than traditional biomass
fuels, especially dung cake, so particulate matter impacts are reduced the most in the
scenarios where these fuels replace a portion of the traditional biomass used currently.
¦ Hard Coal
¦ Kerosene
¦ Biogas from Cattle Dung
¦ Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
0.0
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
1.0 2.0 3.0 4.0 5.0
kg PM10 eq/GJ Delivered Heat for Cooking
6.0
7.0
Figure 3-15. Particulate Matter Formation Potential for Current and Future Fuel Mix
Scenarios in India
3-16
-------
Life Cycle Assessment Results for India
3.2.6 Photochemical Oxidant Formation Potential
Figure 3-16 displays the effect of various fuel use scenarios on photochemical oxidant
formation potential impacts. All of the study scenarios lead to improved environmental
performance within this impact category when compared to the current scenario. The replacement
of biomass fuel with LPG is the scenario that leads to the greatest reduction in photochemical
oxidant formation. Both scenarios with increased use of electricity as a cooking fuel lead to only
marginal improvements over the current Indian fuel mix scenario. Firewood, crop residues, and
dung cake are the dominant fuels contributing to impacts within this category across all of the
study scenarios.
¦ Hard Coal
I Kerosene
¦ Biogas from Cattle Dung
¦ Firewood
Current |
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric |
0.0
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
1.0 2.0 3.0 4.0 5.0
kg NMVOC eq/GJ Delivered Heat for Cooking
6.0
Figure 3-16. Photochemical Oxidant Formation Potential for Current and Future Fuel Mix
Scenarios in India
3-17
-------
Life Cycle Assessment Results for India
3.2.7 Freshwater Eutrophication Potential
Figure 3-17 depicts the influence of fuel use scenarios on freshwater eutrophication
potential impacts. Dung is the predominant fuel contributing to freshwater eutrophication. This is
true despite the relatively small contribution of dung cake to the Indian fuel mix, with none of the
scenarios utilizing more than 10.6% dung per GJ of delivered cooking heat (Table 1-5).
Alternatively, firewood has a relatively modest impact compared to dung per GJ of delivered
heat, however it comprises a much more substantial portion of the fuel mix within each scenario,
varying between 32 and 49%.
¦ Hard Coal
¦ Kerosene
¦ Biogas from Cattle D
¦ Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
0 0.1 0.2 0.3 0.4 0.5
kg P eq/GJ Delivered Heat for Cooking
Figure 3-17. Freshwater Eutrophication Potential for Current and Future Fuel Mix
Scenarios in India
¦ LPG from NG ¦ LPG from Oil
¦ Electricity ¦ Sugarcane Ethanol
¦ Charcoal from Wood ¦ Biomass Pellets
¦ Crop Residue ¦ Dung Cake
3-18
-------
Life Cycle Assessment Results for India
3.2.8 Terrestrial Acidification Potential
The influence of studied fuel use scenarios on terrestrial acidification potential is displayed
in Figure 3-18. Both scenarios in which electricity is increased as a cooking fuel lead to
significantly higher acidification impacts than the current scenario. All other scenarios lead to
minor improvements when compared against the current scenario. In general, the results in this
impact category are driven by coal use, either directly as a cooking fuel or indirectly in the
production of electricity.
I Hard Coal
Kerosene
I Biogas from Cattle Dung
I Firewood
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
0.1 0.2 0.3 0.4 0.5 0.6 0.7
kg S02 eq/GJ Delivered Heat for Cooking
0.8
0.9
Figure 3-18. Terrestrial Acidification Potential for Current and Future Fuel Mix Scenarios
in India
3-19
-------
Life Cycle Assessment Results for India
3.2.9 Ozone Depletion Potential
The influence of fuel scenarios on ozone depletion potential impact scores is presented
below in Figure 3-19. Unlike many of the other impact categories, the majority of studied scenarios
lead to an increase in ozone depletion potential beyond that estimated for the current scenario. The
use of LPG, particularly LPG produced from crude oil feedstock, dominates contributions to the
studied scenarios in this impact category. Consequently, the scenarios in which LPG is used to
replace biomass are two of the three worst performers. Ethanol production has an even more
pronounced impact on the scenario in which it is assumed to replace traditional biomass and dung.
Ethanol alone contributes approximately half of the ozone depletion impacts while comprising
only 10% of the scenarios fuel mix. Ethanol ozone depletion impacts are driven by emissions from
application of herbicides during cane production. Electricity use also contributes to impact results
in the scenarios in which its use is scaled up.
I Hard Coal
Kerosene
I Biogas from Cattle Dung
I Firewood
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
0.0E+00 2.0E-07 4.0E-07 6.0E-07 8.0E-07 1.0E-06 1.2E-06 1.4E-06
kg CFC-11 eq/GJ Delivered Heat for Cooking
Figure 3-19. Ozone Depletion Potential for Current and Future Fuel Mix Scenarios in India
3-20
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Life Cycle Assessment Results for India
3.2.10 Black Carbon and Short-Lived Climate Pollutants
The summary impacts of fuel scenarios on the BC impact category are displayed in Figure
3-20. All of the alternative scenarios show a reduced impact compared to the current cook fuel
scenario. Scenarios that replace the burning of biomass with fossil fuel alternatives that tend to
have higher thermal stove efficiencies reduces emissions contributing to this impact category.
Across all of the study scenarios firewood, dung cake, and to a lesser extent crop residues, account
for the majority of impacts. Dung cake in particular, due to its poor thermal efficiency, is
responsible for a disproportionate share of the impacts considering it accounts for 10.6% or less
of the fuel mix in all of the study scenarios.
¦ Hard Coal
I Kerosene
¦ Biogas from Cattle Dung
¦ Firewood
Current
Biogas Replaces Biomass
Ethanol Replaces Biomass
Increase Biomass Pellets
Increase Clean Electric
LPG Replaces Rural Biomass
LPG Replaces Biomass
Increase Urban LPG
Increase Urban Electric
I LPG from NG
I Electricity
I Charcoal from Wood
I Crop Residue
I LPG from Oil
I Sugarcane Ethanol
I Biomass Pellets
I Dung Cake
0.0 0.2 0.4 0.6 0.8 1.0
kg BC eq/GJ Delivered Heat for Cooking
1.2
1.4
Figure 3-20. Black Carbon and Short-Lived Climate Pollutant Impacts for Current and
Future Fuel Mix Scenarios in India
3-21
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Life Cycle Assessment Results for India
3.2.11 Relative Impacts of Current and Cleaner Electrical Grid Scenarios in India
Two scenarios were developed that featured an increase in the use of electrical energy as a
cooking fuel. One of these scenarios was developed using the current national grid energy mix as
it exists in India. The second scenario is based on projections regarding the introduction of a
cleaner mix of fuels into the Indian national grid. The result of these grid scenarios for each impact
category are depicted in the previous sections. Figure 3-21 and Figure 3-22 display the relative
environmental impacts of each grid per GJ of delivered heat, with each figure presenting results
for five of the impact categories. The fuel mix for each of the grids is displayed in an earlier section
(Table 2-3). In the clean electric grid scenario, a fraction of coal-fired generation is replaced with
hydropower, natural gas, wind, and nuclear energy. These substitutions yield an improvement in
environmental performance in seven of the ten impact categories. These improvements fall within
the range of between 4 and 18%. Ozone depletion, black carbon, and water depletion impacts are
each higher in the cleaner grid scenario by 32%, 21%, and 20%, respectively. The increase in water
depletion impacts is due to evaporative losses from reservoirs resulting from the increase in
hydroelectric power. The increase in black carbon impacts associated with the cleaner electricity
grid scenario can be traced to the decreased contribution of coal in the cleaner electricity mix. The
sulfur based particulate emissions associated with coal exhibit a short-term cooling effect, thereby
decreasing black carbon impacts, relative to the clean electricity scenario. Coal also has a relatively
low ozone depletion potential when compared to the liquid fossil fuels, which explains the increase
in ozone depletion impacts associated with the clean electricity mix scenario.
Current Cleaner Current Cleaner Current Cleaner Current Cleaner Current Cleaner
Global Climate Cumlative Energy Fossil Depletion (kg Water Depletion Particulate Matter
Change (kg C02 eq) Demand (MJ) oil eq) (m3) Formation (kg PM10
eq)
Figure 3-21. Relative Global Climate Change, Cumulate Energy Demand,
Fossil Depletion, Water Depletion, and Particulate Matter Formation Impacts of Study
Electricity Grids in India
3-22
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Life Cycle Assessment Results for India
Current Cleaner Current Cleaner Current Cleaner Current Cleaner Current Cleaner
Photochemical Freshwater Terrestrial Ozone Depletion (kg Black Carbon (kg BC-
Oxidant Formation Eutrophication (kg P Acidification (kg S02 CFC-11 eq) eq)
(kg NMVOC eq) eq) eq)
Figure 3-22. Relative Photochemical Oxidant Formation, Eutrophication, Acidification,
Ozone Depletion, and Black Carbon Impacts of Study Electricity Grids in India
3.3 Summary Tables for Fuel and Fuel Scenarios in India
This section presents summary tables that allow an easier (simplified) visual side-by-side
comparison of individual fuels and fuel scenarios across impact categories. In each indicator
column, the results are assigned numbers, with lower numbers and green coloration associated
with lower (better) relative environmental results. The numbering and color coding should not be
interpreted as indications that differences between fuels and fuels scenarios are statistically
significant. A binary interpretation as comparatively better systems (green) and relatively worse
systems (yellow) is more appropriate. Additionally, the relative importance of individual impact
categories themselves is subjective and should be considered carefully when interpreting the
results or drawing conclusions about the performance of one fuel or fuel scenario over another.
Despite these cautionary statements and the trade-offs that exist between impact categories,
Table 3-1 does show some notable trends across the considered fuels. Biogas consistently emerges
as a low-impact fuel across the majority of impact categories. None of the other fuels exhibit such
consistently favorable results across all indicators. In contrast, dung cake and hard coal are often
found on the less favorable end of environmental performance.
3-23
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Life Cycle Assessment Results for India
Table 3-1. Ranked Performance of Fuels by Impact Category in India
Cumulative
Particulate
Photochemical
Climate
Energy
Fossil
Water
Matter
Oxidant
Freshwater
Terrestrial
Ozone
Black
Change
Demand
Depletion
Depletion
Formation
Formation
Eutrophication
Acidification
Depletion
Carbon
Hard Coal
12
12
12
6
10
9
3
11
7
10
LPG from NG
7
1
8
7
2
4
2
4
10
3
LPG from CO
8
4
9
8
3
5
4
5
9
5
Kerosene
5
5
10
10
6
6
5
6
11
7
Electricity
9
6
11
12
7
7
6
12
8
1
Sugarcane
Ethanol
2
7
7
11
4
3
8 8
12
2
Bio gas from
Dung
1
2
1
4
1
1
1
1
1
4
Charcoal from
Wood
11
10
4
3
11
11
11
2
4
11
Biomass
Pellets
4
3
6
9
5
2
7
3
6
6
Firewood
10
8
2
1
8 8 9
7
2
8
Crop Residue
3
9
3
2
9
10
10
9
3
9
Dung Cake
6
11
5
5
12
12
12
10
5
12
3-24
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Life Cycle Assessment Results for India
A summary table presenting the relative life cycle environmental results for each fuel
scenario by impact category is included below in Table 3-2. Scenarios are numbered from 1
through 9 across rows corresponding to the magnitude of their relative results from lowest (best)
to highest (worst) in each environmental impact category. Scenarios (columns) with more green
have comparatively better environmental results than scenarios in columns with more yellow. As
described for the previous table on individual fuels, the numerical values lack precision necessary
to state that significant differences in life cycle environmental impact results are present between
scenarios; therefore, when interpreting results it is more appropriate to use the simplified color
scale to identify fuel systems that tend to perform better (green) or worse (yellow) in the categories
of interest.
Table 3-2 does indicate a number of notable trends. As in the previous table, the scenario
with increased use of biogas has consistently positive environmental results. The current fuel mix
scenario, on the other hand, demonstrates relatively higher (worse) performance in seven of the
ten impact categories and relatively better performance in the remaining three (fossil fuel, water
depletion, and ozone depletion), showing clear trade-offs inherent in the current mix. Other
scenarios show more mixed results; however, 'LPG replaces biomass' has generally better
environmental performance while the two scenarios with increased use of electricity show
consistently higher impact trends. While these tables do not conclusively identify the best and
worst options, the tables indicate where further analysis of model sensitivity and significance
should be pursued.
3-25
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Life Cycle Assessment Results for India
Table 3-2. Ranked Performance of Fuel Scenarios by Impact Category in India
LPG
LPG
Replaces
Increase
Increase
Ethanol
Biogas
Increase Urban
Increase
Replaces
Rural
Clean
Biomass
Replaces
Replaces
Electric
Urban LPG
Biomass
Biomass
Electric
Pellets
Biomass
Biomass
Current
Climate Change
8
6
1
4
7
5
3
2
9
Cumulative Energy
8
5
2
1
7
4
6
3
9
Fossil Depletion
7
5
9
8
6
3
4
1
2
Water Depletion
3
7
1
8
6
5
9
4
2
Particulate Matter
8
6
5
1
7
4
3
2
9
Photochemical Oxidant
Formation
8
6
5
1
7
3
4
2
9
Eutrophication
8
6
5
1
7
3
4
2
9
Acidification
9
5
4
2
8
3
6
1
7
Ozone Depletion
4
5
8
7
6
3
9
1
2
Black Carbon and
Short-Lived Climate
Pollutants
6
8
5
1
6
4
2
3
9
3-26
-------
Life Cycle Assessment Results for China
4. Life Cycle Assessment Results for China
This section presents cookstove fuel LCA results for China first by individual cooking fuel
type, followed by fuel mix scenario.
4.1 Results for China by Cooking Fuel Type
The following 10 sections provide the results analysis of the LCI and LCIA categories for
the individual fuels used within China. Results are provided in graphical format in this section and
companion tables for each figure are provided in Appendix B: Detailed LCA Results Tables.
4.1.1 Global Climate Change Potential
Figure 4-1 displays the GCCP results for China for each cookstove fuel included in this
study. Fossil fuel GCCP impacts are dominated by combustion emissions in the cookstove use
stage. Coal has the highest impacts, since it is derived from non-renewable carbon and the thermal
efficiency of coal stoves (27.2%-37.1%) is relatively low compared to stoves used for the other
fossil fuel options (e.g., natural gas stove efficiency is 44.8%-45.9%). Coal is widely used and
transported long distances in China, resulting in a notable contribution of GHGs from the
distribution life cycle stage. Electricity in China is derived primarily from coal (79%) and
hydroelectric facilities (14.8%), which is the primary reason electricity impacts are similar to but
slightly lower than coal. For consistency with other fuels, the fuel combustion emissions associated
with electricity generation are shown in the use stage here, although electricity-related fuel
combustion emissions do not occur at the household level. Crop residues are derived from
renewable biomass that removed CO2 from the atmosphere during growth; therefore, the CO2
emissions released from combustion of these residues are considered carbon neutral. Impacts for
the renewable crop residue fuels during the use phase are driven by nitrous oxide and methane
emissions during cookstove use.
Based on the trend in forest area in China and the annual generation of biomass per hectare,
57%) of the firewood required for cooking can be sustainably sourced; therefore, the combustion
emissions for the non-renewable 43%> of wood are not considered carbon-neutral. This adjustment
is also applied to the portion of biomass pellets derived from wood.
4-1
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Life Cycle Assessment Results for China
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
1,400
u 1,289
1,200
CuO
c
Figure 4-1. Global Climate Change Potential Impacts of Cooking Fuels per GJ of Delivered
Heat for China
4.1.2 Cumulative Energy Demand
Figure 4-2 displays the CED results for China for each cookstove fuel included in this
study. Energy demand tracks all energy inputs across the life cycle of the fuel, with combustion
energy impacts shown at the point of use of the relevant fuel.
The cumulative energy demand results are largely a function of the fuel heating value and
thermal efficiency of the fuel and stove combination. Stoves with higher efficiencies (e.g., used
for LPG, kerosene, natural gas, DME, and biomass pellets) have a lower cumulative energy
demand overall, because more of the heating value of the fuel is converted into useful cooking
energy and therefore less fuel must be produced, transported, and burned to deliver the same
amount of cooking energy.
4-2
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Life Cycle Assessment Results for China
A number of observations can be made regarding energy results for the various types of
fuels. The biomass pellets have a lower cumulative energy demand than traditional wood or crop
residues. Biomass pellets typically have a lower moisture content, greater energy content, and
greater surface area than the traditional solid biomass, which allows the fuel to combust more
efficiently. It is also more common to see improved cookstoves, which have higher stove thermal
efficiencies, used in combination with biomass pellets in China.
Overall, liquid and gas fuels, which includes piped natural gas, as well as processed solid
biomass fuels that do not require additional combustion of solid fuel for processing (e.g., wood
pellets) are the fuels that show the lowest overall cumulative energy demand impacts. Hard coal
shows the highest overall cumulative energy demand due to the energy required for coal mining
and distribution and the low coal stove thermal efficiency. While DME is produced from coal
feedstock via gasification, lower cumulative energy demand impacts are seen for DME as
compared to coal due to its use in more efficient gas stoves.
ClO
¦g 14,000
o
u
Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use ® TOTAL
12,764
(D
"S 10,000
i—
"aj
o 8,000
>«
CuO
i—
(D
C
6,000
~ 4/°00
D
E
5 2,000
12,000 10,506
.
7,905
7,563 7'151
6,538
.
6,060
i
6,395
It
2,943
2,784
. J
2,049 2,3691
1/
jjK'
Z'
&
r&>
^ 4^ <5^ 91
Figure 4-2. Cookstove Fuel Cumulative Energy Demand Impacts for China
4-3
-------
Life Cycle Assessment Results for China
4.1.3 Fossil Depletion
Figure 4-3 displays the fossil depletion results for China for each cookstove fuel included
in this study. All fuels are normalized to the unit, kg oil equivalents, based on the heating value of
the fossil fuel relative to oil. The fossil depletion associated with traditional biomass fuels and
biogas is negligible, as these fuels are not derived from fossil fuel, and collection of these fuels is
done manually. Fossil depletion for biomass pellets is associated with electricity usage for
pelletization and some transport. Fossil depletion impacts are highest for electricity (primarily
fossil-fuel derived), coal, DME (from coal gas), LPG, kerosene and natural gas, as these sources
of cooking energy rely on fossil fuels. The greatest impacts are seen for coal. When compared to
the liquid fossil fuels, coal demonstrates both a lower heating value (MJ/kg) and a lower stove
thermal efficiency (-22%), which leads to more coal being burnt to realize the same amount of
cooking energy.
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
250
213
Figure 4-3. Cookstove Fuel Fossil Depletion Impacts for China
4-4
-------
Life Cycle Assessment Results for China
4.1.4 Water Depletion
Figure 4-4 displays the water depletion results for China for each cookstove fuel included
in this study. Water may be incorporated in the fuel product, evaporated, or returned to the same
or different water body or to land. If the water is returned to the same water body, it is assumed
the water is returned at a degraded quality, and therefore is considered consumptive use. Water
consumption includes evaporative losses from establishment of hydroelectric dams but does not
include the water passing through the turbine, since that water is not removed from its source. The
hydropower in the electricity mix drives the overall water depletion impacts. In this case, for
simplicity, electricity impacts have been allocated to the use stage of the cooking fuel life cycle.
Water depletion associated with fossil fuel use is also due to electricity usage during fuel
processing and/or distribution. Water depletion impacts are negligible for the traditional biomass
fuels. Because the water content of these fuels comes from the atmosphere as rainfall, the water
released back to the atmosphere when the biomass is dried or combusted is not considered
consumptive use.
Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
e?
C
O
200
(D
a 100
CD
O
i—
CD
m 0
r
g" 600
15 r 524
o
o
^ 500
o
4—
4—1
03
£ 400
"a
CD
i—
(D
J 300
O)
O
445 7
76.3
63.7
57.1 72-3
27.5
ili
0.063 0.019 0.12 jk
c c c
5.77 49.2
1 i a 1
y y V /y ^
° sN° £ *
Figure 4-4. Cookstove Fuel Water Depletion Impacts for China
4-5
-------
Life Cycle Assessment Results for China
4.1.5 Particulate Matter Formation Potential
Figure 4-5 displays the particulate matter formation results for China for each cookstove
fuel included in this study. Most particulate matter formation impacts occur during cookstove use
at the household with the exception of electricity, in which case the particulates are emitted at
power plants during grid fuels' combustion. Due to the complexity of life cycle stages for the
numerous fuels in the electricity grid, all electricity burdens have been allocated to the use phase,
although the actual particulate matter emissions for electricity do not occur at the household level.
Most of the particulate matter impacts for electricity are derived from the coal mix in the average
China electrical grid. At the household level, non-briquette forms of coal and unprocessed biomass
fuels lead to the greatest particulate matter formation impacts, with agricultural residues having
the highest overall impacts. Advanced liquid fuels as well as biomass pellets have comparably
small particulate matter impacts.
Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
4.0
QlO
.E 3.5
"o 2.96
o
^ 3.0
o
S 2.5
0.0
3.40
1.81
1
2.34
*
1.49
OA
0.68 0.63
1 I
i
"O
(D
S 2.0
J O ¦ ¦ ¦ 1.33
aj
Q 1.5
0
a-
aj 1.0
o
T—\
^ 0.5
CUD
¦ ¦¦¦¦¦ I • • 71
0 20
0.23
A
I
0.21
0.75
** / / / f ¦/ / ^ # / y
C° s?° J? » 4/ J* J? J-
/ & if ^
o° o°
X>
c/ <
Figure 4-5. Cookstove Fuel Particulate Matter Formation Potential Impacts for China
4.1.6 Photochemical Oxidant Formation Potential
Figure 4-6 displays the photochemical oxidant formation results for China for each
cookstove fuel included in this study. Coal-derived fuels and traditional biomass lead to the
greatest photochemical formation impacts, with coal powder having the highest overall impacts.
4-6
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Life Cycle Assessment Results for China
For DME, impacts are driven by the distribution stage resulting from long-distance transport
NMVOC emissions of the coal gas from plant to rural consumer via a high pressure pipeline
network. Electricity impacts are primarily associated with utilization of hard coal in the grid mix.
Electricity impacts are shown in the use stage here for simplicity, although the contributing
emissions are not released at the household level. Photochemical oxidant formation impacts are
relatively small for the liquid fuels and biomass pellets.
CbO
E 3.5
o
O 3.0
•2 2.5
+-»
TO
(D
X 2.0
"O
(D
s- 15
aj -L¦~,
>
2 L0
^5. 0.5
o-
cu
U 0.0
O
Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
3.31
2.33
T 1 2
2.52
ik
O
1.81
1.5/
1
2.01
1.50
1.20 \
ft*
i
0.40
/
0.42
0 26
.
¦
.
.
i a
0.23 -f
• *
^ ,4? J? & J?
-------
Life Cycle Assessment Results for China
4.1.7 Freshwater Eutrophication Potential
Figure 4-7 displays the freshwater eutrophication results for China for each cookstove fuel
included in this study. Agricultural residues result in the highest eutrophication potential impacts.
This is due to the much larger ash quantity produced from these fuels compared to all other fuels.
The ash from traditional fuels is assumed to be land applied, which provides a pathway to runoff
into water bodies for eventual eutrophication impacts. Ash production and disposal (shown in the
use phase) is also the reason that coal-derived fuels have a relatively high eutrophication impact.
Impacts from advanced gas fuels and biomass pellets are minimal compared to the coal-derived
and traditional biomass fuels. Eutrophication impacts for electricity, primarily associated with
utilization of hard coal in the grid mix, are shown in the use stage here for simplicity; however,
impacts do not occur at the household level but rather during extraction and beneficiation of the
coal resources.
¦ Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use • TOTAL
0.4
m a 0.38
1 °-4
u
£ 0.3
¦*-»
ro
(D
X 0.3 0.20
Figure 4-7. Cookstove Fuel Freshwater Eutrophication Potential Impacts for China
4-8
-------
Life Cycle Assessment Results for China
4.1.8 Terrestrial Acidification Potential
Figure 4-8 displays the terrestrial acidification results for China for each cookstove fuel
included in this study. Acidification impacts are dominated by coal usage, either as a direct fuel or
as an input to electricity generation. Sulfur dioxide emissions from coal and coal-derived fuels are
notably higher than sulfur dioxide emissions from combustion of other fuels. Coal briquette results
are lower than coal mix and coal powder, assuming the same sulfur content. Results are lower for
coal briquettes because of their higher heating values and stove efficiencies relative to other coal
types, so that less coal must be burned per GJ of cooking energy. Traditional biomass fuels and
liquid fuels have low acidification impacts. The lowest overall acidification impacts are seen for
natural gas.
I Feedstock Production ¦ Fuel Processing ¦ Distribution I Cookstove Use •TOTAL
7.00
m 5.94
| 6.00 U
u
I—
^ 5.00 , 4.27
03
(D
-a 4.00
(D
i—
a>
>
~aj 3.00
O
ID
QJ
0.00
3.72
.
1.60
1.42
1
*
•
0.87
0.68
1
0.29 0.29 030 © *
o
" 1.00 ¦ _ — „ _
m ¦ ¦ H 0.30 r. ® 039
0.17
1.18
O
I
y # ^/¦ ^ &•
Figure 4-8. Cookstove Fuel Terrestrial Acidification Potential Impacts for China
4-9
-------
Life Cycle Assessment Results for China
4.1.9 Ozone Depletion Potential
Figure 4-9 displays the ozone depletion results for China for each cookstove fuel included
in this study. Ozone depletion impacts are greatest for the fossil fuels. For fossil-derived fuels, the
impacts generally come from halon 1301 or hydrochlorofluorocarbon (HCFC)-22 emissions
during feedstock production and fuel processing. Overall, normalized ozone depletion impacts are
generally on a much smaller magnitude than other indicators covered, suggesting that less
importance should be placed on this indicator when assessing fuel options.
I Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
ao
c
o
o
u
T3
CD
dJ
O
15
U
Ll_
u
CuO
4.5E-05
4.0E-05
3.5E-05
3.0E-05
2.5E-05
2.0E-05
1.5E-05
1.0E-05 6.4E-06
5.0E-06
0.0E+00
3.8E-05
1.3E-05
1.1E-05
6.4E-I
*
*
8.4E-07
6
*
E
9.9E-10
3.3E-09
6
i
/ / f ^ /
^ ^ J* *
3.4E-05
2.3E-05
A°
os
oS
<&
2.3E-07
6.2E-09
Figure 4-9. Cookstove Fuel Ozone Depletion Potential Impacts for China
4-10
-------
Life Cycle Assessment Results for China
4.1.10 Black Carbon and Short-Lived Climate Pollutants
Figure 4-10 displays the black carbon results for China for each cookstove fuel included in
this study. Black carbon impacts are greatest for the biomass based fuels, especially agricultural
residues. The increased thermal efficiency associated with the use of pelletized biomass
significantly reduces impacts in this category. Relatively clean burning fossil fuels with high sulfur
contents such as LPG and kerosene and electricity (largely derived from coal) have net negative
black carbon impacts due to the cooling effects of their associated SOx emissions.
I Feedstock Production ¦ Fuel Processing ¦ Distribution ¦ Cookstove Use •TOTAL
QlO
c
o
o
u
(U
cu
~o
OJ
&_
OJ
>
"ai
o
0
O"
OJ
u
CO
QlO
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
0.47
0.041
0.30
0.043
0.047
0.044
# &
*
&
c&
Figure 4-10. Cookstove Fuel Black Carbon and Short-Lived Climate Pollutant Impacts for
China
4-11
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Life Cycle Assessment Results for China
4.2 Results for China by Baseline and Potential Scenarios
Given the magnitude of impacts resulting from the use of cookstoves on both the
environment and human health it is important to consider how future changes in the cookstove fuel
mix in China might affect cumulative life cycle impacts associated with cooking fuels. Eight
potential fuel use scenarios were developed in order to explore how impacts in each of the ten
studied environmental impact categories may change in the future. Table 1-7 provides a list of full
scenario names and maps them to the abbreviated scenario names, which are referred to both in
text and figures within this section.
4.2.1 Global Climate Change Potential
Figure 4-11 depicts the effects of various future fuel mix scenarios on GCCP. In general,
future scenario results show an improvement in climate change impacts over those generated by
the current fuel mix. The scenario in which 'LPG Replaces Coal' yields the greatest climate change
benefit. Conversely, if LPG is used to replace biomass, impacts in this category increase slightly.
Increasing the use of biomass pellets and using a cleaner electricity grid are also scenarios that
result in lower greenhouse gas emissions. Despite the assumption that biogenic carbon is neutral
in respect to global warming potential, biomass fuels are still seen to contribute to this impact
category due to the effects of land use change, use of non-renewable wood, and the emission of
carbon monoxide and dinitrogen monoxide.
¦ Coal Powder ¦ Coal Briquettes ¦ Honeycomb Coal Briquettes
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
kg C02 eq/GJ Delivered Heat for Cooking
Figure 4-11. Global Climate Change Potential Impacts for Current and Future Fuel Mix
Scenarios in China
¦ Ag Residues ¦ LPG
¦ Electricity ¦ Natural Gas
¦ DME
0 100 200 300 400 500
4-12
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Life Cycle Assessment Results for China
4.2.2 Cumulative Energy Demand
Figure 4-12 depicts the results of potential future cookstove fuel mix scenarios on impact
results for CED. Seven of the eight future scenarios lead to a decrease in cumulative energy
demand over the current scenario. The Ag residue scenario, where crop residues are utilized to
replace fuel and brush wood, leads to a slight increase in overall cumulative energy demand.
Replacing rural coal use with LPG yields the greatest decrease in CED. The use of biomass pellets
in place of coal or non-pelletized biomass also yields marked improvement in this impact category.
In all three cases stove efficiencies change with the shifting use of fuel feedstock, which affects
energy demand, and thus impacts in this category.
I Coal Powder
I Fuel & Brush Wood
I Kerosene
I Biomass Pellets
I Coal Briquettes
I Ag Residues
I Electricity
I DME
Honeycomb Coal Briquettes
I LPG
I Natural Gas
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
1,000 2,000 3,000 4,000 5,000
MJ/Delivered Heat for Cooking
6,000 7,000
Figure 4-12. Cumulative Energy Demand for Current and Future Fuel Mix Scenarios in
China
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Life Cycle Assessment Results for China
4.2.3 Fossil Depletion
Figure 4-13 provides summary results showing how potential future shifts in cookstove
fuel mix affect the demand for fossil fuel resources. The largest decrease in fossil fuel use among
the study scenarios is realized by replacing coal with LPG as a cookstove fuel. The clean electricity
scenario also reduces fossil fuel use significantly. In this scenario, the corresponding increases in
stove efficiency that accompany many of the fuel shifts are a major contributor to the decrease in
fuel use. Conversely, replacing biomass with either LPG or DME fuel demonstrates the expected
increase in fossil depletion due to the nature of the fuels themselves. In both of these scenarios the
increase in stove efficiency is not enough to overcome the fact that biogenic feedstock is
replaced with fossil fuel based substitutes.
¦ Coal Powder
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
¦ Coal Briquettes
¦ Ag Residues
¦ Electricity
¦ DME
Honeycomb Coal Briquettes
¦ LPG
¦ Natural Gas
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0 20 40 60 80 100
kg oil eq/GJ Delivered Heat for Cooking
Figure 4-13. Fossil Depletion for Current and Future Fuel Mix Scenarios in China
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Life Cycle Assessment Results for China
4.2.4 Water Depletion
Figure 4-14 shows the effects of future cookstove fuel mix scenarios on the water depletion
impact category. Water depletion increases dramatically in both scenarios where electrical energy
increases as a cooking fuel. Only slight differences in water demand are observed between the
clean and current electrical grid, with the cleaner grid demanding slightly less water use. Water
depletion impacts in the electricity scenarios are driven by evaporative losses associated with
hydroelectric power. Current and clean Chinese grid fuel mixes are displayed in Table 2-4. All
other scenarios produce water depletion impacts in a relatively tight range (87-98 m3) per GJ of
delivered cooking energy. In general, electricity is the predominant contributing fuel to results in
this impact category for all fuel mix scenarios evaluated.
¦ Coal Powder ¦ Coal Briquettes I Honeycomb Coal Briquettes
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
m3 water/GJ Delivered Heat for Cooking
Figure 4-14. Water Depletion Impacts for Current and Future Fuel Mix Scenarios in China
¦ Ag Residues ¦ LPG
¦ Electricity ¦ Natural Gas
DME
0 50 100 150 200
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Life Cycle Assessment Results for China
4.2.5 Particulate Matter Formation Potential
The effects of various future fuel mix scenarios on particulate matter formation potential
are displayed in Figure 4-15. The Ag residue scenario is the only study scenario that generates
higher particulate matter impacts than does the current scenario. It is also the only scenario where
the increased cookstove fuel is used in a cookstove with a lower thermal efficiency. Biomass, coal,
and electricity all contribute significantly to the results in this impact category. LPG can be seen
to have a relatively low contribution to this impact category despite its consistently high presence
in the fuel mix. As a result of these factors the scenario that yields the lowest particulate matter
impact is the one in which it is assumed that LPG replaces biomass. A strategy which increases
the use of pelletized biomass also positively affects impact scores in this category.
I Coal Powder
I Fuel & Brush Wood
I Kerosene
I Biomass Pellets
I Coal Briquettes
I Ag Residues
I Electricity
I DME
Honeycomb Coal Briquettes
LPG
Natural Gas
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0.00
0.50
1.00
1.50
2.00
kg PM10 eq/GJ Delivered Heat for Cooking
Figure 4-15. Particulate Matter Formation Potential for Current and Future Fuel Mix
Scenarios in China
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Life Cycle Assessment Results for China
4.2.6 Photochemical Oxidant Formation Potential
The influence of potential fuel use scenarios on photochemical oxidant formation potential
impact is presented in Figure 4-16. As in the previous section, it can be seen that the replacement
of wood with crop residue as a cooking fuel leads to higher impacts in this category, due in part to
the lower thermal efficiencies of stoves that burn crop residues. Among the studied scenarios the
replacement of biomass stoves with those utilizing LPG yield the most dramatic decrease in
photochemical oxidation impacts. Increased use of biomass pellets is also an effective means of
reducing the impact in this category, due not only to the properties of the fuel but also the
corresponding increase in thermal efficiency of the pellet cookstoves.
¦ Coal Powder ¦ Coal Briquettes I Honeycomb Coal Briquettes
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0.00 0.50 1.00 1.50 2.00
kg NMVOC eq/GJ Delivered Heat for Cooking
Figure 4-16. Photochemical Oxidant Formation Potential for Current and Future Fuel Mix
Scenarios in China
¦ Ag Residues ¦ LPG
¦ Electricity ¦ Natural Gas
DME
4-17
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Life Cycle Assessment Results for China
4.2.7 Freshwater Eutrophication Potential
Figure 4-17 shows the results of potential fuel use scenarios on the freshwater
eutrophication impacts. Agricultural residues dominate the results in this impact category due
to land application of crop residue ash after combustion. Consequently, the scenario where
Ag residues replace wood based biomass yields the largest overall impact among the studied
scenarios. The scenario in which LPG replaces biomass yields the lowest overall result.
Pelletization of biomass fuels prior to their use as a cooking fuel also results in
improved environmental performance within this impact category, including the beneficial
effect of higher efficiencies for pellet stoves.
¦ Coal Powder
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0.0000 0.0200 0.0400 0.0600 0.0800 0.1000 0.1200 0.1400
kg P eq/GJ Delivered Heat for Cooking
Figure 4-17. Freshwater Eutrophication Potential for Current and Future Fuel Mix
Scenarios in China
¦ Coal Briquettes ¦ Honeycomb Coal Briquettes
¦ Ag Residues ¦ LPG
¦ Electricity ¦ Natural Gas
¦ DME
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Life Cycle Assessment Results for China
4.2.8 Terrestrial Acidification Potential
The effects of fuel use scenarios on terrestrial acidification potential impacts are depicted
in Figure 4-18. Both switching electricity for coal and LPG for biomass, Scenarios 1 and 3
respectively, lead to an increase in terrestrial acidification impacts. However, the increase is not a
dramatic one. Substituting LPG for coal leads to a more significant decrease in acidification
impacts, and the lowest overall impact score of all the studied scenarios. The burning of coal either
directly in stoves or as a feedstock for electricity production is a driver of impacts in this category.
¦ Coal Powder
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0.00 0.50 1.00 1.50 2.00
kg S02 eq/GJ Delivered Heat for Cooking
Figure 4-18. Terrestrial Acidification Potential for Current and Future Fuel Mix Scenarios
in China
Coal Briquettes
I Ag Residues
I Electricity
DME
Honeycomb Coal Briquettes
I LPG
I Natural Gas
4-19
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Life Cycle Assessment Results for China
4.2.9 Ozone Depletion Potential
Figure 4-19 shows the effect of fuel use scenarios on ozone depletion impacts. In general,
the scenario results are dominated by contributions from fossil fuels. Petroleum and coal-based
fuels have a significantly higher contribution to ozone depletion per GJ of delivered heat than do
biomass fuels. The scenarios where LPG or DME is used as a fuel substitute generates
significantly greater ozone depletion impacts compared to the current scenario.
I Coal Powder
I Fuel & Brush Wood
I Kerosene
I Biomass Pellets
I Coal Briquettes
I Ag Residues
I Electricity
I DME
Honeycomb Coal Briquettes
LPG
Natural Gas
Current
Ag Residue replace Wood
Coal Swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
0.0E+00
5.0E-06 1.0E-05 1.5E-05
kg CFC-11 eq/GJ Delivered Heat for Cooking
2.0E-05
Figure 4-19. Ozone Depletion Potential for Current and Future Fuel Mix Scenarios in
China
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Life Cycle Assessment Results for China
4.2.10 Black Carbon and Short-Lived Climate Pollutants
The contribution of studied fuel mix scenarios on black carbon impacts are depicted in
Figure 4-20. Biomass based cooking fuels dominate results in the study scenarios. Unlike other
impact categories, there are negative results associated with LPG, kerosene, electricity and natural
gas fuels that contribute to the various scenarios. For these fuels the cooling effects of SOx and
organic carbon emissions exceed the contribution to warming created by the other emissions,
leading to a net negative radiative forcing impact. These negative values are not sufficient in any
of the scenarios to completely eliminate the contribution of black carbon emissions to climate
change. The Ag residue scenario has the greatest overall BC impact and exceeds that of the current
scenario. The scenario in which LPG replaces biomass has the lowest net impacts among the
scenarios within this impact category.
¦ Coal Powder
¦ Fuel & Brush Wood
¦ Kerosene
¦ Biomass Pellets
¦ Coal Briquettes ¦ Honeycomb Coal Briquettes
¦ Ag Residues ¦ LPG
¦ Electricity ¦ Natural Gas
¦ DME
Current
Ag residue replace wood
Coal swap
Increase DME
Increase Biomass Pellets
Increase Clean Electric
LPG replaces Biomass
LPG replaces Coal
Increase Electric
~°Os
°00 °Os °i0
kg BC eq/GJ Delivered Heat for Cooking
°lS
°-20
Figure 4-20. Black Carbon and Short-Lived Climate Pollutant Impacts for Current and
Future Fuel Mix Scenarios in China
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Life Cycle Assessment Results for China
4.2.11 Relative Impacts of Current and Cleaner Electrical Grid Scenarios in China
Two scenarios were developed that featured an increase in the use of electrical energy as a
cooking fuel. One of these scenarios was developed using the current national grid energy mix as
it exists in China. The second scenario is based on projections regarding the introduction of a
cleaner mix of fuels into the Chinese national grid. The result of these grid scenarios for each
impact category are depicted in the previous section. Figure 4-21 and Figure 4-22 display the
relative impacts of each grid per GJ of delivered heat, with each figure presenting results for five
of the impact categories. The fuel mix for each of the grids is displayed in an earlier section in
Table 2-4. In the clean electric grid scenario, a fraction of the coal-fired generation is replaced with
hydropower, natural gas, wind, and nuclear energy. These substitutions yields an improvement in
environmental performance in eight of the ten impact categories between 1 and 25%. Ozone
depletion and black carbon impacts are both higher in the cleaner grid scenario, with ozone
depletion impacts increasing by 69%. The increase in black carbon impacts is due to the decreased
contribution of coal in the cleaner electricity mix. The sulfur based particulate emissions associated
with coal exhibit a short-term cooling effect, thereby decreasing black carbon impacts, relative to
the clean electricity scenario. Coal also has a relatively low ozone depletion potential when
compared to the liquid fossil fuels, which explains the increase in ozone depletion impacts
associated with the clean electricity mix scenario.
Current Cleaner Current Cleaner Current Cleaner Current Cleaner Current Cleaner
Global Climate Cumlative Energy Fossil Depletion Water Depletion Particulate
Change (kg C02 Demand (MJ) (kg oil eq) (m3) Matter Formation
eq) (kgPMlOeq)
Figure 4-21. Relative Global Climate Change, Cumulative Energy Demand, Fossil
Depletion, Water Depletion, and Particulate Matter Formation Impacts of Study
Electricity Grids in China
4-22
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Life Cycle Assessment Results for China
100%
90%
¦g
£5 80%
I ¦ ¦
I I I
S50%
ill
O10,
8 0%
a! Current Cleaner Current Cleaner Current Cleaner Current Cleaner Current Cleaner
Photochemical Freshwater Terrestrial Ozone Depletion Black Carbon (kg
Oxidant Formation Eutrophication (kg Acidification (kg (kgCFC-lleq) BC-eq)
(kg NMVOC eq) P eq) S02 eq)
Figure 4-22. Relative Photochemical Oxidant Formation, Eutrophication, Acidification,
Ozone Depletion, and Black Carbon Impacts of Study Electricity Grids in China
4.3 Summary Tables for Fuel and Fuel Scenarios in China.
This section presents summary tables that allow an easier (simplified) visual side-by-side
comparison of individual fuels and fuel scenarios across impact categories. In each indicator
column, the results are assigned numbers, with lower numbers and green coloration associated
with lower (better) relative environmental results. The numbering and color coding should not be
interpreted as indications that differences between fuels and fuels scenarios are statistically
significant. A binary interpretation as comparatively better systems (green) and relatively worse
systems (yellow) is more appropriate. Additionally, the relative importance of individual impact
categories themselves is subjective and should be considered carefully when interpreting the
results or drawing conclusions about the performance of one fuel or fuel scenario over another.
Despite these cautionary statements and the trade-offs that exist between impact categories,
Table 4-1 does show some notable trends across the considered fuels. Natural gas, biomass pellets,
and LPG are generally in the higher end of environmental performance with some exceptions. The
various forms of coal emerge as having consistently worse relative environmental performance for
most impacts. It is also interesting to note the tradeoffs in areas where unprocessed biomass fuels
perform well (fossil fuel, water, acidification, ozone) and where they perform poorly (particulate
matter, photochemical oxidation, and black carbon).
4-23
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Life Cycle Assessment Results for China
Table 4-1. Ranked Performance of Fuels by Impact Category in China
Black
Carbon &
Short-
Cumulative Particulate Photochemical Lived
Climate Energy Fossil Water Matter Oxidant Freshwater Terrestrial Ozone Climate
Change Demand Depletion Depletion Formation Formation Eutrophication Acidification Depletion Pollutants
Coal Mix
12
12
12
7
10
11
10
11
7
7
Coal Powder
13
13
13
5
12
13
11
13
5
6
Coal
Briquettes
11
11
11
12
6
5
9
10
9
9
Honeycomb
Coal
10
9
10
10
5
6
8
9
8
8
Briquettes
Biomass Mix
3
8
2
2
11
10
12
3
2
12
Fuel & Brush
Wood
7
7
1
1
9
7
5
2
1
11
Ag Residues
1
10
3
3
13
12
13
4
3
13
LPG
4
3
6
9
2
3
2
6
11
3
Kerosene
5
4
7
11
4
4
3
7
13
2
Electricity
9
5
8
13
00
00
12
6
1
Natural Gas
6
1
5
4
1
1
1
1
12
4
Biomass
Pellets
2
2
4
8
3
2
4
5
4
5
DME
00
9
6
7
9
7
8
10
10
4-24
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Life Cycle Assessment Results for China
A summary table presenting the relative life cycle environmental results for each fuel
scenario by impact category is included below in Table 4-2. Scenarios are numbered from 1
through 9 across rows corresponding to the magnitude of their relative results from lowest (best)
to highest (worst) in each environmental impact category. Scenarios (columns) with more green
have comparatively better environmental results than scenarios in columns with more yellow. As
described for the previous table on individual fuels, the numerical values lack precision that would
ideally be needed for meaningful conclusions about differences in life cycle environmental impact
results; therefore, when interpreting results it is more appropriate to use the simplified color scale
to identify fuel systems that tend to perform better (green) or worse (yellow) in the categories of
interest.
The table shows that both the 'Increase Biomass Pellet' and 'LPG replace Coal' scenarios
demonstrate better environmental performance in almost all impact categories. As with India, the
current scenario has generally worse environmental performance for most indicators with a few
exceptions. Interestingly, both electricity scenarios exhibit better relative performance in China
than they do in the Indian context although the performance of the electricity scenarios has some
unfavorable results for certain impact categories, including water depletion (for both electricity
scenarios) and acidification (for increasing current electricity). Results for other scenarios are
equally or more mixed. While these tables do not conclusively identify the best and worst options,
they indicate where further analysis of model sensitivity and significance should be pursued.
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Life Cycle Assessment Results for China
Table 4-2. Ranked Performance of Fuel Scenarios by Impact Category in China
LPG LPG Increase Increase Ag reside
Increase replaces replaces Clean Biomass Increase Coal replace
Electric Coal Biomass Electric Pellets DME swap wood Current
Climate Change
3
1
9
2
4
5
6
7
8
Cumulative Energy
Demand
4
1
5
3
2
6
7
9
8
Fossil Depletion
3
1
9
2
4
8
5
7
6
Water Depletion
9
4
7
8 6
3
5
2
1
Particulate Matter
Formation
7
3
1
5
2
4
6
9
8
Photochemical Oxidant
A
1
7
Q
O
Formation
L
J
J
Eutrophication
6
3
1
5
2
4
7
9
8
Acidification
9
1
8
4
2
5
3
7
6
Ozone Depletion
1
8
9
5
2
7
6
4
3
Black Carbon & Short-
A
f.
1
•s
9
~L
c
q
7
Lived Climate Pollutants
4-26
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Conclusions and Next Steps
5. Conclusions and Next Steps
This study developed an LCA of commonly used cookstove fuels and potentially cleaner
alternatives. LCA allows for a holistic assessment of the life cycle impacts of the fuel, including
not only the impacts at point of use of the fuel but also the impacts associated with fuel feedstock
production, fuel processing, and distribution. In addition to examining life cycle impacts for
individual cookstove fuels in China and India, impacts of the current fuel mix and possible future
changes to the fuel mix used in cookstoves were assessed.
Stove efficiency was found to be a key parameter driving impact results in both countries.
Fuels used in stoves with higher efficiencies (e.g., LPG, kerosene, biogas, ethanol, natural gas,
electricity and biomass pellets) had generally lower environmental impacts compared to low
efficiency stoves burning traditional fuels (e.g., firewood, dung cake, crop residues, and coal). In
India, biogas consistently emerged as a low-impact fuel across the majority of life cycle impact
categories. Ethanol from sugarcane also performed well in most categories; however, higher water
depletion impacts were seen for this fuel since irrigation is required during cane production. This
could be a particular challenge in India, which is currently a water-stressed nation. None of the
other fuels exhibit such consistently high or low performance, although results for dung cake and
hard coal are often found on the lower end of environmental performance. Traditional fuels had
particularly high impacts for particulate matter formation and black carbon emissions. For China,
natural gas, biomass pellets, and LPG generally showed lower (better) life cycle impacts in most
categories, with some exceptions. The various forms of coal investigated emerged as having
consistently worse relative environmental performance. These impacts are also transferred to
electricity based systems that also rely upon coal as a major fuel source. Water impacts were also
significant for electricity due to the contribution of hydroelectric power to the grid mix.
Establishments of dams for hydropower leads to notable evaporative losses. The findings from the
individual cooking fuel type analysis were then leveraged to understand the results from the fuel
mix scenarios.
5.1 Key Takeawavs
The following are the key takeaways from the comparison of the environmental footprint
of the baseline and possible cooking fuel mixes in India:
• Firewood makes the largest contribution to GCCP across all fuel mix scenarios,
since firewood makes up roughly 30% to 50% of fuel use, depending on the
scenario, and 41% of harvested wood in India is considered non-renewable.
• If households are able to replace firewood with another fuel with low climate
change impacts, such as biogas from dung, ethanol from sugarcane, or biomass
pellets, the environmental footprint of the cooking fuel mix will improve.
• The highest energy demand comes from the use of firewood and dung which are
used within traditional cookstoves. The traditional mud stoves used with these fuels
are extremely inefficient, which increases amount of fuel (and therefore, energy)
required to deliver a GJ of useful cooking energy, compared to more efficient
cookstoves used for processed fuels.
5-1
-------
Conclusions and Next Steps
• Increasing use of electricity (whether India's current electrical grid or a cleaner
grid) would reduce energy demand; however, the improvement is small due to
the fact that the electricity grid mix has a high percentage of fossil fuels.
• The lowest CED would be realized by replacing firewood and dung use with either
advanced liquid fuels or biomass pellets using a high efficiency stove.
• The current mix of cookstove fuels in India has the lowest water depletion impacts
compared to all the future scenarios. Increased electricity usage would greatly
increase water depletion due to more evaporative water loss associated with
hydroelectric dams. While it is desirable to move towards a cleaner grid mix by
replacing coal with electricity from renewable sources, the increase in water
consumption due to hydropower is noteworthy given the high water stress levels in
India.
• Particulate matter and photochemical oxidant formation from cookstoves in India
could both be reduced if any of the potential future cookstove fuel mix scenarios
were achieved, especially in the scenarios where dung cake or firewood are
replaced with cleaner burning fuels such as LPG, kerosene, biogas, or biomass
pellets.
• Even though dung cake currently only provides about 10% or less of total cookstove
energy for Indian households, its combustion results in a large quantity of land-
applied ash that has significant freshwater eutrophication impacts. However, the
nutrients from dung are likely necessary for agricultural production regardless of
whether the dung cake is burnt. Shifting to use of LPG, biogas, ethanol or biomass
pellets would reduce eutrophi cation considerably.
• Terrestrial acidification is not greatly affected by changes in cookstove fuel mixes,
except that acidification would rise with increased electricity use due to higher SOx
emissions from greater use of coal.
• Except for scenarios where biomass is replaced with another bio-based fuel like
biogas or biomass pellets, the current fuel mix scenario has the lowest ozone
depletion impacts.
• Since traditional biomass is the main source of black carbon emissions shifting the
cookstove fuel mix towards fossil fuels or processed biomass fuels would result in
decreased impacts.
The following are the key takeaways from the comparison of the environmental footprint
of the baseline and possible cooking fuel mixes in China:
• Replacing some coal use with LPG or biomass pellets or greater use of a cleaner
electricity grid would significantly reduce GCCP, CED, and fossil depletion
impacts.
5-2
-------
Conclusions and Next Steps
• If households are able to replace coal with another fuel with low climate change
impacts, such as agricultural residues or biomass pellets, the GCCP of the cooking
fuel mix will improve.
• Replacing agricultural residue and fuelwood use with LPG or DME would cause
an increase in fossil depletion.
• The current cookstove fuels mix and the scenarios with agriculture residue
replacing fuel wood have the lowest water depletion impacts in comparison with
other future scenarios. Increased electricity usage would significantly increase
water depletion due to more evaporative water loss associated with hydroelectric
dams.
• Particulate matter formation from cookstoves in China could be reduced if any of
the potential future cookstove fuel mix scenarios were achieved with the exception
of increasing agricultural residue use. Replacing biomass or coal with LPG,
kerosene, DME, or biomass pellets is especially effective. Even replacing coal
powder with coal briquettes would have a beneficial effect.
• Replacing traditional biomass or coal powder with LPG or biomass pellets or
increasing use of electricity with a cleaner grid would lead to reduced
photochemical oxidant formation impacts.
• Increasing agricultural residue use would increase freshwater eutrophication
impacts, while all other potential cookstove fuel mix scenarios diminish
eutrophi cation impacts compared to the baseline scenario.
• In scenarios where coal use is shifted to other fuels, terrestrial acidification
decreases. However, acidification would rise with increased electricity use due to
higher SOx emissions from greater use of coal in the generation of electricity.
• SOx emissions from combustion of fossil fuels such as LPG, coal combustion at
power plants, kerosene, and natural gas reduce radiative forcing while traditional
biomass emissions raise black carbon impacts. Thus, replacing inefficient biomass
cookstoves with a highly efficient LPG cookstove would lower black carbon
emissions and resulting impacts.
Overall trends and observations about similarities and differences in LCA results for India
and China include the following:
• The production and use of coal requires the most energy and has the greatest
amount of climate change potential. Therefore, any reduction of coal will result in
a better environmental footprint for the cooking fuel use within either country.
• Processed biomass energy sources such as biogas from dung in India and biomass
pellets in China perform well across many of the LCA results categories in
comparison to both traditional and fossil fuels. Scenarios where these fuels partially
5-3
-------
Conclusions and Next Steps
displace traditional biomass show some promise of reducing point of use emissions
in the home that can be harmful to human health without significant tradeoffs such
as increased global climate change potential or water depletion.
• Increased use of LPG in the future could also result in lower impacts for most LCA
results categories in both countries. However, this is only true for certain scenarios
where LPG replaces the worst performing fuels such as dung in India and coal in
China.
• While increasing use of electric cookstoves will not decrease GCCP, CED, and
fossil depletion impacts in India due to the large share of electricity that is generated
from coal combustion, replacing use of coal cookstoves with electric cookstoves in
China does result in reductions in these impact categories largely because the
efficiency of the electric cookstove is so much higher than the efficiency of the coal
cookstoves used in the home, and because some of the grid electricity is derived
from cleaner, non-fossil sources such as hydropower.
• Finally, a large portion of energy demand and global climate change results
originates from the use phase of the life cycle of the cooking fuels. The evaluated
fuels have a range of heating values; however, when cooking, the amount of useful
energy delivered to the cookstove depends not only on the energy content of the
fuel, but also on the cookstove efficiency. If the cookstove has a low efficiency,
more fuel must be used to provide a given amount of cooking energy. If more fuel
is required due to the use of a low efficiency stove, the benefits of using a fuel with
a low environmental profile could be offset.
5.2 Next Steps
This research built a framework model for examining the life cycle impacts of cookstove
fuels in developing countries. There are a number of other research questions to examine within
the LCA model, including refining modeling assumptions or using alternative modeling
approaches. Several topics that may warrant further research include:
• While the focus of this study was on the cooking fuel supply-chain, the overall
efficiency of the stove proved to be a key parameter influencing the environmental
performance of the scenarios investigated. Future research tasks will involve
analyzing ranges for assumed efficiencies by stove type to understand the potential
minimum and maximum air emissions at point of use.
• As discussed in Chapter 2 Section 2.3, this study employed the cut-off allocation
method. In this method, all burdens for the specified unit process are allocated to
the primary product for a process that has multiple co-products. Several fuels
examined such as crop residues, ethanol, and biogas are from multi-product output
processes. For crop residues, no burdens for primary cultivation of the crop were
assigned to the residues. Impacts may increase notably if choosing a different
allocation method that partitions some of these burdens to the residue.
5-4
-------
Conclusions and Next Steps
• Electricity is often a co-benefit of ethanol production. This study did not include a
credit for grid electricity displaced by electricity co-produced with ethanol.
Inclusion of this credit could decrease the overall environmental impacts for
ethanol.
• Additionally, biogas results in digested sludge which may be land applied to benefit
household level crop production. The potential incremental increase in crop
production at the household was not evaluated in this assessment.
• Increasing the infrastructure and associated maintenance for some of the fuel
scenarios assessed may have notable impacts if the current infrastructure in China
and India cannot support the production volume increase. While this study excluded
infrastructure from its scope, the relative impacts of increasing infrastructure and
associated infrastructure maintenance for "clean" cooking fuel types could be
investigated in the next research steps.
• It is apparent that there is a larger difference in environmental impacts between
fuels than between the fuel mix scenarios; therefore, the study will investigate
other, more differentiated scenarios. These future scenarios will consider how to
optimize human and environmental impacts of cookstove fuels. Additional research
will be conducted to understand the timeframe for when these fuels might penetrate
urban or rural regions. More fuel mix scenarios will also be considered, such as
expansion of piped natural gas in urban areas of China.
Conducting sensitivity analyses on these key allocation and scenario questions, and other
assumptions such as the portion of fuel wood estimated to be sustainable in each country, would
provide insight into the relative range of each fuel's environmental impact. This study collected
multiple data points for energy inputs and emissions across the life cycle of each fuel where
possible. Building on this robust foundation of existing data collected, uncertainty analyses using
the Monte Carlo method may be performed to better interpret the range in results and determine
significant differences between cooking fuel type burdens.
In addition to these sensitivity analyses, alternate visualizations of the results could help in
the interpretation of the study findings. The magnitude of impact assessment results is often
difficult to interpret. Normalization is an optional step in LCA that aids in understanding the
significance of the impact assessment results. In future research to update and extend this study,
normalization will be conducted by dividing the impact category results by a normalized value.
The normalized value is typically the environmental burdens of the region of interest either on an
absolute or per capita basis. In this task, we will evaluate normalized impact scores between impact
categories to inform discussion of relative magnitude (and therefore importance) of different
impacts from cooking fuels. The geographic scope of the analysis may also be extended to include
other regions of the world such as Africa.
The environmental and human health impacts from burning traditional fuels are widespread
in the developing world. The LCA model built here can serve as the basis to further understanding
of the quantifiable tradeoffs between fuel choices to help spur initiatives to change cooking fuel
use patterns. This work can be continually improved upon as it is enhanced with additional
5-5
-------
Conclusions and Next Steps
sensitivity and uncertainty analyses, and more current data on cookstove fuel impacts become
publicly available.
The data presented in this report will be part of an EPA tool that provides users access to
data and facilitates analyses to evaluate differences in fuels and other parameters that affect
selection of future cookstove fuels. The tool will provide information on the LCA environmental
tradeoffs that affect the environmental performance of cookstove fuels. The tool will also link to
a Global Alliance for Clean Cookstoves' tool - the Fuel Analysis, Comparison and Integration
Tool (FACIT) - providing information on environmental, economic and social impacts associated
with several types of fuels used in cookstoves.
5-6
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Appendix A - Detailed LCI Unit Process Tables
APPENDIX A: DETAILED LCI UNIT PROCESS TABLES
The following tables provide the background LCI unit process data tables for both India
and China. Table A-l provides the Code Key for the each of the LCI unit process tables. Table A-
2 presents a data quality key for all data quality indicators in each LCI unit process table. Table
A-3 provides further description of the data quality indicators used. Table A-4 through Table A-
28 show all energy and emissions data for each unit process used within the LCI models for India.
Table A-29 through Table A-72 display all energy and emissions data for each unit process used
within the LCI models for China.
Table A-l. Code Key for LCI Tables
Category
Code
Full Name
Input Groups
4
From Nature
5
From Technosphere
0
Reference Product
Output Groups
2
Co - Product
4
To Nature
CN
China
IN
India
Countries [a]
MA
Morocco
RER
Europe
UCTE
Union for Co-ordination of Transmission of Electricity
US
United States
a] Countries indicate the location of the flow used for purposes of modeling. In some cases, India and China
specific flows were not available, so other country datasets were applied, as indicated by the country code in the unit
process tables.
Table A-2. Data Quality Index Methodology [1]
Indicator
Score
1
2
3
4
5
Source
Reliability
(for most
applications,
data verified based
on measurements
data verified
based on some
assumptions
and/or standard
science and
engineering
calculations
data verified with
many
assumptions, or
non-verified but
from quality
source
qualified
estimate
non-qualified
estimate
source quality
guidelines are
only factor)
source quality guidelines met
source quality guidelines not met
data cross checks,
greater than or
equal to 3 quality
sources
2 or fewer data sources available for
cross check, or data sources available
that do not meet quality standards
no data available for cross check
A-l
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-2. Data Quality Index Methodology [1]
Indicator
Score
1
2
3
4
5
Completeness
representative data
from a sufficient
sample of sites over
an adequate period
of time
smaller number
of sites, but an
adequate period
of time
sufficient number
of sites, but a less
adequate period
of time
smaller number
of sites and
shorter periods
or incomplete
data from an
adequate
number of sites
or periods
representativeness
unknown or
incomplete data sets
Temporal
Correlation
less than 3 years of
difference to year of
study/current year
less than 6 years
of difference
less than 10 years
of difference
less than 15
years of
difference
age of data
unknown or more
than 15 years of
difference
Geographical
Correlation
data from area
under study
average data from
larger area or
specific data from
a close area
data from area
with similar
production
conditions
data from area
with slightly
similar
production
conditions
data from unknown
area or area with
very different
production
conditions
Technological
Correlation
data from
technology, process,
or materials being
studied
data from a different technology using
the same process and/or materials
data on related
process or
material using
the same
technology
data or related
process or material
using a different
technology
Uncertainty
Correlation
data sample
uncertainty
measurement
information is
available; normal or
logarithmic normal
distribution
data sample
uncertainty
measurement
information is
available; triangle
distribution
data sample
uncertainty
measurement
information
available;
uniform
distribution
No uncertainty measurement
information is available or data sample
size = 1
Precision
Correlation
logarithmic normal
or normal
distribution and low
geometric standard
or standard
deviation
logarithmic normal or normal distribution and high
geometric standard or standard deviation; or triangle or
uniform distribution
no dispersion
information
available
l]Taken from US Federal Digital Commons Life Cycle Inventory unit Process Template; originally derived from
NETL LCI&C Guideline Document, adapted from Weidema and Wenaes.
A-2
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-3. Data Quality Indicator Descriptions [1]
Source Reliability — This indicator relates to the quality of the data source and the verification of the data collection methods used within the source.
Data Verification — Source data that have been verified within error bounds by either the source author (with a high level of transparency) or the LCI modeler.
Verification can be done by measurement, including on-site checking, recalculation, or mass or energy balance analysis. If the source data cannot be verified
without making assumptions (e.g., not enough data are available to close the mass/energy balance), then the score should be a 2 or 3, depending on the number
of assumptions. If no source data are available, a qualified estimate from an expert in the field should receive a score of 4, and an estimate from a non-expert
should receive a score of 5. Mostly applicable to primary data.
Source Quality Guidelines — The highest quality source should be
o From a peer reviewed journal or a government sponsored study. If the source is an LCA, it must meet ISO requirements,
o Publicly available either for free or at cost, or directly representative of the process of interest,
o Written/published by an unbiased party,
o An unbiased survey of experts or process locations.
When the source used for data is a reputable model that does not specifically meet the above criteria, it is the discretion of the modeler to determine the rank of
the source. An example for justification would be if the data have been used in published reports that met the data quality standards.
Data Cross-Check — The number of sources that verify the same data point or series, within reason. As a general benchmark, a high standard is greater than or
equal to three data cross checks with quality approved sources. This typically refers to primary data, and if no other data sources are available, this can be
omitted.
Completeness — This indicator quantifies the statistical robustness of the source data. This ranking is based on how many data points were taken, how
representative the sample is to the studied process, and whether the data were taken for an acceptable time period to even out normal process fluctuations. The
following examples are given to help clarify this indicator.
Temporal Correlation ~ This indicator represents how well the time period in which the data were collected corresponds with the year of the study. If the
study is set to evaluate the use of a technology from 2000 to 2040, data from 1970 would not be very accurate. It is important when assigning this ranking to
take notice of any discrepancies between the year the source was published and the year(s) the data were collected.
Geographical Correlation — This indicator represents the appropriateness between the region of study and the source data region. This indicator becomes
important when comparing data from different countries. For example, technological advances might reasonably be expected to develop differently in different
countries, so efficiency and energy use might be very different. This is also important when looking at best management practices for carbon mitigation.
Technological Correlation — This indicator embodies all other differences that may be present between the study goals and the data source. From the above
example, using data for a type of biomass that is not being studied in the LCA should result in a lower technological representativeness ranking.
Uncertainty Correlation — This indicator represents the characterization of the dispersion of values attributed to a measured quantity; it has probabilistic basis
and relates to how well the measurement upon which the input or output value is derived was performed.
Precision Correlation — This indicator represents the degree of spread or variability in a set of data values or measurements relative to the mean of the data
values; it reflects the degree to which the measurement/experimental system used to derive the input/output value is reproducible and repeatable to achieve the
same results.
l]Taken from US Federal Digital Commons Life Cycle Inventory unit Process Template; originally derived from NETL LCI&C Guideline Document, adapted
from Weidema and Wenaes.
A-3
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Appendix A - Detailed LCI Unit Process Tables
India LCI Unit Process Tables
Table A-4. Biogas; Production from Dung; At Anaerobic Digester (IN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Biogas; Production From Dung;
at Anaerobic Digester
IN
1.00
kg
1
4
Energy, Calorific Value, in
Organic Substance
energy
resources
renewable energy
resources
18.2
MJ
2
2
2
2
1
4
5
1
4
Carbon Dioxide
air
unspecified
5.7E-05
kg
2
2
2
2
1
4
5
1,2,3,4,5,6
4
Methane
air
unspecified
0.036
kg
2
2
2
2
1
4
5
1,2,3,4,5,6
2
Digested Slurry
IN
1.06
kg
2
2
2
2
1
4
5
1,2,3,4,5,6
4
Nitrogen
air
unspecified
5.3E-4
kg
2
2
2
2
1
4
5
1,2,3,4,5,6
4
Hydrogen Sulfide
air
(unspecified)
2.2E-5
kg
2
2
2
2
1
4
5
1,2,3,4,5,6
4
Water, unspecified Natural
Origin/kg
resource
in water
10.4
kg
2
2
2
2
1
4
5
1
[1] Singh P, H., Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian households. International
Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Environmental Engineering 2(1): 20-
30.
[3] UN (United Nations). 2007. Bagepalli CDM project: project definition document. https://cdm.unfccc.int/filestorage/s/c/62U354IQDXJKCZSPORVW01LYAG9H7T.pdf/121-
20130813-PDD.pdf?t=TnN8bnh5cTFyfDCrNtJ4UeZWTopC4hnYrrMO. Accessed 17 November 2015.
[4] Vivekanandan S. and G., Kamraj. 2011. Investigation on cow dung as co-substrate with pre-treated sodium hydroxide on rice chaff for efficient biogas production. International
Journal of Science and Advanced Techno logy 1(4): 76-80.
[5] Afrane G., and A. Ntiamoah. 2011. Comparative life cycle assessment of charcoal, biogas andLPG as cooking fuels in Ghana. Journal of Industrial Ecology. 15(4): 539-549.
[6] Boijesson P., and M. Berglund. 2006. Environmental systems analysis of biogas systems-Part 1: fuel-cycle emissions. Biomass and Bioenergy 30(5): 469-485.
A-4
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-5. Charcoal; Production from Wood; At Earth Mound Kiln (IN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Completeness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Charcoal; Production from Wood; at Earth
Mound Kiln
IN
1.00
kg
1
4
Energy, Gross Calorific Value, in Biomass,
Primary Forest
resource
biotic
11.8
MJ
2
2
3
3
1
4
5
2
4
Energy, Gross Calorific Value, in Biomass
resource
biotic
37.2
MJ
2
2
3
3
1
4
5
2
4
Carbon Dioxide
air
unspecified
1.25
kg
2
2
3
3
1
4
5
1
4
Carbon Monoxide
air
unspecified
0.28
kg
2
2
3
3
1
4
5
1
4
Methane
air
unspecified
0.030
kg
2
2
3
3
1
4
5
1
4
Nitrogen Oxides
air
unspecified
3.8E-05
kg
2
2
3
3
1
4
5
1
4
Dinitrogen Monoxide
air
unspecified
4.8E-05
kg
2
2
3
3
1
4
5
1
4
Particulates, > 2.5 Urn, and < lOum
air
unspecified
0.090
kg
2
2
3
3
1
4
5
1
4
NMVOC, Non-Methane Volatile Organic
Compounds, unspecified Origin
air
unspecified
0.013
kg
2
2
3
3
1
4
5
1
5
Disposal, Wood Ash Mixture, Pure, 0% Water,
to Land fanning
CH
0.062
kg
2
2
3
3
1
4
5
1
[1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
A-5
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-6. Electricity; Average Production; At Consumer; Production Mix (IN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Completeness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Electricity; average production; at consumer; production mix
IN
1.00
kWh
1
5
Electricity, hard coal, at power plant
IN
0.92
kWh
3
2
2
2
2
4
5
1
5
Electricity, natural gas, at power plant
IN
0.11
kWh
3
2
2
2
2
4
5
1
5
Electricity, oil, at power plant
IN
0.026
kWh
3
2
2
2
2
4
5
1
5
Electricity, hydropower, at reservoir power plant, non alpine
regions
RER
0.14
kWh
3
2
2
4
3
4
5
1
5
Electricity, nuclear, at power plant
UCTE
0.038
kWh
3
2
2
4
3
4
5
1
5
Electricity, at wind power plant
RER
0.033
kWh
3
2
2
4
3
4
5
1
5
Electricity, at cogen with biogas engine, allocation exergy
CH
0.022
kWh
3
2
2
4
3
4
5
1
5
Electricity, production mix photovoltaic, at plant
US
0.0024
kWh
3
2
2
4
3
4
5
1
[1] IEA (International Energy Agency). 2012. India: Electricity and heat for 2012
http://www.iea.org/statistics/statisticssearch/report/?country=INDIA&product=electricityandheat&yeai=2012. Accessed 17 November 2015.
A-6
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-7. Hard Coal; Extraction; At Open Cast Mine (IN)
s.
Data Quality
Input groui
Output grou
Flow
Category
Subcategor
Location
Amount
Unit
Reliability
Complete-
ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Hard Coal; Extraction; at
Open Cast Mine
IN
1.00
kg
1
4
Coal, Hard
resource
in ground
1.00
kg
2
2
3
1
2
4
5
1
5
Diesel; Production From
Crude Oil; at Plant;
Production Mix
IN
6.9E-04
kg
2
2
3
1
2
4
5
1,3,4
4
Carbon Dioxide
air
unspecified
0.0022
kg
2
2
3
1
2
4
5
1,3,4
4
Carbon Monoxide
air
unspecified
7.2E-04
kg
2
2
3
1
2
4
5
1,3,4
4
Methane
air
unspecified
9.5E-04
kg
2
2
3
1
2
4
5
1,3,4
4
Nitrogen Oxides
air
unspecified
2.0E-04
kg
2
2
3
1
2
4
5
1,4,5
4
Dinitrogen Monoxide
air
unspecified
9.6E-08
kg
2
2
3
1
2
4
5
1,3,4
4
Particulates, > 2.5 urn,
and < lOum
air
unspecified
0.0029
kg
2
2
3
1
2
4
5
1,3,4
4
NMVOC, Non-Methane
Volatile Organic
Compounds, unspecified
Origin
air
unspecified
2.5E-06
kg
2
2
3
1
2
4
5
1,3,4
4
Sulfur Dioxide
air
unspecified
2.1E-05
kg
2
2
3
1
2
4
5
1,3,4
4
COD, Chemical Oxygen
Demand
water
unspecified
1.5E-05
kg
2
2
3
1
2
4
5
1,3,4
4
Suspended Solids,
unspecified
water
unspecified
4.2E-05
kg
2
2
3
1
2
4
5
1,3,4
4
Fluorine
water
unspecified
1.2E-06
kg
2
2
3
1
2
4
5
1,3,4
4
Chlorine
water
unspecified
3.8E-05
kg
2
2
3
1
2
4
5
1,3,4
A-7
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-7. Hard Coal; Extraction; At Open Cast Mine (IN)
a
Data Quality
Input groui
Output grou
Flow
Category
Subcategor
Location
Amount
Unit
Reliability
Complete-
ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Sulfur
water
unspecified
4.2E-04
kg
2
2
3
1
2
4
5
1,3,4
4
Nitrate
water
unspecified
2.0E-08
kg
2
2
3
1
2
4
5
1,3,4
4
Zinc
water
unspecified
8.6E-07
kg
2
2
3
1
2
4
5
1,3,4
4
Manganese
water
unspecified
7.2E-06
kg
2
2
3
1
2
4
5
1,3,4
4
Water, Well, in Ground
resource
in ground
5.6E-04
m3
2
2
2
3
2
4
5
2
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Dones, R., C., Bauer, and R., Bollinger, et al. 2007. Sachbilanzen von Energiesvstemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. [Life cycle of energy systems: foundations for the ecological comparison of energy
systems and the inclusion of energy systems in life cycle assessment for the Switzerland.] Final report ecoinvent No. 6-VT, Paul Scherrer Institut Villigen, Swiss
Centre for Life Cycle Inventories, Dubendorf, CH.
[3] Ghose, M.K. 2004. Emission factors for the quantification of dust in Indian coal mines. Journal of Scientific and Industrial Research. 63(9): 763-768.
[4] Ghose, M.K. 2007. Generation and quantification of hazardous dusts from coal mining in the Indian context. Enviromnental Monitoring and Assessment
130(1-3): 35-45.
A-8
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-8. LPG; Production from Natural Gas; at Plant; Production Mix (IN)
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
LPG; Production from Natural Gas; At Plant;
Production Mix
IN
1.00
kg
1
4
NMVOC, Non-Methane Volatile Organic
Compounds, unspecified Origin
air
unspecified
5.0E-04
kg
2
2
2
1
1
4
5
1
4
Sulfur Dioxide
air
unspecified
0.035
kg
2
2
2
1
1
4
5
1
4
Carbon Dioxide
air
unspecified
0.064
kg
2
2
2
1
1
4
5
1
4
Carbon Monoxide
air
unspecified
1.0E-04
kg
2
2
2
1
1
4
5
1
4
Methane
air
unspecified
0.013
kg
2
2
2
1
1
4
5
1
4
Nitrogen Oxides
air
unspecified
0.0014
kg
2
2
2
1
1
4
5
1
4
Dinitrogen Monoxide
air
unspecified
5.2E-06
kg
2
2
2
1
1
4
5
1
4
Particulates, >2.5 urn, and < lOum
air
unspecified
4.4E-04
kg
2
2
2
1
1
4
5
1
5
Electricity; Average Production; At Consumer;
Production Mix
IN
0.30
kWh
2
2
2
1
2
4
5
1
5
Natural Gas; Extraction; At Plant; Production Mix
IN
8.61
kg
2
2
2
1
1
4
5
1
5
Transport, Natural Gas, Pipeline, Long Distance
RER
2.50
t*km
2
2
2
3
4
5
1
2
Lean Gas; Production from Natural Gas; At Plant;
Production Mix
IN
11.4
kg
2
2
2
1
1
4
5
1
2
Naptha; Production from Natural Gas; At Plant;
Production Mix
IN
0.34
kg
2
2
2
1
1
4
5
1
4
Ammonia
air
unspecified
7.3E-06
kg
2
2
2
1
1
4
5
1
4
Aldehydes, unspecified
air
unspecified
3.7E-06
kg
2
2
2
1
1
4
5
1
4
Water, unspecified Natural Origin/kg
resource
in water
0.20
kg
2
2
2
1
1
4
5
1
5
Propane/ Butane, At Refinery
RER
0.0043
kg
2
2
2
4
3
4
5
1
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-9
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-9. LPG from Crude Oil; Petroleum Refining; At Plant; Production Mix (IN)
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
LPG from crude oil; petroleum refining; at
plant; production mix
IN
1.00
kg
1
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
6.3E-04
kg
2
1
1
3
1
2
1
1
4
Sulfur dioxide
air
unspecified
0.048
kg
2
1
1
3
1
2
1
1
4
Carbon dioxide
air
unspecified
4.59
kg
2
1
1
3
1
2
1
1
4
Carbon monoxide
air
unspecified
1.22
kg
2
1
1
3
1
2
1
1
4
Methane
air
unspecified
0.022
kg
2
1
1
3
1
2
1
1
4
Nitrogen oxides
air
unspecified
0.017
kg
2
1
1
3
1
2
1
1
4
Dinitrogen monoxide
air
unspecified
3.3E-05
kg
2
1
1
3
1
2
1
1
4
Particulates, >2.5 urn, and < lOum
air
unspecified
0.023
kg
2
1
1
3
1
2
1
1
5
Electricity; average production; at
consumer; production mix
IN
0.024
kWh
2
1
1
1
1
1
1
1
5
Crude oil; extraction; at plant; production
mix
IN
27.3
kg
2
1
1
1
1
1
1
1
4
Ammonia
air
unspecified
0.0049
kg
2
1
1
3
1
2
1
1
4
Aldehydes, unspecified
air
unspecified
0.0016
kg
2
1
1
3
1
2
1
1
5
Propane/ butane, at refinery
RER
1.00
kg
2
1
1
5
1
3
1
1
5
Transport, combination truck, average fuel
mix
US
5.47
t*km
2
1
1
5
1
3
1
1
5
Operation, freight train
RER
16.4
t*km
2
1
1
5
1
3
1
1
2
Kerosene; production from crude oil; at
plant; production mix
IN
1.02
kg
2
1
1
1
1
1
1
1
2
Motor spirit; production from crude oil; at
plant; production mix
IN
3.47
kg
2
1
1
1
1
1
1
1
A-10
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-9. LPG from Crude Oil; Petroleum Refining; At Plant; Production Mix (IN)
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
2
Naptha; production from crude oil; at
plant; production mix
IN
2.33
kg
2
1
1
1
1
1
1
1
2
Other petroleum products; production
from crude oil; at plant; production mix
IN
3.09
kg
2
1
1
1
1
1
1
1
2
Fuel oil; production from crude oil; at
plant; production mix
IN
2.72
kg
2
1
1
1
1
1
1
1
2
Diesel; production from crude oil; at plant;
production mix
IN
10.4
kg
2
1
1
1
1
1
1
1
5
Diesel; production from crude oil; at plant;
production mix
IN
0.038
kg
2
1
1
1
1
1
1
1
5
Transport, transoceanic freight ship
OCE
9.57
t*km
2
1
1
1
1
1
1
4
Water, surface
resource
in water
34.8
kg
2
1
1
1
1
1
1
1
4
Water, ground
resource
in water
7.84
kg
2
1
1
1
1
1
1
1
5
Fuel oil; production from crude oil; at
plant; production mix
IN
0.62
kg
2
1
1
1
1
1
1
1
2
Jet fuel; production from crude oil; at
plant; production mix
IN
1.27
kg
2
1
1
1
1
1
1
1
4
Catalyst waste
final-waste-flow
unspecified
0.0014
kg
2
1
1
1
1
1
1
1
4
BOD5, Biological Oxygen Demand
water
unspecified
5.1E-05
kg
2
1
1
2
1
2
1
1
4
COD, Chemical Oxygen Demand
water
unspecified
4.3E-04
kg
2
1
1
2
1
2
1
1
4
Suspended solids, unspecified
water
unspecified
6.8E-05
kg
2
1
1
2
1
2
1
1
4
Phenol
water
unspecified
1.2E-06
kg
2
1
1
2
1
2
1
1
4
Oils, unspecified
water
unspecified
1.7E-05
kg
2
1
1
2
1
2
1
1
4
Sulfide
water
unspecified
1.7E-06
kg
2
1
1
2
1
2
1
1
A-ll
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-9. LPG from Crude Oil; Petroleum Refining; At Plant; Production Mix (IN)
a
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Ammonia
water
unspecified
5.1E-05
kg
2
1
1
2
1
2
1
1
4
Phosphorus
water
unspecified
1.0E-05
kg
2
1
1
2
1
2
1
1
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-12
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-10. Molasses; Production from Sugarcane; At Plant (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Molasses; production from sugarcane; at
plant
IN
0.050
kg
1
2
Sugar; production from sugarcane; at plant
IN
0.091
kg
2
2
2
1
1
4
5
1
2
Electricity; average production; at
consumer; production mix
IN
0.054
kWh
2
2
3
1
1
4
5
1,2
5
Sugarcane; production; at farm
IN
1.00
kg
2
2
2
1
1
4
5
1
5
Sulphur dioxide, liquid, at plant
RER
0.0015
kg
2
2
2
4
3
4
5
1
5
Limestone, at mine
US
0.0019
kg
2
2
2
4
3
4
5
1
5
Sodium hydroxide, 50% in FLO.
production mix, at plant
RER
5.0E-04
kg
2
2
2
4
3
4
5
1
5
Single superphosphate, as P2O5, at regional
storehouse
RER
1.0E-04
kg
2
2
2
4
3
4
5
1
5
Soda, powder, at plant
RER
3.0E-05
kg
2
2
2
4
3
4
5
1
5
Chemicals organic, at plant
GLO
1.0E-05
kg
2
2
2
2
3
4
5
1
5
Lubricating oil, at plant/RER U
RER
6.0E-04
kg
2
2
2
4
3
4
5
1
4
Water, unspecified natural origin/kg
resource
in water
0.030
kg
2
2
2
1
1
4
5
1
5
Phosphoric acid, industrial grade, 85% in
H2O, at plant
RER
1.0E-05
kg
2
2
2
4
3
4
5
1
5
Transport, combination truck, average fuel
mix
US
0.013
t*km
2
2
2
4
3
4
5
1
[1]Tsiropoulos, I., A.P.C., Faaij, J.E.A. Seabra, et al. 2014. Life cycle assessment of sugarcane ethanol production in India in comparison to Brazil. International
Journal of Lifecycle Assessment 19: 1049-1067.
[2]Prakash R.. A., Henham, and I.K. Bhat. 2005. Gross carbon emissions from alternative transport fuels in India. Energy for Sustainable Development 9(2): 10-
A-13
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-ll. Sugarcane; Production; At Farm (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Sugarcane; production; at farm
IN
1.00
kg
1
4
Occupation, arable
resource
land
0.17
nf*a
2
2
2
1
1
4
5
1
4
Water, unspecified natural origin/m3
resource
in water
0.060
m3
2
2
2
1
1
4
5
1
5
Ammonium sulphate, as N, at regional storehouse
RER
4.2E-04
kg
2
2
2
4
2
4
5
1
5
Ammonium nitrate, as N, at regional storehouse
RER
4.2E-04
kg
2
2
2
4
2
4
5
1
5
Diammonium phosphate, as N, at regional
storehouse
RER
3.7E-04
kg
2
2
2
4
2
4
5
1
5
Potassium nitrate, as N, at regional storehouse
RER
2.5E-04
kg
2
2
2
4
2
4
5
1
5
Urea, as N, at regional storehouse
RER
0.0012
kg
2
2
2
4
2
4
5
1
5
Diammonium phosphate, as P2O5, at regional
storehouse
RER
6.2E-04
kg
2
2
2
4
2
4
5
1
5
Single superphosphate, as P2O5, at regional
storehouse
RER
4.0E-04
kg
2
2
2
4
2
4
5
1
5
Triple superphosphate, as P2O5, at regional
storehouse
RER
2.0E-04
kg
2
2
2
4
2
4
5
1
5
Phosphate rock, as P2O5, beneficiated, dry, at plant
MA
7.0E-05
kg
2
2
2
4
2
4
5
1
5
Potassium chloride, as K20, at regional storehouse
RER
8.0E-04
kg
2
2
2
4
2
4
5
1
5
Potassium nitrate, as K20, at regional storehouse
RER
8.0E-06
kg
2
2
2
4
2
4
5
1
5
Potassium sulphate, as K20, at regional storehouse
RER
8.0E-06
kg
2
2
2
4
2
4
5
1
5
Herbicides, at regional storehouse
RER
5.6E-05
kg
2
2
2
4
2
4
5
1
5
Triazine-compounds, at regional storehouse
RER
1.1E-05
kg
2
2
2
4
2
4
5
1
5
Phenoxy-compounds, at regional storehouse
RER
3.0E-06
kg
2
2
2
4
2
4
5
1
5
Glyphosate, at regional storehouse
RER
4.0E-06
kg
2
2
2
4
2
4
5
1
5
Diuron, at regional storehouse
RER
9.0E-06
kg
2
2
2
4
2
4
5
1
5
Insecticides, at regional storehouse
RER
5.0E-05
kg
2
2
2
4
2
4
5
1
A-14
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-ll. Sugarcane; Production; At Farm (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
5
Fungicides, at regional storehouse
RER
3.0E-06
kg
2
2
2
4
2
4
5
1
5
Electricity; average production; at consumer;
production mix
IN
0.012
kWh
2
2
2
1
1
4
5
1
5
Diesel, combusted in industrial equipment
US
5.4E-04
1
2
2
2
3
2
4
5
1
4
Energy, gross calorific value, in biomass
resource
biotic
4.95
MJ
2
2
2
3
2
4
5
1
4
Dinitrogen monoxide
air
unspecified
0.30
kg
2
2
2
3
2
4
5
2
4
Phosphorus
water
unspecified
7.3E-06
kg
2
2
2
3
2
4
5
1
1] Tsiropoulos, I., A.P.C., Faaij, J.E.A. Seabra, et al. 2014. Life cycle assessment of sugarcane ethanol production in India in comparison to Brazil. International
Journal of Lifecycle Assessment 19: 1049-1067.
[2] Macedo, I.C., J.E. A., Seabra, and J.E.A.R., Silva. 2008. Greenhouse gases emissions in the production and use of ethanol from sugarcane in Brazil: the
2005/2006 averages and a prediction for 2020. Biomass and Bioenergy 32(7): 582-595.
A-15
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-12. Ethanol; Production from Sugarcane Molasses; At Plant (IN)
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Ethanol; production from sugarcane molasses; at
plant
IN
1.00
kg
1
2
Electricity; average production; at consumer;
production mix
IN
0.060
kWh
2
2
2
1
1
4
5
1
5
Molasses; production from sugarcane; at plant
IN
5.06
kg
2
2
2
1
1
4
5
1
5
Sulphuric acid, liquid, at plant
RER
4.1E-04
kg
2
2
2
4
2
4
5
1
5
Magnesium sulphate, at plant
RER
1.1E-04
kg
2
2
2
4
2
4
5
1
5
Urea, as N, at regional storehouse
RER
0.0013
kg
2
2
2
4
2
4
5
1
5
Phosphoric acid, industrial grade, 85% in FLO, at
plant
RER
1.4E-04
kg
2
2
2
4
2
4
5
1
5
Chlorine, liquid, production mix, at plant
RER
3.8E-04
kg
2
2
2
4
2
4
5
1
5
Soda, powder, at plant
RER
6.0E-05
kg
2
2
2
4
2
4
5
1
5
Chromium oxide, flakes, at plant
RER
1.0E-04
kg
2
2
2
4
2
4
5
1
5
Sodium hydroxide, 50% in FLO, production mix, at
plant
RER
6.0E-04
kg
2
2
2
4
2
4
5
1
5
Zinc, primary, at regional storage
RER
1.2E-04
kg
2
2
2
4
2
4
5
1
5
Formaldehyde, production mix, at plant
RER
2.0E-05
kg
2
2
2
4
2
4
5
1
4
Water, unspecified natural origin/m3
resource
in water
0.011
m3
2
2
2
1
1
4
5
1
5
Transport, combination truck, average fuel mix
US
0.38
t*km
2
2
2
3
2
4
5
1
[1] Tsiropoulos, I., A.P.C., Faaij, J.E.A. Seabra, et al. 2014. Life cycle assessment of sugarcane ethanol production in India in comparison to Brazil. International
Journal of Lifecycle Assessment 19: 1049-1067.
A-16
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-13. Biomass Pellet Production, At Consumer (IN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Biomass pellets; at consumer
IN
1.00
1
4
Energy, gross calorific value, in biomass
resource
biotic
12.3
MJ
1
2
2
1
1
2
3
2,3
4
Energy, gross calorific value, in biomass, primary
forest
resource
biotic
5.41
MJ
1
2
2
1
1
2
3
2,3
5
Electricity; average production; at consumer;
production mix
IN
0.27
kWh
2
2
3
2
2
4
5
1
5
Transport, lorry >16t, fleet average
RER
0.060
t*km
2
2
3
2
2
4
5
1
5
Operation, freight train
RER
0.12
t*km
2
2
3
2
2
4
5
1
5
Disposal, wood untreated, 20% water, to sanitary
landfill
CH
0.29
kg
1
2
2
1
1
2
3
1
[1] Jungbluth N.. M., Chudacoff, and A., Dauriat, et al. 2007b. Life Cycle Inventories of Bioenergy. Final report ecoinvent data v2.0. Volume: 17. Swiss
Centre for LCI, ESU. Duebendorf and Uster, CH.ESU. Duebendorf and Uster, CH.
[2] Dalberg Global Development Advisors. 2013. India cookstoves and fuels market assessment. Global Alliance for Clean Cookstoves.
www.cleancookstoves.org/resources_files/india-cookstove-and-fuels-market-assessment.pdf. Accessed 6 October 2014.
[3] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
A-17
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-14. Crude Oil; Extraction; At Plant; Production Mix (IN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Crude oil; extraction; at plant; production mix
IN
1.00
kg
1
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
4.6E-05
kg
2
2
2
1
1
4
5
1
4
Sulfur dioxide
air
unspecified
3.9E-06
kg
2
2
2
1
1
4
5
1
4
COD, Chemical Oxygen Demand
water
unspecified
2.4E-05
kg
2
2
2
1
1
4
5
1
4
Suspended solids, unspecified
water
unspecified
2.4E-05
kg
2
2
2
1
1
4
5
1
4
Carbon dioxide
air
unspecified
0.046
kg
2
2
2
1
1
4
5
1
4
Carbon monoxide
air
unspecified
1.4E-04
kg
2
2
2
1
1
4
5
1
4
Methane
air
unspecified
0.0017
kg
2
2
2
1
1
4
5
1
4
Nitrogen oxides
air
unspecified
3.2E-04
kg
2
2
2
1
1
4
5
1
4
Dinitrogen monoxide
air
unspecified
1.0E-06
kg
2
2
2
1
1
4
5
1
4
Particulates, > 2.5 urn, and < lOum
air
unspecified
5.1E-05
kg
2
2
2
1
1
4
5
1
5
Diesel; production from crude oil; at plant; production
mix
IN
0.0070
kg
2
2
2
1
1
4
5
1
5
Electricity; average production; at consumer; production
mix
IN
0.020
kWh
2
2
2
2
2
4
5
1
4
Water, unspecified natural origin/kg
resource
in water
0.95
kg
2
2
2
1
1
4
5
1
5
Lubricating oil, at plant
RER
3.4E-04
kg
2
2
2
3
3
4
5
1
4
Oil, crude
resource
in ground
1.04
kg
2
2
2
1
1
4
5
1
4
BOD5, Biological Oxygen Demand
water
unspecified
7.0E-06
kg
2
2
2
1
1
4
5
1
4
Chloride
water
unspecified
1.4E-04
kg
2
2
2
1
1
4
5
1
4
Sulfate
water
unspecified
2.4E-04
kg
2
2
2
1
1
4
5
1
4
Phenol
water
unspecified
3.0E-07
kg
2
2
2
1
1
4
5
1
4
Oils, unspecified
water
unspecified
8.0E-06
kg
2
2
2
1
1
4
5
1
A-18
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-14. Crude Oil; Extraction; At Plant; Production Mix (IN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Dissolved organics
water
unspecified
5.0E-04
kg
2
2
2
1
1
4
5
1
4
Oil waste
final-waste-flow
unspecified
0.013
kg
2
2
2
1
1
4
5
1
[1] Singh
P, H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-19
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-15. Natural Gas; Extraction; At Plant; Production Mix (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Natural gas; extraction; at plant;
production mix
IN
1.00
kg
1
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
4.5E-05
kg
2
2
2
1
1
4
5
1
4
Sulfur dioxide
air
unspecified
3.8E-06
kg
2
2
2
1
1
4
5
1
4
COD, Chemical Oxygen Demand
water
unspecified
2.3E-05
kg
2
2
2
1
1
4
5
1
4
Suspended solids, unspecified
water
unspecified
2.3E-05
kg
2
2
2
1
1
4
5
1
4
Carbon dioxide
air
unspecified
0.045
kg
2
2
2
1
1
4
5
1
4
Carbon monoxide
air
unspecified
1.4E-04
kg
2
2
2
1
1
4
5
1
4
Methane
air
unspecified
0.0017
kg
2
2
2
1
1
4
5
1
4
Nitrogen oxides
air
unspecified
3.1E-04
kg
2
2
2
1
1
4
5
1
4
Dinitrogen monoxide
air
unspecified
9.0E-07
kg
2
2
2
1
1
4
5
1
4
Particulates, > 2.5 urn, and < lOum
air
unspecified
5.0E-05
kg
2
2
2
1
1
4
5
1
5
Diesel; production from crude oil; at
plant; production mix
IN
0.0069
kg
2
2
2
1
1
4
5
1
5
Electricity; average production; at
consumer; production mix
IN
0.020
kWh
2
2
2
2
2
4
5
1
4
Water, unspecified natural origin/kg
resource
in water
0.93
kg
2
2
2
1
1
4
5
1
5
Lubricating oil, at plant
RER
1.5E-03
kg
2
2
2
3
3
4
5
1
4
Gas, natural, in ground
resource
in ground
1.04
kg
2
2
2
1
1
4
5
1
4
BOD5, Biological Oxygen Demand
water
unspecified
7.0E-06
kg
2
2
2
1
1
4
5
1
4
Chloride
water
unspecified
1.4E-04
kg
2
2
2
1
1
4
5
1
4
Sulfate
water
unspecified
2.3E-04
kg
2
2
2
1
1
4
5
1
4
Phenol
water
unspecified
3.0E-07
kg
2
2
2
1
1
4
5
1
4
Oils, unspecified
water
unspecified
7.0E-06
kg
2
2
2
1
1
4
5
1
4
Dissolved organics
water
unspecified
4.9E-04
kg
2
2
2
1
1
4
5
1
4
Oil waste
final-waste-flow
unspecified
0.012
kg
2
2
2
1
1
4
5
1
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-20
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-16. Bottling; LPG from Crude Oil; At Plant (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Bottling; LPG from crude oil; at plant
IN
1.00
kg
1
4
NMVOC, non-methane volatile
organic compounds, unspecified
origin
air
unspecified
3.4E-05
kg
2
2
1
1
1
4
5
1
5
Electricity; average production; at
consumer; production mix
IN
0.025
kWh
2
2
1
1
2
4
5
1
5
LPG from crude oil; petroleum
refining; at plant; production mix
IN
1.04
kg
2
2
1
1
1
4
5
1
4
Water, unspecified natural origin/m3
resource
in water
1.3E-04
m3
2
2
1
1
1
4
5
1
4
BOD5, Biological Oxygen Demand
water
unspecified
1.5E-06
kg
2
2
1
1
1
4
5
1
4
Chloride
water
unspecified
4.9E-05
kg
2
2
1
1
1
4
5
1
4
Sulfate
water
unspecified
4.9E-05
kg
2
2
1
1
1
4
5
1
4
Phenol
water
unspecified
2.5E-07
kg
2
2
1
1
1
4
5
1
4
Oils, unspecified
water
unspecified
9.8E-07
kg
2
2
1
1
1
4
5
1
4
Dissolved organics
water
unspecified
1.0E-04
kg
2
2
1
1
1
4
5
1
4
COD, Chemical Oxygen Demand
water
unspecified
1.2E-05
kg
2
2
1
1
1
4
5
1
4
Suspended solids, unspecified
water
unspecified
4.9E-06
kg
2
2
1
1
1
4
5
1
4
Sulfide
water
unspecified
1.4E-07
kg
2
2
1
1
1
4
5
1
4
Ammonia
water
unspecified
2.5E-07
kg
2
2
1
1
1
4
5
1
5
Transport, combination truck,
average fuel mix
US
0.21
t*km
2
2
2
4
3
4
5
1
5
Operation, freight train
RER
0.62
t*km
2
2
2
4
3
4
5
1
1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-21
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-17. Bottling; LPG from Natural Gas; At Plant (IN)
Q-
Data Quality
Input group
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Bottling; LPG from natural gas;
at plant
IN
1.00
kg
1
4
NMVOC, non-methane volatile
organic compounds,
unspecified origin
air
unspecified
3.4E-05
kg
2
2
1
1
1
4
5
1
5
Electricity; average production;
at consumer; production mix
IN
0.025
kWh
2
2
1
1
2
4
5
1
5
LPG; production from natural
gas; at plant; production mix
IN
1.04
kg
2
2
1
1
1
4
5
1
4
Water, unspecified natural
origin/m3
resource
in water
1.3E-04
m3
2
2
1
1
1
4
5
1
4
BOD5, Biological Oxygen
Demand
water
unspecified
1.5E-06
kg
2
2
1
1
1
4
5
1
4
Chloride
water
unspecified
4.9E-05
kg
2
2
1
1
1
4
5
1
4
Sulfate
water
unspecified
4.9E-05
kg
2
2
1
1
1
4
5
1
4
Phenol
water
unspecified
2.5E-07
kg
2
2
1
1
1
4
5
1
4
Oils, unspecified
water
unspecified
9.8E-07
kg
2
2
1
1
1
4
5
1
4
Dissolved organics
water
unspecified
1.0E-04
kg
2
2
1
1
1
4
5
1
4
COD, Chemical Oxygen
Demand
water
unspecified
1.2E-05
kg
2
2
1
1
1
4
5
1
4
Suspended solids, unspecified
water
unspecified
4.9E-06
kg
2
2
1
1
1
4
5
1
4
Sulfide
water
unspecified
1.4E-07
kg
2
2
1
1
1
4
5
1
4
Ammonia
water
unspecified
2.5E-06
kg
2
2
1
1
1
4
5
1
5
Transport, combination truck,
average fuel mix
US
0.21
t*km
2
2
2
4
3
4
5
1
5
Operation, freight train
RER
0.62
t*km
2
2
2
4
3
4
5
1
1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-22
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-18. Heat from Biomass Pellets; Pellet Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from biomass pellets; pellet stove; at
consumer
IN
1.00
GJ
5
Biomass pellets; at consumer
IN
96.7
kg
1
1
2
3
1
4
5
1
4
Carbon dioxide, biogenic
air
low population density
3.4E+01
kg
1
1
2
3
1
4
5
1
4
Carbon monoxide, biogenic
air
low population density
9.0E-02
kg
1
1
2
3
1
4
5
1
4
Dinitrogen monoxide
air
low population density
0.0E+00
kg
1
1
2
3
1
4
5
1
4
Methane, biogenic
air
low population density
1.0E-01
kg
1
1
2
3
1
4
5
1
4
Nitrogen oxides
air
low population density
6.0E-02
kg
1
1
2
3
1
4
5
2
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
low population density
0.0E+00
kg
1
1
2
3
1
4
5
1
4
Particulates, < 2.5 um
air
low population density
9.0E-02
kg
1
1
2
3
1
4
5
1
4
Sulfur dioxide
air
low population density
0.0E+00
kg
1
1
2
3
1
4
5
1
5
Disposal, wood ash mixture, pure, 0%
water, to landfanning
CH
2.9E-04
kg
1
1
2
3
1
4
5
1
[1] Jetter, J., Y., Zhao, K.R., Smith, et al. 2012. Pollutant emissions and energy efficiency under controlled conditions for household biomass cookstoves and
implications for metrics useful in setting international test standards. Enviromnental Science & Tecal test standards. Enviromnental Science & Technology, 46:
10827-10834.
[2] Boman, C. 2005. Particulate and gaseous emissions from residential biomass combustion. Ph.D thesis, Umea University, Umea, Sweden.
A-23
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-19. Heat from Sugarcane Ethanol; Alcohol Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
¦
Heat from sugarcane ethanol; alcohol stove; at
consumer
¦
GJ
1
4
Carbon dioxide
air
unspecified
63.0
kg
2
2
2
2
2
3
4
1
4
Carbon monoxide
air
unspecified
1.35
kg
2
2
2
2
2
3
4
1
4
Methane
air
unspecified
0.038
kg
2
2
2
2
2
3
4
1
4
Particulates, <2.5 um
air
unspecified
4.3E-
04
kg
2
2
2
2
2
3
4
2
5
Ethanol; production from sugarcane molasses; at plant
IN
35.3
kg
2
2
2
2
2
3
4
1
5
Transport, combination truck, average fuel mix
US
29.1
t*km
2
2
3
5
3
4
5
3
5
Transport, van <3.5t
RER
3.88
t*km
2
2
3
5
3
4
5
3
1] MacCarty, N. 2009. Results of Testing of the Clean Cook Stove for Fuel Use and Carbon Emissions. Aprovecho Research Center: Advanced Studies in
Appropriate Technology Laboratory, www.aprovecho.org/lab/rad/rl/perf-stud/doc/125/raw. Accessed 17 November 2019.
[2] Aprovecho Research Center, Shell Foundation, U.S. EPA. Results of Testing of the Clean Cook Stove for Fuel Use and Carbon Emissions. 2011
[3] Singh P, H„ Gundimeda, and M., Stucki. 2014a. Enviromnental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
A-24
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-20. Heat from Biogas; Biogas Stove; At Consumer (IN)
a
a
3
•-
Data Quality
%
o
u
s
a
c
HH
U
S
a
s
O
Flow
Category
o
#J3
"3
O
A
s
cn
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
o
s
K
•-
***
&
0
Heat from biogas; biogas stove; at
consumer
IN
1.00
GJ
1,3,4,5
4
Carbon dioxide, biogenic
air
unspecified
145
kg
2
2
3
2
1
4
5
1,3,4,5
4
Carbon monoxide, biogenic
air
unspecified
0.19
kg
2
2
3
2
1
4
5
1,3,4,5
4
Methane, biogenic
air
unspecified
0.043
kg
2
2
3
2
1
4
5
1,3,4,5
4
Nitrogen oxides
air
unspecified
0.038
kg
2
2
3
2
1
4
5
1,3,4,5
4
Sulfur dioxide
air
unspecified
0.085
kg
2
2
3
2
1
4
5
1,3,4,5
4
Dinitrogen monoxide
air
unspecified
9.0E-04
kg
2
2
3
2
1
4
5
1,3,4,5
4
Particulates, >2.5 urn, and < lOum
air
unspecified
0.18
kg
2
2
3
2
1
4
5
1,3,4,5
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
0.056
kg
2
2
3
2
1
4
5
1,3,4,5
5
Biogas; production from dung; at
anaerobic digester
IN
100.0
kg
2
2
3
2
1
4
5
1,2
[1] Singh P, H., Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian households. International
Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Environmental Engineering 2(1): 20-
30.
[3] Smith K.R., R., Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the Environment 61:
212-220.
[4] Boijesson P., and M. Berglund. 2006. Environmental systems analysis of biogas systems-Part 1: fuel-cycle emissions. Biomass and Bioenergy 30(5): 469-485.
[5] KadianR., R.P., Dahiya, andH.P., Garg. 2007. Energy related emissions and mitigation opportunities from household sector in Dehli. Energy Policy 35(12): 6195-6211.
A-25
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-21. Heat from Charcoal; Metal Stove; At Consumer (IN)
a
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Heat from charcoal; metal
stove; at consumer
IN
1.00
GJ
1
4
Carbon dioxide, biogenic
air
unspecified
543
kg
2
2
3
2
1
4
5
1,3,4,5
4
Carbon monoxide, biogenic
air
unspecified
57.3
kg
2
2
3
2
1
4
5
1,3,4,5
4
Methane, biogenic
air
unspecified
1.65
kg
2
2
3
2
1
4
5
1,3,4,5
4
Nitrogen oxides
air
unspecified
0.24
kg
2
2
3
2
1
4
5
1,3,4,5
4
Sulfur dioxide
air
unspecified
0.070
kg
2
2
3
2
1
4
5
1,3,4,5
4
Dinitrogen monoxide
air
unspecified
0.016
kg
2
2
3
2
1
4
5
1,3,4,5
4
Particulates, > 2.5 urn, and <
lOum
air
unspecified
0.63
kg
2
2
3
2
1
4
5
1,3,4,5
4
NMVOC, non-methane volatile
organic compounds,
unspecified origin
air
unspecified
2.15
kg
2
2
3
2
1
4
5
1,3,4,5
5
Disposal, wood ash mixture,
pure, 0% water, to landfanning
CH
15.4
kg
2
2
3
5
4
4
5
1,3,4,5
5
Charcoal; production from
wood; at earth mound kiln
IN
208
kg
2
2
3
2
1
4
5
1,2
1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
[3] Smith K.R., R.. Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the
Enviromnent 61: 212-220.
[4] Bhattacharya S.C., P.A. Salam, and M. Shanna. 2000. Emissions from biomass energy use in some selected Asian Countries. Energy 25(2): 169-188.
[5] Kadian R.. R.P., Dahiya, and H.P., Garg. 2007. Energy related emissions and mitigation opportunities from household sector in Dehli. Energy Policy 35(12):
6195-6211.
A-26
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-22. Heat from Hard Coal; Metal Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from hard coal; metal stove; at consumer
IN
1.00
GJ
1
4
Carbon dioxide
air
unspecified
855
kg
2
2
3
3
1
4
5
1,3,4,5
4
Carbon monoxide
air
unspecified
26.9
kg
2
2
3
3
1
4
5
1,3,4,5
4
Methane
air
unspecified
2.57
kg
2
2
3
3
1
4
5
1,3,4,5
4
Nitrogen oxides
air
unspecified
0.55
kg
2
2
3
3
1
4
5
1,3,4,5
4
Sulfur dioxide
air
unspecified
1.46
kg
2
2
3
3
1
4
5
1,3,4,5
4
Dinitrogen monoxide
air
unspecified
4.4E-05
kg
2
2
3
3
1
4
5
1,3,4,5
4
Particulates, >2.5 urn, and < lOum
air
unspecified
17.2
kg
2
2
3
3
1
4
5
1,3,4,5
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
5.76
kg
2
2
3
3
1
4
5
1,3,4,5
5
Hard coal; extraction; at open cast mine
IN
554
kg
2
2
3
3
1
4
5
2
5
Disposal, lignite ash from stove, 0% water, to
sanitary landfill
CH
219
kg
2
2
3
5
4
4
5
1,3,4,5
5
Operation, freight train
RER
55.4
tkm
2
2
4
5
4
4
5
2
[1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
[3] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric
Enviromnent. 36(4): 677-697.
[4] Chen Y„ G. Zlii, and Y. Feng, et al. 2006. Measurements of emission factors for primary carbonaceous particles from residential raw-coal combustion in
China. Geophysical Research Letters 33(20): L20815.
[5] Zlii G., Y„ Chen, and Y„ Feng, et al. 2008. Emission characteristics of carbonaceous particles from various residential coal-stoves in China. Enviromnental
Science and Technology 42(9): 3310-3315.
A-27
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-23. Heat from Firewood; Traditional Mud Stove; At Consumer (IN)
a
a
s
£¦
Data Quality
s
W)
s
a
c
HH
2
s
s.
s
O
Flow
Categorj
#J3
"3
O
A
s
cn
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
Reference
0
Heat from firewood; traditional mud stove; at
consumer
IN
1.00
GJ
1,2
4
Carbon dioxide, biogenic
air
unspecified
721
kg
2
2
3
1
1
4
5
1,3,6
4
Carbon monoxide, biogenic
air
unspecified
36.6
kg
2
2
3
1
1
4
5
1,4,6
4
Methane, biogenic
air
unspecified
2.23
kg
2
2
3
1
1
4
5
1,3,6
4
Nitrogen oxides
air
unspecified
0.41
kg
2
2
2
1
1
4
5
1,5
4
Sulfur dioxide
air
unspecified
0.17
kg
2
2
2
1
1
4
5
1,5
4
Dinitrogen monoxide
air
unspecified
0.047
kg
2
2
3
1
1
4
5
1,3
4
Particulates, >2.5 urn, and < lOum
air
unspecified
4.60
kg
2
2
2
1
1
4
5
1,4
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
3.90
kg
2
2
2
1
1
4
5
1,5
5
Disposal, wood ash mixture, pure, 0% water, to
landfanning
CH
16.0
kg
2
2
2
5
4
4
5
1,5
4
Energy, gross calorific value, in biomass, primary
forest
resource
biotic
5.86
GJ
2
2
1
1
1
4
5
1,2
4
Energy, gross calorific value, in biomass
resource
biotic
1.85
GJ
2
2
1
1
1
4
5
1,2
[1] Singh P. H., Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian households. International Journal of
Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Environmental Engineering 2(1): 20-30.
[3] Smith K.R., R., Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the Environment 61: 212-220.
[4] Venkataraman C., and G.U.M. Rao. 2001. Emission factors of carbon monoxide and size resolved aerosols from biofuel combustion. Environmental Science and Technology 35(10):
2100-2107.
[5] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric Environment. 36(4): 677-697.
[6] Saud T., R., Gautam, and T.K., Mandal, et al. 2012. Emission estimates of organic and elemental carbon from household biomass fuel used over the Indo-Gangetic Plain (IGP), India.
Atmospheric Environment. 61: 212-220.
A-28
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-24. Heat from Natural Gas LPG; LPG Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from natural gas LPG; LPG stove; at consumer
IN
1.00
GJ
1,3,4,5
4
Carbon dioxide
air
unspecified
120
kg
2
2
3
1
2
4
5
1,3,4,5
4
Carbon monoxide
air
unspecified
0.58
kg
2
2
3
1
2
4
5
1,3,4,5
4
Methane
air
unspecified
0.0030
kg
2
2
3
1
2
4
5
1,3,4,5
4
Nitrogen oxides
air
unspecified
0.060
kg
2
2
3
1
2
4
5
1,3,4,5
4
Sulfur dioxide
air
unspecified
0.082
kg
2
2
3
1
2
4
5
1,3,4,5
4
Dinitrogen monoxide
air
unspecified
0.58
kg
2
2
3
1
2
4
5
1,3,4,5
4
Particulates, >2.5 urn, and < lOum
air
unspecified
0.030
kg
2
2
3
1
2
4
5
1,3,4,5
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
0.41
kg
2
2
3
1
2
4
5
1,3,4,5
5
Bottling; LPG from natural gas; at plant
IN
38.8
kg
2
2
3
1
2
4
5
1
5
Transport, combination truck, average fuel mix
US
29.1
t*km
2
2
3
5
3
4
5
1,3,4,5
5
Transport, van <3.5t
RER
3.88
t*km
2
2
3
5
3
4
5
1,3,4,5
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
[3] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric
Enviromnent. 36(4): 677-697.
[4] Smith K.R., R„ Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the
Enviromnent 61: 212-220.
[5] Kadian R„ R.P., Daliiya, and H.P., Garg. 2007. Energy related emissions and mitigation opportunities from household sector in Dehli. Energy Policy 35(12):
6195-6211.
A-29
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-25. Heat from Crop Residue; Traditional Mud Stove; At Consumer (IN)
a
a
s
f
Data Quality
3
£
S
a
c
HH
2
S
a
3
O
Flow
Category
o
#J3
"3
O
A
s
cn
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
Reference
0
Heat from crop residue; traditional mud stove; at
consumer
IN
1.00
GJ
1
4
Carbon dioxide, biogenic
air
unspecified
922
kg
2
2
3
1
1
4
5
1,3,6
4
Carbon monoxide, biogenic
air
unspecified
46.4
kg
2
2
3
1
1
4
5
1,4,6
4
Methane, biogenic
air
unspecified
4.81
kg
2
2
3
1
1
4
5
1,3,6
4
Nitrogen oxides
air
unspecified
0.76
kg
2
2
2
1
1
4
5
1,5
4
Sulfur dioxide
air
unspecified
0.19
kg
2
2
2
1
1
4
5
1,5
4
Dinitrogen monoxide
air
unspecified
0.035
kg
2
2
3
1
1
4
5
1,3
4
Particulates, > 2.5 urn and < lOum
air
unspecified
11.1
kg
2
2
2
1
1
4
5
1,4
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
5.81
kg
2
2
2
1
1
4
5
1,5
5
Disposal, wood ash mixture, pure, 0% water, to
landfanning
CH
19.1
kg
2
2
2
5
4
4
5
1,5
4
Energy, gross calorific value, in biomass
resource
biotic
9.67
GJ
2
2
1
1
1
4
5
1,2
[1] Singh P., Gundimeda H., Stucki, M. 2014. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian households. Int
J Life Cycle Assess 19:1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
[3] Smith K.R., R.. Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the
Enviromnent 61: 212-220.
[4] Venkataraman C., and G.U.M. Rao. 2001. Emission factors of carbon monoxide and size resolved aerosols frombiofuel combustion. Enviromnental Science
and Technology 35(10): 2100-2107.
[5] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric
Enviromnent. 36(4): 677-697.
[6] Saud T., R„ Gautam, and T.K., Mandal, et al. 2012. Emission estimates of organic and elemental carbon from household biomass fuel used over the Indo-
Gangetic Plain (IGP), India. Atmospheric Enviromnent. 61: 212-220.
A-30
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-26. Heat from Dung Cake; Traditional Mud Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from dung cake; traditional mud
stove; at consumer
IN
1.00
GJ
1
4
Carbon dioxide, biogenic
air
unspecified
1,035
kg
2
2
3
1
1
4
5
1,3,6
4
Carbon monoxide, biogenic
air
unspecified
39.5
kg
2
2
3
1
1
4
5
1,4,6
4
Methane, biogenic
air
unspecified
5.64
kg
2
2
3
1
1
4
5
1,3,6
4
Nitrogen oxides
air
unspecified
0.76
kg
2
2
2
1
1
4
5
1,5
4
Sulfur dioxide
air
unspecified
0.32
kg
2
2
2
1
1
4
5
1,5
4
Dinitrogen monoxide
air
unspecified
0.18
kg
2
2
3
1
1
4
5
1,3
4
Particulates, > 2.5 urn and < lOum
air
unspecified
23.4
kg
2
2
2
1
1
4
5
1,4
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
16.0
kg
2
2
2
1
1
4
5
1,5
5
Disposal, wood ash mixture, pure, 0%
water, to landfanning
CH
390
kg
2
2
2
5
4
4
5
1,5
4
Energy, calorific value, in organic
substance
Energy
resources
Renewable energy
resources
12.9
GJ
2
2
1
1
1
4
5
1,2
[1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Enviromnental
Engineering 2(1): 20-30.
[3] Smith K.R., R.. Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the
Enviromnent 61: 212-220.
[4] Venkataraman C., and G.U.M. Rao. 2001. Emission factors of carbon monoxide and size resolved aerosols frombiofuel combustion. Enviromnental Science
and Technology 35(10): 2100-2107.
[5] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric
Enviromnent. 36(4): 677-697.
[6] Saud T., R„ Gautam, and T.K., Mandal, et al. 2012. Emission estimates of organic and elemental carbon from household biomass fuel used over the Indo-
Gangetic Plain (IGP), India. Atmospheric Enviromnent. 61: 212-220.
A-31
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-27. Heat from Crude Oil LPG; LPG Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from crude oil LPG; LPG stove; at consumer
IN
1.00
GJ
1,2,3,4
4
Carbon dioxide
air
unspecified
120
kg
2
2
3
1
2
4
5
1,2,3,4
4
Carbon monoxide
air
unspecified
0.58
kg
2
2
3
1
2
4
5
1,2,3,4
4
Methane
air
unspecified
0.003
kg
2
2
3
1
2
4
5
1,2,3,4
4
Nitrogen oxides
air
unspecified
0.060
kg
2
2
3
1
2
4
5
1,2,3,4
4
Sulfur dioxide
air
unspecified
0.082
kg
2
2
3
1
2
4
5
1,2,3,4
4
Dinitrogen monoxide
air
unspecified
0.58
kg
2
2
3
1
2
4
5
1,2,3,4
4
Particulates, >2.5 urn, and < lOum
air
unspecified
0.030
kg
2
2
3
1
2
4
5
1,2,3,4
4
NMVOC, non-methane volatile organic compounds,
unspecified origin
air
unspecified
0.41
kg
2
2
3
1
2
4
5
1,2,3,4
5
Bottling; LPG from crude oil; at plant
IN
38.8
kg
2
2
3
5
3
4
5
1
5
Transport, combination truck, average fuel mix
US
29.1
t*km
2
2
3
5
3
4
5
1,2,3,4
1] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.
[3] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric
Enviromnent. 36(4): 677-697.
[4] Smith K.R., R., Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the
Enviromnent 61: 212-220.
[5] Kadian R.. R.P., Dahiya, and H.P., Garg. 2007. Energy related emissions and mitigation opportunities from household sector in Dehli. Energy Policy 35(12):
6195-6211.
A-32
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-28. Heat from Kerosene; Kerosene Pressure Stove; At Consumer (IN)
s.
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from kerosene; kerosene pressure stove; at
consumer
IN
1.00
GJ
1
4
Carbon dioxide
air
unspecified
146
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Carbon monoxide
air
unspecified
3.08
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Methane
air
unspecified
0.036
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Nitrogen oxides
air
unspecified
0.050
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Sulfur dioxide
air
unspecified
0.13
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Dinitrogen monoxide
air
unspecified
0.0045
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
Particulates, > 2.5 urn, and < lOum
air
unspecified
0.15
kg
2
2
3
1
2
4
5
1,3,4,5,6
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
0.66
kg
2
2
3
1
2
4
5
1,3,4,5,6
5
Kerosene; production from crude oil; at plant;
production mix
IN
49.6
kg
2
2
3
1
2
4
5
2
5
Transport, combination truck, average fuel mix
US
14.9
t*km
2
2
3
5
3
4
5
1,3,4,5,6
5
Transport, van <3.5t
RER
0
t*km
2
2
3
5
3
4
5
1,3,4,5,6
5
Operation, freight train
RER
0
t*km
2
2
3
5
3
4
5
1,3,4,5,6
1] Singh P, H., Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian households. International
Journal of Life Cycle Assessment 19: 1036-1048.
[2] Singh, P., and H., Gundimeda. 2014b. Life cycle energy analysis (LCEA) of cooking fuel sources used in India households. Energy and Environmental Engineering 2(1): 20-
30.
[3] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric Environment. 36(4): 677-
697.
[4] Smith K.R., R., Uma, and V.V.N. Kishore, et al. 2000. Greenhouse implications of household stoves: an analysis for India. Annual Review of Energy and the Environment 61:
212-220.
[5] KadianR., R.P., Dahiya, andH.P., Garg. 2007. Energy related emissions and mitigation opportunities from household sector inDehli. Energy Policy 35(12): 6195-6211.
[6] Reddy M.S., and C., Venkataraman. 2002. Inventory of aerosol and sulphur dioxide emissions from India-Part I: fossil fuel combustion. Atmospheric Environment. 36(4): 677-
697.
A-33
-------
Appendix A - Detailed LCI Unit Process Tables
China LCI Tables
Table A-29. Biomass Pellets, At Consumer, National Mix (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
5
Fuel wood, at consumer
CN
0.28
kg
1
2
2
1
1
2
3
1,2
5
Brush wood, at consumer
CN
0.28
kg
1
2
2
1
1
2
3
1,2
5
Maize residue, at consumer
CN
0.21
kg
1
2
2
1
1
2
3
1,2
5
Wheat residue, at consumer
CN
0.21
kg
1
2
2
1
1
2
3
1,2
5
Rice straw, at consumer
CN
0.025
kg
1
2
2
1
1
2
3
1,2
5
Electricity, medium voltage, at grid 2011
CN
0.30
kWh
2
2
3
2
2
4
5
3,4
5
Transport, lorry >16t, fleet average
RER
0.065
t*km
2
2
3
2
2
4
5
3,4
5
Transport, freight, rail 2011
CN
0.13
t*km
2
2
3
2
2
4
5
3,4
0
Biomass pellets, at consumer, national mix
CN
1.00
kg
3,4
1] Jingjing L, Z., Xing, P., DeLauil P. et al. 2001. Biomass energy in Cliina and its potential. Energy for Sustainable Development V(4): 66-80.
[2] Liu Z, A., Xu, and B. Long. 2011. Energy from combustion of rice straw: Status and challenges to China. Energy and Power Engineering 3(3): 325-331.
[3] Werner F.. H. J., Althaus, and T.. Kiinniger T, et al. 2007. Life cycle inventories of wood as fuel and construction material. Final report ecoinvent data v2.0
No. 9. Swiss Centre for Life Cycle Inventories, Diibendorf, CH.
[4] Zhang J., K.R., Smith KR, and Y„ Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
A-34
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-30. Bottling, DME from Coal Gas, At Plant (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Bottling, DME from coal gas, at plant
CN
1.00
kg
1
4
NMVOC, non-methane volatile
organic compounds, unspecified origin
air
unspecified
3.4E-05
kg
2
1
1
3
1
2
1
1
5
Electricity, production mix 2011
CN
0.025
kWh
2
1
1
3
1
2
1
1
5
Coal gas, at consumer
CN
1.04
kg
2
1
1
3
1
2
1
1
4
Water, unspecified natural origin/m3
resource
in water
1.3E-04
m3
2
1
1
3
1
2
1
1
4
BOD5, Biological Oxygen Demand
water
unspecified
1.5E-06
kg
2
1
1
3
1
2
1
1
4
Chloride
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Sulfate
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Phenol
water
unspecified
2.5E-07
kg
2
1
1
3
1
2
1
1
4
Oils, unspecified
water
unspecified
9.8E-07
kg
2
1
1
3
1
2
1
1
4
Dissolved organics
water
unspecified
1.0E-04
kg
2
1
1
3
1
2
1
1
4
COD, Chemical Oxygen Demand
water
unspecified
1.2E-05
kg
2
1
1
3
1
2
1
1
4
Suspended solids, unspecified
water
unspecified
4.9E-06
kg
2
1
1
3
1
2
1
1
4
Sulfide
water
unspecified
1.4E-07
kg
2
1
1
3
1
2
1
1
4
Ammonia
water
unspecified
2.5E-06
kg
2
1
1
3
1
2
1
1
5
Transport, lorry >16t, fleet average
RER
0.21
t*k
m
2
1
1
3
1
2
1
1
5
Transport, freight, rail 2011
CN
0.62
t*k
m
2
1
1
3
1
2
1
1
1] Singh P. H.. Gundimeda, and M., Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048 (Supplementary Materials S1-S6.)
A-35
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-31. Bottling, LPG from Crude Oil, At Plant (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Bottling, LPG from crude oil. at plant
CN
1.00
kg
1
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
3.4E-05
kg
2
1
1
3
1
2
1
1
5
Electricity, production mix 2011
CN
0.025
kWh
2
1
1
3
1
2
1
1
5
Liquefied petroleum gas, at service station
2011
CN
1.04
kg
2
1
1
3
1
2
1
1
4
Water, unspecified natural origin/m3
resource
in water
1.3E-04
m3
2
1
1
3
1
2
1
1
4
BOD5, Biological Oxygen Demand
water
unspecified
1.5E-06
kg
2
1
1
3
1
2
1
1
4
Chloride
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Sulfate
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Phenol
water
unspecified
2.5E-07
kg
2
1
1
3
1
2
1
1
4
Oils, unspecified
water
unspecified
9.8E-07
kg
2
1
1
3
1
2
1
1
4
Dissolved organics
water
unspecified
1.0E-04
kg
2
1
1
3
1
2
1
1
4
COD, Chemical Oxygen Demand
water
unspecified
1.2E-05
kg
2
1
1
3
1
2
1
1
4
Suspended solids, unspecified
water
unspecified
4.9E-06
kg
2
1
1
3
1
2
1
1
4
Sulfide
water
unspecified
1.4E-07
kg
2
1
1
3
1
2
1
1
4
Ammonia
water
unspecified
2.5E-06
kg
2
1
1
3
1
2
1
1
~5~
Transport, lorry >16t, fleet average
RER
0.21
t*km
2
1
1
3
1
2
1
1
5
Transport, freight, rail 2011
CN
0.62
t*km
2
1
1
3
1
2
1
1
1] Singh P. H., Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fue
households. International Journal of Life Cycle Assessment 19: 1036-1048 (Supplementary Materials S1-S6.)
sources used in Indian
A-36
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-32. Bottling, LPG from Natural Gas, At Plant (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Bottling, LPG from natural gas, at plant
CN
1.00
kg
1
4
NMVOC, non-methane volatile organic
compounds, unspecified origin
air
unspecified
3.4E-05
kg
2
1
1
3
1
2
1
1
5
Electricity, production mix 2011
CN
0.025
kWh
2
1
1
3
1
2
1
1
5
Liquefied petroleum gas, at service station
2011
CN
1.04
kg
2
1
1
3
1
2
1
1
4
Water, unspecified natural origin/m3
resource
in water
1.3E-04
m3
2
1
1
3
1
2
1
1
4
BOD5, Biological Oxygen Demand
water
unspecified
1.5E-06
kg
2
1
1
3
1
2
1
1
4
Chloride
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Sulfate
water
unspecified
4.9E-05
kg
2
1
1
3
1
2
1
1
4
Phenol
water
unspecified
2.5E-07
kg
2
1
1
3
1
2
1
1
4
Oils, unspecified
water
unspecified
9.8E-07
kg
2
1
1
3
1
2
1
1
4
Dissolved organics
water
unspecified
1.0E-04
kg
2
1
1
3
1
2
1
1
4
COD, Chemical Oxygen Demand
water
unspecified
1.2E-05
kg
2
1
1
3
1
2
1
1
4
Suspended solids, unspecified
water
unspecified
4.9E-06
kg
2
1
1
3
1
2
1
1
4
Sulfide
water
unspecified
1.4E-07
kg
2
1
1
3
1
2
1
1
4
Ammonia
water
unspecified
2.5E-06
kg
2
1
1
3
1
2
1
1
~5~
Transport, lorry >16t, fleet average
RER
0.21
t*km
2
1
1
3
1
2
1
1
5
Transport, freight, rail 2011
CN
0.62
t*km
2
1
1
3
1
2
1
1
1] Singh P. H., Gundimeda, and M„ Stucki. 2014a. Environmental footprint of cooking fuels: a life cycle assessment of ten fue
households. International Journal of Life Cycle Assessment 19: 1036-1048 (Supplementary Materials S1-S6.)
sources used in Indian
A-37
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-33. Brush Wood, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Brush wood, at consumer
CN
1.00
kg
1
4
Energy, gross calorific value, in biomass
resource
biotic
9.60
MJ
1
1
4
1
2
4
5
1,2,3,4,5,6
4
Energy, gross calorific value, in biomass, primary forest
resource
biotic
5.72
MJ
1
1
4
1
2
4
5
1,2,3,4,5,6
[1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Singh P. H., Gundimeda, and M„ Stucki. 2014a. Enviromnental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048 (Supplementary Materials S1-S6.)
[3] FAO (Food and Agriculture Organization). 2010. Global forest resources assessment 2010: main report. FAO Forestry Paper 163. Food and Agriculture
Organization of the United Nations, Rome, Italy.
[4] Zhou, N„ M.A., McNeil, and D. Fridley, et al. 2007. Energy use China: Sectoral trends and future outlook. Lawrence Berkeley National Laboratory, LBNL-
61904.
[5] Tonooka Y., M. Hailin, and Y. Ning, et al. 2003. Energy consumption in residential house and emissions inventory of GHGs, air pollutants in China. Journal
of Asian Architecture and Building Engineering 1: 1-8.
[6] Jingjing L, Z., Xing, P., DeLauil P, et al. 2001. Biomass energy in China and its potential. Energy for Sustainable Development V(4): 66-80.
A-38
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-34. Coal Briquette, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Coal briquette, at consumer
CN
0.032
kg
1
5
Transport, barge
RER
0.126
t*km
1
1
4
3
2
4
5
1
5
Transport, coal freight, rail 2011
CN
1.04
t*km
1
1
4
3
2
4
5
1
5
Transport, lorry >16t, fleet average
RER
0.0069
t*km
1
1
4
3
2
4
5
1
5
Hard coal briquettes, at plant 2011
CN
1.00
MI
1
1
4
1
2
4
5
1
[1] Dones, R., C., Bauer, andR., Bollinger, et al. 2007. Sachbilanzen von Energiesystemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. Final report ecoinvent No. 6-VI, Paul Scherrer Institut Villigen, Swiss Centre for Life
Cycle Inventories, Dubendorf, CH.
Table A-35. Coal Gas, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Coal gas, at consumer
CN
1.00
kg
1
5
Coal gas, high pressure, at consumer 2011
CN
43.8
MI
1
1
4
1
2
4
5
2
[1] Dones, R., C., Bauer, andR., Bollinger, et al. 2007. Sachbilanzen von Energiesystemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. Final report ecoinvent No. 6-VI. Paul Scherrer Institut Villigen, Swiss Centre for Life
Cycle Inventories, Dubendorf, CH.
[2] Zhang I., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
A-39
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-36. Coal Powder, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Coal powder, at consumer
CN
1.00
kg
5
Hard coal supply mix, at regional storage 2011
CN
1.00
kg
1
1
4
1
2
4
5
1
[1] Dones, R., C., Bauer, andR., Bollinger, et al. 2007. Sachbilanzen von Energiesystemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. Final report ecoinvent No. 6-VI, Paul Scherrer Institut Villigen, Swiss Centre for Life
Cycle Inventories, Dubendorf, CH.
A-40
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-37. Fuel Wood, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Fuel wood, at consumer
CN
1.00
kg
1
4
Energy, gross calorific value, in biomass
resource
biotic
10.2
MJ
1
1
4
1
2
4
5
1,2,3,4,5,6
4
Energy, gross calorific value, in biomass, primary
forest
resource
biotic
6.07
MJ
1
1
4
1
2
4
5
1,2,3,4,5,6
[1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Singh P. H.. Gundimeda, and M„ Stucki. 2014a. Enviromnental footprint of cooking fuels: a life cycle assessment of ten fuel sources used in Indian
households. International Journal of Life Cycle Assessment 19: 1036-1048.; Supplementary Materials S1-S6.
[3] FAO (Food and Agriculture Organization). 2010. Global forest resources assessment 2010: main report. FAO Forestry Paper 163. Food and Agriculture
Organization of the United Nations, Rome, Italy.
[4] Zhou, N„ M.A., McNeil, and D. Fridley, et al. 2007. Energy use China: Sectoral trends and future outlook. Lawrence Berkeley National Laboratory, LBNL-
61904.
[5] Tonooka Y., M. Hailin, and Y. Ning, et al. 2003. Energy consumption in residential house and emissions inventory of GHGs, air pollutants in China. Journal
of Asian Architecture and Building Engineering 1: 1-8.
[6] Jingjing L, Z., Xing, P., DeLauil P, et al. 2001. Biomass energy in China and its potential. Energy for Sustainable Development V(4): 66-80.
A-41
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-38. Kerosene, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Kerosene, at consumer
CN
1.00
kg
5
Kerosene, at regional storage 2011
CN
1.00
kg
1
1
3
2
2
4
5
1
[1] Dones, R., C., Bauer, andR., Bollinger, et al. 2007. Sachbilanzen von Energiesystemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. Final report ecoinvent No. 6-VI, Paul Scherrer Institut Villigen, Swiss Centre for Life
Cycle Inventories, Dubendorf, CH.
Table A-39. LPG At Consumer (CN)
a
s.
Subcategory
Data Quality
Input grou
Output groii
Flow
Category
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
LPG, at consumer
CN
1.00
kg
5
Bottling, LPG from natural gas, at plant
CN
0.500
kg
1
1
1
1
1
2
3
N/A
5
Bottling, LPG from crude oil, at plant
CN
0.500
kg
1
1
1
1
1
2
3
N/A
A-42
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-40. Maize Residue, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Maize residue, at consumer
CN
1.00
kg
1
4
Energy, gross calorific value, in biomass
resource
biotic
16.1
MJ
1
1
4
1
2
4
5
1
[1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
Table A-41. Natural Gas, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Natural gas, at consumer
CN
1.00
kg
2
5
Natural gas, high pressure, at consumer 2011
CN
51.3
MJ
1
1
4
1
2
4
5
1
[1] Dones, R., C., Bauer, andR., Bollinger, et al. 2007. Sachbilanzen von Energiesystemen: Grundlagen fur den okologischen Vergleich von Energiesystemen
und den Einbezug von Energiesystemen in Okobilanzen fur die Schweiz. [Life cycle of energy systems: founde Schweiz. Final report ecoinvent No. 6-V, Paul
Scherrer Institut Villigen, Swiss Centre for Life Cycle Inventories, Diibendorf, CH. Online: www.ecoinvent.ch.
[2] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
A-43
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-42. Rice Straw, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Rice straw, at consumer
CN
1.00
kg
1
4
Energy, gross calorific value, in biomass
resource
biotic
18.0
MJ
1
1
4
1
2
4
5
1
[1] LiuZ, A., Xu, and B. Long. 2011. Energy from combustion of rice straw: Status and challenges to China. Energy and Power Engineering 3(3): 325-331.
Table A-43. Wheat Residue, At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Wheat residue, at consumer
CN
1.00
kg
1
4
Energy, gross calorific value, in biomass
resource
biotic
14.0
MJ
1
1
4
1
2
2
3
1
[1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
A-44
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-44. Heat from Biomass Pellets; Pellet Stove; At Consumer
CL
s.
Subcategory
Data Quality
Input grou
s
ex
-w
s
s.
s
O
Flow
Category
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
Reference}
0
Heat from biomass pellets; pellet stove; at
consumer
CN
1.00
MJ
5
Biomass pellets, at consumer, national mix
CN
0.12
kg
1
1
2
3
1
4
5
4,5,6
4
Carbon dioxide, biogenic
air
low population density
0.26
kg
1
1
2
3
1
4
5
1
4
Carbon dioxide, fossil
air
low population density
0.075
kg
1
1
2
3
1
4
5
1
4
Carbon monoxide
air
low population density
2.0E-04
kg
1
1
2
3
1
4
5
1
4
Carbon monoxide, biogenic
air
low population density
7.0E-04
kg
1
1
2
3
1
4
5
1
4
Methane, biogenic
air
low population density
7.8E-05
kg
1
1
2
3
1
4
5
1
4
Methane, fossil
air
low population density
2.2E-05
kg
1
1
2
3
1
4
5
1
4
Nitrogen oxides
air
low population density
6.0E-05
kg
1
1
2
3
1
4
5
2
4
Particulates, < 2.5 um
air
low population density
9.0E-05
kg
1
1
2
3
1
4
5
1
5
Disposal, wood ash mixture, pure, 0% water,
to landfanning
CN
0.0015
kg
1
1
2
3
1
4
5
3
[1] Jetter, J., Y., Zhao, K.R., Smith, et al. 2012. Pollutant emissions and energy efficiency under controlled conditions for household biomass cookstoves and
implications for metrics useful in setting international test standards. Enviromnental Science & Tecal test standards. Enviromnental Science & Technology, 46:
10827-10834.
[2] Boman, C. 2005. Particulate and gaseous emissions from residential biomass combustion. Ph.D thesis, Umea University, Umea, Sweden.
[3] Roy M.M., A., Dutta, and K., Corscadden. 2013. An experimental study of combustion and emissions of biomass pellets in a prototype pellet furnace.
Applied Energy 108: 298-307.
[4] Jingjing L, Z., Xing, P., DeLauil P, et al. 2001. Biomass energy in China and its potential. Energy for Sustainable Development V(4): 66-80.
[5] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[6] Liu Z, A., Xu, and B. Long. 2011. Energy from combustion of rice straw: Status and challenges to China. Energy and Power Engineering 3(3): 325-331.
A-45
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-45. Heat from Biomass; Cookstove; At Consumer; National Mix (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
5
Heat from brush wood, brick stove with flue, at consumer
CN
0.16
MJ
1
1
1
1
2
4
4
1,2
5
Heat from brush wood, improved brick stove with flue, at consumer
CN
0.059
MJ
1
1
1
1
2
4
4
1,2
5
Heat from brush wood, India metal stove without flue, at consumer
CN
0.059
MJ
1
1
1
1
2
4
4
1,2
5
Heat from fuel wood, brick stove with flue, at consumer
CN
0.16
MJ
1
1
1
1
2
4
4
1,2
5
Heat from fuel wood, improved brick stove with flue, at consumer
CN
0.12
MJ
1
1
1
1
2
4
4
1,2
5
Heat from fuel wood, improved brick stove without flue, at consumer
CN
0.091
MJ
1
1
1
1
2
4
4
1,2
5
Heat from maize residue, brick stove with flue, at consumer
CN
0.12
MJ
1
1
1
1
2
4
4
1,2
5
Heat from maize residue, improved brick stove with flue, at consumer
CN
0.091
MJ
1
1
1
1
2
4
4
1,2
5
Heat from wheat residue, brick stove with flue, at consumer
CN
0.12
MJ
1
1
1
1
2
4
4
1,2
5
Heat from wheat residue, brick stove without flue, at consumer
CN
0.091
MJ
1
1
1
1
2
4
4
1,2
5
Heat from rice straw, improved brick stove with flue, at consumer
CN
0.025
MJ
1
1
1
1
2
4
4
1,2
0
Heat from biomass; cookstove; at consumer; national mix
CN
1.00
MJ
1,2
[1] Dalberg Global Development Advisors. 2014. China stoves and fuels market assessment. Global Alliance for Clean Cookstoves. May presentation:
preliminary findings, 19 May 2014.
[2] Jingjing L, Z., Xing, P., DeLauil P, et al. 2001. Biomass energy in China and its potential. Energy for Sustainable Development V(4): 66-80.
A-46
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-46. Heat from Brush Wood; Brick Stove With Flue; At Consumer (CN)
s.
Data Quality
Input Groui
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Heat from brush wood;
brick stove with flue; at
consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.29
kg
1
1
4
1
2
2
3
1
5
Brush wood, at consumer
CN
0.47
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.45
kg
1
1
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.27
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide
air
low population density
0.012
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.021
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
7.5E-04
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
4.4E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
9.3E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic
compounds
air
low population density
5.4E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0013
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
2.4E-06
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
9.6E-05
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
3.5E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
2.0E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
6.7E-06
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
9.3E-05
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
1.8E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
8.1E-06
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
4.1E-07
kg
1
1
4
1
2
4
5
2
A-47
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-46. Heat from Brush Wood; Brick Stove With Flue; At Consumer (CN)
a
Data Quality
Input Groui
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
1-butylene
Air
low population density
9.6E-07
kg
1
1
4
1
2
4
5
2
4
Butane
Air
low population density
2.8E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
Air
low population density
3.1E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
Air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
1-Pentene
Air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
Air
low population density
6.7E-06
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
Air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
4
Decane
Air
low population density
9.5E-05
kg
1
1
4
1
2
4
5
2
5
Disposal, wood ash
mixture, pure, 0% water, to
landfanning
CN
0.0083
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-48
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-47. Heat from Brush Wood; India Metal Stove Without Flue; At Consumer (CN)
_ a
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technologica
Uncertainty
References
0
Heat from brush wood; India metal stove
without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.22
kg
1
1
4
1
2
2
3
5
Brush wood, at consumer
CN
0.38
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.35
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.21
kg
1
4
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.024
kg
1
4
4
1
2
2
3
1
4
Carbon monoxide
air
low population density
0.014
kg
1
4
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.0014
kg
1
4
4
1
2
2
3
1
4
Methane, fossil
air
low population density
8.1E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
6.1E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0019
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0017
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
9.2E-07
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
2.1E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
2.8E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
4.9E-06
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
2.0E-04
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
2.8E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.1E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
9.4E-06
kg
1
1
4
1
2
4
5
2
5
Disposal, wood ash mixture, pure, 0% water, to
landfanning
CN
0.0067
kg
1
1
4
1
2
4
5
1
[1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission factors. Atmospheric Environment
34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China. Environmental Science & Technology 37(13):
2869-2877.
A-49
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-48. Heat from Coal Briquette; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
"fi
P
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal briquette; metal stove with
flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.27
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.27
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.42
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
5.1E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
7.5E-05
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.0054
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
2.9E-06
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
2.1E-06
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
4.9E-05
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
7.6E-08
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
2.0E-07
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
3.8E-08
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
5.3E-08
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
8.4E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
7.8E-09
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.2E-08
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
8.6E-09
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.9E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
6.8E-09
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
6.3E-09
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
1.1E-09
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
1.2E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
2.7E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.6E-09
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
2.7E-09
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
1.1E-09
kg
1
1
4
1
2
4
5
2
A-50
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-48. Heat from Coal Briquette; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
"fi
P
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2-Methyl-2-butene
air
low population density
3.5E-09
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
2.2E-10
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
4.3E-09
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
3.1E-09
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
3.9E-09
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
8.6E-09
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
1.3E-09
kg
1
1
4
1
2
4
5
2
4
2,4-Dimethylpentane
air
low population density
1.1E-09
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
2.1E-09
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
2.2E-10
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
3.4E-09
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
9.3E-09
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
4.6E-09
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
8.2E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
2.6E-09
kg
1
1
4
1
2
4
5
2
4
3-Ethylhexane
air
low population density
2.4E-09
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
8.5E-09
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
2.2E-08
kg
1
1
4
1
2
4
5
2
4
Cumene
air
low population density
5.7E-09
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
3.9E-08
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.11
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-51
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-49. Heat from Coal Briquette; Metal Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal briquette; metal stove
without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.21
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.19
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.31
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
2.3E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.9E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.004
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
4.0E-06
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
1.8E-05
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
6.3E-06
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.5E-06
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
6.7E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
3.4E-07
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
4.7E-07
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
7.5E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
7.0E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
7.7E-08
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.7E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
6.1E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
5.6E-08
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
A-52
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-49. Heat from Coal Briquette; Metal Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
iso-Pentane
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
2.4E-08
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.4E-08
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
9.1E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
2.4E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
3.1E-08
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
3.8E-08
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
2.8E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
3.5E-08
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
7.7E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
1.2E-08
kg
1
1
4
1
2
4
5
2
4
2,4-Dimethylpentane
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
1.9E-08
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
3.0E-08
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
8.3E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
4.1E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
7.3E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
2.3E-08
kg
1
1
4
1
2
4
5
2
4
3-Ethylhexane
air
low population density
2.1E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
7.6E-08
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
8.9E-08
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.9E-07
kg
1
1
4
1
2
4
5
2
A-53
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-49. Heat from Coal Briquette; Metal Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Cumene
air
low population density
5.1E-08
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
3.5E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.084
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-54
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-50. Heat from Coal Gas; Traditional Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal gas; traditional gas
stove without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.043
kg
1
1
4
1
2
2
3
5
Coal gas, at consumer
CN
0.050
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.093
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
8.3E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
8.9E-05
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
3.0E-08
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
9.8E-06
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.9E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
8.0E-08
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
3.1E-07
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
2.5E-08
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
4.7E-08
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
6.4E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.3E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
3.5E-08
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
A-55
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-50. Heat from Coal Gas; Traditional Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2-Methylpentane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
7.0E-09
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
8.5E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
N-propylbenzene
air
low population density
1.5E-08
kg
1
1
4
1
2
4
5
2
4
para-Ethyltoluene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
meta-Ethyltoluene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
1,2,4-Trimethylbenzene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-56
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-51. Heat from Coal Powder; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal powder; brick stove with
flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.39
kg
1
1
4
1
2
2
3
5
Coal powder, at consumer
CN
0.22
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.54
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
5.6E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
5.0E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.044
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
2.7E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
1.5E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
4.3E-04
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
3.7E-06
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
4.9E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.7E-06
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
7.9E-06
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
5.5E-06
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
7.7E-07
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
8.7E-08
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
2.7E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
6.6E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-Butene
air
low population density
2.5E-07
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
2.6E-08
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
4.0E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
8.7E-08
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
9.6E-08
kg
1
1
4
1
2
4
5
2
A-57
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-51. Heat from Coal Powder; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
trans-2-Pentene
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
1.8E-08
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
8.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
5.8E-08
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
5.2E-08
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
6.1E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
1.0E-06
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
4.0E-08
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
1,2,4-Trimethylbenzene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.015
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-58
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-52. Heat from Coal Powder; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal powder; metal stove
with flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.58
kg
1
1
4
1
2
2
3
5
Coal powder, at consumer
CN
0.21
kg
1
4
4
1
2
3
3
1
4
Carbon dioxide, fossil
air
low population density
0.74
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
1.2E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.2E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.026
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
0.0011
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
3.8E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0013
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
3.9E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
7.9E-06
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
3.1E-06
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
2.6E-04
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
0.00106
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
3.1E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
5.8E-05
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
1.7E-04
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
3.7E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
3.0E-05
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.6E-05
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
9.6E-06
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
8.4E-07
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
2.8E-06
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
5.2E-07
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
9.0E-06
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
A-59
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-52. Heat from Coal Powder; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2-Methylpentane
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
5.3E-07
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
4.1E-06
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
6.2E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
1.6E-06
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
5.1E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
3.7E-07
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
3.7E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
4.2E-07
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
4.2E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
6.0E-05
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
4.9E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
3.7E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.015
kg
1
1
4
1
2
3
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-60
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-53. Heat from Coal Powder; Metal Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from coal powder; metal stove
without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.43
kg
1
1
4
1
2
4
5
5
Coal powder, at consumer
CN
0.26
kg
1
4
4
1
2
4
5
1
4
Carbon dioxide, fossil
air
low population density
0.64
kg
1
1
4
1
2
4
5
1
4
Sulfur dioxide
air
low population density
3.8E-05
kg
1
1
4
1
2
4
5
1
4
Nitrogen oxides
air
low population density
3.9E-05
kg
1
1
4
1
2
4
5
1
4
Carbon monoxide, fossil
air
low population density
0.018
kg
1
1
4
1
2
4
5
1
4
Methane, fossil
air
low population density
0.0027
kg
1
1
4
1
2
4
5
1
4
Non methane total organic compounds
air
low population density
6.2E-04
kg
1
1
4
1
2
4
5
1
4
Particulates, < 2.5 um
air
low population density
0.0022
kg
1
1
4
1
2
4
5
1
4
Benzene
air
low population density
6.4E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
1.3E-05
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
5.0E-06
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
4.2E-04
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
0.0017
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
5.0E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
9.4E-05
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
2.7E-04
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
6.1E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
4.9E-05
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
2.6E-05
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
1.6E-05
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
4.7E-06
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
8.5E-07
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
1.5E-05
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
A-61
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-53. Heat from Coal Powder; Metal Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2-Methylpentane
air
low population density
3.0E-06
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
8.7E-07
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
6.8E-06
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
2.6E-06
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
8.3E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
6.0E-07
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
6.1E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
6.8E-07
kg
1
1
4
1
2
4
5
2
4
2,2,4 -T rime thy lpentane
air
low population density
2.1E-06
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
6.8E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
9.8E-05
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
2.3E-06
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
8.0E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
6.1E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.018
kg
1
1
4
1
2
4
5
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-62
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-54. Heat from DME; Traditional Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from DME; traditional gas stove
without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.016
kg
1
1
4
1
2
2
3
5
Bottling; DME from coal gas; at plant
CN
0.077
kg
1
4
4
1
2
2
3
1,3
4
Carbon dioxide, fossil
air
low population density
0.093
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
8.3E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
8.9E-05
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
3.0E-08
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
9.8E-06
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.9E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
8.0E-08
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
3.1E-07
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
2.5E-08
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
4.7E-08
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
6.4E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.3E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
cis-2-Butene
air
low population density
3.5E-08
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
3.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
A-63
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-54. Heat from DME; Traditional Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2-Methylpentane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
7.0E-09
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
8.5E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
6.0E-09
kg
1
1
4
1
2
4
5
2
4
N-propylbenzene
air
low population density
1.5E-08
kg
1
1
4
1
2
4
5
2
4
para-Ethyltoluene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
meta-Ethyltoluene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
1,2,4-Trimethylbenzene
air
low population density
1.0E-09
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
[3] Larson, E„ and H„ Yang. 2004. Dimethyl ether (DME) from coal as a household cooking fuel in China. Energy for Sustainable Development VIII(3): 115-
126.
A-64
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-55. Heat from Fuel Wood; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Heat from fuel wood; brick stove with
flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.33
kg
1
1
4
1
2
2
3
5
Fuel wood, at consumer
CN
0.47
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.49
kg
1
1
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.29
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.0093
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide
air
low population density
0.0056
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
7.8E-04
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
4.7E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
2.3E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
9.0E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0011
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.6E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
5.8E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
3.4E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
1.1E-05
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
1.6E-04
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
3.0E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
1.4E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
6.8E-07
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.6E-06
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
4.6E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
5.1E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-Butene
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
2.7E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
1.1E-05
kg
1
1
4
1
2
4
5
2
A-65
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-55. Heat from Fuel Wood; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Ethyl benzene
air
low population density
2.9E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
1.6E-04
kg
1
1
4
1
2
4
5
2
5
Disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.0054
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-66
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-56. Heat from Fuel Wood; Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from fuel wood; improved brick stove
with flue; at consumer
CN
1.00
MT
1
4
Air, from nature
resource
air
0.16
kg
1
1
4
1
2
2
3
5
Fuel wood, at consumer
CN
0.26
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.25
kg
1
1
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.15
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.011
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide
air
low population density
0.0067
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
6.3E-04
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
3.7E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.4E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0015
kg
1
1
4
1
2
2
3
1
4
Particulates, <2.5 urn
air
low population density
0.0011
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
7.6E-06
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.6E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
2.2E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
3.8E-06
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
1.6E-04
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
2.2E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
8.0E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.9E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
2.4E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
7.4E-06
kg
1
1
4
1
2
4
5
2
5
Disposal, wood ash mixture, pure, 0%
water, to landfarming
CN
0.0030
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-67
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-57. Heat from Fuel Wood; Improved Brick Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
'3
P
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from fuel wood; improved brick
stove without flue; at consumer
CN
1.00
MJ
1
4
Air, from nature
resource
air
0.25
kg
1
1
4
1
2
2
3
5
Fuel wood, at consumer
CN
0.29
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.31
kg
1
1
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.19
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.01
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide
air
low population density
0.01
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.00
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
0.00
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
2.8E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0019
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0015
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
7.1E-07
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
2.0E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
2.7E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
4.8E-06
kg
1
1
4
1
2
4
5
2
4
Ethene
air
low population density
2.0E-04
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
2.8E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.0E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
9.3E-06
kg
1
1
4
1
2
4
5
2
5
Disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.0033
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-68
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-58. Heat from Honeycomb Coal Briquette; Improved Metal Stove without Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from honeycomb coal briquette;
improved metal stove without flue; at
consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.23
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.11
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.30
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
9.2E-06
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
4.9E-05
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.0065
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
6.2E-07
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
5.3E-05
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
1.5E-06
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
5.8E-08
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
2.2E-07
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
6.7E-08
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
1.7E-08
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
1.5E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
3.9E-08
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.3E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.7E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
2.0E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
2.6E-07
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
4.2E-08
kg
1
1
4
1
2
4
5
2
A-69
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-58. Heat from Honeycomb Coal Briquette; Improved Metal Stove without Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Ethyl benzene
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.9E-07
kg
1
1
4
1
2
4
5
2
4
1,2,4-Trimethylbenzene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
4.1E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.028
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-70
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-59. Heat from Honeycomb Coal Briquette; Metal Stove with Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from honeycomb coal briquette;
metal stove with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.60
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.32
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.82
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
6.0E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.4E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.019
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
3.3E-06
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
1.1E-07
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
7.0E-05
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
8.9E-07
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
2.8E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
4.9E-07
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
4.8E-07
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
5.8E-08
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
9.2E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.6E-08
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
7.0E-09
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.4E-08
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
9.0E-09
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
1.3E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
1.2E-08
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
2.5E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
1.0E-08
kg
1
1
4
1
2
4
5
2
A-71
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-59. Heat from Honeycomb Coal Briquette; Metal Stove with Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
3-Methylhexane
air
low population density
2.4E-08
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
Heptane
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.9E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
3.3E-08
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
4.6E-08
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
1,2,4-Trimethylbenzene
air
low population density
6.1E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.082
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-72
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-60. Heat from Honeycomb Coal Briquette; Metal Stove without Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from honeycomb coal briquette;
metal stove without flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.42
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.22
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.57
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
2.6E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
9.7E-05
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.015
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
4.1E-06
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
5.9E-06
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
6.2E-05
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
2.6E-06
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
4.5E-07
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
1.6E-06
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
3.5E-07
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
7.6E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
8.6E-08
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
7.3E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
4.3E-08
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
4.3E-08
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
A-73
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-60. Heat from Honeycomb Coal Briquette; Metal Stove without Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Cyclopentane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
2.2E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
6.9E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.2E-07
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
6.3E-08
kg
1
1
4
1
2
4
5
2
4
2,4-Dimethylpentane
air
low population density
8.6E-08
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
7.9E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
4.0E-09
kg
1
1
4
1
2
4
5
2
4
3-Ethylhexane
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
1.2E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
3.1E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
4.1E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.056
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-74
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-61. Heat from Kerosene; Pressure Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from kerosene; pressure stove
without flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.11
kg
1
1
4
1
2
2
3
5
Kerosene, at consumer
CN
0.050
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.16
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
5.8E-07
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
7.8E-05
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
3.8E-04
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
5.2E-07
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
2.1E-05
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
3.0E-06
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
1.5E-07
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
1.3E-05
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
6.6E-06
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
8.6E-08
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
2.3E-06
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
9.5E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
2.4E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
6.9E-07
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
1.5E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
5.7E-08
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
5.7E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
3.0E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
6.8E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
3.5E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
2.1E-08
kg
1
1
4
1
2
4
5
2
A-75
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-61. Heat from Kerosene; Pressure Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
2 -Methy 1-2 -butene
air
low population density
2.8E-08
kg
1
1
4
1
2
4
5
2
4
Cyclopentene
air
low population density
4.8E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
3.0E-07
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
2.8E-09
kg
1
1
4
1
2
4
5
2
4
2,2,4 -T rime thy lpentane
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
4.1E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
9.5E-08
kg
1
1
4
1
2
4
5
2
4
2,3,4-Trimethy lpentane
air
low population density
1.4E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
5.5E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
3.0E-08
kg
1
1
4
1
2
4
5
2
4
3-Ethylhexane
air
low population density
5.4E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
8.2E-08
kg
1
1
4
1
2
4
5
2
4
Particulates, < 2.5 um
air
low population density
8.7E-06
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-76
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-62. Heat from LPG; Infrared Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from LPG; infrared gas stove
without flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.11
kg
1
1
4
1
2
2
3
5
LPG, at consumer
CN
0.048
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.15
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
1.3E-08
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
4.1E-06
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.0010
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
1.6E-05
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
2.4E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 urn
air
low population density
5.4E-07
kg
1
1
4
1
2
2
3
1
4
1-butylene
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
3.2E-08
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
7.9E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
3.2E-08
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
7.9E-09
kg
1
1
4
1
2
4
5
2
4
benzene
air
low population density
5.5E-06
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
1.1E-08
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
3.7E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
2.2E-07
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
7.9E-09
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
5.4E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
1.7E-06
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
4.9E-08
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
6.0E-08
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
2.5E-07
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.7E-07
kg
1
1
4
1
2
4
5
2
A-77
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-62. Heat from LPG; Infrared Gas Stove without Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
iso-Butene
air
low population density
9.4E-08
kg
1
1
4
1
2
4
5
2
4
neopentane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
2.7E-07
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
3.7E-07
kg
1
1
4
1
2
4
5
2
4
styrene
air
low population density
1.2E-05
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
2.2E-06
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
7.5E-08
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
3.7E-06
kg
1
1
4
1
2
4
5
2
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-78
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-63. Heat from LPG; Traditional Gas Stove without Flue; At Consumer (CN)
CL
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from LPG; traditional gas stove
without flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.095
kg
1
1
4
1
2
2
3
5
LPG, at consumer
CN
0.045
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.14
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.5E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
1.0E-04
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
2.3E-05
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
1.5E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
2.5E-05
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
3.4E-06
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
7.0E-09
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
2.3E-06
kg
1
1
4
1
2
4
5
2
4
styrene
air
low population density
7.6E-06
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
3.1E-08
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
3.8E-08
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
7.1E-08
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
8.4E-08
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.0E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
5.9E-08
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
9.9E-08
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
2.3E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
4.7E-08
kg
1
1
4
1
2
4
5
2
4
neopentane
air
low population density
6.9E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
A-79
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-63. Heat from LPG; Traditional Gas Stove without Flue; At Consumer (CN)
Q-
Data Quality
Input group
Output grou
Flow
Category
Subcategorj
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
cis-2-Pentene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
2.0E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
2.0E-08
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
3.4E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.7E-07
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-80
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-64. Heat from Maize Residue; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
References
0
Heat from maize residue; brick stove
with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.17
kg
1
1
4
1
2
2
3
5
Maize residue, at consumer
CN
0.57
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.67
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
8.0E-06
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
7.0E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.025
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
9.8E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0019
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0010
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
5.2E-05
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
2.1E-05
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
1.5E-04
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
1.2E-04
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
2.6E-06
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
1.6E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
5.7E-07
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
2.4E-06
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
4.6E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
2.2E-07
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
2.9E-07
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
A-81
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-64. Heat from Maize Residue; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Octane
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
5
disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.035
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-82
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-65. Heat from Maize Residue; Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grouj
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from maize residue; improved
brick stove with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.076
kg
1
1
4
1
2
2
3
5
Maize residue, at consumer
CN
0.33
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.35
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
6.5E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
2.0E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.029
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.0020
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
8.5E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0013
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
6.3E-05
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
5.2E-08
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
9.4E-06
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
1.1E-04
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
1.7E-04
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
4.2E-06
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
1.8E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
2.2E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
3.8E-06
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
6.9E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
2.6E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
4.9E-07
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
1.1E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
4.5E-07
kg
1
1
4
1
2
4
5
2
4
2-Methy 1-1 -butene
air
low population density
9.1E-08
kg
1
1
4
1
2
4
5
2
A-83
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-65. Heat from Maize Residue; Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output grou]
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
pentane
air
low population density
1.5E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
2.0E-07
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
4.4E-07
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
4.2E-07
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
8.0E-08
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
6.0E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
3.1E-06
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
4.6E-08
kg
1
1
4
1
2
4
5
2
5
disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.020
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-84
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-66. Heat from Natural Gas; Traditional Gas Stove without Flue; At Consumer (CN)
CL
s.
Data Quality
Input grou
o
•-
#J3
3
s.
s
o
Flow
Category
Subcategor
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from natural gas; traditional gas
stove without flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.089
kg
1
1
4
1
2
2
3
5
Natural gas, at consumer
CN
0.036
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.13
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
5.4E-08
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.1E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
9.5E-06
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
3.3E-06
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
4.1E-06
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
6.4E-07
kg
1
1
4
1
2
4
5
2
4
styrene
air
low population density
2.5E-08
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
2.9E-07
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
2.1E-07
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
4.3E-08
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
3.6E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
4.7E-08
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
5.0E-09
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
5.7E-08
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
2.0E-07
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
1.5E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
4.4E-08
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
2.0E-08
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
1.2E-08
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.1E-08
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
A-85
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-66. Heat from Natural Gas; Traditional Gas Stove without Flue; At Consumer (CN)
c.
a
Data Quality
s
o
-
W)
s
a
c
o
-
S
a
s
Flow
Category
•-
o
ex
0>
"ea
u
.a
s
Location
Amount
Unit
£
S
03
(A
1*1
4>
e
i
a>
&
-
o
c.
s
2
&
C3
U
bJj
o
*C3
CJ
"3d
©
c
-w
a
u
4>
CJ
a
2
References
HH
O
cn
M
c
o
U
H
3
CJ
4>
H
=
p
a.
4
2-Methylhexane
air
low population density
2.0E-09
kg
1
1
4
i
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
7.0E-09
kg
1
1
4
i
2
4
5
2
4
3-Methylhexane
air
low population density
2.2E-08
kg
1
1
4
i
2
4
5
2
4
heptane
air
low population density
7.0E-09
kg
1
1
4
i
2
4
5
2
4
Toluene
air
low population density
6.3E-07
kg
1
1
4
i
2
4
5
2
4
Octane
air
low population density
8.0E-09
kg
1
1
4
i
2
4
5
2
.
4
Ethyl benzene
air
low population density
5.7E-08
kg
1
1
4
i
2
4
5
2
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-86
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-67. Heat from Rice Straw; Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from rice straw; improved brick
stove with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.092
kg
1
1
4
1
2
2
3
5
Rice straw, at consumer
CN
0.29
kg
1
4
4
1
2
2
3
3
4
Carbon dioxide, biogenic
air
low population density
0.35
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
6.5E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
2.0E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.029
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.0020
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
8.5E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0013
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
4.1E-06
kg
2
2
3
1
3
5
5
2
4
Xylene
air
low population density
3.4E-09
kg
2
2
3
1
3
5
5
2
4
Ethane
air
low population density
6.2E-07
kg
2
2
3
1
3
5
5
2
4
Ethane
air
low population density
7.1E-06
kg
2
2
3
1
3
5
5
2
4
Ethyne
air
low population density
1.1E-05
kg
2
2
3
1
3
5
5
2
4
Propane
air
low population density
2.8E-07
kg
2
2
3
1
3
5
5
2
4
Propene
air
low population density
1.2E-06
kg
2
2
3
1
3
5
5
2
4
iso-Butane
air
low population density
1.4E-08
kg
2
2
3
1
3
5
5
2
4
iso-Butene
air
low population density
8.1E-08
kg
2
2
3
1
3
5
5
2
4
1-butylene
air
low population density
2.5E-07
kg
2
2
3
1
3
5
5
2
4
Butane
air
low population density
4.5E-08
kg
2
2
3
1
3
5
5
2
4
trans-2-Butene
air
low population density
1.7E-07
kg
2
2
3
1
3
5
5
2
4
cis-2-butene
air
low population density
3.2E-08
kg
2
2
3
1
3
5
5
2
4
3 -methyl-1 -butene
air
low population density
1.4E-08
kg
2
2
3
1
3
5
5
2
4
iso-Pentane
air
low population density
7.2E-10
kg
2
2
3
1
3
5
5
2
A-87
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-67. Heat from Rice Straw; Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
1-Pentene
air
low population density
3.0E-08
kg
2
2
3
1
3
5
5
2
4
2-Methyl-1 -butene
air
low population density
6.0E-09
kg
2
2
3
1
3
5
5
2
4
Pentane
air
low population density
9.9E-10
kg
2
2
3
1
3
5
5
2
4
trans-2-Pentene
air
low population density
1.3E-08
kg
2
2
3
1
3
5
5
2
4
cis-2-Pentene
air
low population density
8.6E-09
kg
2
2
3
1
3
5
5
2
4
2 -Methy 1-2 -butene
air
low population density
2.9E-08
kg
2
2
3
1
3
5
5
2
4
1-Hexene
air
low population density
2.7E-08
kg
2
2
3
1
3
5
5
2
4
Hexane
air
low population density
5.3E-09
kg
2
2
3
1
3
5
5
2
4
Heptane
air
low population density
3.9E-09
kg
2
2
3
1
3
5
5
2
4
Toluene
air
low population density
2.0E-07
kg
2
2
3
1
3
5
5
2
4
Ethyl benzene
air
low population density
3.0E-09
kg
2
2
3
1
3
5
5
2
5
disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.0020
kg
1
1
4
1
2
2
3
1,3
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
[3] Liu Z, A., Xu, and B. Long. 2011. Energy from combustion of rice straw: Status and challenges to China. Energy and Power Engineering 3(3): 325-331.
A-88
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-68. Heat from Shanxi Coal Powder; Metal Stove with Flue; At Consumer (CN)
fi
Data Quality
Flow Informatio
Output group
Flow
Category
Subcategory
Location
Amount
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from Shanxi coal powder; metal
stove with flue; at consumer
CN
1.00
M
J
i
4
air, from nature
resource
air
1.03
kg
1
1
4
1
2
2
3
5
Coal powder, at consumer
CN
0.70
kg
1
4
4
1
2
3
3
i
4
Carbon dioxide, fossil
air
low population density
1.44
kg
1
1
4
1
2
2
3
i
4
Sulfur dioxide
air
low population density
0.014
kg
1
1
4
1
2
2
3
i
4
Nitrogen oxides
air
low population density
0.0027
kg
1
1
4
1
2
2
3
i
4
Carbon monoxide, fossil
air
low population density
0.060
kg
1
1
4
1
2
2
3
i
4
Methane, fossil
air
low population density
0.0039
kg
1
1
4
1
2
2
3
i
4
Non methane total organic compounds
air
low population density
1.2E-04
kg
1
1
4
1
2
2
3
i
4
Particulates, < 2.5 um
air
low population density
9.4E-05
kg
1
1
4
1
2
2
3
i
4
benzene
air
low population density
1.2E-04
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
2.4E-06
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
9.4E-07
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
7.9E-05
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
3.3E-04
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
9.4E-05
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
1.8E-05
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
5.1E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
9.2E-06
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
4.9E-06
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
2.9E-06
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
2.6E-07
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
8.7E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
A-89
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-68. Heat from Shanxi Coal Powder; Metal Stove with Flue; At Consumer (CN)
fi
Data Quality
Flow Informatio
Output group
Flow
Category
Subcategory
Location
Amount
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
pentane
air
low population density
2.8E-06
kg
1
1
4
1
2
4
5
2
4
2,3 -Dimethybutane
air
low population density
3.7E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
5.6E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
4.8E-07
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
4.0E-07
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
3.6E-07
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
1.8E-05
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
4.3E-07
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
1.5E-07
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.21
kg
1
1
4
1
2
3
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-90
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-69. Heat from Shanxi Honeycomb Coal Briquette; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from Shanxi honeycomb coal
briquette; metal stove with flue; at
consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.20
kg
1
1
4
1
2
2
3
5
Coal briquette, at consumer
CN
0.11
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.27
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
8.9E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.2E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.0077
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
4.1E-04
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
1.1E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
7.2E-05
kg
1
1
4
1
2
2
3
1
4
1,2,4-Trimethylbenzene
air
low population density
6.1E-04
kg
1
1
4
1
2
4
5
2
4
1-butene
air
low population density
7.1E-06
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
1.5E-04
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
1.2E-05
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
2.4E-05
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
Benzene
air
low population density
9.0E-04
kg
1
1
4
1
2
4
5
2
4
Butane
air
low population density
1.4E-05
kg
1
1
4
1
2
4
5
2
4
Decane
air
low population density
1.8E-04
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
2.8E-04
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
5.0E-04
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
4.6E-05
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
4.8E-04
kg
1
1
4
1
2
4
5
2
A-91
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-69. Heat from Shanxi Honeycomb Coal Briquette; Metal Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
Heptane
air
low population density
3.4E-05
kg
1
1
4
1
2
4
5
2
4
Hexane
air
low population density
2.5E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.6E-05
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
9.1E-06
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
1.9E-05
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
1.0E-04
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
3.3E-05
kg
1
1
4
1
2
4
5
2
4
Pentane
air
low population density
1.3E-05
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
5.9E-05
kg
1
1
4
1
2
4
5
2
4
Propene
air
low population density
9.3E-05
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
2.1E-04
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
1.0E-04
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
4.0E-02
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-92
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-70. Heat from Washed Coal Powder; Metal Stove with Flue; At Consumer (CN)
_ a
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from washed coal powder; metal
stove with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.55
kg
1
1
4
1
2
2
3
5
Coal powder, at consumer
CN
0.36
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, fossil
air
low population density
0.86
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
3.7E-04
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
6.3E-05
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, fossil
air
low population density
0.032
kg
1
1
4
1
2
2
3
1
4
Methane, fossil
air
low population density
0.0052
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
6.9E-04
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0052
kg
1
1
4
1
2
2
3
1
4
Benzene
air
low population density
1.5E-04
kg
1
1
4
1
2
4
5
2
4
Butadiene
air
low population density
4.4E-06
kg
1
1
4
1
2
4
5
2
4
Xylene
air
low population density
8.6E-07
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
3.7E-04
kg
1
1
4
1
2
4
5
2
4
Ethane
air
low population density
4.6E-04
kg
1
1
4
1
2
4
5
2
4
Ethyne
air
low population density
1.3E-04
kg
1
1
4
1
2
4
5
2
4
Propane
air
low population density
1.3E-04
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
1.7E-04
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
1.0E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
1.3E-05
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
3.7E-05
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
4.0E-05
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
5.9E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
1.1E-06
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
3.0E-06
kg
1
1
4
1
2
4
5
2
4
iso-Pentane
air
low population density
8.9E-06
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
3.6E-07
kg
1
1
4
1
2
4
5
2
4
2-Methy 1-1 -butene
air
low population density
2.7E-06
kg
1
1
4
1
2
4
5
2
A-93
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-70. Heat from Washed Coal Powder; Metal Stove with Flue; At Consumer (CN)
_ a
Data Quality
Input grouj
Output grou
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
pentane
air
low population density
2.3E-05
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
3.4E-07
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
3.0E-07
kg
1
1
4
1
2
4
5
2
4
Cyclopentane
air
low population density
1.4E-06
kg
1
1
4
1
2
4
5
2
4
2,3-Dimethybutane
air
low population density
2.5E-06
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
6.0E-06
kg
1
1
4
1
2
4
5
2
4
3-Methylpentane
air
low population density
1.6E-06
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
9.0E-06
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.6E-05
kg
1
1
4
1
2
4
5
2
4
Methyl cyclopentane
air
low population density
4.4E-06
kg
1
1
4
1
2
4
5
2
4
Cyclohexane
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylhexane
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
2,3 Dimethylpentane
air
low population density
1.9E-06
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
2.2E-06
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
1.1E-05
kg
1
1
4
1
2
4
5
2
4
Methyl cyclohexane
air
low population density
2.0E-06
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
2.2E-05
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
3-Ethylhexane
air
low population density
2.3E-07
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
3.2E-06
kg
1
1
4
1
2
4
5
2
4
Nonane
air
low population density
3.3E-07
kg
1
1
4
1
2
4
5
2
5
Disposal, lignite ash from stove, 0%
water, to sanitary landfill
CN
0.013
kg
1
1
4
1
2
2
3
1
[1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-94
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-71. Heat from Wheat Residue; At Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
heat from wheat residue; at improved
brick stove with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.13
kg
1
1
4
1
2
2
3
5
Wheat residue, at consumer
CN
0.46
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.45
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
3.9E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
1.1E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.084
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.0042
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0046
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0085
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
5.8E-04
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
5.0E-06
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
3.9E-05
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
7.9E-04
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
9.5E-04
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
8.5E-06
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
1.0E-04
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
4.0E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
5.3E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
1.3E-05
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
1.0E-06
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
1.8E-05
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
1.8E-06
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
A-95
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-71. Heat from Wheat Residue; At Improved Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
iso-Pentane
air
low population density
1.6E-07
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
2.0E-06
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
1.0E-06
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
4.1E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
1.0E-06
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
6.6E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
5.4E-08
kg
1
1
4
1
2
4
5
2
4
Cyclopentene
air
low population density
1.8E-07
kg
1
1
4
1
2
4
5
2
4
4-Methyl-1 -pentene
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
6.8E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
2.1E-06
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
1.3E-07
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
2.2E-08
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
5.8E-07
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
7.1E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
5.0E-05
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
3.4E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
3.4E-09
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
3.3E-07
kg
1
1
4
1
2
4
5
2
5
disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.040
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y., Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-96
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-72. Heat from Wheat Residue; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
0
Heat from wheat residue; brick stove
with flue; at consumer
CN
1.00
MJ
1
4
air, from nature
resource
air
0.36
kg
1
1
4
1
2
2
3
5
Wheat residue, at consumer
CN
0.74
kg
1
4
4
1
2
2
3
1
4
Carbon dioxide, biogenic
air
low population density
0.98
kg
1
1
4
1
2
2
3
1
4
Sulfur dioxide
air
low population density
2.2E-05
kg
1
1
4
1
2
2
3
1
4
Nitrogen oxides
air
low population density
8.1E-04
kg
1
1
4
1
2
2
3
1
4
Carbon monoxide, biogenic
air
low population density
0.046
kg
1
1
4
1
2
2
3
1
4
Methane, biogenic
air
low population density
0.0020
kg
1
1
4
1
2
2
3
1
4
Non methane total organic compounds
air
low population density
0.0027
kg
1
1
4
1
2
2
3
1
4
Particulates, < 2.5 um
air
low population density
0.0037
kg
1
1
4
1
2
2
3
1
4
benzene
air
low population density
3.4E-04
kg
1
1
4
1
2
4
5
2
4
butadiene
air
low population density
2.9E-06
kg
1
1
4
1
2
4
5
2
4
xylene
air
low population density
7.4E-07
kg
1
1
4
1
2
4
5
2
4
ethane
air
low population density
2.3E-05
kg
1
1
4
1
2
4
5
2
4
ethene
air
low population density
4.7E-04
kg
1
1
4
1
2
4
5
2
4
ethyne
air
low population density
5.6E-04
kg
1
1
4
1
2
4
5
2
4
propane
air
low population density
5.0E-06
kg
1
1
4
1
2
4
5
2
4
propene
air
low population density
6.1E-05
kg
1
1
4
1
2
4
5
2
4
iso-Butane
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
iso-Butene
air
low population density
3.2E-06
kg
1
1
4
1
2
4
5
2
4
1-butylene
air
low population density
7.8E-06
kg
1
1
4
1
2
4
5
2
4
butane
air
low population density
6.2E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Butene
air
low population density
1.1E-05
kg
1
1
4
1
2
4
5
2
4
cis-2-butene
air
low population density
1.0E-06
kg
1
1
4
1
2
4
5
2
4
3 -methyl-1 -butene
air
low population density
7.2E-07
kg
1
1
4
1
2
4
5
2
A-97
-------
Appendix A - Detailed LCI Unit Process Tables
Table A-72. Heat from Wheat Residue; Brick Stove with Flue; At Consumer (CN)
Data Quality
Input group
Output group
Flow
Category
Subcategory
Location
Amount
Unit
Reliability
Complete-ness
Temporal
Geographic
Technological
Uncertainty
Precision
References
4
iso-Pentane
air
low population density
9.2E-08
kg
1
1
4
1
2
4
5
2
4
1-Pentene
air
low population density
1.2E-06
kg
1
1
4
1
2
4
5
2
4
2-Methyl-1 -butene
air
low population density
6.0E-07
kg
1
1
4
1
2
4
5
2
4
pentane
air
low population density
2.4E-07
kg
1
1
4
1
2
4
5
2
4
trans-2-Pentene
air
low population density
6.0E-07
kg
1
1
4
1
2
4
5
2
4
cis-2-Pentene
air
low population density
3.9E-07
kg
1
1
4
1
2
4
5
2
4
2-Methyl-2-butene
air
low population density
3.2E-08
kg
1
1
4
1
2
4
5
2
4
Cyclopentene
air
low population density
1.1E-07
kg
1
1
4
1
2
4
5
2
4
4-Methyl-1 -pentene
air
low population density
1.4E-07
kg
1
1
4
1
2
4
5
2
4
2-Methylpentane
air
low population density
4.0E-08
kg
1
1
4
1
2
4
5
2
4
1-Hexene
air
low population density
1.3E-06
kg
1
1
4
1
2
4
5
2
4
hexane
air
low population density
7.9E-08
kg
1
1
4
1
2
4
5
2
4
3-Methylhexane
air
low population density
1.3E-08
kg
1
1
4
1
2
4
5
2
4
2,2,4-Trimethylpentane
air
low population density
3.4E-07
kg
1
1
4
1
2
4
5
2
4
heptane
air
low population density
4.2E-08
kg
1
1
4
1
2
4
5
2
4
Toluene
air
low population density
3.0E-05
kg
1
1
4
1
2
4
5
2
4
2-Methylheptane
air
low population density
2.0E-08
kg
1
1
4
1
2
4
5
2
4
Octane
air
low population density
2.0E-09
kg
1
1
4
1
2
4
5
2
4
Ethyl benzene
air
low population density
2.0E-07
kg
1
1
4
1
2
4
5
2
5
disposal, wood ash mixture, pure, 0%
water, to landfanning
CN
0.064
kg
1
1
4
1
2
2
3
1
1] Zhang J., K.R., Smith KR, and Y.. Ma, et al. 2000. Greenhouse gases and other airborne pollutants from household stoves in China: a database for emission
factors. Atmospheric Enviromnent 34(26): 4537-4549.
[2] Tsai S.M., J., Zhang, and K.R. Smith, et al. 2003. Characterization of non-methane hydrocarbons emitted from various cookstoves used in China.
Enviromnental Science & Technology 37(13): 2869-2877.
A-98
-------
Appendix B - Detailed LCA Results Tables
APPENDIX B: DETAILED LCA RESULTS TABLES
Appendix B provides detailed LCA results tables by impact category for India and China.
Results for each country are included by cooking fuel type and by baseline and potential scenarios.
Given the magnitude of impacts resulting from the use of cookstoves on both the environment and
human health it is important to consider how future changes in cookstove fuel mix might affect
these impacts. Eight potential fuel use scenarios were developed in order to explore how impacts
in each of the ten studied environmental impact categories may change in the future.
Detailed Results Tables for India by Cooking Fuel Type
This section offers the detailed results tables by life cycle stage of the selected LCI and
LCIA categories for the individual cooking fuels used within India (Table B-l through Table B-
10). Refer to Section 3.1, Results for India by Cooking Fuel Type, of the report for discussion and
a visual of each table in this section.
Table B-l. Detailed Results for Global Climate Change Potential by Cooking Fuel Type in
India
TOTAL
Cookstove
Use
Feedstock
Production
Fuel
Processing
Distribution
Hard Coal
16.2
1.62
945
963
LPG from NG
3.13
2.77
12.0
274
292
LPG from Oil
5.29
11.2
12.0
274
303
Kerosene
6.54
13.9
12.7
148
181
Electricity
415
415
Sugarcane
Ethanol
Climate
79.
5.29
9.71
0.96
95.7
Biogas from
Cattle Dung
9.19
1.33
10.5
Charcoal from
Wood
274
29.0
270
572
Biomass Pellets
27.
1.10
105
134
Firewood
539
539
Crop Residue
132
132
Dung Cake
191
191
Potential
(kg CO 2 eq)
Per GJ Delivered Heat for
Life Cycle Stage
B-l
-------
Appendix B - Detailed LCA Results Tables
Table B-2. Detailed Results for Cumulative Energy Demand by Cooking Fuel Type in India
Hard Coal
Feedstock
Production
7,315
Fuel
Processing
0
Distribution
10.S
Cookstove
Use
6,452
LPG from NG
18.1
44.3
27.0
1,302
LPG from Oil
27.4
67.0
40.£
1,971
Kerosene
33.6
93.2
28.8
2,428
Electricity
5,443
Sugarcane
Ethanol
222
4,378
20.3
1,887
Biogas from
Cattle Dung
1,820
Charcoal from
Wood
4,494
0.39
5,715
Biomass Pellets
189
3.01
1,847
Firewood
7,716
Crop Residue
9,670
Dung Cake
12,859
Table B-3. Detailed Results for Fossil Depletion by Cooking Fuel Type in India
J Delivered Heat lor
LPG from NG
LPG from Oil
Kerosene
Feedstock
Production
129
Fuel
Processing
0
Distribution
Cookstove
Use
0.19
114
0.47
1.15
0.70
33.*
0.70
1.71
1.04
50.2
0.85
2.37
0.73
61.7
Electricity
91.4
Sugarcane Ethanol
12.2
2.80
3.30
Biogas from Cattle
Dung
Charcoal from
Wood
0.10
0.0094
0.0061
Biomass Pellets
5.S
0.37
1.8E-04
Firewood
0.0064
Crop Residue
0.0076
Dung Cake
0.15
B-2
-------
Appendix B - Detailed LCA Results Tables
Table B-4. Detailed Results for Water Depletion by Cooking Fuel Type in India
Feedstock
1 Production
Fuel
Processing
Distribution
Cookstove
Use
TOTAL
1 Hard Coal
0.38
0
8.53
7.70
16.6
1 LPG from NG
0.74
1.25
24.7
0
26.7
1 LPG from Oil
1.24
5.74
24.7
0
31.7
Kerosene
1.53
7.09
27.7
0
36.3
Electricity
0
0
0
515
515
Sugarcane Ethanol
55.4
13.4
19.8
0
88.6
Biogas from Cattle Dung
0
1.04
0
0
1.04
Charcoal from Wood
0
0.58
9.0E-05
0.047
0.63
Biomass Pellets
0
32.9
2.70
8.8E-04
35.6
Firewood
0
0
0
0.049
0.049
Crop Residue
0
0
0
0.058
0.058
| Dung Cake
0
0
0
1.19
1.19
Table B-5. Detailed Results for Particulate Matter Formation by Cooking Fuel Type in
India
(kgPMlO
eq)
Feedstock
1 Production
Fuel
Processing
Distribution
Cookstove
Use
TOTAL
Hard Coal
1.66
0
0.0038
17.6
19.3
LPG from NG
0.0058
0.029
0.025
0.060
0.12
LPG from Oil
0.010
0.070
0.025
0.060
0.16
Kerosene
0.012
0.086
0.023
0.19
0.31
Electricity
0
0
0
1.69
1.69
Sugarcane Ethanol
0.11
0.035
0.018
4.3E-04
0.17
Biogas from Cattle Dung
0
0
0
0.077
0.077
Charcoal from Wood
0
18.8
0.050
0.70
19.5
Biomass Pellets
0
0.11
0.0027
0.10
0.21
Firewood
0
0
0
4.72
4.72
Crop Residue
0
0
0
11.3
11.3
Dung Cake
0
0
0
23.6
23.6
B-3
-------
Appendix B - Detailed LCA Results Tables
Table B-6. Detailed Results for Photochemical Oxidant Formation by Cooking Fuel Type
in India
(kg
NMVOC
eq)
Feedstock
1 Production
Fuel
Processing
Distribution
Cookstove
Use
TOTAL
Hard Coal
0.14
0
0.010
7.71
7.86
LPG from NG
0.014
0.022
0.079
0.50
0.62
LPG from Oil
0.024
0.15
0.079
0.50
0.76
Kerosene
0.029
0.18
0.083
0.86
1.16
Electricity
0
0
0
2.01
2.01
Sugarcane Ethanol
0.17
0.047
0.064
0.062
0.34
Biogas from Cattle Dung
0
0.0037
0
0.11
0.11
Charcoal from Wood
0
5.30
0.21
5.03
10.5
Biomass Pellets
0
0.13
0.0096
0.10
0.24
Firewood
0
0
0
6.02
6.02
Crop Residue
0
0
0
8.75
8.75
Dung Cake
0
0
0
18.7
18.7
Table B-7. Detailed Results for Freshwater Eutrophication by Cooking Fuel Type in India
Feedstock
1 Production
Fuel
Processing
Distribution
Cookstove
Use
TOTAL
1 Hard Coal
7.6E-06
0
0.0011
0.0010
0.0021
1 LPG from NG
8.6E-06
2.0E-05
5.2E-04
0.0015
0.0021
1 LPG from Oil
1.4E-05
7.9E-04
5.2E-04
0.0015
0.0029
Kerosene
1.8E-05
9.7E-04
0.0023
0
0.0033
Electricity
0
0
0
0.0034
0.0034
Sugarcane Ethanol
0.033
0.0021
0.0016
1.1E-06
0.037
Biogas from Cattle Dung
0
0
0
0
0
Charcoal from Wood
0
0.13
1.0E-07
0.15
0.28
Biomass Pellets
0
2.7E-04
3.1E-04
0.0028
0.0034
Firewood
0
0
0
0.16
0.16
Crop Residue
0
0
0
0.19
0.19
| Dung Cake
0
0
0
3.82
3.82
B-4
-------
Appendix B - Detailed LCA Results Tables
Table B-8. Detailed Results for Terrestrial Acidification by Cooking Fuel Type in India
Feedstock
Production
Hard Coal
0.076
Fuel
Processing
0
Distribution
0.0094
Cookstove
Use
1.78
TOTAL
LPG from NG
0.011
0.12
0.056
0.12
LPG from Oil
0.018
0.14
0.056
0.12
Kerosene
0.023
0.17
0.052
0.16
Electricity
0
0
4.00
Sugarcane Ethanol
0.31
0.15
0.039
Biogas from Cattle Dung
0
0
0.11
Charcoal from Wood
0.0046
0
0.20
Biomass Pellets
Firewood
Crop Residue
Dung Cake
0.25
0.0063
0
0.034
0.40
0.62
0.75
Table B-9. Detailed Results for Ozone Depletion by Cooking Fuel Type in India
Per GJ Deliv
Feedstock
1 Production
Fuel
Processing
Distribution
Cookstove
Use
TOTAL
Hard Coal
8.1E-09
0
1.1E-07
7.0E-07
8.2E-07
LPG from NG
6.4E-09
1.2E-06
1.1E-06
0
2.3E-06
LPG from Oil
1.1E-08
8.5E-07
1.1E-06
0
2.0E-06
Kerosene
1.3E-08
1.0E-06
1.4E-06
0
2.4E-06
Electricity
0
0
0
1.4E-06
1.4E-06
Depletion
Sugarcane Ethanol
4.6E-06
6.9E-07
1.0E-06
0
6.3E-06
(kg CFC 11
Biogas from Cattle Dung
0
0
0
0
0
eq)
Charcoal from Wood
0
2.1E-09
0
2.5E-09
4.5E-09
Biomass Pellets
0
1.7E-07
1.5E-07
4.6E-11
3.2E-07
Firewood
0
0
0
2.6E-09
2.6E-09
Crop Residue
0
0
0
3.1E-09
3.1E-09
Dung Cake
0
0
0
6.2E-08
6.2E-08
B-5
-------
Appendix B - Detailed LCA Results Tables
Table B-10. Detailed Results for Black Carbon by Cooking Fuel Type in India
Feedstock
Production
Hard Coal
0.34
Fuel
Processing
0
Distribution
Cookstove
Use
1.3E-05
3.58
LPGfromNG
3.6E-04
-0.0061
8.1E-04
0.0055
LPG from Oil
6.2E-04
0.0072
8.1E-04
0.0055
Kerosene
7.6E-04
0.0089
0.0010
0.034
Electricity
0
0
0
-0.019
Sugarcane Ethanol
-0.0017
-0.0073
8.1E-04
0.0028
Biogas from Cattle Dung
0
0
0
0.0068
Charcoal from Wood
4.02
0
0.26
Biomass Pellets
Firewood
Crop Residue
Dung Cake
-0.0010
0
8.9E-05
0
0.021
1.04
2.42
5.01
Detailed Results Tables for China by Cooking Fuel Type
This section provides ten tables with detailed results analysis of LCI and LCIA categories
for the individual fuels used within China (Table B-l 1 through Table B-20). Refer to Section 4.1,
Results for China by Cooking Fuel Type, of the report for discussion and a visual of each table in
this section.
Table B-ll. Detailed Results for Global Climate Change by Cooking Fuel Type in China
Per GJ Del
Global
Climate
Change
(kg CO 2
eq)
TOTAL
Feedstock
Production
Fuel
Processing
Cookstove
Use
Distribution
Coal Mix
Coal Powder
Coal Briquettes
Honeycomb Coal Briquettes
Biomass Mix
Fuel & Brush Wood
Ag Residues
LPG
Kerosene
Electricity
Natural Gas
Biomass Pellets
310
3.16
72.3
15.3
154
13.5
22.6
1.35
33.4
12.6
9.33
30.1
40.9
2.60
336
40.1
19.1
1.30
27.1
974
361
487
180
281
54.7
145
160
496
147
77.3
DME
148
37.9
67.£
92.0
B-6
-------
Appendix B - Detailed LCA Results Tables
Table B-12. Detailed Results for Cumulative Energy Demand by Cooking Fuel Type in
China
TOTAL
Feedstock
Production
Fuel
Processing
Cookstove
Use
Distribution
Coal Mix
5.061
1.014
3.658
10,506
Coal Powder
6.149
1.232
4.445
12,764
Coal Briquettes
4.303
3.110
8,932
Honeycomb Coal Briquettes
3.643
2.633
7,563
Biomass Mix
7.151
7,151
Fuel & Brush Wood
6.538
6,538
Ag Residues
7.905
7,905
2.291
2,784
Kerosene
2.205
2,943
Electricity
6.060
6,060
Natural Gas
1.660
2,049
Biomass Pellets
1.781
2,369
DME
3.546
2.174
6,395
Table B-13. Detailed Results for Fossil Depletion by Cooking Fuel Type in China
Per GJ Deliv
Fossil
Depletion
(kg oil eq)
TOTAL
Feedstock
Production
Fuel
Processing
Cookstove
Use
Distribution
Coal Mix
Coal Powder
Coal Briquettes
Honeycomb Coal Briquettes
Biomass Mix
Fuel & Brush Wood
Ag Residues
LPG
Kerosene
Electricity
Natural Gas
Biomass Pellets
DME
86.4
103
76.0
64.3
6.44
16.4
1.46
61.6
17.3
20.6
15.2
12.9
4.55
0.12
0.12
8.09
0.18
13.2
15.7
11.6
9.82
0.43
0.43
7.65
0.030
11.5
62.5
74.2
54.9
46.5
0.0082
0.0025
0.015
53.0
50.7
95.6
39.4
1.8E-04
37.8
179
213
158
134
0.0082
0.0025
0.015
64.4
67.7
95.6
48.6
8.12
111
B-7
-------
Appendix B - Detailed LCA Results Tables
Table B-14. Detailed Results for Water Depletion by Cooking Fuel Type in China
Feedstock
Production
Coal Mix
9.45
Fuel
Processing
7.83
Distribution
23.9
Cookstove
Use
3.36
TOTAL
Coal Powder
10.1
3.84
2.69
2.49
Coal Briquettes
9.57
11.3
48.8
6.68
Honeycomb Coal Briquettes
8.11
12.4
41.4
1.78
Biomass Mix
0.063
Fuel & Brash Wood
0.019
Ag Residues
0.12
LPG
53.9
1.61
1.56
Kerosene
7.00
63.5
1.76
Electricity
524
Natural Gas
3.50
0.20
2.07
0
Biomass Pellets
DME
20.4
49.2
3.03
4.11
0.0049
0
Table B-15. Detailed Results for Particulate Matter Formation by Cooking Fuel Type in
China
TOTAL
Feedstock
Production
Fuel
Processing
Cookstove
Use
Distribution
0.070
Coal Powder
0.0087
0.0079
Coal Briquettes
Honeycomb Coal Briquettes
Biomass Mix
Fuel & Brash Wood
Ag Residues
(kgPMlO
eq)
0.0037
0.0030
0.032
Kerosene
0.0011
0.0043
0.018
Electricity
Natural Gas
0.019
6.8E-04
0.018
0.019
Biomass Pellets
DME
0.0068
0.036
0.046
B-8
-------
Appendix B - Detailed LCA Results Tables
Table B-16. Detailed Results for Photochemical Oxidant Formation by Cooking Fuel Type
in China
Feedstock
Production
Coal Mix
0.21
Fuel
Processing
0.041
Distribution
0.27
Cookstove
Use
1.80
Coal Powder
0.26
0.012
0.031
3.00
Coal Briquettes
0.18
0.071
0.56
0.39
Honeycomb Coal
Briquettes
0.15
0.067
0.47
0.81
Biomass Mix
0
2.13
Fuel & Brash Wood
1.81
Ag Residues
0
0
2.52
LPG
0.27
0.0052
0.017
0.11
Kerosene
0.34
0.0020
0.0088
0.073
Electricity
0
0
0
1.87
Natural Gas
0.077
7.6E-04
0.081
0.066
Biomass Pellets
DME
0
0.17
0.16
0.010
0_
1.73
0.10
0.095
Table B-17. Detailed Results for Freshwater Eutrophication by Cooking Fuel Type in
China
Feedstock
Production
Coal Mix
0.10
Fuel
Processing
0.0021
Distribution
0.0028
Cookstove
Use
4.3E-04
Coal Powder
0.14
4.1E-04
3.1E-04
3.2E-04
Coal Briquettes
0.079
0.0040
0.0057
8.6E-04
Honeycomb Coal
Briquettes
0.067
0.0037
0.0049
2.3E-04
Biomass Mix
0
0
0
0.20
Fuel & Brash Wood
0.061
Ag Residues
0
0
0
0.38
LPG
0.0078
1.7E-04
1.2E-04
Kerosene
0.010
5.1E-05
2.0E-04
0
Electricity
0
0
0
0.063
Natural Gas
3.1E-04
2.1E-05
3.6E-04
0
Biomass Pellets
DME
0
0.062
0.0052
3.2E-04
0_
7.4E-04
0.015
0
B-9
-------
Appendix B - Detailed LCA Results Tables
Table B-18. Detailed Results for Terrestrial Acidification by Cooking Fuel Type in China
Feedstock
Production
Coal Mix
1.03
Fuel
Processing
0.077
Distribution
0.17
Cookstove
Use
2.45
TOTAL
Coal Powder
1.32
0.028
0.019
4.57
Coal Briquettes
0.79
0.13
0.35
0.32
Honeycomb Coal Briquettes
0.67
0.12
0.30
0.34
Biomass Mix
0.29
Fuel & Brash Wood
0.29
Ag Residues
0
0
0.30
LPG
0.62
0.012
0.0072
0.046
Kerosene
0.82
0.0035
0.013
0.030
Electricity
0
0
0
4.27
Natural Gas
0.083
0.0014
0.049
0.036
Biomass Pellets
DME
0
0.93
0.36
0.022
0
0.098
0.034
0.13
Table B-19. Detailed Results for Ozone Depletion by Cooking Fuel Type in China
Feedstock
Production
Coal Mix
1.1E-06
Fuel
Processing
2.4E-06
Distribution
Cookstove
Use
2.3E-06
5.8E-07
Coal Powder
3.0E-07
1.8E-08
2.9E-07
2.3E-07
Coal Briquettes
3.5E-07
6.7E-06
5.3E-06
6.1E-07
Honeycomb Coal Briquettes
3.3E-06
2.9E-06
3.4E-06
1.3E-06
Biomass Mix
0
0
0
3.3E-09
Fuel & Brash Wood
9.9E-10
Ag Residues
0
0
0
6.2E-09
LPG
2.9E-05
5.9E-09
1.6E-07
0
Kerosene
3.8E-05
0
8.8E-08
0
Electricity
0
0
0
2.3E-06
Natural Gas
3.2E-05
2.7E-08
2.5E-06
0
Biomass Pellets
0
2.3E-07
0
2.3E-10
DME
2.1E-05
6.2E-08
2.1E-06
0
B-10
-------
Appendix B - Detailed LCA Results Tables
Table B-20. Detailed Results for Black Carbon by Cooking Fuel Type in China
Per GJ Del
Black
Carbon &
Short
Lived
Climate
Pollutants
(kg BC
eq)
Feedstock
Production
Fuel
Processing
Cookstove
Use
Distribution
Coal Mix
Coal Powder
Coal Briquettes
Honeycomb Coal Briquettes
Biomass Mix
Fuel & Brash Wood
Ag Residues
LPG
Kerosene
Electricity
Natural Gas
Biomass Pellets
DME
-0.0045
-0.0043
-0.0049
-0.0046
0
0
0.0028
-0.029
0
-0.0037
0
-0.031
0.038
0.036
0.041
0.038
0
0
-0.019
-0.0047
0
5.1E-05
-0.010
0.087
0.017
0.016
0.018
0.017
0
0
-0.0062
-2.3E-04
0
-7.2E-05
1.4E-04
-6.9E-04
-0.0067
-0.0064
-0.0072
-0.0068
0.47
0.30
0.69
0.0046
0.0023
-0.12
0.0015
0.021
-0.0022
Detailed LCA Results Tables for India by Baseline and Potential Scenarios
This section offers the detailed results tables by baseline and potential scenarios of the
selected LCI and LCIA categories for the individual cooking fuels used within India (Table B-21
through Table B-29). Refer to Section 3.2, Results for India by Baseline and Potential Scenarios,
of the report for discussion and a visual of each table in this section.
Table B-21. Detailed Results for Global Climate Change Potential by Baseline and
Potential Scenarios in India
Global Climate Change Potential (kg CO2 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
18.3
18.3
18.3
18.3
18.3
18.3
18.3
18.3
18.3
LPG from NG
15.4
21.6
27.7
27.7
15.4
15.4
15.4
15.4
15.4
LPG from Oil
60.2
84.1
108
108
60.2
60.2
60.2
60.2
60.2
Kerosene
5.80
5.80
5.80
5.80
5.80
5.80
5.80
5.80
5.80
Electricity
43.1
1.66
1.66
1.66
38.7
1.66
1.66
1.66
1.66
Sugarcane Ethanol
0
0
0
0
0
0
9.57
0
0
Biogas from Cattle
Dung
0.042
0.042
0.042
0.042
0.042
0.042
0.042
1.09
0.042
Charcoal from
Wood
2.29
2.29
2.29
2.29
2.29
2.29
2.29
2.29
2.29
B-ll
-------
Appendix B - Detailed LCA Results Tables
Table B-21. Detailed Results for Global Climate Change Potential by Baseline and
Potential Scenarios in India
Global Climate Change Potential (kg CO2 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Biomass Pellets
0
0
0
0
0
13.4
0
0
0
Firewood
219
219
174
197
219
242
242
242
264
Crop Residue
9.49
9.49
7.51
8.50
9.49
10.5
10.5
10.5
11.8
Dung Cake
20.2
20.2
20.2
10.7
20.2
10.7
10.7
10.7
20.2
TOTAL
394
383
365
380
390
381
377
368
400
Table B-22. Detailed Results for Cumulative Energy Demand by Baseline and Potential
Scenarios in India
Cumulative Energy Demand (MJ)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
262
262
262
262
262
262
262
262
262
LPG from NG
73.6
103
132
132
73.6
73.6
73.6
73.6
73.6
LPG from Oil
419
586
752
752
419
419
419
419
419
Kerosene
82.7
82.7
82.7
82.7
82.7
82.7
82.7
82.7
82.7
Electricity
566
21.8
21.8
21.8
546
21.8
21.8
21.8
21.8
Sugarcane Ethanol
0
0
0
0
0
0
651
0
0
Biogas from Cattle
Dung
7.28
7.28
7.28
7.28
7.28
7.28
7.28
189
7.28
Charcoal from
Wood
40.8
40.8
40.8
40.8
40.8
40.8
40.8
40.8
40.8
Biomass Pellets
0
0
0
0
0
204
0
0
0
Firewood
3.142
3.142
2.486
2.814
3.142
3.470
3.470
3.470
3.781
Crop Residue
695
695
550
622
695
767
767
767
861
Dung Cake
1.363
1.363
1.363
720
1.363
720
720
720
1.363
TOTAL
6.651
6.302
6.912
5.454
6.631
6.068
6.515
6.046
6.912
B-12
-------
Appendix B - Detailed LCA Results Tables
Table B-23. Detailed Results for Fossil Depletion by Baseline and Potential Scenarios in
India
Fossil Depletion (kg oil eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase
in Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
4.61
4.61
4.61
4.61
4.61
4.61
4.61
4.61
4.61
LPG from NG
1.91
2.67
3.42
3.42
1.91
1.91
1.91
1.91
1.91
LPG from Oil
10.7
14.9
19.2
19.2
10.7
10.7
10.7
10.7
10.7
Kerosene
2.10
2.10
2.10
2.10
2.10
2.10
2.10
2.10
2.10
Electricity
9.51
0.37
0.37
0.37
8.98
0.37
0.37
0.37
0.37
Sugarcane Ethanol
0
0
0
0
0
0
1.83
0
0
Biogas from Cattle
Dung
0
0
0
0
0
0
0
0
0
Charcoal from
Wood
4.7E-04
4.7E-04
4.7E-04
4.7E-04
4.7E-04
4.7E-04
4.7E-04
4.7E-04
4.7E-04
Biomass Pellets
0
0
0
0
0
0.63
0
0
0
Firewood
0.0026
0.0026
0.0020
0.0023
0.0026
0.0029
0.0029
0.0029
0.0031
Crop Residue
5.4E-04
5.4E-04
4.3E-04
4.9E-04
5.4E-04
6.0E-04
6.0E-04
6.0E-04
6.7E-04
Dung Cake
0.016
0.016
0.016
0.0087
0.016
0.0087
0.0087
0.0087
0.016
TOTAL
28.8
24.7
29.7
29.7
28.3
20.3
21.5
19.7
19.7
Table B-24. Detailed Results for Water Depletion by Baseline and Potential Scenarios in
India
Water Depletion (m3)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase
in Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
0.32
0.32
0.32
0.32
0.32
0.32
0.32
0.32
0.32
LPG from NG
1.41
1.98
2.54
2.54
1.41
1.41
1.41
1.41
1.41
LPG from Oil
6.32
8.82
11.3
11.3
6.32
6.32
6.32
6.32
6.32
Kerosene
1.16
1.16
1.16
1.16
1.16
1.16
1.16
1.16
1.16
Electricity
53.5
2.06
2.06
2.06
67.0
2.06
2.06
2.06
2.06
Sugarcane Ethanol
0
0
0
0
0
0
8.86
0
0
Biogas from Cattle
Dung
0.0042
0.0042
0.0042
0.0042
0.0042
0.0042
0.0042
0.11
0.0042
Charcoal from
Wood
0.0025
0.0025
0.0025
0.0025
0.0025
0.0025
0.0025
0.0025
0.0025
Biomass Pellets
0
0
0
0
0
3.56
0
0
0
Firewood
0.020
0.020
0.016
0.018
0.020
0.022
0.022
0.022
0.024
Crop Residue
0.0042
0.0042
0.0033
0.0037
0.0042
0.0046
0.0046
0.0046
0.0052
B-13
-------
Appendix B - Detailed LCA Results Tables
Table B-24. Detailed Results for Water Depletion by Baseline and Potential Scenarios in
India
Water Depletion (m3)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG
in
Urban
Increase in
LPG /
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG /
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase
in Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Dung Cake
0.13
0.13
0.13
0.066
0.13
0.066
0.066
0.066
0.13
TOTAL
62.9
14.5
17.6
17.5
76.4
14.9
20.2
11.5
11.4
Table B-25. Detailed Results for Particulate Matter Formation by Baseline and Potential
Scenarios in India
Particulate Matter Formation (kg PM10 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
0.37
0.37
0.37
0.37
0.37
0.37
0.37
0.37
0.37
LPG from NG
0.0063
0.0088
0.011
0.011
0.0063
0.0063
0.0063
0.0063
0.0063
LPG from Oil
0.033
0.046
0.059
0.059
0.033
0.033
0.033
0.033
0.033
Kerosene
0.0099
0.0099
0.0099
0.0099
0.0099
0.0099
0.0099
0.0099
0.0099
Electricity
0.18
0.0067
0.0067
0.0067
0.15
0.0067
0.0067
0.0067
0.0067
Sugarcane Ethanol
0
0
0
0
0
0
0.017
0
0
Biogas from Cattle
Dung
3.1E-04
3.IE-04
3.1E-04
3.1E-04
3.1E-04
3.1E-04
3.1E-04
0.0080
3.1E-04
Charcoal from
Wood
0.078
0.078
0.078
0.078
0.078
0.078
0.078
0.078
0.078
Biomass Pellets
0
0
0
0
0
0.021
0
0
0
Firewood
1.92
1.92
1.52
1.72
1.92
2.12
2.12
2.12
2.31
Crop Residue
0.81
0.81
0.64
0.73
0.81
0.90
0.90
0.90
1.01
Dung Cake
2.51
2.51
2.51
1.32
2.51
1.32
1.32
1.32
2.51
TOTAL
5.91
5.76
5.20
4.30
5.88
4.87
4.86
4.85
6.33
B-14
-------
Appendix B - Detailed LCA Results Tables
Table B-26. Detailed Results for Photochemical Oxidant Formation by Baseline and
Potential Scenarios in India
Photochemical Oxidant Formation (kg NMVOC eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
0.15
0.15
0.15
0.15
0.15
0.15
0.15
0.15
0.15
LPG from NG
0.033
0.046
0.059
0.059
0.033
0.033
0.033
0.033
0.033
LPG from Oil
0.15
0.21
0.27
0.27
0.15
0.15
0.15
0.15
0.15
Kerosene
0.037
0.037
0.037
0.037
0.037
0.037
0.037
0.037
0.037
Electricity
0.21
0.0081
0.0081
0.0081
0.17
0.0081
0.0081
0.0081
0.0081
Sugarcane Ethanol
0
0
0
0
0
0
0.034
0
0
Biogas from Cattle
Dung
4.5E-04
4.5E-04
4.5E-04
4.5E-04
4.5E-04
4.5E-04
4.5E-04
0.012
4.5E-04
Charcoal from
Wood
0.042
0.042
0.042
0.042
0.042
0.042
0.042
0.042
0.042
Biomass Pellets
0
0
0
0
0
0.024
0
0
0
Firewood
2.45
2.45
1.94
2.19
2.45
2.71
2.71
2.71
2.95
Crop Residue
0.63
0.63
0.50
0.56
0.63
0.69
0.69
0.69
0.78
Dung Cake
1.98
1.98
1.98
1.05
1.98
1.05
1.05
1.05
1.98
TOTAL
5.68
5.55
4.98
4.37
5.64
4.89
4.90
4.88
6.13
Table B-27. Detailed Results for Freshwater Eutrophication by Baseline and Potential
Scenarios in India
Freshwater Eutrophication (kg P eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
4.1E-05
4.1E-05
4.1E-05
4.1E-05
4.1E-05
4.1E-05
4.1E-05
4.1E-05
4.1E-05
LPG from NG
1.1E-04
1.6E-04
2.0E-04
2.0E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
LPG from Oil
5.7E-04
8.0E-04
0.0010
0.0010
5.7E-04
5.7E-04
5.7E-04
5.7E-04
5.7E-04
Kerosene
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
1.1E-04
Electricity
3.5E-04
1.4E-05
1.4E-05
1.4E-05
3.2E-04
1.4E-05
1.4E-05
1.4E-05
1.4E-05
Sugarcane Ethanol
0
0
0
0
0
0
0.0037
0
0
Biogas from Cattle
Dung
0
0
0
0
0
0
0
0
0
Charcoal from
Wood
0.0011
0.0011
0.0011
0.0011
0.0011
0.0011
0.0011
0.0011
0.0011
Biomass Pellets
0
0
0
0
0
3.4E-04
0
0
0
Firewood
0.064
0.064
0.051
0.057
0.064
0.071
0.071
0.071
0.077
Crop Residue
0.013
0.013
0.011
0.012
0.013
0.015
0.015
0.015
0.017
B-15
-------
Appendix B - Detailed LCA Results Tables
Table B-27. Detailed Results for Freshwater Eutrophication by Baseline and Potential
Scenarios in India
Freshwater Eutrophication (kg P eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG
in
Urban
Increase in
LPG /
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG /
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Dung Cake
0.40
0.40
0.40
0.21
0.40
0.21
0.21
0.21
0.40
TOTAL
0.48
0.48
0.47
0.29
0.48
0.30
0.31
0.30
0.50
Table B-28. Detailed Results for Terrestrial Acidification by Baseline and Potential
Scenarios in India
Terrestrial Acidification (kg SO2 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
0.036
0.036
0.036
0.036
0.036
0.036
0.036
0.036
0.036
LPG from NG
0.016
0.023
0.029
0.029
0.016
0.016
0.016
0.016
0.016
LPG from Oil
0.065
0.091
0.12
0.12
0.065
0.065
0.065
0.065
0.065
Kerosene
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
0.013
Electricity
0.42
0.016
0.016
0.016
0.35
0.016
0.016
0.016
0.016
Sugarcane Ethanol
0
0
0
0
0
0
0.050
0
0
Biogas from Cattle
Dung
4.3E-04
4.3E-04
4.3E-04
4.3E-04
4.3E-04
4.3E-04
4.3E-04
0.011
4.3E-04
Charcoal from
Wood
8.4E-04
8.4E-04
8.4E-04
8.4E-04
8.4E-04
8.4E-04
8.4E-04
8.4E-04
8.4E-04
Biomass Pellets
0
0
0
0
0
0.029
0
0
0
Firewood
0.16
0.16
0.13
0.15
0.16
0.18
0.18
0.18
0.20
Crop Residue
0.044
0.044
0.035
0.040
0.044
0.049
0.049
0.049
0.055
Dung Cake
0.079
0.079
0.079
0.042
0.079
0.042
0.042
0.042
0.079
TOTAL
0.83
0.47
0.45
0.44
0.77
0.45
0.47
0.43
0.48
B-16
-------
Appendix B - Detailed LCA Results Tables
Table B-29. Detailed Results for Ozone Depletion by Baseline and Potential Scenarios in
India
Ozone Depletion (kg CFC 11 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use ill
Urban
Increase
of LPG
in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease in
Biomass &
Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
1.6E-08
1.6E-08
1.6E-08
1.6E-08
1.6E-08
1.6E-08
1.6E-08
1.6E-08
1.6E-08
LPG from NG
1.2E-07
1.7E-07
2.2E-07
2.2E-07
1.2E-07
1.2E-07
1.2E-07
1.2E-07
1.2E-07
LPG from Oil
3.9E-07
5.5E-07
7.0E-07
7.0E-07
3.9E-07
3.9E-07
3.9E-07
3.9E-07
3.9E-07
Kerosene
7.8E-08
7.8E-08
7.8E-08
7.8E-08
7.8E-08
7.8E-08
7.8E-08
7.8E-08
7.8E-08
Electricity
1.4E-07
5.6E-09
5.6E-09
5.6E-09
2.1E-07
5.6E-09
5.6E-09
5.6E-09
5.6E-09
Sugarcane Ethanol
0
0
0
0
0
0
6.3E-07
0
0
Biogas from Cattle
Dung
0
0
0
0
0
0
0
0
0
Charcoal from
Wood
1.8E-11
1.8E-11
1.8E-11
1.8E-11
1.8E-11
1.8E-11
1.8E-11
1.8E-11
1.8E-11
Biomass Pellets
0
0
0
0
0
3.2E-08
0
0
0
Firewood
1.0E-09
1.0E-09
8.2E-10
9.3E-10
1.0E-09
1.2E-09
1.2E-09
1.2E-09
1.3E-09
Crop Residue
2.2E-10
2.2E-10
1.7E-10
2.0E-10
2.2E-10
2.4E-10
2.4E-10
2.4E-10
2.7E-10
Dung Cake
6.6E-09
6.6E-09
6.6E-09
3.5E-09
6.6E-09
3.5E-09
3.5E-09
3.5E-09
6.6E-09
TOTAL
7.6E-07
8.2E-07
1.0E-06
1.0E-06
8.3E-07
6.5E-07
1.2E-06
6.2E-07
6.2E-07
Table B-30. Detailed Results for Black Carbon & Short-Lived Climate Pollutants by
Baseline and Potential Scenarios in India
Black Carbon & Co emitted Species (kg BC eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG in
Urban
Increase in
LPG/
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease
in Biomass
& Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Biogas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Hard Coal
0.074
0.074
0.074
0.074
0.074
0.074
0.074
0.074
0.074
LPG from NG
2.9E-05
4.1E-05
5.3E-05
5.3E-05
2.9E-05
2.9E-05
2.9E-05
2.9E-05
2.9E-05
LPG from Oil
0.0028
0.0039
0.0050
0.0050
0.0028
0.0028
0.0028
0.0028
0.0028
Kerosene
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
Electricity
-0.0020
-7.6E-05
-7.6E-05
-7.6E-05
-0.0020
-7.6E-05
-7.6E-05
-7.6E-05
-7.6E-05
Sugarcane Ethanol
0
0
0
0
0
0
-5.4E-04
0
0
Biogas from Cattle
Dung
2.7E-05
2.7E-05
2.7E-05
2.7E-05
2.7E-05
2.7E-05
2.7E-05
7.1E-04
2.7E-05
Charcoal from
Wood
0.017
0.017
0.017
0.017
0.017
0.017
0.017
0.017
0.017
Biomass Pellets
0
0
0
0
0
0.0020
0
0
0
Firewood
0.42
0.42
0.34
0.38
0.42
0.47
0.47
0.47
0.51
Crop Residue
0.17
0.17
0.14
0.16
0.17
0.19
0.19
0.19
0.22
B-17
-------
Appendix B - Detailed LCA Results Tables
Table B-30. Detailed Results for Black Carbon & Short-Lived Climate Pollutants by
Baseline and Potential Scenarios in India
Black Carbon & Co emitted Species (kg BC eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
of
Electrical
Use in
Urban
Increase
of LPG in
Urban
Increase in
LPG /
Decrease in
Biomass in
both Urban
and Rural
Increase in
LPG/
Decrease
in Biomass
& Dung in
Rural
Cleaner
Electrical
Grid with
Increase in
Urban
Increased
Biomass
Pellets/
Decreased
Biomass &
Dung
Increased
Ethanol/
Decreased
Biomass &
Dung
Increased
Bio gas/
Decreased
Biomass &
Dung
Current
Cookstove
Fuel Use
Dung Cake
0.53
0.53
0.53
0.28
0.53
0.28
0.28
0.28
0.53
TOTAL
1.22
1.23
1.10
0.91
1.22
1.04
1.04
1.04
1.35
Detailed LCA Results for China by Baseline and Potential Scenarios
This section offers the detailed results tables by baseline and potential scenarios of the
selected LCI and LCIA categories for the individual cooking fuels used within China
(Table B-31 through
Table B-40). Refer to Section 4.2, Results for China by Baseline and Potential Scenarios,
of the report for discussion and a visual of each table in this section.
Table B-31. Detailed Results for Global Climate Change Potential by Baseline and
Potential Scenarios in China
Global Climate Change Potential (kg CO: eq)/GJ Heat Delivered for Cooking
Increase
Electric
LPG
LPG
Increase
Increase
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Fuels:
Replaces
Coal
Replaces
Biomass
Clean
Electric
Biomass
Pellets
Current
Coal Mix
90.3
90.3
293
90.3
192
192
293
293
293
Coal Powder
57.4
57.4
186
57.4
122
122
93.1
186
186
Coal Briquettes
17.4
17.4
56.7
17.4
37.1
37.1
85.0
56.7
56.7
Honeycomb Coal
Briquettes
15.5
15.5
50.2
15.5
32.8
32.8
75.3
50.2
50.2
Biomass Mix
48.0
48.0
12.0
48.0
30.0
30.0
48.0
29.7
48.0
Fuel & Brush Wood
41.4
41.4
10.4
41.4
25.9
25.9
41.4
18.8
41.4
Ag Residues
6.54
6.54
1.64
6.54
4.09
4.09
6.54
11.0
6.54
LPG
58.4
96.0
96.0
58.4
58.4
58.4
58.4
58.4
58.4
Kerosene
0.62
0.62
0.62
0.62
0.62
0.62
0.62
0.62
0.62
Electricity
152
52.6
52.6
118
52.6
52.6
52.6
52.6
52.6
Natural Gas
5.12
5.12
5.12
5.12
5.12
5.12
5.12
5.12
5.12
Biomass Pellets
0
0
0
0
23.7
0
0
0
0
DME
0
0
0
0
0
69.1
0
0
0
TOTAL
354
293
459
320
362
408
418
440
458
B-18
-------
Appendix B - Detailed LCA Results Tables
Table B-32. Detailed Results for Cumulative Energy Demand by Baseline and Potential
Scenarios in China
Cumulative Energy Demand (MJ)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
935
935
3,036
935
1,986
1,986
3,036
3,036
3,036
Coal Powder
568
568
1,844
568
1,206
1,206
922
1,844
1,844
Coal Briquettes
199
199
645
199
422
422
968
645
645
Honeycomb Coal
Briquettes
168
168
546
168
357
357
820
546
546
Biomass Mix
1,909
1,909
479
1,909
1,194
1,194
1,909
2,019
1,909
Fuel & Brash Wood
964
964
242
964
603
603
964
436
964
Ag Residues
946
946
237
946
591
591
946
1,583
946
LPG
866
1,423
1,423
866
866
866
866
866
866
Kerosene
8.83
8.83
8.83
8.83
8.83
8.83
8.83
8.83
8.83
Electricity
1,854
642
642
1,510
642
642
642
642
642
Natural Gas
49.2
49.2
49.2
49.2
49.2
49.2
49.2
49.2
49.2
Biomass Pellets
0
0
0
0
474
0
0
0
0
DME
0
0
0
0
0
1,279
0
0
0
TOTAL
5,623
4,967
5,638
5,278
5,220
6,025
6,185
6,622
6,512
Table B-33. Detailed Results for Fossil Depletion by Baseline and Potential Scenarios in
China
Fossil Depletion (kg oil eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
16.0
16.0
51.8
16.0
33.9
33.9
51.8
51.8
51.8
Coal Powder
9.48
9.48
30.8
9.48
20.1
20.1
15.4
30.8
30.8
Coal Briquettes
3.51
3.51
11.4
3.51
7.46
7.46
17.1
11.4
11.4
Honeycomb Coal
Briquettes
2.97
2.97
9.65
2.97
6.31
6.31
14.5
9.65
9.65
Biomass Mix
0.0022
0.0022
5.5E-04
0.0022
0.0014
0.0014
0.0022
0.0032
0.0022
Fuel & Brash Wood
3.6E-04
3.6E-04
9.1E-05
3.6E-04
2.3E-04
2.3E-04
3.6E-04
1.6E-04
3.6E-04
Ag Residues
0.0018
0.0018
4.6E-04
0.0018
0.0012
0.0012
0.0018
0.0031
0.0018
LPG
20.0
32.9
32.9
20.0
20.0
20.0
20.0
20.0
20.0
Kerosene
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
Electricity
29.2
10.1
10.1
24.1
10.1
10.1
10.1
10.1
10.1
Natural Gas
1.17
1.17
1.17
1.17
1.17
1.17
1.17
1.17
1.17
Biomass Pellets
0
0
0
0
1.62
0
0
0
0
DME
0
0
0
0
0
22.2
0
0
0
TOTAL
66.6
60.4
96.2
61.5
67.1
87.6
78.5
83.4
83.4
B-19
-------
Appendix B - Detailed LCA Results Tables
Table B-34. Detailed Results for Water Depletion by Baseline and Potential Scenarios in
China
Water Depletion (m3)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
3.96
3.96
12.9
3.96
8.42
8.42
12.9
12.9
12.9
Coal Powder
0.85
0.85
2.76
0.85
1.80
1.80
1.38
2.76
2.76
Coal Briquettes
1.70
1.70
5.51
1.70
3.61
3.61
8.27
5.51
5.51
Honeycomb Coal
Briquettes
1.42
1.42
4.60
1.42
3.01
3.01
6.90
4.60
4.60
Biomass Mix
0.017
0.017
0.0042
0.017
0.011
0.011
0.017
0.025
0.017
Fuel & Brash Wood
0.0028
0.0028
7.0E-04
0.0028
0.0017
0.0017
0.0028
0.0013
0.0028
Ag Residues
0.014
0.014
0.0035
0.014
0.0088
0.0088
0.014
0.024
0.014
LPG
17.7
29.2
29.2
17.7
17.7
17.7
17.7
17.7
17.7
Kerosene
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.22
0.22
Electricity
160
55.6
55.6
158
55.6
55.6
55.6
55.6
55.6
Natural Gas
0.14
0.14
0.14
0.14
0.14
0.14
0.14
0.14
0.14
Biomass Pellets
0
0
0
0
9.84
0
0
0
0
DME
0
0
0
0
0
5.50
0
0
0
TOTAL
183
89.1
98.0
180
92.0
87.6
90.3
86.6
86.6
Table B-35. Detailed Results for Particulate Matter Formation by Baseline and Potential
Scenarios in China
Particulate Matter Formation (kg PM10 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
0.16
0.16
0.52
0.16
0.34
0.34
0.52
0.52
0.52
Coal Powder
0.13
0.13
0.43
0.13
0.28
0.28
0.21
0.43
0.43
Coal Briquettes
0.015
0.015
0.049
0.015
0.032
0.032
0.074
0.049
0.049
Honeycomb Coal
Briquettes
0.014
0.014
0.046
0.014
0.030
0.030
0.068
0.046
0.046
Biomass Mix
0.63
0.63
0.16
0.63
0.39
0.39
0.63
0.78
0.63
Fuel & Brash Wood
0.22
0.22
0.055
0.22
0.14
0.14
0.22
0.10
0.22
Ag Residues
0.41
0.41
0.10
0.41
0.25
0.25
0.41
0.68
0.41
LPG
0.062
0.10
0.10
0.062
0.062
0.062
0.062
0.062
0.062
Kerosene
7.0E-04
7.0E-04
7.0E-04
7.0E-04
7.0E-04
7.0E-04
7.0E-04
7.0E-04
7.0E-04
Electricity
0.41
0.14
0.14
0.31
0.14
0.14
0.14
0.14
0.14
Natural Gas
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
0.0014
Biomass Pellets
0
0
0
0
0.043
0
0
0
0
DME
0
0
0
0
0
0.15
0
0
0
TOTAL
1.26
1.03
0.92
1.16
0.98
1.09
1.19
1.51
1.35
B-20
-------
Appendix B - Detailed LCA Results Tables
Table B-36. Detailed Results for Photochemical Oxidant Formation by Baseline and
Potential Scenarios in China
Photochemical Oxidant Formation (kg NMVOC eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
0.21
0.21
0.67
0.21
0.44
0.44
0.67
0.67
0.67
Coal Powder
0.15
0.15
0.48
0.15
0.31
0.31
0.24
0.48
0.48
Coal Briquettes
0.027
0.027
0.087
0.027
0.057
0.057
0.13
0.087
0.087
Honeycomb Coal
Briquettes
0.033
0.033
0.11
0.033
0.071
0.071
0.16
0.11
0.11
Biomass Mix
0.57
0.57
0.14
0.57
0.35
0.35
0.57
0.62
0.57
Fuel & Brash Wood
0.27
0.27
0.067
0.27
0.17
0.17
0.27
0.12
0.27
Ag Residues
0.30
0.30
0.076
0.30
0.19
0.19
0.30
0.50
0.30
LPG
0.12
0.20
0.20
0.12
0.12
0.12
0.12
0.12
0.12
Kerosene
0.0013
0.0013
0.0013
0.0013
0.0013
0.0013
0.0013
0.0013
0.0013
Electricity
0.57
0.20
0.20
0.44
0.20
0.20
0.20
0.20
0.20
Natural Gas
0.0054
0.0054
0.0054
0.0054
0.0054
0.0054
0.0054
0.0054
0.0054
Biomass Pellets
0
0
0
0
0.052
0
0
0
0
DME
0
0
0
0
0
0.40
0
0
0
TOTAL
1.48
1.18
1.23
1.35
1.18
1.53
1.43
1.63
1.57
Table B-37. Detailed Results for Freshwater Eutrophication by Baseline and Potential
Scenarios in China
Freshwater Eutrophication (kg P eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
0.0098
0.0098
0.032
0.0098
0.021
0.021
0.032
0.032
0.032
Coal Powder
0.0061
0.0061
0.020
0.0061
0.013
0.013
0.0099
0.020
0.020
Coal Briquettes
0.0020
0.0020
0.0065
0.0020
0.0042
0.0042
0.0097
0.0065
0.0065
Honeycomb Coal
Briquettes
0.0017
0.0017
0.0055
0.0017
0.0036
0.0036
0.0082
0.0055
0.0055
Biomass Mix
0.054
0.054
0.014
0.054
0.034
0.034
0.054
0.080
0.054
Fuel & Brash Wood
0.0089
0.0089
0.0022
0.0089
0.0056
0.0056
0.0089
0.0040
0.0089
Ag Residues
0.045
0.045
0.011
0.045
0.028
0.028
0.045
0.076
0.045
LPG
0.0025
0.0041
0.0041
0.0025
0.0025
0.0025
0.0025
0.0025
0.0025
Kerosene
3.1E-05
3.1E-05
3.1E-05
3.1E-05
3.1E-05
3.1E-05
3.1E-05
3.1E-05
3.1E-05
Electricity
0.019
0.0067
0.0067
0.014
0.0067
0.0067
0.0067
0.0067
0.0067
Natural Gas
1.6E-05
1.6E-05
1.6E-05
1.6E-05
1.6E-05
1.6E-05
1.6E-05
1.6E-05
1.6E-05
Biomass Pellets
0
0
0
0
0.0040
0
0
0
0
DME
0
0
0
0
0
0.013
0
0
0
TOTAL
0.086
0.075
0.056
0.081
0.068
0.077
0.091
0.12
0.095
B-21
-------
Appendix B - Detailed LCA Results Tables
Table B-38. Detailed Results for Terrestrial Acidification by Baseline and Potential
Scenarios in China
Terrestrial Acidification (kg SO2 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
0.33
0.33
1.08
0.33
0.70
0.70
1.08
1.08
1.08
Coal Powder
0.26
0.26
0.86
0.26
0.56
0.56
0.43
0.86
0.86
Coal Briquettes
0.036
0.036
0.12
0.036
0.076
0.076
0.17
0.12
0.12
Honeycomb Coal
Briquettes
0.032
0.032
0.10
0.032
0.067
0.067
0.15
0.10
0.10
Biomass Mix
0.079
0.079
0.020
0.079
0.049
0.049
0.079
0.080
0.079
Fuel & Brash Wood
0.043
0.043
0.011
0.043
0.027
0.027
0.043
0.019
0.043
Ag Residues
0.036
0.036
0.0090
0.036
0.023
0.023
0.036
0.060
0.036
LPG
0.21
0.35
0.35
0.21
0.21
0.21
0.21
0.21
0.21
Kerosene
0.0026
0.0026
0.0026
0.0026
0.0026
0.0026
0.0026
0.0026
0.0026
Electricity
1.31
0.45
0.45
0.99
0.45
0.45
0.45
0.45
0.45
Natural Gas
0.0041
0.0041
0.0041
0.0041
0.0041
0.0041
0.0041
0.0041
0.0041
Biomass Pellets
0
0
0
0
0.078
0
0
0
0
DME
0
0
0
0
0
0.24
0
0
0
TOTAL
1.94
1.22
1.90
1.61
1.50
1.66
1.51
1.83
1.83
Table B-39. Detailed Results for Ozone Depletion by Baseline and Potential Scenarios in
China
Ozone Depletion (kg CFC 11 eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
5.7E-07
5.7E-07
1.8E-06
5.7E-07
1.2E-06
1.2E-06
1.8E-06
1.8E-06
1.8E-06
Coal Powder
3.7E-08
3.7E-08
1.2E-07
3.7E-08
7.9E-08
7.9E-08
6.0E-08
1.2E-07
1.2E-07
Coal Briquettes
2.9E-07
2.9E-07
9.3E-07
2.9E-07
6.1E-07
6.1E-07
1.4E-06
9.3E-07
9.3E-07
Honeycomb Coal
Briquettes
2.4E-07
2.4E-07
7.9E-07
2.4E-07
5.1E-07
5.1E-07
1.2E-06
7.9E-07
7.9E-07
Biomass Mix
8.9E-10
8.9E-10
2.2E-10
8.9E-10
5.5E-10
5.5E-10
8.9E-10
1.3E-09
8.9E-10
Fuel & Brash Wood
1.5E-10
1.5E-10
3.6E-11
1.5E-10
9.1E-11
9.1E-11
1.5E-10
6.6E-11
1.5E-10
Ag Residues
7.4E-10
7.4E-10
1.9E-10
7.4E-10
4.6E-10
4.6E-10
7.4E-10
1.2E-09
7.4E-10
LPG
9.2E-06
1.5E-05
1.5E-05
9.2E-06
9.2E-06
9.2E-06
9.2E-06
9.2E-06
9.2E-06
Kerosene
1.1E-07
1.1E-07
1.1E-07
1.1E-07
1.1E-07
1.1E-07
1.1E-07
1.1E-07
1.1E-07
Electricity
7.0E-07
2.4E-07
2.4E-07
2.1E-06
2.4E-07
2.4E-07
2.4E-07
2.4E-07
2.4E-07
Natural Gas
8.2E-07
8.2E-07
8.2E-07
8.2E-07
8.2E-07
8.2E-07
8.2E-07
8.2E-07
8.2E-07
Biomass Pellets
0
0
0
0
4.7E-08
0
0
0
0
DME
0
0
0
0
0
4.5E-06
0
0
0
TOTAL
1.1E-05
1.7E-05
1.8E-05
1.3E-05
1.2E-05
1.6E-05
1.3E-05
1.2E-05
1.2E-05
B-22
-------
Appendix B - Detailed LCA Results Tables
Table B-40. Detailed Results for Black Carbon & Short-Lived Climate Pollutants by
Baseline and Potential Scenarios in China
Black Carbon (kg BC eq)/GJ Heat Delivered for Cooking
Fuels:
Increase
Electric
LPG
Replaces
Coal
LPG
Replaces
Biomass
Increase
Clean
Electric
Increase
Biomass
Pellets
Increase
DME
Coal
Swap
Ag
Residue
Replace
Wood
Current
Coal Mix
0.0039
0.0039
0.013
0.0039
0.0082
0.0082
0.013
0.013
0.013
Coal Powder
0.0018
0.0018
0.0060
0.0018
0.0039
0.0039
0.0030
0.0060
0.0060
Coal Briquettes
0.0010
0.0010
0.0034
0.0010
0.0022
0.0022
0.0050
0.0034
0.0034
Honeycomb Coal
Briquettes
9.7E-04
9.7E-04
0.0032
9.7E-04
0.0021
0.0021
0.0047
0.0032
0.0032
Biomass Mix
0.13
0.13
0.032
0.13
0.079
0.079
0.13
0.13
0.13
Fuel & Brash Wood
0.044
0.044
0.011
0.044
0.027
0.027
0.044
0.020
0.044
Ag Residues
0.083
0.083
0.021
0.083
0.052
0.052
0.083
0.14
0.083
LPG
-0.0055
-0.0091
-0.0091
-0.0055
-0.0055
-0.0055
-0.0055
-0.0055
-0.0055
Kerosene
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
-9.6E-05
Electricity
-0.037
-0.013
-0.013
-0.028
-0.013
-0.013
-0.013
-0.013
-0.013
Natural Gas
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
-5.2E-05
Biomass Pellets
0
0
0
0
0.0021
0
0
0
0
DME
0
0
0
0
0
0.011
0
0
0
TOTAL
0.088
0.11
0.022
0.097
0.071
0.080
0.12
0.15
0.12
B-23
------- |