United States
Environmental Protection
Agency
Global Anthropogenic Non-002
Greenhouse Gas Emissions: 1990-2020
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How to Obtain Copies
You may electronically download this document from the U.S. EPA's webpage at
http ://www. epa. gov/nonco2/econ-inv/international .html.
To obtain additional copies of this report, call 1-800-490-9198.
How to Obtain the Data
You may electronically download the data compiled for this report in .xls format from the
U.S. EPA's webpage at:
http ://www. epa. gov/nonco2/econ-inv/international .html.
For Further Information:
Contact Elizabeth Scheehle, Climate Change Division,
Office of Atmospheric Programs, U.S. Environmental Protection Agency,
202-343-9758; scheehle.elizabeth@,epa.gov.
Peer Reviewed Document
This report has undergone an external peer review consistent with the guidelines of the
U.S. EPA Peer Review Policy. Comments were received from experts in the private
sector, academia, non-governmental organizations, and other government agencies. See
the Acknowledgments section for a list of reviewers. A copy of the EPA Peer Review
guidelines may be downloaded from the following web page at
http://epa.gov/osa/spc/2peerrev.htm.
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Global Anthropogenic Non-CO2
Greenhouse Gas Emissions: 1990 - 2020
June 2006 Revised
Office of Atmospheric Programs
Climate Change Division
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, NW
Washington, DC 20460
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Acknowledgments
Elizabeth Scheehle edited and directed the completion of the report. EPA's Lead Authors include:
Elizabeth Scheehle (Energy, Waste, & Agriculture), Dave Godwin (Ozone-Depleting Substitutes), and
Deborah Ottinger (Industrial Fluorinated Gases). We thank EPA reviewers: Francisco de la Chesnaye,
Dina Kruger, Brian Guzzone, Steve Rose, Clark Talkington, Roger Fernandez, Benjamin DeAngelo, and
Tom Wirth.
The staff at ERG assisted in compiling and finalizing the report. The staff at ICF Consulting and RTI
prepared many of the individual analyses. Special Recognition goes to Stephanie Finn at ERG and
Marian Van Pelt at ICF Consulting.
Special thanks to Jochen Harnisch and Sina Wartman of Ecofys for their valuable help in integrating the
results of their 2005 study, "Reductions of SF6 Emissions from High and Medium Voltage Electrical
Equipment: Final Report to CAPIEL."
We also thank external reviewers: Paul Ashford (Caleb Group), Ward Atkinson (SAE, retired), Dave
Bateman (DuPont Fluoroproducts), Donald Bivens (DuPont Fluoroproducts), Nick Campbell (Arkema),
Jim Crawford (The Trane Company), David F. Crawley (Eurelectric), Hugh Crowther (McQuay
International), William Dietrich (York), Tony Digmanese (York), Chuck Fraust (SIA), Maureen Hardwick
(International Pharmaceutical Aerosol Consortium), Jochen Harnisch (Ecofys), Susan Herrenbruck
(Extruded Polystyrene Foam Association), Kenneth Hickman (York, retired), William Hill (General Motors),
Jerry Marks (Jerry Marks & Associates), Enrique Otegui Martinez (Capiel), Archie McCulloch (Marbury
Technical Consulting and University of Bristol, UK), Abid Merchant (DuPont), John Mutton (The Dow
Chemical Company), Jos Olivier (RIVM), John Owens (3M), Friedrich Plb'ger (Siemens), J. Patrick Rynd
(Owens Corning), Winfried Schwarz (Oekorecherche), Eugene Smithart (Danfoss Turbocor), Silvio
Stangherlin (CIGRE; ABB Switzerland Ltd), Tom Tripp (US Magnesium), Dan Verdonik (Hughes
Associates, Inc.), William Walter (Carrier Corporation), Kert Werner (3M), Robert Wickham (Wickham
Associates), and Takeshi Yokota (Toshiba; CIGRE). Although these individuals participated in the review
of this analysis, their efforts do not constitute an endorsement of the report's results or of any U.S. EPA
policies and programs.
June 2006 Revised Table of Contents Page ii
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Acronyms
AAMA - American Automobile Manufacturer's Association
AE - anode effects
AFEAS -Alternative Fluorocarbons Environmental Acceptability Study
ALGAS - Asia Least-Cost Greenhouse Gas Abatement Strategy
BAD - business as usual
BOD - biological oxygen demand
COM - Clean Development Mechanism
CEIT - countries with economies in transition
CFC - chlorofluorocarbon
CF4 - perfluoromethane
C2F6 - hexafluoroethane
C3F8 - perfluoropropane
c-C4F8 - perfluorocyclobutane
CH4 - methane
CO2 - carbon dioxide
CPA - Centrally Planned Asia
CRF - Common Reporting Format
CRW - combustible renewables and waste
CWPB - Center-Worked Prebake
DOC - degradable organic carbon
EDGAR - Emission Database for Global Atmospheric Research
EF - emission factor
EIA - Energy Information Administration
EPA- U.S. Environmental Protection Agency
EU - European Union
FAO - Food and Agriculture Organization
FSU - Former Soviet Union
FIAM - Foundry Impact Analysis Model
FWHA - U.S. Federal Highway Administration
GHG - greenhouse gas
Gg - gigagram
GTAP - Global Trade Analysis Project
GWP - global warming potential
HCFC - hydrochlorofluorocarbon
HCFC-22 - chlorodifluoromethane
HFC-23 - triflouromethane
MFCs - hydrofluorocarbons
HSS - Horizontal Stud Soderberg
IAI - International Aluminum Institute
IEA - International Energy Agency
IFPRI - International Food Policy Research Institute
IRRI - International Rice Research Institute
IMA - International Magnesium Association
IPCC - Intergovernmental Panel on Climate Change
Kg - kilogram
MCF - methane correction factor
MDI - metered dose inhalers
MtCO2Eq - million metric tons of carbon dioxide equivalent
MSW- municipal solid waste
mt - metric ton
MVAC - motor vehicle air conditioner
N - nitrogen
NIR - National Inventory Report
N2O - nitrous oxide
NF3- nitrogen trifluoride
OOP - ozone-depleting potential
ODS - ozone-depleting substance
June 2006 Revised Table of Contents Page Mi
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OECD - The Organization for Economic Cooperation and Development
PFBB - Point Feed Prebake
PFC - perfluorocarbons
PEVM - PFC Emissions Vintage Model
SAR - Second Assessment Report
SF6 - sulfur hexafluoride
SO2-sulfur dioxide
SRES - Special Report on Emissions Scenarios
SWPB - Side-Worked Prebake
SWDS - solid waste disposal site
TAR - Third Assessment Report
Tg -terag ram
Tj -terajoule
UNFCCC - United Nations Framework Convention on Climate Change
UNDP - United Nations Development Programme
VSS - Vertical Stud Soderberg
WEC - World Energy Council
WEO - World Energy Outlook
WFW-World Fab Watch
WSC - World Semiconductor Council
VAIP-Voluntary Aluminum Industrial Partnership
June 2006 Revised Table of Contents Pageiv
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TABLE OF CONTENTS
Global Anthropogenic Non-CO2 Greenhouse Gas Emissions: 1990-2020
Section Page
1 Introduction/Overview 1-1
1.1 Introduction 1-1
1.2 Overview of Non-CO2 Greenhouse Gas Emissions 1-1
1.3 Emission Sources 1-2
1.4 Approach 1-2
1.5 Limitations 1-7
1.6 Organization of This Report 1-8
2 Summary Results 2-1
2.1 Summary Estimates 2-1
2.2 Trends by Region 2-2
2.3 Trends by Gas and Source Category 2-4
2.4 Other Global Datasets 2-5
3 Energy 3-1
3.1 Introduction 3-1
3.2 Natural Gas and Oil Systems (Methane) 3-2
3.2.1 Source Description 3-2
3.2.2 Source Results 3-2
3.3 Coal Mining Activities (Methane) 3-4
3.3.1 Source Description 3-4
3.3.2 Source Results 3-4
3.4 Stationary and Mobile Combustion (Nitrous Oxide and Methane) 3-6
3.4.1 Source Description 3-6
3.4.2 Source Results 3-6
3.5 Biomass Combustion (Methane and Nitrous Oxide) 3-9
3.5.1 Source Description 3-9
3.5.2 Source Results 3-9
4 Industry 4-1
4.1 Introduction 4-1
4.1.1 Trends in Emissions from Industrial Sources 4-1
4.1.2 The Technology-Adoption and No-Action Baselines 4-2
4.1.3 Global Warming Potentials for High GWP Gases 4-3
4.2 Production of Adipic Acid and Nitric Acid (Nitrous Oxide) 4-5
4.2.1 Source Description 4-5
4.2.2 Source Results 4-5
4.3 Use of Substitutes for Ozone Depleting Substances 4-7
4.3.1 Source Description 4-7
4.3.2 Source Results 4-7
4.4 Production of HCFC-22 (Hydrofluorocarbons) 4-9
4.4.1 Source Description 4-9
4.4.2 Source Results 4-9
4.5 Operation of Electric Power Systems (Sulfur Hexafluoride) 4-13
4.5.1 Source Description 4-13
4.5.2 Source Results 4-13
4.6 Primary Aluminum Production (Perfluorocarbons) 4-15
4.6.1 Source Description 4-15
4.6.2 Source Results 4-16
4.7 Manufacture of Semiconductors (Hydrofluorocarbons, Perfluorocarbons, Sulfur
Hexafluoride) 4-18
June 2006 Revised Table of Contents Page v
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4.7.1 Source Description 4-18
4.7.2 Source Results 4-19
4.8 Magnesium Manufacturing (Sulfur Hexafluoride) 4-21
4.8.1 Source Description 4-21
4.8.2 Source Results 4-22
4.9 Other Non-Agricultural Sources (Methane and Nitrous Oxide) 4-24
4.9.1 Source Description 4-24
4.9.2 Source Results 4-24
5 Agriculture 5-1
5.1 Introduction 5-1
5.2 Agricultural Soils (Nitrous Oxide) 5-2
5.2.1 Source Description 5-2
5.2.2 Source Results 5-3
5.3 Enteric Fermentation (Methane) 5-4
5.3.1 Source Description 5-4
5.3.2 Source Results 5-5
5.4 Rice Cultivation (Methane) 5-6
5.4.1 Source Description 5-6
5.4.2 Source Results 5-6
5.5 Manure Management (Methane and Nitrous Oxide) 5-7
5.5.1 Source Description 5-7
5.5.2 Source Results 5-8
5.6 Other Agricultural Sources (Methane and Nitrous Oxide) 5-10
5.6.1 Source Description 5-10
5.6.2 Source Results 5-11
6 Waste 6-1
6.1 Introduction 6-1
6.2 Landfilling of Solid Waste (Methane) 6-2
6.2.1 Source Description 6-2
6.2.2 Source Results 6-2
6.3 Wastewater (Methane) 6-3
6.3.1 Source Description 6-3
6.3.2 Source Results 6-4
6.4 Human Sewage - Domestic Wastewater (Nitrous Oxide) 6-5
6.4.1 Source Description 6-5
6.4.2 Source Results 6-6
6.5 Other Non-Agricultural Sources (Methane and Nitrous Oxide) 6-7
6.5.1 Source Description 6-7
6.5.2 Source Results 6-7
7 Methodologies Used to Compile and Estimate Historical and Projected Emissions 7-1
Overview 7-1
7.1 Data Sources for Historical and Projected Emissions 7-1
7.1.1 Methane and Nitrous Oxide 7-1
7.1.2 High Global Warming Potential Gas Emissions 7-3
7.2 Specific Methodologies for Methane and Nitrous Oxide Sources 7-3
7.2.1 Methane Emissions from Natural Gas and Oil Systems 7-3
7.2.2 Methane from Coal Mining Activities 7-5
7.2.3 Nitrous Oxide and Methane Emissions from Stationary and Mobile
Combustion 7-7
7.2.4 Methane and Nitrous Oxide Emissions from Biomass Combustion 7-10
7.2.5 Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production 7-11
7.2.6 Nitrous Oxide Emissions from Agricultural Soils 7-13
7.2.7 Methane Emissions from Enteric Fermentation 7-14
7.2.8 Methane Emissions from Rice Cultivation 7-15
7.2.9 Methane and Nitrous Oxide Emissions from Manure Management 7-18
7.2.10 Methane and Nitrous Oxide Emissions from Other Agricultural Sources 7-20
June 2006 Revised Table of Contents Pagevi
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7.2.11 Methane Emissions from Landfilling of Solid Waste 7-20
7.2.12 Methane Emissions from Wastewater 7-22
7.2.13 Nitrous Oxide from Human Sewage 7-22
7.2.14 Other Non-Agricultural Sources 7-23
7.3 Estimation and Projection Approaches Used for High Global Warming
Potential Gases 7-23
7.3.1 The Technology-Adoption and No-Action Baselines 7-23
7.3.2 HFC and PFC Emissions from the Use of Substitutes for ODS 7-25
7.3.3 HFC-23 Emissions as a Byproduct of HCFC-22 Production 7-33
7.3.4 Sulfur Hexafluoride (SF6) Emissions from Electric Power Systems 7-37
7.3.5 Perfluorocarbon (PFC) Emissions from Primary Aluminum Production 7-42
7.3.6 Emissions from Semiconductor Manufacturing 7-46
7.3.7 Sulfur Hexafluoride (SF0) Emissions from Magnesium Production 7-50
References 8-1
June 2006 Revised Table of Contents Pagevii
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Appendices
A-1 Combined Methane, Nitrous Oxide, and High GWP Emissions by Country (MtCO2eq)
A-2 Methane Emissions by Country (MtCO2eq)
A-3 Nitrous Oxide Emissions by Country (MtCO2eq)
A-4 High GWP Emissions by Country (MtCO2eq)
B-1 Methane Emissions from Fugitives from Natural Gas and Oil Systems
B-2 Methane Emissions from Fugitives from Coal Mining Activities
B-3 Methane Emissions from Stationary and Mobile Combustion
B-4 Methane Emissions from Biomass Combustion
B-5 Methane Emissions from Other Industrial Non-Agricultural Sources
B-6 Methane Emissions from Enteric Fermentation
B-7 Methane Emissions from Rice Cultivation
B-8 Methane Emissions from Manure Management
B-9 Methane Emissions from Other Agricultural Sources
B-10 Methane Emissions from Landfilling of Solid Waste
B-11 Methane Emissions from Wastewater
B-12 Methane Emissions from Other Non-Agricultural Sources (Waste and Other)
C-1 Nitrous Oxide Emissions from Stationary and Mobile Combustion
C-2 Nitrous Oxide Emissions from Biomass Combustion
C-3 Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
C-4 Nitrous Oxide Emissions from Other Industrial Non-Agricultural Sources
C-5 Nitrous Oxide Emissions from Agricultural Soils
C-6 Nitrous Oxide Emissions from Manure Management
C-7 Nitrous Oxide Emissions from Other Agricultural Sources
C-8 Nitrous Oxide Emissions from Human Sewage
C-9 Nitrous Oxide Emissions from Other Non-Agricultural Sources (Waste and Other)
D-1 HFC and PFC Emissions from ODS Substitutes - Aerosols (MDI)
D-2 HFC and PFC Emissions from ODS Substitutes - Aerosols (non-MDI)
D-3 HFC and PFC Emissions from ODS Substitutes - Fire Extinguishing
D-4 HFC and PFC Emissions from ODS Substitutes - Foams
D-5 HFC and PFC Emissions from ODS Substitutes - Refrigeration/Air Conditioning
D-6 HFC and PFC Emissions from ODS Substitutes - Solvents
D-7 HFC-23 Emissions from HCFC-22 Production (Technology-Adoption)
D-7b HFC-23 Emissions from HCFC-22 Production (No-Action)
D-8 SF6 Emissions from Electric Power Systems (Technology-Adoption)
D-8b SF6 Emissions from Electric Power Systems (No-Action)
D-9 PFC Emissions from Primary Aluminum Production (Technology-Adoption)
D-9b PFC Emissions from Primary Aluminum Production (No-Action)
D-10 HFC, PFC, and SF6 Emissions from Semiconductor Manufacturing (Technology-Adoption)
D-1 Ob HFC, PFC, and SF6 Emissions from Semiconductor Manufacturing (No-Action)
D-11 SF6 Emissions from Magnesium Manufacturing (Technology-Adoption)
D-11 b SF6 Emissions from Magnesium Manufacturing (No-Action)
E-1 Data Sources and Methodologies for Methane Emissions from Fugitives from Natural Gas and Oil
Systems
E-2 Data Sources and Methodologies for Methane Emissions from Fugitives from Coal Mining
Activities
E-3 Data Sources and Methodologies for Methane and Nitrous Oxide Emissions from Stationary and
Mobile Combustion
E-4 Data Sources and Methodologies for Methane and Nitrous Oxide Emissions from Biomass
Combustion
E-5 Data Sources and Methodologies for Nitrous Oxide Emissions from Adipic Acid and Nitric Acid
Production
E-6 Data Sources and Methodologies for Nitrous Oxide Emissions from Agricultural Soils
June 2006 Revised Table of Contents Page viii
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E-7 Data Sources and Methodologies for Methane Emissions from Enteric Fermentation
E-8 Data Sources and Methodologies for Methane Emissions from Rice Cultivation
E-9 Data Sources and Methodologies for Methane Emissions from Manure Management
E-9b Data Sources and Methodologies for Nitrous Oxide Emissions from Manure Management
E-10 Data Sources and Methodologies for Methane Emissions from Landfilling of Solid Waste
E-11 Data Sources and Methodologies for Methane Emissions from Wastewater
E-12 Data Sources and Methodologies for Nitrous Oxide Emissions from Human Sewage
F Methodology and Adjustments to Approaches Used to Estimate Nitrous Oxide Emissions from
Agricultural Soils
G U.S. EPA Vintaging Model Framework
H Regional Definitions
1-1 HCFC-22 Production Activity Data for Selected Countries (Metric Tons)
I-2 Activity Data for Electric Power Systems Net Electricity Consumption by Selected
Countries (Billion Kilowatt-hours)
l-2b Developing Country/Region-Specific Net Electricity Consumption Annual Growth Rates (percent)
I-3 Aluminum Production Activity Data for Selected Countries (Thousand Metric Tons)
I-4 Magnesium Activity Data for Selected Countries (includes primary, secondary, and die
casting production) (Metric Tons)
June 2006 Revised Table of Contents Page ix
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LIST OF TABLES
Table
Table 1-1 Global Warming Potentials 1-3
Table 1-2 Global Greenhouse Gas (GHG) Emissions for 2000 (MtCO2eq) 1-3
Table 1-3 Sources Included 1-4
Table 1-4 Definition of Regional Groupings 1-6
Table 2-1 Percentage Change by Decade and by Region 2-3
Table 2-2 Comparison of EPA Global Database to Other Global Inventories (MtCC^eq) 2-7
Table 3-1 Percentage Change in Methane Emissions from Natural Gas and Oil Systems
Between 1990 and 2020 3-3
Table 3-2 Percentage Change in N2O and CH4 Emissions Between 1990 and 2020 3-9
Table 4-1 High GWP Chemicals - Partial List 4-4
Table 7-1 Sector and Modes 7-8
Table 7-2 Fuel Types Included Under Main Fossil Fuel Categories 7-9
Table 7-3 Global and Regional Emission Reduction Commitments 7-24
Table 7-4 Adjustment Factors Applied in Each Sector/Country 7-28
Table 7-5 Timing Factors Applied to ODS Substitute Emissions 7-28
Table 7-6 Annual Change in GDP Relative to Previous Year (Percent) 7-28
Table 7-7 Projected Regional Annual Growth Rates from 2001-2020 (Percent) 7-29
Table 7-8 Recycling Adjustment Applied to Refrigeration Emissions Estimates 7-30
Table 7-9 Percentage of Newly Manufactured Vehicles Assumed to Have Operational Air
Conditioning Units 7-31
Table 7-10 Cell Type Specific Production Weighted AE Minutes per Cell Day 7-43
Table 7-11 Slope Coefficients by Cell Type (kg PFC/metric ton AI/AE minutes/cell day) 7-43
Table 7-12 Reduction Efficiency of Potential Reduction Opportunities (Percent) 7-44
Table 7-13 Ratios between Reported and FIAM Estimated WSC Emissions and the Resulting
Adjustment Factors 7-48
Table 7-14 Annual Growth Rates for Primary Casting and Recycling Production (Annual Percent
Increase) 7-53
Table 7-15 Historical (1990 and 1995) Emission Factors for Primary Casting and Recycling
Production 7-53
Table 7-16 Current and Projected (2000-2020) Emission Factors for Primary, Casting, and
Recycling Production, No-Action Baseline 7-54
June 2006 Revised
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LIST OF EXHIBITS
Exhibit
Exhibit 1-1 Contribution of Anthropogenic Emissions of Greenhouse Gases to the Enhanced
Greenhouse Effect from Pre-lndustrial to Present (measured in Watts/meter2) 1-2
Exhibit 2-1 Total Global Non-CO2 Emissions by Gas (MtCO2eq) 2-1
Exhibit 2-2 Total Global Non-CO2 Emissions by Region (MtCO2eq) 2-2
Exhibit 2-3 Total Global Non-CO2 Emissions by Region and Group (MtCO2eq) 2-4
Exhibit 2-4 Global Non-CO2 Emissions by Sector and Year (MtCO2eq) 2-5
Exhibit 3-1 Total Emissions from the Energy Sector by Source (MtCO2eq) 3-1
Exhibit 3-2 Methane Emissions from Natural Gas and Oil Systems 1990 - 2020 (MtCO2eq) 3-2
Exhibit 3-3 Methane Emissions from Coal Mining Activities 1990-2020 (MtCO2eq) 3-5
Exhibit 3-4.1 Methane Emissions from Stationary and Mobile Combustion
1990-2020 (MtCO2eq) 3-8
Exhibit 3-4.2 Nitrous Oxide Emissions from Stationary and Mobile Combustion 1990 - 2020
(MtC02eq) 3-8
Exhibit 3-5.1 Methane Emissions from Biomass Combustion 1990-2020 (MtCO2eq) 3-10
Exhibit 3-5.2 Nitrous Oxide Emissions from Biomass Combustion 1990-2020 (MtCO2eq) 3-10
Exhibit 4-1 Emissions from Industrial Processes by Source (MtCO2eq) 4-2
Exhibit 4-2 Technology-Adoption and No-Action Baseline Emissions by Year (MtCO2eq) 4-2
Exhibit 4-3 Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production 1990
- 2020 (MtC02eq) 4-6
Exhibit 4-4 HFC and PFC Emissions from Substitutes for Ozone Depleting Substances
1990-2020 by Region (MtCO2eq) 4-8
Exhibit 4-5 HFC and PFC Emissions from Substitutes for Ozone Depleting Substances
1990-2020 by Sector (MtCO2eq) 4-9
Exhibit 4-6 HFC-23 Emissions as a Byproduct of HCFC-22 Production Based on a No-Action
Baseline 1990-2020 (MtCO2eq) 4-10
Exhibit 4-7 HFC-23 Emissions as a Byproduct of HCFC-22 Production Based on a Technology-
Adoption Baseline 1990 - 2020 (MtCO2eq) 4-12
Exhibit 4-8 SF6 Emissions from Electric Power Systems Based on a Technology-Adoption
Baseline 1990-2020 (MtC02eq) 4-14
Exhibit 4-9 SF6 Emissions from Electric Power Systems Based on a No-Action Baseline
1990-2020 (MtCO2eq) 4-15
Exhibit 4-10 PFC Emissions from Aluminum Production Based on a Technology-Adoption
Baseline 1990-2020 (MtCO2eq) 4-17
Exhibit 4-11 PFC Emissions from Aluminum Production Based on a Non-Action Baseline 1990
Baseline 1990-2020 (MtC02eq) 4-18
Exhibit 4-12 PFC Emissions from Semiconductor Manufacturing Based on a Technology-Adoption
Baseline 1990-2020 (MtC02eq) 4-20
Exhibit 4-13 WSC and non-WSC Countries' Contribution to Global PFC Emissions (MtCO2eq) ..4-20
Exhibit 4-14 PFC Emissions from Semiconductor Manufacturing Based on a No-Action Baseline
1990-2020 (MtCO2eq) 4-21
Exhibit 4-15 SF6 Emissions from Magnesium Manufacturing Based on a Technology-Adoption
Baseline 1990-2020 (MtCO2eq) 4-23
Exhibit 4-16 SF6 Emissions from Magnesium Manufacturing Based on a No-Action Baseline
1990-2020 (MtC02eq) 4-24
June 2006 Revised
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Page xi
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Exhibit 5-1 Total Emissions from the Agricultural Sector by Source (MtCO2eq) 5-2
Exhibit 5-2 Nitrous Oxide Emissions from Agricultural Soils 1990-2020 (MtCO2eq) 5-3
Exhibit 5-3 Methane Emissions from Enteric Fermentation 1990-2020 (MtCC^eq) 5-5
Exhibit 5-4 Methane Emission from Rice Cultivation 1990-2020 (MtCO2eq) 5-7
Exhibit 5-5 Methane Emission from Manure Management 1990- 2020 (MtCO2eq) 5-9
Exhibit 5-6 Nitrous Oxide Emissions from Manure Management 1990-2020 (MtCC^eq) 5-9
Exhibit 5-7.1 Methane Emissions from Other Agricultural Sources 1990-2020 (MtCO2eq) 5-11
Exhibit 5-7.2 Nitrous Oxide Emissions from Other Agricultural Sources 1990 -
2020 (MtCO2eq) 5-12
Exhibit 6-1 Total Emissions from the Waste Sector by Source (MtCO2eq) 6-1
Exhibit 6-2 Methane Emission from Landfilling of Solid Waste 1990-2020 (MtCC^eq) 6-3
Exhibit 6-3 Methane Emission from Wastewater 1990 - 2020 (MtCO2eq) 6-5
Exhibit 6-4 Nitrous Oxide from Human Sewage 1990-2020 (MtCO2eq) 6-6
June 2006 Revised
Table of Contents
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1. Introduction and Overview
1.1 Introduction
The aim of this report is to provide historical and projected estimates of emissions of non-carbon dioxide
(non-CO2) greenhouse gases (GHGs) from anthropogenic sources. The report provides a consistent and
comprehensive estimate of non-CO2 greenhouse gases for over ninety individual countries and eight
regions. The analysis provides information that can be used to understand national contributions of GHG
emissions, historical progress on reductions, and mitigation opportunities. Readers can find the dataset
compiled for this report in spreadsheet (.xls) format on the U.S. EPA's webpage at:
http://www.epa.gov/nonco2/econ-inv/international.html.
The gases included in this report are the direct GHGsother than CO2covered by the United Nations
Framework Convention on Climate Change (UNFCCC): methane (CH4), nitrous oxide (N2O), and the high
global warming potential (high GWP) gases. The high GWP gases include hydrofluorocarbons (MFCs),
perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). Compounds covered by the Montreal Protocol
are not included in this report. Historical estimates are reported for 1990, 1995, and 2000 and projections
of emissions are provided for 2005, 2010, 2015, and 2020. Projections reflect the currently achieved
impact of sector specific climate policy programs, agreements, and measures that are already in place,
but exclude GHG reductions due to additional planned activities whose impacts are less certain.
The U.S. Environmental Protection Agency (EPA) collects emission estimates from publicly available
nationally-prepared GHG reports that are prepared in a manner consistent with the Revised 1996
Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories
(IPCC Guidelines) (IPCC, 1997) and the IPCC Good Practice Guidance and Uncertainty Management in
National Greenhouse Gas Inventories (IPCC Good Practice Guidance) (IPCC, 2000). If national
estimates are not available, EPA estimates emissions in order to produce a complete inventory for the
world. EPA's calculated emissions estimates are prepared in a consistent manner across all countries
using IPCC default methodologies, international statistics for activity data, and the IPCC Tier 1 default
emission factors.
1.2 Overview of Non-CO2 Greenhouse Gas Emissions
As shown in Exhibit 1-1, global emissions of methane, nitrous oxide, and high GWP gases account for
approximately 30 percent of the enhanced greenhouse effect since pre-industrial times (IPCC, 2001).
Emissions of non-CO2 GHGs contribute significantly to radiative forcing1 since they are more effective at
trapping heat than CO2. The IPCC uses the concept of the global warming potential (GWP) to compare
the ability of different gases to trap heat in the atmosphere relative to carbon dioxide. Emissions of non-
CO2 gases are converted to a CO2-equivalent basis using the 100-year GWPs published in the IPCC's
Second Assessment Report (SAR) (see Table 1-1).2
EPA estimates that global non-CO2 GHG emissions in 2000 were 9,514 million metric tons of carbon
dioxide equivalents (MtCO2eq). When compared to the IPCC estimate for 2000 global carbon dioxide
emissions of approximately 31,868 MtCO2 (de la Chesnaye, F.C. et al., 2006), anthropogenic non-CO2
emissions sources are responsible for over 23 percent of the global GHG emissions emitted annually.
Table 1-2 presents additional information on the breakdown of 2000 CC^ and non-CO2 emissions by
sector.
1 Radiative forcing is the change in the balance between radiation coming into the atmosphere and radiation going out. A positive
radiative forcing tends on average to warm the surface of the Earth, and negative forcing tends on average to cool the surface.
(IPCC, 1996).
2 Although the GWPs have been updated by the IPCC in the Third Assessment Report (TAR), estimates of emissions in this report
continue to use the GWPs from the SAR, in order to be consistent with international reporting standards under the UNFCCC.
However, some of the high GWP gases estimated in this report only have GWPs in the TAR. In these cases, this report uses the
TAR GWPs (see Table 4-1 for additional gases).
June 2006 Revised 1. Introduction Page 1-1
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High GWP Gases
0.4%
Source: IPCC, 2001; Table 6-1.
Exhibit 1-1. Contribution of Anthropogenic Emissions of Greenhouse Gases to the Enhanced
Greenhouse Effect from Pre-1 ndustrial to Present (measured in Watts/meter2)
1.3 Emission Sources
This report focuses exclusively on anthropogenic sources of the non-CC>2 GHGs. Table 1-3 lists the
source categories discussed in this report. All anthropogenic sources of methane and nitrous oxide are
included (with a few exceptions that are noted in Section 1.5). The major sources are considered
individually and are listed in Table 1-3. Emissions from minor sources are combined under "Other"
categories; these minor sources are also listed in Table 1-3. The high GWP sources include substitutes
for ozone-depleting substances (ODS) and industrial sources of MFCs, PFCs, and SF6.
1.4 Approach
In this analysis, EPA presents emissions for individual countries for 1990 - 2020 in five-year increments.
In addition to the individual country data, EPA presents overall trends by region, gas, and source category
and explanations for why these trends are expected.
June 2006 Revised
1. Introduction
Page 1 -2
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Table 1-1. Global Warming Potentials
Gas
Carbon dioxide (CC>2)
Methane (CH4)
Nitrous Oxide (N2O)
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4Fio
CeF-M
SF6
GWPa
1
21
310
11,700
650
2,800
1,300
3,800
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
Source: IPCC, 1996
a 100 year time horizon.
Table 1-2. Global Greenhouse Gas (GHG) Emissions for 2000 (MtCO2eq)
Sectors
Energy
Agriculture
Industry
Waste
Global Total
Percentage of
Global Total
C02a
23,408
7,631
829
31,868
77%
CH4
1,646
3,113
6
1,255
6,020
15%
N2O
237
2,616
155
106
3,114
8%
High
GWP
380
380
1%
Global
Total
25,291
13,360
1,370
1,361
41,382
Percentage
of Global
Total
61%
32%
3%
3%
100%
Source: de la Chesnaye, F.C., et al., 2006
June 2006 Revised
1. Introduction
Page 1 -3
-------
Table 1-3. Sources Included
Methane
Nitrous Oxide
High GWP Gases
ENERGY
Coal Mining Activities
Natural Gas and Oil Systems
Stationary and Mobile Combustion
Biomass Combustion
INDUSTRIAL
Other Industrial Non-Agricultural:
Chemical Production
Iron and Steel Production
Metal Production
Mineral Products
Petrochemical Production
Silicon Carbide Production
AGRICULTURE
Manure Management
Enteric Fermentation
Rice Cultivation
Other Agricultural:
Agricultural Soils
Field Burning of Agricultural
Residues
Prescribed Burning of
Savannas
WASTE
Landfilling of Solid Waste
Wastewater
Other Non-Agricultural (included
with waste totals)a:
Solvent and Other Product
Use
Waste Combustion
ENERGY
Biomass Combustion
Stationary and Mobile Combustion
INDUSTRIAL
Adipic Acid and Nitric Acid Production
Other Industrial Non-Agricultural:
Metal Production
Miscellaneous Industrial
Processes
AGRICULTURE
Manure Management
Agricultural Soils
Other Agricultural:
Field Burning of Agricultural
Residues
Prescribed Burning of
Savannas
WASTE
Human Sewage
Other Non-Agricultural (included with
waste totals)a:
Fugitives from Solid Fuels
Fugitives from Natural Gas and
Oil Systems
Solvent and Other Product Use
Waste Combustion
INDUSTRIAL (category and gas)
Substitutes for Ozone-Depleting
Substances:
MFCs, PFCs
HCFC-22 Production:
HFC-23
Primary Aluminum Production:
PFCs
Magnesium Manufacturing:
SF6
Electrical Power Systems:
SF6
Semiconductor Manufacturing:
HFC, PFCs, SF6
Other Non-Agricultural is included in the waste sector because waste combustion is the dominant sub-source of
emissions.
June 2006 Revised
1. Introduction
Page 1-4
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The regional groupings include countries in the following geographic or geopolitical classifications:
OECD 1990 & EU3 - all of the countries in the Organization for Economic Cooperation and
Development (OECD) as of 1990, the 25 current members of the European Union (EU), and
countries whose accession to the EU is scheduled for2007,4
Africa,
China and Centrally Planned Asia (China/CPA),
Latin America,
Middle East,
Non-European Union nations that are newly independent states from the former Soviet Union
(non-EU FSU),
Other non-EU nations in Eastern Europe (non-EU Eastern Europe), and
South and Southeast Asia (S&E Asia).
These regional country groupings are further defined in Table 1-4 and Appendix H.
The general approach for developing the emissions estimates is to use data from a hierarchy of country-
prepared, publicly-available reports. These include Annex I inventory submissions to the UNFCCC
Secretariat which consist of a National Inventory Report (NIR) and Common Reporting Format (CRF),
National Communications to the UNFCCC, the Asia Least-Cost Greenhouse Gas Abatement Strategy
(ALGAS) Reports, and/or other country prepared reports. The preferred source for historical data is the
2005 CRFs since these provide the latest GHG emissions estimates for most Annex I Parties.5
National Communications are the preferred source for projections and non-Annex I historical data, with
the Third National Communication available for most Annex I Parties and First and Second National
Communications available for many non-Annex I countries. The estimates in the UNFCCC inventory
submissions and National Communications for each reporting Party are comparable because they rely on
the IPCC methodologies and are reported for the standard list of IPCC source categories which generally
follow the categories shown in Table 1-3.
The projections represent a business as usual (BAU) scenario where currently achieved reductions are
incorporated and future mitigation actions are included only if either a well established program or an
international sector agreement is in place.6 As discussed below, a secondary set of projections that do
not include reductions from international agreements (the "No-Action" Baselines) are included for the high
GWP sources in Section 4. This second set of projections demonstrates the impact of the international
agreements.
3 The OECD90 & EU is referred to simply as OECD in the text, but as OECD90 & EU in graphs and tables.
4 The Holy See, Liechtenstein, Monaco, Andorra, and San Marino are also included in OECD90 & EU grouping.
5 Annex I Parties include the industrialized countries that were members of the OECD in 1992, plus countries with economies in
transition (the EIT Parties), including the Russian Federation, the Baltic States, and several Central and Eastern European States.
Annex I countries are noted in Table 1-4.
6 Estimates in this report are presented at the source category level, therefore, only policies and programs that affect source level
emissions directly are reflected in the BAU projections. For example, the reductions attributable to the EU landfill directive
regulations, U.S. sector level voluntary programs, and international sector agreements such as the World Semiconductor Council
agreement are reflected in BAU projections presented here. The reductions associated with Kyoto commitments are not reflected in
projections by GHG or source category because these are country level goals that are difficult to disaggregate to the required
degree.
June 2006 Revised 1. Introduction Page 1-5
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Table 1-4. Definition of Regional Groupings
Africa
China/CPA
Latin America
Middle East
-Algeria
-Democratic Republic of
Congo (Kinshasa)
-Egypt
-Ethiopia
-Nigeria
-Senegal
-South Africa
-Uganda
-"Rest of Africa"1'2
-Cambodia
-China
-Laos
-Mongolia
-North Korea
-Viet Nam
-"Rest of China/CPA"1'2
-Argentina
-Bolivia
-Brazil
-Chile
-Colombia
-Ecuador
-Mexico
-Peru
-Uruguay
-Venezuela
-"Rest of Latin America"
-Iran
-Iraq
-Israel
-Jordan
-Kuwait
-Saudi Arabia
-United Arab Emirates
-"Rest of Middle East"1'2
Non-EU Eastern
Europe
-Albania
-Croatia A
-Macedonia
-"Rest of Non-EU Eastern
Europe"1'2
Non-EU Former
Soviet Union
-Armenia
-Azerbaijan
-Belarus A
-Georgia
-Kazakhstan
-Kyrgyzstan
-Moldova
-Russian Federation
(Russia) A
-Tajikistan
-Turkmenistan
-Ukraine A
-Uzbekistan
South & Southeast
Asia
-Bangladesh
-India
-Indonesia
-Myanmar
-Nepal
-Pakistan
-Philippines
-Singapore
-South Korea
-Thailand
-"Rest of South & Southeast
Asia"1'2
OECD1990&EU
-Australia A' °
-Austria A'E'°
-Belgium A'E'°
-Bulgaria A'c
-Canada A' °
-Czech Republic A'E'
-Denmark A'E'°
-Estonia A'E'
-Finland A'E'°
-France A'E'°
-Germany A'E' °
-Greece X'E'°
-Hungary A'E'
-Iceland A'°
-Ireland A'E'°
-Italy A'E'°
-Japan A'°
-Latvia A'E
-Liechtenstein A
-Lithuania A'E
-Luxembourg A'E'°
-Monaco A
-Netherlands A'E'°
-New Zealand A'°
-Norway A' °
-Poland A'E'
-Portugal A'E'°
-Romania A'c
-Slovak Republic A'E'
-Slovenia A'E
-Spain A'E'°
-Sweden A'E'°
-Switzerland A' °
-Turkey A'°
-United Kingdom (UK)'
-United States (U.S.) A'
"RestofOECD"1'2
Codes:
A - Annex I countries.
C - Countries whose accession to the European Union (EU) is scheduled for 2007.
E - European Union (EU) countries.
O - OECD countries as of 1990.
Notes:
1.
2.
The complete list of countries included in the "Rest Of" groupings can be found in Appendix H.
In this report, when emissions totals are presented for a region, the regional sum includes the estimates for all
of the individually reported countries AND the aggregated value for the "Rest Of countries. Thus, the
emissions total for the "Middle East" found in the graphs and Appendices A-D, includes the sum of Iran, Iraq,
Israel, Jordan, Kuwait, Saudi Arabia, the United Arab Emirates AND the smaller emitters already aggregated
under "Rest of Middle East"
June 2006 Revised
1. Introduction
Page 1 -6
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If no nationally developed emissions data are available or if the data are insufficient, EPA estimates
emissions or projections using the default methodologies presented in the IPCC Guidelines and the IPCC
Good Practice Guidance. EPA uses the IPCC Tier 1 methodologies and available country or region-
specific activity data to estimate emissions.
Most countries do not include detailed estimates for high GWP emissions and projections in their National
Communications. To compile the high GWP inventory, this analysis applies consistent methodologies
and modeling techniques to estimate emissions for all countries for the high GWP source categories. For
high GWP sources, the projections include an analysis with and without planned climate measures since
the major emitting industries have agreed to clearly defined international reduction goals that will have a
substantial impact on emissions. Both of these scenarios are presented in the industry section
(Section 4) and Appendices D-7 to D-11 b. However, the summary section (Section 2) and the summary
tables for total emissions by gas and country (Appendices A-1 to A-4), present emission projections that
include the anticipated results of established programs and international sectoral agreements.
A detailed description of the methodology used for each country and category can be found in Section 7
and Appendices E-1 to E-12.
1.5 Limitations
Although the latest available information is reflected in these estimates, the projections are sensitive to
changes in key assumptions regarding technological changes and production/consumption patterns. For
example, the emission rates of new equipment using ODS substitutes are likely to be much lower than
the emission rates of the older equipment. This newer equipment is only now being phased in, and the
long-term emission characteristics are not yet well known. In the agriculture sector the effect of changing
consumer preferences on product demand, such as increased beef consumption, is extremely difficult to
predict and creates large uncertainties in the projected emissions from many of the agricultural sources.
While efforts have been made to provide projected emissions on a consistent basis, the distinction
between currently achieved GHG reductions from climate mitigation measures in place and those from
additionally planned activities is not always clearly defined in the reported data. The inclusion of
incidental GHG reductions in projected emissions as a result of climate related actions or government
polices still in development is a possibility in some isolated cases. However, due to the consistent
approaches established for reporting projected data and policies and measures in the National
Communications, the information developed from these sources are generally considered comparable.
Another limitation of this report is that since data are only presented in five-year increments and reported
data for Annex I countries are available on a yearly basis through 2003, there may, in some cases, be a
disconnect between reported 2003 data and projected 2005 data. This is due to the fact that projected
rates of growth were derived from the older National Communications and applied to the 2000 base year
from the more recently reported data from the CRFs. Projections from the earlier report may have under-
or over-estimated the actual 2003 trend line.
Finally, data gaps exist in both historical and projected emissions data for several countries. To fill gaps,
EPA uses methods ranging from interpolation to growth patterns based on analogous countries. Also,
estimates for many smaller, non-Annex I countries are not available in any form, and are prepared using
IPCC default methodologies. There are substantial uncertainties in applying the default factors on a
country-by-country basis due to the variety of national conditions encountered. The Appendices E-1 to
E-12 describe specific adjustments for each country and source.
Sources of Non-CO2 Greenhouse Gas Emissions Not Included in This Estimate
Due to methodological limitations, a few sources have not been fully included in this analysis. These
include methane from hydroelectric reservoirs and abandoned coal mines, nitrous oxide from wastewater,
and high GWP emissions from flat panel displays and the manufacture of electrical equipment. If a
country report included an estimate, this estimate is included in the country total in the "other" category.
June 2006 Revised 1. Introduction Page 1-7
-------
1.6 Organization of this Report
The remainder of this report expands upon these results in six main sections. Section 2 presents a
summary of global emissions and briefly discusses global trends. Sections 3 to 6 present information and
emission estimates for methane, nitrous oxide, and high GWP gases for the following sectors: energy,
industry, agriculture, and waste. Within each of these chapters, the discussion is divided into key sources
that contribute to emissions. These source category discussions present an overview of global emissions
for that category and regional trends for 1990 to 2020. Section 7 presents the methodology used to
gather the most recent emissions inventory and projection data, and the data sources and methods used
to adjust the available data for each country in order to make the overall estimates internally consistent
and comparable. Documentation of individual data points, references, and data tables presenting
detailed estimates by country and source category as well as global summary emissions for each gas and
country are provided in the Appendices A-E.
June 2006 Revised 1. Introduction Page 1-8
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2. Summary Results
2.1 Summary Estimates
Global anthropogenic non-CO2 emissions are estimated at nearly 9,000 MtCO2eq for 1990 and are
expected to grow approximately 44 percent by 2020. This scenario represents a business as usual
(BAD) scenario in which currently achieved reductions are incorporated but future mitigation actions are
included only if either a regulation, well established program, or an international sector agreement is in
place.1 As illustrated in Exhibit 2-1, non-CO2 GHG emissions grow slowly early in the study period, but
are expected to increase more rapidly between 2005 and 2020. Methane emissions increase from 5,816
MtCO2eq to 7,904 MtCO2eq between 1990 and 2020, while nitrous oxide emissions increase from 2,871
MtCO2eq to 4,057 MtCO2eq during the same period. High GWP emissions increase from 239 MtCG^eq
in 1990 to 935 MtCO2eq in 2020.
The historical trends observed for methane and nitrous oxide are the cumulative effect of several drivers.
Although the basic activities have increased (waste generation and landfilling, energy production and
consumption, etc.), several factors have mitigated emission growth. First, recovery and use of methane
has reduced emissions in many countries. Second, sectoral level restructuring has decreased emissions.
For example, European agricultural policies led to more efficient farming practices and decreased use of
fertilizer. Finally, economic restructuring in several countries such as Russia and Germany caused a
decrease in emissions in the 1990s. After 2000, emissions begin to increase again due to a number of
factors including 1) economic and sectoral growth in recently restructured countries and sectors, and
2) only partial mitigation coverage in the BAD projections (as described above). High GWP emissions,
although relatively small in 1990, are projected to nearly quadruple over the study period as new
chemicals are deployed as substitutes for the ozone-depleting substances (ODS) that are being phased
out under the Montreal Protocol.
14,000
1990 1995
2000
2005
Year
2010
2015
2020
DCH4
DN2O
D High GWP
Exhibit 2-1. Total Global Non-CO2 Emissions by Gas (MtCO2eq)
1 Estimates in this report are presented at the source category level, therefore, only policies and programs that affect source level
emissions directly are reflected in the BAU projections. For example, the reductions attributable to the EU landfill directive
regulations, U.S. sector level voluntary programs, and international sector agreements such as the World Semiconductor Council
agreement are reflected in BAU projections presented here. The reductions associated with Kyoto commitments are not taken into
account because these are country level goals that are difficult to disaggregate to the source category level.
June 2006 Revised
2. Summary
Page 2-1
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2.2 Trends by Region
Exhibit 2-2 shows the regional contribution of emissions from 1990 to 2020. Over the entire period, BAD
emissions of non-CO2 GHGs are projected to increase in every region except the non-EU FSU. The non-
EU FSU shows a 38 percent decrease from 1990 to 2000 that is followed by a gradual increase, however,
even 2020 emission levels are not expected to reach the1990 level. On an individual country basis,
China, Brazil, India, and the U.S. show the largest absolute increases in projected emissions between
1990 and 2020, growing by 741, 357, 306, and 212 MtCC^eq, respectively.
14,000
12,000
1990
2020
QOECD90&EU
Non-EU FSU
D Middle East
DChina/CPA HSEAsia
E3 Latin America H Africa
D Non-EU Eastern Europe
Exhibit 2-2. Total Global Non-CO2 Emissions by Region (MtCO2eq)
Table 2-1 shows regional growth rates. The cumulative growth rate in emissions is largest in the
developing regions of the Middle East, Africa, Latin America, S&E Asia, and China/CPA with growth rates
of 197 percent, 104 percent, 86 percent, 64 percent, and 58 percent respectively. Developed regions
tend to increase at much slower rates with the OECD emissions predicted to grow at 10 percent from
1990-2020.
June 2006 Revised
2. Summary
Page 2-2
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Table 2-1. Percent Change by Decade and by Region
Region
Middle East
Africa
Latin America
S&E Asia
China/CPA
Non-EU Eastern Europe
OECD90 & EU
Non-EU FSU
% Change
1990-2000
50%
40%
24%
19%
16%
-9%
-6%
-38%
2000-2010
47%
20%
21%
19%
17%
12%
4%
16%
2010-2020
35%
21%
24%
16%
16%
15%
12%
13%
1990-2020
197%
104%
86%
64%
58%
18%
10%
-1 9%
A review of the decadal growth rates reveals different patterns for each region. The non-EU Eastern
Europe, OECD, and non-EU FSU have declining emissions through 2000, followed by a period of
increasing emissions. Economic and sectoral restructuring, and methane recovery and use are factors in
these regions. The projected emissions reflect economic and population growth and represent BAU
conditions, as described earlier in the chapter. Additionally, although these countries are expected to see
future growth, the rates are not as large as for the other regions. In contrast, developing regions show a
steady increase in the level of emissions throughout the study period, although the accelerated growth
rates of the late 1990s and early 2000s begin to slow somewhat in later periods in areas such as the
Middle East, and Africa. The S&E Asia, China/CPA, and Latin America regions show sustained growth
rates throughout the period.
Exhibit 2-3 shows the total emissions from 1990 to 2020 for countries in the following groupings:
1) Group 1 - Africa, China/CPA, Latin America, Middle East, and S&E Asia; and
2) Group 2 - The OECD, non-EU FSU and non-EU Eastern Europe.
The consistent increases in global emissions in Group 1 are due to several factors in the developing
world, including rapid industrialization, expanding economies, and a large and growing population. As
mentioned earlier, the trends in Group 2 are due, in part, to the restructuring of several industries in key
countries or regions and the historical decrease in emissions from 1990 to 2000 as a result of methane
emission reductions in sources including coal mining and landfills. In the 1990s, coal production declined
rapidly in England and Germany, which substantially reduced methane emissions from this category in
the EU. In the EU, a waste directive that limits the disposal of organic waste significantly decreased
current and projected emissions from landfills in that region. A decline in the U.S. methane emissions
from landfills and coal mining also significantly impacted the OECD trend during the period 1990 to 2000.
June 2006 Revised
2. Summary
Page 2-3
-------
14,000
12,000
10,000
O
O 8,000 -
° 6,000 -
W
w
E
LU
4,000 -
2,000 -
Group 2: OECD, non-EU FSU and non-EU
Eastern Europe
Group 1: Africa, China/CPA, Latin America, Middle East
and South & Southeast Asia
0
1990
1995
2000
2005
Year
2010
2015
2020
Exhibit 2-3. Total Global Non-CO2 Emissions by Region and Group (MtCO2eq)
For non-EU Eastern Europe and non-EU FSU, two main forces account for declines in methane and
nitrous oxide emissions. First, the economic transitions to market economies during the early 1990s
resulted in historical GHG emissions decline due to restructuring within many industries. Second, in
Russia and other Eastern European coal producing countries, many of the gassiest underground mines
were closed during this period resulting in a sustained decrease in methane emissions in the projection
years. However, overall GHG emissions are expected to start gradually increasing around 2005-2010 in
many of these countries, as economic recovery widens and domestic production increases in many
sectors.
2.3 Trends By Gas and Source Category
Agricultural sources are the largest global source of non-CO2 emissions, as illustrated in Exhibit 2-4. In
absolute terms, emissions from agricultural sources are projected to increase more than 2,000 MtCC^eq
between 1990 and 2020. Countries with large, sustained agricultural production sectors such as the U.S.
and Australia and countries with fast-growing populations and economies such as China/CPA, S&E Asia,
Latin America, and Africa offset the emission reductions experienced by other countries in this sector.
Nitrous oxide emissions from agricultural soils and methane from enteric fermentation compose the
largest agricultural sources. These two sources account for nearly 70 percent of emissions from the
category throughout the study period.
Non-CO2 emissions from the energy sector also increase significantly (927 MtCO2eq) during the study
period. Significant increases are predicted for natural gas and oil systems (84 percent) and stationary
and mobile combustion (42 percent). However, emissions from coal mines are projected to fall by
13 percent through 2020. The largest non-agricultural source of nitrous oxide emissions shifts from adipic
and nitric acid production to stationary and mobile sources. Adipic acid and nitric acid production
emissions dropped dramatically between 1990 and 2000 and are expected to stay near 2000 levels to
2020. However, total nitrous oxide emissions increase overall due to an increase in mobile source
emissions and steadily increasing emissions from agricultural soils after 2000.
June 2006 Revised
2. Summary
Page 2-4
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14,000
12,000
10,000
O 8,000
O
w 6,000
o
E 4,000
2,000
1990
1995
2000
2005
Year
2010
2015
2020
D Agriculture
I Energy
D Waste
I Industrial Processes
Exhibit 2-4. Global Non-CO2 Emissions by Sector and Year (MtCO2eq)
Emissions from high GWP gases occur exclusively in the industrial sector and dominate emissions and
trends in that sector. High GWP and thus industrial emissions increase significantly from 1990 to 2020
for all regions. Unlike methane and nitrous oxide, emissions of high GWP gases are expected to grow
significantly over this period due to the phase out of ODS under the Montreal Protocol, and strong
predicted growth in other applications such as semiconductor manufacturing. As ODS are phased out in
developed countries, other gases, including MFCs and PFCs, are substituted. The rate of growth is
uncertain, however, because the choice of chemicals and potential new technologies or operating
procedures could eliminate or diminish the need for these gases.
In the waste sector, methane from landfills accounts for more than half of non-CG^ emissions in 1990.
After increasing slightly between 1990 and 1995, landfill emissions drop to a low point in 2000 before
beginning a gradual increase through 2020. Increases in waste generation and population drive
emissions upward but increases in waste-related regulations and gas recovery and use will temper that
increase. Wastewater emissions exhibit a much higher growth rate than landfills and by 2020 account for
nearly an equal share of global non-CO2 waste emissions. Projected wastewater emissions are driven by
population growth and the underlying assumption that growing populations in the developing world are
served by latrines and open sewers and not advanced wastewater treatment systems.
2.4 Other Global Datasets
Although non-CO2 global emissions data are not as prevalent as CO2 data, other datasets exist and EPA
has included information on those datasets for comparison. It should be noted that in some cases, those
datasets rely partly on either segments or earlier versions of the dataset presented in this report.
Additionally, the dataset presented in this report includes data on biomass burning taken from the
Emission Database for Global Atmospheric Research (EDGAR).
June 2006 Revised
2. Summary
Page 2-5
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Table 2-2 presents global historical and projected emissions of methane, nitrous oxide, and high GWP
gases for 2000, 2010, and 2020 from the following sources:
Energy Management Forum 21 (EMF-21) Analysis (U.S. EPA, 2003).
IPCC Special Report on Emissions Scenarios (SRES) (IPCC, 2001).
Emission Database for Global Atmospheric Research (EDGAR) 3.2 Fast Track 2000 dataset
(Olivier etal., 2005).
For the SRES, the IPCC created 40 future emissions scenarios which make different assumptions about
(among other things) economic and population growth rates, energy sources, environmental policies, and
future technologies. This report uses the A2 and B2 marker scenarios in its comparison table. The data
compiled for EMF-21 share many of the data sources and methods EPA employed in this report for
methane and nitrous oxide. The EDGAR 3.2 Fast Track 2000 dataset assumes that control technologies
have not changed since 1995, but does apply emissions reductions when country-specific reduction
information is available. EDGAR inventories are compiled using international statistics as activity data
and emission factors from the scientific literature.
Although there are differences among individual numbers, the trends are similar. Furthermore, the
difference between EPA's methane and nitrous oxide data and the other datasets does not exceed
22 percent for any single year. A slightly larger gap appears among the high GWP data; EPA's 2010
projection for high GWP emissions differs by 44 percent from the SRES projection.
June 2006 Revised 2. Summary Page 2-6
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Table 2-2. Comparison of EPA Global Database to Other Global Inventories (MtCO2eq)
Inventory
EPA Global Database (2006)
EMF-21 Analysis (2003)a
IPCC SRES Version (2001)"
EDGAR 3.2 Fast Track 2000C
Methane
2000
6,020
5,922
6,783-
7,287
6,741
2010
6,875
6,573
7,329-
7,770
NE
2020
7,904
7,866
8,064-
8,904
NE
Nitrous Oxide
2000
3,114
3,483
3,410
3,784
2010
3,514
3,968
3,020-
3,945
NE
2020
4,057
4,613
2,972-
4,676
NE
High GWP
2000
380
443
498
465d
2010
602
780
867-869
NE
2020
935
1102
1 ,032-
1,041
NE
Codes:
NE indicates "not estimated."
Notes:
a Energy Management Forum 21 (EMF-21) Analysis (U.S. EPA, 2003).
b IPCC Special Report on Emissions Scenarios (SRES) (IPCC, 2001).
c Emission Database for Global Atmospheric Research (EDGAR) 3.2 Fast Track 2000 (Olivier, et al., 2005).
d 295 metric tons of C7Fi6 not included in total; unknown GWP.
June 2006 Revised
2. Summary
Page 2-7
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3. Energy
3.1 Introduction
This chapter presents global methane and nitrous oxide emissions for 1990 to 2020 for the following
anthropogenic sources:
Natural gas and oil systems (methane)
Coal mining activities (methane)
Stationary and mobile combustion (methane and nitrous oxide)
Biomass combustion (nitrous oxide and methane).
The energy sector is the second largest contributor (22 percent) to global emissions of non-CC>2
emissions. In 1990, the energy sector accounts for 1,931 MtCO2eq of non-CO2 GHG emissions. As
shown in Exhibit 3-1, fugitive emissions from natural gas and oil systems are the largest source of non-
CO2 GHG emissions from this sector, accounting for 51 and 63 percent of energy related emissions in
1990 and 2020, respectively. The next largest source in this sector is fugitive emissions from coal mining,
but this source has a declining share over time, constituting roughly 27 percent of the energy sector in
1990, 20 percent in 2000, and 16 percent by 2020.
Several key factors play a role in the emissions from the energy sector as a whole: economic
restructuring in Eastern Europe and the Former Soviet Union (FSU); a shift from coal to natural gas as an
energy source in several regions; restructuring in several key coal mining countries and expansive growth
in energy consumption in less developed regions. These effects are further discussed within each source
discussion.
^ nnn -
9 ^nn
^
%
o
00 nnn
s
d
° 1 ^nn
'in '>DUU
0)
E
LU
1,000 -
500
n
:
1
1990
=
-
-
~
-
-
1995 2000 2005 2010 2015 2020
Year
D Natural Gas and Oil Systems DCoal Mining
D Fossil Fuel Combustion D Biomass Combustion
Exhibit 3-1. Total Emissions from the Energy Sector by Source (MtCO2eq)
June 2006 Revised
3. Energy
Page 3-1
-------
3.2 Natural Gas and Oil Systems (Methane)
3.2.1 Source Description
Methane is the principal component (95 percent) of natural gas and is emitted from natural gas
production, processing, transmission and distribution. Oil production and processing can also emit
methane in significant quantities since natural gas is often found in conjunction with petroleum deposits.
In both oil and natural gas systems, methane is a fugitive emission from leaking equipment, system
upsets, and deliberate flaring and venting at production fields, processing facilities, transmission lines,
storage facilities, and gas distribution lines.
3.2.2 Source Results
Total Methane Emissions
from Natural Gas and Oil Systems
Year
MtCO2eq
GgCH4
1990
1995
2000
2005
2010
2015
2020
994
977
1,030
1,165
1,354
1,570
1,828
47,313
46,536
49,041
55,478
64,496
74,749
87,028
2,000
1,800
1990
1995
2000
2005
Year
2010
2015
2020
ENon-EUFSU
D Middle East
DChina/CPA
DOECD90&EU
E3SE Asia
SNon-EU Eastern Europe
Q Latin America
ID Africa
Exhibit 3-2: Methane Emissions from Natural Gas and Oil Systems 1990 - 2020 (MtCO2eq)
June 2006 Revised
3. Energy
Page 3-2
-------
Global oil and gas methane emissions are projected to increase by 84 percent between 1990 and 2020,
with a slight decrease from 1990 to 1995 and an increasingly positive growth rate after 1995, as shown in
Exhibit 3-2. Three key factors influence the overall trend in global emissions from 1990 to 2020: the non-
EU FSU economic transition; the mild growth in production in parts of the OECD; and the accelerated
growth in energy production and demand in all other regions, especially Asia. Increasing emissions over
the period 1990 to 2020 are expected in all regions except the non-EU FSU, as shown in Table 3-1.
Although the rank order of the regions does not change during the study period, each region's
contribution to global emissions changes dramatically. For example, in 1990, the non-EU FSU and
OECD countries account for 75 percent of the global methane emissions. By 2020, their collective share
falls to 47 percent.
The non-EU FSU is the only region where the 2020 emissions level is expected to remain level over the
30 year study period, as illustrated in Exhibit 3-2 and Table 3-1. Russian natural gas emissions dominate
this region's emissions and trends. Russia's economic transition causes a short term decline in the
production and use of natural gas and oil, which leads to a sharp decrease in emissions from 1990 to
2000. The emissions are expected to increase after 2000, but the percentage of Russia's contribution to
the global emissions still falls to 11 percent by 2020, from 33 percent in 1990. Without Russia in the total,
this region still shows a decline from 1990 to 2000 since most FSU countries experienced a similar,
though sometimes smaller, economic decline during the period. However, the growth in the rest of the
non-EU FSU region is large enough to overcome the temporary decline in emissions, leading to an
overall growth rate of over 98 percent from 1990 to 2020 for these countries.
After the non-EU FSU region, OECD countries have the next lowest growth rate, as illustrated in
Exhibit 3-2 and Table 3-1. The OECD countries experience only mild growth (40 percent) compared to
the developing regions. Several reasons may underlie this trend. Many of these countries have mature
natural gas and oil industries with stabilized or limited growth in production sectors. Additionally, many
OECD countries have instituted air quality and safety rules that have the ancillary benefit of reducing
methane emissions. However, it is likely there will be a continued and growing demand for natural gas in
the OECD, which may result in increased emissions in the distribution and transmission sectors.
By contrast, the Middle East, Latin American, and S&E Asian regions are expected to account for a much
greater share of global emissions by 2020, increasing from 22 percent in 1990 to 44 percent in 2020. In
the less developed countries of these regions, electricity production and demand are expected to
increase rapidly as populations become more urbanized and concentrated, and industries expand. In
turn, these energy demands are expected to drive the rapid growth in fuel production and consumption.
Also, the Middle East includes some of the largest oil production and exporting countries, and emissions
are expected to increase there as a result of increasing world demand for oil. China/CPA shows the
largest rate of growth in emissions at 812 percent; however, it still accounts for only about 1 percent of
the global total in 2020 since it relies more heavily on coal than oil and gas production for its energy
needs.
Table 3-1. Percentage Change in Methane Emissions from Natural Gas and Oil Systems Between
1990 and 2020
Region
China/CPA
Africa
Middle East
Latin America
S&E Asia
Non-EU Eastern Europe
OECD90 & EU
Non-EU FSU
Global
% change
812%
370%
321%
285%
211%
55%
40%
0%
84%
June 2006 Revised
3. Energy
Page 3-3
-------
Actual future emissions may differ from these projections for several reasons. Efforts are underway to
modernize gas and oil facilities in Russia and many Eastern European countries, which could help reduce
fugitive emissions. In areas where gas production is projected to increase, such as Western Europe,
emissions will not necessarily increase at the same rate. Leakage and venting do not necessarily
increase linearly with throughput, and newer equipment tends to leak less than older equipment.
Projections of oil and natural gas production and consumption are, by nature, highly uncertain. The
uncertain future of gas prices adds an additional level of uncertainty.
3.3 Coal Mining Activities (Methane)
3.3.1 Source Description
Methane is produced during the process of coalification, where vegetation is converted by geological and
biological forces into coal. Methane is stored within the coal seams and the surrounding rock strata and
is liberated when the pressure above or surrounding the coal bed is reduced as a result of natural
erosions, faulting, or mining (U.S. EPA, 1993; U.S. EPA, 1999).
The quantity of gas emitted from mining operations is a function of two primary factors: coal rank and coal
depth. Coal rank is a measure of the carbon content of the coal, with higher coal ranks corresponding to
higher carbon content and generally higher methane content. Coals such as anthracite and
semianthracite have the highest coal ranks, while peat and lignite have the lowest. Pressure increases
with depth and prevents methane from migrating to the surface. Thus, underground mining operations
typically emit more methane than surface mining (EPA, 1993).
Methane emissions from the coal mining sector come from four main sources:
Underground Mines. Underground mines account for the majority of global methane emissions
from coal mining. Geologic pressure traps larger volumes of methane in deeper coal seams and
the surrounding rock strata. Because methane is explosive at concentrations of between five and
fifteen percent, methane is removed from underground mines by ventilation or degasification as a
safety precaution (U.S. EPA 1993; U.S. EPA, 1999).
Surface Mines. As the coal seam is exposed during surface mining, methane is liberated directly
to the atmosphere. Surface mines generally emit considerably less methane than underground
mines because coal ranks are typically lower and there is less pressure to trap methane in the
coal.
Post-Mining Operations. Post-mining operations refer to the processing, storage, and
transportation of the mined coal. Coal can continue to emit methane for months after mining,
depending on the characteristics of the coal and the handling procedures. The highest releases
occur when coal is crushed, sized, and dried for industrial and utility uses (EPA, 1999).
Abandoned Mines. Methane emissions from coal mines can continue after operations have
ceased. The key factors are surrounding strata permeability and emissions while active.
Abandoned mines are not considered in this analysis due to a lack of data. Methane recovery and use is
not explicitly estimated in this analysis, however, if a country includes such estimates in its historical
emissions, it is included here.
3.3.2 Source Results
As shown in Exhibit 3-3, global coal mine methane emissions decline substantially from 1990 to 2000, but
are expected to increase steadily after 2000 and return to nearly 1990 levels by 2020. Key factors
influencing both the historical and projected trends are the changes in coal production in China,
restructuring of the energy industries in Europe and the non-EU FSU, and industry changes in the U.S.
June 2006 Revised 3. Energy Page 3-4
-------
o
o
CO
d
o
'
E
LU
600 -i
500
400 -
300 -
200 -
100 -
1990
1995
2000
2005
Year
2010
2015
2020
QOECD90&EU
DSE Asia
DNon-EU Eastern Europe
DChina/CPA
0 Africa
B Middle East
H Non-EU FSU
ID Latin America
Exhibit 3-3. Methane Emission from Coal Mining Activities 1990 - 2020 (MtCO2eq)
The China/CPA region shows an increase and then subsequent decline between 1990 and 2000. The
upward trend from 1990 to 1995 in the China/CPA region is largely due to an increase in coal mining in
China and North Korea, which account for most of the emissions in the region and are among the top six
emitters for the source. The declining trend from 1995 to 2000 is caused primarily by changes in the
Chinese coal industry. Many mines closed during this period and coal production slowed significantly.
This trend is not predicted to continue past 2000, with China's emissions expected to increase 50 percent
by 2020 in response to increased coal production to meet expanding energy needs.
The non-EU FSU and OECD regions experienced a significant decline in emissions from 1990 to 2000.
In the 1990s, coal production declined rapidly in England and Germany, contributing substantially to the
reduction in OECD emissions from 1990 to 2000. In Russia and Eastern European coal producing
countries, restructuring of the energy industries caused many of the gassiest underground mines to close
during the 1990s resulting in a decrease in emissions that has been sustained in the projection years.
Emissions in non-EU FSU region are expected to decline throughout the analysis period, though more
gradually after 2000 as economic recovery widens and domestic production increases in many sectors of
these countries.
Emissions from coal mining activities are expected to decrease in the U.S. through 2020, which also
affects the downward trend in OECD emissions. Production is shifting from underground coal mines to
surface mines, as well as shifting to the less gassy western basins for a portion of the remaining
underground mining. Additionally, reductions due to methane recovery and use of coal bed methane will
impact emissions. These reductions in emissions are expected despite anticipated growth in overall coal
production over the analysis period.
June 2006 Revised
3. Energy
Page 3-5
-------
Total Methane Emissions
from Coal Mining Activities
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
517
452
377
388
408
426
449
GgCH4
24,607
21,502
17,946
18,483
19,408
20,265
21,404
3.4 Stationary and Mobile Combustion (Nitrous Oxide and Methane)
3.4.1 Source Description
Nitrous oxide is a product of the reaction between nitrogen and oxygen during combustion of fossil fuels
and biomass. Both mobile and stationary sources emit nitrous oxide, and the volume emitted varies
according to the type of fuel, combustion technology, and pollution control device used, as well as
maintenance and operating practices. Stationary and mobile combustion also result in methane
emissions due to incomplete combustion. However, combustion is a relatively minor contributor to overall
methane emissions.
Stationary combustion encompasses all fossil fuel combustion activities except transportation (i.e., mobile
combustion). These activities primarily include combustion of fossil fuels and commercially-traded
biomass fuels1 used in large power plants and boilers. Total emissions from stationary and mobile
combustion are small in comparison to other sources, amounting to only 6 percent of global nitrous oxide
emissions.
Mobile combustion sources such as automobiles and airplanes emit nitrous oxide as an exhaust emission
from a variety of engine and fuel configurations. As with stationary sources, nitrous oxide emissions are
closely related to air-fuel mixtures and combustion temperature, as well as pollution control equipment on
transportation vehicles. Key factors affecting fuel consumption and, ultimately emissions, for mobile
sources include the distance traveled for vehicles, hours of operation for off-road equipment, age of
vehicles, and mode of operation. Road transport accounts for the majority of mobile source fuel
consumption, and as a result, the majority of mobile nitrous oxide emissions.
3.4.2 Source Results
In 1990, the OECD nations contribute 76 and 67 percent to global nitrous oxide and methane emissions
from combustion sources, respectively. However, as shown in Table 3-2, the expected growth in
emissions between 1990 and 2020 for the OECD is among the lowest of all regions (32 percent for
nitrous oxide and -15 percent for methane). Although the percent contribution of the OECD nations is
expected to decline, the OECD nations are expected to remain the largest emitters throughout the period,
accounting for 66 percent and 48 percent for methane and nitrous oxide emissions in 2020, respectively,
as illustrated in Exhibits 3-4.1 and 3-4.2. The third largest emitter of nitrous oxide in 1990, the non-EU
FSU, is predicted to have a negative growth rate (-39 percent) between 1990 and 2020 and is projected
to drop to the seventh largest emitter in 2020. This region is surpassed by the increasing emissions of
the developing nations of S&E Asia, Latin America, China/CPA, and Africa. China/CPA, the second
largest source of nitrous oxide in 1990 (6 percent), is expected to increase its emissions nearly 2.5 times
by 2020 and S&E Asia is predicted to have a growth rate well over 200%. The increases in these
1 This report includes emissions for biomass fuels along with stationary and mobile combustion only for the Annex I countries. For
these countries, biomass combustion emissions are reported together with fossil fuels in the Common Report Format. For non-
Annex I countries, emissions for biomass were calculated separately and are reported in Appendices B-4 and C-2. See Section 3.5
for more information.
June 2006 Revised 3. Energy Page 3-6
-------
developing regions are driven by higher demand for and production of energy and the increased use of
automobiles.
Total Methane and Nitrous Oxide Emissions
from Stationary and Mobile Combustion
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
233
256
268
265
286
300
331
GgCH4
3,171
3,004
2,933
3,040
3,242
3,478
3,771
GgN20
537
622
667
648
703
731
813
From 1990 to 1995, the two driving forces behind the decrease in stationary combustion emissions are
the decline in energy consumption in Russia and Eastern Europe and a shift in Western Europe from coal
to natural gas. However, as the economies of Eastern Europe and Russia recover after 2000, energy
demand is expected to rise and emissions are expected to grow. High-emitting coal boilers and furnaces
will continue to be the primary source of emissions in these regions as long as coal remains a major
source of energy. Emissions from the EU are also expected to increase with energy consumption;
however, emissions per unit of energy will decrease because of a shift from coal to natural gas, and the
increased use of fluidized bed systems in coal-fired plants, which reduce nitrous oxide emissions. The
remaining regions all show increases over the time period, though none approach the level of emissions
from the OECD.
The increase in nitrous oxide emissions from mobile sources in the OECD region is due to two factors.
First, an increasing share of the automotive fleet is equipped with emission reduction catalysts. Certain
types of catalyst technologies, while achieving substantial reductions in volatile organic compounds
(VOCs), carbon monoxide (CO), and nitrogen oxides (NOX), may actually result in higher nitrous oxide
emissions. In the U.S. and Canada, the automobile industry is currently phasing-in new emission control
technologies that produce lower nitrous oxide emissions. The penetration of these new control
technologies is expected to occur somewhat later and at a slower rate in the EU. Second, a substantial
increase in distance traveled and fuel consumption has occurred since 1990 due to strong economic
growth and low fuel prices during the 1990s. The trend in increased distance traveled is likely to continue
in the future as the driving population increases. However, some of this increased activity may also be
dampened by increasing fuel costs and offset by increasing energy efficiency of passenger cars.
June 2006 Revised 3. Energy Page 3-7
-------
1990
2015
2020
DOECD90&EU
D Latin America
D SE Asia
DNon-EUFSU
E3 Middle East
HNon-EU Eastern Europe
B Africa
IIChina/CPA
Exhibit 3-4.1. Methane Emissions from Stationary and Mobile Combustion 1990 - 2020 (MtCO2eq)
300 -i
250
cr
200 --
» 100 -
LU
50 -
1990
1995
2000
2005
Year
2010
2015
2020
EOECD90&EU
D Africa
D Middle East
DChina/CPA
H Latin America
HNon-EU Eastern Europe
HNon-EUFSU
USE Asia
Exhibit 3-4.2. Nitrous Oxide Emissions from Stationary and Mobile Combustion 1990 - 2020
(MtCO2eq)
June 2006 Revised
3. Energy
Page 3-8
-------
Table 3-2. Percentage Change in N2O and CH4 Emissions Between 1990 and 2020
Region
Non-EU Eastern Europe
S&E Asia
Latin America
China/CPA
Middle East
Africa
OECD90 & EU
Non-EU FSU
N20
391%
268%
173%
146%
144%
92%
32%
-39%
CH4
54%
280%
165%
310%
179%
86%
-15%
-22%
3.5 Biomass Combustion (Methane and Nitrous Oxide)
3.5.1 Source Description
Methane and nitrous oxide are produced as a result of incomplete biomass combustion. Fuel wood,
charcoal, agricultural residues, agricultural waste, and municipal waste combustion are the major
contributors to methane and nitrous oxide emissions within this category. Biomass combustion in the
developing world often refers to the combustion of biofuels in small-scale combustion devices for heating,
cooking, and lighting purposes. Because of the wide variety in the types and conditions under which
these fuels are burned, estimates for this category are highly uncertain and difficult to predict.
The data presented here are for non-Annex I countries only. Emissions from biomass combustion for
Annex I countries are included in the stationary and mobile combustion section due to UNFCCC reporting
(see Section 3.4).
3.5.2 Source Results
Total Methane and Nitrous Oxide Emissions
from Biomass Combustion
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
187
196
208
218
229
239
249
GgCH4
7,666
7,985
8,458
8,869
9,323
9,721
10,137
GgN20
84
92
98
102
108
112
118
June 2006 Revised
3. Energy
Page 3-9
-------
250
1990
1995
2000
2005
Year
2010
2015
2020
QSE Asia
D Latin America
D Middle East
DChina/CPA
HOECD90&EU
SNon-EUFSU
E2 Africa
IDNon-EU Eastern Europe
Exhibit 3-5.1. Methane Emissions from Biomass Combustion 1990- 2020 (MtCO2eq)
1990
1995
2000
2005
Year
2010
2015
2020
[DChina/CPA
Latin America
DNon-EU Eastern Europe
D Africa
0OECD90&EU
BNon-EUFSU
0SE Asia
m Middle East
Exhibit 3-5.2. Nitrous Oxide Emissions from Biomass Combustion 1990 - 2020 (MtCO2eq)
June 2006 Revised
3. Energy
Page 3-10
-------
Both methane and nitrous oxide emissions from biomass combustion show an upward trend from 1990 to
2020. The combined regions of S&E Asia, China/CPA, and Africa contribute over 90 and 84 percent of
the methane and nitrous oxide emissions, respectively. The largest sub-source for this sector is
residential solid biomass combustion fuels. The activity data for solid fuel in the energy and
manufacturing sector are also high but the emission factors are an order of magnitude lower for methane
since the processes tend to be more efficient. Nitrous oxide emissions are minimal, with an emission
factor from 10 to 100 times smaller than the methane emission factor for the main categories of
emissions. In the future, this section may be integrated fully into the stationary and mobile emissions
sector.
June 2006 Revised 3. Energy Page 3-11
-------
4. Industry
4.1 Introduction
This section presents non-CO2 emissions from the industrial sector for 1990-2020. The industrial sector
includes industrial sources of nitrous oxide (N2O) and methane (CH4), along with several sources of the
high global warming potential (high GWP) gases. The high GWP sources include the use of substitutes
for ozone-depleting substances (ODS) and industrial sources of hydrofluorocarbons (MFCs),
perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). The categories and their GHG emissions
presented in this section are as follows:
Adipic acid and nitric acid production (N2O)
Substitutes for ozone-depleting substances (MFCs, PFCs)
HCFC-22 production (MFCs)
Electric power systems (SF6)
Primary aluminum production (PFCs)
Semiconductor manufacturing (MFCs, PFCs, SF6)
Magnesium manufacturing (SF6)
Other miscellaneous industrial sources (CH4 N2O).
4.1.1 Trends in Emissions from Industrial Sources
As shown in Exhibit 4-11, emissions from this sector increase by 138 percent between 1990 and 2020.
Through 2000, the largest emissions source is adipic acid and nitric acid production. In 1990, this source
contributed nearly 48 percent of the emissions for this sector. However, by 2020, this source will
contribute only 16 percent of the sector's emissions. During the 30-year period from 1990 to 2020, the
replacement of ODS with MFCs and PFCs will lead to a large increase in high GWP emissions from ODS
substitutes. ODS substitutes have a wide variety of applications including use as refrigerants, aerosol
propellants, solvents, foam blowing agents, medical sterilization carrier gases, and fire extinguishing
agents.
It should be noted that the ODSs themselves are greenhouse gases; however, following international
conventions, the emissions of these substances are not included in the baseline emissions presented
here. Only emissions of non-ozone-depleting fluorinated gases used as substitutes for ODSs are
included in the baseline emissions.
ODS substitutes will grow at a rate of more than 1200% between 1995 and 2020 and are expected to
account for 66 percent of the sector's emissions in 2020. Emissions from electric power systems and
semiconductor manufacturing will also increase during the study period at rates of 36 and 193 percent,
respectively. Three categories will show significant declines in emissions during the study period as new
technologies are implemented: emissions from primary aluminum production (-54 percent), HCFC-22
production (-14 percent), and magnesium production (-60 percent).
Projected estimates incorporate the planned reductions from the "Technology-Adoption" Baselines.
June 2006 Revised 4. Industry Page 4-1
-------
1 ,200
1 ,000
« 800 -
O
9
| 600
o
'en
en
1 400
LU
200
0
''.''.''.''.
1990
^$$5
.H-H-H-H-i
-^~^-
;^sss
M
HI
^ss^
n
ii
_
(PIPIPIPK
1995 2000 2005 2010 2015 2020
Year
D Adipic and Nitric Acid Production Q Aluminum Production
HCFC-22 Production D Electric Power Systems
D Magnesium Manufacturing S Semiconductors
Other Non-Agricultural D ODS Substitutes
Exhibit 4-1. Emissions from Industrial Processes by Source (MtCO2eq)
4.1.2 The Technology-Adoption and No-Action Baselines
This section presents two future scenarios for the industrial sources2 that emit high GWP gases, as
shown in Exhibit 4-2.
500
1990
1995
2000
2005
2010
2015
2020
TAB NAB TAB NAB TAB NAB TAB NAB TAB NAB TAB NAB TAB NAB
Technology Adoption Baseline (TAB) and No Action Baseline (NAB)
HCFC-22 Production D Electric Power Systems Q Aluminum Production
D Semiconductor Manufacturing Magnesium Manufacturing
Exhibit 4-2. Technology-Adoption and No-Action Baseline Emissions by Year (MtCO2eq)
This discussion does not include high GWP emissions from ODS Substitutes.
June 2006 Revised
4. Industry
Page 4-2
-------
The first scenario, the "Technology-Adoption Baseline," is based on the assumption that those industries
that have announced clearly defined, industry-specific global or regional reduction goals will achieve their
goals for the year 2010 and beyond. These industries include the production of aluminum,
semiconductors, magnesium, and HCFC-22, and the use of electrical equipment. The goals are
discussed in more detail in Section 7.3 of the methodology discussion. The second scenario, the "No-
Action Baseline," is based on the assumption that emission rates will remain constant from the present
onward in these industries.
EPA believes that actual future emissions are likely to be far closer to those envisioned in the
Technology-Adoption Baseline than those envisioned in the No-Action Baseline. Since 1990, all five
industries have already made great progress in reducing their emission rates, and research is continuing
into methods to further reduce those rates. Nevertheless, additional actions will be required to actually
realize additional reductions. These actions range from process optimization and chemical recycling to
chemical replacement. Thus, depending on the context, either baseline may be of interest. For example,
analysts interested in the incremental costs of reducing emissions below the levels anticipated in current
global industry commitments can use the Technology-Adoption Baseline. On the other hand, analysts
interested in the future costs of achieving the currently planned industry reductions can use the No-Action
Baseline. The difference between the two baselines is itself of interest, demonstrating that the industry
commitments are likely to avert very large emissions.
Past emissions (1990-2000) for all sources are identical under either scenario, but they are provided with
both scenarios to provide context for the divergent future trends.
As shown in Exhibit 4-2, GWP-weighted emissions from this sector are predicted to decrease by
16 percent from 1990-2020 under the Technology-Adoption Baseline; under the No-Action Baseline,
emissions would increase by 122 percent over that same period. Historically, the largest sources of high-
GWP emissions have been HCFC-22 production and aluminum production. Under the Technology-
Adoption Baseline, HCFC-22 production is expected to remain the largest contributor to total GWP-
weighted emissions through 2020, accounting for 33 percent of emissions in 2020. However, emissions
from aluminum production are expected to decline in both absolute and relative terms as that industry
continues to implement emission reduction measures to meet the International Aluminum Institute's (IAI)
global emission reduction goal. Given similar efforts to control emissions in the semiconductor and
magnesium industries, emissions from electric power systems are predicted to increase in relative
importance to become the second largest source of industrial high-GWP emissions (29 percent) in 2020
in the Technology-Adoption Baseline. As discussed further in the section on electric power systems, the
primary driver for emissions growth in this sector is the growth of electrical grids in developing countries;
this growth counteracts expected declines in emissions from developed countries.
HCFC-22 production emissions would remain one of the largest contributors under the No-Action
Baseline as well. However, in this scenario, which does not account for efforts by the semiconductor
industry to reduce emission rates, the high activity growth rate for semiconductor manufacturing
translates directly into a rapid growth in emissions. Consequently, under the No-Action Baseline,
emissions from semiconductor manufacturing account for almost half (44 percent) of total high-GWP
industrial emissions in 2020.
4.1.3 Global Warming Potentials for High GWP Gases
Table 4-1 lists the high GWP gases included in this analysis of the industrial sector with their atmospheric
lifetime, global warming potentials (GWP), and associated uses or emission sources. Although the GWPs
have been updated by the IPCC in the Third Assessment Report (TAR), estimates of emissions in this
report continue to use the GWPs from the Second Assessment Report (SAR) in order to be consistent
with international reporting standards under the United Nations Framework Convention on Climate
Change (UNFCCC). However, some of the high GWP gases estimated in this report only have GWPs in
the TAR. In these cases, this report uses the TAR GWPs.
June 2006 Revised 4. Industry Page 4-3
-------
Table 4-1. High GWP Chemicals - Partial List
Chemical
Life-
time
(yrs)
GWP
(100-yr)
Use
Hydrofluorocarbons (MFCs)
HFC-23
HFC-32
HFC-41
HFC-125
HFC-134
HFC-134a
HFC-152a
HFC-143
HFC-143a
HFC-227ea
HFC-236ea
HFC-236fa
HFC-245ca
HFC-245fa
HFC-365mfc
HFC-43-10mee
264
5.6
3.7
32.6
10.6
14.6
1.5
3.8
48.3
36.5
10.0a
209
6.6
7.2a
9.9a
17.1
11,700
650
150
2,800
1,000
1,300
140
300
3,800
2,900
1200a
6,300
560
950a
890a
1,300
Byproduct of HCFC-22 production, used in very-low temperature refrigeration, blend
component in fire suppression, and plasma etching and cleaning in semiconductor
production.
Blend component of numerous refrigerants.
Not in commercial use today.
Blend component of numerous refrigerants and a fire suppressant.
Not in commercial use today.
Most widely used HFC refrigerant, blend component of other refrigerants, propellant in
metered-dose inhalers and aerosols, and foam blowing agent.
Blend component of refrigerant blends, propellant in aerosols, foam blowing agent, and
under consideration as a stand-alone refrigerant for use in motor vehicle air conditioners.
Not in commercial use today.
Refrigerant blend component.
Fire suppressant and propellant for metered-dose inhalers.
Not in commercial use today.
Refrigerant and fire suppressant.
Not in commercial use today.
Foam blowing agent and under consideration as a refrigerant.
Foam blowing agent.
Cleaning solvent.
Perfluorocarbons (PFCs)
CF4
C2F6
C3F8
C4Fio
c-C4F8
C5F12
C6F14
50,000
10,000
2,600
2,600
3,200
4,100
3,200
6,500
9,200
7,000
7,000
8,700
7,500
7,400
Byproduct of aluminum production. Plasma etching and cleaning in semiconductor
production and component of low temperature refrigerant blends.
Byproduct of aluminum production. Plasma etching and cleaning in semiconductor
production.
Component of low-temperature refrigerant blends and fire suppressant. Used in plasma
cleaning in semiconductor production.
Fire suppressant.
Not in much use, if at all, today. Emerging for plasma etching in semiconductor production.
Not in much use, if at all, today.
Precision cleaning solvent.
Nitrogen Trifluoride (NF3)
NF3
740b
8,000b
Plasma cleaning in semiconductor production.
Sulfur Hexafluoride (SFe)
SF6
3,200
23,900
Cover gas in magnesium production and casting, dielectric gas and insulator in electric
power equipment, used to test fire suppression discharge in military systems and civilian
aircraft, atmospheric and subterranean tracer gas, sound insulation, process flow-rate
measurement, medical applications, and formerly an aerosol propellant. Used for plasma
etching in semiconductor production.
Hydrofluoroethers (HFEs)
C4F9OCH3
C4F9OC2H5
5.0a
0.77a
390a
55a
Cleaning solvent and heat transfer fluid.
Cleaning solvent.
Table excludes ozone-depleting substances controlled by the Montreal Protocol.
GWPs and atmospheric lives are reprinted from the Intergovernmental Panel on Climate Change, Second Assessment Report (IPCC,
1996), except as noted below:
aIPCC, 2001. Third Assessment Report.
b Molina, L.T., P.J. Woodbridge, and M. Molina, 1995.
June 2006 Revised
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4.2 Production of Adipic Acid and Nitric Acid (Nitrous Oxide)
4.2.1 Source Description
Nitrous oxide (N2O) is emitted during the production of adipic and nitric acids, both of which are
feedstocks or components to the manufacture of a variety of commercial products.
Adipic acid (hexane-1, 6-dioxic acid) is a white crystalline solid used as a feedstock in the manufacture of
synthetic fibers, coatings, plastics, urethane foams, elastomers, and synthetic lubricants. Commercially, it
is the most important of the aliphatic dicarboxylic acids, which are used to manufacture polyesters. In the
U.S., for example, 90 percent of all adipic acid is used in the production of nylon 6,6 (SRI, 1999). Adipic
acid is produced through a two-stage process with nitrous oxide generated in the second stage. By
treating nitrogen oxides (NOX) and other regulated pollutants in the waste gas stream, nitrous oxide
emissions can be reduced. Studies confirm that these abatement technologies can reduce nitrous oxide
emissions by up to 99 percent, depending on plant specifications (Riemer et al., 2000).
Nitric acid (HNO3) is an inorganic compound used primarily to make synthetic commercial fertilizer. It is
also a major component in the production of adipic acid and explosives. During the catalytic oxidation of
ammonia, nitrous oxide is formed as a byproduct and released from reactor vents into the atmosphere.
While the waste gas stream may be cleaned of other pollutants such as nitrogen dioxide (NO2), there are
currently no control measures aimed at eliminating nitrous oxide.
4.2.2 Source Results
Total Nitrous Oxide Emissions
from Adipic Acid and Nitric Acid Production
Year MtCO2eq Gg N2O
1990 223 721
1995 220 710
2000 154 497
2005 156 505
2010 165 531
2015 170 550
2020 177 570
June 2006 Revised 4. Industry Page 4-5
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250
1990
1995
2015
2020
DOECD90&EU
QNon-EUFSU
DNon-EU Eastern Europe
0 China/CPA
m Latin America
D Middle East
DSE Asia
D Africa
Exhibit 4-3. Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production 1990 - 2020
(MtCO2eq)
As shown in Exhibit 4-3, global nitrous oxide emissions from adipic and nitric acid production peaked in
1990 at 223 MtCO2eq Efforts to control nitrous oxide emissions from adipic acid production resulted in a
steep decline in emissions through 2000. However, the post-2000 period is characterized by a steady but
gradual increase in emissions. By 2020, emissions from this source reach 79 percent of the 1990 levels.
Exhibit 4-3 illustrates the changing regional distribution of adipic and nitric acid emissions. In 1990, the
OECD was responsible for nearly 80 percent of the emissions from this source. China/CPA, the second
largest regional source, accounted for only 9 percent of emissions. Between 1990 and 2020, OECD
emissions decrease by 40 percent, leaving this region with only a 61 percent share of the global
emissions. Projections indicate that by 2020, the China/CPA, S&E Asia, and Latin America regions will
contribute approximately 34 percent of the world's emissions.
Efforts in the U.S., EU, and Canada to reduce nitrous oxide emissions from the adipic acid production
process came into effect in the late 1990s. Their effects can be seen in Exhibit 4-3 in the substantial
reduction in emissions from 1995 to 2000. These changes in the adipic acid production process have the
capability of reducing nitrous oxide emissions by more than 95 percent, and their long-term affects may
have an even greater effect than illustrated in Exhibit 4-3 for countries that have a high penetration rate
for these process changes. Capacity expansions to meet increased global demand for adipic acid
demand are expected in the Far East, while market restructuring is expected in Western Europe and
North America.
Fertilizer demand, and thus nitric acid use, is expected to decline in Western Europe but increase
elsewhere. The decline in Western Europe is due to concerns about nitrates in the water supply. Since
nitric acid involves little global trade (SRI, 1999; U.S. EPA, 2001), it is expected that nitric acid production
in this region will decline as well, leading to a decline in nitrous oxide emissions from this source in the
EU. As demand for fertilizer increases in other regions after 2000, so will nitrous oxide emissions,
counteracting the trend in Western Europe.
June 2006 Revised
4. Industry
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4.3 Use of Substitutes for Ozone-Depleting Substances
(Hydrofluorocarbons and Perfluorocarbons)
4.3.1 Source Description
Hydrofluorocarbons (MFCs) and, to a lesser extent, perfluorocarbons (PFCs) and hydrofluoroethers
(HFEs), are used as alternatives to several classes of ODS that are being phased out under the terms of
the Montreal Protocol. Ozone-depleting substances, which include chlorofluorocarbons (CFCs), halons,
carbon tetrachloride, methyl chloroform, and hydrochlorofluorocarbons (HCFCs), have been used in a
variety of industrial applications including refrigeration and air conditioning equipment, aerosols, solvent
cleaning, fire extinguishing, foam production, and sterilization. Although the MFCs and PFCs that would
replace the ODSs are not harmful to the stratospheric ozone layer, they are powerful greenhouse gases.
4.3.2 Source Results
Total HFC and RFC Emissions
from Substitutes for Ozone-Depleting Substances
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
0
53
164
279
431
585
734
GgHFC-134aEq
0
41
126
214
331
450
564
Exhibit 4-4 illustrates the rapid growth expected in the emissions for this source. In 1995, ODS substitute
emissions were only 53 MtCO2eq,3 but by 2020, global emissions are expected to exceed 734 MtCO2eq.
In 1995, nearly all ODS substitute emissions originated in the OECD countries, but by 2020, all regions
will make some contribution to global emissions. In 2020, the OECD, China/CPA, S&E Asia, and Latin
America are projected to account for 66 percent, 10 percent, 9 percent, and 6 percent of emissions,
respectively.
3 1990 emissions for ODS substitutes were not estimated for all countries and so are not presented here. In 1990, emissions for
this category were negligible with U.S. emissions accounting for less than 0.5 MtCO2eq.
June 2006 Revised 4. Industry Page 4-7
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800
700
1990
1995
2000
2005
Year
2010
2015
2020
E3OECD90&EU
ID Latin America
Middle East
DNon-EUFSU HSEAsia
DChina/CPA D Africa
DNon-EU Eastern Europe
Exhibit 4-4. HFC and PFC Emissions from Substitutes for Ozone-Depleting Substances
1990 - 2020 by Region (MtCO2eq)
The dramatic increase in HFC and PFC emissions shown in Exhibits 4-4 and 4-5 is the result of efforts to
phaseout CFCs and other ODSs. This trend is expected to continue for many years, and will accelerate
in the early part of this century as HCFCs, which are interim substitutes in many applications, are
themselves phased out under the provisions of the Copenhagen Amendments to the Montreal Protocol.
In addition, in some ODS replacement applications, such as solvent cleaning or aerosol applications, the
substitutes are emitted immediately, but in others, such as refrigeration and air conditioning applications,
the substitutes are replacing ODSs in equipment that slowly releases the gas. Therefore, the rate of
increase in ODS substitute emissions is driven by the pace of the phaseout in each country and by the
emissions profile for the source in which the gas is used. Global emissions by end-use sector are
provided in Exhibit 4-5.
June 2006 Revised
4. Industry
Page 4-8
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800
700
2015
2020
0Refrigeration/AC
HAerosols (MDI)
DAerosols (Non-MDI)
D Foams
E3 Solvents
Fire Extinguishing
Exhibit 4-5. HFC and PFC Emissions from Substitutes for Ozone-Depleting Substances
1990 - 2020 by Sector (MtCO2eq)
4.4 Production of HCFC-22 (Hydrofluorocarbons)
4.4.1 Source Description
Trifluoromethane (HFC-23) is generated and emitted as a byproduct during the production of
chlorodifluoromethane (HCFC-22). HCFC-22 is used both in emissive applications (primarily air
conditioning and refrigeration) and as a feedstock for production of synthetic polymers. Because HCFC-
22 depletes stratospheric ozone, its production for non-feedstock uses is scheduled to be phased out
under the Montreal Protocol. However, feedstock production is permitted to continue indefinitely.
Nearly all producers in developed countries have implemented process optimization or thermal
destruction to reduce HFC-23 emissions. In a few cases, HFC-23 is collected and used as a substitute
for ozone-depleting substances, mainly in very-low temperature refrigeration and air conditioning
systems. Emissions from this use are quantified under air conditioning and refrigeration and are therefore
not included here. HFC-23 exhibits the highest global warming potential of the HFCs, 11,700 under a
100-year time horizon, with an atmospheric lifetime of 264 years.
4.4.2 Source Results
No-Action Baseline
The table below presents No-Action Baseline emissions of HFC-23 from HCFC-22 production.
June 2006 Revised
4. Industry
Page 4-9
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No-Action Baseline HFC-23 Emissions
from HCFC-22 Production
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
77
84
96
120
118
149
138
Gg HFC-23
7
7
8
10
10
13
12
As shown above, global HFC-23 emissions from HCFC-22 production grew by 24 percent between 1990
and 2000, driven by an over 60 percent growth in global HCFC-22 production during that period.
(Emissions grew more slowly than production due to the implementation of thermal destruction and
process optimization in Europe and the U.S.)
Under the No-Action Baseline, between 2000 and 2015, world HFC-23 emissions from HCFC-22
production are expected to grow by an additional 56 percent, but between 2015 and 2020 emissions are
expected to decline as a result of the phaseout of non-feedstock HCFC-22 production in developing
countries.
Exhibit 4-6 reveals a striking shift of the majority of emissions from OECD countries to China and other
developing countries. This is due to (1) a combination of increased use of emission controls and the
phaseout of HCFC-22 under the Montreal Protocol in OECD countries and (2) increased HCFC-22
production in China. (These drivers are discussed further below.) Thus, while HFC-23 emissions from
developed countries are expected to decline by over 60 percent from 1990 to 2020 in the No-Action
Baseline, HFC-23 emissions in the China/CPA region are expected to increase dramatically. S&E Asia
and Latin America are also projected to show increasing emissions through this period. In 1990, the
three largest emitters for this source were the U.S., Japan, and France, which together accounted for
over two-thirds of all emissions. In 2020, the three largest emitters are projected to be China, India, and
the U.S. These nations are anticipated to account for 90 percent of all HFC-23 emissions, while China
alone is expected to be the world's major HFC-23 emitter, accounting for over 65 percent of total
emissions.
160 n
1990
2015
2020
m China/CPA
[D Africa
SEAsia
CD Non-EU FSU
D Latin America
D OECD90 & EU
Exhibit 4-6. HFC-23 Emissions as a Byproduct of HCFC-22 Production Based on a No-Action
Baseline 1990 - 2020 (MtCO2eq)
June 2006 Revised
4. Industry
Page 4-10
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In the developed world, HFC-23 emissions decreased between 1990 and 2000 due to process
optimization and thermal destruction, although there were increased emissions in the intervening years.
The U.S. and the European Union (EU) drove these trends in the developed world. Although emissions
increased in the EU between 1990 and 1995 due to increased production of HCFC-22, a combination of
process optimization and thermal oxidation led to a sharp decline in EU emissions after 1995, resulting in
a net decrease in emissions of 67 percent for this region between 1990 and 2000. U.S. emissions also
declined by 15 percent during the same period, despite a 35 percent increase in HCFC-22 production;
however, during that time period U.S. emissions demonstrate two distinct trends. Between 1990 and
1995, U.S. emissions declined by 23 percent due to a steady decline in the emission rate of HFC-23 (i.e.,
the amount of HFC-23 emitted per kilogram of HCFC-22 manufactured). Between 1995 and 2000, U.S.
emissions increased due to increases in HCFC-22 production.4
As illustrated in Exhibit 4-6 under the No-Action Baseline, HFC-23 emissions in developed countries are
predicted to continue to decrease through 2020 as a result of (1) Japan's implementation of either thermal
abatement or HFC-23 capture (for use) for 100% of its production beginning in 2005 (JICOP, 2006),
(2) 100% implementation of thermal abatement in all EU countries except Spain by 2010, (3) closure of
the HCFC-22 production plant in Greece in 2006 and (4) the HCFC-22 production phaseout scheduled
under the Montreal Protocol.
In the developing world, particularly China, emissions are increasing quickly due to a rapid increase in the
production of HCFC-22. This production is meeting growing demand for unitary air conditioning, for
commercial refrigeration, and for substitutes for chlorofluorocarbons, which are currently being phased
out in developing countries under the Montreal Protocol (UNEP, 2003). Under the No-Action Baseline,
the increase in HFC-23 emissions is expected to continue through 2015, when HCFC-22 itself will begin
to be phased out by developing countries for most end uses under the Montreal Protocol.
Technology-Adoption Baseline
The table below presents Technology-Adoption Baseline emissions of HFC-23 from HCFC-22 production.
Technology-Adoption Baseline HFC-23 Emissions
from HCFC-22 Production
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
77
84
96
102
45
78
66
Gg HFC-23
7
7
8
9
4
7
6
As shown in the table above, global HFC-23 emissions from HCFC-22 production are expected to decline
by 31 percent between 2000 and 2020. These trends are mainly a result of the expected implementation
of Clean Development Mechanism (COM) projects in China, India, Korea, and Mexico, as well as
implementation of thermal oxidation in Spain and the HCFC-22 production phaseout scheduled under the
Montreal Protocol.
However, as seen in Exhibit 4-7, the most striking trend apparent in the Technology-Adoption Baseline is
the dramatic decline in emissions from China (and thus for the world, since by 2005 China accounts for
the majority of emissions) between 2005 and 2010, followed by an increase in emissions from 2010 to
2015, at which point emissions again decline. The primary driver of this zig zag pattern is the
implementation of COM projects in China. However, despite the constant abatement of HFC-23
emissions as a result of the implementation of the COM projects, HFC-23 emissions continue to increase
beyond 2010 as a result of the increase in production of HCFC-22 in China (as discussed under the No-
4The apparent increase in U.S. emissions between 2000 and 2005 is an artifact of the method used to estimate U.S. emissions in
the No-Action baseline. Under this approach, the U.S. emission factor was assumed to revert to its relatively high 1990 level in
2005, despite reductions in earlier years.
June 2006 Revised 4. Industry Page 4-11
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Action Baseline). The increase in HFC-23 emissions is expected to continue through 2015, when
HCFC-22 itself will begin to be phased out by developing countries for most end uses under the Montreal
Protocol.
120 n
1990
1995
2015
2020
m China/CPA
[Q Africa
SEAsia
ED Non-EU FSU
D Latin America
D OECD90 & EU
Exhibit 4-7. HFC-23 Emissions as a Byproduct of HCFC-22 Production Based on a Technology-
Adoption Baseline 1990 - 2020 (MtCO2eq)
Emissions in OECD countries are expected to decline by 86 percent between 1995 and 2015. As
Exhibit 4-7 reveals, the majority of these emissions shift to China and other developing countries. This is
due to (1) a combination of increased use of emission controls and the phase-out of HCFC-22 under the
Montreal Protocol in OECD countries and (2) increased HCFC-22 production in China. Thus, while HFC-
23 emissions from developed countries are expected to decline by 85 percent from 1990 to 2020, HFC-23
emissions in the China/CPA region are expected to increase dramatically, despite the adoption of
abatement measures under the COM. S&E Asia and Latin America are also projected to show increasing
emissions through this period.
Global emissions in years 1990 to 2000 follow the same trends as in the No-Action Baseline. As
illustrated in Exhibit 4-7, HFC-23 emissions in developed countries are predicted to decrease to lower
levels than the No-Action Baseline during the period from 2010 to 2020 mainly as a result of the U.S.'s
implementation of thermal abatement.
June 2006 Revised
4. Industry
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4.5 Operation of Electric Power Systems (Sulfur Hexafluoride)
4.5.1 Source Description
Sulfur hexafluoride (SF6) is a colorless, odorless, non-toxic, and non-flammable gas with a GWP that is
23,900 times that of carbon dioxide over a 100-year time horizon, and an atmospheric lifetime of 3,200
years (U.S. EPA, 2005). SF6 is used as both an arc quenching and insulating medium in electrical
transmission and distribution equipment. Several factors affect SF6 emissions from electrical equipment,
including the type and age of SF6-containing equipment, and the handling and maintenance protocols
used by electric utilities. Historically, approximately 20 percent of total global SF6 sales have gone to
electric power systems, where the SF6 is believed to have been used primarily to replace emitted SF6.
Approximately 60 percent of global sales have gone to manufacturers of electrical equipment, where the
SF6 is believed to have been mostly banked in new equipment (Smythe, 2004).
SF6 emissions from electrical equipment used in transmission and distribution systems occur through
leakage and handling losses. Leakage losses can occur at gasket seals, flanges, and threaded fittings,
and are generally larger in older equipment. Handling emissions occur when equipment is opened for
servicing, SF6 gas analysis, or disposal. Baseline emission estimates under both a Technology-Adoption
and a No-Action Baseline are presented below.
4.5.2 Source Results
Total SF6 Emissions from Electric Power Systems
Year
1990
1995
2000
2005
2010
2015
2020
Technology-Adoption
MtCO2eq
42
34
27
43
47
52
57
GgSF6
1.8
1.4
1.1
1.8
2.0
2.2
2.4
Year
1990
1995
2000
2005
2010
2015
2020
No-Action
MtCO2eq
42
34
27
47
52
59
66
GgSF6
1.8
1.4
1.1
1.9
2.2
2.5
2.8
Technology-Adoption Baseline
As shown above, global emissions from electric power systems are believed to have fallen significantly
between 1990 and 1995, based on SF6 sales to utilities and estimated equipment retirements.5 This
decline was due to a significant increase in the cost of SF6 gas in the mid-1990s, which motivated electric
utilities to implement better management practices to reduce their use of SF6. However, sales of SF6
increased by over 37 percent between 2000 and 2003, reversing the trend (Smythe, 2004). In addition,
equipment retirements (based on a 40-year equipment lifetime) are estimated to have more than doubled
between 2000 and 2003. Together, these two trends result in an estimated 55 percent increase in global
emissions between 2000 and 2003, resulting in emissions levels similar to those observed in 1990.
These global trends are reflected in the trends of the individual regions except for the U.S., the EU-25+3,6
and Japan. For the U.S., emission estimates for 1990-2003 are taken from Vne Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2003 (U.S. EPA, 2005). For the EU-25+3, Reductions of
SF6 Emissions from High and Medium Voltage Electrical Equipment in Europe (Ecofys, 2005) is the
source of emission estimates for 1990 through 2020. For Japan, Recent Practice for Huge Reduction of
SF6 Gas Emission from GIS&GCB in Japan (Yokota et al., 2005), as well as personal communications
5 The relationship between emissions, SF6 sales to utilities, and equipment retirements is discussed in detail in Section 7,
Methodology.
6 The EU-25+3 includes the 25 member countries of the European Union (EU) and Norway, Switzerland, and Iceland. Appendix I
contains a complete list of EU countries.
June 2006 Revised 4. Industry Page 4-13
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with T. Yokota (2006) provided emission estimates for 1990 through 2010. These studies show declining
emissions in these regions through 2003.
As illustrated in Exhibit 4-8, beyond 2005, emissions in developed countries are expected either to remain
steady or to decline. Emissions in Non-EU Eastern Europe and Non-EU FSU are expected to remain
relatively constant through 2020. Since the electric grids in these countries are mature and well
developed, it is assumed that there will be no additional growth of emissions from their electric
transmission and distribution systems. Any system growth is expected to be offset by decreases in the
equipment's average SF6 capacity and emission rate as new, small, leak-tight equipment gradually
replaces old, large, leaky equipment. In the U.S., the EU-25+3, and Japan, emissions are expected to
continue to decline as utilities, through government-sponsored voluntary and mandatory programs,
implement reduction measures such as leak detection and repair and gas recycling practices.
In contrast, emissions from developing countries (i.e., Latin America, S&E Asia, Middle East, Africa and
China/CPA) are expected to continue growing over the next 15 years. In these countries, it is assumed
that SF6-containing equipment has been installed relatively recently, and that all equipment is new.
Consequently, as infrastructure expands to meet the demands of growing populations and economies,
emissions are estimated to grow at a rate proportional to country- or region-specific net electricity
consumption (EIA, 2002). This growth drives global emissions growth, resulting in world-wide emissions
of 57 MtCO2eq in 2020. By 2020, Latin America, S&E Asia, Middle East, Africa and China/CPA are
expected to account for 63 percent of total emissions, versus approximately 10 percent in 1990. The
OECD is projected to account for only 29 percent of global emissions in 2020, versus approximately 82
percent in 1990.
70 n
1990
2015
2020
D OECD90 & EU
0 Non-EU Eastern Europe
D] Africa
m China/CPA
D Latin America
D Mddle East
SEAsia
ED Non-EU FSU
Exhibit 4-8. SF6 Emissions from Electric Power Systems Based on a Technology-Adoption
Baseline 1990 - 2020 (MtCO2eq)
No-Action Baseline
As illustrated in Exhibit 4-9, No-Action Baseline emissions for the period 1990 through 2000 follow the
same trajectory as those under the Technology-Adoption Baseline, with both baselines diverging after
2003. Assumptions and emissions estimates for developing regions (i.e., Latin America, S&E Asia,
Middle East, Africa, and China/CPA) are the same as discussed under the Technology-Adoption
Baseline. For the U.S., Japan, and the EU-25+3, it is assumed that no additional voluntary measures are
adopted after 2003. For the U.S., the EU-25+3, and Japan, emissions are expected to increase from
2003 levels, with system growth being the driver in the EU and Japan. The marked increase in U.S.
emissions after 2000 is an artifact of the method used to estimate U.S. emissions in the No-Action
June 2006 Revised
4. Industry
Page 4-14
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Baseline. Under this approach, the U.S. emission factor was assumed to revert to its relatively high 1999
level in 2005, despite reductions in earlier years.
The assumption that the U.S., the EU-25+3, and Japan will pursue no additional voluntary measures after
2003 increases their contribution to world emissions in 2020. Unlike the Technology-Adoption Baseline,
in which the OECD accounts for only 29 percent of emissions in 2020, in the No-Action Baseline, OECD
accounts for 38 percent. In contrast, the contribution of developing regions, of Latin America, S&E Asia,
Middle East, Africa, and China/CPA decrease to 55 percent of total 2020 emissions in the No-Action
Baseline, versus 63 percent under the Technology-Adoption Baseline.
1990
1995
2015
2020
D OECD90 & EU m China/CPA
0 Non-EU Eastern Europe n Latin America
m Africa D IVlddle East
SEPsia
0 Non-EU FSU
Exhibit 4-9. SF6 Emissions from Electric Power Systems Based on a No-Action Baseline
1990 - 2020 (MtCO2eq)
4.6 Primary Aluminum Production (Perfluorocarbons)
4.6.1 Source Description
The primary aluminum production industry is currently the largest source of RFC emissions globally.
During the aluminum smelting process, when the alumina ore content of the electrolytic bath falls below
critical levels required for electrolysis, rapid voltage increases occur. These are termed "anode effects"
(AEs). Anode effects produce CF4 and C2F6 emissions when carbon from the anode and fluorine from the
dissociated molten cryolite bath combine. In general, the magnitude of emissions fora given level of
production depends on the frequency and duration of these anode effects; the more frequent and long-
lasting the anode effects, the greater the emissions.
June 2006 Revised
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4.6.2 Source Results
Total PFC Emissions from Aluminum Production
(MtCO2eq)
Year
1990
1995
2000
2005
2010
2015
2020
Technology-
Adoption
98
61
58
43
39
42
45
No-Action
98
61
58
66
70
73
77
Technology-Adoption Baseline
Under the Technology-Adoption Baseline, it is assumed that aluminum producers will continue to
introduce technologies and practices aimed at reducing PFC emissions. It is assumed that under the
Technology-Adoption Baseline, global aluminum producers, in accordance with International Aluminum
Institute (IAI) PFC emission reduction commitments will reduce their PFC emission intensity (i.e., PFC
emissions per ton of produced aluminum) by 80 percent from 1990 levels by 2010. This reduction can be
achieved by retrofitting smelters with emission-reducing technologies such as computer control systems
and point feeding systems, by shifting production to Point-Feed Prebake (PFPB) technology, and by
adopting management and work practices aimed at reducing PFC emissions.
Five different electrolytic cell types are used to produce aluminum: Vertical Stud Soderberg (VSS),
Horizontal Stud Soderberg (HSS), Side-Worked Prebake (SWPB), Center-Worked Prebake (CWPB), and
Point Feed Prebake (PFPB), which is considered the most technologically-advanced process to produce
aluminum. Although PFPB systems can be improved through the implementation of management and
work practices, as well as improved control software, the analysis assumes that retrofit abatement options
will only occur on existing VSS, HSS, SWPB, and CWPB cells.
Exhibit 4-10 presents total PFC emissions from aluminum production under the Technology-Adoption
Baseline from 1990 to 2020. Between 1990 and 1995, global emissions declined from 98 to 61 MtCC^eq.
This significant decline was the result of voluntary measures undertaken by global smelters to reduce
their AE minutes per cell day. These measures included incremental improvements in smelter
technologies and practices, and a shift in the share of SWPB-related production to more state-of-the-art
PFPB facilities. Although a continuation of this AE minute reduction trend occurred through 2000,
emission reductions were offset by a 24 percent increase in global aluminum production between 1995
and 2000.
The declining global emission levels through 2010 reflect the successful adoption of IAI emission
reduction goals through both retrofits and a continued shift of production from VSS, HSS, and SWPB to
PFPB. From 2010 to 2020, the emissions intensity is assumed to remain constant; consequently,
emissions will be driven by increasing aluminum production. PFC emissions in OECD, as well as Non-EU
Eastern Europe, Non-EU FSU, China/CPA, and S&E Asia are projected to remain relatively constant from
2010 to 2020, due to slowing aluminum production growth. Trends in the U.S. and the EU reflect overall
trends in the developed (OECD) countries. Africa, Latin America, and the Middle East are projected to
increase their share of global emissions from 2010 to 2020, due to strong growth in aluminum production.
In 2020, China/CPA, Latin America, Africa, and the Middle East are collectively expected to account for
50 percent of global emissions. In comparison, OECD is projected to account for 36 percent of global
emissions, down from 51 percent in 2000.
June 2006 Revised 4. Industry Page 4-16
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1990
1995
2015
2020
D OECD90 & EU
El Non-EU FSU
SE Asia
m China/CPA
n Africa
D Middle East
E3 Non-EU Eastern Europe
D Latin America
Exhibit 4-10. PFC Emissions from Aluminum Production Based on a Technology-Adoption
Baseline 1990 - 2020 (MtCO2eq)
No-Action Baseline
Under the No-Action Baseline, it is assumed that aluminum producers will take no retrofit actions to
reduce their emissions below the levels of the late 1990s; as a result, emission projections do not reflect
anticipated technology adoptions and/or the implementation of improved work and management practices
to reduce emissions. Exhibit 4-11 presents total PFC emissions from aluminum production under the No-
Action Baseline from 1990 to 2020. The trends from 1990 through 2000 are the same as those in the
Technology-Adoption Baseline. From 2000 through 2020, no additional abatement retrofits are assumed
to occur; however, as in the Technology-Adoption Baseline, it is assumed that the global historical trend
in the shift of production from SWPB to PFPB continues (IAI, 2000; IAI, 2005). Based on these
assumptions, global emissions under this scenario rise to 77 MtCO2eq in 2020, a 33 percent increase
over 2000 levels. This is primarily driven by increasing global aluminum production.
In 1990, OECD emissions accounted for approximately 60 percent of global emissions; however, by
2020, this share is reduced to 40 percent in this scenario. This reduction is the result of relatively flat
aluminum production levels between 2000 and 2020, as cheaper aluminum from developing countries
enters the global marketplace. The primary sources of this cheaper aluminum are China/CPA, the Middle
East, Latin America and Africa, which in 2020 are projected to have production levels approximately
200 percent greater than their 2000 levels. In 2020, China/CPA is projected to account for 17.5 percent
of global emissions, compared to 3 percent in 1990 and 9 percent in 2000.
The EU and the U.S. reflect the general OECD trend, except that between 2000 and 2005 there is an
increase in U.S. emissions and a decrease in EU emissions. The decrease in EU emissions is primarily
the result of their transition from SWPB to PFPB technology. The increase in U.S. emissions is an artifact
of the baseline calculation methodology. Past U.S. emissions reflect reductions already implemented by
members of EPA's Voluntary Aluminum Industrial Partnership (VAIP), but under this scenario, future U.S.
emissions (from 2005 forward) are projected to occur at a higher rate.
June 2006 Revised
4. Industry
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1990
2015
2020
D OECD90 & EU
ED Non-EU FSU
SEAsia
§ China/CPA
m Africa
D Middle East
EJ Non-EU Eastern Europe
D Latin America
Exhibit 4-11. PFC Emissions from Aluminum Production Based on a No-Action Baseline
1990 - 2020 (MtCO2eq)
4.7 Manufacture of Semiconductors (Hydrofluorocarbons,
Perfluorocarbons, Sulfur Hexafluoride)
4.7.1 Source Description
The semiconductor industry currently uses several fluorinated compounds (CF4, C2F6, C3F8, C4F8, HFC-
23, NF3 and SF6) during the fabrication process.7 A fraction of each of these gases is emitted during two
manufacturing steps: (1) the plasma etching of thin films, and (2) the cleaning of chemical-vapor-
deposition chambers. In addition, byproduct emissions of CF4 also result when a fraction of the heavier
gases consumed is converted during the manufacturing process. Total PFC emissions from this source
vary by process and device type.8 Estimates of historical and forecasted semiconductor manufacturing
PFC emissions 1990 through 2020 under two different scenarios are presented below.
7 The chemical compound CHF3 is more commonly referred to as HFC-23; thus, the latter term is used here.
8 Note that while the term PFC (strictly referring to only perfluorocarbon compounds) does not include all of the fluorinated
compounds emitted from this source, the semiconductor industry commonly refers to the mix of fluorinated compounds as PFCs;
this report adopts the same convention.
June 2006 Revised
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4.7.2 Source Results
Total HFC, RFC, SF6 Emissions from Manufacture
of Semiconductors
(MtCO2eq)
Year
1990
1995
2000
2005
2010
2015
2020
Technology-
Adoption
10
15
27
30
37
32
28
No-Action
10
15
27
48
99
147
232
Technology-Adoption Baseline
The Technology-Adoption Baseline incorporates those reductions that have resulted or are anticipated to
result from international voluntary climate commitments. In April 1999, the semiconductor manufacturing
industry set an aggressive target to reduce RFC emissions. The World Semiconductor Council (WSC)
then agreed to reduce RFC emissions to 10 percent below 1995 levels by the year 2010. Since WSC
members then accounted for production of over 90 percent of the world's semiconductors, the goal is
expected to have dramatic effects in decreasing emissions overtime, widening the gap between emission
forecasts shown under the two scenarios presented in Exhibit 4-12 and Exhibit 4-14 (note that the scales
are different in the two graphs).
The OECD and Asia (including China/CPA and S&E Asia) regions are expected to account for the vast
majority of production, and therefore emissions, throughout the study period. The highest-emitting
countries worldwide in 2000 were Japan, the U.S., Taiwan, South Korea, and Russia. By 2010, and
through 2020, the highest emitting country worldwide is expected to be China, followed by the U.S.,
Japan, South Korea, Singapore,9 and Malaysia. The appearance of China, Singapore, and Malaysia
among the top emitting countries reflects a geographic shift in production such that the majority of future
growth takes place in these countries. This reflects an industry trend toward outsourcing production to
dedicated manufacturing firms, called foundries, concentrated in these countries.
Global emissions are estimated to have grown at a compound annual growth rate of 11 percent per year
through the year 2000. Following the introduction of voluntary commitments and resulting mitigation
efforts, however, a noticeable shift in direction is expected to occur under the Technology-Adoption
Baseline. As shown in Exhibit 4-12, the overall trend in OECD emissions is reflected in the emissions
from the U.S., the EU, and Japan. WSC members, representing most manufacturing in these regions,
are expected to achieve their stated emission reduction goal by 2010. In the long run, even countries
whose manufacturers have not adopted the WSC goal, such as China and other Asian countries not part
of the WSC, are expected to reduce their emission rates as new, lower-emitting manufacturing equipment
saturates the global market in response to demand from WSC members. This expectation accounts for
the reduction in emissions from China and S&E Asia between 2010 and 2020.
9 This reflects the top emitting countries in 2020, in descending order of emissions; in 2010, Singapore has greater emissions than
South Korea.
June 2006 Revised 4. Industry Page 4-19
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1990
2015
2020
D OECD90 & EU
El Non-EU FSU
SE Asia m China/CPA n Middle East
d Africa n Latin America
Exhibit 4-12. PFC Emissions from Semiconductor Manufacturing Based on a Technology-
Adoption Baseline 1990 - 2020 (MtCO2eq)
2015
2020
Exhibit 4-13. WSC and non-WSC Countries' Contribution to Global PFC Emissions (MtCO2eq)
Exhibit 4-13, which shows the relative distribution of global emissions under the Technology-Adoption
Baseline between WSC and non-WSC members, illustrates these trends even more clearly. Note that
emissions from WSC countries peak in 2000.
No-Action Baseline
The No-Action Baseline estimates emissions that would result from normal industry activity with no
emission control measures, voluntary or regulation-driven. This trajectory can be considered an upper
bound, and can serve as a reference level to which the alternative Technology-Adoption Baseline
emissions can be compared. The difference between these two emission sets represents the emission
June 2006 Revised
4. Industry
Page 4-20
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reductions achieved by semiconductor manufacturers as they implement emission control technologies or
other mitigation measures.
250 n
1990
1995
2000
2005
Year
2010
2015
2020
D OECD90 & EU
D Latin America
SEAsia
D Mddle East
m China/CPA
m Africa
E3 Non-EU FSU
Exhibit 4-14. PFC Emissions from Semiconductor Manufacturing Based on a No-Action Baseline
1990 - 2020 (MtCO2eq)
Exhibit 4-14 shows the relative distribution of global emissions under the No-Action Baseline. As in the
Technology-Adoption Baseline, the OECD and Asia regions are expected to remain the largest emitters
throughout the time horizon studied; emissions from these regions (including OECD, China/CPA, and
S&E Asia) combined are expected to comprise 98 percent of global emissions in 2020.
Historical trends are the same as those presented for the Technology-Adoption Baseline, including the
11 percent per year annual growth through 2000. However, in the No-Action Baseline, this high annual
growth continues virtually unabated through 2010 and is particularly pronounced in Asia beyond 2010. In
these countries, most notably China, Singapore, and Malaysia, semiconductor manufacturing is expected
to increase significantly, as discussed above in the Technology-Adoption Baseline, contributing to higher
emissions over the study period. Beyond 2010, the growth rate is assumed to decline by one half,
reflecting slower growth in demand for semiconductors. Nevertheless, global emissions continue to climb
substantially, reaching 232 MtCO2eq by 2020.
4.8 Magnesium Manufacturing (Sulfur Hexafluoride)
4.8.1 Source Description
The magnesium metal production and casting industry uses sulfur hexafluoride (SF6) as a cover gas to
prevent the violent oxidation of molten magnesium in the presence of air. The industry originally adopted
SF6 to replace sulfur dioxide (SO2) as the primary cover gas. Although recent studies indicate some
destruction of SF6 in its use as a cover gas (Bartos et al., 2003), this analysis follows current IPCC
guidelines (IPCC, 2000), which assume that all SF6 used is emitted to the atmosphere. Fugitive SF6
emissions occur primarily during three magnesium manufacturing processes: primary production, die-
casting, and recycling-based production. Additional processes that may use SF6 include sand and gravity
casting; however, these are believed to be minor sources and are not included in the analysis. Baseline
emission estimates under both a Technology-Adoption and a No-Action Baseline are presented below.
June 2006 Revised
4. Industry
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4.8.2 Source Results
Total SF6 Emissions from Magnesium Manufacturing
Year
1990
1995
2000
2005
2010
2015
2020
Technology-Adoption
MtCO2eq
12
12
9
7
4
3
5
GgSF6
0.5
0.5
0.4
0.3
0.1
0.1
0.2
Year
1990
1995
2000
2005
2010
2015
2020
No-Action
MtCO2eq
12
12
9
9
12
15
18
GgSF6
0.5
0.5
0.4
0.4
0.5
0.6
0.8
Technology-Adoption Baseline
Under the Technology-Adoption Baseline, it is assumed that magnesium producers and processors
outside of China will introduce technologies and practices aimed at reducing SF6 emissions. Specific
technologies include alternative cover gases, such as Novec 612 (a proprietary fluoroketone produced
by 3M) and HFC-134a, and better containment and pollution control systems, which enable the use of
SO2 without the toxicity and odor problems of the past. Under this scenario, International Magnesium
Association (IMA) members, who account for 80 percent of the global magnesium industry outside of
China (DOE, 2003) meet a target of eliminating the use of SF6 by 2011.
Exhibit 4-15 presents total SF6 emissions from the magnesium industry under the Technology-Adoption
Baseline from 1990 to 2020. As shown in the graph, total emissions from the magnesium industry
remained fairly constant through the mid 1990s, but fall sharply to 9 MtCC^eq in 2000. The drop in global
emissions between 1995 and 2000 is the result of both facility closures in the U.S. and global reductions
in SF6 usage through more efficient operational practices. The latter is a response to increasing SF6 gas
prices during the middle 1990s. Additional plant closings have been reported in Norway, Canada, and
Japan, adding to the decline in the OECD's share of global emissions through 2020. This lost production
has been primarily absorbed by China, which has dominated the foreign market with low-cost exports.
From 2000 through 2010, the steep decline in global SF6 emissions is attributable to the adoption of
alternative cover gases; either SO2 or Novec 612 and HFC-134a. By 2011, in accordance with the IMA
goal, all countries except China and the U.S. are assumed to have eliminated the use of SF6 from
magnesium production and casting operations.
For China, it is assumed that some primary production and all casting facilities will use SF6 to produce
high quality magnesium and products for the world market. Because Chinese producers and processors
are not IMA members and have not committed to the IMA emission reduction goal, their SF6 use is
assumed to continue through 2020. Consequently, from 2010 through 2020, the increase in global
emissions from 4 to 5 MtCO2eq will be driven entirely by China, whose emissions are expected to
increase from 2 to 4 MtCO2eq. In 2020, the China/CPA share of global emissions is expected to be
77 percent, compared to 0.3 percent in 1990. OECD's share of global emissions is projected to decrease
from 77 percent in 1990 to 21 percent in 2020, due to adoption of the IMA goal and reduction in
production capacity. In 2020, U.S. emissions account for a majority of OECD emissions. These
emissions are due to U.S. casting and recycling firms that have not committed to phase out use of SF6
(U.S., EPA, 2005).
June 2006 Revised 4. Industry Page 4-22
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1990
1995
2000
2005
Year
2010
2015
2020
D OECD90 & EU
D IVlddle East
El Non-EU FSU
D Latin America
iChina/CPA
ISE Asia
Exhibit 4-15. SF6 Emissions from Magnesium Manufacturing Based on a Technology-Adoption
Baseline - 1990 through 2020 (MtCO2eq)
No-Action Baseline
Under the No-Action Baseline, magnesium producers and processors take no action to reduce their
emissions; as a result, emission projections do not reflect anticipated technology adoptions and/or
preventive maintenance steps taken to reduce emissions.
Exhibit 4-16 presents total SF6 emissions from magnesium production under the No-Action Baseline from
1990 to 2020. The trends from 1990 to 2000 are the same as those discussed in the Technology-
Adoption Baseline. From 2000 through 2020, global emissions in this scenario double to 18 MtCO^eq as
the industry experiences strong growth, particularly in the die casting and recycling segments.
China/CPA registers particularly significant emissions growth between 1990 and 2020, increasing its
global share of emissions from 0.3 percent in 1990 to approximately 21 percent in 2020. OECD,
emissions continue to drop between 2000 and 2005 because of facility closures in Canada stemming
from pricing pressure from Chinese imports. However, by 2020, OECD emissions are expected to return
to 1990 levels as production levels increase. Since global emissions increase by over 50 percent during
this period, this results in the OECD share of global emissions falling from 77 percent in 1990 to 53
percent in 2020.
June 2006 Revised
4. Industry
Page 4-23
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1990
1995
2000
2005
Year
2010
2015
2020
D OECD90 & EU
D Middle East
0 Non-EU FSU
D Latin America
I China/CPA
iSEAsia
Exhibit 4-16. SFe Emissions from Magnesium Manufacturing Based on a No-Action Baseline
1990 - 2020 (MtCO2eq)
Increasing Chinese primary production and die casting is being fueled by local and foreign investment,
which has driven the overall increase in China/CPA's share of global emissions. China's emissions
growth is driven by their die-casting and by the 10 percent of their primary production that is assumed to
use SF6 as the cover gas mechanism.
4.9 Other Non-Agricultural Sources (Methane and Nitrous Oxide)
4.9.1 Source Description
This category includes miscellaneous industrial emission sources which are generally small. The data
presented here include:
Methane from chemical production
Methane from iron and steel production
Methane from metal production
Methane from mineral products
Methane from petrochemical production
Methane from silicon carbide production
Nitrous oxide from metals production.
4.9.2 Source Results
Data presented below are for mainly from Annex I countries. These data are not fully comparable as
emissions were not calculated for all countries in these regions.
June 2006 Revised
4. Industry
Page 4-24
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Total Methane and Nitrous Oxide Emissions
from Other Industrial Non-Agricultural Activities
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
7
7
7
7
7
7
7
GgCH4
301
306
308
293
294
294
295
GgN20
3
3
3
3
3
3
3
June 2006 Revised 4. Industry Page 4-25
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5. Agriculture
5.1 Introduction
This section presents global methane and nitrous oxide emissions for 1990 to 2020 for the following
agricultural sources:
Agricultural soils (nitrous oxide)
Enteric fermentation (methane)
Rice cultivation (methane)
Manure management (methane and nitrous oxide)
Other agricultural sources, including:
> Savanna burning (methane and nitrous oxide)
> Field burning of agricultural residues (methane and nitrous oxide)
> Open burning from forest clearing (methane and nitrous oxide)
> Agricultural soils (methane)
The agricultural sector is the largest contributor (59 percent in 1990; 57 percent in 2020) to global
emissions of non-CO2 emissions. In 1990, the agricultural sector accounted for 5,223 MTCO2eq of GHG
emissions. The sector is dominated by nitrous oxide emissions from agricultural soils and methane from
enteric fermentation, which constitute 38 percent and 34 percent, respectively, of all agricultural
emissions in 1990, as illustrated in Exhibit 5-1. Emissions from agricultural soils are projected to increase
by more than 46 percent by 2020, with its share of the sector's total emissions growing to 40 percent.
Enteric fermentation emissions are expected to grow by 32 percent from 1990 to 2020, but its relative
share of agricultural emissions will remain approximately the same.
Methane emissions from rice cultivation, methane and nitrous oxide emissions from manure
management, and other smaller agricultural sources constitute the remaining non-CO2 emissions from
this sector. Although emissions from rice cultivation and manure management both are projected to grow
from 1990 to 2020, the expected growth is moderate compared to the larger sources. The emissions
from these and all other agricultural sources combined represent only 28 percent of total agricultural
emissions in both 1990 and 2020. Meanwhile, combined emissions from agricultural soils and enteric
fermentation are expected to contribute more than 72 percent of total agricultural emissions in 2020.
The key driver for this sector is agricultural production, which is expected to increase to meet the demand
of fast-growing population centers in China/CPA, S&E Asia, Latin America, and Africa. Increases in both
population and income in many areas of these regions will cause consumption of agricultural products to
rise quickly. Also, changes in diet preferences, such as an increase in per-capita meat consumption, are
expected to increase consumer demand for a variety of agricultural products. Increases in consumption
will be met by domestic production gains from increased yields, livestock herds, and agricultural acreage,
as well as imports from traditionally high-producing countries. Increased commercialization of production
in less developed regions is also expected to increase fertilizer usage and livestock production capacity.
June 2006 Revised 5. Agriculture Page 5-1
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8,000 -,
2020
D Agricultural Soils
O Other Agricultural
D Enteric Fermentation
Manure Management
DRice Cultivation
Exhibit 5-1. Total Emissions from the Agricultural Sector by Source (MtCO2eq)
5.2 Agricultural Soils (Nitrous Oxide)
5.2.1 Source Description
Nitrous oxide is produced naturally in soils through the microbial process of denitrification and nitrification.
A number of anthropogenic activities add nitrogen to the soils, thereby increasing the amount of nitrogen
available for nitrification and denitrification, and ultimately the amount of nitrous oxide emitted.
Anthropogenic activities may add nitrogen to the soils either directly or indirectly.
Direct additions of nitrogen occur from the following activities:
Various cropping practices, including: (1) application of fertilizers, (2) production of nitrogen-fixing
crops (e.g., beans, pulses, and alfalfa), (3) incorporation of crop residues into the soil, and (4)
cultivation of high organic content soils (histosols); and
Livestock waste management, including: (1) spreading of livestock wastes on cropland and
pasture, and (2) direct deposition of wastes by grazing livestock.
Indirect additions occur through volatilization and subsequent atmospheric deposition of ammonia and
oxides of nitrogen that originate from (a) the application of fertilizers and livestock wastes onto cropland
and pastureland, and (b) subsequent surface runoff and leaching of nitrogen from these same sources.
June 2006 Revised
5. Agriculture
Page 5-2
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5.2.2 Source Results
Total Nitrous Oxide Emissions
from Agricultural Soils
Year
MtCO2eq
GgN20
1990
1995
2000
2005
2010
2015
2020
2,001
2,023
2,146
2,299
2,482
2,696
2,937
6,455
6,525
6,922
7,418
8,005
8,696
9,474
3,500 -,
2015
2020
QOECD90& EU
D Africa
D Middle East
DChina/CPA
0Non-EU FSU
HNon-EU Eastern Europe
Q Latin America
USE Asia
Exhibit 5-2. Nitrous Oxide Emissions from Agricultural Soils 1990 - 2020 (MtCO2eq)
Emissions of nitrous oxide from agricultural soils are projected to increase by 47 percent from 1990 to
2020 (Exhibit 5-2). In 1990, four regions accounted for more than 80 percent of nitrous oxide from
agricultural soils: OECD, China/CPA, Latin America, and Africa. By 2020, OECD is expected to
contribute only 23 percent of emissions, compared to 32 percent in 1990. Over the same period,
China/CPA and S&E Asia are expected to experience growth rates of more than 50 percent, while Africa,
Latin America, and the Middle East are expected to experience growth rates of over 100 percent. These
regional increases are driven largely by projected emissions increases in China, Brazil, Argentina,
Nigeria, Bangladesh, India, and Iran. Only a handful of OECD countries are expected to show increased
emissions through 2020; prominent among these are the U.S., Canada, Turkey, New Zealand, Australia,
and Spain. The non-EU FSU is the only region expected to show a decrease in emissions between 1990
and 2020.
The primary factor for the increase in emissions illustrated in Exhibit 5-2 is the expected increase in crop
and livestock production, with expanded use of synthetic fertilizers, to meet the growing consumption
requirements of S&E Asia, China/CPA, Latin America, and Africa. Emission increases in these areas are
June 2006 Revised
5. Agriculture
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somewhat offset by declining or slower growth in developed countries (such as the EU and U.S.) due to
decreases in agricultural acreage, economic and environmental agricultural policies, and the changing
world market for goods. Due to the complexities of agricultural product markets and the influences of
disruptions in the industry (such as food safety issues), many of these factors are hard to predict. The
following paragraphs explain some of the relevant current developments that influence emissions.
Overall, the expected decrease in emissions for most of the OECD region, economic transitioning in
Eastern European countries of the OECD, and an expected modest increase in the emissions for the
U.S., result in a projected moderate rate of growth over the study period for the OECD. Many OECD
countries have little opportunity for expanding crop acreage for key crops (e.g., wheat, corn) and
therefore growth in production is in the form of yield growth, which tends to have less of an impact on
emissions growth than acreage increases. The market restructuring during the 1990s in Eastern Europe,
as well as in the non-EU FSU countries, resulted in an economic downturn in those countries. Because
of lower farm income, farmers purchased and used less fertilizer, a main driver for emissions from this
category. During the same period, EU farmers reduced their use of fertilizer in response to the Common
Agricultural Policy (CAP), which reduced market support prices to world prices while offsetting the
negative financial impact on farmers with direct payments. In the U.S., the 1990s were characterized by
increases in synthetic fertilizer usage, crop and forage production, and manure production. However, the
use of synthetic fertilizers is estimated to have peaked in the late 1990s and is expected to decrease in
the future. Offsetting this decreasing trend in emissions to some extent will be the expectation that OECD
countries will continue to be important agricultural exporters to the fast-growing regions of the developing
world.
In China/CPA, S&E Asia, Africa, and Latin America, the anticipated growth in agricultural soils emissions
has several causes. Increases in population as well as per-capita income, particularly in China, India,
and parts of Latin America, will increase the demand for agricultural products such as cereal grains, milk,
oilseed products, and meat. In addition, livestock operations are expected to become more advanced in
these areas, thereby increasing demand for high-quality feed crops (e.g., corn-based). While some of
this demand will be addressed in the short term through increases in imports, long term expansion of
domestic production capabilities is expected. The increased commercialization of the livestock industries
in these growing countries is also expected to increase livestock productive capacity and the production
of livestock manure, an important component of nitrous oxide emissions for this source category.
5.3 Enteric Fermentation (Methane)
5.3.1 Source Description
Normal digestive processes in animals result in methane emissions. Enteric fermentation refers to a
fermentation process whereby microbes in an animal's digestive system ferment food. Methane is
produced as a byproduct and can be exhaled by the animal.
Domesticated ruminants such as cattle, buffalo, sheep, goats, and camels account for the majority of
methane emissions in this sector. Other domesticated non-ruminants such as swine and horses also
produce methane as a byproduct of enteric fermentation, but emissions per animal species vary
significantly. Total emissions are driven by the size of livestock populations and the management
practices in use, particularly the feed regime used. The quantity, quality, and type of feed are significant
determinants of methane emissions. Feed intake varies by animal type, as well as by weight, age, and
growth patterns for individual animals.
June 2006 Revised 5. Agriculture Page 5-4
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5.3.2 Source Results
Total Methane Emissions
from Enteric Fermentation
Year
MtCO2eq
GgCH4
1990
1995
2000
2005
2010
2015
2020
1,772
1,804
1,799
1,929
2,079
2,204
2,344
84,388
85,909
85,648
91,851
99,002
104,963
111,633
2,500 -,
1990
1995
2000
2005
Year
2010
2015
2020
GOECD90&EU
D Africa
D Middle East
D Latin America
BChina/CPA
HNon-EU Eastern Europe
ESE Asia
ID Non-EU FSU
Exhibit 5-3. Methane Emissions from Enteric Fermentation 1990 - 2020 (MtCO2eq)
Global emissions from this source are projected to increase 32 percent by 2020. However, three regions
are projected to show declining emissions through 2020: OECD (-9 percent), non-EU FSU (-34 percent),
and non-EU Eastern Europe (-20 percent), as illustrated in Exhibit 5-3. The remaining regions are
expected to show significant increases in methane emissions over the same period: China (90 percent),
Latin America (43 percent), Africa (73 percent), S&E Asia (50 percent), and the Middle East (81 percent).
By 2020, Latin America is projected to be the largest contributor of methane emissions for this category,
followed closely by S&E Asia and the OECD. In 1990, the top five countries were China, Brazil, India, the
U.S., and Russia. These five nations accounted for 43 percent or 761 MtCO2eq of global methane
emissions from enteric fermentation in 1990. In 2020, the top five are expected to be China, Brazil, India,
the U.S., and Pakistan.
Historical trends in enteric emissions follow beef, dairy, or buffalo production cycles, since these animals
are responsible for the majority of the world enteric emissions. Despite recent setbacks in the beef
industry due to concerns about food safety, world projections for the period 2003 to 2013 show increases
in meat and dairy product consumption, production, and trade (FAPRI, 2004). A combination of
June 2006 Revised
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advancing domestic beef and dairy production capabilities in some key developing countries, combined
with the maintenance of relatively high levels of production (but not necessarily high productivity growth)
for large exporting countries, are expected to shape the emissions projections for this source.
In Latin America, Africa, India, and China, urban population growth and an increase in per capita income
are expected to lead to an increase in livestock product demand, domestic livestock populations, and thus
methane emissions. For example, it is estimated that over 44 percent of the increase in global milk
production in the next decade will occur in China and India (FAPRI, 2004). Also, the anticipated
transformation of management systems from dispersed, pasture operations to larger-sized,
commercialized production is expected to increase breeding herd productivity, animal size, and overall
meat production. Such transformations are occurring now throughout the developing world and will likely
increase emissions, particularly in Africa and Latin America.
In many developed countries, methane emissions from enteric fermentation are expected to decline by
2020. In the EU, where approximately two-thirds of all cows are dairy cows, the cattle population is
decreasing by approximately 2 percent per year due to milk quotas and increasing yields per animal. The
number of beef cows (as well as sheep and goats) is expected to remain stable and emissions are not
expected to increase in the EU after 2000. During the 1990s, the farm industries in Eastern European
countries and the non-EU FSU reduced their livestock production as part of their transition to market
economies; however this trend is expected to gradually reverse after 2000 as production increases to
meet growing demand. A slight decline in emissions is projected for the U.S. from 2000 to 2020, resulting
from increased production efficiencies, such as those occurring in the dairy industry, and the dampening
effect on export production between 2003 and 2005 due to bovine spongiform encephalopathy (BSE)
cases in the industry. Also, in many of the mature beef production industries, such as the U.S. and
Australia, there are normal cyclical population fluctuations from year to year that follow animal growing
cycles, and emissions will track these cycles.
5.4 Rice Cultivation (Methane)
5.4.1 Source Description
The anaerobic decomposition of organic matter in flooded rice fields produces methane. When fields are
flooded, aerobic decomposition of organic material gradually depletes the oxygen present in the soil and
flood water, causing anaerobic conditions in the soil to develop. Once the environment becomes
anaerobic, methane is produced through anaerobic decomposition of soil organic matter by
methanogenic bacteria. Several factors influence the amount of methane produced, including water
management practices and the quantity of organic material available to decompose.
5.4.2 Source Results
Total Methane Emissions
from Rice Cultivation
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
601
621
634
672
708
744
776
GgCH4
28,628
29,564
30,169
31,995
33,726
35,416
36,958
June 2006 Revised 5. Agriculture Page 5-6
-------
1990
1995
2000
2005
Year
2010
2015
2020
O China/CPA
DOECD90&EU
D Middle East
D SE Asia
H Latin America
gNon-EU Eastern Europe
E2 Africa
IDNon-EU FSU
Exhibit 5-4. Methane Emission from Rice Cultivation 1990 - 2020 (MtCO2eq)
The China/CPA and S&E Asian regions are the largest sources of methane emissions from rice
cultivation, accounting for nearly 90 percent of the emissions for this source in 1990, as illustrated in
Exhibit 5-4. The single largest contributors in these regions are China, India, Thailand, Indonesia,
Vietnam, and Myanmar, which together emit 78 percent of all emissions from rice cultivation. Emissions
from China/CPA are projected to increase 10 percent between 1990 and 2020, while S&E Asia's
emissions are expected to increase by 36 percent during the same period.
The projected increase in emissions from 1990 to 2020 is primarily attributed to increased demand for
rice due to expected population growth in rice consuming countries. Total global rice consumption is
expected to rise in the projection years; however, this increase is partially offset by projected decreases in
per-capita consumption over the next 10 years (FAPRI, 2004). Emissions growth has also been
tempered by innovations that increased rice production without increasing rice acreage-the most
important determinant of rice methane emissions. It is anticipated that yield growth, as opposed to
acreage growth, will continue to be the main source of the production growth, with the continued
development and adoption of higher-yielding rice varieties in many producing countries (FAPRI, 2004).
Thailand, Vietnam, and India are projected to dominate global rice exports through the 2005 to 2015
projection period, with an estimated 60 percent or greater share of the global export market. Continued
yield growth in Vietnam, and both yield and area growth in Myanmar, is expected to increase production
in those key rice-producing countries. China is expected to continue to be a significant contributor, but at
a lower rate of growth due to decreases in production area. (FAPRI, 2004)
5.5 Manure Management (Methane and Nitrous Oxide)
5.5.1 Source Description
Manure management produces methane and nitrous oxide. Methane is produced during the anaerobic
decomposition of manure, while nitrous oxide is produced by the nitrification and denitrification of the
organic nitrogen content in livestock manure and urine. Emissions from only the managed collection,
June 2006 Revised
5. Agriculture
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handling, storage, and treatment of manure are included here; emissions from the distribution of manure
on pastures, ranges, and paddocks are included with agricultural soils emissions and are discussed in
Section 5.2.
The quantity of methane emitted from manure management operations is a function of three primary
factors: the type of treatment or storage facility, the ambient climate, and the composition of the manure.
When manure is stored or treated in liquid systems such as lagoons, ponds or pits, anaerobic conditions
can often develop and the decomposition process results in methane emissions. Ambient temperature
and moisture content also affect methane formation, with higher ambient temperature and moisture
conditions favoring methane production. The composition of manure is directly related to animal types
and diets. For example, milk production in dairy cattle is associated with higher feed intake, and therefore
higher manure excretion rates than non-dairy cattle. Also, supplemental feeds with higher energy content
generally result in a higher potential for methane generation per unit of waste excreted than lower quality
pasture diets. However, some higher energy feeds are more digestible than lower quality forages, which
can result in less overall waste excreted. Ultimately, a combination of all these factors affects the actual
emissions from manure management systems.
Nitrous oxide generation is a function of the composition of the manure, the type of bacteria involved in
the decomposition process, and the oxygen and liquid content of manure. Nitrous oxide emissions occur
through the processes of nitrification and denitrification, where the manure is first treated aerobically
(nitrification) and then handled anaerobically (denitrification). Nitrous oxide generation is most likely to
occur in dry manure handling systems that can also create pockets of anaerobic conditions.
5.5.2 Source Results
Total Methane and Nitrous Oxide Emissions
from Manure Management
Year MtCO2eq Gg CH4 Gg N2O
1990
1995
2000
2005
2010
2015
2020
418
424
421
445
470
496
523
10,596
10,727
10,732
11,170
11,617
12,221
12,832
631
642
632
679
728
771
818
Global methane emissions from manure management are projected to increase by 21 percent between
1990 and 2020, with increasing emissions in all regions except the non-EU FSU countries, as illustrated
in Exhibit 5-5. Historically, methane emissions from manure management are largely from the OECD,
which account for nearly 55 percent of all emissions in 1990. The top emitting countries in 1990 are: the
U.S., Germany, India, China, France, Russia, Turkey, and Brazil. Emissions from the OECD, however,
are projected to increase by only 3 percent between 1990 and 2020. In contrast, the expected growth
rate is large and positive in several of the other regions during the same period: S&E Asia (53 percent),
China/CPA (89 percent), Latin America (51 percent), and Africa (66 percent).
June 2006 Revised 5. Agriculture Page 5-8
-------
O
300 -i
250 -
200 H
150 ^
g
1 100 1
LU
50 -
1990
1995
QOECD90&EU
DChina/CPA
D Middle East
2000
2005
Year
2010
2015
2020
D SE Asia
0 Latin America
BNon-EU Eastern Europe
BNon-EUFSU
m Africa
Exhibit 5-5. Methane Emissions from Manure Management 1990 - 2020 (MtCO2eq)
300 -i
1990
1995
2000
2005
Year
2010
2015
QOECD90&EU
DSE Asia
DNon-EU Eastern Europe
DChina/CPA
E3 Latin America
H Middle East
0Non-EUFSU
ID Africa
2020
Exhibit 5-6. Nitrous Oxide Emissions from Manure Management 1990 - 2020 (MtCO2eq)
June 2006 Revised
5. Agriculture
Page 5-9
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Nitrous oxide emissions from manure management, illustrated in Exhibit 5-6, also are expected to
increase globally, with a growth rate estimated at 30 percent between 1990 and 2020. Emissions are
dominated by three regions: OECD, China/CPA, and the non-EU FSU. The top 10 emitters by country in
1990 are China, Russia, the U.S., Japan, Ukraine, Poland, France, Brazil, Thailand, and Germany.
These 10 countries account for over 71 percent of the nitrous oxide emissions from manure management
in 1990. This ranking is projected to change little by 2020. It is also important to note that while the
1990-2020 emissions growth in most regions is either positive or stable, there was a substantial historical
decline in emissions for the non-EU FSU during the early 1990s due to the general decline in production
as a result of market restructuring.
The key factors influencing both methane and nitrous oxide emissions in this category are expected to be
the growth in livestock populations necessary to meet the expected worldwide demand for dairy and meat
products, and the trend toward larger, more commercialized livestock management operations. These
larger operations typically result in more liquid-based manure management systems that produce higher
methane emissions. All of the factors related to the increase in cattle and buffalo production described in
the enteric fermentation section are pertinent to manure management as well, since livestock population
increases will lead to increased manure production. However, poultry and swine are other livestock
categories that are particularly important for manure management emissions. Trends for these livestock
are described in the following paragraphs.
Poultry and swine can contribute significantly to manure management emissions. Expected increases in
worldwide poultry production, estimated to have the fastest rate of growth of all livestock types (over
26 percent) over the next decade (FAPRI, 2004), will in particular drive increases in nitrous oxide
emissions because of the relatively high nitrogen content of poultry waste and the management systems
used. China/CPA, S&E Asia, and Latin America (particularly Brazil and Argentina) all are expected to
strongly increase poultry production (generally over 2.6 percent for key producing countries) as industry
investments in these areas improve productivity and producers expand exporting capabilities. Continued
steady growth in traditionally large poultry producing and exporting countries, such as the U.S., also
contributes significantly to the projected increases in nitrous oxide emissions for this category.
Swine production can have a large influence on methane emissions. Continued transformation of the
pork industry from locally dispersed individual producers to larger commercialized operations in countries
such as China and Brazil is expected to increase both production and livestock population. In addition,
larger commercialized operations tend to utilize more liquid-based manure management systems, which
generate more methane emissions than smaller, individual feedlot operations. In the U.S., one of the
largest and most commercialized pork producing countries in the world, swine are responsible for almost
half of the methane emissions from manure management primarily because a large portion of the manure
is handled with liquid-based systems. As other key pork producing countries transform to larger
management systems, the trend will likely be toward increasing methane emissions.
5.6 Other Agricultural Sources (Methane and Nitrous Oxide)
5.6.1 Source Description
Methane and nitrous oxide are produced from the open burning of biomass during agricultural activities
and from land use change. The sources included in this section are savanna burning, agricultural residue
burning, and open burning from forest clearing1. This category also includes minor amounts of country-
reported emissions data on methane from agricultural soils. However, biomass burning constitutes the
majority of emissions for this source.
11990 and 1995 estimates for biomass burning were obtained from the Emission Database for Global Atmospheric Research
(EDGAR), Version 3.2 (Olivier and Berdowski, 2001; Olivier, 2002). Estimates for 2000 were obtained from the EDGAR 3.2 Fast
Track 2000 dataset (32FT2000) (Olivier, 2005).
June 2006 Revised 5. Agriculture Page 5-10
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5.6.2 Source Results
Total Methane and Nitrous Oxide Emissions
from Other Agricultural Activities
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
431
425
730
730
730
730
730
GgCH4
12,745
13,068
21,689
21,691
21,693
21,696
21,698
GgN20
526
487
886
885
885
885
885
Exhibits 5-7.1 and 5-7.2 graphically depict trends in methane and nitrous oxide emissions for this
category. Latin America, Africa, and S&E Asia are the largest emitters in this source category. These
three regions account for 91 percent of the nitrous oxide emissions and 85 percent of the methane
emissions in 1990. Projections for future years have been held constant at 2000 levels due to a lack of
information for projecting the variety of emissions within this category.
500 -i
450
1990
1995
2000
2005
Year
2010
2015
2020
D Africa
0SE Asia
ENpn-EUFSU
D Middle East
D Latin America
DOECD90&EU
IDChina/CPA
BNon-EU Eastern Europe
Exhibit 5-7.1. Methane Emissions from Other Agricultural Sources 1990- 2020 (MtCO2eq)
June 2006 Revised
5. Agriculture
Page 5-11
-------
300 -i
1995
2000
O Latin America
HSE Asia
HOECD90&EU
D Middle East
2005
Year
2010
2015
2020
D Africa
DChina/CPA
IDINon-EUFSU
BNon-EU Eastern Europe
Exhibit 5-7.2. Nitrous Oxide Emissions from Other Agricultural Sources 1990-2020 (MtCO2eq)
June 2006 Revised
5. Agriculture
Page 5-12
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6. Waste
6.1 Introduction
This section presents global methane and nitrous oxide emissions for 1990 to 2020 for the following
sources in the waste sector:
Landfilling of solid waste (methane)
Wastewate r (m eth a n e)
Human sewage (nitrous oxide)
Other non-agricultural sources (methane and nitrous oxide).
The "other non-agricultural" category contains minor emissions from miscellaneous waste generating
activities, waste combustion, and minor emissions from other sources not accounted for elsewhere in this
document.
The waste sector is the third largest contributor to global emissions of non-CO2 GHGs. The two largest
sources of non-CO2 GHG emissions within the waste sector are landfilling of solid waste and wastewater.
Although the sector as a whole accounts for only 15 percent of all non-CO2 GHG emissions, landfilling is
the fourth largest individual source of non-CO2 GHG emissions (761 MtCO2eq), following agricultural soils
(2,001 MtCO2eq), enteric fermentation (1,772 MtCO2eq), and natural gas and oil systems (993 MtCO2eq).
o
o
CO
co
E
LU
1990
1995
2000
2005
Year
2010
2015
2020
I Landfills
D Waste water
D Human Sewage
I Other Non-Agricultural
Exhibit 6-1. Total Emissions from the Waste Sector by Source (MtCO2eq)
June 2006 Revised
6. Waste
Page 6-1
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6.2 Landfilling of Solid Waste (Methane)
6.2.1 Source Description
Methane is produced and emitted from the anaerobic decomposition of organic material in landfills. The
major drivers of emissions are the amount of organic material deposited in landfills, the extent of
anaerobic decomposition, and the level of landfill methane collection and combustion (e.g., energy use or
flaring). The amount of waste deposited in landfills can be affected by waste-reduction and recycling
efforts. Because organic material deep within landfills takes many years to decompose completely, past
landfill disposal practices greatly influence present day emissions.
6.2.2 Source Results
The OECD countries emit nearly 49 percent of the global methane produced from the landfilling of solid
wastes in 1990, as shown in Exhibit 6-2. In the same year, the remaining regions each contribute less
than 15 percent of the methane emissions for this source category. Within the OECD, the U.S. is the
largest source of emissions from the landfilling of solid waste. In 1990, the U.S. emitted over
170 MtCO2eq of methane, which is almost 46 percent of the OECD total and 23 percent of the global
total.
Total Methane Emissions
from Landfilling of Solid Waste
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
761
770
730
747
761
788
817
GgCH4
36,257
36,653
34,777
35,589
36,220
37,527
38,898
Long-term projections show significant shifts in contributions to landfill emissions. The OECD is projected
to have an almost 31 percent decrease in emissions between 1990 and 2020, decreasing from
49 percent to 32 percent of the global emissions for this source. By 2020, three regions are projected to
hold more than a 10 percent share of the global emissions pool: Africa (16 percent), Latin America
(13 percent), and S&E Asia (14 percent). The factors behind these trends are described in the following
paragraphs.
Driving factors for landfill emission trends are growing populations, increases in personal incomes, and
expanding industrialization, all of which can lead to increases in the amount of solid waste generated fora
country. Countries with fast-growing economies and populations are expected to contribute more to the
global methane total from landfills as their economies grow and waste generation rates increase.
Countries with more steady-state economic growth, and small or even declining population growth rates,
are likely to experience minimal growth in landfill emissions. Waste reduction programs, as well as
methane recovery and use, will also impact the amount of methane that is actually released to the
atmosphere.
The decline in emissions from 1990 to 1995 in the OECD is largely due to non-climate regulatory
programs and the collection and flaring or use of landfill methane. In many OECD countries, landfill
methane emissions are not expected to grow, despite continued or even increased waste generation,
because of non-climate change related regulations that result in mitigation of air emissions, collection of
gas, or closure of facilities. A major driver in the OECD is the European Union Landfill Directive, which
limits the amount of organic matter that can enter solid waste facilities. Although organic matter is
expected to decrease rapidly in the EU, emissions occur as a result of total waste in place. Emissions will
have a gradual decline overtime.
June 2006 Revised 6. Waste Page 6-2
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In regions other than the OECD, an increase in methane emissions is projected. In these regions, solid
waste is expected to be increasingly diverted to managed landfills as a means of improving overall waste
management. The combined effects of rapid economic change, expansive growth policies, and
population increase, particularly in the urban centers of developing countries, will result in changing
consumption patterns and increases in waste generation. Per-capita waste generation rates can increase
by three or four times in the transition from a rural, low-income scenario to higher income urban-based
populations. Areas showing high growth in emissions between 1990 and 2020 (e.g., Africa at 77 percent
growth, S&E Asia at 34 percent, Latin America at 52 percent) are all undergoing such transformations.
A major limitation to this sector is the use of default emission factors. Many large developing countries
did not report emissions or used default parameters. This leads to some unusual trends such as the low
level of emissions in many Asian countries. The improvements in both method and default values in the
2006 IPCC Guidelines will help improve these estimates in the future.
1990
1995
2000
2005
Year
2010
2015
2020
EIOECD90&EU
D Latin America
H Middle East
D SE Asia
HNon-EUFSU
HNon-EU Eastern Europe
0 Africa
OIChina/CPA
Exhibit 6-2. Methane Emission from Landfilling of Solid Waste 1990 - 2020 (MtCO2eq)
6.3 Wastewater (Methane)
6.3.1 Source Description
Methane is emitted both incidentally and deliberately during the handling and treatment of municipal and
industrial wastewater. The organic material in the wastewater produces methane when it decomposes
anaerobically. Most developed countries rely on centralized aerobic wastewater treatment to handle their
municipal wastewater, so that methane emissions are small and incidental. However, in developing
country areas with little or no collection and treatment of wastewater, anaerobic systems such as latrines,
open sewers, or lagoons are more prevalent. Industrial wastewater can also be treated anaerobically,
with significant methane being emitted from those industries with high organic loadings in their
wastewater stream, such as food processing and pulp and paper facilities.
June 2006 Revised
6. Waste
Page 6-3
-------
Total Methane Emissions
from Wastewater
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
446
484
523
558
594
630
665
GgCH4
21,232
23,039
24,883
26,577
28,287
29,997
31,665
6.3.2 Source Results
In 1990, S&E Asia and China/CPA account for 57 percent (33 percent and 24 percent, respectively) of
global methane emissions due to wastewater handling. Three regions account for between 10-12 percent
each in 1990: Africa, OECD, and Latin America. The largest emitters by country in 1990 are China
(21 percent), India (18 percent), the U.S. (6 percent), and Indonesia (4 percent). In 2020, S&E Asia and
China/CPA are expected to obtain a 56 percent share of global emissions for this source in 2020.
Wastewater emissions are growing most rapidly in Africa and the Middle East. Wastewater methane in
Africa and the Middle East is expected to approximately double between 1995 and 2020.
The main driver for increasing municipal wastewater emissions is population growth, particularly growth
associated with countries that rely on less advanced, anaerobic treatment and collection systems such as
latrines, septic tanks, open sewers, and lagoons. Most developed countries have an extensive
infrastructure to collect and treat urban wastewater, in which the majority of systems rely on aerobic
treatment with minimal methane production and thus less effect on the emissions trend. In contrast, there
is widespread use of less advanced, anaerobic systems in some of the fastest growing parts of the world.
It is estimated that over 80 percent of domestic wastewater goes uncollected and untreated in large
portions of the China/CPA, S&E Asia, and Africa. For rural areas, the amount is likely to be even higher.
Much of this untreated wastewater is found in open sewers, pits, latrines, or lagoons where there is
potential for methane production. For example, nearly 75 percent of China's wastewater emissions come
from latrines, with the majority of wastewater generated in rural China being untreated. The largest share
of India's emissions also comes from latrines (62 percent), but open sewers contribute a sizable amount
as well (34 percent). Like India, most of Indonesia's emissions come from latrines and open sewers. As
long as populations grow significantly without large scale advances in wastewater treatment, these areas
will continue to have a major influence on the upward trend in wastewater methane emissions. The
impact of urban center growth in these regions, however, may offset this trend if migrating rural
populations are served by more advanced urban treatment systems.
Less advanced treatment systems are still widely used in some developed countries. In the U.S., for
example, septic tanks are responsible for 75 percent of the emissions, though only 25 percent of
treatment. Septic tanks are utilized in many parts of the developed world where centralized sewer
infrastructure is not available; however, their usage is not expected to increase significantly in the future
since there are economic and site considerations that limit their widespread applicability.
June 2006 Revised 6. Waste Page 6-4
-------
700 -i
600
1995
2000
2005
Year
2010
2015
2020
QSE Asia
D Latin America
Middle East
DChina/CPA
H Africa
HNon-EU Eastern Europe
BOECD90&EU
mNon-EUFSU
Exhibit 6-3. Methane Emission from Wastewater 1990- 2020 (MtCO2eq).
6.4 Human Sewage - Domestic Wastewater (Nitrous Oxide)
6.4.1 Source Description
Domestic and industrial wastewater are also a source of nitrous oxide emissions. Domestic wastewater
includes human waste as well as flows from shower drains, sink drains, washing machines and other
domestic effluent. Some industries produce wastewater with significant nitrogen loadings that is
discharged to the city sewer, where it mixes with domestic, commercial, and institutional wastewater. The
wastewater is transported by a collection system to an on-site, decentralized wastewater treatment
(WWT) system, or a centralized WWT system. Decentralized WWT systems are septic systems and
package plants. Centralized WWT systems may include a variety of processes, ranging from treatment in
a lagoon to advanced tertiary treatment technology for removing nutrients. After processing, treated
effluent may be discharged to a receiving water environment (e.g., river, lake, estuary) applied to soils, or
disposed of below the surface.
Nitrous oxide may be generated during both nitrification and denitrification of the nitrogen present in the
wastewater stream, usually in the form of urea, ammonia, and proteins. These are converted to nitrate
via nitrification, an aerobic process converting ammonia-nitrogen into nitrate (NO3-). Denitrification occurs
under anoxic conditions (without free oxygen), and involves the biological conversion of nitrate into
dinitrogen (N2). Nitrous oxide can be an intermediate product of both processes, but is more often
associated with denitrification.
Although several waste streams potentially lead to nitrous oxide emission, this section only covers human
sewage emissions unless reported emissions include additional sources.
June 2006 Revised
6. Waste
Page 6-5
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Total Nitrous Oxide Emissions
from Human Sewage
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
81
85
91
95
99
103
107
GgCH4
260
275
293
306
320
333
346
120 n
LU
1990
1995
2000
2005
Year
2010
2015
2020
DOECD90&EU
D Latin America
H Middle East
DChina/CPA
0 Africa
HNon-EU Eastern Europe
E2SE Asia
IHNon-EUFSU
Exhibit 6-4. Nitrous Oxide from Human Sewage 1990 - 2020 (MtCO2eq)
6.4.2 Source Results
In 1990, the OECD, China/CPA, and S&E Asian regions account for over 70 percent of the nitrous oxide
emissions from human sewage, as illustrated in Exhibit 6-4. Within these regions, the top countries are:
China, the U.S., Germany, and Indonesia. The U.S. accounts for nearly 50 percent of the OECD's
emissions. Overall, nitrous oxide emissions from human sewage are projected to increase by almost
33 percent by 2020. Although the same three regions are expected to continue to constitute
approximately 70 percent of the emissions, Africa is projected to grow by 86 percent and contribute over
11 percent of the emissions for this source in 2020. Emissions in several of the EU countries are
expected to decrease by 2020.
The main driver for human sewage emissions is population increase. Emissions may be linked to
treatment type (lagoons versus advanced treatment such as nitrification/denitrification plant), not enough
information is available to account for advanced treatment methods. The IPCC default methodology uses
June 2006 Revised
6. Waste
Page 6-6
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the same emission factor for all wastewater generated). Therefore, the total quantity of wastewater
generated, regardless of treatment type, is the principle factor.
In addition to population, rise in per-capita income tends to increase the amount of nitrogen available in
the wastewater generated due to increases in per-capita protein consumption. Milk and meat
consumption in developed countries can be more than five times higher than in developing countries.
However, per capita consumption of meat and dairy products rises fastest in countries where current
consumption levels are low, rapid urbanization is occurring, and incomes are growing rapidly from a low
base. Therefore, the long term trend of nitrous oxide emissions from human sewage will be largely
impacted by fast-growing economies such as China and India.
6.5 Other Non-Agricultural Sources (Methane and Nitrous Oxide)
6.5.1 Source Description
This category includes emission sources that are relatively small and provided by specific countries.
These countries have chosen to estimate emissions for these sources with their own methods as these
are generally sources without IPCC methodologies. The data presented here include the following
sources of methane and nitrous oxide:
Fugitives from natural gas and oil systems (nitrous oxide)
Fugitives from solid fuels (nitrous oxide)
Miscellaneous waste handling practices ("other waste") (methane and nitrous oxide)
Solvent and other product use (nitrous oxide)
Waste combustion (methane and nitrous oxide).
The sources listed above encompass several different sectors, but are placed in the waste sector
because waste combustion emissions dominate these miscellaneous sources. These emissions are NOT
included elsewhere in this report.
6.5.2 Source Results
The OECD and non-EU FSU regions constitute the majority of the emissions. The data in the table below
are not fully comparable to data in the remainder of this report since emissions are not calculated for all
countries in these regions. If a projection of future emissions was not available, EPA assumed future
emissions remain constant.
Total Methane and Nitrous Oxide Emissions
from Other Non-Agricultural Sources
Year
1990
1995
2000
2005
2010
2015
2020
MtCO2eq
15
16
17
18
19
20
21
GgCH4
53
68
88
83
78
74
72
GgN2O
44
47
48
53
57
60
64
June 2006 Revised
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7. Methodologies Used to Compile and
Estimate Historical and Projected
Emissions
Overview
This chapter outlines the methodologies used to compile and estimate category and country-
specific historical and projected emissions of methane (CH4), nitrous oxide (N2O), and high global
warming potential (GWP) gases. The preferred approach for estimating historical and projected
emissions is to use a hierarchy of country-prepared, publicly-available reports. If country-supplied
data are not available, EPA estimates emissions consistent with the Revised 1996IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC Guidelines) (IPCC, 1997) and the
IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
Inventories (IPCC Good Practice Guidance) (IPCC, 2000). A preferred data source for historical
emissions is the 2005 Inventory and accompanying Common Reporting Format (CRF) submitted
to the United Nations Framework Convention on Climate Change (UNFCCC) Secretariat by
Annex I countries. As identified by the UNFCCC, Annex I countries, include all OECD countries in
1992, plus countries with economies in transition and most of Central and Eastern Europe.
Annex I countries are noted in Table 1-4 and Appendix H. The 2005 CRFs contain inventory data
from 1990 through 2003. Data for non-Annex I countries are obtained from a mixture of country-
reported data (e.g., First National Communications), country reports, and EPA developed
estimates. The hierarchy of data sources and an overview of the methods used to augment
missing historical and projected estimates are discussed below in Section 7.1. A detailed
discussion of the methodology associated with each source category and gas begins in
Section 7.2.
This report does not describe in detail the methodology used to generate the publicly-available
CRF data. However, the CRF inventory data are generally comparable across countries because
they are based on IPCC methodologies and are reported for a standard list of IPCC source
categories. Although the CRFs provide the latest historical GHG emissions data for Annex I
countries, they do not contain projected emissions. A preferred source for projected emissions is
the National Communications, the Third National Communication for Annex I countries and the
First or Second National Communications for non-Annex I countries. The Third National
Communications were submitted primarily in 2001 and 2002. The National Communications are
documents that were submitted by each Party to the UNFCCC Secretariat to report on steps taken
to implement the Convention; they contain emissions and projections to 2020. The non-Annex I
countries have a more flexible schedule, with submissions of First and/or Second National
Communications from 1997 to 2005. The projected information from the National Communication
is adjusted to be compatible with the most recent inventory data, if necessary.
7.1 Data Sources for Historical and Projected Emissions
7.1.1 Methane and Nitrous Oxide
The preferred approach for estimating historical and projected emissions is to use country-
prepared, publicly-available reports. If reported estimates do not exist, EPA estimates methane
and nitrous oxide emissions in order to produce a complete inventory for the world. When
developing emissions estimates or projections, EPA uses the default methodologies presented in
the IPCC Guidelines and IPCC Good Practice Guidance. In other cases, it is necessary to modify
data from publicly-available reports in order to ensure consistency in the presentation of the data.
For example, some countries report projections that account for additional GHG mitigation
strategies over and above current effects of measures in place. Since the purpose of this report is
to provide projected emissions that reflect the currently achieved effects of climate policy programs
and measures that are already in place, but to exclude reductions due to future impacts of current
June 2006 Revised 7. Methodology Page 7-1
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programs or additional planned activities that are much less certain, the anticipated emissions
reductions due to these "additional" measures have been added back into the estimates, if
necessary.
The following country-specific or country-provided data sources are used to compile the methane
and nitrous oxide emissions in this report:
Annex I Countries:
2005 National Inventory Report (NIR) and Accompanying Common Reporting Format
(CRF) submissions to the UNFCCC. The 2005 CRF is the preferred data source for
historical estimates. The 2005 CRFs contain inventory data from 1990-2003 and are
prepared in accordance with IPCC Guidelines and the IPCC Good Practice Guidance.
Third National Communication. If CRF data are not available, Third National
Communications are the preferred source for historical data. The Third National
Communications are also the preferred source for developing projected emissions
estimates. If CRF historical estimates are available, EPA extracts emissions projections
through 2020 from the Third National Communication and scales these projected data to
CRF historical emissions. EPA uses projected data that reflect the current impact of
existing mitigation programs, but in a small number of cases, the only available projections
include planned mitigation measures. In these cases, EPA makes adjustments to the
projected data.
Other Country-Prepared Publications. If the CRF or Third National Communication is not
submitted or is incomplete, EPA uses the next most recent country-prepared publication.
For some countries, EPA uses country-specific reports that have more recent projection
information than the information provided in the most recently submitted National
Communication. The projections obtained from the country-prepared publication are
scaled to historical estimates from either the CRF or most recent National Communication.
IPCC Tier 1 Estimates. If data are not available from any of these sources, EPA estimates
emissions in accordance with IPCC Guidelines and IPCC Good Practice Guidance using
IPCC Tier 1 methodologies.
Non-Annex I Countries:
For non-Annex I countries, EPA first seeks country-specific data using the following preference
hierarchy: 1) Second National Communication, 2) First National Communication, 3) Country Case
Study report, or 4) Asia Least-Cost Greenhouse Gas Abatement Strategy (ALGAS) report. If data
are not available from any of these sources, EPA prepares estimates in accordance with IPCC
Guidelines and Good Practice Guidance using the IPCC Tier 1 methodology.
Augmenting Missing Historical Estimates
Many of the historical emissions time series have gaps. In addition, some countries aggregate
projections (e.g., livestock), which have to be disaggregated into their constituents (e.g., enteric
fermentation and manure management). The following steps are taken if the emissions data are
available, but are either incomplete or aggregated:
When two years are reported such that a year requiring an estimate (e.g., 1995) occurred
between the reported years (e.g., 1993 and 1997), EPA interpolates the missing estimate
(1995) using the reported estimates. EPA then "backcasts" or forecasts as described
below to complete the series for 1990, 1995 and 2000.
June 2006 Revised 7. Methodology Page 7-2
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For countries that report emissions for any year (or years) between 1990-1995, the 1990-
1995 Tier 1 growth rate1 is applied to backcast emissions to 1990 and forecast emissions
to 1995. Then, the 1995-2000 Tier 1 growth rate is applied to the 1995 estimate to obtain
the 2000 estimate.
For countries that report emissions for any year (or years) between 1995-2000, the 1995-
2000 Tier 1 growth rate is applied to backcast emissions to 1995 and forecast emissions
to 2000. Then, the 1990-1995 Tier 1 growth rate is applied to the 1995 estimate to obtain
the 1990 estimate.
If a country reports an estimate for an individual source for one year, but reports
aggregate estimates for other years, EPA disaggregates the estimates using the percent
contribution of the individual source in the latest reported year.
Projecting Estimates to 2020
For countries with CRF data, EPA forecasts emissions for 2005, 2010, 2015, and 2020
using growth rates calculated either from Third National Communications or other reported
data. In some cases, the 2000-2010 growth rate is applied to 2010-2020 if projections
past 2010 are not available in the country-reported data. If projections are not available
for any years in a National Communication or other country-specific data source, EPA
applies Tier 1 derived growth rates to historical data.
For non-Annex I countries, projections for 2005, 2010, 2015, and 2020 are usually created
by applying Tier I derived growth rates to reported historical data. However, for a few
countries, the National Communications provide BAD projected estimates and these are
given priority over EPA estimates.
For specific details on how estimates are developed for each country, category and year, see
Appendices E-1 to E-12.
7.1.2 High Global Warming Potential Gas Emissions
For most countries, emissions and projections are not available for the sources of high GWP
gases. Therefore, EPA estimates high GWP emissions and projections using detailed source
methodologies described later in this chapter (see Section 7.3).
7.2 Specific Methodologies for Methane and Nitrous Oxide Sources
The following sections describe the detailed methodologies used to develop historical and
projected emissions for countries for which reported data are not available or data are available for
only part of the time series. In these cases, EPA uses the IPCC Tier 1 methodology from the
IPCC Guidelines as the basis for calculating emissions. For each category, the source of historical
and projected data to calculate emissions is presented.
7.2.1 Methane Emissions from Natural Gas and Oil Systems
If no estimates are available or the data are insufficient, EPA uses the IPCC Tier 1 methodology to
estimate emissions. The Tier 1 basic equation to estimate fugitive methane emissions from oil and
natural gas production, transmission, and distribution systems is as follows:
1 A Tier 1 growth rate is a rate of growth (or decline) derived from historical and future emissions estimated using IPCC
Tier 1 methodology. Growth/decline ratios are calculated at five-year intervals for: 1990-1995, 1995-2000, 2000-2005,
2005-2010, and 2015-2020.
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Fugitive CH4 Emissions =
(Annual Oil Production x Emission Factor + Annual Oil Consumption x Emission Factor) +
(Annual Natural Gas Production x Emission Factor + Annual Natural Gas Consumption x Emission
Factor) + (Venting & Flaring Activity Data * Venting and Flaring Emission Factor)
Assuming that the emission factors do not change, the driver for determining fugitive methane
emissions from oil and natural gas is the respective production and consumption of these fuels.
Historical Emissions
Activity Data
Obtain historic natural gas and oil production and consumption data from U.S. Energy
Information Agency (EIA) for 1980 through 2000 (EIA, 2002).
Emission Factors and Emissions
Use IPCC (IPCC, 1997) default factors for natural gas production, natural gas
consumption, oil production, oil consumption, and venting and flaring for 1990, 1995, and
2000 emissions.
Multiply appropriate oil and natural gas production and consumptions statistics for 1990,
1995, and 2000 by IPCC (IPCC, 1997) default factors.
If country-provided historical data combines oil and natural gas emissions into one
estimate, EPA determines the percentage of emissions generated from each industry
sector using the IPCC Tier 1 methodology. EPA applies this percentage to country-
provided historical data to determine the approximate emissions associated with each
industry.
For missing historical years, EPA extrapolates emissions based on changes in oil and
natural gas production and consumption from EIA (EIA, 2002).
If emissions are not reported and EIA production data are not available, EPA assumes zero
emissions for this source.
Projected Emissions
Activity Data
Projections of natural gas and oil production and consumption are available from the EIA (EIA,
2002). EPA uses growth rates as provided by EIA "reference case" projections for 2000-2005,
2005-2010, 2010-2015, and 2015-2020. These are available by country or region.
Emissions
EPA applies the average annual consumption growth rate for the corresponding periods, to the
emissions attributed to consumption of oil and the average annual production growth rate, for the
corresponding periods, to the emissions attributed to production of oil. For natural gas, only a
consumption rate is provided; consequently, EPA applies this rate to all reported natural gas
emissions to project emissions to 2020.
June 2006 Revised 7. Methodology Page 7-4
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Adjustments to General Approach
Azerbaijan, Kazakhstan, Turkmenistan and Uzbekistan: The countries of the Former Soviet
Union (FSU) are expected to be key producers in the future. Since EIA (EIA, 2002) provides only
natural gas consumption projections, EPA used country-specific production projections to 2020
from Oil and Gas Journal (OGJ, 2001).
Uncertainties
The greatest uncertainties are due to the use of default emission factors, and difficulties in
projecting oil and natural gas consumption and production through 2020 for rapidly changing
global economies such as those in the FSU and developing Asia. In addition, methane emissions
from oil and natural gas systems are not linearly related to throughput, so the IPCC Tier 1
methodology and emission factors can lead to overestimates.
Appendix B-1 presents historical and projected emissions for all countries for this source.
Appendix E-1 contains data sources and methodology summaries for each country.
7.2.2 Methane from Coal Mining Activities
If no estimates are available or the data are insufficient, EPA uses the IPCC Tier 1 methodology to
estimate emissions. The Tier 1 basic equation to estimate fugitive methane emissions from
underground, surface, and post-mining operations is as follows:
Fugitive CH4 Emissions = Annual Coal Production x Emission Factor
Assuming that the emission factors do not change, the driver for determining fugitive methane
emissions from coal mining is coal production. Because a default methodology for fugitive
emissions from abandoned mines is not currently available, this source is not considered in this
report.
If a country does not report emissions and does not produce coal domestically according to both
the International Energy Outlook (EIA, 2002) and the International Energy Agency (IEA), methane
emissions are assumed to be zero.
Unless otherwise noted, EPA assumes that hard coal is produced in underground coal mines and
soft coal is produced in surface mines. However, this assumption does not have a major impact
on the overall emission estimates for this category because most countries that do not report
fugitive methane emissions from coal mining have relatively insignificant levels of coal production.
Historical Emissions
Activity Data
EPA obtains historic coal production data from 1980 to 2000 (EIA, 2002).
Emission Factors and Emissions
EPA multiplies hard coal production for 1990, 1995, and 2000 by IPCC (IPCC, 1997)
default factors for underground and associated post-mining activities.
EPA multiplies soft coal production for 1990, 1995, and 2000 by IPCC (IPCC, 1997)
default factors for surface and associated post-mining activities.
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Projected Emissions
Activity Data
EPA extrapolates production data from 2000 to 2020, with each five-year interval based
on changes in coal production from 1995 to 2000.
EPA assumes a zero production level for regions if production is projected to fall below
zero.
Emission Factors and Emissions
EPA projects emissions to 2020 based on estimates of future coal production, using
average emission factors based on the IPCC high and low default values (IPCC, 1997).
Adjustments to General Approach
For a few countries, EPA adjusts the above methodology, as outlined below:
China: China is one of the countries for which methane emission estimates through 2020 are
available (UNDP, 1998). However, energy policy in China has changed significantly since the
report was published. By 1999, coal production fell below 1990 levels. To account for the
unexpected reduction in coal production, EPA adjusts the estimates from 2000 to 2020 as follows:
The emission factor is assumed to remain the same as in the United Nations Development
Programme (UNDP) analysis. UNDP provides projections of coal production for each
10-year increment, including the year 2000. The implied emission factor is determined by
dividing the emissions by the production.
The updated production estimate for 2000 (EIA, 2002) is multiplied by the implied
emission factor to produce an adjusted emission estimate for 2000.
For 2005 to 2020, emissions are estimated by applying the growth rates from UNDP to the
adjusted 2000 emission estimate.
Estimates derived using the method outlined above are scaled to thel 994 estimate
provided in China's First National Communications.
India: The First National Communications provides methane emission estimates for 1994. World
Energy Council (WEC, 2000) reports production estimates for 2000 to 2020. The projected
production is in line with reports that India's coal production will potentially double by 2010 (Mining
India, 2000).
The 1994 estimate is extrapolated through 2020 based on changes in coal production, assuming
the average emission factor will remain constant.
Kazakhstan and Uzbekistan: In the early 1990s, the countries of the Former Soviet Union (FSU)
began a transition to market economies. This transformation led to an economic downturn in
many sectors, including coal mining. As these countries recover, coal production is expected to
stop decreasing as quickly. Therefore, projecting emissions based on recent coal production
trends would likely lead to underestimated emissions. To account for the unique situation of these
countries, emission estimates after 2000 were assumed to follow the trend predicted for Russia.
North Korea: Using the general methodology, coal production and thus emissions, are projected
to decline drastically from 2000 to 2020. This trend seems unlikely as coal is expected to remain
the key energy source in North Korea. North Korea does not export coal and imports only a small
amount of coal. Assuming this trade situation remains the same, coal consumption was used to
determine production.
June 2006 Revised 7. Methodology Page 7-6
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For 2000 through 2020, EPA assumes coal production grows at the same rate as coal
consumption in developing Asia (EIA, 2002).
EPA multiplies the projected coal production by the default emission factors to determine
projected methane emissions through 2020.
South Korea: In the 1990s, South Korea began supporting programs to decrease coal production
and consumption for local environmental reasons. The recent coal production decline is not likely
to continue, however, and appears to have been leveling off in the last few years. There may be
some additional decline similar to the most recent years. As a result, coal production decline rates
are kept constant at the 2000-2005 level.
Russia: Estimates from 1990 to 2010 are from Russia's Third National Communications.
Projected emissions from 2010-2020 are based on a draft EPA report that focused exclusively on
historical and projected coal mining methane emissions in Russia. For the majority of
underground mines, the methodology is consistent with the IPCC Tier 3 methodology, using
measurement data collected by the individual mines. For the remaining underground mines and
for surface and post-mining, EPA estimates emissions using the IPCC Tier 2 methodology. To
determine the projected emissions, the total projected coal production for that year is multiplied by
the share of coal production in the region for the year, and then multiplied by the average 1990-
1998 emission factor for the specific region. Projected estimates derived using the method
described above are scaled to the estimates reported in Russia's Third National Communications.
Poland: The National Communication reports that emissions are expected to decline sharply by
2010, largely due to anticipated closings of a large number of privatized mines. The pace of mine
closures might be slower than anticipated, however, because of social and economic
considerations. Unlike Germany and the United Kingdom (U.K.), which are expecting drastic
reductions in coal production, the Polish economy is largely coal-based (97 percent of energy
consumption (IEA, 2002)), with negligible natural gas and oil reserves. Also, Poland will continue
to sell some coal to foreign markets to earn foreign currency. Many of Poland's highest methane
producing mines are located near major industries, and there is the possibility of increased
methane recovery and use, especially as mines try to remain profitable. With the expected closing
of high-methane producing longwall mines and modest increases in methane recovery and use, it
is expected that coal emissions will decline 5 percent over each five-year period to 2010.
Uncertainties
The greatest uncertainties are due to the use of default emission factors, and difficulties in
projecting coal production through the year 2020 for rapidly changing global economies, such as
those in developing Asia. The assumption that all production comes from underground mines if
emissions are not reported could result in estimates that are significantly higher than actual
emissions because default underground mining emission factors are 10 times greater than surface
mining emission factors. However, this uncertainty does not have a major impact on the estimates
because the countries that report emissions account for over 95 percent of annual global coal
production and over 90 percent of estimated global emissions.
Appendix B-2 presents historical and projected emissions for all countries for this source.
Appendix E-2 contains data sources and methodology summaries for each country.
7.2.3 Nitrous Oxide and Methane Emissions from Stationary and Mobile
Combustion
If no historical nitrous oxide and methane emissions data are available or the data are insufficient,
EPA developed emissions using fuel consumption data from the International Energy Agency's
(IEA) Energy Balances (IEA, 2001 a; IEA, 2001 b) and the IPCC Tier 1 methodology. If no
projections are available, EPA develops projections by applying projected growth rates of energy
consumption from lEA's World Energy Outlook (WEO) (IEA, 2001 c) to historical emission
estimates.
June 2006 Revised 7. Methodology Page 7-7
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The basic equations to estimate emissions from mobile and stationary sources are as follows:
CH4 Emissions = Annual Fuel Consumption (by sector and fuel type)
x Emission Factor (by sector and fuel type)
N2O Emissions = Annual Fuel Consumption (by sector and fuel type)
x Emission Factor (by sector and fuel type)
For mobile sources, some emission factors also vary by mode (aviation, road, railway, and
navigation). Assuming that the emission factors do not change overtime, the driver for
determining nitrous oxide and methane emissions from stationary and mobile sources is fuel
consumption.
Table 7-1 presents the IEA- and IPCC-defined sectors and modes that constitute stationary and
mobile combustion. Table 7-1 shows how the IEA categories fit into the IPCC-defined sectors.
Table 7-1. Sectors and Modes
lEA-Defined Sectors
IPCC-Defined Sectors
1. Energy Industries
2. Total Industry Sector
3. Total Transport Sector
- International Civil Aviation
- Domestic Air Transport
- Road
-Rail
- Pipeline Transport
- Internal Navigation
- Non-specified Transport
4. Total Other Sectors
-Agriculture
- Commercial and Public Services
- Residential
- Non-specified Other
1. Energy Industries
2. Manufacturing Industries and Construction
3. Transport
(not used, bunker fuels)
- Aviation
-Road
- Railways
(used EF for Manufacturing Industries and Construction)
- Navigation
(assumptions depends on fuel type)
4. Total Other Sectors
- Agriculture/Forestry/Fishing
- Commercial/Institutional
- Residential
(used EF for residential or agriculture)
This sector comprises an aggregate of categories assumed to consume fuel primarily for the generation of
heat and power. This determination was made after consultation with both IEA and ICF energy experts.
The following categories are included: public electricity plants, autoproducer electricity plants, public
combined heat and power (CHP) plants, autoproducer CHP plants, public heat plants, autoproducer heat
plants, and own use.
Historical Emissions
If the historical time series of emissions is incomplete, EPA uses annual growth rates for energy
consumption from lEA's Energy Balances (IEA, 2001 a; IEA, 2001 b) to backcast and forecast
emissions to the missing years. For a few countries, no fuel consumption data are available from
lEA's Energy Balances. In these cases, EPA applies annual growth rates for energy consumption
by region from lEA's WEO to backcast and forecast emissions from available historical data. The
WEO provides rates for 1971-1997 and 1997-2010.
If no historical emissions estimates are available, EPA estimates emissions for a country and/or
region using the IPCC Tier 1 methodology. This methodology allows for an estimate of emissions
by sector and primary fuel type. The following inputs are used to estimate emissions:
Activity Data
Fossil fuel consumption data by country, fuel product, and sector use are collected from
lEA's Energy Balances for all major fuel types (IEA, 2001 a; IEA, 2001 b). The sectors
included in the analysis are listed in Table 7-1. The main fuel categories includes coal, oil,
and natural gas (see Table 7-2 for a listing of product categories). Biomass combustion
emissions are not calculated, but are included (for non-Annex I countries) in the category
Biomass Combustion, and discussed in Section 7.2.4.
June 2006 Revised
7. Methodology
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Table 7-2. Fuel Types Included Under Main Fossil Fuel Categories
Coal
Hard Coal
Brown Coal
Coke Oven Coke
Gas Coke
Peat
Brown Coal/Peat Briquettes (BKB)
Natural Gas
Natural Gas
Refinery Gas (in metric tons)
Ethane
Liquefied Petroleum Gases
Gas Works Gas
Coke Oven Gas
Blast Furnace Gas
Oxygen Steel Furnace Gas
Oil
Crude
Motor Gasoline
Aviation Gasoline
Gasoline - Type Jet Fuel
Kerosene - Type Jet Fuel
Kerosene
Gas/Diesel Oil
Residual Fuel Oil
Petroleum Coke
Non-specified Petroleum Products
Naphtha
Patent Fuel
Source: IEA, 2001 a; IEA, 2001 b
Emission Factors and Emissions
EPA multiplies the IEA fuel consumption data by the IPCC Tier 1 nitrous oxide and
methane uncontrolled emission factors for each fuel type and sector to obtain emissions.
Projected Emissions
EPA projects emissions based on forecasts of coal, oil, and natural gas consumption for
each region/country, by sector, provided by IEA WEO (IEA, 2001 c). Use of IEA WEO
data assumes that countries within the same region have the same growth rate. EPA
applies the forecasted annual growth rate of fuel consumption to emissions, based on the
following scenarios:
> For 2000, 2005, and 2010: EPA forecasts 2000, 2005, and 2010 emissions using the
1997-2010 annual growth rate for energy consumption for the appropriate region, by
sector and fuel type.
> For 2015 and 2020: EPA forecasts 2015 and 2020 emissions using the 2010-2020
annual growth rate for energy consumption for the appropriate region, by sector, and
fuel type.
Appendices B-3 and C-1 present historical and projected emissions for all countries for this
source. Appendix E-3 contains data sources and methodology summaries for each country.
Uncertainties
Large uncertainties are associated with the IPCC Tier 1 default emission factors used to calculate
emissions. The IPCC Good Practice Guidance estimates uncertainty for the methane combustion
emission factors at ±50 to 150 percent. Uncertainty for nitrous oxide combustion emission factors
are estimated to be "an order of magnitude," and are highly uncertain due to limited testing data on
which the factors are based. Also, the use of uncontrolled IPCC default emission factors may
overestimate emissions in those developing countries that have adopted some level of emission
control strategies for combustion sources.
Higher certainty is associated with the aggregate fuel consumption data on which estimates are
based, due to well-developed statistical approaches and surveys used to collect IEA data.
2 The regions and countries are: Transition Countries, Russia, China, South Asia, India, East Asia, Latin America, Brazil,
Africa, and the Middle East.
June 2006 Revised
7. Methodology
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Estimates of uncertainty for fossil fuel consumption data range from ±3 to 20 percent (IPCC,
2001).
7.2.4 Methane and Nitrous Oxide Emissions from Biomass Combustion
The basic equation to estimate emissions from biomass combustion is as follows:
Emissions = Emission Factor * Activity
Where:
The emission factor is specific to each fuel type (solid biomass, charcoal, liquid biomass,
other) and sector (such as energy industries and manufacturing).
The activity is the energy input in terajoules (TJ) or metric tons of fuel.
Historical Emissions
If only 1990 reported emissions estimates are available from the National Communication, Asia
Least-Cost Greenhouse Gas Abatement Strategy (ALGAS), or Country Study report, the
remainder of the historical time series is based on applying growth rates to this base year estimate
as follows:
EPA applies regional (or country-specific when available) annual growth rates to the
emissions estimates to fill out the rest of the historical series emissions. Compound
growth rates are directly from Part D of International Energy Agency's (IEA) World Energy
Outlook (WEO) 2000, Combustible Renewables and Waste (CRW) category (IEA, 2001 a),
for the years through 2010.
If historical emissions are not reported for any part of the time series, EPA applies the following
steps:
Activity Data
EPA establishes historical energy demand for each country, using 1990, 1995, and 1999
consumption data from the IEA Energy Statistics of non-OECD countries (IEA 2001 b).3
Consumption data are presented for the following sectors and subsectors: total solid
biomass composed of industry (energy and manufacturing), transportation, and non-
energy use; other (which is composed of residential, commercial, agricultural, and
unspecified other); liquid biomass; charcoal; and industrial waste.
EPA forecasts 2000 emissions by applying annual growth rates from Part D of lEA's WEO
2000, CRW category, EPA applies country-specific growth rates when they are available;
otherwise it applies regional growth rates to the year 2000. In projecting consumption, the
distribution of energy supplied by biomass into the relevant subsector is assumed to stay
constant.
Emission Factors and Emissions
EPA determines methane and nitrous oxide emissions from biomass combustion by
multiplying activity data (i.e., biomass fuel consumption by sector for each country) by
uncontrolled, default Tier 1 IPCC emission factors.
For Mexico and Turkey, consumption data are from IEA Energy Statistics of OECD Countries (IEA, 2001c).
June 2006 Revised 7. Methodology Page 7-10
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Projected Emissions
Activity Data
EPA uses 2000 as base year to project biomass fuel consumption in 2005 and 2010.
Compound growth rates are directly from Part D of lEA's WEO 2000, CRW category, for
the years through 2010. For the 2015 and 2020 estimates, the growth rate is calculated
from projected regional consumption reported in WEO 2000.
Emission Factors and Emissions
The emission factors used to calculate projected emissions are the same IPCC default
factors used in the historical time series calculations.
Adjustments to General Approach
EPA does not develop estimates for biomass combustion for Annex I countries. Emissions for
these countries are extracted from the 2005 CRFs and are included under stationary and mobile
combustion.
Uncertainties
Emission factors for biomass fuel are not as well developed as those for fossil fuels due to limited
test data for the variety of types and conditions under which these fuels are burned. Uncertainties
are at least as great as those for fossil fuel nitrous oxide and methane factors (± 50 to 150
percent).
Activity data for biomass fuel combustion also tends to be much more uncertain than fossil fuels
due to the smaller, dispersed and localized collection and use of these fuels, which makes tracking
consumption more difficult. Estimates in IPCC Good Practice Guidance suggest uncertainties in
the range of ±10 to 100 percent.
Appendices B-4 and C-2 present historical and projected emissions for all countries for this
source. Appendix E-4 contains data sources and methodology summaries for each country.
7.2.5 Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
If no country-reported estimates are available, EPA uses the IPCC Tier 1 methodology to estimate
emissions. The basic Tier 1 equation to estimate emissions from adipic acid production is as
follows:
N2O emissions = Adipic Acid Production * Emission Factor
[1 - (Destruction Factor * Abatement Utility Factor)]
The basic Tier 1 equation to estimate emissions from nitric acid production is as follows:
N2O emissions = Nitric Acid Production * Emission Factor
Historical Emissions - Adipic Acid Production
Activity Data
Production data are estimated based on adipic acid plant capacity figures and estimated
capacity utilization (Chemical Week, 1999a). Capacity utilization is assumed to be 75
percent for 1990, 80 percent for 1995, and 90 percent for 2000.
June 2006 Revised 7. Methodology Page 7-11
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Emission Factors and Emissions
The IPCC uncontrolled default emission factor for nitrous oxide generation (IPCC, 2000) is
applied to all plants with the exception of one plant in Singapore, which has abatement
technology. The destruction factor for this plant is assumed at 98 percent and abatement
utility factor at 95 percent (Reimer, 2000).
Projected Emissions - Adi pic Acid Production
Activity Data
Production is forecast to increase by 2 percent annually until 2010 and 1 percent per year
from 2011 to 2020 based on various expert projections and a historical growth of 2 percent
per year (CMR, 1998; SRI Consulting, 1999; Reimer, 2000).
Emission Factors
Emission factors used for projections are the same as those used in historical time series
calculations.
Historical Emissions - Nitric Acid Production
Activity Data
Nitric acid production for China, Brazil, and Mexico is estimated based on production
figures from various sources (C&EN, 1997; Chemical Week, 1999a, BICCA, 2000). For
other countries, production figures are estimated based on regional fertilizer plant
capacities and estimated capacity utilization (Chemical Week, 1999b).
Emission Factors and Emissions
The emission factor for developing countries is assumed to be 10 kilograms N2O per
metric ton nitric acid (IPCC, 2000).
Non-selective catalytic reduction is assumed to reduce emissions by 80 percent. It is
estimated to be used in 1 percent of plants in Asia.
Projected Emissions - Nitric Acid Production
Activity Data
Emissions from nitric acid production are projected based on increases in fertilizer production as
discussed in the agricultural soils section (see Section 7.2.6).
Emission Factors
Emission factors used for projections are the same as those used in the historical time
series calculations.
Uncertainties
In general, IPCC default adipic acid emission factors are more certain than nitric acid emission
factors because they are derived from stoichiometry of the process chemical reaction. IPCC Good
Practice Guidance estimates uncertainty for adipic acid emission factor at ±10 percent, and for
nitric acid emission factor at -20 to +90 percent based on the range provided for "other countries"
(IPCC, 2000).
Regarding activity data, estimates of nitric acid production derived from national fertilizer usage
are much more uncertain than those from published nitric acid production statistics. Fertilizer
June 2006 Revised 7. Methodology Page 7-12
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production capacities are used as a surrogate for actual production and may not reflect true annual
production of nitric acid, which has other uses besides fertilizer production.
Appendix C-3 presents historical and projected emissions for all countries for this source.
Appendix E-5 contains data sources and methodology summaries for each country.
7.2.6 Nitrous Oxide Emissions from Agricultural Soils
If no country-reported estimates are available, EPA uses the IPCC Tier 1 methodology to estimate
emissions. EPA estimates nitrous oxide for five components of nitrous oxide emissions from
agricultural soils:
Direct emissions from commercial synthetic fertilizer application
Direct emissions from cultivation of nitrogen-fixing crops
Direct emissions from the incorporation of crop residues
Direct emissions from manure (pasture, range and paddock and all applied manure)
Indirect emissions from agricultural soils.
Appendix F presents the detailed methodology and country-specific approaches the EPA used to
estimate nitrous oxide emissions from agricultural soils
Historical Emissions
Activity Data
EPA obtained activity data on fertilizer consumption, corn, wheat, soybean, and pulse production
and animal populations from the Food and Agriculture Organization (FAO, 2002).
Projected Emissions
Activity Data
For estimating emissions for 2005 to 2020, EPA projects country-specific activity data based on (1)
FAO regional fertilizer consumption growth rate for 1995 and 1997 to 2015 for direct emissions
from fertilizer usage, (2) the historical 1990 to 2000 crop growth rate for direct emissions from
nitrogen-fixing crops and crop residues, and (3) International Food Policy Research Institute
(IFPRI) livestock population growth rates for direct emissions from manure applied to soils. Using
the projected activity data and IPCC Tier 1 methodology, EPA calculates 2005 to 2020 emissions.
Adjustments to General Approach
To develop "Rest-of-World"4 emissions from agricultural soils, EPA obtains activity data
from FAO for production of soybeans, pulses, corn, and wheat (FAO, 2001), nitrogenous
fertilizer use, and animal populations (FAO, 2002) for each country in the "Rest of..."
regions for 1990 to 2000. EPA combines these data into one value (e.g., all the fertilizer
consumption in Kyrgystan and Tajikistan were combined into one "Rest of Former Soviet
Union" fertilizer consumption value). The same methodology as described above was
used to estimate emissions for the regions.
For growth rates in crop production (all years) and manure applied to soils (all years), EPA
uses a rate that was determined by summing the activity data from all "Rest-of-World"
countries in a given region for 1990 and the latest year available, and then determining the
growth rate from those two numbers. For example, to obtain the Rest of China/CPA
4 The countries combined under "Rest of World" groupings for this source category differ slightly from the other categories.
For all other categories, Kyrgystan, Tajikistan, Cambodia, and Laos were reported as individual countries.
June 2006 Revised 7. Methodology Page 7-13
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region crop production growth rate, EPA sums the crop production of Cambodia and Laos
in 2000 and in 1990. Then, from those summed numbers, EPA determines the growth
rate over the time period just as was done for individual countries. To project activity data,
these growth rates for crop production and manure applied to soils are applied to the latest
corresponding activity data available. For fertilizer consumption beyond 2000, EPA uses
the regional growth rates provided by FAO (2000) to project activity data.
Uncertainties
The greatest uncertainties are in the completeness of the activity data used to derive the
emissions estimates. Emissions from fertilizers are estimated from only synthetic fertilizer use. In
reality, organic fertilizers (other than the estimated manure and crop residues) also contribute to
nitrous oxide emissions from soils, but this activity is not captured in these estimates. Only two
nitrogen-fixing crops are used in these estimates; other crops besides soybeans and pulses fix
nitrogen and therefore contribute to nitrous oxide emissions. Similarly, other crop residues
besides soybeans, pulses, corn, and wheat may be left on the field, thus resulting in nitrous oxide
emissions. The identity and quantity of these crops would vary among the different countries. The
livestock nitrogen excretion values, while based on detailed population statistics, do not accurately
reflect country-to-country variations in animal weight or feeding regimes. Finally, emissions from
histosols and from sewage sludge are not calculated or included in these estimates. Though small
components of the total nitrous oxide emissions from this source category, both of these sources
do contribute to emissions.
Uncertainty also exists in the projected emissions. For many subcategories, growth is based on
historical trends. Additionally, when EPA uses previously published projections, they are on a
regional level, not a country-specific level.
Appendix C-5 presents historical and projected emissions for all countries for this source.
Appendix E-6 contains data sources and methodology summaries for each country.
7.2.7 Methane Emissions from Enteric Fermentation
The basic equation to estimate emissions from enteric fermentation is as follows:
Emission Factor (kg/head/yr) x Animal Population (head) /(106 kg/Gg) = Emissions (Gg/yr)
The default emission factors are taken from the IPCC Guidelines (IPCC, 1997) and the population
data are obtained from the Food and Agriculture Organization (FAO, 2003). Assuming that the
animal characteristics upon which the default emission factors are based do not change
significantly overtime, the primary driver for determining methane emissions from enteric
fermentation is animal population.
Historical Emissions
If reported estimates are not available, EPA uses the IPCC Tier 1 methodology for each country
for which FAO animal population data are available.
Activity Data
EPA obtains 1990, 1995, and 2000 animal population data from FAO. Populations of non-
dairy cattle are obtained by subtracting FAO dairy cattle populations from FAO total cattle
populations. These data are modified for several countries. In 1990, animal population
data were not available for certain countries that were formed after the breakup of the
Former Soviet Union (FSU) (Latvia, Moldova, Ukraine, Uzbekistan, and others),
Yugoslavia (Bosnia, Croatia, Macedonia, Slovenia, and Serbia and Montenegro),
Czechoslovakia (Czech Republic and Slovakia), and Ethiopia (Ethiopia and Eritrea).
Therefore, for each region, EPA determines the percent contribution of each country to its
regional total using 1995 animal population data. EPA then applied these percentages to
estimate 1990 animal population for these countries.
June 2006 Revised 7. Methodology Page 7-14
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Emission Factors
Tier 1 default emission factors from the IPCC Guidelines are used in the calculated
emissions. For buffalo, sheep, goats, camels, horses, mules and asses, and swine,
enteric fermentation emission factors for "developing countries" were used. For dairy and
non-dairy cattle, enteric fermentation emission factors for world regions are used, with
factors assigned to countries based on the region in which they are located.
Projected Emissions
Activity Data
EPA uses reported estimates for 2005, 2010, 2015, and 2020 if possible. If projections
are not available, EPA projects emissions from 2005-2020 based on livestock population
growth rates developed by International Food Policy Research Institute (IFPRI, 2004).5
The IFPRI dataset contains population estimates for the years 2000, 2010, and 2020 for
each of the main livestock species reported by country and world regions. Average
annual growth rates for the periods 2000-2010 and 2010-2020 are developed from these
estimates. Starting with the historical year 2000 FAO animal population statistics, these
growth rates are then applied to obtain 2005, 2010, 2015, and 2020 populations for each
livestock species.
Emission Factors
Emission factors used for calculating projections are the same as those described above
for the historical time series calculations.
Projected populations for each livestock species are multiplied by the animal-specific
emission factors to obtain projected methane emissions.
Uncertainties
The greatest uncertainties are associated with the use of default emission factors due to the lack
of information on country-specific animal diets. Emission estimates for countries with a variety of
animal diets could be inaccurate, particularly when projecting emissions since there is a lack of
information on potential changes in the quality, quantity, and type of feed that could affect
emissions in future years. Also, the impacts of world markets and consumption patterns on
national livestock production patterns are often difficult to predict, further increasing the uncertainty
of projected emissions from this source.
Appendix B-6 presents historical and projected emissions for all countries for this source.
Appendix E-7 contains data sources and methodology summaries for each country.
7.2.8 Methane Emissions from Rice Cultivation
The IPCC Good Practice Guidance (IPCC, 2000) provides the following overall equation for the
calculation of methane emissions from rice production:
Emissions from Rice Production (Tg/yr) =ZZZ(EFijk *Aijk * 10~12)
Where:
EFijk = A seasonally integrated emission factor for i, j, and k conditions in g CH4/m2
Ajjk = Annual harvested area for i, j, k conditions in m2/yr; and
5 The IFPRI growth rates are generated by a model that incorporates supply and demand parameters. These parameters
include the feed mix applied according to relative price movements, international trade, national income, population, and
urban growth rates as well as anticipated changes in these rates over time.
June 2006 Revised 7. Methodology Page 7-15
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i,j,k = Represent different ecosystems, water management regimes, and other
conditions under which methane emissions from rice may vary.
Rice emissions vary according to the conditions under which rice is grown. Using the approach
outlined above, the harvested area can be subdivided by different growing conditions (e.g., water
management regime) and multiplied by an emission factor appropriate to the conditions. The sum
of these individual products represents the total national estimate.
In practice, it is difficult to obtain specific emission factors for each commonly occurring set of rice
production conditions in a country, so the IPCC Guidelines instruct countries to first obtain a
baseline emission factor (EFC) for continuously flooded fields without organic amendments.
Different scaling factors are then applied to this seasonally integrated emission factor to obtain an
adjusted seasonally integrated emission factor for the harvested area as follows:
EF, = EFC*SFW*SF0*SFS
Where:
EF, = Adjusted seasonally integrated emission factor for a particular harvested area
EFC = Seasonally integrated emission factor for continuously flooded fields without
organic amendments
SFW = Scaling factor to account for the differences in ecosystem and water
management regime
SF0 = Scaling factors for organic amendments (should vary for both type and amount
of amendment applied)
SFS = Scaling factor for soil type, if available.
Historical Emissions
If no estimates are available, EPA uses the IPCC Tier 1 methodology for each country/region, as
detailed below:
Activity Data
EPA obtains data on area harvested for rice cultivation from 1990 through 2000 (FAO,
2001).
EPA obtains information on type of water management regime (upland, irrigated, rain-fed,
or other) from International Rice Research Institute (IRRI, 2001). If information is not
available from IRRI, data are obtained from the IPCC Guidelines (IPCC, 1997).
Emission Factors
Country-applicable emission factors are developed for each of the five main water
management types: irrigated (constantly flooded), irrigated (intermittently flooded), rain-fed
lowland (flood-prone), rain-fed lowland (drought-prone), and upland. Starting point
emission factors obtained from IPCC (IPCC, 1997) are based on the continuously irrigated
water regime. Scaling factors from IPCC (IPCC, 2000) are then applied to adjust the
starting point emission factor for each of the other water regimes. The scaling factors
June 2006 Revised 7. Methodology Page 7-16
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0.35, 0.8, 0.4, and 0, are used for intermittently flooded, rain-fed lowland (flood-prone),
rain-fed lowland (drought-prone), and upland, respectively.6
In addition to the scaling factors discussed above, emission factors are further adjusted to
account for the use of organic amendments (fertilizers) and the increased emissions from
soils to which organic amendments are applied. A factor of two is applied to 40 percent of
rice production to account for organic amendments. The factor of two is based on the
IPCC-recommended default correction factor of two, while the 40 percent figure is an
assumption based on expert opinion, and is applied equally to all country-specific
emission factors.
The combination of all the above adjustment factors provides the adjusted country-specific
emission factors used in the emission equation above.
If a country is similar to a country with a IPCC published emission factor, that emission
factor was used:
> Thailand's emission factors are applied to Laos, Malaysia and Cambodia.
> India's emission factors are applied to Bhutan and Nepal.
Irrigated Land: Due to limited information, EPA assumes that all irrigated land is
continuously flooded with no aeration. This assumption is conservative and could lead to
overestimates in emissions.
Rainfed Land: Proportions of flood-prone and drought-prone rain-fed paddy types are
based on country-specific allocations published in IPCC (IPCC, 1997) for 19 of 26
countries. For remaining countries, equal allocations of rain-fed total allocation are made
to drought-prone and flood-prone types.
Emissions
EPA multiplies area harvested for 1990, 1995, and 2000 by percentage in each water
management type.
EPA multiplies area harvested for each year and in each water management type by
appropriate emission factor (IPCC, 1997; IPCC, 2000).
EPA sums methane emissions from each water management type.
If no reported emissions or FAO/IRRI production data are not available, EPA assumes zero
emissions from this source.
Projected Emissions
If projections are not available, EPA uses the following methodology to project emission estimates:
Activity Data
Due to the lack of projections on future rice area harvested, EPA uses population as the
driver for methane emissions from rice cultivation. Since this does not account for
increases in yield or lack of available area, this methodology is likely to overestimate
emissions in 2020.
6 The adjustment factor 0.35 is used for intermittently flooded irrigated lowlands (relative to IPCC emission factors specific
to continuously flooded fields). This value is calculated as the average of 0.5 (range of 0.2 - 0.7) and 0.2 (range of 0.1 -
0.3), respectively the IPCC-recommended scaling factors for single aeration and multiple aeration, which are the two
subsets of the intermittently flooded category.
June 2006 Revised 7. Methodology Page 7-17
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EPA obtains population projections from World Population Prospects: the 2002 Revision,
published by the United Nations Population Division (UN, 2003). EPA uses these
population projections to create growth rates for each country and region for each five-
year increment from 2000 to 2020.
Emissions
EPA applies the population growth rates to the historical emissions attributed to rice
cultivation to develop projections at five-year intervals.
Uncertainties
Significant uncertainties are in the estimation of methane emissions from rice cultivation. The
default emission factors are one of the greatest uncertainties. The IPCC emission factor is
country-specific for only a few countries. It is adjusted for water management, but, it is not
adjusted for other parameters such as ratooning. Also, country-specific information is not readily
available on the amount of organic amendment, flooding, and aeration in irrigated areas. A
significant area of uncertainty is the use of population as a driver for projecting harvested area.
Future work will examine the historic relationship between demand, yield, and area harvested to
improve projections of rice production areas.
Appendix B-7 presents historical emissions and projected emissions for all countries for this
source. Appendix E-8 contains data sources and methodology summaries for each country.
7.2.9 Methane and Nitrous Oxide Emissions from Manure Management
Many developing countries report estimates of methane emissions and some countries also report
nitrous oxide emissions for manure management; however, there is generally less coverage of
nitrous oxide emissions in the published inventory data.
The basic equation to estimate emissions from manure management is as follows:
Emission Factor (kg/head/yr) x Animal Population (head) /(106 kg/Gg) = Emissions (Gg/yr)
The default emission factors are taken from the IPCC Guidelines and IPCC Good Practice
Guidance and the population data are obtained from the Food and Agriculture Organization (FAO,
2003). Assuming that the waste management and animal characteristics upon which the default
emission factors are based do not change significantly over time, the key driver for determining
emissions from manure management is animal population.
Historical Emissions
If reported estimates are not available, EPA uses the IPCC Tier 1 methodology for each country
for which FAO animal population data are available.
Activity Data
EPA obtains 1990, 1995, and 2000 animal population data from FAO (FAO, 2003)7
Estimates for non-dairy cattle are obtained by subtracting FAO dairy cattle estimates from
FAO total cattle estimates. The population data is modified in several instances. In 1990,
animal population data are not available for certain countries that have since been
established after the breakup of the Former Soviet Union (FSU) (Latvia, Moldova, Ukraine,
Uzbekistan and others), Yugoslavia (Bosnia, Croatia, Macedonia, Slovenia, and Serbia
and Montenegro), Czechoslovakia (Czech Republic and Slovakia), and Ethiopia (Ethiopia
and Eritrea). Therefore, for each region, EPA determines the percent contribution of each
7 1990 and 2000 data for Pakistan for all livestock categories except poultry are obtained from Pakistan's ALGAS report.
1995 livestock population data are interpolated. 1990, 1995, and 2000 poultry data are obtained from FAO.
June 2006 Revised 7. Methodology Page 7-18
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country to their regional total using 1995 animal population data. EPA then applies these
percentages to estimate 1990 animal population for these countries.
Emission Factors
For sheep, goats, camels and other camelids, horses, asses and mules, and poultry,
emission factors for "developing countries" are obtained from the IPCC Guidelines.
For cattle, swine and buffalo, emission factors from the IPCC Guidelines and IPCC Good
Practice Guidance are used, and the selection depend on region and climate type (i.e.,
cool, temperate, and warm) for the country.
EPA estimates climate type for most countries using data from the Global Historical
Climatology Network, which is published by the National Climatic Data Center and
contains annual average temperatures for most country's capital/major cities. These
annual averages are for a range of years, which vary by country. Given the lack of animal
population data by areas within a country, EPA assumes that 100 percent of the animal
populations are located in a climate defined by the average temperature of the country
capital.
For Bolivia, Chile, Colombia, Ecuador, and Peru: Geographic Information System (CIS)
information on temperature ranges is used to determine the climate type applicable to
livestock areas in these countries (ESRI, 1999).
Projected Emissions
Activity Data
If projections are not available, EPA projects emissions estimates from 2005-2020 based
on livestock population growth rates developed by IFPRI (IFPRI, 2004).8 The IFPRI
dataset contains population estimates for the years 2000, 2010, and 2020 for each of the
main livestock species reported by country and world regions. Average annual growth
rates for the periods 2000-2010 and 2010-2020 are developed from these estimates.
Starting with the historical year 2000 FAO animal population statistics, these growth rates
are then applied to obtain 2005, 2010, 2015, and 2020 populations for each livestock
species.
Emission Factors
Emission factors for calculating projections are the same as those described above for the
historical time series calculations.
Projected populations for each livestock species are multiplied by the animal-specific
emission factors to obtain projected methane emissions.
Uncertainties
The greatest uncertainties are due to the use of default emission factors due to the lack of
information on country-specific manure management systems and the geographic concentration of
animal populations, which affects the climate zone assignment. Considerable uncertainty in
projected emissions is due to the lack of information on potential changes to management system
types and animal feeding characteristics that could affect emissions in the future years. Also, the
impacts of world markets and livestock product consumption patterns on national livestock
production patterns are often difficult to predict, further increasing the uncertainty of projected
emissions from this source.
8 The IFPRI growth rates are generated by a model that incorporates supply and demand parameters. These parameters
include the feed mix applied according to relative price movements, international trade, national income, population, and
urban growth rates as well as anticipated changes in these rates over time.
June 2006 Revised 7. Methodology Page 7-19
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Appendices B-8 and C-6 present historical and projected emissions for all countries for this
source. Appendices E-9 (CH4) and E-9b (N2O) contain data sources and methodology summaries
for each country.
7.2.10 Methane and Nitrous Oxide Emissions from Other Agricultural
Sources
The sources included in this category are savanna burning, agricultural residue burning, and open
burning from forest clearing. This category also includes minor amounts of country-reported
emissions data on methane from agricultural soils. However, biomass burning constitutes the
majority of emissions for this source.
1990 and 1995 estimates for biomass burning were obtained from the Emission Database for
Global Atmospheric Research (EDGAR), Version 3.2 (Olivier and Berdowski, 2001), (Olivier,
2002). Estimates for 2000 were obtained from the EDGAR 3.2 Fast Track 2000 dataset
(32FT2000) (Olivier, 2005). EDGAR sub-divides biomass burning into the following subcategories:
Tropical forest fires; deforestation
Savannah and shrubs fires
Agricultural waste burning
Middle and high latitude forest fires; temperate vegetation fires
Indirect N2O from tropical forest fires
Middle and high latitude grassland fires (reported for 2000 only).
Data from all of these subcategories are included here.
Austria, Belgium, and Japan provided estimates for methane for agricultural soils.
Some of the inventory estimates may be incomplete, indicating that the values are not fully
comparable. If a projection of future emissions is not available, future emissions are assumed to
remain constant at the value for the latest reported year.
Appendices B-9 and C-7 present historical emissions estimates and projections for all countries
7.2.11 Methane Emissions from Landfilling of Solid Waste
If no estimates are available or the data are insufficient, EPA uses the IPCC Tier 1 methodology to
estimate emissions. The Tier 1 basic equation to estimate fugitive methane emissions from
landfills is as follows:
CH4 Emissions = (MSWT * MSWF * MCF * DOC * DOCF * F * 16/12-R)*(1-OX)
Where:
MSWT = Total municipal solid waste (MSW) generated = Population * waste
generation per person
MSWF = Fraction of MSW disposed to solid waste disposal sites
MCF = Methane correction factor (fraction)
DOC = Degradable organic carbon (fraction)
DOCF = Fraction DOC dissimilated
F = Fraction of methane in landfill gas (default is 0.5)
R = Recovered methane
OX = Oxidation factor (fraction - default is 0)
June 2006 Revised 7. Methodology Page 7-20
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Activity Data
Urban population data are from the World Population Prospects: the 2002 Revision,
published by the United Nations Population Division (UN, 2003).
Emission Factors
The first two terms in the equation, MSWT and MSWF are not readily available, thus these
terms are estimated in aggregate using the following formula:
MSW disposal rate (kg/cap/day) x population (cap) x 365 (days/yr) / 10A6 (Gg/kg) = MSW
disposed (Gg) = MSWT x MSWF
The MSW disposal rate is from the IPCC Guidelines (IPCC, 1997) or the International
Energy Agency (IEA, 1999).
The MCF is from IPCC 1997 or IEA, 1999. Most countries use the IPCC default value for
an uncategorized solid waste disposal site (SWDS) of 0.6. For the remaining countries,
the MCF is calculated by multiplying the percent of MSW attributed to each SWDS type by
its IPCC default correction factor and then summing these SWDS-specific products.
DOCF, R, and OX are IPCC default values (IPCC, 1997). The values for DOC are
primarily from the IPCC Guidelines (IPCC, 1997), supplemented with values from IEA,
1999 if IPCC default values are not available.
Oxidation (OX) and recovery (R) are assumed to equal zero.
Projected Emissions
If projections are not available, EPA uses the following methodology to project emission estimates:
Activity Data
EPA obtains population projections from World Population Prospects: the 2002 Revision
(UN, 2003), published by the United Nations Population Division. EPA uses these
projections to determine growth rates for each country and region for each five-year
increment from 2000 to 2020.
EPA obtains Gross Domestic Product (GDP) projections by country from the World Bank.
Emission Factors
The MSW per capita generation rate is assumed to increase at the rate of projected GDP.
The proportion of wastes placed in landfills versus open dumps increases at the rate of
per capita GDP growth.
Uncertainties
Uncertainties in the estimation of methane emissions from landfills are due in large part to the lack
of one or more country-specific values for the following parameters: MSW generation per person,
percent to MSW, percent to managed landfills, DOC fractions, oxidation factors, and recovery.
Also, while the drivers for projections were selected to capture future trends in the movement of
waste to MSW landfills, there is considerable uncertainty, particularly in the developing regions of
the world, in predicting landfill utilization.
Appendix B-10 presents historical and projected emissions for all countries for this source.
Appendix E-10 contains data sources and methodology summaries for each country.
June 2006 Revised 7. Methodology Page 7-21
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7.2.12 Methane Emissions from Wastewater
The basic equation to estimate emissions from wastewater is as follows:
CH4 Emissions = Emission Factor * Total Organic Waste
Where:
Emission Factor
Maximum CH4 Producing Capacity
Methane Conversion Factor (MCF)
Total Organic Waste
Maximum CH4 producing capacity * the CH4
conversion factor (MCF)
Maximum amount of CH4 that can be
produced from a given quantity of wastewater
A weighted average of the amount of
Wastewater handled by different systems
times the appropriate MCF.
Human population *the degradable organic
component
Country-provided data are used for Annex I countries if they are available. For all other countries
(non-Annex I and Annex I without available data), EPA calculates estimates for this category using
the IPCC Tier 1 methodology for each country and/or region. The methodology is described in
detail in Doom (1999), with the exception of the emission factor. The maximum methane
producing capacity, part of the emission factor, used in this analysis is 0.6 kg CH4/kg biological
oxygen demand (BOD), the recommended factor in the IPCC Good Practice Guidance.
Assuming that the emission factors do not change, the driver for determining methane emissions
from wastewater is population. The emission factor may change with time, however, if countries
modernize or change their handling and treatment systems as their GDP increases.
Appendix B-11 presents historical emissions estimates and projections for all countries.
Appendix E-11 contains data sources and methodology summaries for each country.
7.2.13 Nitrous Oxide from Human Sewage
If no estimates are available or the data were insufficient, EPA uses the IPCC Tier 1 methodology
to estimate emissions. The Tier 1 basic equation to estimate nitrous oxide from human sewage as
follows:
i = Protein x FracNPR x NRPEOPLE x EF6
Where:
N20(s)
Protein
NRpEOPLE
EFK
Fraci
NPR
N2O emissions from human sewage (kg N2O-N/yr)
Annual per capita protein intake (kg/person/yr)
Number of people in country.
Emission factor (default 0.01 (0.002-0.12) kg N2O-N/kg
sewage N produced)
Fraction of nitrogen in protein (default = 0.16 kg N/kg
protein)
Appendix C-8 presents historical and projected emissions for all countries for this source.
Appendix E-12 contains data sources and methodology summaries for each country.
June 2006 Revised
7. Methodology
Page 7-22
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7.2.14 Other Non-Agricultural Sources
This category includes methane emissions sources such as waste combustion, metals production,
and petrochemical production. It also includes nitrous oxide sources such as solvent use, waste
combustion and miscellaneous industrial processes. These sources are typically small
contributors compared to the primary sources discussed above. Some of the inventory estimates
for these sources may be incomplete, indicating that the values are not fully comparable. If
projected emissions are not available, future emissions are assumed to remain constant at the
value for the last reported year. These "other non-agricultural" data are mainly from Annex I
countries and are presented as either (other non-agricultural) industrial or waste-related emissions
in Sections 4.9.1 and 6.5.1, respectively.
Appendices B-5, B-12, C-4, and C-9 present historical and projected emissions for all countries for
this source.
7.3 Estimation and Projection Approaches Used for High
Global Warming Potential Gases
High global warming potential (high GWP) gas emissions result from the use of substitutes for
ozone-depleting substances (ODSs), from the production of aluminum, magnesium,
semiconductors, flat panel display, HCFC-22, and electrical equipment, and from the use of
electrical equipment9. Until recently, few nations have made significant efforts to track and project
use and emissions of hydrofluorocarbons (MFCs), perfluorocarbons (PFCs), and sulfur
hexafluoride (SF6). If countries did present information on these gases, it was often incomplete or
aggregated. Partial or aggregated estimates do not contain the level of detail required for this
analysis; thus, EPA used the methods described below to estimate emissions from individual
source categories.
7.3.1 The Technology-Adoption and No-Action Baselines
This report presents two future scenarios for five industries emitting high GWP gases for which
clearly defined, industry-specific global or regional emission reduction goals have been
announced. These industries include the primary production of aluminum, semiconductors,
magnesium, and HCFC-22, and the use of electrical equipment. In response to concerns
regarding the high GWPs and long lifetimes of their emissions, the global aluminum,
semiconductor, and magnesium industries have committed to reduce future emissions by
substantial percentages. Similarly, users (and, in some cases, manufacturers) of electrical
equipment in Japan, Europe, and the U.S. have committed to reduce emissions in those countries
and regions. Finally, HCFC-22 producers in several developing countries have agreed to host
mitigation projects funded by developed countries under the Clean Development Mechanism
(COM) of the Kyoto Protocol. The HFC-23 abatement projects considered in this analysis are
either registered or are in the process of being registered in the COM pipeline. (HCFC-22
producers in developed countries are also continuing to reduce emissions.) These global and
regional emission reduction goals are summarized in the table below.
The production of electrical equipment is not included in this analysis.
June 2006 Revised 7. Methodology Page 7-23
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Table 7-3. Global and Regional Emission Reduction Commitments
Industry
Semiconductor
Manufacturing
Magnesium
Manufacturing
Primary Production
of Aluminum
Electrical Equipment
(use)
HCFC-22 Production
Global Industry
Association, Region,
or Country
World Semiconductor
Council (WSC)
International
Magnesium Association
(IMA)
International Aluminum
Institute (IAI)
EU-25+3lu, Japan, U.S.
China, India, South
Korea, Mexico
Percent of World
Production/
Emissions in 2003
85%
70% (about 90% of
sector's SF6
emissions)
70% (but goal
applies to entire
industry)
40% of use
emissions
65% of emissions
Goal
Reduce fluorinated emissions
to 90% of 1995 level by 20 10
Phase out SF6 use by 201 1
Reduce PFCs/ton Aluminum by
80% relative to 1 990 levels by
2010
Country-specific reductions
from 2003 totaling 2.5
MtCO2eq, or 15% of these
countries' 2003 emissions from
use.
COM projects totaling 55
MtCO2eq, or 63% of these
countries' 2010 emissions.
The first scenario presented in this report, called the "Technology-Adoption Baseline," is based on
the assumption that these industries will achieve their announced global or regional emission
reduction goals for the year 2010. The second scenario, called the "No-Action Baseline," is based
on the assumption that emission rates will remain constant from the present onward in these
industries.
EPA believes that actual future emissions are likely to be far closer to those envisioned in the
Technology-Adoption Baseline than those envisioned in the No-Action Baseline. Since 1990, all
five industries have already made great progress in reducing their emission rates, and research is
continuing into methods to further reduce those rates. Nevertheless, additional actions will be
required to actually realize additional reductions. These actions range from process optimization
and chemical recycling to chemical replacement. Thus, depending on the context, either baseline
may be of interest. For example, analysts interested in the incremental costs of reducing
emissions below the levels anticipated in current global industry commitments can use the
Technology-Adoption Baseline. On the other hand, analysts interested in the future costs of
achieving the currently planned industry reductions can use the No-Action Baseline. The
difference between the two baselines is itself of interest, demonstrating that the industry
commitments are likely to avert very large emissions.
It should be noted that EPA modeled only those reduction efforts that had been clearly announced
and quantified on an industry-specific basis at the time this report was being prepared. This
means that even in the Technology-Adoption Baseline, significant reduction opportunities remain
in 2010 and 2020, primarily in developing countries. This is particularly true for the HCFC-22 and
electric power system industries. In fact, there is a significant probability that many of these
emissions will be averted, e.g., by fuller implementation of COM or other reduction efforts.
However, the precise extent of additional reduction actions is uncertain. Thus, the Technology-
Adoption baseline reflects only current, quantitative, industry-specific goals.
10 The EU-25+3 includes the 25 member countries of the European Union (EU) and Norway, Switzerland, and Iceland.
Appendix I contains a complete list of EU countries.
June 2006 Revised
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7.3.2 HFC and PFC Emissions from the Use of Substitutes for ODS
This section provides further detail on how EPA developed the baseline estimates for the various
ODS substitute end-use sectors, which include refrigeration/air-conditioning, foams, aerosols, fire
extinguishing, and solvents. In general, EPA used a modeling approach to determine emissions,
because, until recently, few nations have made significant efforts to track and project use and
emissions of MFCs and PFCs from ODS substitutes. However, where ODS substitute emission
information was available, such as countries' submissions for the first National Communication
process under the United Nations Framework Convention on Climate Change (UNFCCC), EPA
used each country's data as the basis for projecting future emissions (the second National
Communications were not yet available when this analysis was performed).
In the absence of reported data, EPA used the following approach. First, EPA used a "Vintaging
Model" of ODS-containing equipment and products to estimate the use and emissions of ODS
substitutes in the U.S. In the second step, emissions from non-U.S. countries were estimated.
This was accomplished for each ODS-consuming end-use in each country. In developing these
estimates, EPA initially assumed that the transition from ODSs to MFCs and other substitutes
follows the same substitution patterns as the U.S. The U.S.-based substitution scenarios were
then customized to each region or country using adjustment factors that take into consideration
differences in historical and projected economic growth, the timing of the phaseout, and the
distribution of ODS use across end-uses in each region or country. The methodology EPA used to
estimate and adjust emissions is described in the following sections.
Estimating ODS Substitute Emissions in the U.S.
EPA uses the Vintaging Model of ODS- and ODS substitute-containing equipment and products to
estimate the use and emissions of ODS substitutes in the U.S. The model tracks the use and
emissions of each of the substances separately for each of the ages or "vintages" of equipment.
The model and the equations used to estimate emissions are discussed in more detail in
Appendix G.
The consumption of ODS and ODS substitutes was modeled by estimating the amount of
equipment or products sold, serviced, and retired each year, and the amount of the chemical
required to manufacture and/or maintain the equipment and products overtime. The model
estimates emissions by applying annual leak rates and/or other emission profiles to each
population of equipment or product. By aggregating the data for more than 40 different end-uses,
the model estimates and projects annual use and emissions of each compound overtime. For this
analysis, the model calculated a "business as usual" (BAU) case that does not incorporate
measures to reduce or eliminate the emissions of these gases other than those regulated by U.S.
law or otherwise largely practiced in the industry.
The major end-use categories defined in the Vintaging Model for characterizing ODS use in the
U.S. are refrigeration and air-conditioning, aerosols (including metered-dose inhalers (MDI)),
solvent cleaning, fire extinguishing equipment, foam production, and sterilization. The Vintaging
Model estimates the use and emissions of ODS substitutes by taking the following steps:
1. Gather historical emissions data. The Vintaging Model is populated with information on
each end-use, taken from published sources and industry experts.
2. Simulate the implementation of new, non-ODS technologies. The Vintaging Model uses
detailed characterizations of the past and existing uses of the ODSs, as well as data on
how the substitutes are replacing the ODSs, to simulate the implementation of new
technologies that ensure compliance with ODS phaseout policies. As part of this
simulation, the ODS substitutes (and/or products containing or made with these
substitutes) are introduced in each of the end uses overtime as needed to comply with the
ODS phaseout regulations.
3. Estimate emissions of the ODS substitutes. The chemical use is estimated from the
amount of substitutes that are required each year for the manufacture, installation, use or
June 2006 Revised 7. Methodology Page 7-25
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servicing of products. The emissions are estimated from the emission profile for each
vintage of equipment or product in each end-use. By aggregating the emissions from
each vintage, a time profile of emissions from each end-use is developed.
Estimating ODS Substitute Emissions in Other Countries
After U.S. emissions are calculated using the Vintaging Model, EPA uses the following
methodology to develop emission estimates for non-U.S. countries by building on the detailed
assessment conducted for the U.S. Details on the assumptions used at each step are included.
The general steps that EPA completed are included below in the general methodology, although
the methodology was modified for several sectors where necessary. Specific deviations from this
basic methodology are discussed following the general methodology description.
General Methodology
The following general steps are applied to estimate country-specific emissions. Steps 1 through 6
result in preliminary emission estimates calculated by Equation 1, below. The preliminary
estimates were adjusted based on a series of factors discussed in Steps 7 through 10.
1. Estimate the base level consumption of ODSs for each country or region, by chemical
group, in unweighted metric tons. UNEP (UNEP, 1999a) provided estimates of 1986 and
1989-1998 ODS consumption in terms of ozone depletion potential (ODP)-weighted totals
for the major types of ODSs: CFCs, HCFCs, halons, carbon tetrachloride, and methyl
chloroform. The data for 1989 were used because, in general, no substitution of ODS had
taken place yet.
2. Calculate the percent of unweighted base level ODS consumption of each chemical group
used in each end-use sector. The amount of ODS use in various industrial applications
differs by country. For developed countries, data on the end-use distributions of ODS in
1990 were available for the following countries:
U.S. from the Vintaging Model,
United Kingdom (U.K.) from U.K. Use and Emissions of Selected Halocarbons,
prepared for the Department of the Environment (March, 1996), and
Russia from Phaseout of Ozone Depleting Substances in Russia, prepared for the
Ministry for Protection of the Environment and Natural Resources of The Russian
Federation and the Danish Environmental Protection Agency (Russian Federation,
1994).
The 1990 end-use sector distribution for the U.S. was assumed to apply to Canada. The
U.K.'s distribution was applied to the EU-1511, Australia and New Zealand. Russia's
distribution was applied to the Former Soviet Union (FSU) countries and the non-EU-15
European countries. For developing countries, data on the 1990 consumption of ODS are
available for many nations by sector and substance from the Multilateral Secretariat. For
developing countries that do not have data available, EPA used a representative average.
In all cases, the 1990 distributions of ODS consumption across sectors were assumed to
be the same as 1989.
3. Calculate the unweighted base level consumption of ODS for each end-use sector (metric
tons). This step involves multiplying the amount of consumption of each chemical group
from Step 1 by the end-use sector distribution percentages from Step 2.
11 The EU-15 is defined as these European Union (EU) members: Austria, Belgium, Denmark, Finland, France, Germany,
Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
June 2006 Revised 7. Methodology Page 7-26
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4. Calculate the ratio of U.S. unweighted ODS substitute consumption (metric tons) to U.S.
base level unweighted ODS consumption (metric tons) for each end-use sector. The ratio
was taken from the Vintaging Model output.
5. Calculate the ratio of U.S. GWP-weighted substitute emissions (MtCO2eq) to U.S.
unweighted substitute consumption (metric tons) for each end-use sector. Similar to
Step 4, this ratio was taken from the Vintaging Model output.
6. Estimate GWP-weighted substitute emissions in a given year in MtCO2eq. This step
involves multiplying the country-specific unweighted base level consumption of ODS (Step
3) by the ratio of unweighted ODS substitute consumption to base level unweighted ODS
consumption (Step 4), and then multiplying that amount by the ratio of GWP-weighted
substitute emissions to unweighted substitute consumption (Step 5), as shown in the
following equation. EPA completed this calculation for each of the end-use sectors to
estimate the GWP-weighted substitute emissions in each year for each country.
Thus, this step produces preliminary estimates based on the general assumption that all
countries will transition away from ODS in a similar manner as the U.S. (e.g., CFC-12
mobile air conditioners transitioned to HFC-134a beginning in 1994 in the U.S. Thus, as a
first estimation, it is assumed that CFC-12 mobile air conditioners transition to HFC-134a
in other countries). In many cases, options for ODS substitutes in each end-use are
technically limited to the same set of alternatives, regardless of geographic region.
Furthermore, alternative technologies used in the U.S. are available and in many cases
are used worldwide. These assumptions may be adjusted in later steps to account for
differences between the U.S. and other countries, as explained below.
Equation 1:
County Specific Unweighted ODS Unweighted Substitute GWP-Weighted Substitute
Substitute Emissions = Consumption x Consumption x Emissions
(MtCO2eq) Unweighted ODS Unweighted Substitutes
Consumption Consumption
(Country-Specific) (US - based) (US - based)
(Step 3) (Step 4) (Step 5)
7. Develop and apply adjustment factors. In this analysis EPA applied adjustment factors to
modify the emission estimates for countries based on what is known qualitatively about
how their transition to alternatives, including MFCs, and technology preferences will likely
differ from that of the U.S. For example, EPA applied adjustment factors less than one to
refrigeration and air-conditioning end-uses, because some nations have been more likely
to use hydrocarbon refrigerants than MFCs and/or because some nations may choose
less emissive designs or practices. Also, HFC use in foams may be adjusted in some
cases because of the use of cyclopentane in lieu of MFCs. Adjustment factors greater
than one were applied to the EU-15 countries for fire-extinguishing in some years to
account for rapid halon decommissioning (and hence HFC uptake) in those countries.
Table 7-4 shows the adjustment factors used for each sector and country grouping.
June 2006 Revised 7. Methodology Page 7-27
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Table 7-4. Adjustment Factors Applied in Each Sector/Country
Ref/AC
Aerosols
Foams
Solvents
Fire-Ext.
Australia/New Zealand
European Union
Non-EU Europe
Canada
Japan
CEITs/Non-Annex 1
0.90
0.70a
0.75
1.00
0.70
0.80
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.40
1.00
1.00
1.00
1.00
1.00
0.80
0.50
1.00
1.00
0.50
1.00
1.00a
1.00
1.00
1.00
1.00
Some of the adjustment factors for the EU-15 vary by year and by region to account for European
Regulation 2037/2000 on Substances that Deplete the Ozone Layer. These adjustments are discussed in the
sector-specific methodologies section.
8. Develop timing factors. Since most developing countries and countries with economies in
transition (CEIT) will transition to substitutes more slowly, EPA reduced the adjusted
emission estimates by multiplying the results in each year by a timing factor to reflect the
assumed delay in their transition. Timing factors for CEIT and non-EU Europe countries
start at 25 percent in 1995 and increase by 25 percent at each 5-year interval, until they
reach 100 percent in 2010, when they are assumed to have caught up to the other Annex I
countries. Non-Annex I countries follow the same timing adjustments as CEIT and non-
EU Europe for the CFC phaseout, but have an even further delayed phaseout of the
HCFCs, to account for the fact that these countries can continue consuming new HCFCs
through 2040. These factors are outlined in Table 7-5.
Table 7-5. Timing Factors Applied to OPS Substitute Emissions
Region 1995
CEITs/Non EU-Europe
CFC 0.25
HCFC 0.25
Non-Annex I
CFC 0.25
HCFC 0.00
All Other Countries
HCFC 1.00
CFC 1.00
2000
0.50
0.50
0.50
0.00
1.00
1.00
2005
0.75
0.75
0.75
0.125
1.00
1.00
2010
1.00
1.00
1.00
0.25
1.00
1.00
2015
1.00
1.00
1.00
0.375
1.00
1.00
2020
1.00
1.00
1.00
0.50
1.00
1.00
9. Develop economic growth factors. Since other countries' economies are growing at
different rates than the U.S., EPA altered emissions based on comparisons between U.S.
and regional historical and projected GDP growth rates. The historical regional percent
changes in GDP are shown in Table 7-6 (USDA, 2002), and the projected regional growth
rates are shown in Table 7-7 (EIA, 2001).
Table 7-6. Annual Change in GDP Relative to Previous Year (Percent)
Region 1990
United States 1.15
Japan 5.08
Western Europe 2.94
Eastern Europe -2.20
Former Soviet Union -3.94
China 3.80
Other Asia 7.93
Latin America -0.40
Middle East 6.84
Africa 0.69
1991
-1.04
3.80
3.29
-10.01
-6.03
9.20
5.73
4.00
4.30
1.22
1992
2.75
1.02
0.97
-1.34
-13.32
14.20
5.60
2.93
6.61
0.91
1993
2.46
0.31
-0.40
1.83
-10.19
13.50
5.82
4.05
3.79
0.88
1994
3.74
0.64
2.83
3.00
-15.28
12.60
7.14
5.40
0.91
2.48
1995
2.37
1.47
2.49
4.18
-6.05
10.50
7.16
0.76
4.54
3.49
1996
3.40
3.92
1.60
1.75
-4.87
9.60
6.46
3.50
6.56
5.14
1997
4.40
0.85
2.45
3.73
0.03
8.80
4.77
4.85
3.97
2.53
1998
4.40
-2.50
2.70
3.17
-4.25
7.80
-1.89
2.17
2.41
2.63
1999
4.10
0.80
2.47
2.72
2.45
7.10
5.92
0.99
2.32
2.83
2000
4.10
1.50
3.38
3.83
7.75
8.00
6.29
3.87
6.01
3.35
Source: USDA, 2002
June 2006 Revised
7. Methodology
Page 7-28
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Table 7-7. Projected Regional Annual Growth Rates from 2001-2020 (Percent)
U.S.
Rate 3.1
Source:
10.
EIA, 2001
Estimate at
Western
Europe Japan
2.3 1.5
liusted GWP-weighte*
Other
China Asia
7.0
dODS
4.9
Middle
East Africa
4.3 3.9
Latin
America
4.2
Substitute emissions in a given year by regioi
Eastern
Europe
4.2
i and
Former
Soviet
Union
3.8
country. EPA estimated emissions and projections for each year by multiplying the
estimates in Step 6 by the adjustment factors (Step 7), the timing factors (Step 8), and the
growth factor (Step 9).
Sector-Specific Adjustments to General Methodology for ODS Substitutes
In addition to the adjustments discussed above, EPA adjusted the methodology for some sectors
to account for information that was available on a country or regional scale. These adjustments
are discussed by sector in more detail below.
Fire-Extinguishing
EPA adjusted global emissions in the fire extinguishing sector by region by developing Vintaging
Model scenarios that were representative of country-specific substitution data. In addition, EPA
adjusted emissions in the EU to account for the rapid halon phaseout due to regulation. Details of
these adjustments include the following:
1. To estimate baseline emissions, information collected on current and projected market
characterizations of international total flooding sectors was used to create country-specific
versions of the Vintaging Model (i.e., country-specific ODS substitution patterns). For this
report, current and projected market information on new total flooding systems in which
halons have been previously used was obtained. Information for Australia, Brazil, China,
India, Japan, Russia, and the U.K. was obtained from Halon Technical Options Committee
(HTOC) members from those countries.12 General information was also collected on
Northern, Southern, and Eastern Europe. Baseline emission information from some of
these countries was used to adjust the substitution patterns for all other non-U.S.
countries, as described below:
Eastern Europe: used as a proxy for the countries in the FSU and CEITs (except
Russia).
Australia: used as proxy for New Zealand.
Brazil: used as a proxy for countries in Latin America and the Caribbean.
China: used as a proxy for Taiwan.
India: used as a proxy for all other developing countries.
For all Annex I countries (other than the U.S.), the U.S. ODS substitution pattern was
used as a proxy.13
12 Fire protection experts in these countries provided confidential information on the status of national halon transition
markets and average costs to install the substitute extinguishing systems in use (on a per volume of protected space basis)
for 2001 through 2020.
13 This analysis assumes that, of the new total flooding protection systems in which halons have been previously used in
the U.S., the market is currently made up of approximately 33 percent HFC-227ea, 1 percent HFC-23, 14 percent inert gas,
and 52 percent other not-in-kind.
June 2006 Revised 7. Methodology Page 7-29
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2. An adjustment factor was applied to EU countries to account for European Regulation
2037/2000 on Substances that Deplete the Ozone Layer, which mandates the
decommissioning of all halon systems and extinguishers in the EU-15 by the end of 2003
(with the exception of those applications that are defined as critical uses). To reflect this,
the methodology assumes that all halon systems in the EU-15 will be decommissioned by
2004. No adjustments were made to the 10 countries that joined the EU in May 2004,
because expansion of the EU membership had not occurred at the time this analysis was
performed.
Refrigeration and Air-Conditioning
EPA applied three sector-specific adjustments to the refrigeration and air-conditioning sector,
described below. The first adjusts the emissions in the EU to account for the accelerated
phaseout of HCFCs, the second accounts for less refrigerant recovery (i.e., more venting) in
developing countries, and the third gives a greater degree of detail to the motor vehicle air-
conditioning end-use.
1. EPA assumed that countries in the EU-15 are in full compliance with EC-Regulation No.
2037/2000, stipulating that no new refrigeration and air-conditioning equipment be
manufactured with HCFCs as of January 1, 2002 (with the exception of two temporary
exemptions).14 The regulation also bans the use of HCFCs in the service of equipment
after January 1, 2015. Compliance with these regulations will likely lead to increased use
of HFCs to replace HCFCs, and is assumed to correspond to an increase in emissions of
20 percent in 2005, 15 percent in 2010, and 15 percent in 2020 relative to a BAU baseline.
These relative emission increases were determined by running a Vintaging Model
scenario wherein the uses of HCFCs were assumed to comply with the regulation. No
baseline adjustments were made to the 10 countries that joined the EU in May 2004,
because expansion of the EU membership had not occurred at the time this analysis was
performed.
2. An additional adjustment factor was applied to the estimates in CEITs, non-Annex I
countries and Turkey to account for increased emissions, compared to the U.S., which
results from a lack of recovery, recycling, and reclamation of refrigerants in these
countries.
These estimates assume that recovery does not occur in these countries in any small refrigeration
and air-conditioning units, but does occur in larger units, such as chillers. To calculate emissions
that would result if refrigerant from small stationary end-uses were not recovered, EPA used a
model developed to estimate the costs and benefits of recycling in the U.S. (the U.S. Clean Air Act
Section 608 Regulatory Impact Analysis model). Residential air-conditioners were omitted from
the calculations because they will transition away from HCFC-22 at a slower rate than in the U.S.
(timing factors to account for this slower HCFC phaseout are applied in Step 8, above).
Information on fleet size and emissions avoided per vehicle in the U.S. (Baker, 2002) was used to
determine the emissions avoided by recycling from motor vehicle air-conditioners (MVACs).
This scenario assumes that recycling efforts in developing countries and CEIT is currently
30 percent, and that these efforts will improve overtime, while recycling in the U.S. is assumed to
be 80 percent. The resulting adjustment factors are shown in Table 7-8.
Table 7-8. Recycling Adjustment Applied to Refrigeration Emissions Estimates
Country Group/Year
All Other Annex I
CEITs/Non-Annex I
2000
1.00
1.22
2005
1.00
1.22
2010
1.00
1.20
2015
1.00
1.18
2020
1.00
1.20
14 The ban was delayed until July 1, 2002 for fixed air-conditioning equipment with a cooling capacity of less than 100 kW,
and until January 1, 2004 for reversible air-conditioning/heat pump systems.
June 2006 Revised 7. Methodology Page 7-30
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3. Because the market penetration of air-conditioning into new vehicles is assumed to vary
among countries and regions,15 and because MVACs are assumed to account for a
different proportion of total refrigeration and air-conditioning emissions in the U.S.
compared to most other developed and developing countries, this end-use has been
modeled separately to achieve a higher degree of accuracy in MVAC emission estimates.
For selected countries, vehicle fleets were modeled based on a variety of available data
on international motor vehicle sales, air-conditioning usage, and refrigerant emissions.
These MVAC emission estimates by region were then used to determine the relative share
of refrigeration and air-conditioning emissions attributable to MVACs and to reapportion
emissions from all other end-uses accordingly, relative to the end-use breakout calculated
for the U.S. The methodology used to perform this analysis is explained in detail below.
For all countries except India and China, the number of operational MVACs was estimated based
on (1) annual historical sales of passenger cars and light trucks, as provided in Ward's (2001); and
(2) estimates of the percentage of the vehicle fleet equipped with air-conditioning, based on
quantitative and qualitative data provided in EC (2003); Hill and Atkinson (2003); OPROZ (2001);
and Barbusse, Clodic, and Roumegoux (1998). MVACs were assumed to increasingly penetrate
vehicle fleets overtime, as shown in Table 7-9 below.
Table 7-9. Percentage of Newly Manufactured Vehicles Assumed to Have Operational Air
Conditioning Units
Country/Region
Annex I countries (other than U.S.)
Latin America and Caribbean
All other non-Annex I countries,
Russia, and Ukraine (except China
and India)
2005
65.5
50.0
23.0
2010
70.0
55.0
28.0
2015
80.5
60.0
33.0
2020
95.0
65.0
38.0
Once the MVAC fleet was estimated by country/region, annual MVAC emissions were calculated
assuming the same annual average leak and service emissions as assumed for the U.S. (i.e., 10.9
percent).16 MVAC emissions at disposal are assumed to be 42.5 percent of the original MVAC
charge in developed countries and 69 percent in developing countries (as a result of zero recovery
assumed).17 All systems are assumed to use HFC-134a refrigerant in the baseline.
India and China were modeled slightly differently to account for the rapid economic growth
experienced in those countries in the past and expected for the future. Specifically, the following
methodology was used:
For India, MVAC fleet estimates were developed based on (1) data on MVAC sales prior
to 2004 from the Society of Indian Automobile Manufacturers (SIAM, 2005), (2) projected
annual growth rates of new vehicle sales, and (3) projected annual growth rates of air-
conditioning penetration. Based on these data, India's future vehicle fleet growth was
assumed to be 8 percent per year,18 while air-conditioning penetration was assumed to
increase linearly reaching 95 percent in 201019 and remaining at that level through 2020.
For China, MVAC estimates were based on data on Chinese production of vehicles with
MVACs from 1994 to 2004, provided by the China Association of Automobile
Manufacturers (2005). Because no future projections of vehicle fleet growth were readily
15 Except for Japan, which is assumed to have the same market penetration of MVACs into new vehicles as the U.S.
16 This emission rate includes emissions released during routine equipment operation from leaks, as well as those released
during the servicing of equipment by both professionals and do-it-yourselfers.
17 This percentage (69 percent) is the implied loss at disposal given the assumption that twice the original MVAC charge is
emitted over the course of a vehicle's lifetime in developing countries.
18 This growth rate is based on the annual growth rate of passenger vehicles (assumed to be linear) between 2000 and
2004, with the fleet size in 2000 based on Ward's (2001) and the fleet size in 2004 based on SIAM (2005).
19 Air-conditioning penetration was grown from 92 percent in 2004, based on data from SIAM (2005).
June 2006 Revised 7. Methodology Page 7-31
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available for China, the future growth rate of vehicles with air conditioning was assumed to
be the same as the fleet growth for India (8 percent per year).
Recently, an EC Directive has banned the use of HFC-134a in new models planned from 2011
onwards, and in all vehicles from 2017. Because this regulation was in draft when this analysis
was performed, it was not directly considered in developing baseline emissions from the
Refrigeration and Air Conditioning sector. Note, however, that other regulations and social factors
that may lead Europe to low-GWP refrigerants are considered in Step 7 above.
Solvents
EPA applied three sector-specific adjustments to the solvent sector. First, PFC/PFPE solvents are
assumed to be used in countries with significant annual output from the electronics industry.
Global PFC usage for solvent cleaning was geographically distributed using the semiconductor
industry as a proxy; specifically, data on the share of world silicon wafer starts per month (8-inch
equivalent) from SEMI International (2003) were used. Based on expert opinion, PFC/PFPE
solvent use is assumed to be discontinued by 2010 in the U.S. and by 2015 in other countries.
Second, emissions in the EU countries are assumed to equal only 80 percent of the preliminary
estimate to reflect that not-in-kind (NIK) technology has taken a more significant market share in
European countries (ECCP, 2001). Consequently, the resulting EU emission estimate was
reduced by 20 percent. This reduction is accounted for in the adjustment factors listed in
Table 7-3.
The third and final adjustment is a 50-percent adjustment factor that was applied to countries with
economies in transition (CEIT), European countries that are not members of the EU, and
developing (non-Annex I) countries. For these countries, the primary barriers to the transition from
ODS solvents to fluorinated solvents has been the high cost of HFC-4310mee and the lack of
domestic production (UNEP, 1999b; UNEP, 1999c). This reduction is accounted for in the
adjustment factors listed in Table 7-3.
Aerosols
Since the ban on CFC use in non-metered dose inhalers (MDI) aerosols caused the U.S. to
transition out of CFCs earlier than other countries, the U.S. consumption of ODS in 1990 for non-
metered dose inhalers (non-MDI) aerosols is equal to zero. In order to determine a non-zero
denominator for the ratio calculated in step 4, EPA used the unweighted U.S. consumption of non-
MDI ODS substitutes (including a large market segment that transitioned into non-GWP, non-ODP
substitutes) as a proxy for U.S. 1990 non-MDI ODS consumption. This assumption is valid if it is
assumed that the market size of U.S. non-MDI aerosols was not affected by the transition from
ODS to ODS substitutes. For countries other than the U.S., it was assumed that 15 percent of the
non-MDI aerosols ODS consumption transitioned to MFCs, while the remainder was assumed to
transition to NIK or hydrocarbon alternatives.
Foams
Most global emissions were estimated in the foam-blowing sector by developing Vintaging Model
scenarios that were representative of country- or region-specific substitution and consumption
patterns. To estimate baseline emissions, current and projected characterizations of international
total foams markets were used to create country or region-specific versions of the Vintaging
Model. The market information was obtained from Ashford (2004), based on research conducted
on global foam markets. Scenarios were developed for Japan, Europe (both EU and non-EU
countries combined), other developed countries (excluding Canada), CEITs, and China. It was
assumed that other non-Annex I countries would not transition to MFCs during the scope of this
analysis. Once the Vintaging Model scenarios had been run, the emissions were disaggregated to
a country specific level based on estimated 1989 CFC consumption for foams developed for this
analysis. Emission estimates were adjusted slightly to account for relative differences in countries'
economic growth as compared to the U.S. (step 9 above).
June 2006 Revised 7. Methodology Page 7-32
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Appendices D-1 to D-6 present historical and projected emissions for all countries for ODS
Substitutes: aerosols (MDI), aerosols (non-MDI), fire-extinguishing, foams, refrigeration and air
conditioning, and solvents.
7.3.3 HFC-23 Emissions as a Byproduct of HCFC-22 Production
Background
Trifluoromethane (HFC-23) is generated and emitted as a byproduct during the production of
chlorodifluoromethane (HCFC-22). HCFC-22 is used both in emissive applications (primarily air
conditioning and refrigeration) and as a feedstock for production of synthetic polymers. Because
HCFC-22 depletes stratospheric ozone, its production for non-feedstock uses is scheduled to be
phased out under the Montreal Protocol. However, feedstock production is permitted to continue
indefinitely.
Nearly all producers in developed countries have implemented process optimization or thermal
destruction to reduce HFC-23 emissions. In a few cases, HFC-23 is collected and used as a
substitute for ozone-depleting substances, mainly in very-low temperature refrigeration and air
conditioning systems. Emissions from this use are quantified under air conditioning and
refrigeration and are therefore not included here. HFC-23 exhibits the highest global warming
potential of the HFCs, 11,700 under a 100-year time horizon, with an atmospheric lifetime of
264 years.
Estimating HFC-23 Emissions in the United States
Historical Activity Data
For both No-Action Baseline and Technology-Adoption Baseline, information on historical (1990-
2003) U.S. HCFC-22 production and historical U.S. HFC-23 emission estimates was reported to
EPA by HCFC-22 manufacturers under a voluntary agreement.
Projected HFC-23 Emissions in the United States - No-Action Baseline
EPA based emission projections on projections of HCFC-22 production and HFC-23 emission
rates, as described below. U.S. feedstock production was projected using a growth rate of
2 percent, which is close to the historical average growth rate for feedstock between 1996 and
2003. Non-feedstock U.S. production was phased out according to the projections of the 2005
version of the Vintaging Model of ODS and their alternatives. Emissions of HFC-23 at plants
where abatement is not implemented are assumed to be 2 percent of HCFC-22 production.
Projected HFC-23 Emissions in the United States - Technology-Adoption Baseline
For projections under the Technology-Adoption Baseline, EPA estimated emissions of HFC-23 for
2004-2010 by assuming that the emission rate declined linearly from the 2000 level of 1.36
percent to 0.76 percent in 2010. The latter value is the lowest collective U.S. industry emission
rate ever achieved. For 2011-2020, emissions were estimated by assuming that the emission rate
remained flat at 0.76 percent in those years. This implies a market penetration of 65 percent by
thermal oxidation, based on an assumed baseline emission rate of 2 percent and an abatement
efficiency of 95 percent.
Estimating HFC-23 Emissions in Other Countries
This section presents assumptions used for estimating non-U.S. historical and projected activity
data (i.e., country-specific levels of HCFC-22 production). Activity data are assumed to be the
same for both the No-Action Baseline and the Technology-Adoption Baseline.
June 2006 Revised 7. Methodology Page 7-33
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Historical Activity Data
EPA estimated historical emissions for 1990, 1995, and 2000 based on available 1990, 1995, and
90
1999 country-specific HCFC production data as reported to the United Nations Environmental
Program (UNEP) Ozone Secretariat: global production of HCFC-22 and other HCFCs reported to
the Alternative Fluorocarbons Environmental Acceptability Study (AFEAS); and 2001 country-
specific production capacity information from the Chemical and Economics Handbook (2001)
(Oberthur, S., 2001; AFEAS, 2001; CEH, 2001).21 The UNEP-reported HCFC production data
were used as the foundation of the 1995 and 1999 production estimates.
For India and Russia, which are not included in AFEAS surveys, and for Latin America (Mexico,
Brazil, and Venezuela), all of the UNEP-reported HCFC production was assumed to consist of
HCFC-22 (World Bank, 2002).22 For other countries included in AFEAS surveys, the UNEP-
reported HCFC production was pooled, and then AFEAS data were used to estimate the share of
this HCFC production that is HCFC-22. The CEH country-specific production capacities were then
used to allocate this production to individual countries.
Finally, 20 percent was added to the production estimates for each country to account for
feedstock production, which is not included in UNEP or AFEAS reports.
Appendix 1-1 presents historical HCFC-22 production activity data.
Projected Activity Data
For all countries except the U.S., China, and Japan23, HCFC-22 production from 1999 was used
as a baseline to project future emissions. Non-feedstock and feedstock production were projected
separately.
The method for projecting HCFC-22 production was as follows:
Project Non-Feedstock Production. To project non-feedstock production, EPA applied the
following assumptions:
For developed countries other than the U.S., Japan, and Greece, non-feedstock
production was assumed to decrease linearly after 1999 so that complete phaseout
occurred by the phaseout date for that country (2015 for most European countries and
2020 for other developed countries and CEIT).
> For Japan, 2005 production data were provided by the Japan Industrial Conference for
Ozone Layer and Climate Protection (JICOP, 2006). JICOP reported that 20 percent
of Japan's 2005 HCFC-22 production was for non-feedstock uses. This fraction was
assumed to decrease linearly to 0 by 2020.
> For Greece, the single HCFC-22 production facility was reported to have closed in
early 2006 (Campbell, 2006). Thus, this analysis assumed that all HCFC-22
production in Greece stopped in 2006 as a result of the plant closure.
20 2000 activity data were based on reported information for 1999. To obtain 2000 production estimates, 1999 production
was grown for one year at the growth rates discussed in the next section.
21 Production estimates for India were based on a later version of the UNEP data (Oberthur, S., 2001), because India had
not reported 1999 HCFC production in time for the 2000 version.
22 For South Korea, which is not included in AFEAS surveys but is known to manufacture several HCFCs, estimates were
based on reported HCFC-22 production (CEH, 2001).
23 Production estimates for China were based on the 2003 actual production data reported on the IPCC/TEAP Special
Report on Safeguarding the Ozone Layer and the Global Climate System (SROC, 2005). Production estimates for Japan
were provided by JICOP (2006).
June 2006 Revised 7. Methodology Page 7-34
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For developing countries other than China, non-feedstock production was assumed to
increase at the expected rate of growth of the GDP (World Bank, 2001) for that country
until 2015, the date when developing countries must begin phasing out HCFCs. After
2015, this production was assumed to decrease linearly so that complete phaseout
occurred by 2040.
> For China, 2000 production was derived in the same way as for other developing
countries. To derive 2005 and 2010 production, the 2003 production data from SROC
(2005) was grown linearly to reach the 2003 SROC-reported production capacity of
200,000 tons in 2010. Production for 2015 was estimated by growing the 2010
production at the expected rate of growth of GDP for China. After 2015, non-
feedstock production was assumed to decrease linearly so that complete phaseout
occurred by 2040.
Project Feedstock Production: To project feedstock production, EPA applied the following
assumptions:
For developed countries other than Japan and Greece, production of HCFC-22 for
feedstock materials was assumed to grow at 2.5 percent per year (the anticipated growth
of "chemical products" in the U.S. in the 2001 Annual Energy Outlook) (EIA, 2001).
> For Japan, 2005 production data were provided by JICOP (2006). JICOP reported that
80 percent of Japan's 2005 HCFC-22 production was for feedstock. Feedstock
production beyond 2005 was assumed to grow at 2.5 percent per year as described
above.
> For Greece, the single HCFC-22 production facility was reported to have closed in
early 2006 (Campbell, 2006). Thus, this analysis assumed that all HCFC-22
production in Greece stopped in 2006 as a result of the plant closure.
Developing country production of HCFC-22 for feedstock materials was assumed to grow
at the expected rate of growth of the GDP for that country.
> For China, 2000 production was derived in the same way as for other developing
countries. To derive 2005 and 2010 production, the 2003 production data from SROC
(2005) was grown linearly to reach the 2003 SROC-reported production capacity of
200,000 tons in 2010. Feedstock production for 2015 and 2020 was estimated by
growing the 2010 production at the expected rate of growth of GDP for China.
Emission Factors and Related Assumptions
To estimate and project emissions of HFC-23, the HCFC-22 production levels estimated above
were multiplied by emission factors (i.e., tons of HFC-23 emitted per ton of HCFC-22 produced).
In some cases the emission estimate was reduced due to assumed market penetrations of thermal
abatement technologies. These emission factors and other assumptions are discussed below.
Historical Emission Factors
The emission factor for estimating 1990 and 1995 emissions was assumed to be 2 percent for
developed countries and 3 percent for developing countries, based on reports from manufacturers
and other sources (U.S. EPA, 2001; Rand et al., 1999). Russia was assumed to have an emission
rate of 3 percent, based on country-specific information (Ahmadzai, 2000).
Projected Emission Factors - No-Action Baseline
To reflect the adoption of thermal oxidation technology between 1995 and the present, EPA
assumed that current emission rates had been reduced relative to historical emission rates in
some regions. In the No-Action Baseline, current emission rates were then assumed to be
June 2006 Revised 7. Methodology Page 7-35
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maintained through 2020. The following levels of abatement were incorporated into the analysis in
the No-Action Baseline:
For developing countries and Russia, the HFC-23 emission rate was kept constant at 3
percent between 2000 and 2020.
In 2000, the baseline market penetration of thermal oxidation was estimated to be
100 percent in France, Germany, Italy and the Netherlands; 75 percent in the U.K.; and
0 percent in Spain and Greece (Harnisch and Hendriks, 2000). Except for the U.K., these
levels were assumed to be maintained through 2020. In 2005, the baseline market
penetration of thermal oxidation in the U.K. was estimated to be 87.5 percent. This was
intended to reflect the 2005 commissioning of a thermal oxidizer at the one U.K. plant that
had not had one previously (Campbell, 2006). In 2006 and following years, the level of
baseline market penetration in the U.K. was estimated to be 100 percent.
In 2000, Japan had no thermal oxidation. However, by 2002, Japan had installed thermal
oxidation for an estimated 25 percent of its HCFC-22 production (JICOP, 2004). By 2005,
Japan had increased the level of thermal oxidation to 65 percent and the level of capture
(for use) to about 35 percent (JICOP, 2006). This level of abatement was assumed to
remain constant through 2020.
Projected Emission Factors - Technology-Adoption Baseline
Future climate policies in many countries are likely to increase levels of thermal oxidation and
thereby lower HFC-23 emission rates below current levels. This analysis quantifies future HFC-23
emission reductions that have been announced, although it does not attempt to quantify future
emission reductions that may occur but that have not yet been announced. Therefore, in addition
to the thermal oxidation modeled for the No-Action Baseline, EPA modeled the following levels of
thermal oxidation for the Technology-Adoption Baseline:
HCFC-22 producers in several developing countries have agreed to host mitigation
projects funded by developed countries under the Clean Development Mechanism (COM)
of the Kyoto Protocol. The HFC-23 abatement projects considered in this analysis are
either registered or are in the process of being registered in the COM pipeline. For all
countries hosting such projects, including China, India, Mexico and Korea, it was assumed
that all currently-identified COM projects are implemented starting in 2010. The absolute
level of abatement (in MtCO2eq) was assumed to remain constant through 2020.
The HCFC-22 manufacturer in Spain has announced its intent to install thermal oxidation
on its Spanish plant by 2010 (Campbell, 2006). Thus, the baseline market penetration of
thermal oxidation was assumed to be 100 percent in Spain in 2010 and 2020.
Uncertainties and Sensitivities
In developing these emission estimates, EPA made use of multiple international data sets,
country-specific information on abatement levels (where available), the IPCC/TEAP Special Report
on Safeguarding the Ozone Layer and the Global Climate System, and the IPCC guidance on
estimating emissions from this source. Nevertheless, uncertainties exist in both the activity data
and the emission rates used to generate these emission estimates. Although EPA used four
separate sources to estimate country-by-country production of HCFC-22 (UNEP-re ported, country-
specific HCFC production; AFEAS-reported global production of HCFC-22 and other HCFCs;
country-by-country production capacities from the Chemical and Economics Handbook; and the
IPCC/TEAP Special Report on Safeguarding the Ozone Layer and the Global Climate System),
none of these sources is comprehensive. Specifically, none provide country-by-country production
of HCFC-22 for all countries.
Future production levels, emission rates and abatement levels are particularly uncertain. Future
policies (e.g., under the Montreal Protocol) could affect total production of HCFC-22 and therefore
June 2006 Revised 7. Methodology Page 7-36
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emissions of HFC-23. Changing emission rates may also have a significant impact on emissions.
In the Technology-Adoption Baseline, EPA assumed that currently identified COM projects will be
implemented in China, India, Korea and Mexico. However, even after implementation of these
projects, significant reduction opportunities remain, both in these countries and elsewhere. There
is a significant probability that many of these emissions will be averted, either through COM or
other mechanisms. In this case, HFC-23 emissions will be lower than projected in the
Technology-Adoption Baseline.
Appendices D-7 and D-7b present historical and projected emissions for all countries for this
source for the Technology-Adoption and No-Action Baselines.
7.3.4 Sulfur Hexafluoride (SFe) Emissions from Electric Power Systems
Estimating Historical Global SFe Emissions
To estimate global emissions from use of electrical equipment,24 EPA used the 2004 RAND survey
of global SF6 sales to electric utilities and equipment manufacturers, estimates of net electricity
consumption, and the following equation, which is derived from the equation for emissions in the
IPCC Good Practice Guidance (IPCC, 2000):
Emissions = SF6 purchased to refill existing equipment + nameplate capacity of retiring equipment. 25
Note that the above equation holds whether the gas from retiring equipment is released or
recovered. If the gas is recovered, it is used to refill existing equipment, lowering the amount of
SF6 purchased by utilities for this purpose.
Gas purchases by utilities and equipment manufacturers from 1961 to 2003 are available from the
2004 RAND survey (Smythe, 2004). For the SF6 markets represented in the RAND survey
(believed to include all SF6-using countries except Russia and China), SF6 purchased to refill
existing equipment in a given year was assumed to be approximately equal to the SF6 purchased
by utilities in that year.26 To estimate the quantity of SF6 released or recovered from retiring
equipment, the nameplate capacity of retiring equipment in a given year was assumed to equal
77.5 percent of the amount of gas purchased by electrical equipment manufacturers 40 years
previous (e.g., in 2000, the nameplate capacity of retiring equipment was assumed to equal
77.5 percent of the gas purchased by original equipment manufacturers (OEMs) in I960).27 The
remaining 22.5 percent was assumed to have been emitted at the time of manufacture. The 22.5
percent emission rate is an average of IPCC SF6 emission rates for Europe and Japan for years
24 This report does not include emissions from the manufacture of electrical equipment.
25 According to the IPCC Good Practice Guidance, emissions from electrical equipment can be summarized by the
following equation:
Emissions = Annual Sales of SF6 - Net Increase in nameplate (SF6) capacity of equipment
- SF6 stockpiled or destroyed
where
Annual Sales = SF6 purchased to fill new equipment + SF6 purchased to refill existing equipment;
Net Increase in nameplate capacity = nameplate capacity of new equipment-nameplate capacity of retiring
equipment; and
SF6 stockpiled or destroyed = SF6 stockpiled or recovered from electrical equipment and destroyed
In general, the quantity of SF6 destroyed is believed to be small compared to the other quantities in the equation. In
addition, if no gas from retiring equipment is used to fill new equipment, then the quantity of new SF6 used to fill new
equipment is equal to the nameplate capacity of the new equipment. In this case, the IPCC equation simplifies to the
expression above.
26 Recent communications with electrical equipment manufacturers indicate that a small but increasing fraction of new
equipment is now filled with gas purchased by utilities rather than by equipment manufacturers. In this analysis, EPA
assumed that in 1999, one percent of new equipment was filled using gas purchased by utilities and that by 2003, this
fraction had grown to five percent. This assumption has the effect of decreasing estimated global refills and emissions by
11 percent in 2003.
27 The volume of SF6sold for use in new equipment before 1961 was assumed to have risen linearly from 0 in 1950 to 91
tons in 1961, the first year for which the RAND survey has data.
June 2006 Revised 7. Methodology Page 7-37
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before 1996 (IPCC, 2000). The 40-year lifetime for electrical equipment is drawn from Reductions
ofSF6 Emissions from High and Medium Voltage Electrical Equipment in Europe (Ecofys, 2005).
To reduce the potential impact of inventory fluctuations on the estimates, EPA applied three-year
smoothing to both the utility and the OEM sales figures. The results of the two components of the
above equation were then summed to yield estimates of total SF6 emissions for all of the countries
represented in the RAND survey from 1990 to 2003.
To estimate total global emissions, EPA also estimated SF6 emissions from Russia and China,
which are not included in the RAND survey. In the absence of more specific data, EPA assumed
Russian and Chinese emissions were proportional to the net electricity consumption of these
countries. Estimates of net electricity consumption were available from the Energy Information
Administration (EIA, 2002; EIA, 2001 a). To obtain global emissions, the total emissions derived
for the countries represented in the RAND survey were multiplied by the ratio of total global net
electricity consumption (including Russia and China) to global net electricity consumption
excluding Russia and China. This increased the estimate of annual global emissions by
approximately 16 percent.
According to a recent report from China's Energy Research Institute (ERI), China's 2003
production of SF6 was 2,150 tons (ERI, 2006). The total 2003 production reported by the RAND
survey was 6,438 tons. Summing together the Chinese and RAND estimates, Chinese SF6
production accounted for 25 percent of global SF6 production in 2003. The ERI did not provide
information on how this SF6 was used, and China may have applied it to a number of end-uses
other than use of electrical equipment. These include manufacture of electrical equipment,
production and processing of magnesium, production of semiconductors, and export for these and
other uses (e.g., manufacture of flat panel display in other Asian countries). However, the large
production figure certainly does not contradict the 16 percent add-on for electric power systems
used in this analysis, which is intended to account for Russia as well as China.
See Appendix I-2 for historical activity data for electric power systems - net electricity consumption
by selected countries.
Estimating Historical Country-by-Country SF6 Emissions
United States
EPA estimated current and historical SF6 emissions in the U.S. electric power system based on
data obtained from the EPA's SF6 Emissions Reduction Partnership for Electric Power Systems.
Participants in the Partnership, which together account for 35 percent of U.S. high-voltage
transmission miles, annually report their emissions to EPA. These emissions are then
extrapolated to the U.S. as a whole using a regression equation that relates emissions to miles of
high-voltage transmission lines. These data are discussed in more detail in the Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2003 (U.S. EPA, 2005a).
EU-25+328
Emission estimates for the EU-25 and Norway, Switzerland, and Iceland (i.e., EU-25+3) were
based on those provided for equipment use and decommissioning in "Reductions of SF6
Emissions from High and Medium Voltage Electrical Equipment: Final Report to CAPIEL" (Ecofys,
2005). The Ecofys study relied on bottom-up estimates of emission rates and of the SF6 bank in
equipment, both of which varied by region and overtime. The study supplemented published
information and national reporting with surveys of electrical equipment manufacturers and users.
The Ecofys report provided estimates on a regional level (EU-1529, EU+10, +3) for the years 1995,
2003, 2010, and 2020. For this analysis, estimates were extrapolated or interpolated to obtain
28 The EU-25+3 includes the 25 member countries of the European Union (EU) and Norway, Switzerland, and Iceland.
Appendix I contains a complete list of EU countries.
29 The EU-15 includes these European Union (EU) members: Austria, Belgium, Denmark, Finland, France, Germany,
Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, and the United Kingdom.
June 2006 Revised 7. Methodology Page 7-38
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values for 1990, 2000, 2005, and 2015, and regional totals were disaggregated to the country level
using either country-specific data (for Germany) or GDP (for all other countries).30 To estimate
1990 emissions from the EU-15 and from Norway, Switzerland, and Iceland, German trends
between 1990 and 1995 were applied. 1990 emissions from the EU-1031 were assumed to have
been the same as in 1995.
Emission estimates for Japan were obtained from Recent Practice for Huge Reduction ofSF6 Gas
Emission from GIS & GCB in Japan (Yokota et al., 2005). This paper includes information on both
historical emissions and efforts to reduce those emissions overtime.
All Other Countries
For all countries except the U.S., Japan, and the EU-25+3, historical emissions (1990-2000) from
electrical equipment were estimated using world sales of SF6 to electrical utilities and net
electricity consumption data (Smythe, 2004; EIA, 2002; EIA, 2001 b). Country-specific SF6
emissions were estimated using the following assumptions:
Global emissions were estimated as described above;
Emissions from the U.S., Japan, and the EU-25+3, were subtracted from this total; and
The remaining emissions were allocated to the remaining countries according to each
country's share of world net electricity consumption (minus the net consumption of the
U.S., Japan, and the EU-25+3). Country-specific electricity consumption data for the
period 1990 to 2000 was obtained from the International Energy Outlook 2002 (EIA,
2002). For those countries not reported in EIA (2002), electricity consumption data were
obtained from the International Energy Annual 2001 (EIA, 2001 b).
Projected Emissions - Technology-Adoption Baseline
Since the mid-to-late 1990s various developed countries have implemented voluntary (and in
some cases, mandatory) programs aimed at reducing SF6 emissions from electric power systems.
These countries include the U.S., Japan, and the EU-25+3. To model the successful attainment of
developed country SF6 reduction goals, a Technology-Adoption Baseline was developed.
United States
For the U.S., EPA assumed that emissions would decline overtime as new, small, leak-tight
equipment gradually replaced old, large, leaky equipment, and as many utilities implemented
reduction measures under EPA's SF6 Emissions Reduction Partnership for Electric Power
Systems (U.S. EPA, 2005b).
EU-25+3
For the EU 25+3, emissions projections are based on those presented for equipment use and
decommissioning in the "Additional Voluntary Action" scenario of the Ecofys study (Ecofys, 2005).
These projections reflect the increasing implementation of reduction measures both historically
(starting in 1995) and in the future. Implementation is assumed to be complete by 2010. The
measures include operator training, equipment repair and replacement, improved gas recycling
techniques (deep recovery), and a decommissioning infrastructure. As in the U.S., the projections
also reflect the increasing leak-tightness of new equipment.
30 Ecofys indicated that within the three European regions, GDP was a slightly better predictor of emissions than net
electricity consumption.
31 The EU-10 includes these EU members: Poland, Hungary, Czech Republic, Slovak Republic, Lithuania, Latria, Slovenia,
Estonia, Cyprus, and Malta.
June 2006 Revised 7. Methodology Page 7-39
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In early 2006, the European Parliament and Council agreed to a regulation on fluorinated
greenhouse gases that requires both operator training and "proper" recovery of SF6 during
equipment servicing and decommissioning. The regulation was expected to be adopted by mid-
2006. In view of this, it appears likely that operator training and gas recycling will be increasingly
implemented throughout the EU-25.
For Japan, estimates were obtained from T. Yokota (2006) and reflect the increasing
implementation of reduction measures both historically (starting in 1995) and in the future.
Japan's 2005 emissions from use of electrical equipment were 13 tons of SF6, considerably below
its original Voluntary Action Plan target for 2005 (set in 1998) of 40 tons SF6 from use (Maruyama,
2001). Emissions were assumed to remain constant at their 2005 level through 2020 (Yokota,
2005). Because the SF6 bank in Japan is expected to grow substantially during the same period,
EPA assumed that implementation of reduction measures would increase in order to maintain this
emission level through 2020.
Other Developed Countries
For the technology adoption scenario, EPA assumed that country-specific SF6 emissions would
grow at different rates in developed and developing countries. For all developed countries except
the U.S., Japan, and the EU-25+3, EPA assumed that emissions would remain constant from
2003 levels through 2020. That is, any system growth was expected to be offset by decreases in
the equipment's average SF6 capacity and emission rate as new, small, leak-tight equipment
gradually replaced old, large, leaky equipment.
Developing Countries
For developing countries, which began to install SF6 equipment relatively recently, all current
equipment was assumed to be new. Consequently, as infrastructure expanded, emissions from
developing countries were estimated to grow at the same rate as country- or region-specific net
electricity consumption projections (EIA, 2002).
Projected Emissions - No Action Baseline
In the No-Action Baseline, estimates represent a hypothetical scenario in which voluntary actions
described in the Technology-Adoption Baseline are not implemented. Consequently, emissions
for the U.S., Japan, the EU-25+3, continue at levels that assume no additional reduction measures
are implemented after the base year.
United States
For the No-Action baseline, U.S. emissions projections through 2020 were estimated based on the
hypothetical assumption that no additional reduction measures were implemented after 1999.
EU-25+3
For the EU 25+3, emissions projections were based on those presented for equipment use and
decommissioning in the "Business As Usual 2003" scenario of the Ecofys study (Ecofys, 2005).
These projections reflect the historical implementation of reduction measures through 2003, but no
additional implementation. Under this scenario, emissions rise slightly between 2003 and 2010 as
the bank of SF6 in equipment increases, but emissions between 2010 and 2020 are assumed to
be constant.
For Japan, 2005 and 2010 No-Action emissions estimates were developed based on the
Technology-Adoption estimates supplied by T. Yokota. The Japanese No-Action estimates were
assumed to have the same relationship to the Japanese Technology-Adoption estimates as the
June 2006 Revised 7. Methodology Page 7-40
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EU-25+3 No-Action (i.e., 2003 BAD) estimates had to the EU-25+3 Technology-Adoption
estimates. That is, EPA assumed that in the Technology-Adoption scenario, Japan would achieve
the same relative (percent) emissions reductions through implementation of additional voluntary
measures as the EU-25+3 countries would achieve in their Technology-Adoption scenario relative
to their No-Action scenario. This is a reasonable assumption, because by 2003, Japan and the
EU countries had implemented reduction measures to approximately the same extent (Ecofys,
2005; Yokota et al., 2005). Consequently, the No-Action Baseline for Japan was calculated by
multiplying the Technology-Adoption Baseline for Japan by the ratio between the EU-25+3 No-
Action and Technology-Adoption Baselines. Emissions were then held constant through 2020 to
reflect the stabilization of regional bank growth.
All other countries
Emissions projections estimates for 2005 through 2020 for all other developed and developing
countries remain the same as under the Technology-Adoption scenario. Again, it is assumed that
in developing countries, emissions will increase with infrastructure growth, while in developed
countries, emissions will hold steady as system growth is countered by decreases in the
equipment's average SF6 capacity and emission rate.
Uncertainties and Sensitivities
In developing these emission estimates, EPA made use of multiple international data sets and
IPCC guidance on estimating emissions from this source. The bottom-up estimates used for the
U.S., Japan, and the EU-25+3 are believed to be reasonably robust, with uncertainties for the U.S.
historical estimates in the range of-20/+40 percent for the EU-25+3 (Harnisch, 2006) and ±15
percent for the U.S. (U.S. EPA, 2005). Nevertheless, this analysis is subject to a number of
uncertainties that affect both global and country-specific emission estimates, particularly estimates
for countries other than the U.S., Japan, and the EU-25+3.
First, the SF6 manufacturers represented in the RAND survey do not represent 100 percent of
global SF6 production and consumption. EPA has attempted to account for unreported Chinese
and Russian SF6 production, consumption, and emissions by assuming that they have the same
relationship to these countries' net electricity consumption that emissions appear to have to net
electricity consumption in the rest of the world. However, this assumption is itself subject to
uncertainty. One source of this uncertainty is the fact that net exports from or imports into Russia
and China affect the relationship between SF6 consumption and net electricity consumption in the
rest of the world. Net exports from Russia and China would make the "consumption factor" (SF6
consumption/net electricity consumption) in the rest of the world appear to be smaller than it
actually is, while net imports would do the reverse. Information from manufacturers of electrical
equipment indicates that exports from Russia and China have fluctuated overtime, peaking
around 2000 and declining more recently. Thus, the apparent dip in global emissions between
1995 and 2000, and the subsequent rise between 2000 and 2005, may be partly an artifact of
these export trends rather than purely a result of changes in emissions from electric power
systems.32 Another source of uncertainty is that the relationship between SF6 emissions and net
electricity consumption varies from country to country, even when imports and exports are properly
accounted for.33
Second, the RAND survey's attribution of SF6 sales to particular end uses is also uncertain,
because SF6 manufacturers frequently sell to distributors rather than directly to end-users.
Although manufacturers would be expected to have a reasonably good understanding of their
markets, this understanding is not always perfect. Thus, some of the SF6 sales that are attributed
in the survey to utilities may actually have been to other uses, or vice versa.
32 The bottom-up studies cited above indicate that emissions from this sector did decline between 1995 and 2000, and
atmospheric studies confirm that emissions declined globally (Maiss and Brenninkmeijer, 2000). Other atmospheric studies
indicate that emissions increased after 2000 (Peters et. al, 2005). However, the post-2000 increase may be from other
sectors, e.g., magnesium or electronics.
33 S. Reiman and M. Vollmer of EMPA have performed a preliminary analysis of this relationship, comparing the SF6
emission reported through national inventories to the net electricity consumption reported by EIA. They find that the ratios
between these two values vary by more than a factor of ten.
June 2006 Revised 7. Methodology Page 7-41
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Third, the typical lifetime of electrical equipment, and therefore the amount of equipment that is
now being retired, is uncertain. This analysis uses a lifetime of 40 years (Ecofys, 2005); however,
other estimates place the lifetime at 30 years (IPCC, 2000). The difference is important because
the amount of equipment built 40 years ago is considerably smaller than that built 30 years ago. If
the average lifetime of equipment were assumed to be 30 years in this analysis, then the estimate
of 2003 global emissions would increase by almost 25 percent.
Fourth, for countries other than the U.S., Japan, and EU-25+3, EPA assumes that each country's
share of past and current global emissions is directly proportional to that country's share of past
and current global net electricity consumption. In fact, as noted above, the relationship between
emissions and electricity consumption varies between regions and overtime, particularly as
regions make efforts to reduce their emission rates. Thus, this analysis may err in its allocation of
global emissions to individual regions.
Finally, emission projections are based on the assumptions that emissions in developing countries
will grow with those countries' net electricity consumption. However, the application, design, and
maintenance of equipment all affect equipment banks and emission rates. All may change over
time, altering current trends.
Appendices D-8 and D-8b present historical and projected emissions for all countries for this
source for the Technology-Adoption and No-Action Baselines.
7.3.5 Perfluorocarbon (RFC) Emissions from Primary Aluminum Production
EPA calculated country-specific emission estimates from primary aluminum production using
historical and forecasted production data and cell type-specific emission factors. This section first
discusses the historical and projected activity data utilized. Next, it discusses the methodology
used to develop PFC emission factors for historical and projected emissions. In particular, this
section details the Technology-Adoption and No-Action Baselines for aluminum production, which
are based on different assumptions regarding the adoption of technology retrofit options in the
baseline.
Historical Activity Data
EPA estimated historical U.S. primary aluminum production based on data from the EPA's
Voluntary Aluminum Industrial Partnership (VAIP). For all other aluminum-producing countries,
except Western Europe, Eastern Europe, and the FSU, historical aluminum production estimates
for 1990, 1995 and 2000 were obtained from International Aluminum Institute (IAI) surveys (IPAI,
1998; IAI 2002; IAI 2005a). Region and country-specific aluminum production was disaggregated
to cell type using information provided by the International Energy Agency (IEA, 2000). However,
the shares of production represented by two cell types, Side-Worked Prebake (SWPB) and Point-
Feed Prebake (PFPB), were adjusted to better reflect the global technology trends observed from
1990 to 2003 in the IAI surveys. In each region, EPA assumed the share of SWPB production
declined linearly by approximately 6 percent per year (expressed as a fraction of the 1990 SWPB
production share in that region) between 1990 and 2000 (IAI, 2000; IAI, 2005b). Globally, this
adjustment resulted in a decline in the SWPB share from 13.9 percent to 7.2 percent between
1990 and 2000, which is comparable to the decline in the SWPB share observed between 1990
and 2000 in the IAI surveys, from 14.7 percent to 7.7 percent. In each region, the share of
production lost by SWPB was assumed to be taken up by PFPB. This is consistent with the trends
observed in the IAI surveys. For Western Europe, Eastern Europe, and the Former Soviet Union
(FSU), production estimates by cell type were obtained from the European Aluminum Association
(Nordheim, 1999).
Appendix I-3 contains historical aluminum production activity data.
Projected Activity Data
For all countries except China and the U.S., Vertical Stud Soderberg (VSS), Horizontal Stud
Soderberg (HSS) and Center-Worked Prebake (CWPB)-specific production projections for 2005 to
June 2006 Revised 7. Methodology Page 7-42
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2020 were drawn from Greenhouse Gas Emissions from the Aluminum Industry (IEA, 2000).
These data were estimated based upon anticipated expansion of smelter capacity, smelter
closings, and regional changes in aluminum demand. Primary aluminum demand by region was
forecasted using regional Gross Domestic Product projections (IEA, 2000). Due to the significant
growth in Chinese aluminum production between 2000 and 2005 (i.e., over 100 percent), EPA
updated IEA (2000) estimates for China using recent IAI production statistics (IAI 2005a). Since
this level of growth cannot be sustained indefinitely, EPA assumed that technology-specific
production in China would remain constant at 2005 levels through 2020. For the U.S., EPA
obtained projected activity data from EPA's VAIP (U.S. EPA, 2005).
Like the IEA historical activity estimates for SWPB and PFPB, the IEA projections for SWPB and
PFPB were adjusted to account for the observed shift of SWPB production to PFPB. Between
2000 and 2005, the global share of SWPB production was assumed to decline by 6 percent per
year (expressed as a fraction of the 1990 SWPB production share in that region), after which it
was assumed to remain constant at 2005 market share levels through 2020.
Emission Factors and Related Assumptions
EPA estimated PFC emission factors using the Intergovernmental Panel for Climate Change
(IPCC) Tier 2 methodology for calculating PFC emissions from primary aluminum production
(IPCC, 2000). These emission factors were derived from smelter operating parameters that
describe anode effect (AE) duration and frequency and a slope-coefficient, which relates the
parameters to actual cell type-specific PFC emissions. AE duration and frequency were combined
into an overall AE minutes-per-cell-day value. The slope coefficient is the parameter that, when
multiplied by the AE minutes per cell day, provides the specific emissions estimates in kg CF4 or
kg C2F6 per metric ton of aluminum.
Historical Emission Factors and Related Assumptions
Except for the U.S., where smelter-specific operating parameter and slope coefficient data are
available, cell type-specific default values for AE duration and frequency and slope coefficients
were used (IAI, 1999; IPCC, 2000). For all countries except the U.S., average cell type-specific
AE duration and frequency data for 1990 and 1995 were obtained from IAI surveys (IAI, 1999).
Table 7-10 illustrates these production-weighted AE minutes per cell-day by cell type used for
1990 and 1995 emission estimates. The reduction in AE minutes between 1990 and 1995 was the
result of several factors, including incremental improvements in smelter technologies and
practices, and the construction of state-of-the-art facilities.
Table 7-10. Cell Type Specific Production Weighted AE Minutes per Cell Day
Cell Type
VSS
HSS
SWPB
CWPB
1990
10.3
3.5
6.5
3.4
1995
7.1
3.1
5.3
1.6
Source: IAI, 1999
Table 7-11 illustrates slope coefficient information for each cell type that was obtained from IPCC
(2000). For the U.S., smelter-specific anode effect duration and frequency, and slope coefficient
data were obtained from the EPA's VAIP (U.S. EPA, 2005).
Table 7-11. Slope Coefficients by Cell Type (kg PFC/metric ton AI/AE minutes/cell day)
Cell Type
VSS
HSS
SWPB
CWPB
CF4
0.07
0.18
0.29
0.14
C2F6
0.003
0.018
0.029
0.018
Source: IPCC, 2000
June 2006 Revised 7. Methodology Page 7-43
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Projected Emission Factors and Related Assumptions - Technology-Adoption Baseline
Recently, the IAI, whose members account for approximately 80 percent of world primary
aluminum production, committed to reducing the industry's RFC emission intensity (i.e., RFC
emissions per metric ton of aluminum produced) by 80 percent from 1990 levels by 2010. To
model the successful attainment of the IAI RFC reduction goal, a Technology-Adoption Baseline
was developed to model the adoption of minor and major retrofit abatement options by global
facilities in the near future. Minor retrofits entail the installation of computer control systems, and
major retrofits entail the installation of point feeding systems. Complete retrofits entail the
installation of both. A complete retrofit essentially converts a cell to the lowest-emitting
technology, Point-Feed Pre-Bake (PFPB).
Projected emission factors were estimated by assuming that minor and major retrofit
improvements to smelter processes continue through 2010. For all countries except the U.S., EPA
modeled these process improvements in the baseline by assuming an increasing level of adoption
of complete retrofits. By 2010, almost all VSS and CWPB smelters were assumed to have
adopted complete retrofits, while 25 percent and 75 percent of SWPB and HSS smelters,
respectively, were assumed to have adopted them.
For the U.S., emission projections were based on smelter-specific production, AE minutes per cell
day, and slope coefficients obtained from the U.S. EPA's VAIP (U.S. EPA, 2005b).
Using these assumptions along with the reduction efficiencies in Table 7-12, the modeled global
2010 PFC emission intensity reduction is 78 percent compared to 1990 levels, which is consistent
with the IAI PFC reduction goal. With the attainment of the IAI goal in 2010, it is assumed that
through 2020, the regional and technology-specific emission factors will remain constant at 2010
levels.
Table 7-12. Reduction Efficiency of Potential Reduction Opportunities (Percent)
Abatement Option/Technology-Type
Computer Controls (Minor retrofit)
Point Feed (Major Retrofit )
VSS
35.5
35.5
HSS
33.5
33.5
SWPB
23
70
CWPB
31
10
Source: U.S. EPA, 2006.
Projected Emissions Factors and Related Assumptions - No-Action Baseline
In the No-Action Baseline, the emission factors for each cell technology were assumed to remain
constant from 2000 to 2020. The No-Action Baseline is intended to model the hypothetical
scenario in which no action is taken by the aluminum industry to reduce their emission rates below
the levels observed during the late 1990s. This would represent a break from the historical trend;
IAI member surveys (IAI 1999; IAI, 2000) have noted significant reductions in AE duration and
frequency for all cell-types during this period. In addition, as noted above, IAI has established a
voluntary goal of reducing global PFC emission intensity by 80 percent, compared to 1990 levels,
by 2010. Thus, it is unlikely that actual emissions will be as high as those presented in the No-
Action Baseline. Nevertheless, the Baseline is presented to provide an upper-bound estimate of
future emissions and to provide a reference to which the Technology-Adoption Baseline can be
compared.
For all countries except the U.S., EPA obtained production-weighted AE minutes per cell-day by
cell type used to estimate emissions for this scenario from 2000 to 2020 from IEA (2000). These
emission factors reflect the declines in AE minutes per cell-day observed during the 1990s. For
the U.S., data were obtained from the EPA's VAIP (U.S. EPA, 2005).
June 2006 Revised 7. Methodology Page 7-44
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Uncertainties and Sensitivities
In developing these emission estimates, EPA made use of multiple international data sets and the
most recent IPCC guidance on estimating emissions from this source. Nevertheless, uncertainties
exist in both the activity data and the emission rates used to generate these emission estimates.
First, while this study incorporated recent data on total aluminum production by region (IAI,
2005a), it relied primarily on the 2000 IEA report, Greenhouse Gas Emissions from the Aluminum
Industry, to disaggregate aluminum production by cell type, and this information was gathered
several years ago. Cell type is important because emissions per ton of aluminum can vary by a
factor of five or more across different cell types (IPCC, 2000). In its 2000 report, IEA attempted to
account for expected plant openings and closings, but these may not be occurring as expected,
particularly given the large increase in Chinese aluminum production since 2000. When EPA
compared the IEA data on regional production by cell type with more recent industry data on
global production by cell type (IAI, 2005; Marks, 2006), it found that the IEA projections had not
fully captured either (1) a sharp decline in production from VSS, HSS, and SWPB smelters (the
most emissive type), or (2) a sharp increase in production by PFPB plants (the least emissive
type). As discussed above, EPA attempted to compensate for this by modeling a shift from SWPB
to PFPB between 1990 and 2005. In addition, EPA modeled increasing levels of adoption of
complete retrofits, which essentially convert VSS, HSS, CWPB, and SWPB cells to PFPB cells.
However, even with the adjustment, EPA appears to be underestimating global production by
PFPB. This may have a significant impact on emission estimates because PFPB is the least
emissive cell type.
Second, EPA also relied on the 2000 IEA report to disaggregate the regional production reported
by IAI into country-by-country production. Again, due to the age of the IEA report and the recent
large growth of production in China, this may no longer accurately represent country-by-country
production. Published IAI (2005) results for PFC emissions in 1990 and 2000 are approximately
14 and 9 percent, respectively, below EPA estimates. While global aluminum production levels
are similar, the difference in PFC emissions is likely the result of differing country-specific
technology mixes, in particular in China, where historic production data are limited.
Third, the technology-adoption scenario assumes that the IAI goal (i.e., an 80 percent reduction in
PFC emission intensity by 2010 from 1990 levels) will be attained, after which there will be no
further improvement in PFC intensity levels. However, it is possible that additional improvement
will occur due to changes in the technology mix and continued operational improvements. If this is
the case, technology-adoption PFC projections may overestimate emissions.
Fourth, EPA used the 1990 and 1995 technology-specific anode effect minutes (AE minutes)
reported by the IAI (IAI, 1999), but it projected AE minutes and emission rates for all other years,
including 2000, based on (1) the estimated levels of adoption of PFC mitigation technology (i.e.,
minor and/or major retrofit), and (2) the estimated reduction efficiencies for these technologies.
Given the changes in the global aluminum industry since 2000, this may under- or overestimate
the actual level of technology adoption (and hence the AE minutes and emissions) for both the
Technology-Adoption Baseline (between 1995 and 2020) and the No-Action Baseline (between
1995 and 2000). Similarly, based on recent technology developments, this approach may
underestimate cell-specific reduction efficiencies and therefore overestimate AE minutes and
emissions. (For example, recently Alcan Pechiney reported an improved software and feed system
that has the potential to make substantial reductions in emissions on cells that are already
considered to be high performing relative to PFC emissions (Marks, 2006)).
Fifth, to estimate emissions, EPA used slope coefficients from the IPCC Good Practice Guidance
(IPCC, 2000). The CF4 and C2F6 slope coefficients recommended in the draft 2006 IPCC
Guidelines are noticeably different from these values. The slope coefficients from the 2006
Guidelines will likely have lower uncertainty than the values from the Good Practice Guidance
because the set of smelter-specific PFC measurements that have been used to develop these
coefficients is significantly larger.
June 2006 Revised 7. Methodology Page 7-45
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Appendices D-9 and D-9b present historical and projected emissions for all countries for this
source for the Technology-Adoption and No-Action Baselines.
7.3.6 Emissions from Semiconductor Manufacturing
Six perfluorinated compounds and one partially fluorinated compoundcollectively called PFCs
are used worldwide in semiconductor manufacturing: perfluoromethane (CF4), hexafluoroethane
(C2F6), perfluoropropane (C3F8), perfluorocyclobutane (c-C4F8), sulfur hexafluoride (SF6), nitrogen
trifluoride (NF3), and trifluoromethane (HFC-23). Note that although NF3 was not listed with a
GWP in the IPCC's Second Assessment Report (SAR) (Molina et al., 1995), this analysis presents
NF3 emissions and emission reduction options being considered by the semiconductor industry.
The semiconductor industry uses a broader definition of the term "RFC"perfluorocompound,
rather than perfluorocarbonand therefore includes HFC-23, NF3, and SF6 when referring to RFC
emissions.
RFC emissions are reported to come from two repeated activities in semiconductor manufacturing:
(1) cleaning of chambers used to deposit thin layers of insulating materials, a process referred to
as chemical vapor deposition (CVD) chamber cleaning, and (2) etching intricate patterns into
successive layers of insulating films and metals, a process referred to as plasma etching. Film
deposition and etching begins with the semi-conductive crystalline silicon (Si) wafer and continues
as successive films (layers) are deposited and etched to form and complete a device (i.e., the
connection of all the elements of the device). Industry reports indicate that approximately 70-80
percent of emissions result from chamber cleaning processes and 20-30 percent from etching
processes (IPCC, 2002; Beu and Brown, 1998).
In the absence of emission control measures, the rapid growth of this industry (11-12 percent per
year through the late 1990s) and the increasing complexity of microchips would be expected to
result in significantly increased future emissions from the semiconductor industry. In view of this
possibility, EPA and the U.S. semiconductor industry launched a voluntary partnership to reduce
RFC emissions in 1996. In 1999, the U.S. partnership catalyzed a global industry commitment
through the World Semiconductor Council (WSC), which represents approximately 85 percent of
world-wide semiconductor manufacturing capacity, to reduce RFC emissions to 90 percent of the
1995 level by 2010.34 As discussed below, this analysis models emissions both with and without
achievement of the WSC goal. These emission scenarios are respectively referred to as the
"Technology-Adoption" and "No-Action" Baselines, respectively.
The methods used in this report for estimating RFC emissions from semiconductor manufacturing
follow those in the RFC Emissions Vintage Model (PEVM, Burton and Beizaie, 2001) and in the
Foundry Impact Analysis Model (FIAM) (Bartos, Lieberman, and Burton, 2004).
The No-Action Baseline is intended to model the hypothetical scenario in which no action is taken
by semiconductor manufacturers to reduce their emission rate (expressed per average layer per
unit area of Si) below the level observed through 2000. In fact, World Semiconductor Council
(WSC) members have already taken significant steps to reduce their emission rates and to
achieve the WSC goal of reducing emissions to 90 percent of the 1995 level by 2010. These
steps include not only research programs in several countries, but the widespread adoption of
technologies (such as NF3 Remote Clean) that are already reducing emissions below the historical
rates. Such actions make it unlikely that actual future emissions will be as high as those
presented in the No-Action Baseline. Nevertheless, the No-Action Baseline is presented to
provide an upper-bound estimate of future emissions and to provide a reference to which the
Technology-Adoption Baseline can be compared.
For the U.S. Semiconductor Industry Association (SIA), Japan Electronic and Information Technology Industries
Association (JEITA) and European Semiconductor Industry Association (ESIA), the baseline year is 1995; for the Korean
Semiconductor Industry Association (KSIA), the baseline year is 1997; and for the Taiwan Semiconductor Industry
Association (TSIA), the baseline is the average of the emission values in 1997 and 1999. According to the World Fab
Watch database (2004), WSC-member companies accounted for approximately 85% of theoretical design manufacturing
capacity in 2003.
June 2006 Revised 7. Methodology Page 7-46
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No-Action Baseline Emissions
U.S. Emissions
Estimates of historical U.S. emissions were drawn from the U.S. Inventory (EPA, 2005). Estimates
of future U.S. emissions were based on estimates in EPA's PFC Emissions Vintage Model
(PEVM). These U.S. figures are consistent with the set estimated by EPA for the upcoming 2006
U.S. Climate Action Report.
Emissions from Other Countries
To generate the No-Action Baseline, EPA used WSC members' reported emissions and the FIAM
presented in Bartos, Lieberman, and Burton (2004).
For WSC members' historical emissions through 2000, EPA adopted those emissions reported
either by (1) countries or regions in their 2005 Greenhouse Gas Inventory Submissions to the
UNFCCC, or by (2) country trade associations at the 11th International Semiconductor
Environment, Safety, and Health Conference in Makuhari, Japan (2004). Inventory submissions
were used for the EU-15 and Japan, while trade association reports were used for South Korea
and Taiwan.
For all other regions and years, emissions were adapted from those obtained from FIAM. In
addition to projecting likely growth in global semiconductor manufacturing and emissions, the
FIAM analysis models the increasing emergence of foundry-type manufacturing facilities and a
geographical shift in manufacturing to Southeast Asia. FIAM therefore captures the growing
industry trend of outsourcing production to foreign (particularly Asian) manufacturing plants. FIAM
provides both historical and forecast emissions for specific countries and world regions under the
No-Action Baseline. This section presents a brief overview of the method through which FIAM
estimated those emissions, and presents the added steps taken in order to adjust those estimates
for inclusion in this report.
FIAM is based on the assumption that PFC emissions from semiconductor manufacturing vary
with (1) silicon consumption (i.e., the area of semiconductors produced) and (2) the number of
layers on each semiconductor device.35 The number of layers is determined by the technology
node or linewidth of the device. Linewidth refers to the smallest feature size used in
manufacturing the device.36 As feature sizes shrink, the number of active elements (e.g.,
transistors) on the same size device increases, requiring additional layers to connect the elements.
Since logic devices (e.g., microprocessors) have more layers than memory devices (e.g., DRAM)
at each technology node, the precision of emission estimates increases if Si projections take into
account the respective portions of Si consumed in logic and memory devices. EPA assumed that
only logic and memory devices are manufactured because Si consumed for the manufacturing of
devices other than logic and memory units has constituted less than 10 percent of total Si
consumption since the early 1990s (VLSI, 2003).
Global activity data comprise historical and projected global Si consumption by linewidth and
device type (i.e., memory vs. logic) provided by VLSI Research, Inc. (VLSI, 2003). For 1990
through 2005, this activity was apportioned to individual countries and regions using information
from the World Fab Watch (WFW) databases on manufacturing capacity by linewidth and country
(WFW, July 1996, 2001, and April 2003 Editions). For 2010, this activity was apportioned to
individual countries and regions using both the WFW data and forecasts of capital expenditures,
which relied on financial analysts' reports that predict investment in new manufacturing capacity.
The WFW data were used to apportion manufacturing of devices with linewidths> 120 nm while
capital expenditures were used to apportion manufacturing of devices with linewidths < 120 nm.
35 FIAM is based on data from EPA's PFC Emissions Vintage Model (PEVM), which is described in detail in Burton &
Beizaie(2001).
36 The term "technology node" refers to the smallest feature size used in manufacturing a semiconductor device
(microprocessor, DRAM, etc.), for example, 130 nm, 90 nm, 65 nm, etc. An organizing principle of the modern
semiconductor sector (known as Moore's Law) is the pursuit of ever-shrinking feature sizes so that, for the same or less
cost, the same size silicon substrate contains more transistors, which increases the cost performance of the device.
June 2006 Revised 7. Methodology Page 7-47
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(That is, capital expenditures were assumed to be devoted to the smallest, most advanced
linewidths.) For all historical and forecast activity, country-by-country estimates of per-node Si
consumption were multiplied by per-node emission factors to obtain country- and linewidth-specific
estimates of emissions.
FIAM uses emission factors from Burton and Beizaie (2001), which used U.S. industry reports of
U.S. emissions to develop an annual emission factor that expresses the industry average RFC
emissions37 per average layer per unit area of Si consumed during manufacture (including wafers
used to test process performance during manufacture that experience RFC treatment). This
"average per-layer" emissions factor remains relatively constant from year to year in the absence
of emission reduction efforts. Given the global nature of the semiconductor industry, the emission
factor was assumed to be applicable to worldwide semiconductor manufacturing as well as to U.S.
manufacturing.
The No-Action Baseline is an adjusted version of the historical and forecast emissions estimates
obtained from FIAM. FIAM's estimates were compared to those reported by members of the WSC
for 1995 and 2000.38 Differences emerged, and these were reasonably constant overtime for
specific regions. Assuming WSC reports are accurate, differences can be attributed to over- or
underestimated emission factors, Si consumption, or a combination of these. To calibrate FIAM's
estimates with those reported by WSC members, FIAM estimates were adjusted across all years
and regions by applying a factor specific to each WSC country. For countries that are not WSC
members, historical and forecast estimates from FIAM were scaled by a factor of 0.8, which is the
average ratio of FIAM estimates to member-reported estimates for 1995 and 2000. Table 7-13
shows the emissions reported by WSC members, the corresponding FIAM estimates, the ratios
between them, and the resulting adjustment factors.
Table 7-13. Ratios Between Reported and FIAM Estimated WSC Emissions and the Resulting
Adjustment Factors
WSC Member
Country/Region
Japan
Europe
Taiwan
South Korea
Total (a,b,c,d)°
or Average (e,f)
Reported
Emissions
(MtC
a b
1995/973 2000
4.1 7.4
1.4 1.9
0.7 4.8
2.6 3.3
8.8 17.4
FIAM-
Estimated
Emissions
02eq)
c d
1995/973 2000
13.3 15.3
2.0 4.3
1.1 3.9
1.8 2.9
18.2 26.4
Ratio
between
Emissions
a/c=e b/d=f
1995 2000
0.31 0.48
0.67 0.44
0.68 1.2
1 .4 1 .2
0.77 0.83
Adjustment
factor
(e+f)/2
0.40
0.56
0.96
1.3
0.80
All values are for 1995, except those for South Korea which uses 1997 as its baseline year.
Due to rounding, values may not sum perfectly.
Because FIAM generates country-specific emission estimates only for seven countries (U.S.,
Japan, Taiwan, South Korea, China, Singapore, and Malaysia), FIAM's regional estimates of
emissions from Europe and from the Rest of World group were broken down using data on each
country's share of capacity as projected by the World Fab Watch (WFW) database of
semiconductor manufacturing facilities (WFW, 2002).
37 The RFC emissions are expressed in units of MMTCE because the semiconductor industry reports its emissions as a
total of all RFC gases.
38 WSC members include SIA in the U.S., JEITA in Japan, ESIA in Europe, TSIA in Taiwan, and KSIA in South Korea.
June 2006 Revised
7. Methodology
Page 7-48
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Finally, because FIAM projects emissions only to 2010, the emission estimates as described
above (adapted from FIAM) were extrapolated to 2020 by assuming that post-2010 emissions
grow at a rate equal to one-half the compound annual growth rate observed over the years 1995 to
2010.
Technology-Adoption Baseline Emissions
Historical emissions under the Technology-Adoption Baseline are the same as under the No-
Action Baseline. The Technology-Adoption Baseline forecast models the scenario in which WSC
members achieve their goal of reducing emissions to 90 percent of the 1995 level by 2010. The
Technology-Adoption Baseline therefore reflects current and future actions to reduce emissions,
such as the adoption of alternative chemistries (e.g., NF3, CH2F2), process optimization, and
thermal and plasma abatement.
U.S. Emissions
Estimates of historical U.S. emissions were drawn from the U.S. Inventory (U.S. EPA, 2005).
Estimates of future U.S. emissions were based on estimates in PEVM, which were adjusted to
reflect the expected achievement of the WSC goal by manufacturers in EPA's PFC
Reduction/Climate Partnership for the Semiconductor Industry. These U.S. figures are consistent
with the set estimated by EPA for the upcoming 2006 U.S. Climate Action Report. Because not all
U.S. semiconductor manufacturers have committed to the 2010 WSC goal, 2010 U.S. emissions
are projected to be approximately 10 percent higher than 1995 U.S. emissions. However, by
2020, total U.S. emissions are expected to decline to less than 90 percent of 1995 emissions,
reflecting the penetration of the entire semiconductor market by low-emitting technologies.
Emissions from Other Countries
For all WSC member countries other than the U.S., EPA assumed that emission levels will reach
stated goals of 10 percent below 199539 levels by 2010. Beyond 2010, these countries' emissions
were assumed to remain constant. Through 2010, non-member countries' emissions were
assumed to match those presented in the No-Action Baseline. Beyond 2010 and through 2020,
however, it was expected that low-emitting equipment will permeate the international market for
semiconductor manufacturing equipment as a result of increased demand from WSC countries.
EPA assumed that non-WSC members will lag about 10 years behind WSC members in their
application of control technologies. Therefore, EPA assumed that 2020 non-members' emissions
under the Technology-Adoption Baseline have the same relationship to 2020 non-WSC No-Action
emissions as the 2010 Technology-Adoption emissions of the WSC members have to 2010 WSC
No-Action emissions.
Uncertainties and Sensitivities
In developing these emission estimates, EPA used multiple international data sets and the most
recent IPCC guidance on estimating emissions from this source. In the Technology-Adoption
Baseline, EPA also attempted to reflect recent technological developments and industry emission
reduction goals. However, several factors, including the high growth rate of this sector, the rapid
pace of technological change in this sector, and a growing industry trend of outsourcing production
to foreign manufacturing plants, make both global and country-specific emissions projections
uncertain.
First, based on the history of this industry, EPA has used relatively high activity growth rates to
project emissions; therefore, slight changes in these rates can lead to large changes in projected
emissions.
Second, the Technology-Adoption Baseline projects emissions assuming that the current
semiconductor manufacturing process continues and that currently available abatement
39 South Korea and Taiwan were assumed to reduce their emissions to 10 percent below the levels of their baseline years,
which are 1997 and 1997/1999 (average), respectively.
June 2006 Revised 7. Methodology Page 7-49
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technologies are used to reduce the resulting RFC emissions. It does not attempt to model a
possible future in which PFCs are no longer used in semiconductor manufacturing at all. Thus,
even the Technology-Adoption Baseline may overestimate emissions.
Appendices D-10 and D-10b present historical and projected emissions for all countries for this
source.
7.3.7 Sulfur Hexafluoride (SF6) Emissions from Magnesium Production
For this analysis EPA developed SF6 baseline emissions for three magnesium metal processes:
primary production, die-casting, and recycling-based or secondary production. Country-specific
emission estimates are expressed as the product of process-specific emission factors and
historical and forecasted production. This section first discusses the historical and projected
activity data utilized, specifically country-specific production and anticipated market trends
(projections), such as future plans to expand, shift, or curtail production. Next, it discusses the
process-specific emission factors used to estimate historical and projected emissions.
In the absence of emission control measures, the rapid growth of this industry would be expected
to result in significantly increased future emissions from magnesium production and processing. In
view of this possibility, EPA and the U.S. magnesium industry launched a voluntary partnership to
reduce SF6 emissions in 1999. In 2003, the U.S. partnership catalyzed a global industry
commitment through the International Magnesium Association (IMA), which represents
approximately 80 percent of magnesium production and processing outside of China, to eliminate
SF6 emissions from magnesium operations by the end of 2010 (U.S. EPA, 2005). As discussed
below, this analysis models emissions both with and without significant reductions in the SF6
emission rate of this industry. These emission scenarios are referred to as the "Technology-
Adoption" and "No-Action" Baselines, respectively.
Historical Activity Data
This section summarizes process-specific production data used to estimate historical (1990-2000)
emissions.
Primary Production
Countries that produced magnesium between 1990 and 2003 include: the U.S., Russia, Ukraine,
Canada, Kazakhstan, Israel, China, Brazil, France and Norway. (French and Norwegian primary
production ceased after 1999 and 2002, respectively). Data for primary magnesium production for
all countries for 1990 to 2003 (except for the U.S. for some years) were obtained from the U.S.
Geological Survey (USGS, 2002 and 2004). U.S. data were obtained from USGS and from
information supplied by the U.S. EPA's SF6 Emissions Reduction Partnership for the Magnesium
Industry (U.S. EPA, 2005).
Die-Casting
United States. EPA obtained U.S. die-casting production data from USGS and from U.S.
EPA's SF6 Emissions Reduction Partnership for the Magnesium Industry (USGS, 2002;
USGS, 2003; USGS, 2004; U.S. EPA, 2005).
European Union (EU). For EU countries that cast some or all of their magnesium using
SF6 as the cover gas, specifically, France, Germany, Italy, Portugal, Spain, Sweden and
the United Kingdom (U.K.), historical emissions were derived from Harnisch and Schwarz
(2003). 2001 emissions were estimated as the product of a region-specific emission factor
and country-specific data on SF6-based magnesium casting from Harnisch and Schwarz.
1995 emissions estimates were derived from the 1995 emissions presented by Harnisch
and Schwarz for the EU as a whole; country-specific emissions were calculated by
multiplying the aggregate EU emission estimate (20 metric tons SF6) by each country's
share of total SF6-based EU die-casting production in 2001. 2000 emissions were
estimated by linearly interpolating between the 1995 and 2001 data. For 1990, emissions
June 2006 Revised 7. Methodology Page 7-50
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were estimated using the 1995 estimates and two trends between 1990 and 1995: (1) EU
auto production, and (2) the quantity of magnesium used per car in the U.S. Between
1990 and 1995, EU auto production declined by three percent. However, the quantity of
magnesium used per car in the U.S. rose by 46 percent. Thus, SF6 emissions in the EU
were assumed to have risen by 42 percent between 1990 and 1995, since emission
factors were believed to have remained constant over the same period.
China (2000 only). 2000 Chinese casting volume was drawn from Edgar (2004).
All Other Countries. Casting estimates for other countries and other historical years (for
China) were not readily available. Consequently, die-casting for the years 1990 to 1999
was estimated as a function of automobile production. That is, for Brazil, Canada, China,
Japan, Russia, and Ukraine, casting was estimated using the ratio of country-specific
automobile production to U.S. automobile production. This ratio was multiplied by U.S.
die-casting production to obtain an estimate of die-casting production in each country.
Automobile production was obtained from Ward's Motor Vehicle Data (Ward's, 2001). For
countries that do not produce automobiles but have growing casting industries, such as
Kazakhstan, Norway, and Israel (IMA, 2002), production was estimated from the ratio of
primary production to casting production for a similar country. Russia was used as a
proxy for estimating production in Kazakhstan, while the U.S. was used as a proxy for
Norway and Israel.
Recycling-based Production
Recycling-based production by country from 1990 to 1999 was obtained from U.S. Geological
Surveys (USGS, 2002). USGS (2002) reports that Brazil, Japan, U.K., the Czech Republic and
the U.S. currently conduct magnesium recycling. The processing of magnesium scrap falls into
two subgroups: magnesium- and aluminum-base alloys. For all countries except the U.S., USGS
(2001) reports country-specific production that combines both magnesium- and aluminum-base
alloy recycling. For the U.S., USGS (2001) reports the production of recycled magnesium from
both magnesium- and aluminum-base alloys separately. Since it is assumed that SF6 is only
consumed during the processing of magnesium-base alloys, the ratio of U.S. magnesium- to
aluminum-base alloy recycling was used to estimate magnesium-base production for the other
countries.
Appendix I-4 contains historical magnesium activity data for primary, secondary, and die-casting
production.
Projected Activity Data
This section discusses the regional growth rates and country-specific assumptions used to
forecast magnesium primary production, casting, and recycling-based production from 2005
through 2020. Growth rates are summarized in Table 7-15. In general, annual growth rates used
in this analysis were assumed to account for new facility construction as well as facility capacity
expansion. Primary production and die-casting growth rates were based on information supplied
by Edgar (2004) for China, by EPA (2005) for the U.S. and by Webb (2005) for the rest of the
world. For recycling, growth rates will be driven by automotive use, and consequently, it is
assumed that they will be similar to casting growth rate estimates for each region.
Primary Production
Growth Rates. In all countries except the U.S. and China, EPA assumed primary production
will grow 3.4 percent per year between 2001 and 2010. Between 2011 and 2020, growth
was assumed to decrease to an annual rate of 1.7 percent. In the U.S., primary production
was assumed to grow to approximately 45,900 tons by 2006. This is based on an October
2004 announcement by U.S. Magnesium that it will expand production capacity to 51,000
metric tons by June 2005. EPA assumed that 90 percent of this capacity will be utilized by
2006. From 2007 to 2020, annual primary production growth was assumed to be 1 percent,
reflecting slower growth after the near-term expansion. From 2000 to 2005, Chinese
June 2006 Revised 7. Methodology Page 7-51
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primary production has increased at an annual rate of approximately 8.2 percent; however,
this rate is expected to decrease to approximately 5.9 percent from 2006 to 2010 (Edgar,
2004). During this period, Chinese producers are expected to maintain 100 percent of their
domestic market, but also increase their share of the global export market. The decrease in
growth rate to 5.9 percent reflects domestic issues that Chinese producers will likely face,
such as increasing costs from chronic domestic electricity shortages and pending national
legislation in banking, health and safety, and environmental standards, as well as potential
trade barriers in the export market (Edgar, 2004). Based on this assumption, growth
projections from 2011 to 2020 were assumed to remain constant at 5.9 percent.
Country-Specific Assumptions. In Norway, primary production at Norsk Hydro's Porsgrunn
facility ceased after 2002 (Norsk Hydro, 2001). EPA assumed that with this closure, no
future primary production will occur in Norway. In Canada, due to pricing pressure from
China and technical problems, magnesium production at a 58,000 metric ton per year facility
in Quebec was shut down indefinitely in April 2003 (USGS, 2004). This facility was
assumed to remain off line through 2020. In Ukraine, USGS (2002) reports that the Kalush
primary production plant that closed in 1999 would reopen in 2003 and produce 10,000
metric tons of magnesium (Mg) that year, after which it is assumed that production will grow
at rate of 3.4 and 1.7 percent between the periods 2004-2010 and 2011-2020, respectively.
Die-Casting
Growth Rates. In Asia (except China), Europe, and Canada, die casting is expected to
grow at 9.6 percent, 8.6 percent, and 1.6 percent respectively from 2004 to 2010 (Webb,
2005). Between 2010 and 2020, growth is expected to decrease to half those rates. This
decrease reflects the likelihood that the current period of high growth will not continue
indefinitely. For China, casting is assumed to grow annually at approximately 10 percent
through 2020 (Edgar, 2004). This growth is spurred by increasing investments by
Western, Japanese and Taiwanese companies in China to meet domestic demand for
camera, computers, and automobile parts. In the U.S., casting is assumed to continue
growing at the recent historical growth rate of 10.4 percent through 2010, and then to
decline to half that rate.
Country-Specific Assumptions. Due to increasing competition from low-cost imports from
China and Taiwan, it is assumed that Japanese die-casting declines and ceases by 2005
(IMA, 2002). Japanese production was assumed to have moved in equal shares to China
and Taiwan. The growth in casting observed in China between 2000 and 2005 is more
than adequate to have absorbed the Chinese share; thus, this additional casting is not
modeled explicitly for China. However, the Japanese casting that is assumed to move to
Taiwan is modeled beginning in 2005.
Recycling-based Production
Growth Rates. For all countries but the U.S., recycling growth rates are equated to
casting growth rates. In the U.S., recycling is assumed to continue growing at the recent
historical growth rate of 9.1 percent through 2010, and then to decline to half that rate.
Country-Specific Assumptions. In the Czech Republic, production at a 10,000 ton
capacity magnesium recycling plant started in mid-2002 (USGS, 2002). This analysis
assumes that approximately 60 percent of its capacity will be utilized in 2002, after which
production output will grow at 8.6 percent annually.
Global Activity Growth Rates
Table 7-14 presents the growth rates used in this analysis:
June 2006 Revised 7. Methodology Page 7-52
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Table 7-14. Annual Growth Rates for Primary Casting and Recycling Production (Annual Percent
Increase)3
Year
2001-2005
2006-2010
2011-2020
Primary Production
Annual Growth Rates
(percent)
Rest of
U.S. China World
8.2 3.4
1a 5.9 3.4
1 5.9 1.7
Casting Annual Growth Rates
(percent)
U.S.
10.4
10.4
5.2
Asia China Europe
9.6 10 8.6
9.6 10 8.6
4.8 10 4.3
Canada
1.6
1.6
0.8
Recycling Annual
Growth Rates
(percent)
Rest of
U.S. World
9.1 Same as
Casting"
9.1 Same as
Casting"
4.6 Same as
Casting"
See text above.
b Source: Primary and casting growth rates are based on Webb (2005). For recycling, it is assumed that
growth rates will be driven by increased use in automotive applications; consequently, growth rates will be
the same as casting estimates. Chinese rates based on Edgar (2004).
Historical Emission Factors and Related Assumptions
In this analysis, SF6 emissions are conservatively assumed to be equivalent to SF6 consumption
(i.e., it is assumed that no SF6 is destroyed during the metal processes). This may overstate
emissions, as recent EPA studies have shown that 5-20 percent of the SF6 is degraded during its
use as a cover gas during at least one type of casting process (Bartos et al., 2003). For the U.S.,
historical emission factors (i.e., SF6 consumption per metric ton of magnesium produced) for each
magnesium process were estimated based on information supplied by the U.S. EPA's SF6
Emissions Reduction Partnership for the Magnesium Industry (U.S. EPA, 2002). For all other
countries except China and the U.K., Table 7-15 summarizes the emission factors utilized to
estimate historical emissions for each of the production processes. The emission factor for
primary production was based on measurements made in 1994 and 1995 by U.S. producers. Due
to the similarity between the primary and recycling production processes, the emission factor for
recycling production was assumed to be the same as that for primary production. The emission
factor for die-casting was drawn from a 1996 international survey of die-casters performed by
Gjestland and Magers (1996).
Table 7-15. Historical (1990 and 1995) Emission Factors for Primary Casting and Recycling
Production
Process
Historical Emission Factors
(kg SF6/metric ton Mg
produced)
Source
Primary Production
Casting
Recycling
1.1
4.1a
1.1
U.S. EPA, 2002
Gjestland and Magers, 1996
U.S. EPA, 2002
Emission factor applied to all countries except France, Germany, Italy, Portugal, Spain, Sweden
and the U.K.. Forthese EU countries, estimates were derived from Harnisch and Schwarz (2003).
In China, in 1990 and 1995, the primary cover gas mechanism in primary production was sulfur
dioxide (SO2) generated from the application of solid sulfur powder. Consequently, Chinese
emissions of SF6 in those years are assumed to be zero for primary production. Similarly,
magnesium recyclers in the U.K. have used SO2 since 1990, and U.K. SF6 emissions from
magnesium recycling in 1990 and 1995 are therefore assumed to be zero.
Current and Projected Emission Factors - No-Action Baseline
In the No-Action Baseline, EPA assumed the emission factors remain constant from 2000 to 2020.
The No-Action Baseline is intended to model the hypothetical scenario in which no action is taken
June 2006 Revised
7. Methodology
Page 7-53
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by magnesium producers or processors to reduce their emission rates below the levels observed
during the late 1990s. In fact, many producers and processors have already taken significant
steps to reduce their emission rates and to achieve the IMA goal of eliminating SF6 emissions from
magnesium operations by the end of 2010. These include research programs in several countries
and, in some cases, the adoption of alternative cover gases such as HFC-134a and SC>2. These
actions make it unlikely that actual emissions will be as high as those presented in the No-Action
Baseline. Nevertheless, the No-Action Baseline is presented to provide an upper-bound estimate
of future emissions and to provide a reference to which the Technology-Adoption Baseline can be
compared.
Table 7-16 summarizes the emission factors EPA used to estimate emissions for this scenario
from 2000 to 2020 for all countries except the U.S., where data was obtained from the EPA's SF6
Emission Reduction Partnership for the Magnesium Industry. The 2000 emission factor for
primary production was based on measurements made recently by four producers (i.e., producers
with domestic U.S. and international operations) (U.S. EPA, 2002).
In China, it is assumed that some Chinese magnesium producers have begun to utilize SF6 in an
effort to produce better quality magnesium for the world market. Between 2000 and 2005, the
fraction of Chinese magnesium producers using SF6 is assumed to have grown from zero to
10 percent. From 2005 through 2020, SF6 cover use is assumed to remain at 10 percent of total
market cover gas usage, with the remaining Chinese primary producers still using SC>2 (Edgar,
2006, Brandt, 2006). Those Chinese producers using SF6 are assumed to emit at the rate shown
in Table 7-16.
For all countries except the U.K. and the Czech Republic, the emission factor for recycling was
conservatively assumed to be slightly higher than that for primary production. For the U.K. as well
as the Czech Republic, SO2 will be the primary cover gas system, so emissions from these
sources will be zero. For all countries including China, the emission factors for die-casting were
estimated based on reports from U.S. die-casters, an international report on emissions of
fluorinated chemicals (IEA, 2001), and a report on emissions from European die-casters (Harnisch
and Schwarz, 2003).
SF6 sales trends provide support for the downward trend observed in the emission factors
between 1995 and 2000. The RAND survey of global SF6 sales shows that SF6 sales to the
magnesium sector declined by 60 percent between 1995 and 2000 (Smythe, 2002). Because the
magnesium sector has grown internationally between 1995 and 2000, this indicates that emission
factors fell significantly during that period.
Table 7-16. Current and Projected (2000-2020) Emission Factors for Primary, Casting, and
Recycling Production, No-Action Baseline
Current/Projected Emission Source
Process Factors
(kg SFe/metric ton Mg
produced)
Primary Production 0.75 U.S. EPA, 2002
Casting 1 (0.85)a U.S. EPA, 2002
Recycling 1 U.S. EPA, 2002
3 Europe-specific casting emission factor (Schwarz, 2006)
Projected Emission Factors -Technology-Adoption Baseline
Industry is currently conducting laboratory evaluations and commercial trial studies of alternate
melt protection technologies, such as Novec 612 (a proprietary fluoroketone produced by 3M)
and HFC-134a. These studies, as well as recent improvements in the equipment and practices for
handling SO2, have led to a marked shift in industry's approach to addressing climate change,
opening up the possibility of eliminating SF6 from daily operations. In fact, the International
Magnesium Association (IMA), which represents approximately 80 percent of magnesium
June 2006 Revised 7. Methodology Page 7-54
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production and processing outside of China, has committed to eliminate SF6 emissions from
magnesium operations by the end of 2010.
To reflect the likely adoption of alternate melt protection technologies by global facilities in the near
future, EPA developed a Technology-Adoption Baseline for magnesium, which models increasing
market penetration by alternative gases from 2002 through 2011 in all countries but China, the
U.K., and the Czech Republic. Under this scenario, alternate gases are first introduced into the
baseline in 2002 and increase linearly through 2011, at which time their market share represents
100 percent of country-specific cover gas use. Inversely, SF6 cover gas use in magnesium
facilities is assumed to decrease linearly from 100 percent in 2001 to 0 percent by year 2011.
From 2011 to 2020, alternate cover gases are assumed to maintain 100 percent market share.
Currently, three gases are leading candidates to replace SF6: SO2, with a global warming potential
(GWP) of 0, a fluoroketone, with a GWP of 1, and HFC-134a, with a GWP of 1,300. An average
GWP of 325 was used to reflect the approximate expected market shares of the three gases and
to estimate the contribution of their emissions to the baseline.
In the U.K., the above approach was applied to casting; however, U.K. magnesium recyclers were
assumed to continue their current practice of using SO2, which has been the norm since 1990. It
was assumed that, with no foreseeable shift to SF6 or alternate cover gas compounds, the use of
SO2 would continue through 2020, and consequently, greenhouse gas emissions from this
segment of the U.K. industry would remain zero. In the Czech Republic, as in the U.K., SC>2 was
assumed to be the primary cover gas system utilized through 2020. In China, magnesium
producers and processors were assumed to continue using SF6, as in the No-Action Baseline. In
the U.S., most producers and processors were expected to adopt alternative cover gases to meet
the industry goal; however, some SF6 emissions were projected to continue through 2020 because
some U.S. casting and recycling firms have not committed to phase out use of the chemical (EPA,
2005).
Uncertainties and Sensitivities
In developing these emissions estimates, EPA used multiple international data sets and the most
recent IPCC guidance on estimating emissions from this source. In the Technology-Adoption
Baseline, EPA also attempted to reflect recent technological developments and industry emission
reduction goals. Nevertheless, the resulting emissions estimates are subject to considerable
uncertainty.
Historical and current emissions from this source are affected by both activity levels and emission
rates. Although country-specific activity levels are fairly well known for primary production, they
are less well known for recycling-based production (particularly the share consisting of
magnesium-base alloys) and for casting. In addition, emission rates vary widely across different
processes and overtime. EPA has attempted to account for these variations (e.g., the decline in
emission rates that occurred between 1995 and 2000), but it may have overlooked some regional
and process-based differences.
To check its estimates of historical global emissions, EPA compared them to the total sales of SF6
to the magnesium industry reported by SF6 manufacturers under the RAND survey (Smythe,
2004). Because the RAND survey did not include SF6 producers from Russia and China, and
Russia and China together accounted for 15 to 20 percent of global emissions from magnesium
production and processing between 1990 and the present, one would expect total global
emissions to slightly exceed the total sales reported by RAND. In fact, the 1990, 1995 and 2003
emissions estimates in this study are 20 to 35 percent higher than the RAND sales estimates for
those years. However, the emissions estimate for 2000 is over twice as high as the RAND sales
estimate for that year. This clearly implies that EPA may have overestimated emissions in 2000.
However, because EPA's 2000 emissions estimate is already significantly lower than either its
1995 or 2003 emissions estimate, it seems unlikely that the difference between the 2000 estimate
and the 2000 sales figure is solely attributable to an overestimate of emissions in this analysis.
Instead, at least part of the difference is likely to be attributable to the magnesium industry's
increased use of SF6 from Russia and China, whose SF6 manufacturers, as noted above, have not
June 2006 Revised 7. Methodology Page 7-55
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been included in the results of the RAND survey. With the exception of the year 2000, there is
surprisingly good agreement between the RAND survey and this analysis.
Projected emissions from magnesium production and processing are quite sensitive to (1)
estimated activity growth rates, and (2) assumptions regarding the adoption and/or retention of
alternate melt protection technologies. EPA has used relatively high activity growth rates to
project emissions; therefore, slight changes in these rates can lead to large changes in projected
emissions. Assumptions regarding the penetration of alternate melt protection technologies are
similarly important. First, the Technology-Adoption Baseline assumes that virtually all IMA
members will phase out use of SF6 by 2011. However, recent discussions with industry
representatives indicate that some IMA members may continue to use SF6 for the foreseeable
future. If this is the case, emissions are likely to be higher than those projected in the Technology-
Adoption Baseline, but not so high as those projected in the No-Action Baseline. Second, this
analysis assumes that some but not all Chinese magnesium producers have adopted SF6 in place
of solid sulfur as they seek to increase the quality of their metal. Because China is currently the
world's largest producer of magnesium, greater penetration of the Chinese market by SF6 could
significantly increase both Chinese and global emissions. On the other hand, penetration of the
Chinese casting market by alternate cover gases would lower Chinese emissions below those
projected here.
Finally, this analysis does not account for the potentially significant impact of yet unannounced
mitigation projects funded by developed countries under the Clean Development Mechanism
(COM) of the Kyoto Protocol. COM projects could significantly decrease SF6 emissions from
magnesium production and processing in China and other developing countries.
Appendices D-11 and D11-b present historical and projected emissions for all countries for this
source for the Technology-Adoption and No-Action Baselines.
June 2006 Revised 7. Methodology Page 7-56
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8. References
Section 1 Introduction and Overview
de la Chesnaye, F.C., C. Delhotal, B. DeAngelo, D. Ottinger Schaefer.and D. Godwin. 2006. Past, Present, and
Future of Non-CC>2 Gas Mitigation Analysis. In Human-Induced Climate Change: An Interdisciplinary Assessment.
Cambridge, UK: Cambridge University Press. In Press.
IPCC. 1996. Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change.
Edited by J.T. Houghton, L.G. Meira Filho, B.A. Callender, N. Harris, A. Kattenberg, and K. Maskell. Cambridge, UK:
Cambridge University Press.
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000). May 2000.
IPCC. 2001. Climate Change 2001: The Scientific Basis, Intergovernmental Panel on Climate Change. Edited by
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell.
Cambridge, UK: Cambridge University Press. Available online at
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Section 2 Summary
IPCC. 2001. Climate Change 2001: The Scientific Basis, Intergovernmental Panel on Climate Change. Edited by
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell.
Cambridge, UK: Cambridge University Press. Available online at
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Olivier, J. 2005. Emission Database for Global Atmospheric Research. EDGAR 3.2 Fast Track 2000 Dataset.
Available online at .
U.S. EPA. 2003. International Analysis of Methane and Nitrous Oxide Abatement Opportunities: Report to Energy
Modeling Forum, Working Group 21. U.S. Environmental Protection Agency. Washington, DC. Available online at
.
Section 3 Energy
U.S. EPA. 1993. Anthropogenic Methane Emissions in the United States: Estimates for 1990, Report to Congress.
Atmospheric Pollution Prevention Division, Office of Air and Radiation, US Environmental Protection Agency.
EPA/430/R/93/012. Washington, DC.
U.S. EPA. 1999. US Methane Emissions 1990-2002: Inventories, Projections, and Opportunities for Reductions.
Climate Protection Division, Office of Air and Radiation, US Environmental Protection Agency. EPA/430/R/99/013.
Washington, DC.
Section 4 Industry
4.1.3 Global Warming Potentials for High GWP Gases
IPCC. 1996. Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change.
Edited by J.T. Houghton, L.G. Meira Filho, B.A. Callender, N. Harris, A. Kattenberg, and K. Maskell. Cambridge, UK:
Cambridge University Press.
IPCC. 2001. Climate Change 2001: The Scientific Basis, Intergovernmental Panel on Climate Change; Edited by
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell.
Cambridge, UK: Cambridge University Press.
Molina, L.T., P.J. Woodbridge, and M. J. Molina. 1995. Atmospheric Reactions and Ultraviolet and Infrared
Absorptivities of Nitrogen Trifluoride. Geophysical Research Letters. 22, no. 14, 1873-76.
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4.2 Adipic Acid and Nitric Acid Production
U.S. EPA. 2001. U.S. Adipic Acid and Nitric Acid N2O Emissions 1990-2020: Inventories, Projections and
Opportunities for Reductions. Available online at .
Reimer, R.A., C.S. Slaten, M. Seapan, A. Koch, and V.G. Triner. 2000. Adipic Acid Industry- N2O Abatement, Non-
002 Gases: Scientific Understanding, Control and Implementation. Edited by J. van Ham et al. Kluwer Academic
Publishers. 2000. 347-58.
SRI. 1999. Quoted in Product focus: Adipic Acid/Adiponitrile. Chemical Week. March 10, 31.
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. Accessed: January 18, 1999.
4.4 Production of HCFC-22 (Hydrofluorocarbons)
JICOP. 2006. Mr. Shigehiro Uemura of Japan Industrial Conference for Ozone Layer Protection (JICOP), emails to
Deborah Ottinger Schaefer of U.S. EPA, May 9, 2006.
UNEP. 2003. Report of the Technology and Economic Assessment Panel. United Nations Environment Programme
(UNEP) HCFC Task Force Report. May 2003.
4.5 Electrical Power Systems
Ecofys. 2005. Reductions ofSF6 Emissions from High and Medium Voltage Electrical Equipment in Europe, Final
Report to Capiel. June 28, 2005.
EIA. 2002. International Energy Outlook 2002. Energy Information Administration, U.S. Department of Energy,
Washington, DC. Report* DOE/EIA-0484(2002). March 26, 2002. Available online at
.
Smythe, K. 2004. Trends in SF6 Sales and End-Use Applications: 1961-2003. International Conference on SF6 and
the Environment: Emission Reduction Technologies, December 1-3, 2004, in Scottsdale, Arizona.
U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. EPA/430/R/05/003. Washington, DC. Available online
at .
Yokota, T., K. Yokotsu, K. Kawakita, H. Yonezawa, T. Sakai, T. Yamagiwa. 2005. Recent Practice for Huge
Reduction of SF6 Gas Emission from GIS&GCB in Japan. CIGRE SC A3 & B3 Joint Colloquium, 2005, in Tokyo,
Japan.
Yokota, T. 2006. E-mail from Takeshi Yokota, T&D Power Systems, Toshiba Corporation, to Debbie Ottinger, U.S.
EPA, April 9, 2006.
4.6 Aluminum Production
IAI. 2000. Perfluorocarbon Emissions Reduction Programme 1990-2000. International Aluminum Institute. London,
United Kingdom. Available online at .
IAI. 2005. The International Aluminum Institute's Report on the Aluminum Industry's Global Perfuorocarbon Gas
Emissions Reduction Programme - Results of the 2003 Anode Effect Survey. International Aluminum Institute.
London, United Kingdom. January 28, 2005. Available online at .
4.8 Magnesium Production and Processes
Bartos S., J. Marks, R. Kantamaneni, C. Laush. 2003. Measured SFe Emissions from Magnesium Die Casting
Operations. Magnesium Technology 2003, Proceedings of the Minerals, Metals & Materials Society (TMS)
Conference, March 2003.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
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online at .
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DOE. 2003. ClimateVISIONVoluntary Innovative Sector Initiatives: Opportunities Now. Private Sector Initiatives-
Magnesium. U.S. Department of Energy. Available online at
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U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. EPA/430/R/05/003. Washington, DC. Available online
at .
Section 5 Agriculture
5.3 Enteric Fermentation
FAPRI. 2004. U.S. and World Agricultural Outlook. Food and Agricultural Policy Research Institute, Iowa State
University, and University of Missouri-Columbia. Ames, Iowa. January 2004.
5.4 Rice Cultivation
FAPRI. 2004. U.S. and World Agricultural Outlook. Food and Agricultural Policy Research Institute, Iowa State
University, and University of Missouri-Columbia. Ames, Iowa. January 2004.
5.5 Manure Management
FAPRI. 2004. U.S. and World Agricultural Outlook. Food and Agricultural Policy Research Institute, Iowa State
University, and University of Missouri-Columbia. Ames, Iowa. January 2004.
5.6 Other Agricultural Sources
Olivier, J.G.J. and J.J.M. Berdowski. 2001. Global Emissions Sources and Sinks. In The Climate System. Edited by
J. Berdowski, R. Guicherit, and B.J. Heij. 33-78. Lisse, The Netherlands: A.A. Balkema Publishers/Swets &
Zeitlinger Publishers. ISBN 90 5809 255 0.
Olivier, J.G.J., 2002. On the Quality of Global Emission Inventories: Approaches, Methodologies, Input Data and
Uncertainties. Thesis, Utrecht University. ISBN 90-393-3103-0.
Olivier, J. 2005. Emission Database for Global Atmospheric Research. EDGAR 3.2 Fast Track 2000 Dataset.
Available online at .
Section 7 Methodology
7 Overview
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
7.2 Methane Emissions from Natural Gas and Oil Systems
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
EIA. 2002. International Energy Outlook 2002. Energy Information Administration (2002), U.S. Department of
Energy. Washington, DC. Report* DOE/EIA-0484(2002). Available online at
OGJ. 2001. Caspian Production Potential. Oil and Gas Journal. 99, no. 51 (December 17, 2001).
7.2.2 Methane Emissions from Coal Mining Activities
EIA. 2002. International Energy Outlook 2002. Energy Information Administration (2002), U.S. Department of
Energy. Washington, DC. Report* DOE/EIA-0484(2002). Available online at .
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IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
Mining India. 2000. Mining India Web site. Available online at . Accessed: April 10,
2000.
UNDP. 1998. Asia Least-Cost Greenhouse Gas Abatement Strategy: People's Republic of China. United Nations
Development Programme, Asian Development.
WEC. 2000. India's Energy Scenario in 2020. World Energy Council. Available online at
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7.2.3 Nitrous Oxide and Methane Emissions from Stationary and Mobile Combustion
IEA. 2001a. Energy Balances of Non-OECD Countries 1971-1999. International Energy Agency. 2001 ed.
CD-ROM. Paris, France.
IEA. 2001b. Energy Balances of OECD Countries 1960-1999. International Energy Agency. 2001 ed. Paris,
France.
IEA. 2001c. World Energy Outlook 2000. International Energy Agency. 2nd ed. February 2001.
7.2.4 Methane and Nitrous Oxide Emissions from Biomass Combustion
IEA. 2001a. World Energy Outlook 2000. International Energy Agency. 2nd ed. February 2001.
IEA. 2001 b. Energy Statistics of Non-OECD Countries 1971-1999. International Energy Agency. 2001 ed. CD-
ROM, ISBN 92-64-06800-7. Paris, France.
IEA. 2001c. Energy Statistics of OECD Countries 1960-1999. International Energy Agency. 2001 ed. Paris,
France. 2001 Edition CD-ROM, ISBN92-64-06757-4. Paris, France.
7.2.5 Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
C&EN. 1997. North America Mexico's Economy, Chemical Trade
Still Robust. Chemical and Engineering News. December 15, 1997.
BICCA. 2000. Brazilian Chemical Industry web site. Available online at . Accessed:
2000.
Chemical Week. 1999a. Product Focus: Adipic Acid/Adiponitrile. Chemical Week, March 10, 31.
Chemical Week. 1999b. Chemical Industry Focus: Fertilizers. Chemical Week, Feb. 15.
CMR. 1998. Chemical Profile: Adipic Acid. Chemical Marketing Reporter, June 15, 33.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
Reimer, R.A., C.S. Slaten, M. Seapan, A. Koch, and V.G. Triner. 2000. Adipic Acid Industry- N2O Abatement.
Non-CO2 Gases: Scientific Understanding, Control and Implementation. Edited by J. van ham et al. Kluwer
Academic Publishers. 347-58.
SRI. 1999. Quoted in Product focus: Adipic Acid/Adiponitrile. Chemical Week. March 10, 31.
SRI Consulting. Menlo Park, CA. Available online at
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7.2.6 Nitrous Oxide Emissions from Agricultural Soils
FAO. 2000. Fertilizer requirements in 2015 and 2030. Food and Agriculture Organization of the United Nations.
FAO. 2001. Agricultural Database of Food and Agricultural Organization ofthe United Nations. Food and
Agricultural Organization ofthe United Nations. Available online at .
FAO. 2002. FAOSTAT, Agricultural Database ofthe Food and Agriculture Organization ofthe United Nations. Food
and Agricultural Organization ofthe United Nations. Available online at
. Accessed: August-October 2002.
7.2.7 Methane Emissions from Livestock Enteric Fermentation
FAO. 2003. FAOSTAT, Agricultural Database ofthe Food and Agriculture Organization ofthe United Nations. Food
and Agricultural Organization ofthe United Nations. Available online at
. Accessed: August-October 2003.
IFPRI. 2004. International Food Policy Research Institute, Spreadsheet communication to U.S. EPA, December.
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
7.2.8 Methane Emissions from Rice Cultivation
FAO. 2001. Agricultural Database of Food and Agricultural Organization ofthe United Nations. Food and
Agricultural Organization ofthe United Nations. Available online at .
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
IRRI. 2001. International Rice Institute. Available online at .
Accessed: December 2001.
UN. 2003. World Population Prospects: the 2002 Revision: File 1-Total Population (Both Sexes Combined) by Major
Area, Region and Country, Annually for 1950-2050. Medium Variant. 2001-2050. Filename:
POP/DBA/VPP/Rev.2002/2/F1. United Nations, Department of Economic and Social Affairs, Population Division.
February, 2003.
7.2.9 Methane and Nitrous Oxide Emissions from Manure Management
FAO. 2003. FAOSTAT, Agricultural Database ofthe Food and Agriculture Organization ofthe United Nations. Food
and Agriculture Organization ofthe United Nations. Available online at
. Accessed: August-October 2003.
ESRI. 1999. Geography Network Explorer, World Temperature Zones. Available online at:
.
IFPRI. 2004. International Food Policy Research Institute. Spreadsheet communication to U.S. EPA (December).
7.2.10 Methane and Nitrous Oxide Emissions from Other Agricultural Sources
Olivier, J.G.J. and J.J.M. Berdowski. 2001. Global emissions sources and sinks. In The Climate System. Edited by
J. Berdowski, R. Guicherit, and B.J. Heij. 33-78. Lisse, The Netherlands: A.A. Balkema Publishers/Swets &
Zeitlinger Publishers. ISBN 90 5809 255 0.
Olivier, J.G.J., 2002. On the Quality of Global Emission Inventories Approaches, Methodologies, Input Data and
Uncertainties. Thesis, Utrecht University. ISBN 90-393-3103-0.
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Olivier, J. 2005. Emission Database for Global Atmospheric Research. EDGAR 3.2 Fast Track 2000 Dataset.
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7.2.11 Methane and Nitrous Oxide Emissions from Landfilling of Solid Waste
IEA Greenhouse Gas R&D Programme. 1999. Technologies for the Abatement of Methane Emissions: Volume 1.
International Energy Agency, Cheltenham, UK. February 1999.
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
UN. 2003. World Population Prospects: the 2002 Revision: File 1-Total Population (Both Sexes Combined) by
Major Area, Region and Country, Annually for 1950-2050. Medium Variant, 2001-2050. File name:
POP/DBAVPP/Rev.2002/2/F1. United Nations, Department of Economic and Social Affairs, Population Division.
February 2003.
7.2.12 Methane and Nitrous Oxide Emissions from Wastewater Treatment
Doom. 1999. Doom, M.J. and D.S. Liles. Quantification of Methane Emissions and Discussion of Nitrous Oxide,
and Ammonia Emissions from Septic Tanks, Latrines, and Stagnant Open Sewers in the World. U.S. Environmental
Protection Agency. EPA/600/R/99/089. Washington, DC. October 1999.
7.3.2 HFC and PFC Emissions from the Use of Substitutes for ODS Substances
Ashford, P. 2004. Peer review comments on U.S. EPA Draft Report, Draft Analysis of International Costs of Abating
HFC Emissions from Foams. Caleb Management Services Ltd. March 3, 2004.
Baker, J.A. 2002. Mobile Air Conditioning Sector Update. 19th Meeting of the Ozone Operations Resource Group
(OORG), The World Bank, March 2002, in Washington, DC.
Barbusse, S., D. Clodic, and J.P. Rouegoux. 1998. Mobile Air Conditioning; Measurement and Simulation of Energy
and Fuel Consumptions. Earth Technologies Forum, Alliance for Responsible Atmospheric Policy, October 1998.
China Association of Automobile Manufacturers. 2005. Workshop on Technology Cooperation for the Next
Generation Mobile Air Conditioning, March 2005, in New Delhi, India.
EC. 2003. How to Considerably Reduce Greenhouse Gas Emissions Due to Mobile Air Conditioners. European
Commissions, Consultation paper from the European Commission Directorate-General Environment. February 2003.
European Climate Change Program (ECCP). 2001. Annex I to the Final Report on European Climate Change
Programme Working Group Industry Work Item Fluorinated Gases: ECCP Solvents. Position paper provided by
European Fluorocarbon Technical Committee (EFTC). February 2001.
EIA. 2001. International Energy Outlook 2001, Table 7, Comparison of Economic Growth Rates by Region, 1997-
2020. Energy Information Administration, U.S. Department of Energy. Available online at
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Hill, W. and W. Atkinson. 2003. Peer review comments on the U.S. EPA Draft Report, DRAFT Analysis of
International Costs of Abating HFC Emissions from Refrigeration and Air-Conditioning. General Motors Corporation
and Sun Test Engineering. October 2003.
March. 1996. UK Use and Emissions of Selected Hydrocarbons. A Study for the Department of the Environment.
March Consulting Group, HMSO, London, 1996.
OPROZ. 2001. Report on the Supply and Consumption of CFCs and Alternatives in Argentina. Oficina Programa
Ozono. February 2001.
Russian Federation. 1994. Phaseout of Ozone Depleting Substances in Russia. Prepared for the Ministry for
Protection of the Environment and Natural Resources of the Russian Federation and the Danish Environmental
Protection Agency, August 1994, x-xi, 27-28.
SEMI International. 2003. Strategic Marketing Associates' World Fab Watch Database (WFW). April Edition.
June 2006 Revised 8. References Page 8-6
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SIAM. 2005. Growth and Projections of Automobile Industry and Mobile Air Conditioning. Workshop on Technology
Cooperation for Next Generation Mobile Air Conditioning (MAC). Presentation by Dilip Chenoy, Director General,
Society of Indian Automobile Manufacturers (SIAM), March 2005, in New Dehli, India.
UNEP. 1999a. Production and Consumption of Ozone Depleting Substances, 1986-1998. United Nations
Environment Programme (UNEP) Ozone Secretariat. Nairobi, 1999.
UNEP. 1999b. 1998 Report of the Solvents, Coatings, and Adhesives Technical Options Committee (STOC): 1998
Assessment. United Nations Environmental Programme (UNEP). Nairobi, Kenya: UNEP Ozone Secretariat.
UNEP. 1999c. The Implications of the Montreal Protocol of the Inclusion of MFCs and PFCs in the Kyoto Protocol.
United Nations Environment Programme (UNEP). United States: UNEP HFC and PFC Task Force of the Technology
and Economic Assessment Panel (TEAP) and Nairobi, Kenya: UNEP Ozone Secretariat.
USDA. 2002. Real GDP (2000 dollars) Historical International Macroeconomic Data Set. United States Department
of Agriculture Economic Research Service. Available online at .
Ward's. 2001. Ward's World Motor Vehicle Data. ISBN 0-910589-79-8. Southfield, Missouri, 2001.
7.3.3 Production of HCFC-22 (Hydrofluorocarbons)
Ahmadzai. 2000. Hasamuddin Ahmadzai, email regarding HFC-23 emission rates in Russia, May 19, 2000.
AFEAS. 2001. Alternative Fluorocarbons Environmental Acceptability Study (AFEAS) (2001), Production of
Fluorocarbons. Available online at . Accessed: May 2, 2003.
Campbell. 2006. Nick Campbell of Arkema, emails to Deborah Ottinger Schaefer of U.S. EPA, April 24, 2006.
Chemical and Economics Handbook (CEH). 2001. Fluorocarbons CEH Marketing Research Report. Chemical and
Economics Handbook.
EIA. 2001. Annual Energy Outlook 2001 with Projections to 2020. Energy Information Administration (2001), U.S.
Department of Energy. Washington, DC. Report* DOE/EIA-0383 (2001).
Harnisch and Hendricks. 2000. Harnish, Jochen and Chris Hendriks. Economic Evaluation of Emission Reductions
of HFCs, PFCs and SF6 in Europe. Contribution to the study Economic Evaluation of Sectoral Emission Reduction
Objectives for Climate Change. Commission of the European Union, Directorate General Environment. April 2000.
JICOP. 2004. Mr. Shigehiro Uemura of Japan Industrial Conference for Ozone Layer Protection (JICOP), emails to
Deborah Ottinger Schaefer of U.S. EPA, April 23, April 28, and May 14, 2004.
JICOP. 2006. Mr. Shigehiro Uemura of Japan Industrial Conference for Ozone Layer Protection (JICOP), emails to
Deborah Ottinger Schaefer of U.S. EPA, May 9, 2006.
Oberthur, S. 2001. Production and Consumption of Ozone Depleting Substances, 1986 - 1999. GTZ Report. 2001.
Rand, etal. 1999. Rand, S., D. Ottinger, and M. Branscome. Opportunities for the Reduction of HFC-23 Emissions
from the Production of HCFC-22. IPCC/TEAP Joint Expert Meeting, May 26-28, 1999, in Petten, Netherlands.
SROC. 2005. IPCC/TEAP Special Report: Safeguarding the Ozone Layer and the Global Climate System: Issues
Related to Hydrofluorocarbons and Perfluorocarbons. Cambridge University Press. 2005.
U.S. EPA. 2001. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1999. United States Environmental
Protection Agency (EPA), Office of Atmospheric Programs. April 2001. EPA/236/R/01/001. Washington, DC.
Available online at
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World Bank. 2001. Country at a Glance Profiles. World Bank (2001). Available online at
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Working Paper No. 14. World Bank (2002). Prepared by ICF Consulting for the World Bank, Latin America and
Caribbean Regional Office, Environmentally and Socially Sustainable Development SMU. December 2002.
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7.3.4 Sulfur Hexafluoride Emissions from Electrical Power Systems
Ecofys. 2005. Reductions of SFe Emissions from High and Medium Voltage Electrical Equipment in Europe, Final
Report to Capiel. June 28, 2005.
EIA. 2001 a. International Energy Outlook 2001. Energy Information Administration, U.S. Department of Energy.
Washington, DC. Report* DOE/EIA-0484(2001). March 2001. Available online at
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EIA. 2001 b. International Energy Annual (IEA). Energy Information Administration, U.S. Department of Energy.
Washington, DC. Report* DOE/EIA-0219(2001). March 2003.
EIA. 2002. International Energy Outlook 2002. Energy Information Administration, U.S. Department of Energy.
Washington, DC. Report* DOE/EIA-0484(2002). March 26, 2002. Available online at
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ERI. 2006. Cui Cheng, Energy Research Institute, NDRC, China email to Susan Wickwire, U.S. EPA, February 16,
2006.
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
Maiss, M. and C.A.M. Brenninkmeijer. 2000. A Reversed Trend in Emissions ofSFdinto the Atmosphere.
Proceedings of the Second International Symposium of Non-CO2 Greenhouse Gases. Kluwer, 2000.
Maruyama, S. 2001. SFe Gas Emission Reduction from Gas Insulated Electrical Equipment in Japan. The
Federation of Electric Power Companies, and the Japan Electrical Manufactures' Association (JEMA) Japan.
Available online at
Peters, W., E. Dlugokencky, J. Olivier, G. Dutton, and K. Smythe. 2005. Surface measurements show a 17%
increase in the release of sulfur-hexafluoride (SF6) to the atmosphere in 2003. Proceedings of the Fourth
International Symposium NCGG-4. Milpress, Rotterdam, 2005.
Smythe, K. 2004 Trends in SF6 Sales and End-Use Applications: 1961-2003. International Conference on SF6 and
the Environment: Emission Reduction Technologies, December 1-3, 2004, in Scottsdale, Arizona.
U.S. EPA. 2005a. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. April 2005. EPA/430/R/05/003. Washington, DC.
Available online at
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U.S. EPA. 2005b. SFe Emissions Reduction Partnership for Electric Power Systems. U.S. Environmental
Protection Agency. Washington, DC. Available online at .
Yokota, T., K. Yokotsu, K., Kawakita, H. Yonezawa, T. Sakai, T, Yamagiwa. 2005. Recent Practice for Huge
Reduction ofSF6 Gas Emission from GIS&GCB in Japan. CIGRE SC A3 & B3 Joint Colloquium, 2005, in Tokyo,
Japan.
7.3.5 Perfluorocarbon Emissions from Primary Aluminum Production
IAI. 1999. Anode Effect Survey 1994 - 1997 and Perfluorocarbon Compounds Emissions Survey 1990 - 1997.
International Aluminum Institute (IAI). Available online at .
IAI. 2000. Perfluorocarbon Emissions Reduction Programme 1990-2000. International Aluminum Institute (IAI)
(2000). London, United Kingdom. Available online at .
IAI. 2002. Historical IAI Statistics: Annual Primary Aluminum Production. International Aluminum Institute (IAI)
(2002). London, United Kingdom. Available online at .
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IAI. 2005a. China's Primary Aluminium Production. International Aluminum Institute (IAI) (2005a). London, United
Kingdom. Available online at .
IAI. 2005b. The International Aluminum Institute's Report on the Aluminum Industry's Global Perfuorocarbon Gas
Emissions Reduction Programme - Results of the 2003 Anode Effect Survey. International Aluminum Institute (IAI)
(2005b). London, United Kingdom. January 28, 2005. Available online at .
IEA. 2000. Greenhouse Gas Emissions from the Aluminum Industry. International Energy Agency (IEA) (2000), The
International Energy Agency Greenhouse Gas Research & Development Program. Cheltenham, United Kingdom.
January 2000.
IPAI. 1998. IPAI Statistical Summary. International Primary Aluminum Institute. London, UK.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
Marks, J. 2006. Personal communication with Jerry Marks, J. Marks & Associates.
Nordheim, E. 1999. Personal communication with Eirik Nordheim, European Aluminum Association.
U.S. EPA. 2005. Voluntary Aluminum Industrial Partnership. U.S. Environmental Protection Agency. Washington,
DC. Available online at .
U.S. EPA. 2006. Global Mitigation of Non-CO2 Greenhouse Gases. United States Environmental
Protection Agency. EPA/430/R/06/005. Washington, DC. Available online at
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7.3.6 Emissions from Semiconductor Manufacturing
Bartos, Scott C., Daniel Lieberman, and C. Shepherd Burton. 2004. Estimating the Impact of Migration to Asian
Foundry Production on Attaining the World Semiconductor Council's 2010 PFC Reduction Goal. Presented at 11th
Annual International Semiconductor Environment, Safety and Health Conference, July 2004, in Mkuhari, Japan.
Beu, L. and P. T. Brown. 1998. An analysis of International and U.S. PFC Emissions Estimating Methods.
Presented at SEMICON South West 98, October 1998, in Austin, Texas, USA.
Burton, C.S., and R. Beizaie. 2001. EPA's PFC Emissions Model (PEVM) v. 2.14: Description and Documentation.
Prepared for the Office of Global Programs, U.S. Environmental Protection Agency. Washington, DC. November
2001.
IPCC. 2002. Background Papers: IPCC Expert Meetings on Good Practice Guidance and Uncertainty Management
in National Greenhouse Gas Inventories. International Panel on Climate Change, 2002, in Kanagawa, Japan.
Molina, L.T., P.J. Woodbridge, and M. J. Molina. 1995. Atmospheric Reactions and Ultraviolet and Infrared
Absorptivities of Nitrogen Trifluoride. Geophysical Research Letters. 22, no. 14, 1873-76.
U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. April 2005. EPA/430/R/05/003. Washington, DC.
Available online at:
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VLSI Research, Inc. 2003. Documents 327031, 327028 and 327029, Volume D1.1 -Worldwide Silicon Demand by
Wafer Size, by Linewidth and Device Type. May 2003. Available online at .
WFW. 1996. World Fab Watch: 1996 Edition. Available online at .
WFW. 2001. World Fab Watch: 2001 Edition. Available online at .
WFW. 2002. World Fab Watch: 2002 Edition. Available online at .
WFW. 2003. World Fab Watch: 2003 Edition. Available online at .
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June 2006 Revised 8. References Page 8-9
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7.3.7 Sulfur Hexafluoride Emissions from Magnesium Production
Bartos S., J. Marks, R. Kantamaneni, C. Laush. 2003. Measured SFe Emissions from Magnesium Die Casting
Operations. Magnesium Technology 2003, Proceedings of The Minerals, Metals & Materials Society (TMS)
Conference, March 2003.
Brandt, H. 2006. Personal communication with Helmut Brandt, Lunt Magnesium.
Edgar, B. 2004. SF6 Usage in the Chinese Magnesium Industry: 2000-2010. Report prepared for U.S.
Environmental Protection Agency. March 2004.
Harnisch and Schwarz. 2003. Cosfs of the Impact on Emissions of Potential Regulatory Framework for Reducing
Emissions of Hydrofluorocarbons, Perfuorocarbons, and Sulphur Hexafluoride. Final Report prepared on behalf of
the European Commission (DG ENV) by Jochen Harnisch and Winfried Schwarz (B4-3040/2002/336380/MAR/E1)
2003.
Gjestland H., and D. Magers. 1996. Practical Usage of Sulfur Hexafluoride for Melt Protection in the Magnesium Die
Casting Industry. #13, 1996 Annual Conference Proceedings, International Magnesium Association in Ube City,
Japan.
IEA. 2001. Abatement of Emissions of Other Greenhouse Gases: Engineered Chemicals. International Energy
Agency (IEA), Greenhouse Gas Research & Development Programme. 2001.
International Magnesium Association (IMA). 2002. Personal communication with Rick Opatick, Vice President.
Norsk Hydro. 2001. Primary Magnesium to Cease at Porsgrunn. October 12, 2001. Available online at
.
Smythe, K. 2002. SF6 Sales and Distribution by End-Use Application (1961-2001). Conference on SF6 and the
Environment: Emissions Reduction Strategies, November 21-22, 2002, in San Diego, California.
Smythe, K. 2004. Trends in SF6 Sales and End-Use Applications: 1961-2003. International Conference on SF6 and
the Environment: Emission Reduction Technologies, December 1-3, 2004, in Scottsdale, Arizona.
Schwarz, W. 2006. Winfried Schwarz, Oko-Recherche, Germany, email to Debbie Ottinger, U.S. EPA, March 2006.
U.S. EPA. 2002. Information from U.S. EPA's SF6 Emission Reduction Partnership for the Magnesium Industry.
U.S. Environmental Protection Agency.
U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. April 2005. EPA/430/R/05/003. Washington, DC.
Available online at
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USGS. 2001. Minerals Yearbook 2001: Magnesium. United States Geological Survey (USGS). GPO Stock #024-
004-02532-8, Reston, Virginia.
USGS. 2002. Minerals Yearbook 2002: Magnesium. United States Geological Survey (USGS). GPO Stock #024-
004-02538-7, Reston, Virginia.
USGS. 2003. Minerals Yearbook 2003: Magnesium. United States Geological Survey (USGS). GPO Stock #024-
004-02538-7, Reston, Virginia.
USGS. 2004. Minerals Yearbook 2004: Magnesium. United States Geological Survey (USGS). GPO Stock #024-
004-02538-7, Reston, Virginia.
Ward's. 2001. Ward's World Motor Vehicle Data. ISBN 0-910589-79-8. Southfield, Missouri, 2001.
Webb, D. 2005. Magnesium Supply and Demand 2004. International Magnesium Association Conference, May 22-
24, 2005, in Berlin, Germany.
Appendix F Agricultural Soils
FAO. 2000. Fertilizer requirements in 2015 and 2030. Food and Agriculture Organization of the United Nations.
June 2006 Revised 8. References Page 8-10
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FAO. 2001. Agricultural Database of Food and Agricultural Organization ofthe United Nations. Food and
Agricultural Organization ofthe United Nations. Available online at .
FAO. 2002. FAOSTAT, Agricultural Database ofthe Food and Agriculture Organization ofthe United Nations. Food
and Agricultural Organization ofthe United Nations. Available online at
. Accessed: August-October 2002.
IPCC. 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris: Intergovernmental
Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and
Development, International Energy Agency.
IPCC. 2000. Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc.10(1.IV.2000), May 2000.
Strehler, A. and Stutzle, W. 1987. Biomass Residues. In Biomass. Edited by D.O. Hall and R.P. Overend. 75-102.
Chichester, UK: John Wiley and Sons, Ltd.
Appendix G U.S. EPA Vintaging Model Framework
IPCC. 1996. Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change.
Edited by J.T. Houghton, L.G. Meira Filho, B.A. Callender, N. Harris, A. Kattenberg, and K. Maskell. UK, Switzerland:
Cambridge University Press.
Scheutz . C., and P. Kjeldsen. 2002. Determination ofthe Fraction of Blowing Agent Released from
Refrigerator/Freezer Foam After Decommissioning the Product. Environment and Resources DTU, Technical
University of Denmark. April 2002.
Scheutz, C., and P. Kjeldsen. 2003. Attenuation of Alternative Blowing Agents in Landfills. Environment and
Resources DTU, Technical University of Denmark. August 2003.
Appendix I
1-1 HCFC-22 Production
Chemical and Economics Handbook (CEH). 2001. Fluorocarbons CEH Marketing Research Report. Chemical and
Economics Handbook.
JICOP. 2006. Mr. Shigehiro Uemura of Japan Industrial Conference for Ozone Layer Protection (JICOP), emails to
Deborah Ottinger Schaefer of U.S. EPA, May 9, 2006.
Oberthur, S. 2001. Production and Consumption of Ozone Depleting Substances, 1986 - 1999. GTZ Report. 2001.
SROC. 2005. IPCC/TEAP Special Report: Safeguarding the Ozone Layer and the Global Climate System: Issues
Related to Hydrofluorocarbons and Perfluorocarbons. Cambridge University Press. 2005.
U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. Washington, DC. April 2005. EPA 430/R/05/003.
Available online at:
.
I-2 Electric Power Systems
EIA. 2002. International Energy Outlook 2002. Energy Information Administration, U.S. Department of Energy.
Washington, DC. Report* DOE/EIA-0484(2002). March 26, 2002. Available online at
.
Ecofys. 2005. Reductions ofSF6 Emissions from High and Medium Voltage Electrical Equipment in Europe, Final
Report to Capiel. June 28, 2005.
U.S. EPA. 2005. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003. Office of Atmospheric
Programs, United States Environmental Protection Agency. Washington, DC. April 2005. EPA/430/R/05/003.
Available online at
.
June 2006 Revised 8. References Page 8-11
-------
Smythe, K. 2004. Trends in SF6 Sales and End-Use Applications: 1961-2003. International Conference on SF6 and
the Environment: Emission Reduction Technologies, December 1-3, 2004, in Scottsdale, Arizona.
Yokota, T., K. Yokotsu, K., Kawakita, H. Yonezawa, T. Sakai, T, Yamagiwa. 2005. Recent Practice for Huge
Reduction ofSF6 Gas Emission from GIS&GCB in Japan. CIGRE SC A3 & B3 Joint Colloquium, 2005, in Tokyo,
Japan.
I-3 Aluminum Production
IAI. 2005. The International Aluminum Institute's Report on the Aluminum Industry's Global Perfuorocarbon Gas
Emissions Reduction Programme - Results of the 2003 Anode Effect Survey. International Aluminum Institute (IAI)
(2005b). London, United Kingdom. January 28, 2005. Available online at .
IEA. 2000. Greenhouse Gas Emissions from the Aluminum Industry. International Energy Agency (IEA) (2000),
Greenhouse Gas Research & Development Program. Cheltenham, United Kingdom. January 2000.
U.S. EPA. 2005. Voluntary Aluminum Industrial Partnership. U.S. Environmental Protection Agency. Washington,
DC. Available online at .
I-4 Magnesium Production
Harnisch and Schwarz. 2003. Cosfs of the Impact on emissions of potential regulatory framework for reducing
emissions of hydrofluorocarbons, perfuorocarbons, and sulphur hexafluoride. Final Report prepared on behalf of the
European Commission (DG ENV) by Jochen Harnisch and Winfried Schwarz (B4-3040/2002/336380/MAR/E1) 2003.
U.S. EPA. 2005. Information from EPA's SFe Emission Reduction Partnership for the Magnesium Industry. U.S.
Environmental Protection Agency.
USGS. 2002. Minerals Yearbook 2002: Magnesium. United States Geological Survey (USGS). GPO Stock #024-
004-02538-7, Reston, Virginia.
Ward's. 2001. Ward's World Motor Vehicle Data. ISBN 0-910589-79-8. Southfield, Missouri, 2001.
June 2006 Revised 8. References Page 8-12
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Appendix A-1: Combined Methane, Nitrous Oxide, and High GWP Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
2.47
28.82
135.62
3.81
139.64
16.09
17.26
76.39
27.90
23.94
24.96
481 .60
34.55
13.53
139.87
18.13
1 ,277.98
77.66
8.50
28.16
46.63
16.66
16.71
36.40
5.43
48.24
14.19
171.72
6.75
224.83
25.60
31.37
0.99
482.39
175.08
61.21
18.06
22.36
9.63
85.00
80.03
1.45
72.74
6.09
6.08
10.21
6.74
0.03
12.13
0.67
2.54
154.45
8.32
0.00
15.26
60.27
29.68
55.60
36.87
1995
2.52
30.57
142.28
2.20
139.29
15.97
14.98
86.68
19.19
24.42
25.73
508.64
22.72
16.00
190.82
20.14
1 ,438.83
84.54
6.78
21.86
49.01
16.22
18.55
43.53
3.01
50.18
13.69
170.77
4.81
196.48
25.27
23.02
0.96
518.81
195.61
75.75
17.62
23.71
11.35
86.54
92.41
2.06
57.37
6.54
3.72
10.59
3.45
0.04
8.80
0.71
2.16
156.07
5.86
0.01
17.02
71.30
32.41
54.22
37.52
2000
3.23
37.65
155.00
2.49
160.35
14.92
12.85
94.53
20.12
23.65
48.41
613.27
16.17
16.01
160.15
20.84
1 ,483.09
102.36
7.07
19.56
88.35
15.28
15.21
50.91
2.86
61.22
12.31
152.23
4.76
155.58
26.24
23.49
1.01
572.10
211.99
87.17
18.84
24.86
14.44
88.77
100.23
2.26
36.35
10.39
3.61
15.08
3.24
0.05
7.44
0.83
2.10
189.99
4.22
0.01
19.19
85.78
34.23
43.65
39.20
2005
4.28
40.96
172.32
2.96
166.79
15.10
15.01
103.34
21.01
22.76
50.01
661 .32
19.50
19.03
170.84
23.08
1 ,637.58
111.31
8.12
20.04
91.04
14.36
16.59
57.30
3.05
67.94
12.24
151.16
4.83
148.04
24.88
24.67
1.03
630.60
226.92
119.24
20.54
23.49
17.25
88.31
91.82
2.65
35.21
10.93
3.82
15.94
3.18
0.05
5.67
0.85
2.15
219.27
4.36
0.01
20.61
92.98
37.23
40.16
42.08
2010
5.32
47.93
195.19
3.25
177.58
14.59
17.04
112.27
21.84
22.76
51.65
718.81
23.16
22.09
184.48
25.34
1 ,734.29
121.27
8.76
19.93
94.15
14.37
18.01
63.82
2.98
75.52
11.98
156.84
4.98
137.15
23.03
25.14
1.22
681.31
238.54
146.89
23.48
22.41
20.46
87.61
105.23
3.12
37.90
14.00
4.00
16.86
3.53
0.05
5.95
0.87
2.18
254.71
4.51
0.01
22.08
98.82
40.46
38.04
43.72
2015
6.35
56.32
222.56
3.41
187.28
14.34
25.37
123.25
22.49
23.32
53.52
775.36
26.25
27.11
202.08
27.80
1,891.57
131.76
9.25
18.78
97.54
14.80
19.39
71.12
2.88
82.84
11.89
158.53
5.10
142.16
23.96
25.87
1.24
737.27
245.81
178.54
26.38
21.71
22.89
93.05
111.41
3.50
41.83
16.12
4.19
17.82
3.74
0.05
6.14
0.92
2.22
301.17
4.69
0.01
23.63
105.27
43.61
37.74
46.58
2020
7.37
66.22
259.20
3.57
196.73
14.27
29.12
134.31
23.13
23.15
55.97
838.74
29.35
32.12
220.07
30.79
2,019.23
143.55
9.57
18.55
101.30
14.66
20.90
79.06
2.68
90.99
11.81
164.50
5.22
140.49
25.07
26.64
1.25
788.12
253.44
218.53
29.52
20.92
25.98
95.18
119.88
3.90
45.51
18.87
4.38
18.77
4.16
0.05
6.35
0.92
2.24
359.39
4.88
0.01
25.22
111.92
47.04
36.06
49.71
-------
Appendix A-1: Combined Methane, Nitrous Oxide, and High GWP Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of China/CPA
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of Non-EU FSU
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
111.96
44.46
15.68
79.58
29.18
48.04
88.03
16.64
68.29
704.13
26.79
11.63
1.37
12.60
3.80
75.66
61.88
60.49
15.93
8.12
9.34
98.10
121.06
23.75
19.70
242.18
21.31
150.35
1 ,066.20
25.90
51.48
87.70
60.70
517.50
3.21
105.77
45.41
29.88
5.83
1.54
119.97
896.54
1 ,425.36
1,157.70
189.96
43.39
1,179.55
2,801.23
1 ,232.76
8,926.48
1995
132.52
39.59
13.33
90.68
34.05
53.19
77.27
17.62
43.22
485.14
29.53
13.41
2.58
9.57
3.61
72.66
52.72
60.70
15.72
7.57
6.39
102.68
124.67
20.27
20.35
193.51
29.32
133.14
1 ,072.84
26.12
54.66
90.02
68.24
557.46
3.96
111.61
55.49
28.14
3.90
1.36
138.53
969.69
1 ,594.22
1,217.74
227.65
39.60
872.00
2,752.53
1,345.18
9,018.62
2000
171.35
41.50
13.58
103.16
40.58
52.56
70.87
16.90
34.40
375.92
35.16
14.63
3.74
8.76
3.86
80.74
59.63
70.16
14.73
7.40
5.24
111.80
131.97
27.68
24.96
171.32
36.03
102.47
1 ,076.76
32.88
62.05
98.00
75.43
725.89
3.91
122.99
81.02
27.25
3.14
1.48
134.87
1,255.71
1,654.21
1 ,439.52
285.31
39.65
729.75
2,645.42
1,464.41
9,513.97
2005
198.82
41.27
12.53
113.20
44.53
58.45
72.41
15.54
36.40
389.11
41.28
15.65
5.23
10.22
4.10
85.36
70.71
71.62
14.70
7.39
4.04
118.11
152.87
49.72
28.27
181.63
43.05
100.99
1 ,054.29
36.22
68.56
111.34
81.42
788.17
4.86
132.42
91.40
26.55
2.66
1.66
151.96
1 ,373.52
1 ,820.72
1,578.41
346.35
41.10
782.92
2,644.78
1 ,608.73
10,196.53
2010
228.32
41.26
12.29
125.36
48.90
64.80
74.59
14.06
40.81
406.69
48.37
16.81
7.64
11.18
4.38
90.97
82.35
71.35
14.93
7.44
4.15
124.91
169.36
75.82
32.20
188.99
53.08
99.01
1,114.42
39.94
74.98
123.50
87.54
861 .39
5.31
144.57
109.40
28.01
2.86
1.95
164.15
1,511.10
1 ,929.45
1,741.89
418.80
44.28
847.01
2,758.39
1 ,740.60
10,991.52
2015
263.22
41.23
12.45
137.16
53.46
70.46
77.70
14.96
45.74
422.74
54.89
18.04
7.65
11.39
4.55
95.09
93.61
74.42
14.62
7.45
4.29
132.70
186.33
87.13
36.60
201 .34
59.33
97.29
1,188.43
43.64
77.82
142.02
94.87
938.24
5.78
157.19
123.04
29.75
3.03
2.17
181.19
1,659.01
2,102.02
1 ,927.87
484.71
47.56
903.43
2,912.25
1 ,877.99
11,914.83
2020
302.46
41.41
12.67
150.89
58.49
76.52
80.82
15.80
50.70
439.39
61.87
19.44
8.23
11.56
4.73
100.10
104.42
75.38
14.36
7.45
4.45
142.11
211.13
98.03
41.80
213.91
67.36
91.26
1 ,278.57
47.72
81.08
170.59
102.34
1 ,023.80
6.40
171.89
139.46
31.85
3.14
2.42
200.84
1,825.18
2,245.51
2,157.24
565.49
51.03
955.82
3,079.32
2,017.83
12,897.41
Projected estimates incorporate the planned reductions from the "Technology-Adoption" Baselines
for the industrial sources of high GWP emissions, and reductions from U.S. voluntary programs
for landfills, coal mining activities, and natural gas and oil systems.
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix A-2: Methane Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
2.34
19.10
78.09
3.46
114.11
9.87
15.60
43.68
16.99
10.79
19.08
291.17
21.49
9.46
77.67
12.58
749.03
49.74
4.19
16.82
33.06
5.82
13.74
24.41
4.37
41.11
6.49
69.97
4.70
132.63
10.43
12.06
0.43
428.62
138.16
46.92
11.65
12.25
8.02
39.30
24.81
1.32
50.14
5.98
5.89
8.27
3.68
0.03
7.97
0.48
2.40
133.12
4.40
0.00
6.43
50.83
20.54
25.77
25.30
1995
2.41
20.93
83.65
1.95
112.63
9.16
13.90
44.68
14.03
10.75
19.99
305.18
14.33
10.58
118.89
13.46
802.04
53.40
3.49
12.91
35.28
6.15
15.75
29.39
2.57
42.00
6.27
69.80
3.90
105.05
10.77
10.19
0.49
460.43
158.60
59.98
11.55
12.95
9.42
38.47
23.43
1.83
41.78
6.34
3.59
8.44
2.29
0.04
5.63
0.47
2.00
137.22
3.18
0.00
6.89
60.44
22.43
23.92
25.52
2000
2.51
26.24
90.26
2.24
124.55
8.19
11.88
48.65
13.45
9.79
31.57
365.55
9.17
11.47
96.56
13.63
788.11
58.44
3.60
10.76
55.51
5.99
14.25
34.32
2.41
49.10
5.49
64.54
3.56
83.10
10.39
10.25
0.51
498.12
170.66
68.65
12.34
13.23
10.52
38.26
20.90
1.94
28.17
9.85
3.49
11.95
2.10
0.04
3.83
0.56
1.94
161.09
2.62
0.00
7.12
69.39
23.93
19.62
26.18
2005
2.93
27.58
95.11
2.69
128.85
8.10
13.99
53.56
13.75
9.14
33.10
389.07
10.32
13.52
102.00
14.80
853.26
62.35
4.12
10.54
58.03
5.58
15.46
37.96
2.50
54.31
5.22
60.92
3.53
68.53
9.73
10.86
0.51
547.69
183.02
95.71
13.13
11.86
11.56
34.57
20.89
2.16
26.89
9.76
3.68
12.77
1.86
0.04
3.94
0.56
1.98
184.82
2.70
0.00
7.52
74.91
25.59
17.33
27.30
2010
3.37
32.06
102.11
2.98
137.51
7.45
15.98
58.53
14.06
8.51
34.66
416.31
12.79
15.62
107.99
15.89
924.19
66.64
4.58
9.61
60.96
5.30
16.68
42.00
2.43
60.17
5.04
57.30
3.52
58.37
8.75
11.26
0.51
597.11
192.40
118.65
15.03
10.91
12.50
30.69
20.87
2.40
29.39
11.82
3.85
13.65
1.90
0.04
4.01
0.56
2.01
217.61
2.79
0.00
7.97
79.08
27.29
14.91
27.20
2015
3.77
38.03
109.78
3.14
144.02
6.96
24.26
63.36
14.23
8.03
36.46
439.33
14.52
18.73
116.33
17.12
992.20
71.02
4.60
8.37
64.15
5.09
17.90
46.55
2.30
65.56
4.67
56.66
3.55
57.08
8.84
11.88
0.51
643.76
197.41
144.47
16.75
10.08
13.30
28.92
20.94
2.62
33.11
13.18
4.03
14.53
1.95
0.04
4.09
0.56
2.04
258.27
2.92
0.00
8.37
83.42
28.74
13.31
27.80
2020
4.17
45.24
120.77
3.30
150.23
6.64
27.96
68.23
14.36
7.67
38.84
463.32
16.29
21.83
124.18
18.71
1 ,057.99
75.95
4.73
7.97
67.69
4.87
19.22
51.40
2.10
71.50
4.31
56.01
3.57
55.14
9.74
12.50
0.51
687.90
202.50
177.30
18.55
9.36
13.99
28.34
21.00
2.84
36.53
14.90
4.21
15.44
2.15
0.04
4.18
0.56
2.06
311.64
3.05
0.00
8.81
87.92
30.24
11.68
28.70
-------
Appendix A-2: Methane Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
77.85
33.51
5.16
68.92
16.91
35.66
59.24
10.47
44.61
561 .55
18.17
6.85
0.84
6.39
2.19
50.48
46.04
29.38
6.59
4.48
4.57
79.92
74.76
23.07
9.54
195.32
20.84
77.52
599.29
15.27
40.07
56.95
50.59
300.94
64.97
31.87
17.26
0.96
80.32
563.33
857.29
751 .64
144.77
26.19
925.74
1 ,553.58
993.53
5,816.07
1995
96.65
35.16
5.38
77.08
17.65
37.75
51.99
11.30
30.81
409.60
20.96
7.68
1.22
5.23
2.04
50.17
33.20
31.33
6.52
4.05
3.24
82.34
82.62
19.68
10.55
161.78
29.00
66.02
592.91
17.97
43.91
64.51
56.95
321 .67
70.07
40.77
17.64
0.91
94.42
614.30
920.07
798.86
179.87
25.54
720.52
1,513.82
1 ,072.59
5,845.57
2000
130.08
34.73
5.31
88.32
19.14
37.47
46.26
10.50
24.64
306.82
24.41
8.22
1.38
4.59
2.05
53.45
31.52
35.60
5.84
3.75
2.86
87.78
90.79
27.09
12.14
148.08
35.65
49.99
546.42
18.41
48.37
73.59
63.49
414.43
79.68
64.12
17.64
0.94
92.10
783.49
916.87
925.60
227.47
25.69
598.64
1 ,393.08
1,149.32
6,020.16
2005
150.54
33.67
5.36
97.75
20.60
41.16
46.40
8.62
26.62
314.46
27.72
9.14
1.68
4.68
2.05
55.30
33.40
36.63
5.70
3.65
2.96
91.60
105.26
49.08
13.41
153.41
41.29
46.23
521 .02
19.88
53.84
83.78
68.59
447.16
85.49
71.97
18.20
0.98
104.09
853.42
989.34
1 ,004.46
273.29
27.22
640.97
1 ,364.36
1 ,254.44
6,407.49
2010
171.74
32.64
5.40
108.78
22.17
44.83
46.66
6.75
30.35
326.21
31.60
10.15
1.77
4.75
2.05
55.93
36.25
37.29
5.57
3.44
3.06
95.10
114.45
75.15
14.92
157.40
50.28
43.10
528.98
21.48
59.19
92.14
73.81
484.32
91.62
86.06
18.94
1.03
112.08
932.24
1 ,067.87
1 ,097.29
328.35
28.89
693.59
1 ,373.70
1,353.21
6,875.14
2015
196.89
31.66
5.43
119.54
23.72
48.28
47.91
6.87
34.16
337.45
35.28
11.20
1.96
4.83
2.05
55.97
38.48
38.12
4.85
3.37
3.19
100.24
123.16
86.43
16.45
164.15
56.02
41.42
534.79
22.89
60.98
107.04
79.13
521 .59
98.11
96.08
19.86
1.07
124.20
1,016.39
1,144.61
1,201.64
377.70
30.27
737.43
1 ,400.99
1 ,449.40
7,358.43
2020
224.56
30.77
5.46
132.11
25.35
51.72
49.20
7.00
37.97
348.61
39.09
12.32
2.17
4.95
2.04
56.52
40.20
38.93
4.13
3.29
3.32
106.22
138.20
97.29
18.17
171.08
63.43
39.42
549.12
24.39
63.01
131.61
84.55
562.45
105.96
108.50
21.15
1.11
138.02
1,109.84
1,219.38
1 ,335.78
438.60
32.11
776.27
1 ,445.00
1 ,547.24
7,904.22
1 Projected estimates include reductions from U.S. voluntary programs for landfills, coal mining activities,
and natural gas and oil systems.
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix A-3: Nitrous Oxide Emissions by Country (MtCO2eq)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.12
9.70
56.61
0.33
20.50
5.74
1.35
32.69
10.82
13.06
5.87
183.07
12.98
4.07
52.33
5.51
521 .04
27.85
4.00
11.30
13.56
10.78
2.96
11.46
1.06
7.13
7.65
93.55
2.03
86.58
14.29
19.13
0.37
51.11
36.53
14.06
6.37
10.03
1.39
40.22
40.15
0.12
22.37
0.07
0.17
1.94
3.06
0.00
4.15
0.18
0.13
19.89
3.89
0.00
8.83
9.43
9.15
21.34
10.41
1995
0.10
9.56
58.18
0.24
22.65
6.14
0.88
41.98
5.10
13.10
5.74
194.28
8.28
5.42
62.75
6.62
626.40
31.04
3.18
8.79
13.73
9.69
2.78
13.81
0.44
8.18
7.25
92.62
0.89
80.94
13.16
12.62
0.34
54.36
36.72
15.57
6.03
10.55
1.50
41.09
40.57
0.20
15.23
0.12
0.11
2.15
1.10
0.00
3.11
0.20
0.15
17.42
2.66
0.00
10.12
10.85
9.98
22.43
11.38
2000
0.71
11.02
63.96
0.24
30.36
5.77
0.78
45.84
6.53
12.88
16.83
241 .42
6.77
4.53
52.05
7.05
645.36
43.62
3.30
8.21
32.84
8.65
0.89
15.96
0.44
12.11
6.55
80.95
1.13
62.26
13.45
12.80
0.35
67.06
40.84
18.31
6.46
11.31
1.67
43.07
37.41
0.23
7.91
0.16
0.11
3.13
0.99
0.01
3.44
0.22
0.15
24.47
1.58
0.00
12.06
16.38
10.29
19.91
12.29
2005
1.33
12.40
75.64
0.25
32.05
5.76
0.78
49.64
6.91
12.14
16.89
264.46
8.67
5.51
57.70
7.86
684.05
48.18
3.80
8.06
32.99
7.81
0.95
17.67
0.53
13.61
6.64
79.93
1.15
63.57
12.99
12.98
0.35
71.29
42.43
22.82
7.36
11.14
1.90
44.67
35.57
0.24
8.08
0.18
0.11
3.16
1.03
0.00
1.40
0.22
0.15
26.78
1.59
0.00
13.07
18.03
11.61
19.96
13.95
2010
1.94
13.99
90.52
0.25
33.05
5.78
0.77
53.49
7.24
12.42
16.95
291.18
9.58
6.48
62.37
8.77
725.29
53.30
3.95
8.10
33.17
7.86
1.01
19.59
0.53
15.32
6.46
86.11
1.18
61.09
13.29
12.60
0.35
75.97
44.26
27.40
8.39
10.97
2.17
46.11
40.71
0.26
8.29
0.20
0.12
3.20
1.16
0.00
1.40
0.22
0.16
28.82
1.62
0.00
14.09
19.69
13.12
19.86
15.58
2015
2.56
15.82
109.51
0.25
35.03
5.79
0.77
59.54
7.60
12.60
17.01
321 .69
10.76
8.39
68.03
9.77
767.51
59.01
4.38
8.01
33.36
7.94
1.06
21.76
0.56
17.25
6.62
82.99
1.20
61.24
13.78
12.44
0.35
81.01
46.12
33.06
9.56
10.91
2.45
48.75
38.81
0.27
8.53
0.22
0.13
3.27
1.21
0.00
1.39
0.22
0.16
31.06
1.65
0.00
15.24
21.79
14.80
19.99
17.69
2020
3.18
18.01
134.39
0.25
37.02
5.80
0.78
65.64
7.99
12.78
17.07
357.36
11.88
10.30
73.76
10.90
811.94
65.41
4.54
7.99
33.58
8.02
1.12
24.24
0.56
19.44
6.79
89.43
1.23
61.39
13.98
12.27
0.35
86.64
48.25
40.02
10.89
10.85
2.77
51.38
40.51
0.29
8.78
0.24
0.14
3.31
1.32
0.00
1.39
0.22
0.17
33.54
1.69
0.00
16.39
23.92
16.72
19.92
19.77
-------
Appendix A-3: Nitrous Oxide Emissions by Country (MtCO2eq)
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of China/CPA
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of Non-EU FSU
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
34.09
10.88
5.06
10.59
12.25
12.34
28.50
6.12
20.07
119.99
8.51
4.78
0.16
6.07
1.51
23.84
13.20
24.33
8.90
3.36
0.49
18.10
45.97
0.66
10.16
45.34
0.10
67.93
376.40
10.62
11.32
27.72
10.09
215.41
3.21
40.72
13.13
9.53
5.83
0.57
38.95
330.12
560.06
393.08
43.75
13.79
224.60
1 ,073.63
232.26
2,871.28
1995
35.85
4.36
4.80
13.50
16.36
15.31
25.00
6.11
11.18
60.39
8.33
5.73
0.77
4.20
1.45
20.79
14.45
22.94
8.70
3.25
0.42
20.13
41.78
0.58
9.80
30.85
0.12
57.12
385.07
8.13
10.66
23.56
11.26
234.89
3.96
41.37
14.39
9.48
3.90
0.43
43.02
352.34
663.66
405.46
46.27
12.91
131.93
1,041.23
261 .05
2,914.86
2000
41.21
6.55
5.22
14.59
21.30
14.33
24.03
6.05
8.26
54.50
9.87
6.39
0.90
3.83
1.54
21.93
15.41
27.77
8.26
3.19
0.40
23.20
40.62
0.58
12.82
22.66
0.14
44.89
395.60
14.38
13.48
22.54
11.85
308.78
3.91
42.51
16.32
8.39
3.14
0.44
36.89
463.08
687.40
498.97
53.15
12.56
113.03
999.86
285.72
3,113.76
2005
48.13
7.03
5.21
14.74
23.57
15.30
25.01
6.40
9.20
57.51
11.22
6.48
1.00
5.01
1.57
23.05
16.86
28.85
8.19
3.00
0.41
24.30
46.31
0.60
14.85
27.01
0.15
45.70
375.84
16.10
14.19
24.48
12.55
338.49
4.86
44.86
17.70
7.87
2.66
0.44
38.92
507.68
730.23
549.77
61.58
13.14
121.26
997.86
304.11
3,285.63
2010
56.31
7.59
5.21
15.42
26.10
16.26
26.29
6.67
9.68
59.59
12.76
6.59
1.12
5.70
1.60
24.24
18.47
28.92
8.38
2.94
0.41
25.60
53.02
0.63
17.27
30.30
0.17
45.87
379.57
18.03
14.97
26.65
13.25
372.88
5.31
49.27
19.88
8.57
2.86
0.49
42.28
559.36
775.21
610.60
71.23
14.62
128.23
1 ,029.95
325.69
3,514.88
2015
65.94
8.21
5.21
16.14
28.92
17.20
27.68
7.16
10.61
61.14
14.51
6.75
1.20
5.73
1.63
25.50
19.73
29.04
8.52
2.85
0.43
26.42
60.84
0.66
20.13
35.77
0.20
41.84
388.36
20.18
15.86
29.06
15.10
411.40
5.78
54.31
22.35
9.34
3.03
0.55
45.86
617.91
823.49
681 .59
82.61
16.45
137.01
1,055.14
349.82
3,764.03
2020
77.36
8.91
5.21
16.93
32.08
18.20
28.92
7.88
11.55
62.53
16.49
7.02
1.29
5.64
1.67
26.87
21.11
29.16
8.65
2.75
0.44
27.27
70.05
0.69
23.62
41.24
0.23
37.81
399.39
22.59
16.91
31.76
16.96
454.93
6.40
59.92
25.13
10.11
3.14
0.62
49.90
685.05
874.22
766.14
96.05
18.00
145.81
1 ,096.70
375.86
4,057.84
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix A-4: High GWP Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.01
0.03
0.92
0.02
5.04
0.47
0.31
0.01
0.08
0.10
0.00
7.37
0.08
0.00
9.87
0.04
7.91
0.07
0.31
0.04
0.01
0.06
0.01
0.53
0.00
0.00
0.05
8.20
0.02
5.62
0.89
0.17
0.20
2.66
0.39
0.24
0.04
0.08
0.22
5.49
15.07
0.01
0.23
0.04
0.02
0.00
0.01
0.00
0.01
0.01
0.01
1.45
0.02
0.00
0.01
0.00
0.00
8.48
1.15
1995
0.01
0.07
0.45
0.01
4.02
0.66
0.21
0.02
0.06
0.58
0.01
9.18
0.11
0.00
9.18
0.05
10.39
0.10
0.12
0.16
0.01
0.37
0.02
0.34
0.00
0.00
0.17
8.35
0.02
10.50
1.33
0.21
0.13
4.03
0.29
0.19
0.04
0.20
0.43
6.97
28.41
0.02
0.37
0.08
0.02
0.00
0.06
0.00
0.06
0.03
0.01
1.43
0.01
0.00
0.00
0.01
0.00
7.86
0.62
2000
0.01
0.39
0.77
0.01
5.44
0.96
0.19
0.05
0.14
0.98
0.01
6.30
0.23
0.00
11.53
0.15
49.62
0.30
0.16
0.59
0.01
0.64
0.07
0.62
0.01
0.01
0.28
6.74
0.07
10.23
2.40
0.45
0.15
6.92
0.50
0.22
0.04
0.33
2.25
7.44
41.91
0.10
0.27
0.38
0.02
0.00
0.15
0.00
0.16
0.05
0.01
4.44
0.03
0.00
0.01
0.01
0.01
4.12
0.73
2005
0.02
0.99
1.57
0.03
5.89
1.24
0.24
0.13
0.35
1.48
0.03
7.79
0.50
0.00
11.14
0.42
100.27
0.78
0.20
1.44
0.02
0.97
0.19
1.68
0.02
0.02
0.38
10.30
0.15
15.94
2.17
0.82
0.17
11.61
1.48
0.72
0.05
0.49
3.79
9.08
35.36
0.25
0.24
1.00
0.03
0.01
0.29
0.00
0.33
0.08
0.02
7.67
0.06
0.00
0.01
0.04
0.03
2.87
0.82
2010
0.02
1.87
2.56
0.02
7.02
1.36
0.28
0.24
0.55
1.84
0.04
11.32
0.79
0.00
14.11
0.68
84.81
1.34
0.23
2.23
0.02
1.21
0.33
2.23
0.02
0.03
0.48
13.42
0.28
17.69
0.99
1.28
0.36
8.24
1.88
0.84
0.06
0.53
5.79
10.81
43.65
0.46
0.22
1.97
0.03
0.02
0.48
0.00
0.54
0.10
0.02
8.28
0.10
0.00
0.02
0.05
0.05
3.27
0.94
2015
0.02
2.47
3.27
0.02
8.23
1.59
0.33
0.34
0.66
2.69
0.05
14.33
0.97
0.00
17.72
0.90
131.86
1.73
0.26
2.39
0.02
1.77
0.43
2.80
0.03
0.04
0.59
18.88
0.35
23.84
1.35
1.56
0.37
12.50
2.28
1.02
0.07
0.72
7.14
15.38
51.66
0.61
0.19
2.72
0.03
0.02
0.58
0.00
0.66
0.14
0.02
11.84
0.12
0.00
0.02
0.07
0.06
4.44
1.09
2020
0.02
2.97
4.04
0.02
9.48
1.83
0.39
0.44
0.79
2.70
0.06
18.07
1.18
0.00
22.12
1.18
149.30
2.19
0.30
2.59
0.03
1.77
0.55
3.43
0.03
0.05
0.72
19.06
0.42
23.95
1.35
1.87
0.39
13.58
2.69
1.21
0.08
0.72
9.23
15.45
58.37
0.77
0.19
3.73
0.03
0.02
0.69
0.00
0.77
0.14
0.02
14.21
0.15
0.00
0.03
0.08
0.09
4.46
1.25
-------
Appendix A-4: High GWP Emissions by Country (MtCO2eq)1
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.02
0.07
5.46
0.07
0.02
0.04
0.29
0.05
3.61
22.60
0.12
0.00
0.37
0.15
0.10
1.34
2.65
6.78
0.43
0.29
4.28
0.08
0.33
0.02
0.00
1.52
0.37
4.91
90.52
0.01
0.09
3.03
0.02
1.16
0.08
0.41
3.08
0.01
0.69
3.09
8.01
12.99
1.44
3.41
29.21
174.02
6.98
239.14
1995
0.03
0.07
3.15
0.10
0.04
0.14
0.27
0.21
1.24
15.15
0.24
0.00
0.58
0.14
0.12
1.70
5.06
6.43
0.50
0.27
2.72
0.21
0.28
0.01
0.00
0.88
0.20
10.00
94.86
0.02
0.09
1.95
0.03
0.90
0.17
0.32
1.02
0.02
1.10
3.04
10.49
13.42
1.52
1.15
19.55
197.48
11.54
258.19
2000
0.06
0.22
3.05
0.25
0.14
0.76
0.57
0.35
1.50
14.59
0.88
0.02
1.46
0.33
0.27
5.36
12.70
6.79
0.63
0.46
1.98
0.83
0.57
0.01
0.00
0.57
0.25
7.59
134.74
0.09
0.21
1.86
0.09
2.68
0.80
0.58
1.22
0.10
5.88
9.14
49.94
14.95
4.69
1.40
18.08
252.48
29.37
380.04
2005
0.16
0.57
1.96
0.71
0.37
2.00
1.00
0.52
0.58
17.14
2.34
0.04
2.55
0.53
0.49
7.01
20.45
6.14
0.81
0.74
0.68
2.22
1.30
0.04
0.01
1.21
1.61
9.06
157.44
0.24
0.53
3.08
0.28
2.52
2.07
1.73
0.49
0.24
8.95
12.43
101.15
24.19
11.49
0.73
20.69
282.55
50.18
503.41
2010
0.27
1.04
1.68
1.16
0.63
3.72
1.64
0.64
0.79
20.89
4.00
0.07
4.75
0.72
0.73
10.80
27.62
5.14
0.98
1.06
0.67
4.21
1.89
0.04
0.01
1.29
2.62
10.04
205.87
0.43
0.82
4.71
0.47
4.20
3.68
3.46
0.51
0.43
9.79
19.50
86.37
34.00
19.21
0.78
25.20
354.74
61.71
601 .50
2015
0.38
1.36
1.81
1.48
0.82
4.98
2.11
0.93
0.96
24.16
5.10
0.09
4.49
0.83
0.87
13.62
35.41
7.26
1.26
1.24
0.68
6.04
2.33
0.04
0.02
1.42
3.12
14.03
265.29
0.57
0.98
5.92
0.64
5.25
4.77
4.62
0.55
0.55
11.12
24.70
133.91
44.63
24.40
0.85
29.00
456.12
78.77
792.37
2020
0.55
1.73
2.00
1.85
1.06
6.60
2.69
0.93
1.18
28.25
6.29
0.10
4.76
0.97
1.02
16.72
43.12
7.29
1.58
1.41
0.69
8.62
2.87
0.05
0.02
1.60
3.70
14.02
330.06
0.74
1.17
7.23
0.83
6.41
6.00
5.82
0.59
0.68
12.91
30.28
151.91
55.32
30.83
0.93
33.74
537.61
94.73
935.36
1 Projected estimates incorporate the planned reductions from the "Technology-Adoption" Baselines
for the industrial sources of high GWP emissions.
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-1: Methane Emissions from Fugitives from Natural Gas and Oil Systems
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.19
9.37
8.13
1.68
6.96
0.27
9.30
0.15
2.12
0.45
1.70
0.99
0.62
0.00
26.18
0.72
2.20
1.38
1.19
0.68
0.00
0.04
0.44
3.11
0.79
0.00
0.01
2.47
1.06
7.01
0.04
1.13
0.00
8.08
32.49
20.73
3.74
0.15
0.02
6.63
0.37
0.05
3.19
5.32
0.47
0.00
0.27
0.00
0.55
0.05
0.00
41.54
1.08
0.00
0.00
0.41
0.00
2.04
0.32
13.40
1995
0.02
10.71
11.10
0.48
7.04
0.29
7.78
0.24
2.32
0.44
1.94
1.13
0.65
0.00
35.09
0.73
2.60
1.48
1.10
0.80
0.00
0.06
0.50
4.72
0.38
0.00
0.08
2.02
0.87
7.54
0.03
1.56
0.00
12.62
42.37
30.74
3.00
0.13
0.02
5.67
0.42
0.11
2.65
5.73
0.17
0.00
0.22
0.00
0.50
0.05
0.00
44.61
0.53
0.00
0.00
0.62
0.00
1.97
0.29
18.53
2000
0.02
14.94
15.13
0.73
5.84
0.30
5.57
0.31
2.52
0.40
2.00
2.05
0.60
0.00
38.27
1.17
4.07
1.85
1.11
0.60
0.00
0.08
0.56
6.88
0.43
0.00
0.06
1.92
0.52
7.35
0.18
1.59
0.00
15.95
44.02
35.79
3.20
0.10
0.02
5.37
0.45
0.11
3.79
9.08
0.13
0.00
0.17
0.00
0.44
0.05
0.00
60.65
0.80
0.00
0.00
1.02
0.00
1.06
0.39
39.56
2005
0.03
15.15
15.13
1.13
7.55
0.31
7.63
0.32
2.74
0.39
2.36
3.68
0.67
0.00
38.27
1.45
6.28
1.91
1.33
0.63
0.00
0.08
0.66
8.30
0.39
0.00
0.06
1.82
0.59
7.70
0.18
1.59
0.00
26.02
48.61
58.66
2.80
0.10
0.02
5.41
0.45
0.11
5.88
8.87
0.17
0.00
0.18
0.00
0.55
0.05
0.00
77.16
0.91
0.00
1.90
0.00
1.06
0.46
51.29
2010
0.04
18.30
16.96
1.30
9.27
0.30
9.55
0.34
2.99
0.38
2.64
7.21
0.83
0.00
39.12
1.63
10.20
2.14
1.56
0.66
0.00
0.08
0.73
10.01
0.36
0.00
0.06
1.72
0.66
7.72
0.19
1.59
0.00
35.95
49.78
76.25
3.40
0.10
0.02
5.74
0.44
0.14
8.64
10.82
0.19
0.00
0.19
0.00
0.62
0.05
0.00
102.70
1.02
0.00
1.98
0.00
1.06
0.47
61.90
2015
0.04
22.71
21.07
1.49
12.00
0.29
17.74
0.43
3.11
0.37
3.28
11.34
0.92
0.00
40.82
2.02
16.70
2.65
1.67
0.74
0.00
0.08
0.90
12.42
0.35
0.00
0.06
1.71
0.75
7.91
0.20
1.59
0.00
49.86
47.97
99.12
3.81
0.10
0.02
6.09
0.43
0.15
12.44
12.07
0.21
0.00
0.20
0.00
0.70
0.05
0.00
136.69
1.16
0.00
2.51
0.00
1.06
0.55
76.67
2020
0.05
27.76
28.36
1.67
14.72
0.29
21.32
0.54
3.18
0.37
4.42
15.45
1.01
0.00
42.09
2.72
19.75
3.55
1.89
0.74
0.01
0.08
1.16
15.16
0.34
0.00
0.06
1.69
0.84
8.09
0.21
1.59
0.00
61.79
46.53
128.85
4.33
0.10
0.02
6.57
0.43
0.17
15.95
13.69
0.24
0.00
0.22
0.00
0.79
0.05
0.00
183.36
1.30
0.00
3.20
0.00
1.06
0.76
93.58
-------
Appendix B-1: Methane Emissions from Fugitives from Natural Gas and Oil Systems
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States1
United States2
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.35
3.60
0.09
0.01
4.10
0.04
20.07
336.00
1.60
0.00
0.01
0.51
0.01
0.01
0.58
0.58
0.00
0.31
0.79
2.86
20.70
19.51
0.00
78.72
19.98
10.66
148.32
148.32
0.00
27.26
29.98
0.01
6.39
1.97
18.00
0.17
0.00
9.11
32.29
2.22
86.93
69.43
1.55
481.18
262.68
57.29
993.57
1995
0.00
0.59
4.82
0.15
0.01
3.90
0.04
11.39
241 .50
2.00
0.01
0.29
0.61
0.01
0.21
1.64
0.73
0.00
0.27
0.19
3.73
29.18
16.72
0.00
82.08
27.91
10.04
152.08
152.08
0.00
30.37
35.12
0.15
6.54
2.95
25.11
0.80
0.00
11.46
40.72
2.75
99.71
94.63
1.92
385.66
274.04
77.81
977.25
2000
0.00
0.65
6.38
0.06
0.01
4.32
0.20
8.34
165.90
2.61
0.01
0.29
0.72
0.01
0.18
3.24
0.83
0.00
0.26
0.05
6.88
39.22
24.35
0.00
87.22
34.35
8.33
149.61
149.61
0.01
34.84
37.93
0.24
7.52
4.89
45.95
0.24
0.00
15.02
69.10
4.32
126.31
131.10
1.37
326.43
278.11
93.12
1 ,029.87
2005
0.00
0.66
6.29
0.06
0.01
5.78
0.23
9.28
172.65
2.77
0.01
0.49
0.72
0.01
0.21
4.07
0.93
0.00
0.24
0.06
7.72
50.88
46.20
0.00
90.77
39.83
8.00
127.61
150.78
0.01
39.65
45.44
0.28
8.23
5.58
51.39
0.26
0.00
19.72
83.18
6.56
153.44
164.45
1.62
368.38
272.23
115.16
1,165.03
2010
0.00
0.67
6.54
0.07
0.01
7.24
0.26
12.01
179.40
3.38
0.01
0.51
0.88
0.01
0.25
6.08
1.04
0.00
0.23
0.07
8.04
57.20
72.13
0.00
94.32
48.65
7.67
142.37
169.88
0.02
44.32
50.96
0.29
9.92
6.25
62.78
0.36
0.00
20.51
100.40
10.49
191.30
205.44
1.95
414.57
300.53
129.74
1 ,354.42
2015
0.00
0.69
8.30
0.09
0.01
9.59
0.27
14.65
186.70
3.76
0.01
0.64
1.02
0.01
0.31
7.58
1.17
0.00
0.23
0.08
10.19
63.50
83.27
0.00
98.15
54.20
7.51
155.03
190.74
0.02
45.43
63.26
0.36
12.28
7.77
69.95
0.42
0.00
26.01
124.41
17.07
249.10
243.09
2.13
450.53
329.91
153.51
1 ,569.74
2020
0.01
0.70
10.56
0.12
0.02
11.95
0.28
17.30
194.01
4.27
0.01
0.81
1.19
0.01
0.38
8.57
1.30
0.00
0.23
0.08
12.96
76.12
93.99
0.00
101.99
61.41
7.35
169.29
216.19
0.02
46.81
85.11
0.45
14.96
10.45
79.22
0.46
0.00
33.05
151.85
20.21
334.72
291 .97
2.41
481 .40
366.97
178.05
1 ,827.58
1 US emissions INCLUDING reductions from voluntary programs; included in OECD90 & EU and World totals
2 US emissions NOT INCLUDING the effect of voluntary programs; not included in OECD90 & EU and World totals
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-2: Methane Emissions from Fugitives from Coal Mining Activities
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
1990
0.07
0.00
0.19
0.00
15.82
0.01
0.00
0.00
0.04
0.00
1.24
1.59
0.00
1.91
0.61
126.13
1.86
0.05
7.60
0.02
0.07
0.00
0.00
0.41
0.00
0.01
4.33
0.07
25.77
1.10
1.12
10.87
0.33
0.29
0.00
0.00
0.00
0.12
2.81
0.00
24.87
0.00
0.30
0.00
0.00
0.12
1.48
0.00
0.00
0.20
0.01
0.00
0.03
0.27
1.83
25.26
0.00
0.90
0.04
0.16
1995
0.06
0.01
0.10
0.00
17.48
0.01
0.00
0.00
0.03
0.00
1.11
1.45
0.00
1.71
0.29
149.10
1.99
0.02
5.81
0.03
0.13
0.00
0.00
0.25
0.00
0.01
4.43
0.01
17.59
1.22
0.70
13.65
0.43
0.30
0.00
0.00
0.00
0.06
1.34
0.00
17.19
0.00
0.04
0.00
0.00
0.13
1.76
0.01
0.00
0.10
0.01
0.00
0.03
0.28
2.86
27.23
0.00
0.99
0.02
0.22
2000
0.00
0.01
0.25
0.00
19.64
0.01
0.00
0.00
0.02
0.00
1.32
1.20
0.00
0.95
0.10
117.57
2.95
0.00
5.02
0.03
0.06
0.00
0.00
0.24
0.00
0.01
2.56
0.00
10.18
1.35
0.57
15.84
0.45
0.37
0.00
0.00
0.00
0.07
0.77
0.00
9.98
0.00
0.03
0.00
0.00
0.13
2.15
0.00
0.00
0.07
0.09
0.00
0.02
0.34
1.24
26.91
0.01
1.03
0.02
0.22
2005
0.00
0.01
0.23
0.00
21.82
0.01
0.00
0.00
0.02
0.00
1.22
1.34
0.00
0.88
0.12
135.66
3.44
0.00
4.82
0.03
0.09
0.00
0.00
0.21
0.00
0.00
2.60
0.00
8.39
1.32
0.49
19.46
0.49
0.39
0.00
0.00
0.00
0.07
0.76
0.00
6.67
0.00
0.03
0.00
0.00
0.14
2.47
0.00
0.00
0.05
0.13
0.00
0.02
0.41
0.02
25.56
0.01
1.06
0.00
0.22
2010
0.00
0.01
0.21
0.00
26.38
0.01
0.00
0.00
0.02
0.00
1.12
1.65
0.00
0.88
0.11
153.75
4.02
0.00
3.91
0.03
0.09
0.00
0.00
0.20
0.00
0.00
2.63
0.00
7.75
1.40
0.43
23.08
0.50
0.42
0.00
0.00
0.00
0.08
0.75
0.00
6.38
0.00
0.03
0.00
0.00
0.15
2.84
0.00
0.00
0.04
0.19
0.00
0.02
0.41
0.00
24.28
0.01
1.09
0.00
0.23
2015
0.00
0.01
0.19
0.00
28.18
0.01
0.00
0.00
0.02
0.00
1.03
1.84
0.00
0.85
0.10
171.84
4.68
0.00
3.11
0.03
0.09
0.00
0.00
0.19
0.00
0.00
2.66
0.00
7.15
1.47
0.38
28.37
0.49
0.45
0.00
0.00
0.00
0.08
0.74
0.00
6.10
0.00
0.02
0.00
0.00
0.16
3.26
0.00
0.00
0.03
0.28
0.00
0.02
0.48
0.00
23.07
0.01
1.12
0.00
0.23
2020
0.00
0.01
0.19
0.00
29.67
0.01
0.00
0.00
0.02
0.00
0.95
2.01
0.00
0.82
0.10
189.93
5.46
0.00
2.97
0.03
0.09
0.00
0.00
0.19
0.00
0.00
2.69
0.00
5.90
1.53
0.33
33.65
0.47
0.47
0.00
0.00
0.00
0.09
0.73
0.00
5.81
0.00
0.02
0.00
0.00
0.17
3.74
0.00
0.00
0.03
0.41
0.00
0.02
0.67
0.00
21.91
0.01
1.15
0.00
0.23
-------
Appendix B-2: Methane Emissions from Fugitives from Coal Mining Activities
MtCO2eq
Country
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States1
United States2
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
16.77
0.07
3.66
60.90
0.00
0.00
0.00
0.57
0.30
6.72
4.83
1.79
0.00
0.10
0.22
1.63
0.00
0.00
55.34
0.00
18.29
81.89
81.89
0.00
0.46
0.02
0.46
1.16
0.00
0.00
0.81
0.00
0.82
9.74
152.05
5.44
0.29
1.05
142.04
187.99
18.13
516.74
1995
15.57
0.00
3.93
36.75
0.00
0.00
0.00
0.62
0.27
6.66
1.61
1.43
0.00
0.01
0.34
1.56
0.00
0.00
30.12
0.00
12.59
65.78
65.78
0.00
0.27
0.04
0.83
1.15
0.00
0.00
0.75
0.00
1.04
10.69
177.26
5.33
0.30
0.96
84.40
154.31
18.28
451 .55
2000
11.90
0.00
2.67
28.98
0.00
0.00
0.00
0.61
0.25
7.08
1.17
1.20
0.00
0.00
0.32
1.70
0.00
0.00
28.33
0.00
7.00
56.22
56.22
0.00
0.26
0.08
1.00
0.96
0.00
0.00
1.72
0.00
1.64
9.31
145.55
6.89
0.37
1.85
67.59
124.56
20.75
376.88
2005
11.33
0.00
2.77
26.25
0.00
0.00
0.00
0.46
0.25
7.40
0.91
1.20
0.00
0.00
0.36
1.83
0.00
0.00
26.32
0.00
6.73
55.33
71.50
0.00
0.24
0.11
1.19
0.96
0.00
0.00
2.16
0.00
1.64
8.41
162.47
7.60
0.39
2.30
59.51
123.17
24.28
388.14
2010
10.77
0.00
2.76
27.51
0.00
0.00
0.00
0.49
0.25
7.21
0.71
0.98
0.00
0.00
0.39
1.96
0.00
0.00
24.48
0.00
6.60
51.09
75.86
0.00
0.23
0.15
1.42
1.00
0.00
0.00
2.82
0.00
1.65
8.25
179.50
8.44
0.42
2.97
58.63
121.50
27.85
407.56
2015
10.26
0.00
2.75
26.91
0.00
0.00
0.00
0.50
0.25
7.10
0.56
0.71
0.00
0.00
0.43
2.10
0.00
0.00
23.77
0.00
6.41
46.44
73.82
0.00
0.22
0.19
1.69
1.08
0.00
0.00
3.77
0.00
1.66
8.22
196.63
9.46
0.45
3.93
57.02
116.71
33.14
425.56
2020
9.75
0.00
2.74
26.30
0.00
0.00
0.00
0.49
0.25
7.44
0.44
0.44
0.00
0.00
0.48
2.25
0.00
0.00
23.23
0.00
6.22
46.42
76.67
0.00
0.21
0.25
2.02
1.20
0.00
0.00
5.16
0.00
1.69
8.68
213.89
10.70
0.47
5.34
55.58
116.31
38.52
449.48
1 US emissions INCLUDING reductions from voluntary programs; included in OECD90 & EU and World totals
2 US emissions NOT INCLUDING the effect of voluntary programs; not included in OECD90 & EU and World totals
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-3: Methane Emissions from Stationary and Mobile Combustion
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
1990
0.12
0.13
0.20
0.03
2.39
0.47
0.09
0.11
0.55
0.26
0.01
0.58
0.10
0.00
4.50
0.08
1.30
0.18
0.19
1.25
0.02
0.19
0.05
0.23
0.09
0.15
0.48
4.93
0.06
4.56
0.41
0.85
0.00
0.15
0.16
1.05
0.18
0.15
0.06
1.55
0.60
0.03
0.13
0.04
0.04
0.27
0.00
0.11
0.05
0.00
0.71
0.15
0.00
0.00
0.01
0.00
0.67
0.21
0.22
0.41
1995
0.01
0.11
0.68
0.03
2.43
0.41
0.06
0.11
0.45
0.24
0.01
0.74
0.08
0.00
4.58
0.10
2.11
0.24
0.11
0.67
0.02
0.47
0.06
0.25
0.12
0.18
0.48
4.62
0.01
1.68
0.44
0.73
0.00
0.19
0.22
1.51
0.21
0.10
0.08
1.82
0.62
0.03
0.13
0.08
0.03
0.28
0.00
0.20
0.05
0.01
0.81
0.09
0.00
0.00
0.02
0.01
0.66
0.18
0.25
0.43
2000
0.01
0.13
0.77
0.02
2.21
0.30
0.06
0.11
0.35
0.21
0.02
0.92
0.06
0.01
5.32
0.13
2.72
0.25
0.13
0.41
0.02
0.58
0.05
0.33
0.11
0.24
0.46
4.08
0.03
1.26
0.47
0.68
0.00
0.20
0.28
1.82
0.22
0.11
0.10
1.73
0.62
0.04
0.10
0.10
0.03
0.25
0.00
0.25
0.07
0.01
0.88
0.03
0.00
0.00
0.02
0.01
0.62
0.12
0.28
0.41
2005
0.01
0.15
0.91
0.02
2.41
0.31
0.06
0.16
0.40
0.21
0.02
1.09
0.07
0.01
5.32
0.15
3.44
0.30
0.16
0.39
0.02
0.55
0.06
0.33
0.10
0.27
0.46
3.87
0.03
1.26
0.41
0.71
0.00
0.25
0.31
2.07
0.25
0.11
0.11
1.74
0.62
0.04
0.10
0.11
0.03
0.26
0.00
0.25
0.07
0.01
1.06
0.03
0.00
0.00
0.03
0.01
0.68
0.14
0.32
0.45
2010
0.01
0.18
1.07
0.03
2.67
0.30
0.06
0.22
0.42
0.21
0.03
1.29
0.08
0.01
5.44
0.18
4.39
0.36
0.19
0.31
0.03
0.52
0.06
0.34
0.09
0.31
0.46
3.66
0.03
1.15
0.40
0.71
0.00
0.32
0.43
2.36
0.28
0.12
0.12
1.85
0.62
0.04
0.11
0.13
0.04
0.28
0.00
0.25
0.07
0.02
1.10
0.03
0.00
0.00
0.03
0.01
0.70
0.15
0.37
0.49
2015
0.01
0.20
1.23
0.03
2.99
0.29
0.07
0.30
0.45
0.21
0.03
1.43
0.09
0.01
5.68
0.20
5.31
0.42
0.20
0.25
0.03
0.49
0.06
0.35
0.09
0.36
0.46
3.63
0.03
1.10
0.40
0.71
0.00
0.39
0.50
2.75
0.33
0.13
0.14
1.96
0.63
0.04
0.11
0.15
0.04
0.30
0.00
0.25
0.07
0.02
1.14
0.03
0.00
0.00
0.03
0.02
0.74
0.17
0.43
0.53
2020
0.01
0.24
1.43
0.04
3.32
0.29
0.08
0.41
0.47
0.21
0.04
1.61
0.10
0.01
5.85
0.23
6.45
0.48
0.23
0.25
0.03
0.46
0.06
0.36
0.09
0.41
0.46
3.61
0.03
1.05
0.41
0.71
0.00
0.49
0.76
3.21
0.38
0.14
0.16
2.11
0.63
0.04
0.12
0.17
0.05
0.32
0.00
0.25
0.07
0.02
1.17
0.04
0.00
0.00
0.03
0.02
0.74
0.24
0.49
0.57
-------
Appendix B-3: Methane Emissions from Stationary and Mobile Combustion
MtCO2eq
Country
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.25
0.07
0.07
0.18
0.79
0.45
0.44
4.20
0.32
0.07
0.05
0.37
0.15
0.75
0.49
1.18
0.56
0.17
0.13
0.04
1.06
0.05
0.01
4.12
0.07
2.51
12.62
0.01
0.26
0.25
0.04
2.16
0.67
0.18
0.00
0.01
0.34
3.74
1.75
2.81
1.93
0.31
9.81
44.64
1.60
66.58
1995
0.26
0.09
0.07
0.25
1.16
0.44
1.07
3.53
0.39
0.14
0.06
0.21
0.14
0.86
0.67
1.09
0.57
0.13
0.01
0.07
0.97
0.05
0.01
1.51
0.09
1.91
12.58
0.01
0.22
0.29
0.04
2.39
0.70
0.25
0.15
0.02
0.46
4.22
2.58
3.72
2.65
0.27
6.12
41.37
2.14
63.08
2000
0.28
0.11
0.08
0.28
1.00
0.43
0.76
4.12
0.46
0.24
0.07
0.17
0.13
0.69
0.90
1.01
0.48
0.11
0.00
0.08
0.76
0.06
0.01
0.74
0.10
2.05
10.71
0.01
0.22
0.31
0.06
2.40
0.92
0.29
0.15
0.02
0.64
4.33
3.20
4.36
3.12
0.31
5.75
37.81
2.73
61.60
2005
0.28
0.14
0.09
0.33
1.04
0.48
0.76
4.12
0.51
0.29
0.09
0.17
0.13
0.75
1.12
0.96
0.43
0.10
0.00
0.09
0.70
0.06
0.01
0.88
0.12
2.46
9.19
0.02
0.24
0.37
0.08
2.73
1.07
0.32
0.16
0.02
0.80
4.88
3.97
5.14
3.53
0.34
5.98
36.68
3.32
63.84
2010
0.28
0.18
0.11
0.34
1.09
0.54
0.76
4.70
0.58
0.34
0.10
0.18
0.13
0.82
1.40
0.91
0.38
0.10
0.00
0.09
0.66
0.07
0.01
0.97
0.13
2.46
8.89
0.02
0.26
0.45
0.10
3.11
1.25
0.36
0.17
0.02
1.00
5.52
4.98
5.91
4.01
0.38
6.73
36.44
4.11
68.09
2015
0.28
0.23
0.12
0.35
1.14
0.56
0.76
5.04
0.67
0.40
0.12
0.18
0.13
0.87
1.67
0.90
0.35
0.09
0.00
0.09
0.65
0.08
0.01
1.02
0.16
2.46
8.91
0.02
0.29
0.54
0.12
3.53
1.42
0.41
0.19
0.03
1.21
6.18
5.96
6.62
4.64
0.42
7.20
37.10
4.91
73.03
2020
0.28
0.29
0.14
0.36
1.19
0.58
0.76
5.38
0.77
0.47
0.14
0.16
0.13
0.94
2.01
0.89
0.33
0.09
0.00
0.10
0.65
0.10
0.02
1.07
0.19
2.46
9.14
0.03
0.33
0.65
0.15
4.00
1.61
0.47
0.21
0.03
1.48
6.95
7.18
7.44
5.38
0.47
7.69
38.01
6.07
79.20
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-4: Methane Emissions from Biomass Combustion
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Azerbaijan
Bangladesh
Bolivia
Brazil
Cambodia
Chile
China
Colombia
Democratic Republic of Congo (Kinshasa)
Ecuador
Egypt
Ethiopia
Georgia
India
Indonesia
Iran
Iraq
Israel
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Macedonia
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
Nigeria
North Korea
Pakistan
Peru
Philippines
Saudi Arabia
Senegal
Singapore
South Africa
South Korea
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
United Arab Emirates
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
1990
0.10
0.00
0.08
0.01
0.00
3.40
0.15
5.95
0.39
0.52
43.34
1.26
2.11
0.38
1.55
3.33
0.01
31.42
6.66
0.18
0.00
0.00
0.00
0.02
0.00
0.00
0.48
0.05
1.56
0.01
0.24
2.34
1.49
0.00
8.29
0.25
2.80
0.85
2.41
0.00
0.23
0.00
1.64
0.04
0.00
9.46
1.90
0.00
1.56
0.00
0.09
0.00
0.06
2.45
17.90
2.68
0.03
0.09
0.00
1.20
1995
0.02
0.01
0.14
0.01
0.00
3.74
0.15
5.49
0.50
0.66
45.10
1.38
2.37
0.39
1.75
3.93
0.01
34.36
7.29
0.18
0.00
0.00
0.00
0.02
0.00
0.00
0.50
0.05
1.59
0.01
0.28
2.38
1.66
0.00
9.34
0.27
3.08
0.91
1.65
0.00
0.26
0.00
1.80
0.04
0.00
9.65
1.79
0.00
1.76
0.00
0.09
0.00
0.06
2.49
16.50
2.66
0.03
0.10
0.00
1.20
2000
0.02
0.02
0.18
0.01
0.00
4.07
0.16
5.48
0.71
0.76
46.70
0.93
2.73
0.41
1.96
4.44
0.02
37.19
7.20
0.19
0.00
0.00
0.00
0.02
0.00
0.00
0.51
0.04
1.61
0.02
0.29
2.44
1.82
0.00
10.65
0.27
3.35
0.97
1.03
0.00
0.29
0.00
1.96
0.04
0.00
9.89
1.83
0.00
1.97
0.00
0.09
0.00
0.06
2.55
18.57
2.77
0.04
0.10
0.00
1.24
2005
0.02
0.02
0.18
0.01
0.00
4.28
0.16
5.76
0.80
0.78
47.41
0.95
3.00
0.42
2.15
4.88
0.02
38.70
7.30
0.21
0.00
0.00
0.00
0.02
0.00
0.00
0.52
0.04
1.65
0.02
0.30
2.54
1.92
0.00
11.70
0.28
3.52
1.00
1.07
0.00
0.32
0.00
2.16
0.05
0.00
10.29
2.19
0.00
2.17
0.00
0.09
0.00
0.06
2.66
20.37
2.84
0.04
0.10
0.00
1.30
2010
0.02
0.02
0.19
0.01
0.00
4.50
0.17
6.05
0.89
0.80
48.12
0.97
3.30
0.43
2.37
5.36
0.02
40.28
7.67
0.23
0.00
0.00
0.00
0.02
0.00
0.00
0.53
0.04
1.69
0.02
0.31
2.64
2.01
0.00
12.85
0.29
3.70
1.02
1.12
0.00
0.35
0.00
2.37
0.05
0.00
10.71
2.61
0.00
2.38
0.00
0.09
0.00
0.06
2.77
22.35
2.91
0.04
0.10
0.00
1.36
2015
0.02
0.03
0.19
0.01
0.00
4.65
0.17
6.24
0.99
0.82
48.56
1.00
3.58
0.44
2.57
5.82
0.02
41.21
8.05
0.32
0.01
0.00
0.00
0.02
0.00
0.00
0.54
0.04
1.74
0.02
0.32
2.76
2.08
0.00
13.96
0.30
3.83
1.05
1.16
0.00
0.39
0.00
2.57
0.05
0.00
11.15
2.99
0.00
2.59
0.01
0.09
0.00
0.06
2.88
24.29
2.99
0.06
0.10
0.00
1.41
2020
0.02
0.03
0.20
0.01
0.00
4.81
0.18
6.44
1.09
0.84
48.99
1.03
3.89
0.45
2.79
6.33
0.02
42.17
8.23
0.46
0.01
0.00
0.00
0.02
0.00
0.00
0.54
0.05
1.78
0.02
0.34
2.87
2.15
0.00
15.16
0.31
3.96
1.08
1.21
0.00
0.42
0.00
2.80
0.05
0.00
11.62
3.41
0.00
2.81
0.01
0.09
0.00
0.07
3.00
26.41
3.07
0.09
0.10
0.00
1.46
-------
Appendix B-4: Methane Emissions from Biomass Combustion
MtCO2eq
Country
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
36.63
47.14
13.57
0.22
0.24
0.05
1.90
61.23
160.98
1995
37.74
49.14
13.53
0.23
0.16
0.05
1.79
65.05
167.68
2000
42.60
51.03
13.41
0.23
0.16
0.06
1.84
68.28
177.61
2005
46.77
51.96
13.89
0.26
0.16
0.06
2.19
70.97
186.25
2010
51.35
52.90
14.39
0.28
0.16
0.06
2.61
74.03
195.79
2015
55.80
53.59
14.80
0.40
0.16
0.06
2.99
76.35
204.15
2020
60.64
54.28
15.22
0.57
0.16
0.06
3.41
78.52
212.87
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-5: Methane Emissions from Other Industrial Non-Agricultural Sources
MtCO2eq
Country
Australia
Austria
Belarus
Belgium
Brazil
Bulgaria
Croatia
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Ireland
Italy
Japan
Lithuania
Luxembourg
Mexico
Netherlands
New Zealand
Nigeria
Norway
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Thailand
Ukraine
United Kingdom
United States
Venezuela
Rest of Africa
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.07
0.01
0.02
0.03
0.06
0.06
0.02
0.12
0.00
0.01
0.00
0.34
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.11
0.34
0.00
0.00
0.10
0.30
0.02
0.00
0.04
0.01
0.27
0.01
0.03
0.48
0.20
0.00
0.07
0.42
0.06
0.00
0.01
0.01
0.10
0.18
2.52
0.10
0.08
0.00
0.15
0.00
0.26
0.24
0.02
0.61
4.54
0.49
6.31
1995
0.08
0.01
0.02
0.03
0.06
0.07
0.01
0.08
0.00
0.01
0.00
0.33
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.11
0.30
0.00
0.00
0.10
0.30
0.06
0.00
0.04
0.01
0.24
0.01
0.02
0.48
0.20
0.00
0.03
0.42
0.07
0.00
0.01
0.01
0.03
0.15
2.86
0.10
0.08
0.00
0.11
0.00
0.26
0.24
0.01
0.52
4.80
0.49
6.44
2000
0.07
0.01
0.03
0.04
0.06
0.07
0.01
0.07
0.00
0.01
0.00
0.38
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.06
0.16
0.00
0.00
0.10
0.30
0.10
0.00
0.04
0.01
0.17
0.01
0.02
0.48
0.20
0.01
0.03
0.42
0.07
0.01
0.01
0.01
0.23
0.08
2.90
0.10
0.08
0.01
0.11
0.00
0.26
0.24
0.01
0.74
4.62
0.49
6.47
2005
0.07
0.01
0.03
0.02
0.06
0.07
0.01
0.07
0.00
0.01
0.00
0.38
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.07
0.16
0.00
0.00
0.10
0.30
0.10
0.00
0.04
0.01
0.13
0.01
0.02
0.48
0.20
0.01
0.03
0.42
0.07
0.01
0.01
0.01
0.23
0.08
2.58
0.10
0.08
0.06
0.11
0.00
0.26
0.24
0.01
0.74
4.25
0.55
6.16
2010
0.07
0.01
0.04
0.02
0.06
0.07
0.01
0.07
0.00
0.01
0.00
0.38
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.07
0.16
0.00
0.00
0.10
0.30
0.10
0.00
0.04
0.01
0.13
0.01
0.02
0.48
0.20
0.00
0.03
0.42
0.07
0.01
0.01
0.01
0.23
0.08
2.59
0.10
0.08
0.06
0.11
0.00
0.26
0.24
0.01
0.74
4.26
0.55
6.17
2015
0.07
0.01
0.04
0.02
0.06
0.07
0.01
0.07
0.00
0.01
0.00
0.38
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.08
0.16
0.00
0.00
0.10
0.30
0.10
0.00
0.04
0.01
0.13
0.01
0.02
0.48
0.20
0.00
0.03
0.42
0.07
0.01
0.01
0.01
0.23
0.08
2.59
0.10
0.08
0.06
0.11
0.00
0.26
0.24
0.01
0.75
4.26
0.55
6.17
2020
0.07
0.01
0.04
0.01
0.06
0.07
0.01
0.07
0.00
0.01
0.00
0.38
0.00
0.01
0.00
0.04
0.01
0.04
0.00
0.08
0.16
0.00
0.00
0.10
0.30
0.10
0.00
0.04
0.01
0.13
0.01
0.02
0.48
0.20
0.00
0.03
0.42
0.07
0.01
0.01
0.01
0.23
0.08
2.62
0.10
0.08
0.06
0.11
0.00
0.26
0.24
0.01
0.75
4.29
0.55
6.20
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-6: Methane Emissions from Enteric Fermentation
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
1990
1.22
3.43
54.89
0.93
67.51
3.57
3.44
10.89
9.90
4.49
9.19
184.95
3.78
2.94
18.68
5.60
186.30
25.95
1.34
3.27
1.52
3.11
5.90
6.79
1.09
28.82
1.87
30.89
1.55
34.29
2.86
2.99
0.27
179.84
17.68
9.75
2.58
9.18
0.62
12.34
7.25
0.36
14.55
0.05
2.57
2.06
2.06
0.01
3.30
0.33
0.98
47.27
1.74
4.93
8.33
10.18
7.32
21.53
23.06
1.19
1995
1.59
3.32
56.44
0.72
63.00
3.44
3.23
10.78
7.53
4.50
9.85
200.40
1.79
3.45
21.26
6.48
221 .32
29.06
0.85
2.05
1.30
3.08
6.74
7.58
0.56
28.04
1.63
29.62
1.16
28.52
2.83
1.82
0.25
190.62
18.93
10.87
1.94
9.65
0.68
12.48
7.12
0.54
14.05
0.06
1.61
2.47
0.83
0.01
2.22
0.33
0.67
44.59
1.47
5.41
9.27
11.07
7.02
22.18
25.27
1.00
2000
1.58
3.98
51.78
0.74
64.36
3.24
3.30
10.68
6.22
4.24
10.86
208.03
1.66
3.60
20.83
6.86
230.79
28.93
0.75
1.70
1.08
2.87
6.94
8.46
0.38
32.12
1.58
29.23
1.18
26.55
2.88
1.77
0.24
201 .89
17.97
13.03
2.01
9.93
0.69
12.25
6.76
0.45
7.09
0.09
1.65
2.26
0.56
0.01
1.31
0.33
0.56
41.53
0.78
5.95
10.22
11.75
6.45
23.07
30.87
0.89
2005
1.57
4.45
55.67
0.78
63.74
3.19
3.27
11.72
6.07
4.13
11.82
226.28
2.17
4.79
23.41
7.43
258.88
30.83
0.87
1.72
1.22
2.70
7.56
8.85
0.61
35.97
1.43
29.14
1.15
22.31
2.90
2.23
0.24
217.80
20.41
15.83
2.16
8.70
0.70
11.97
6.97
0.48
7.11
0.10
1.71
2.52
0.53
0.01
1.31
0.33
0.55
44.89
0.77
6.32
11.41
12.43
6.28
23.87
34.10
0.94
2010
1.57
5.12
59.86
0.84
64.97
3.10
3.25
12.88
5.93
4.02
12.87
246.35
2.26
5.97
25.68
8.06
291 .32
32.86
0.97
1.78
1.38
2.57
8.24
9.26
0.69
40.33
1.43
29.04
1.12
18.81
2.89
2.68
0.24
235.03
23.21
19.60
2.34
7.78
0.71
11.52
7.18
0.51
7.21
0.11
1.77
2.80
0.56
0.01
1.31
0.33
0.55
48.58
0.76
6.72
12.75
13.12
6.02
23.66
37.67
0.99
2015
1.56
6.03
62.53
0.82
65.28
3.01
3.23
13.93
5.78
3.91
13.81
262.07
2.19
8.02
28.67
8.63
320.23
34.65
0.97
1.81
1.54
2.53
8.83
9.58
0.71
44.16
1.43
29.13
1.10
18.87
2.88
3.37
0.24
246.41
25.02
20.71
2.46
6.95
0.71
11.17
7.39
0.54
7.33
0.12
1.82
3.08
0.61
0.01
1.31
0.33
0.55
51.90
0.74
7.07
14.06
13.81
5.82
23.96
40.97
1.03
2020
1.56
7.55
65.33
0.80
65.60
2.92
3.24
15.08
5.65
3.80
14.82
278.91
2.24
10.07
31.66
9.24
352.74
36.54
0.97
1.85
1.72
2.48
9.48
9.92
0.72
48.37
1.43
29.22
1.08
18.93
2.87
4.06
0.24
258.38
26.98
21.88
2.60
6.21
0.71
10.83
7.60
0.57
7.47
0.12
1.87
3.38
0.65
0.01
1.31
0.33
0.54
55.48
0.73
7.45
15.50
14.50
5.63
24.26
44.57
1.06
-------
Appendix B-6: Methane Emissions from Enteric Fermentation
MtCO2eq
Country
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
1.71
40.50
7.33
5.51
16.66
2.59
11.15
93.03
1.57
2.82
0.01
2.44
0.73
19.25
2.58
12.65
3.03
2.77
2.58
13.04
25.52
2.38
4.15
36.50
0.24
18.17
117.86
12.38
5.84
13.44
6.51
123.87
29.78
4.56
4.07
0.17
9.45
213.71
203.93
396.68
19.73
7.62
175.01
457.46
298.01
1,772.14
1995
1.76
44.86
7.74
5.64
11.86
2.57
6.62
68.27
1.85
3.23
0.00
1.55
0.71
17.54
3.75
12.86
3.11
2.65
2.05
12.74
23.90
1.81
4.48
28.79
0.34
17.96
122.97
13.73
6.38
15.03
7.22
133.48
31.41
4.44
4.17
0.18
9.91
224.25
240.87
421 .49
20.70
7.27
137.08
434.86
317.58
1,804.10
2000
1.75
51.34
8.58
6.04
9.08
2.57
5.69
43.61
1.85
3.61
0.00
1.10
0.69
17.96
2.83
14.26
2.90
2.52
1.79
10.35
21.36
1.50
5.10
16.19
0.45
17.30
115.60
13.35
6.09
16.13
7.67
150.23
31.15
5.17
3.33
0.18
9.53
253.41
251.17
424.13
23.74
6.21
90.15
417.20
332.60
1,798.61
2005
1.77
57.12
9.42
6.79
8.35
2.61
6.37
47.84
1.95
4.04
0.00
1.22
0.69
18.51
3.07
14.60
2.83
2.48
1.84
11.71
22.26
1.54
5.65
18.38
0.52
17.11
112.88
14.63
6.27
17.72
8.62
167.29
34.06
5.57
3.26
0.20
10.38
280.08
282.06
460.31
27.31
6.26
96.73
413.26
362.85
1 ,928.87
2010
1.79
63.86
10.36
7.62
7.68
2.66
7.08
52.07
2.06
4.53
0.01
1.17
0.69
19.07
3.34
14.95
2.75
2.42
1.88
13.26
23.23
1.60
6.27
19.11
0.60
16.83
114.72
16.03
6.46
19.48
9.68
186.59
37.30
6.02
3.20
0.21
11.31
310.23
317.48
499.99
31.96
6.29
101.99
414.72
396.38
2,079.05
2015
1.81
68.74
11.28
8.42
7.07
2.72
7.95
57.02
2.13
5.05
0.01
1.13
0.69
19.19
3.59
15.31
2.75
2.36
1.92
14.62
23.91
1.64
6.81
20.83
0.70
16.61
110.54
17.27
6.63
21.03
10.71
204.43
40.14
6.36
3.13
0.22
12.16
337.76
350.14
532.14
33.73
6.20
108.86
414.64
420.76
2,204.23
2020
1.82
74.72
12.30
9.29
6.50
2.77
8.82
61.96
2.21
5.62
0.01
1.09
0.69
19.32
3.86
15.67
2.75
2.30
1.97
16.13
24.62
1.68
7.39
22.56
0.82
16.38
108.64
18.60
6.80
22.71
11.85
224.41
43.24
6.75
3.05
0.23
13.08
368.87
386.56
566.63
35.66
6.12
115.80
417.14
447.52
2,344.30
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-7: Methane Emissions from Rice Cultivation
MtCO2eq
Country
Albania
Algeria
Argentina
Australia
Azerbaijan
Bangladesh
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Chile
China
Colombia
Croatia
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Finland
France
Greece
Hungary
India
Indonesia
Iran
Iraq
Ireland
Italy
Japan
Kazakhstan
Kyrgyzstan
Laos
Luxembourg
Macedonia
Mexico
Myanmar
Nepal
Nigeria
North Korea
Pakistan
Peru
Philippines
Portugal
Romania
Russian Federation
Senegal
South Africa
South Korea
Spain
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United States
Uruguay
Uzbekistan
Venezuela
1990
0.00
0.00
0.32
0.49
0.00
16.11
0.00
0.09
5.03
0.09
3.08
0.13
237.30
3.53
0.00
2.47
0.00
2.21
3.99
0.00
0.10
0.07
0.05
85.66
41.25
2.23
0.47
0.00
1.54
7.08
1.22
0.01
3.34
0.00
0.01
0.35
27.89
5.94
15.33
3.02
4.57
1.06
12.60
0.26
0.17
2.41
0.11
0.01
8.61
0.23
0.08
42.79
0.27
0.08
0.49
0.41
7.12
1.45
0.26
0.47
1995
0.00
0.00
0.79
0.65
0.01
15.36
0.00
0.11
6.03
0.01
3.16
0.13
220.23
3.05
0.00
3.00
0.00
3.24
5.38
0.00
0.13
0.11
0.02
85.89
47.90
2.40
1.03
0.00
1.71
7.20
1.44
0.04
2.82
0.00
0.00
0.26
35.34
6.43
22.80
2.70
4.67
1.16
14.27
0.16
0.03
1.44
0.10
0.01
7.30
0.14
0.11
44.32
0.29
0.06
0.70
0.17
7.62
2.72
0.29
0.73
2000
0.00
0.00
0.80
0.74
0.01
16.52
0.00
0.13
5.06
0.03
3.32
0.11
215.95
3.30
0.00
2.27
0.00
3.12
6.04
0.00
0.10
0.08
0.01
89.50
48.25
2.58
0.76
0.00
1.57
6.02
1.24
0.05
3.47
0.00
0.00
0.33
35.15
6.91
26.16
2.49
5.00
1.71
15.33
0.18
0.01
1.45
0.14
0.01
7.21
0.29
0.13
45.30
0.35
0.15
0.91
0.11
7.49
3.44
0.11
0.62
2005
0.00
0.00
0.84
0.74
0.01
18.27
0.00
0.14
5.38
0.04
3.74
0.11
223.92
3.57
0.00
2.62
0.00
3.36
6.67
0.00
0.10
0.08
0.02
96.54
51.39
2.65
0.87
0.00
1.57
6.20
1.22
0.06
3.89
0.00
0.00
0.35
37.48
7.39
29.69
2.55
5.65
1.85
16.76
0.18
0.01
1.41
0.16
0.01
7.42
0.29
0.14
45.72
0.38
0.16
1.07
0.00
7.64
3.57
0.12
0.68
2010
0.00
0.00
0.89
0.74
0.01
20.01
0.00
0.16
5.68
0.04
4.19
0.12
231.13
3.83
0.00
3.03
0.00
3.58
7.36
0.00
0.10
0.08
0.02
103.31
54.37
2.71
0.99
0.00
1.57
6.39
1.20
0.06
4.34
0.00
0.00
0.37
39.47
7.87
33.27
2.60
6.37
1.98
18.15
0.19
0.01
1.37
0.18
0.01
7.56
0.29
0.15
46.16
0.40
0.17
1.28
0.00
6.83
3.69
0.13
0.73
2015
0.00
0.00
0.93
0.74
0.01
21.72
0.00
0.17
5.95
0.04
4.65
0.13
237.47
4.08
0.00
3.47
0.00
3.80
8.02
0.00
0.10
0.08
0.02
109.69
57.12
2.77
1.12
0.00
1.57
6.58
1.21
0.06
4.79
0.00
0.00
0.40
41.23
8.08
36.87
2.65
7.17
2.11
19.50
0.19
0.01
1.33
0.20
0.01
7.65
0.29
0.16
46.62
0.42
0.18
1.53
0.00
6.89
3.79
0.14
0.79
2020
0.00
0.00
0.97
0.74
0.02
23.37
0.00
0.18
6.18
0.04
5.10
0.13
242.07
4.33
0.00
3.95
0.00
4.01
8.63
0.00
0.10
0.08
0.02
115.49
59.54
2.84
1.24
0.00
1.57
6.76
1.22
0.07
5.24
0.00
0.00
0.41
42.79
8.29
40.39
2.70
7.97
2.24
20.79
0.19
0.01
1.29
0.22
0.01
7.70
0.29
0.17
47.12
0.44
0.20
1.81
0.00
6.86
3.90
0.15
0.84
-------
Appendix B-7: Methane Emissions from Rice Cultivation
MtCO2eq
Country
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
29.18
7.28
2.34
0.00
8.53
29.69
275.92
16.99
2.69
0.01
4.48
17.46
253.94
601.19
1995
32.75
11.73
2.44
0.00
8.25
43.72
261 .66
20.67
3.43
0.00
3.55
18.06
269.74
620.84
2000
37.06
13.82
2.61
0.00
8.03
49.36
262.28
21.22
3.34
0.00
3.26
16.89
277.20
633.55
2005
39.64
15.88
2.79
0.00
8.86
56.11
273.75
22.64
3.51
0.00
3.12
17.27
295.48
671 .89
2010
42.27
18.19
2.95
0.00
9.67
63.32
284.53
23.99
3.70
0.00
3.09
16.67
312.95
708.25
2015
44.93
20.76
3.10
0.00
10.40
70.86
294.49
25.26
3.89
0.00
3.11
16.94
329.19
743.74
2020
47.47
23.58
3.23
0.00
11.13
78.59
302.58
26.42
4.08
0.00
3.10
17.12
344.22
776.12
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-8: Methane Emissions from Manure Management
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
1990
0.07
0.17
2.16
0.06
1.54
1.02
0.63
1.53
1.22
2.57
0.38
7.10
1.50
0.38
3.13
0.21
15.70
0.63
0.23
1.02
0.10
0.74
0.19
0.49
0.37
1.07
0.21
13.79
0.28
27.10
0.50
0.84
0.02
18.83
1.08
0.39
0.14
1.26
0.18
4.03
1.07
0.02
1.72
0.01
0.36
0.30
0.28
0.00
0.49
0.02
0.07
0.94
0.31
0.18
0.91
0.65
2.97
0.57
1.20
0.16
1995
0.12
0.17
2.36
0.04
1.72
0.99
0.59
1.52
0.94
2.75
0.42
7.87
0.72
0.47
3.36
0.26
18.89
0.73
0.16
0.76
0.10
0.86
0.22
0.61
0.19
1.04
0.23
13.66
0.21
23.76
0.48
0.50
0.02
20.13
1.25
0.44
0.08
1.36
0.21
3.88
0.99
0.03
1.04
0.01
0.25
0.37
0.11
0.00
0.33
0.02
0.05
1.17
0.21
0.20
1.11
0.71
3.04
0.58
1.33
0.09
2000
0.31
0.20
2.05
0.05
1.98
0.90
0.60
1.50
0.79
2.67
0.47
7.98
0.57
0.49
3.32
0.30
19.76
0.73
0.16
0.69
0.09
0.94
0.25
0.68
0.06
1.19
0.22
13.30
0.21
23.27
0.49
0.50
0.02
21.52
1.01
0.60
0.09
1.43
0.22
3.86
0.93
0.03
0.54
0.02
0.27
0.31
0.08
0.00
0.20
0.02
0.05
1.29
0.13
0.22
1.31
0.76
2.67
0.55
1.59
0.09
2005
0.49
0.22
2.21
0.05
1.95
0.89
0.59
1.66
0.78
2.66
0.50
8.67
0.74
0.65
3.80
0.33
21.91
0.78
0.18
0.70
0.10
0.89
0.27
0.71
0.09
1.33
0.20
13.25
0.21
19.63
0.49
0.73
0.02
23.20
1.13
0.69
0.10
1.25
0.23
3.96
0.96
0.03
0.55
0.02
0.28
0.34
0.07
0.00
0.20
0.02
0.05
1.39
0.12
0.24
1.43
0.80
2.54
0.62
1.75
0.10
2010
0.67
0.25
2.39
0.05
2.00
0.86
0.59
1.83
0.77
2.64
0.55
9.45
0.77
0.81
4.10
0.36
24.35
0.83
0.20
0.72
0.11
0.82
0.30
0.75
0.10
1.49
0.20
13.21
0.21
16.54
0.49
0.76
0.02
25.01
1.28
0.82
0.10
1.12
0.24
4.06
0.99
0.03
0.56
0.02
0.29
0.38
0.08
0.00
0.20
0.02
0.05
1.49
0.12
0.25
1.56
0.85
2.41
0.61
1.93
0.11
2015
0.76
0.29
2.52
0.05
2.00
0.84
0.58
1.98
0.76
2.63
0.58
10.08
0.75
1.09
4.59
0.39
26.24
0.87
0.20
0.73
0.13
0.77
0.32
0.78
0.11
1.62
0.20
13.25
0.20
16.59
0.49
0.77
0.02
26.22
1.37
0.87
0.11
1.00
0.25
4.16
1.01
0.03
0.57
0.02
0.29
0.41
0.08
0.00
0.20
0.02
0.05
1.59
0.12
0.27
1.69
0.89
2.29
0.65
2.09
0.12
2020
0.84
0.36
2.65
0.05
2.02
0.82
0.58
2.16
0.76
2.62
0.62
10.76
0.77
1.37
5.07
0.42
28.32
0.92
0.20
0.74
0.14
0.71
0.34
0.81
0.11
1.78
0.20
13.29
0.20
16.65
0.49
0.78
0.02
27.48
1.47
0.92
0.11
0.89
0.25
4.26
1.04
0.03
0.58
0.02
0.30
0.45
0.09
0.00
0.20
0.02
0.05
1.69
0.12
0.29
1.82
0.94
2.17
0.68
2.27
0.12
-------
Appendix B-8: Methane Emissions from Manure Management
MtCO2eq
Country
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.30
3.70
0.23
1.38
1.16
1.56
3.90
10.50
0.18
0.12
0.05
0.37
0.27
1.75
0.22
6.22
0.36
0.45
0.17
2.74
8.41
0.43
0.15
4.63
0.01
2.92
31.19
0.29
0.80
0.53
2.21
5.74
1.08
0.21
0.70
0.13
2.35
10.79
18.93
13.74
1.15
1.07
21.10
122.29
33.44
222.52
1995
0.31
4.11
0.24
1.41
1.03
1.45
2.37
7.98
0.20
0.15
0.03
0.28
0.21
1.64
0.30
7.07
0.42
0.43
0.14
2.90
8.28
0.34
0.16
3.46
0.02
2.88
36.07
0.31
0.87
0.63
2.85
6.14
1.12
0.22
0.66
0.15
2.72
11.33
22.87
15.32
1.22
0.99
16.07
121.27
36.20
225.26
2000
0.32
4.85
0.27
1.51
0.76
1.43
1.94
5.12
0.24
0.17
0.03
0.20
0.19
1.69
0.31
8.44
0.40
0.40
0.12
2.74
7.59
0.26
0.19
2.20
0.03
2.76
38.08
0.30
0.82
0.71
3.47
6.87
1.17
0.26
0.60
0.16
2.27
12.66
24.35
15.53
1.48
1.11
11.11
121.32
37.81
225.38
2005
0.32
5.40
0.29
1.73
0.74
1.45
2.09
5.82
0.25
0.19
0.03
0.28
0.19
1.74
0.34
9.00
0.38
0.40
0.12
3.09
7.88
0.27
0.21
2.50
0.03
2.55
39.18
0.33
0.84
0.78
3.92
7.64
1.27
0.28
0.60
0.16
2.47
13.89
27.16
16.83
1.64
1.32
12.13
120.31
41.29
234.57
2010
0.32
6.03
0.32
1.99
0.72
1.48
2.29
6.01
0.27
0.21
0.04
0.31
0.19
1.80
0.37
9.42
0.37
0.39
0.12
3.49
8.18
0.28
0.23
2.62
0.04
2.47
40.07
0.36
0.87
0.85
4.42
8.51
1.37
0.29
0.60
0.18
2.69
15.27
30.33
18.27
1.82
1.53
12.47
119.12
45.14
243.95
2015
0.32
6.51
0.35
2.21
0.70
1.51
2.49
6.53
0.28
0.23
0.04
0.31
0.19
1.81
0.40
9.97
0.37
0.39
0.13
3.85
8.39
0.28
0.25
2.86
0.04
2.53
42.32
0.39
0.89
0.92
4.86
9.33
1.46
0.31
0.60
0.18
2.88
16.54
32.98
19.47
1.92
1.61
13.27
122.83
48.04
256.65
2020
0.32
7.12
0.39
2.46
0.68
1.54
2.70
7.05
0.29
0.26
0.04
0.31
0.19
1.82
0.43
10.52
0.37
0.38
0.13
4.26
8.61
0.29
0.27
3.11
0.05
2.55
43.83
0.41
0.91
0.99
5.33
10.26
1.57
0.34
0.60
0.19
3.08
17.96
35.88
20.76
2.02
1.69
14.07
125.84
51.25
269.47
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-9: Methane Emissions from Other Agricultural Sources
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.02
0.27
2.47
0.02
9.59
0.08
0.05
0.12
0.12
0.17
6.40
54.34
0.14
1.57
4.37
1.70
1.97
4.16
0.07
0.11
18.82
0.12
2.50
0.01
3.35
0.07
1.34
0.04
-0.14
0.45
0.20
0.00
1.27
12.70
0.63
0.03
0.11
1.13
0.15
0.01
0.44
0.00
0.04
1.44
0.03
0.03
0.00
0.12
3.11
0.06
0.59
4.22
0.28
0.08
0.05
3.85
1995
0.02
0.22
1.81
0.01
9.52
0.03
0.03
0.01
0.10
0.12
6.20
48.44
0.12
1.71
32.13
1.53
0.40
3.57
0.05
0.09
18.90
0.03
2.29
0.01
3.70
0.06
0.40
0.03
-0.51
0.24
0.16
0.00
0.98
12.24
0.66
0.01
0.11
0.22
0.16
0.01
0.21
0.00
0.02
1.53
0.01
0.03
0.02
2.84
0.06
0.59
4.14
0.28
0.02
0.05
3.95
2000
0.03
0.02
8.28
0.01
19.19
0.05
0.04
1.09
0.10
0.12
16.45
98.40
0.15
1.87
4.61
0.70
1.71
6.50
0.05
0.10
38.68
0.03
0.37
0.00
0.01
5.30
0.01
0.28
0.04
-0.45
0.07
0.17
0.00
4.38
21.48
0.41
0.00
0.01
0.10
0.30
0.22
0.00
0.60
0.00
0.04
4.55
0.01
0.00
0.03
0.01
0.03
9.69
0.07
0.00
0.24
10.76
0.08
0.02
0.04
5.57
2005
0.03
0.02
8.28
0.01
19.19
0.05
0.04
1.09
0.10
0.12
16.45
98.40
0.15
1.87
4.61
0.70
1.71
6.50
0.05
0.10
38.68
0.03
0.37
0.00
0.01
5.30
0.01
0.28
0.04
-0.45
0.07
0.17
0.00
4.38
21.48
0.41
0.00
0.01
0.10
0.30
0.22
0.00
0.60
0.00
0.04
4.55
0.01
0.00
0.03
0.01
0.03
9.69
0.07
0.00
0.24
10.76
0.08
0.02
0.04
5.57
2010
0.03
0.02
8.28
0.01
19.19
0.05
0.04
1.09
0.10
0.12
16.45
98.40
0.15
1.87
4.61
0.70
1.71
6.50
0.05
0.10
38.68
0.03
0.37
0.00
0.01
5.30
0.01
0.28
0.04
-0.45
0.07
0.17
0.00
4.38
21.48
0.41
0.00
0.01
0.10
0.30
0.22
0.00
0.60
0.00
0.04
4.55
0.01
0.00
0.03
0.01
0.03
9.69
0.07
0.00
0.24
10.76
0.08
0.02
0.04
5.57
2015
0.03
0.02
8.28
0.01
19.19
0.05
0.04
1.09
0.10
0.12
16.45
98.40
0.15
1.87
4.61
0.70
1.71
6.50
0.05
0.10
38.68
0.03
0.37
0.00
0.01
5.30
0.01
0.28
0.04
-0.45
0.07
0.17
0.00
4.38
21.48
0.41
0.00
0.01
0.10
0.30
0.22
0.00
0.60
0.00
0.04
4.55
0.01
0.00
0.03
0.01
0.03
9.69
0.07
0.00
0.24
10.76
0.08
0.02
0.04
5.57
2020
0.03
0.02
8.28
0.01
19.19
0.05
0.04
1.09
0.10
0.12
16.45
98.40
0.15
1.87
4.61
0.70
1.71
6.50
0.05
0.10
38.68
0.03
0.37
0.00
0.01
5.30
0.01
0.28
0.04
-0.45
0.07
0.17
0.00
4.38
21.48
0.41
0.00
0.01
0.10
0.30
0.22
0.00
0.60
0.00
0.04
4.55
0.01
0.00
0.03
0.01
0.03
9.69
0.07
0.00
0.24
10.76
0.08
0.02
0.04
5.57
-------
Appendix B-9: Methane Emissions from Other Agricultural Sources
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.02
0.34
2.80
3.38
0.45
0.75
0.26
6.78
0.17
1.30
0.00
0.06
0.02
2.87
0.41
1.59
0.08
0.03
0.02
2.80
1.37
0.04
1.72
0.64
0.00
0.32
0.69
0.07
0.17
5.03
1.82
70.83
7.78
0.14
0.16
0.16
7.73
103.01
7.39
90.36
1.07
0.36
8.41
23.81
33.24
267.64
1995
0.00
0.28
2.50
3.08
0.42
0.88
0.30
2.42
0.19
1.29
0.00
0.05
0.01
2.58
0.47
0.81
0.02
0.01
0.02
2.18
1.45
0.04
1.73
0.52
0.00
0.08
0.66
0.09
0.14
4.58
1.79
70.02
7.55
0.20
0.15
0.02
8.30
102.39
6.03
81.39
1.18
0.24
3.61
47.63
31.97
274.43
2000
0.08
0.01
0.04
2.14
0.61
0.44
0.07
0.31
12.76
0.19
0.94
0.01
0.05
0.01
3.56
0.39
0.25
0.02
0.01
0.02
5.38
1.50
0.05
1.98
0.58
0.00
0.10
0.79
0.15
0.15
8.88
1.89
130.34
13.22
0.15
0.20
0.02
5.58
186.39
10.35
164.77
0.85
0.31
14.45
28.57
49.79
455.48
2005
0.08
0.01
0.04
2.14
0.61
0.44
0.07
0.31
12.76
0.19
0.94
0.01
0.05
0.01
3.56
0.39
0.25
0.02
0.01
0.02
5.38
1.50
0.05
1.98
0.58
0.00
0.10
0.82
0.15
0.15
8.88
1.89
130.34
13.22
0.15
0.20
0.02
5.58
186.39
10.35
164.77
0.85
0.31
14.45
28.60
49.79
455.51
2010
0.08
0.01
0.04
2.14
0.61
0.44
0.07
0.31
12.76
0.19
0.94
0.01
0.05
0.01
3.56
0.39
0.25
0.02
0.01
0.02
5.38
1.50
0.05
1.98
0.58
0.00
0.10
0.87
0.15
0.15
8.88
1.89
130.34
13.22
0.15
0.20
0.02
5.58
186.39
10.35
164.77
0.85
0.31
14.45
28.65
49.79
455.56
2015
0.08
0.01
0.04
2.14
0.61
0.44
0.07
0.31
12.76
0.19
0.94
0.01
0.05
0.01
3.56
0.39
0.25
0.02
0.01
0.02
5.38
1.50
0.05
1.98
0.58
0.00
0.10
0.92
0.15
0.15
8.88
1.89
130.34
13.22
0.15
0.20
0.02
5.58
186.39
10.35
164.77
0.85
0.31
14.45
28.70
49.79
455.61
2020
0.08
0.01
0.04
2.14
0.61
0.44
0.07
0.31
12.76
0.19
0.94
0.01
0.05
0.01
3.56
0.39
0.25
0.02
0.01
0.02
5.38
1.50
0.05
1.98
0.58
0.00
0.10
0.97
0.15
0.15
8.88
1.89
130.34
13.22
0.15
0.20
0.02
5.58
186.39
10.35
164.77
0.85
0.31
14.45
28.75
49.79
455.66
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-10: Methane Emissions from Landfilling of Solid Waste
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.26
3.69
5.51
0.50
7.47
4.14
1.35
0.92
2.35
2.63
0.38
12.98
12.20
0.11
18.53
1.43
40.38
6.55
0.79
1.96
4.96
1.33
0.84
4.07
1.42
0.50
3.68
11.21
1.07
31.48
2.65
3.63
0.11
10.69
7.80
5.67
2.78
1.23
6.56
10.35
4.04
0.52
2.29
0.34
1.64
0.24
0.42
0.02
3.40
0.00
0.92
26.04
0.73
0.00
0.07
2.60
0.13
12.04
2.18
3.86
1995
0.29
4.11
5.89
0.39
8.31
3.67
1.41
1.19
1.94
2.45
0.42
14.54
8.39
0.12
20.36
1.55
42.63
7.21
0.86
1.99
5.89
1.29
0.93
4.49
0.93
0.59
3.62
13.80
1.05
25.26
3.33
3.54
0.19
12.22
8.44
6.24
3.24
1.46
7.77
10.86
4.24
0.68
3.35
0.27
0.95
0.27
0.64
0.02
2.24
0.00
0.94
28.51
0.48
0.00
0.07
3.01
0.19
10.54
1.75
4.47
2000
0.32
4.46
6.28
0.41
7.97
3.06
1.47
1.32
2.72
1.67
0.47
15.56
4.23
0.14
22.86
1.66
44.58
7.88
1.08
1.60
6.44
1.19
1.01
4.94
0.98
0.68
3.01
11.72
1.03
14.37
3.42
3.82
0.22
13.95
9.05
6.64
3.73
1.39
8.78
11.36
3.93
0.81
3.17
0.36
0.78
0.30
0.83
0.02
1.28
0.05
0.97
30.95
0.47
0.00
0.09
3.50
0.25
8.14
1.40
5.15
2005
0.56
4.85
6.66
0.42
8.69
3.01
1.54
1.58
2.92
1.27
0.52
16.56
4.44
0.16
25.29
1.76
46.01
8.53
1.20
1.54
7.44
1.00
1.09
5.46
0.88
0.77
2.91
8.49
0.98
9.12
2.82
3.82
0.22
15.93
9.64
7.07
4.26
1.41
9.71
7.84
3.49
0.92
3.11
0.43
0.84
0.34
0.61
0.02
1.28
0.05
0.99
33.28
0.47
0.10
4.06
0.31
6.09
1.49
5.84
2010
0.80
5.24
7.02
0.47
9.42
2.54
1.62
1.74
3.12
0.87
0.56
17.47
6.08
0.18
27.72
1.86
47.50
9.16
1.29
1.49
8.58
0.96
1.16
6.02
0.77
0.86
2.73
5.27
0.95
6.28
1.79
3.82
0.22
17.05
10.20
7.55
4.86
1.50
10.55
3.87
3.06
1.02
3.07
0.49
0.89
0.38
0.58
0.03
1.28
0.05
1.01
35.45
0.47
0.11
4.28
0.39
4.04
1.57
6.55
2015
1.10
5.62
7.36
0.46
10.64
2.22
1.71
1.88
3.31
0.60
0.61
18.29
7.42
0.20
30.66
1.96
48.80
9.77
1.20
0.99
9.84
0.87
1.24
6.56
0.66
0.97
2.36
4.49
0.92
5.35
1.83
3.82
0.22
18.10
10.72
8.14
5.49
1.59
11.29
1.91
2.72
1.12
3.11
0.54
0.94
0.41
0.56
0.03
1.28
0.05
1.03
37.42
0.46
0.11
4.47
0.50
2.72
1.66
7.25
2020
1.41
5.97
7.68
0.46
11.87
2.03
1.78
2.03
3.50
0.41
0.66
19.00
8.67
0.22
33.61
2.06
49.75
10.34
1.08
0.70
11.20
0.78
1.30
7.06
0.47
1.08
2.00
3.71
0.90
4.41
2.68
3.82
0.22
19.06
11.17
8.67
6.10
1.69
11.90
0.94
2.38
1.21
3.12
0.59
0.99
0.45
0.69
0.03
1.28
0.05
1.04
39.16
0.46
0.12
4.63
0.64
1.41
1.75
7.95
-------
Appendix B-10: Methane Emissions from Landfilling of Solid Waste
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States1
United States2
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
1.18
2.46
1.57
1.84
3.80
16.11
3.89
3.33
37.80
12.55
1.61
0.42
1.06
0.51
14.05
23.47
3.46
2.55
0.71
0.14
0.39
8.16
0.19
0.05
14.23
0.33
23.76
172.23
172.23
0.60
2.92
4.70
1.17
40.65
11.03
5.53
10.24
0.42
34.66
73.43
43.14
71.89
34.28
12.22
65.21
374.78
86.44
761 .40
1995
1.26
2.39
1.93
2.01
4.25
15.94
4.84
3.27
37.80
14.38
1.82
0.48
1.07
0.53
15.16
12.40
5.14
2.40
0.53
0.13
0.41
8.93
0.22
0.06
14.48
0.40
19.70
162.40
162.40
0.62
3.05
5.28
1.39
45.70
12.85
6.63
9.89
0.45
43.94
82.30
45.75
79.83
39.62
11.99
65.26
356.49
88.48
769.71
2000
1.31
2.24
2.22
2.19
4.71
17.00
4.79
3.22
35.13
16.79
2.05
0.56
1.01
0.58
16.29
10.24
6.82
2.04
0.41
0.13
0.43
9.67
0.24
0.07
12.09
0.45
11.60
130.68
130.68
0.64
3.34
5.85
1.56
51.84
13.79
7.68
10.29
0.47
39.95
91.93
47.99
86.30
45.23
12.66
60.99
299.03
86.18
730.32
2005
1.35
2.25
2.65
2.36
5.15
17.00
3.05
3.35
34.15
19.43
2.31
0.61
1.02
0.58
16.78
10.68
6.90
2.04
0.36
0.13
0.46
10.38
0.26
0.08
13.39
0.50
8.41
130.58
156.60
0.67
3.60
6.42
1.80
57.86
14.72
8.83
10.43
0.49
44.21
101.39
49.76
92.59
51.15
13.17
61.82
282.21
95.28
747.38
2010
1.37
2.27
2.99
2.53
5.58
17.00
1.32
3.47
33.18
22.12
2.59
0.64
1.02
0.58
16.64
10.88
6.98
2.04
0.24
0.14
0.48
11.04
0.28
0.10
14.75
0.54
6.09
125.43
157.30
0.69
3.87
6.98
1.92
64.13
15.62
10.13
10.46
0.50
48.18
110.72
51.46
98.53
57.27
13.57
62.79
263.91
102.38
760.63
2015
1.40
2.27
3.36
2.70
5.99
17.00
1.32
3.61
32.19
24.81
2.88
0.65
1.03
0.58
16.39
11.01
7.06
1.34
0.24
0.15
0.49
11.64
0.30
0.12
16.36
0.58
4.93
124.15
160.20
0.71
4.12
7.52
2.04
70.69
16.46
11.55
10.43
0.52
51.89
120.32
52.97
104.05
63.52
13.76
64.05
260.33
109.06
788.07
2020
1.43
2.27
3.73
2.86
6.39
17.00
1.32
3.74
31.13
27.48
3.15
0.67
1.07
0.58
16.18
11.09
7.15
0.64
0.24
0.16
0.51
12.14
0.32
0.14
17.98
0.61
3.48
123.51
164.30
0.73
4.33
8.03
2.16
77.50
17.26
13.09
10.35
0.53
55.56
130.22
54.13
109.09
69.66
13.87
65.14
259.26
115.48
816.86
1 US emissions INCLUDING reductions from voluntary programs; included in OECD90 & EU and World totals
2 US emissions NOT INCLUDING the effect of voluntary programs; not included in OECD90 & EU and World totals
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix B-11: Methane Emissions from Wastewater
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.23
2.03
3.95
0.25
2.27
0.29
0.73
10.44
0.72
0.08
0.80
17.95
1.40
0.98
0.36
1.59
94.40
4.24
0.31
0.83
3.02
0.20
1.25
4.18
0.19
3.88
0.15
0.71
0.56
2.23
2.36
1.25
0.02
81.77
18.01
5.96
1.76
0.25
0.46
1.34
1.10
0.33
1.71
0.22
0.45
0.42
0.35
0.00
0.08
0.03
0.13
10.02
0.30
0.00
0.23
4.13
1.85
0.32
0.16
6.80
1995
0.22
2.26
4.22
0.26
2.40
0.30
0.78
11.73
0.72
0.08
0.90
19.35
1.04
1.16
0.38
1.72
99.65
4.68
0.32
0.65
3.66
0.22
1.39
4.61
0.13
4.52
0.15
0.95
0.55
0.89
2.09
1.15
0.02
89.73
19.51
6.59
2.05
0.25
0.55
1.39
1.03
0.43
1.70
0.17
0.47
0.48
0.20
0.00
0.12
0.03
0.14
10.98
0.30
0.00
0.25
4.53
2.09
0.28
0.16
7.85
2000
0.22
2.47
4.49
0.26
2.55
0.30
0.82
13.04
0.71
0.08
1.01
20.67
0.59
1.34
0.40
1.85
104.25
5.11
0.32
0.58
4.16
0.22
1.53
5.05
0.22
5.13
0.13
1.15
0.54
0.17
1.45
1.11
0.02
97.65
20.94
7.18
2.34
0.27
0.62
1.43
1.03
0.50
1.65
0.20
0.50
0.54
0.20
0.00
0.33
0.03
0.14
11.91
0.30
0.00
0.26
4.87
2.35
0.26
0.16
9.01
2005
0.23
2.70
4.77
0.26
2.68
0.29
0.85
14.48
0.70
0.06
1.13
21.97
0.62
1.51
0.41
1.96
108.04
5.53
0.33
0.57
4.91
0.22
1.67
5.49
0.21
5.79
0.13
1.17
0.52
0.17
1.45
1.08
0.02
105.36
22.25
7.69
2.69
0.28
0.68
1.38
1.04
0.58
1.62
0.22
0.53
0.60
0.19
0.00
0.33
0.03
0.14
12.78
0.30
0.00
0.27
5.16
2.64
0.27
0.17
10.26
2010
0.23
2.91
5.03
0.27
2.80
0.25
0.87
15.94
0.68
0.04
1.24
23.23
0.85
1.70
0.43
2.06
111.73
5.96
0.32
0.57
5.82
0.22
1.81
5.89
0.20
6.52
0.13
1.19
0.51
0.17
1.44
1.06
0.02
112.66
23.47
8.25
3.05
0.29
0.74
1.38
1.05
0.66
1.61
0.25
0.56
0.67
0.19
0.00
0.33
0.03
0.14
13.59
0.29
0.00
0.29
5.41
2.95
0.27
0.17
11.63
2015
0.24
3.10
5.28
0.27
2.92
0.22
0.89
17.38
0.67
0.03
1.36
24.43
1.04
1.90
0.44
2.17
115.34
6.39
0.32
0.56
6.86
0.22
1.93
6.28
0.19
7.32
0.13
1.20
0.49
0.17
1.43
1.03
0.02
119.09
24.69
8.89
3.42
0.31
0.79
1.35
1.05
0.73
1.63
0.28
0.60
0.75
0.18
0.00
0.33
0.04
0.14
14.35
0.29
0.00
0.31
5.64
3.28
0.28
0.18
13.08
2020
0.25
3.30
5.50
0.26
3.03
0.20
0.91
18.76
0.66
0.02
1.48
25.55
1.22
2.09
0.46
2.28
118.29
6.79
0.32
0.56
8.05
0.22
2.05
6.67
0.18
8.24
0.13
1.21
0.47
0.17
1.41
1.01
0.02
124.98
25.85
9.54
3.78
0.32
0.83
1.33
1.04
0.81
1.64
0.31
0.63
0.82
0.18
0.00
0.33
0.04
0.14
15.05
0.29
0.00
0.34
5.89
3.62
0.28
0.18
14.58
-------
Appendix B-11: Methane Emissions from Wastewater
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
2.04
0.02
10.88
2.62
6.23
2.93
0.87
1.60
9.44
1.57
0.60
0.31
1.01
0.19
3.36
4.37
1.25
IE
0.03
0.54
5.59
5.72
0.37
1.41
0.63
0.21
0.70
24.85
0.38
2.09
2.37
6.74
24.88
7.63
3.22
1.01
0.08
6.13
50.15
104.81
52.78
13.74
1.69
17.80
55.20
149.72
445.87
1995
2.18
0.02
12.25
2.86
6.97
1.86
0.90
1.81
9.43
1.74
0.68
0.35
0.85
0.14
3.69
4.59
1.48
IE
0.03
0.59
5.99
6.27
0.43
1.64
0.63
0.24
0.72
29.89
0.39
2.33
2.65
7.43
27.92
8.38
3.89
0.97
0.08
7.12
56.83
111.15
57.51
15.67
1.66
18.18
57.97
164.86
483.82
2000
2.27
0.02
13.99
3.11
7.72
1.60
0.82
1.68
9.26
2.08
0.77
0.41
0.74
0.18
4.00
4.77
1.80
IE
0.03
0.62
6.41
6.80
0.48
1.90
0.39
0.27
0.77
34.34
0.40
2.54
2.93
7.97
31.81
9.15
4.59
1.01
0.09
8.19
64.29
116.63
62.17
17.76
1.70
18.08
61.56
180.35
522.54
2005
2.35
0.02
15.89
3.37
8.47
1.59
0.52
1.66
8.97
2.43
0.87
0.45
0.75
0.17
4.15
4.93
1.80
IE
0.03
0.64
6.79
7.27
0.53
2.23
0.37
0.29
0.78
35.21
0.42
2.72
3.21
8.51
35.78
9.95
5.38
1.03
0.09
9.07
72.19
121.29
66.76
19.96
1.72
18.02
62.71
195.48
558.11
2010
2.42
0.02
17.97
3.63
9.17
1.58
0.23
1.64
8.72
2.82
0.98
0.47
0.65
0.17
4.17
5.06
1.79
IE
0.03
0.68
7.11
7.67
0.58
2.66
0.36
0.31
0.79
36.13
0.43
2.91
3.48
9.05
40.10
10.76
6.28
1.03
0.10
10.07
80.66
125.86
71.23
22.36
1.73
18.03
63.89
210.27
594.04
2015
2.49
0.02
20.24
3.87
9.78
1.57
0.23
1.61
8.49
3.24
1.10
0.49
0.60
0.17
4.12
5.17
1.76
IE
0.03
0.72
7.40
8.06
0.62
3.16
0.34
0.33
0.79
36.99
0.45
3.12
3.75
9.63
44.77
11.56
7.29
1.02
0.10
10.95
89.79
130.42
75.54
24.97
1.73
18.12
65.27
224.10
629.93
2020
2.57
0.02
22.57
4.10
10.35
1.56
0.23
1.58
8.26
3.68
1.23
0.50
0.58
0.17
4.06
5.25
1.73
IE
0.03
0.78
7.66
8.46
0.66
3.74
0.33
0.34
0.79
37.84
0.46
3.32
3.99
10.23
49.71
12.33
8.40
1.02
0.10
11.85
99.56
134.33
79.58
27.69
1.73
18.20
66.62
237.27
664.97
Regional country groupings are defined in Table 1-4 and Appendix H.
Codes:
IE - Estimated, but included elsewhere.
-------
Appendix B-12: Methane Emissions from Other Non-Agricultural Sources (Waste and Other)
MtCO2eq
Country
Albania
Algeria
Argentina
Austria
Belgium
Bolivia
Canada
Denmark
Finland
France
Greece
Ireland
Italy
Japan
Luxembourg
Moldova
Monaco
Netherlands
Nigeria
Norway
Portugal
Saudi Arabia
Slovenia
Spain
Switzerland
Ukraine
United Kingdom
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.07
0.00
0.19
0.01
0.06
0.00
0.01
0.02
0.00
0.18
0.00
0.00
0.16
0.01
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.37
0.01
0.00
0.00
0.00
0.00
0.19
0.00
0.07
0.02
0.83
0.00
1.12
1995
0.06
0.01
0.10
0.02
0.11
0.00
0.01
0.02
0.00
0.17
0.00
0.00
0.27
0.01
0.00
0.02
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.52
0.01
0.00
0.00
0.01
0.00
0.10
0.00
0.06
0.02
1.22
0.00
1.42
2000
0.00
0.01
0.25
0.02
0.35
0.00
0.01
0.02
0.00
0.20
0.00
0.00
0.25
0.01
0.00
0.02
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.62
0.00
0.00
0.00
0.01
0.00
0.25
0.00
0.00
0.02
1.57
0.00
1.86
2005
0.00
0.01
0.23
0.02
0.27
0.00
0.01
0.02
0.00
0.20
0.00
0.00
0.25
0.01
0.00
0.02
0.00
0.07
0.00
0.00
0.00
0.00
0.00
0.62
0.00
0.00
0.00
0.01
0.00
0.23
0.00
0.00
0.02
1.48
0.00
1.75
2010
0.00
0.01
0.21
0.02
0.18
0.00
0.01
0.02
0.00
0.20
0.00
0.00
0.25
0.01
0.00
0.02
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.62
0.00
0.00
0.00
0.01
0.00
0.21
0.00
0.00
0.02
1.39
0.00
1.64
2015
0.00
0.01
0.19
0.02
0.13
0.00
0.01
0.02
0.00
0.20
0.00
0.00
0.25
0.01
0.00
0.02
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.62
0.00
0.00
0.00
0.01
0.00
0.19
0.00
0.00
0.02
1.33
0.00
1.55
2020
0.00
0.01
0.19
0.02
0.09
0.00
0.01
0.02
0.00
0.20
0.00
0.00
0.25
0.01
0.00
0.02
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.62
0.00
0.00
0.00
0.01
0.00
0.19
0.00
0.00
0.02
1.28
0.00
1.51
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-1: Nitrous Oxide Emissions from Stationary and Mobile Combustion
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
1990
0.02
0.09
1.39
0.04
2.35
0.67
0.07
0.01
0.24
2.09
0.01
0.57
3.65
0.00
8.44
0.33
9.32
0.12
0.08
1.42
0.00
0.59
0.11
3.54
0.05
0.07
0.90
4.53
0.09
10.42
3.09
2.89
0.03
2.06
0.22
2.11
0.15
0.95
0.12
8.53
6.22
0.06
0.62
0.03
0.09
0.17
0.00
0.29
0.03
0.00
2.20
0.18
0.00
0.00
0.00
0.00
0.52
0.14
1.13
0.89
1995
0.00
0.09
1.53
0.02
3.79
0.83
0.05
0.01
0.19
2.28
0.02
0.71
3.03
0.00
10.95
0.47
12.39
0.19
0.08
1.33
0.00
0.76
0.14
3.80
0.04
0.10
1.30
5.62
0.01
11.06
3.18
2.74
0.04
2.91
0.29
2.68
0.17
1.13
0.17
8.62
7.87
0.13
0.64
0.09
0.03
0.12
0.00
0.21
0.05
0.04
2.57
0.04
0.00
0.00
0.02
0.01
0.72
0.18
1.29
0.95
2000
0.00
0.10
1.94
0.02
5.19
0.79
0.04
0.01
0.13
2.39
0.04
0.90
2.41
0.00
11.39
0.62
12.47
0.19
0.15
1.48
0.00
0.79
0.15
4.92
0.04
0.13
1.15
6.96
0.04
10.26
3.71
2.62
0.06
3.29
0.62
3.09
0.18
1.50
0.22
9.72
8.97
0.14
0.48
0.13
0.03
0.13
0.00
0.17
0.06
0.04
2.82
0.02
0.00
0.00
0.02
0.01
0.76
0.22
1.42
0.91
2005
0.00
0.12
2.56
0.03
7.05
0.79
0.04
0.02
0.14
1.81
0.05
1.05
2.75
0.00
13.37
0.74
14.77
0.23
0.15
1.32
0.00
0.85
0.15
5.06
0.04
0.15
1.29
4.88
0.04
11.53
3.89
2.62
0.06
4.04
0.73
3.47
0.20
1.63
0.27
11.23
5.23
0.15
0.49
0.14
0.04
0.13
0.00
0.16
0.06
0.04
3.39
0.02
0.00
0.00
0.03
0.01
0.85
0.25
1.64
0.99
2010
0.00
0.15
3.41
0.03
7.63
0.79
0.04
0.02
0.14
2.02
0.06
1.24
3.09
0.01
14.55
0.89
17.60
0.29
0.15
1.35
0.00
0.92
0.16
5.21
0.04
0.17
1.42
10.25
0.05
11.89
4.24
2.62
0.06
4.97
0.97
3.91
0.22
1.76
0.33
12.73
8.80
0.15
0.50
0.16
0.04
0.13
0.00
0.16
0.06
0.05
3.52
0.02
0.00
0.00
0.03
0.02
0.91
0.25
1.90
1.10
2015
0.01
0.17
4.34
0.04
9.49
0.79
0.04
0.03
0.16
2.12
0.08
1.38
3.53
0.01
16.06
1.03
20.32
0.34
0.15
1.26
0.00
1.01
0.16
5.36
0.04
0.20
1.53
6.60
0.05
12.94
4.70
2.62
0.06
5.90
1.38
4.44
0.25
1.98
0.38
15.28
5.13
0.15
0.51
0.17
0.04
0.13
0.00
0.16
0.06
0.05
3.64
0.02
0.00
0.00
0.03
0.02
0.99
0.28
2.18
1.23
2020
0.01
0.21
5.56
0.04
11.35
0.79
0.05
0.04
0.17
2.23
0.09
1.56
3.96
0.01
17.59
1.20
23.55
0.40
0.15
1.23
0.00
1.10
0.17
5.50
0.04
0.22
1.64
12.52
0.05
14.00
5.15
2.62
0.06
7.02
2.01
5.07
0.28
2.19
0.45
17.84
5.08
0.16
0.53
0.19
0.05
0.13
0.00
0.16
0.06
0.06
3.76
0.02
0.00
0.00
0.03
0.02
1.07
0.28
2.51
1.38
-------
Appendix C-1: Nitrous Oxide Emissions from Stationary and Mobile Combustion
MtCO2eq
Country
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.31
0.18
0.05
0.35
1.80
0.51
0.36
5.27
0.40
0.01
0.13
0.26
0.15
1.09
0.66
1.74
1.52
0.23
0.03
0.14
0.43
0.12
1.25
1.54
0.07
5.47
55.99
0.06
0.11
0.20
0.07
0.65
0.58
0.18
0.00
0.03
0.60
7.82
10.27
5.63
3.12
0.10
8.41
126.77
4.37
166.47
1995
0.46
0.19
0.07
0.46
2.09
0.66
0.48
3.41
0.47
0.01
0.17
0.26
0.17
1.19
0.91
2.49
1.68
0.30
0.03
0.29
0.51
0.12
1.45
0.68
0.08
6.36
66.65
0.07
0.11
0.24
0.07
0.82
0.86
0.24
0.18
0.03
0.78
8.76
13.41
6.87
4.03
0.30
5.33
147.97
6.05
192.71
2000
0.74
0.19
0.08
0.51
2.23
0.84
0.35
3.38
0.55
0.02
0.19
0.26
0.22
1.30
1.24
3.42
1.70
0.32
0.03
0.36
0.58
0.12
1.68
0.46
0.09
8.26
67.16
0.08
0.12
0.24
0.13
1.04
1.07
0.29
0.17
0.03
1.12
10.62
13.51
8.13
4.67
0.37
4.88
156.90
7.57
206.64
2005
0.74
0.24
0.09
0.59
2.72
1.03
0.35
3.38
0.61
0.02
0.22
0.28
0.26
1.45
1.53
3.49
1.77
0.23
0.03
0.42
0.57
0.13
1.91
0.46
0.10
9.77
50.65
0.09
0.13
0.30
0.15
1.19
1.23
0.32
0.19
0.04
1.37
11.54
15.92
9.90
5.25
0.40
4.94
143.69
9.19
200.83
2010
0.74
0.29
0.10
0.61
3.17
1.17
0.35
3.38
0.69
0.03
0.26
0.33
0.29
1.61
1.88
3.49
2.09
0.18
0.04
0.43
0.57
0.15
2.17
0.46
0.12
10.53
43.79
0.11
0.15
0.37
0.19
1.36
1.43
0.36
0.22
0.04
1.67
12.59
18.90
11.59
5.93
0.42
4.99
152.38
11.15
217.95
2015
0.74
0.35
0.12
0.62
4.07
1.49
0.35
3.38
0.77
0.03
0.30
0.38
0.32
1.77
2.25
3.53
2.26
0.12
0.05
0.44
0.56
0.16
2.47
0.46
0.14
7.12
44.71
0.12
0.16
0.44
0.23
1.54
1.62
0.40
0.24
0.04
2.00
13.71
21.78
13.28
6.71
0.45
5.07
152.44
13.31
226.76
2020
0.74
0.42
0.13
0.64
4.96
1.82
0.35
3.38
0.87
0.03
0.34
0.31
0.36
1.94
2.68
3.56
2.42
0.07
0.05
0.45
0.55
0.18
2.82
0.46
0.16
3.71
47.04
0.14
0.18
0.53
0.29
1.76
1.84
0.45
0.26
0.05
2.41
14.99
25.22
15.39
7.63
0.48
5.16
167.04
16.07
251 .97
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-2: Nitrous Oxide Emissions from Biomass Combustion
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Azerbaijan
Bangladesh
Bolivia
Brazil
Cambodia
Chile
China
Colombia
Democratic Republic of Congo (Kinshasa)
Ecuador
Egypt
Ethiopia
Georgia
India
Indonesia
Iran
Iraq
Israel
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Macedonia
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
Nigeria
North Korea
Pakistan
Peru
Philippines
Saudi Arabia
Senegal
Singapore
South Africa
South Korea
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
United Arab Emirates
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
1990
0.02
0.00
0.06
0.00
0.00
0.68
0.04
1.55
0.08
0.13
10.58
0.29
0.51
0.05
0.08
0.55
0.00
0.57
1.35
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.39
0.00
0.03
0.25
0.30
0.00
0.91
0.05
0.00
0.19
0.51
0.00
0.05
0.00
0.37
0.01
0.00
0.28
0.37
0.00
1.46
0.00
0.03
0.00
0.03
0.47
2.72
0.84
0.00
0.02
0.00
0.26
1995
0.00
0.00
0.11
0.00
0.00
0.75
0.04
1.62
0.10
0.17
10.58
0.35
0.57
0.05
0.09
0.83
0.00
0.62
1.48
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.41
0.00
0.03
0.26
0.33
0.00
1.02
0.05
1.09
0.20
0.47
0.00
0.06
0.00
0.41
0.01
0.00
0.28
0.35
0.00
1.64
0.00
0.03
0.00
0.03
0.48
3.03
0.72
0.01
0.02
0.00
0.25
2000
0.00
0.00
0.13
0.00
0.00
0.82
0.05
1.82
0.13
0.19
10.96
0.26
0.66
0.05
0.10
0.94
0.00
0.67
1.29
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.37
0.00
0.03
0.27
0.36
0.00
1.16
0.05
1.20
0.21
0.36
0.00
0.06
0.00
0.45
0.01
0.00
0.29
0.36
0.00
1.84
0.00
0.02
0.00
0.03
0.49
3.41
0.74
0.01
0.02
0.00
0.29
2005
0.00
0.00
0.14
0.00
0.00
0.86
0.05
1.91
0.15
0.20
11.13
0.26
0.73
0.05
0.11
1.03
0.00
0.70
1.33
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.38
0.00
0.03
0.28
0.38
0.00
1.28
0.05
1.26
0.22
0.38
0.00
0.07
0.00
0.49
0.01
0.00
0.30
0.43
0.00
2.02
0.00
0.03
0.00
0.03
0.51
3.74
0.76
0.01
0.02
0.00
0.30
2010
0.00
0.00
0.14
0.00
0.00
0.90
0.05
2.01
0.17
0.20
11.29
0.27
0.80
0.05
0.12
1.13
0.00
0.73
1.38
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.39
0.00
0.03
0.29
0.40
0.00
1.40
0.06
1.33
0.22
0.39
0.00
0.08
0.00
0.54
0.01
0.00
0.32
0.51
0.00
2.22
0.00
0.03
0.00
0.03
0.53
4.11
0.78
0.01
0.02
0.00
0.31
2015
0.00
0.01
0.14
0.00
0.00
0.93
0.05
2.08
0.19
0.21
11.40
0.28
0.87
0.05
0.13
1.23
0.00
0.74
1.43
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.40
0.00
0.04
0.30
0.42
0.00
1.52
0.06
1.37
0.23
0.41
0.00
0.08
0.00
0.58
0.01
0.00
0.33
0.59
0.00
2.41
0.00
0.03
0.00
0.03
0.55
4.47
0.80
0.01
0.02
0.00
0.33
2020
0.00
0.01
0.15
0.00
0.00
0.96
0.05
2.14
0.22
0.21
11.50
0.29
0.94
0.06
0.14
1.33
0.00
0.76
1.45
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.41
0.00
0.04
0.31
0.43
0.00
1.66
0.06
1.42
0.23
0.43
0.00
0.09
0.00
0.64
0.01
0.00
0.34
0.67
0.00
2.62
0.00
0.03
0.00
0.03
0.58
4.85
0.82
0.01
0.02
0.00
0.34
-------
Appendix C-2: Nitrous Oxide Emissions from Biomass Combustion
MtCO2eq
Country
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
6.64
11.25
3.60
0.05
0.05
0.01
0.37
4.21
26.18
1995
7.66
11.28
3.72
0.06
0.03
0.01
0.35
5.54
28.65
2000
8.62
11.71
3.88
0.06
0.03
0.01
0.36
5.56
30.23
2005
9.47
11.91
4.02
0.07
0.03
0.01
0.43
5.80
31.75
2010
10.40
12.12
4.17
0.08
0.03
0.01
0.51
6.06
33.39
2015
11.30
12.28
4.29
0.11
0.03
0.01
0.59
6.26
34.87
2020
12.28
12.43
4.42
0.15
0.03
0.01
0.67
6.45
36.45
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-3: Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Lithuania
Luxembourg
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
1990
0.01
0.31
0.17
0.00
IE
0.91
0.00
0.00
0.35
3.93
0.00
2.48
2.26
11.50
0.31
19.55
0.00
0.93
1.21
0.00
1.04
0.00
0.31
0.00
1.60
24.14
0.50
23.48
0.71
3.21
0.05
2.43
0.00
0.68
0.00
1.04
0.00
6.75
7.42
0.00
0.00
0.00
0.43
0.00
0.65
0.00
0.00
0.00
0.00
7.57
IE
0.00
0.00
2.06
0.00
0.00
0.00
5.00
0.57
8.94
1995
0.01
0.31
0.19
0.00
IE
0.86
0.00
0.00
0.26
4.64
0.00
4.34
1.92
11.51
0.25
27.52
0.08
0.84
1.13
0.00
0.90
0.00
0.31
0.00
1.39
26.17
0.16
24.99
0.56
1.35
0.04
2.79
0.00
0.68
0.00
0.81
0.00
7.15
7.37
0.00
0.00
0.00
1.11
0.00
0.85
0.00
0.00
0.00
0.00
7.52
IE
0.00
0.00
1.64
0.00
0.19
0.00
4.90
0.60
3.63
2000
0.01
0.31
0.31
0.00
IE
0.95
0.00
0.00
0.31
4.56
0.00
5.03
1.31
1.70
0.31
30.10
0.00
0.85
1.12
0.00
1.00
0.00
0.31
0.00
1.32
11.46
0.16
5.55
0.50
1.80
0.02
3.01
0.00
0.68
0.00
0.81
0.00
7.80
4.25
0.00
0.00
0.00
1.88
0.00
0.95
0.00
0.00
0.00
0.00
7.14
IE
0.00
0.00
1.73
0.00
0.19
0.00
4.35
0.44
2.89
2005
0.01
0.31
0.31
0.00
IE
0.98
0.00
0.00
0.31
4.72
0.00
5.53
2.28
1.76
0.31
32.00
0.00
0.85
1.12
0.00
1.00
0.00
0.31
0.00
1.50
12.90
0.16
5.72
0.50
1.32
0.02
3.19
0.00
0.68
0.00
0.81
0.00
8.22
4.59
0.00
0.00
0.00
0.51
0.00
1.01
0.00
0.00
0.00
0.00
7.49
IE
0.00
0.00
1.72
0.00
0.19
0.00
4.35
0.44
2.89
2010
0.01
0.31
0.31
0.00
IE
1.03
0.00
0.00
0.31
4.89
0.00
6.09
2.67
1.87
0.31
34.05
0.00
0.85
1.12
0.00
1.00
0.00
0.31
0.00
1.50
14.35
0.16
5.89
0.50
1.32
0.02
3.39
0.00
0.68
0.00
0.81
0.00
8.64
4.59
0.00
0.00
0.00
0.51
0.00
1.08
0.00
0.00
0.00
0.00
7.69
IE
0.00
0.00
1.72
0.00
0.19
0.00
4.35
0.44
2.89
2015
0.01
0.31
0.31
0.00
IE
1.07
0.00
0.00
0.31
5.06
0.00
6.40
2.90
1.87
0.31
35.49
0.00
0.85
1.12
0.00
1.00
0.00
0.31
0.00
1.55
14.40
0.16
6.06
0.50
1.32
0.02
3.60
0.00
0.68
0.00
0.81
0.00
9.10
4.78
0.00
0.00
0.00
0.51
0.00
1.15
0.00
0.00
0.00
0.00
8.08
IE
0.00
0.00
1.72
0.00
0.19
0.00
4.35
0.44
2.89
2020
0.01
0.31
0.31
0.00
IE
1.12
0.00
0.00
0.31
5.23
0.00
6.73
3.40
1.93
0.31
36.99
0.00
0.85
1.12
0.00
1.00
0.00
0.31
0.00
1.60
14.46
0.16
6.23
0.50
1.32
0.02
3.82
0.00
0.68
0.00
0.81
0.00
9.57
4.96
0.00
0.00
0.00
0.51
0.00
1.23
0.00
0.00
0.00
0.00
8.28
IE
0.00
0.00
1.72
0.00
0.19
0.00
4.35
0.44
2.89
-------
Appendix C-3: Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
MtCO2eq
Country
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of China/CPA
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of Non-EU FSU
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.93
0.00
0.00
0.00
0.51
0.00
1.81
5.71
2.88
0.83
0.10
0.00
0.00
0.00
0.00
5.20
0.00
29.27
33.05
0.00
0.31
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
2.43
19.55
3.67
0.68
0.94
7.29
180.46
8.33
223.36
1995
0.31
0.00
0.00
0.59
0.63
0.00
2.25
6.09
2.38
0.72
0.10
0.00
0.00
0.00
0.00
1.45
0.00
18.99
37.09
0.00
0.31
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
2.87
27.52
5.97
0.68
0.85
2.49
170.11
9.64
220.12
2000
0.31
0.00
0.00
0.68
0.70
0.00
2.25
7.13
2.33
0.65
0.10
0.00
0.00
0.00
0.00
2.29
0.00
6.25
25.63
0.00
0.31
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
2.87
30.10
6.87
0.68
0.87
3.38
98.25
10.94
153.97
2005
0.31
0.00
0.00
0.76
0.70
0.00
2.25
7.87
2.32
0.54
0.10
0.00
0.00
0.00
0.00
2.41
0.00
6.25
22.41
0.00
0.31
0.09
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
2.87
32.00
7.44
0.68
0.87
3.50
97.18
11.94
156.48
2010
0.31
0.00
0.00
0.83
0.70
0.00
2.25
8.69
2.32
0.43
0.10
0.00
0.00
0.00
0.00
2.41
0.00
6.25
23.90
0.00
0.31
0.09
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
2.87
34.05
8.07
0.68
0.87
3.50
101.51
13.03
164.58
2015
0.31
0.00
0.00
0.88
0.70
0.00
2.25
9.13
2.32
0.40
0.10
0.00
0.00
0.00
0.00
2.41
0.00
6.25
25.48
0.00
0.31
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
2.87
35.49
8.46
0.68
0.87
3.50
104.80
13.73
170.40
2020
0.31
0.00
0.00
0.92
0.70
0.00
2.25
9.60
2.32
0.37
0.10
0.00
0.00
0.00
0.00
2.41
0.00
6.25
27.18
0.00
0.31
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
2.87
36.99
8.87
0.68
0.87
3.50
108.38
14.46
176.62
Regional country groupings are defined in Table 1-4 and Appendix H.
Codes:
IE - Estimated, but included elsewhere.
-------
Appendix C-4: Nitrous Oxide Emissions from Other Industrial Non-Agricultural Sources
MtCO2eq
Country
Australia
Belgium
Denmark
France
Greece
Iceland
Ireland
Netherlands
Portugal
Slovenia
Sweden
Switzerland
Ukraine
United Kingdom
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.94
0.00
0.00
0.04
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
1.02
0.00
1.02
1995
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.83
0.00
0.00
0.04
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.90
0.00
0.90
2000
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.72
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.81
0.00
0.81
2005
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.70
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.78
2010
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.70
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.78
2015
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.70
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.78
2020
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.70
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.78
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-5: Nitrous Oxide Emissions from Agricultural Soils
MtCO2eq
Country
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Latvia
Liechtenstein
Lithuania
Luxembourg
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
1990
7.97
52.07
0.05
15.18
3.07
0.61
30.40
9.95
5.68
0.04
132.06
5.77
1.66
26.86
3.76
412.72
23.16
2.46
7.57
0.34
8.31
0.02
6.54
0.95
4.96
4.29
56.05
0.94
43.88
9.75
10.43
0.25
42.99
16.28
9.31
6.01
7.29
0.93
18.87
9.75
0.00
18.62
2.52
0.00
3.35
0.15
12.88
2.77
8.19
2.08
7.66
10.88
10.02
29.08
9.00
2.42
7.68
7.90
5.68
12.60
1995
7.75
54.27
0.01
15.45
3.34
0.25
39.55
4.42
4.41
0.04
147.56
2.62
2.21
29.78
4.93
497.16
26.72
1.87
5.40
0.34
7.27
0.03
8.51
0.36
5.49
3.81
52.52
0.29
37.59
8.74
6.81
0.23
45.26
16.23
10.11
5.64
7.84
0.93
19.33
8.80
0.00
12.13
0.74
0.00
1.55
0.15
10.04
1.81
9.46
3.36
8.37
11.91
10.94
30.26
2.72
2.41
9.27
12.12
8.68
9.73
2000
9.22
58.81
0.01
19.03
2.85
0.02
42.15
5.81
4.15
0.05
154.44
2.40
2.17
32.85
5.43
509.26
37.01
1.97
4.73
0.31
6.15
0.04
9.42
0.37
9.23
3.42
54.36
0.45
39.22
8.55
6.74
0.24
54.62
17.20
12.59
6.04
8.17
1.03
19.23
8.14
0.00
5.76
0.68
0.00
1.10
0.15
12.84
0.87
11.45
4.65
8.84
9.92
11.80
34.19
4.93
2.44
10.19
17.84
10.66
10.71
2005
10.43
69.80
0.02
18.85
2.81
0.02
45.72
6.11
4.08
0.06
176.00
3.01
2.64
35.92
6.09
536.10
41.46
2.47
4.73
0.37
5.35
0.04
10.87
0.45
10.54
3.23
53.78
0.48
39.57
7.91
6.80
0.24
57.68
18.08
16.59
6.89
7.86
1.18
18.79
8.34
0.01
5.91
0.73
0.00
0.45
0.15
14.39
0.88
12.42
6.05
10.03
9.55
13.43
40.51
5.27
2.44
10.34
19.98
11.21
11.03
2010
11.81
83.75
0.02
19.21
2.78
0.02
49.32
6.44
4.01
0.06
201 .08
3.20
3.10
38.84
6.82
563.92
46.45
2.63
4.73
0.43
5.35
0.05
12.54
0.45
12.04
2.96
53.20
0.52
36.97
7.87
6.35
0.24
61.00
19.00
20.57
7.85
7.55
1.37
18.24
8.54
0.01
6.09
0.85
0.00
0.45
0.15
16.12
0.91
13.39
7.44
11.40
9.18
15.05
48.01
5.68
2.44
10.50
22.39
11.78
11.57
2015
13.37
101.75
0.02
19.31
2.75
0.02
55.13
6.79
3.95
0.07
230.40
3.72
4.03
42.37
7.64
595.25
52.05
3.06
4.73
0.51
5.35
0.06
14.47
0.48
13.76
2.96
53.61
0.55
35.91
7.90
6.17
0.24
64.71
19.97
25.52
8.96
7.27
1.58
17.78
8.74
0.01
6.29
0.90
0.00
0.45
0.15
18.06
0.94
14.50
9.30
12.95
8.83
17.13
56.94
6.13
2.44
10.68
25.09
12.38
11.89
2020
15.14
125.36
0.02
19.40
2.72
0.02
60.99
7.17
3.88
0.08
264.79
3.92
4.96
45.91
8.56
627.74
58.32
3.21
4.73
0.60
5.35
0.06
16.69
0.48
15.72
2.96
54.01
0.59
34.85
7.65
5.99
0.24
68.82
20.99
31.66
10.22
6.99
1.82
17.31
8.94
0.01
6.50
1.00
0.00
0.45
0.15
20.23
0.98
15.61
11.16
14.72
8.49
19.21
67.58
6.64
2.44
10.94
28.11
13.01
12.12
-------
Appendix C-5: Nitrous Oxide Emissions from Agricultural Soils
MtCO2eq
Country
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of China/CPA
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of Non-EU FSU
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
3.51
10.05
86.65
7.31
4.17
0.00
4.16
0.89
18.51
4.24
16.26
5.39
2.41
8.70
41.71
0.01
6.55
27.52
30.41
252.99
10.41
10.22
21.03
7.00
181.13
3.21
30.83
12.48
8.35
5.83
0.33
26.16
259.24
441 .78
294.15
36.04
10.81
163.17
643.98
151.88
2,001.05
1995
3.24
6.46
35.22
6.98
5.09
0.00
2.55
0.91
15.52
4.00
14.82
5.26
2.25
10.98
37.26
0.00
5.74
20.04
29.08
244.72
7.90
9.85
17.24
8.06
200.59
3.96
31.37
13.52
7.69
3.90
0.34
28.88
279.30
523.56
312.21
37.19
9.56
87.93
598.57
174.58
2,022.90
2000
3.16
4.44
27.31
8.28
5.91
0.00
2.34
0.95
16.25
3.66
18.76
4.95
2.16
13.52
36.08
0.00
8.34
14.28
27.63
263.86
14.11
12.67
14.88
9.12
226.85
3.91
31.80
15.40
6.71
3.14
0.31
28.01
319.73
540.83
347.24
43.34
8.68
70.33
622.04
193.52
2,145.71
2005
3.21
5.39
28.12
9.41
5.96
0.00
3.41
0.95
17.15
3.85
19.67
4.93
2.05
14.21
41.56
0.00
9.89
18.00
26.92
263.98
15.81
13.35
16.67
9.69
255.16
4.86
33.82
16.67
6.16
2.66
0.31
29.49
360.87
570.98
394.11
50.74
8.63
75.57
631 .87
206.66
2,299.43
2010
3.25
5.87
29.50
10.70
6.04
0.00
4.06
0.95
18.12
4.05
19.67
4.91
2.03
14.94
48.03
0.00
11.77
21.10
26.32
272.43
17.71
14.12
18.68
10.25
288.09
5.31
37.86
18.73
6.87
2.86
0.36
32.24
408.85
601 .65
450.98
59.23
9.50
81.57
648.07
221 .66
2,481.50
2015
3.31
6.81
30.33
12.17
6.17
0.00
4.05
0.95
19.18
4.25
19.67
4.91
2.00
15.70
55.68
0.00
14.06
26.15
25.69
278.21
19.85
14.98
20.92
11.95
325.27
5.78
42.46
21.05
7.63
3.03
0.41
35.25
463.72
637.64
518.34
69.29
10.68
89.09
666.73
240.34
2,695.83
2020
3.38
7.75
30.91
13.85
6.39
0.00
4.04
0.95
20.34
4.47
19.67
4.91
1.97
16.50
64.69
0.00
16.90
31.19
25.07
284.70
22.24
16.00
23.44
13.64
367.26
6.40
47.71
23.68
8.40
3.14
0.48
38.63
526.62
675.00
598.90
81.24
11.61
96.51
686.78
260.24
2,936.92
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-6: Nitrous Oxide Emissions from Manure Management
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Macedonia
Mexico
Moldova
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
Norway
1990
0.02
0.83
0.15
0.20
0.52
0.79
0.57
0.51
0.00
0.95
0.24
5.89
1.03
0.64
3.45
0.14
49.51
0.35
0.38
0.66
0.00
0.68
0.26
0.05
0.02
0.22
0.62
6.90
0.41
4.47
0.30
2.15
0.03
0.29
3.02
0.14
0.05
0.63
0.21
3.83
13.55
0.01
2.78
0.00
0.00
0.28
0.30
0.00
0.00
0.09
0.01
0.50
0.48
1.73
0.57
0.67
0.04
0.64
0.72
0.13
1995
0.03
0.93
0.18
0.16
0.93
0.77
0.47
0.59
0.00
0.98
0.28
6.20
0.50
1.20
3.85
0.20
60.01
0.38
0.25
0.48
0.00
0.64
0.31
0.07
0.01
0.23
0.50
6.64
0.34
3.14
0.28
1.30
0.03
0.31
3.62
0.16
0.02
0.67
0.24
3.98
12.65
0.01
2.19
0.00
0.00
0.37
0.18
0.00
0.17
0.09
0.01
0.38
0.50
1.89
0.62
0.74
0.05
0.76
0.41
0.15
2000
0.64
1.05
0.25
0.16
1.31
0.73
0.62
0.62
0.00
0.97
0.33
5.68
0.43
1.24
3.88
0.31
62.34
0.40
0.22
0.42
0.00
0.60
0.38
0.08
0.01
0.26
0.48
6.51
0.40
3.00
0.29
1.29
0.03
0.34
3.22
0.18
0.02
0.70
0.26
4.05
12.00
0.01
1.32
0.00
0.00
0.34
0.12
0.00
0.23
0.09
0.01
0.26
0.49
2.17
0.71
0.74
0.06
0.89
0.40
0.14
2005
1.25
1.16
0.27
0.15
1.30
0.73
0.61
0.68
0.00
0.94
0.36
6.18
0.43
1.71
4.38
0.33
69.12
0.43
0.22
0.43
0.00
0.51
0.41
0.08
0.01
0.29
0.45
6.43
0.39
2.53
0.29
1.89
0.03
0.36
3.64
0.20
0.02
0.70
0.28
4.15
12.30
0.01
1.34
0.00
0.00
0.37
0.12
0.00
0.21
0.09
0.01
0.26
0.53
2.37
0.77
0.74
0.06
0.98
0.44
0.14
2010
1.86
1.32
0.29
0.15
1.33
0.73
0.60
0.75
0.00
0.91
0.39
6.73
0.43
2.17
4.80
0.36
76.80
0.46
0.22
0.44
0.00
0.49
0.45
0.09
0.01
0.32
0.41
6.36
0.38
2.13
0.29
1.95
0.03
0.39
4.11
0.21
0.03
0.70
0.29
4.25
12.59
0.01
1.36
0.00
0.00
0.40
0.12
0.00
0.21
0.09
0.01
0.25
0.57
2.59
0.84
0.74
0.05
1.08
0.47
0.14
2015
2.48
1.53
0.31
0.14
1.33
0.73
0.59
0.82
0.00
0.89
0.42
7.18
0.43
3.10
5.37
0.39
82.76
0.48
0.22
0.45
0.00
0.48
0.49
0.09
0.01
0.35
0.41
6.41
0.38
2.14
0.29
1.98
0.03
0.41
4.40
0.22
0.03
0.70
0.29
4.36
12.89
0.01
1.39
0.00
0.00
0.47
0.13
0.00
0.21
0.09
0.01
0.25
0.60
2.79
0.91
0.74
0.05
1.17
0.50
0.14
2020
3.10
1.88
0.33
0.14
1.34
0.73
0.59
0.89
0.00
0.86
0.45
7.66
0.43
4.03
5.93
0.42
89.32
0.51
0.22
0.46
0.00
0.47
0.52
0.09
0.01
0.39
0.41
6.45
0.37
2.15
0.29
2.00
0.03
0.43
4.72
0.24
0.03
0.70
0.30
4.47
13.18
0.01
1.41
0.00
0.00
0.50
0.14
0.00
0.21
0.09
0.01
0.25
0.64
3.01
0.99
0.74
0.05
1.27
0.53
0.14
-------
Appendix C-6: Nitrous Oxide Emissions from Manure Management
MtCO2eq
Country
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.57
0.59
1.12
8.13
0.94
0.28
21.30
0.03
0.05
0.03
1.09
0.36
0.43
1.70
1.63
0.80
0.45
0.40
5.56
1.97
0.47
0.21
9.26
0.00
1.51
16.26
0.04
0.31
0.26
0.00
2.47
0.93
0.03
0.90
0.03
2.01
4.90
51.62
8.84
0.47
1.39
36.21
75.21
17.11
195.76
1995
0.65
0.61
1.29
7.33
0.95
0.16
16.60
0.04
0.06
0.02
0.73
0.29
0.02
2.48
1.56
0.67
0.42
0.34
5.83
2.04
0.38
0.24
7.35
0.00
1.50
17.13
0.05
0.30
0.37
0.00
2.59
1.05
0.09
1.33
0.03
2.36
4.90
62.49
9.64
0.56
1.70
28.51
71.45
19.67
198.93
2000
0.73
0.70
1.56
5.78
1.02
0.14
17.20
0.06
0.08
0.02
0.50
0.25
0.02
2.48
1.61
0.63
0.41
0.31
5.25
1.89
0.37
0.28
4.31
0.00
1.44
17.81
0.06
0.28
0.47
0.00
2.66
1.18
0.09
1.21
0.06
1.46
5.31
64.82
9.77
0.63
2.16
25.21
69.52
18.55
195.97
2005
0.33
0.76
1.79
5.95
1.12
0.14
19.50
0.06
0.09
0.02
0.59
0.25
0.02
2.69
1.71
0.63
0.40
0.31
5.56
1.96
0.37
0.31
4.87
0.00
1.44
17.40
0.07
0.29
0.51
0.00
3.11
1.27
0.09
1.21
0.06
1.60
6.04
72.16
10.61
0.66
2.77
28.09
70.40
19.80
210.53
2010
0.39
0.84
2.05
6.24
1.22
0.14
20.30
0.06
0.10
0.02
0.58
0.25
0.02
2.91
1.79
0.62
0.40
0.31
6.08
2.04
0.38
0.34
5.10
0.00
1.44
17.83
0.07
0.29
0.56
0.00
3.52
1.36
0.09
1.18
0.06
1.76
6.78
80.41
11.54
0.69
3.35
29.14
71.74
21.90
225.56
2015
0.45
0.92
2.28
6.42
1.32
0.14
21.10
0.06
0.11
0.03
0.56
0.25
0.02
3.14
1.90
0.62
0.39
0.31
6.08
2.09
0.39
0.37
5.57
0.00
1.44
18.09
0.08
0.30
0.60
0.00
3.76
1.55
0.09
1.18
0.06
1.87
7.41
87.43
12.42
0.72
3.97
30.43
73.45
23.17
238.99
2020
0.49
1.00
2.53
6.54
1.65
0.14
22.00
0.07
0.12
0.03
0.55
0.25
0.02
3.38
2.00
0.62
0.39
0.31
6.08
2.14
0.40
0.40
6.04
0.00
1.44
18.39
0.09
0.31
0.65
0.00
4.14
1.61
0.09
1.15
0.06
1.98
8.32
95.02
13.24
0.74
4.56
31.83
75.37
24.53
253.61
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-7: Nitrous Oxide Emissions from Other Agricultural Sources
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.01
0.22
2.17
0.01
1.91
0.03
0.02
0.14
0.04
0.02
5.48
36.79
0.05
1.59
0.74
0.84
1.80
3.56
0.02
0.04
12.57
0.04
2.42
0.00
1.02
0.04
0.42
0.01
0.19
0.11
0.07
0.00
0.79
13.53
0.47
0.01
0.04
0.31
0.08
0.01
0.14
0.00
0.01
1.58
0.01
0.01
0.00
0.02
2.45
0.02
0.10
4.84
0.34
0.03
0.02
1.35
1995
0.01
0.16
1.24
0.00
1.91
0.01
0.01
0.02
0.03
0.24
5.27
30.13
0.04
1.77
5.25
0.61
0.20
2.91
0.02
0.03
12.64
0.01
2.13
0.00
1.22
0.06
0.14
0.01
0.05
0.05
0.06
0.00
0.29
12.80
0.46
0.00
0.04
0.07
0.09
0.01
0.06
0.00
0.01
1.70
0.00
0.01
0.01
2.11
0.02
0.10
4.75
0.34
0.01
0.02
1.39
2000
0.01
0.00
1.82
0.01
4.24
0.01
0.01
1.06
0.04
0.23
16.28
69.56
0.05
0.83
0.75
0.19
0.84
5.31
0.02
0.03
31.67
0.01
0.14
0.00
0.00
1.21
0.00
0.12
0.01
0.06
0.02
0.06
0.00
2.77
16.03
0.15
0.00
0.00
0.04
0.09
0.06
0.00
0.13
0.00
0.01
2.69
0.00
0.00
0.01
0.00
0.01
5.92
0.02
0.00
0.05
8.66
0.02
0.01
0.02
2.25
2005
0.01
0.00
1.82
0.01
4.24
0.01
0.01
1.06
0.04
0.01
16.28
69.56
0.05
0.83
0.75
0.19
0.84
5.31
0.02
0.03
31.67
0.01
0.14
0.00
0.00
1.21
0.00
0.12
0.01
0.06
0.02
0.06
0.00
2.77
16.03
0.15
0.00
0.00
0.04
0.09
0.06
0.00
0.13
0.00
0.01
2.69
0.00
0.00
0.01
0.00
0.01
5.92
0.02
0.00
0.05
8.66
0.02
0.01
0.02
2.25
2010
0.01
0.00
1.82
0.01
4.24
0.01
0.01
1.06
0.04
0.01
16.28
69.56
0.05
0.83
0.75
0.19
0.84
5.31
0.02
0.03
31.67
0.01
0.14
0.00
0.00
1.21
0.00
0.12
0.01
0.06
0.02
0.06
0.00
2.77
16.03
0.15
0.00
0.00
0.04
0.09
0.06
0.00
0.13
0.00
0.01
2.69
0.00
0.00
0.01
0.00
0.01
5.92
0.02
0.00
0.05
8.66
0.02
0.01
0.02
2.25
2015
0.01
0.00
1.82
0.01
4.24
0.01
0.01
1.06
0.04
0.01
16.28
69.56
0.05
0.83
0.75
0.19
0.84
5.31
0.02
0.03
31.67
0.01
0.14
0.00
0.00
1.21
0.00
0.12
0.01
0.06
0.02
0.06
0.00
2.77
16.03
0.15
0.00
0.00
0.04
0.09
0.06
0.00
0.13
0.00
0.01
2.69
0.00
0.00
0.01
0.00
0.01
5.92
0.02
0.00
0.05
8.66
0.02
0.01
0.02
2.25
2020
0.01
0.00
1.82
0.01
4.24
0.01
0.01
1.06
0.04
0.01
16.28
69.56
0.05
0.83
0.75
0.19
0.84
5.31
0.02
0.03
31.67
0.01
0.14
0.00
0.00
1.21
0.00
0.12
0.01
0.06
0.02
0.06
0.00
2.77
16.03
0.15
0.00
0.00
0.04
0.09
0.06
0.00
0.13
0.00
0.01
2.69
0.00
0.00
0.01
0.00
0.01
5.92
0.02
0.00
0.05
8.66
0.02
0.01
0.02
2.25
-------
Appendix C-7: Nitrous Oxide Emissions from Other Agricultural Sources
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.01
0.39
3.18
3.83
0.16
0.14
0.10
1.41
0.06
0.42
0.00
0.02
0.01
0.89
0.19
0.38
0.03
0.01
0.01
2.90
0.49
0.01
0.54
0.23
0.12
0.37
0.03
0.06
5.78
1.53
25.41
6.97
0.09
0.06
0.16
8.66
42.43
6.60
69.65
0.67
0.11
1.98
6.12
35.61
163.17
1995
0.00
0.31
2.79
3.44
0.15
0.15
0.12
0.58
0.07
0.41
0.00
0.02
0.00
0.57
0.25
0.15
0.01
0.00
0.01
2.17
0.53
0.01
0.54
0.19
0.00
0.03
0.38
0.03
0.05
5.22
1.52
24.47
6.73
0.12
0.05
0.01
9.35
41.42
5.29
59.17
0.69
0.09
0.99
9.61
33.72
150.97
2000
0.02
0.00
0.01
1.88
0.18
0.16
0.02
0.11
2.37
0.07
0.21
0.00
0.02
0.00
0.76
0.14
0.07
0.01
0.00
0.01
3.17
0.54
0.02
0.47
0.20
0.00
0.03
0.46
0.04
0.05
6.40
0.90
71.01
7.04
0.05
0.06
0.01
4.57
107.60
5.33
114.58
0.31
0.10
2.88
7.21
36.60
274.61
2005
0.02
0.00
0.01
1.88
0.18
0.16
0.02
0.11
2.37
0.07
0.21
0.00
0.02
0.00
0.76
0.14
0.07
0.01
0.00
0.01
3.17
0.54
0.02
0.47
0.20
0.00
0.03
0.48
0.04
0.05
6.40
0.90
71.01
7.04
0.05
0.06
0.01
4.57
107.60
5.33
114.58
0.31
0.10
2.88
7.01
36.60
274.40
2010
0.02
0.00
0.01
1.88
0.18
0.16
0.02
0.11
2.37
0.07
0.21
0.00
0.02
0.00
0.76
0.14
0.07
0.01
0.00
0.01
3.17
0.54
0.02
0.47
0.20
0.00
0.03
0.50
0.04
0.05
6.40
0.90
71.01
7.04
0.05
0.06
0.01
4.57
107.60
5.33
114.58
0.31
0.10
2.88
7.03
36.60
274.42
2015
0.02
0.00
0.01
1.88
0.18
0.16
0.02
0.11
2.37
0.07
0.21
0.00
0.02
0.00
0.76
0.14
0.07
0.01
0.00
0.01
3.17
0.54
0.02
0.47
0.20
0.00
0.03
0.54
0.04
0.05
6.40
0.90
71.01
7.04
0.05
0.06
0.01
4.57
107.60
5.33
114.58
0.31
0.10
2.88
7.07
36.60
274.46
2020
0.02
0.00
0.01
1.88
0.18
0.16
0.02
0.11
2.37
0.07
0.21
0.00
0.02
0.00
0.76
0.14
0.07
0.01
0.00
0.01
3.17
0.54
0.02
0.47
0.20
0.00
0.03
0.57
0.04
0.05
6.40
0.90
71.01
7.04
0.05
0.06
0.01
4.57
107.60
5.33
114.58
0.31
0.10
2.88
7.10
36.60
274.49
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-8: Nitrous Oxide Emissions from Human Sewage
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
North Korea
1990
0.05
0.28
0.62
0.04
0.48
0.02
0.09
0.95
0.24
0.11
0.07
3.72
0.22
0.11
0.87
0.00
17.56
0.37
0.14
0.20
0.14
0.09
0.10
0.94
0.03
0.31
0.14
1.27
0.06
2.21
0.33
0.17
0.01
1.98
2.12
1.30
0.17
0.11
0.09
1.04
1.10
0.04
0.21
0.04
0.07
0.04
0.06
0.06
0.01
0.00
1.31
0.05
0.00
0.03
0.52
0.28
0.52
0.15
0.98
0.22
1995
0.05
0.31
0.66
0.04
0.51
0.06
0.09
1.06
0.20
0.28
0.08
3.72
0.18
0.13
0.92
0.00
18.54
0.41
0.13
0.20
0.17
0.09
0.12
1.04
0.03
0.31
0.13
1.29
0.06
2.18
0.35
0.16
0.01
2.17
2.30
1.44
0.19
0.11
0.11
1.05
1.09
0.06
0.21
0.03
0.07
0.05
0.05
0.06
0.01
0.00
1.44
0.05
0.00
0.03
0.57
0.31
0.47
0.15
1.13
0.24
2000
0.05
0.34
0.70
0.04
0.54
0.16
0.10
1.18
0.23
0.30
0.09
3.97
0.16
0.16
0.96
0.00
19.39
0.45
0.08
0.20
0.19
0.07
0.13
1.13
0.03
0.35
0.11
1.36
0.06
2.24
0.38
0.16
0.01
2.36
2.47
1.57
0.22
0.13
0.13
1.06
1.05
0.07
0.21
0.03
0.06
0.05
0.05
0.06
0.01
0.00
1.56
0.05
0.00
0.03
0.61
0.35
0.43
0.16
1.29
0.25
2005
0.05
0.37
0.74
0.04
0.57
0.16
0.10
1.31
0.23
0.30
0.09
4.22
0.15
0.18
1.00
0.00
20.10
0.48
0.08
0.20
0.22
0.06
0.14
1.23
0.02
0.40
0.11
1.39
0.06
2.24
0.38
0.16
0.01
2.55
2.62
1.68
0.25
0.13
0.14
1.05
1.06
0.08
0.20
0.04
0.07
0.06
0.05
0.06
0.01
0.00
1.67
0.05
0.00
0.04
0.65
0.39
0.44
0.16
1.47
0.26
2010
0.05
0.40
0.78
0.04
0.59
0.16
0.10
1.44
0.22
0.30
0.10
4.47
0.14
0.20
1.04
0.00
20.78
0.52
0.08
0.20
0.27
0.06
0.15
1.32
0.02
0.45
0.11
1.41
0.06
2.23
0.38
0.15
0.01
2.72
2.76
1.80
0.29
0.14
0.15
1.04
1.06
0.09
0.20
0.04
0.07
0.06
0.05
0.06
0.01
0.00
1.78
0.05
0.00
0.04
0.68
0.44
0.44
0.17
1.67
0.26
2015
0.05
0.43
0.82
0.04
0.62
0.15
0.11
1.58
0.22
0.30
0.11
4.70
0.14
0.23
1.08
0.00
21.45
0.56
0.08
0.20
0.31
0.06
0.16
1.41
0.02
0.50
0.11
1.42
0.06
2.21
0.37
0.15
0.01
2.88
2.91
1.94
0.32
0.15
0.16
1.02
1.06
0.10
0.20
0.05
0.07
0.07
0.05
0.06
0.01
0.00
1.88
0.05
0.00
0.04
0.71
0.49
0.45
0.17
1.88
0.27
2020
0.05
0.45
0.86
0.04
0.64
0.15
0.11
1.70
0.22
0.30
0.12
4.91
0.13
0.25
1.11
0.00
22.00
0.60
0.08
0.19
0.37
0.06
0.17
1.50
0.02
0.57
0.11
1.43
0.05
2.19
0.37
0.15
0.01
3.02
3.04
2.08
0.36
0.15
0.17
0.99
1.04
0.11
0.21
0.05
0.08
0.08
0.05
0.06
0.01
0.00
1.97
0.05
0.00
0.04
0.74
0.54
0.45
0.17
2.09
0.28
-------
Appendix C-8: Nitrous Oxide Emissions from Human Sewage
MtCO2eq
Country
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.09
1.76
0.34
0.85
0.80
0.45
0.34
3.72
0.70
0.08
0.02
0.06
0.74
0.68
1.00
0.20
0.02
0.05
0.53
0.99
0.05
0.16
1.56
0.04
1.03
13.02
0.06
0.30
0.34
1.03
3.03
0.58
0.34
0.21
0.02
1.09
6.65
18.99
7.51
2.72
0.40
6.44
27.22
10.75
80.68
1995
0.10
1.98
0.37
0.95
0.81
0.52
0.33
3.57
0.77
0.10
0.01
0.05
0.82
0.72
1.05
0.19
0.02
0.05
0.57
1.09
0.06
0.18
1.13
0.04
1.04
14.22
0.06
0.05
0.38
1.13
3.38
0.63
0.41
0.21
0.02
1.23
7.43
20.12
7.87
3.06
0.38
5.57
28.83
11.86
85.12
2000
0.11
2.27
0.41
1.06
0.81
0.55
0.33
3.41
0.92
0.11
0.01
0.06
0.89
0.75
1.09
0.15
0.02
0.05
0.60
1.18
0.07
0.21
1.11
0.05
1.17
15.56
0.06
0.05
0.42
1.22
3.82
0.69
0.48
0.21
0.02
1.33
8.34
21.10
8.48
3.46
0.34
5.44
30.67
12.98
90.81
2005
0.11
2.57
0.44
1.16
0.80
0.56
0.32
3.30
1.07
0.12
0.01
0.06
0.93
0.77
1.09
0.15
0.02
0.06
0.64
1.26
0.07
0.25
1.06
0.05
1.18
15.74
0.06
0.05
0.47
1.30
4.29
0.74
0.56
0.22
0.02
1.47
9.28
21.93
9.07
3.87
0.35
5.29
31.03
14.13
94.95
2010
0.11
2.91
0.47
1.26
0.80
0.56
0.32
3.21
1.25
0.14
0.01
0.06
0.93
0.79
1.08
0.14
0.02
0.06
0.67
1.33
0.08
0.29
1.01
0.06
1.19
15.93
0.06
0.05
0.50
1.38
4.79
0.80
0.64
0.22
0.03
1.61
10.26
22.74
9.65
4.32
0.35
5.16
31.34
15.28
99.09
2015
0.11
3.28
0.50
1.34
0.79
0.55
0.31
3.12
1.44
0.16
0.01
0.06
0.92
0.81
1.07
0.14
0.02
0.06
0.70
1.40
0.09
0.35
0.97
0.06
1.20
16.12
0.07
0.05
0.54
1.47
5.34
0.85
0.74
0.21
0.03
1.73
11.29
23.54
10.20
4.80
0.35
5.05
31.59
16.41
103.23
2020
0.11
3.65
0.53
1.42
0.79
0.55
0.31
3.04
1.63
0.17
0.01
0.06
0.91
0.82
1.05
0.14
0.02
0.07
0.72
1.47
0.09
0.41
0.93
0.06
1.20
16.29
0.07
0.06
0.58
1.56
5.91
0.91
0.84
0.21
0.03
1.85
12.38
24.22
10.72
5.31
0.35
4.93
31.80
17.51
107.22
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix C-9: Nitrous Oxide Emissions from Other Non-Agricultural Sources (Waste and Other)
MtCO2eq
Country
Australia
Austria
Belarus
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
Latvia
Moldova
Monaco
Netherlands
New Zealand
Norway
Portugal
Russian Federation
Saudi Arabia
Slovak Republic
Slovenia
Spain
Sweden
Switzerland
Ukraine
United Kingdom
United States
Venezuela
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.04
0.26
0.00
0.28
0.47
0.20
0.02
0.06
0.23
1.92
0.00
0.22
0.01
0.00
0.88
2.04
0.00
0.37
0.00
0.23
0.04
0.04
0.00
0.71
0.00
IE
0.04
0.42
0.09
0.14
0.02
0.11
4.72
0.02
0.00
0.00
0.02
0.00
0.00
1.10
12.47
0.00
13.59
1995
0.03
0.28
0.00
0.26
0.50
0.21
0.03
0.06
0.23
1.92
0.00
0.20
0.01
0.00
0.89
2.71
0.00
0.36
0.00
0.24
0.04
0.04
0.00
0.71
0.00
IE
0.02
0.48
0.13
0.16
0.02
0.11
4.88
0.02
0.00
0.00
0.02
0.00
0.00
1.09
13.44
0.00
14.55
2000
0.03
0.28
0.00
0.28
0.52
0.21
0.03
0.06
0.19
1.92
0.00
0.14
0.00
0.00
1.12
2.93
0.00
0.36
0.00
0.18
0.05
0.05
0.03
0.53
0.00
IE
0.04
0.49
0.13
0.18
0.01
0.10
5.12
0.02
0.00
0.00
0.02
0.00
0.00
0.90
14.10
0.00
15.02
2005
0.03
0.28
0.08
0.28
0.53
0.22
0.03
0.06
0.43
1.92
0.00
0.14
0.00
0.00
1.12
3.98
0.00
0.36
0.00
0.18
0.05
0.05
0.03
0.53
0.00
0.00
0.04
0.49
0.13
0.20
0.01
0.10
5.18
0.02
0.00
0.00
0.02
0.00
0.00
0.99
15.47
0.00
16.48
2010
0.03
0.28
0.08
0.28
0.53
0.22
0.03
0.06
0.43
1.92
0.00
0.14
0.00
0.00
1.12
5.07
0.00
0.36
0.00
0.18
0.05
0.05
0.03
0.53
0.00
0.00
0.04
0.49
0.13
0.22
0.01
0.10
5.19
0.02
0.00
0.00
0.02
0.00
0.00
0.99
16.59
0.00
17.60
2015
0.03
0.28
0.08
0.28
0.53
0.22
0.03
0.06
0.43
1.92
0.00
0.14
0.00
0.00
1.12
6.15
0.00
0.36
0.00
0.18
0.05
0.05
0.03
0.53
0.00
0.00
0.04
0.49
0.13
0.21
0.01
0.10
5.21
0.02
0.00
0.00
0.02
0.00
0.00
0.99
17.69
0.00
18.70
2020
0.03
0.28
0.08
0.28
0.53
0.22
0.03
0.06
0.43
1.92
0.00
0.14
0.00
0.00
1.12
7.24
0.00
0.36
0.00
0.18
0.05
0.05
0.03
0.53
0.00
0.00
0.04
0.49
0.13
0.20
0.01
0.10
5.22
0.02
0.00
0.00
0.02
0.00
0.00
0.99
18.78
0.00
19.79
Regional country groupings are defined in Table 1-4 and Appendix H.
Codes:
IE - Estimated, but included elsewhere.
-------
Appendix D-1: HFC and PFC Emissions from OPS Substitutes -Aerosols (MDI)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.12
0.01
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.02
0.29
0.00
0.40
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.27
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.07
0.02
0.00
2000
0.00
0.00
0.00
0.00
0.15
0.02
0.00
0.00
0.00
0.06
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.02
0.34
0.00
0.47
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.31
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.08
0.02
0.00
2005
0.00
0.02
0.00
0.00
0.16
0.02
0.00
0.00
0.00
0.06
0.00
0.01
0.01
0.00
0.02
0.00
0.08
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.02
0.37
0.00
0.51
0.03
0.00
0.01
0.02
0.00
0.00
0.00
0.01
0.01
0.34
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.09
0.03
0.00
2010
0.00
0.19
0.05
0.00
0.23
0.04
0.00
0.04
0.01
0.08
0.00
0.06
0.02
0.00
0.16
0.00
0.72
0.00
0.00
0.02
0.00
0.06
0.00
0.00
0.00
0.00
0.03
0.51
0.00
0.71
0.04
0.01
0.01
0.23
0.06
0.00
0.00
0.02
0.07
0.47
0.95
0.02
0.00
0.03
0.00
0.00
0.01
0.00
0.01
0.00
0.00
0.29
0.00
0.00
0.00
0.00
0.00
0.12
0.03
0.00
2015
0.00
0.37
0.09
0.00
0.29
0.05
0.00
0.07
0.01
0.11
0.00
0.12
0.03
0.00
0.30
0.01
1.60
0.00
0.00
0.03
0.00
0.07
0.01
0.00
0.00
0.00
0.03
0.65
0.00
0.89
0.05
0.02
0.01
0.48
0.12
0.00
0.00
0.02
0.14
0.59
1.65
0.04
0.00
0.06
0.00
0.00
0.01
0.00
0.01
0.01
0.00
0.58
0.00
0.00
0.00
0.00
0.00
0.15
0.04
0.00
2020
0.00
0.41
0.10
0.00
0.32
0.06
0.00
0.09
0.01
0.11
0.00
0.15
0.04
0.00
0.33
0.01
2.17
0.00
0.00
0.03
0.00
0.07
0.01
0.00
0.00
0.00
0.03
0.68
0.00
0.94
0.05
0.02
0.01
0.57
0.14
0.00
0.00
0.03
0.18
0.63
1.64
0.04
0.00
0.08
0.00
0.00
0.01
0.00
0.01
0.01
0.00
0.67
0.00
0.00
0.00
0.00
0.00
0.16
0.04
0.01
-------
Appendix D-1: HFC and PFC Emissions from OPS Substitutes -Aerosols (MDI)
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.02
0.00
0.00
0.00
0.02
0.02
0.01
0.19
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.07
0.01
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
1.81
0.00
2.00
2000
0.00
0.05
0.00
0.00
0.00
0.04
0.02
0.02
0.40
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.08
0.02
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.28
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.01
0.00
0.41
2.41
0.01
2.87
2005
0.00
0.07
0.00
0.00
0.00
0.08
0.02
0.04
0.69
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.15
0.08
0.03
0.00
0.01
0.00
0.00
0.00
0.02
0.00
0.30
0.33
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.00
0.00
0.01
0.04
0.08
0.05
0.03
0.00
0.72
2.98
0.07
3.97
2010
0.01
0.11
0.00
0.00
0.01
0.13
0.03
0.06
1.13
0.05
0.00
0.02
0.01
0.01
0.12
0.03
0.21
0.10
0.04
0.00
0.11
0.01
0.00
0.00
0.04
0.01
0.42
2.70
0.01
0.01
0.02
0.03
0.07
0.05
0.10
0.00
0.00
0.04
0.38
0.76
0.49
0.28
0.00
1.18
7.35
0.53
10.99
2015
0.03
0.11
0.00
0.00
0.01
0.16
0.04
0.08
1.35
0.09
0.00
0.04
0.02
0.01
0.23
0.05
0.27
0.11
0.05
0.00
0.22
0.02
0.00
0.00
0.05
0.02
0.53
5.09
0.01
0.02
0.03
0.07
0.15
0.11
0.20
0.00
0.01
0.08
0.75
1.69
0.97
0.55
0.01
1.43
11.52
1.07
17.99
2020
0.03
0.12
0.00
0.00
0.02
0.19
0.04
0.09
1.54
0.11
0.00
0.05
0.02
0.01
0.26
0.08
0.28
0.12
0.06
0.00
0.27
0.02
0.00
0.00
0.05
0.02
0.56
5.49
0.01
0.02
0.04
0.08
0.17
0.13
0.24
0.00
0.01
0.11
0.85
2.28
1.14
0.66
0.01
1.63
12.22
1.33
20.12
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-2: HFC and PFC Emissions from OPS Substitutes -Aerosols (Non-MDI)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.55
0.23
0.00
0.00
0.00
0.27
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.01
0.09
0.00
0.18
0.00
0.00
0.00
0.00
0.07
1.67
0.00
2.29
0.12
0.08
0.00
0.00
0.00
0.00
0.00
0.06
0.00
1.53
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.04
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.40
0.05
0.00
2000
0.00
0.00
0.00
0.00
0.67
0.26
0.00
0.00
0.00
0.32
0.00
0.00
0.10
0.00
0.00
0.00
0.01
0.00
0.02
0.21
0.00
0.21
0.00
0.00
0.00
0.00
0.08
1.93
0.00
2.64
0.13
0.19
0.01
0.00
0.00
0.00
0.00
0.07
0.00
1.76
0.00
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.09
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.46
0.06
0.00
2005
0.00
0.01
0.00
0.00
0.74
0.28
0.00
0.00
0.00
0.34
0.00
0.00
0.17
0.00
0.00
0.00
0.02
0.00
0.03
0.37
0.00
0.22
0.00
0.00
0.01
0.00
0.09
2.05
0.00
2.81
0.14
0.32
0.01
0.01
0.00
0.00
0.00
0.08
0.00
1.87
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.15
0.02
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.49
0.06
0.00
2010
0.00
0.01
0.00
0.00
0.82
0.29
0.00
0.00
0.00
0.36
0.00
0.00
0.27
0.00
0.00
0.00
0.03
0.00
0.05
0.57
0.00
0.23
0.00
0.00
0.01
0.00
0.09
2.17
0.00
2.98
0.15
0.50
0.01
0.01
0.00
0.00
0.00
0.08
0.00
1.99
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.23
0.02
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.52
0.07
0.00
2015
0.00
0.01
0.00
0.00
0.90
0.31
0.00
0.00
0.00
0.38
0.00
0.00
0.32
0.00
0.00
0.00
0.04
0.00
0.06
0.66
0.00
0.25
0.00
0.00
0.01
0.00
0.10
2.31
0.00
3.17
0.16
0.59
0.01
0.01
0.00
0.00
0.00
0.09
0.00
2.11
0.00
0.00
0.00
0.00
0.00
0.00
0.23
0.00
0.26
0.02
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.55
0.07
0.00
2020
0.00
0.01
0.00
0.00
1.00
0.33
0.00
0.00
0.00
0.40
0.00
0.00
0.37
0.00
0.00
0.00
0.05
0.00
0.07
0.77
0.00
0.26
0.00
0.00
0.01
0.00
0.11
2.45
0.00
3.36
0.17
0.68
0.02
0.01
0.00
0.00
0.00
0.09
0.00
2.24
0.00
0.00
0.00
0.00
0.00
0.00
0.26
0.00
0.30
0.02
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.58
0.08
0.00
-------
Appendix D-2: HFC and PFC Emissions from OPS Substitutes -Aerosols (Non-MDI)
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.02
0.00
0.00
0.00
0.08
0.09
0.02
0.75
0.00
0.00
0.00
0.03
0.04
0.00
0.00
0.69
0.10
0.08
0.00
0.00
0.00
0.00
0.00
0.03
0.00
1.36
8.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.79
18.33
0.00
19.14
2000
0.00
0.04
0.00
0.00
0.00
0.19
0.11
0.05
1.60
0.00
0.00
0.00
0.08
0.09
0.00
0.00
0.80
0.11
0.17
0.00
0.00
0.00
0.00
0.00
0.07
0.00
1.57
9.95
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.00
0.02
1.67
22.44
0.01
24.16
2005
0.00
0.06
0.00
0.00
0.00
0.33
0.12
0.08
2.74
0.00
0.00
0.00
0.13
0.16
0.00
0.00
0.85
0.12
0.28
0.00
0.00
0.00
0.00
0.00
0.12
0.00
1.67
10.98
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.02
0.01
0.01
0.03
2.87
25.12
0.01
28.08
2010
0.00
0.09
0.00
0.00
0.00
0.52
0.12
0.13
4.18
0.00
0.00
0.00
0.21
0.25
0.00
0.00
0.90
0.13
0.39
0.00
0.00
0.00
0.00
0.00
0.19
0.00
1.77
12.13
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.03
0.02
0.01
0.05
4.37
28.20
0.02
32.71
2015
0.00
0.09
0.00
0.00
0.00
0.60
0.13
0.15
4.77
0.00
0.00
0.00
0.24
0.29
0.01
0.00
0.96
0.14
0.42
0.00
0.00
0.00
0.00
0.00
0.22
0.00
1.88
13.39
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.02
0.04
0.02
0.01
0.06
4.99
30.78
0.02
35.94
2020
0.00
0.10
0.00
0.00
0.00
0.70
0.14
0.17
5.45
0.00
0.00
0.00
0.28
0.34
0.01
0.00
1.01
0.14
0.44
0.00
0.01
0.00
0.00
0.00
0.25
0.00
2.00
14.78
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.02
0.05
0.03
0.01
0.07
5.70
33.62
0.03
39.53
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-3: HFC and PFC Emissions from OPS Substitutes - Fire Extinguishing
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.31
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.02
0.00
0.03
0.00
0.00
0.00
0.01
0.01
0.00
0.00
0.00
0.03
0.02
0.15
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.00
2005
0.00
0.01
0.00
0.00
0.01
0.01
0.01
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.08
0.01
1.01
0.00
0.00
0.00
0.00
0.01
0.00
0.06
0.00
0.00
0.01
0.10
0.00
0.14
0.01
0.01
0.00
0.03
0.03
0.00
0.00
0.00
0.08
0.09
0.37
0.01
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.02
0.03
0.00
2010
0.00
0.01
0.01
0.00
0.02
0.01
0.03
0.00
0.00
0.04
0.00
0.01
0.00
0.00
0.10
0.01
2.04
0.00
0.01
0.00
0.00
0.02
0.00
0.11
0.00
0.00
0.02
0.23
0.00
0.30
0.02
0.03
0.00
0.05
0.05
0.00
0.00
0.01
0.14
0.21
0.61
0.02
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.05
0.05
0.00
2015
0.00
0.01
0.01
0.00
0.03
0.02
0.05
0.00
0.00
0.05
0.00
0.01
0.00
0.00
0.11
0.01
3.40
0.00
0.01
0.00
0.00
0.03
0.00
0.16
0.00
0.00
0.03
0.34
0.00
0.43
0.02
0.04
0.00
0.08
0.07
0.00
0.00
0.01
0.21
0.31
0.81
0.02
0.00
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.07
0.06
0.00
2020
0.00
0.02
0.01
0.00
0.03
0.02
0.07
0.00
0.01
0.07
0.00
0.02
0.00
0.00
0.12
0.02
4.86
0.00
0.01
0.00
0.00
0.04
0.00
0.20
0.00
0.00
0.04
0.45
0.00
0.57
0.03
0.06
0.00
0.10
0.10
0.00
0.00
0.01
0.27
0.41
0.94
0.03
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.10
0.07
0.00
-------
Appendix D-3: HFC and PFC Emissions from OPS Substitutes - Fire Extinguishing
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.34
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.37
0.00
0.39
2000
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.01
0.03
0.00
0.01
0.00
0.00
0.04
0.07
0.01
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.02
0.73
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.06
0.31
0.01
0.07
0.00
0.01
1.07
0.12
1.67
2005
0.00
0.01
0.02
0.00
0.01
0.00
0.01
0.00
0.04
0.09
0.00
0.03
0.00
0.00
0.11
0.21
0.04
0.01
0.01
0.00
0.00
0.02
0.00
0.00
0.00
0.01
0.06
1.24
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.05
0.19
1.01
0.05
0.21
0.00
0.06
2.32
0.38
4.22
2010
0.00
0.02
0.04
0.00
0.01
0.01
0.01
0.00
0.11
0.16
0.00
0.06
0.00
0.00
0.20
0.38
0.10
0.03
0.02
0.00
0.01
0.04
0.00
0.00
0.00
0.03
0.11
1.64
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.10
0.33
2.04
0.09
0.39
0.01
0.14
3.71
0.70
7.41
2015
0.00
0.03
0.06
0.00
0.02
0.01
0.02
0.00
0.20
0.24
0.00
0.09
0.00
0.00
0.29
0.58
0.14
0.04
0.02
0.00
0.01
0.06
0.00
0.00
0.00
0.04
0.14
1.76
0.00
0.00
0.02
0.00
0.02
0.01
0.02
0.00
0.00
0.15
0.48
3.40
0.13
0.58
0.01
0.25
4.60
1.07
10.52
2020
0.00
0.04
0.08
0.00
0.03
0.02
0.03
0.00
0.30
0.31
0.00
0.12
0.00
0.00
0.37
0.77
0.19
0.05
0.03
0.00
0.02
0.08
0.00
0.00
0.00
0.05
0.17
1.92
0.00
0.00
0.02
0.00
0.02
0.01
0.02
0.00
0.00
0.20
0.61
4.86
0.17
0.74
0.01
0.38
5.50
1.41
13.68
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-4: HFC and PFC Emissions from OPS Substitutes - Foams
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.01
0.12
0.00
0.17
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.21
0.00
0.29
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.19
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
2005
0.00
0.00
0.00
0.00
0.02
0.11
0.00
0.00
0.00
0.15
0.00
0.00
0.00
0.00
0.13
0.00
0.01
0.00
0.00
0.00
0.00
0.10
0.00
0.00
0.00
0.00
0.04
0.88
0.00
1.21
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.81
2.39
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.00
2010
0.00
0.00
0.00
0.00
0.08
0.13
0.00
0.00
0.00
0.18
0.00
0.00
0.00
0.00
0.38
0.00
0.02
0.00
0.00
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.05
1.08
0.00
1.48
0.07
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.99
3.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.26
0.01
0.00
2015
0.00
0.00
0.00
0.00
0.11
0.17
0.00
0.00
0.00
0.23
0.00
0.00
0.00
0.00
0.53
0.00
0.04
0.00
0.00
0.00
0.00
0.15
0.00
0.00
0.00
0.00
0.06
1.42
0.00
1.95
0.10
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
1.30
3.95
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.34
0.01
0.00
2020
0.00
0.00
0.00
0.00
0.17
0.25
0.00
0.00
0.00
0.34
0.00
0.00
0.00
0.00
0.76
0.00
0.05
0.00
0.00
0.00
0.00
0.22
0.00
0.00
0.00
0.00
0.09
2.08
0.00
2.86
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.08
0.00
1.91
4.81
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.49
0.02
0.00
-------
Appendix D-4: HFC and PFC Emissions from OPS Substitutes - Foams
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.10
0.15
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.84
0.00
0.84
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.29
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
1.47
0.00
1.48
2005
0.00
0.01
0.00
0.00
0.00
0.00
0.05
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.37
0.07
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.72
2.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.01
9.42
0.00
9.44
2010
0.00
0.02
0.00
0.00
0.00
0.00
0.06
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.45
0.09
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.88
5.67
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.03
15.33
0.00
15.38
2015
0.00
0.02
0.00
0.00
0.00
0.00
0.08
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.59
0.12
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.16
7.94
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.03
20.39
0.00
20.46
2020
0.00
0.03
0.00
0.00
0.00
0.01
0.12
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.86
0.18
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.70
11.31
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.00
0.04
28.54
0.00
28.64
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-5: HFC and PFC Emissions from OPS Substitutes - Refrigeration/Air Conditioning
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.05
0.05
0.00
0.30
0.10
0.00
0.00
0.01
0.12
0.00
0.20
0.01
0.00
0.87
0.01
0.53
0.03
0.00
0.02
0.00
0.08
0.01
0.04
0.00
0.00
0.03
0.18
0.01
0.99
0.05
0.02
0.00
0.07
0.02
0.00
0.00
0.03
0.10
0.66
4.75
0.01
0.00
0.04
0.00
0.00
0.01
0.00
0.01
0.01
0.00
0.19
0.00
0.00
0.00
0.00
0.00
0.17
0.03
0.01
2000
0.00
0.35
0.39
0.00
1.20
0.36
0.03
0.03
0.10
0.44
0.00
1.46
0.08
0.00
3.44
0.10
4.12
0.24
0.02
0.16
0.00
0.29
0.06
0.30
0.00
0.01
0.12
1.51
0.06
3.66
0.18
0.14
0.00
0.49
0.15
0.00
0.00
0.10
0.78
2.44
16.37
0.08
0.00
0.33
0.00
0.00
0.06
0.00
0.07
0.02
0.00
1.41
0.02
0.00
0.00
0.00
0.01
0.63
0.10
0.04
2005
0.00
0.86
0.99
0.00
1.98
0.55
0.07
0.07
0.24
0.83
0.01
3.68
0.20
0.00
5.76
0.25
11.88
0.61
0.04
0.40
0.00
0.55
0.15
0.75
0.01
0.02
0.19
5.01
0.14
6.94
0.35
0.36
0.01
1.30
0.38
0.00
0.00
0.19
1.98
4.63
24.68
0.21
0.00
0.84
0.00
0.00
0.14
0.00
0.17
0.04
0.00
3.55
0.05
0.00
0.00
0.01
0.02
1.20
0.17
0.10
2010
0.00
1.55
1.82
0.00
2.94
0.72
0.12
0.13
0.43
1.11
0.02
6.90
0.38
0.00
8.76
0.46
25.81
1.14
0.07
0.74
0.00
0.73
0.27
1.35
0.01
0.03
0.27
7.95
0.25
9.30
0.47
0.65
0.03
2.60
0.72
0.00
0.00
0.26
3.85
6.20
32.59
0.39
0.00
1.63
0.00
0.00
0.26
0.00
0.30
0.06
0.00
6.61
0.09
0.00
0.01
0.02
0.04
1.61
0.28
0.20
2015
0.00
1.94
2.36
0.00
3.97
0.88
0.16
0.18
0.54
1.85
0.03
9.12
0.50
0.00
12.03
0.62
39.91
1.47
0.09
0.95
0.00
1.22
0.36
1.69
0.01
0.04
0.34
12.97
0.32
15.50
0.78
0.82
0.04
3.73
0.95
0.00
0.00
0.43
5.38
10.34
39.45
0.51
0.00
2.27
0.00
0.00
0.33
0.00
0.37
0.10
0.00
8.66
0.11
0.00
0.01
0.03
0.05
2.68
0.40
0.30
2020
0.00
2.37
3.01
0.00
5.03
1.01
0.19
0.25
0.66
1.71
0.03
11.99
0.65
0.00
15.51
0.84
61.73
1.88
0.11
1.18
0.00
1.13
0.47
2.06
0.02
0.04
0.42
12.22
0.39
14.31
0.72
1.02
0.06
5.40
1.22
0.00
0.00
0.40
7.56
9.54
45.10
0.65
0.00
3.18
0.00
0.00
0.41
0.00
0.45
0.09
0.00
11.24
0.14
0.00
0.01
0.03
0.07
2.48
0.53
0.45
-------
Appendix D-5: HFC and PFC Emissions from OPS Substitutes - Refrigeration/Air Conditioning
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.03
0.00
0.02
0.02
0.09
0.02
0.04
0.00
0.18
0.09
0.00
0.02
0.01
0.01
0.23
0.50
0.30
0.04
0.01
0.00
0.09
0.04
0.00
0.00
0.01
0.01
0.59
14.61
0.01
0.02
0.09
0.01
0.05
0.10
0.04
0.00
0.01
0.10
0.38
0.56
0.71
0.30
0.01
0.24
24.12
0.91
27.22
2000
0.19
0.03
0.16
0.11
0.70
0.15
0.15
0.04
1.27
0.69
0.01
0.14
0.06
0.07
1.70
3.73
1.10
0.17
0.10
0.00
0.67
0.29
0.00
0.00
0.06
0.08
2.18
58.01
0.08
0.14
0.63
0.05
0.41
0.71
0.31
0.03
0.09
0.77
2.83
4.37
5.21
2.27
0.05
1.67
93.79
6.85
117.04
2005
0.50
0.08
0.42
0.28
1.81
0.40
0.29
0.11
3.31
1.74
0.04
0.37
0.15
0.18
4.20
9.69
2.09
0.29
0.24
0.00
1.76
0.72
0.00
0.01
0.15
0.20
4.13
97.30
0.21
0.35
1.60
0.14
1.03
1.78
0.80
0.08
0.23
2.00
7.01
12.52
13.10
5.76
0.11
4.31
160.54
17.84
221 .20
2010
0.95
0.23
0.79
0.53
3.49
0.84
0.38
0.26
6.95
3.19
0.07
0.80
0.27
0.32
7.65
18.59
2.81
0.49
0.44
0.00
3.56
1.34
0.01
0.01
0.29
0.40
5.53
148.60
0.39
0.63
2.99
0.27
1.91
3.29
1.51
0.14
0.42
3.88
12.77
27.03
24.42
10.97
0.21
8.78
237.57
34.62
356.36
2015
1.24
0.38
1.04
0.70
4.70
1.21
0.64
0.40
9.86
4.06
0.08
1.29
0.36
0.41
9.72
24.99
4.68
0.72
0.56
0.00
5.18
1.76
0.01
0.02
0.40
0.58
9.22
204.75
0.51
0.79
3.94
0.37
2.49
4.23
2.01
0.18
0.53
5.28
16.27
41.52
32.00
14.81
0.27
12.19
331 .58
47.42
496.07
2020
1.59
0.54
1.33
0.90
6.27
1.67
0.59
0.58
13.40
5.06
0.10
2.10
0.45
0.51
12.18
33.18
4.32
0.96
0.67
0.00
7.60
2.27
0.01
0.02
0.53
0.85
8.51
264.59
0.67
0.97
5.16
0.51
3.22
5.36
2.67
0.23
0.66
7.15
20.44
63.84
41.55
19.96
0.33
16.31
400.31
64.60
627.35
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-6: HFC and PFC Emissions from OPS Substitutes - Solvents
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.06
0.01
0.00
0.00
0.00
0.03
0.00
0.01
0.00
0.00
0.08
0.00
0.01
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.16
0.00
0.21
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.14
1.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
2000
0.00
0.00
0.00
0.00
0.14
0.02
0.00
0.00
0.00
0.05
0.00
0.05
0.00
0.00
0.17
0.00
3.97
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.01
0.88
0.00
1.18
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.02
0.69
3.54
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.08
0.02
0.00
2005
0.00
0.00
0.00
0.00
0.07
0.01
0.00
0.00
0.00
0.03
0.00
0.04
0.00
0.00
0.09
0.00
2.66
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.53
0.00
2.03
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.41
1.99
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
2010
0.00
0.00
0.00
0.00
0.07
0.01
0.00
0.00
0.00
0.02
0.00
0.05
0.00
0.00
0.08
0.00
1.37
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.33
0.00
1.11
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.02
0.27
1.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
2015
0.00
0.00
0.01
0.00
0.08
0.01
0.00
0.00
0.00
0.03
0.00
0.06
0.00
0.00
0.09
0.00
0.08
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.16
0.00
0.22
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.02
0.14
0.87
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
2020
0.00
0.00
0.01
0.00
0.08
0.01
0.00
0.00
0.00
0.03
0.00
0.07
0.00
0.00
0.10
0.00
0.11
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.01
0.17
0.00
0.23
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.03
0.15
0.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
-------
Appendix D-6: HFC and PFC Emissions from OPS Substitutes - Solvents
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.06
0.01
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.13
1.10
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.01
0.01
0.00
0.00
0.00
3.13
0.02
3.19
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.66
0.05
0.00
0.02
1.56
0.13
0.02
0.01
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.57
2.36
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
3.97
0.05
0.02
0.00
0.00
10.02
2.26
16.35
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.45
0.03
0.00
0.01
1.05
0.07
0.01
0.01
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.34
1.63
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
2.66
0.04
0.02
0.00
0.00
7.35
1.53
11.62
2010
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.24
0.02
0.00
0.02
0.57
0.06
0.01
0.01
0.00
0.03
0.01
0.00
0.00
0.00
0.00
0.23
1.67
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
1.37
0.06
0.02
0.00
0.01
5.37
0.84
7.70
2015
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.02
0.00
0.00
0.02
0.07
0.07
0.01
0.01
0.00
0.04
0.01
0.00
0.00
0.00
0.00
0.13
1.85
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.08
0.07
0.02
0.00
0.01
3.78
0.15
4.14
2020
0.00
0.00
0.00
0.00
0.01
0.00
0.01
0.00
0.01
0.00
0.00
0.03
0.00
0.01
0.02
0.09
0.07
0.01
0.01
0.00
0.05
0.01
0.00
0.00
0.00
0.00
0.14
2.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.11
0.08
0.03
0.00
0.01
4.07
0.18
4.51
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-7: HFC-23 Emissions from HCFC-22 Production (Technology-Adoption)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.28
0.00
0.00
0.00
0.00
3.58
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
5.92
0.00
2.64
0.54
0.00
0.00
1.13
0.00
0.00
0.00
0.00
0.00
2.09
9.85
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.06
0.00
0.00
0.00
0.00
0.00
2.96
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.61
0.00
0.00
0.00
0.00
5.27
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.35
0.00
4.79
0.89
0.00
0.00
2.41
0.00
0.00
0.00
0.00
0.00
2.36
16.15
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.90
0.00
0.00
0.00
0.00
0.00
4.44
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
33.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
0.00
0.20
1.78
0.00
0.00
4.71
0.00
0.00
0.00
0.00
0.00
0.18
13.64
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2.63
0.00
0.00
0.00
0.00
0.00
0.26
0.00
0.00
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.00
0.00
0.00
64.43
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.15
1.33
0.00
0.00
6.13
0.00
0.00
0.00
0.00
0.00
0.14
0.77
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.24
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.00
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.00
0.00
27.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.00
0.10
0.00
0.00
0.00
1.14
0.00
0.00
0.00
0.00
0.00
0.09
0.80
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.26
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.24
0.00
0.00
0.00
0.00
57.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.05
0.00
0.00
0.00
3.54
0.00
0.00
0.00
0.00
0.00
0.05
0.84
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.19
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.00
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.00
0.00
0.00
47.79
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.06
0.00
0.00
0.00
2.35
0.00
0.00
0.00
0.00
0.00
0.06
0.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.57
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.00
-------
Appendix D-7: HFC-23 Emissions from HCFC-22 Production (Technology-Adoption)
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.34
0.00
0.00
0.00
0.00
0.00
0.14
1.22
2.07
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.49
34.98
0.00
0.00
0.66
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
3.58
3.20
0.00
0.00
3.34
64.54
2.35
77.16
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.41
0.00
0.00
0.00
0.00
0.00
0.43
2.35
2.84
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
6.39
27.03
0.00
0.00
0.67
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.43
5.27
3.18
0.00
0.00
1.41
69.23
4.76
84.27
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.08
0.00
0.00
0.00
0.00
0.00
0.00
3.67
2.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.53
29.79
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
33.26
2.97
0.00
0.00
1.08
49.93
8.39
95.62
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.89
0.00
0.00
0.00
0.00
0.00
0.00
4.60
1.78
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.68
17.21
0.00
0.00
0.23
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
64.43
3.64
0.00
0.00
0.89
22.39
10.73
102.07
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.69
0.00
0.00
0.00
0.00
0.00
0.00
4.36
0.06
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
9.34
0.00
0.00
0.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
27.01
0.72
0.00
0.00
0.69
10.75
5.50
44.67
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.50
0.00
0.00
0.00
0.00
0.00
0.00
5.81
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.07
8.43
0.00
0.00
0.29
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
57.12
1.73
0.00
0.00
0.50
9.59
9.35
78.29
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.32
0.00
0.00
0.00
0.00
0.00
0.00
4.92
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.08
8.53
0.00
0.00
0.25
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
47.79
1.03
0.00
0.00
0.32
9.78
7.27
66.19
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-7b : HFC-23 Emissions from HCFC-22 Production (No-Action)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.28
0.00
0.00
0.00
0.00
3.58
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
5.92
0.00
2.64
0.54
0.00
0.00
1.13
0.00
0.00
0.00
0.00
0.00
2.09
9.85
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.06
0.00
0.00
0.00
0.00
0.00
2.96
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.61
0.00
0.00
0.00
0.00
5.27
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.35
0.00
4.79
0.89
0.00
0.00
2.41
0.00
0.00
0.00
0.00
0.00
2.36
16.15
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.90
0.00
0.00
0.00
0.00
0.00
4.44
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
33.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
0.00
0.20
1.78
0.00
0.00
4.71
0.00
0.00
0.00
0.00
0.00
0.18
13.64
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2.63
0.00
0.00
0.00
0.00
0.00
0.26
0.00
0.00
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
0.00
0.00
0.00
64.43
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.15
1.33
0.00
0.00
6.13
0.00
0.00
0.00
0.00
0.00
0.14
0.77
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.24
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.00
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.00
0.00
70.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.00
0.10
0.00
0.00
0.00
7.98
0.00
0.00
0.00
0.00
0.00
0.09
0.80
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.24
0.00
0.00
0.00
0.00
100.31
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.05
0.00
0.00
0.00
10.38
0.00
0.00
0.00
0.00
0.00
0.05
0.84
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.94
0.00
0.00
0.00
0.00
0.00
0.07
0.00
0.00
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.00
0.00
0.00
90.98
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.06
0.00
0.00
0.00
9.18
0.00
0.00
0.00
0.00
0.00
0.06
0.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.32
0.00
0.00
0.00
0.00
0.00
0.08
0.00
0.00
-------
Appendix D-7b : HFC-23 Emissions from HCFC-22 Production (No-Action)
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.34
0.00
0.00
0.00
0.00
0.00
0.14
1.22
2.07
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.49
34.98
0.00
0.00
0.66
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
3.58
3.20
0.00
0.00
3.34
64.54
2.35
77.16
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.41
0.00
0.00
0.00
0.00
0.00
0.43
2.35
2.84
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
6.39
27.03
0.00
0.00
0.67
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.43
5.27
3.18
0.00
0.00
1.41
69.23
4.76
84.27
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.08
0.00
0.00
0.00
0.00
0.00
0.00
3.67
2.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.53
29.79
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
33.26
2.97
0.00
0.00
1.08
49.93
8.39
95.62
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.89
0.00
0.00
0.00
0.00
0.00
0.00
4.60
1.78
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.68
34.85
0.00
0.00
0.23
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
64.43
3.64
0.00
0.00
0.89
40.03
10.73
119.72
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.69
0.00
0.00
0.00
0.00
0.00
0.00
5.76
1.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
26.32
0.00
0.00
0.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
70.20
4.46
0.00
0.00
0.69
28.87
13.73
117.96
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.50
0.00
0.00
0.00
0.00
0.00
0.00
7.21
0.63
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.07
23.75
0.00
0.00
0.29
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
100.31
5.48
0.00
0.00
0.50
25.51
17.58
149.39
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.32
0.00
0.00
0.00
0.00
0.00
0.00
6.32
0.71
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.08
24.04
0.00
0.00
0.25
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
90.98
4.78
0.00
0.00
0.32
25.97
15.50
137.55
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-8: SF6 Emissions from Electric Power Systems (Technology-Adoption)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.01
0.03
0.09
0.02
0.27
0.08
0.04
0.01
0.08
0.09
0.00
0.45
0.08
0.00
0.85
0.04
1.12
0.07
0.02
0.03
0.01
0.06
0.01
0.08
0.00
0.00
0.05
0.53
0.02
0.20
0.05
0.03
0.00
0.50
0.08
0.10
0.04
0.05
0.03
0.44
1.43
0.01
0.18
0.04
0.02
0.00
0.00
0.00
0.01
0.01
0.01
0.21
0.02
0.00
0.01
0.00
0.00
0.16
0.06
1995
0.01
0.03
0.10
0.01
0.25
0.06
0.02
0.02
0.05
0.08
0.00
0.46
0.06
0.00
0.75
0.04
1.47
0.06
0.02
0.03
0.01
0.05
0.01
0.08
0.00
0.00
0.04
0.44
0.01
0.17
0.04
0.03
0.00
0.60
0.09
0.12
0.04
0.04
0.04
0.37
1.43
0.01
0.10
0.03
0.02
0.00
0.00
0.00
0.01
0.01
0.01
0.22
0.01
0.00
0.00
0.01
0.00
0.13
0.05
2000
0.01
0.03
0.12
0.01
0.26
0.05
0.02
0.02
0.04
0.06
0.01
0.52
0.04
0.00
0.73
0.05
1.78
0.06
0.02
0.04
0.01
0.05
0.01
0.10
0.00
0.00
0.03
0.37
0.01
0.18
0.04
0.04
0.00
0.71
0.12
0.15
0.04
0.03
0.05
0.31
0.52
0.01
0.07
0.04
0.02
0.00
0.00
0.00
0.01
0.00
0.01
0.26
0.01
0.00
0.00
0.01
0.00
0.11
0.05
2005
0.02
0.10
0.31
0.02
0.71
0.04
0.07
0.06
0.11
0.05
0.02
1.37
0.11
0.00
1.85
0.17
6.79
0.16
0.06
0.05
0.02
0.04
0.04
0.29
0.00
0.00
0.03
0.30
0.01
0.21
0.03
0.04
0.00
2.00
0.39
0.49
0.05
0.03
0.15
0.25
0.30
0.03
0.07
0.13
0.03
0.01
0.00
0.00
0.01
0.00
0.02
0.77
0.01
0.00
0.01
0.03
0.01
0.09
0.13
2010
0.02
0.11
0.38
0.02
0.71
0.03
0.07
0.07
0.11
0.04
0.02
1.63
0.11
0.00
1.85
0.20
9.00
0.20
0.06
0.04
0.02
0.03
0.05
0.35
0.00
0.00
0.02
0.24
0.03
0.24
0.02
0.03
0.00
2.42
0.47
0.58
0.06
0.02
0.18
0.20
0.30
0.04
0.19
0.16
0.03
0.02
0.00
0.00
0.01
0.00
0.02
1.01
0.01
0.00
0.01
0.03
0.01
0.07
0.13
2015
0.02
0.14
0.48
0.02
0.71
0.03
0.07
0.09
0.11
0.03
0.02
1.99
0.11
0.00
1.85
0.26
11.69
0.25
0.06
0.03
0.02
0.02
0.06
0.41
0.00
0.00
0.02
0.19
0.03
0.21
0.02
0.03
0.00
2.92
0.55
0.68
0.07
0.02
0.21
0.16
0.30
0.04
0.19
0.18
0.03
0.02
0.00
0.00
0.01
0.00
0.02
1.27
0.01
0.00
0.02
0.04
0.01
0.05
0.13
2020
0.02
0.16
0.59
0.02
0.71
0.02
0.07
0.10
0.11
0.03
0.02
2.42
0.11
0.00
1.85
0.31
14.94
0.30
0.06
0.03
0.03
0.02
0.07
0.47
0.00
0.00
0.01
0.17
0.03
0.18
0.01
0.03
0.00
3.46
0.63
0.79
0.08
0.01
0.24
0.14
0.30
0.05
0.19
0.21
0.03
0.02
0.00
0.00
0.00
0.00
0.02
1.57
0.01
0.00
0.02
0.04
0.01
0.05
0.13
-------
Appendix D-8: SF6 Emissions from Electric Power Systems (Technology-Adoption)
MTCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.02
0.07
0.10
0.07
0.02
0.04
0.09
0.05
0.13
1.87
0.12
0.00
0.03
0.01
0.01
0.28
0.18
0.24
0.09
0.15
0.03
0.08
0.10
0.02
0.00
0.46
0.03
0.58
28.89
0.01
0.09
0.10
0.02
0.12
0.08
0.05
0.10
0.01
0.22
0.53
1.22
1.08
0.42
0.13
2.85
34.92
1.22
42.36
1995
0.02
0.04
0.08
0.08
0.02
0.05
0.09
0.04
0.09
1.19
0.15
0.00
0.03
0.01
0.01
0.26
0.28
0.20
0.07
0.12
0.02
0.11
0.12
0.01
0.00
0.27
0.04
0.48
21.13
0.01
0.07
0.11
0.02
0.11
0.07
0.06
0.06
0.01
0.26
0.50
1.54
1.12
0.49
0.09
1.79
26.51
1.52
33.55
2000
0.02
0.03
0.06
0.08
0.03
0.06
0.11
0.03
0.07
1.09
0.16
0.00
0.04
0.01
0.01
0.26
0.33
0.17
0.06
0.09
0.02
0.12
0.16
0.01
0.00
0.21
0.05
0.41
14.96
0.01
0.06
0.11
0.03
0.11
0.09
0.08
0.05
0.01
0.32
0.52
1.85
1.27
0.59
0.09
1.57
19.10
1.81
26.78
2005
0.06
0.07
0.03
0.27
0.08
0.17
0.13
0.03
0.16
2.88
0.50
0.00
0.11
0.01
0.01
0.76
1.18
0.14
0.05
0.05
0.05
0.41
0.44
0.03
0.00
0.54
0.14
0.33
13.94
0.03
0.17
0.31
0.14
0.31
0.27
0.25
0.17
0.01
0.95
1.52
7.03
3.52
1.75
0.26
4.00
19.64
5.59
43.30
2010
0.07
0.08
0.03
0.33
0.10
0.21
0.11
0.02
0.16
2.88
0.60
0.00
0.11
0.01
0.01
0.91
1.39
0.11
0.04
0.04
0.05
0.50
0.44
0.03
0.00
0.54
0.17
0.26
12.83
0.04
0.17
0.37
0.17
0.37
0.33
0.30
0.17
0.01
1.15
1.82
9.28
4.33
2.08
0.26
4.14
18.18
6.69
46.77
2015
0.08
0.09
0.03
0.39
0.12
0.24
0.09
0.02
0.16
2.88
0.70
0.00
0.11
0.01
0.01
1.10
1.59
0.09
0.03
0.04
0.05
0.58
0.44
0.03
0.00
0.54
0.20
0.21
12.29
0.05
0.17
0.47
0.20
0.45
0.42
0.35
0.17
0.01
1.35
2.20
12.02
5.39
2.44
0.26
4.14
17.36
7.87
51.69
2020
0.09
0.11
0.03
0.45
0.15
0.28
0.08
0.01
0.16
2.88
0.81
0.00
0.11
0.01
0.01
1.29
1.77
0.08
0.03
0.04
0.05
0.67
0.44
0.03
0.00
0.54
0.23
0.18
11.81
0.05
0.17
0.57
0.23
0.52
0.51
0.41
0.17
0.01
1.56
2.56
15.32
6.57
2.83
0.26
4.14
16.72
9.08
57.48
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-8b : SF6 Emissions from Electric Power Systems (No-Action)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.01
0.03
0.09
0.02
0.27
0.08
0.04
0.01
0.08
0.09
0.00
0.45
0.08
0.00
0.85
0.04
1.12
0.07
0.02
0.03
0.01
0.06
0.01
0.08
0.00
0.00
0.05
0.53
0.02
0.20
0.05
0.03
0.00
0.50
0.08
0.10
0.04
0.05
0.03
0.44
1.43
0.01
0.18
0.04
0.02
0.00
0.00
0.00
0.01
0.01
0.01
0.21
0.02
0.00
0.01
0.00
0.00
0.16
0.06
1995
0.01
0.03
0.10
0.01
0.25
0.06
0.02
0.02
0.05
0.08
0.00
0.46
0.06
0.00
0.75
0.04
1.47
0.06
0.02
0.03
0.01
0.05
0.01
0.08
0.00
0.00
0.04
0.44
0.01
0.17
0.04
0.03
0.00
0.60
0.09
0.12
0.04
0.04
0.04
0.37
1.43
0.01
0.10
0.03
0.02
0.00
0.00
0.00
0.01
0.01
0.01
0.22
0.01
0.00
0.00
0.01
0.00
0.13
0.05
2000
0.01
0.03
0.12
0.01
0.26
0.05
0.02
0.02
0.04
0.06
0.01
0.52
0.04
0.00
0.73
0.05
1.78
0.06
0.02
0.04
0.01
0.05
0.01
0.10
0.00
0.00
0.03
0.37
0.01
0.18
0.04
0.04
0.00
0.71
0.12
0.15
0.04
0.03
0.05
0.31
0.52
0.01
0.07
0.04
0.02
0.00
0.00
0.00
0.01
0.00
0.01
0.26
0.01
0.00
0.00
0.01
0.00
0.11
0.05
2005
0.02
0.10
0.31
0.02
0.71
0.05
0.07
0.06
0.11
0.06
0.02
1.37
0.11
0.00
1.85
0.17
6.79
0.16
0.06
0.04
0.02
0.04
0.04
0.29
0.00
0.00
0.03
0.33
0.01
0.24
0.03
0.04
0.00
2.00
0.39
0.49
0.05
0.03
0.15
0.27
0.33
0.03
0.07
0.13
0.03
0.01
0.01
0.00
0.01
0.00
0.02
0.77
0.01
0.00
0.01
0.03
0.01
0.10
0.13
2010
0.02
0.11
0.38
0.02
0.71
0.05
0.07
0.07
0.11
0.06
0.02
1.63
0.11
0.00
1.85
0.20
9.00
0.20
0.06
0.05
0.02
0.04
0.05
0.35
0.00
0.00
0.03
0.33
0.03
0.34
0.03
0.05
0.00
2.42
0.47
0.58
0.06
0.03
0.18
0.28
0.42
0.04
0.19
0.16
0.03
0.02
0.01
0.00
0.01
0.00
0.02
1.01
0.01
0.00
0.01
0.03
0.01
0.10
0.13
2015
0.02
0.14
0.48
0.02
0.71
0.05
0.07
0.09
0.11
0.06
0.02
1.99
0.11
0.00
1.85
0.26
11.69
0.25
0.06
0.05
0.02
0.04
0.06
0.41
0.00
0.00
0.03
0.33
0.03
0.34
0.03
0.05
0.00
2.92
0.55
0.68
0.07
0.03
0.21
0.28
0.42
0.04
0.19
0.18
0.03
0.02
0.01
0.00
0.01
0.00
0.02
1.27
0.01
0.00
0.02
0.04
0.01
0.10
0.13
2020
0.02
0.16
0.59
0.02
0.71
0.05
0.07
0.10
0.11
0.06
0.02
2.42
0.11
0.00
1.85
0.31
14.94
0.30
0.06
0.05
0.03
0.04
0.07
0.47
0.00
0.00
0.03
0.33
0.03
0.34
0.03
0.05
0.00
3.46
0.63
0.79
0.08
0.03
0.24
0.28
0.42
0.05
0.19
0.21
0.03
0.02
0.01
0.00
0.01
0.00
0.02
1.57
0.01
0.00
0.02
0.04
0.01
0.10
0.13
-------
Appendix D-8b : SF6 Emissions from Electric Power Systems (No-Action)
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.02
0.07
0.10
0.07
0.02
0.04
0.09
0.05
0.13
1.87
0.12
0.00
0.03
0.01
0.01
0.28
0.18
0.24
0.09
0.15
0.03
0.08
0.10
0.02
0.00
0.46
0.03
0.58
28.89
0.01
0.09
0.10
0.02
0.12
0.08
0.05
0.10
0.01
0.22
0.53
1.22
1.08
0.42
0.13
2.85
34.92
1.22
42.36
1995
0.02
0.04
0.08
0.08
0.02
0.05
0.09
0.04
0.09
1.19
0.15
0.00
0.03
0.01
0.01
0.26
0.28
0.20
0.07
0.12
0.02
0.11
0.12
0.01
0.00
0.27
0.04
0.48
21.13
0.01
0.07
0.11
0.02
0.11
0.07
0.06
0.06
0.01
0.26
0.50
1.54
1.12
0.49
0.09
1.79
26.51
1.52
33.55
2000
0.02
0.03
0.06
0.08
0.03
0.06
0.11
0.03
0.07
1.09
0.16
0.00
0.04
0.01
0.01
0.26
0.33
0.17
0.06
0.09
0.02
0.12
0.16
0.01
0.00
0.21
0.05
0.41
14.96
0.01
0.06
0.11
0.03
0.11
0.09
0.08
0.05
0.01
0.32
0.52
1.85
1.27
0.59
0.09
1.57
19.10
1.81
26.78
2005
0.06
0.07
0.04
0.27
0.08
0.17
0.13
0.03
0.16
2.88
0.50
0.00
0.11
0.01
0.01
0.76
1.18
0.15
0.06
0.06
0.05
0.41
0.44
0.03
0.00
0.54
0.14
0.36
17.01
0.03
0.17
0.31
0.14
0.31
0.27
0.25
0.17
0.01
0.95
1.52
7.03
3.52
1.75
0.26
4.00
22.91
5.59
46.57
2010
0.07
0.08
0.04
0.33
0.10
0.21
0.15
0.03
0.16
2.88
0.60
0.00
0.11
0.02
0.02
0.91
1.39
0.15
0.06
0.05
0.05
0.50
0.44
0.03
0.00
0.54
0.17
0.36
17.62
0.04
0.17
0.37
0.17
0.37
0.33
0.30
0.17
0.01
1.15
1.82
9.28
4.33
2.08
0.26
4.14
23.73
6.69
52.32
2015
0.08
0.09
0.04
0.39
0.12
0.24
0.15
0.03
0.16
2.88
0.70
0.00
0.11
0.02
0.02
1.10
1.59
0.15
0.06
0.05
0.05
0.58
0.44
0.03
0.00
0.54
0.20
0.36
18.24
0.05
0.17
0.47
0.20
0.45
0.42
0.35
0.17
0.01
1.35
2.20
12.02
5.39
2.44
0.26
4.14
24.35
7.87
58.68
2020
0.09
0.11
0.04
0.45
0.15
0.28
0.15
0.03
0.16
2.88
0.81
0.00
0.11
0.02
0.02
1.29
1.77
0.15
0.06
0.05
0.05
0.67
0.44
0.03
0.00
0.54
0.23
0.36
18.89
0.05
0.17
0.57
0.23
0.52
0.50
0.41
0.17
0.01
1.56
2.56
15.32
6.57
2.83
0.26
4.14
25.00
9.08
65.76
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-9: PFC Emissions from Primary Aluminum Production (Technology-Adoption)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.63
0.00
4.76
0.36
0.27
0.00
0.00
0.00
0.00
5.30
0.00
0.00
8.07
0.00
2.93
0.00
0.29
0.00
0.00
0.00
0.00
0.46
0.00
0.00
0.00
1.59
0.00
2.23
0.30
0.13
0.19
0.81
0.32
0.14
0.00
0.00
0.00
2.84
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.00
5.32
1.10
0.00
1995
0.00
0.00
0.30
0.00
2.72
0.18
0.18
0.00
0.00
0.00
0.00
6.40
0.00
0.00
5.70
0.00
2.56
0.00
0.09
0.00
0.00
0.00
0.00
0.22
0.00
0.00
0.00
0.88
0.00
0.66
0.19
0.06
0.12
0.63
0.19
0.07
0.00
0.00
0.00
1.35
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
2.53
0.47
0.00
2000
0.00
0.00
0.25
0.00
3.00
0.16
0.13
0.00
0.00
0.00
0.00
3.89
0.00
0.00
5.06
0.00
5.21
0.00
0.11
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.00
0.89
0.00
0.69
0.21
0.06
0.13
0.75
0.22
0.07
0.00
0.00
0.00
1.24
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
2.32
0.47
0.00
2005
0.00
0.00
0.26
0.00
2.15
0.17
0.09
0.00
0.00
0.00
0.00
2.31
0.00
0.00
2.70
0.00
9.18
0.00
0.07
0.00
0.00
0.00
0.00
0.57
0.00
0.00
0.00
0.61
0.00
1.10
0.21
0.06
0.14
1.69
0.67
0.22
0.00
0.00
0.00
0.30
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.45
0.39
0.00
2010
0.00
0.00
0.29
0.00
2.11
0.08
0.05
0.00
0.00
0.00
0.00
2.41
0.00
0.00
2.51
0.00
6.48
0.00
0.04
0.00
0.00
0.00
0.00
0.42
0.00
0.00
0.00
0.61
0.00
1.01
0.21
0.03
0.30
1.17
0.57
0.26
0.00
0.00
0.00
0.24
0.08
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.42
0.36
0.00
2015
0.00
0.00
0.32
0.00
2.11
0.08
0.05
0.00
0.00
0.00
0.00
2.77
0.00
0.00
2.64
0.00
6.62
0.00
0.04
0.00
0.00
0.00
0.00
0.55
0.00
0.00
0.00
0.59
0.00
1.03
0.21
0.03
0.30
1.22
0.59
0.33
0.00
0.00
0.00
0.24
0.09
0.00
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.42
0.36
0.00
2020
0.00
0.00
0.32
0.00
2.11
0.08
0.05
0.00
0.00
0.00
0.00
3.20
0.00
0.00
3.33
0.00
6.75
0.00
0.04
0.00
0.00
0.00
0.00
0.69
0.00
0.00
0.00
0.59
0.00
1.06
0.20
0.03
0.29
1.26
0.61
0.42
0.00
0.00
0.00
0.24
0.11
0.00
0.00
0.19
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.42
0.36
0.00
-------
Appendix D-9: PFC Emissions from Primary Aluminum Production (Technology-Adoption)
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
3.84
0.00
0.00
0.00
0.20
0.00
3.48
15.40
0.00
0.00
0.00
0.14
0.09
0.89
0.00
4.45
0.33
0.12
4.25
0.00
0.23
0.00
0.00
0.43
0.34
0.64
18.34
0.00
0.00
2.27
0.00
1.04
0.00
0.36
2.99
0.00
0.00
2.38
2.93
8.34
0.83
3.27
20.35
58.78
1.12
98.01
1995
0.00
2.03
0.00
0.00
0.00
0.06
0.00
1.12
10.03
0.00
0.00
0.00
0.09
0.07
0.72
0.00
2.13
0.17
0.02
2.70
0.00
0.11
0.00
0.00
0.29
0.15
0.41
11.83
0.00
0.00
1.08
0.00
0.73
0.00
0.22
0.95
0.00
0.00
1.67
2.56
7.84
0.44
1.04
13.20
32.95
0.82
60.51
2000
0.00
1.97
0.00
0.00
0.00
0.07
0.00
1.33
7.46
0.00
0.00
0.00
0.13
0.09
3.24
0.00
1.95
0.16
0.02
1.96
0.00
0.10
0.00
0.00
0.22
0.11
0.44
8.95
0.00
0.00
0.92
0.00
2.15
0.00
0.17
1.14
0.00
0.00
5.59
5.21
5.12
0.35
1.24
9.77
29.51
0.97
57.78
2005
0.00
1.54
0.00
0.00
0.00
0.05
0.00
0.19
4.93
0.00
0.00
0.00
0.19
0.13
1.81
0.00
0.64
0.16
0.07
0.62
0.00
0.11
0.00
0.00
0.25
0.72
0.45
4.69
0.00
0.00
0.94
0.00
1.17
0.00
0.66
0.24
0.00
0.00
3.55
9.18
3.57
1.60
0.31
5.90
16.60
2.37
43.07
2010
0.00
1.15
0.00
0.00
0.00
0.03
0.00
0.18
3.34
0.00
0.00
0.00
0.19
0.13
1.77
0.00
0.44
0.09
0.06
0.62
0.00
0.05
0.00
0.00
0.20
1.27
0.44
4.56
0.00
0.00
1.06
0.00
1.83
0.00
1.54
0.19
0.00
0.06
4.02
6.48
3.82
3.18
0.24
4.21
15.29
1.81
39.06
2015
0.00
1.14
0.00
0.00
0.00
0.03
0.00
0.18
3.33
0.00
0.00
0.00
0.20
0.14
2.14
0.00
0.45
0.09
0.06
0.63
0.00
0.05
0.00
0.00
0.20
1.66
0.43
4.50
0.00
0.00
1.15
0.00
2.15
0.00
2.03
0.19
0.00
0.06
4.84
6.62
4.31
4.18
0.23
4.21
15.38
1.87
41.64
2020
0.00
1.13
0.00
0.00
0.00
0.03
0.00
0.18
3.32
0.00
0.00
0.00
0.20
0.14
2.51
0.00
0.45
0.09
0.07
0.64
0.00
0.05
0.00
0.00
0.21
2.05
0.42
4.45
0.00
0.00
1.17
0.00
2.47
0.00
2.48
0.19
0.00
0.06
5.67
6.75
4.75
5.15
0.23
4.22
16.03
1.94
44.73
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-9b : PFC Emissions from Primary Aluminum Production (No-Action)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.63
0.00
4.76
0.36
0.27
0.00
0.00
0.00
0.00
5.30
0.00
0.00
8.07
0.00
2.93
0.00
0.29
0.00
0.00
0.00
0.00
0.46
0.00
0.00
0.00
1.59
0.00
2.23
0.30
0.13
0.19
0.81
0.32
0.14
0.00
0.00
0.00
2.84
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.00
5.32
1.10
0.00
1995
0.00
0.00
0.30
0.00
2.72
0.18
0.18
0.00
0.00
0.00
0.00
6.40
0.00
0.00
5.70
0.00
2.56
0.00
0.09
0.00
0.00
0.00
0.00
0.22
0.00
0.00
0.00
0.88
0.00
0.66
0.19
0.06
0.12
0.63
0.19
0.07
0.00
0.00
0.00
1.35
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
2.53
0.47
0.00
2000
0.00
0.00
0.25
0.00
3.00
0.16
0.13
0.00
0.00
0.00
0.00
3.89
0.00
0.00
5.06
0.00
5.21
0.00
0.11
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.00
0.89
0.00
0.69
0.21
0.06
0.13
0.75
0.22
0.07
0.00
0.00
0.00
1.24
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
2.32
0.47
0.00
2005
0.00
0.00
0.31
0.00
2.34
0.27
0.14
0.00
0.00
0.00
0.00
2.94
0.00
0.00
4.11
0.00
13.49
0.00
0.11
0.00
0.00
0.00
0.00
0.87
0.00
0.00
0.00
0.64
0.00
1.23
0.22
0.10
0.14
2.39
0.80
0.27
0.00
0.00
0.00
0.38
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.53
0.46
0.00
2010
0.00
0.00
0.37
0.00
2.34
0.24
0.14
0.00
0.00
0.00
0.00
3.47
0.00
0.00
4.42
0.00
13.16
0.00
0.11
0.00
0.00
0.00
0.00
1.01
0.00
0.00
0.00
0.64
0.00
1.16
0.22
0.09
0.32
2.21
0.73
0.32
0.00
0.00
0.00
0.37
0.15
0.00
0.00
0.12
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.53
0.46
0.00
2015
0.00
0.00
0.41
0.00
2.34
0.24
0.13
0.00
0.00
0.00
0.00
4.06
0.00
0.00
4.67
0.00
13.32
0.00
0.11
0.00
0.00
0.00
0.00
1.30
0.00
0.00
0.00
0.63
0.00
1.20
0.22
0.09
0.31
2.29
0.76
0.41
0.00
0.00
0.00
0.37
0.18
0.00
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.53
0.46
0.00
2020
0.00
0.00
0.41
0.00
2.34
0.24
0.13
0.00
0.00
0.00
0.00
4.72
0.00
0.00
4.92
0.00
13.49
0.00
0.11
0.00
0.00
0.00
0.00
1.65
0.00
0.00
0.00
0.62
0.00
1.23
0.21
0.09
0.31
2.36
0.78
0.52
0.00
0.00
0.00
0.37
0.20
0.00
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.53
0.46
0.00
-------
Appendix D-9b : PFC Emissions from Primary Aluminum Production (No-Action)
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
3.84
0.00
0.00
0.00
0.20
0.00
3.48
15.40
0.00
0.00
0.00
0.14
0.09
0.89
0.00
4.45
0.33
0.12
4.25
0.00
0.23
0.00
0.00
0.43
0.34
0.64
18.34
0.00
0.00
2.27
0.00
1.04
0.00
0.36
2.99
0.00
0.00
2.38
2.93
8.34
0.83
3.27
20.35
58.78
1.12
98.01
1995
0.00
2.03
0.00
0.00
0.00
0.06
0.00
1.12
10.03
0.00
0.00
0.00
0.09
0.07
0.72
0.00
2.13
0.17
0.02
2.70
0.00
0.11
0.00
0.00
0.29
0.15
0.41
11.83
0.00
0.00
1.08
0.00
0.73
0.00
0.22
0.95
0.00
0.00
1.67
2.56
7.84
0.44
1.04
13.20
32.95
0.82
60.51
2000
0.00
1.97
0.00
0.00
0.00
0.07
0.00
1.33
7.46
0.00
0.00
0.00
0.13
0.09
3.24
0.00
1.95
0.16
0.02
1.96
0.00
0.10
0.00
0.00
0.22
0.11
0.44
8.95
0.00
0.00
0.92
0.00
2.15
0.00
0.17
1.14
0.00
0.00
5.59
5.21
5.12
0.35
1.24
9.77
29.51
0.97
57.78
2005
0.00
2.01
0.00
0.00
0.00
0.08
0.00
0.23
7.45
0.00
0.00
0.00
0.20
0.14
2.17
0.00
0.89
0.24
0.09
0.68
0.00
0.17
0.00
0.00
0.36
0.80
0.47
14.67
0.00
0.00
1.12
0.00
1.61
0.00
0.69
0.33
0.00
0.00
4.65
13.49
4.43
1.76
0.44
8.63
29.76
3.19
66.36
2010
0.00
1.89
0.00
0.00
0.00
0.08
0.00
0.23
7.40
0.00
0.00
0.00
0.20
0.14
2.46
0.00
0.83
0.22
0.08
0.69
0.00
0.15
0.00
0.00
0.38
1.41
0.47
14.67
0.00
0.00
1.35
0.00
2.54
0.00
1.60
0.32
0.00
0.06
6.01
13.16
5.25
3.46
0.43
8.62
29.90
3.01
69.84
2015
0.00
1.89
0.00
0.00
0.00
0.08
0.00
0.23
7.35
0.00
0.00
0.00
0.21
0.14
2.98
0.00
0.84
0.22
0.08
0.71
0.00
0.15
0.00
0.00
0.39
1.84
0.47
14.67
0.00
0.00
1.47
0.00
3.00
0.00
2.11
0.32
0.00
0.07
7.28
13.32
6.00
4.53
0.43
8.58
30.21
3.11
73.47
2020
0.00
1.89
0.00
0.00
0.00
0.07
0.00
0.23
7.30
0.00
0.00
0.00
0.21
0.15
3.51
0.00
0.84
0.22
0.09
0.72
0.00
0.16
0.00
0.00
0.41
2.28
0.46
14.67
0.00
0.00
1.49
0.00
3.46
0.00
2.58
0.32
0.00
0.07
8.62
13.49
6.69
5.59
0.42
8.55
30.51
3.20
77.07
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-10: HFC, RFC, SF6 Emissions from Semiconductor Manufacturing (Technology-Adoption)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.01
0.04
0.00
0.00
0.00
0.01
0.00
0.04
0.00
0.00
0.14
0.00
0.25
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.30
0.00
0.01
0.00
0.21
0.00
0.00
0.00
0.03
0.19
0.08
2.66
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.02
0.06
0.00
0.00
0.00
0.01
0.00
0.06
0.00
0.00
0.22
0.00
0.38
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.46
0.00
0.02
0.00
0.33
0.00
0.00
0.00
0.05
0.29
0.12
4.10
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.03
0.07
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.32
0.00
0.76
0.00
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.37
0.00
0.54
0.00
0.02
0.00
0.23
0.00
0.00
0.00
0.09
0.58
0.23
7.37
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
2005
0.00
0.00
0.00
0.01
0.03
0.06
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.13
0.00
3.10
0.00
0.00
0.61
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.28
0.00
0.54
0.00
0.02
0.00
0.44
0.00
0.00
0.00
0.14
1.00
0.18
4.57
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.00
0.00
2010
0.00
0.00
0.00
0.01
0.04
0.04
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.19
0.00
10.68
0.00
0.00
0.86
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.38
0.00
0.03
0.00
0.61
0.00
0.00
0.00
0.09
1.39
0.13
3.69
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
2015
0.00
0.00
0.00
0.01
0.03
0.04
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.16
0.00
8.90
0.00
0.00
0.72
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.38
0.00
0.02
0.00
0.51
0.00
0.00
0.00
0.09
1.16
0.13
3.69
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
2020
0.00
0.00
0.00
0.01
0.03
0.04
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.13
0.00
7.12
0.00
0.00
0.57
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.38
0.00
0.02
0.00
0.41
0.00
0.00
0.00
0.09
0.93
0.13
3.69
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
-------
Appendix D-10: HFC, RFC, SF6 Emissions from Semiconductor Manufacturing (Technology-Adoption)
MTCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.00
0.34
0.00
0.00
0.03
1.25
0.01
0.02
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
2.93
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.48
0.03
0.25
0.08
0.19
0.00
0.19
6.65
2.28
9.67
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.53
0.00
0.00
0.05
1.92
0.02
0.03
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.29
5.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.74
0.05
0.38
0.12
0.29
0.00
0.30
10.73
3.51
15.38
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.00
0.61
0.00
0.00
0.10
3.34
0.02
0.01
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.40
6.39
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.78
0.10
0.76
0.06
0.58
0.00
0.78
16.21
8.96
27.45
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.03
0.00
0.00
1.59
0.01
0.00
0.10
3.71
0.00
0.01
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.54
0.37
5.30
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
5.88
0.10
3.10
0.00
1.54
0.00
1.05
12.39
11.62
29.79
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.45
0.00
0.00
3.52
0.01
0.00
0.14
2.31
0.00
0.01
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.75
0.26
5.49
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.54
0.14
10.68
0.00
2.15
0.00
1.45
11.50
10.98
36.90
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.20
0.00
0.00
2.93
0.01
0.00
0.11
2.31
0.00
0.01
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.63
0.26
4.44
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.18
0.11
8.90
0.00
1.79
0.00
1.21
10.26
9.94
32.21
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.96
0.00
0.00
2.34
0.01
0.00
0.09
2.31
0.00
0.01
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.50
0.26
4.14
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.82
0.09
7.12
0.00
1.43
0.00
0.97
9.78
8.89
28.28
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-10b : HFC, RFC, SF6 Emissions from Semiconductor Manufacturing (No-Action)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
Nigeria
1990
0.00
0.00
0.00
0.00
0.01
0.04
0.00
0.00
0.00
0.01
0.00
0.04
0.00
0.00
0.14
0.00
0.25
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.30
0.00
0.01
0.00
0.21
0.00
0.00
0.00
0.03
0.19
0.08
2.66
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.02
0.06
0.00
0.00
0.00
0.01
0.00
0.06
0.00
0.00
0.22
0.00
0.38
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.21
0.00
0.46
0.00
0.02
0.00
0.33
0.00
0.00
0.00
0.05
0.29
0.12
4.10
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.03
0.07
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.32
0.00
0.76
0.00
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.37
0.00
0.54
0.00
0.02
0.00
0.23
0.00
0.00
0.00
0.09
0.58
0.23
7.37
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.06
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
2005
0.00
0.00
0.00
0.01
0.03
0.08
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.13
0.00
3.10
0.00
0.00
0.61
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.39
0.00
0.76
0.00
0.02
0.00
0.44
0.00
0.00
0.00
0.19
1.00
0.26
6.46
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
0.00
2010
0.00
0.00
0.00
0.03
0.04
0.18
0.00
0.00
0.00
0.03
0.00
0.00
0.01
0.00
0.19
0.00
10.68
0.00
0.00
0.86
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.88
0.00
1.69
0.00
0.03
0.00
0.61
0.00
0.00
0.00
0.43
1.39
0.57
10.99
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.29
0.00
0.00
2015
0.00
0.00
0.00
0.04
0.05
0.23
0.00
0.00
0.00
0.04
0.00
0.00
0.01
0.00
0.24
0.00
19.98
0.00
0.00
1.09
0.00
0.00
0.00
0.00
0.00
0.00
0.01
1.11
0.00
2.15
0.00
0.03
0.00
0.78
0.00
0.00
0.00
0.54
1.76
0.73
12.98
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.36
0.00
0.00
2020
0.00
0.00
0.00
0.05
0.06
0.29
0.00
0.00
0.00
0.05
0.00
0.00
0.01
0.00
0.30
0.00
37.47
0.00
0.00
1.37
0.00
0.00
0.00
0.00
0.00
0.00
0.01
1.41
0.00
2.72
0.00
0.04
0.00
0.98
0.00
0.00
0.00
0.69
2.22
0.92
15.34
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.46
0.00
0.00
-------
Appendix D-10b : HFC, RFC, SF6 Emissions from Semiconductor Manufacturing (No-Action)
MtCO2eq
Country
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
0.00
0.00
0.34
0.00
0.00
0.03
1.25
0.01
0.02
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.19
2.93
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.48
0.03
0.25
0.08
0.19
0.00
0.19
6.65
2.28
9.67
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.53
0.00
0.00
0.05
1.92
0.02
0.03
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.29
5.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.74
0.05
0.38
0.12
0.29
0.00
0.30
10.73
3.51
15.38
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.78
0.00
0.00
0.61
0.00
0.00
0.10
3.34
0.02
0.01
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.40
6.39
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
4.78
0.10
0.76
0.06
0.58
0.00
0.78
16.21
8.96
27.45
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.03
0.00
0.00
1.59
0.02
0.00
0.10
7.18
0.00
0.01
0.05
0.00
0.00
0.00
0.00
0.00
0.00
0.54
0.52
12.64
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
11.18
0.10
3.10
0.00
1.54
0.00
1.05
22.32
20.39
48.49
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.45
0.00
0.00
3.52
0.04
0.00
0.14
13.42
0.00
0.03
0.11
0.00
0.00
0.00
0.00
0.00
0.00
0.75
1.17
28.21
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
21.45
0.14
10.68
0.00
2.15
0.00
1.48
45.74
39.01
99.19
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.83
0.00
0.00
4.87
0.05
0.00
0.17
18.76
0.00
0.03
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.95
1.48
35.44
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
41.10
0.17
19.98
0.00
2.71
0.00
1.87
56.72
65.51
146.96
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2.31
0.00
0.00
6.74
0.06
0.00
0.22
26.21
0.00
0.04
0.17
0.00
0.00
0.00
0.00
0.00
0.00
1.20
1.88
46.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
82.48
0.22
37.47
0.00
3.43
0.00
2.36
71.97
116.42
231 .86
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-11: SF6 Emissions from Magnesium Manufacturing (Technology-Adoption)
MTCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.81
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
1.09
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.44
0.00
0.00
1.53
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.35
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.89
0.00
0.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.24
0.00
0.00
1.74
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.35
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.79
0.06
0.22
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.00
0.38
0.00
1.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.30
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.56
0.05
0.04
0.00
0.17
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
0.00
0.08
0.00
1.65
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.08
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.01
0.01
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.01
0.00
2.47
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.01
0.00
3.74
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-------
Appendix D-11: SF6 Emissions from Magnesium Manufacturing (Technology-Adoption)
MTCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
1.52
0.00
0.00
0.00
0.00
0.00
0.00
1.80
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.63
0.00
0.01
5.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.30
0.00
0.00
2.47
9.13
0.00
11.95
1995
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.01
0.00
1.09
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.27
0.00
0.02
5.57
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16
0.44
0.00
0.00
1.63
9.47
0.00
11.69
2000
0.00
0.00
0.90
0.00
0.00
0.00
0.00
0.01
0.00
0.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
3.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
0.24
0.79
0.00
1.09
6.54
0.00
8.83
2005
0.00
0.00
0.15
0.00
0.00
0.00
0.00
0.01
0.00
0.60
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.00
0.01
2.82
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.05
0.00
1.11
0.20
0.56
0.00
0.89
3.81
0.05
6.63
2010
0.00
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.14
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
1.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
1.65
0.05
0.14
0.00
0.20
1.49
0.02
3.55
2015
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.84
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2.47
0.01
0.02
0.00
0.03
0.88
0.00
3.41
2020
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.99
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
3.74
0.01
0.02
0.00
0.03
1.04
0.00
4.84
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix D-11b : SF6 Emissions from Magnesium Manufacturing (No-Action)
MtCO2eq
Country
Albania
Algeria
Argentina
Armenia
Australia
Austria
Azerbaijan
Bangladesh
Belarus
Belgium
Bolivia
Brazil
Bulgaria
Cambodia
Canada
Chile
China
Colombia
Croatia
Czech Republic
Democratic Republic of Congo (Kinshasa)
Denmark
Ecuador
Egypt
Estonia
Ethiopia
Finland
France
Georgia
Germany
Greece
Hungary
Iceland
India
Indonesia
Iran
Iraq
Ireland
Israel
Italy
Japan
Jordan
Kazakhstan
Kuwait
Kyrgyzstan
Laos
Latvia
Liechtenstein
Lithuania
Luxembourg
Macedonia
Mexico
Moldova
Monaco
Mongolia
Myanmar
Nepal
Netherlands
New Zealand
1990
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.81
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
1.09
0.00
0.04
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1995
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.44
0.00
0.00
1.53
0.00
0.16
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.35
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.89
0.00
0.26
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2000
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.24
0.00
0.00
1.74
0.00
0.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.00
0.35
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.79
0.06
0.22
0.00
0.20
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2005
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.33
0.00
0.00
0.63
0.00
1.11
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.06
0.00
0.49
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.93
0.08
0.07
0.00
0.28
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2010
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.48
0.00
0.00
0.73
0.00
1.65
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.00
0.75
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.24
0.13
0.11
0.00
0.34
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2015
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.58
0.00
0.00
0.78
0.00
2.47
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.10
0.00
0.92
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.45
0.16
0.14
0.00
0.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
2020
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.71
0.00
0.00
0.83
0.00
3.74
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
1.13
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.70
0.19
0.18
0.00
0.41
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-------
Appendix D-11b : SF6 Emissions from Magnesium Manufacturing (No-Action)
MtCO2eq
Country
Nigeria
North Korea
Norway
Pakistan
Peru
Philippines
Poland
Portugal
Romania
Russian Federation
Saudi Arabia
Senegal
Singapore
Slovak Republic
Slovenia
South Africa
South Korea
Spain
Sweden
Switzerland
Tajikistan
Thailand
Turkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
Uzbekistan
Venezuela
Viet Nam
Rest of Africa
Rest of Latin America
Rest of Middle East
Rest of Non-EU Eastern Europe
Rest of OECD90 & EU
Rest of SE Asia
Africa
China/CPA
Latin America
Middle East
Non-EU Eastern Europe
Non-EU FSU
OECD90 & EU
SE Asia
World Totals
1990
0.00
0.00
1.52
0.00
0.00
0.00
0.00
0.00
0.00
1.80
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.63
0.00
0.01
5.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.30
0.00
0.00
2.47
9.13
0.00
11.95
1995
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.01
0.00
1.09
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.27
0.00
0.02
5.57
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.16
0.44
0.00
0.00
1.63
9.47
0.00
11.69
2000
0.00
0.00
0.90
0.00
0.00
0.00
0.00
0.01
0.00
0.89
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.01
3.18
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.18
0.24
0.79
0.00
1.09
6.54
0.00
8.83
2005
0.00
0.00
0.25
0.00
0.00
0.00
0.00
0.01
0.00
0.99
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.20
0.00
0.02
3.46
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.09
0.00
1.11
0.33
0.93
0.00
1.47
5.09
0.09
9.02
2010
0.00
0.00
0.37
0.00
0.00
0.00
0.00
0.01
0.00
1.22
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.23
0.00
0.03
4.57
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.13
0.00
1.65
0.48
1.24
0.00
1.80
6.80
0.13
12.10
2015
0.00
0.00
0.46
0.00
0.00
0.00
0.00
0.02
0.00
1.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.03
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.25
0.00
0.03
5.36
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.17
0.00
2.47
0.58
1.45
0.00
1.99
8.00
0.17
14.66
2020
0.00
0.00
0.56
0.00
0.00
0.00
0.00
0.02
0.00
1.53
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.04
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.28
0.00
0.04
6.35
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.22
0.00
3.74
0.71
1.70
0.00
2.22
9.49
0.22
18.07
Regional country groupings are defined in Table 1-4 and Appendix H.
-------
Appendix E-1: Data Sources and Methodologies for
Methane Emissions from Fugitives from Natural Gas and Oil Systems
Countries
Data Sources
Historical
Projected
Methodology/Adjustments
Albania, Bangladesh, Cambodia, Chile,
Congo (Kinshasa) DPRC, Ethiopia, Georgia,
Iraq, Jordan, Kuwait, Laos, Macedonia,
Moldova, Myanmar, Nepal, North Korea,
Singapore, Turkey, Uganda, United Arab
Emirates
Estimated using
IPCCTieM
EIA 2002
Reference Case
Used IPCC Tier 1 Methodology to develop historical estimates.
Used 1997 IPCC default emission factors. Obtained historic
natural gas and oil production and consumption data from 1980
through 2000 (EIA 2002). Missing historical estimates
extrapolated from changes in oil and natural gas production and
consumption (EIA 2002). Obtained EIA 'reference case'
projections of natural gas production and oil production and
consumption for the periods 2000-2005, 2005-2010, 2010-2015
and 2015-2020 from EIA 2002. Assumed growth rate for
natural gas consumption the same as natural gas production.
Created projections by applying the average annual
consumption or production growth rate to emissions attributed
to consumption or production.
Algeria, Armenia, Bolivia, Brazil, China,
Columbia, Dominican Republic, Ecuador,
Egypt, Indonesia, India, Iran, Israel,
Kyrgyzstan, Nigeria, Pakistan, Peru,
Philippines, South Africa, Saudia Arabia,
Senegal, Tajikistan, Thailand, Taiwan,
Uruguay, Venezuela, Viet Nam
First National
Communication
EIA 2002
Reference Case
Missing historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from the
Tier 1 estimated emissions. Tier 1 methodology described
below.
Argentina
Addendum to First
National
Communication
EIA 2002
Reference Case
Used reported data for 1990. Missing historical estimates
extrapolated from changes in oil and natural gas production and
consumption (EIA 2002). Obtained EIA 'reference case'
projections of natural gas production and oil production and
consumption for the periods 2000-2005, 2005-2010, 2010-2015
and 2015-2020 from EIA 2002. Assumed growth rate for
natural gas consumption the same as natural gas production.
Created projections by applying the average annual
consumption or production growth rate to emissions attributed
to consumption or production.
Australia, Austria, Belarus, Belgium,
Bulgaria, Canada, Croatia, Czech Republic,
Denmark, Estonia, Finland, France,
Germany, Greece, Hungary, Ireland,
Iceland, Italy, Japan, Latvia, Lithuania,
Monaco, Netherlands, New Zealand,
Norway, Poland, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden,
Switzerland, Ukraine, United Kingdom
2005 Common
Reporting Format
(CRF)
Third National
Communication
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected estimates
extracted from Third National Communication (or other country-
reported data) to CRF historical estimates.
Azerbaijan, Kazakhstan, Turkmenistan,
Uzbekistan
First National
Communication
Oil and Gas
Journal
Used reported data for 1990. Missing historical and projected
estimates obtained from the Oil and Gas Journal.
Liechtenstein
Third National
Communication
Third National
Communication
Historical and projected emissions from Third National
Communication.
Luxembourg
First National
Communication
Not Applicable.
Used reported data for 1990-2000. Projections kept constant at
2000 levels.
Mexico
Second National
Communication
EIA 2002
Reference Case
Used reported emissions from National Communication from
1994 and 1996. Interpolated 1995. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 methodology described above.
-------
Appendix E-1: Data Sources and Methodologies for
Methane Emissions from Fugitives from Natural Gas and Oil Systems
Mongolia
Russia
South Korea
United States
Data Sources
ALGAS
Third National
Communication
Second National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
EIA 2002
Reference Case
U.S. EPA
EIA 2002
Reference Case
U.S. EPA-
Internal Draft 4th
National
Communication
No oil/gas production or consumption.
Used reported data for 1990-2000. Forecast emissions through
2010 using natural gas production. Growth rate for 2000-2010
used for 201 0-2020.
Used reported emissions from National Communication from
1990-2000. Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
methodology described above.
-------
Appendix E-2: Data Sources and Methodologies for
Methane Emissions from Fugitives from Coal Mining Activities
Countries
Albania
Algeria, Armenia, Azerbaijan, Bangladesh,
Bolivia, Cambodia, Chile, Democratic Republic of
Congo (Kinshasa), Ecuador, Egypt, Ethiopia,
Georgia, Iraq, Israel, Lao People's Democratic
Republic, Macedonia, Moldova, Myanmar, Nepal,
North Korea, Saudi Arabia, Senegal, Singapore,
Turkey, Turkmenistan, Uganda, United Arab
Emirates. Also estimated emissions for many
smaller countries combined under "Rest Of
Africa, FSU, Latin America, Middle East, Non-
EU Eastern Europe, OECD 90 & EU, and S&E
Asia
Argentina, Tajikistan
Australia, Austria, Belgium, Bulgaria, Canada,
Croatia, Czech Republic, Denmark, Estonia,
Finland, France, Germany, Greece, Hungary,
Ireland, Iceland, Italy, Japan, Latvia, Monaco,
Netherlands, New Zealand, Norway, Poland,
Portugal, Romania, Slovak Republic, Slovenia,
Spain, Sweden, Switzerland, Ukraine, United
Kingdom
Brazil, China, Indonesia, India, Iran, Malawi,
Nigeria, Pakistan, Philippines, Taiwan,
Venezuela, Viet Nam.
Columbia
Kazakhstan
Kyrgyzstan
Mexico
Mongolia
Peru, Swaziland
Data Sources
Historical
First National
Communication
IPCCTier 1/
EIA 2000
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
First National
Communication/
EIA 2000
Tier 3/2 Inventory
Project
First National
Communication
Country Studies
Report
First National
Communication
First National
Communication
Projected
EIA 2002
IPCCTier 1/
EIA 2002
IPCCTieM/
EIA 2002
Third National
Communication
IPCCTier 1
Estimated using
IPCCTier 1/
EIA 2000
Russian Trend
IPCCTier 1/
EIA 2002
IPCCTier 1/
EIA 2002
IPCCTieM/
EIA 2002
IPCCTieM/
EIA 2002
Methodology/Adjustments
Used reported 1995 emissions. Missing historical
estimates extrapolated from changes in coal production
using EIA 2002 data. Coal production was zero in 2000
and is expected to remain at zero.
Used IPCC Tier 1 methodology to develop historical and
projected estimates. Calculated historical estimates by
multiplying 1997 IPCC default emission factors for hard
and soft coal by corresponding hard and soft coal
production data. Obtained historic coal production data
from 1980 through 2000 from EIA (2002). Extrapolated
future coal production based on the change in production
from 1995 to 2000. Projected emissions to 2020 using
average emission factors based on high and low IPCC
default values. (Note: If IEA (2002) and EIA indicated
that a country did not produce coal, methane emissions
were assumed to be zero.)
Used reported 1990 emissions. Missing historical
estimates were extrapolated from changes in coal
production using EIA 2002 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported emissions from National Communication
(1994 often used as proxy for 1995). Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions were developed
as described above.
Used reported 1990 and 1995 emissions. Missing
historical estimate extrapolated from changes in coal
production using EIA 2000 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions were developed as described above.
Used reported emissions for 1990 to 2000 from Tier 3/2
Inventory Project. Projections follow Russian trend.
Used reported 1990, 1995, and 2000 emissions. Created
projections by applying growth rates from Tier 1
estimated emissions. Tier 1 emissions are described
above.
Used reported 1990 emissions. Missing historical
estimates were extrapolated from changes in coal
production using EIA 2002 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
Used reported 1990 and 1995 emissions. Missing
historical estimate extrapolated from changes in coal
production using EIA 2002 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
Used reported 1995 emissions. Missing historical
estimates were extrapolated from changes in coal
production using EIA 2002 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
-------
Appendix E-2: Data Sources and Methodologies for
Methane Emissions from Fugitives from Coal Mining Activities
Russia
South Africa
South Korea
Thailand
United States
Uruguay
Uzbekistan
Data Sources
Third National
Communication
Country Report on
Coal Mining (PJD
Lloyd)
Second National
Communication
National
Communication/
ALGAS
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
First National
Communication
First National
Communication
Third National
Communication/
EPA
Country Report on
Coal Mining (PJD
Lloyd)
IPCCTieM/
EIA 2002
IPCCTieM/
EIA 2002
U.S. EPA-
Internal Draft 4th
National
Communication
IPCCTieM/
EIA 2002
Russian Trend
Used reported emissions from 1990-2010. Projected to
2020 by scaling projected estimates from EPA internal
report.
Used reported emissions from 1990-2020.
Used reported emissions from 1990-2000. Developed
projections by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below.
Used reported 1990 and 1995 emissions. Missing
historical estimate extrapolated from changes in coal
production using EIA 2002 data. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
Used reported 1990 and 1995 emissions. Coal
production was zero in 2000 and is expected to remain at
zero.
Used reported 1990 and 1995 emissions. Missing
historical estimates and projections filled in using trend
from Russia's data.
-------
Appendix E-3: Data Sources and Methodologies for
Methane and Nitrous Oxide Emissions from Stationary and Mobile Combustion
Countries
Albania, Algeria, Brazil, Congo (Kinshasa) DPRC,
Iraq, Israel, Kuwait, Macedonia, Nepal, North
Korea (DPRK), Peru, Saudi Arabia, Singapore,
South Africa, Turkey, United Arab Emirates. Also
estimated emissions for many smaller countries
combined under "Rest Of Africa, FSU, Latin
America, Middle East, Non-EU Eastern Europe,
OECD 90 & EU and S&E Asia.
Argentina
Armenia, Cambodia, Dominican Republic,
Ethiopia, Gambia, Indonesia, India, Iran,
Kyrgyrzstan, Madagascar, Nigeria, Pakistan,
Tajikistan, Taiwan, Viet Nam
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithuania, Monaco, Netherlands, New Zealand,
Norway, Poland, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland,
Ukraine, United Kingdom
Azerbaijan
Bangladesh
Data Sources
Historical
IPCCTier!/
IEA Energy
Balances
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
ALGAS
Projected
IEAWEO2000
IEAWEO2000
IEAWE02000
Third National
Communication
IEAWEO2000
IEAWEO2000
Methodology/Adjustments
Used IPCC Tier 1 methodology to develop historical
estimates. Fuel consumption data from IEA Energy
Balances are multiplied by IPCC nitrous oxide and
methane uncontrolled emission factors for each fuel and
sector. Projections are created by applying regional or
country-specific annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO. Used
1997-2010 growth rate to project to 2000, 2005, 2010;
and used 2010-2020 growth rate to project to 2015 and
2020.
Used reported 1990, 1994, and 1997 emissions.
Interpolated between values to estimate 1995 emissions.
Applied the annual growth rates for fuel consumption by
sector from lEA's Energy Balances to forecast emissions
for 1999. Allocated 1999 emissions to primary fuel type
using the proportion that these fuels were consumed in
1999 from lEA's Energy Balances. Applied regional
annual growth rates for fuel consumption by sector and
primary fuel type from lEA's WEO to project emissions.
Used 1997-2010 growth rate to project to 2000, 2005,
2010; and used 2010-2020 growth rate to project to 2015
and 2020.
Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported 1990 and 1995 emissions; applied annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to the given values to forecast
emissions for 1999. Allocated 1999 emissions to primary
fuel type using the proportion that these fuels were
consumed in 1999 from lEA's Energy Balances. Applied
regional annual growth rates for fuel consumption by
sector and primary fuel type from lEA's WEO to project
emissions. Used 1997-2010 growth rate to project to
2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Used reported 1990 emissions. Applied the annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to the given values to forecast
emissions for 1995 and 1999. Allocated 1999 emissions
to primary fuel type using the proportion that these fuels
were consumed in 1999 from lEA's Energy Balances.
Applied regional annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO to
project emissions. Used 1997-2010 growth rate to project
to 2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
-------
Appendix E-3: Data Sources and Methodologies for
Methane and Nitrous Oxide Emissions from Stationary and Mobile Combustion
Bolivia, Jordan, Philippines, Senegal, Thailand
Data Sources
First National
Communication
IEAWE02000
Used reported 1994 emissions; applied annual growth
rates for fuel consumption by sector from lEA's Energy
Balances to the given value to backcast to 1990 and
forecast to 1995 and 1999. Allocated 1999 emissions to
primary fuel type using the proportion that these fuels
were consumed in 1999 from lEA's Energy Balances.
Applied regional annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO to
project emissions. Used 1997-2010 growth rate to project
to 2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Chile
First National
Communication
IEA WEO 2000
Used reported data for 1993 and 1994; applied annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to the given value to backcast to 1990
and forecast to 1995 and 1999. Allocated 1999
emissions to primary fuel type using the proportion that
these fuels were consumed in 1999 from lEA's Energy
Balances. Applied regional annual growth rates for fuel
consumption by sector and primary fuel type from lEA's
WEO to project emissions. Used 1997-2010 growth rate
to project to 2000, 2005, 2010; and used 2010-2020
growth rate to project to 2015 and 2020.
China
ALGAS (CH4); IEA
Energy Balances
(N20)
I EA WEO 2000
For CH4 used reported data for 1990. Applied the annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to forecast emissions for 1995 and
1999. Allocated 1999 emissions to primary fuel type
using the proportion that these fuels were consumed in
1999 from lEA's Energy Balances. For N2O, used fuel
consumption data from IEA Energy Balances and IPCC
Tier 1 methodology to estimate historical emissions.
Applied regional annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO to
project emissions. Used 1997-2010 growth rate to project
to 2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Colombia
First National
Communication
I EA WEO 2000
Used reported 1990 and 1994 emissions; applied annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to the given values to forecast
emissions for 1995 and 1999. Allocated 1999 emissions
to primary fuel type using the proportion that these fuels
were consumed in 1999 from lEA's Energy Balances.
Applied regional annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO to
project emissions. Used 1997-2010 growth rate to project
to 2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Ecuador, Egypt, Uruguay
First National
Communication
I EA WEO 2000
Used reported 1990 emissions. Applied the annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to forecast emissions for 1995 and
1999. Allocated 1999 emissions to primary fuel type
using the proportion that these fuels were consumed in
1999 from lEA's Energy Balances. Applied regional
annual growth rates for fuel consumption by sector and
primary fuel type from lEA's WEO to project emissions.
Used 1997-2010 growth rate to project to 2000, 2005,
2010; and used 2010-2020 growth rate to project to 2015
and 2020.
-------
Appendix E-3: Data Sources and Methodologies for
Methane and Nitrous Oxide Emissions from Stationary and Mobile Combustion
Georgia
Kazakhstan
Liechtenstein
Luxembourg
Mexico
Moldova, Uzbekistan
Mongolia
Myanmar
Data Sources
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
Second National
Communication
First National
Communication
IPCCTieM/
IEA Energy
Balances
Not estimated.
ALGAS
IEAWE02000
IEAWE02000
Third National
Communication
EPA
IEAWEO2000
IEAWE02000
Not estimated.
IEAWEO2000
Used reported 1990, 1995, and 1997 emissions; applied
annual growth rates for fuel consumption by sector from
lEA's Energy Balances to the given values to forecast
emissions for 1999. Allocated 1999 emissions to primary
fuel type using the proportion that these fuels were
consumed in 1999 from lEA's Energy Balances. Applied
regional annual growth rates for fuel consumption by
sector and primary fuel type from lEA's WEO to project
emissions. Used 1997-2010 growth rate to project to
2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Used reported 1990 emissions. Used regional fuel
consumption growth rates by sector from lEA's WEO to
forecast emissions for 1995 (IEA Energy Balance data
not available for 1990). Applied the annual growth rates
for fuel consumption by sector from lEA's Energy
Balances to forecast emissions for 1999. Allocated 1999
emissions to primary fuel type using the proportion that
these fuels were consumed in 1999 from lEA's Energy
Balances. Applied regional annual growth rates for fuel
consumption by sector and primary fuel type from lEA's
WEO to project emissions. Used 1997-2010 growth rate
to project to 2000, 2005, 2010; and used 2010-2020
growth rate to project to 2015 and 2020.
Historical and projected Emissions from Third National
Communication.
Projections kept constant at 2000 levels.
Used reported 1994, 1996, and 1998 emissions.
Interpolated to estimate 1995 emissions. Applied the
annual growth rates for fuel consumption by sector from
lEA's Energy Balances to the given values to backcast to
1990 and forecast to 1999. Allocated 1999 emissions to
primary fuel type using the proportion that these fuels
were consumed in 1999 from lEA's Energy Balances.
Applied regional annual growth rates for fuel consumption
by sector and primary fuel type from lEA's WEO to
project emissions. Used 1997-2010 growth rate to project
to 2000, 2005, 2010; and used 2010-2020 growth rate to
project to 2015 and 2020.
Used fuel consumption data from IEA Energy Balances
and IPCC Tier 1 methodology to estimate historical
emissions for 1995 and 1999. Estimated 1990 emissions
by applying the country's share of FSU's total emissions
in 1995 to FSU's emissions in 1990. Applied regional
annual growth rates for fuel consumption by sector and
primary fuel type from lEA's WEO to project emissions.
Used 1997-2010 growth rate to project to 2000, 2005,
2010; and used 2010-2020 growth rate to project to 2015
and 2020.
Used reported 1990 emissions. Applied the annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to forecast emissions for 1995 and
1999. Allocated 1999 emissions to primary fuel type
using the proportion that these fuels were consumed in
1999 from lEA's Energy Balances. Applied regional
annual growth rates for fuel consumption by sector and
primary fuel type from lEA's WEO to project emissions.
Used 1997-2010 growth rate to project to 2000, 2005,
2010; and used 2010-2020 growth rate to project to 2015
and 2020.
-------
Appendix E-3: Data Sources and Methodologies for
Methane and Nitrous Oxide Emissions from Stationary and Mobile Combustion
Russia
South Korea
Turkmenistan
Uganda, Venezuela
United States
Data Sources
Second National
Communication /
2000 Inventory
Second National
Communication
First National
Communication
Country Study
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
EPA
IEAWEO2000
IEAWE02000
IEAWEO2000
U.S. EPA-
Internal Draft 4th
National
Communication
Used reported emissions from National Communication
for 2000. Applied regional annual growth rates for fuel
consumption by sector and primary fuel type from lEA's
WEO to project emissions. Used 1997-2010 growth rate
to project to 2000, 2005, 2010; and used 2010-2020
growth rate to project to 2015 and 2020.
Used reported 1994 emissions; used regional fuel
consumption growth rates by sector from lEA's WEO to
backcast to 1990 and forecast to 1995 (IEA Energy
Balance data not available for 1990). Applied annual
growth rates for fuel consumption by sector from lEA's
Energy Balances to the given value to forecast emissions
for 1999. Allocated 1999 emissions to primary fuel type
using the proportion that these fuels were consumed in
1999 from lEA's Energy Balances. Applied regional
annual growth rates for fuel consumption by sector and
primary fuel type from lEA's WEO to project emissions.
Used 1997-2010 growth rate to project to 2000, 2005,
2010; and used 2010-2020 growth rate to project to 2015
and 2020.
Used reported 1990 emissions. Applied the regional fuel
consumption growth rates by sector from lEA's WEO to
forecast emissions for 1995 and 1999. Allocated 1999
emissions to primary fuel type using the proportion that
these fuels were consumed in 1999 from lEA's Energy
Balances. Applied regional annual growth rates for fuel
consumption by sector and primary fuel type from lEA's
WEO to project emissions. Used 1997-2010 growth rate
to project to 2000, 2005, 2010; and used 2010-2020
growth rate to project to 2015 and 2020.
-------
Appendix E-4: Data Sources and Methodologies for
Methane and Nitrous Oxide Emissions from Biomass Combustion
Countries
Albania, Algeria, Argentina, Azerbaijan, Brazil,
Chile, Colombia, Congo (Kinshasa) DPRC,
Georgia, Iraq, Israel, Jordan, Kazakhstan, Kuwait,
Kyrgyzstan, Macedonia, Mexico, Moldova, Nepal,
North Korea, Peru, Philippines, Saudi Arabia,
Senegal, Singapore, South Africa, Tajikistan,
Turkey, Turkmenistan, United Arab Emirates,
Uruguay, Uzbekistan, Venezuela. Also estimated
emissions for many smaller countries combined
under "Rest Of Africa, FSU, Latin America,
Middle East, Non-EU Eastern Europe, OECD90
& EU.andS&EAsia
Armenia, Ecuador, Egypt, Laos
Bangladesh, Myanmar, Pakistan, South Korea,
Thailand
Bolivia, India, Madagascar, Nigeria, Iran, Viet
Nam
Cambodia
China
Dominican Republic, Ethiopia, Malawi, Mongolia
Indonesia
Uganda
Data Sources
Historical
IPCCTier 1/
IEA Energy
Statistics
First National
Communication
ALGAS
First National
Communication
First National
Communication
First National
Communication
(CH4); Estimated
using IPCC Tier 1
(N20)
First National
Communication
First National
Communication
Country Study
Projected
IEAWEO2000
IEAWEO2000
IEAWE02000
IEAWEO2000
First National
Communication
IEAWE02000
IEAWEO2000
IEAWE02000
IEAWE02000
Methodology/Adjustments
Used IPCC Tier 1 methodology to develop historical
estimates. Multiplied biomass fuel consumption by
sector by default IPCC emission factors. Used IEA
statistics for 1990-99 activity data (Section 7.3.4, IEA
2001 b and 2001 c). Created projections (2000-2020) by
applying annual regional or country-specific growth rates
from WEO 2000 (IEA 2001a).
Used reported 1990 emissions. Missing historical and
projected estimates backcast/forecast from country-
reported data by applying regional or country-specific
annual growth rates (from WEO 2000) to the given
estimates (IEA2001a).
Used reported 1990 emissions. Missing historical and
projected estimates backcast/forecast from country-
reported data by applying regional or country-specific
annual growth rates (from WEO 2000) to the given
estimates (I EA2001a).
Used reported data for 1994 (1994 used as proxy for
1995). Missing historical and projected estimates
backcast/forecast from country-reported data by applying
regional or country-specific annual growth rates (from
WEO 2000) to the given estimates (IEA 2001a).
Used reported 1995 emissions. Backcast 1990. Used
reported data for 2000, 2010, 2020. Interpolated 2005
and 201 5.
For methane, used reported data for 1994. Assumed
1995 emissions = 1994 emissions. Created projections
by applying annual PRC growth rates (from WEO 2000)
to the given estimates. For N2O, used IPCC Tier 1
methodology to develop historical estimates. Multiplied
biomass fuel consumption by sector by default IPCC
emission factors. Used IEA statistics for 1990-99 activity
data (IEA 2001 b). Created projections by applying
annual PRC growth rates from WEO 2000 (IEA 2001a).
Used reported data for 1990 and 1995. Missing historical
and projected estimates backcast/forecast from country-
reported data by applying regional or country-specific
annual growth rates (from WEO 2000) to the given
estimates (IEA2001a).
Used reported emissions from 1990-2000. Created
projections by applying regional annual growth rates
(from WEO 2000) to the given estimates (IEA 2001a).
Used reported 1990 emissions. Missing historical and
projected estimates backcast/forecast from country-
reported data by applying regional or country-specific
annual growth rates (from WEO 2000) to the given
estimates (I EA2001a).
-------
Appendix E-5: Data Sources and Methodologies for
Nitrous Oxide Emissions from Adipic Acid and Nitric Acid Production
Countries
Algeria, Chile
Albania, Columbia, India, Iran, Peru
Argentina, Georgia
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Finland, France, Germany, Greece, Hungary,
Iceland, Ireland, Italy, Japan, Latvia, Lithuania,
Netherlands, New Zealand, Norway, Poland,
Portugal, Romania, Slovak Republic, Slovenia,
Spain, Sweden, Switzerland, Ukraine, United
Kingdom
Brazil, Indonesia, South Africa
Singapore
Mexico
Russia
South Korea
United States
Uzbekistan
Venezuela
Data Sources
Historical
First National
Communication
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
IPCCTier 1
Second National
Communication
Third National
Communication
Second National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
First National
Communication
First National
Communication
Projected
Kept constant.
IPCCTieM
Kept constant.
See Methodology
Section 7.2.5.
IPCCTier 1
IPCCTier 1
IPCCTieM
Kept constant.
IPCCTier 1
U.S. EPA-
Internal Draft 4th
National
Communication
Kept constant.
IPCCTier 1
Methodology/Adjustments
Used reported emissions for 1995. Missing
historical years and projections kept constant at
1995 levels.
Used reported emissions for 1995 (1994 often
used as proxy for 1995). Missing historical
estimates and projections backcast/forecast from
country-reported data by applying growth rates
from the Tier 1 estimated emissions.
Used reported emissions for 1990 and 1995.
Projections kept constant at 1995 levels.
Used reported data froml 990-2000.
Used reported emissions for 1990 and 1994
(1994 used as proxy for 1995). Missing historical
estimates and projections backcast/forecast from
country-reported data by applying growth rates
from the Tier 1 estimated emissions.
See Methodology Section 7.2.5.
Used reported emissions from 1994 and 1996.
Interpolated 1995. Missing historical estimates
and projections backcast/forecast from country-
reported data by applying growth rates from the
Tier 1 estimated emissions.
Used reported emissions from 1990 to 2000.
Projections held constant at 2000 levels.
Used reported emissions for 2001 (2001 used as
proxy for 2000). Missing historical estimates and
projections backcast/forecast from country-
reported data by applying growth rates from the
Tier 1 estimated emissions.
Used reported emissions for 1990. Missing
historical years and projections kept constant at
1990 levels.
Used reported emissions for 2000. Missing
historical estimates and projections
backcast/forecast from country-reported data by
applying growth rates from the Tier 1 estimated
emissions.
-------
Appendix E-6: Data Sources and Methodologies for
Nitrous Oxide Emissions from Agricultural Soils
Countries
Algeria, Brazil, Cambodia, Democratic Republic
of the Congo (Kinshasa), Indonesia, India, Iran,
Nepal, Pakistan, South Africa, Saudia Arabia,
Thailand, Taiwan, Uruguay, Venezuela, Viet Nam
Argentina, Uzbekistan
Armenia, Azerbaijan, Ecuador, Egypt
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithuania, Netherlands, New Zealand, Norway,
Poland, Portugal, Romania, Slovak Republic,
Slovenia, Spain, Sweden, Switzerland, Ukraine,
United Kingdom.
Bangladesh, China, Iraq, Kazakhstan,
Liechtenstein, Luxembourg, Moldova, Mongolia,
Nigeria, North Korea (DPRK), Senegal, Turkey,
Uganda
Bolivia, Chile, Ethiopia, Israel, Jordan, Peru,
Turkmenistan
Colombia
Georgia
Mexico
Myanmar
Philippines
Russia
Singapore
South Korea
Data Sources
Historical
First National
Communication
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
IPCCTier 1/
FAO
First National
Communication
First National
Communication
First National
Communication
Second National
Communication
ALGAS
ALGAS & First
National
Communication
Third National
Communication
First National
Communication
Second National
Communication
Projected
FAO
FAO
FAO
Third National
Communication
FAO
FAO
FAO
FAO
FAO
ALGAS
FAO
Second National
Communication
First National
Communication
FAO
Methodology/Adjustments
Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described below.
Used Tier 1 methodology. Projected activity data based
on FAO fertilizer consumption 1995/1997 to 2015 growth
rate, historical crop production growth rates, and 1990 to
2020 methane from manure growth rates. Calculated
growth rates based on Tier 1 results for 1995 to 2020 and
applied these growth rates to reported 1990 and 1995
(proxy year) values.
Used reported 1990 emissions, extrapolated to 2000
based on country-specific fertilizer consumption growth
rate, and extrapolated to 2020 based on FAO 1995/1997
to 2015 regional fertilizer consumption growth rate.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used Tier 1 methodology for historical and projected
estimates. Projected activity data based on FAO fertilizer
consumption 1995/1997 to 2015 growth rate, historical
crop production growth rates, and 1990 to 2020 methane
from manure growth rates.
Used reported 1995 (or proxy year) value and applied
country-specific fertilizer consumption growth rate to
estimate 1990 and 2000, then extrapolated to 2020
based on FAO 1995/1997 to 2015 regional fertilizer
consumption growth rate.
Used reported 1990 and 1995 (proxy year) emissions,
applied country-specific fertilizer consumption growth rate
until 2000, and then extrapolated to 2020 based on FAO
1995/1997 to 2015 regional fertilizer consumption growth
rate.
Used reported 1990 and 1995 emissions, applied country
specific fertilizer consumption growth rate until 2000, and
extrapolated to 2020 based on FAO 1995/1997 to 2015
regional fertilizer consumption growth rate.
Used reported 1994 and 1996 emissions. Interpolated
1995. Applied country-specific fertilizer consumption
growth rate to estimate 1990 and 2000; extrapolated to
2020 based on FAO 1995/1997 to 2015 regional fertilizer
consumption growth rate.
Used ALGAS estimates for 1990, 2000, 2010, and 2020,
and interpolated 2005 and 2015.
Used reported 1990 and 1995 (proxy year) emissions,
applied country-specific fertilizer consumption growth rate
until 2000, and then extrapolated to 2020 based on FAO
1995/1997 to 2015 regional fertilizer consumption growth
rate.
Used reported emissions from 1990-2000. Projected to
2020 by scaling projected estimates extracted from
Second National Communication to Third National
Communication historical data.
Used reported estimates and projections for 1990 to
2020.
Used reported emissions from 1990-2000. Extrapolated
to 2020 based on FAO 1995/1997 to 2015 regional
fertilizer consumption growth rate.
-------
Appendix E-6: Data Sources and Methodologies for
Nitrous Oxide Emissions from Agricultural Soils
United States
Data Sources
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
U.S. EPA-
Internal Draft 4th
National
Communication
-------
Appendix E-7: Data Sources and Methodologies for
Methane Emissions from Enteric Fermentation
Countries
Albania, Algeria, Bolivia, China, Democratic
Republic of the Congo (Kinshasa), Gambia, India,
Nigeria, Pakistan, Viet Nam
Argentina
Armenia, Kyrgyrzstan
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithuania, Monaco, Netherlands, New Zealand,
Norway, Poland, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland,
Ukraine, United Kingdom
Azerbaijan
Bangladesh
Brazil, Dominican Republic, Malawi, South Africa
Cambodia
Chile
Colombia, Uzbekistan
Ecuador, Egypt, Laos, Saudi Arabia, Uruguay
Data Sources
Historical
First National
Communication
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
ALGAS
First National
Communication
First National
Communication
First National
Communication
First National
Communication
First National
Communication
Projected
IPCCTier 1/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
Third National
Communication
First National
Communication
ALGAS
IPCCTier 1/
IFPRI
IPCCTier 1/
IFPRI
IPCCTier 1/
IFPRI
IPCCTier 1/
IFPRI
IPCCTier 1/
IFPRI
Methodology/Adjustments
Used reported 1994 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below.
Used reported emissions for 1990, 1994, and 1997.
Interpolated for 1995 emissions using 1994 and 1997
reported estimates. Forecast 2000 emissions based on
1995-2000 Tier 1 annual growth rate of emissions and
1997 reported emissions. Projected from 2000 to 2005-
2020 based on IFPRI growth rates.
Used reported emissions from National Communication
from 1990-2000. Developed projections by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described below.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported 1990 emissions. Determined the percent
contribution of enteric fermentation to total agriculture
CH4 emissions in 1990 and applied this to total
agriculture CH4 estimates for 1995, 2000, 2005, 2010,
2015, and 2020 to project emissions.
Used reported emissions for 1990. Determined the
percent contribution of enteric fermentation to total
livestock CH4 emissions in 1990 and applied this to total
agriculture CH4 estimates for 2000, 2010, and 2020 to
estimate emissions. Interpolated for 1995, 2005, 2015.
Used reported 1990 and 1994 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions were
developed as described below.
Used reported 1994 and 2000 emissions. Developed
projections by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below.
Determined the percent contribution of enteric
fermentation to total agriculture CH4 emissions in 1995
using Tier 1 methodology, and applied this to reported
emissions from livestock in 1993 and 1994. Backcast
1990 and forecast 1995 emissions based on 1990-1995
Tier 1 annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Projected from 2000 to 2005-2020 based
on IFPRI growth rates.
Used reported emissions for 1990 and 1994. Forecast
1995 emissions based on 1990-1995 Tier 1 annual
growth rate of emissions. Forecast 2000 emissions
based on 1995-2000 Tier 1 annual growth rate of
emissions. Projected from 2000 to 2005-2020 based on
IFPRI growth rates.
Used reported 1990 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above.
-------
Appendix E-7: Data Sources and Methodologies for
Methane Emissions from Enteric Fermentation
Ethiopia
Georgia
Indonesia
Iran
Iraq, North Korea, Singapore, Turkey
Israel
Jordan
Kazakhstan
Mexico
Moldova
Data Sources
First National
Communication
First National
Communication
National
Communication
and ALGAS
First National
Communication
IPCCTierl/
FAO
First National
Communication
First National
Communication
First National
Communication
Second National
Communication
First National
Communication
IPCCTierl/
IFPRI
National
Communication
and IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
IPCCTierl/
IFPRI
Used reported 1990 and 1995 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described below.
Applied the 1990 percent contribution of enteric
fermentation to CH4 emissions to emissions from
livestock for 1990, 1995, 2000, 2005, and 2010 to
estimate 1990, 1995, 2000, 2005, and 2010 methane
emissions from enteric fermentation. Ranges of
emissions were reported for 2000, 2005, and 2010
estimates; the midpoint of the range was applied.
Projected from 2010 to 2015-2020 based on IFPRI
growth rates.
Used National Communications reported total emissions
of livestock for 1994 and applied the percent contribution
by enteric fermentation from ALGAS. Backcast 1990
and forecast 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Projected from 2000 to 2005-2020 based
on IFPRI growth rates.
Used reported emissions from National Communication
from 1994 and 2000. Developed projections by applying
growth rates from the Tier 1 estimated emissions.
Used IPCC Tier 1 methodology to develop historical
estimates. Estimated emissions by multiplying IPCC
default emission factors for each animal type (non-dairy
and dairy cattle, swine, sheep, etc.) by livestock
populations, and summing livestock-specific emissions.
FAO provided historical livestock data. Developed
projections by applying livestock population growth rates
provided by IFPRI1 to historical estimates.
Used reported 1996 emissions. Backcast to 1995
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Then backcast 1990 emissions based on
1990-1995 annual growth rate of emissions. Forecast
2000 emissions from 1996 reported estimate based on
1995-2000 Tier 1 annual growth rate of emissions.
Projected from 2000 to 2005-2020 based on IFPRI
growth rates.
Used reported emissions for 1994. Backcast 1990 and
forecasted 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions. Forecasted 2000
emissions based on 1995-2000 Tier 1 growth rate of
emissions. Projected from 2000 to 2005-2020 based on
IFPRI growth rates.
Used reported emissions for 1990 and 1994. Forecast
1995 emissions based on 1990-1995 Tier 1 annual
growth rate of emissions. Forecast 2000 emissions
based on 1995-2000 Tier 1 annual growth rate of
emissions. Projected from 2000 to 2005-2020 based on
IFPRI growth rates.
Used reported emissions from National Communication
from 1994 and 1996. Interpolated 1995. Developed
projections by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below.
Used reported emissions for 1990, 1995, and 1998.
Forecasted to 2000 using 1998 reported data and 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates.
-------
Appendix E-7: Data Sources and Methodologies for
Methane Emissions from Enteric Fermentation
Mongolia
Myanmar
Nepal, Sudan
Peru, Turkmenistan
Philippines
Russia
Senegal
South Korea
Thailand
Uganda
United States
Venezuela
Data Sources
ALGAS
ALGAS
First National
Communication
First National
Communication
First National
Communications
and ALGAS
Third National
Communication
First National
Communication
Second National
Communication
First National
Communication
Country Study
Report
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
First National
Communication
ALGAS
ALGAS
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
ALGAS
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
First National
Communication
IPCCTier 1/
IFPRI
U.S. EPA-
Internal Draft 4th
National
Communication
IPCCTier 1/
IFPRI
Applied 1990 contribution of enteric fermentation to total
livestock CH4 emissions in ALGAS to total reported
methane from livestock in 1995, 2000, 2010, and 2020.
Interpolated to find 2005 and 2015 emissions. (Although
the NC is more recent, ALGAS reports the same
historical data, and additionally projects emissions to
2020.)
Used reported emissions for 1990, 2000, 2010, and
2020. Interpolated for 1995, 2005, 2015.
Used reported 1995 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions.
Used reported 1994 emissions. Backcast 1990 and
forecasted 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Projected from 2000 to 2005-2020 based
on IFPRI growth rates.
Used 1994 NC reported estimate of domestic livestock
methane emissions to adjust the available reported
projections in ALGAS. Applied the ALGAS reported
percent contribution of enteric fermentation to total
livestock CH4 emissions to the ALGAS reported livestock
emission totals for 1990, 1995, 2000, 2005, 2010, 2015,
and 2020.
Used reported 1990, 1995, and 2000 emissions.
Used reported emissions for 1991 . Backcast 1990 and
forecast 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 growth rate of
emissions. Projected from 2000 to 2005-2020 based on
IFPRI growth rates.
Used reported emissions from 1990-2000. Developed
projections by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions were developed
as described below.
Used reported 1994, 2000, 2005, 2010, 2015, and 2020
estimates. Dairy cattle not included in estimates;
therefore, projected the dairy cattle estimates at the same
rate as reported cattle estimates (2000-2020) using 1994
reported dairy cattle methane estimate. Interpolated
1995 using 1994 and 2000 data. Used 1990-1995 Tier 1
annual growth rate of emissions to backcast to 1990
emissions.
Used reported emissions for 1990. Forecast 1995
emissions based on 1990-1995 Tier 1 annual growth rate
of emissions. Forecast 2000 emissions based on 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates.
Used reported emissions from National Communication
for 2000. Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described above.
1 IFPRI. 2004. International Food Policy Research Institute (IFPRI) provided herd size growth rates to EPA to project FAO herd size data.
-------
Appendix E-8: Data Sources and Methodologies for
Methane Emissions from Rice Cultivation
Countries
Afghanistan, Algeria, Angola, Belize, Benin,
Bhutan, Brunei Darussalam, Cameroon, Central
African Republic, Comoros, Fiji, Gabon, Guinea-
Bissau, Iraq, Jamaica, Kenya, Liberia,
Mozambique, North Korea, Papua New Guinea,
Paraguay, Reunion, Rwanda, Senegal, Sierra
Leone, Somalia, South Africa, Sudan, Suriname,
Swaziland, Syrian Arab Republic, Trinidad and
Tobago, Turkey, United Republic of Tanzania,
Zambia, Zimbabwe
Albania
Argentina
Australia, Austria, Belgium, Bulgaria, Canada,
Croatia, Denmark, Estonia, Finland, France,
Germany, Greece, Hungary, Ireland, Iceland,
Italy, Japan, Latvia, Netherlands, New Zealand,
Poland, Portugal, Romania, Slovak Republic,
Slovenia, Spain, Sweden, Switzerland, Ukraine,
United Kingdom
Azerbaijan, Colombia, Cuba, Dominican
Republic, Ghana, Indonesia, Kazakhstan, Malawi,
Niger, Uzbekistan
Bangladesh, Myanmar
Bolivia, Burkina Faso, Cambodia, Chile, Costa
Rica, Cote d'lvoire, Democratic Republic of
Congo (Kinshasa), El Salvador, Gambia, Guinea,
Guyana, Haiti, Honduras, India, Madagascar,
Malaysia, Mali, Mauritania, Morocco, Nepal,
Nicaragua, Nigeria, Pakistan, Panama, Peru,
Republic of the Congo (Brazzaville), Sri Lanka,
Togo, Turkmenistan, Viet Nam
Brazil
Burundi, Venezuela
Chad, Egypt, Guatemala, Laos, Uruguay
Data Sources
Historical
IPCCTier 1/
FAO
First National
Communication
Revision to the
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
ALGAS
First National
Communication
Inventory
First National
Communication
First National
Communication
Projected
IPCCTier 1/
UN POP
First National
Communication
IPCCTieM/
UN POP
Third National
Communication
IPCCTieM/
UN POP
IPCCTieM/
UN POP
IPCCTier 1/
UN POP
IPCCTieM/
UN POP
IPCCTier 1/
UN POP
IPCCTieM/
UN POP
Methodology/Adjustments
Used IPCC Tier 1 methodology to develop historical and
projected estimates. Tier 1 Emissions were estimated
using FAO data on total area harvested for rice cultivation
and IPCC emission factors based on water management
regime. Breakdown of area harvested by water
management regime obtained from IPCC or IRRI.
Created projections by applying growth rates derived from
UN population data to historical data.
National Communication states "Rice cultivation and
production after 1990 practically stopped and therefore
there are no reported statistical data of cultivation for this
crop."
Used reported 1990 and 1995 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described above.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported 1990 and 1995 emissions (1994 often
used as proxy for 1995). Missing historical estimates and
projections backcast/forecast from country-reported data
by applying growth rates from the Tier 1 estimated
emissions. Tier 1 emissions are described above.
Used reported emissions from ALGAS Report for 1990.
Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described above.
Used reported 1995 emissions (1993 or 1994 often used
as proxy for 1995). Missing historical estimates and
projections backcast/forecast from country-reported data
by applying growth rates from the Tier 1 estimated
emissions. Tier 1 emissions are described above.
Used reported emissions from Inventory from 1990 to
1995
(httcV/www.mct. aov.br/clima/inales/comunic old/in).
Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described above.
Used reported 2000 emissions. Missing historical
estimates and projections extrapolated from country-
reported data, based on observed growth rates from the
Tier 1 estimated emissions. Tier 1 emissions were
developed as described above.
Used reported 1990 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above.
-------
Appendix E-8: Data Sources and Methodologies for
Methane Emissions from Rice Cultivation
China, Philippines
Ecuador, Uganda
Iran, Thailand
Kyrgyzstan, Tajikistan, Macedonia, Taiwan
Mexico
Russia
South Korea
United States
Data Sources
Nutrient Cycling in
Agroecosystems
Vol.64, Nos. 1-2,
2002 pp ix - xv
Country Study
First National
Communication
First National
Communication
Second National
Communication
Third National
Communication
Second National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
IPCCTieM/
UN POP
Country Study/
IPCCTier 1
IPCCTier 1/
UN POP
IPCCTier 1/
UN POP
IPCCTieM/
UN POP
UN POP
IPCCTieM/
UN POP
U.S. EPA-
Internal Draft 4th
National
Communication
Used reported 1990 emissions from Journal. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described above.
Used reported emissions from Country Study for 1990.
Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described above.
Used reported 1995 and 2000 emissions (1994 used as
proxy for 1995). Missing historical estimates and
projections backcast/forecast from country-reported data
by applying growth rates from the Tier 1 estimated
emissions. Tier 1 emissions are described above.
Used reported 1990 and 2000 emissions. Projections
extrapolated from country-reported data, based on
observed growth rates from the Tier 1 estimated
emissions. Tier 1 emissions are described above.
Used reported 1994 and 1996 emissions. Interpolated
1995 emissions. Projections extrapolated from country-
reported data, based on observed growth rates from the
Tier 1 estimated emissions. Tier 1 emissions are
described above.
Used reported 1990, 1995, and 2000 emissions.
Projections extrapolated from country-reported data,
based on observed population growth rates.
Used reported 1990, 1995, and 2000 emissions.
Projections extrapolated from country-reported data,
based on observed growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above.
-------
Appendix E-9: Data Sources and Methodologies for
Methane Emissions from Manure Management
Countries
Albania, Algeria, China, Democratic Republic of
the Congo (Kinshasa), India, Malawi, Nigeria,
Pakistan
Argentina
Armenia, Kyrgyrzstan
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithaunia, Monaco, Netherlands, New Zealand,
Norway, Poland, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland,
Ukraine, United Kingdom
Azerbaijan
Bangladesh
Bolivia
Brazil, Dominican Republic, South Africa, Sudan,
Viet Nam
Cambodia, Iran
Chile
Data Sources
Historical
First National
Communication
First National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
First National
Communication
ALGAS
First National
Communication
First National
Communication
First National
Communication
First National
Communication
Projected
IPCCTier 1/
IFPRI
IPCCTieM/
IFPRI
IPCCTier 1/
IFPRI
Third National
Communication
First National
Communication
ALGAS
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
Methodology/Adjustments
Used reported 1994 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below (under Ecuador).
Used reported emissions for 1990, 1994, and 1997.
Interpolated for 1995 emissions using 1994 and 1997
reported estimates. Forecast 2000 emissions based on
1995-2000 Tier 1 annual growth rate of emissions and
1997 reported emissions. Projected emissions from
2005-2020 by applying livestock population growth rates
provided by IFPRI1 to historical estimates.
Used reported emissions from National Communication
from 1990-2000. Developed projections by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions are described below (under Ecuador).
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported 1990 emissions. Determined the percent
contribution of manure management to total agriculture
emissions in 1990 and applied this to total agriculture
estimates for 1995, 2000, 2005, 2010, 2015, and 2020 to
project emissions.
Used reported emissions for 1990. Determined the
percent contribution of manure management to total
livestock emissions in 1990 and applied this to total
agriculture estimates for 2000, 2010, and 2020 to
estimate emissions. Interpolated for 1995, 2005, 2015.
Used reported emissions for 1994. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below (under Ecuador).
Used reported 1990 and 1994 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described below (under Ecuador).
Used reported 1994 and 2000 emissions. Interpolated
1995. Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions were developed as described below (under
Ecuador).
Determined the percent contribution of manure
management to total agriculture emissions in 1995 using
Tier 1 methodology, and applied this to reported
emissions from livestock in 1993 and 1994. Backcast
1990 and forecast 1995 emissions based on 1990-1995
Tier 1 annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Projected from 2000 to 2005-2020 based
on IFPRI growth rates.
-------
Appendix E-9: Data Sources and Methodologies for
Methane Emissions from Manure Management
Colombia, Uzbekistan
Ecuador, Iraq, North Korea, Senegal, Singapore,
Uruguay
Egypt
Ethiopia
Georgia
Indonesia
Israel
Jordan
Kazakhstan
Data Sources
First National
Communication
IPCCTieM/
FAO
First National
Communication
First National
Communication
First National
Communication
First National
Communication
and ALGAS
First National
Communication
First National
Communication
First National
Communication
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
National
Communication
and IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
IPCCTieM/
IFPRI
Used reported 1990 and 1994 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described below (under Ecuador).
Used IPCC Tier 1 methodology to develop historical
estimates. Estimated emissions by multiplying IPCC
default emission factors for each animal type (non-dairy
and dairy cattle, swine, sheep, etc.) by livestock
populations, and summing livestock-specific emissions.
FAO provided historical livestock data. Developed
projections by applying livestock population growth rates
provided by IFPRI1 to historical estimates.
Used reported 1990 emissions. Forecast 1995 emissions
based on 1990-1995 Tier 1 annual growth rate of
emissions. Forecast 2000 emissions based on 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates
Used reported emissions from National Communication
from 1990 and 1995. Missing historical estimates and
projections backcast/forecast from country-reported data
by applying growth rates from the Tier 1 estimated
emissions. Tier 1 emissions are described above (under
Ecuador).
Applied the 1990 percent contribution of manure to total
livestock emissions to emissions from livestock for 1990,
1995, 2000, 2005, and 2010 to estimate 1990, 1995,
2000, 2005, and 2010 methane emissions from manure
management. Ranges of emissions were reported for
2000, 2005, and 2010 estimates; the midpoint of the
range was applied. Projected from 2010 to 2015-2020
based on IFPRI growth rates.
Used National Communication reported total emissions of
livestock for 1994 and applied the percent contribution by
manure from ALGAS. Backcast 1990 and forecast 1995
emissions based on 1990-1995 Tier 1 annual growth rate
of emissions. Forecast 2000 emissions based on 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates.
Used reported 1996 emissions. Backcast to 1995
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Backcast 1990 emissions based on 1990-
1995 annual growth rate of emissions, forecast 2000
emissions from 1996 reported estimate based on 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates.
Used reported emissions for 1994. Backcast 1990 and
forecast 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions. Forecast 2000
emissions based on 1995-2000 Tier 1 growth rate of
emissions. Projected from 2000 to 2005-2020 based on
IFPRI growth rates.
Used reported 1990 and 1995 emissions. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described above (under Ecuador).
-------
Appendix E-9: Data Sources and Methodologies for
Methane Emissions from Manure Management
Laos, Saudi Arabia
Mexico
Moldova
Mongolia
Myanmar
Nepal, Sudan
Peru, Turkmenistan
Philippines
Russia
South Korea
Thailand
Turkey
Data Sources
First National
Communication
Second National
Communication
First National
Communication
ALGAS
ALGAS
First National
Communication
First National
Communication
First National
Communication
and ALGAS
Third National
Communication
Second National
Communication
First National
Communication
IPCCTier 1/
FAO
IPCCTieM/
IFPRI
IFPRI
ALGAS
ALGAS
IPCCTieM/
IFPRI
IPCCTier 1/
IFPRI
ALGAS
First National
Communication
IPCCTier 1/
IFPRI
Used reported 1990 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above (under Ecuador).
Used reported 1994 and 1996 emissions . Interpolated
1995. Missing historical estimates and projections
backcast/forecast from country-reported data by applying
growth rates from the Tier 1 estimated emissions. Tier 1
emissions were developed as described above (under
Ecuador).
Used reported emissions for 1990, 1995, and 1998.
Forecast to 2000 using 1998 reported data and 1995-
2000 Tier 1 annual growth rate of emissions. Projected
from 2000 to 2005-2020 based on IFPRI growth rates.
Applied 1990 manure/enteric fermentation ratio in
ALGAS to total reported methane from livestock in 1995,
2000, 2010, and 2020. Interpolated to find 2005 and
2015 emissions. (Although the NC is more recent,
ALGAS reports the same historical data, and additionally
projects emissions to 2020.)
Used reported emissions for 1990, 2000, 2010, and
2020. Interpolated for 1995, 2005, 2015.
Used reported 1995 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions were developed as
described below (under Ecuador).
Used reported 1994 emissions. Backcast 1990 and
forecast 1995 emissions based on 1990-1995 Tier 1
annual growth rate of emissions, forecast 2000
emissions based on 1995-2000 Tier 1 annual growth rate
of emissions. Projected from 2000 to 2005-2020 based
on IFPRI growth rates
Used 1994 NC reported estimate of domestic livestock
methane emissions to adjust the available reported
projections in ALGAS. Applied the ALGAS reported
percent contribution of manure management to total
livestock CH4 emissions to the ALGAS reported livestock
emission totals for 1990, 1995, 2000, 2005, 2010, 2015,
and 2020.
Used reported 1990, 1995, and 2000 emissions.
Used reported 2001 emissions from National
Communication (2001 used as proxy for 2000). Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions were
developed as described above (under Ecuador).
Used reported 1994, 2000, 2005, 2010, 2015, and 2020
estimates. Dairy cattle not included in estimates;
therefore, projected the dairy cattle estimates at the same
rate as reported cattle estimates (2000-2020) using 1994
reported dairy cattle methane estimate. Interpolated
1995 using 1994 and 2000 data. Used 1990-1995 Tier 1
annual growth rate of emissions to backcast to 1990
emissions.
Used FAO data and Tier 1 methodology for 1990, 1995,
2000 emissions and Projected from 2000 to 2005-2020
based on growth rate for CH4 emissions.
-------
Appendix E-9: Data Sources and Methodologies for
Methane Emissions from Manure Management
Uganda
United States
Venezuela
Data Sources
Country Study
Report
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
First National
Communication
IPCCTieM/
IFPRI
U.S. EPA-
Internal Draft 4th
National
Communication
IPCCTier 1/
IFPRI
Used reported 1990 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above (under Ecuador).
Used reported 1996 emissions. Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
above (under Ecuador).
1 IFPRI. 2004. International Food Policy Research Institute (IFPRI) provided herd size growth rates to EPA to project FAO herd size data.
-------
Appendix E-9b: Data Sources and Methodologies for
Nitrous Oxide Emissions from Manure Management
Countries
Albania, Algeria, Cambodia, Democratic Republic
of the Congo (Kinshasa), India, Malawi, Nepal,
Peru, Viet Nam
Argentina
Armenia, Azerbaijan, Bangladesh, Bolivia, Chile,
China, Colombia, Ecuador, Egypt, Ethiopia,
Georgia, Indonesia, Iran, Iraq, Jordan,
Kazakhstan, Kuwait, Laos, Macedonia, Moldova,
Mongolia, Myanmar, Nigeria, North Korea,
Philippines, Russia, Saudi Arabia, Senegal,
Singapore, Tajikistan, Turkey, Turkmenistan,
Uganda, United Arab Emirates, Uruguay
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithuania, Netherlands, New Zealand, Norway,
Poland, Portugal, Romania, Slovak Republic,
Slovenia, Spain, Sweden, Switzerland, Ukraine,
United Kingdom
Brazil, South Africa
Israel
Kyrgyrzstan
Liechtenstein
Mexico
Pakistan
South Korea
Data Sources
Historical
First National
Communication
Revision to the
First National
Communication/
IPCCTier 1
IPCCTieM/
FAO
2005 Common
Reporting Format
(CRF)
First National
Communication
National
Communication
First National
Communication
2005 Common
Reporting Format
(CRF)
Second National
Communication
ALGAS
Second National
Communication
Projected
IPCCTier 1/
CH4 rate
IPCCTier/
CH4 rate
IPCCTieM/
CH4 rate
Third National
Communication
IPCCTier 1/
CH4 rate
IPCCTier 1/
CH4 rate
IPCCTieM
N/A
IPCCTier 1/
CH4 rate
ALGAS
IPCCTier 1/
CH4 rate
Methodology/Adjustments
Used reported emissions for 1995 (1994 often used as
proxy for 1995). Missing historical emissions and
projections backcast/forecast from country-reported data
based on growth rates for CH4 emissions.
Used reported emissions for 1990, 1994, and 1997.
Interpolated 1995 emissions. Forecast 2000-2020
emissions based on growth rate for CH4 emissions.
Used IPCC Tier 1 methodology to develop historical
estimates. Estimated 1990, 1995, and 2000 emissions
by multiplying IPCC default emission factors for each
manure management system by population for each
animal type (non-dairy and dairy cattle, swine, sheep,
poultry and others) and summed emissions for each
system. FAO provided historical livestock data.
Projected from 2000 to 2005-2020 based on growth rate
for CH4 emissions.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported emissions for 1990 and 1995 (1994 used
as proxy for 1995). Missing historical emissions and
projections backcast/forecast from country-reported data
based on growth rates for CH4 emissions.
Used reported 1996 emissions. Backcast 1990
emissions based on 1990-1995 Tier 1 annual growth rate
of emissions. Backcast to 1995 emissions based on
1995-2000 Tier 1 annual growth rate of emissions.
Forecast 2000 emissions based on 1995-2000 Tier 1
annual growth rate of emissions. Projected from 2000 to
2005-2020 based on growth rate for Tier 1 estimated CH4
emissions.
Used reported emissions for 1990-2000. Projections
extrapolated from country-reported data, based on
calculated growth rates from the Tier 1 estimated
emissions.
No reported data.
Country reported emissions for 1994 and 1996.
Interpolated 1995 emissions. Missing historical
emissions and projections backcast/forecast from country
reported data based on growth rates for CH4 emissions.
Used 1990-2020 animal population data and projections
from ALGAS and Tier 1 methodology to estimate
emissions for 1990-2020.
Used reported emissions for 2000. Missing historical
emissions and projections backcast/forecast from country
reported data based on growth rates for Tier 1 estimated
CH4 emissions.
-------
Appendix E-9b: Data Sources and Methodologies for
Nitrous Oxide Emissions from Manure Management
Thailand
United States
Uzbekistan
Venezuela
Data Sources
First National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
First National
Communication
First National
Communication
First National
Communication
U.S. EPA-
Internal Draft 4th
National
Communication
IPCCTier 1/
CH4 rate
IPCCTier 1/
CH4 rate
Used reported 1994, 2000, 2005, 2010, 2015, and 2020
estimates. Dairy cattle not included in estimates;
therefore, projected the dairy cattle estimates at the same
rate as reported cattle estimates (2000-2020) using 1994
reported dairy cattle N2O estimate. Interpolated 1995
using 1994 and 2000 data. Used 1990-1995 Tier 1
annual growth rate of emissions to backcast to 1990
emissions.
Used reported emissions for 1990 and 1994. Forecast
1995-2020 based on growth rate for CH4 emissions.
Used reported emissions for 2000. Missing historical
emissions and projections backcast/forecast from country
reported data based on growth rates for CH4 emissions.
-------
Appendix E-10: Data Sources and Methodologies for
Methane Emissions from Landfilling of Solid Waste
Countries
Albania, Armenia, China, Dominican Republic,
Gambia, India, Jordan, Laos, Nigeria, Nepal,
Pakistan, South Africa, Saudia Arabia, Senegal,
Tajikistan, Venezuela, Viet Nam.
Algeria, Azerbaijan, Bolivia, Brazil, Cambodia,
Chile, Colombia, Democratic Republic of Congo
(Kinshasa), Ecuador, Egypt, Ethiopia, Georgia,
Indonesia, Iran, Israel, Kazakhstan, Kyrgyzstan,
Macedonia, Mexico, Moldova, Peru, Philippines,
Thailand, Turkmenistan, Uganda, Uruguay,
Uzbekistan.
Argentina, Iraq, Jordan, Kuwait, Liechtenstein,
North Korea, Singapore, Turkey, United Arab
Emirates. Also estimated emissions for many
smaller countries combined under "Rest Of
Africa, Latin America, Middle East, Non-EU
Eastern Europe, OECD90 & EU, and S&E Asia
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Japan, Latvia,
Lithuania, Monaco, Netherlands, New Zealand,
Norway, Poland, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland,
Ukraine, United Kingdom
Bangladesh, Myanmar
Luxembourg
Mexico
Mongolia
Russia
South Korea
United States
Data Sources
Historical
First National
Communication
First National
Communication
IPCCTieM/
UN POP
2005 Common
Reporting Format
(CRF)
ALGAS
2003 Inventory
Submission
Second National
Communication
First National
Communication
Third National
Communication
Second National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
Projected
IPCCTier 1/
UN POP
IPCCTier 1/
UN POP
IPCCTieM/
UN POP
Third National
Communication
IPCCTieM/
UN POP
Not Applicable.
IPCCTieM/
UN POP
IPCCTieM/
UN POP
IPCCTieM/
UN POP
IPCCTieM/
UN POP
U.S. EPA-
Internal Draft 4th
National
Communication
Methodology/Adjustments
Used reported emissions from National Communication
(1994 often used as proxy for 1995). Missing historical
estimates and projections backcast/forecast from country-
reported data by applying growth rates from the Tier 1
estimated emissions. Tier 1 emissions are described
below.
Used reported 1990 and 1995 emissions (1994 often
used as proxy for 1995). Created missing historical
estimates and projections by applying growth rates from
Tier 1 estimated emissions. Tier 1 emissions are
described below.
Used IPCC Tier 1 methodology to develop historical
estimates. Tier 1 Emissions were estimated using UN
population data and IPCC or IEA MSW disposal rates.
The methane correction factor was either the IEA or
default IPCC value for uncategorized disposal sites or
was calculated using country-specific proportions for
each disposal site type and their corresponding IPCC
defaults. The DOC fraction was calculated based on
country-specific waste stream composition figures and
IPCC default percent DOC values, otherwise, default
IPCC DOC fractions or IEA default DOC fractions were
used. IPCC defaults were used for the fractions of DOC
dissimilated, methane in landfill gas, recovered methane,
and for the oxidation factor. Emissions from 2005-2020
forecast by applying population growth rates to Tier 1
estimated emissions.
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
Used reported emissions for 1990-2005. Created
projections by applying growth rates from Tier 1
estimated emissions. Tier 1 emissions are described
above.
Used reported data for 2000. Projections kept constant
at 2000 levels.
Used reported emissions from National Communication
from 1994 and 1996. Interpolated 1995. Missing
historical estimates and projections backcast/forecast
from country-reported data by applying growth rates from
the Tier 1 estimated emissions. Tier 1 emissions are
described above.
Used reported emissions for 1990-2005. Created
projections by applying growth rates from Tier 1
estimated emissions. Tier 1 emissions are described
above.
Used reported 1990, 1995, and 2000 emissions.
Developed projections by applying growth rates from the
Tier 1 estimated emissions. Tier 1 emissions are
described above.
Used reported 1990, 1995, and 2000 emissions.
Developed projections by applying growth rates from the
Tier 1 estimated emissions. Tier 1 emissions are
described above.
-------
Appendix E-11: Data Sources and Methodologies for
Methane Emissions from Wastewater
Countries
Albania, Algeria, Argentina, Armenia, Azerbaijan,
Bangladesh, Bolivia, Brazil, Cambodia, Chile,
China, Colombia, Democratic Republic of Congo
(Kinshasa), Ecuador, Egypt, Ethiopia, Georgia,
Iceland, India, Indonesia, Iran, Iraq, Israel,
Jordan, Kazakhstan, Kuwait, Kyrgyzstan, Laos,
Liechtenstein, Luxembourg, Macedonia, Mexico,
Moldova, Mongolia, Myanmar, Nepal, Nigeria,
North Korea, Peru, Philippines, Russia, Saudi
Arabia, Senegal, South Africa, South Korea,
Tajikistan, Thailand, Turkey, Turkmenistan,
Uganda, United Arab Emirates, Uruguay,
Uzbekistan, Venezuela, Viet Nam. Also
estimated emissions for many smaller countries
combined under "Rest Of Africa, Latin America,
Middle East, Non-EU Eastern Europe, OECD90
& EU, and S&E Asia
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Estonia, Finland, France, Germany, Greece,
Hungary, Ireland, Italy, Japan, Latvia, Lithuania,
Monaco, Netherlands, New Zealand, Norway,
Poland, Portugal, Romania, Slovak Republic,
Slovenia, Spain, Sweden, Switzerland, Ukraine,
United Kingdom
United States
Data Sources
Historical
IPCCTier 1
2005 Common
Reporting Format
(CRF)
Inventory of US
GHG Emissions
and Sinks: 1990-
2003;4/15/2005
Projected
IPCCTier 1/
UN POP
IPCCTieM/
UN POP
U.S. EPA-
Internal Draft 4th
National
Communication
Methodology/Adjustments
Used IPCC Tier 1 methodology for each country and/or
region. The maximum methane producing capacity, part
of the emission factor, used in this analysis is 0.6 kg
CH4/kg biological oxygen demand (BOD), the
recommended factor in the IPCC Good Practice
Guidance. Assuming that the emission factors do not
change, the driver for determining methane emissions
from wastewater is population.
IPCC Tier 1 estimates scaled to historical estimates.
-------
Appendix E-12: Data Sources and Methodologies for Human Sewage
Nitrous Oxide Emissions from Human Sewage
Countries
Albania, Algeria, Brazil, Cambodia, Democratic
Republic of the Congo (Kinshasa), Ethiopia, India,
Iran, Kyrgyzstan, Nepal, Pakistan, Philippines,
Peru, South Africa, Saudi Arabia, Sudan,
Venezuela, Viet Nam
Argentina, Armenia, Azerbaijan, Bangladesh,
Bolivia, Chile, China, Colombia, Ecuador, Egypt,
Estonia, Georgia, Hungary, Iceland, Indonesia,
Iraq, Israel, Jordan, Kazakhstan, Kuwait, Laos,
Lithuania, Luxembourg, Macedonia, Mexico,
Moldova, Mongolia, Myanmar, Nepal, Nigeria,
North Korea, Peru, Russian Federation, Saudi
Arabia, Senegal, South Korea, Tajikistan,
Thailand, Turkey, Turkmenistan, Uganda, United
Arab Emirates, Uruguay, Uzbekistan. Also
estimated emissions for many smaller countries
combined under "Rest Of Africa, Latin America,
Middle East, Non-EU Eastern Europe, OECD90
& EU, and S&E Asia
Australia, Austria, Belarus, Belgium, Bulgaria,
Canada, Croatia, Czech Republic, Denmark,
Finland, France, Germany, Greece, Ireland, Italy,
Japan, Latvia, Monaco, Netherlands, New
Zealand, Norway, Portugal, Romania, Slovak
Republic, Slovenia, Spain, Sweden, Switzerland,
Ukraine, United Kingdom
Poland
Russia
United States
Data Sources
Historical
First National
Communication
Estimated using
IPCCTieM
2005 Common
Reporting Format
(CRF)
2005 Common
Reporting Format
(CRF)
Third National
Communication
Inventory of US
GHG Emissions
and Sinks: 1990-
2003; 4/15/2005
Projected
IPCCTier 1/
UN POP
IPCCTier 1/
UN POP
Third National
Communication
IPCCTieM/
UN POP
U.S. EPA-
Internal Draft 4th
National
Communication
Methodology/Adjustments
IPCC Tier 1 estimates scaled to historical estimates.
Used IPCC Tier 1 methodology to develop historical and
projected estimates. Tier 1 emissions were estimated
using UN population data, 1999 FAO protein per capita
per day intake (kg/person/year), the IPCC default
emission factor (0.01 kg N2O-N/kg sewage N produced),
and the IPCC default fraction of nitrogen in protein (0.16
kg/N/kg protein).
Used reported emissions from CRF from 1990 to 2000.
Projected emissions to 2020 by scaling projected
estimates extracted from Third National Communication
(or other country-reported data) to CRF historical
estimates.
2005 CRF supplied data for 2000; 1990 and 1995
backcast using Tier 1 rates. Created projections by
applying growth rates from Tier 1 estimated emissions.
Tier 1 emissions are described above.
Used reported 1990, 1995, and 2000 emissions.
-------
Appendix F: Methodology and Adjustments to
Approaches Used to Estimate Nitrous Oxide
Emissions from Agricultural Soils
This appendix presents the methodology and country-specific approaches the EPA used to estimate
nitrous oxide emissions from agricultural soils. EPA estimated nitrous oxide for five components of
nitrous oxide emissions from agricultural soils:
Direct emissions from commercial synthetic fertilizer application
Direct emissions from cultivation of nitrogen-fixing crops
Direct emissions from the incorporation of crop residues
Direct emissions from manure (pasture, range, and paddock and all applied manure)
Indirect emissions from agricultural soils.
Direct Emissions from Commercial Synthetic Fertilizer Application
Historical Activity Data
EPA obtained commercial synthetic fertilizer consumption data from the FAO database of agricultural
statistics, FAOSTAT. These data are available for most countries from 1990-2000. Specifically, EPA
used the consumption of nitrogenous fertilizers data, reported in metric tons of N1. EPA used several
assumptions for countries without complete data:
Ethiopia before 1993. In 1993, the former Ethiopia divided into Ethiopia and Eritrea. To estimate
the fertilizer consumption of the current Ethiopia in 1990-1992, EPA determined the ratio of the
fertilizer consumption of the current Ethiopia to the fertilizer consumption of the former Ethiopia in
1993 (FAO reports consumption for both former Ethiopia and Ethiopia in 1993). This ratio
(96 percent for fertilizer consumption) was then applied to the fertilizer consumption of the former
Ethiopia for 1990-1992 to estimate the fertilizer consumption of the current Ethiopia for 1990-
1992.
Former Soviet Union (FSU) before 1992. In 1992, the Soviet Union divided into separate
countries. The distribution of fertilizer consumption among the FSU countries in 1992 was
assumed to be the same for 1990 and 1991. Consequently, Soviet Union consumption data in
1990 and 1991 were allocated among the FSU countries by their percentages in 1992.
Projected Activity Data
EPA estimated the growth rate of fertilizer consumption for 2005 to 2020 by using the regional growth
rates available from FAO (2000) for 1995/1997 to 2015. These rates are not provided annually. EPA
then projected nitrogenous fertilizer consumption data for 2005 to 2020 based on the regional growth rate
from FAO.
Historical and Projected Emissions
As recommended in the Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories (IPCC
Guidelines) (IPCC, 1997) and IPCC Good Practice Guidance and Uncertainty Management in National
Greenhouse Gas Inventories (IPCC Good Practice Guidance) (IPCC, 2000), EPA assumed that
1 In the FAO online database, fertilizer data appear to be reported in metric tons, but data are actually reported in metric tons of N.
This was corroborated by paper copies of the FAO statistics.
June 2006 Revised Appendix F Page F-1
-------
1.25 percent of all nitrogen from fertilizer consumption, excluding the 10 percent of nitrogen in fertilizer
that volatilizes as NOX and NH3 is directly emitted as nitrous oxide. Therefore, emissions were calculated
as follows:
Gg N2O = [F country - (F country * 0.10)] * 0.0125 * 44/28 * 1000
Where:
F country = fertilizer consumption for the specified year and country in metric tons of N
0.10 = fraction of N volatilized
0.0125 = emissions factor in kg N2O-N/kg N
44/28 = N to N2O conversion
1000 = conversion from metric tons to Gg
Direct Emissions from Cultivation of Nitrogen-fixing Crops
The cultivation of nitrogen-fixing crops such as soybeans and pulses result in emissions of nitrous oxide.
Historical Activity Data
EPA obtained production statistics for soybeans and pulses from the FAOSTAT database. The
availability of data and the assumptions for each category are discussed below:
Soybeans. For 1990-2000, data on soybean production are available for all of the countries
examined except Mongolia, Bangladesh, Singapore, Armenia, Turkmenistan, Uzbekistan, Chile,
Algeria, Senegal, Israel, Jordan, and Saudi Arabia, which EPA assumed did not produce
soybeans. For 1990 no data are available for any FSU countries (including Moldova), or Ethiopia,
but the data are available for 1992 and after for FSU and 1993 and after for Ethiopia. For
Ethiopia and FSU countries, data were estimated from 1990-1992 (for FSU) and 1990-1993 (for
Ethiopia) using the same methodology used to estimate fertilizer consumption.
Total pulses. For 1990-2000, pulses were produced in all of the countries examined except
Singapore, which EPA assumed did not produce pulses.
Projected Activity Data
EPA estimated future production of soybeans and pulses using the following methodologies:
Soybeans. Neither projected soybean production data nor regional growth rates were available
for any countries. Therefore, country-specific growth rates were determined by taking historical
soybean production and deriving an average annual growth rate where; = ((2000
production/1990 production)A(1/10)) - 1. This rate was applied to 2000 onwards to obtain
projected production to 2020.
Total pulses. Projections of pulses were not available. Country-specific annual growth rates
were derived by applying the same methodology as for soybeans.
Historical and Projected Emissions
EPA first adjusted the crop production statistics to kg N by multiplying the crops' residue-to-crop-mass
ratios and dry matter fractions for residue (Strehler and Stutzle, 1987). To convert to units of nitrogen,
EPA applied the IPCC recommendation that 3 percent of the total crop dry mass for all crops was
nitrogen (IPCC, 1997).2 To convert to kg N and account for the aboveground biomass nitrogen, EPA
used the following equation:
kg N = Production (metric ton) * (1 + residue-to-crop ratio) * dry matter fraction * N content * 1000
2 For the pulse factors, EPA used an average of the residue-to-crop-mass ratios and dry matter fractions of peas, beans, and
peanuts. Also, the crop production statistics account for only the mass of the crop rather than the entire aboveground plant.
June 2006 Revised Appendix F Page F-2
-------
Units in kg N were then multiplied by the emissions factor of 0.0125 kg N2O-N/kg N and converted from
kg to Gg by multiplying by 1/10A6. Finally Gg N2O-N were converted to Gg N2O by multiplying by 44/28,
the molecular weight ratio of N2O to N.
Direct Emissions from the Incorporation of Crop Residues
Residues from corn, wheat, beans, and pulses are typically incorporated into soils. Incorporation of crop
residues directly adds nitrogen to the soil, resulting in an increase in nitrous oxide emissions.
Historical Activity Data
FAO provided historical production statistics for corn, wheat, beans, and pulses; residues of which are
typically incorporated into soils. Bean and pulse production were estimated in the previous section.
Historical production data for corn and wheat were available for all countries examined from 1990-2000,
with the following exceptions: Viet Nam, Indonesia, Philippines, and Senegal (no wheat data), Mongolia
(no corn data), and Singapore (no corn or wheat data) (FAO, 2002). For these countries EPA assumed
zero production for these crops.
Historical Emissions
EPA assumed that 75 percent of all crop residues are returned to the soils in developing countries (IPCC,
1997). Crop residue biomass, in dry matter kg, was derived based on the following equation:
Crop residue biomass (kg N) = Production (metric ton) * (residue-to-crop ratio) * dry matter
fraction * N content * 75% applied to fields * 1000 kg/metric ton
The data for these calculations were obtained from Table 4.16 in the IPCC Good Practice Guidance.
IPCC estimates that 1.25 percent of all nitrogen from incorporated residues is directly emitted as nitrous
oxide, so crop residue biomass was multiplied by 0.0125 to convert from kg N to kg N2O-N. The estimate
was then converted from kg to Gg N2O by multiplying the value in kg by 44/28, the molecular weight ratio
of N2Oto N.
Projected Activity Data and Emissions
EPA assumed that nitrous oxide emissions from incorporation of crop residue grow in proportion to
production. Using historical average annual growth rates from 1990-2000 (derived through same
methodology as soybean growth rates), the production of corn and wheat was estimated for 2005-2020.
EPA calculated projected crop residue biomass using the projected production estimates in the equation
listed under historical emissions.
Direct Emissions from Manure (Pasture, Range, and Paddock, and All Applied
Manure)
Direct nitrous oxide emissions result from livestock manure that is applied to soils either through daily
spread operations (all applied manure) or direct deposition on pastures, range, and paddocks (PRP) by
grazing livestock.
Historical Activity Data
EPA obtained animal population from FAOSTAT for most countries for 1990, 1995, and 2000 (FAO,
2001). The exceptions include FSU countries (including Moldova), and Ethiopia, none of which have data
until 1995. The ratio of the current countries' animal populations to the former countries' animal
populations in 1995 was established as described in previous sections. The animal populations from the
former countries in 1990 were multiplied by this ratio to obtain an estimate for the animal population of the
current country in 1990.
June 2006 Revised Appendix F Page F-3
-------
Historical Emissions
EPA calculated total livestock nitrogen excretion, for each animal type (non-dairy cattle, dairy cattle,
swine, sheep, poultry, and others) and divided it among animal waste management systems using IPCC
default assumptions. EPA assumed that 20 percent of total annual excreted livestock nitrogen was
volatilized (IPCC, 1997). Finally, EPA separated the value of the remainder of the excreted livestock
nitrogen into manure applied to soils and PRP manure. Each was then multiplied by the emission factor
specific to the animal manure management systems; 0.0125 kg N2O-N/kg N excreted for manure applied
to soils and 0.02 kg N2O-N/ kg N excreted for manure in PRP. The complete equations are as follows:
Emissions from manure applied to soils:
kg N2O-N from manure applied to soils = kg N applied to soils * 0.8 non-volatilized N * 0.0125 kg
N2O-N/kg N
Emissions from manure applied to PRP:
kg N20-N from PRP manure = kg N applied to PRP * 0.02 kg N2O-N/kg N
Projected Emissions
EPA assumed that emissions would grow at the same rate as methane emissions from manure, as
reported by five-year increments in the methane and nitrous oxide emissions from manure management
section of this report (Section 7.2.9). This approach was taken as projections of animal populations are
not available.
Indirect Emissions from Agricultural Soils
This component accounts for nitrous oxide that is emitted indirectly from nitrogen applied as fertilizer and
excreted by livestock. Nitrous oxide enters the atmosphere indirectly through one of two pathways:
1) atmospheric deposition of NOX and NH3 (originating from fertilizer use and livestock excretion of
nitrogen), and 2) leaching and runoff of nitrogen from fertilizer applied to agricultural fields and from
livestock excretion. Emissions from each of these pathways are described below.
Emissions from fertilizer consumption. Nitrogen consumption data and forecasts, determined for
the fertilizer application section, were used to calculate indirect nitrous oxide emissions from
fertilizer consumption. The IPCC recommends that 10 percent of the applied synthetic fertilizer
nitrogen volatilizes to NH3 and NOX, and one percent of the total volatilized nitrogen was emitted
as N2O (IPCC, 1997). To estimate emissions from leaching and run-off, EPA uses the IPCC
recommendation that 30 percent of the total nitrogen applied is lost to leaching and surface
runoff, and 2.5 percent of this lost nitrogen is emitted as nitrous oxide (IPCC, 1997).
Emissions from livestock excretion. Historical estimates of total livestock excretion, as calculated
under the nitrous oxide emissions from livestock manure management section, were used to
calculate historical nitrous oxide emissions from livestock excretion. According to the IPCC,
20 percent of nitrous oxide in livestock excretion volatilizes to NH3 and NOX, and that one percent
of the total volatilized nitrogen is emitted as nitrous oxide (IPCC, 1997). To estimate emissions
from leaching and runoff, EPA used the IPCC recommendation that 30 percent of the total
nitrogen applied is lost to leaching and surface runoff, and 2.5 percent of this lost nitrogen is
emitted as nitrous oxide (IPCC 1997). Livestock excretion projections for 2005-2020 were not
available. Therefore, the indirect emissions from animal waste were expected to grow at the
same rate as direct emissions from animal waste, as determined in the methane and nitrous
oxide emissions from livestock manure management section (Section 7.2.9).
June 2006 Revised Appendix F Page F-4
-------
Appendix G: U.S. EPA Vintaging Model
Framework
Vintaging Model Overview
The Vintaging Model estimates emissions from six industrial sectors: refrigeration and air-conditioning,
foams, aerosols, solvents, fire extinguishing, and sterilization. Within these sectors, over 40
independently modeled end-uses exist. The model requires information on the market growth for each of
the end-uses, as well as a history of the market transition from ozone-depleting substances (ODS) to
alternatives. As ODS are phased out, a percentage of the market share originally filled by the ODS is
allocated to each of its substitutes.
The model, named for its method of tracking the emissions of annual "vintages" of new equipment that
enter into service, is a "bottom-up" model. It models the consumption of chemicals based on estimates of
the quantity of equipment or products sold, serviced, and retired each year, and the amount of the
chemical required to manufacture and/or maintain the equipment. The Vintaging Model makes use of this
market information to build an inventory of the in-use stocks of the equipment in each of the end-uses.
Emissions are estimated by applying annual leak rates, service emission rates, and disposal emission
rates to each population of equipment. By aggregating the emission and consumption output from the
different end-uses, the model produces estimates of total annual use and emissions of each chemical.
For the purpose of projecting the use and emissions of chemicals into the future, the available information
about probable evolutions of the end-use market is incorporated into the model.
The following sections discuss the forms of the estimation equations used in the Vintaging Model for each
broad end-use category. These equations are applied separately for each chemical used within each of
over 40 different end-uses. In the majority of these end-uses, more than one ODS substitute chemical is
used.
In general, the modeled emissions are a function of the amount of chemical consumed in each end-use
market. Estimates of the consumption of ODS alternatives can be inferred by extrapolating forward in
time from the amount of regulated ODS used in the early 1990s, adjusted for factors that might affect
ODS substitute consumption, such as different charge sizes and lower emission rates. Using data
gleaned from a variety of sources, assessments are made regarding which alternatives will likely be used,
and what fraction of the ODS market in each end-use will be captured by that alternative. By combining
this information with estimates of the total end-use market growth, a consumption value is estimated for
each chemical used within each end-use.
Emissions Equations
Refrigeration and Air-Conditioning
For refrigeration and air conditioning products, emission calculations are split into two categories:
emissions during equipment lifetime, which arise from annual leakage and service losses, and disposal
emissions, which occur at the time of discard. Equation 1 calculates the lifetime emissions from leakage
and service, and Equation 2 calculates the emissions resulting from disposal of the equipment. These
lifetime emissions and disposal emissions are added to calculate the total emissions from refrigeration
and air-conditioning (Equation 3). As new technologies replace older ones, it is generally assumed that
there are improvements in their leak, service, and disposal emission rates. In addition, the charge size
assumed for equipment using an ODS substitute may be different than that for equipment using the ODS.
Lifetime emissions from any piece of equipment include both the amount of chemical leaked during
equipment operation and during service, including recharges. Emissions from leakage and servicing can
be expressed as follows:
ESj = (la + ls) x E QCj_i+i for i=1 -^ k Eq. 1
June 2006 Revised Appendix G Page G-1
-------
Where:
Qc
Emissions from equipment serviced. Emissions in year j from normal leakage and
servicing (recharging) of equipment.
Annual leak rate. Average annual leak rate during normal equipment operation
(expressed as a percentage of total chemical charge).
Service leak rate. Average leakage during equipment servicing (expressed as a
percentage of total chemical charge).
Quantity of chemical in new equipment. Total amount of a specific chemical used to
charge new equipment in a given year, by weight.
Lifetime. The average lifetime of the equipment.
Year of emission.
Counter. Runs from 1 to lifetime (k).
The disposal emission equations assume that a certain percentage of the chemical charge will be emitted
to the atmosphere when that vintage is discarded. Disposal emissions are thus a function of the quantity
of chemical contained in the retiring equipment fleet and the proportion of chemical released at disposal:
Where:
Edj
Qc
rm
re
k
j
Where:
j = QCj.k x [1 - (rm x re)]
Eq.2
Emissions from equipment disposed. Emissions in year j from the disposal of equipment.
Quantity of chemical in new equipment. Total amount of a specific chemical used to
charge new equipment one lifetime (k) ago (e.g., j - k), by weight.
Chemical remaining. Amount of chemical remaining in equipment at the time of disposal
(expressed as a percentage of total chemical charge)
Chemical recovery rate. Amount of chemical that is recovered just prior to disposal
(expressed as a percentage of chemical remaining at disposal (rm))
Lifetime. The average lifetime of the equipment.
Year of emission.
E = ESj + Edj Eq. 3
EJ = Total emissions. Emissions from refrigeration and air conditioning equipment in year j.
Es = Emissions from equipment serviced. Emissions in a given year from normal leakage and
servicing (recharging) of equipment.
Ed = Emissions from equipment disposed. Emissions in a given year from the disposal of
equipment.
j = Year of emission.
Aerosols
All MFCs used in aerosols are assumed to be emitted in the year of manufacture. Since there is currently
no aerosol recycling, it is assumed that all of the annual production of aerosol propellants is released to
the atmosphere. Equation 4 describes the emissions from the aerosols sector.
Where:
Qc
EJ = Qq
Eq. 4
Emissions. Total emissions of a specific chemical in year j from use in aerosol products,
by weight.
Quantity of chemical. Total quantity of a specific chemical contained in aerosol products
sold in a given year, by weight.
Year of Emission.
June 2006 Revised
Appendix G
Page G-2
-------
Solvents
Generally during the solvent cleaning process, a portion of used solvent is assumed to remain in the
liquid phase and is not emitted as gas. Thus, emissions are considered "incomplete," and are set as a
percentage of the amount of solvent consumed in a year. The remainder of the consumed solvent is
assumed to be reused or disposed without being released to the atmosphere. Equation 5 calculates
emissions from solvent applications.
Ej = I x Qq Eq. 5
Where:
EJ = Emissions. Total emissions of a specific chemical in year j from use in solvent
applications, by weight.
I = Percent leakage. The percentage of the total chemical that is lost to the atmosphere,
assumed to be 90 percent.
Qc = Quantity of chemical. Total quantity of a specific chemical sold for use in solvent
applications in a given year, by weight.
j = Year of emission.
Fire Extinguishing
Total emissions from fire extinguishing are assumed, in aggregate, to equal a percentage of the total
quantity of chemical in operation at a given time (Equation 6). For modeling purposes, it is assumed that
fire extinguishing equipment leaks at a constant rate for an average equipment lifetime.
Ej = r x z QCj.i+1 for i=1>k Eq. 6
Where:
EJ = Emissions. Total emissions of a specific chemical in year j for fire extinguishing
equipment, by weight.
r = Percent Released. The percentage of the total chemical in operation that is released to
the atmosphere.
Qc = Quantity of chemical. Total amount of a specific chemical used in new fire extinguishing
equipment one lifetime (k) ago (e.g., j - k + 1), by weight.
i = Counter. Runs from 1 to lifetime (k).
j = Year of emission.
k = Lifetime. The average lifetime of the equipment.
Foam Blowing
Foams are given emission profiles depending on the foam type (open cell or closed cell). Open cell
foams are assumed to be 100 percent emissive in the year of manufacture, as described in Equation 7
below. Closed cell foams are assumed to emit a portion of their total HFC content upon manufacture, a
portion at a constant rate over the lifetime of the foam, a portion at disposal, and a portion post-disposal,
as described in Equations 8 through 12, below.1
1 Emissions from foams may vary because of handling and disposal of the foam; shredding of foams may increase emissions, while
landfilling of foams may abate some emissions (Scheutz and Kjeldsen, 2002; Scheutz and Kjeldsen, 2003). Average annual
emissions are assumed in the model, which may not fully account for the range of foam handling and disposal practices.
June 2006 Revised Appendix G Page G-3
-------
Open-Cell Foam
Ej = Qq Eq. 7
Where:
EJ = Emissions. Total emissions of a specific chemical in year j used for open-cell foam
blowing, by weight.
Qc = Quantity of chemical. Total amount of a specific chemical used for open-cell foam
blowing in a given year, by weight.
j = Year of emission.
Closed-Cell Foam
Emissions from foams occur at many different stages, including manufacturing, lifetime, disposal and
post-disposal.
Manufacturing emissions occur in the year of foam manufacture, and are calculated as presented in
Equation 8.
En"ij = Im x Qq Eq. 8
Where:
Errij = Emissions from manufacturing. Total emissions of a specific chemical in year j due to
manufacturing losses, by weight.
Im = Loss Rate. Percent of original blowing agent emitted during foam manufacture.
Qc = Quantity of chemical. Total amount of a specific chemical used to manufacture closed-
cell foams in a given year.
j = Year of emission.
Lifetime emissions occur annually from closed cell foams throughout the lifetime of the foam, as
calculated using Equation 9.
EUJ = lu x ZQCj_i+i for i = 1 -^ k Eq. 9
Where:
EUJ = Emissions from lifetime losses. Total emissions of a specific chemical in year j due to
lifetime losses during use, by weight.
lu = Leak Rate. Percent of original blowing agent emitted during lifetime use.
Qc = Quantity of chemical. Total amount of a specific chemical used to manufacture closed-
cell foams in a given year.
k = Lifetime. Average lifetime of foam product.
i = Counter. Runs from 1 to lifetime (k).
j = Year of Emission.
Disposal emissions occur in the year the foam is disposed, and are calculated as presented in
Equation 10.
Edj = Id x QCj.k Eq. 10
Where:
Edj = Emissions from disposal. Total emissions of a specific chemical in year j at disposal, by
weight.
Id = Loss Rate. Percent of original blowing agent emitted at disposal.
Qc = Quantity of chemical. Total amount of a specific chemical used to manufacture closed-
cell foams in a given year.
k = Lifetime. Average lifetime of foam product.
j = Year of emission.
June 2006 Revised Appendix G Page G-4
-------
Post-disposal emissions occur in the years after the foam is disposed, and are assumed to occur while
the disposed foam is in a landfill. Currently, the only foam type assumed to have post-disposal emissions
is polyurethane appliance foam, which is expected to continue to emit for 32 years post-disposal, and are
calculated as presented in Equation 11.
Epj = Ip x ZQCj_m for m = k -^ k + 32 Eq. 11
Where:
Epj = Emissions post disposal. Total post-disposal emissions of a specific chemical in year j,
by weight.
Ip = Leak rate. Percent of original blowing agent emitted post disposal.
Qc = Quantity of chemical. Total amount of a specific chemical used in closed-cell foams in a
given year.
k = Lifetime. Average lifetime of foam product.
m = Counter. Runs from lifetime (k) to (k + 32).
j = Year of emission.
To calculate total emissions from foams in any given year, emissions from all foam stages must be
summed, as presented in Equation 12.
Ej = Emj + EUJ + Edj + Epj Eq. 12
Where:
EJ = Total emissions. Total emissions of a specific chemical in year j, by weight.
Errij = Emissions from manufacturing losses. Total emissions of a specific chemical in year j
due to manufacturing losses, by weight.
EUJ = Emissions from lifetime losses. Total emissions of a specific chemical in year j due to
lifetime losses during use, by weight.
Edj = Emissions at disposal. Total emissions of a specific chemical in year j due to disposal, by
weight.
Epj = Emissions post disposal. Total post-disposal emissions of a specific chemical in year j,
by weight.
Sterilization
For sterilization applications, all chemicals that are used in the equipment in any given year are assumed
to be emitted in that year, as shown in Equation 13.
Ej = Qq Eq. 13
Where:
EJ = Emissions. Total emissions of a specific chemical in year j from use in sterilization
equipment, by weight.
Qc = Quantity of chemical. Total quantity of a specific chemical used in sterilization equipment
in a given year, by weight.
j = Year of emission.
Model Output
By repeating these calculations for each year from 1990-2020, the Vintaging Model creates annual
profiles of use and emissions for ODS and ODS substitutes. The results can be shown for each year in
two ways: 1) on a chemical-by-chemical basis, summed across the end-uses, or 2) on an end-use basis.
Values for use and emissions are calculated both in metric tons and in million metric tons of carbon
dioxide equivalents (MtCO2eq). The conversion of metric tons of chemical to MtCO2eq is accomplished
through a linear scaling of tonnage by the global warming potential (GWP) of each chemical. The GWP
values that are used in the model correspond to those published in the IPCC Second Assessment Report
(SAR)(IPCC, 1996).
June 2006 Revised Appendix G Page G-5
-------
Appendix H: Regional Definitions
Africa
Algeria
Democratic-
Republic of-
Congo (Kinshasa)
Rest of Africa1
Angola
Benin
Botswana
Burundi
Burkina Faso
Cameroon
Cape Verde
Central African-
Republic
China/CPA
Cambodia2
China
Latin America
Argentina
Bolivia
Brazil
Egypt
Ethiopia
Nigeria
Senegal
Chad
Comoros
Cote d'lvoire
Djibouti
Equatorial Guinea
Eritrea
Gabon
Gambia
Ghana
South Africa
Uganda
Guinea
Guinea Bissau
Kenya
Lesotho
Liberia
Libya
Madagascar
Malawi
Mali
Mauritania
Mauritius
Morocco
Mozambique
Namibia
Niger
Republic ofthe-
Congo-
(Brazzaville)
Democratic People's-
Republic of Korea (North Korea)
Hong Kong
Laos2
Chile
Colombia
Ecuador
Mongolia
Mexico
Peru
Uruguay
Venezuela
Rwanda
Sao Tome and
Principe
Sierra Leone
Somalia
Sudan
Swaziland
Togo
Tunisia
Vietnam
Macau
United Republic-
of Tanzania
Zambia
Zimbabwe
Rest of Latin America1
Antigua and-
Barbuda
Bahamas
Barbados
Belize
Middle East
Iran
Iraq
Costa Rica
Cuba
Dominica
Dominican-
Republic
Israel
Jordan
El-Salvador
Grenada
Guatemala
Guyana
Haiti
Kuwait
Saudi Arabia
Honduras
Jamaica
Nicaragua
Panama
Paraguay
United Arab-
Emirates
St. Kitts and
Nevis
St. Lucia
St. Vincent and-
the Grenadines
Suriname
Trinidad and-
Tobago
Rest of Middle East1
Bahrain Lebanon
Oman
Qatar
Syria
Yemen
June 2006 Revised
Appendix H
Page H-1
-------
Appendix H. Regional Definitions (Cont.)
Non- EU Eastern Europe
Albania
Croatia A
The former Republic of Yugoslavia-Macedonia
Rest of Eastern Europe1
Bosnia & Herzegovina
Serbia & Montenegro
Non-EU FSU
Armenia
Azerbaijan
Belarus A
Georgia
Kazakhstan
Kyrgyzstan2
Moldova
Russian
Federation'
Tajikistan
Turkmenistan
Ukraine A
Uzbekistan
OECD1990&EU3
Australia AAT
Canada A'°
Japan A'°
New Zealand AAT
United States A'°'T
EU-25:
Austria A'°
Belgium A'°
Czech Republic'
Denmark A'°'T
Estonia A
Finland A'°
France
A,0,T
Germany
A,0
Greece A'°
Hungary A
Ireland A'°
Italy A<°
Latvia A
Lithuania A
Luxembourg A'° United Kingdom
Netherlands^0 (U.K.)AAT
Poland A "'" ;-
Portugal A'°
Slovak Republic
Slovenia A
Spain A'°
Sweden A'°
umieu r\niL
(U.K.)AAT~
EU Accession:
Bulgaria A
Romania A
Non-EU Western
Europe'.
Iceland A'°
Liechtenstein A
MonacoA
Norway A'°'T
Switzerland A'°
Turkey A'°
Rest of OECD1990&EU1
Rest of EU-25:
Cyprus
Malta
Rest of Non-EU Western Europe:
Holy See
San Marino
Andorra
South & Southeast Asia
Bangladesh Indonesia Nepal Philippines
India Myanmar Pakistan
Rest of South & Southeast Asia1
Afghanistan Fiji Marshall Islands Papua New-
Bhutan Kiribati Micronesia Guinea
Brunei Darussalam Malaysia Nauru Samoa
East Timor Maldives Palau Islands Seychelles
Republic of Korea
(South Korea)
Solomon Islands
Sri Lanka
Tonga
Singapore
Thailand
Taiwan
Tuvalu
Vanuatu
Codes:
A - Annex I countries.
O - OECD countries as of 1990.
T - Countries with territories whose emissions are assumed included in country totals.
Notes:
1. In this report, when emissions totals are presented for a region, the regional sum includes the estimates for all of the individually
reported countries AND the aggregated value for the "Rest Of countries. Thus, the emissions total for the "Middle East" found in
the graphs and Appendices A-D, includes the sum of Iran, Iraq, Israel, Jordan, Kuwait, Saudi Arabia, the United Arab Emirates
AND the smaller emitters already aggregated under "Rest of Middle East."
2. Agricultural Soils includes emissions for Cambodia and Laos under "Rest of China/CPA" and emissions for Kyrgyzstan and
Tajikistan under "Rest of non-EU FSU." For all other categories, these countries are reported independently.
3. The Holy See, Liechtenstein, Monaco, Andorra, and San Marino are also included in the OECD90 & EU grouping.
June 2006 Revised
Appendix H
Page H-2
-------
Appendix 1-1. HCFC-22 Production Activity
Data for Selected Countries (Metric Tons)
Country
United States
China
Japan
United Kingdom
Netherlands
Germany
Italy
France
India
Spain
South Korea
Greece
Mexico
Russia
Venezuela
Brazil
South Africa
Argentina
1990
138,900
10,200
42,093
14,904
12,642
1 1 ,276
8,934
25,319
3,226
8,842
3,480
2,300
3,011
9,524
1,872
3,644
411
583
1995
154,700
15,000
69,007
27,299
18,958
20,475
10,097
18,579
6,855
12,133
6,692
3,792
2,570
4,019
1,903
4,591
1,239
N/A
2000
186,905
94,762
58,290
22,765
22,132
17,074
15,809
15,493
13,430
10,118
10,460
7,588
7,487
3,079
562
405
N/A
N/A
2005
138,369
183,571
65,715
17,112
16,637
12,834
11,883
1 1 ,646
17,469
7,605
13,098
5,704
9,241
2,522
643
483
N/A
N/A
2010
104,495
200,000
68,242
11,532
11,211
8,649
8,008
7,848
22,724
5,125
16,400
0
1 1 ,406
1,974
734
576
N/A
N/A
2020
95,452
259,192
76,140
6,825
6,635
5,119
4,740
4,645
26,163
3,033
18,007
0
12,302
911
720
596
N/A
N/A
N/A = Data not available.
Sources: CEH, 2001; Oberthur, S., 2001; U.S. EPA, 2005; SROC, 2005; JICOP, 2006.
June 2006 Revised
Appendix I
Page 1-1
-------
Appendix 1-2. Activity Data for Electric
Power Systems Net Electricity Consumption
by Selected Countries (Billion Kilowatt
Hours)
Country
United States3
Russia
Japan3
China
Germany3
Canada
France3
United Kingdom3
India
Brazil
Ukraine
Italy3
South Africa
Australia
Spain3
1990
2,837
955
764
551
489
435
324
290
257
229
235
222
144
136
133
1995
3,164
740
881
884
473
468
366
303
370
288
169
247
161
153
151
2000
3,592
761
940
1,201
502
511
407
343
493
361
145
282
184
182
201
2003
3,656
812
946
1,671
510
521
433
346
519
371
153
302
197
201
231
Sources: EIA, 2002.
3 For the U.S., Japan, Germany, France, U.K, Italy and Spain (as well as other EU-25+3
countries) net electricity consumption is not used to estimate emissions. U.S. SF6 emissions
from electric power systems were obtained from U.S. EPA (U.S. EPA, 2005). EU-25+3 and
Japan SF6 emissions were obtained from Ecofys, 2005 and Yokota et al., 2005, respectively.
Estimated Global SF6 Emissions
Year
1990
1995
2000
2003
Estimated
Emissions3
(metric tons)
1,772
1,404
1,121
1,737
3 Estimates based on RAND survey of SF6 manufacturers, including reported sales to utilities in a
given year and reported sales to equipment manufacturers 40 years previous (Smythe, 2004).
RAND data are adjusted upward by 16 percent to account for consumption and emissions in
Russia and China. See methodology section for more detail.
June 2006 Revised Appendix I Pagel-2
-------
Appendix l-2b. Developing Country-/Region-
Specific Net Electricity Consumption Annual
Growth Ratesa>b (percent)
Country
China
India
South Korea
Other Asia
Middle East
Africa
Brazil
Other Central/South America
2010
5.9
3.9
3.7
3.8
3.2
3.7
3.1
3.7
2020
5.5
3.8
2.9
3.4
3.1
3.6
3.6
4.1
Source: EIA, 2002.
a Averaged over 10-year periods.
b Country-specific SF6 emissions grow at different rates in developed and developing countries.
For all developed countries, except the U.S., Japan, and EU-25+3, emissions remain constant
from 2003 levels through 2020. For developing countries, emissions are estimated to grow at the
same rate as country- or region-specific net electricity consumption projections.
June 2006 Revised Appendix I Pagel-3
-------
Appendix 1-3. Aluminum Production Activity
Data for Selected Countries (Thousand
Metric Tons)
Country
United States
Russia
Canada
Australia
Brazil
Norway
China
Germany
Spain
France
United Kingdom
India
Greece
Ukraine
Slovakia
1990
4,048
2,997
1,623
1,243
923
817
812
638
411
363
250
242
120
92
54
1995
3,375
2,757
2,002
1,288
1,177
831
1,141
509
258
445
332
332
162
69
79
2000
3,668
2,544
2,174
1,732
1,130
994
2,794
608
308
532
397
378
193
63
122
2010
3,310
2,774
2,940
1,922
1,534
1,108
6,390
979
222
528
423
1,106
204
110
186
2020
3,310
2,737
3,126
1,922
2,069
1,093
6,505
1,026
227
509
408
1,163
197
116
196
Sources: IEA, 2000; IAI, 2005 (China); U.S. EPA, 2005 (U.S.).
June 2006 Revised Appendix I Pagel-4
-------
Appendix 1-4. Magnesium Activity Data for
Selected Countries (Includes Primary,
Secondary, and Die Casting Production)
(Metric Tons)
Country
United States
Russia
Norway
Canada
Ukraine
France
Germany
Japan
Brazil
Italy
China0
Kazakhstan
United Kingdom
Spain
Portugal
Israel
1990
169,610
64,062
50,817
26,768
23,896
14,000b
N/A
13,293
9,604
N/A
3,789
1,661
N/A
N/A
N/A
0
1995
179,631
38,612
30,642
50,792
10,076
14,450b
N/A
10,157
11,716
N/A
95,204
9,267
N/A
N/A
N/A
0
2000
141,983
48,456
55,010
94,409
104
2,000a
17,530a
9,045
1 1 ,463
3,000a
197,350
10,791
600a
600a
300a
41,119
2010
211,410
65,351
30,927
37,050
12,857
4,187
36,697
4,756
21,950
6,280
416,613
18,673
1,256
1,256
628
61,329
2020
298,727
80,791
47,016
42,773
15,294
6,365
55,787
7,593
31,906
9,547
773,568
22,486
1,909
1,909
916
82,220
3 2001 values. Includes only production/processing that uses SF6.
b Includes primary production only. Casting emissions estimated separately.
c Figures for China include production/processing that uses SO2 as well as production/processing
that uses SF6.
N/A = Not Applicable; emissions estimate derived without direct use of activity data.
Sources: USGS, 2002; Ward's, 2001; U.S. EPA, 2005 (U.S.); Harnisch and Schwarz, 2003
(France, Germany, Italy, U.K., Spain, and Portugal).
June 2006 Revised Appendix I Pagel-5
-------
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Environmental Protection
Agency
Office of Atmospheric Programs
Climate Change Division (6202J)
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, NW
Washington, DC 20460
EPA»430»R»06~003
June 2006
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