of U.S. Greenhouse Gas
Emissions and Sinks: 1990-2005
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How to Obtain Copies
You can electronically download this document on the U .S. EPA's Clinkate Change homepage
emissions/usinventoryreport.html>. To request free copies of this report
Publications (NSCEP) at (800) 490-9198, or visit the NSCEP web s
All data tables of this document are available for the full time series 1990 through 2005, inclusive, at the internet site
mentioned above.
For Further Information
Contact Mr. Leif Hockstad, Environmental Protection Agency, (202
Or Ms. Lisa Hanle, Environmental Protection Agency, (202) 343-9^ 34
For more information regarding climate change and greenhouse ga
gov/climatechange/index .html>.
Released for printing: April 15,2007
Key Categories
The photos on the front and back cover of this report depict the eigh
The IPCC's Good Practice Guidance (IPCC 2000) defines a key ca
within the national inventory system because its estimate has a sign ficant
greenhouse gases in terms of the absolute level of emissions, the tre
are sources or sinks that have the greatest contribution to the absolut
covered by the time series. Key category names can differ from thos
conventions necessary to comply with UNFCCC reporting guidelin
Carbon Dioxide Emissions from Non-Energy Use f Fuels
Rather than being combusted for energy, fuels c
reagents in fabricating other materials. These fo
perspective since they often provide long-term s
increased 21 percent since 1990.
single
Direct Nitrous Oxide Emissions from Agricultural
(Photo by Lynn Belts, USDA Natural Resources Conservation
Agricultural soil management is the largest
accounting for 5 percent of U.S. greenhouse gas ei nissions in 2005
on the amounts of nitrogen inputs such as fertilize
precipitation, and other factors. Emissions from t
and nitrogen inputs, and have not changed signifi
at .
343-9432, hockstad.leif@epa.gov.
, hanle.lisa@epa.gov.
emissions, see the EPA web site at
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INVENTORY OF U.S. GREENHOUSE GAS
EMISSIONS AND SINKS:
1990-2O05
April 15,2007
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
U.S.A.
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Acknowledgments
The Environmental Protection Agency would like to acknowledge the many individual and organizational
contributors to this document, without whose efforts this report would not be complete. Although the complete
list of researchers, government employees, and consultants who have provided technical and editorial support
is too long to list here, EPA's Office of Atmospheric Programs would like to thank some key contributors and reviewers
whose work has significantly improved this year's report.
Work on fuel combustion and industrial process emissions was led by Leif Hockstad and Mausami Desai. Work on
methane emissions from the energy sector was directed by Lisa Hanle. Calculations for the waste sector were led by Melissa
Weitz. Tom Wirth directed work on the Agriculture chapter, and Kimberly Klunich directed work on the Land Use, Land-
Use Change, and Forestry chapter. Work on emissions of HFCs, PFCs, and SF6 was directed by Deborah Ottinger and Dave
Godwin. John Davies directed the work on mobile combustion.
Within the EPA, other Offices also contributed data, analysis, and technical review for this report. The Office of
Transportation and Air Quality and the Office of Air Quality Planning and Standards provided analysis and review for several
of the source categories addressed in this report. The Office of Solid Waste and the Office of Research and Development
also contributed analysis and research.
The Energy Information Administration and the Department of Energy contributed invaluable data and analysis on
numerous energy-related topics. The U.S. Forest Service prepared the forest carbon inventory, and the Department of
Agriculture's Agricultural Research Service and the Natural Resource Ecology Laboratory at Colorado State University
contributed leading research on nitrous oxide and carbon fluxes from soils.
Other government agencies have contributed data as well, including the U.S. Geological Survey, the Federal Highway
Administration, the Department of Transportation, the Bureau of Transportation Statistics, the Department of Commerce,
the National Agricultural Statistics Service, the Federal Aviation Administration, and the Department of Defense.
We would also like to thank Marian Martin Van Pelt, Randall Freed, and their staff at ICF International's Energy and
Resources Practice, including Don Robinson, Diana Pape, Susan Asam, Michael Grant, Ravi Kantamaneni, Robert Lanza,
Chris Steuer, Lauren Flinn, Kamala Jayaraman, Jeremy Scharfenberg, Mollie Averyt, Sarah Shapiro, Stacy Hetzel, Brian
Gillis, Zachary Schaffer, Vineet Aggarwal, Colin McGroarty, Hemant Mallya, Lauren Pederson, Erin Fraser, Joseph Herr,
Victoria Thompson, Jean Kim, Pankaj Kumar, David Berv, Allison Osborne, and Toby Krasney for synthesizing this report
and preparing many of the individual analyses. Eastern Research Group, RTI International, Raven Ridge Resources, and
Arcadis also provided significant analytical support.
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The United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas
Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention
on Climate Change (UNFCCC).1 Under decision 3/CP.5 of the UNFCCC Conference of the Parties, national
inventories for UNFCCC Annex I parties should be provided to the UNFCCC Secretariat each year by April 15.
In an effort to engage the public and researchers across the country, the EPA has instituted an annual public review
and comment process for this document. The availability of the draft document is announced via Federal Register Notice
and is posted on the EPA web site.2 Copies are also mailed upon request. The public comment period is generally limited
to 30 days; however, comments received after the closure of the public comment period are accepted and considered for
the next edition of this annual report.
1 See Article 4(1 )(a) of the United Nations Framework Convention on Climate Change .
2 See .
Ill
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Table of Contents
Acknowledgments — i
Table of Contents v
List of Tables, Figures, and Boxes viii
Tables viii
Figures xvi
Boxes xviii
Executive Summary , ES-1
ES.l. Background Information ES-2
ES.2. Recent Trends in U.S. Greenhouse Gas Emissions and Sinks ES-3
ES.3. Overview of Sector Emissions and Trends ES-10
ES.4. Other Information ES-14
1, Introduction , 1-1
1.1. Background Information 1-2
1.2. Institutional Arrangements 1-7
1.3. Inventory Process 1-7
1.4. Methodology and Data Sources 1-10
1.5. Key Categories 1-11
1.6. Quality Assurance and Quality Control (QA/QC) 1-11
1.7. Uncertainty Analysis of Emission Estimates 1-13
1.8. Completeness 1-15
1.9. Organization of Report 1-15
2. Trends in Greenhouse Gas Emissions 2-1
2.1. Recent Trends in U.S. Greenhouse Gas Emissions 2-1
2.2. Emissions by Economic Sector 2-22
2.3. Indirect Greenhouse Gas Emissions (CO, NOX, NMVOCs, and SO2) 2-28
3. Energy , 3-1
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source Category 1 A) 3-3
3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-19
3.3. Stationary Combustion (excluding CO2) (IPCC Source Category 1A) 3-23
3.4. Mobile Combustion (excluding CO2) (IPCC Source Category 1A) 3-28
3.5. Coal Mining (IPCC Source Category IBla) 3-34
3.6. Abandoned Underground Coal Mines (IPCC Source Category IBla) 3-37
3.7. Natural Gas Systems (IPCC Source Category lB2b) 3-40
3.8. Petroleum Systems (IPCC Source Category lB2a) 3-44
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3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5) 3-47
3.10. Energy Sources of Indirect Greenhouse Gas Emissions 3-51
3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items) 3-51
3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1 A) 3-56
4. Industrial Processes 4-1
4.1. Cement Manufacture (IPCC Source Category 2A1) 4-4
4.2. Iron and Steel Production (IPCC Source Category 2C1) 4-6
4.3. Ammonia Manufacture and Urea Application (IPCC Source Category 2B1) 4-10
4.4. Lime Manufacture (IPCC Source Category 2A2) 4-13
4.5. Limestone and Dolomite Use (IPCC Source Category 2A3) 4-16
4.6. Soda Ash Manufacture and Consumption (IPCC Source Category 2A4) 4-18
4.7. Titanium Dioxide Production (IPCC Source Category 2B5) 4-20
4.8. Ferroalloy Production (IPCC Source Category 2C2) 4-22
4.9. Phosphoric Acid Production (IPCC Source Category 2B5) 4-25
4.10. Carbon Dioxide Consumption (IPCC Source Category 2B5) 4-27
4.11. Zinc Production (IPCC Source Category 2C5) 4-30
4.12. Lead Production (IPCC Source Category 2C5) 4-33
4.13. Petrochemical Production (IPCC Source Category 2B5) 4-34
4.14. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption 4-37
4.15. Nitric Acid Production (IPCC Source Category 2B2) 4-39
4.16. Adipic Acid Production (IPCC Source Category 2B3) 4-40
4.17. Substitution of Ozone Depleting Substances (IPCC Source Category 2F) 4-42
4.18. HCFC-22 Production (IPCC Source Category 2E1) 4-45
4.19. Electrical Transmission and Distribution (IPCC Source Category 2F7) 4-46
4.20. Semiconductor Manufacture (IPCC Source Category 2F6) 4-50
4.21. Aluminum Production (IPCC Source Category 2C3) 4-54
4.22. Magnesium Production and Processing (IPCC Source Category 2C4) 4-57
4.23. Industrial Sources of Indirect Greenhouse Gases 4-60
5. Solvent and Other Product Use 5-1
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D) 5-1
5.2. Indirect Greenhouse Gas Emissions from Solvent Use 5-4
6. Agriculture 6-1
6.1. Enteric Fermentation (IPCC Source Category 4A) 6-2
6.2. Manure Management (IPCC Source Category 4B) 6-6
6.3. Rice Cultivation (IPCC Source Category 4C) 6-11
6.4. Agricultural Soil Management (IPCC Source Category 4D) 6-16
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F) 6-31
VI
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7. Land Use, Land-Use Change, and Forestry 7-1
7.1. Forest Land Remaining Forest Land 7-2
7.2. Land Converted to Forest Land (IPCC Source Category 5A2) 7-17
7.3. Cropland Remaining Cropland (IPCC Source Category 5B1) 7-17
7.4. Land Converted to Cropland (IPCC Source Category 5B2) 7-27
7.5. Grassland Remaining Grassland (IPCC Source Category 5C1) 7-31
7.6. Land Converted to Grassland (IPCC Source Category 5C2) 7-35
7.7. Settlements Remaining Settlements 7-39
7.8. Land Converted to Settlements (Source Category 5E2) 7-44
7.9. Other (IPCC Source Category 5G) 7-44
8. Waste 8-1
8.1. Landfills (IPCC Source Category 6A1) 8-2
8.2. Wastewater Treatment (IPCC Source Category 6B) 8-6
8.3. Waste Sources of Indirect Greenhouse Gases 8-14
9. Other 9-1
10. Recalculations and Improvements 10-1
11. References 11-1
List of Annexes (Annexes available on CD version only)
ANNEX 1. Key Category Analysis
ANNEX 2. Methodology and Data for Estimating C02 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of CO2 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3. Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from
Stationary Combustion
3.2. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from
Mobile Combustion and Methodology for and Supplemental Information on
Transportation-Related Greenhouse Gas Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 Emissions from Petroleum Systems
3.6. Methodology for Estimating CO2 and N2O Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
VII
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3.10. Methodology for Estimating CH4 and N2O Emissions from Manure Management
3.11. Methodology for Estimating N2O Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on
Croplands and Grasslands
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4. IPCC Reference Approach for Estimating C02 Emissions from Fossil Fuel Combustion
ANNEX 5. Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded
ANNEX 6. Additional Information
6.1. Global Warming Potential Values
6.2. Ozone Depleting Substance Emissions
6.3. Sulfur Dioxide Emissions
6.4. Complete List of Source Categories
6.5. Constants, Units, and Conversions
6.6. Abbreviations
6.7. Chemical Formulas
ANNEX 7. Uncertainty
7.1. Overview
7.2. Methodology and Results
7.3. Planned Improvements
7.4. Additional Information on Uncertainty Analysis by Source
List of Tables, Figures, and Boxes
Tables
Table ES-1: Global Warming Potentials (100-Year Time Horizon) Used in This Report ES-3
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) ES-5
Table ES-3: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) ES-8
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg CO2 Eq.) ES-11
Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) ES-13
Table ES-6: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) ES-13
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.) ES-14
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with
Electricity-Related Emissions Distributed (Tg CO2 Eq.) ES-15
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100) ES-16
Table ES-10: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) ES-17
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and
Atmospheric Lifetime (years) of Selected Greenhouse Gases 1-3
Table 1-2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report 1-7
Table 1-3: Comparison of 100-Year GWPs 1-8
VIII
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Table 1-4: Key Categories for the United States (1990-2005) Based on Tier 1 Approach 1-12
Table 1-5: Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent) 1-14
Table 1-6: IPCC Sector Descriptions 1-15
Table 1-7: List of Annexes 1-16
Table 2-1: Annual Change in CO2 Emissions from Fossil Fuel Combustion for
Selected Fuels and Sectors (Tg CO2 Eq. and Percent) 2-2
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100) 2-4
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) 2-6
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-7
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg CO2 Eq.) 2-8
Table 2-6: Emissions from Energy (Tg CO2 Eq.) 2-9
Table 2-7: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 2-10
Table 2-8: Emissions from Industrial Processes (Tg CO2 Eq.) 2-14
Table 2-9: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.) 2-18
Table 2-10: Emissions from Agriculture (Tg CO2 Eq.) 2-18
Table 2-11: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-20
Table 2-12: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-21
Table 2-13: Emissions from Waste (Tg CO2 Eq.) 2-22
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors
(Tg CO2 Eq. and Percent of Total in 2005) 2-23
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-25
Table 2-16: U.S Greenhouse Gas Emissions by Economic Sector and Gas with
Electricity-Related Emissions Distributed (Tg CO2 Eq. and Percent of Total in 2005) 2-26
Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-27
Table 2-18: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) 2-30
Table 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.) 3-2
Table 3-2: CO2, CH4, and N2O Emissions from Energy (Gg) 3-3
Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.) 3-4
Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for Selected Fuels and
Sectors (Tg CO2 Eq. and Percent) 3-4
Table 3-5: CO2 Emissions from International Bunker Fuels (Tg CO2 Eq.) 3-7
Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 3-7
Table 3-7: CO2 Emissions from Fossil Fuel Combustion in the Transportation End-Use Sector (Tg CO2 Eq.) . 3-9
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu) 3-13
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg CO2 Eq./QBtu) 3-13
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-Related
Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent) 3-17
Table 3-11: CO2 Emissions from Fossil Fuel Consumption for Non-Energy Use (Tg CO2 Eq.) 3-19
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-20
IX
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Table 3-13: 2005 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-21
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO, Emissions from
Non-Energy Uses of Fossil Fuels (Tg CO2 Eq. and Percent) 3-22
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of
Non-Energy Uses of Fossil Fuels (Percent) 3-22
Table 3-16: CH4 Emissions from Stationary Combustion (Tg CO2 Eq.) 3-24
Table 3-17: N2O Emissions from Stationary Combustion (Tg CO2 Eq.) 3-25
Table 3-18: CH4 Emissions from Stationary Combustion (Gg) 3-25
Table 3-19: N2O Emissions from Stationary Combustion (Gg) 3-26
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Stationary Combustion, Including Biomass (Tg CO2 Eq. and Percent) 3-27
Table 3-21: CH4 Emissions from Mobile Combustion (Tg CO2 Eq.) 3-29
Table 3-22: N2O Emissions from Mobile Combustion (Tg CO2 Eq.) 3-30
Table 3-23: CH4 Emissions from Mobile Combustion (Gg) 3-30
Table 3-24: N2O Emissions from Mobile Combustion (Gg) 3-31
Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Mobile Combustion (Tg CO2 Eq. and Percent) 3-33
Table 3-26: CH4 Emissions from Coal Mining (Tg CO2 Eq.) 3-35
Table 3-27: CH4 Emissions from Coal Mining (Gg) 3-35
Table 3-28: Coal Production (Thousand Metric Tons) 3-36
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Coal Mining (Tg CO2 Eq. and Percent) 3-36
Table 3-30: CH4 Emissions from Abandoned Underground Coal Mines (Tg CO2 Eq.) 3-38
Table 3-31: CH4 Emissions from Abandoned Underground Coal Mines (Gg) 3-38
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Abandoned Underground Coal Mines (Tg CO2 Eq. and Percent) 3-40
Table 3-33: CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-41
Table 3-34: CH4 Emissions from Natural Gas Systems (Gg) 3-41
Table 3-35: Non-energy CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-41
Table 3-36: Non-energy CO2 Emissions from Natural Gas Systems (Gg) 3-41
Table 3-37: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-energy CO2 Emissions from
Natural Gas Systems (Tg CO2 Eq. and Percent) 3-43
Table 3-38: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-45
Table 3-39: CH4 Emissions from Petroleum Systems (Gg) 3-45
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Petroleum Systems (Tg CO2 Eq. and Percent) 3-47
Table 3-41: Emissions of CO2 from EOR Operations and Pipelines (Tg CO2 Eq.) 3-48
Table 3-42: Emissions of CO2 from EOR Operations and Pipelines (Gg) 3-48
Table 3-43: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Tg CO2 Eq.) 3-49
Table 3-44: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Gg) 3-49
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Table 3-45: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-50
Table 3-46: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from
Municipal Solid Waste Combustion (Tg CO2 Eq. and Percent) 3-50
Table 3-47: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg) 3-51
Table 3-48: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.) 3-53
Table 3-49: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg) 3-53
Table 3-50: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-54
Table 3-51: Marine Fuel Consumption for International Transport (Million Gallons) 3-54
Table 3-52: CO7 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.) 3-56
Table 3-53: CO2 Emissions from Wood Consumption by End-Use Sector (Gg) 3-56
Table 3-54: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq. and Gg) 3-57
Table 3-55: Woody Biomass Consumption by Sector (Trillion Btu) 3-57
Table 3-56: Ethanol Consumption (Trillion Btu) 3-57
Table 3-57: CH4 Emissions from Non-Combustion Fossil Sources (Gg) 3-58
Table 3-58: Formation of CO2 through Atmospheric CH4 Oxidation (Tg CO2 Eq.) 3-59
Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.) 4-2
Table 4-2: Emissions from Industrial Processes (Gg) 4-3
Table 4-3: CO2 Emissions from Cement Production (Tg CO2 Eq. and Gg) 4-5
Table 4-4: Cement Production (Gg) 4-6
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Cement Manufacture (Tg CO2 Eq. and Percent) 4-6
Table 4-6: CO2 and CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-7
Table 4-7: CO2 and CH4 Emissions from Iron and Steel Production (Gg) 4-7
Table 4-8: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg) 4-8
Table 4-9: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from
Iron and Steel Production (Thousand Metric Tons) 4-9
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from
Iron and Steel Production (Tg. CO2 Eq. and Percent) 4-9
Table 4-11: CO2 Emissions from Ammonia Manufacture and Urea Application (Tg CO2 Eq.) 4-11
Table 4-12: CO2 Emissions from Ammonia Manufacture and Urea Application (Gg) 4-11
Table 4-13: Ammonia Production, Urea Production, and Urea Net Imports (Gg) 4-12
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Ammonia Manufacture and Urea Application (Tg CO2 Eq. and Percent) 4-12
Table 4-15: Net CO2 Emissions from Lime Manufacture (Tg CO2 Eq.) 4-13
Table 4-16: CO2 Emissions from Lime Manufacture (Gg) 4-13
Table 4-17: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and
Dead-Burned-Dolomite Lime Production (Gg) 4-14
Table 4-18: Adjusted Lime Production and Lime Use for Sugar Refining and PCC (Gg) 4-14
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Lime Manufacture (Tg CO2 Eq. and Percent) 4-15
Table 4-20: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.) 4-16
XI
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Table 4-21: CO2 Emissions from Limestone & Dolomite Use (Gg) 4-16
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-17
Table 4-23: Dolomitic Magnesium Metal Production Capacity (Metric Tons) 4-17
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Limestone and Dolomite Use (Tg CO2 Eq. and Percent) 4-18
Table 4-25: CO2 Emissions from Soda Ash Manufacture and Consumption (Tg CO2 Eq.) 4-19
Table 4-26: CO2 Emissions from Soda Ash Manufacture and Consumption (Gg) 4-19
Table 4-27: Soda Ash Manufacture and Consumption (Gg) 4-20
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Soda Ash Manufacture and Consumption (Tg CO2 Eq. and Percent) 4-20
Table 4-29: CO2 Emissions from Titanium Dioxide Production (Tg CO2 Eq. and Gg) 4-21
Table 4-30: Titanium Dioxide Production (Gg) 4-21
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Titanium Dioxide Production (Tg CO2 Eq. and Percent) 4-22
Table 4-32: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.) 4-23
Table 4-33: CO2 and CH4 Emissions from Ferroalloy Production (Gg) 4-23
Table 4-34: Production of Ferroalloys (Metric Tons) 4-23
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from
Ferroalloy Production (Tg CO2 Eq. and Percent) 4-24
Table 4-36: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. and Gg) 4-25
Table 4-37: Phosphate Rock Domestic Production, Exports, and Imports (Gg) 4-26
Table 4-38: Chemical Composition of Phosphate Rock (percent by weight) 4-26
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Phosphoric Acid Production (Tg CO2 Eq. and Percent) 4-27
Table 4-40: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg) 4-28
Table 4-41: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for
Jackson Dome and Bravo Dome 4-29
Table 4-42: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
CO2 Consumption (Tg CO2 Eq. and Percent) 4-29
Table 4-43: CO2 Emissions from Zinc Production (Tg CO2 Eq. and Gg) 4-30
Table 4-44: Zinc Production (Metric Tons) 4-32
Table 4-45: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Zinc Production (Tg CO2 Eq. and Percent) 4-32
Table 4-46: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg) 4-33
Table 4-47: Lead Production (Metric Tons) 4-33
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Lead Production (Tg CO2 Eq. and Percent) 4-34
Table 4-49: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.) 4-35
Table 4-50: CO2 and CH4 Emissions from Petrochemical Production (Gg) 4-35
Table 4-51: Production of Selected Petrochemicals (Thousand Metric Tons) 4-35
XII
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Table 4-52: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock
(Secondary Feedstock) Consumption (Thousand Metric Tons) 4-36
Table 4-53: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from
Petrochemical Production (Tg CO2 Eq. and Percent) 4-37
Table 4-54: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.) 4-37
Table 4-55: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg) 4-38
Table 4-56: Production and Consumption of Silicon Carbide (Metric Tons) 4-38
Table 4-57: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from
Silicon Carbide Production and Consumption (Tg CO2 Eq. and Percent) 4-38
Table 4-58: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg) 4-39
Table 4-59: Nitric Acid Production (Gg) 4-40
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from
Nitric Acid Production (Tg CO2 Eq. and Percent) 4-40
Table 4-61: N2O Emissions from Adipic Acid Production (Tg CO, Eq. and Gg) 4-41
Table 4-62: Adipic Acid Production (Gg) 4-42
Table 4-63: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from
Adipic Acid Production (Tg CO2 Eq. and Percent) 4-42
Table 4-64: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) 4-43
Table 4-65: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-43
Table 4-66: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from
ODS Substitutes (Tg CO, Eq. and Percent) 4-45
Table 4-67: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg) 4-45
Table 4-68: HCFC-22 Production (Gg) 4-46
Table 4-69: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from
HCFC-22 Production (Tg CO2 Eq. and Percent) 4-46
Table 4-70: SF6 Emissions from Electric Power Systems and Electrical Equipment
Manufactures (Tg CO, Eq.) 4-47
Table 4-71: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufactures (Gg) 4-47
Table 4-72: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from
Electrical Transmission and Distribution (Tg CO2 Eq. and Percent) 4-49
Table 4-73: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.) 4-51
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-51
Table 4-75: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from
Semiconductor Manufacture (Tg CO2 Eq. and Percent) 4-53
Table 4-76: CO, Emissions from Aluminum Production (Tg CO2 Eq. and Gg) 4-54
Table 4-77: PFC Emissions from Aluminum Production (Tg CO2 Eq.) 4-54
Table 4-78: PFC Emissions from Aluminum Production (Gg) 4-54
Table 4-79: Production of Primary Aluminum (Gg) 4-56
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for CO, and PFC Emissions from
Aluminum Production (Tg CO2 Eq. and Percent) 4-57
Table 4-81: SF6 Emissions from Magnesium Production and Processing (Tg CO, Eq. and Gg) 4-58
XIII
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Table 4-82: SF6 Emission Factors (kg SF6 per metric ton of magnesium) 4-58
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from
Magnesium Production and Processing (Tg CO2 Eq. and Percent) 4-59
Table 4-84: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-60
Table 5-1: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg) 5-1
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg) 5-1
Table 5-3: N2O Emissions from N2O Product Usage (Tg CO2 Eq. and Gg) 5-2
Table 5-4: N2O Production (Gg) 5.3
Table 5-5: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from
N2O Product Usage (Tg CO2 Eq. and Percent) 5-3
Table 5-6: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg) 5-5
Table 6-1: Emissions from Agriculture (Tg CO9 Eq.) 6-1
Table 6-2: Emissions from Agriculture (Gg) 6-2
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg CO2 Eq.) 6-3
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg) 6-3
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from
Enteric Fermentation (Tg CO2 Eq. and Percent) 6-5
Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2 Eq.) 6-7
Table 6-7: CH4 and N2O Emissions from Manure Management (Gg) 6-8
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Manure Management (Tg CO2 Eq. and Percent) 6-9
Table 6-9: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.) 6-12
Table 6-10: CH4 Emissions from Rice Cultivation (Gg) 6-13
Table 6-11: Rice Areas Harvested (Hectares) 6-14
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Rice Cultivation (Tg CO2 Eq. and Percent) 6-15
Table 6-13: N2O Emissions from Agricultural Soils (Tg CO2 Eq.) 6-18
Table 6-14: N2O Emissions from Agricultural Soils (Gg N2O) 6-18
Table 6-15: Direct N2O Emissions from Agricultural Soils by Land Use and N Input (Tg CO2 Eq.) 6-18
Table 6-16: Indirect N2O Emissions from all Land-Use Types and Managed Manure Systems (Tg CO2 Eq.). 6-19
Table 6-17: Quantitative Uncertainty Estimates of N2O Emissions from
Agricultural Soil Management in 2005 (Tg CO2 Eq. and Percent) 6-28
Table 6-18: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.) 6-32
Table 6-19: CH4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg) 6-32
Table 6-20: Agricultural Crop Production (Gg of Product) 6-33
Table 6-21: Percent of Rice Area Burned by State 6-34
Table 6-22: Percent of Rice Area Burned in California, 1990-1998 6-34
Table 6-23: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-34
Table 6-24: Greenhouse Gas Emission Ratios 6-35
Table 6-25: Tier 2 Uncertainty Estimates for CH4 and N2O Emissions from
Field Burning of Agricultural Residues (Tg CO2 Eq. and Percent) 6-35
XIV
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Table 7-1: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 7-2
Table 7-2: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg C) 7-3
Table 7-3: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 7-4
Table 7-4: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-4
Table 7-5: Net Annual Changes in C Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools 7-6
Table 7-6: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools 7-6
Table 7-7: Forest area (1,000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools 7-7
Table 7-8: Estimates of CO2 (Tg/yr) Emissions for the Lower 48 States and Alaska 7-8
Table 7-9: Tier 2 Quantitative Uncertainty Estimates for Net CO2 Flux from
Forest Land Remaining Forest Land: Changes in Forest C Stocks (Tg CO2 Eq. and Percent) 7-11
Table 7-10: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. Forests 7-15
Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Gg Gas) for U.S. Forests 7-15
Table 7-12: Estimated Carbon Released from Forest Fires for U.S. Forests 7-15
Table 7-13: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from
Forest Fires in Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent) 7-15
Table 7-14: N2O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Gg) 7-16
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of N2O Fluxes from
Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent) 7-17
Table 7-16: Net Soil C Stock Changes and Liming Emissions in
Cropland Remaining Cropland (Tg CO2 Eq.) 7-19
Table 7-17: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C) .. . . 7-19
Table 7-18: Applied Minerals (Million Metric Tons) 7-24
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within
Cropland Remaining Cropland (Tg CO2 Eq. and Percent) 7-25
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.) 7-27
Table 7-21: Net Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-27
Table 7-22: Quantitative Uncertainty Estimates for C Stock Changes occurring within
Land Converted to Cropland (Tg CO2 Eq. and Percent) 7-30
Table 7-23: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.) 7-31
Table 7-24: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-31
Table 7-25: Quantitative Uncertainty Estimates for C Stock Changes occurring within
Grassland Remaining Grassland (Tg CO2 Eq. and Percent) 7-34
Table 7-26: Net Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.) 7-36
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-36
Table 7-28: Quantitative Uncertainty Estimates for C Stock Changes occurring within
Land Converted to Grassland (Tg CO2 Eq. and Percent) 7-39
Table 7-29: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C) 7-40
Table 7-30: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr),
Tree Cover (Percent), and Annual Carbon Sequestration per Area of
Tree Cover (kg C/m2 cover-yr) for Ten U.S. Cities 7-41
XV
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Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from
Changes in C Stocks in Urban Trees (Tg CO2 Eq. and Percent) 7-42
Table 7-32: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg) 7-43
Table 7-33: Tier 2 Quantitative Uncertainty Estimates of N2O Emissions from
Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Percent) 7-44
Table 7-34: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.) 7-45
Table 7-35: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C) 7-45
Table 7-36: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%),
Initial C Content (%), and Half-Life (years) for Yard Trimmings and
Food Scrap Stocks in Landfills 7-47
Table 7-37: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-47
Table 7-38: Tier 2 Quantitative Uncertainty Estimates for CO2 P;lux from
Yard Trimmings and Food Scrap Stocks in Landfills (Tg CO2 Eq. and Percent) 7-48
Table 8-1: Emissions from Waste (Tg CO2 Eq.) 8-1
Table 8-2: Emissions from Waste (Gg) 8-1
Table 8-3: CH4 Emissions from Landfills (Tg CO2 Eq.) 8-2
Table 8-4: CH4 Emissions from Landfills (Gg) 8-2
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Landfills (Tg CO2 Eq. and Percent) 8-5
Table 8-6: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.) .... 8-7
Table 8-7: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg) 8-7
Table 8-8: U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg) 8-8
Table 8-9: U.S. Pulp and Paper; Meat and Poultry; and Vegetables, Fruits and Juices Production (Tg) 8-9
Table 8-10: Wastewater Flow (rrvVton) and BOD Production (g/L) for U.S. Vegetables,
Fruits and Juices Production 8-10
Table 8-11: U.S. Population (Millions) and Average Protein Intake [kg/(person-year)] 8-12
Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Wastewater Treatment (Tg CO2 Eq. and Percent) 8-12
Table 8-13: Emissions of NOX, CO, and NMVOC from Waste (Gg) 8-14
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO, Eq.) 10-2
Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from
Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 10-3
Figures
Figure ES-1: U.S. Greenhouse Gas Emissions by Gas ES-4
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions ES-4
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 ES-4
Figure ES-4: 2005 Greenhouse Gas Emissions by Gas (percents based on Tg CO2 Eq.) ES-4
Figure ES-5: 2005 Sources of CO2 ES-6
Figure ES-6: 2005 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type ES-7
Figure ES-7: 2005 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion ES-7
Figure ES-8: 2005 Sources of CH4 ES-9
XVI
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Figure ES-9: 2005 Sources of N2O ES-10
Figure ES-10: 2005 Sources of HFCs, PFCs, and SF6 ES-10
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector ES-11
Figure ES-12: 2005 U.S. Energy Consumption by Energy Source ES-11
Figure ES-13: Emissions Allocated to Economic Sectors ES-14
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors ES-15
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product ES-16
Figure ES-16: 2005 Key Categories-Tier 1 Level Assessment ES-18
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas 2-1
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 2-2
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 2-2
Figure 2-4: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-4
Figure 2-5: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector 2-5
Figure 2-6: 2005 Energy Chapter Greenhouse Gas Sources 2-8
Figure 2-7: 2005 U.S. Fossil Carbon Flows (Tg CO, Eq.) 2-9
Figure 2-8: 2005 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-10
Figure 2-9: 2005 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 2-10
Figure 2-10: 2005 Industrial Processes Chapter Greenhouse Gas Sources 2-13
Figure 2-11: 2005 Agriculture Chapter Greenhouse Gas Sources 2-19
Figure 2-12: 2005 Waste Chapter Greenhouse Gas Sources 2-21
Figure 2-13: Emissions Allocated to Economic Sectors 2-24
Figure 2-14: Emissions with Electricity Distributed to Economic Sectors 2-25
Figure 3-1: 2005 Energy Chapter Greenhouse Gas Sources 3-1
Figure 3-2: 2005 U.S. Fossil Carbon Flows (Tg CO2 Eq.) 3-2
Figure 3-3: 2005 U.S. Energy Consumption by Energy Source 3-5
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu) 3-5
Figure 3-5: 2005 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-5
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2005) 3-6
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2005) 3-6
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the
United States (1974-2005) 3-6
Figure 3-9: 2005 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 3-7
Figure 3-10: Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990-2005 3-8
Figure 3-11: Sales of New Automobiles and Light-Duty Trucks, 1990-2005 3-8
Figure 3-12: Industrial Production Indices (Index 2002=100) 3-10
Figure 3-13: Heating Degree Days 3-11
Figure 3-14: Cooling Degree Days 3-11
Figure 3-15: Electricity Generation Retail Sales by End-Use Sector 3-12
Figure 3-16: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and Per Dollar GDP 3-13
Figure 3-17: Mobile Source CH4 and N2O Emissions 3-29
Figure 4-1: 2005 Industrial Processes Chapter Greenhouse Gas Sources 4-1
XVII
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Figure 6-1: 2005 Agriculture Chapter Greenhouse Gas Sources 6-1
Figure 6-2: Agricultural Sources and Pathways of N that Result in N2O Emissions 6-17
Figure 6-3: Major Crops, Average Annual Direct N2O Emissions, 1990-2005 (Tg CO2 Eq./county/year). . . . 6-20
Figure 6-4: Grasslands, Average Annual Direct N2O Emissions. 1990-2005 (Tg CO2 Eq./county/year) 6-20
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions,
1990-2005 (Tg CO2 Eq./county/year) 6-21
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions,
1990-2005 (Tg CO2 Eq./county/year) 6-21
Figure 7-1: Forest Sector Carbon Pools and Flows 7-5
Figure 7-2: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools 7-7
Figure 7-3: Average C Density in the Forest Tree Pool in the Conterminous United States During 2005 .... 7-8
Figure 7-4: Net Soil C Stock Change for Mineral Soils in Cropland Remaining Cropland, 2005 7-20
Figure 7-5: Net Soil C Stock Change for Organic Soils in Cropland Remaining Cropland, 2005 7-20
Figure 7-6: Net Soil C Stock Change for Mineral Soils in Land Converted to Cropland, 2005 7-28
Figure 7-7: Net Soil C Stock Change for Organic Soils in Land Converted to Cropland, 2005 7-28
Figure 7-8: Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 2005 7-32
Figure 7-9: Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 2005 7-32
Figure 7-10: Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 2005 7-37
Figure 7-11: Net Soil C Stock Change for Organic Soils in Land Converted to Grassland, 2005 7-37
Figure 8-1: 2005 Waste Chapter Greenhouse Gas Sources 8-1
Boxes
Box ES-1: Recalculations of Inventory Estimates ES-2
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data ES-16
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials 1-8
Box 1-2: IPCC Reference Approach 1-10
Box 2-1: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data 2-4
Box 2-2: Methodology for Aggregating Emissions by Economic Sector 2-28
Box 2-3: Sources and Effects of Sulfur Dioxide 2-29
Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends 3-6
Box 3-2: Carbon Intensity of U.S. Energy Consumption 3-12
Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage 3-48
Box 3-4: Formation of CO2 through Atmospheric CH4 Oxidation 3-58
Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions 6-22
Box 7-1: CO2 Emissions from Forest Fires 7-8
Box 7-2: Tier 3 Inventory for Soil C Stocks compared to Tier 1 or 2 Approaches 7-22
Box 8-1: Biogenic Emissions and Sinks of Carbon 8-5
XVIII
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Executive Summary
An emissions inventory that identifies and quantifies a country's primary anthropogenic1 sources and sinks of
greenhouse gases is essential for addressing climate change. This inventory adheres to both (1) a comprehensive
and detailed set of methodologies for estimating sources and sinks of anthropogenic greenhouse gases, and (2) a
common and consistent mechanism that enables Parties to the United Nations Framework Convention on Climate Change
(UNFCCC) to compare the relative contribution of different emission sources and greenhouse gases to climate change.
In 1992, the United States signed and ratified the UNFCCC. As stated in Article 2 of the UNFCCC, "The ultimate
objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to achieve, in
accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere
at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved
within a time-frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is
not threatened and to enable economic development to proceed in a sustainable manner."2
Parties to the Convention, by ratifying, "shall develop, periodically update, publish and make available...national
inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the
Montreal Protocol, using comparable methodologies...."3 The United States views this report as an opportunity to fulfill
these commitments.
This chapter summarizes the latest information on U.S. anthropogenic greenhouse gas emission trends from 1990 through
2005. To ensure that the U .S. emissions inventory is comparable to those of other UNFCCC Parties, the estimates presented
here were calculated using methodologies consistent with those recommended in the Revised 1996 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997), the IPCC Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories (IPCC 2000), and the IPCC Good Practice Guidance for Land
Use, Land-Use Change, and Forestry (IPCC 2003). Additionally, the U.S. emission inventory has begun to incorporate
new methodologies and data from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). The
structure of this report is consistent with the UNFCCC guidelines for inventory reporting.4 For most source categories, the
Intergovernmental Panel on Climate Change (IPCC) methodologies were expanded, resulting in a more comprehensive
and detailed estimate of emissions.
1 The term "anthropogenic," in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result
of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
2 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See .
3 Article 4(1 )(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent decisions by the
Conference of the Parties elaborated the role of Annex I Parties in preparing national inventories. See .
4 See .
Executive Summary ES-1
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Box ES-1: Recalculations of Inventory Estimates
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse Gas Emissions and
Sinks, as attempts are made to improve both the analyses themselves, through the use of better methods or data, and the overall usefulness
of the report. In this effort, the United States follows the IPCC Good Practice Guidance (IPCC 2000), which states, regarding recalculations
of the time series, "It is good practice to recalculate historic emissions when methods are changed or refined, when new source categories
are included in the national inventory, or when errors in the estimates are identified and corrected." In general, recalculations are made to the
U.S. greenhouse gas emission estimates either to incorporate new methodologies or, most commonly, to update recent historical data.
In each Inventory report, the results of all methodology changes and historical data updates are presented in the "Recalculations
and Improvements" chapter; detailed descriptions of each recalculation are contained within each source's description contained in the
report, if applicable. In general, when methodological changes have been implemented, the entire time series (in the case of the most
recent inventory report, 1990 through 2004) has been recalculated to reflect the change, per IPCC Good Practice Guidance. Changes
in historical data are generally the result of changes in statistical data supplied by other agencies. References for the data are provided
for additional information.
ES.1. Background Information
Naturally occurring greenhouse gases include water
vapor, carbon dioxide (CO2), methane (CH4), nitrous oxide
(N2O), and ozone (O3). Several classes of halogenated
substances that contain fluorine, chlorine, or bromine are also
greenhouse gases, but they are, for the most part, solely a
product of industrial activities. Chlorofluorocarbons (CFCs)
and hydrochlorofluorocarbons (HCFCs) are halocarbons that
contain chlorine, while halocarbons that contain bromine
are referred to as bromofluorocarbons (i.e., halons). As
stratospheric ozone depleting substances, CFCs, HCFCs,
and halons are covered under the Montreal Protocol on
Substances that Deplete the Ozone Layer. The UNFCCC
defers to this earlier international treaty. Consequently,
Parties to the UNFCCC are not required to include these
gases in their national greenhouse gas emission inventories.5
Some other fluorine-containing halogenated substances —
hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and
sulfur hexafluoride (SF6)—do not deplete stratospheric ozone
but are potent greenhouse gases. These latter substances are
addressed by the UNFCCC and accounted for in national
greenhouse gas emission inventories.
There are also several gases that do not have a direct
global warming effect but indirectly affect terrestrial and/or
solar radiation absorption by influencing the formation or
destruction of greenhouse gases, including tropospheric and
stratospheric ozone. These gases include carbon monoxide
(CO), oxides of nitrogen (NOX), and non-CH4 volatile organic
compounds (NMVOCs). Aerosols, which are extremely
small particles or liquid droplets, such as those produced by
sulfur dioxide (SO2) or elemental carbon emissions, can also
affect the absorptive characteristics of the atmosphere.
Although the direct greenhouse gases CO2, CH4, and
N2O occur naturally in the atmosphere, human activities
have changed their atmospheric concentrations. From
the pre-industrial era (i.e., ending about 1750) to 2004,
concentrations of these greenhouse gases have increased
globally by 35, 143, and 18 percent, respectively (IPCC
200l,Hofmann 2004).
Beginning in the 1950s, the use of CFCs and other
stratospheric ozone depleting substances (ODS) increased
by nearly 10 percent per year until the mid-1980s, when
international concern about ozone depletion led to the
entry into force of the Montreal Protocol. Since then, the
production of ODS is being phased out. In recent years, use
of ODS substitutes such as HFCs and PFCs has grown as
they begin to be phased in as replacements for CFCs and
HCFCs. Accordingly, atmospheric concentrations of these
substitutes have been growing (IPCC 2001).
Global Warming Potentials
Gases in the atmosphere can contribute to the greenhouse
effect both directly and indirectly. Direct effects occur when
1 Emissions estimates of CFCs, HCFCs. halons and other ozone-depleting substances are included in the annexes of this report for informational
purposes.
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 199D-2Q05
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the gas itself absorbs radiation. Indirect radiative forcing
occurs when chemical transformations of the substance
produce other greenhouse gases, when a gas influences
the atmospheric lifetimes of other gases, and/or when a
gas affects atmospheric processes that alter the radiative
balance of the earth (e.g., affect cloud formation or albedo).6
The IPCC developed the Global Warming Potential (GWP)
concept to compare the ability of each greenhouse gas to trap
heat in the atmosphere relative to another gas.
The GWP of a greenhouse gas is defined as the ratio of
the time-integrated radiative forcing from the instantaneous
release of 1 kilogram (kg) of a trace substance relative to
that of 1 kg of a reference gas (IPCC 2001). Direct radiative
effects occur when the gas itself is a greenhouse gas. The
reference gas used is COi, and therefore GWP-weighted
emissions are measured in teragrams of CO2 equivalent (Tg
CO2 Eq.).7 All gases in this Executive Summary are presented
in units of Tg CO2 Eq.
The UNFCCC reporting guidelines for national
inventories were updated in 2002,8 but continue to require
the use of GWPs from the IPCC Second Assessment Report
(SAR) (IPCC 1996). This requirement ensures that current
estimates of aggregate greenhouse gas emissions for 1990
to 2005 are consistent with estimates developed prior to
the publication of the IPCC Third Assessment Report
(TAR). Therefore, to comply with international reporting
standards under the UNFCCC, official emission estimates
are reported by the United States using SAR GWP values.
All estimates are provided throughout the report in both
CO2 equivalents and unweighted units. A comparison of
emission values using the SAR GWPs versus the TAR
GWPs can be found in Chapter 1 and, in more detail, in
Annex 6.1 of this report. The GWP values used in this report
are listed below in Table ES-1.
Global warming potentials are not provided for CO,
NOX, NMVOCs, SO2, and aerosols because there is no
agreed-upon method to estimate the contribution of gases that
are short-lived in the atmosphere, spatially variable, or have
only indirect effects on radiative forcing (IPCC 1996).
Table ES-1: Global Warming Potentials (100-Year Time
Horizon) Used in This Report
Gas
C02
CH4*
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-1433
HFC-1523
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^F-io
"6M4
SF6
GWP
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)
* The CH4 GWP includes the direct effects and those indirect effects due
to the production of tropospheric ozone and stratospheric water vapor.
The indirect effect due to the production of C02 is not included.
ES.2. Recent Trends in U.S.
Greenhouse Gas Emissions and
Sinks
In 2005, total U.S. greenhouse gas emissions were
7,260.4 Tg CO2 Eq. Overall, total U.S. emissions have risen
by 16.3 percent from 1990 to 2005, while the U.S. gross
domestic product has increased by 55 percent over the same
period (BEA 2006). Emissions rose from 2004 to 2005,
increasing by 0.8 percent (56.7 Tg CO2 Eq.). The following
factors were primary contributors to this increase: (1) strong
economic growth in 2005, leading to increased demand for
electricity and (2) an increase in the demand for electricity
due to warmer summer conditions. These factors were
moderated by decreasing demand for fuels due to warmer
winter conditions and higher fuel prices.
Albedo is a measure of the Earth's reflectivity, and is defined as the fraction of the total solar radiation incident on a body that is reflected by it.
7 Carbon constitutes 12/44ths of carbon dioxide by weight
* See .
Executive Summary ES-3
-------
Figure ES-1
U.S. Greenhouse Gas Emissions by Gas
MFCs, PFCs, & SF«
Nitrous Oxide
Methane
Carbon Dioxide
Figure ES-2
Annual Percent Change in U.S. Greenhouse Gas Emissions
5.0%-
4.0%-
3.0%-
2.0%-
1.0%-
0.0%
-1.0%-
-2.0%
2.5%
ll
11.4%
iiiili
I
Figure ES-3
Cumulative Change in U.S. Greenhouse Gas
Emissions Relative to 1990
1,100
1,000
900
800
j- 700
r 600
» 500
400
300
200
100
0
-100
g 3 g 5
Figure ES-1 through Figure ES-3 illustrate the overall
trends in total U.S. emissions by gas, annual changes, and
absolute change since 1990. Table ES-2 provides a detailed
summary of U.S. greenhouse gas emissions and sinks for
1990 through 2005.
Figure ES-4 illustrates the relative contribution of the
direct greenhouse gases to total U.S. emissions in 2005.
The primary greenhouse gas emitted by human activities
in the United States was CO2, representing approximately
83.9 percent of total greenhouse gas emissions. The largest
source of CO2, and of overall greenhouse gas emissions,
was fossil fuel combustion. CH4 emissions, which have
steadily declined since 1990, resulted primarily from
decomposition of wastes in landfills, natural gas systems,
and enteric fermentation associated with domestic livestock.
Agricultural soil management and mobile source fossil fuel
combustion were the major sources of N2O emissions. The
emissions of substitutes for ozone depleting substances and
emissions of HFC-23 during the production of HCFC-22
were the primary contributors to aggregate HFC emissions.
Electrical transmission and distribution systems accounted
for most SF6 emissions, while PFC emissions resulted from
semiconductor manufacturing and as a by-product of primary
aluminum production.
Overall, from 1990 to 2005, total emissions of CO2
increased by 1,027.9 Tg CO2 Eq. (20.3 percent), while CH4
and N>O emissions decreased by 69.8 Tg CO2 Eq. (11.5
percent) and 13.4 Tg CO2 Eq. (2.8 percent), respectively.
During the same period, aggregate weighted emissions
of MFCs, PFCs, and SF6 rose by 73.7 Tg CO2 Eq. (82.5
Figure ES-4
2005 Greenhouse Gas Emissions by Gas
(percents based on Tg C02 Eq.)
MFCs, PFCs, & SF,
N20
CH,
C02
83.9%
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 199(1-2005
-------
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
Carbon Dioxide Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
Land Use, Land-Use Change, and Forestry (Sink)*
International Bunker Fuels'1
Wood Biomass and Ethanol Consumption11
CH4
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production and Consumption
Ferroalloy Production
International Bunker Fuelsb
N20
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
Adipic Acid Production
Settlements Remaining Settlements
N20 Product Usage
Forest Land Remaining Forest Land
Field Burning of Agricultural Residues
Municipal Solid Waste Combustion
International Bunker Fuels"
HFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
Net Emissions (Sources and Sinks)
1990
5,061.6
4,724.1
117.3
33.3
84.9
33.7
10.9
19.3
11.3
5.5
4.1
6.8
2.2
1.3
2.2
1.5
1.4
0.9
0.3
0.4
(712.8)
113.7
219.3
609.1
161.0
115.7
124.5
81.9
30.9
34.4
24.8
7.1
8.0
7.1
6.0
4.7
0.9
1.3
0.7
+
+
0.2
482.0
366.9
43.7
17.8
12.3
8.6
6.4
15.2
5.1
4.3
0.8
0.4
0.5
1.0
89.3
0.3
35.0
27.1
2.9
18.5
5.4
6,242.0
5,529.2
1995
5,384.6 :
5,030.0 '
133.2 .
36.8
73.3
33.8 '
15.7 ,-
20.5
12.8
7.4
4.3 '
5.7
2.8
1.7
2.0
1.5 "
1.4
1.0 -
0.3
0.3
(828.8)
100.6
236.8
598.7
157.1
120.6
128.1 .
66.5
35.1 '
31.1
25.1
4.0
7.8
7.6 '•
8.2
4.3
1.1 '
1.3
0.7
+
+
0.1
484.2
353.4
53.7
19.9
12.8
9.0
6.9
17.2
5.5
4.5
0.6
0.4
0.5
0.9
103.5
32.2
27.0
21.8
5.0
11.8
5.6
6,571.0
5,742.2
2000
5,940.0
5,584.9
141.0
41.2
65.1
29.4
17.9
19.6
13.3
6.0
4.2
6.1
3.0
1.9
1.9
1.4
1.4
1.1
0.3
0.2
(756.7)
101.1
228.3
563.7
131.9
113.5
126.6
55.9
38.7
27.8
26.4
14.0
7.4
7.5
7.3
3.5
1.2
1.2
0.8
+
+
0.1
499.8
376.8
53.2
19.6
14.0
9.6
7.6
6.0
5.6
4.8
1.7
0.5
0.4
0.9
143.8
80.9
29.8
15.2
6.3
8.6
3.0
7,147?
6,390.5
2001
5,843.0
5,511.7
131.4
41.4
57.9
28.8
18.3
16.7
12.9
5.7
4.1
4.4
2.8
1.9
1.5
1.3
0.8
1.0
0.3
0.2
(767.5)
97.6
203.2
547.7
127.6
112.5
125.4
55.5
40.1
27.4
25.9
6.0
6.8
7.6
6.7
3.2
1.1
1.1
0.8
+
+
0.1
502.5
389.0
49.7
15.9
13.5
9.8
7.6
4.9
5.5
4.8
1.0
0.5
0.4
0.9
133.8
88.6
19.8
15.1
4.5
3.5
2.4
7,027.0
6,259.5
2002
5,892.7
5,557.2
135.3
42.9
54.6
29.6
18.5
17.8
12.3
5.9
4.1
4.5
2.9
2.0
1.3
1.3
1.0
0.9
0.3
0.2
(811.9)
89.1
204.4
549.7
130.4
112.6
125.0
52.0
41.1
26.8
25.8
10.4
6.8
6.8
6.1
3.1
1.1
1.0
0.7
+
+
0.1
479.2
366.1
47.1
17.2
13.4
9.7
7.7
5.9
5.6
4.3
1.4
0.4
0.4
0.8
143.0
96.9
19.8
14.3
4.4
5.2
2.4
7,064.6
6,252.7
2003
5,952.5
5,624.5
131.3
43.1
53.4
28.4
19.5
16.2
13.0
4.7
4.1
4.5
2.8
2.0
1.3
1.4
1.3
0.5
0.3
0.2
(811.9)
83.7
209.6
549.2
134.9
113.0
123.7
52.1
40.5
25.8
25.6
8.1
7.0
6.9
5.9
2.9
1.1
1.0
0.8
+
+
0.1
459.8
350.2
43.8
16.7
13.7
9.3
7.8
6.2
5.8
4.3
1.2
0.4
0.4
0.8
142.7
105.5
12.3
13.8
4.3
3.8
2.9
7,104.2
6,292.3
2004
6,064.3
5,713.0
150.2
45.6
51.3
28.2
20.1
16.9
13.7
6.7
4.2
4.2
2.9
2.3
1.4
1.4
1.2
0.5
0.3
0.2
(824.8)
97.2
224.8
540.3
132.1
110.5
119.0
54.5
39.7
25.4
25.7
6.9
7.1
7.6
5.8
2.8
1.2
1.0
0.9
+
+
0.1
445.2
338.8
41.2
16.0
13.9
9.4
7.9
5.7
6.0
4.3
1.1
0.5
0.4
0.9
153.9
114.5
15.6
13.6
4.7
2.8
2.6
7,203.7
6,378.9
2005
6,089.5
5,751.2
142.4
45.9
45.2
28.2
20.9
16.3
13.7
7.4
4.2
4.2
2.9
1.9
1.4
1.4
1.3
0.5
0.3
0.2
(828.5)
97.2
206.5
539.3
132.0
112.1
111.1
52.4
41.3
28.5
25.4
11.6
6.9
6.9
5.5
2.6
1.1
1.0
0.9
+
+
0.1
468.6
365.1
38.0
15.7
13.8
9.5
8.0
6.0
5.8
4.3
1.5
0.5
0.4
0.9
163.0
123.3
16.5
13.2
4.3
3.0
2.7
7,260.4
6,431.9
+ Does not exceed 0.05 Tg C02 Eq.
a Parentheses indicate negative values or sequestration. The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the
United States. Sinks are only included in net emissions total.
b Emissions from International Bunker Fuels and Biomass Combustion are not included in totals.
Note: Totals may not sum due to independent rounding.
Executive Summary ES-5
-------
percent). Despite being emitted in smaller quantities relative
to the other principal greenhouse gases, emissions of HFCs,
PFCs, and SF6 are significant because many of them have
extremely high global warming potentials and, in the cases
of PFCs and SF6, long atmospheric lifetimes. Conversely,
U.S. greenhouse gas emissions were partly offset by carbon
sequestration in forests, trees in urban areas, agricultural
soils, and landfilled yard trimmings and food scraps, which,
in aggregate, offset 11.4 percent of total emissions in 2005.
The following sections describe each gas" contribution to
total U.S. greenhouse gas emissions in more detail.
Carbon Dioxide Emissions
The global carbon cycle is made up of large carbon
flows and reservoirs. Billions of tons of carbon in the form
of CO2 are absorbed by oceans and living biomass (i.e.,
sinks) and are emitted to the atmosphere annually through
natural processes (i.e., sources). When in equilibrium,
carbon fluxes among these various reservoirs are roughly
balanced. Since the Industrial Revolution (i.e..about 1750).
global atmospheric concentrations of CO2 have risen about
35 percent (IPCC 2001. Hofmann 2004). principally due
to the combustion of fossil fuels. Within the United States.
fuel combustion accounted for 94 percent of CO2 emissions
in 2005. Globally, approximately 27,044 Tg of CO2 were
added to the atmosphere through the combustion of fossil
fuels in 2004, of which the United States accounted for about
22 percent.9 Changes in land use and forestry practices can
also emit CO2 (e.g., through conversion of forest land to
agricultural or urban use) or can act as a sink for CO2 (e.g.,
through net additions to forest biomass).
U.S. anthropogenic sources of CO2 are shown in
Figure ES-5. As the largest source of U.S. greenhouse gas
emissions, CO? from fossil fuel combustion has accounted
for approximately 77 percent of GWP-weighted emissions
since 1990, growing slowly from 76 percent of total
GWP-weighted emissions in 1990 to 79 percent in 2005.
Emissions of CO? from fossil fuel combustion increased at
an average annual rate of 1.3 percent from 1990 to 2005.
The fundamental factors influencing this trend include (1)
a generally growing domestic economy over the last 15
years, and (2) significant overall growth in emissions from
electricity generation and transportation activities. Between
Figure ES-5
2005 Sources of CO
Fossil Fuel Combustion
Non-Energy Use of Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Soda Asb Manufacture and Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phospboric Acid Production
Carbon Dioxide Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
5,751.2
<0.5
<0.5
<0.5
50 75 100 125 150 175
Tj COZ Eq.
1990 and 2005, CO2 emissions from fossil fuel combustion
increased from 4,724.1 Tg CO2 Eq. to 5,751.2 Tg CO2 Eq.—a
21.7 percent total increase over the fifteen-year period. From
2004 to 2005, these emissions increased by 38.2 Tg CO2 Eq.
(0.7 percent).
Historically, changes in emissions from fossil fuel
combustion have been the dominant factor affecting U.S.
emission trends. Changes in CO2 emissions from fossil fuel
combustion are influenced by many long-term and short-term
factors, including population and economic growth, energy
price fluctuations, technological changes, and seasonal
temperatures. On an annual basis, the overall consumption
of fossil fuels in the United States generally fluctuates in
response to changes in general economic conditions, energy
prices, weather, and the availability of non-fossil alternatives.
For example, in a year with increased consumption of
goods and services, low fuel prices, severe summer and
winter weather conditions, nuclear plant closures, and lower
precipitation feeding hydroelectric dams, there would likely
be proportionally greater fossil fuel consumption than a
year with poor economic performance, high fuel prices,
mild temperatures, and increased output from nuclear and
hydroelectric plants.
The four major end-use sectors contributing to CO2
emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity
9 Global CCh emissions from fossil fuel combustion were taken from Energy Information Administration International Energy Annual 2004
(ElA2006a).
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19913-2005
-------
generation also emits CO2. although these emissions are
produced as they consume fossil fuel to provide electricity
to one of the four end-use sectors. For the discussion below,
electricity generation emissions have been distributed to each
end-use sector on the basis of each sector's share of aggregate
electricity consumption. This method of distributing
emissions assumes that each end-use sector consumes
electricity that is generated from the national average mix
of fuels according to their carbon intensity. Emissions from
electricity generation are also addressed separately after the
end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated
separately due to a lack of specific consumption data for the
individual end-use sectors.
Figure ES-6, Figure ES-7, and Table ES-3 summarize
COo emissions from fossil fuel combustion by end-use
sector.
Transportation End-Use Sector. Transportation activities
(excluding international bunker fuels) accounted for 33
percent of CO2 emissions from fossil fuel combustion in
2005.l() Virtually all of the energy consumed in this end-use
sector came from petroleum products. Over 60 percent of the
emissions resulted from gasoline consumption for personal
vehicle use. The remaining emissions came from other
Figure ES-7
Figure ES-6
2005 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
Natural Gas
Petroleum
I Coal
Relative Contribution
by Fuel Type
2,500 -i
2,000
1,500
1,000 -
500 -
0 -1
Residential Commercial Industrial Transportation Electricity U.S.
Generation Territories
Note: Electricity generation also includes emissions of less than 1 Tg C02 Eq. trom geothermal-based
electricity generation.
2005 End-Use Sector Emissions of C02 from
Fossil Fuel Combustion
2,000 -i
1,500
, 1,000 -
500 -
0 -1
From Electricity
Consumption
| From Direct Fossil
Fuel Combustion
Residential Commercial Industrial Transportation U.S.
Territories
transportation activities, including the combustion of diesel
fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial CO2 emissions,
resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed
by industry, accounted for 27 percent of CO2 from fossil fuel
combustion in 2005. About half of these emissions resulted
from direct fossil fuel combustion to produce steam and/or
heat for industrial processes. The other half of the emissions
resulted from consuming electricity for motors, electric
furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The
residential and commercial end-use sectors accounted for
21 and 18 percent, respectively, of CO2 emissions from
fossil fuel combustion in 2005. Both sectors relied heavily
on electricity for meeting energy demands, with 70 and
78 percent, respectively, of their emissions attributable to
electricity consumption for lighting, heating, cooling, and
operating appliances. The remaining emissions were due to
the consumption of natural gas and petroleum for heating
and cooking.
Electricity Generation. The United States relies on
electricity to meet a significant portion of its energy demands,
especially for lighting, electric motors, heating, and air
conditioning. Electricity generators consumed 36 percent of
U.S. energy from fossil fuels and emitted 41 percent of the
111 If emissions from international bunker fuels are included, the transportation end-use sector accounted for 35 percent of U.S. emissions from fossil fuel
combustion in 2005.
Executive Summary ES-7
-------
Table ES-3: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990
1,467.0 :
1,464.0
3.0
1,539.8
857.1
682.7
929.9
340.3
589.6
759.2
224.3
534.9
28.3 ,
4,724.1
1,810.2
1995
1,593.3 ?
1,590.2
3.0
1,595.8
882.7
713.1
995.4
356.4
639.0
810.6
226.4
584.2
35.0
5,030.0
1,939.3
2000
1,787.8
1,784.4
3.4
1,660.1
875.0
785.1
1,131.5
373.5
758.0
969.3
232.3
736.9
36.2
5,584.9
2,283.5
2001
1,761.5
1,758.2
3.3
1,596.6
869.9
726.7
1,124.8
363.9
760.9
979.7
225.1
754.6
49.0
5,511.7
2,245.5
2002
1,815.7
1,812.3
3.4
1,575.5
857.7
717.8
1,147.9
362.4
785.5
973.8
225.7
748.0
44.3
5,557.2
2,254.7
2003
1,814.8
1,810.5
4.3
1,595.1
858.3
736.8
1,179.1
383.8
795.3
984.2
236.6
747.6
51.3
5,624.5
2,284.0
2004
1,868.9
1,864.5
4.4
1,615.2
875.6
739.6
1,175.9
369.9
806.0
999.1
233.3
765.8
54.0
5,713.0
2,315.8
2005
1,897.9
1,892.8
5.2
1,575.2
840.1
735.1
1,208.7
358.7
849.9
1,016.8
225.8
791.0
52.5
5,751.2
2,381.2
Note: Totals may not sum due to independent rounding.
electricity consumption by each end-use sector.
Combustion-related emissions from electricity generation are allocated based on aggregate national
CO2 from fossil fuel combustion in 2005. The type of fuel
combusted by electricity generators has a significant effect
on their emissions. For example, some electricity is generated
with low CO2 emitting energy technologies, particularly non-
fossil options such as nuclear, hydroelectric, or geothermal
energy. However, electricity generators rely on coal for over
half of their total energy requirements and accounted for 93
percent of all coal consumed for energy in the United States
in 2005. Consequently, changes in electricity demand have
a significant impact on coal consumption and associated
CO2 emissions.
Other significant CO2 trends included the following:
• CO2 emissions from non-energy use of fossil fuels have
increased 25.1 Tg CO2 Eq. (21 percent) from 1990
through 2005. Emissions from non-energy uses of fossil
fuels were 142.4Tg CO2 Eq. in 2005, which constituted
2.5 percent of overall fossil fuel CO2 emissions and 2.3
percent of total national CO2 emissions, approximately
the same proportion as in 1990.
• CO2 emissions from cement production increased to 45.9
Tg CO2 Eq. in 2005, a 38 percent increase in emissions
since 1990. Emissions mirror growth in the construction
industry. In contrast to many other manufacturing
sectors, demand for domestic cement remains strong
because it is not cost-effective to transport cement far
from its point of manufacture.
• CO2 emissions from iron and steel production decreased
to 45.2 Tg CO2 Eq. in 2005, and have declined by 39.6
Tg CO2 Eq. (47 percent) from 1990 through 2005,
due to restructuring of the industry, technological
improvements, and increased scrap utilization.
• CO2 emissions from municipal solid waste combustion
(20.9 Tg CO2 Eq. in 2005) increased by 10.0 Tg CO2
Eq. (91 percent) from 1990 through 2005, as the volume
of plastics and other fossil carbon-containing materials
in municipal solid waste grew.
• Net CO2 sequestration from Land Use, Land-Use
Change, and Forestry increased by 115.7 Tg CO2 Eq.
(16 percent) from 1990 through 2005. This increase was
primarily due to an increase in the rate of net carbon
accumulation in forest carbon stocks, particularly in
aboveground and belowground tree biomass. Annual
carbon accumulation in landfilled yard trimmings and
food scraps slowed over this period, while the rate of
carbon accumulation in urban trees increased.
Methane Emissions
According to the IPCC, CH4 is more than 20 times as
effective as CO2 at trapping heat in the atmosphere. Over the
last two hundred and fifty years, the concentration of CH4
in the atmosphere increased by 143 percent (IPCC 2001,
Hofmann 2004). Anthropogenic sources of CH4 include
landfills, natural gas and petroleum systems, agricultural
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19913 -2005
-------
activities, coal mining, wastewater treatment, stationary
and mobile combustion, and certain industrial processes
(see Figure ES-8).
Some significant trends in U.S. emissions of CH4 include
the following:
• Landfills are the largest anthropogenic source of CH4
emissions in the United States. In 2005, landfill CH4
emissions were 132.0 Tg CO2 Eq. (approximately 24
percent of total CH4 emissions), which represents a
decline of 29.0 Tg CO2 Eq., or 18 percent, since 1990.
Although the amount of solid waste landfilled each year
continues to grow, the amount of CH4 captured and
burned at landfills has increased dramatically, countering
this trend.11
• In 2005, CH4 emissions from coal mining were 52.4 Tg
CO2 Eq. This decline of 29.5 Tg CO2 Eq. (36 percent)
from 1990 results from the mining of less gassy coal
from underground mines and the increased use of CH4
collected from degasification systems.
• CH4 emissions from natural gas systems were 111.1
Tg CO2 Eq. in 2005; emissions have declined by 13.3
Tg CO2 Eq. (11 percent) since 1990. This decline
has been due to improvements in technology and
management practices, as well as some replacement of
old equipment.
Figure ES-8
2005 Sources of CH*
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production and Consumption
Ferroalloy Production
CH4 as a Portion
of all Emissions
<0.05
<0.05
0 20 40 60 80 100 120 140
Tg CO, Eq.
• CH4 emissions from manure management were 41.3
Tg CO2 Eq. in 2005. From 1990 to 2005, emissions
from this source increased by 10.4 Tg CO2 Eq. (34
percent). The bulk of this increase was from swine and
dairy cow manure, and is attributed to the shift in the
composition of the swine and dairy industries toward
larger facilities. Larger swine and dairy farms tend to use
liquid management systems, where the decomposition
of materials in the manure tends to produce CH4.
Nitrous Oxide Emissions
N2O is produced by biological processes that occur in
soil and water and by a variety of anthropogenic activities
in the agricultural, energy-related, industrial, and waste
management fields. While total N2O emissions are much
lower than CO2 emissions, N2O is approximately 300 times
more powerful than CO2 at trapping heat in the atmosphere.
Since 1750, the global atmospheric concentration of N2O has
risen by approximately 18 percent (IPCC 2001, Hofmann
2004). The main anthropogenic activities producing N2O
in the United States are agricultural soil management, fuel
combustion in motor vehicles, manure management, nitric
acid production, wastewater treatment, and stationary fuel
combustion (see Figure ES-9).
Some significant trends in U.S. emissions of N2O include
the following:
• Agricultural soil management activities such as
fertilizer application and other cropping practices were
the largest source of U.S. N2O emissions, accounting
for 78 percent (365.1 Tg CO2 Eq.) of 2005 emissions.
N2O emissions from this source have not shown any
significant long-term trend, as they are highly sensitive
to the amount of N applied to soils, which has not
changed significantly over the time-period.
• In 2005, N2O emissions from mobile combustion were
38.0 Tg CO2 Eq. (approximately 8 percent of U.S. N2O
emissions). From 1990 to 2005, N2O emissions from
mobile combustion decreased by 13 percent. However,
from 1990 to 1998 emissions increased by 10 percent,
due to control technologies that reduced NOX emissions
while increasing N2O emissions. Since 1998, newer
' The CO2 produced from combusted landfill CH4 is not counted in national inventories as it is considered part of the natural C cycle of decomposition.
Executive Summary ES-9
-------
Figure ES-9
Figure ES-10
2005 Sources of N,0
365.1
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management |
Wastewater Treatment |
Adipic Acid Production |
Settlements Remaining Settlements |
N,0 Product Usage |
Forest Land Remaining Forest Land |
Municipal Solid Waste Combustion |
Field Burning of Agricultural Residues |
0
10
20 30
Tg COZ Eq.
40
50
control technologies have led to a steady decline in N2O
from this source.
HFC, RFC, and SF6 Emissions
HFCs and PFCs are families of synthetic chemicals
that are used as alternatives to the ODSs, which are being
phased out under the Montreal Protocol and Clean Air
Act Amendments of 1990. HFCs and PFCs do not deplete
the stratospheric ozone layer, and are therefore acceptable
alternatives under the Montreal Protocol.
These compounds, however, along with SF6, are
potent greenhouse gases. In addition to having high
global warming potentials. SF6 and PFCs have extremely
long atmospheric lifetimes, resulting in their essentially
irreversible accumulation in the atmosphere once emitted.
Sulfur hexafluoride is the most potent greenhouse gas the
IPCC has evaluated.
Other emissive sources of these gases include HCFC-22
production, electrical transmission and distribution systems,
semiconductor manufacturing, aluminum production, and
magnesium production and processing (see Figure ES-10).
Some significant trends in U.S. HFC, PFC, and SF6
emissions include the following:
• Emissions resulting from the substitution of ozone
depleting substances (e.g., CFCs) have been increasing
from small amounts in 1990 to 123.3 Tg CO2 Eq. in
2005. Emissions from substitutes for ozone depleting
substances are both the largest and the fastest
growing source of HFC, PFC, and SF6 emissions.
2005 Sources of HFCs, PFCs, and SF6
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Electrical Transmission
and Distribution
Semiconductor
Manufacture
Aluminum Production
Magnesium Production
and Processing
HFCs, PFCs, and
SF, as a Portion of
all Emissions
2.2% \
25
50 75
Tg CO, Eq.
100
125
These emissions have been increasing as phase-outs
required under the Montreal Protocol come into effect,
especially after 1994 when full market penetration
was made for the first generation of new technologies
featuring ODS substitutes.
• The increase in ODS substitute emissions is offset
substantially by decreases in emission of HFCs,
PFCs, and SF6 from other sources. Emissions from
aluminum production decreased by 84 percent (15.6
Tg CO2 Eq.) from 1990 to 2005, due to both industry
emission reduction efforts and lower domestic aluminum
production.
• Emissions from the production of HCFC-22 decreased
by 53 percent (18.4 Tg CO2 Eq.) from 1990 through
2(105, 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) and the use of
thermal oxidation at some plants to reduce HFC-23
emissions.
• Emissions from electric power transmission and
distribution systems decreased by 51 percent (13.9
Tg CO2 Eq.) from 1990 to 2005, primarily because of
higher purchase prices for SF6 and efforts by industry
to reduce emissions.
ES.3. Overview of Sector Emissions
and Trends
In accordance with the Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997), and the 2003 UNFCCC Guidelines on
ES-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19(10-2005
-------
Figure ES-11
Figure ES-12
U.S. Greenhouse Gas Emissions and Sinks
by Chapter/IPCC Sector
Waste LULUCF (non-CO,|
Land Use, Land-Use Change, and Forestry (net CO, (lux)
Reporting and Review (UNFCCC 2003), the Inventory of U .S.
Greenhouse Gas Emissions and Sinks report is segregated
into six sector-specific chapters. Figure ES-11 and Table ES-4
aggregate emissions and sinks by these chapters.
Energy
The Energy chapter contains emissions of all greenhouse
gases resulting from stationary and mobile energy activities
including fuel combustion and fugitive fuel emissions.
Energy-related activities, primarily fossil fuel combustion,
accounted for the vast majority of U.S. CO2 emissions for
the period of 1990 through 2005. In 2005, approximately
86 percent of the energy consumed in the United States (on
a Btu basis) was produced through the combustion of fossil
fuels. The remaining 14 percent came from other energy
2005 U.S. Energy Consumption by Energy Source
Natural Gas ,"^**B!
Coal
Petroleum
23%
23%
40%
sources such as hydropower, biomass, nuclear, wind, and
solar energy (see Figure ES-12). Energy related activities are
also responsible for CH4 and N2O emissions (38 percent and
11 percent of total U.S. emissions of each gas, respectively).
Overall, emission sources in the Energy chapter account
for a combined 85 percent of total U.S. greenhouse gas
emissions in 2005.
Industrial Processes
The Industrial Processes chapter contains by-product
or fugitive emissions of greenhouse gases from industrial
processes not directly related to energy activities such as
fossil fuel combustion. For example, industrial processes
can chemically transform raw materials, which often release
waste gases such as CO2, CH4, and N2O. The processes
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product
Agriculture
Land Use, Land-Use Cham
and Forestry (Non-C02 1
Waste
Total
Use
36,
imissions)
199
5,202
300
4,
530
13
192,
6,242,
10
.2
.1
.3
.3
.0
.2
.0
198
5,525
314
4
526
10
189
6,571
15
.8
.8
.5
.8
.1
.1
.0
2000
6,069.2
338.7
4.8
547.4
21.3
165.9
7,147.2
2001
5,978.9
309.6
4.8
560.3
12.4
161.1
7,027.0
2002
6,021.4
320.2
4.3
537.4
17.4
163.9
7,064.6
2003
6,079.1
316.4
4.3
521.1
15.0
168.4
7,104.2
2004
6,181.7
330.6
4.3
507.4
13.9
165.7
7,203.7
2005
6,201.9
333.6
4.3
536.3
18.9
165.4
7,260.4
Net C02 Flux from Land Use,
Land-Use Change, and Forestry* (712.8) (828.8)
(756.7) (767.5) (811.9) (811.9) (824.8) (828.5)
Net Emissions (Sources and Sinks) 5,529.2
5,742.2
6,390.5 6,259.5 6,252.7 6,292.3 6,378.9 6,431.9
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions total.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values or sequestration.
Executive Summary ES-11
-------
include iron and steel production, lead and zinc production,
cement manufacture, ammonia manufacture and urea
application, lime manufacture, limestone and dolomite
use (e.g., flux stone, flue gas desulfurization, and glass
manufacturing), soda ash manufacture and use, titanium
dioxide production, phosphoric acid production, ferroalloy
production, CO2 consumption, aluminum production,
petrochemical production, silicon carbide production, nitric
acid production, and adipic acid production. Additionally,
emissions from industrial processes release HFCs, PFCs,
and SF6. Overall, emission sources in the Industrial Process
chapter accounted for 4.6 percent of U.S. greenhouse gas
emissions in 2005.
Solvent and Other Product Use
The Solvent and Other Product Use chapter contains
greenhouse gas emissions that are produced as a by-product
of various solvent and other product uses. In the United
States, emissions from N2O Product Usage, the only source
of greenhouse gas emissions from this sector, accounted for
less than 0.1 percent of total U.S. anthropogenic greenhouse
gas emissions on a carbon equivalent basis in 2005.
Agriculture
The Agriculture chapter contains anthropogenic
emissions from agricultural activities (except fuel combustion,
which is addressed in the Energy chapter, and agricultural
CO2 fluxes, which are addressed in the Land Use, Land-
Use Change, and Forestry Chapter). Agricultural activities
contribute directly to emissions of greenhouse gases through
a variety of processes, including the following source
categories: enteric fermentation in domestic livestock,
livestock manure management, rice cultivation, agricultural
soil management, and field burning of agricultural residues.
CH4 and N2O were the primary greenhouse gases emitted
by agricultural activities. CH4 emissions from enteric
fermentation and manure management represented about
21 percent and 8 percent of total CH4 emissions from
anthropogenic activities, respectively, in 2005. Agricultural
soil management activities such as fertilizer application
and other cropping practices were the largest source of U.S.
N2O emissions in 2005, accounting for 78 percent. In 2005,
emission sources accounted for in the Agriculture chapter
were responsible for 7.4 percent of total U.S. greenhouse
gas emissions.
Land Use, Land-Use Change, and Forestry
The Land Use, Land-Use Change, and Forestry chapter
contains emissions of CH4 and N2O, and emissions and
removals of CO2 from forest management, other land-use
activities, and land-use change. Forest management practices,
tree planting in urban areas, the management of agricultural
soils, and the landfilling of yard trimmings and food scraps
have resulted in a net uptake (sequestration) of C in the United
States. Forests (including vegetation, soils, and harvested
wood) accounted for approximately 84 percent of total
2005 sequestration, urban trees accounted for 11 percent,
agricultural soils (including mineral and organic soils and the
application of lime) accounted for 2 percent, and landfilled
yard trimmings and food scraps accounted for 1 percent of
the total sequestration in 2005. The net forest sequestration
is a result of net forest growth and increasing forest area,
as well as a net accumulation of carbon stocks in harvested
wood pools. The net sequestration in urban forests is a result
of net tree growth in these areas. In agricultural soils, mineral
soils account for a net C sink that is almost two times larger
than the sum of emissions from organic soils and liming. The
mineral soil C sequestration is largely due to the conversion
of cropland to permanent pastures and hay production, a
reduction in summer fallow areas in semi-arid areas, an
increase in the adoption of conservation tillage practices,
and an increase in the amounts of organic fertilizers (i.e.,
manure and sewage sludge) applied to agriculture lands. The
landfilled yard trimmings and food scraps net sequestration is
due to the long-term accumulation of yard trimming carbon
and food scraps in landfills. Land use, land-use change, and
forestry activities in 2005 resulted in a net C sequestration of
828.5 Tg CO, Eq. (Table ES-5). This represents an offset of
approximately 13.6 percent of total U.S. CO2 emissions, or
11.4 percent of total greenhouse gas emissions in 2005. Total
land use, land-use change, and forestry net C sequestration
increased by approximately 16 percent between 1990 and
2005, primarily due to an increase in the rate of net C
accumulation in forest C stocks, particularly in aboveground
and belowground tree biomass. Annual C accumulation in
landfilled yard trimmings and food scraps slowed over this
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table ES-5: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon
Stocks and Liming Emissions
Land Converted to Cropland
Changes in Agricultural Soil
Carbon Stocks
Grassland Remaining Grassland
Changes in Agricultural Soil
Carbon Stocks
Land Converted to Grassland
Changes in Agricultural Soil
Carbon Stocks
Settlements Remaining Settlements
Urban Trees
Other
Landfilled Yard Trimmings and
Food Scraps
Total
1990
(598.5)
(598.5)
(28.1)
(28.1)
8.7
8.7
0.1
0.1
(14.6)
(14.6)
(57.5)
(57.5)
(22.8)
(22.8)
(712.8)
1995
(717.5)
(717.5)
(37.4)
(37.4)
7.2
7.2
16.4
16.4
(16.3)
(16.3)
(67.8)
(67.8)
(13.3)
(13.3)
(828.8)
2000
(638.7)
(638.7)
(36.5)
(36.5)
7.2
7.2
16.3
16.3
(16.3)
(16.3)
(78.2)
(78.2)
(10.5)
(10.5)
(756.7)
2001
(645.7)
(645.7)
(38.0)
(38.0)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(80.2)
(80.2)
(10.6)
(10.6)
(767.5)
2002
(688.1)
(688.1)
(37.8)
(37.8)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(82.3)
(82.3)
(10.8)
(10.8)
(811.9)
2003
(687.0)
(687.0)
(38.3)
(38.3)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(84.4)
(84.4)
(9.3)
(9.3)
(811.9)
2004
(697.3)
(697.3)
(39.4)
(39.4)
7.2
7.2
16.1
16.1
(16.3)
(16.3)
(86.4)
(86.4)
(8.7)
(8.7)
(824.8)
2005
(698.7)
(698.7)
(39.4)
(39.4)
7.2
7.2
16.1
16.1
(16.3)
(16.3)
(88.5)
(88.5)
(8.8)
(8.8)
(828.5)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Table ES-6: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Category
1990
1995
2000 2001 2002 2003 2004 2005
Forest Land Remaining Forest Land
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
N20 Emissions from Soils
Settlements Remaining Settlements
N20 Emissions from Soils
7.8
7.1
0.7
0.1
5.1
5.1
4.5
4.0
0.4
0.2
5.5
5.5
15.7
14.0
1.4
0.3
5.6
5.6
6.9
6.0
0.6
0.3
5.5
5.5
11.8
10.4
1.1
0.3
5.6
5.6
9.2
8.1
0.8
0.3
5.8
5.8
8.0
6.9
0.7
0.3
6.0
6.0
13.1
11.6
1.2
0.3
5.8
5.8
Total
13.0
10.1
21.3
12.4
17.4
15.0
13.9
18.9
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
period, while the rate of annual C accumulation increased
in urban trees. Net U.S. emissions (all sources and sinks)
increased by 16.4 percent from 1990 to 2005.
Non-CO2 emissions from Land Use, Land-Use Change,
Ware
The Waste chapter contains emissions from waste
management activities (except waste incineration, which
is addressed in the Energy chapter). Landfills were the
and Forestry are shown in Table ES-6. The application of largest source of anthropogenic CH4 emissions, accounting
synthetic fertilizers to forest and settlement soils in 2005 for 24 percent of total U.S. CH4 emissions.12 Additionally,
resulted in direct N2O emissions of 6.2 Tg CO2 Eq. Direct wastewater treatment accounts for just under 5 percent of
N2O emissions from fertilizer application increased by U.S. CH4 emissions. N2O emissions from the discharge of
approximately 19 percent between 1990 and 2005. Non- wastewater treatment effluents into aquatic environments
CO2 emissions from forest fires in 2005 resulted in CH4 were estimated, as were N2O emissions from the treatment
emissions of 11.6 Tg CO2 Eq., and in N2O emissions of 1.2 process itself. Overall, in 2005, emission sources accounted
TgCO2Eq.
for in the Waste chapter generated 2.3 percent of total U.S.
greenhouse gas emissions.
'- Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land-
Use. Land-Use Change, and Forestry chapter.
-------
ES.4. Other Information
Emissions by Economic Sector
Throughout this report, emission estimates are grouped
into six sectors (i.e., chapters) defined by the IPCC: Energy,
Industrial Processes, Solvent Use, Agriculture, Land Use,
Land-Use Change, and Forestry, and Waste. While it is
important to use this characterization for consistency with
UNFCCC reporting guidelines, it is also useful to allocate
emissions into more commonly used sectoral categories. This
section reports emissions by the following economic sectors:
Residential, Commercial, Industry, Transportation, Electricity
Generation, and Agriculture, and U.S. Territories.
Table ES-7 summarizes emissions from each of these
sectors, and Figure ES-13 shows the trend in emissions by
sector from 1990 to 2005.
Using this categorization, emissions from electricity
generation accounted for the largest portion (33 percent)
of U.S. greenhouse gas emissions in 2005. Transportation
activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted
for 19 percent of U.S. greenhouse gas emissions in 2005.
In contrast to electricity generation and transportation,
emissions from industry have in general declined over the
past decade. The long-term decline in these emissions has
been due to structural changes in the U.S. economy (i.e., shifts
from a manufacturing-based to a service-based economy),
fuel switching, and energy efficiency improvements. The
remaining 20 percent of U.S. greenhouse gas emissions
were contributed by the residential, agriculture, and
Figure ES-13
Emissions Allocated to Economic Sectors
3,000 -
2,500 -
2,000 -
cr
LU
8 1,500 -
F
1,000 -
500-
0-
Or-c\im*Tincor~
o)a)9>o)o>aiO)ai
Note: Does not include U.S. territories
Electricity Generation
Transportation
Industry
.^Agriculture
Commercial
Residential
commercial sectors, plus emissions from U.S. territories.
The residential sector accounted for about 5 percent, and
primarily consisted of CO2 emissions from fossil fuel
combustion. Activities related to agriculture accounted for
roughly 8 percent of U.S. emissions; unlike other economic
sectors, agricultural sector emissions were dominated by
N2O emissions from agricultural soil management and CH4
emissions from enteric fermentation, rather than CO2 from
fossil fuel combustion. The commercial sector accounted
for about 6 percent of emissions, while U.S. territories
accounted for 1 percent.
CO2 was also emitted and sequestered by a variety
of activities related to forest management practices, tree
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq.)
Implied Sectors
Electric Power Industry
Transportation
Industry
Agriculture
Commercial
Residential
U.S. Territories
Total Emissions
Land Use, Land-Use Change, and
Forestry (Sinks)
Net Emissions (Sources and Sinks)
1990
1,859.7
1,523.0
1,470.9
585.3
417.8
351.3
34.1
6,242.0
(712.8)
5,529.2
1995
1,989.5
1,677.2
1,478.4
589.2
420.5
375.1
41.1
6,571.0
(828.8)
5,742.2
2000
2,329.9
1,903.2
1,443.3
614.4
415.5
393.6
47.3
7,147.2
(756.7)
6,390.5
2001
2,292.0
1,876.4
1,395.4
618.4
406.6
383.6
54.5
7,027.0
(767.5)
6,259.5
2002
2,300.7
1,931.2
1,380.0
602.6
413.7
382.7
53.6
7,064.6
(811.9)
6,252.7
2003
2,330.2
1,928.2
1,371.8
575.7
433.5
404.8
60.0
7,104.2
(811.9)
6,292.3
2004
2,363.4
1,982.6
1,403.3
567.0
432.6
391.6
63.2
7,203.7
(824.8)
6,378.9
2005
2,429.8
2,008.9
1,352.8
595.4
431.4
380.7
61.5
7,260.4
(828.5)
6,431.9
Note: Totals may not sum due to independent rounding. Emissions include C02, CH4, N20, HFCs, PFCs, and SF6.
See Table 2-14 for more detailed data.
ES-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
planting in urban areas, the management of agricultural soils,
and landfilling of yard trimmings.
Electricity is ultimately consumed in the economic
sectors described above. Table ES-8 presents greenhouse
gas emissions from economic sectors with emissions related
to electricity generation distributed into end-use categories
(i.e., emissions from electricity generation are allocated to
the economic sectors in which the electricity is consumed).
To distribute electricity emissions among end-use sectors,
emissions from the source categories assigned to electricity
generation were allocated to the residential, commercial,
industry, transportation, and agriculture economic sectors
according to retail sales of electricity.13 These source
categories include CO2 from fossil fuel combustion and the
use of limestone and dolomite for flue gas desulfurization,
CO2 and N2O from waste combustion, CH4 and N2O from
stationary sources, and SF6 from electrical transmission and
distribution systems.
When emissions from electricity are distributed among
these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (28 percent) in 2005. Emissions
from the residential and commercial sectors also increase
substantially when emissions from electricity are included,
due to their relatively large share of electricity consumption
(e.g., lighting, appliances, etc.). Transportation activities
remain the second largest contributor to total U.S. emissions
(28 percent). In all sectors except agriculture, CO2 accounts
for more than 80 percent of greenhouse gas emissions,
Figure ES-14
Emissions with Electricity Distributed
to Economic Sectors
2,500
2,000
a 1'500~
1,000-
500-
o-1
Industrial
Transportation
Residential
o T- .
Executive Summary ES-15
-------
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include:
(1) emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions; (2) emissions
per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels; (3) emissions per
unit of electricity consumption, because the electric power industry—utilities and nonutilities combined—was the largest source of U.S.
greenhouse gas emissions in 2005; (4) emissions per unit of total gross domestic product as a measure of national economic activity; or
(5) emissions per capita.
Table ES-9 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse
gas emissions in the United States have grown at an average annual rate of 1.0 percent since 1990. This rate is slightly slower than that for
total energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total
U.S. greenhouse gas emissions have also grown slightly slower than national population since 1990 (see Figure ES-15).
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100)
Variable
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Population"
Greenhouse Gas Emissions6
1990
100
100
100
100
100
100
1995
113
112
107
108
107
105
2000
138
127
117
117
113
115
2001
139
125
115
114
114
113
2002
141
128
116
116
115
113
2003
145
129
118
117
116
114
2004
150
131
119
119
117
115
2005
155
134
119
118
118
116
Growth
Rate"
3.0%
2.0%
1.2%
1.1%
1.1%
1.0%
a Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2006)
c Energy-content-weighted values (EIA 2006b)
" U.S. Census Bureau (2006)
e GWP-weighted values
Figure ES-15
U.S. Greenhouse Gas Emissions Per Capita and
Per Dollar of Gross Domestic Product
160
150
= 130
o 12°
I 110
"jjTlOO
I 90
80
70
Real GDP
Population
Emissions
per capita
Emissions
per SGDP
oi-cMro*fincor**coaio
o)o>o)O)O)0)0>0)O)O)o
CM co ^ m
§ § § §
Source: BEA (2006), U.S. Census Bureau (2006), and emission estimates in :his report.
1S-16 inventory of U,£, lireer^cusse
-------
terrestrial radiation absorption by influencing the formation
and destruction of tropospheric and stratospheric ozone, or, in
the case of SO2, by affecting the absorptive characteristics of
the atmosphere. Additionally, some of these gases may react
with other chemical compounds in the atmosphere to form
compounds that are greenhouse gases.
Since 1970, the United States has published estimates
of annual emissions of CO, NOX, NMVOCs, and SO2 (EPA
2006),15 which are regulated under the Clean Air Act. Table
ES-10 shows that fuel combustion accounts for the majority
of emissions of these indirect greenhouse gases. Industrial
processes—such as the manufacture of chemical and allied
products, metals processing, and industrial uses of solvents—
are also significant sources of CO, NOX, and NMVOCs.
Key Categories
The IPCC's Good Practice Guidance (IPCC 2000)
defines a key category as a "[source or sink category] that
is prioritized within the national inventory system because
its estimate has a significant influence on a country's total
inventory of direct greenhouse gases in terms of the absolute
level of emissions, the trend in emissions, or both."16 By
Table ES-10: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
NOX
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Oil and Gas Activities
Municipal Solid Waste Combustion
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Municipal Solid Waste Combustion
Industrial Processes
Agricultural Burning
Oil and Gas Activities
Waste
Solvent Use
NMVOCs
Mobile Fossil Fuel Combustion
Solvent Use
Industrial Processes
Stationary Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
Waste
Agricultural Burning
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
Waste
Solvent Use
Agricultural Burning
1990
21,645
10,920
9,883
591
139
82
28
1
0
130,581
119,480
5,000
978
4,125
691
302
1
5
20,930
10,932
5,216
2,422
912
554
222
673
NA
20,935
18,407
1,307
793
390
38
0
0
NA
1995
21,272
10,622
9,821
607
100
88
29
3
1
109,157
97,755
5,383
1,073
3,959
663
316
2
5
19,520
8,745
5,609
2,642
973
582
237
731
NA
16,891
14,724
1,117
672
335
42
1
1
NA
2000
19,203
10,310
8,002
626
111
114
35
3
2
92,897
83,680
4,340
1,670
2,217
792
146
8
46
15,228
7,230
4,384
1,773
1,077
389
257
119
NA
14,829
12,848
1,031
632
286
29
1
1
NA
2001
18,410
9,819
7,667
656
113
114
35
3
2
89,333
79,972
4,377
1,672
2,339
774
147
8
45
15,048
6,872
4,547
1,769
1,080
400
258
122
NA
14,452
12,461
1,047
624
289
30
1
1
NA
2002
18,141
10,319
6,837
532
316
97
33
5
2
86,796
77,382
5,224
1,440
1,710
709
323
7
1
14,968
6,608
3,911
1,811
1,733
546
244
116
NA
13,541
11,852
752
681
233
23
1
0
NA
2003
17,327
9,911
6,428
533
317
98
34
5
2
84,370
74,756
5,292
1,457
1,730
800
327
7
1
14,672
6,302
3,916
1,813
1,734
547
244
116
NA
13,648
12,002
759
628
235
23
1
0
NA
2004
16,466
9,520
5,952
534
317
98
39
5
2
82,073
72,269
5,361
1,475
1,751
879
331
7
1
14,391
6,011
3,921
1,815
1,735
547
244
116
NA
13,328
11,721
766
579
238
23
1
0
NA
2005
15,965
9,145
5,824
535
318
98
39
5
2
79,811
69,915
5,431
1,493
1,772
858
335
7
1
14,123
5,734
3,926
1,818
1,736
548
245
116
NA
13,271
11,698
774
535
240
23
1
0
NA
Source: (EPA 2006, disaggregated based on EPA 2003} except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
15 NOX and CO emission estimates from Held burning of agricultural residues were estimated separately, and therefore not taken from EPA (2006).
16 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000). .
(executive Summary ES-17
-------
definition, key categories are sources or sinks that have the
greatest contribution to the absolute overall level of national
emissions in any of the years covered by the time series. In
addition, when an entire time series of emission estimates
is prepared, a thorough investigation of key categories
must also account for the influence of trends of individual
source and sink categories. Finally, a qualitative evaluation
of key categories should be performed, in order to capture
any key categories that were not identified in either of the
quantitative analyses.
Figure ES-16 presents 2005 emission estimates for
the key categories as defined by a level analysis (i.e., the
contribution of each source or sink category to the total
inventory level). The UNFCCC reporting guidelines
request that key category analyses be reported at an
appropriate level of disaggregation, which may lead to
source and sink category names which differ from those
used elsewhere in this report. For more information
regarding key categories, see section 1.5 and Annex 1 of
this report.
Quality Assurance and Quality Control
(QA/QC)
The United States seeks to continually improve the
quality, transparency, and credibility of the Inventory of
U.S. Greenhouse Gas Emissions and Sinks. To assist in these
efforts, the United States implemented a systematic approach
to QA/QC. While QA/QC has always been an integral part
of the U.S. national system for inventory development, the
procedures followed for the current inventory have been
formalized in accordance with the QA/QC plan and the
UNFCCC reporting guidelines.
Uncertainty Analysis of Emission
Estimates
While the current U.S. emissions inventory provides a
solid foundation for the development of a more detailed and
comprehensive national inventory, there are uncertainties
associated with the emission estimates. Some of the current
estimates, such as those for CO2 emissions from energy-
Figure ES-16
2005 Key Categories-Tier 1 Level Assessment
C02 Emissions from Stationary Combustion - Coal
COZ Emissions from Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion - Gas
CO, Emissions from Stationary Combustion - Oil
Direct NZ0 Emissions from Agricultural Soil Management
CO; Emissions from Mobile Combustion: Aviation
C02 Emissions from Non-Energy Use of Fuels
CH, Emissions from Landfills
Emissions from Substitutes for Ozone Depleting Substances
CH, Emissions from Enteric Fermentation
Fugitive CH, Emissions from Natural Gas Systems
CO; Emissions from Mobile Combustion: Marine
Indirect N20 Emissions from Applied Nitrogen
Fugitive CH, Emissions from Coal Mining
C02 Emissions from Cement Manufacture
CO, Emissions from Iron and Steel Production
Note: For a complete discussion ot the key source analysis see Annex 1.
I I I I I I I I I T I
200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200
Tg COZ Eq.
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
related activities and cement processing, are considered
to have low uncertainties. For some other categories
of emissions, however, a lack of data or an incomplete
understanding of how emissions are generated increases
the uncertainty associated with the estimates presented.
Acquiring a better understanding of the uncertainty
associated with inventory estimates is an important step
in helping to prioritize future work and improve the
overall quality of the Inventory. Recognizing the benefit of
conducting an uncertainty analysis, the UNFCCC reporting
guidelines follow the recommendations of the IPCC Good
Practice Guidance (IPCC 2000) and require that countries
provide single estimates of uncertainty for source and sink
categories.
Currently, a qualitative discussion of uncertainty is
presented for all source and sink categories. Within the
discussion of each emission source, specific factors affecting
the uncertainty surrounding the estimates are discussed. Most
sources also contain a quantitative uncertainty assessment,
in accordance with UNFCCC reporting guidelines.
Executive Summary ES-19
-------
-------
Introduction
This report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions
and sinks for the years 1990 through 2005. A summary of these estimates is provided in Table 2-3 and Table 2-4
by gas and source category in the Trends in Greenhouse Gas Emissions chapter. The emission estimates in these
tables are presented on both a full molecular mass basis and on a Global Warming Potential (GWP) weighted basis in order
to show the relative contribution of each gas to global average radiative forcing.' This report also discusses the methods
and data used to calculate these emission estimates.
In 1992, the United States signed and ratified the United Nations Framework Convention on Climate Change (UNFCCC).
As stated in Article 2 of the UNFCCC, "The ultimate objective of this Convention and any related legal instruments that
the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions of the Convention,
stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic
interference with the climate system. Such a level should be achieved within a time-frame sufficient to allow ecosystems
to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development
to proceed in a sustainable manner."2-3
Parties to the Convention, by ratifying, "shall develop, periodically update, publish and make available...national
inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the
Montreal Protocol, using comparable methodologies...."4 The United States views this report as an opportunity to fulfill
these commitments under the UNFCCC.
In 1988, preceding the creation of the UNFCCC, the World Meteorological Organization (WMO) and the United
Nations Environment Programme (UNEP) jointly established the Intergovernmental Panel on Climate Change (IPCC). The
role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the scientific, technical and socio-
economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential
impacts and options for adaptation and mitigation (IPCC 2003). Under Working Group 1 of the IPCC, nearly 140 scientists
and national experts from more than thirty countries collaborated in the creation of the Revised 1996 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) to ensure that the emission inventories submitted to
the UNFCCC are consistent and comparable between nations. The IPCC accepted the Revised 1996 IPCC Guidelines at its
Twelfth Session (Mexico City, September 11-13,1996). This report presents information in accordance with these guidelines.
1 See the section below entitled Global Warming Potentials for an explanation of GWP values.
2 The term "anthropogenic." in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result
of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
3 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See . (UNEP/WMO 2000).
4 Article 4( 1 )(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent decisions by the Conference
of the Parties elaborated the role of Annex I Parties in preparing national inventories. See .
introduction
-------
In addition, this Inventory is in accordance with the IPCC
Good Practice Guidance and Uncertainty Management
in National Greenhouse Gas Inventories and the Good
Practice Guidance for Land Use, Land-Use Change, and
Forestry, which further expanded upon the methodologies
in the Revised 1996 IPCC Guidelines. The IPCC has also
accepted the 2006 Guidelines for National Greenhouse
Gas Inventories (IPCC 2006) at its Twenty-Fifth Session
(Mauritius, April 2006). The 2006 IPCC Guidelines build
on the previous bodies of work and includes new sources
and gases ".. .as well as updates to the previously published
methods whenever scientific and technical knowledge have
improved since the previous guidelines were issued." Many
of the methodological improvements presented in the 2006
Guidelines have been adopted in this Inventory.
Overall, this Inventory of anthropogenic greenhouse gas
emissions provides a common and consistent mechanism
through which Parties to the UNFCCC can estimate emissions
and compare the relative contribution of individual sources,
gases, and nations to climate change. The structure of this
report is consistent with the current UNFCCC Guidelines
on Annual Inventories (UNFCCC 2006).
1.1. Background Information
Greenhouse Gases
Although the earth's atmosphere consists mainly of
oxygen and nitrogen, neither plays a significant role in
enhancing the greenhouse effect because both are essentially
transparent to terrestrial radiation. The greenhouse effect
is primarily a function of the concentration of water
vapor, carbon dioxide (CO2), and other trace gases in the
atmosphere that absorb the terrestrial radiation leaving the
surface of the earth (IPCC 2001). Changes in the atmospheric
concentrations of these greenhouse gases can alter the balance
of energy transfers between the atmosphere, space, land, and
the oceans.5 A gauge of these changes is called radiative
forcing, which is a measure of the influence a factor has in
altering the balance of incoming and outgoing energy in the
earth-atmosphere system (IPCC 2001). Holding everything
else constant, increases in greenhouse gas concentrations in
the atmosphere will produce positive radiative forcing (i.e.,
a net increase in the absorption of energy by the earth).
Climate change can be driven by changes in
the atmospheric concentrations of a number of
radiatively active gases and aerosols. We have
clear evidence that human activities have affected
concentrations, distributions and life cycles of these
gases (IPCC 1996).
Naturally occurring greenhouse gases include water
vapor, CO2, methane (CH4), nitrous oxide (N2O), and
ozone (O3). Several classes of halogenated substances that
contain fluorine, chlorine, or bromine are also greenhouse
gases, but they are, for the most part, solely a product
of industrial activities. Chlorofluorocarbons (CFCs) and
hydrochlorofluorocarbons (HCFCs) are halocarbons that
contain chlorine, while halocarbons that contain bromine
are referred to as bromofluorocarbons (i.e., halons). As
stratospheric ozone depleting substances, CFCs, HCFCs,
and halons are covered under the Montreal Protocol on
Substances that Deplete the Ozone Layer. The UNFCCC
defers to this earlier international treaty. Consequently, Parties
to the UNFCCC are not required to include these gases in
national greenhouse gas inventories.6 Some other fluorine-
containing halogenated substances —hydrofluorocarbons
(HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride
(SF6) — do not deplete stratospheric ozone but are potent
greenhouse gases. These latter substances are addressed by
the UNFCCC and accounted for in national greenhouse gas
inventories.
There are also several gases that, although they
do not have a commonly agreed upon direct radiative
forcing effect, do influence the global radiation budget.
These tropospheric gases include carbon monoxide
(CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and
tropospheric (ground level) O3. Tropospheric O3 is formed
by two precursor pollutants, volatile organic compounds
(VOCs) and nitrogen oxides (NOX) in the presence of
ultraviolet light (sunlight). Aerosols are extremely small
particles or liquid droplets that are often composed of
sulfur compounds, carbonaceous combustion products,
crustal materials, and other human-induced pollutants.
3 For more on the science of climate change, see NRC (2001).
6 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in this document for informational purposes.
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
They can affect the absorptive characteristics of the
atmosphere. Comparatively, however, the level of scientific
understanding of aerosols is still very low (IPCC 2001).
CO2, CH4, and N2O are continuously emitted to
and removed from the atmosphere by natural processes
on earth. Anthropogenic activities, however, can cause
additional quantities of these and other greenhouse gases
to be emitted or sequestered, thereby changing their global
average atmospheric concentrations. Natural activities such
as respiration by plants or animals and seasonal cycles of
plant growth and decay are examples of processes that only
cycle carbon or nitrogen between the atmosphere and organic
biomass. Such processes, except when directly or indirectly
perturbed out of equilibrium by anthropogenic activities,
generally do not alter average atmospheric greenhouse gas
concentrations over decadal timeframes. Climatic changes
resulting from anthropogenic activities, however, could
have positive or negative feedback effects on these natural
systems. Atmospheric concentrations of these gases, along
with their rates of growth and atmospheric lifetimes, are
presented in Table 1-1.
A brief description of each greenhouse gas, its sources,
and its role in the atmosphere is given below. The following
section then explains the concept of GWPs, which are
assigned to individual gases as a measure of their relative
average global radiative forcing effect.
Water Vapor (H2O). Overall, the most abundant and
dominant greenhouse gas in the atmosphere is water vapor.
Water vapor is neither long-lived nor well mixed in the
atmosphere, varying spatially from 0 to 2 percent (IPCC
1996). In addition, atmospheric water can exist in several
physical states including gaseous, liquid, and solid. Human
activities are not believed to affect directly the average
global concentration of water vapor, but the radiative
forcing produced by the increased concentrations of other
greenhouse gases may indirectly affect the hydrologic cycle.
While a warmer atmosphere has an increased water holding
capacity, increased concentrations of water vapor affects the
formation of clouds, which can both absorb and reflect solar
and terrestrial radiation. Aircraft contrails, which consist of
water vapor and other aircraft emittants, are similar to clouds
in their radiative forcing effects (IPCC 1999).
Carbon Dioxide. In nature, carbon is cycled between
various atmospheric, oceanic, land biotic, marine biotic,
and mineral reservoirs. The largest fluxes occur between the
atmosphere and terrestrial biota, and between the atmosphere
and surface water of the oceans. In the atmosphere,
carbon predominantly exists in its oxidized form as CO2.
Atmospheric CO2 is part of this global carbon cycle, and
therefore its fate is a complex function of geochemical and
biological processes. CO2 concentrations in the atmosphere
increased from approximately 280 parts per million by
volume (ppmv) in pre-industrial times to 376.7 ppmv in 2004,
a 35 percent increase (IPCC 2001 and Hofmann 2004),7-8
The IPCC definitively states that "the present atmospheric
CO2 increase is caused by anthropogenic emissions of CO2"
(IPCC 2001). The predominant source of anthropogenic CO2
emissions is the combustion of fossil fuels. Forest clearing,
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (years)
of Selected Greenhouse Gases
Atmospheric Variable
Pre-industrial atmospheric concentration
Atmospheric concentration3
Rate of concentration change"
Atmospheric lifetime
C02
280 ppm
376.7 ppm
1,610ppm/yr
50-200°
CH4
0.722 ppm
1.756 ppm
0.005 ppm/yr
12d
N20
0.270 ppm
0.31 9 ppm
0.0007 ppm/yr
114d
SF6
Oppt
5.4 ppt
0.23 ppt/yr
3,200
CF4
40 ppt
80 ppt
1 .0 ppl/yr
>50,000
Source: Current atmospheric concentrations and rate of concentration changes for all gases but CF4 are from Hofmann (2004); data for CF4 are from IPCC
(2001). Pre-industrial atmospheric concentration and atmospheric lifetime taken from IPCC (2001).
a Concentration for CF4 was measured in 2000. Concentrations for all other gases were measured in 2004.
b Rate is calculated over the period 1990 to 2004 for C02, CH4, and N20; 1996 to 2004 for SF6; and 1990 to 1999 for CF4.
c No single lifetime can be defined for C02 because of the different rates of uptake by different removal processes.
d This lifetime has been defined as an "adjustment time" that takes into account the indirect effect of the gas on its own residence time.
7 The pre-industrial period is considered as the time preceding the year 1750 (IPCC 2001).
s Carbon dioxide concentrations during the last 1,000 years of the pre-industrial period (i.e.. 750-1750). a time of relative climate stability, fluctuated by
about ±10 ppmv around 280 ppmv (IPCC 2001).
introduction 13
-------
other biomass burning, and some non-energy production
processes (e.g., cement production) also emit notable
quantities of CO2.
In its second assessment, the IPCC also stated that "ft]he
increased amount of CO2 [in the atmosphere] is leading
to climate change and will produce, on average, a global
warming of the earth's surface because of its enhanced
greenhouse effect—although the magnitude and significance
of the effects are not fully resolved" (IPCC 1996).
Methane. CH4 is primarily produced through anaerobic
decomposition of organic matter in biological systems.
Agricultural processes such as wetland rice cultivation,
enteric fermentation in animals, and the decomposition
of animal wastes emit CH4, as does the decomposition
of municipal solid wastes. CH4 is also emitted during the
production and distribution of natural gas and petroleum, and
is released as a by-product of coal mining and incomplete
fossil fuel combustion. Atmospheric concentrations of CH4
have increased by about 143 percent since 1750, from a
pre-industrial value of about 722 ppb to 1,756 ppb in 2004,
although the rate of increase has been declining. The IPCC
has estimated that slightly more than half of the current
CH4 flux to the atmosphere is anthropogenic, from human
activities such as agriculture, fossil fuel use, and waste
disposal (IPCC 2001).
CH4 is removed from the atmosphere through a reaction
with the hydroxyl radical (OH) and is ultimately converted
to CO2. Minor removal processes also include reaction
with chlorine in the marine boundary layer, a soil sink, and
stratospheric reactions. Increasing emissions of CH4 reduce
the concentration of OH, a feedback that may increase the
atmospheric lifetime of CH4 (IPCC 2001).
Nitrous Oxide. Anthropogenic sources of N2O emissions
include agricultural soils, especially production of nitrogen-
fixing crops and forages, the use of synthetic and manure
fertilizers, and manure deposition by livestock; fossil fuel
combustion, especially from mobile combustion; adipic
(nylon) and nitric acid production; wastewater treatment and
waste combustion; and biomass burning. The atmospheric
concentration of N7O has increased by 18 percent since
1750, from a pre-industrial value of about 270 ppb to 319
ppb in 2004, a concentration that has not been exceeded
during the last thousand years. N2O is primarily removed
from the atmosphere by the photolytic action of sunlight in
the stratosphere (IPCC 2001).
O~one. Ozone is present in both the upper stratosphere,9
where it shields the earth from harmful levels of ultraviolet
radiation, and at lower concentrations in the troposphere,10
where it is the main component of anthropogenic
photochemical "smog." During the last two decades,
emissions of anthropogenic chlorine and bromine-containing
halocarbons, such as CFCs, have depleted stratospheric
ozone concentrations. This loss of ozone in the stratosphere
has resulted in negative radiative forcing, representing
an indirect effect of anthropogenic emissions of chlorine
and bromine compounds (IPCC 1996). The depletion of
stratospheric ozone and its radiative forcing was expected to
reach a maximum in about 2000 before starting to recover,
with detection of such recovery not expected to occur much
before 2010 (IPCC 2001).
The past increase in tropospheric ozone, which is also
a greenhouse gas, is estimated to provide the third largest
increase in direct radiative forcing since the pre-industrial
era, behind CO2 and CH4. Tropospheric ozone is produced
from complex chemical reactions of volatile organic
compounds mixing with NOX in the presence of sunlight.
The tropospheric concentrations of ozone and these other
pollutants are short-lived and, therefore, spatially variable
(IPCC 2001).
Halocarbons, Perfluorocarbons, and Sulfur Hexafluoride.
Halocarbons are, for the most part, man-made chemicals
that have both direct and indirect radiative forcing effects.
Halocarbons that contain chlorine (CFCs, HCFCs, methyl
chloroform, and carbon tetrachloride) and bromine (halons,
methyl bromide, and hydrobromofluorocarbons [HBFCs])
result in stratospheric ozone depletion and are therefore
controlled under the Montreal Protocol on Substances that
Deplete the Ozone Layer. Although CFCs and HCFCs include
potent global warming gases, their net radiative forcing
effect on the atmosphere is reduced because they cause
9 The stratosphere is the layer from the troposphere up to roughly 50 kilometers. In the lower regions the temperature is nearly constant but in the upper
layer the temperature increases rapidly because of sunlight absorption by the ozone layer. The ozone layer is the part of the stratosphere from 19 kilometers
up to 48 kilometers where the concentration of ozone reaches up to 10 parts per million.
10 The troposphere is the layer from the ground up to II kilometers near the poles and up to 16 kilometers in equatorial regions (i.e., the lowest layer of
the atmosphere where people live). It contains roughly 80 percent of the mass of all gases in the atmosphere and is the site for most weather processes,
including most of the water vapor and clouds.
1-4 Inventory of 0.8. Greenhouse Gas Emissions and Sinks; 1990- 2005
-------
stratospheric ozone depletion, which itself is an important
greenhouse gas in addition to shielding the earth from
harmful levels of ultraviolet radiation. Under the Montreal
Protocol, the United States phased out the production and
importation of halons by 1994 and of CFCs by 1996. Under
the Copenhagen Amendments to the Protocol, a cap was
placed on the production and importation of HCFCs by non-
Article 5" countries beginning in 1996, and then followed
by a complete phase-out by the year 2030. While ozone
depleting gases covered under the Montreal Protocol and
its Amendments are not covered by the UNFCCC; they are
reported in this Inventory under Annex 6.2 of this report for
informational purposes.
HFCs, PFCs, and SF6 are not ozone depleting
substances, and therefore are not covered under the Montreal
Protocol. They are, however, powerful greenhouse gases.
HFCs are primarily used as replacements for ozone depleting
substances but also emitted as a by-product of the HCFC-
22 manufacturing process. Currently, they have a small
aggregate radiative forcing impact, but it is anticipated that
their contribution to overall radiative forcing will increase
(IPCC 2001). PFCs and SF6 are predominantly emitted from
various industrial processes including aluminum smelting,
semiconductor manufacturing, electric power transmission
and distribution, and magnesium casting. Currently, the
radiative forcing impact of PFCs and SF6 is also small,
but they have a significant growth rate, extremely long
atmospheric lifetimes, and are strong absorbers of infrared
radiation, and therefore have the potential to influence
climate far into the future (IPCC 2001).
Carbon Monoxide. Carbon monoxide has an indirect
radiative forcing effect by elevating concentrations of CH4
and tropospheric ozone through chemical reactions with
other atmospheric constituents (e.g., the hydroxyl radical,
OH) that would otherwise assist in destroying CH4 and
tropospheric ozone. Carbon monoxide is created when
carbon-containing fuels are burned incompletely. Through
natural processes in the atmosphere, it is eventually oxidized
to CO2. Carbon monoxide concentrations are both short-lived
in the atmosphere and spatially variable.
Nitrogen Oxides. The primary climate change effects of
nitrogen oxides (i.e., NO and NO2) are indirect and result
from their role in promoting the formation of ozone in the
troposphere and, to a lesser degree, lower stratosphere,
where it has positive radiative forcing effects.12 Additionally,
NOX emissions from aircraft are likely to decrease CH4
concentrations, thus having a negative radiative forcing
effect (IPCC 1999). Nitrogen oxides are created from
lightning, soil microbial activity, biomass burning (both
natural and anthropogenic fires), fuel combustion, and,
in the stratosphere, from the photo-degradation of N2O.
Concentrations of NOX are both relatively short-lived in the
atmosphere and spatially variable.
Nonmethane Volatile Organic Compounds (NMVOCs).
Non-CH4 volatile organic compounds include substances such
as propane, butane, and ethane. These compounds participate,
along with NOX, in the formation of tropospheric ozone
and other photochemical oxidants. NMVOCs are emitted
primarily from transportation and industrial processes, as
well as biomass burning and non-industrial consumption of
organic solvents. Concentrations of NMVOCs tend to be both
short-lived in the atmosphere and spatially variable.
Aerosols. Aerosols are extremely small particles or liquid
droplets found in the atmosphere. They can be produced by
natural events such as dust storms and volcanic activity,
or by anthropogenic processes such as fuel combustion
and biomass burning. Aerosols affect radiative forcing
differently than greenhouse gases, and their radiative effects
occur through direct and indirect mechanisms: directly by
scattering and absorbing solar radiation; and indirectly
by increasing droplet counts that modify the formation,
precipitation efficiency, and radiative properties of clouds.
Aerosols are removed from the atmosphere relatively
rapidly by precipitation. Because aerosols generally have
short atmospheric lifetimes, and have concentrations and
compositions that vary regionally, spatially, and temporally,
their contributions to radiative forcing are difficult to quantify
(IPCC 2001).
The indirect radiative forcing from aerosols is typically
divided into two effects. The first effect involves decreased
droplet size and increased droplet concentration resulting
1' Article 5 of the Montreal Protocol covers several groups of countries, especially developing countries, with low consumption rates of ozone depleting
substances. Developing countries with per capita consumption of less than 0.3 kg of certain ozone depleting substances (weighted by their ozone depleting
potential) receive financial assistance and a grace period often additional years in the phase-out of ozone depleting substances.
'- NOX emissions injected higher in the stratosphere, primarily from fuel combustion emissions from high altitude supersonic aircraft, can lead to
stratospheric ozone depletion.
-------
from an increase in airborne aerosols. The second effect
involves an increase in the water content and lifetime
of clouds due to the effect of reduced droplet size on
precipitation efficiency (IPCC 2001). Recent research has
placed a greater focus on the second indirect radiative forcing
effect of aerosols.
Various categories of aerosols exist, including
naturally produced aerosols such as soil dust, sea salt,
biogenic aerosols, sulfates, and volcanic aerosols, and
anthropogenically manufactured aerosols such as industrial
dust and carbonaceous13 aerosols (e.g., black carbon, organic
carbon) from transportation, coal combustion, cement
manufacturing, waste incineration, and biomass burning.
The net effect of aerosols on radiative forcing is believed
to be negative (i.e., net cooling effect on the climate),
although because they remain in the atmosphere for only days
to weeks, their concentrations respond rapidly to changes in
emissions.14 Locally, the negative radiative forcing effects
of aerosols can offset the positive forcing of greenhouse
gases (IPCC 1996). "However, the aerosol effects do not
cancel the global-scale effects of the much longer-lived
greenhouse gases, and significant climate changes can still
result" (IPCC 1996).
The IPCC's Third Assessment Report notes that "the
indirect radiative effect of aerosols is now understood to also
encompass effects on ice and mixed-phase clouds, but the
magnitude of any such indirect effect is not known, although
it is likely to be positive" (IPCC 2001). Additionally, current
research suggests that another constituent of aerosols, black
carbon, may have a positive radiative forcing (Jacobson
2001). The primary anthropogenic emission sources of black
carbon include diesel exhaust and open biomass burning.
Global Warming Potentials
A global warming potential is a quantified measure of
the globally averaged relative radiative forcing impacts of
a particular greenhouse gas (see Table 1-2). It is defined as
the ratio of the time-integrated radiative forcing from the
instantaneous release of 1 kilogram (kg) of a trace substance
relative to that of 1 kg of a reference gas (IPCC 2001).
Direct radiative effects occur when the gas itself absorbs
radiation. Indirect radiative forcing occurs when chemical
transformations involving the original gas produce a gas or
gases that are greenhouse gases, or when a gas influences
other radiatively important processes such as the atmospheric
lifetimes of other gases. The reference gas used is CO2,
and therefore GWP-weighted emissions are measured in
teragrams of CO2 equivalent (Tg CO2 Eq.)15 The relationship
between gigagrams (Gg) of a gas and Tg CO2 Eq. can be
expressed as follows:
where,
ol Carbon Dioxi
(i j -- ' iigagtan^ (equivalent to a th.iuv.iiui
metric ton-.!
C'v\ P _. ! ilcbal Vv'amiifi!.' Potential
i : - k'ru-:iai i-
GWP values allow for a comparison of the impacts of
emissions and reductions of different gases. According to the
IPCC, GWPs typically have an uncertainty of ±35 percent.
The parties to the UNFCCC have also agreed to use GWPs
based upon a 100-year time horizon although other time
horizon values are available.
Greenhouse gas emissions and removals should
be presented on a gas-by-gas basis in units of
mass... In addition, consistent with decision 21
CP.3, Parties should report aggregate emissions
and removals of greenhouse gases, expressed in
CO2 equivalent terms at summary inventory level,
using GWP values provided by the IPCC in its
Second Assessment Report... based on the effects of
greenhouse gases over a 100-year time horizon.16
13 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot) (IPCC 2001).
14 Volcanic activity can inject significant quantities of aerosol-producing sulfur dioxide and other sulfur compounds into the stratosphere, which can result
in a longer negative forcing effect (i.e., a few years) (IPCC 1996).
15 Carbon comprises 12/44ths of carbon dioxide by weight.
16 Framework Convention on Climate Change; ; 1 November 2002; Report of the Conference of the Parties
at its eighth session; held at New Delhi from 23 October to 1 November 2002; Addendum; Part One: Action taken by the Conference of the Parties at
its eighth session; Decision -/CP.8; Communications from Parties included in Annex I to the Convention: Guidelines for the Preparation of National
Communications by Parties Included in Annex I to the Convention, Part 1: UNFCCC reporting guidelines on annual inventories; p. 7. (UNFCCC 2003)
6 Inventory of U.S. Greenhouse Gas; Emissions and Sinks: 1990 2005
-------
Table 1-2: Global Warming Potentials and Atmospheric
Lifetimes (Years) Used in this Report
Gas Atmospheric Lifetime
C02
CH4b
N20
HFC-23
HFC-32
HFC-125
HFC-1343
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
^FIO
CeFi4
SF6
50-200
12±3
120
264
5.6
32.6
14.6
48.3
1.5
36.5
209
17.1
50,000
10,000
2,600
3,200
3,200
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
" The GWP of CH4 includes the direct effects and those indirect effects
due to the production of tropospheric ozone and stratospheric water
vapor. The indirect effect due to the production of C02 is not included.
Greenhouse gases with relatively long atmospheric
lifetimes (e.g., CO2, CH4, N2O, HFCs, PFCs, and SF6)
tend to be evenly distributed throughout the atmosphere,
and consequently global average concentrations can be
determined. The short-lived gases such as water vapor,
carbon monoxide, tropospheric ozone, ozone precursors
(e.g., NOX and NMVOCs), and tropospheric aerosols
(e.g., SO2 products and carbonaceous particles), however,
vary regionally, and consequently it is difficult to quantify
their global radiative forcing impacts. No GWP values are
attributed to these gases that are short-lived and spatially
inhomogeneous in the atmosphere.
12 Institutional Arrangements
The U.S. Environmental Protection Agency (EPA), in
cooperation with other U.S. government agencies, prepares
the Inventory of U.S. Greenhouse Gas Emissions and Sinks.
A wide range of agencies and individuals are involved in
supplying data to, reviewing, or preparing portions of the
U.S. Inventory —including federal and state government
authorities, research and academic institutions, industry
associations, and private consultants.
Within EPA, the Office of Atmospheric Programs (GAP)
is the lead office responsible for the emission calculations
provided in the Inventory, as well as the completion of the
National Inventory Report and the Common Reporting Format
tables. The Office of Transportation and Air Quality (OTAQ)
is also involved in calculating emissions for the Inventory.
While the U.S. Department of State officially submits the
annual Inventory to the UNFCCC, EPA's GAP serves as
the focal point for technical questions and comments on the
U.S. Inventory. The staff of OAP and OTAQ coordinates the
annual methodological choice, activity data collection, and
emission calculations at the individual source category level.
Within OAP, an inventory coordinator compiles the entire
Inventory into the proper reporting format for submission
to the UNFCCC, and is responsible for the collection and
consistency of cross-cutting issues in the Inventory.
Several other government agencies contribute to the
collection and analysis of the underlying activity data
used in the Inventory calculations. Formal relationships
exist between EPA and other U.S. agencies that provide
official data for use in the Inventory. The U.S. Department
of Energy's Energy Information Administration provides
national fuel consumption data and the U.S. Department of
Defense provides military fuel consumption and bunker fuels.
Informal relationships also exist with other U.S. agencies to
provide activity data for use in EPA's emission calculations.
These include: the U.S. Department of Agriculture, the U.S.
Geological Survey, the Federal Highway Administration, the
Department of Transportation, the Bureau of Transportation
Statistics, the Department of Commerce, the National
Agricultural Statistics Service, and the Federal Aviation
Administration. Academic and research centers also provide
activity data and calculations to EPA, as well as individual
companies participating in voluntary outreach efforts with
EPA. Finally, the U .S. Department of State officially submits
the Inventory to the UNFCCC each April.
1.3. Inventory Process
EPA has a decentralized approach to preparing the
annual U.S. Inventory, which consists of a National Inventory
Report (NIR) and Common Reporting Format (CRF)
tables. The Inventory Coordinator at EPA is responsible for
compiling all emission estimates, and ensuring consistency
and quality throughout the NIR and CRF tables. Emission
Introduction 1-7
-------
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials
In 2001, the IPCC published its Third Assessment Report (TAR), which provided an updated and more comprehensive scientific
assessment of climate change. Within this report, the GWPs of several gases were revised relative to the IPCC's Second Assessment Report
(SAR), and new GWPs have been calculated for an expanded set of gases. Since the SAR, the IPCC has applied an improved calculation of
C02 radiative forcing and an improved C02 response function (presented in WMO 1999). The GWPs are drawn from WMO (1999) and the
SAR, with updates for those cases where significantly different new laboratory or radiative transfer results have been published. Additionally,
the atmospheric lifetimes of some gases have been recalculated. Because the revised radiative forcing of C02 is about 12 percent lower
than that in the SAR, the GWPs of the other gases relative to C02 tend to be larger, taking into account revisions in lifetimes. In addition, the
values for radiative forcing and lifetimes have been calculated for a variety of halocarbons, which were not presented in the SAR. Table 1-3
presents the new GWPs, relative to those presented in the SAR.
Table 1-3: Comparison of 100-Year GWPs
Gas
C02
CH4*
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^FIO
C6Fi4
SF6
SAR
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
TAR
1
23
296
12,000
550
3,400
1,300
4,300
120
3,500
9,400
1,500
5,700
11,900
8,600
9,000
22,200
Change
NC
2
(14)
300
(100)
600
NC
500
(20)
600
3,100
200
(800)
2,700
1,600
1,600
(1,700)
NC
10%
(5%)
3%
(15%)
21%
NC
13%
(14%)
21%
49%
15%
(12%)
29%
23%
22%
(7%)
Source: IPCC (2001)
NC: No Change
Note: Parentheses indicate negative values.
* The GWP of CH4 includes the direct effects and those indirect effects due
to the production of tropospheric ozone and stratospheric water vapor. The
indirect effect due to the production of C02 is not included.
To comply with international reporting standards under the UNFCCC, official emission estimates are reported by the United States using
SAR GWP values. The UNFCCC reporting guidelines for national inventories17 were updated in 2002 but continue to require the use of GWPs
from the SAR so that current estimates of aggregate greenhouse gas emissions for 1990 through 2005 are consistent and comparable with
estimates developed prior to the publication of the TAR. For informational purposes, emission estimates that use the updated GWPs are
presented in Annex 6.1 of this report. All estimates provided throughout this report are also presented in unweighted units.
calculations for individual sources are the responsibility expertise in the source category, as well as coordinating
of individual source leads, who are most familiar with with researchers and contractors familiar with the sources.
each source category and the unique characteristics of its A multi-stage process for collecting information from the
emissions profile. The individual source leads determine the individual source leads and producing the Inventory is
most appropriate methodology and collect the best activity undertaken annually to compile all information and data.
data to use in the emission calculations, based upon their
17 See .
:-8 inventory of U.S. tktemiosrie fias f/^sstMS am: Sniks: 199C-2Q!,i5
-------
Methodology Development, Data
Collection, and Emissions and Sink
Estimation
Source leads at EPA collect input data and, as necessary,
evaluate or develop the estimation methodology for the
individual source categories. For most source categories,
the methodology for the previous year is applied to the
new "current" year of the Inventory, and inventory analysts
collect any new data or update data that have changed from
the previous year. If estimates for a new source category are
being developed for the first time, or if the methodology is
changing for an existing source category (e.g., the United
States is implementing a higher Tiered approach for that
source category), then the source category lead will develop
a new methodology, gather the most appropriate activity
data and emission factors (or in some cases direct emission
measurements) for the entire time series, and conduct a
special source-specific peer review process involving relevant
experts from industry, government, and universities.
Once the methodology is in place and the data are
collected, the individual source leads calculate emissions and
sink estimates. The source leads then update or create the
relevant text and accompanying annexes for the Inventory.
Source leads are also responsible for completing the relevant
sectoral background tables of the Common Reporting
Format, conducting quality assurance and quality control
(QA/QC) checks, and uncertainty analyses.
Comilation and
-ummar pn-d
The Inventory Coordinator at EPA collects the source
categories' descriptive text and Annexes, and also aggregates
the emission estimates into a summary spreadsheet that
links the individual source category spreadsheets together.
This summary sheet contains all of the essential data in
one central location, in formats commonly used in the
Inventory document. In addition to the data from each source
category, national trend and related data are also gathered
in the summary sheet for use in the Executive Summary,
Introduction, and Recent Trends sections of the Inventory
report. Electronic copies of each year's summary spreadsheet,
which contains all the emission and sink estimates for the
United States, are kept on a central server at EPA under the
jurisdiction of the Inventory Coordinator.
Mationa! inventory Report Preparation
The NIR is compiled from the sections developed
by each individual source lead. In addition, the Inventory
Coordinator prepares a brief overview of each chapter that
summarizes the emissions from all sources discussed in the
chapters. The Inventory Coordinator then carries out a key
category analysis for the Inventory, consistent with the IPCC
Good Practice Guidance, IPCC Good Practice Guidance for
Land Use, Land Use Change and Forestry, and in accordance
with the reporting requirements of the UNFCCC. Also at
this time, the Introduction, Executive Summary, and Recent
Trends sections are drafted, to reflect the trends for the most
recent year of the current Inventory. The analysis of trends
necessitates gathering supplemental data, including weather
and temperature conditions, economic activity and gross
domestic product, population, atmospheric conditions, and
the annual consumption of electricity, energy, and fossil
fuels. Changes in these data are used to explain the trends
observed in greenhouse gas emissions in the United States.
Furthermore, specific factors that affect individual sectors
are researched and discussed. Many of the factors that affect
emissions are included in the Inventory document as separate
analyses or side discussions in boxes within the text. Text
boxes are also created to examine the data aggregated in
different ways than in the remainder of the document, such
as a focus on transportation activities or emissions from
electricity generation. The document is prepared to match
the specification of the UNFCCC reporting guidelines for
National Inventory Reports.
Common Reporting Formal Table
Compilation
The CRF tables are compiled from individual tables
completed by each individual source lead, which contain
source emissions and activity data. The Inventory Coordinator
integrates the source data into the UNFCCC's "CRF Reporter"
for the United States, assuring consistency across all sectoral
tables. The summary reports for emissions, methods, and
emission factors used, the overview tables for completeness
and quality of estimates, the recalculation tables, the notation
key completion tables, and the emission trends tables are then
completed by the Inventory Coordinator. Internal automated
quality checks on the CRF Reporter, as well as reviews by
the source leads, are completed for the entire time series of
CRF tables before submission.
introduction !-9
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QA/QC and Uncertainty
QA/QC and uncertainty analyses are supervised by
the QA/QC coordinator, who has general oversight over
the implementation of the QA/QC plan and the overall
uncertainty analysis for the Inventory (see sections on
QA/QC and Uncertainty, below). The QA/QC coordinator
works closely with the source leads to ensure a consistent
QA/QC plan and uncertainty analysis is implemented across
all inventory sources. The inventory QA/QC plan, detailed in
a following section, is consistent with the quality assurance
procedures outlined by EPA.
Expert and Public Review Periods
During the Expert Review period, a first draft of the
document is sent to a select list of technical experts outside
of EPA. The purpose of the Expert Review is to encourage
feedback on the methodological and data sources used in
the current Inventory, especially for sources which have
experienced any changes since the previous Inventory.
Once comments are received and addressed, a second
draft of the document is released for public review by
publishing a notice in the U.S. Federal Register and posting
the document on the EPA Web site. The Public Review
period allows for a 30 day comment period and is open to
the entire U.S. public.
Final Submittal to UNFCCC and Document
Printing
After the final revisions to incorporate any comments
from the Expert Review and Public Review periods,
EPA prepares the final National Inventory Report and
the accompanying Common Reporting Format Reporter
database. The U.S. Department of State sends the official
submission of the U.S. Inventory to the UNFCCC. The
Box 1-2: IPCC Reference Approach
document is then formatted for printing, posted online,
printed by the U.S. Government Printing Office, and made
available for the public.
1.4. Methodology and Data Sources
Emissions of greenhouse gases from various source and
sink categories have been estimated using methodologies
that are consistent with the Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997). In addition, the United States references
the additional guidance provided in the IPCC Good Practice
Guidance and Uncertainty Management in National
Greenhouse Gas Inventories (IPCC 2000), the IPCC Good
Practice Guidance for Land Use, Land-Use Change, and
Forestry (IPCC 2003), and the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC 2006). To the
extent possible, the present report relies on published activity
and emission factor data. Depending on the emission source
category, activity data can include fuel consumption or
deliveries, vehicle-miles traveled, raw material processed,
etc. Emission factors are factors that relate quantities of
emissions to an activity.
The IPCC methodologies provided in the Revised
1996 IPCC Guidelines represent baseline methodologies
for a variety of source categories, and many of these
methodologies continue to be improved and refined as new
research and data become available. This report uses the
IPCC methodologies when applicable, and supplements them
with other available methodologies and data where possible.
Choices made regarding the methodologies and data sources
used are provided in conjunction with the discussion of each
source category in the main body of the report. Complete
documentation is provided in the annexes on the detailed
methodologies and data sources utilized in the calculation
of each source category.
The UNFCCC reporting guidelines require countries to complete a "top-down" reference approach for estimating C02 emissions from
fossil fuel combustion in addition to their "bottom-up" sectoral methodology. This estimation method uses alternative methodologies and
different data sources than those contained in that section of the Energy chapter. The reference approach estimates fossil fuel consumption
by adjusting national aggregate fuel production data for imports, exports, and stock changes rather than relying on end-user consumption
surveys (see Annex 4 of this report). The reference approach assumes that once carbon-based fuels are brought into a national economy,
they are either saved in some way (e.g., stored in products, kept in fuel stocks, or left unoxidized in ash) or combusted, and therefore the
carbon in them is oxidized and released into the atmosphere. Accounting for actual consumption of fuels at the sectoral or sub-national
level is not required.
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1900-2005
-------
1.5. Key Categories
The IPCC's Good Practice Guidance (IPCC 2000)
defines a key category as a "[source or sink category] that
is prioritized within the national inventory system because
its estimate has a significant influence on a country's total
inventory of direct greenhouse gases in terms of the absolute
level of emissions, the trend in emissions, or both."18 By
definition, key categories include those sources that have
the greatest contribution to the absolute level of national
emissions. In addition, when an entire time series of emission
estimates is prepared, a thorough investigation of key
categories must also account for the influence of trends of
individual source and sink categories. This analysis culls out
source and sink categories that diverge from the overall trend
in national emissions. Finally, a qualitative evaluation of key
categories is performed to capture any categories that were
not identified in either of the quantitative analyses.
A Tier 1 approach, as defined in the IPCC's Good
Practice Guidance (IPCC 2000), was implemented to
identify the key categories for the United States. This analysis
was performed twice; one analysis included sources and
sinks from the Land Use, Land-Use Change, and Forestry
(LULUCF) sector, the other analysis did not include the
LULUCF categories.
In addition to conducting Tier 1 level and trend
assessments, a qualitative assessment of the source
categories, as described in the IPCC's Good Practice
Guidance (IPCC 2000), was conducted to capture any key
categories that were not identified by either quantitative
method. One additional key category, international bunker
fuels, was identified using this qualitative assessment.
International bunker fuels are fuels consumed for aviation or
marine international transport activities, and emissions from
these fuels are reported separately from totals in accordance
with IPCC guidelines. If these emissions were included in
the totals, bunker fuels would qualify as a key category
according to the Tier 1 approach. The amount of uncertainty
associated with estimation of emissions from international
bunker fuels also supports the qualification of this source
category as key.
Table 1-4 presents the key categories for the United
States based on the Tier 1 approach (including and
excluding LULUCF categories) using emissions data in
this report, and ranked according to their sector and GWP-
weighted emissions in 2005. The table also indicates the
criteria used in identifying these categories (i.e., level,
trend, and/or qualitative assessments). Annex 1 of this
report provides additional information regarding the key
categories in the United States and the methodologies used
to identify them.
1.6. Quality Assurance and Quality
Control (QA/QC)
As part of efforts to achieve its stated goals for inventory
quality, transparency, and credibility, the United States has
developed a quality assurance and quality control plan
designed to check, document and improve the quality of
its Inventory over time. QA/QC activities on the Inventory
are undertaken within the framework of the U.S. QA/QC
plan, Quality Assurance/Quality Control and Uncertainty
Management Plan for the U.S. Greenhouse Gas Inventory:
Procedures Manual for QA/QC and Uncertainty Analysis.
In particular, key attributes of the QA/QC plan
include:
• specific detailed procedures (or protocols) and templates
(or forms) that serve to standardize the process of
documenting and archiving information, as well as to
guide the implementation of QA/QC and the analysis
of the uncertainty of the inventory estimates;
• expert review as well as QC—for both the inventory
estimates and the Inventory (which is the primary
vehicle for disseminating the results of the inventory
development process). In addition, the plan provides
for public review of the Inventory;
• both Tier 1 (general) and Tier 2 (source-specific) quality
controls and checks, as recommended by IPCC Good
Practice Guidance',
• consideration of secondary data quality and source-
specific quality checks (Tier 2 QC) in parallel and
coordination with the uncertainty assessment; the
18 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
introduction 1 11
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Table 1-4: Key Categories for the United States (1990-2005) Based on Tier 1 Approach
IPCC Source Categories
Energy
C02 Emissions from Stationary Combustion — Coal
C02 Emissions from Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion— Gas
C02 Emissions from Stationary Combustion— Oil
C02 Emissions from Mobile Combustion: Aviation
C02 Emissions from Non-Energy Use of Fuels
Fugitive CH4 Emissions from Natural Gas Systems
International Bunker Fuels"
C02 Emissions from Mobile Combustion: Marine
Fugitive CH4 Emissions from Coal Mining
Fugitive CH4 Emissions from Petroleum Systems
C02 Emissions from Natural Gas Systems
C02 Emissions from Municipal Solid Waste Combustion
N20 Emissions from Mobile Combustion: Road & Other
Industrial Processes
Emissions from Substitutes for Ozone Depleting
Substances
C02 Emissions from Cement Production
C02 Emissions from Iron and Steel Production
HFC-23 Emissions from HCFC-22 Production
C02 Emissions from Ammonia Manufacture and
Urea Application
SF6 Emissions from Electrical Transmission and
Distribution
N20 Emissions from Adipic Acid Production
PFC Emissions from Aluminum Production
Agriculture
Direct N20 Emissions from Agricultural Soils
CH4 Emissions from Enteric Fermentation in
Domestic Livestock
Indirect N20 Emissions from Nitrogen Used in Agriculture
CH4 Emissions from Manure Management
Waste
CH4 Emissions from Landfills
Land Use, Land-Use Change, and Forestry
C02 Emissions from Forest Land Remaining Forest Land
C02 Emissions from Settlements Remaining Settlements
C02 Emissions from Cropland Remaining Cropland
C02 Emissions from Grassland Remaining Grassland
C02 Emissions from Landfilled Yard Trimmings
and Food Scraps
Subtotal Without LULUCF
Total Emissions Without LULUCF
Percent of Total Without LULUCF
Subtotal With LULUCF
Total Emissions With LULUCF
Percent of Total With LULUCF
Gas
C02
C02
C02
C02
C02
C02
CH4
Several
C02
CH4
CH4
C02
C02
N20
Several
C02
C02
HFCs
C02
SF6
N20
PFCs
N20
CH4
N20
CH4
CH4
C02
C02
C02
C02
C02
Level Trend Level Trend 2005
Without Without With With Emissions
LULUCF LULUCF LULUCF LULUCF dual3 (TgC02Eq.)
/ / / / 2,093.6
/ / / / 1,642.9
/ / 1,138.2
/ / / / 626.3
/ / / / 186.1
/ / / 142.4
/ / / / 111.1
/ 98.2
/ / / / 63.7
/ / / / 52.4
/ / / / 28.5
/ / / / 28.2
/ / 20.9
/ / / / 13.8
/ / / / 123.3
/ / / / 45.9
/ / / / 45.2
/ / / / 16.5
/ / 16.3
/ / 13.2
/ / 6.0
/ / 3.0
/ / / / 310.5
/ / / / 112.1
/ / / / 54.6
/ 9.5
/ / / / 132.0
/ (698.7)
/ / (88.5)
/ / (39.4)
/ 16.1
/ (8.8)
7,036.4
7,241.5
97.2%
6,217.0
6,431.9
96.7%
a Qualitative criteria.
b Emissions from this source not included in totals.
Note: Parentheses indicate negative values or sequestration. The Tier 1 approach for identifying key source categories does not directly include assessment
of uncertainty in emissions estimates.
1-12 Inventory of U.S. Greenhouse Ga?, emissions and Sinks: 19SD-2005
-------
development of protocols and templates provides for
more structured communication and integration with
the suppliers of secondary information;
• record-keeping provisions to track which procedures
have been followed, and the results of the QA/QC
and uncertainty analysis, and contains feedback
mechanisms for corrective action based on the results
of the investigations, thereby providing for continual
data quality improvement and guided research efforts;
• implementation of QA/QC procedures throughout the
whole inventory development process —from initial
data collection, through preparation of the emission
estimates, to publication of the Inventory;
• a schedule for multi-year implementation; and
• promotion of coordination and interaction within the
EPA, across Federal agencies and departments, state
government programs, and research institutions and
consulting firms involved in supplying data or preparing
estimates for the Inventory. The QA/QC plan itself is
intended to be revised and reflect new information that
becomes available as the program develops, methods are
improved, or additional supporting documents become
necessary.
In addition, based on the national QA/QC plan for
the Inventory, source-specific QA/QC plans have been
developed for a number of sources. These plans follow the
procedures outlined in the national QA/QC plan, tailoring
the procedures to the specific text and spreadsheets of the
individual sources. For the current Inventory, source-specific
plans have been developed and implemented for the majority
of sources within the Energy and Industrial Process sectors.
Throughout this Inventory, a minimum of a Tier 1 QA/QC
analysis has been undertaken. Where QA/QC activities for
a particular source go beyond the minimum Tier 1 level,
further explanation is provided within the respective source
category text.
The quality checking and control activities described
in the U.S. QA/QC plan occur throughout the inventory
process; QA/QC is not separate from, but is an integral part
of, preparing the Inventory. Quality control—in the form
of both good practices (such as documentation procedures)
and checks on whether good practices and procedures are
being followed —is applied at every stage of inventory
development and document preparation. In addition,
quality assurance occurs at two stages —an expert review
and a public review. While both phases can significantly
contribute to inventory quality, the public review phase is
also essential for promoting the openness of the inventory
development process and the transparency of the inventory
data and methods.
QA/QC procedures guide the process of ensuring
inventory quality by describing data and methodology
checks, developing processes governing peer review and
public comments, and developing guidance on conducting
an analysis of the uncertainty surrounding the emission
estimates. The QA/QC procedures also include feedback
loops and provide for corrective actions that are designed
to improve the inventory estimates over time.
1.7. Uncertainty Analysis of
Emission Estimates
Uncertainty estimates are an essential element of a
complete and transparent emissions Inventory. Uncertainty
information is not intended to dispute the validity of
the inventory estimates, but to help prioritize efforts to
improve the accuracy of future inventories and guide
future decisions on methodological choice. While the U.S.
Inventory calculates its emission estimates with the highest
possible accuracy, uncertainties are associated to a varying
degree with the development of emission estimates for any
inventory. Some of the current estimates, such as those for
CO2 emissions from energy-related activities and cement
processing, are considered to have minimal uncertainty
associated with them. For some other categories of emissions,
however, a lack of data or an incomplete understanding
of how emissions are generated increases the uncertainty
surrounding the estimates presented. Despite these
uncertainties, the UNFCCC reporting guidelines follow the
recommendation in the 1996IPCC Guidelines (IPCC/UNEP/
OECD/IEA 1997) and require that countries provide single
point estimates of uncertainty for each gas and emission
or removal source category. Within the discussion of each
emission source, specific factors affecting the uncertainty
associated with the estimates are discussed.
Introduction 1-13
-------
Additional research in the following areas could help
reduce uncertainty in the U.S. Inventory:
• Incorporating excluded emission sources. Quantitative
estimates for some of the sources and sinks of greenhouse
gas emissions are not available at this time. In particular,
emissions from some land-use activities and industrial
processes are not included in the Inventory either
because data are incomplete or because methodologies
do not exist for estimating emissions from these source
categories. See Annex 5 of this report for a discussion
of the sources of greenhouse gas emissions and sinks
excluded from this report.
• Improving the accuracy of emission factors. Further
research is needed in some cases to improve the accuracy
of emission factors used to calculate emissions from a
variety of sources. For example, the accuracy of current
emission factors applied to CH4 and N2O emissions from
stationary and mobile combustion is highly uncertain.
• Collecting detailed activity data. Although methodologies
exist for estimating emissions for some sources,
problems arise in obtaining activity data at a level
of detail in which aggregate emission factors can be
applied. For example, the ability to estimate emissions
of SF6 from electrical transmission and distribution is
limited due to a lack of activity data regarding national
SF6 consumption or average equipment leak rates.
The overall uncertainty estimate for the U.S. Greenhouse
Gas Emissions Inventory was developed using the IPCC
Tier 2 uncertainty estimation methodology. A preliminary
estimate of the overall quantitative uncertainty is shown
below, in Table 1-5.
TSie IPCC provides good practice guidance on two
approaches—Tier 1 and Tier 2—to estimating uncertainty
for individual source categories. Tier 2 uncertainty analysis,
employing the Monte Carlo Stochastic Simulation technique,
was applied wherever data and resources permitted; further
explanation is provided within the respective source category
text. Consistent with the IPCC good practice guidance,
over a multi-year timeframe, the United States expects to
continue to improve the uncertainty estimates presented in
this report.
Emissions calculated for the U.S. Inventory reflect
current best estimates; in some cases, however, estimates
are based on approximate methodologies, assumptions, and
incomplete data. As new information becomes available
in the future, the United States will continue to improve
and revise its emission estimates. See Annex 7 of this
report for further details on the U.S. process for estimating
uncertainties associated with emission estimates and for a
more detailed discussion of the limitations of the current
analysis and plans for improvement. Annex 7 also includes
details on the uncertainty analysis performed for selected
source categories.
Table 1-5: Estimated Overall Inventory Quantitative Uncertainty (Tg C02 Eq. and Percent)
2005 Emission
Estimate
Gas (Tg C02 Eq.)
C02
CH4
N20
RFC, HFC & SF6d
Total
Net Emissions
(Sources and Sinks)
6,089.5
539.3
468.6
163.0
7,260.4
6,431.9
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound0
5,992.1
487.5
392.7
152.8
7,170.3
6,256.1
Upper Bound0
6,397.2
623.6
578.8
188.6
7,634.0
6,862.4
Lower Bound0
-2%
-10%
-16%
-6%
-1%
-3%
Upper Bound0
5%
16%
24%
16%
5%
7%
Standard
Meanb Deviation
(Tg C02 Eq.)
6,193.5
554.0
486.0
170.2
7,403.7
6,559.9
106.0
34.6
47.5
9.3
120.9
155.5
a Range of emission estimates for a 95 percent confidence interval.
b Mean value indicates the arithmetic average of the simulated emission estimates; standard deviation indicates the extent of deviation of the simulated
values from the mean.
c The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high emission estimates for the
sub-source categories do not sum to total emissions.
d The overall uncertainty estimate did not take into account the uncertainty in the GWP values for CH4, N20 and high GWP gases used in the inventory
emission calculations for 2005.
1-14 Inventory of U.S. Greer house Gas Emissions and Sinks: 199 3-2005
-------
1.8. Completeness
This report, along with its accompanying CRF reporter,
serves as a thorough assessment of the anthropogenic sources
and sinks of greenhouse gas emissions for the United States
for the time series 1990 through 2005. Although this report
is intended to be comprehensive, certain sources have been
identified yet excluded from the estimates presented for
various reasons. Generally speaking, sources not accounted
for in this Inventory are excluded due to data limitations or a
lack of thorough understanding of the emission process. The
United States is continually working to improve upon the
understanding of such sources and seeking to find the data
required to estimate related emissions. As such improvements
are made, new emission sources are quantified and included
in the Inventory. For a complete list of sources excluded, see
Annex 5 of this report.
1.9. Organization of Report
In accordance with the Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997), and the 2003 UNFCCC Guidelines on
Reporting and Review (UNFCCC 2003), this Inventory of
U.S. Greenhouse Gas Emissions and Sinks is segregated
into six sector-specific chapters, listed below in Table 1 -6. In
addition, chapters on Trends in Greenhouse Gas Emissions
and Other information to be considered as part of the U.S.
Inventory submission are included.
Within each chapter, emissions are identified by the
anthropogenic activity that is the source or sink of the
greenhouse gas emissions being estimated (e .g., coal mining).
Overall, the following organizational structure is consistently
applied throughout this report:
Chapter/IPCC Sector Overview of emission trends for each
IPCC defined sector
Source category: Description of source pathway and
emission trends.
Methodology: Description of analytical methods
employed to produce emission estimates and
identification of data references, primarily for
activity data and emission factors.
Uncertainty: A discussion and quantification of the
uncertainty in emission estimates and a discussion
of time-series consistency.
QA/QC and Verification: A discussion on steps taken
to QA/QC and verify the emission estimates, where
beyond the overall U.S. QA/QC plan, and any key
findings.
Recalculations: A discussion of any data
or methodological changes that necessitated a
recalculation of previous years' emission estimates,
and the impact of the recalculation on the emission
estimates, if applicable.
Planned Improvements: A discussion on any source-
specific planned improvements, if applicable.
Special attention is given to CO2 from fossil fuel
combustion relative to other sources because of its share of
emissions and its dominant influence on emission trends.
Table 1-6: IPCC Sector Descriptions
Chapter/IPCC Sector
Activities Included
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and Forestry
Waste
Emissions of all greenhouse gases resulting from stationary and mobile energy activities
including fuel combustion and fugitive fuel emissions.
By-product or fugitive emissions of greenhouse gases from industrial processes not
directly related to energy activities such as fossil fuel combustion.
Emissions, of primarily NMVOCs, resulting from the use of solvents and N20 from
product usage.
Anthropogenic emissions from agricultural activities except fuel combustion, which is
addressed under Energy.
Emissions and removals of C02, CH4, and N20 from forest management, other land-use
activities, and land-use change.
Emissions from waste management activities.
Source: IPCC/UNEP/OECD/IEA (1997)
Introduction 1-15
-------
For example, each energy-consuming end-use sector (i.e.,
residential, commercial, industrial, and transportation),
as well as the electricity generation sector, is described
individually. Additional information for certain source
categories and other topics is also provided in several
Annexes listed in Table 1-7.
Table 1-7: List of Annexes
ANNEX 1 Key Category Analysis
ANNEX 2 Methodology and Data for Estimating C02 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of C02 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3 Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Stationary Combustion
3.2. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Mobile Combustion and
Methodology for and Supplemental Information on Transportation-Related Greenhouse Gas Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 Emissions from Petroleum Systems
3.6. Methodology for Estimating C02 and N20 Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.8. Methodology for Estimating HFC and RFC Emissions from Substitution of Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
3.10. Methodology for Estimating CH4 and N20 Emissions from Manure Management
3.11. Methodology for Estimating N20 Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on Croplands
and Grasslands
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4 IPCC Reference Approach for Estimating C02 Emissions from Fossil Fuel Combustion
ANNEX 5 Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded
ANNEX 6 Additional Information
6.1. Global Warming Potential Values
6.2. Ozone Depleting Substance Emissions
6.3. Sulfur Dioxide Emissions
6.4. Complete List of Source Categories
6.5. Constants, Units, and Conversions
6.6. Abbreviations
6.7. Chemical Formulas
ANNEX 7 Uncertainty
7.1. Overview
7.2. Methodology and Results
7.3. Planned Improvements
7.4. Additional Information on Uncertainty Analysis by Source
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2(305
-------
2. Trends in Greenhouse Gas
Emissions
2,1. Recent Trends in U.S. Greenhouse Gas Emissions
In 2005, total U.S. greenhouse gas emissions were 7,260.4 teragrams of carbon dioxide equivalents (Tg CO2 Eq.).1
Overall, total U.S. emissions have risen by 16.3 percent from 1990 to 2005, while the U.S. gross domestic product
has increased by 55 percent over the same period (BEA 2006). Emissions rose from 2004 to 2005, increasing by 0.8
percent (56.7 Tg CO2 Eq.). The following factors were primary contributors to this increase: (1) strong economic growth in
2005, leading to increased demand for electricity and (2) an increase in the demand for electricity due to warmer summer
conditions. These factors were moderated by decreasing demand for fuels due to warmer winter conditions and higher
fuel prices. Figure 2-1 through Figure 2-3 illustrate the overall trends in total U.S. emissions by gas,2 annual changes, and
absolute changes since 1990.
As the largest source of U.S. greenhouse gas emissions, carbon dioxide (CO2) from fossil fuel combustion has accounted
for approximately 77 percent of global warming potential (GWP) weighted emissions since 1990, growing slowly from
76 percent of total GWP-weighted emissions in 1990 to 79 percent in 2005. Emissions from this source category grew by
21.7 percent (1,027.1 Tg CO2 Eq.) from 1990 to 2005 and were responsible for most of the increase in national emissions
Figure 2-1
U.S. Greenhouse Gas Emissions by Gas
8,000 -|
7,000
6,000
^ 5,000 -
. 4,000
3,000 -
2,000
1,000
0
MFCs, PFCs, & SF,
Nitrous Oxide
Methane
Carbon Dioxide
during this period. From 2004 to 2005, these emissions
increased by 0.7 percent (38.2 Tg CO2 Eq.), slightly less
than the source's average annual growth rate of 1.4 percent
from 1990 through 2005. Historically, changes in emissions
from fossil fuel combustion have been the dominant factor
affecting U.S. emission trends.
Changes in CO2 emissions from fossil fuel combustion
are influenced by many long-term and short-term factors,
including population and economic growth, energy
price fluctuations, technological changes, and seasonal
temperatures. On an annual basis, the overall consumption
of fossil fuels in the United States generally fluctuates in
response to changes in general economic conditions, energy
prices, weather, and the availability of non-fossil alternatives.
1 Estimates are presented in units of teragrams of carbon dioxide equivalent (Tg CO2 Eq.), which weight each gas by its global warming potential, or
GWP, value. (See section on global warming potentials. Chapter 1.)
2 See the following section for an analysis of emission trends by general economic sector.
Trends in Greenhouse Gas Emissions 2-1
-------
Figure 2-2
Annual Percent Change in U.S. Greenhouse Gas Emissions
Figure 2-3
5% -
4% -
3% -
2% -
1% -
o%
-1% -
-2% -
IliiLi
0)aioooo
1— 1— C\J C\J C\4 CM
For example, in a year with increased consumption of
goods and services, low fuel prices, severe summer and
winter weather conditions, nuclear plant closures, and lower
precipitation feeding hydroelectric dams, there would likely
be proportionally greater fossil fuel consumption than in
a year with poor economic performance, high fuel prices,
mild temperatures, and increased output from nuclear and
hydroelectric plants.
In the longer-term, energy consumption patterns
respond to changes that affect the scale of consumption (e.g.,
population, number of cars, and size of houses), the efficiency
with which energy is used in equipment (e.g., cars, power
plants, steel mills, and light bulbs) and consumer behavior
(e.g., walking, bicycling, or telecommuting to work instead
of driving).
Energy-related CO2 emissions also depend on the type
of fuel or energy consumed and its carbon (C) intensity.
Producing a unit of heat or electricity using natural gas
Cumulative Change in U.S. Greenhouse Gas
Emissions Relative to 1990
1,100 -|
900
^700
LU
" 500 -
?
300
100 -
0
-100
905
962
1,018
678 688
-56
g 5 S S § S
o o o o o o
CM CM CM CM CM CM
instead of coal, for example, can reduce the CO2 emissions
because of the lower C content of natural gas. Table 2-1
shows annual changes in emissions during the last five years
for coal, petroleum, and natural gas in selected sectors.
After emissions significantly decreased in 2001 due to
the economic slowdown, emissions from fuel combustion
resumed modest growth in 2002, slightly less than the
average annual growth rate since 1990. There were a
number of reasons behind this increase. The U.S. economy
experienced moderate growth, recovering from weak
economic conditions in 2001. Prices for fuels remained at or
below 2001 levels; the cost of natural gas, motor gasoline,
and electricity were all lower—triggering an increase in
demand for fuel. In addition, the United States experienced
one of the hottest summers on record, causing a significant
increase in electricity use in the residential sector as the
use of air-conditioners increased. Partially offsetting this
increased consumption of fossil fuels, however, were
Table 2-1: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors
(Tg C02 Eq. and Percent)
Sector
Electricity Generation
Electricity Generation
Electricity Generation
Transportation3
Residential
Commercial
Industrial
Industrial
All Sectors"
Fuel Type
Coal
Natural Gas
Petroleum
Petroleum
Natural Gas
Natural Gas
Coal
Natural Gas
All Fuels"
2001 to 2002
16.0
16.1
-22.9
51.8
6.4
6.6
-10.1
9.4
45.5
0.9%
5.5%
-22.5%
3.0%
2.5%
4.0%
-7.6%
2.2%
0.8%
2002 to 2003
38.0
-27.7
19.0
2.0
11.5
2.6
0.6
-14.5
67.3
2.0%
-9.0%
24.0%
0.1%
4.3%
1.5%
0.5%
-3.3%
1.2%
2003 to 2004
11.4
18.4
2.0
55.1
-12.2
-3.1
2.3
0.6
88.5
0.6%
6.6%
2.0%
3.1%
-4.4%
-1.8%
1.8%
0.1%
1.6%
2004 to 2005
40.8
22.4
2.2
28.8
-3.4
-4.2
-4.0
-34.8
38.2
2.1%
7.5%
2.2%
1 .6%
-1.3%
-2.5%
-3.2%
-8.2%
0.7%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table (see Table 3-3 for complete list of fuels by sector).
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1890 2005
-------
increases in the use of nuclear and renewable fuels. Nuclear
facilities operated at the highest capacity on record in 2002.
Furthermore, there was a considerable increase in the use
of hydroelectric power in 2002 after a very low output the
previous year.
Emissions from fuel combustion continued growing in
2003, at about the average annual growth rate since 1990. A
number of factors played a major role in the magnitude of this
increase. The U.S. economy experienced moderate growth
from 2002, causing an increase in the demand for fuels. The
price of natural gas escalated dramatically, causing some
electric power producers to switch to coal, which remained
at relatively stable prices. Colder winter conditions brought
on more demand for heating fuels, primarily in the residential
sector. Though a cooler summer partially offset demand for
electricity as the use of air-conditioners decreased, electricity
consumption continued to increase in 2003. The primary
drivers behind this trend were the growing economy and the
increase in U.S. housing stock. Nuclear capacity decreased
slightly, for the first time since 1997. Use of renewable fuels
rose slightly due to increases in the use of hydroelectric
power and biofuels.
From 2003 to 2004, these emissions increased at a rate
slightly higher than the average growth rate since 1990. A
number of factors played a major role in the magnitude of
this increase. A primary reason behind this trend was strong
growth in the U.S. economy and industrial production,
particularly in energy-intensive industries, causing an
increase in the demand for electricity and fossil fuels.
Demand for travel was also higher, causing an increase
in petroleum consumed for transportation. In contrast,
the warmer winter conditions led to decreases in demand
for heating fuels, principally natural gas, in both the
residential and commercial sectors. Moreover, much of the
increased electricity demanded was generated by natural
gas combustion and nuclear power, which moderated the
increase in CO2 emissions from electricity generation. Use
of renewable fuels rose very slightly due to increases in the
use of biofuels.
Emissions from fuel combustion increased from 2004 to
2005 at a rate slightly lower than the average annual growth
rate since 1990. A number of factors played a role in this
slight increase. This small increase is primarily a result of the
restraint on fuel consumption, primarily in the transportation
sector, caused by rising fuel prices. Although electricity
prices increased slightly, there was a significant increase in
electricity consumption in the residential and commercial
sectors due to warmer summer weather conditions. This led
to an increase in emissions in these sectors with the increased
use of air-conditioners. As electricity emissions increased
among all end-use sectors, the fuels used to generate
electricity increased as well. Despite a slight decrease in
industrial energy-related emissions, industrial production
and manufacturing output actually increased. The price of
natural gas escalated dramatically, causing a decrease in
consumption of natural gas in the industrial sector. Use of
renewable fuels decreased slightly due to decreased use of
biofuels and decreased electricity output by hydroelectric
power plants.
Other significant trends in emissions from additional
source categories over the fifteen-year period from 1990
through 2005 included the following:
• CO2 emissions from waste combustion increased by 10.0
Tg CO2 Eq. (91 percent), as the volume of plastics and
other fossil-carbon-containing materials in municipal
solid waste grew.
• Net CO2 sequestration from Land Use, Land-Use
Change, and Forestry increased by 115.7 Tg CO2 Eq.
(16 percent) from 1990 through 2005. This increase
was primarily due to an increase in the rate of net
C accumulation in forest C stocks, particularly in
aboveground and belowground tree biomass. Annual
C accumulation in landfilled yard trimmings and food
scraps slowed over this period, while the rate of C
accumulation in urban trees increased.
• Methane (CH4) emissions from coal mining declined by
29.5 Tg CO2 Eq. (36 percent) from 1990 to 2005 as a
result of the mining of less gassy coal from underground
mines and the increased combustion of CH4 collected
from degasification systems.
• From 1990 to 2005, nitrous oxide (N2O) emissions
from mobile combustion decreased by 13.1 percent.
However, from 1990 to 1998 emissions increased by 26
percent, due to control technologies that reduced CH4
emissions while increasing N9O emissions. Since 1998,
new control technologies have led to a steady decline in
N2O from this source.
• Emissions resulting from the substitution of ozone
depleting substances (ODS, e.g., chlorofluorocarbons
Trends in Greenhouse Gas Emissions 2-3
-------
Box 2-1: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include: (1)
emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions; (2) emissions
per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels; (3) emissions per
unit of electricity consumption, because the electric power industry—utilities and nonutilities combined—was the largest source of U.S.
greenhouse gas emissions in 2005; (4) emissions per unit of total gross domestic product as a measure of national economic activity; or
(5) emissions per capita.
Table 2-2 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse
gas emissions in the United States have grown at an average annual rate of 1.1 percent since 1990. This rate is slightly slower than that for
total energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total
U.S. greenhouse gas emissions have also grown slightly slower than national population since 1990 (see Figure 2-4).
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100)
Variable
GDP"
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Population11
Greenhouse Gas Emissions6
1990
100
100
100
100
100
100
1995
113
112
107
108
107
105
2000
138
127
117
117
113
115
2001
139
125
115
114
114
113
2002
141
128
116
116
115
113
2003
145
129
118
117
116
114
2004
150
131
119
119
117
115
2005
155
134
119
118
118
116
Growth
Rate3
3.0%
2.0%
1.2%
1.1%
1.1%
1.0%
a Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2006)
c Energy-content-weighted values (EIA 2006b)
d U.S. Census Bureau (2006)
e GWP-weighted values
Figure 2-4
U.S. Greenhouse Gas Emissions Per Capita and
Per Dollar of Gross Domestic Product
160
150
_14D
= 130
o 120
I 110
f 100
I 90-
80
70
ST— OjeO^-lft
cncnoicncn
oo
oo
Real GDP
Population
Emissions
per capita
~" Emissions
per$GDP
oooo
Source: BEA (2006), U.S. Census Bureau (2006), and emission estimates in tlie this report.
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks 1990 2005
-------
[CFCs]) have increased dramatically, from small
amounts in 1990 to 123.3 Tg CO2 Eq. in 2005. These
emissions have been increasing as phase-outs of ODS
required under the Montreal Protocol come into effect.
• The increase in ODS substitutes emissions is
offset substantially by decreases in emission of
hydrofluorocarbons (HFCs), perfluorocarbons (PFCs),
and sulfur hexafluoride (SF6) from other sources.
Emissions from aluminum production decreased by
84 percent (15.6 Tg CO2 Eq.) from 1990 to 2005, due
to both industry emission reduction efforts and lower
domestic aluminum production. Emissions from the
production of HCFC-22 decreased by 53 percent (18.4
Tg CO2 Eq.) from 1990 to 2005, 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) and
the use of thermal oxidation at some plants to reduce
HFC-23 emissions. Emissions from electric power
transmission and distribution systems decreased by 51
percent (13.9 Tg CO2 Eq.) from 1990 to 2005, primarily
because of higher purchase prices for SF6 and efforts by
industry to reduce emissions.
Overall, from 1990 to 2005, total emissions of CO2
increased by 1,027.9 Tg CO2 Eq. (20 percent), while CH4
and N2O emissions decreased by 69.8 Tg CO2 Eq. (11
percent) and 13.4 Tg CO2 Eq. (2.8 percent) respectively.
During the same period, aggregate weighted emissions
of HFCs, PFCs, and SF6 rose by 73.7 Tg CO2 Eq. (82.5
percent). Despite being emitted in smaller quantities relative
to the other principal greenhouse gases, emissions of HFCs,
PFCs, and SF6 are significant because many of them have
extremely high GWPs and, in the cases of PFCs and SF6,
long atmospheric lifetimes. Conversely, U.S. greenhouse gas
emissions were partly offset by C sequestration in managed
forests, trees in urban areas, agricultural soils, and landfilled
yard trimmings, which was estimated to be 11 percent of
total emissions in 2005.
Table 2-3 summarizes emissions and sinks from all U.S.
anthropogenic sources in weighted units of Tg CO2 Eq.,
while unweighted gas emissions and sinks in gigagrams (Gg)
are provided in Table 2-4. Figure 2-5 and Table 2-5 show
emissions and sinks aggregated by sector/chapter.
Emissions of all gases can be summed from each
source category from Intergovernmental Panel on Climate
Change (IPCC) guidance. Over the fifteen-year period of
1990 to 2005, total emissions in the Energy, Industrial
Processes, and Agriculture sectors climbed by 1,001.5
Tg CO2 Eq. (19 percent), 33.6 Tg CO2 Eq. (11 percent),
and 6.0TgCO2 Eq. (1.1 percent), respectively. Emissions
decreased from the Solvent and Other Product Use and
Waste sectors by 0.02 Tg CO2 Eq. (less than 1 percent)
and 26.7 Tg CO2 Eq. (14 percent), respectively. Over the
same period, estimates of net C sequestration in the Land
Use, Land-Use Change, and Forestry sector increased by
109.5 Tg CO2 Eq. (16 percent).
Figure 2-5
U.S. Greenhouse Gas Emissions and Sinks
by Chapter/IPCC Sector
Industrial Processes
Agriculture /
Waste LULUCF (non-CD,)
Land Use, Land-Use Change, and Forestry (net CO, flux)
(2,000) -
O) 01 0» 01 0»
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and
Other Product Use sector.
TresfiJs in Greenhouse 8os Emissions,
-------
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
Net CO 2 Flux from Land Use,
Land-Use Change, and Forestry3
International Bunker Fuels"
Wood Biomass and Ethanol Consumption*1
CH4
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Ferroalloy Production
Silicon Carbide Production and Consumption
International Bunker Fuels"
N20
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
Adipic Acid Production
Settlements Remaining Settlements
N20 Product Usage
Forest Land Remaining Forest Land
Municipal Solid Waste Combustion
Field Burning of Agricultural Residues
International Bunker Fuels"
HFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
Net Emissions (Sources and Sinks)
1990
5,061.6
4,724.1
117.3
33.3
84.9
33.7
10.9
19.3
11.3
5.5
4.1
6.8
2.2
1.3
2.2
1.5
1.4
0.9
0.3
0.4
(712.8)
113.7
219.3
609.1
161.0
115.7
124.5
81.9
30.9
34.4
24.8
7.1
8.0
7.1
6.0
4.7
0.9
1.3
0.7
+
+
0.2
482.0
366.9
43.7
17.8
12.3
8.6
6.4
15.2
5.1
4.3
0.8
0.5
0.4
1.0
89.3
0.3
35.0
27.1
2.9
18.5
5.4
6,242.0
5,529.2
1995
5,384.6
5,030.0
133.2
36.8
73.3
33.8
15.7
20.5
12.8
7.4
4.3
5.7
2.8
1.7
2.0
1.5
1.4
1.0
0.3
0.3
(828.8)
100.6
236.8
598.7
157.1
120.6
128.1
66.5
35.1
31.1
25.1
4.0
7.8
7.6
8.2
4.3
1.1
1.3
0.7
+
+
0.1
484.2
353.4
53.7
19.9
12.8
9.0
6.9
17.2
5.5
4.5
0.6
0.5
0.4
0.9
103.5
32.2
27.0
21.8
5.0
11.8
5.6
6,571.0
5,742.2
2000
5,940.0
5,584.9
141.0
41.2
65.1
29.4
17.9
19.6
13.3
6.0
4.2
6.1
3.0
1.9
1.9
1.4
1.4
1.1
0.3
0.2
(756.7)
101.1
228.3
563.7
131.9
113.5
126.6
55.9
38.7
27.8
26.4
14.0
7.4
7.5
7.3
3.5
1.2
1.2
0.8
+
+
0.1
499.8
376.8
53.2
19.6
14.0
9.6
7.6
6.0
5.6
4.8
1.7
0.4
0.5
0.9
143.8
80.9
29.8
15.2
6.3
8.6
3.0
7,147.2
6,390.5
2001
5,843.0
5,511.7
131.4
41.4
57.9
28.8
18.3
16.7
12.9
5.7
4.1
4.4
2.8
1.9
1.5
1.3
0.8
1.0
0.3
0.2
(767.5)
97.6
203.2
547.7
127.6
112.5
125.4
55.5
40.1
27.4
25.9
6.0
6.8
7.6
6.7
3.2
1.1
1.1
0.8
+
+
0.1
502.5
389.0
49.7
15.9
13.5
9.8
7.6
4.9
5.5
4.8
1.0
0.4
0.5
0.9
133.8
88.6
19.8
15.1
4.5
3.5
2.4
7,027.0
6,259.5
2002
5,892.7
5,557.2
135.3
42.9
54.6
29.6
18.5
17.8
12.3
5.9
4.1
4.5
2.9
2.0
1.3
1.3
1.0
0.9
0.3
0.2
(811.9)
89.1
204.4
549.7
130.4
112.6
125.0
52.0
41.1
26.8
25.8
10.4
6.8
6.8
6.1
3.1
1.1
1.0
0.7
+
+
0.1
479.2
366.1
47.1
17.2
13.4
9.7
7.7
5.9
5.6
4.3
1.4
0.4
0.4
0.8
143.0
96.9
19.8
14.3
4.4
5.2
2.4
7,064.6
6,252.7
2003
5,952.5
5,624.5
131.3
43.1
53.4
28.4
19.5
16.2
13.0
4.7
4.1
4.5
2.8
2.0
1.3
1.4
1.3
0.5
0.3
0.2
(811.9)
83.7
209.6
549.2
134.9
113.0
123.7
52.1
40.5
25.8
25.6
8.1
7.0
6.9
5.9
2.9
1.1
1.0
0.8
+
+
0.1
459.8
350.2
43.8
16.7
13.7
9.3
7.8
6.2
5.8
4.3
1.2
0.4
0.4
0.8
142.7
105.5
12.3
13.8
4.3
3.8
2.9
7,104 ?
6,292.3
2004
6,064.3
5,713.0
150.2
45.6
51.3
28.2
20.1
16.9
13.7
6.7
4.2
4.2
2.9
2.3
1.4
1.4
1.2
0.5
0.3
0.2
(824.8)
97.2
224.8
540.3
132.1
110.5
119.0
54.5
39.7
25.4
25.7
6.9
7.1
7.6
5.8
2.8
1.2
1.0
0.9
+
+
0.1
445.2
338.8
41.2
16.0
13.9
9.4
7.9
5.7
6.0
4.3
1.1
0.4
0.5
0.9
153.9
114.5
15.6
13.6
4.7
2.8
2.6
7,203.7
6,378.9
2005
6,089.5
5,751.2
142.4
45.9
45.2
28.2
20.9
16.3
13.7
7.4
4.2
4.2
2.9
1.9
1.4
1.4
1.3
0.5
0.3
0.2
(828.5)
97.2
206.5
539.3
132.0
112.1
111.1
52.4
41.3
28.5
25.4
11.6
6.9
6.9
5.5
2.6
1.1
1.0
0.9
+
+
0.1
468.6
365.1
38.0
15.7
13.8
9.5
8.0
6.0
5.8
4.3
1.5
0.4
0.5
0.9
163.0
123.3
16.5
13.2
4.3
3.0
2.7
7P604
6,431.9
+ Does not exceed 0.05 Tg C02 Eq.
a The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total. Parentheses indicate negative values or sequestration.
" Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.
Note: Totals may not sum due to independent rounding.
2-6 Inventory o! U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
Net CO 2 Flux from Land Use,
Land-Use Change, and Forestry*
International Bunker Fuels"
Wood Biomass and Ethanol Consumption1'
CH4
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Ferroalloy Production
Silicon Carbide Production and Consumption
International Bunker Fuels'1
N20
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
Adipic Acid Production
Settlements Remaining Settlements
N20 Product Usage
Forest Land Remaining Forest Land
Municipal Solid Waste Combustion
Field Burning of Agricultural Residues
International Bunker Fuels'1
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
1990
5,061,634
4,724,149
117,307
33,278
84,904
33,729
10,950
19,306
11,273
5,533
4,141
6,831
2,221
1,308
2,152
1,529
1,415
949
285
375
(772, 778)
113,683
219,341
29,003
7,668
5,510
5,927
3,899
1,471
1,640
1,180
337
382
339
286
226
41
63
33
1
1
8
1,555
1,184
141
58
40
28
21
49
17
14
2
2
1
3
M
M
3
1
M
M
+
1995
5,384,615
5,030,036
133,228
36,847
73,333
33,807
15,712
20,453
12,844
7,359
4,304
5,659
2,750
1,670
2,036
1,513
1,423
1,013
298
329
(828,798)
100,627
236,775
28,509
7,479
5,744
6,101
3,165
1,673
1,482
1,195
189
373
363
391
207
52
62
32
1
1
6
1,562
1,140
173
64
41
29
22
56
18
14
2
1
1
3
M
M
2
1
M
M
+
2000
5,939,968
5,584,880
141,005
41,190
65,115
29,390
17,889
19,616
13,344
5,960
4,181
6,086
3,004
1,918
1,893
1,382
1,416
1,140
311
248
(756,705)
101,125
228,308
26,842
6,280
5,404
6,027
2,662
1,844
1,325
1,257
667
351
357
349
165
58
57
38
1
1
6
1,612
1,215
172
63
45
31
24
19
18
15
6
1
1
3
M
M
3
1
M
M
+
2001
5,843,025
5,511,719
131,375
41,357
57,927
28,793
18,344
16,719
12,861
5,733
4,147
4,381
2,787
1,857
1,459
1,264
825
986
293
199
(767,472)
97,563
203,163
26,080
6,078
5,356
5,971
2,644
1,911
1,303
1,232
285
324
364
318
154
51
51
37
+
+
5
1,621
1,255
160
51
44
32
25
16
18
15
3
1
1
3
M
M
2
1
M
M
+
2002
5,892,744
5,557,242
135,327
42,898
54,595
29,630
18,513
17,766
12,330
5,885
4,139
4,490
2,857
1,997
1,349
1,338
978
937
290
183
(811,892)
89,101
204,351
26,176
6,210
5,361
5,951
2,476
1,959
1,275
1,229
494
324
325
292
146
52
48
34
+
+
4
1,546
1,181
152
56
43
31
25
19
18
14
5
1
1
3
M
M
2
1
M
M
+
2003
5,952,538
5,624,500
131,334
43,082
53,370
28,445
19,490
16,173
13,022
4,720
4,111
4,503
2,777
2,013
1,305
1,382
1,310
507
289
202
(811,945)
83,690
209,603
26,154
6,425
5,379
5,891
2,480
1,928
1,229
1,220
384
334
328
282
136
51
49
38
+
+
4
1,483
1,130
141
54
44
30
25
20
19
14
4
1
1
2
M
M
1
1
M
M
+
2004
6,064,329
5,713,018
150,208
45,603
51,309
28,190
20,115
16,894
13,728
6,702
4,205
4,231
2,895
2,259
1,419
1,395
1,199
477
259
224
(824,785)
97,177
224,825
25,727
6,292
5,262
5,669
2,597
1,892
1,209
1,222
330
340
360
275
131
55
50
42
+
+
5
1,436
1,093
133
52
45
30
26
19
19
14
3
1
2
3
M
M
1
1
M
M
+
2005
6,089,490
5,751,200
142,368
45,910
45,235
28,185
20,912
16,321
13,660
7,397
4,228
4,208
2,897
1,921
1,392
1,383
1,324
465
265
219
(828,453)
97,191
206,475
25,681
6,286
5,340
5,292
2,494
1,966
1,357
1,210
551
330
328
263
125
51
45
41
+
+
5
1,512
1,178
123
51
45
31
26
19
19
14
5
1
2
3
M
M
1
1
M
M
+
+ Does not exceed 0.5 Gg.
M Mixture of multiple gases.
a The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total. Parentheses indicate negative values or sequestration.
b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.
Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-7
-------
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and
Forestry (Non-C02 Emissions)
Waste
Total
Net C02 Flux from Land Use,
Land-Use Change, and Forestry*
Net Emissions (Sources and Sinks)
1990
5,202.2
300.1
4.3
530.3
13.0
192.2
6,242.0
(712.8)
5,529.2
1995
5,525.8
314.8
4.5
526.8
10.1
189.1
6,571.0
(828.8)
5,742.2
2000
6,069.2
338.7
4.8
547.4
21.3
165.9
7,147.2
(756.7)
6,390.5
2001
5,978.9
309.6
4.8
560.3
12.4
161.1
7,027.0
(767.5)
6,259.5
2002
6,021.4
320.2
4.3
537.4
17.4
163.9
7,064.6
(811.9)
6,252.7
2003
6,079.1
316.4
4.3
521.1
15.0
168.4
7,104.2
(811.9)
6,292.3
2004
6,181.7
330.6
4.3
507.4
13.9
165.7
7,203.7
(824.8)
6,378.9
2005
6,201.9
333.6
4.3
536.3
18.9
165.4
7,260.4
(828.5)
6,431.9
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions total.
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
Energy
Energy-related activities, primarily fossil fuel
combustion, accounted for the vast majority of U.S. CO2
emissions for the period of 1990 through 2005. In 2005,
approximately 86 percent of the energy consumed in the
United States (on a Btu basis) was produced through the
combustion of fossil fuels. The remaining 14 percent came
from other energy sources such as hydropower, biomass,
nuclear, wind, and solar energy (see Figure 2-6 and Figure
2-7). A discussion of specific trends related to CO2 as well
as other greenhouse gas emissions from energy consumption
is presented below. Energy-related activities are also
responsible for CH4 and N2O emissions (38 percent and 11
percent of total U.S. emissions of each gas, respectively).
Table 2-6 presents greenhouse gas emissions from the Energy
chapter, by source and gas.
Figure 2-6
2005 Energy Chapter Greenhouse Gas Sources
5,751.2
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion
Municipal Solid Waste «
Combustion •
Abandoned Underground •
Energy as a Portion
of all Emissions
Coal Mines
25
50 75 100
Tg CO, Eq.
125 150
Fossil Fuel ComtoiiSliO:; (5 75 S.2 'fu CCU Eq j
As fossil fuels are combusted, the C stored in them is
emitted almost entirely as CO2. The amount of C in fuels
per unit of energy content varies significantly by fuel type.
For example, coal contains the highest amount of C per unit
of energy, while petroleum and natural gas have about 25
percent and 45 percent less C than coal, respectively. From
1990 through 2005, petroleum supplied the largest share of
U.S. energy demands, accounting for an average of 44 percent
of total energy consumption, with natural gas and coal each
accounting for 28 percent of total energy consumption.
Petroleum was consumed primarily in the transportation
end-use sector, the vast majority of coal was used by electric
power generators, and natural gas was consumed largely in
the industrial and residential end-use sectors.
Emissions of CO2 from fossil fuel combustion increased
at an average annual rate of 1.4 percent from 1990 to 2005.
The fundamental factors influencing this trend include (1) a
generally growing domestic economy over the last 15 years,
and (2) significant growth in emissions from electricity
generation and transportation activities. Between 1990 and
2005, CO2 emissions from fossil fuel combustion increased
from 4,724.1 Tg CO2 Eq. to 5,751.2 Tg CO2 Eq. —a 21.7
percent total increase over the fifteen-year period.
The four major end-use sectors contributing to CO2
emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity
generation also emits CO2, although these emissions are
produced as they consume fossil fuel to provide electricity
to one of the four end-use sectors. For the discussion below,
electricity generation emissions have been distributed to
2-8 Inventory of U.S. Greenhouse Gas Emissions anc. Sinks: 1990 -2005
-------
Figure 2-7
2005 U.S. Fossil Carbon Flows (Tg C02 Eq.)
Coal Emissions
2.027
Natural Gas Emissions
1.191
NEU = Non-Energy Use
NG = Natural Gas
Table 2-6: Emissions from Energy (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Municipal Solid Waste Combustion
International Bunker Fuels*
Wood Biomass and Ethanol
Consumption*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
International Bunker Fuels *
N20
Mobile Combustion
Stationary Combustion
Municipal Solid Waste Combustion
International Bunker Fuels *
Total
1990
4,886.1
4,724.1
117.3
33.7
10.9
113.7
219.3
259.6
124.5
81.9
34.4
8.0
6.0
4.7
0.2
56.5
43.7
12.3
0.5
1.0
5,202.2
1995
5,212.8
5,030.0
133.2
33.8
15.7
100.6
236.8
246.1
128.1
66.5
31.1
7.8
8.2
4.3
0.1
66.9
53.7
12.8
0.5
0.9
5,525.8
2000
5,773.2
5,584.9
141.0
29.4
17.9
101.1
228.3
228.5
126.6
55.9
27.8
7.4
7.3
3.5
0.1
67.6
53.2
14.0
0.4
0.9
6,069.2
2001
5,690.2
5,511.7
131.4
28.8
18.3
97.6
203.2
225.0
125.4
55.5
27.4
6.8
6.7
3.2
0.1
63.6
49.7
13.5
0.4
0.9
5,978.9
2002
5,740.7
5,557.2
135.3
29.6
18.5
89.1
204.4
219.7
125.0
52.0
26.8
6.8
6.1
3.1
0.1
60.9
47.1
13.4
0.4
0.8
6,021.4
2003
5,803.8
5,624.5
131.3
28.4
19.5
83.7
209.6
217.4
123.7
52.1
25.8
7.0
5.9
2.9
0.1
57.9
43.8
13.7
0.4
0.8
6,079.1
2004
5,911.5
5,713.0
150.2
28.2
20.1
97.2
224.8
214.6
119.0
54.5
25.4
7.1
5.8
2.8
0.1
55.5
41.2
13.9
0.4
0.9
6,181.7
2005
5,942.7
5,751.2
142.4
28.2
20.9
97.2
206.5
207.1
111.1
52.4
28.5
6.9
5.5
2.6
0.1
52.2
38.0
13.8
0.4
0.9
6,201.9
* These values are presented for informational purposes only and are not included in totals or are already accounted for in other source categories.
Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-9
-------
each end-use sector on the basis of each sector's share
of aggregate electricity consumption. This method of
distributing emissions assumes that each end-use sector
consumes electricity that is generated from the national
average mix of fuels according to their C intensity. Emissions
from electricity generation are also addressed separately after
the end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated
separately due to a lack of specific consumption data for the
individual end-use sectors.
Table 2-7, Figure 2-8, and Figure 2-9 summarize CO2
emissions from fossil fuel combustion by end-use sector.
Transportation End-Use Sector. Transportation activities
(excluding international bunker fuels) accounted for 33
percent of CO2 emissions from fossil fuel combustion in
2005 .•' Virtually all of the energy consumed in this end-use
sector came from petroleum products. Over 60 percent of the
emissions resulted from gasoline consumption for personal
vehicle use. The remaining emissions came from other
Table 2-7: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990
1,467.0
1,464.0
3.0
1,539.8
857.1
682.7
929.9
340.3
589.6
759.2
224.3
534.9
28.3
4,724.1
1,810.2
1995
1,593.3
1,590.2
3.0
1,595.8
882.7
713.1
995.4
356.4
639.0
810.6
226.4
584.2
35.0
5,030.0
1,939.3
2000
1,787.8
1,784.4
3.4
1,660.1
875.0
785.1
1,131.5
373.5
758.0
969.3
232.3
736.9
36.2
5,584.9
2,283.5
2001
1,761.5
1,758.2
3.3
1,596.6
869.9
726.7
1,124.8
363.9
760.9
979.7
225.1
754.6
49.0
5,511.7
2,245.5
2002
1,815.7
1,812.3
3.4
1,575.5
857.7
717.8
1,147.9
362.4
785.5
973.8
225.7
748.0
44.3
5,557.2
2,254.7
2003
1,814.8
1,810.5
4.3
1,595.1
858.3
736.8
1,179.1
383.8
795.3
984.2
236.6
747.6
51.3
5,624.5
2,284.0
2004
1,868.9
1,864.5
4.4
1,615.2
875.6
739.6
1,175.9
369.9
806.0
999.1
233.3
765.8
54.0
5,713.0
2,315.8
2005
1,897.9
1,892.8
5.2
1,575.2
840.1
735.1
1,208.7
358.7
849.9
1,016.8
225.8
791.0
52.5
5,751.2
2,381.2
Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated based on aggregate national
electricity consumption by each end-use sector.
Figure 2-8
Figure 2-9
2005 C02 Emissions from Fossil Fuel Combustion
by Sector and Fuel Type
2005 End-Use Sector Emissions of C02 from
Fossil Fuel Combustion
2,500 -|
2,000 -
1,500 -
1,000
500 -
Relative Contribution
by Fuel Type
Natural Gas
Petroleum
! Coal
o -1
Residential Commercial Industrial Transportation Electricity U.S.
Generation Territories
2,000 -i
1,500-
1,000-
500-
O-1
From Electricity
Consumption
I From Direct Fossil
Fuel Combustion
Residential Commercial Industrial Transportation U.S.
Territories
3 If emissions from international bunker fuels are included, the transportation end-use sector accounted for 35 percent of U.S. emissions from fossil fuel
combustion in 2005.
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
transportation activities, including the combustion of diesel
fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial CO2 emissions,
resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed
by industry, accounted for 27 percent of CO2 emissions from
fossil fuel combustion in 2005. About half of these emissions
resulted from direct fossil fuel combustion to produce steam
and/or heat for industrial processes. The other half of the
emissions resulted from consuming electricity for motors,
electric furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The
residential and commercial end-use sectors accounted for
21 and 18 percent, respectively, of CO2 emissions from
fossil fuel combustion in 2005. Both sectors relied heavily
on electricity for meeting energy demands, with 70 and
78 percent, respectively, of their emissions attributable to
electricity consumption for lighting, heating, cooling, and
operating appliances. The remaining emissions were due to
the consumption of natural gas and petroleum for heating
and cooking.
Electricity Generation. The United States relies on
electricity to meet a significant portion of its energy demands,
especially for lighting, electric motors, heating, and air
conditioning. Electricity generators consumed 36 percent of
U.S. energy from fossil fuels and emitted 41 percent of the
CO2 from fossil fuel combustion in 2005. The type of fuel
combusted by electricity generators has a significant effect
on their emissions. For example, some electricity is generated
with low-CO2-emitting energy technologies,particularly non-
fossil options such as nuclear, hydroelectric, or geothermal
energy. However, electricity generators rely on coal for over
half of their total energy requirements and accounted for 93
percent of all coal consumed for energy in the United States
in 2005. Consequently, changes in electricity demand have
a significant impact on coal consumption and associated
CO2 emissions.
Non-Energy Use of Fossil Fuels (142.4 Tg CO? Eq.)
In addition to being combusted for energy, fossil fuels
are also consumed for non-energy uses (NEUs). Fuels are
used in the industrial and transportation end-use sectors for a
variety of NEUs, including application as solvents, lubricants,
and waxes, or as raw materials in the manufacture of plastics,
rubber, and synthetic fibers. CO2 emissions arise from non-
energy uses via several pathways. Emissions may occur during
the manufacture of a product, as is the case in producing
plastics or rubber from fuel-derived feedstocks. Additionally,
emissions may occur during the product's lifetime, such as
during solvent use. Where appropriate data and methodologies
are available, NEUs of fossil fuels used for industrial processes
are reported in the Industrial Processes chapter. Emissions in
2005 for non-energy uses of fossil fuels were 142.4 Tg CO2
Eq., which constituted 2.5 percent of overall fossil fuel CO2
emissions and 2 percent of total national CO2 emissions,
approximately the same proportion as in 1990. CO2 emissions
from non-energy use of fossil fuels increased by 25.1 Tg CO2
Eq. (21 percent) from 1990 through 2005.
Natural Gas Systems (139.3 Tg CO, Eq.)
CH4 and non-energy CO2 emissions from natural gas
systems are generally process-related, with normal operations,
routine maintenance, and system upsets being the primary
contributors. Emissions from normal operations include:
natural gas engines and turbine uncombusted exhaust, bleed
and discharge emissions from pneumatic devices, and fugitive
emissions from system components. Routine maintenance
emissions originate from pipelines, equipment, and wells
during repair and maintenance activities. Pressure surge relief
systems and accidents can lead to system upset emissions. In
2005, CH4 emissions from U.S. natural gas systems accounted
for approximately 21 percent of U.S. CH4 emissions. Also
in 2005, natural gas systems accounted for approximately
0.5 percent of U.S. CO2 emissions (28.2 Tg CO2 Eq.). From
1990 through 2005, CH4 and CO2 emissions from natural gas
systems decreased by 13.3 Tg CO2 Eq. (11 percent), and 5.5
Tg CO, Eq. (16 percent) respectively.
Coal Mining (52.4 Tg C02 Eq.)
Produced millions of years ago during the formation of
coal, CH4 trapped within coal seams and surrounding rock
strata is released when the coal is mined. The quantity of CH4
released to the atmosphere during coal mining operations
depends primarily upon the type of coal and the method
and rate of mining.
CH4 from surface mines is emitted directly to the
atmosphere as the rock strata overlying the coal seam are
removed. Because CH4 in underground mines is explosive
at concentrations of 5 to 15 percent in air, most active
underground mines are required to vent this CH4, typically
to the atmosphere. At some mines, CH4-recovery systems
Trends in Greenhouse Gas Emissions 2-11
-------
may supplement these ventilation systems. During 2005, coal
mining activities emitted 10 percent of U.S. CH4 emissions.
From 1990 to 2005, emissions from this source decreased
by 29.5 Tg CO, Eq. (36 percent) due to increased use of the
CH4 collected by mine degasification systems and a general
shift toward surface mining.
Mobile Combustion (40.6 Tg CO? Eq.)
In addition to CO2, mobile combustion results in N2O
and CH4 emissions. N2O is a product of the reaction that
occurs between nitrogen and oxygen during fuel combustion.
The quantity emitted varies according to the type of fuel,
technology, and pollution control device used, as well as
maintenance and operating practices. For example, some
types of catalytic converters installed to reduce motor
vehicle pollution can promote the formation of N2O. In
2005, N2O emissions from mobile combustion were 38.0 Tg
CO2 Eq. (8 percent of U.S. N,O emissions). From 1990 to
2005, N2O emissions from mobile combustion decreased by
5.7 Tg CO2 Eq. (13 percent). In 2005, CH4 emissions were
estimated to be 2.6 Tg CO2 Eq. The combustion of gasoline
in highway vehicles was responsible for the majority of the
CH4 emitted from mobile combustion. From 1990 to 2005.
CH4 emissions from mobile combustion decreased by 2.1
Tg CO, Eq. (45 percent).
Petroleum Systems (28.5 Tg C02 Eq.}
Petroleum is often found in the same geological structures
as natural gas, and the two are often retrieved together. Crude
oil is saturated with many lighter hydrocarbons, including CH4.
When the oil is brought to the surface and processed, many
of the dissolved lighter hydrocarbons (as well as water) are
removed through a series of high-pressure and low-pressure
separators. The remaining hydrocarbons in the oil are emitted
at various points along the system. CH4 emissions from the
components of petroleum systems generally occur as a result
of system leaks, disruptions, and routine maintenance. In 2005,
emissions from petroleum systems were about 5 percent of
U.S. CH4 emissions. From 1990 to 2005, CH4 emissions from
petroleum systems decreased by 6 Tg CO2 Eq. (17 percent).
Municipal Solid Waste Combustion (21.3 "g C0:> Eq.)
Combustion is used to manage about 14 percent of the
municipal solid waste generated in the United States. The
burning of garbage and non-hazardous solids, referred to as
municipal solid waste, as well as the burning of hazardous
waste, is usually performed to recover energy from the waste
materials. CO2 and N2O emissions arise from the organic
materials found in these wastes. The CO2 emissions from
municipal solid waste containing C of biogenic origin (e.g.,
paper, yard trimmings) are not accounted for in this Inventory,
since they are presumed to be offset by regrowth of the original
living source, and are ultimately accounted for in the Land Use,
Land-Use Change, and Forestry chapter. Several components
of municipal solid waste, such as plastics, synthetic rubber,
synthetic fibers, and carbon black, are of fossil-fuel origin,
and are included as sources of CO2 and N2O emissions. In
2005, CO2 emissions from waste combustion amounted to
20.9 Tg CO2 Eq., while N2O emissions amounted to 0.4 Tg
CO2 Eq. From 1990 through 2005, CO2 emissions from waste
combustion increased by 10 Tg CO2 Eq. (91 percent), while
N2O emissions decreased by 0.1 Tg CO2 Eq. (15 percent).
Stationary Combustion (20.1 Tn 00;. Eq.)
In addition to CO2, stationary combustion results in
N2O and CH4 emissions. In 2005, N2O emissions from
static nary combustion accounted for 13.8 Tg CO2 Eq. (3
percent of U.S. N2O emissions). From 1990 to 2005, N,O
emissions from stationary combustion increased by 1.5 Tg
CO2 Eq. (12 percent), due to increased fuel consumption.
In 2005, CH4 emissions were 6.9 Tg CO2 Eq. (1 percent of
U.S. CH4 emissions). From 1990 to 2005, CH4 emissions
from stationary combustion decreased by 1.1 Tg CO2
Eq. (13.5 percent). The majority of CH4 emissions from
stationary combustion resulted from the burning of wood
in the residential end-use sector.
Abandonee! Underc round Coal Mines (5.5 Tg C02 lEq.)
Coal mining activities result in the emission of CH4 into
the atmosphere. However, the closure of a coal mine does
not correspond with an immediate cessation in the release of
emissions. Following an initial decline, abandoned mines can
liberate CH4 at a near-steady rate over an extended period
of time, or, if flooded, produce gas for only a few years. In
2005., the emissions from abandoned underground coal mines
constituted 1 percent of U.S. CH4 emissions. Between 1990
and 2005, emissions from this source decreased by 0.5 Tg
CO, Eq. (8 percent).
Wooc Biornass anc Ethanol Consumption (206.5 TCI C02 Eq.)
Biomass refers to organically-based C fuels (as opposed
to fossil-based). Biomass in the form of fuel wood and wood
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: I9:t0 2005
-------
waste was used primarily in the industrial sector, while the
transportation sector was the predominant user of biomass-
based fuels, such as ethanol from corn and woody crops.
Although these fuels do emit CO2, in the long run the
CO2 emitted from biomass consumption does not increase
atmospheric CO2 concentrations if the biogenic C emitted
is offset by the growth of new biomass. For example, fuel
wood burned one year but re-grown the next only recycles
C, rather than creating a net increase in total atmospheric
C. Net C fluxes from changes in biogenic C reservoirs in
forest lands or croplands are accounted for in the estimates
for the Land Use, Land-Use Change, and Forestry sector.
As a result, CO9 emissions from biomass combustion have
been estimated separately from fossil-fuel-based emissions
and are not included in the U.S. totals. CH4 emissions
from biomass combustion are included in the Stationary
Combustion source.
The consumption of wood biomass in the industrial,
residential, electric power, and commercial end-use sectors
accounted for 56,21,8, and 4 percent of gross CO2 emissions
from wood biomass and ethanol consumption, respectively.
Ethanol consumption in the transportation end-use sector
accounted for the remaining 11 percent.
CO2 emissions from wood biomass and ethanol
consumption decreased by 12.9 Tg CO2 Eq. (approximately
6 percent) from 1990 through 2005.
io'ernaiional Sunkpf Fuess i98,2 Tg CO.. Eq.)
Greenhouse gases emitted from the combustion of fuels
used for international transport activities, termed international
bunker fuels underthe UNFCCC, include CO2,CH4, and N2O.
Emissions from these activities are currently not included in
national emission totals, but are reported separately based upon
location of fuel sales. The decision to report emissions from
international bunker fuels separately, instead of allocating them
to a particular country, was made by the Intergovernmental
Negotiating Committee in establishing the Framework
Convention on Climate Change. These decisions are reflected
in the Revised 1996IPCC Guidelines, in which countries are
requested to report emissions from ships or aircraft that depart
from their ports with fuel purchased within national boundaries
and are engaged in international transport separately from
national totals (IPCC/UNEP/OECD/IEA 1997).
Two transport modes are addressed under the IPCC
definition of international bunker fuels: aviation and marine.
Emissions from ground transport activities — by road vehicles
and trains, even when crossing international borders —are
allocated to the country where the fuel was loaded into
the vehicle and, therefore, are not counted as bunker fuel
emissions. Emissions of CO2,CH4, and N2O from international
bunker fuel combustion were 97.2,0.1, and 0.9 Tg CO2 Eq. in
2005, respectively. From 1990 through 2005, CO2, CH4, and
N2O emissions from international bunker fuels decreased by
16.5 Tg CO2 Eq. (15 percent), 0.1 Tg CO2 Eq. (35 percent),
and 0.1 Tg CO? Eq. (9 percent), respectively.
Industrial Processes
Emissions are produced as a by-product of many non-
energy-related industrial process activities. For example,
industrial processes can chemically transform raw materials,
which often release waste gases such as CO2, CH4, and N2O.
These processes include iron and steel production, cement
manufacture, ammonia manufacture and urea application,
lime manufacture, limestone and dolomite use (e.g., flux
stone, flue gas desulfurization, and glass manufacturing),
soda ash manufacture and use, titanium dioxide production,
phosphoric acid production, ferroalloy production, CO2
Figure 2-10
2005 Industrial Processes Chapter
Greenhouse Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
HCFC-22 Production f§
Ammonia Manufacture and Urea Application H
Nitric Acid Production ^
Lime Manufacture K
Electrical Transmission and Distribution H
Limestone and Dolomite Use |
Aluminum Production ^j
Adipic Acid Production jjj
Semiconductor Manufacture |
Soda Ash Manufacture and Consumption f
Petrochemical Production f
Magnesium Production and Processing (
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
Carbon Dioxide Consumption
Zinc Production <0.5
Lead Production <0.5
Silicon Carbide Production and Consumption <0.5
Industrial Processes
as a Portion of
all Emissions
4.6%'
25
50 75 100
TgCOzEq.
125
Trends in Greenhouse Gas Emissions 2-13
-------
consumption, silicon carbide production and consumption,
aluminum production, petrochemical production, nitric acid
production, adipic acid production, lead production, and zinc
production (see Figure 2-10). Additionally, emissions from
industrial processes release HFCs, PFCs and SF6. Table 2-8
presents greenhouse gas emissions from industrial processes
by source category.
Substitution of Ozone Depleting Substances
i123.3TgC02Eq.)
The use and subsequent emissions of HFCs and PFCs as
substitutes for ODSs have increased from small amounts in
Table 2-8: Emissions from Industrial Processes (Tg C02 Eg.)
1990 to 123 Tg CO2 Eq. in 2005, accounting for 76 percent
of aggregate HFC, PFC, and SF6 emissions, an increase of
36,899 percent over this time period. This increase was in
large part the result of efforts to phase-out CFCs and other
ODSs in the United States, especially the introduction of
HFC-134a as a CFC substitute in refrigeration and air-
conditioning applications. In the short term, this trend is
expected to continue, and will likely accelerate over the
coming decade as HCFCs, which are interim substitutes
in many applications, are themselves phased-out under the
provisions of the Copenhagen Amendments to the Montreal
Gas/Source
C02
Cement Manufacture
Iron and Steel Production
Ammonia Manufacture & Urea Application
Lime Manufacture
Limestone and Dolomite Use
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
CH4
Petrochemical Production
Iron and Steel Production
Ferroalloy Production
Silicon Carbide Production and Consumption
N20
Nitric Acid Production
Adipic Acid Production
HFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
1990
175.5
33.3
84.9
19.3
11.3
5.5
4.1
6.8
2.2
1.3
2.2
1.5
1.4
0.9
0.3
0.4
2.2
0.9
1.3
+
+
33.0
17.8
15.2
89.3
0.3
35.0
27.1
2.9
18.5
5.4
300.1
1995
171.8
36.8
73.3
20.5
12.8
7.4
4.3
5.7
2.8
1.7
2.0
1.5
1.4
1.0
0.3
0.3
2.4
1.1
1.3
+
+
37.1
19.9
17.2
103.5
32.2
27.0
21.8
5.0
11.8
5.6
314.8
2000
166.8
41.2
65.1
19.6
13.3
6.0
4.2
6.1
3.0
1.9
1.9
1.4
1.4
1.1
0.3
0.2
2.5
1.2
1.2
+
+
25.6
19.6
6.0
143.8
80.9
29.8
15.2
6.3
8.6
3.0
338.7
2001
152.8
41.4
57.9
16.7
12.9
5.7
4.1
4.4
2.8
1.9
1.5
1.3
0.8
1.0
0.3
0.2
2.2
1.1
1.1
+
+
20.8
15.9
4.9
133.8
88.6
19.8
15.1
4.5
3.5
2.4
309.6
2002
152.0
42.9
54.6
17.8
12.3
5.9
4.1
4.5
2.9
2.0
1.3
1.3
1.0
0.9
0.3
0.2
2.1
1.1
1.0
+
+
23.1
17.2
5.9
143.0
96.9
19.8
14.3
4.4
5.2
2.4
320.2
2003
148.8
43.1
53.4
16.2
13.0
4.7
4.1
4.5
2.8
2.0
1.3
1.4
1.3
0.5
0.3
0.2
2.1
1.1
1.0
+
+
22.9
16.7
6.2
142.7
105.5
12.3
13.8
4.3
3.8
2.9
316.4
2004
152.8
45.6
51.3
16.9
13.7
6.7
4.2
4.2
2.9
2.3
1.4
1.4
1.2
0.5
0.3
0.2
2.2
1.2
1.0
+
+
21.8
16.0
5.7
153.9
114.5
15.6
13.6
4.7
2.8
2.6
330.6
2005
146.8
45.9
45.2
16.3
13.7
7.4
4.2
4.2
2.9
1.9
1.4
1.4
1.3
0.5
0.3
0.2
2.0
1.1
1.0
+
+
21.7
15.7
6.0
163.0
123.3
16.5
13.2
4.3
3.0
2.7
333.6
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
2-14 inventory of U.S. Greenhouse Gas Emissions and Sinks: 19SO--2I3Q5
-------
Protocol. Improvements in the technologies associated with
the use of these gases and the introduction of alternative
gases and technologies, however, may help to offset this
anticipated increase in emissions.
ifjn and Ssee! Production (46.2 Tg CO,, Eg,)
Pig iron is the product of combining iron oxide (i.e., iron
ore) and sinter with metallurgical coke in a blast furnace.
The pig iron production process, as well as the thermal
processes used to create sinter and metallurgical coke,
results in emissions of CO2 and CH4. In 2005, iron and steel
production resulted in 1.0 Tg CO2 Eq. of CH4 emissions,
with the majority of the emissions coming from the pig iron
production process. The majority of CO2 emissions from iron
and steel processes come from the production of coke for use
in pig iron creation, with smaller amounts evolving from the
removal of carbon from pig iron used to produce steel. CO2
emissions from iron and steel amounted to 45.2 Tg CO2 Eq.
in 2005. From 1990 to 2005, CO2 and CH4 emissions from
this source decreased by 39.7 Tg CO2 Eq. (47 percent), and
0.4 Tg CO2 Eq. (28 percent) respectively.
Cement Manufat.Ui.f- (45 9 Tg CO- £q.)
Clinker is an intermediate product in the formation of
finished portland and masonry cement. Heating calcium
carbonate (CaCO3) in a cement kiln forms lime and CO2.
The lime combines with other materials to produce clinker,
and the CO2 is released into the atmosphere. From 1990 to
2005, emissions from this source increased by 12.6Tg CO2
Eq. (38 percent).
HCH-/?2 ProdiUtion ^S.D sg CCb to ;
HFC-23 is a by-product of the production of HCFC-
22. Emissions from this source have decreased by 18.4 Tg
CO2 Eq. (53 percent) since 1990. The HFC-23 emission
rate (i.e., the amount of HFC-23 emitted per kilogram of
HCFC-22 manufactured) has declined significantly since
1990, although production has been increasing.
Ammonia Manufactuie and Urea Application (15.3 Tg CU- ttj.;
In the United States, roughly 98 percent of synthetic
ammonia is produced by catalytic steam reforming of natural
gas, and the remainder is produced using naphtha (i.e., a
petroleum fraction) or the electrolysis of brine at chlorine
plants (EPA 1997). The two fossil fuel-based reactions
produce carbon monoxide and hydrogen gas. This carbon
monoxide is transformed into CO2 in the presence of a
catalyst. The CO2 is generally released into the atmosphere,
but some of the CO?, together with ammonia, is used as a
raw material in the production of urea [CO(NH2)2], which
is a type of nitrogenous fertilizer. The carbon in the urea
that is produced and assumed to be subsequently applied
to agricultural land as a nitrogenous fertilizer is ultimately
released into the environment as CO2. Since 1990, CO2
emissions from ammonia manufacture and urea application
have decreased by 3.0 Tg CO2 Eq. (15.5 percent).
Nitric Acid Production (15.7 Tg CO, Eq.)
Nitric acid production is an industrial source of N2O
emissions. Used primarily to make synthetic commercial
fertilizer, this raw material is also a major component in
the production of adipic acid and explosives. Virtually
all of the nitric acid manufactured in the United States
is produced by the oxidation of ammonia, during which
N2O is formed and emitted to the atmosphere. In 2005,
N2O emissions from nitric acid production accounted for
3 percent of U.S. N2O emissions. From 1990 to 2005,
emissions from this source category decreased by 2.2
Tg CO2 Eq. (12 percent) with the trend in the time series
closely tracking the changes in production.
Lime Manufacture {13.7 Tg C0; Eq,;
Lime is used in steel making, construction, flue gas
desulfurization, and water and sewage treatment. It is
manufactured by heating limestone (mostly CaCO3) in a kiln,
creating quicklime (calcium oxide, CaO) and CO2, which
is normally emitted to the atmosphere. From 1990 to 2005,
CO2 emissions from lime manufacture increased by 2.4 Tg
CO2Eq.(21 percent).
Electrical Transmission and Distribution Systems
03.2TgCOpFq.i
The primary use of SF6 is as a dielectric in electrical
transmission and distribution systems. Fugitive emissions
of SF6 occur from leaks in and servicing of substations
and circuit breakers, especially from older equipment. The
gas can also be released during equipment manufacturing,
installation, servicing, and disposal. Estimated emissions
from this source decreased by 13.9 Tg CO2 Eq. (51 percent)
since 1990, primarily due to higher SF6 prices and industrial
efforts to reduce emissions.
Trends in Greenhouse Gas Emissions 2-15
-------
Limestone and Dolomite Use (7.4 Tg C02 E!t|.)
Limestone (CaCO3) and dolomite (CaMg(CO3)2) are
basic raw materials used in a wide variety of industries,
including construction, agriculture, chemical, and metallurgy.
For example, limestone can be used as a purifier in refining
metals. In the case of iron ore, limestone heated in a blast
furnace reacts with impurities in the iron ore and fuels,
generating CO2 as a by-product. Limestone is also used in
flue gas desulfurization systems to remove sulfur dioxide
from the exhaust gases. From 1990 to 2005, emissions from
this source increased by 1.9 Tg CO2 Eq. (34 percent).
Aluminum Production (7.2 Tg C02 Eq.)
Aluminum production results in emissions of CO2, CF4
and C2F6. CO2 is emitted when alumina (aluminum oxide,
A12O3) is reduced to aluminum. The reduction of the alumina
occurs through electrolysis in a molten bath of natural or
synthetic cryolite. The reduction cells contain a carbon lining
that serves as the cathode. Carbon is also contained in the
anode, which can be a carbon mass of paste, coke briquettes,
or prebaked carbon blocks from petroleum coke. During
reduction, some of this carbon is oxidized and released to the
atmosphere as CO2. In 2005, CO2 emissions from aluminum
production amounted to 4.2 Tg CO2 Eq. Since 1990, CO2
emissions from this source have decreased by 2.6 Tg CO2
Eq. (38 percent).
During the production of primary aluminum, CF4 and
C2F6 are emitted as intermittent by-products of the smelting
process. These PFCs are formed when fluorine from the
cryolite bath combines with carbon from the electrolyte
anode. PFC emissions from aluminum production have
decreased by 15.6 Tg CO2 Eq. (84 percent) between 1990 and
2005 due to emission reduction efforts by the industry and
falling domestic aluminum production, although there was a
slight increase in emissions between 2004 and 2005, due to
slightly higher production. In 2005, CF4 and C2F6 emissions
from aluminum production amounted to 3.0 Tg CO2 Eq.
Adipic Acid! Production (6.0 Tg CO? Eq.)
Most adipic acid produced in the United States is used
to manufacture nylon 6,6. Adipic acid is also used to produce
some low-temperature lubricants and to add a "tangy" flavor
to foods. N2O is emitted as a by-product of the chemical
synthesis of adipic acid. In 2005, U.S. adipic acid plants
emitted 1.3 percent of U.S. N2O emissions. Even though
adipic acid production has increased in recent years, by
1998 all three major adipic acid plants in the United States
had voluntarily implemented N2O abatement technology. As
a result, emissions have decreased by 9.2 Tg CO2 Eq. (61
percent) between 1990 and 2005.
Semiconductor Manufacture ,43 Tg C0:; ECJ
The semiconductor industry uses combinations of MFCs,
PFCs, SF6, and other gases for plasma etching and to clean
chemical vapor deposition tools. Emissions from this source
category have increased 1.4 Tg CO2 Eq. (48 percent) since
1990 with the growth in the semiconductor industry and the
rising intricacy of chip designs. However, the growth rate
in emissions has slowed since 1997, and emissions actually
declined between 1999 and 2005. This later reduction is due
to the implementation of PFC emission reduction methods,
such as process optimization.
Soda fish Manufacture and Consumption (4.2 Tg CO? Eq.}
Commercial soda ash (sodium carbonate, Na2CO3)
is used in many consumer products, such as glass, soap
and detergents, paper, textiles, and food. During the
manufacturing of soda ash, some natural sources of sodium
carbonate are heated and transformed into a crude soda ash,
in which CO2 is generated as a by-product. In addition, CO,
is often released when the soda ash is consumed. From 1990
to 2005,emissions from this source increased by 0.1 Tg CO2
Eq. (2 percent).
Petrocnemical Production (4.3 Fg C02 Eq.)
The production process for carbon black results in the
release CO2 emissions to the atmosphere. Carbon black is
a black powder generated by the incomplete combustion of
an aromatic petroleum or coal-based feedstock production.
The majority of carbon black produced in the United States
is consumed by the tire industry, which adds it to rubber to
increase strength and abrasion resistance. Small amounts
of CH4 are also released during the production of five
petrochemicals: carbon black, ethylene, ethylene dichloride,
styrene, and methanol. These production processes resulted
in emissions of 2.9 Tg CO2 Eq. of CO2 and 1.1 Tg CO2 Eq.
of CH4 in 2005. Emissions from this source increased by 0.9
Tg CO2 Eq. (29 percent) between 1990 and 2005.
Magnesium Production and Processing |2.7 Tg C0; Eq.)
Sulfur hexafluoride is also used as a protective cover
gas for the casting of molten magnesium. Emissions from
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 2005
-------
primary magnesium production and magnesium casting
have decreased by 2.8 Tg CO2 Eq. (5 1 percent) since 1990.
This decrease has primarily taken place since 1999, due to a
decline in the quantity of magnesium die cast and the closure
of a U.S. primary magnesium production facility.
Titanium Dioxide ^r-iducuon U 9 lg iC^- i:q }
Titanium dioxide (TiO2) is a metal oxide manufactured
from titanium ore, and is principally used as a pigment. It is
used in white paint and as a pigment in the manufacture of
white paper, foods, and other products. Two processes, the
chloride process and the sulfate process, are used for making
TiO2. CO, is emitted from the chloride process, which uses
petroleum coke and chlorine as raw materials. Since 1990,
emissions from this source increased by 0.6 Tg CO2 Eq.
(47 percent).
ic Acid Production n 4 Tg C0? fcq i
Phosphoric acid is a basic raw material in the production
of phosphate-based fertilizers. The phosphate rock consumed
in the United States originates from both domestic mines,
located primarily in Florida, North Carolina, Idaho, and Utah ,
and foreign mining operations in Morocco. The primary use
of this material is as a basic component of a series of chemical
reactions that lead to the production of phosphoric acid, as
well as the by-products CO2 and phosphogypsum. From 1 990
to 2005, CO2 emissions from phosphoric acid production
decreased by 0.1 Tg CO2 Eq. (9.5 percent).
CO2 is emitted from the production of several ferroalloys.
Ferroalloys are composites of iron and other elements such
as silicon, manganese, and chromium. When incorporated
in alloy steels, ferroalloys are used to alter the material
properties of the steel. From 1990 to 2005, emissions from
this source decreased by 0.8 Tg CO2 Eq. (35 percent).
'•arbon Dioxide Consumption ; 1 'i lo (,02 fcq.)
Many segments of the economy consume CO2, including
food processing, beverage manufacturing, chemical
processing, and a host of industrial and other miscellaneous
applications. CO2 may be produced as a by-product from
the production of certain chemicals (e.g., ammonia), from
select natural gas wells, or by separating it from crude oil
and natural gas. The majority of the CO2 used in these
applications is eventually released to the atmosphere. Since
1990, emissions from CO2 consumption have decreased by
0.1 Tg CO2 Eq. (6.5 percent).
Zinc Production >0.5 Tg C0? En.)
CO2 emissions from the production of zinc in the United
States occur through the primary production of zinc in the
electro-thermic production process, or through the secondary
production of zinc using a Waelz Kiln furnace or the electro-
thermic production process. Both the electro-thermic and
Waelz Kiln processes are emissive due to the use of a
carbon-based material (often metallurgical coke); however,
zinc is also produced in the United States using non-emissive
processes. Due to the closure of an electro-thermic plant in
2003, the only emissive zinc production process remaining
occurs through the recycling of electric-arc-furnace (EAF)
dust in a Waelz Kiln furnace (secondary production) at a
plant in Palmerton, Pennsylvania. From 1990 to 2005, CO2
emissions from zinc production decreased by 0.5 Tg CO2
Eq. (51 percent).
Lead Production 10 3 Tg CO-, tqj
Primary and secondary production of lead in the
United States results in CO2 emissions when carbon-based
materials (often metallurgical coke) are used as a reducing
agent. Primary production involves the direct smelting
of lead concentrates while secondary production largely
occurs through the recycling of lead-acid batteries. In
2005, emissions from primary lead production decreased
by 40 percent due to the closure of one of two primary
lead production plants located in Missouri. Secondary lead
production accounted for 86 percent of total lead production
emissions in 2005. Since 1990, emissions from this source
have decreased by 7.2 percent.
Silicon Casbuie Production ami Consumption (0,2 Tg C0; Eq.i
Small amounts of CH4 are released during the production
of silicon carbide (SiC), a material used as an industrial
abrasive. Additionally, small amounts of CO2 are released
when SiC is consumed for metallurgical and other non-
abrasive purposes (e.g., iron and steel production). Silicon
carbide is made through a reaction of quartz (SiO2) and
carbon (in the form of petroleum coke). CH4 is produced
during this reaction from volatile compounds in the petroleum
coke. CH4 emissions from silicon carbide production have
declined significantly due to a 67 percent decrease in silicon
carbide production since 1990. CO2 emissions from SiC
Trends in Greenhouse Gas Emission
-------
Table 2-9: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq.)
Gas/Source
N20
N20 Product Usage
Total
1990
4.3
4.3
4.3
1995
4.5
4.5
4.5
2000
4.8
4.8
4.8
2001
4.8
4.8
4.8
2002
4.3
4.3
4.3
2003
4.3
4.3
4.3
2004
4.3
4.3
4.3
2005
4.3
4.3
4.3
consumption have fluctuated significantly between years
dependent on consumption, but overall have decreased by
42 percent since 1990.
Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product
of various solvent and other product uses. In the United
States, emissions from N2O Product Usage, the only source
of greenhouse gas emissions from this chapter, accounted
for 4.3 Tg CO2 Eq. of N2O, or less than 0.1 percent of total
U.S. emissions in 2005 (see Table 2-9).
li?0 Product Usagfi (4 3 Tg CO- f:q.|
N2O is used in carrier gases with oxygen to administer
more potent inhalation anesthetics for general anesthesia and
as an anesthetic in various dental and veterinary applications.
As such, it is used to treat short-term pain, for sedation in
minor elective surgeries, and as an induction anesthetic.
The second main use of N2O is as a propellant in pressure
and aerosol products, the largest application being pressure-
packaged whipped cream. In 2005, N2O emissions from
product usage constituted approximately 1 percent of U.S.
N2O emissions. From 1990 to 2005, emissions from this
source category decreased by less than 1 percent.
Agriculture
Agricultural activities contribute directly to emissions of
greenhouse gases through a variety of processes, including
the following source categories: enteric fermentation in
domestic livestock, livestock manure management, rice
cultivation, agricultural soil management, and field burning
of agricultural residues.
In 2005, agricultural activities were responsible for
emissions of 536.3 Tg CO2 Eq., or 7.4 percent of total U.S.
greenhouse gas emissions. CH4 and N2O were the primary
greenhouse gases emitted by agricultural activities. CH4
emissions from enteric fermentation and manure management
represented about 21 percent and 8 percent of total CH4
emissions from anthropogenic activities, respectively, in
2005. Agricultural soil management activities, such as
fertilizer application and other cropping practices, were the
largest source of U.S. N2O emissions in 2005, accounting
for 78 percent. Table 2-10 and Figure 2-11 present emission
estimates for the Agriculture chapter.
Table 2-10: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural Residues
Total
1990
154.4
115.7
30.9
7.1
0.7
375.9
366.9
8.6
0.4
530.3
1995
164.0
120.6
35.1
7.6
0.7
362.7
353.4
9.0
0.4
526.8
2000
160.5
113.5
38.7
7.5
0.8
386.9
376.8
9.6
0.5
547.4
2001
161.0
112.5
40.1
7.6
0.8
399.2
389.0
9.8
0.5
560.3
2002
161.2
112.6
41.1
6.8
0.7
376.3
366.1
9.7
0.4
537.4
2003
161.1
113.0
40.5
6.9
0.8
359.9
350.2
9.3
0.4
521.1
2004
158.7
110.5
39.7
7.6
0.9
348.7
338.8
9.4
0.5
507.4
2005
161.2
112.1
41.3
6.9
0.9
375.1
365.1
9.5
0.5
536.3
Note: Totals may not sum due to independent rounding.
2-18 Inventory of U.S. Greenhouse Gas Hmissions- assd Sinks; 1990-2005
-------
Figure 2-11
2005 Agriculture Chapter Greenhouse Gas Sources
365.1
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
Agriculture
as a Portion of
all Emissions
50 100 150 200
Tg CO, Eq.
nqricullurai SOM (Vkm-ige.T'SHt (JuS fg C0;. Eq.;
N2O is produced naturally in soils through microbial
nitrification and denitrification processes. A number of
anthropogenic activities add to the amount of nitrogen
available to be emitted as N7O by microbial processes.
These activities may add nitrogen to soils either directly or
indirectly. Direct additions occur through the application
of synthetic and organic fertilizers; production of nitrogen-
fixing crops and forages; the application of livestock
manure, crop residues, and sewage sludge; cultivation of
high-organic-content soils; and direct excretion by animals
onto soil. Indirect additions result from volatilization and
subsequent atmospheric deposition, and from leaching and
surface run-off of some of the nitrogen applied to or deposited
on soils as fertilizer, livestock manure, and sewage sludge. In
2005, agricultural soil management accounted for 78 percent
of U.S. N2O emissions. From 1990 to 2005, emissions from
this source decreased by 1.8 Tg CO2 Eq. (0.5 percent);
year-to-year fluctuations are largely a reflection of annual
variations in weather, synthetic fertilizer consumption, and
crop production.
;• i!ir.:r,y F^nT'Oni,-"::!! • : : 'j , 1 ?< G'j '.Qj
During animal digestion, CH4 is produced through the
process of enteric fermentation, in which microbes residing
in animal digestive systems break down food. Ruminants,
which include cattle, buffalo, sheep, and goats, have the
highest CH4 emissions among all animal types because
they have a rumen, or large fore-stomach, in which CH4-
producing fermentation occurs. Non-ruminant domestic
animals, such as pigs and horses, have much lower CH4
emissions. In 2005, enteric fermentation was the source
of about 21 percent of U.S. CH4 emissions, and about
70 percent of the CH4 emissions from agriculture. From
1990 to 2005, emissions from this source decreased by
3.6 Tg CO2 Eq. (3 percent). Generally, emissions have
been decreasing since 1995, mainly due to decreasing
populations of both beef and dairy cattle and improved
feed quality for feedlot cattle.
Manure ivltfnagfcwen- 150.8 ?LJ C-0-. iq.i
Both CH4 and N2O result from manure management.
The decomposition of organic animal waste in an anaerobic
environment produces CH4. The most important factor
affecting the amount of CH4 produced is how the manure
is managed, because certain types of storage and treatment
systems promote an oxygen-free environment. In particular,
liquid systems tend to encourage anaerobic conditions and
produce significant quantities of CH4, whereas solid waste
management approaches produce little or no CH4. Higher
temperatures and moist climatic conditions also promote
CH4 production.
CH4 emissions from manure management were 41.3
Tg CO2 Eq., or about 8 percent of U.S. CH4 emissions in
2005 and 26 percent of the CH4 emissions from agriculture.
From 1990 to 2005, emissions from this source increased
by 10.4 Tg CO2 Eq. (34 percent). The bulk of this increase
was from swine and dairy cow manure, and is attributed to
the shift of the swine and dairy industries towards larger
facilities. Larger swine and dairy farms tend to use liquid
management systems.
N2O is also produced as part of microbial nitrification
and denitrification processes in managed and unmanaged
manure. Emissions from unmanaged manure are accounted
for within the agricultural soil management source category.
Total N2O emissions from managed manure systems in
2005 accounted for 9.5 Tg CO2 Eq., or 2 percent of U.S.
N2O emissions. From 1990 to 2005, emissions from this
source category increased by 0.9 Tg CO2 Eq. (10 percent),
primarily due to increases in swine and poultry populations
over the same period.
Rise Cu!tiv',t:ion 10 y i;t CO.. to ;
Most of the world's rice, and all of the rice in the United
States, is grown on flooded fields. When fields are flooded,
anaerobic conditions develop and the organic matter in the
soil decomposes, releasing CH4 to the atmosphere, primarily
-e Gas Emissions
-------
through the rice plants. In 2005, rice cultivation was the source
of 1 percentof U.S. CH4 emissions, and about 4 percent of U.S.
CH4 emissions from agriculture. Emission estimates from this
source have decreased about 3 percent since 1990.
field Burning of Agriculture Residues (1 4 ig CC2 Eq.)
Burning crop residues releases N2O and CH4. Because
field burning is not a common debris clearing method in the
United States, it was responsible for only 0.2 percent of U.S.
CH4 (0.9 Tg CO2 Eq.) and 0.1 percent of U.S. N2O (0.5 Tg
CO2 Eq.) emissions in 2005. Since 1990,emissions from this
source have increased by approximately 28 percent.
Land Use, Land-Use Crtange, and Forestry
When humans alter the terrestrial biosphere through land
use, changes in land use, and land management practices, they
also alter the background carbon fluxes between biomass,
soils, and the atmosphere. Forest management practices, tree
planting in urban areas, the management of agricultural soils,
and the landfilling of yard trimmings and food scraps have
resulted in a net uptake (sequestration) of carbon in the United
States, which offset about 11 percent of total U.S. greenhouse
gas emissions in 2005. Forests (including vegetation, soils, and
harvested wood) accounted for approximately 85 percent of
total 2005 sequestration, urban trees accounted for 11 percent,
agricultural soils (including mineral and organic soils and the
application of lime) accounted for 3 percent, and landfilled
yard trimmings and food scraps accounted for 1 percent of
the total sequestration in 2005. The net forest sequestration
is a result of net forest growth and increasing forest: area, as
well as a net accumulation of carbon stocks in harvested wood
pools. The net sequestration in urban forests is a result of net
tree growth in these areas. In agricultural soils, mineral soils
account for a net carbon sink that is almost two times larger
than the sum of emissions from organic soils and liming. The
mineral soil C sequestration is largely due to the conversion
of cropland to permanent pastures and hay production, a
reduction in summer fallow areas in semi-arid areas, an
increase in the adoption of conservation tillage practices, and
an increase in the amounts of organic fertilizers (i.e., manure
and sewage sludge) applied to agriculture lands. The landfilled
yard trimmings and food scraps net sequestration is due to the
long-term accumulation of yard trimming carbon and food
scraps in landfills.
Land use, land-use change, and forestry activities in
2005 resulted in a net C sequestration of 828.4 Tg CO2 Eq.
(Table 2-11). This represents an offset of approximately 13.6
percent of total U.S. CO2 emissions, or 11.4 percent of total
greenhouse gas emissions in 2005. Total land use, land-
use change, and forestry net C sequestration increased by
approximately 16 percent between 1990 and 2005, primarily
due to an increase in the rate of net C accumulation in forest
C stocks, particularly in aboveground and belowground tree
biomass. Annual C accumulation in landfilled yard trimmings
and food scraps slowed over this period, while the rate of
annual C accumulation increased in urban trees. Net U.S.
emissions (all sources and sinks) increased by 16.4 percent
from 1990 to 2005.
Table 2-11: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon Stocks and
Liming Emissions
Land Converted to Cropland
Changes in Agricultural Soil Carbon Stocks
Grassland Remaining Grassland
Changes in Agricultural Soil Carbon Stocks
Land Converted to Grassland
Changes in Agricultural Soil Carbon Stocks
Settlements Remaining Settlements
Urban Trees
Other
Landfilled Yard Trimmings and Food Scraps
Total
1990
(598.5)
(598.5)
(28.1)
(28.1)
8.7
8.7
0.1
0.1
(14.6)
(14.6)
(57.5)
(57.5)
(22.8)
(22.8)
(712.8)
1995
(717.5)
(717.5)
(37.4)
(37.4)
7.2
7.2
16.4
16.4
(16.3)
(16.3)
(67.8)
(67.8)
(13.3)
(13.3)
(828.8)
2000 2001 2002 2003 2004 2005
(638.7) (645.7) (688.1) (687.0) (697.3) (698.7)
(638.7) (645.7) (688.1) (687.0) (697.3) (698.7)
(36.5) (38.0) (37.8) (38.3) (39.4) (39.4)
(36.5) (38.0) (37.8) (38.3) (39.4) (39-4)
7.2 7.2 7.2 7.2 7.2 7.2
7.2 7.2 7.2 7.2 7.2 7.2
16.3 16.2 16.2 16.2 16.1 16.1
16.3 16.2 16.2 16.2 16.1 16.1
(16.3) (16.3) (16.3) (16.3) (16.3) (16.3)
(16.3) (16.3) (16.3) (16.3) (16.3) (16.3)
(78.2) (80.2) (82.3) (84.4) (86.4) (88.5)
(78.2) (80.2) (82.3) (84.4) (86.4) (88.5)
(10.5) (10.6) (10.8) (9.3) (8.7) (8.8)
(10.5) (10.6) (10.8) (9.3) (8.7) (8.8)
(756.7) (767.5) (811.9) (811.9) (824.8) (828.5)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
2 20 taventOFtf cf U.S. Greenhouse Gas E.niss nm and Sh
-------
Table 2-12: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
Forest Land Remaining Forest
Land
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
N20 Emissions from Soils
Settlements Remaining
Settlements
N20 Emissions from Soils
Total
1990
7.8
7.1
0.7
0.1
5.1
5.1
13.0
1995
4.5
4.0
0.4
0.2
5.5
5.5
10.1
2000
15.7
14.0
1.4
0.3
5.6
5.6
21.3
2001
6.9
6.0
0.6
0.3
5.5
5.5
12.4
2002
11.8
10.4
1.1
0.3
5.6
5.6
17.4
2003
9.2
8.1
0.8
0.3
5.8
5.8
15.0
2004
8.0
6.9
0.7
0.3
6.0
6.0
13.9
2005
13.1
11.6
1.2
0.3
5.8
5.8
18.9
Note: Totals may not sum due to independent rounding.
Land use, land-use change, and forestry activities in
2005 also resulted in emissions of N2O (7.3 Tg CO2 Eq.)
from application of fertilizers to forests and settlements
and from forest fires, and of CH4 (11.6 Tg CO2 Eq.) from
forest fires, as shown in Table 2-12. Total N2O emissions
from the application of fertilizers to forests and settlements
increased by approximately 19 percent between 1990 and
2005. Emissions of CH4 and N2O from forest fires fluctuate
widely from year to year, but overall increased by 64 percent
between 1990 and 2005.
s-'irew L:i,miir<:.. Forest Und ;T3.^ "'£j CU. tc •
As with other agricultural applications, forests may be
fertilized to stimulate growth rates. The relative magnitude
of the impact of this practice is limited, however, because
forests are generally only fertilized twice during their life
cycles, and applications account for no more than one percent
of total U.S. fertilizer applications annually. In terms of
trends, however, N7O emissions from forest soils for 2005
were more than 5 times higher than in 1990, primarily the
result of an increase in the fertilized area of pine plantations
in the southeastern United States. This source accounts for
approximately 0.1 percent of total U.S. N7O emissions.
Non-CO2 emissions from forest fires are directly related to
the area of forest burned, which varies greatly from year to
year. CH4 from this source (11.6 Tg CO2 Eq.) accounts for
approximately 2 percent of total U.S. CH4 emissions, while
N2O from forest fires (! .2 Tg CO2 Eq.) accounts for about
0.3 percent of U.S. N2O emissions. From 1990 to 2005, CH4
and N2O emissions from Forest Land Remaining Forest Land
increased by 4.5 Tg CO2 Eq. (64 percent) and 0.8 Tg CO2
Eq. (98 percent), respectively.
Settlements Rewnmg Settlf>ir:e5 8 Tg CO, Ea !
Of the fertilizers applied to soils in the United States,
approximately 10 percent are applied to lawns, golf
courses, and other landscaping within settled areas. In
2005, N2O emissions from settlement soils constituted
approximately 1 percent of total U.S. N2O emissions.
There has been an overall increase in emissions of 13
percent since 1990, a result of a general increase in the
applications of synthetic fertilizers.
Waste
Waste management and treatment activities are sources
of greenhouse gas emissions (see Figure 2-12). Landfills
were the largest source of anthropogenic CH4 emissions,
accounting for 24 percent of total U.S. CH4 emissions.4
Additionally, wastewater treatment accounts for 5 percent
of U.S. CH4 emissions, and 2 percent of N2O emissions.
Nitrogen oxides (NOX), carbon monoxide (CO), and non-CH4
volatile organic compounds (NMVOCs) are also emitted by
Figure 2-12
2005 Waste Chapter Greenhouse Gas Sources
Landfills
Wastewater
Treatment
Waste as a Portion
of all Emissions
2.3%
20
40
60 80
Tg CO, Eq.
100
120
140
4 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land
Use. Land-Use Change, and Forestry chapter.
Trends in Greenhoyse Gas Emissions
-------
Table 2-13: Emissions from Waste (Tg C02 Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Wastewater Treatment
Total
1990
185.8
161.0
24.8
6.4
6.4
192.2
1995
182.2
157.1
25.1
6.9
6.9
189.1
2000
158.3
131.9
26.4
7.6
7.6
165.9
2001
153.5
127.6
25.9
7.6
7.6
161.1
2002
156.2
130.4
25.8
7.7
7.7
163.9
2003
160.5
134.9
25.6
7.8
7.8
168.4
2004
157.8
132.1
25.7
7.9
7.9
165.7
2005
157.4
132.0
25.4
8.0
8.0
165.4
Note: Totals may not sum due to independent rounding.
waste activities. A summary of greenhouse gas emissions
from the Waste chapter is presented in Table 2-13.
Overall, in 2005, waste activities generated emissions
of 165.4Tg CO2 Eq.,or2.3 percent of total U.S. greenhouse
gas emissions.
Landfills (132.0 TgC02Eq.)
Landfills are the largest anthropogenic source of CH4
emissions in the United States, accounting for approximately
24 percent of total CH4 emissions in 2005. In an environment
where the oxygen content is low or zero, anaerobic bacteria
decompose organic materials, such as yard waste, household
waste, food waste, and paper, resulting in the generation of
CH4 and biogenic CO2. Factors such as waste composition
and moisture influence the level of CH4 generation. From
1990 to 2005, net CH4 emissions from landfills decreased by
29 Tg CO2 Eq. (18 percent), with small increases occurring
in some interim years. This downward trend in overall
emissions is the result of increases in the amount of landfill
gas collected and combusted,5 which has more than offset
the additional CH4 emissions resulting from an increase in
the amount of municipal solid waste landfilled.
Wastewater Treatment (33.4 TCI C02 Eq.i
Wastewater from domestic sources (i.e., municipal
sewage) and industrial sources is treated to remove soluble
organic matter, suspended solids, pathogenic organisms and
chemical contaminants. Soluble organic matter is generally
removed using biological processes in which microorganisms
consume the organic matter for maintenance and growth.
Microorganisms can biodegrade soluble organic material
in wastewater under aerobic or anaerobic conditions, with
the latter condition producing CH4. During collection and
treatment, wastewater may be accidentally or deliberately
managed under anaerobic conditions. In addition, the sludge
may be further biodegraded under aerobic or anaerobic
conditions. Untreated wastewater may also produce CH4 if
contained under anaerobic conditions. N2O may be generated
during both nitrification and denitrification of the nitrogen
present, usually in the form of urea, ammonia, and proteins. In
2005, wastewater treatment was the source of approximately
5 percent of U.S. CH4 emissions, and 2 percent of N2O
emissions. From 1990 to 2005, CH4 and N2O emissions
from wastewater treatment increased by 0.6 Tg CO2 Eq. (2.5
percent) and 1.6 Tg CO2 Eq. (26 percent), respectively.
2.2. Emissions by Economic Sector
Throughout this report, emission estimates are
grouped into six sectors (i.e., chapters) defined by the
IPCC: Energy; Industrial Processes; Solvent and Other
Product Use; Agriculture; Land Use, Land-Use Change,
and Forestry; and Waste. While it is important to use this
characterization for consistency with UNFCCC reporting
guidelines, it is also useful to allocate emissions into more
commonly used sectoral categories. This section reports
emissions by the following economic sectors: residential,
commercial, industry, transportation, electricity generation,
and agriculture, as well as U.S. territories.
Using this categorization, emissions from electricity
generation accounted for the largest portion (34 percent)
of U.S. greenhouse gas emissions in 2005. Transportation
activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted
for 19 percent of U.S. greenhouse gas emissions in 2005.
In contrast to electricity generation and transportation,
emissions from industry have in general declined over
the past decade. The long-term decline in these emissions
5 The CO2 produced from combusted landfill CH4 at landfills is not counted in national inventories as it is considered part of the natural C cycle of
decomposition.
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
has been due to structural changes in the U.S. economy
(i.e., shifts from a manufacturing-based to a service-based
economy), fuel switching, and efficiency improvements. The
remaining 20 percent of U .S. greenhouse gas emissions were
contributed by the residential, agriculture, and commercial
sectors,plus emissions from U.S. territories. The residential
sector accounted for about 5 percent, and primarily consisted
of CO, emissions from fossil fuel combustion. Activities
related to agriculture accounted for roughly 8 percent of
U.S. emissions; unlike other economic sectors, agricultural
sector emissions were dominated by N2O emissions from
agricultural soil management and CH4 emissions from enteric
fermentation, rather than CO2 from fossil fuel combustion.
The commercial sector accounted for about 6 percent of
emissions, while U.S. territories accounted for 1 percent.
CO2 was also emitted and sequestered by a variety
of activities related to forest management practices, tree
planting in urban areas, the management of agricultural soils,
and landiilling of yard trimmings.
Table 2-14 presents a detailed breakdown of emissions
from each of these economic sectors by source category, as
they are denned in this report. Figure 2-13 shows the trend
in emissions by sector from 1990 to 2005.
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq. and Percent of Total in 2005)
Sector/Source
Electric Power Industry
C02 from Fossil Fuel Combustion
Municipal Solid Waste Combustion
Electrical Transmission and Distribution
Stationary Combustion
Limestone and Dolomite Use
Transportation
C02 from Fossil Fuel Combustion
Substitution of Ozone Depleting
Substances
Mobile Combustion
Non-Energy Use of Fuels
Industry
C02 from Fossil Fuel Combustion
Natural Gas Systems
Non-Energy Use of Fuels
Coal Mining
Iron and Steel Production
Cement Manufacture
Petroleum Systems
HCFC-22 Production
Ammonia Manufacture and Urea
Application
Nitric Acid Production
Lime Manufacture
Aluminum Production
Adipic Acid Production
Substitution of Ozone Depleting
Substances
Abandoned Underground Coal Mines
Stationary Combustion
Semiconductor Manufacture
N20 Product Usage
Soda Ash Manufacture and
Consumption
Petrochemical Production
Limestone and Dolomite Use
Magnesium Production and Processing
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
Carbon Dioxide Consumption
Mobile Combustion
Zinc Production
Lead Production
1990
1,859.7
1,810.2
11.4
27.1
8.1
2.8
1,523.0
1,464.0
+
47.2
11.9
1,470.9
810.3
158.2
99.7
81.9
86.2
33.3
34.4
35.0
19.3
17.8
11.3
25.4
15.2
+
6.0
5.3
2.9
4.3
4.1
3.1
2.8
5.4
1.3
2.2
1.5
1.4
0.9
0.9
0.3
1995
1,989.5
1,939.3
16.2
21.8
8.6
3.7
1,677.2
1,590.2
19.2
56.5
11.3
1,478.4
825.4
161.9
115.9
66.5
74.6
36.8
31.1
27.0
20.5
19.9
12.8
17.5
17.2
1.2
8.2
5.6
5.0
4.5
4.3
3.8
3.7
5.6
1.7
2.0
1.5
1.4
1.0
1.0
0.3
2000
2,329.9
2,283.5
18.3
15.2
10.0
3.0
1,903.2
1,784.4
51.6
55.2
12.1
1,443.3
824.1
156.0
118.0
55.9
66.3
41.2
27.8
29.8
19.6
19.6
13.3
14.7
6.0
3.3
7.3
5.5
6.3
4.8
4.2
4.2
3.0
3.0
1.9
1.9
1.4
1.4
1.1
1.1
0.3
2001
2,292.0
2,245.5
18.7
15.1
9.8
2.9
1,876.4
1,758.2
55.8
51.3
11.1
1,395.4
819.3
154.2
115.0
55.5
59.0
41.4
27.4
19.8
16.7
15.9
12.9
7.8
4.9
3.2
6.7
5.1
4.5
4.8
4.1
3.9
2.9
2.4
1.9
1.5
1.3
0.8
1.2
1.0
0.3
2002
2,300.7
2,254.7
18.9
14.3
9.8
2.9
1,931.2
1,812.3
59.4
48.5
10.9
1,380.0
804.8
154.6
115.2
52.0
55.6
42.9
26.8
19.8
17.8
17.2
12.3
9.7
5.9
3.9
6.1
5.0
4.4
4.3
4.1
4.0
2.9
2.4
2.0
1.4
1.3
1.0
1.2
0.9
0.3
2003
2,330.2
2,284.0
19.9
13.8
10.1
2.4
1,928.2
1,810.5
62.5
45.0
10.1
1,371.8
813.3
152.1
112.8
52.1
54.4
43.1
25.8
12.3
16.2
16.7
13.0
8.3
6.2
4.6
5.9
4.9
4.3
4.3
4.1
3.9
2.4
2.9
2.0
1.3
1.4
1.3
1.3
0.5
0.3
2004
2,363.4
2,315.8
20.5
13.6
10.1
3.4
1,982.6
1,864.5
65.6
42.2
10.2
1,403.3
824.5
147.2
130.9
54.5
52.4
45.6
25.4
15.6
16.9
16.0
13.7
7.1
5.7
5.1
5.8
5.2
4.7
4.3
4.2
4.1
3.4
2.6
2.3
1.4
1.4
1.2
1.3
0.5
0.3
2005
2,429.8
2,381.2
21.3
13.2
10.4
3.7
2,008.9
1,892.8
67.1
38.9
10.2
1,352.8
794.6
139.3
123.4
52.4
46.2
45.9
28.5
16.5
16.3
15.7
13.7
7.2
6.0
5.5
5.5
4.6
4.3
4.3
4.2
4.0
3.7
2.7
1.9
1.4
1.4
1.3
1.3
0.5
0.3
Percent3
33.5%
32.8%
0.3%
0.2%
0.1%
0.1%
27.7%
26.1%
0.9%
0.5%
0.1%
18.6%
10.9%
1.9%
1 .7%
0.7%
0.6%
0.6%
0.4%
0.2%
0.2%
0.2%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
+
+
+
+
+
+
+
+
Trends in Greenhouse Gas Emissions 2-23
-------
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq. and Percent of Total in 2005)
(continued)
Sector/Source
Silicon Carbide Production and
Consumption
Agriculture
Agricultural Soil Management
Enteric Fermentation
Manure Management
C02 from Fossil Fuel Combustion
Forest Land Remaining Forest Land
Rice Cultivation
Field Burning of Agricultural Residues
Mobile Combustion
Stationary Combustion
Commercial
C02 from Fossil Fuel Combustion
Landfills
Substitution of Ozone Depleting
Substances
Wastewater Treatment
Stationary Combustion
Residential
C02 from Fossil Fuel Combustion
Substitution of Ozone Depleting
Substances
Settlement Soil Fertilization
Stationary Combustion
U.S. Territories
C02 from Fossil Fuel Combustion
Total Emissions
Sinks
Forests
Urban Trees
C02 Flux from Agricultural Soils
Landfilled Yard Trimmings and Food
Scraps
1990
0.4
585.3
366.9
115.7
39.5
46.8
7.9
7.1
1.1
0.4
+
417.8
224.3
161.0
+
31.2
1.3
351.3
340.3
0.3
5.1
5.5
34.1
34.1
6,242.0
(712.8)
(598.5)
(57.5)
(33.9)
(22.8)
1995
0.3
589.2
353.4
120.6
44.1
57.3
4.5
7.6
1.0
0.5
+
420.5
226.4
157.1
3.8
32.0
1.3
375.1
356.4
8.1
5.5
5.0
41.1
41.1
6,571.0
(828.8)
(717.5)
(67.8)
(30.1)
(13.3)
2000
0.3
614.4
376.8
113.5
48.3
50.9
15.7
7.5
1.3
0.4
+
415.5
232.3
131.9
16.0
34.0
1.3
393.6
373.5
10.1
5.6
4.4
47.3
47.3
7,147.2
(756.7)
(638.7)
(78.2)
(29.4)
(10.5)
2001
0.2
618.4
389.0
112.5
50.0
50.7
6.9
7.6
1.2
0.4
+
406.6
225.1
127.6
19.1
33.5
1.2
383.6
363.9
10.4
5.5
3.9
54.5
54.5
7,027.0
(767.5)
(645.7)
(80.2)
(30.9)
(10.6)
2002
0.2
602.6
366.1
112.6
50.8
52.9
11.8
6.8
1.1
0.5
+
413.7
225.7
130.4
22.9
33.5
1.2
382.7
362.4
10.7
5.6
4.0
53.6
53.6
7,064.6
(811.9)
(688.1)
(82.3)
(30.7)
(10.8)
2003
0.2
575.7
350.2
113.0
49.8
45.0
9.2
6.9
1.2
0.4
+
433.5
236.6
134.9
27.3
33.4
1.3
404.8
383.8
11.0
5.8
4.2
60.0
60.0
7,104.2
(811.9)
(687.0)
(84.4)
(31.2)
(9.3)
2004
0.2
567.0
338.8
110.5
49.2
51.1
8.0
7.6
1.4
0.4
+
432.6
233.3
132.1
32.3
33.6
1.3
391.6
369.9
11.5
6.0
4.3
63.2
63.2
7,203.7
(824.8)
(697.3)
(86.4)
(32.4)
(8.7)
2005
0.2
595.4
365.1
112.1
50.8
45.5
13.1
6.9
1.4
0.4
+
431.4
225.8
132.0
38.9
33.4
1.2
380.7
358.7
11.9
5.8
4.3
61.5
61.5
7,260.4
(828.5)
(698.7)
(88.5)
(32.4)
(8.8)
Percent3
+
8.2%
5.0%
1 .5%
0.7%
0.6%
0.2%
0.1%
+
+
+
5.9%
3.1%
1.8%
0.5%
0.5%
+
5.2%
4.9%
0.2%
0.1%
0.1%
0.8%
0.8%
100.0%
-11.4%
-9.6%
-1.2%
-0.4%
-0.1%
Net Emissions (Sources and Sinks)
5,529.2
5,742.2
6,390.5 6,259.5 6,252.7 6,292.3 6,378.9 6,431.9 88.6%
Note: Includes all emissions of C02, CH4, I\I20, MFCs, PFCs,
Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq. or 0.05%.
a Percent of total emissions for year 2005.
and SF6. Parentheses indicate negative values or sequestration.
Figure 2-13
Emissions Allocated to Economic Sectors
3,000 -
2,500 -
2,000
' 1,500
1,000-
500
Electricity Generation
Transportation
Industry
Agriculture
Commercial
Residential
o *- evi m -*
CM <\j oj CM
-------
well as other entities, such as power marketers and nonutility
power producers. The majority of electricity generated by
these entities was through the combustion of coal in boilers to
produce high-pressure steam that is passed through a turbine.
Table 2-15 provides a detailed summary of emissions from
electricity generation-related activities.
To distribute electricity emissions among economic
end-use sectors, emissions from the source categories
assigned to the electricity generation sector were allocated
to the residential, commercial, industry, transportation,
and agriculture economic sectors according to retail sales
of electricity (EIA 2006c and Duffield 2006). These three
source categories include CO2 from Fossil Fuel Combustion,
CH4 and N2O from Stationary Combustion, and SF6 from
Electrical Transmission and Distribution Systems.6
When emissions from electricity are distributed among
these sectors, industry accounts for the largest share of
U.S. greenhouse gas emissions (28 percent), followed
closely by emissions from transportation activities, which
also account for 28 percent of total emissions. Emissions
from the residential and commercial sectors also increase
substantially when emissions from electricity are included,
due to their relatively large share of electricity consumption.
In all sectors except agriculture, CO2 accounts for more than
80 percent of greenhouse gas emissions, primarily from the
combustion of fossil fuels.
Table 2-16 presents a detailed breakdown of emissions
from each of these economic sectors, with emissions from
electricity generation distributed to them. Figure 2-14 shows
the trend in these emissions by sector from 1990 to 2005.
Figure 2-14
Emissions with Electricity Distributed to Economic Sectors
2,500
2,000
1,500
1,000
500-
o-1
T-esjc?*3-mtor-cocn
a)0>0>oi0>o>a)O)a)
Industrial
Transportation
-Residential
-Commercial
Agriculture
§ | | | |
M M CM CSJ CNJ
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Fuel Type or Source
C02
C02 from Fossil Fuel Combustion
Coal
Natural Gas
Petroleum
Geothermal
Municipal Solid Waste
Combustion
Limestone and Dolomite Use
CH4
Stationary Combustion*
N20
Stationary Combustion*
Municipal Solid Waste
Combustion
SF6
Electrical Transmission and
Distribution
Total
1990
1,823.9
1,810.2
1,531.3
176.8
101.8
0.4
10.9
2.8
0.6
0.6
8.0
7.6
0.5
27.1
27.1
1,859.7
1995
1,958.7
1,939.3
1,648.7
229.5
60.7
0.3
15.7
3.7
0.6
0.6
8.5
8.0
0.5
21.8
21.8
1,989.5
2000
2,304.3
2,283.5
1,909.6
282.0
91.5
0.4
17.9
3.0
0.7
0.7
9.7
9.3
0.4
15.2
15.2
2,329.9
2001
2,266.7
2,245.5
1,852.3
290.8
102.0
0.4
18.3
2.9
0.7
0.7
9.5
9.1
0.4
15.1
15.1
2,292.0
2002
2,276.2
2,254.7
1,868.3
307.0
79.1
0.4
18.5
2.9
0.7
0.7
9.5
9.1
0.4
14.3
14.3
2,300.7
2003
2,305.8
2,284.0
1,906.2
279.3
98.1
0.4
19.5
2.4
0.7
0.7
9.8
9.4
0.4
13.8
13.8
2,330.2
2004
2,339.2
2,315.8
1,917.6
297.7
100.1
0.4
20.1
3.4
0.7
0.7
9.8
9.4
0.4
13.6
13.6
2,363.4
2005
2,405.8
2,381.2
1,958.4
320.1
102.3
0.4
20.9
3.7
0.7
0.7
10.0
9.6
0.4
13.2
13.2
2,429.8
Note: Totals may not sum due to independent rounding.
* Includes only stationary combustion emissions related to the generation of electricity.
6 Emissions were not distributed to U.S. territories, since the electricity generation sector only includes emissions related to the generation of electricity
in the 50 states and the District of Columbia.
Trends in Greenhouse Gas Emissions 2-25
-------
Table 2-16: U.S Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related Emissions
Distributed (Tg C02 Eq. and Percent of Total in 2005)
Sector/Gas
Industry
Direct Emissions
C02
CH4
N20
HFCs, PFCs, and SF6
Electricity-Related
C02
CH4
N20
SF6
Transportation
Direct Emissions
C02
CH4
N20
MFCs"
Electricity-Related
C02
CH4
N20
SF6
Commercial
Direct Emissions
C02
CH4
N20
HFCs
Electricity-Related
C02
CH4
N20
SF6
Residential
Direct Emissions
C02
CH4
N20
HFCs
Electricity-Related
C02
CH4
N20
SF6
Agriculture
Direct Emissions
C02
CH4
N20
Electricity-Related
C02
CH4
N20
SF6
U.S. Territories
Total
1990
2,111.1
1,470.9
1,082.8
284.9
41.3
61.9
640.2
627.9
0.2
2.8
9.3
1,526.1
1,523.0
1,475.8
4.5
42.7
+
3.1
3.1
+
+
+
967.2
417.8
224.3
186.7
6.8
+
549.5
538.9
0.2
2.4
8.0
956.9
351.3
340.3
4.4
6.2
0.3
605.7
594.0
0.2
2.6
8.8
646.5
585.3
46.8
161.6
377.0
61.2
60.0
+
0.3
0.9
34.1
6,242.0
1995
2,141.5
1,478.4
1,109.5
272.5
45.8
50.6
663.1
652.8
0.2
2.8
7.3
1,680.3
1,677.2
1,601.5
4.1
52.5
19.2
3.1
3.1
+
+
+
1,019.8
420.5
226.4
183.1
7.2
3.8
599.3
590.0
0.2
2.6
6.6
1,030.6
375.1
356.4
4.0
6.5
8.1
655.5
645.4
0.2
2.8
7.2
657.6
589.2
57.3
168.2
363.7
68.5
67.4
+
0.3
0.8
41.1
6,571.0
2000
2,185.0
1,443.3
1,105.9
251.8
34.6
50.9
741.7
733.6
0.2
3.1
4.8
1,9067
1,903.2
1,796.5
3.2
52.0
51.6
3.5
3.5
+
+
+
1,167.4
415.5
232.3
159.2
7.9
16.0
751.9
743.7
0.2
3.1
4.9
1,167.0
393.6
373.5
3.5
6.5
10.1
773.4
764.9
0.2
3.2
5.0
673.9
614.4
50.9
174.6
388.9
59.4
58.8
+
0.2
0.4
47.3
7,147.2
2001
2,067.1
1,395.4
1,084.2
248.1
29.7
33.4
671.6
664.2
0.2
2.8
4.4
1,879.8
1,876.4
1,769.3
2.9
48.4
55.8
3.4
3.3
+
+
+
1,176.8
406.6
225.1
154.4
7.9
19.1
770.2
761.7
0.2
3.2
5.1
1,160.3
383.6
363.9
3.1
6.3
10.4
776.6
768.1
0.2
3.2
5.1
688.5
618.4
50.7
167.2
400.5
70.1
69.3
+
0.3
0.5
54.5
7,027.0
2002
2,046.6
1,380.0
1,069.2
243.8
31.4
35.6
666.6
659.5
0.2
2.8
4.2
1,934.7
1,931.2
1,823.3
2.8
45.8
59.4
3.5
3.4
+
+
+
1,177.0
413.7
225.7
157.1
8.0
22.9
763.3
755.2
0.2
3.2
4.8
1,184.3
382.7
362.4
3.1
6.5
10.7
801.5
793.0
0.2
3.3
5.0
668.4
602.6
52.9
171.8
377.9
65.8
65.1
+
0.3
0.4
53.6
7,064.6
2003
2,061.4
1,371.8
1,072.5
240.2
31.2
27.9
689.6
682.4
0.2
2.9
4.1
1,932.5
1,928.2
1,820.6
2.6
42.4
62.5
4.3
4.3
+
+
+
1,196.2
433.5
236,6
161.5
8.2
27.3
762.7
754.8
0.2
3.2
4.5
1,216.2
404.8
383.8
3.3
6.7
11.0
811.4
802.9
0.2
3.4
4.8
637.9
575.7
45.0
169.3
361.4
62.1
61.5
+
0.3
0.4
60.0
7,104.2
2004
2,090.1
1,403.3
1,104.9
237.4
30.3
30.8
686.7
679.7
0.2
2.9
4.0
1 987.1
1,982.6
1,874.7
2.5
39.8
65.7
4.5
4.4
+
+
+
1,214.1
432.6
233.3
158.7
8.3
32.3
781.5
773.5
0.2
3.2
4.5
1,214.2
391.6
369.9
3.3
6.9
11.5
822.6
814.2
0.2
3.4
4.7
635.0
567.0
51.1
165.8
350.1
68.0
67.4
+
0.3
0.4
63.2
7,203.7
2005
2,039.2
1,352.8
1,061.2
229.8
29.9
32.0
686.5
679.7
0.2
2.8
3.7
2,014.2
2,008.9
1,903.0
2.3
36.5
67.1
5.3
5.2
+
+
+
1,238.5
431.4
225.8
158.3
8.4
38.9
807.1
799.2
0.2
3.3
4.4
1,248.0
380.7
358.7
3.4
6.7
11.9
867.3
858.7
0.3
3.6
4.7
659.1
595.4
45.5
172.9
377.0
63.7
63.0
+
0.3
0.3
61.5
7,260.4
Percent"
28.1%
18.6%
14.6%
3.2%
0.4%
0.4%
9.5%
9.4%
+
+
0.1%
27.7%
27.7%
26.2%
+
0.5%
0.9%
0.1%
0.1%
+
+
+
17.1%
5.9%
3.1%
2.2%
0.1%
0.5%
11.1%
11.0%
+
+
0.1%
17.2%
5.2%
4.9%
+
0.1%
0.2%
11.9%
11.8%
+
+
0.1%
9.1%
8.2%
0.6%
2.4%
5.2%
0.9%
0.9%
+
+
+
0.8%
100.0%
Note: Emissions from electricity generation are allocated based on aggregate electricity consumption in each end-use sector.
Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
a Percent of total emissions for year 2005.
b Includes primarily HFC-134a.
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19(10-2005
-------
Transportation
Transportation activities accounted for 28 percent
of U.S. greenhouse gas emissions in 2005. Table 2-17
provides a detailed summary of greenhouse gas emissions
from transportation-related activities. Total emissions in
Table 2-17 differ slightly from those shown in Table 2-16
primarily because the table below excludes a few minor
non-transportation mobile sources, such as construction and
industrial equipment.
From 1990 to 2005, transportation emissions rose by
32 percent due, in part, to increased demand for travel and
the stagnation of fuel efficiency across the U.S. vehicle
fleet. Since the 1970s, the number of highway vehicles
registered in the United States has increased faster than
the overall population, according to the Federal Highway
Administration (FHWA). Likewise, the number of miles
driven (up 21 percent from 1990 to 2005) and the gallons
of gasoline consumed each year in the United States have
increased steadily since the 1980s, according to the FHWA
and Energy Information Administration, respectively. These
increases in motor vehicle usage are the result of a confluence
of factors including population growth, economic growth,
urban sprawl, low fuel prices, and increasing popularity of
sport utility vehicles and other light-duty trucks that tend
to have lower fuel efficiency. A similar set of social and
economic trends has led to a significant increase in air travel
Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Vehicle Type
C02
Passenger Cars
Light-Duty Trucks
Other Trucks
Buses
Aircraft3
Ships and Boats
Locomotives
Other"
International Bunker Fuels0
CH4
Passenger Cars
Light-Duty Trucks
Other Trucks and Buses
Aircraft
Ships and Boats
Locomotives
Motorcycles
International Bunker Fuels0
N20
Passenger Cars
Light-Duty Trucks
Other Trucks and Buses
Aircraft
Ships and Boats
Locomotives
Motorcycles
International Bunker Fuels0
MFCs
Mobile Air Conditioners'1
Comfort Cooling in Buses
and Trains
Refrigerated Transport
Total
1990
1,478.8
615.1
314.0
227.0
8.3
180.0
46.8
38.1
49.6
113.7
4.5
2.6
1.4
0.2
0.2
0.1
0.1
+
0,2
42.7
25.4
14.1
0.8
1.7
0.4
0.3
+
1.0
+
+
+
+
1,526.1
1995
1,604.6
599.6
401.6
270.9
9.0
174.6
55.4
42.2
51.3
100.6
4.1
2.1
1.4
0.2
0.1
0.1
0.1
+
0.1
52.5
26.9
22.1
1.0
1.7
0.4
0.3
+
0.9
19.2
16.8
+
2.3
1,680.4
2000
1,799.9
632.0
459.2
343.2
11.0
196.4
63.8
45.1
49.1
101.1
3.2
1.6
1.1
0.1
0.2
0.1
0.1
+
0.1
52.0
24.7
23.3
1.2
1.9
0.5
0.3
+
0.9
51.6
41.6
0.2
9.8
1,906.7
2001
1,772.6
634.7
462.7
343.3
10.1
186.6
43.0
45.1
47.2
97.6
2.9
1.5
1.0
0.1
0.1
0.1
0.1
+
0.1
48.4
23.2
21.4
1.3
1.8
0.3
0.3
+
0.9
55.8
44.9
0.2
10.8
1,879.7
2002
1,826.7
649.6
476.6
358.1
9.7
178.0
60.6
44.9
49.2
89. 1
2.8
1.4
1.0
0.1
0.1
0.1
0.1
+
0.1
45.8
21.9
20.1
1.3
1.7
0.5
0.3
+
0.8
59.4
47.7
0.2
11.5
1,934.6
2003
1,824.9
629.1
510.7
355.4
10.6
174.7
53.3
46.6
44.4
83.7
2.6
1.3
0.9
0.1
0.1
0.1
0.1
+
0.1
42.4
20.3
18.3
1.3
1.7
0.4
0.3
+
0.8
62.5
50.0
0.2
12.3
1,932.4
2004
1,879.1
628.7
533.6
368.5
14.9
179.7
61.1
49.2
43.5
97.2
2.5
1.2
0.8
0.1
0.1
0.1
0.1
+
0.1
39.7
18.8
17.0
1.3
1.7
0.5
0.3
+
0.9
65.6
52.2
0.3
13.1
1,986.9
2005
1,908.1
614.9
550.3
384.6
15.1
186.1
63.7
50.3
43.1
97.2
2.3
1.1
0.8
0.1
0.1
0.1
0.1
+
0.1
36.5
17.0
15.6
1.2
1.8
0.5
0.4
+
0.9
67.1
53.1
0.3
13.6
2,014.0
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
a Aircraft emissions consist of emissions from all jet fuel (less bunker fuels) and aviation gas consumption.
b "Other" C02 emissions include motorcycles, pipelines, and lubricants.
c Emissions from International Bunker Fuels include emissions from both civilian and military activities, but are not included in totals.
d Includes primarily HFC-134a.
Trends in Greenhouse Gas Emissions 2-27
-------
and freight transportation by both air and road modes during O *5 InfiSJiTPPt GrPPflhOU^P
the time series. ». . . mn »i/ii aiKiuirm
Emissions (CO, NOX, NMVOCs,
Almost all of the energy consumed for transportation rf Ofl \
was supplied by petroleum-based products, with nearly l>
two-thirds being related to gasoline consumption in _. . . „ , TTXT__._,,-v7
The reporting requirements of the UNFCCC'request
automobiles and other highway vehicles. Other fuel uses, . ,. . .,,.,.
that information be provided on indirect greenhouse gases,
especially diesel fuel for freight trucks and jet fuel for ,.,-,, ^n XT^ ^,*r^^ _, ~^ ^
F 6 J which include CO, NOX, NMVOCs, and SO2- These gases
aircraft, accounted for the remainder. The primary driver , , ,. , , , . , . ,. .
do not have a direct global warming effect, but indirectly
of transportation-related emissions was CO? from fossil ... ..... , . _
aftect terrestrial radiation absorption by influencing the
fuel combustion, which increased by 29 percent from r , , . , . , .
formation and destruction of troposphenc and stratospheric
1990 to 2005. This rise in CO? emissions, combined with . „ _.. . ... , ,
ozone, or, in the case of SO2, by affecting the absorptive
an increase of 67.1 Tg CO7 Eq. in HFC emissions over the , . . .. . , .,,..,,
characteristics of the atmosphere. Additionally, some of
same period, led to an increase in overall emissions from , .,,,., , - ,
these gases may react with other chemical compounds in the
transportation activities of 32 percent.
Box 2-2: Methodology for Aggregating Emissions by Economic Sector
In order to aggregate emissions by economic sector, source category emission estimates were generated according to the methodologies
outlined in the appropriate sections of this report. Those emissions were then simply reallocated into economic sectors. In most cases,
the IPCC subcategories distinctly fit into an apparent economic sector category. Several exceptions exist, and the methodologies used to
disaggregate these subcategories are described below:
• Agricultural C02 Emissions from Fossil Fuel Combustion, and Non-C02 Emissions from Stationary and Mobile Combustion.
Emissions from on-farm energy use were accounted for in the Energy chapter as part of the industrial and transportation end-use
sectors. To calculate agricultural emissions related to fossil fuel combustion, energy consumption estimates were obtained from
economic survey data from the U.S. Department of Agriculture (Duffield 2006) and fuel sales data (EIA1991 through 2005). To
avoid double-counting, emission estimates of C02 from fossil fuel combustion and non-C02 from stationary and mobile combustion
were subtracted from the industrial economic sector, although some of these fuels may have been originally accounted for under
the transportation end-use sector.
Landfills and Wastewater Treatment. CH4 emissions from landfills and CH4 and N20 emissions from wastewater treatment were
allocated to the commercial sector.
Municipal Solid Waste Combustion. C02 and N20 emissions from waste combustion were allocated completely to the electricity
generation sector since nearly all waste combustion occurs in waste-to-energy facilities.
Limestone and Dolomite Use. C02 emissions from limestone and dolomite use are allocated to the electricity generation (50
percent) and industrial (50 percent) sectors, because 50 percent of the total emissions for this source are due to flue gas
desulfurization.
• Substitution of Ozone Depleting Substances. All greenhouse gas emissions resulting from the substitution of ozone depleting
substances were placed in the industrial economic sector, with the exception of emissions from domestic, commercial, and mobile
and transport refrigeration/air-conditioning systems, which were placed in the residential, commercial, and transportation sectors,
respectively. Emissions from non-MDI aerosols were attributed to the residential economic sector.
• Settlement Soil Fertilization, Forest Soil Fertilization. Emissions from settlement soil fertilization were allocated to the residential
economic sector; forest soil fertilization was allocated to the agriculture economic sector.
• Forest Fires. N20 and CH4 emissions from forest fires were allocated to the agriculture economic sector.
' See .
2-28 Inventory of U.S. iireenhouse Gas f missions and Sinks: 19HO-2905
-------
atmosphere to form compounds that are greenhouse gases.
Carbon monoxide is produced when carbon-containing
fuels are combusted incompletely. Nitrogen oxides (i.e.,
NO and NO2) are created by lightning, fires, fossil fuel
combustion, and in the stratosphere from N2O. Non-CH4
volatile organic compounds —(which include hundreds of
organic compounds that participate in atmospheric chemical
reactions (i.e.,propane, butane, xylene, toluene,ethane, and
many others) —are emitted primarily from transportation,
industrial processes, and non-industrial consumption of
organic solvents. In the United States, SO2 is primarily
emitted from coal combustion for electric power generation
and the metals industry. Sulfur-containing compounds emitted
into the atmosphere tend to exert a negative radiative forcing
(i.e., cooling) and therefore are discussed separately.
One important indirect climate change effect of
NMVOCs and NOX is their role as precursors for tropospheric
Box 2-3: Sources and Effects of Sulfur Dioxide
ozone formation. They can also alter the atmospheric
lifetimes of other greenhouse gases. Another example
of indirect greenhouse gas formation into greenhouse
gases is CO's interaction with the hydroxyl radical—the
major atmospheric sink for CH4 emissions—to form CO2.
Therefore, increased atmospheric concentrations of CO
limit the number of hydroxyl molecules (OH) available to
destroy CH4.
Since 1970, the United States has published estimates
of annual emissions of CO, NOX, NMVOCs, and SO2
(EPA 2005),8 which are regulated under the Clean Air
Act. Table 2-18 shows that fuel combustion accounts for
the majority of emissions of these indirect greenhouse
gases. Industrial processes —such as the manufacture
of chemical and allied products, metals processing, and
industrial uses of solvents —are also significant sources
of CO, NOX, and NMVOCs.
Sulfur dioxide (S02) emitted into the atmosphere through natural and anthropogenic processes affects the earth's radiative budget
through its photochemical transformation into sulfate aerosols that can (1) scatter radiation from the sun back to space, thereby reducing
the radiation reaching the earth's surface; (2) affect cloud formation; and (3) affect atmospheric chemical composition (e.g., by providing
surfaces for heterogeneous chemical reactions). The indirect effect of sulfur-derived aerosols on radiative forcing can be considered in
two parts. The first indirect effect is the aerosols' tendency to decrease water droplet size and increase water droplet concentration in the
atmosphere. The second indirect effect is the tendency of the reduction in cloud droplet size to affect precipitation by increasing cloud lifetime
and thickness. Although still highly uncertain, the radiative forcing estimates from both the first and the second indirect effect are believed
to be negative, as is the combined radiative forcing of the two (IPCC 2001). However, because S02 is short-lived and unevenly distributed
in the atmosphere, its radiative forcing impacts are highly uncertain.
Sulfur dioxide is also a major contributor to the formation of regional haze, which can cause significant increases in acute and chronic
respiratory diseases. Once S02 is emitted, it is chemically transformed in the atmosphere and returns to the earth as the primary source of
acid rain. Because of these harmful effects, the United States has regulated S02 emissions in the Clean Air Act.
Electricity generation is the largest anthropogenic source of S02 emissions in the United States, accounting for 88 percent in
2005. Coal combustion contributes nearly all of those emissions (approximately 92 percent). Sulfur dioxide emissions have decreased
in recent years, primarily as a result of electric power generators switching from high-sulfur to low-sulfur coal and installing flue gas
desulfurization equipment.
* NOX and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken from EPA (2005).
Trends in Greenhouse Gas Emissions 2 29
-------
Table 2-18: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
NOX
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Oil and Gas Activities
Municipal Solid Waste Combustion
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Municipal Solid Waste Combustion
Agricultural Burning
Oil and Gas Activities
Waste
Solvent Use
NMVOCs
Mobile Fossil Fuel Combustion
Solvent Use
Industrial Processes
Stationary Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
Waste
Agricultural Burning
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
Waste
Solvent Use
Agricultural Burning
1990
21,645
10,920
9,883
591
139
82
28
1
0
130,581
119,480
5,000
4,125
978
691
302
1
5
20,930
10,932
5,216
2,422
912
554
222
673
NA
20,935
18,407
1,307
793
390
38
0
0
NA
1995
21,272
10,622
9,821
607
100
88
29
3
1
109,157
97,755
5,383
3,959
1,073
663
316
2
5
19,520
8,745
5,609
2,642
973
582
237
731
NA
16,891
14,724
1,117
672
335
42
1
1
NA
2000
19,203
10,310
8,002
626
111
114
35
3
2
92,897
83,680
4,340
2,217
1,670
792
146
8
46
15,228
7,230
4,384
1,773
1,077
389
257
119
NA
14,829
12,848
1,031
632
286
29
1
1
NA
2001
18,410
9,819
7,667
656
113
114
35
3
2
89,333
79,972
4,377
2,339
1,672
774
147
8
45
15,048
6,872
4,547
1,769
1,080
400
258
122
NA
14,452
12,461
1,047
624
289
30
1
1
NA
2002
18,141
10,319
6,837
532
316
97
33
5
2
86,796
77,382
5,224
1,710
1,440
709
323
7
1
14,968
6,608
3,911
1,811
1,733
546
244
116
NA
13,541
11,852
752
681
233
23
1
0
NA
2003
17,327
9,911
6,428
533
317
98
34
5
2
84,370
74,756
5,292
1,730
1,457
800
327
7
1
14,672
6,302
3,916
1,813
1,734
547
244
116
NA
13,648
12,002
759
628
235
23
1
0
NA
2004
16,466
9,520
5,952
534
317
98
39
5
2
82,073
72,269
5,361
1,751
1,475
879
331
7
1
14,391
6,011
3,921
1,815
1,735
547
244
116
NA
13,328
11,721
766
579
238
23
1
0
NA
2005
15,965
9,145
5,824
535
318
98
39
5
2
79,811
69,915
5,431
1,772
1,493
858
335
7
1
14,123
5,734
3,926
1,818
1,736
548
245
116
NA
13,271
11,698
774
535
240
23
1
0
NA
Source: (EPA 2005) except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
2-30 Inventory of U.S. Greenhouse Gas (Emissions and Sinks: 1990-2005
-------
3. Energy
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting
for 85 percent of total emissions on a carbon (C) equivalent basis in 2005. This included 98, 38, and 11 percent
of the nation's carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions, respectively. Energy-
related CO2 emissions alone constituted 82 percent of national emissions from all sources on a C equivalent basis, while
the non-CO7 emissions from energy-related activities represented a much smaller portion of total national emissions (4
percent collectively).
Emissions from fossil fuel combustion comprise the vast majority of energy-related emissions, with CO2 being the
primary gas emitted (see Figure 3-1). Globally, approximately 27,044 Tg of CO2 were added to the atmosphere through the
combustion of fossil fuels in 2004, of which the United States accounted for about 22 percent.1 Due to the relative importance
of fossil fuel combustion-related CO2 emissions, they are considered separately, and in more detail than other energy-related
emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N2O, as well as indirect greenhouse gases such as
nitrogen oxides (NOX), carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs). Mobile fossil fuel
combustion was the second largest source of N2O emissions in the United States, and overall energy-related activities were
collectively the largest source of these indirect greenhouse gas emissions.
Energy-related activities other than fuel combustion,
such as the production, transmission, storage, and distribution
of fossil fuels, also emit greenhouse gases. These emissions
consist primarily of fugitive CH4 from natural gas systems,
petroleum systems, and coal mining. Smaller quantities of
CO2, CO, NMVOCs, and NOX are also emitted.
The combustion ofbiomass and biomass-based fuels also
emits greenhouse gases. CO2 emissions from these activities,
however, are not included in national emissions totals because
biomass fuels are of biogenic origin. It is assumed that the C
released during the consumption of biomass is recycled as
U.S. forests and crops regenerate, causing no net addition
of CO2 to the atmosphere. The net impacts of land-use and
forestry activities on the C cycle are accounted for within the
Land Use, Land-Use Change, and Forestry chapter. Emissions
of other greenhouse gases from the combustion of biomass
Figure 3-1
2005 Energy Chapter Greenhouse Gas Sources
5,751.2
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion
Municipal Solid Waste mm
Combustion •
Abandoned Underground m
Coal Mines 1
Energy as a Portion
of all Emissions
25
50 75 100
Tg COZ Eq.
125 150
' Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy Annual 2004
EIA (2006).
Energy 3-1
-------
Figure 3-2
2005 U.S. Fossil Carbon Flows (Tg C02 Eq.)
Fossil Fuel
Energy Exports
261
NEU Emissions
22
Natural Gas Emissions
1,191
NEU Emissions 124
Non-Energy Use
Carbon Sequestered
2M
Fossil Fuel
Combustion Residual
(Not Oxidized Fraction)
53
Note: Totals may not sum due to independent rounding.
Other 183
The "Balancing Item" above accounts for the statistical imbalances
and unknowns in the reported data sets combined here.
NEU - Non-Energy Use
NG - Natural Gas
Table 3-1: C02, CH4, and N20 Emissions from Energy (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Municipal Solid Waste Combustion
International Bunker Fuels*
Wood Biomass and Ethanol
Consumption*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
International Bunker Fuels*
N20
Mobile Combustion
Stationary Combustion
Municipal Solid Waste Combustion
International Bunker Fuels*
Total
1990
4,886.1
4,724.1
117.3
33.7
10.9
113.7
219.3
259.6
124.5
81.9
34.4
8.0
6.0
4.7
0.2
56.5
43.7
12.3
0.5
1.0
5,202.2
1995
5,212.8
5,030.0
133.2
33.8
15.7
100.6
236.8
246.1
128.1
66.5
31.1
7.8
8.2
4.3
0.1
66.9
53.7
12.8
0.5
0.9
5,525.8
2000
5,773.2
5,584.9
141.0
29.4
17.9
101.1
228.3
228.5
126.6
55.9
27.8
7.4
7.3
3.5
0.7
67.6
53.2
14.0
0.4
0.9
6,069.2
2001
5,690.2
5,511.7
131.4
28.8
18.3
97.6
203.2
225.0
125.4
55.5
27.4
6.8
6.7
3.2
0.1
63.6
49.7
13.5
0.4
0.9
5,978.9
2002
5,740.7
5,557.2
135.3
29.6
18.5
89.1
204.4
219.7
125.0
52.0
26.8
6.8
6.1
3.1
0.1
60.9
47.1
13.4
0.4
0.8
6,021.4
2003
5,803.8
5,624.5
131.3
28.4
19.5
83.7
209.6
217.4
123.7
52.1
25.8
7.0
5.9
2.9
0.7
57.9
43.8
13.7
0.4
0.8
6,079.1
2004
5,911.5
5,713.0
150.2
28.2
20.1
97.2
224.8
214.6
119.0
54.5
25.4
7.1
5.8
2.8
0.7
55.5
41.2
13.9
0.4
0.9
6,181.7
2005
5,942.7
5,751.2
142.4
28.2
20.9
97.2
206.5
207.1
111.1
52.4
28.5
6.9
5.5
2.6
0.7
52.2
38.0
13.8
0.4
0.9
6,201.9
*These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to independent rounding.
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 3-2: C02, CH4, and N20 Emissions from Energy (Gg)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Municipal Solid Waste Combustion
International Bunker Fuels *
Wood Biomass and Ethanol
Consumption*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal
Mines
Mobile Combustion
International Bunker Fuels *
N20
Mobile Combustion
Stationary Combustion
Municipal Solid Waste Combustion
International Bunker Fuels *
1990
4,886,134
4,724,149
117,307
33,729
10,950
113,683
219,341
12,360
5,927
3,899
1,640
382
286
226
8
182
141
40
2
3
1995
5,212,782
5,030,036
133,228
33,807
15,712
100,627
236,775
11,718
6,101
3,165
1,482
373
391
207
6
216
173
41
1
3
2000
5,773,163
5,584,880
141,005
29,390
17,889
101,125
228,308
10,879
6,027
2,662
1,325
351
349
165
6
218
172
45
1
3
2001
5,690,231
5,511,719
131,375
28,793
18,344
97,563
203,163
10,714
5,971
2,644
1,303
324
318
154
5
205
160
44
1
3
2002
5,740,712
5,557,242
135,327
29,630
18,513
89,101
204,351
10,463
5,951
2,476
1,275
324
292
146
4
197
152
43
1
3
2003
5,803,770
5,624,500
131,334
28,445
19,490
83,690
209,603
10,352
5,891
2,480
1,229
334
282
136
4
187
141
44
1
2
2004
5,911,530
5,713,018
150,208
28,190
20,115
97,177
224,825
10,221
5,669
2,597
1,209
340
275
131
5
179
133
45
1
3
2005
5,942,665
5,751,200
142,368
28,185
20,912
97,191
206,475
9,862
5,292
2,494
1,357
330
263
125
5
168
123
45
1
3
"These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to independent rounding.
and biomass-based fuels are included in national totals under
stationary and mobile combustion.
Table 3-1 summarizes emissions from the Energy sector
in units of teragrams of CO2 equivalents (Tg CO2 Eq.), while
unweighted gas emissions in gigagrams (Gg) are provided in
Table 3-2. Overall, emissions due to energy-related activities
were 6,201.9 Tg CO2 Eq. in 2005, an increase of 19 percent
since 1990.
3.1. Carbon Dioxide Emissions from
Fossil Fuel Combustion (IPCC Source
Category 1A)
CO2 emissions from fossil fuel combustion in 2005
increased by 0.7 percent from the previous year. This
small increase is primarily a result of the restraint on fuel
consumption caused by rising fuel prices, primarily in the
transportation sector. Additionally, warmer winter conditions
in 2005 decreased the demand for heating fuels. In contrast,
warmer summer conditions in 2005 increased the demand
for electricity. In 2005, CO2 emissions from fossil fuel
combustion were 5,751.2 Tg CO2 Eq., or 22 percent above
emissions in 1990 (see Table 3-3).2
Trends in CO2 emissions from fossil fuel combustion
are influenced by many long-term and short-term factors. On
a year-to-year basis, the overall demand for fossil fuels in
the United States and other countries generally fluctuates in
response to changes in general economic conditions, energy
prices, weather, and the availability of non-fossil alternatives.
For example, in a year with increased consumption of
goods and services, low fuel prices, severe summer and
winter weather conditions, nuclear plant closures, and lower
precipitation feeding hydroelectric dams, there would likely
be proportionally greater fossil fuel consumption than a
year with poor economic performance, high fuel prices,
mild temperatures, and increased output from nuclear and
hydroelectric plants.
Longer-term changes in energy consumption patterns,
however, tend to be more a function of aggregate societal
trends that affect the scale of consumption (e .g., population,
number of cars, and size of houses), the efficiency with which
energy is used in equipment (e.g., cars, power plants, steel
mills, and light bulbs), and social planning and consumer
behavior (e.g., walking, bicycling, or telecommuting to work
instead of driving).
additional discussion of fossil fuel emission trends is presented in the Trends in U.S. Greenhouse Gas Emissions Chapter.
Energy 3-3
-------
Table 3-3: C02 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.)
Fuel/Sector
Coal
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Geothermal*
Total
1990
1,699.0
3.0
11.8
152.3
NE
1,531.3
0.6
1,011.4
240.0
143.3
415.3
36.1
176.8
NO
2,013.3
97.4
69.2
289.5
1,427.9
101.8
27.6
0.40
4,724.1
1995
1,805.5
1.7
11.1
143.0
NE
1,648.7
0.9
1,169.6
264.3
165.2
472.2
38.4
229.5
NO
2,054.6
90.5
50.1
267.5
1,551.8
60.7
34.0
0.34
5,030.0
2000
2,053.9
1.1
8.8
133.5
NE
1,909.6
0.9
1,227.6
272.0
173.2
464.0
35.7
282.0
0.7
2,303.0
100.5
50.3
277.4
1,748.7
91.5
34.6
0.36
5,584.9
2001
1,997.2
1.1
9.2
133.5
NE
1,852.3
1.0
1,178.7
260.5
165.0
426.2
34.9
290.8
1.2
2,335.5
102.2
50.9
310.2
1,723.3
102.0
46.8
0.35
5,511.7
2002
2,003.3
1.2
8.6
123.4
NE
1,868.3
1.9
1,219.6
266.9
171.7
435.6
37.2
307.0
1.2
2,333.9
94.4
45.5
298.7
1,775.1
79.1
41.1
0.37
5,557.2
2003
2,043.3
1.2
7.8
124.0
NE
1,906.2
4.1
1,187.9
278.4
174.3
421.2
33.4
279.3
1.4
2,392.9
104.2
54.5
313.2
1,777.1
98.1
45.8
0.37
5,624.5
2004
2,058.6
1.3
9.6
126.2
NE
1,917.6
3.9
1,190.4
266.2
171.2
421.8
32.3
297.7
1.3
2,463.6
102.5
52.5
327.6
1,832.2
100.1
48.7
0.37
5,713.0
2005
2,093.6
1.0
8.0
122.2
NE
1,958.4
4.0
1,170.0
262.8
167.0
387.0
31.8
320.1
1.3
2,487.2
95.0
50.9
330.9
1,861.0
102.3
47.2
0.37
5,751.2
NE (Not estimated)
NO (Not occurring)
*Although not technically a fossil fuel, geothermal energy-related C02 emissions are included for reporting purposes.
Note: Totals may not sum due to independent rounding.
Table 3-4: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors
(Tg C02 Eq. and Percent)
Sector
Electricity Generation
Electricity Generation
Electricity Generation
Transportation3
Residential
Commercial
Industrial
Industrial
All Sectors"
Fuel Type
Coal
Natural Gas
Petroleum
Petroleum
Natural Gas
Natural Gas
Coal
Natural Gas
All Fuels"
2001 to 2002
16.0
16.1
-22.9
51.8
6.4
6.6
-10.1
9.4
45.5
1%
6%
-22%
3%
2%
4%
-8%
2%
1%
2002 to 2003
38.0
-27.7
19.0
2.0
11.5
2.6
0.6
-14.5
67.3
2%
-9%
24%
0%
4%
2%
0%
-3%
1%
2003 to 2004
11.4
18.4
2.0
55.1
-12.2
-3.1
2.3
0.6
88.5
1%
7%
2%
3%
-4%
-2%
2%
0%
2%
2004 to 2005
40.8
22.4
2.2
28.8
-3.4
-4.2
-4.0
-34.8
38.2
2%
8%
2%
2%
-1%
-2%
-3%
-8%
1%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
CO? emissions also depend on the source of energy and
its C intensity. The amount of C in fuels varies significantly
by fuel type. For example, coal contains the highest amount
of C per unit of useful energy. Petroleum has roughly 75
percent of the C per unit of energy as coal, and natural
gas has only about 55 percent.3 Producing a unit of heat or
electricity using natural gas instead of coal can reduce the
CO2 emissions associated with energy consumption, and
using nuclear or renewable energy sources (e.g., wind) can
essentially eliminate emissions (see Box 3-2). Table 3-4
shows annual changes in emissions during the last five years
for coal, petroleum, and natural gas in selected sectors.
In me United States ^ 86 percent of the energy consumed
in 2005 was produced through the combustion of fossil fuels
3 Based on national aggregate carbon content of all coal, natural gas. and petroleum fuels combusted in the United States.
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks; 1990-2005
-------
such as coal, natural gas, and petroleum (see Figure 3-3 and
Figure 3-4). The remaining portion was supplied by nuclear
electric power (8 percent) and by a variety of renewable
energy sources (6 percent), primarily hydroelectric power
and biofuels (ElA 2()06a). Specifically, petroleum supplied
the largest share of domestic energy demands, accounting
for an average of 44 percent of total fossil fuel based energy
consumption in 2005. Natural gas and coal followed in
order of importance, each accounting for 28 percent of total
consumption. Petroleum was consumed primarily in the
transportation end-use sector, the vast majority of coal was
used in electricity generation, and natural gas was broadly
Figure 3-3
2005 U.S. Energy Consumption by Energy Source
Renewable
Nuclear °
Natural Gas
Coal
Petroleum
6%
23%
23%
40%
Figure 3-4
U.S. Energy Consumption (Quadrillion Btu)
120n
100
| 60-
O
CO
I 40-
c
LU
20-
0-
Total Energy
Fossil Fuels
Renewable & Nuclear
§ 5 S 8
S S S 3
Note: Expressed as gross calorific values.
consumed in all end-use sectors except transportation (see
Figure 3-5) (EIA2006a).
Fossil fuels are generally combusted for the purpose
of producing energy for useful heat and work. During the
combustion process, the C stored in the fuels is oxidized and
emitted as CO2 and smaller amounts of other gases, including
CH4, CO, and NMVOCs.4 These other C-containing non-
CO^ gases are emitted as a by-product of incomplete fuel
combustion, but are, for the most part, eventually oxidized
to CO2 in the atmosphere. Therefore, it is assumed that all
the C in fossil fuels used to produce energy is eventually
converted to atmospheric CO:.
For the purpose of international reporting, the
Intergovernmental Panel on Climate Change (IPCC)
(IPCC/UNEP/OECD/IEA 1997) recommends that particular
adjustments be made to national fuel consumption statistics.
Certain fossil fuels can be manufactured into plastics, asphalt,
lubricants, or other products. A portion of the C consumed for
these non-energy products can be stored (i.e., sequestered)
indefinitely. To account for the fact that the C in these fuels
ends up in products instead of being combusted (i.e., oxidized
and released into the atmosphere), consumption of fuels for
non-energy purposes is estimated and subtracted from total
fuel consumption estimates. Emissions from non-energy uses
of fuels are estimated in the Carbon Emitted and Stored in
Products from Non-Energy Uses of Fossil Fuels section in
this chapter.
Figure 3-5
2005 C02 Emissions from Fossil Fuel Combustion
by Sector and Fuel Type
2,500 -|
2,000 -
1,500 -
1,000 -
500 -
Natural Gas
Petroleum
if Coal
Relative Contribution
by Fuel Type
0 -1
Residential Commercial Industrial Transportation Electricity U.S.
Generation Territories
Note: The electricity generation sector also includes emissions o) less than 0.01 Tg C03 Eq.
from geothermal-based electricity generation
4 See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-CO2 gas emissions from fossil fuel
combustion.
Energy 3-5
-------
Box 3-1: Weather and Non-Fossil Energy Effects on C02 from Fossil Fuel Combustion Trends
In 2005, weather conditions became warmer in both the winter and summer. The winter was slightly milder than usual, with heating
degree days in the United States 5 percent below normal (see Figure 3-6). Warmer winter conditions led to a decrease in demand for heating
fuels. Summer temperatures were substantially warmer than usual, with cooling degree days 15 percent above normal (see Figure 3-7) (EIA
2006f),5 thereby increasing the demand for electricity.
Figure 3-6
• I L
Annual Deviations from Normal Heating Degree Days for the United States (1950-2005)
II z
Z o
Figure
12 -i
9 - Normal (4.576 Heating Degree Days)
l: II
j: "II " "
_9 _ g 99% Confidence
-12 -
Note: Climatological normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1 961 through 1 990.
3-7
n i
r jrii-ii
il
Annual Deviations from Normal Cooling Degree Days for the United States (1050-2005)
n TO
o E
;i
"i
si
-1
*jh 99% Confidence
i mi _ i
-5-11
-1{H
1 Normal (1,193 Cooling Degree Days)
Note: Climatological normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1961 through 1990.
i • ii .L I
I "
oioicnoioooo
Although no new U.S. nuclear power plants have been
constructed in recent years, the utilization (i.e., capacity factors6)
of existing plants in 2005 remained high at slightly over 89 percent.
Electricity output by hydroelectric power plants decreased in 2005
by approximately 1 percent. Electricity generated by nuclear plants
in 2005 provided almost 3 times as much of the energy consumed
in the United States as hydroelectric plants (EIA 2006a). Aggregate
nuclear and hydroelectric power plant capacity factors since 1973
are shown in Figure 3-8.
Figure 3-8
Aggregate Nuclear and Hydroelectric Power Plant
Capacity Factors in the United States (1974-2005)
70 -
60
i 50
£
£• 40
S. 30
S 20-
10-
tO CO O CM -* tO
r-. f-. co co eo eo
01 at o> o) o» o>
o» o> o» o
csj c\j CM
5 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily temperature below 65 °F,
while cooling degree days are deviations of the mean daily temperature above 65 °F. Heating degree days have a considerably greater affect on energy
demand and related emissions than do cooling degree days. Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000. The
variation in these normals during this time period was ±10 percent and ±14 percent for heating and cooling degree days, respectively (99 percent
confidence interval).
6 The capacity factor is defined as the ratio of the electrical energy produced by a generating unit for a given period of time to the electrical energy that
could have been produced at continuous full-power operation during the same period (EIA 2006a).
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 2005
-------
Table 3-5: C02 Emissions from International Bunker Fuels (Tg C02 Eq.)*
Vehicle Mode
Aviation
Marine
Total
1990
45.7
68.0
113.7
1995
50.2
50.4
100.6
2000
59.9
41.3
101.1
2001
58.7
38.9
97.6
2002
61.1
28.0
89.1
2003
58.8
24.9
83.7
2004
62.2
34.9
97.2
2005
62.6
34.6
97.2
*See International Bunker Fuels section for additional detail.
Note: Totals may not sum due to independent rounding.
According to the UNFCCC reporting guidelines,
CO2 emissions from the consumption of fossil fuels for
aviation and marine international transport activities (i.e.,
international bunker fuels) should be reported separately,
and not included in national emission totals. Estimates of
international bunker fuel emissions for the United States are
provided in Table 3-5.
fend-Use Sector Consumption
An alternative method of presenting CO2 emissions is
to allocate emissions associated with electricity generation
to the sectors in which it is used. Four end-use sectors
were denned: industrial, transportation, residential, and
commercial. For the discussion below, electricity generation
emissions have been distributed to each end-use sector based
upon the sector's share of national electricity consumption.
This method of distributing emissions assumes that each
sector consumes electricity generated from an equally
carbon-intensive mix of fuels and other energy sources.
After the end-use sectors are discussed, emissions from
electricity generation are addressed separately. Emissions
from U.S. territories are also calculated separately due to
a lack of end-use-specific consumption data. Table 3-6 and
Figure 3-9 summarize CO2 emissions from direct fossil fuel
combustion and pro-rated electricity generation emissions
from electricity consumption by end-use sector.
Figure 3-9
2005 End-Use Sector Emissions of C02 from
Fossil Fuel Combustion
2,000 -i
1,500 -
»1,000 -
500 -
From Electricity
Consumption
Sf, From Direct Fossil
Fuel Combustion
0 -1
Residential Commercial Industrial Transportation U.S.
Territories
Table 3-6: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990
1,467.0
1,464.0
3.0
1,539.8
857.1
682.7
929.9
340.3
589.6
759.2
224.3
534.9
28.3
4,724.1
1,810.2
1995
1,593.3
1,590.2
3.0
1,595.8
882.7
713.1
995.4
356.4
639.0
810.6
226.4
584.2
35.0
5,030.0
1,939.3
2000
1,787.8
1,784.4
3.4
1,660.1
875.0
785.1
1,131.5
373.5
758.0
969.3
232.3
736.9
36.2
5,584.9
2,283.5
2001
1,761.5
1,758.2
3.3
1,596.6
869.9
726.7
1,124.8
363.9
760.9
979.7
225.1
754.6
49.0
5,511.7
2,245.5
2002
1,815.7
1,812.3
3.4
1,575.5
857.7
717.8
1,147.9
362.4
785.5
973.8
225.7
748.0
44.3
5,557.2
2,254.7
2003
1,814.8
1,810.5
4.3
1,595.1
858.3
736.8
1,179.1
383.8
795.3
984.2
236.6
747.6
51.3
5,624.5
2,284.0
2004
1,868.9
1,864.5
4.4
1,615.2
875.6
739.6
1,175.9
369.9
806.0
999.1
233.3
765.8
54.0
5,713.0
2,315.8
2005
1,897.9
1,892.8
5.2
1,575.2
840.1
735.1
1,208.7
358.7
849.9
1,016.8
225.8
791.0
52.5
5,751.2
2,381.2
Note: Totals may not sum due to independent rounding. Emissions from fossil fuel combustion by electricity generation are allocated based on aggregate
national electricity consumption by each end-use sector.
-------
Transportation End-Use Sector
Using this allocation method, the transportation end-use
sector accounted for 1,897.9 Tg CO2 in 2005, or approximately
33 percent of total CO2 emissions from fossil fuel combustion.
the largest share of any end-use economic sector.7 Between
1990 and 2005, transportation CO2 emissions increased by
431.0 Tg CO2, representing approximately 41 percent of
the growth in energy-related CO2 emissions from all sectors.
Almost all of the energy consumed in the transportation sector
was petroleum-based, including motor gasoline, diesel fuel,
jet fuel, and residual oil.
Table 3-7 provides a detailed breakdown of CO2
emissions by fuel category and vehicle type for the
transportation end-use sector. As detailed in the table, overall
transportation CO2 emissions increased by 29 percent from
1990 to 2005, representing an average annual increase of
1.8 percent. Between 2004 and 2005 transportation CO,
emissions increased by 1.6 percent.
Transportation fuel consumption is broadly affected by
travel activity and the amount of energy vehicles use to move
people and goods by various travel modes. In the short-term,
changes in transportation energy consumption and CO2
emissions primarily reflect variation in travel activity that
accompanies year-to-year economic fluctuations. Long-term
factors, especially the cost of fuel, can impact travel patterns
and vehicle energy efficiency. Since 1990, there has been
a significant increase in vehicle miles traveled (VMT) by
light-duty trucks, freight trucks, and aircraft. At the same
time, the fuel economy of light-duty trucks and freight trucks
has remained roughly constant. By contrast, commercial
aircraft have become noticeably more fuel efficient and have
operated with an increasing percentage of seats occupied.
As shown in Table 3-7, automobiles and light-duty
trucks (consuming both gasoline and diesel) accounted for
approximately 61 percent of transportation CO2 emissions in
2005. From 1990 to 2005, CO2 emissions from automobiles
and light-duty trucks increased roughly 25 percent (236.2
Tg CO2). Over this period, automobile and light-duty truck
VMT increased by 39 percent, outweighing a small increase
in overall fleet fuel economy. Much of the small increase in
overall fleet fuel economy resulted from the retirement of
older, less fuel efficient vehicles. Figure 3-10 presents the
overall sales-weighted fuel economy of new vehicles sold
in the United States over the 1990 to 2005 time period. The
trend for new-vehicle fuel economy reflects a substantial
increase in the sales of light-duty trucks when compared to
the generally declining sales of automobiles (Figure 3-11).
Carbon dioxide emissions from freight trucks8 increased
by 69 percent (157.7 Tg CO2 Eq.) from 1990 to 2005,
representing the largest emissions rate increase of any major
transportation mode. Fuel economy for the freight truck fleet
was relatively constant over this period, while truck VMT
increased by 51 percent. Aircraft9 CO2 emissions increased
by approximately 3.4 percent (6.1 Tg CO2 Eq.) between
1990 and 2005, reflecting both an increase in emissions from
Figure 3-10
Sales-Weighted fuel Economy of New Automobiles
and Light-Duty Trucks, 1990-2005 i
25-
24-
23-
I "~
3 21-
I 20-
03
I 19-
18
17
16
15-1
a>o»CT>OJa>o>o>oiO)
Figure 3-11
~les of Now Automobiles and Light-Duty Trucks,
1990-2005
10,000
1 8,000-
1 6,000-
GO
1 4,000
s
2,000
A
Passenger Cars
Light Duty Trucks
o T— c»aco^-mcor*-coo)OT— esico^-m
7 Note that electricity generation is the largest emitter of CO2 when electricity is not distributed among end-use sectors.
8 Includes "other trucks" fueled by gasoline, diesel and LPG.
9 Includes consumption of jet fuel and aviation gasoline. Does not include aircraft bunkers, which are not accounted for in national emission totals.
3-8 Inventory •->( U.S. {Srt-.3iitiDis.st Gas IViSssmiS :nsc: Sinks; H390 -?OGa
-------
Table 3-7: C02 Emissions from Fossil Fuel Combustion in the Transportation End-Use Sector (Tg C02 Eq.)a
Fuel/Vehicle Type
Gasoline
Automobiles
Light-Duty Trucks
Other Trucks"
Buses
Motorcycles
Boats (Recreational)
Distillate Fuel Oil (Diesel)
Automobiles
Light-Duty Trucks
Other Trucksb
Buses
Locomotives
Ships & Boats
Ships (Bunkers)
Jet Fuel0
Commercial Aircraft
Military Aircraft
General Aviation Aircraft
Aircraft (Bunkers)
Aviation Gasoline
General Aviation Aircraft
Residual Fuel Oil
Ships & Boats"
Ships (Bunkers)"
Natural Gas
Automobiles
Light Trucks
Buses
Pipeline
LPG
Light Trucks
Other Trucks6
Buses
Electricity
Rail
Total (Including Bunkers)6
Total (Excluding Bunkers)6
1990
961.7
607.3
302.1
37.9
0.3
1.7
12.4
272.7
7.8
11.3
188.3
7.9
35.1
10.7
11.6
222.6
136.3
34.3
6.3
45.7
3.1
3.1
80.1
23.7
56.4
36.1
+
+
36.1
1.4
0.5
0.8
+
3.0
3.0
1,580.7
1,467.0
1995
1,029.7
591.7
386.4
35.5
0.4
1.7
14.0
325.1
7.7
14.7
234.9
8.6
39.2
10.9
9.2
222.1
142.8
23.8
5.3
50.2
2.7
2.7
71.7
30.5
41.2
38.4
0.1
0.1
38.2
1.1
0.5
0.5
+
3.0
3.0
1,693.9
1,593.3
2000
1,121.9
628.4
441.6
35.3
0.4
1.8
14.4
401.0
3.6
17.3
307.5
10.2
41.7
14.4
6.3
253.8
164.2
20.5
9.2
59.9
2.5
2.5
69.9
34.9
35.0
35.7
+
0.4
35.2
0.7
0.3
0.4
+
3.4
3.4
1,888.9
1,787.8
2001
1,127.1
631.1
445.3
34.3
0.3
1.7
14.4
401.6
3.7
17.0
308.5
9.3
41.8
16.0
5.3
242.8
152.6
22.5
9.1
58.7
2.4
2.4
46.1
12.6
33.6
34.9
+
0.5
34.4
0.8
0.3
0.5
+
3.3
3.3
1,859.1
1,761.5
2002
1,155.8
645.8
458.8
34.8
0.3
1.6
14.4
415.1
3.7
17.5
322.7
8.8
41.5
15.7
5.1
236.8
145.7
20.4
9.5
61.1
2.3
2.3
53.3
30.5
22.8
37.2
+
0.6
36.6
0.8
0.3
0.5
+
3.4
3.4
1,904.8
1,815.7
2003
1,159.5
624.9
488.5
29.9
0.3
1.6
14.3
421.8
4.2
21.9
324.8
9.6
42.4
12.9
6.0
231.5
143.9
19.9
8.8
58.8
2.1
2.1
45.0
26.2
18.8
33.4
+
0.7
32.7
1.0
0.4
0.6
+
4.3
4.3
1,898.5
1,814.8
2004
1,180.8
624.3
509.8
30.3
0.4
1.7
14.2
447.3
4.3
23.4
337.5
13.8
44.8
16.5
7.1
239.8
147.2
21.0
9.3
62.2
2.2
2.2
58.3
30.4
27.9
32.3
+
0.7
31.5
1.1
0.4
0.7
+
4.4
4.4
1,966.0
1,868.9
2005
1,182.4
610.4
524.9
30.6
0.4
1.8
14.3
462.3
4.4
25.0
353.4
14.0
45.2
13.6
6.8
246.3
156.5
17.6
9.6
62.6
2.4
2.4
63.7
36.3
27.4
31.8
+
0.7
31.1
1.1
0.4
0.7
+
5.2
5.2
1,995.1
1,897.9
Note: Totals may not sum due to independent rounding.
a This table does not include emissions from non-transportation mobile sources, such as agricultural equipment and construction equipment; it also does
not include emissions associated with electricity consumption by pipelines or lubricants used in transportation.
b Includes medium- and heavy-duty trucks over 8,500 Ibs.
c Due to a change in methodology for estimating jet fuel consumption by aircraft type, the amount of jet fuel assigned to commercial aircraft is higher than
in previous inventories; the "other aircraft" category has also been eliminated as a result of this change in methodology.
d Fluctuations in emission estimates from the combustion of residual fuel oil are currently unexplained, but may be related to data collection problems.
e Official estimates exclude emissions from the combustion of both aviation and marine international bunker fuels; however, estimates including international
bunker fuel-related emissions are presented for informational purposes.
+ Less than 0.05 Tg C02 Eq.
commercial aircraft emissions and a decrease in domestic
military aircraft emissions. While CO2 emissions from
commercial aircraft grew by approximately 14.8 percent
(20.2 Tg CO2 Eq.) from 1990 to 2005, passenger miles
traveled increased by 69 percent over the same period,
reflecting improvements in the fuel efficiency of planes
and an increasing percentage of occupied seats per plane.
For further information on all greenhouse gas emissions
from transportation sources, please refer to Table A-108 in
Annex 3.2.
Table 3-7 provides a detailed breakdown of CO2
emissions by fuel category and vehicle type for the
transportation end-use sector. Fifty-seven percent of the
emissions from this end-use sector in 2005 were the result of
Energy 3-8
-------
the combustion of motor gasoline in automobiles and light-
duty trucks. Other trucks and jet aircraft were also significant
contributors, respectively accounting for 20 and 12 percent
of CO2 emissions from the transportation end-use sector.10
For information on CO2 emissions from off-road equipment
and vehicles (i.e., non-transportation mobile sources), please
refer to Table A-107 in Annex 3.2.
Industrial End-Use Sedos
The industrial end-use sector accounted for 27 percent
of CO2 emissions from fossil fuel combustion. On average,
53 percent of these emissions resulted from the direct
consumption of fossil fuels for steam and process heat
production. The remaining 47 percent was associated with
their consumption of electricity for uses such as motors,
electric furnaces, ovens, and lighting.
The industrial end-use sector includes activities such as
manufacturing, construction, mining, and agriculture. The
largest of these activities in terms of energy consumption
is manufacturing, of which six industries—Petroleum
Refineries, Chemicals, Primary Metals, Paper, Food, and
Nonmetallic Mineral Products—represent the vast majority
of the energy use (EIA 2006a and 2005b).
In theory, emissions from the industrial end-use sector
should be highly correlated with economic growth and
industrial output, but heating of industrial buildings and
agricultural energy consumption is also affected by weather
conditions.11 In addition, structural changes within the U.S.
economy that lead to shifts in industrial output away from
energy intensive manufacturing products to less energy
intensive products (e.g., from steel to computer equipment)
also have a significant affect on industrial emissions.
From 2004 to 2005, total industrial production and
manufacturing output increased by 3.3 and 4.0 percent,
respectively (FRB 2006). Over this period, output increased
for Paper, Food, and Nonmetallic Mineral Products, but
declined for Petroleum Refineries, Chemicals, and Primary
Metals (see Figure 3-12).
Despite the growth in industrial output (56 percent) and
the overall U.S. economy (55 percent) from 1990 to 2005,
CO, emissions from the industrial end-use sector increased
Figure 3-12
Industrial Production Indices (Index 2002=100)
110
100
90
80
70
ISO
110
100
90
80
110
100
90
80
70
120 -,
110 -
100 --
90 -
80 -
Total
Industrial
Index
Paper
Total excluding Computers,
Communications Equipment,
and Semiconductors
Foods
Stone, Clay & Glass Products
Chemicals
Primary Metals
Petroleum Refineries
__
____
by only 2.3 percent. A number of factors are believed to
have caused this disparity between rapid growth in industrial
output and decrease in industrial emissions, including: (1)
more rapid growth in output from less energy-intensive
industries relative to traditional manufacturing industries,
and (2) improvements in energy efficiency. In 2005, CO2
emissions from fossil fuel combustion and electricity use
within the industrial end-use sectors were 1,575.2 Tg CO2
Eq., or 2.5 percent below 2004 emissions.
Rtoidianua 311.1 GoiivefCiai t vs-usifc Sectors
The residential and commercial end-use sectors
accounted for an average 21 and 18 percent, respectively,
of CO2 emissions from fossil fuel combustion. Both end-use
sectors were heavily reliant on electricity for meeting energy
needs, with electricity consumption for lighting, heating,
air conditioning, and operating appliances contributing to
about 70 and 78 percent of emissions from the residential
and commercial end-use sectors, respectively. The remaining
emissions were largely due to the direct consumption of
natural gas and petroleum products, primarily for heating and
10 These percentages include emissions from bunker fuels.
11 Some commercial customers are large enough to obtain an industrial price for natural gas and/or electricity and are consequently grouped with the
industrial end-use sector in U.S. energy statistics. These misclassifications of large commercial customers likely cause the industrial end-use sector to
appear to be more sensitive to weather conditions.
inventory of U.S. Greenhouse Q?.^ > missions ants Sinks: 1990-200E
-------
cooking needs. Coal consumption was a minor component
of energy use in both of these end-use sectors. In 2005, CO2
emissions from fossil fuel combustion and electricity use
within the residential and commercial end-use sectors were
1,208.7 Tg CO2 Eq. and 1,016.8 Tg CO2 Eq., respectively.
Emissions from the residential and commercial
sectors have generally been increasing since 1990, and
are often correlated with short-term fluctuations in energy
consumption caused by weather conditions, rather than
prevailing economic conditions (see Table 3-6). In the long-
term, both end-use sectors are also affected by population
growth, regional migration trends, and changes in housing
and building attributes (e.g., size and insulation).
Emissions from natural gas consumption represent
over 73 percent of the direct (not including electricity)
fossil fuel emissions from the residential and commercial
sectors. In 2005, natural gas emissions decreased by 1 and 2
percent, respectively, in each of these sectors, due to warmer
conditions in the United States (see Figure 3-13).
Electricity sales to the residential and commercial
end-use sectors in 2005 increased by 5 and 3 percent,
respectively, from 2004. This trend can largely be attributed
to the growing economy (3.2 percent), which led to increased
demand for electricity. Increased air conditioning-related
electricity consumption in these sectors was also attributable
to the warmer summer (see Figure 3-14). Electricity-related
Figure 3-14
Figure 3-13
120-1
g 100--
90-
80 -1
Heating Degree Days12
Normal
(4,524 Heating Degree Days)
« •
* •
s
o>o>o>aio>o>o)o>o)o>
§ §
Note: Excludes Alaska and Hawaii
Cooling Degree Days1
120 -i
5110-
80
100
90
Normal
(1,215 Cooling Degree Days)
OT— CNJco^-mtor-cooJOi— cxim^-m
cnojoiojcncncnoioicno^^^oo
Note: Excludes Alaska and Hawaii
emissions in both the residential and commercial sectors
rose due to increased consumption; total emissions from
the residential sector increased by 2.8 percent in 2005, with
emissions from the commercial sector 1.8 percent higher
than in 2004.
Electricity Generation
The process of generating electricity is the single largest
source of CO2 emissions in the United States, representing
39 percent of total CO2 emissions from all CO2 emissions
sources across the United States. Electricity generation
also accounted for the largest share of CO2 emissions from
fossil fuel combustion, approximately 41 percent in 2005.
Electricity was consumed primarily in the residential,
commercial, and industrial end-use sectors for lighting,
heating, electric motors, appliances, electronics, and air
conditioning (see Figure 3-15).
The electric power industry includes all power producers,
consisting of both regulated utilities and nonutilities (e.g.
independent power producers, qualifying cogenerators,
and other small power producers). For the underlying
energy data used in this chapter, the Energy Information
Administration (EIA) categorizes electric power generation
into three functional categories: the electric power sector,
the commercial sector, and the industrial sector. The electric
power sector consists of electric utilities and independent
power producers whose primary business is the production
12 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily temperature below 65 °F.
Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
11 Degree days are relative measurements of outdoor air temperature. Cooling degree days are deviations of the mean daily temperature above 65 °F.
Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
Energy 3-11
-------
Figure 3-15
Electricity Generation Retail Sales by End-Use! Sector
1,400
1,200
I 1,000
c
I 800
fiQ
600
400
Residential
Industrial
Commercial
Note: The transportation end-use sector consumes minor quanties of electricity.
of electricity,14 while the other sectors consist of those
producers that indicate their primary business is other than
the production of electricity.
In 2005, the amount of electricity generated (in kWh)
increased by 2.4 percent, largely due to the growing economy,
expanding industrial production, and wanner summer
conditions. However, CO2 emissions increased by 2.8
percent, as a larger share of electricity was generated by coal.
Coal and natural gas consumption for electricity generation
increased by 2.1 percent and 7.5 percent, respectively, in
2005, and nuclear power decreased by 1.1 percent. As a result
of the increase in coal consumption, C intensity from direct
fossil fuel combustion increased slightly overall in 2005 (see
Table 3-9). Coal is consumed primarily by the electric power
Box 3-2: Carbon Intensity of U.S. Energy Consumption
Fossil fuels are the dominant source of energy in the United States, and C02 is emitted as a product from their combustion. Useful
energy, however, is generated in the United States from many other sources that do not emit C02 in the energy conversion process, such as
renewable (i.e., hydropower, biofuels, geothermal, solar, and wind) and nuclear sources.15
Energy-related C02 emissions can be reduced by not only lowering total energy consumption (e.g., through conservation measures)
but also by lowering the C intensity of the energy sources employed (e.g., fuel switching from coal to natural gas). The amount of C emitted
from the combustion of fossil fuels is dependent upon the C content of the fuel and the fraction of that C that is oxidized. Fossil fuels vary in
their average C content, ranging from about 53 Tg C02 Eq./QBtu for natural gas to upwards of 95 Tg C02 Eq./QBtu for coal and petroleum
coke.16 In general, the C content per unit of energy of fossil fuels is the highest for coal products, followed by petroleum, and then natural gas.
Other sources of energy, however, may be directly or indirectly C neutral (i.e., 0 Tg C02 Eq./Btu). Energy generated from nuclear and many
renewable sources do not result in direct emissions of C02. Biofuels such as wood and ethanol are also considered to be C neutral; although
these fuels do emit C02, in the long run the C02 emitted from biomass consumption does not increase atmospheric C02 concentrations if
the biogenic C emitted is offset by the growth of new biomass.17 The overall C intensity of the U.S. economy is thus dependent upon the
quantity and combination of fuels and other energy sources employed to meet demand.
Table 3-8 provides a time series of the C intensity for each sector of the U.S. economy. The time series incorporates only the energy
consumed from the direct combustion of fossil fuels in each sector. For example, the C intensity for the residential sector does not include
the energy from or emissions related to the consumption of electricity for lighting or wood for heat. Looking only at this direct consumption
of fossil fuels, the residential sector exhibited the lowest C intensity, which is related to the large percentage of its energy derived from natural
gas for heating. The C intensity of the commercial sector has predominantly declined since 1990 as commercial businesses shift away
from petroleum to natural gas. The industrial sector was more dependent on petroleum and coal than either the residential or commercial
sectors, and thus had higher C intensities over this period. The C intensity of the transportation sector was closely related to the C content
of petroleum products (e.g., motor gasoline and jet fuel, both around 70 Tg C02 Eq./EJ), which were the primary sources of energy. Lastly,
the electricity generation sector had the highest C intensity due to its heavy reliance on coal for generating electricity.
14 Utilities primarily generate power for the U.S. electric grid for sale to retail customers. Nonutilities produce electricity for their own use, to sell to
large consumers, or to sell on the wholesale electricity market (e.g., to utilities for distribution and resale to customers).
15 Small quantities of CO2, however, are released from some geologic formations tapped for geothermal energy. These emissions are included with
fossil fuel combustion emissions from the electricity generation. Carbon dioxide emissions may also be generated from upstream activities (e.g..
manufacture of the equipment) associated with fossil fuel and renewable energy activities, but are not accounted for here.
16 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
17 Net carbon fluxes from changes in biogenic carbon reservoirs in wooded or croplands are accounted for in the estimates for Land Use, Land-Use
Change, and Forestry.
-------
Box 3-2: Carbon Intensity of U.S. Energy Consumption (continued)
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg C02 Eq./QBtu)
Sector
Residential3
Commercial3
Industrial3
Transportation3
Electricity Generation"
U.S. Territories0
All Sectors0
1990
57.3
59.6
63.8
71.0
86.7
74.1
72.7
1995
56.6
57.8
62.7
71.0
86.0
74.1
72.2
2000
56.7
57.3
62.6
71.0
85.6
73.2
72.6
2001
56.9
57.6
63.5
71.0
85.1
73.6
72.7
2002
56.6
57.1
63.0
71.0
85.0
73.7
72.5
2003
56.8
57.4
63.4
71.0
85.7
74.1
72.8
2004
56.9
57.6
63.5
71.1
85.4
74.0
72.9
2005
56.7
57.5
64.0
71.1
85.0
74.1
73.1
a Does not include electricity or renewable energy consumption.
b Does not include electricity produced using nuclear or renewable energy.
c Does not include nuclear or renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
In contrast to Table 3-8, Table 3-9 presents C intensity values that incorporate energy consumed from all sources (i.e., fossil fuels,
renewables, and nuclear). In addition, the emissions related to the generation of electricity have been attributed to both electricity generation
and the end-use sectors in which that electricity was eventually consumed.18 This table, therefore, provides a more complete picture of the
actual C intensity of each end-use sector per unit of energy consumed. The transportation end-use sector in Table 3-9 emerges as the most
C intensive when all sources of energy are included, due to its almost complete reliance on petroleum products and relatively minor amount
of biomass-based fuels used, such as ethanol. The "other end-use sectors" (i.e., residential, commercial, and industrial) use significant
quantities of biofuels such as wood, thereby lowering the overall C intensity. The C intensity of the electricity generation sector differs greatly
from the scenario in Table 3-8, where only the energy consumed from the direct combustion of fossil fuels was included. This difference is
due almost entirely to the inclusion of electricity generation from nuclear and hydropower sources, which do not emit C02.
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg C02 Eq./QBtu)
Sector
Transportation3
Other End-Use Sectors3' b
Electricity Generation0
All Sectors"
1990
70.8
57.6
59.0
61.1
1995
70.6
56.5
57.9
60.3
2000
70.6
57.9
59.9
61.4
2001
70.5
58.4
60.0
61.8
2002
70.5
57.6
58.9
61.3
2003
70.4
58.1
59.6
61.6
2004
70.3
58.0
59.4
61.5
2005
70.2
58.5
59.8
61.9
a Includes electricity (from fossil fuel, nuclear, and renewable sources) and direct renewable energy consumption.
b Other End-Use Sectors includes the residential, commercial, and industrial sectors.
c Includes electricity generation from nuclear and renewable sources.
d Includes nuclear and renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
By comparing the values in Table 3-8 and Table 3-9, a few
observations can be made. The use of renewable and nuclear energy
sources has resulted in a significantly lower C intensity of the U.S.
economy. Over the fifteen-year period of 1990 through 2005, however,
the C intensity of U.S. energy consumption has been fairly constant, as
the proportion of renewable and nuclear energy technologies have not
changed significantly. Per capita energy consumption has fluctuated, but
is now roughly equivalent to levels in 1990 (see Figure 3-16). Due to a
general shift from a manufacturing-based economy to a service-based
economy, as well as overall increases in efficiency, energy consumption
and energy-related C02 emissions per dollar of gross domestic product
(GDP) have both declined since 1990 (BEA 2006).
C intensity estimates were developed using nuclear and renewable
energy data from EIA (2006a) and fossil fuel consumption data as
discussed above and presented in Annex 2.1.
Figure 3-16
U.S. Energy Consumption and Energy-Related C02
Emissions Per Capita and Per Dollar GDP
110-
105-
§100-
o 95~
O)
5 90-
1 85-
E=
80-
75-
Energy
Consumption/ CO, /capita
capita ~-^
^C02 /Energy
Consumption
C02/$GDP
Energy Consumption/$GOP
18 In other words, the emissions from the generation of electricity are intentionally double counted by attributing them both to electricity generation and
the end-use sector in which electricity consumption occurred.
-------
sector in the United States, which accounted for 94 percent
of total coal consumption for energy purposes in 2005. The
amount of electricity generated from renevvables decreased
by 1.7 percent in 2005.
Methodology
The methodology used by the United States for
estimating CO2 emissions from fossil fuel combustion is
conceptually similar to the approach recommended by the
IPCC for countries that intend to develop detailed, sectoral-
based emission estimates (IPCC 2006). A detailed description
of the U.S. methodology is presented in Annex 2.1, and is
characterized by the following steps:
1. Determine total fuel consumption by fuel type and sector.
Total fossil fuel consumption for each year is estimated
by aggregating consumption data by end-use sector (e.g.,
commercial, industrial, etc.), primary fuel type (e.g.,
coal,petroleum, gas), and secondary fuel category (e.g.,
motor gasoline, distillate fuel oil, etc.). Fuel consumption
data for the United States were obtained directly from
the Energy Information Administration (EIA) of the
U.S. Department of Energy (DOE), primarily from the
Monthly Energy Review and unpublished supplemental
tables on petroleum product detail (EIA 2006b). The
United States does not include territories in its national
energy statistics, so fuel consumption data for territories
were collected separately from Grillot (2006).19
For consistency of reporting, the IPCC has recommended
that countries report energy data using the International
Energy Agency (IEA) reporting convention and/or
IEA data. Data in the IEA format are presented "top
down"—that is, energy consumption for fuel types
and categories are estimated from energy production
data (accounting for imports, exports, stock changes,
and losses). The resulting quantities are referred to
as "apparent consumption." The data collected in the
United States by EIA, and used in this inventory, are,
instead, "bottom up" in nature. In other words, they are
collected through surveys at the point of delivery or use
and aggregated to determine national totals.20
It is also important to note that U.S. fossil fuel energy
statistics are generally presented using gross calorific
values (GCV) (i.e., higher heating values). Fuel
consumption activity data presented here have not been
adjusted to correspond to international standard, which
are to report energy statistics in terms of net calorific
values (NCV) (i.e., lower heating values).21
2. Subtract uses accounted for in the Industrial Processes
chapter. Portions of the fuel consumption data for six fuel
categories—coking coal, industrial other coal, petroleum
coke, natural gas, residual fuel oil, and other oil —were
reallocated to the Industrial Processes chapter, as they
were consumed during non-energy-related industrial
activity. To make these adjustments, additional data
were collected from Gambogi (2006), EFMA (1995),
U.S. Census Bureau (1991 through 1994), U.S. Census
Bureau (2006), USITC (2006), U.S. Census Bureau
(2005), EIA (2005a), EIA (200 Ib), US AA (2006), USGS
(1998 through 2002), USGS (1995), Corathers (2006),
USGS (199la through 2005a), USGS (1991b through
2005b), U.S. International Trade Commission (2006),
U.S. International Trade Commission (2004), Onder and
Bagdoyan (1993), and Johnson (2006).22
3. Adjust for biofuels, conversion of fossil fuels, and exports
ofCO2. Fossil fuel consumption estimates are adjusted
downward to exclude (1) fuels with biogenic origins,
(2) fuels created from other fossil fuels, and (3) exports
of CO2. Fuels with biogenic origins are assumed to
result in no net CO2 emissions, and must be subtracted
from fuel consumption estimates. These fuels include
ethanol added to motor gasoline and biomass gas used
as natural gas. Synthetic natural gas is created from
19 Fuel consumption by U.S. territories (i.e., American Samoa. Guam, Puerto Rico, U.S. Virgin Islands, Wake Island, and other U.S. Pacific Islands) is
included in this report and contributed emissions of 53 Tg CCK Eq. in 2005.
20 See IPCC Reference Approach for estimating CO, emissions from fossil fuel combustion in Annex 4 for a comparison of U.S. estimates using top-
down and bottom-up approaches.
21 A crude convention to convert between gross and net calorific values is to multiply the heat content of solid and liquid fossil fuels by 0.95 and
gaseous fuels by 0.9 to account for the water content of the fuels. Biomass-based fuels in U.S. energy statistics, however, are generally presented using
net calorific values.
22 See sections on Iron and Steel Production, Ammonia Manufacture, Petrochemical Production, Titanium Dioxide Production, Ferroalloy Production,
Aluminum Production, and Silicon Carbide Production in the Industrial Processes chapter.
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
industrial coal, and is currently included in EIA statistics
for both coal and natural gas. Therefore, synthetic
natural gas is subtracted from energy consumption
statistics.23 Since October 2000, the Dakota Gasification
Plant has been exporting CO2 to Canada by pipeline.
Since this CO2 is not emitted to the atmosphere in
the United States, energy used to produce this CO2
is subtracted from energy consumption statistics. To
make these adjustments, additional data for ethanol
and biogas were collected from EIA (2006b) and data
for synthetic natural gas were collected from EIA
(2006e), and data for CO2 exports were collected from
the Dakota Gasification Company (2006), Fitzpatrick
(2002), Erickson (2003), EIA (2001 a), EIA (2004), EIA
(2006e), and Kass (2005).
4. Adjust Sectoral Allocation of Distillate Fuel Oil.
EPA had conducted a separate bottom-up analysis
of transportation fuel consumption based on FHWA
Vehicle Miles Traveled (VMT) that indicated that
the amount of distillate consumption allocated to
the transportation sector in the EIA statistics should
be adjusted. Therefore, for these estimates, the
transportation sector's distillate fuel consumption was
adjusted higher to match the value obtained from the
bottom-up analysis based on VMT. As the total distillate
consumption estimate from EIA is considered to be
accurate at the national level, the distillate consumption
totals for the residential, commercial, and industrial
sectors were adjusted downward proportionately.
The data sources used in the bottom-up analysis of
transportation fuel consumption include AAR (2005),
Benson (2002 through 2004), DOE (1993 through
2004), EIA (2006a), EIA (1991 through 2005), EPA
(2004), and FHWA (1996 through 2006).
5. Adjust for file Is consumed for non-energy uses. U.S.
aggregate energy statistics include consumption of
fossil fuels for non-energy purposes. Depending on
the end-use, this can result in storage of some or all
of the C contained in the fuel for a period of time.
As the emission pathways of C used for non-energy
purposes are vastly different than fuel combustion,
these emissions are estimated separately in the Carbon
Emitted and Stored in Products from Non-Energy Uses
of Fossil Fuels section in this chapter. Therefore, the
amount of fuels used for non-energy purposes was
subtracted from total fuel consumption. Data on non-
fuel consumption was provided by EIA (2006b).
6. Subtract consumption of international bunker fuels.
According to the UNFCCC reporting guidelines
emissions from international transport activities,
or bunker fuels, should not be included in national
totals. U.S. energy consumption statistics include
these bunker fuels (e.g., distillate fuel oil, residual
fuel oil, and jet fuel) as part of consumption by the
transportation end-use sector, however, so emissions
from international transport activities were calculated
separately following the same procedures used for
emissions from consumption of all fossil fuels (i.e.,
estimation of consumption, and determination of C
content) ,24 The Office of the Under Secretary of Defense
(Installations and Environment) and the Defense
Energy Support Center (Defense Logistics Agency) of
the U.S. Department of Defense (DoD) (DESC 2006)
supplied data on military jet fuel use. Commercial jet
fuel use was obtained from BEA (1991 through 2006)
and DOT (1991 through 2006); residual and distillate
fuel use for civilian marine bunkers was obtained from
DOC (1991 through 2006). Consumption of these fuels
was subtracted from the corresponding fuels in the
transportation end-use sector. Estimates of international
bunker fuel emissions are discussed further in the
section entitled International Bunker Fuels.
7. Determine the total C content of fuels consumed. Total
C was estimated by multiplying the amount of fuel
consumed by the amount of C in each fuel. This total C
estimate defines the maximum amount of C that could
potentially be released to the atmosphere if all of the
C in each fuel was converted to CO2. The C content
coefficients used by the United States were obtained
from EIA's Emissions of Greenhouse Gases in the
United States 2005 (EIA 2006c) and EIA's Monthly
Energy Review and unpublished supplemental tables
on petroleum product detail (EIA 2006b). They are
presented in Annexes 2.1 and 2.2.
23 These adjustments are explained in greater detail in Annex 2.1.
24 See International Bunker Fuels section in this chapter for a more detailed discussion.
Energy 3-15
-------
8. Estimate CO2 Emissions. Total CO-> emissions are the
product of the adjusted energy consumption (from the
previous methodology steps 1 through 6), the C content
of the fuels consumed, and the fraction of C that is
oxidized. The fraction oxidized was assumed to be 100
percent for petroleum, coal, and natural gas based on
guidance in IPCC (2006) (see Annex 2.1).
9. Allocate transportation emissions by vehicle type.
This report provides a more detailed accounting of
emissions from transportation because it is such a
large consumer of fossil fuels in the United States. For
fuel types other than jet fuel, fuel consumption data
by vehicle type and transportation mode were used
to allocate emissions by fuel type calculated for the
transportation end-use sector.
For highway vehicles, annual estimates of combined
motor gasoline and diesel fuel consumption by vehicle
category were obtained from FHWA (1996 through
2006); for each vehicle category, the percent gasoline,
diesel, and other (e.g., CNG, LPG) fuel consumption are
estimated using data from DOE (1993 through 2004).
For non-highway vehicles, activity data were obtained
from AAR (2005), BEA (1991 through 2006), Benson
(2002 through 2004), DOE (1993 through 2004), DESC
(2006), DOC (1991 through 2006), DOT (1991 through
2006), El A (2006a), El A (2006d), El A (2006g), El A
(2002), EIA (1991 through 2005), EPA (2004), and
FAA(2005).
For jet fuel used by aircraft, CO2 emissions were
calculated directly based on reported consumption of
fuel as reported by EIA, and allocated to commercial
aircraft using flight-specific fuel consumption data
from the Federal Aviation Administration's (FAA)
System for assessing Aviation's Global Emission
(SAGE) model.25 Allocation to domestic general
aviation was made using FAA Aerospace Forecast data,
and allocation to domestic military uses was made
using DoD data (see Annex 3.7).
Heat contents and densities were obtained from EIA
(2006a)andUSAF(1998).26
., :, ;:."'!W.
For estimates of CO2 from fossil fuel combustion, the
amount of CO2 emitted is directly related to the amount of
fuel consumed, the fraction of the fuel that is oxidized, and
the carbon content of the fuel. Therefore, a careful accounting
of fossil fuel consumption by fuel type, average carbon
contents of fossil fuels consumed, and production of fossil
fuel-based products with long-term carbon storage should
yield an accurate estimate of CO2 emissions.
Nevertheless, there are uncertainties in the consumption
data, carbon content of fuels and products, and carbon
oxidation efficiencies. For example, given the same primary
fuel type (e.g., coal, petroleum, or natural gas), the amount
of carbon contained in the fuel per unit of useful energy
can vary. For the United States, however, the impact of
these uncertainties on overall CO2 emission estimates is
believed to be relatively small. See, for example, Marland
and Pippin (1990).
Although statistics of total fossil fuel and other energy
consumption are relatively accurate, the allocation of this
consumption to individual end-use sectors (i.e., residential,
commercial, industrial, and transportation) is less certain. For
example, for some fuels the sectoral allocations are based on
price rates (i.e., tariffs), but a commercial establishment may
be able to negotiate an industrial rate or a small industrial
establishment may end up paying an industrial rate, leading
to a misallocation of emissions. Also, the deregulation of
the natural gas industry and the more recent deregulation of
the electric power industry have likely led to some minor
problems in collecting accurate energy statistics as firms in
these industries have undergone significant restructuring.
To calculate the total CO2 emission estimate from
energy-related fossil fuel combustion, the amount of
fuel used in these non-energy production processes were
subtracted from the total fossil fuel consumption for 2005.
25 FAA's System for assessing Aviation's Global Emissions (SAGE) model develops aircraft fuel burn and emissions for all commercial flights globally
in a given year. The SAGE model dynamically models aircraft performance, fuel burn, and emissions, and is based on actual flight-by-flight aircraft
movements. See .
26 For a more detailed description of the data sources used for the analysis of the transportation end use sector see the Mobile Combustion (excluding
CO2) and International Bunker Fuels sections of the Energy chapter, Annex 3.2, and Annex 3.7.
-------
The amount of CO2 emissions resulting from non-energy
related fossil fuel use has been calculated separately and
reported in the Carbon Emitted from Non-Energy Uses of
Fossil Fuels section of this report. These factors all contribute
to the uncertainty in the CO2 estimates. Detailed discussions
on the uncertainties associated with C emitted from Non-
Energy Uses of Fossil Fuels can be found within that section
of this chapter.
Various sources of uncertainty surround the estimation
of emissions from international bunker fuels, which are
subtracted from the U.S. totals (see the detailed discussions
on these uncertainties provided in the International Bunker
Fuels section of this chapter). Another source of uncertainty
is fuel consumption by U.S. territories. The United States
does not collect energy statistics for its territories at the
same level of detail as for the fifty states and the District of
Columbia. Therefore, estimating both emissions and bunker
fuel consumption by these territories is difficult.
Uncertainties in the emission estimates presented above
also result from the data used to allocate CO2 emissions from
the transportation end-use sector to individual vehicle types
and transport modes. In many cases, bottom-up estimates of
fuel consumption by vehicle type do not match aggregate
fuel-type estimates from El A. Further research is planned to
improve the allocation into detailed transportation end-use
sector emissions. In particular, residual fuel consumption
data for marine vessels are highly uncertain, as shown by the
large fluctuations in emissions that do not mimic changes in
other variables such as shipping ton miles.
The uncertainty analysis was performed by primary fuel
type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Energy-Related Fossil Fuel
Combustion by Fuel Type and Sector (Tg C02 Eq. and Percent)
Fuel/Sector
2005 Emission Estimate
(TgC02Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Coal"
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas"
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum"
Residential
Commercial
Industrial
Transportation
Electric Utilities
U.S. Territories
Total (excluding Geothermal)"
2,093.6
1.0
8.0
122.2
NE
1,958.4
4.0
1,170.0
262.8
167.0
387.0
31.8
320.1
1.3
2,487.2
95.0
50.9
330.9
1,861.0
102.3
47.2
5,750.8
Lower Bound
2,024.6
0.9
7.6
117.5
NE
1,882.7
3.5
1,179.5
255.4
162.3
395.9
30.9
311.0
1.1
2,355.4
90.1
48.6
283.9
1,739.2
98.6
43.7
5,656.3
Upper Bound
2,290.6
1.1
9.2
142.3
NE
2,146.7
4.7
1,245.4
281.2
178.6
435.7
34.1
336.5
1.5
2,628.1
99.5
52.9
387.0
1,979.1
108.1
52.3
6,060.1
Lower Bound
-3%
-5%
-5%
-4%
NA
-4%
-12%
1%
-3%
-3%
2%
-3%
-3%
-12%
-5%
-5%
-5%
-14%
-7%
-4%
-7%
-2%
Upper Bound
+9%
+15%
+ 15%
+16%
NA
+10%
+19%
+6%
+7%
+ 7%
+ 13%
+ 7%
+ 5%
+ 17%
+6%
+5%
+4%
+ 17%
+6%
+ 6%
+ 11%
+5%
Geothermal
Total (including Geothermal)"0
0.4
5,751.2
5,656.3
6,060.1
NE
-2%
+5%
NA (Not Applicable)
NE (Not Estimated)
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high emission estimates for the
sub-source categories do not sum to total emissions.
c Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for C02 emissions from geothermal production.
Energy
-------
Simulation technique, with @RISK software. For this
uncertainty estimation, the inventory estimation model for
CO2 from fossil fuel combustion was integrated with the
relevant inventory variables from the inventory estimation
model for International Bunker Fuels to realistically
characterize the interaction (or endogenous correlation)
between the variables of these two models. About 150 input
variables were modeled for CO2 from energy-related Fossil
Fuel Combustion (including about 10 for non-energy fuel
consumption and about 20 for International Bunker Fuels).
In developing the uncertainty estimation model, uniform
distributions were assumed for all activity-related input
variables and emission factors, based on the SAIC/EIA
(2001) report.27 Triangular distributions were assigned for
the oxidization factors (or combustion efficiencies). The
uncertainty ranges were assigned to the input variables
based on the data reported in SAIC/EIA (2001) and on
conversations with various agency-personnel.2*
The uncertainty ranges for the activity-related input
variables were typically asymmetric around their inventory
estimates; the uncertainty ranges for the emissions factors
were symmetric. Bias (or systematic uncertainties) associated
with these variables accounted for much of the uncertainties
associated with these variables (SAIC/EIA 2001).29 For
purposes of this uncertainty analysis, each input variable was
simulated 10,000 times through Monte Carlo Sampling.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-10. Fossil fuel combustion CO2
emissions in 2005 were estimated to be between 5,656.3 and
6,060.1 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 2 percent below to 5 percent above the
2005 emission estimate of 5,751.2 Tg CO2 Eq.
QA/QC and Verification
A source-specific QA/QC plan for CO2 from fossil fuel
combustion was developed and implemented. This effort
included a Tier 1 analysis, as well as portions of a Tier 2
analysis. The Tier 2 procedures that were implemented
involved checks specifically focusing on the activity data and
methodology used for estimating CO2 emissions from fossil
fuel combustion in the United States. Emission totals for the
different sectors and fuels were compared and trends were
investigated to determine whether any corrective actions
were needed. Minor corrective actions were taken.
Recalculation;; Discussion
The most significant change impacting fuel combustion
estimates in the current Inventory was updating the C
oxidation factor for all fuel types to 100 percent. This change
was made according to IPCC (2006) and impacted emission
estimates for all fuel types for all years.
An additional adjustment for silicon carbide used for
petroleum coke manufacturing was added to the current
Inventory as a source that is accounted for in the Industrial
Processes chapter. This was reallocated to the Industrial
Processes chapter, as the silicon carbide was consumed
during non-energy related industrial activity.
The Energy Information Administration (EIA 2006b)
updated energy consumption data for all years. These revisions
primarily impacted the emission estimates for 2004. EIA
(2006b) no longer reports a small amount of consumption
of other liquids in the electricity generation sector, which
represented a change from the previous Inventory.
Overall, changes resulted in an average annual increase
of 36.9 Tg CO, Eq. (0.7 percent) in CO2 emissions from fossil
fuel combustion for the period 1990 through 2004.
Planned Improvements
To reduce uncertainty of CO2 from fossil fuel combustion
estimates, efforts will be taken to work with EIA and other
agencies to improve the quality of the U.S. territories data.
This improvement is not all-inclusive, and is part of an
ongoing analysis and efforts to continually improve the CO2
from fossil fuel combustion estimates.
27 SAIC/EIA (2001) characterizes the underlying probability density function for the input variables as a combination of uniform and normal
distributions (the former to represent the bias component and the latter to represent the random component). However, for purposes of the current
uncertainty analysis, it was determined that uniform distribution was more appropriate to characterize the probability density function underlying each
of these variables.
28 In the SAIC/EIA (2001) report, the quantitative uncertainty estimates were developed for each of the three major fossil fuels used within each
end-use sector; the variations within the sub-fuel types within each end-use sector were not modeled. However, for purposes of assigning uncertainty
estimates to the sub-fuel type categories within each end-use sector in the current uncertainty analysis, SAIC/EIA (2001 (-reported uncertainty estimates
were extrapolated.
29 Although, in general, random uncertainties are the main focus of statistical uncertainty analysis, when the uncertainty estimates are elicited from experts,
their estimates include both random and systematic uncertainties. Hence, both these types of uncertainties are represented in this uncertainty analysis.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
3.2. Carbon Emitted from
Non-Energy Uses of Fossil Fuels
(IPCC Source Category 1 A)
In addition to being combusted for energy, fossil fuels are
also consumed for non-energy uses (NEU) in the United States.
The fuels used for these purposes are diverse, including natural
gas, liquefied petroleum gases (LPG), asphalt (a viscous
liquid mixture of heavy crude oil distillates), petroleum coke
(manufactured from heavy oil), and coal coke (manufactured
from coking coal). The non-energy applications are equally
diverse, and include feedstocks for the manufacture of plastics,
rubber, synthetic fibers and other materials; reducing agents
for the production of various metals and inorganic products;
and non-energy products such as lubricants, waxes, and asphalt
(IPCC 2006).
CO2 emissions arise from non-energy uses via several
pathways. Emissions may occur during the manufacture of
a product, as is the case in producing plastics or rubber from
fuel-derived feedstocks. Additionally, emissions may occur
during the product's lifetime, such as during solvent use.
Overall, throughout the time series and across all uses, about
61 percent of the total C consumed for non-energy purposes
was stored in products, and not released to the atmosphere;
the remaining 39 percent was emitted.
There are several areas in which non-energy uses of
fossil fuels are closely related to other parts of the Inventory.
For example, some of the NEU products release CO2 at the
end of their commercial life when they are combusted after
disposal; these emissions are reported separately within the
Energy chapter in the Municipal Solid Waste Combustion
source category. In addition, there is some overlap between
fossil fuels consumed for non-energy uses and the fossil-
derived CO2 emissions accounted for in the Industrial
Processes chapter, especially for fuels used as reducing
agents. To avoid double-counting, the "raw" non-energy fuel
consumption data reported by El A are modified to account for
these overlaps. There are also net exports of petrochemicals
that are not completely accounted for in the EIA data, and
these affect the mass of C in non-energy applications.
As shown in Table 3-11, fossil fuel emissions in 2005
from the non-energy uses of fossil fuels were 142.3 Tg CO2
Eq., which constituted approximately 3 percent of overall
fossil fuel emissions, approximately the same proportion as
in 1990. In 2005, the consumption of fuels for non-energy
uses (after the adjustments described above) was 5,492 TBtu,
an increase of 22 percent since 1990 (see Table 3-12). About
66.3 Tg of the C (243.1 Tg CO2 Eq.) in these fuels was stored,
while the remaining 38.8 Tg C (142.4 Tg CO, Eq.) was
emitted. The proportion of C emitted as CO2 has remained
about constant since 1990, at about 36 to 40 percent of total
non-energy consumption (see Table 3-11).
Methodology
The first step in estimating C stored in products was to
determine the aggregate quantity of fossil fuels consumed
for non-energy uses. The C content of these feedstock
fuels is equivalent to potential emissions, or the product of
consumption and the fuel-specific C content values. Both
the non-energy fuel consumption and C content data were
supplied by the EIA (2006) (see Annex 2.1). Consumption
of natural gas, LPG, pentanes plus, naphthas, other oils, and
special naphtha were adjusted to account for net exports of
these products that are not reflected in the raw data from EIA.
Consumption values for industrial coking coal, petroleum
coke, other oils, and natural gas in Table 3-12 and Table
3-13 have been adjusted to subtract non-energy uses that are
included in the source categories of the Industrial Processes
chapter.30 Consumption values were also adjusted to subtract
exports of intermediary chemicals.
For the remaining non-energy uses, the quantity of C
stored was estimated by multiplying the potential emissions
Table 3-11: C02 Emissions from Fossil Fuel Consumption for Non-Energy Use (Tg C02 Eq.)
Storage/Emissions
Potential Emissions
C Stored
Emissions as a % of Potential
Emissions
1990
312.8
195.6
37%
117.2
1995
346.7
213.6
38%
133.1
2000
385.5
244.5
37%
141.0
2001
364.9
233.5
36%
131.3
2002
368.4
233.1
37%
135.3
2003
356.4
225.1
37%
131.3
2004
396.6
246.4
38%
150.2
2005
385.5
243.1
37%
142.3
•Ml These source categories include Iron and Steel Production. Lead Production, Zinc Production, Ammonia Manufacture, Carbon Black Manufacture
(included in Petrochemical Production). Titanium Dioxide Production. Ferroalloy Production. Silicon Carbide Production, and Aluminum Production.
Energy 3-19
-------
by a storage factor. For several fuel types—petrochemical
feedstocks (including natural gas for non-fertilizer uses, LPG,
pentanes plus, naphthas, other oils, still gas, special naphtha,
and industrial other coal), asphalt and road oil, lubricants,
and waxes —U.S. data on C stocks and flows were used to
develop C storage factors, calculated as the ratio of (a) the
C stored by the fuel's non-energy products to (b) the total
C content of the fuel consumed. A lifecycle approach was
used in the development of these factors in order to account
for losses in the production process and during use. Because
losses associated with municipal solid waste management are
handled separately in this sector under the Municipal Solid
Waste Combustion source category, the storage factors do not
account for losses at the disposal end of the life cycle. For
industrial coking coal and distillate fuel oil, storage factors
were taken from IPCC/UNEP/OECD/IEA (1997), which in
turn draws from Marland and Rotty (1984). For the remaining
fuel types (petroleum coke, miscellaneous products, and
other petroleum), IPCC does not provide guidance on storage
factors,, and assumptions were made based on the potential
fate of C in the respective NEU products.
Lastly, emissions were estimated by subtracting the
C stored from the potential emissions (see Table 3-11).
More detail on the methodology for calculating storage
and emissions from each of these sources is provided in
Annex 2.3.
\Vhere storage factors were calculated specifically for
the United States, data were obtained on (1) products such as
asphalt, plastics, synthetic rubber, synthetic fibers, cleansers
(soaps and detergents), pesticides, food additives, antifreeze
and deicers (glycols), and silicones; and (2) industrial
releases including volatile organic compound, solvent, and
non-combustion CO emissions, Toxics Release Inventory
(TRI) releases, hazardous waste incineration, and energy
recovery. Data were taken from a variety of industry sources,
government reports, and expert communications. Sources
include EPA reports and databases such as compilations of
air emission factors (EPA 1995,2001), National Air Quality
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Sector/Use
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical Plants,
Other Uses
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401 °F)
Other Oil (> 401 °F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc. Prod.)
Total
1990
4,223.7
0.0
8.2
278.4
1,170.2
1,119.1
186.3
77.3
325.7
677.2
21.3
81.0
100.9
7.0
33.3
137.8
176.0
176.0
86.7
0.7
86.0
4,486.4
1995
4,771.7
43.8
11.3
330.3
1,178.2
1,484.7
177.8
285.3
350.6
612.7
40.1
44.1
66.9
8.0
40.6
97.1
167.9
167.9
90.8
2.0
88.8
5,030.5
2000
5,261.2
62.8
12.4
421.3
1,275.7
1,604.6
189.9
228.7
592.8
554.3
12.6
47.8
94.4
11.7
33.1
119.2
179.4
179.4
165.5
16.4
149.1
5,606.1
2001
5,045.2
25.5
11.3
408.6
1,256.9
1,539.0
174.0
199.8
489.4
525.9
35.8
128.1
77.9
11.7
36.3
124.9
164.3
164.3
80.3
0.0
80.3
5,289.8
2002
5,032.3
46.4
12.0
364.6
1,240.0
1,565.4
171.9
166.1
564.2
456.2
57.8
110.2
99.5
11.7
32.2
134.2
162.4
162.4
138.6
1.5
137.2
5,333.3
2003
4,864.3
72.0
11.9
348.8
1,219.5
1,437.7
159.0
158.3
573.4
501.0
59.0
79.3
75.7
11.7
31.0
126.0
150.1
150.1
127.9
9.3
118.6
5,142.4
2004
5,295.4
214.7
11.9
340.2
1,303.9
1,435.9
161.0
156.4
687.5
547.5
63.5
169.8
47.2
11.7
30.8
113.4
152.1
152.1
136.6
10.0
126.6
5,584.1
2005
5,208.2
136.6
11.9
365.8
1,323.2
1,441.6
160.2
146.0
678.5
515.1
67.7
145.0
60.9
11.7
31.4
112.8
151.3
151.3
132.2
9.6
122.6
5,491.7
Note: To avoid double-counting, coal coke, petroleum coke, natural gas consumption, and other oils are adjusted for industrial process consumption
reported in the Industrial Processes sector. Natural gas, LPG, Pentanes Plus, Naphthas, Special Naphtha, and Other Oils are adjusted to account for exports
of chemical intermediates derived from these fuels. For residual oil (not shown in the table), all non-energy use is assumed to be consumed in C black
production, which is also reported in the Industrial Processes chapter.
Note: Totals may not sum due to independent rounding.
-------
Table 3-13:2005 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Sector/Fuel Type
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical Plants
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401 °F)
Other Oil (>401 °F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc. Prod.)
Total
Adjusted
Non-Energy
Use3
(TBtu)
5,208.2
136.6
11.9
365.8
1,323.2
1,441.6
160.2
146.0
678.5
515.1
67.7
145.0
60.9
11.7
31.4
112.8
151.3
151.3
132.2
9.6
122.6
5,491.7
Carbon
Content
(TgC)
99.4
4.2
0.3
5.3
27.3
24.2
3.2
2.7
12.3
10.3
1.2
4.0
1.2
0.2
0.6
2.3
3.1
3.1
2.6
0.2
2.5
105.1
Storage
Factor
-
0.10
0.61
0.61
1.00
0.61
0.09
0.61
0.61
0.61
0.61
0.50
0.61
0.50
0.58
0.00
-
0.09
-
0.09
0.10
Carbon
Stored
(TgC)
65.8
0.4
0.2
3.2
27.3
14.9
0.3
1.6
7.6
6.3
0.7
2.0
0.7
0.1
0.4
0.0
0.3
0.3
0.3
0.0
0.2
66.3
Carbon
Emissions
(TgC)
33.7
3.8
0.1
2.0
0.0
9.4
2.9
1.0
4.8
4.0
0.5
2.0
0.5
0.1
0.3
2.3
2.8
2.8
2.4
0.2
2.2
38.8
Carbon Emissions
(TgC02Eq.)
123.4
14.0
0.4
7.5
0.0
34.3
10.8
3.8
17.4
14.6
1.7
7.4
1.7
0.4
1.0
8.4
10.2
10.2
8.7
0.6
8.1
142.3
- Not applicable.
a To avoid double counting, exports have been deducted.
Note: Totals may not sum due to independent rounding.
and Emissions Trends Report (EPA 2006a), Toxics Release
Inventory, 1998 (2000a), Biennial Reporting System (EPA
2004a, 2006b), and pesticide sales and use estimates (EPA
1998, 1999, 2002, 2004b); the EIA Manufacturer's Energy
Consumption Survey (MECS) (EIA 1994, 1997, 2001,
2005); the National Petrochemical & Refiners Association
(NPRA 2001); the National Asphalt Pavement Association
(Connolly 2000); the Emissions Inventory Improvement
Program (EIIP 1998, 1999); the U.S. Census Bureau
(1999, 2003, 2004); the American Plastics Council (APC
2000, 2001, 2003, 2005, 2006; Eldredge-Roebuck 2000);
the Society of the Plastics Industry (SP1 2000); Bank of
Canada (2006); Financial Planning Association (2006);
INEGI (2006); Statistics Canada (2006); the United States
International Trade Commission (2006); the Pesticide
Action Network (PAN 2002); Gosselin, Smith, and Hodge
(1984); the Rubber Manufacturers' Association (RMA 2002,
2006; STMC 2003); the International Institute of Synthetic
Rubber Products (IISRP 2000, 2003); the Fiber Economics
Bureau (FEE 2001, 2003, 2005,2006); the Material Safety
Data Sheets (Miller 1999); the Chemical Manufacturer's
Association (CMA 1999); and the American Chemistry
Council (ACC 2005,2006.) Specific data sources are listed
in full detail in Annex 2.3.
An uncertainty analysis was conducted to quantify the
uncertainty surrounding the estimates of emissions and storage
factors from non-energy uses. This analysis, performed
using @RISK software and the IPCC-recommended Tier 2
methodology (Monte Carlo Simulation technique), provides
for the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results presented
below provide the 95 percent confidence interval, the range
of values within which emissions are likely to fall, for this
source category.
As noted above, the non-energy use analysis is based
on U.S.-specinc storage factors for (1) feedstock materials
(natural gas, LPG, pentanes plus, naphthas, other oils, still
-------
gas, special naphthas, and other industrial coal), (2) asphalt,
(3) lubricants, and (4) waxes. For the remaining fuel types
(the "other" category), the storage factors were taken directly
from the IPCC Guidelines for National Greenhouse Gas
Inventories, where available, and otherwise assumptions
were made based on the potential fate of carbon in the
respective NEU products. To characterize uncertainty, five
separate analyses were conducted, corresponding to each of
the five categories. In all cases, statistical analyses or expert
judgments of uncertainty were not available directly from
the information sources for all the activity variables; thus,
uncertainty estimates were determined using assumptions
based on source category knowledge.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-14 (emissions) and Table 3-15
(storage factors). Carbon emitted from non-energy uses of
fossil fuels in 2005 was estimated to be between 113.1 and
153.7 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 21 percent below to 8 percent above the
2005 emission estimate of 142.3 Tg CO2 Eq. The uncertainty
in the emission estimates is a function of uncertainty in both
the quantity of fuel used for non-energy purposes and the
storage factor.
In Table 3-15, feedstocks and asphalt contribute least
to overall storage factor uncertainty on a percentage basis.
Although the feedstocks category—the largest use category
in terms of total carbon flows —appears to have tight
confidence limits, this is to some extent an artifact of the
way the uncertainty analysis was structured. As discussed
in Annex 2.3, the storage factor for feedstocks is based on
an analysis of six fates that result in long-term storage (e.g.,
plastics production), and eleven that result in emissions (e.g.,
volatile organic compound emissions). Rather than modeling
the total uncertainty around all of these fate processes, the
current analysis addresses only the storage fates, and assumes
that all C that is not stored is emitted. As the production
statistics that drive the storage values are relatively well-
characterized, this approach yields a result that is probably
biased toward understating uncertainty.
As is the case with the other uncertainty analyses
discussed throughout this document, the uncertainty
results above address only those factors that can be readily
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Non-Energy Uses of Fossil Fuels
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.)
Feedstocks
Asphalt
Lubricants
Waxes
Other
Total
C02
C02
C02
C02
C02
CO,
81.9
0.0
21.6
1.0
37.9
142.3
Lower Bound
65.4
0.2
17.9
0.7
17.4
113.1
Upper Bound
98.1
0.7
25.0
1.5
40.1
153.7
Lower Bound
-20%
NA
-17%
-25%
-54%
-21%
Upper Bound
+20%
NA
+ 16%
+55%
+6%
+ 8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
NA (Not Applicable)
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels (Percent)
2005 Storage Factor
Source
Gas
Uncertainty Range Relative to Inventory Factor3
(%) (%, Relative)
Feedstocks
Asphalt
Lubricants
Waxes
Other
C02
C02
C02
C02
C02
61%
100%
9%
58%
22%
Lower Bound
59%
99%
4%
44%
20%
Upper Bound
63%
100%
18%
69%
64%
Lower Bound
-4%
-1%
-57%
-25%
-10%
Upper Bound
+3%
+0%
+90%
+20%
+ 189%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval, as a percentage of the inventory value
(also expressed in percent terms).
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
quantified. More details on the uncertainty analysis are
provided in Annex 2.3.
QA/QC and Verification
A source-specific QA/QC plan for non-energy uses of
fossil fuels was developed and implemented. This effort
included a Tier 1 analysis, as well as portions of a Tier
2 analysis for non-energy uses involving petrochemical
feedstocks. The Tier 2 procedures that were implemented
involved checks specifically focusing on the activity data
and methodology for estimating the fate of C (in terms of
storage and emissions) across the various end-uses of fossil
C. Emission and storage totals for the different subcategories
were compared, and trends across the time series were
analyzed to determine whether any corrective actions were
needed. Corrective actions were taken to rectify minor
errors and to improve the transparency of the calculations,
facilitating future QA/QC.
Recalculations Discussion
The methodology of the current Inventory reflects three
corrections and two minor changes. Plastics data from the
American Plastics Council includes some Mexican and
Canadian production in addition to U.S. production. In the
previous Inventory, the plastics geography correction was not
correctly accounting for Mexican and Canadian production
from 2002 through 2004. This correction caused an increase
in the quantity of C emitted by 0.64 Tg C, 0.98 Tg C, and
1.02 Tg C compared to the previously reported estimates for
2002 though 2004.
As noted earlier, there is some overlap between fossil
fuels consumed for non-energy uses and the fossil-derived
CO2 emissions accounted for in the Industrial Processes
chapter. For the current Inventory, for the first time, silicon
carbide production is reported as a specific industrial process.
To avoid double-counting of C emissions in the NEU section
and the Industrial Processes chapter, the quantity of petroleum
coke used as an input to silicon carbide was deducted from
the potential emissions covered in this chapter.
In addition, in the previous Inventory, the cleanser
consumption data was not properly accounting for data over
the whole time series. The update in the current Inventory
resulted in an increase in exports throughout the time series
and decreased C emissions across the time series. Also, in the
uncertainty analysis, Industrial Other Coal was previously
being counted as an Other rather than a Feedstock. The
calculations presented are now correctly accounting for
Industrial Other Coal.
Additionally, the oxidation factor for MECS data was
increased from 99 percent to 100 percent to be consistent
throughout the Energy and Industrial Processes chapters. This
change caused an increase in the quantity of C emitted by
0.10 to 0.20 Tg C compared to the previous Inventory.
Planned Improvements
There are several improvements planned for the
future:
• Updating the analysis to comply with IPCC (2006).
These changes will affect both the non-energy use and
industrial processes sections.
• Improving the uncertainty analysis. Most of the input
parameter distributions are based on professional
judgment rather than rigorous statistical characterizations
of uncertainty.
• Better characterizing flows of fossil C. Additional
"fates" may be researched, including the fossil C load
in organic chemical wastevvaters, plasticizers, adhesives,
films, paints, and coatings. There is also a need to further
clarify the treatment of fuel additives and backflows
(especially methyl tert-butyl ether, MTBE).
Finally, although U.S.-specific storage factors have been
developed for feedstocks, asphalt, lubricants, and waxes,
default values from IPCC are still used for two of the non-
energy fuel types (industrial coking coal and distillate oil),
and broad assumptions are being used for the remaining
fuels (petroleum coke, miscellaneous products, and other
petroleum). Over the long term, there are plans to improve
these storage factors by conducting analyses of C fate similar
to those described in Annex 2.3.
3.3. Stationary Combustion (excluding
C02) (IPCC Source Category 1A)
Stationary combustion encompasses all fuel combustion
activities from fixed sources (versus mobile combustion).
Other than CO2, which was addressed in the previous
section, gases from stationary combustion include the
Energy 3-23
-------
greenhouse gases CH4 and N2O and the indirect greenhouse
gases NOX, CO, and NMVOCs.31 Emissions of these gases
from stationary combustion sources depend upon fuel
characteristics, size and vintage, along with combustion
technology, pollution control equipment, and ambient
environmental conditions. Emissions also vary with
operation and maintenance practices.
N2O and NOX emissions from stationary combustion are
closely related to air-fuel mixes and combustion temperatures,
as well as the characteristics of any pollution control equipment
that is employed. Carbon monoxide emissions from stationary
combustion are generally a function of the efficiency of
combustion; they are highest when less oxygen is present in
the air-fuel mixture than is necessary for complete combustion.
These conditions are most likely to occur during start-up,
shutdown and during fuel switching (e.g., the switching of
coal grades at a coal-burning electric utility plant). CH4 and
NMVOC emissions from stationary combustion are primarily
a function of the CH4 and NMVOC content of the fuel and
combustion efficiency.
Emissions of CH4 decreased 13 percent overall since
1990 to 6.9 Tg CO2 Eq. (330 Gg) in 2005. This decrease in
CH4 emissions was primarily due to lower wood consumption
in the residential sector. Conversely, N2O emissions rose 12
percent since 1990 to 13.8 Tg CO2 Eq. (45 Gg) in 2005. The
largest source of N2O emissions was coal combustion by
electricity generators, which alone accounted for 65 percent
of total N2O emissions from stationary combustion in 2005.
Overall, however, stationary combustion is a small source
of CH4 and N2O in the United States.
Table 3-16 and Table 3-17 provide CH4 and N2O
emission estimates inTg CO2 Eq.; Table 3-18 and Table 3-19
present these estimates in Gg of each gas.
CH4 and N2O emissions were estimated by multiplying
fossil fuel and wood consumption data by emission factors
(by sector and fuel type). National coal, natural gas, fuel
oil, and wood consumption data were grouped by sector:
industrial, commercial, residential, electric power, and U.S.
territories. For the CH4 and N2O estimates, fuel consumption
data for coal, natural gas, and fuel oil for the United States
were obtained from EIA's Monthly Energy Review and
unpublished supplemental tables on petroleum product
Table 3-16: CH4 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
0.6
0.3
0.1
0.1
0.1
2.1
0.3
0.1
0.8
0.9
0.9
+
0.2
0.3
0.4
4.4
0.2
0.3
0.5
3.5
+
+
+
+
+
8.0
1995
0.6
0.4
+
0.1
0.1
2.3
0.3
0.1
0.9
1.0
0.9
+
0.1
0.3
0.4
4.0
0.1
0.3
0.5
3.1
+
+
+
+
+
7.8
2000
0.7
0.4
0.1
0.1
0.1
2.3
0.3
0.1
0.9
1.0
0.9
+
0.1
0.3
0.4
3.5
0.1
0.3
0.5
2.6
0.1
+
+
+
+
7.4
2001
0.7
0.4
0.1
0.1
0.1
2.1
0.3
0.1
0.8
0.9
0.9
+
0.1
0.3
0.4
3.1
0.1
0.3
0.5
2.2
0.1
+
0.1
+
+
6.8
2002
0.7
0.4
0.1
0.1
0.1
2.0
0.3
0.1
0.8
0.8
0.9
+
0.1
0.3
0.4
3.1
0.1
0.3
0.5
2.3
0.1
+
0.1
+
+
6.8
2003
0.7
0.4
0.1
0.1
0.1
2.0
0.3
0.1
0.8
0.8
0.9
+
0.2
0.3
0.4
3.3
0.1
0.3
0.5
2.4
0.1
+
0.1
+
+
7.0
2004
0.7
0.4
0.1
0.1
0.1
2.1
0.3
0.1
0.8
0.9
0.9
+
0.2
0.3
0.4
3.4
0.1
0.3
0.5
2.5
0.1
+
0.1
+
+
7.1
2005
0.7
0.4
0.1
0.1
0.1
1.9
0.3
0.1
0.7
0.7
0.9
+
0.1
0.3
0.4
3.4
0.1
0.3
0.5
2.5
0.1
+
0.1
+
+
6.9
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
1 Sulfur dioxide (SO2) emissions from stationary combustion are addressed in Annex 6.3.
•v in«;«*<•<
-------
Table 3-17: N20 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
7.6
7.1
0.2
0.1
0.2
3.2
0.7
0.6
0.2
1.7
0.4
0.1
0.2
0.1
0.1
1.1
+
0.3
0.1
0.7
0.1
+
0.1
+
+
12.3
1995
8.0
7.6
0.1
0.1
0.1
3.3
0.7
0.5
0.3
1.9
0.4
0.1
0.1
0.1
0.1
1.0
+
0.2
0.1
0.6
0.1
+
0.1
+
+
12.8
2000
9.3
8.8
0.2
0.2'
0.2
3.3
0.6
0.5
0.3
1.9
0.4
+
0.1
0.1
0.1
0.9
+
0.3
0.2
0.5
0.1
+
0.1
+
+
14.0
2001
9.1
8.5
0.2
0.2
0.1
3.1
0.6
0.5
0.2
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.4
0.1
+
0.1
+
+
13.5
2002
9.1
8.6
0.2
0.2
0.2
3.0
0.6
0.5
0.2
1.6
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.4
0.1
+
0.1
+
+
13.4
2003
9.4
8.8
0.2
0.2
0.2
2.9
0.6
0.5
0.2
1.6
0.4
+
0.1
0.1
0.1
0.9
+
0.3
0.2
0.5
0.1
+
0.1
+
+
13.7
2004
9.4
8.8
0.2
0.2
0.2
3.1
0.6
0.6
0.2
1.7
0.4
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
+
+
13.9
2005
9.6
9.0
0.2
0.2
0.2
2.8
0.6
0.6
0.2
1.5
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
+
+
13.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 3-18: CH4 Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
27
16
4
3
4
101
16
6
37
41
42
1
9
13
19
210
9
14
21
165
2
+
2
+
+
382
1995
27
18
2
4
4
110
15
5
42
47
43
1
7
15
21
190
5
13
24
148
2
+
2
+
+
373
2000
33
20
3
5
4
108
14
5
42
47
44
1
7
16
20
165
3
15
24
122
2
+
2
+
+
351
2001
32
20
4
5
4
99
14
6
38
41
42
1
7
15
19
147
4
15
23
105
3
+
3
+
+
324
2002
32
20
3
5
4
97
13
5
39
40
42
1
6
15
20
150
4
14
24
108
3
+
3
+
+
324
2003
34
20
4
5
5
96
13
6
38
39
44
1
7
16
20
158
4
15
25
114
3
+
3
+
+
334
2004
34
20
4
5
5
99
14
6
38
42
44
1
8
15
20
160
4
15
24
117
3
+
3
+
+
340
2005
35
21
4
6
5
89
13
6
35
35
43
1
7
15
20
160
3
14
24
120
3
+
3
+
+
330
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
-------
Table 3-19: N20 Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
24
23
1
+
+
10
2
2
1
5
1
+
1
+
+
4
+
1
+
2
+
+
+
+
+
40
1995
26
25
+
+
+
11
2
1
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
41
2000
30
28
1
1
1
11
2
2
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
45
2001
29
28
1
1
+
10
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
44
2002
29
28
1
1
1
10
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
43
2003
30
28
1
+
1
9
2
2
1
5
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
44
2004
30
28
1
1
1
10
2
2
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
45
2005
31
29
1
1
1
9
2
2
1
5
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
45
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
detail (EIA 2006a). Wood consumption data for the United
States was obtained from EIA's Annual Energy Review (EIA
2006b). Because the United States does not include territories
in its national energy statistics, fuel consumption data for
territories were provided separately by Grillot (2006).32 Fuel
consumption for the industrial sector was adjusted to subtract
out construction and agricultural use, which is reported
under mobile sources.33 Construction and agricultural fuel
use was obtained from EPA (2004). Estimates for wood
biomass consumption for fuel combustion do not include
wood wastes, liquors, municipal solid waste, tires, etc. that
are reported as biomass by EIA.
Emission factors for the four end-use sectors were
provided by the Revised 1996IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA
1997). U.S. territories' emission factors were estimated using
the U.S. emission factors for the primary sector in which
each fuel was combusted.
More detailed information on the methodology for
calculating emissions from stationary combustion, including
emission factors and activity data, is provided in Annex 3.1.
Uncertainty
CH4 emission estimates from stationary sources exhibit
high uncertainty, primarily due to difficulties in calculating
emissions from wood combustion (i.e., fireplaces and wood
stoves). The estimates of CH4 and N2O emissions presented
are based on broad indicators of emissions (i.e., fuel use
multiplied by an aggregate emission factor for different
sectors), rather than specific emission processes (i.e., by
combustion technology and type of emission control).
An uncertainty analysis was performed by primary fuel
type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo
Simulation technique, with @RISK software.
12 U.S. territories data also include combustion from mobile activities because data to allocate territories' energy use were unavailable. For this reason,
CH4 and N^O emissions from combustion by U.S. territories are only included in the stationary combustion totals.
•" Though emissions from construction and farm use occur due to both stationary and mobile sources, detailed data was not available to determine the
magnitude from each. Currently, these emissions are assumed to be predominantly from mobile sources.
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
The uncertainty estimation model for this source
category was developed by integrating the CH4 and N2O
stationary source inventory estimation models with the
model for CO2 from fossil fuel combustion to realistically
characterize the interaction (or endogenous correlation)
between the variables of these three models. A total of 115
input variables were simulated for the uncertainty analysis
of this source category (85 from the CO2 emissions from
fossil fuel combustion inventory estimation model and 30
from the stationary source inventory models).
In developing the uncertainty estimation model,uniform
distribution was assumed for all activity-related input
variables and N2O emission factors, based on the SAIC/
EIA (2001) report.34 For these variables, the uncertainty
ranges were assigned to the input variables based on the
data reported in SAIC/EIA (2001).35 However, the CH4
emission factors differ from those used by EIA. Since these
factors were obtained from IPCC/UNEP/OECD/IEA (1997),
uncertainty ranges were assigned based on IPCC default
uncertainty estimates (IPCC 2000).
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-20. Stationary combustion CH4
emissions in 2005 (including biomass) were estimated to be
between 4.8 and 14.7 Tg CO2 Eq. at a 95 percent confidence
level. This indicates a range of 30 percent below to 112
percent above the 2005 emission estimate of 6.9 Tg CO2 Eq.36
Stationary combustion N2O emissions in 2005 (including
biomass) were estimated to be between 10.8 and 39.9 Tg
CO2 Eq. at a 95 percent confidence level. This indicates a
range of 22 percent below to 189 percent above the 2005
emissions estimate of 13.8 Tg CO2 Eq.
The uncertainties associated with the emission
estimates of CH4 and N2O are greater than those associated
with estimates of CO2 from fossil fuel combustion, which
mainly rely on the carbon content of the fuel combusted.
Uncertainties in both CH4 and N2O estimates are due to the
fact that emissions are estimated based on emission factors
representing only a limited subset of combustion conditions.
For the indirect greenhouse gases, uncertainties are partly
due to assumptions concerning combustion technology types,
age of equipment, emission factors used, and activity data
projections.
QA/QC and Verification
A source-specific QA/QC plan for stationary combustion
was developed and implemented. This effort included a
Tier 1 analysis, as well as portions of a Tier 2 analysis. The
Tier 2 procedures that were implemented involved checks
specifically focusing on the activity data and emission factor
sources and methodology used for estimating CH4, N2O, and
the indirect greenhouse gases from stationary combustion in
the United States. Emission totals for the different sectors and
fuels were compared and trends were investigated.
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Stationary Combustion,
Including Biomass (Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Stationary Combustion
Stationary Combustion
CH4
N20
6.9
13.8
Lower Bound
4.8
10.8
Upper Bound
14.7
39.9
Lower Bound
-30%
-22%
Upper Bound
+ 112%
+ 189%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
14 SAIC/EIA (2001) characterizes the underlying probability density function for the input variables as a combination of uniform and normal
distributions (the former distribution to represent the bias component and the latter to represent the random component). However, for purposes of
the current uncertainty analysis, it was determined that uniform distribution was more appropriate to characterize the probability density function
underlying each of these variables.
i5 In the SAIC/EIA (2001) report, the quantitative uncertainty estimates were developed for each of the three major fossil fuels used within each
end-use sector; the variations within the sub-fuel types within each end-use sector were not modeled. However, for purposes of assigning uncertainty
estimates to the sub-fuel type categories within each end-use sector in the current uncertainty analysis, SAIC/EIA (2001 )-reported uncertainty estimates
were extrapolated.
1(1 The low emission estimates reported in this section have been rounded down to the nearest integer values and the high emission estimates have been
rounded up to the nearest integer values.
Energy 3-27
-------
Recalculations Discussion
Historical CH4 and N2O emissions from stationary
sources (excluding CO2) were revised due to several changes.
Slight changes to emission estimates for sectors are due to
revised data from EIA (2006a). This revision is explained in
greater detail in the section on CO2 Emissions from Fossil
Fuel Combustion within this sector. Wood consumption
data from EIA (2006b) were revised for the commercial/
institutional and residential sectors. The combination of the
methodological and historical data changes resulted in an
average annual increase of 0.2 Tg CO2 Eq. (2.0 percent) in
CH4 emissions from stationary combustion and an average
annual increase of 0.1 Tg CO2 Eq. (0.2 percent) in N2O
emissions from stationary combustion for the period 1990
through 2004.
Planned Improvements
Several items are being evaluated to improve the CH4
and N2O emission estimates from stationary combustion
and to reduce uncertainty. Efforts will be taken to work with
EIA and other agencies to improve the quality of the U.S.
territories data. Because these data are not broken out by
stationary and mobile uses, further research will be aimed at
trying to allocate consumption appropriately. In addition, the
uncertainty of biomass emissions will be further investigated
since it was expected that the exclusion of biomass from the
uncertainty estimates would reduce the uncertainty; and in
actuality the exclusion of biomass increases the uncertainty.
These improvements are not all-inclusive, but are part of an
ongoing analysis and efforts to continually improve these
stationary estimates.
3,4, Mobile Combustion (axciutiing
C02) (IPCC Source Category 1 A)
Mobile combustion produces greenhouse gases other
than CO2, including CH4, N2O, and indirect greenhouse
gases including NOX, CO, and NMVOCs. As with stationary
combustion, N2O and NOX emissions are closely related to
fuel characteristics, air-fuel mixes, combustion temperatures,
and the use of pollution control equipment. N2O, in particular,
can be formed by the catalytic processes used to control
NOX, CO, and hydrocarbon emissions. Carbon monoxide
emissions from mobile combustion are significantly
affected by combustion efficiency and the presence of post-
combustion emission controls. Carbon monoxide emissions
are highest when air-fuel mixtures have less oxygen than
required for complete combustion. These emissions occur
especially in idle, low speed, and cold start conditions.
CH4 and NMVOC emissions from motor vehicles are a
function of the CH4 content of the motor fuel, the amount
of hydrocarbons passing uncombusted through the engine,
and any post-combustion control of hydrocarbon emissions
(such as catalytic converters).
Emissions from mobile combustion were estimated
by transport mode (e.g., highway, air, rail), fuel type (e.g.
motor gasoline, diesel fuel, jet fuel), and vehicle type (e.g.
passenger cars, light-duty trucks). Road transport accounted
for the majority of mobile source fuel consumption, and
hence, the majority of mobile combustion emissions. Table
3-21 and Table 3-22 provide CH4 and N2O emission estimates
in Tg CO2 Eq.; Table 3-23 and Table 3-24 present these
estimates in Gg of each gas/"
Mobile combustion was responsible for a small portion
of national CH4 emissions (0.5 percent) but was the second
largest source of U.S. N2O emissions (8 percent). From
1990 to 2005, mobile source CH4 emissions declined by 45
percent, to 2.6 Tg CO, Eq. (125 Gg), due largely to control
technologies employed on highway vehicles since the mid-
1990s to reduce CO, NOX, NMVOC, and CH4 emissions.
Mobile source emissions of N2O decreased by 13 percent,
to 38.0 Tg CO2 Eq. Earlier generation control technologies
initially resulted in higher N2O emissions, causing a 26
percent increase in N2O emissions from mobile sources
between 1990 and 1998. Improvements in later-generation
emission control technologies have reduced N2O output,
resulting in a 31 percent decrease in mobile source N2O
emissions from 1998 to 2005. As a result, N2O emissions in
2005 were 13 percent lower than in 1990,at38.0TgCO2Eq.
(123 Gg) (see Figure 3-17). Overall, CH4 and N2O emissions
were predominantly from gasoline-fueled passenger cars and
light-duty trucks.
Methodology
Estimates of CH4 and N2O emissions from mobile
combustion were calculated by multiplying emission factors
by measures of activity for each fuel and vehicle type (e.g.,
light-duty gasoline trucks). Activity data included vehicle
57 See Annex 3.2 for a complete time series of emission estimates for 1990 through 2005.
3-28 inventory of U.S., Greenhouse Gas ?rnis-;ions aisri S^s: i9i;0-2'S05
-------
Figure 3-17
60-
50-
40
30
20
10
0J
Mobile Source CH4 and N20 Emissions
N20
CH4
oioioioioioioiaiajo)
ooo
ooo
miles traveled (VMT) for highway (on-road) vehicles and
fuel consumption for non-road mobile sources. The activity
data and emission factors used are described in the subsections
that follow. A complete discussion of the methodology used to
estimate emissions from mobile combustion and the emission
factors used in the calculations is provided in Annex 3.2.
EPA (2006c), EPA (2005) and EPA (2003) provide
emission estimates of NOX, CO, and NMVOCs for eight
categories of highway vehicles,38 aircraft, and seven
categories of non-highway vehicles.39 These emission
estimates primarily reflect EPA data, which, in final iteration,
will be published on the National Emission Inventory (NEI)
Air Pollutant Emission Trends web site. The methodology
used to develop these estimates can be found on EPA's Air
Pollutant Emission Trends website, at .
Highway V;"fH;ie;j
Estimates of CH4 and N2O emissions from gasoline and
diesel highway vehicles are based on VMT and emission
factors by vehicle type, fuel type, model year, and control
technology. Emission estimates from alternative fuel vehicles
(AFVs)40 are based on VMT and emission factors by vehicle
and fuel type.
Emission factors for gasoline and diesel highway
vehicles utilizing Tier 2 and Low Emission Vehicle (LEV)
Table 3-21: CH4 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel Type/Vehicle Type3
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other"
Total
1990
4.2
2.6
1.4
0.2
+
+
+
+
+
+
0.5
0.1
0.1
0.2
0.1
+
0.1
4.7
1995
3.8
2.1
1.4
0.2
+
+
+
+
+
+
0.5
0.1
0.1
0.1
0.1
0.1
0.1
4.3
2000
2.8
1.6
1.1
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.2
0.1
0.1
0.1
3.5
2001
2.6
1.5
1.0
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.1
0.1
0.1
0.1
3.2
2002
2.4
1.4
1.0
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.1
0.1
0.1
0.1
3.1
2003
2.2
1.2
0.9
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.1
0.1
0.1
0.1
2.9
2004
2.1
1.2
0.8
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.1
0.1
0.1
0.1
2.8
2005
1.9
1.1
0.8
0.1
+
+
+
+
+
+
0.6
0.1
0.1
0.1
0.1
0.1
0.1
2.6
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
a See Annex 3.2 for definitions of highway vehicle types.
b "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment.
w These categories included: gasoline passenger cars, diesel passenger cars, light-duty gasoline trucks less than 6,000 pounds in weight, light-duty
gasoline trucks between 6,000 and 8,500 pounds in weight, light-duty diesel trucks, heavy-duty gasoline trucks and buses, heavy-duty diesel trucks and
buses, and motorcycles.
39 These categories included: locomotives, marine vessels, farm equipment, construction equipment, other off-highway liquid fuel (e.g. recreational
vehicles and lawn and garden equipment), and other off-highway gaseous fuel (e.g., other off-highway equipment running on compressed natural gas).
40 Alternative fuel and advanced technology vehicles are those that can operate using a motor fuel other than gasoline or diesel. This includes electric or
other bifuel or dual fuel vehicles that may be partially powered by gasoline or diesel.
-------
Table 3-22: N20 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990
40.1
25.4
14.1
0.6
+
0.2
+
+
0.2
0.1
3.4
0.4
0.3
1.7
0.2
0.3
0.4
43.7
1995
49.8
26.9
22.1
0.7
+
0.3
+
+
0.2
0.1
3.6
0.4 ,
0.3
1.7
0.3
0.4
0.5
53.7
2000
48.8
24.7
23.3
0.9
+
0.3
+
+
0.3
0.1
4.0
0.5
0.3
1.9
0.3
0.4
0.5
53.2
2001
45.5
23.2
21.4
0.9
+
0.3
+
+
0.3
0.1
3.8
0.3
0.3
1.8
0.3
0.5
0.6
49.7
2002
42.8
21.9
20.0
0.9
+
0.3
+
+
0.3
0.1
3.9
0.5
0.3
1.7
0.3
0.5
0.6
47.1
2003
39.5
20.3
18.2
0.9
+
0.3
+
+
0.3
0.1
3.9
0.4
0.3
1.7
0.3
0.5
0.6
43.8
2004
36.7
18.8
17.0
0.9
+
0.3
+
+
0.3
0.1
4.0
0.5
0.3
1.7
0.4
0.5
0.6
41.2
2005
33.4
17.0
15.6
0.8
+
0.3
+
+
0.3
0.1
4.1
0.5
0.4
1.8
0.4
0.5
0.6
38.0
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
*"0ther" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment.
Table 3-23: CH4 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990
201
125
65
10
1
1
+
+
1
+
24
3
3
7
4
2
3
226
1995
180
101
69
9
1
1
+
+
1
+
26
4
3
7
5
3
3
207
2000
135
76
53
5
1
1
+
+
1
1
28
5
3
7
5
3
4
165
2001
124
70
49
5
1
1
+
+
1
1
27
3
3
7
6
3
4
154
2002
115
65
45
4
1
1
+
+
1
2
28
4
3
7
6
3
4
146
2003
106
59
42
4
1
1
+
+
1
2
28
4
3
6
6
4
4
136
2004
99
56
39
4
1
1
+
+
1
2
29
5
4
7
6
4
4
131
2005
92
51
37
3
1
1
+
+
1
2
30
5
4
7
7
4
4
125
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
*"0ther" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment.
technologies were developed by ICF (2006b); all other vehicle and control technology types. The EPA, CARB and
gasoline and diesel highway vehicle emissions factors Environment Canada tests were designed following the
were developed by ICF (2004). These factors were derived Federal Test Procedure (FTP), which covers three separate
from EPA, California Air Resources Board (CARB) and driving segments, since vehicles emit varying amounts of
Environment Canada laboratory test results of different GHGs depending on the driving segment. These driving
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1900-2005
-------
Table 3-24: N20 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990 J,
129 1
82 • "-,
45 ::
2 -
+ '..'
1 ;;^
+ ,\-c
+ »'
1 *;.=.,
+ /"•
11 -• .
1 if.
1 f-
63>
fg -
1 -V
1 1>
1 14;
141 ^
1995 ,
161
87
71
2
+ -'-'
1
+
+ ,
1 '•'
+ ">'.•
12 '.-,
1 1". *
1 :/
5 ;••
1 ;~v
1 '*
2;^r
173 ^ "
2000
158
80
75
3
+
1
+
+
1
+
13
2
1
6
1
1
2
172
2001
147
75
69
3
+
1
+
+
1
+
12
1
1
6
1
1
2
160
2002
138
71
65
3
+
1
+
+
1
+
13
2
1
6
1
2
2
152
2003
127
66
59
3
+
1
+
+
1
+
12
1
1
5
1
2
2
141
2004
118
61
55
3
+
1
+
+
1
+
13
2
1
6
1
2
2
133
2005
108
55
50
3
+
1
+
+
1
+
13
2
1
6
1
2
2
123
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
*"0ther" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment.
segments are: (1) a transient driving cycle that includes
cold start and running emissions, (2) a cycle that represents
running emissions only, and (3) a transient driving cycle that
includes hot start and running emissions. For each test run, a
bag was affixed to the tailpipe of the vehicle and the exhaust
was collected; the content of this bag was then analyzed
to determine quantities of gases present. The emissions
characteristics of segment 2 were used to define running
emissions, and subtracted from the total FTP emissions to
determine start emissions. These were then recombined
based upon the ratio of start to running emissions for each
vehicle class from MOBILE6.2 to approximate average
driving characteristics.
Emission factors for AFVs were developed by ICF
(2006a) after examining Argonne National Laboratory's
GREET 1.7-Transportation Fuel Cycle Model (ANL 2006)
and Lipman and Delucchi (2002). These sources describe
AFV emission factors in terms of ratios to conventional
vehicle emission factors. Ratios of AFV to conventional
vehicle emissions factors were then applied to estimated
Tier 1 emissions factors from light-duty gasoline vehicles
to estimate light-duty AFVs. Emissions factors for heavy-
duty AFVs were developed in relation to gasoline heavy-
duty vehicles. A complete discussion of the data source and
methodology used to determine emission factors from AFVs
is provided in Annex 3.2.
Annual VMT data for 1990 through 2005 were obtained
from the Federal Highway Administration's (FHWA)
Highway Performance Monitoring System database as
reported in Highway Statistics (FHWA 1996 through 2006).
VMT was then allocated from FHWA's vehicle categories to
fuel-specific vehicle categories using the calculated shares
of vehicle fuel use for each vehicle category by fuel type
reported in DOE (1993 through 2006) and information on
total motor vehicle fuel consumption by fuel type from
FHWA (1996 through 2006). VMT for AFVs were taken from
Browning (2003). The age distributions of the U.S. vehicle
fleet were obtained from EPA (2006e) and EPA (2000), and
the average annual age-specific vehicle mileage accumulation
of U.S. vehicles were obtained from EPA (2000).
Control technology and standards data for highway
vehicles were obtained from EPA's Office of Transportation
and Air Quality (EPA 2006a, 2006b, 2000,1998, and 1997)
and Browning (2005). These technologies and standards are
defined in Annex 3.2, and were compiled from EPA (1993),
EPA (1994a), EPA (1994b), EPA (1998), EPA (1999a), and
IPCC/UNEP/OECD/IEA (1997).
Energy 3-31
-------
These emission estimates were obtained from preliminary
data (EPA 2006c), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site.
Non- Highwav Vehicles
To estimate emissions from non-highway vehicles,
fuel consumption data were employed as a measure of
activity, and multiplied by fuel-specific emission factors (in
grams of N2O and CH4 per kilogram of fuel consumed).41
Activity data were obtained from AAR (2006), APTA
(2006), BEA (1991 through 2005), Benson (2002 through
2004), DOE (1993 through 2006), DESC (2006), DOC
(1991 through 2006), DOT (1991 through 2006), EIA
(2006a), EIA (2006b), EIA (2004), EIA (2002), EIA (1991
through 2006), EPA (2006e), Esser (2003 through 2004),
FAA (2006a and 2006b), Lou (2002), and Whorton (2006).
Emission factors for non-highway modes were taken from
IPCC/UNEP/OECD/IEA (1997).
Uncertainty
This section discusses the uncertainty of the emission
estimates for CH4 and N2O. Uncertainty was analyzed
separately for highway vehicles and non-highway vehicles
due to differences in their characteristics and their
contributions to total mobile source emissions.
A quantitative uncertainty analysis was conducted
for the highway portion of the mobile source sector using
the IPCC-recommended Tier 2 uncertainty estimation
methodology, Monte Carlo Simulation technique, using
@RISK software. The uncertainty analysis was performed
on 2005 estimates of CH4 and N2O emissions, incorporating
probability distribution functions associated with the major
input variables. For the purposes of this analysis, the
uncertainty was modeled for the following two major sets
of input variables: (1) vehicle miles traveled (VMT) data,
by vehicle and fuel type and (2) emission factor data, by
vehicle, fuel, and control technology type.
The emission factors for highway vehicles used in the
Inventory were obtained from ICE (2006b) and ICE (2004).
These factors were based on laboratory testing of vehicles.
While the controlled testing environment simulates real
driving conditions, emission results from such testing can
only approximate real world conditions and emissions.
For some vehicle and control technology types, the testing
did not yield statistically significant results within the 95
percent confidence interval, requiring expert judgment to
be used in developing the emission factors. In those cases,
the emission factors were developed based on comparisons
of fuel consumption between similar vehicle and control
technology categories.
The estimates of VMT for highway vehicles by vehicle
type in the United States were provided by FHWA (1996
through 2006), and were generated through the cooperation
of FHWA and state and local governments. While the
uncertainty associated with total U.S. VMT is believed to
be low, the uncertainty within individual source categories
was assumed to be higher given uncertainties associated with
apportioning total VMT into individual vehicle categories,
by fuel type, by technology type, and equipment age.
A significant amount of uncertainty is associated with
the emission estimates for non-road sources. A primary
cause is a large degree of uncertainty regarding emission
factors. The IPCC Good Practice Guidance reports that
CH4 emissions from aviation and marine sources may be
uncertain by a factor of two, while N2O emissions may be
uncertain by an order of magnitude for marine sources and
several orders of magnitude for aviation. No information
is provided on the uncertainty of emission factors for other
non-highway sources.
Fuel consumption data have a lower uncertainty than
emission factors, though large uncertainties do exist for
individual sources.
The results of the Tier 2 quantitative uncertainty analysis
are stimmarized in Table 3-25. Mobile combustion CH4
emissions in 2005 were estimated to be between 2.5 and 2.8
Tg CO2 Eq. at a 95 percent confidence level (or in 19 out
of 20 Monte Carlo Simulations). This indicates a range of 6
percent below to 6 percent above the 2005 emission estimate
of 2.6 Tg CO2 Eq. Also at a 95 percent confidence level,
mobile combustion N2O emissions in 2005 were estimated
to be between 31.0 and 45.0 Tg CO2 Eq., indicating a range
41 The consumption of international bunker fuels is not included in these activity data, but is estimated separately under the International Bunker Fuels
source category.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Mobile Combustion
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mobile Sources
Mobile Sources
CH4
N20
2.6
38.0
2.5 2.8 -6% +6%
31.0 45.0 -18% +19%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
of 18 percent below to 19 percent above the 2005 emission
estimate of 38.0 Tg CO2 Eq.
This uncertainty analysis is a continuation of a multi-
year process for developing quantitative uncertainty estimates
for this source category using the 1PCC Tier 2 approach to
uncertainty analysis. As a result, as new information becomes
available, uncertainty characterization of input variables may
be improved and revised.
QA/QC and Verification
A source-specific QA/QC plan for mobile combustion
was developed and implemented. This effort included a
Tier 1 analysis, as well as portions of a Tier 2 analysis.
The Tier 2 procedures focused on the emission factor and
activity data sources, as well as the methodology used for
estimating emissions. These procedures included a qualitative
assessment of the emissions estimates to determine whether
they appear consistent with the most recent activity data
and emission factors available. A comparison of historical
emissions between the current Inventory and the previous
Inventory was also conducted to ensure that the changes in
estimates were consistent with the changes in activity data
and emission factors.
Recalculations Discussion
In order to ensure that these estimates are continuously
improved, the calculation methodology is revised annually
based on comments from internal and external reviewers. A
number of adjustments were made to the historical data used
in calculating emissions in the current Inventory.
For highway sources, vehicle age distributions for 1999
to the present were revised based on new data obtained
from EPA's MOVES model (EPA 2006e). Diesel fractions
for light trucks and medium-heavy trucks for 1998 through
2003 were updated based on data obtained from the
Transportation Energy Data Book (DOE 2006). The highway
vehicle emissions estimation procedures now include a new
gasoline vehicle emission control technology, Tier 2, and
updated emissions factors for LEVs (ICE 2006b). These
changes resulted in a reduction in gasoline highway vehicle
emissions from 1996 onward, and most notably since 2002.
In addition, revisions were made to both the light-duty
and heavy-duty alternative fuel vehicle (AFV) emissions
factors (ICE 2006a), which resulted in an increase in N9O
emissions and a decrease in CH4 from AFVs. Lastly, VMT
and fuel consumption estimates for non-highway vehicles
were revised for 2004 based on updated data from FHWA's
Highway Statistics (FHWA 1996 through 2006).
Several improvements and updates were also made
in the calculation of emissions from non-road vehicles.
Commercial aircraft energy consumption estimates now
come from the Federal Aviation Administration's (FAA)
System for Assessing Aviation's Global Emissions (SAGE)
database (FAA 2006b), rather than from the Bureau of
Transportation Statistics. This change increased estimates
of fuel consumption and emissions attributed to commercial
aircraft, but does not affect the total aircraft emissions figures,
since the "Other Aviation" category was eliminated. Class
II and 111 railroad diesel use estimates for 2002 and 2004
were obtained from the American Short Line and Regional
Railroad Association (Whorton 2006), instead of the Upper
Great Plains Institute. EPA's updated NONROAD model
was used to recalculate fuel consumption for non-highway
mobile sources.
As a result of these changes, average estimates of CH4
and N2O emissions from mobile combustion were slightly
higher—showing an increase of no more than 0.32 Tg CO, Eq.
(less than 0.6 percent) each year—for the period 1990 through
2000. In contrast, emissions estimates were lower in every year
between 2001 and 2004, compared to last year's inventory.
Specifically, estimates decreased 1.16 Tg CO9 Eq. (2.4 percent)
in 2003 and 1.83 Tg CO2 Eq. (4 percent) in 2004.
Energy 3-33
-------
Planned Improvements
While the data used for this report represent the most
accurate information available, four areas have been
identified that could potentially be improved in the short-
term given available resources:
1) Improve estimation of VMT and fuel consumption
by vehicle type (e.g., passenger car, light-duty truck,
heavy-duty truck, bus): Potential improvements in the
breakdown of VMT and fuel consumption by vehicle type
could be developed based on further investigation of the
methodologies and data sources used. Estimates of motor
vehicle travel and fuel consumption by vehicle type are
taken from FHWA's Highway Statistics (FHWA 1996 to
2006), which in turn are based on data from the Highway
Performance Monitoring System, fuel tax receipts, Vehicle
Inventory and Use Survey (VIUS), and other sources. FHWA
annually updates only the most recent year of historical
VMT and fuel consumption estimates (for instance, only the
2004 estimates in 2005 Highway Statistics are recalculated,
while 1990-2003 remain constant). Additional data might
help to develop improved estimates of historical VMT and
fuel consumption by vehicle type going back through 1990.
Moreover, the shares of VMT associated with each vehicle
type reported by FHWA are quite different from estimates
used in EPA's MOBILE model, and these differences should
be investigated.
2) Improve the process of apportioning VMT by vehicle
type to each fuel type: The current inventory process for
estimating VMT by vehicle/fuel type category involves
apportioning VMT by vehicle type to each fuel type on
the basis of fuel consumption. While this is a reasonable
simplification, this approach implicitly assumes the same
average fuel economy for gasoline and diesel vehicles.
A more accurate apportionment of VMT by fuel type for
light-duty trucks and medium/heavy-duty trucks could
potentially be developed using data on vehicle travel from
the Vehicle Inventory and Use Survey (U.S. Census Bureau
2000) and other publications, or using VMT breakdowns
by vehicle/fuel type combinations from the MOBILE6 or
MOVES models.
3) Continue the Reconciliation of Fuel Consumption
Estimates used for Calculating N2OICH4 and CO2: Estimates
of transportation fuel consumption by fuel type from EIA
are used as the basis for estimating CO2 emissions from the
transportation sector. These estimates are then apportioned
to mode and vehicle category based on "bottom up"
estimates of fuel consumption from sources such as FHWA's
Highway Statistics (FHWA 1996 through 2006) and DOE's
Transportation Energy Data Book (DOE 1993 through
2006). These sources are also used to develop N2O and CH4
estimates. The EPA fuel consumption estimates, however,
differ from the estimates derived using "bottom up'" sources.
For this Inventory, estimates of distillate fuel consumption
have been reconciled. Potential improvements include
reconciling additional fuel consumption estimates from EIA
and other data sources, and revising the current process of
allocating CO2 emissions to particular vehicle types.
4) Continue to examine ways to utilize EPA's MOVES
model in the development of the Inventory estimates,
including use for uncertainty analysis: Although the
inventory uses some of the underlying data from MOVES,
such as vehicle age distributions by model year, MOVES is
not used directly in calculating mobile source emissions. The
use of MOVES should be further explored.
3.5. Coal Mining (IPCC Source
Category 1B1 a)
Three types of coal-mining-related activities release CH4
to the atmosphere: underground mining, surface mining, and
post-mining (i.e., coal-handling) activities. Underground coal
mines contribute the largest share of CH4 emissions. All 115
gassy underground coal mines in the United States employ
ventilation systems to ensure that CH4 levels remain within
safe concentrations. These systems can exhaust significant
amounts of CH4 to the atmosphere in low concentrations.
Additionally, 24 U.S. coal mines supplement ventilation
systems with degasification systems. Degasification systems
are wells drilled from the surface or boreholes drilled inside
the mine that remove large volumes of CH4 before, during,
or after mining. In 2005, 13 coal mines collected CH4 from
degasification systems and sold this gas to a pipeline, thus
reducing emissions to the atmosphere. In addition, one coal
mine used CH4 from its degasification system to heat mine
ventilation air on site. Two of the coal mines that sold gas
to pipelines also used CH4 to generate electricity or fuel a
thermal coal dryer. Surface coal mines also release CH4 as
the overburden is removed and the coal is exposed, but the
level of emissions is much lower than from underground
mines. Finally, some of the CH4 retained in the coal after
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 3-26: CH4 Emissions from Coal Mining (Tg C02 Eq.)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
Total
1990
62.1
67.6
(5.6)
10.4
7.7
1.7
81.9
1995
49.2
61.6
(12.4)
8.9
6.9
1.4 -
66.5
2000
39.1
53.9
(14.8)
8.8
6.7
1.4
55.9
2001
38.1
54.5
(16.5)
9.2
6.8
1.5
55.5
2002
35.4
52.7
(17.4)
8.8
6.4
1.4
52.0
2003
35.8
51.3
(15.5)
8.4
6.4
1.4
52.1
2004
37.9
53.9
(16.0)
8.6
6.6
1.4
54.5
2005
35.6
50.6
(15.0)
8.9
6.4
1.4
52.4
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-27: CH4 Emissions from Coal Mining (Gg)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
Total
1990
2,955
3,220
(265)
497
367
81 ..:..
3,899
1995
2,343 l
2,935
(592)
425
328
69 ;,"
3,165
2000
1,860
2,565
(704)
417
317
68
2,662
2001
1,812
2,596
(784)
438
323
71
2,644
2002
1,684
2,511
(827)
420
304
68
2,476
2003
1,707
2,443
(736)
402
305
65
2,480
2004
1,803
2,565
(762)
411
315
67
2,597
2005
1,696
2,408
(712)
425
305
69
2,494
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
mining is released during processing, storage, and transport
of the coal.
Total CH4 emissions in 2005 were estimated to be 52.4
Tg CO2 Eq. (2,494 Gg), a decline of 36 percent since 1990
(see Table 3-26 and Table 3-27). Of this amount, underground
mines accounted for 68 percent, surface mines accounted
for 17 percent, and post-mining emissions accounted for 15
percent. The decline in CH4 emissions from underground
mines from 1996 to 2002 was the result of the reduction of
overall coal production, the mining of less gassy coal, and an
increase in CH4 recovered and used. CH4 emissions increased
slightly in 2003 due to additional gas drainage being vented
to the atmosphere and a reduction in CH4 recovery. Although
overall emissions declined, recovery decreased again in 2005
with reduced production from pre-drainage wells, increased
use of horizontal gob wells that are vented to the atmosphere,
and temporary closure of a major project due to a mine fire.
Surface mine emissions and post-mining emissions remained
relatively constant from 1990 to 2005.
Methodology
The methodology for estimating CH4 emissions from
coal mining consists of two parts. The first part involves
estimating CH4 emissions from underground mines. Because
of the availability of ventilation system measurements,
underground mine emissions can be estimated on a mine-by-
mine basis and then summed to determine total emissions.
The second step involves estimating emissions from surface
mines and post-mining activities by multiplying basin-
specific coal production by basin-specific emission factors.
Underground mines. Total CH4 emitted from
underground mines was estimated as the sum of CH4
liberated from ventilation systems and CH4 liberated by
means of degasification systems, minus CH4 recovered and
used. The Mine Safety and Heath Administration (MSHA)
samples CH4 emissions from ventilation systems for all
mines with detectable42 CH4 concentrations. These mine-
by-mine measurements are used to estimate CH4 emissions
from ventilation systems.
Some of the higher-emitting underground mines also
use degasification systems (e.g., wells or boreholes) that
remove CH4 before, during, or after mining. This CH4
can then be collected for use or vented to the atmosphere.
Various approaches were employed to estimate the quantity
of CH4 collected by each of the twenty-four mines using
these systems, depending on available data. For example,
42 MSHA records coal mine CH4 readings with concentrations of greater than 50 ppm (parts per million) CH4. Readings below this threshold are
considered non-detectable.
Energy 3-35
-------
some mines report to EPA the amount of CH4 liberated from
their degasification systems. For mines that sell recovered
CH4 to a pipeline, pipeline sales data published by state
petroleum and natural gas agencies were used to estimate
degasification emissions. For those mines for which no
other data are available, default recovery efficiency values
were developed, depending on the type of degasification
system employed.
Finally, the amount of CH4 recovered by degasification
systems and then used (i.e., not vented) was estimated. In
2005, thirteen active coal mines sold recovered CH4 into
the local gas pipeline networks, while one coal mine used
recovered CH4 on site. Emissions avoided for these projects
were estimated using gas sales data reported by various
state agencies. For most mines with recovery systems,
companies and state agencies provided individual well
production information, which was used to assign gas sales
to a particular year. For the few remaining mines, coal mine
operators supplied information regarding the number of years
in advance of mining that gas recovery occurs.
Surface Mines and Post-Mining Emissions. Surface
mining and post-mining CH4 emissions were estimated by
multiplying basin-specific coal production. obtained from the
Energy Information Administration's Annual Coal Report
(see Table 3-28) (EIA 2006), by basin-specific emission
factors. Surface mining emission factors were developed by
Table 3-28: Coal Production (Thousand Metric Tons)
assuming that surface mines emit two times as much CH4
as the average in situ CH4 content of the coal. Revised data
on in situ CH4 content and emissions factors are taken from
EPA(1996) and AAPG (1984).This calculation accounts for
CH4 released from the strata surrounding the coal seam. For
post-mining emissions, the emission factor was assumed to
be 32.5 percent of the average in situ CH4 content of coals
mined in the basin.
Uncertainty
A quantitative uncertainty analysis was conducted for the
coal mining source category using the IPCC-recommended
Tier 2 uncertainty estimation methodology. Because emission
estimates from underground ventilation systems were
based on actual measurement data, uncertainty is relatively
low. A. degree of imprecision was introduced because the
measurements used were not continuous but rather an
average of quarterly instantaneous readings. Additionally,
the measurement equipment used can be expected to have
resulted in an average of 10 percent overestimation of annual
CH4 emissions (Mutmansky and Wang 2000). Estimates of
CH4 liberated and recovered by degasification systems are
relatively certain because many coal mine operators provided
information on individual well gas sales and mined through
dates. Many of the recovery estimates use data on wells within
100 feet of a mined area. Uncertainty also exists concerning the
radius of influence of each well. The number of wells counted,
and thus the avoided emissions, may increase if the drainage
area is found to be larger than currently estimated.
Compared to underground mines, there is considerably
more uncertainty associated with surface mining and post-
mining emissions because of the difficulty in developing
accurate emission factors from field measurements. However,
since underground emissions comprise the majority of total
coal mining emissions, the uncertainty associated with
underground emissions is the primary factor that determines
overall uncertainty. The results of the Tier 2 quantitative
uncertainty analysis are summarized in Table 3-29. Coal
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg C02 Eq. and Percent)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Underground
384,250
359,477
338,173
345,305
324,219
320,047
333,449
334,404
Surface
546,818
577,638
635,592
676,142
667,619
651,251
674,551
691,460
Total
931,068
937,115
973,765
1,021,446
991,838
971,297
1,008,000
1,025,864
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate8
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Coal Mining
CH4
52.4
49.8
58.7
-5%
+ 12%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
mining CH4 emissions in 2005 were estimated to be between
49.8 and 58.7 Tg CO2 Eq. at a 95 percent confidence level.
This indicates a range of 5 percent below to 12 percent above
the 2005 emission estimate of 52.4 Tg CO2 Eq.
Recalculations Discussion
In 2005, recalculations of emissions avoided at three
Jim Walter Resources (JWR) coal mines in Alabama were
performed because the mining company provided mine
maps describing mined-out areas for each month from 2000
through 2005. In previous Inventories, emissions-avoided
calculations for any pre-drainage wells at JWR coal mines
were based on publicly-available data records from the
Alabama State Oil & Gas Board. Also in previous Inventories,
emission reductions were calculated for pre-drainage wells
that were located inside the mine plan boundaries and were
declared "shut-in" by the O&G Board. In recent years, JWR
had mined-through numerous pre-drainage wells that were
subsequently converted to gob wells for further coal mine
degasification. Because they were never shut in, emissions
avoided were not calculated.
The mine maps provided by JWR allowed for a more
accurate accounting as to when and which pre-drainage
wells should be included in the emissions avoided
calculations. As a result, recalculations were performed on
years 2000 through 2004. The most pronounced changes to
the Inventory were made in the years 2003 through 2004,
where corrections led to an overall reduction of emissions
in 2003 and 2004 by 2.7 and 1.8 Tg CO, Eq., respectively.
Minor changes were made to JWR emissions avoided for
1995 through 1996 as well.
For the current Inventory, recalculations were performed
on all years, with negligible changes in 1994, 1996, and
1998 through 2002, as QA/QC of databases uncovered
that emissions avoided had been miscalculated. Some
recalculations were done in 2003 on Alabama mines but were
not linked retroactively. These recalculations either led to
no change in net emissions, or a change of 0.1 Tg CO, Eq.
Emissions avoided for 2003 were adjusted downward as a
major operator reported in 2004 that double-counting of some
pre-drainage wells had previously occurred. Correction of
this error led to a reduction in emissions avoided of 1.0 Tg
CO2 Eq., which contributed to the reduction in emissions in
2003 from 54.8 to 52.1 Tg CO, Eq.
3,6= Abandoned Underground Coal
IVIines (IPCC Source Category 181 a)
All underground and surface coal mining liberates
CH4 as part of the normal mining operations. The amount
of CH4 liberated depends on the amount that resides in the
coal ("in situ") and surrounding strata when mining occurs.
The in-situ CH4 content depends upon the amount of CH4
created during the coal formation (i .e., coalification) process,
and the geologic characteristics of the coal seams. During
coalification, more deeply buried deposits tend to generate
more CH4 and retain more of the gas after uplift to minable
depths. Deep underground coal seams generally have higher
CH4 contents than shallow coal seams or surface deposits.
Underground coal mines contribute the largest share of
CH4 emissions, with active underground mines the leading
source of underground emissions. However, mines also
continue to release CH4 after closure. As mines mature
and coal seams are mined through, mines are closed and
abandoned. Many are sealed and some flood through intrusion
of groundwater or surface water into the void. Shafts or
portals are generally filled with gravel and capped with a
concrete seal, while vent pipes and boreholes are plugged
in a manner similar to oil and gas wells. Some abandoned
mines are vented to the atmosphere to prevent the buildup
of CH4 that may find its way to surface structures through
overburden fractures. As work stops within the mines, the
CH4 liberation decreases but it does not stop completely.
Following an initial decline, abandoned mines can liberate
CH4 at a near-steady rate over an extended period of time,
or, if flooded, produce gas for only a few years. The gas
can migrate to the surface through the conduits described
above, particularly if they have not been sealed adequately. In
addition, diffuse emissions can occur when CH4 migrates to
the surface through cracks and fissures in the strata overlying
the coal mine. The following factors influence abandoned
mine emissions:
• Time since abandonment;
• Gas content and adsorption characteristics of coal;
• CH4 flow capacity of the mine:
• Mine flooding;
• Presence of vent holes; and
• Mine seals.
Energy 3-37
-------
Table 3-30: CH4 Emissions from Abandoned Underground Coal Mines (Tg C02 Eq.)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
Abandoned Underground Mines 6.0
Recovered & Used 0.0
8.9
0.7
1.5
8.1
1.5
7.7
1.6
7.5
1.5
7.3
1.5
7.0
1.4
Total
6.0
8.2
7.3
6.7
6.1
5.9
5.8
5.5
Note: Totals may not sum due to independent rounding.
Table 3-31: CH4 Emissions from Abandoned Underground Coal Mines (Gg)
Activity
1990
1995
2000 2001
2002
2003
2004
2005
Abandoned Underground Mines 287 422
Recovered & Used 0 , 32
421
72
387
70
367
75
354
72
345
70
331
68
Total
286
391
349
318
292
282
275
263
Note: Totals may not sum due to independent rounding.
Gross abandoned mine CH4 emissions ranged from
6.0 to 9.1 Tg CO2 Eq. from 1990 through 2005, varying,
in general, by less than 1 to approximately 19 percent from
year to year. Fluctuations were due mainly to the number of
mines closed during a given year as well as the magnitude
of the emissions from those mines when active. Abandoned
mine emissions peaked in 1996 (9.1 Tg CO2 Eq.) due to the
large number of mine closures from 1994 to 1996 (70 gassy
mines closed during the three-year period). In spite of this
rapid rise, abandoned mine emissions have been generally on
the decline since 1996. There were fewer than fifteen gassy
mine closures during each of the years from 1998 through
2005, with only two closures in 2005. By 2005, abandoned
mine emissions declined to 5.5 Tg CO2 Eq. (see Table 3-30
and Table 3-31).
Methodology
Estimating CH4 emissions from an abandoned coal mine
requires predicting the emissions of a mine from the time of
abandonment through the inventory year of interest. The flow
of CH4 from the coal to the mine void is primarily dependent
on the mine's emissions when active and the extent to which
the mine is flooded or sealed. The CH4 emission rate before
abandonment reflects the gas content of the coal, rate of
coal mining, and the flow capacity of the mine in much the
same way as the initial rate of a water-free conventional gas
well reflects the gas content of the producing formation and
the flow capacity of the well. Existing data on abandoned
mine emissions through time, although sparse, appear to
fit the hyperbolic type of decline curve used in forecasting
production from natural gas wells.
In order to estimate CH4 emissions over time for a
given mine, it is necessary to apply a decline function,
initiated upon abandonment, to that mine. In the analysis,
mines were grouped by coal basin with the assumption
that they will generally have the same initial pressures,
permeability and isotherm. As CH4 leaves the system, the
reservoir pressure, Pr, declines as described by the isotherm.
The emission rate declines because the mine pressure (Pw)
is essentially constant at atmospheric pressure, for a vented
mine, and the PI term is essentially constant at the pressures
of interest (atmospheric to 30 psia). A rate-time equation can
be generated that can be used to predict future emissions.
This decline through time is hyperbolic in nature and can be
empirically expressed as:
q - q.U+bCt.t)'
where,
q = Gas rate at time t in nicf/d
q, = Initial gas rate at time /.ero (tu) in million cubic
feet per day (mct'd)
b = The hyperbolic exponent, dimensionless
D = Initial decline rate, i/yi
t = Elapsed time from t,, (years)
This equation is applied to mines of various initial
emission rates that have similar initial pressures, permeability
and adsorption isotherms (EPA 2003).
The decline curves are also affected by both sealing
and flooding. Based on field measurement data, it was
assumed that most U.S. mines prone to flooding will become
completely flooded within eight years and therefore no
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
longer have any measurable CH4 emissions. Based on this
assumption, an average decline rate for flooding mines was
established by fitting a decline curve to emissions from field
measurements. An exponential equation was developed from
emissions data measured at eight abandoned mines known to
be filling with water located in two of the five basins. Using
a least squares, curve-fitting algorithm, emissions data were
matched to the exponential equation shown below. There was
not enough data to establish basin-specific equations as was
done with the vented, non-flooding mines (EPA 2003).
where,
q ~- Ga^ Ihm r;ite a! nine 1 in mct/d
i.|, -" initial i.',^ lluu rale ,
-------
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal Mines
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Abandoned Underground
Coal Mines CH4
5.5
4.6
6.5
-16%
+ 18%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
multiplied by 1.22 and 1.02 to account for all U.S. abandoned
mine emissions. From 1993 through 2005, emission totals
were downwardly adjusted to reflect abandoned mine CH4
emissions avoided from those mines. The inventory totals
were not adjusted for abandoned mine reductions in 1990
through 1992, because no data was reported for abandoned
coal mining CH4 recovery projects during that time.
Uncertainty
A quantitative uncertainty analysis was conducted
to estimate the uncertainty surrounding the estimates
of emissions from abandoned underground coal mines.
The uncertainty analysis described below provides for
the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide
the range within which, with 95 percent certainty, emissions
from this source category are likely to fall.
As discussed above, the parameters for which values
must be estimated for each mine in order to predict its decline
curve are: (1) the coal's adsorption isotherm; (2) CH4 flow
capacity as expressed by permeability; and (3) pressure at
abandonment. Because these parameters are not available
for each mine, a methodological approach to estimating
emissions was used that generates a probability distribution
of potential outcomes based on the most likely value and
the probable range of values for each parameter. The range
of values is not meant to capture the extreme values, but
values that represent the highest and lowest quartile of the
cumulative probability density function of each parameter.
Once the low, mid, and high values are selected, they are
applied to a probability density function.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-32. Abandoned coal mines CH4
emissions in 2005 were estimated to be between 4.6 and 6.5
Tg CO2 Eq. at a 95 percent confidence level. This indicates
a range of 16 percent below to 18 percent above the 2005
emission estimate of 5.5 Tg CO2 Eq. One of the reasons for
the relatively narrow range is that mine-specific data is used
in the methodology. The largest degree of uncertainty is
associated with the unknown status mines (which account for
40 percent of the mines), with a ±50 percent uncertainty.
fifi' , IllM? K<, 'MirUS
Quality assurance/quality control of the calculation
spreadsheets for the 1990 through 2004 inventory years
revealed an equation link that contained a minor error. The
error was tracked back to the 1 998 calculation worksheet and
carried through 2004. The equation was corrected and the
emissions recalculated for 1998 through 2004. In addition,
a few other minor data corrections were completed during
the recalculation process.
-
iyy
The U.S. natural gas system encompasses hundreds
of thousands of wells, hundreds of processing facilities,
and over a million miles of transmission and distribution
pipelines. Overall, natural gas systems emitted 1 1 1 . 1 Tg CO2
Eq. (5.292 Gg) of CH4 in 2005, an 11 percent decrease over
1990 emissions (see Table 3-33 and Table 3-34), and 28.2
Tg CO2 Eq. (28,185 Gg) of non-energy CO2 in 2005, a 16
percent decrease over 1990 emissions (see Table 3-35 and
Table 3-36). Improvements in management practices and
technology, along with the replacement of older equipment,
have helped to stabilize emissions.
CH4 and non-energy CO2 emissions from natural
gas systems are generally process related, with normal
operations, routine maintenance, and system upsets being
the primary contributors. Emissions from normal operations
include: natural gas engines and turbine uncombusted
3 40
-------
Table 3-33. CH4 Emissions from Natural Gas Systems (Tg C02 Eq.)*
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
31.8
14.8
46.8
31.0
124.5
1995
36.6
14.9
46.3
30.3
128.1
2000
38.5
14.5
44.1
29.4
126.6
2001
41.2
14.7
41.0
28.6
125.4
2002
42.4
14.1
42.5
25.9
125.0
2003
40.9
13.5
42.3
27.0
123.7
2004
38.0
13.5
40.6
26.9
119.0
2005
35.2
11.9
36.8
27.4
111.1
"Including CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-34. CH4 Emissions from Natural Gas Systems (Gg)4
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
1,514
706
2,230
1,477
5,927
1995
1,745
709
2,205
1,442
6,101
2000
1,832
692
2,102
1,401
6,027
2001
1,963
698
1,950
1,360
5,971
2002
2,021
673
2,025
1,231
5,951
2003
1,949
645
2,013
1,284
5,891
2004
1,811
643
1,934
1,281
5,669
2005
1,675
564
1,751
1,303
5,292
"Including CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-35. Non-energy C02 Emissions from Natural Gas Systems (Tg C02 Eq.)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
5.9
27.8
0.1
+
33.7
1995
9.1
24.6
0.1
+
33.8
2000
6.0
23.3
0.1
+
29.4
2001
6.3
22.4
0.1
+
28.8
2002
6.5
23.1
0.1
+
29.6
2003
6.3
22.0
0.1
+
28.4
2004
6.3
21.8
0.1
+
28.2
2005
6.4
21.7
0.1
+
28.2
Note: Totals may not sum due to independent rounding.
Table 3-36. Non-energy C02 Emissions from Natural Gas Systems (Gg)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
5,876
27,752
58
43
33,729
1995
9,083
24,621
60
42
33,807
2000
5,955
23,333
61
41
29,390
2001
6,307
22,387
59
40
28,793
2002
6,462
23,066
62
40
29,630
2003
6,341
22,002
61
40
28,445
2004
6,309
21,780
62
40
28,190
2005
6,350
21,736
60
39
28,185
Note: Totals may not sum due to independent rounding.
exhaust, bleed and discharge emissions from pneumatic Field Production. In this initial stage, wells are used to
devices, and fugitive emissions from system components. withdraw raw gas from underground formations. Emissions
Routine maintenance emissions originate from pipelines, arise from the wells themselves, gathering pipelines, and well-
equipment, and wells during repair and maintenance site gas treatment facilities such as dehydrators and separators.
activities. Pressure surge relief systems and accidents can Fugitive emissions and emissions from pneumatic devices
lead to system upset emissions. Below is a characterization account for the majority of CH4 emissions. Flaring emissions
of the four major stages of the natural gas system. Each of account for the majority of the non-energy CO2 emissions.
the stages is described and the different factors affecting Emissions from field production accounted for approximately
CH4 and non-energy CO2 emissions are discussed. 32 percent of CH4 emissions and about 23 percent of non-
energy CO2 emissions from natural gas systems in 2005.
-------
Processing. In this stage, natural gas liquids and various
other constituents from the raw gas are removed, resulting in
"pipeline quality" gas, which is injected into the transmission
system. Fugitive CH4 emissions from compressors, including
compressor seals, are the primary emission source from this
stage. The majority of non-energy CO2 emissions come from
acid gas removal units, which are designed to remove CO,
from natural gas. Processing plants account for about 11
percent of CH4 emissions and approximately 77 percent of
non-energy CO2 emissions from natural gas systems.
Transmission and Storage. Natural gas transmission
involves high pressure, large diameter pipelines that transport
gas long distances from field production and processing areas
to distribution systems or large volume customers such as
power plants or chemical plants. Compressor station facilities,
which contain large reciprocating and turbine compressors, are
used to move the gas throughout the United States transmission
system. Fugitive CH4 emissions from these compressor
stations and from metering and regulating stations account
for the majority of the emissions from this stage. Pneumatic
devices and engine uncombusted exhaust are also sources of
CH4 emissions from transmission facilities.
Natural gas is also injected and stored in underground
formations, or liquefied and stored in above ground tanks,
during periods of low demand (e .g., summer), and withdrawn,
processed, and distributed during periods of high demand
(e.g., winter). Compressors and dehydrators are the primary
contributors to emissions from these storage facilities. CH4
emissions from the transmission and storage sector account
for approximately 34 percent of emissions from natural
gas systems, while CO2 emissions from transmission and
storage account for less than 1 percent of the non-energy
CO2 emissions from natural gas systems.
Distribution. Distribution pipelines take the high-pressure
gas from the transmission system at "city gate" stations,
reduce the pressure and distribute the gas through primarily
underground mains and service lines to individual end users.
There were over 1,034,000 miles of distribution mains in
2005, an increase from just over 888,000 miles in 1990 (OPS
2006b). Distribution system emissions, which account for
approximately 25 percent of CH4 emissions from natural gas
systems and less than 1 percent of non-energy CO2 emissions,
result mainly from fugitive emissions from gate stations and
non-plastic piping (cast iron, steel).43 An increased use of
plastic piping, which has lower emissions than other pipe
materials, has reduced emissions from this stage. Distribution
system CH4 emissions in 2005 were 12 percent lower than
1990 levels.
Methodology
The primary basis for estimates of CH4 and non-energy-
related CO2 emissions from the U.S. natural gas industry is a
detailed study by the Gas Research Institute and EPA (EPA/
GRI 1996). The EPA/GRI study developed over 80 CH4
emission and activity factors to characterize emissions from
the various components within the operating stages of the U.S.
natural gas system. The same activity factors were used to
estimate both CH4 and non-energy CO2 emissions. However,
the CH4 emission factors were adjusted for CO2 content when
estimating fugitive and vented non-energy CO2 emissions.
The EPA/GRI study was based on a combination of process
engineering studies and measurements at representative gas
facilities. From this analysis, a 1992 emission estimate was
developed using the emission and activity factors. For other
years, a set of industry activity factor drivers was developed
that can be used to update activity factors. These drivers
include statistics on gas production, number of wells, system
throughput, miles of various kinds of pipe, and other statistics
that characterize the changes in the U.S. natural gas system
infrastructure and operations.
See Annex 3.4 for more detailed information on the
methodology and data used to calculate CH4 and non-energy
CO2 emissions from natural gas systems.
Activity factor data were taken from the following
sources: American Gas Association (AGA 1991-1998);
American Petroleum Institute (API 2005); Minerals and
Management Service (MMS 2006a-e); Monthly Energy
Review (ElA 2006e); Natural Gas Liquids Reserves Report
(ElA 2005); Natural Gas Monthly (EIA 2006c,d,f); the
Natural Gas STAR Program annual emissions savings (EPA
2006); Oil and Gas Journal (OGJ 1997-2006); Office of
Pipeline Safety (OPS 2006a-b) and other Energy Information
Administration publications (EIA 2004, 2006a,b,g); World
Oil Magazine (2006a-b). Data for estimating emissions from
hydrocarbon production tanks is incorporated (EPA 1999).
Coalbed CH4 well activity factors were taken from the
3 The percentages of total emissions from each stage may not sum to 100 percent due to independent rounding.
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Wyoming Oil and Gas Conservation Commission (Wyoming
2006) and the Alabama State Oil and Gas Board (Alabama
2006). Other state well data was taken from: American
Association of Petroleum Geologists (AAPG 2004);
Brookhaven College (Brookhaven 2004); Kansas Geological
Survey (Kansas 2006); Montana Board of Oil and Gas
Conservation (Montana 2006); Oklahoma Geological Survey
(Oklahoma 2006); Morgan Stanley (Morgan Stanley 2005);
Rocky Mountain Production Report (Lippman 2003); New
Mexico Oil Conservation Division (New Mexico 2006a,b);
Texas Railroad Commission (Texas 2006a-d); Utah Division
of Oil, Gas and Mining (Utah 2006). Emission factors were
taken from EPA/GRI (1996). GRI's Unconventional Natural
Gas and Gas Composition Databases (GRI 2001) were used
to adapt the CH4 emission factors into non-energy related
COi emission factors. Additional information about CO2
content in transmission quality natural gas was obtained via
the internet from numerous U.S. transmission companies to
help further develop the non-energy CO2 emission factors.
Uncertainty
A quantitative uncertainty analysis was conducted to
determine the level of uncertainty surrounding estimates
of emissions from natural gas systems. Performed using
@RISK software and the IPCC-recommended Tier 2
methodology (Monte Carlo Simulation technique), this
analysis provides for the specification of probability density
functions for key variables within a computational structure
that mirrors the calculation of the inventory estimate. The
results presented below provide with 95 percent certainty
the range within which emissions from this source category
are likely to fall.
The heterogeneous nature of the natural gas industry
makes it difficult to sample facilities that are completely
representative of the entire industry. Because of this, scaling
up from model facilities introduces a degree of uncertainty.
Additionally, highly variable emission rates were measured
among many system components, making the calculated
average emission rates uncertain. The results of the Tier 2
quantitative uncertainty analysis are summarized in Table
3-37. Natural gas systems CH4 emissions in 2005 were
estimated to be between 82.2 and 144.4 Tg CO2 Eq. at a 95
percent confidence level. Natural gas systems non-energy
CO^ emissions in 2005 were estimated to be between 20.8
and 36.6 Tg CO2 Eq. at a 95 percent confidence level.
Recalculations Discussion
Significant changes were made to the emission
calculations in the Production sector. The first change
implemented was to incorporate a variable CH4 content of
the natural gas produced in the United States to the emission
factors of the production sector. In the past, CH4 content for
the emission factors was kept constant for each year and
different National Energy Modeling System (NEMS) regions.
For the revised method, the CH4 content is first estimated
in two base years, 1990 and 1995, using GRI and GTI data
source estimates, respectively. Then the CH4 content for other
years in the time series 1990 through 2005 are driven by the
natural gas production for each state and year. Each NEMS
region's CH4 content is calculated separately to reflect the
differences in the reservoir basins around the country. The
net effect of this restructuring on the historical emission
estimates is an average 3 percent increase in emissions. The
varying CH4 content in each region added another source of
uncertainty to the uncertainty analysis.
The second change to the production sector of the
Inventory was replacement of activity factors for five
sources: separators, heaters, pneumatic devices, chemical
injection pumps and compressors. The new activity factors
were developed by re-organizing the original GRI activity
Table 3-37: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-Energy C02 Emissions from Natural Gas
Systems (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Natural Gas Systems
Natural Gas Systems'1
CH4
C02
111.1
28.2
Lower Bound
82.2
20.8
Upper Bound
144.4
36.6
Lower Bound
-26%
-26%
Upper Bound
+30%
+30%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b An uncertainty analysis for the non-energy C02 emissions was not performed. The relative uncertainty estimated (expressed as a percent) from the CH4
uncertainty analysis was applied to the point estimate of non-energy C02 emissions.
Energy 3-43
-------
factor data into the new NEMS production regions. The
net effect of this change is a 2 percent decrease in 2004
emission estimates.
Another change in the estimates for the current Inventory
is the accounting of CH4 emission reductions from U.S. EPA
National Emissions Standards for Hazardous Air Pollutants
(NESHAP) regulations, which is the civil enforcement of
the Maximum Achievable Control Technology or MACT
standard. These federal regulations were enacted in 1999
and require a 95 percent reduction of emissions from
dehydrator vents and condensate tanks with throughputs
above the threshold levels set by the regulation. The
inventory methodology now incorporates these emission
reductions when describing the total emissions from natural
gas systems. Overall, the net effect on the historical CH4
emission estimates from this change is less than an average
1 percent decrease in emissions since 1999.
Finally, the Inventory now contains estimates for non-
energy related (vented, fugitive, flared) CO2 emissions
from the natural gas industry. The estimation uses the same
activity and emission factors as the CH4 emission estimates
but adjusts the emission factors using the ratio of CO2/CH4
content of the natural gas. Efforts were made to ensure that
there was no double-accounting of CO2 emissions from other
systems reported elsewhere in the U.S. Inventory.
The combination of these methodological and historical
data changes resulted in an average annual decrease of 0.3
Tg CO2 Eq. (0.3 percent) in CH4 emissions from natural gas
systems for the period 1990 through 2004.
Planned Improvements
One improvement being contemplated involves a trend
analysis for the time series. As discussed above, the natural
gas systems inventory now reflects changing emissions
factors based on changing CH4 content in natural gas in
different NEMS regions. The uncertainty analysis, for the
sake of simplicity, currently assumes a constant uncertainty
across all years in the emissions time series. A trend analysis
reflecting changing uncertainty in the time series will be
conducted to more closely follow the IPCC Guidelines.
Additional improvements include developing region specific
emission and activity factors and incorporating any new data
that becomes available from new studies in the future into
the emissions model.
3,8, Petroleum Systems (IPCC
Source Category 1B2a)
CH4 emissions from petroleum systems are primarily
associated with crude oil production, transportation, and
refining operations. During each of these activities, CH4
is released to the atmosphere as fugitive emissions, vented
emissions, emissions from operational upsets, and emissions
from fuel combustion. Total CH4 emissions from petroleum
systems in 2005 were 28.5 Tg CO2 Eq. (1,357 Gg). Since
1990, emissions have declined by 17 percent, due to a decline
in domestic oil production and industry efforts to reduce
emissions (see Table 3-38 and Table 3-39). The emission
increase exhibited between 2004 and 2005 resulted from
an increase in the number of offshore platforms (primarily
shallow water, but also deep water). The various sources of
emissions are detailed below.
Production Field Operations .Production field operations
account for over 97 percent of total CH4 emissions from
petroleum systems. Vented CH4 from field operations
account for approximately 91 percent of the emissions
from the production sector, fugitive emissions account for
3.5 percent, combustion emissions 5.3 percent, and process
upset emissions, slightly over one-tenth of a percent. The
most dominant sources of vented emissions are offshore oil
platforms (shallow and deep water platforms), field storage
tanks and natural-gas-powered pneumatic devices (low
bleed and high bleed). These five sources alone emit over
86 percent of the production field operations emissions.
Offshore platform emissions are a combination of fugitive,
vented, and combustion emissions from all equipment housed
on the platform for both oil and associated gas on those
labeled as oil platforms. Emissions from storage tanks occur
when the CH4 entrained in crude oil under pressure volatilizes
once the crude oil is put into storage tanks at atmospheric
pressure. Emissions from high and low-bleed pneumatics
occur when pressurized gas that is used for control devices
is bled to the atmosphere as they cycle open and closed
to modulate the system. Two additional large sources,
chemical injection pumps and gas engines, together account
for nine percent of emissions from the production sector.
The remaining five percent of the emissions are distributed
among 26 additional activities within the four categories:
vented, fugitive, combustion and process upset emissions.
3-44 inventory of U.S, Greenhouse Gas Emissions ami Sinks: 19SO-2005
-------
Table 3-38: CH4 Emissions from Petroleum Systems (Tg C02 Eq.)
Activity
Production Field Operations
Pneumatic Device Venting
Tank Venting
Combustion & Process
Upsets
Misc. Venting & Fugitives
Wellhead Fugitives
Crude Oil Transportation
Refining
Total
1990
33.8
10.3
3.8
1.9
17.4
0.5
0.1
0.5
34.4
1995
30.5
9.7
3.4
1.7
15.1
0.5
0.1
0.5
31.1
2000
27.1
9.0
3.2
1.6
12.8
0.5
0.1
0.6
27.8
2001
26.7
8.9
3.2
1.6
12.5
0.5
0.1
0.6
27.4
2002
26.1
8.9
3.2
1.6
12.0
0.5
0.1
0.6
26.8
2003
25.1
8.7
3.2
1.5
11.3
0.5
0.1
0.6
25.8
2004
24.7
8.6
3.0
1.5
11.2
0.4
0.1
0.6
25.4
2005
27.8
8.5
2.8
1.5
14.5
0.4
0.1
0.6
28.5
Note: Totals may not sum due to independent rounding.
Table 3-39: CH4 Emissions from
Activity
Production Field Operations
Pneumatic Device Venting
Tank Venting
Combustion & Process
Upsets
Misc. Venting & Fugitives
Wellhead Fugitives
Crude Oil Transportation
Refining
Total
Petroleum
1990
1,609
489
179
88
827
26
7
25
1,640
Systems (Gg)
1995
1,450
463
161
82
719
25
6
25
1,482
2000
1,292
428
154
76
612
22
5
28
1,325
2001
1,271
425
154
75
594
22
5
27
1,303
2002
1,242
424
151
75
570
23
5
27
1,275
2003
1,196
412
150
73
540
22
5
27
1,229
2004
1,176
408
142
72
533
21
5
28
1,209
2005
1,324
406
133
72
692
21
5
28
1,357
Note: Totals may not sum due to independent rounding.
For more detailed, source-level, data on methane emissions
in production field operations refer to Annex 3.5.
Crude Oil Transportation. Crude oil transportation
activities account for less than one percent of total CH4
emissions from the oil industry. Venting from tanks and
marine vessel loading operations accounts for 65 percent
of CH4 emissions from crude oil transportation. Fugitive
emissions, almost entirely from floating roof tanks, account
for 18 percent. The remaining 17 percent is distributed
among seven additional sources within these two categories.
Emissions from pump engine drivers and heaters were not
estimated due to lack of data.
Crude Oil Refining. Crude oil refining processes and
systems account for slightly over two percent of total CH4
emissions from the oil industry because most of the CH4
in crude oil is removed or escapes before the crude oil is
delivered to the refineries. There is an insignificant amount
of CH4 in all refined products. Within refineries, vented
emissions account for about 87 percent of the emissions,
while fugitive and combustion emissions account for
approximately six and seven percent, respectively. Refinery
system blowdowns for maintenance and the process of asphalt
blowing—with air, to harden the asphalt—are the primary
venting contributors. Most of the fugitive CH4 emissions
from refineries are from leaks in the fuel gas system. Refinery
combustion emissions include small amounts of unburned
CH4 in process heater stack emissions and unburned CH4 in
engine exhausts and flares.
Methodology
The methodology for estimating CH4 emissions
from petroleum systems is a bottom-up approach, based
on comprehensive studies of CH4 emissions from U.S.
petroleum systems (EPA 1999, EPA 1996). These studies
combined emission estimates from 64 activities occurring
in petroleum systems from the oil wellhead through crude
oil refining, including 33 activities for crude oil production
field operations, 11 for crude oil transportation activities,
and 20 for refining operations. Annex 3.5 provides greater
detail on the emission estimates for these 64 activities. The
estimates of CH4 emissions from petroleum systems do
not include emissions downstream of oil refineries because
Energy 3-45
-------
these emissions are very small compared to CH4 emissions
upstream of oil refineries.
The methodology for estimating CH4 emissions from
the 64 oil industry activities employs emission factors
initially developed by EPA (1999) and activity factors that
are based on two EPA studies (1996, 1999). Emissions are
estimated for each activity by multiplying emission factors
(e.g., emission rate per equipment item or per activity) by
their corresponding activity factor (e.g., equipment count or
frequency of activity). The report provides emission factors
and activity factors for all activities except those related to
offshore oil production. For offshore oil production, two
emission factors were calculated using data collected over a
one-year period for all federal offshore platforms (EPA 2005,
MMS 2005c). One emission factor is for oil platforms in
shallow water, and one emission factor is for oil platforms in
deep water. Emission factors are held constant for the period
1990 through 2005. The number of platforms in shallow
water and the number of platforms in deep water are used
as activity factors and are taken from Minerals Management
Service statistics (MMS 2005a, b, d).
Activity factors for years 1990 through 2005 were
collected from a wide variety of statistical resources. For
some years, complete activity factor data were not available.
In such cases, one of three approaches was employed. Where
appropriate, the activity factor was calculated from related
statistics using ratios developed for EPA (1996). For example,
EPA (1996) found that the number of heater treaters (a source
of CH4 emissions) is related to both number of producing
wells and annual production. To estimate the activity factor
for heater treaters, reported statistics for wel Is and production
were used, along with the ratios developed for EPA (1996).
In other cases, the activity factor was held constant from
1990 through 2005 based on EPA (1999). Lastly, the previous
year's data were used when data for the current year were
unavailable. See Annex 3.5 for additional detail.
Nearly all emission factors were taken from EPA (1995,
1996, 1999). The remaining emission factors were taken
from EPA default values in (EPA 2005) and the consensus
of industry peer review panels.
Among the more important references used to obtain
activity factors are the Energy Information Administration
annual and monthly reports (ElA 1990 through 2005,1990
through 2006, 1995 through 2005, 1995 through 2006),
Methane Emissions from the Natural Gas Industry by the
Gas Research Institute and EPA (EPA & GRI 1996a-d),
Estimates of Methane Emissions from the U.S. Oil Industry
(EPA 1999), consensus of industry peer review panels,
MMS reports (MMS 2001. 2005a,b,d), ICE analysis of
MMS (EPA 2005, MMS 2005c), the Oil & Gas Journal
(OGJ 2005-2006) and the United States Army Corps of
Enginsers (1995-2004).
Uncertainty
This section describes the analysis conducted to quantify
uncertainty associated with the estimates of emissions from
petroleum systems. Performed using @RISK software and
the IPCC-recommended Tier 2 methodology (Monte Carlo
Simulation technique), the method employed provides for
the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide
the range within which, with 95 percent certainty, emissions
from this source category are likely to fall.
The detailed, bottom-up inventory analysis used to
evaluate U.S. petroleum systems reduces the uncertainty
related to the CH4 emission estimates in comparison with
a top-down approach. However, some uncertainty still
remains. Emission factors and activity factors are based on
a combination of measurements, equipment design data,
engineering calculations and studies, surveys of selected
facilities and statistical reporting. Statistical uncertainties
arise from natural variation in measurements, equipment
types, operational variability and survey and statistical
methodologies. Published activity factors are not available
every year for all 64 activities analyzed for petroleum
systems; therefore, some are estimated. Because of the
dominance of five major sources, which account for 86
percent of the total emissions, the uncertainty surrounding
these five sources has been estimated most rigorously, and
serves as the basis for determining the overall uncertainty
of petroleum systems emission estimates.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 3-40. Petroleum systems
CH4 emissions in 2005 were estimated to be between 21.7
and 70.7 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 24 percent below to 148 percent above
the 2005 emission estimate of 28.5 Tg CO2 Eq.
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19!30-2005
-------
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(TgC02Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Petroleum Systems
CH4
28.5
21.7
70.7
-24%
+148%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Two types of activity factor and activity driver revisions
were made in the 2005 Petroleum Systems emissions
inventory. Some revisions were due to a change in data
sources referenced, while some revisions were due to
updating previous years' data with revised data from existing
data sources. Overall changes resulted in an annual decrease
of approximately 0.14 Tg CO2 Eq. (0.6 percent) for 2003 and
0.26 Tg CO2 Eq. (1 percent) for 2004, relative to the previous
Inventory. For other years in the time series, the emission
estimates increased by less than 0.1 percent.
Planned Improvements
A key improvement being contemplated is to include
fugitive, vented, and combustion CO7 emissions sources in
the Petroleum Systems inventory.
/ 9 Mumuu*
•IPCCSOir -
O Waste Combustion
Combustion is used to manage about 7 to 1 7 percent
of the municipal solid wastes (MSW) generated in the
United States, depending on the source of the estimate
and the scope of materials included in the definition of
solid waste (EPA 2000b, Goldstein and Matdes 2001,
Kaufman et al. 2004a, Simmons et al. 2006). Almost all
combustion of MSW in the United States occurs at waste-
to-energy facilities where useful energy is recovered, and
thus emissions from waste combustion are accounted for
in the Energy chapter. Combustion of municipal solid
wastes results in conversion of the organic inputs to CO7.
According to IPCC guidelines, when the CO2 emitted is of
fossil origin, it is counted as a net anthropogenic emission
of CO2 to the atmosphere. Thus, the emissions from waste
combustion are calculated by estimating the quantity of
waste combusted and the fraction of the waste that is C
derived from fossil sources.
Most of the organic materials in municipal solid wastes
are of biogenic origin (e.g., paper, yard trimmings), and have
their net C flows accounted for under the Land Use, Land-Use
Change, and Forestry chapter. However, some components—
plastics, synthetic rubber, synthetic fibers, and carbon
black— are of fossil origin. Plastics in the U.S. waste stream
are primarily in the form of containers, packaging, and durable
goods. Rubber is found in durable goods, such as carpets, and
in non-durable goods, such as clothing and footwear. Fibers in
municipal solid wastes are predominantly from clothing and
home furnishings. Tires (which contain rubber and carbon
black) are also considered a "non-hazardous" waste and are
included in the municipal solid waste combustion estimate,
though waste disposal practices for tires differ from the rest of
municipal solid waste (viz., most combustion occurs outside
of MSW combustion facilities).
Approximately 34 million metric tons of municipal solid
wastes were combusted in the United States in 2005 (Simmons
et al. 2006). CO2 emissions from combustion of municipal
solid wastes rose 91 percent since 1990, to an estimated 20.9
Tg CO2 Eq. (20,912 Gg) in 2005, as the volume of plastics
and other fossil C-containing materials in MSW increased
(see Table 3-43 and Table 3-44). Waste combustion is also
a source of N2O emissions (De Soete 1993). N2O emissions
from municipal solid waste combustion were estimated to be
0.4 Tg CO2 Eq. (1 Gg N2O) in 2005, and have not changed
significantly since 1990.
Emissions of CO2 from MSW combustion include
CO2 generated by the combustion of plastics, synthetic
fibers, and synthetic rubber, as well as the combustion of
synthetic rubber and carbon black in tires. These emissions
were estimated by multiplying the amount of each material
combusted by the C content of the material and the fraction
oxidized (98 percent). Plastics combusted in MSW were
categorized into seven plastic resin types, each material
-------
Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage
Carbon dioxide is produced, captured, transported, and used for Enhanced Oil Recovery (EOR) as well as commercial and non-EOR
industrial applications. This C02 is produced from both naturally-occurring C02 reservoirs and from industrial sources such as natural
gas processing plants and ammonia plants. In the current Inventory, emissions from naturally-produced C02 are estimated based on the
application.
In the current Inventory report, the C02 that is used in non-EOR industrial and commercial applications (e.g., food processing, chemical
production) is assumed to be emitted to the atmosphere during its industrial use. These emissions are discussed in the Carbon Dioxide
Consumption section. The naturally-occurring C02 used in EOR operations is assumed to be fully sequestered. Additionally, all anthropogenic
C02 emitted from gas processing and ammonia plants is assumed to be emitted to the atmosphere, regardless of whether the C02 is captured
or not. These emissions are currently included in the Natural Gas Systems and the Ammonia Manufacture and Urea Application sections of
the Inventory report, respectively.
IPCC (2006) includes, for the first time, methodological guidance to estimate emissions from the capture, transport, injection, and
geological storage of C02. The methodology is based on the principle that the carbon capture and storage system should be handled in a
complete and consistent manner across the entire Energy sector. The approach accounts for C02 captured at natural and industrial sites as well
as emissions from capture, transport, and use. For storage specifically, a Tier 3 methodology is outlined for estimating and reporting emissions
based on site-specific evaluations. If site-specific monitoring and reporting data are not available, and the carbon capture and storage system
cannot, therefore, be considered in a complete and consistent manner, the assumption is that the captured C02 is emitted. The assumption
that, in the absence of site specific data, all C02 injected in storage sites is emitted is opposite from the current methodology implemented
by the United States. The new methodology will not affect emission estimates for C02 consumption for non-EOR applications.
The United States initiated data collection efforts to incorporate this new methodology for the current Inventory report. However, time
was not sufficient to fully implement this guidance and the estimates are not yet included in national totals. Preliminary estimates indicate that
the amount of C02 emitted from EOR operations and pipelines is 35.2 Tg C02 Eq. (35,156 Gg C02) (see Table 3-41). Site-specific monitoring
and reporting data for C02 injection sites (i.e., EOR operations) were not readily available. Therefore, these estimates assume all C02 is
emitted. The United States is initiating a process to collect the necessary data to fully implement the 2006 IPCC Guidelines methodology for
this source category in subsequent Inventory reports.
Table 3-41: Emissions of C02 from EOR Operations and Pipelines (Tg C02 Eq.)
Year
Acid Gas Removal Plants
Naturally Occurring C02
Ammonia Production Plants
Pipelines Transporting C02
Total
1990
4.8
20.8
0.0
0.0
25.6
1995
3.7
22.7
0.7
0.0
27.0
2000
2.3
22.7
0.7
0.0
25.6
2001
2.9
23.0
0.7
0.0
26.6
2002
2.9
21.9
0.7
0.0
25.5
2003
3.0
24.3
0.7
0.0
28.0
2004
3.7
27.1
0.7
0.0
31.5
2005
6.0
28.5
0.7
0.0
35.2
Table 3-42: Emissions of C02 from EOR Operations and Pipelines (Gg)
Year
Acid Gas Removal Plants
Naturally Occurring C02
Ammonia Production Plants
Pipelines Transporting C02
Total
1990
4,832
20,752
0
8
25,592
1995
3,672
22,687
676
8
27,044
2000
2,264
22,649
676
8
25,598
2001
2,894
23,015
676
8
26,593
2002
2,943
21,854
676
8
25,482
2003
2,993
24,273
676
8
27,951
2004
3,719
27,085
676
7
31,489
2005
5,992
28,481
676
7
35,156
3-48 Inventory of U.S. Greenhouse Gas hnis5»ions ami Sinks: 19SD- 2005
-------
Table 3-43: C02 and N20 Emissions from Municipal Solid Waste Combustion (Tg C02 Eq.)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N20
Total
1990
10.9
8.0
0.2
0.2
1.3
1.2
0.5
11.4
1995
15.7
10.3
0.8
1.1
1.6
1.8
0.5
16.2
2000
17.9
12.1
0.9
1.2
1.7
2.1
0.4
18.3
2001
18.3
12.4
0.9
1.2
1.8
2.1
0.4
18.7
2002
18.5
12.4
1.0
1.2
1.8
2.2
0.4
18.9
2003
19.5
13.0
1.0
1.3
1.9
2.3
0.4
19.9
2004
20.1
13.4
1.1
1.4
1.9
2.3
0.4
20.5
2005
20.9
13.9
1.2
1.6
1.9
2.4
0.4
21.3
Table 3-44: C02 and N20 Emissions from Municipal Solid Waste Combustion (Gg)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N20
1990
10,950
7,976
191
249
1,334
1,200
2
1995
15,712
10,347
841
1,099
1,596
1,830
1
2000
17,889
12,068
893
1,167
1,678
2,083
1
2001
18,344
12,378
895
1,170
1,762
2,139
1
2002
18,513
12,365
952
1,245
1,767
2,184
1
2003
19,490
12,984
1,010
1,320
1,862
2,315
1
2004
20,115
13,381
1,108
1,449
1,875
2,302
1
2005
20,912
13,852
1,207
1,579
1,899
2,375
1
having a discrete C content. Similarly, synthetic rubber is
categorized into three product types, and synthetic fibers were
categorized into four product types, each having a discrete C
content. Scrap tires contain several types of synthetic rubber,
as well as carbon black. Each type of synthetic rubber has
a discrete C content, and carbon black is 100 percent C.
Emissions of CO2 were calculated based on the number of
scrap tires used for fuel and the synthetic rubber and carbon
black content of the tires.
More detail on the methodology for calculating
emissions from each of these waste combustion sources is
provided in Annex 3.6.
For each of the methods used to calculate CO2 emissions
from municipal solid waste combustion, data on the quantity
of product combusted and the C content of the product are
needed. For plastics, synthetic rubber, and synthetic fibers,
the amount of material in MSW and its portion combusted
were taken from the Characterization of Municipal Solid
Waste in the United States (EPA 2000b, 2002,2003, 2005a,
2006b) and detailed unpublished backup data for some years
not shown in the reports (Schneider 2007). For synthetic
rubber and carbon black in scrap tires, information was
obtained from U.S. Scrap Tire Markets in the United States
2005 Edition (RMA 2006) and Scrap Tires, Facts and Figures
(STMC 2000,2001, 2002,2003, 2006).
Average C contents for the "Other" plastics category,
synthetic rubber in MSW, and synthetic fibers were calculated
from 1998 production statistics, which divide their respective
markets by chemical compound. Information about scrap tire
composition was taken from the Scrap Tire Management
Council's internet site (STMC 2006).
The assumption that 98 percent of organic C is oxidized
(which applies to all MSW combustion categories for CO2
emissions) was reported in the EPA's life cycle analysis of
greenhouse gas emissions and sinks from management of
solid waste (EPA 2006a).
Combustion of MSW also results in emissions of N2O.
These emissions were calculated as a function of the total
estimated mass of MSW combusted and an emission factor.
The N2O emission estimates are based on different data
sources. As noted above, N2O emissions are a function of
total waste combusted in each year; for 1990 through 2005,
these data were derived from the information published
in BioCycle (Simmons et al. 2006). Data on total waste
combusted was not available for 2005, so the value for 2005
was assumed to equal the most recent value available (2004).
Table 3-45 provides data on MSW generation and percentage
combustion for the total waste stream. The emission factor of
N2O emissions per quantity of MSW combusted is an average
of values from IPCC's Good Practice Guidance (2000).
Energy 3-49
-------
Table 3-45: Municipal Solid Waste Generation
(Metric Tons) and Percent Combusted
Year
1990
1995
2000
2001
2002
2003
2004
2005
Waste Generation
266,365,714
296,390,405
371,071,109
353,086,962a
335,102,816
343,482,645b
351,862,474
351,862,474°
Combusted (%)
11.5
10.0
7.0
7.4a
7.7
7.6b
7.4
7.4C
a Interpolated between 2000 and 2002 values.
b Interpolated between 2002 and 2004 values.
0 Assumed equal to 2004 value.
Uncertainty
A Tier 2 Monte Carlo analysis was performed to
determine the level of uncertainty surrounding the estimates
of CO2 emissions and N2O emissions from M SW combustion.
IPCC Tier 2 analysis allows the specification of probability
density functions for key variables within a computational
structure that mirrors the calculation of the inventory
estimate. Uncertainty estimates and distributions for waste
generation variables (i.e., plastics, synthetic rubber, and textiles
generation) were obtained through a conversation with one of
the authors of the Municipal Solid Waste in the United States
reports. Statistical analyses or expert judgments of uncertainty
were not available directly from the information sources for the
other variables; thus, uncertainty estimates for these variables
were determined using assumptions based on source category
knowledge and the known uncertainty estimates for the waste
generation variables.
The uncertainties in the waste combustion emission
estimates arise from both the assumptions applied to
the data and from the quality of the data. Key factors
include MSW combustion rate; fraction oxidized; missing
data on MSW composition: average C content of MSW
components; assumptions on the synthetic/biogenic C ratio;
and combustion conditions affecting N2O emissions. The
highest levels of uncertainty surround the variables that
are based on assumptions (e.g., percent of clothing and
footwear composed of synthetic rubber); the lowest levels
of uncertainty surround variables that were determined by
quantitative measurements (e.g., combustion efficiency, C
content of C black).
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-46. Municipal solid waste
combustion CO2 emissions in 2005 were estimated to be
between 15.5 and 25.0 Tg CO, Eq. at a 95 percent confidence
level. This indicates a range of 26 percent below to 19 percent
above the 2005 emission estimate of 20.9 Tg CO2 Eq. Al so at a
95 percent confidence level, municipal solid waste combustion
N2O emissions in 2005 were estimated to be between 0.11
and 1.02 Tg CO2 Eq. This indicates a range of 74 percent
below to 153 percent above the 2005 emission estimate of
0.40 Tg CO2 Eq.
QA./QC and Verification
A source-specific QA/QC plan was implemented for
MSW Combustion. This effort included a Tier 1 analysis, as
well as portions of a Tier 2 analysis. The Tier 2 procedures
that were implemented involved checks specifically focusing
on the activity data and specifically focused on the emission
factor and activity data sources and methodology used for
estimating emissions from MSW combustion. Trends across
the time series were analyzed to determine whether any
corrective actions were needed. Corrective actions were
taken to rectify minor errors and to improve the transparency
of the calculations, facilitating future QA/QC.
Table 3-46: Tier 2 Quantitative Uncertainty Estimates for C02 and N20 from Municipal Solid Waste Combustion
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Municipal Solid Waste
Combustion
Municipal Solid Waste
Combustion
C02
N20
20.9
0.4
Lower Bound
15.5
0.1
Upper Bound
25.0
1.0
Lower Bound
-26%
-74%
Upper Bound
+ 19%
+153%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
3-50 invent'?!s
' hotr rf s<<
-------
Planned Improvements
EPA will investigate additional data sources for calculating
an N2O emission factor for U.S. MSW combustion.
3,10, Energy Sources of Indirect
Greenhouse Gas Emissions
In addition to the main greenhouse gases addressed
above, many energy-related activities generate emissions of
indirect greenhouse gases. Total emissions of nitrogen oxides
(NOX), carbon monoxide (CO), and non-CH4 volatile organic
compounds (NMVOCs) from energy-related activities from
1990 to 2005 are reported in Table 3-47.
Methodology
These emission estimates were obtained from preliminary
data (EPA 2006), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emissions were calculated either for individual
categories or for many categories combined, using basic
activity data (e.g., the amount of raw material processed)
as an indicator of emissions. National activity data were
collected for individual categories from various agencies.
Depending on the category, these basic activity data may
include data on production, fuel deliveries, raw material
processed, etc.
Activity data were used in conjunction with emission
factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the
EPA's Compilation of Air Pollutant Emission Factors, AP-42
(EPA 1997). The EPA currently derives the overall emission
control efficiency of a source category from a variety of
information sources, including published reports, the 1985
National Acid Precipitation and Assessment Program
emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the
accuracy of the emission factors used and accurate estimates
of activity data. A quantitative uncertainty analysis was
not performed.
3,11 international Bunker Fuels
ilPCC Source Category 1
items i
Emissions resulting from the combustion of fuels used
for international transport activities, termed international
bunker fuels under the UNFCCC, are currently not included
in national emission totals, but are reported separately
based upon location of fuel sales. The decision to report
emissions from international bunker fuels separately, instead
of allocating them to a particular country, was made by the
Table 3-47: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg)
Gas/Source
NOX
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
International Bunker Fuels *
CO
Mobile Combustion
Stationary Combustion
Municipal Solid Waste Combustion
Oil and Gas Activities
International Bunker Fuels*
NMVOCs
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Municipal Solid Waste Combustion
International Bunker Fuels *
1990
21,024
10,920
9,883
139
82
7,985
125,759
119,480
5,000
978
302
115
12,620
10,932
912
554
222
59
1995
20,631
10,622
9,821
100
88
1,540
104,527
97,755
5,383
1,073
316
113
10,538
8,745
973
582
237
48
2000
18,537
10,310
8,002
111
114
1,334
89,835
83,680
4,340
1,670
146
124
8,953
7,230
1,077
389
257
44
2001
17,714
9,819
7,667
113
114
7,266
86,167
79,972
4,377
1,672
147
720
8,610
6,872
1,080
400
258
42
2002
17,569
10,319
6,837
316
97
988
84,369
77,382
5,224
1,440
323
778
9,131
6,608
1,733
546
244
35
2003
16,753
9,911
6,428
317
98
900
81,832
74,756
5,292
1,457
327
772
8,827
6,302
1,734
547
244
32
2004
15,886
9,520
5,952
317
98
1,179
79,435
72,269
5,361
1,475
331
124
8,538
6,011
1,735
547
244
40
2005
15,385
9,145
5,824
318
98
7,755
77,173
69,915
5,431
1,493
335
722
8,263
5,734
1,736
548
245
40
*These values are presented for informational purposes only and are not included in totals.
Note: Totals may not sum due to independent rounding.
-------
Intergovernmental Negotiating Committee in establishing the
Framework Convention on Climate Change.44 These decisions
are reflected in the Revised 1996IPCC Guidelines, as well
as the 2006 IPCC GLs, in which countries are requested to
report emissions from ships or aircraft that depart from their
ports with fuel purchased within national boundaries and are
engaged in international transport separately from national
totals (IPCC/UNEP/OECD/IEA 1997)45
Greenhouse gases emitted from the combustion of
international bunker fuels, like other fossil fuels, include
CO2, CH4, and N2O. Two transport modes are addressed
under the IPCC definition of international bunker fuels:
aviation and marine.46 Emissions from ground transport
activities—by road vehicles and trains—even when crossing
international borders are allocated to the country where
the fuel was loaded into the vehicle and, therefore, are not
counted as bunker fuel emissions.
The IPCC Guidelines distinguish between different
modes of air traffic. Civil aviation comprises aircraft used for
the commercial transport of passengers and freight, military
aviation comprises aircraft under the control of national
armed forces, and general aviation applies to recreational and
small corporate aircraft. The IPCC Guidelines further define
international bunker fuel use from civil aviation as the fuel
combusted for civil (e.g., commercial) aviation purposes by
aircraft arriving or departing on international flight segments.
However, as mentioned above, and in keeping with the IPCC
Guidelines, only the fuel purchased in the United States and
used by aircraft taking-off (i.e., departing) from the United
States are reported here. The standard fuel used for civil
aviation is kerosene-type jet fuel, while the typical fuel used
for general aviation is aviation gasoline.47
Emissions of CO2 from aircraft are essentially a function
of fuel use. CH4 and N2O emissions also depend upon engine
characteristics, flight conditions, and flight phase (i.e., take-
off, climb, cruise, decent, and landing). CH4 is the product
of incomplete combustion and occurs mainly during the
landing and take-off phases. In jet engines, N2O is primarily
produced by the oxidation of atmospheric nitrogen, and
the majority of emissions occur during the cruise phase.
International marine bunkers comprise emissions from fuels
burned by ocean-going ships of all flags that are engaged
in international transport. Ocean-going ships are generally
classified as cargo and passenger carrying, military (i.e.,
Navy), fishing, and miscellaneous support ships (e.g.,
tugboats). For the purpose of estimating greenhouse gas
emissions, international bunker fuels are solely related to
cargo and passenger carrying vessels, which is the largest of
the four categories, and military vessels. Two main types of
fuels are used on sea-going vessels: distillate diesel fuel and
residual fuel oil. CO2 is the primary greenhouse gas emitted
from marine shipping.
Overall, aggregate greenhouse gas emissions in 2005
from the combustion of international bunker fuels from
both aviation and marine activities were 98.2 Tg CO2 Eq.,
or 14 percent below emissions in 1990 (see Table 3-48 and
Table 3-49). Although emissions from international flights
departing from the United States have increased significantly
(34 percent), emissions from international shipping voyages
departing the United States have decreased by 50 percent
since 1990. The majority of these emissions were in the
form of CO2; however, small amounts of CH4 and N2O were
also emitted.
Methodology
Emissions of CO2 were estimated by applying C content
and fraction oxidized factors to fuel consumption activity
data. This approach is analogous to that described under
CO2 from Fossil Fuel Combustion. C content and fraction
oxidized factors for jet fuel, distillate fuel oil, and residual
fuel oil were taken directly from EIA and are presented in
Annex 2.1, Annex 2.2, and Annex 3.7 of this Inventory.
Density conversions were taken from Chevron (2000),
ASTM (1989),and USAF(1998). Heat content for distillate
fuel oil and residual fuel oil were taken from EIA (2006) and
USAF (1998), and heat content for jet fuel was taken from
EIA (2006). A complete description of the methodology
and a listing of the various factors employed can be found
44 See report of the Intergovernmental Negotiating Committee for a Framework Convention on Climate Change on the work of its ninth session, held at
Geneva from 7 to 18 February 1994 (A/AC.237/55, annex I, para. le).
45 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil Aviation Organization.
46 Most emission related international aviation and marine regulations are under the rubric of the International Civil Aviation Organization (ICAO)
or the International Maritime Organization (IMO), which develop international codes, recommendations, and conventions, such as the International
Convention of the Prevention of Pollution from Ships (MARPOL).
47 Naphtha-type jet fuel was used in the past by the military in turbojet and turboprop aircraft engines.
3-52 inventory of U.S. Greenhouse Gas (Missions and Sink;;: 1990--2005
-------
Table 3-48: C02, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
Total
1990
113.7
45.7
68.0
0.2
+
0.1
1.0
0.5
0.5
114.8
1995
100.6
50.2
50.4
0.1
+
0.1
0.9
0.5
0.4
101.6
2000
101.1
59.9
41.3
0.1
+
0.1
0.9
0.6
0.3
102.2
2001
97.6
58.7
38.9
0.1
+
0.1
0.9
0.6
0.3
98.6
2002
89.1
61.1
28.0
0.1
+
0.1
0.8
0.6
0.2
90.0
2003
83.7
58.8
24.9
0.1
+
0.1
0.8
0.6
0.2
84.5
2004
97.2
62.2
34.9
0.1
+
0.1
0.9
0.6
0.3
98.2
2005
97.2
62.6
34.6
0.1
+
0.1
0.9
0.6
0.3
98.2
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-49: C02, CH4 and N20 Emissions from International Bunker Fuels (Gg)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
1990
113,683
45,731
67,952
8
1
7
3
1
2
1995
100,627
50,202
50,425
6
1
5
3
2
1
2000
101,125
59,853
41,272
6
2
4
3
2
1
2001
97,563
58,696
38,866
5
2
4
3
2
1
2002
89,101
61,120
27,981
4
2
3
3
2
1
2003
83,690
58,806
24,884
4
2
2
2
2
1
2004
97,177
62,241
34,937
5
2
3
3
2
1
2005
97,191
62,598
34,593
5
2
3
3
2
1
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
in Annex 2.1. See Annex 3.7 for a specific discussion
on the methodology used for estimating emissions from
international bunker fuel use by the U.S. military.
Emission estimates for CH4 and N2O were calculated
by multiplying emission factors by measures of fuel
consumption by fuel type and mode. Emission factors used
in the calculations of CH4 and N2O emissions were obtained
from the Revised 1996 IPCC Guidelines (IPCC/UNEP/
OECD/IEA 1997). For aircraft emissions, the following
values, in units of grams of pollutant per kilogram of fuel
consumed (g/kg), were employed: 0.09 for CH4 and 0.1
for N2O. For marine vessels consuming either distillate
diesel or residual fuel oil the following values (g/MJ) were
employed: 0.32 for CH4 and 0.08 for N2O. Activity data
for aviation included solely jet fuel consumption statistics,
while the marine mode included both distillate diesel and
residual fuel oil.
Activity data on aircraft fuel consumption were
collected from three government agencies. Jet fuel
consumed by U.S. flag air carriers for international flight
segments was supplied by the Bureau of Transportation
Statistics (DOT 1991 through 2006). It was assumed that
50 percent of the fuel used by U.S. flagged carriers for
international flights —both departing and arriving in the
United States —was purchased domestically for flights
departing from the United States. In other words, only
one-half of the total annual fuel consumption estimate was
used in the calculations. Data on jet fuel expenditures by
foreign flagged carriers departing U.S. airports was taken
from unpublished data collected by the Bureau of Economic
Analysis (BEA) under the U.S. Department of Commerce
(BEA 1991 through 2006). Approximate average fuel prices
paid by air carriers for aircraft on international flights was
taken from DOT (1991 through 2006) and used to convert
the BEA expenditure data to gallons of fuel consumed. Data
on U.S. Department of Defense (DoD) aviation bunker fuels
and total jet fuel consumed by the U.S. military was supplied
by the Office of the Under Secretary of Defense (Installations
and Environment), DoD. Estimates of the percentage of each
Service's total operations that were international operations
were developed by DoD. Military aviation bunkers included
international operations, operations conducted from
energy
-------
naval vessels at sea, and operations conducted from U.S.
installations principally over international water in direct
support of military operations at sea. Military aviation
bunker fuel emissions were estimated using military fuel
and operations data synthesized from unpublished data by
the Defense Energy Support Center, under DoD's Defense
Logistics Agency (DESC 2006). Together, the data allow the
quantity of fuel used in military international operations to
be estimated. Densities for each jet fuel type were obtained
from a report from the U.S. Air Force (USAF 1998). Final
jet fuel consumption estimates are presented in Table 3-50.
See Annex 3.7 for additional discussion of military data.
Activity data on distillate diesel and residual fuel oil
consumption by cargo or passenger carrying marine vessels
departing from U.S. ports were taken from unpublished
data collected by the Foreign Trade Division of the U.S.
Department of Commerce's Bureau of the Census (DOC
1991 through 2006). Activity data on distillate diesel
consumption by military vessels departing from U.S. ports
were provided by DESC (2006). The total amount of fuel
provided to naval vessels was reduced by 13 percent to
account for fuel used while the vessels were not-underway
(i.e., in port). Data on the percentage of steaming hours
underway versus not-underway were provided by the U.S.
Navy. These fuel consumption estimates are presented in
Table 3-51.
Uncertainty
Emission estimates related to the consumption
of international bunker fuels are subject to the same
uncertainties as those from domestic aviation and marine
mobile combustion emissions; however, additional
uncertainties result from the difficulty in collecting accurate
fuel consumption activity data for international transport
activities separate from domestic transport activities.48
For example, smaller aircraft on shorter routes often carry
sufficient fuel to complete several flight segments without
refueling in order to minimize time spent at the airport gate or
take advantage of lower fuel prices at particular airports. This
practice, called tankering, when done on international flights,
complicates the use of fuel sales data for estimating bunker
fuel emissions. Tankering is less common with the type of
large, long-range aircraft that make many international flights
from the United States, however. Similar practices occur in
the marine shipping industry where fuel costs represent a
significant portion of overall operating costs and fuel prices
vary from port to port, leading to some tankering from ports
with low fuel costs.
Particularly for aviation, the DOT (1991 through
2006) international flight segment fuel delta used for U.S.
flagged carriers does not include smaller air carriers and
unfortunately defines flights departing to Canada and some
flights to Mexico as domestic instead of international. As
Table 3-50: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
U.S. Carriers
Foreign Carriers
U.S. Military
Total
1990
1,954
2,051
862
4,867
1995
2,221
2,544
581
5,347
2000
2,737
3,162
480
6,380
2001
2,619
3,113
524
6,255
2002
2,495
3,537
482
6,515
2003
2,418
3,377
473
6,268
2004
2,465
3,671
498
6,634
2005
2,760
3,450
462
6,673
Note: Totals may not sum due to independent rounding.
Table 3-51: Marine Fuel Consumption for International Transport (Million Gallons)
Fuel Type
Residual Fuel Oil
Distillate Diesel Fuel & Other
U.S. Military Naval Fuels
Total
1990
4,781
617
522
5,920
1995
3,495
573
334
4,402
2000
2,967
290
329
3,586
2001
2,846
204
318
3,368
2002
1,937
158
348
2,443
2003
1,597
137
459
2,193
2004
2,363
167
530
3,059
2005
2,320
241
471
3,032
Note: Totals may not sum due to independent rounding.
48 See uncertainty discussions under Carbon Dioxide Emissions from Fossil Fuel Combustion.
-------
for the BEA (1991 through 2006) data on foreign flagged
carriers, there is some uncertainty as to the average fuel price,
and to the completeness of the data. It was also not possible
to determine what portion of fuel purchased by foreign
carriers at U.S. airports was actually used on domestic flight
segments; this error, however, is believed to be small.49
Uncertainties exist with regard to the total fuel used by
military aircraft and ships, and in the activity data on military
operations and training that were used to estimate percentages
of total fuel use reported as bunker fuel emissions. Total
aircraft and ship fuel use estimates were developed from
DoD records, which document fuel sold to the Navy and
Air Force from the Defense Logistics Agency. These data
may slightly over- or under-estimate actual total fuel use in
aircraft and ships because each Service may have procured
fuel from, and/or may have sold to, traded with, and/or given
fuel to other ships, aircraft, governments, or other entities.
There are uncertainties in aircraft operations and training
activity data. Estimates for the quantity of fuel actually used
in Navy and Air Force flying activities reported as bunker
fuel emissions had to be estimated based on a combination
of available data and expert judgment. Estimates of marine
bunker fuel emissions were based on Navy vessel steaming
hour data, which reports fuel used while underway and fuel
used while not underway. This approach does not capture
some voyages that would be classified as domestic for a
commercial vessel. Conversely, emissions from fuel used
while not underway preceding an international voyage are
reported as domestic rather than international as would be
done for a commercial vessel. There is uncertainty associated
with ground fuel estimates for 1997 through 2001. Small fuel
quantities may have been used in vehicles or equipment other
than that which was assumed for each fuel type.
There are also uncertainties in fuel end-uses by fuel-
type, emissions factors, fuel densities, diesel fuel sulfur
content, aircraft and vessel engine characteristics and fuel
efficiencies, and the methodology used to back-calculate
the data set to 1990 using the original set from 1995. The
data were adjusted for trends in fuel use based on a closely
correlating, but not matching, data set. All assumptions used
to develop the estimate were based on process knowledge.
Department and military Service data, and expert judgments.
The magnitude of the potential errors related to the various
uncertainties has not been calculated, but is believed to be
small. The uncertainties associated with future military
bunker fuel emission estimates could be reduced through
additional data collection.
Although aggregate fuel consumption data have been
used to estimate emissions from aviation, the recommended
method for estimating emissions of gases other than CO2 in
the Revised 1996 IPCC Guidelines is to use data by specific
aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC
also recommends that cruise altitude emissions be estimated
separately using fuel consumption data, while landing and
take-off (LTO) cycle data be used to estimate near-ground
level emissions of gases other than CO2.M)
There is also concern as to the reliability of the existing
DOC (1991 through 2006) data on marine vessel fuel
consumption reported at U.S. customs stations due to the
significant degree of inter-annual variation.
QA/QC and Verification
A source-specific QA/QC plan for international bunker
fuels was developed and implemented. This effort included
a Tier 1 analysis, as well as portions of a Tier 2 analysis. The
Tier 2 procedures that were implemented involved checks
specifically focusing on the activity data and emission
factor sources and methodology used for estimating CO2,
CH4, and N2O from international bunker fuels in the United
States. Emission totals for the different sectors and fuels
were compared and trends were investigated. No corrective
actions were necessary.
49 Although foreign Hagged air carriers are prevented from providing domestic flight services in the United States, passengers may be collected from
multiple airports before an aircraft actually departs on its international flight segment. Emissions from these earlier domestic flight segments should be
classified as domestic, not international, according to the IPCC.
50 U.S. aviation emission estimates for CO. NO,, and NMVOCs are reported by EPA's National Emission Inventory (NEI) Air Pollutant Emission
Trends web site, and reported under the Mobile Combustion section. It should be noted that these estimates are based solely upon LTO cycles and
consequently only capture near ground-level emissions, which are more relevant for air quality evaluations. These estimates also include both domestic
and international flights. Therefore, estimates reported under the Mobile Combustion section overestimate IPCC-defmed domestic CO. NO,, and
NMVOC emissions by including landing and take-off (LTO) cycles by aircraft on international flights, but underestimate because they do not include
emissions from aircraft on domestic flight segments at cruising altitudes. The estimates in Mobile Combustion are also likely to include emissions from
ocean-going vessels departing from U.S. ports on international voyages.
Energy 3-55
-------
Recalculations Discussion
Historical activity data for aviation was slightly revised
for both U.S. and foreign carriers. These changes were due
to revisions to international fuel cost for foreign carriers and
international jet fuel consumption for U.S. carriers, provided
by DOT (1991 through 2006). The density for jet fuel was
also revised to reflect data obtained from Chevron (2000)
and ASTM (1989). This revision increased the heat content
for aviation jet fuel by 2 percent for all years. The C content
coefficient was also revised from 0.99 to 1 for all fuel types
based on guidance in IPCC (2006). These historical data
changes resulted in changes to the emission estimates for
1990 through 2004, which averaged to an annual increase
in emissions from international bunker fuels of 0.1 Tg CO2
Eq. (0.1 percent) in CO2 emissions, annual increase of less
than 0.1 Tg CO2 Eq. (less than 0.2 percent) in CH4 emissions,
and annual increase of less than 0.1 Tg CO2 Eq. (0.2 percent)
in N2O emissions.
3.12. Wood Biomass and Ethanol
Consumption (IPCC Source
Category 1 A)
The combustion of biomass fuels —such as wood,
charcoal, and wood waste —and biomass-based fuels —
such as ethanol from corn and woody crops —generates
CO2. However, in the long run the CO2 emitted from
biomass consumption does not increase atmospheric CO2
concentrations, assuming that the biogenic C emitted is
offset by the uptake of CO2 that results from the growth
of new biomass. As a result, CO2 emissions from biomass
combustion have been estimated separately from fossil fuel-
based emissions and are not included in the U.S. totals. Net
C fluxes from changes in biogenic C reservoirs in wooded
or crop lands are accounted for in the Land Use, Land-Use
Change, and Forestry chapter.
In 2005, total CO2 emissions from the burning of
woody biomass in the industrial, residential, commercial,
and electricity generation sectors were approximately 184.1
Tg CO2 Eq. (184,067 Gg) (see Table 3-52 and Table 3-53).
As the largest consumer of woody biomass, the industrial
sector was responsible for 63 percent of the CO2 emissions
from this source. The residential sector was the second
largest emitter, constituting 24 percent of the total, while
the commercial and electricity generation sectors accounted
for the remainder.
B iomass-derived fuel consumption in the United States
consisted primarily of ethanol use in the transportation
sector Ethanol is primarily produced from corn grown
in the Midwest, and was used mostly in the Midwest and
South. Pure ethanol can be combusted, or it can be mixed
with gasoline as a supplement or octane-enhancing agent.
The most common mixture is a 90 percent gasoline, 10
percent ethanol blend known as gasohol. Ethanol and ethanol
blends are often used to fuel public transport vehicles such
as buses, or centrally fueled fleet vehicles. These fuels burn
Table 3-52: C02 Emissions from Wood Consumption by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
135.3
59.8
6.8
13.3
215.2
1995
155.1
53.6
7.5
12.9
229.1
2000
153.6
44.3
7.4
13.9
219.1
2001
135.4
38.2
6.9
13.0
193.5
2002
131.1
39.2
7.1
15.5
192.8
2003
128.0
41.2
7.4
17.3
193.8
2004
138.5
42.3
7.3
17.0
205.1
2005
116.2
43.3
7.2
17.3
184.1
Note: Totals may not sum due to independent rounding.
Table 3-53: C02 Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
135,348
59,808
6,779
13,252
215,186
1995
155,075
53,621
7,463
12,932
229,091
2000
153,559
44,340
7,370
13,851
219,119
2001
135,415
38,153
6,887
13,034
193,489
2002
131,079
39,184
7,080
15,487
192,830
2003
127,970
41,247
7,366
17,250
193,833
2004
138,522
42,278
7,252
17,034
205,086
2005
116,238
43,309
7,236
17,284
184,067
Note: Totals may not sum due to independent rounding.
3-56 Inventory of 0,8. Greenhouse Gas Emissions and Silks: 1990-2GQ5
-------
cleaner than gasoline (i.e., lower in NOX and hydrocarbon
emissions), and have been employed in urban areas with poor
air quality. However, because ethanol is a hydrocarbon fuel,
its combustion emits CO2.
In 2005, the United States consumed an estimated
3.4 trillion Btu of ethanol, and as a result, produced
approximately 22.4 Tg CO, Eq. (22,408 Gg) (see Table 3-
54) of CO2 emissions. Ethanol production and consumption
has grown steadily every year since 1990, with the
exception of 1996 due to short corn supplies and high
prices in that year.
Methodology
Woody biomass emissions were estimated by applying
two El A gross heat contents (Lindstrom 2006) to U.S.
consumption data (ElA 2006) (see Table 3-55), provided in
energy units for the industrial, residential, commercial, and
electric generation sectors. One heat content (16.953114
MMBtu/MT wood and wood waste) was applied to the
industrial sector's consumption, while the other heat content
(15.432359 MMBtu/MT wood and wood waste) was applied
to the consumption data for the other sectors. An EIA
emission factor of 0.434 MT C/MT wood (Lindstrom 2006)
was then applied to the resulting quantities of woody biomass
to obtain CO2 emission estimates. It was assumed that the
woody biomass contains black liquor and other wood wastes,
has a moisture content of 12 percent, and is converted into
CO2 with 100 percent efficiency. The emissions from ethanol
consumption were calculated by applying an EIA emission
Table 3-54: C02 Emissions from Ethanol Consumption
(Tg C02 Eq. and Gg)
Table 3-55: Woody Biomass Consumption by Sector
(Trillion Btu)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
4.2
7.7
9.2
9.7
11.5
15.8
19.7
22.4
Gg
4,155
7,683
9,188
9,673
11,520
15,770
19,740
22,408
Year
1990
1995
2000
2001
2002
2003
2004
2005
Industrial
1,442
1,652
1,636
1,443
1,396
1,363
1,476
1,238
Residential
580
520
430
370
380
400
410
420
Commercial
66
72
71
67
69
71
70
70
Electricity
Generation
129
125
134
126
150
167
165
168
Table 3-56: Ethanol Consumption (Trillion Btu)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Trillion Btu
63
117
139
147
175
239
299
340
factor of 17.99 Tg C/QBtu (Lindstrom 2006) to U.S. ethanol
consumption estimates that were provided in energy units
(EIA 2006) (see Table 3-56).
Uncertainty
It is assumed that the combustion efficiency for
woody biomass is 100 percent, which is believed to be an
overestimate of the efficiency of wood combustion processes
in the United States. Decreasing the combustion efficiency
would increase emission estimates. Additionally, the heat
content applied to the consumption of woody biomass in
the residential, commercial, and electric power sectors is
unlikely to be a completely accurate representation of the
heat content for all the different types of woody biomass
consumed within these sectors. Emission estimates from
ethanol production are more certain than estimates from
woody biomass consumption due to better activity data
collection methods and uniform combustion techniques.
Energy 3-5"
-------
DiSCUSSiOn (EIA 2006>- EIA (2006) also reported minor changes in
Commercial wood consumption values were revised wood consumption by the residential and industrial sectors
for the full time series, based on updated information from for the ful1 time series'and in ethanol consumption for 2001
EIA's Commercial Building Energy Consumption Survey through 2004.
Box 3-4: Formation of C02 through Atmospheric CH4 Oxidation
CH4 emitted to the atmosphere will eventually oxidize into C02, which remains in the atmosphere for up to 200 years. The global
warming potential (GWP) of CH4, however, does not account for the radiative forcing effects of the C02 formation that results from this CH4
oxidation. The IPCC Guidelines for Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) do not explicitly recommend a procedure
for accounting for oxidized CH4, but some of the resulting C02 is, in practice, included in the inventory estimates because of the intentional
"double-counting" structure for estimating C02 emissions from the combustion of fossil fuels. According to the IPCC Guidelines, countries
should estimate emissions of CH4, CO, and NMVOCs from fossil fuel combustion, but also assume that these compounds eventually oxidize
to C02 in the atmosphere. This is accomplished by using C02 emission factors that do not factor out carbon in the fuel that is released in the
form of CH4, CO, and NMVOC molecules. Therefore, the carbon in fossil fuel is intentionally double counted, as an atom in a CH4 molecule
and as an atom in a C02 molecule.51 While this approach does account for the full radiative forcing effect of fossil fuel-related greenhouse
gas emissions, the timing is not accurate because it may take up to 12 years for the CH4 to oxidize and form C02.
There is no similar IPCC approach to account for the oxidation of CH4 emitted from sources other than fossil fuel combustion (e.g., landfills,
livestock, and coal mining). CH4 from biological systems contains carbon that is part of a rapidly cycling biological system, and therefore
any C created from oxidized CH4 from these sources is matched with carbon removed from the atmosphere by biological systems-likely
during the same or subsequent year. Thus, there are no additional radiative forcing effects from the oxidation of CH4 from biological systems.
For example, the C content of CH4 from enteric fermentation is derived from plant matter, which itself was created through the conversion
of atmospheric C02 to organic compounds.
The remaining anthropogenic sources of CH4 (e.g., fugitive emissions from coal mining and natural gas systems, industrial process
emissions) do increase the long-term C02 burden in the atmosphere, and this effect is not captured in the Inventory. The following tables
provide estimates of the equivalent C02 production that results from the atmospheric oxidation of CH4 from these remaining sources. The
estimates for CH4 emissions are gathered from the respective sections of this report, and are presented in Table 3-57. The C02 estimates
are summarized in Table 3-58.
Table 3-57: CH4 Emissions from Non-Combustion Fossil Sources (Gg)
Source
Coal Mining
Abandoned Underground Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production
Total
1990
3,899
286
5,927
1,640
41
1
63
11,858
1995
3,165
391
6,101
1,482
52
1
62
11,254
2000
2,662
349
6,027
1,325
58
1
57
10,479
2001
2,644
318
5,971
1,303
51
+
51
10,339
2002
2,476
292
5,951
1,275
52
+
48
10,094
2003
2,480
282
5,891
1,229
51
+
49
9,982
2004
2,597
275
5,669
1,209
55
+
50
9,855
2005
2,494
263
5,292
1,357
52
+
45
9,504
Note: These emissions are accounted for under their respective source categories. Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg
51 It is assumed that 100 percent of the CH4 emissions from combustion sources are accounted for in the overall carbon emissions calculated as CO2 for
sources using emission factors and carbon mass balances. However, it may be the case for some types of combustion sources that the oxidation factors
used for calculating CO: emissions do not accurately account for the full mass of carbon emitted in gaseous form (i.e., partially oxidized or still in
hydrocarbon form).
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1999-2005
-------
Box 3-4: Formation of C02 through Atmospheric CH4 Oxidation (continued)
Table 3-58: Formation of C02 through Atmospheric CH4 Oxidation (Tg C02 Eq.)
Source
Coal Mining
Abandoned Underground Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production
Total
1990
10.7
0.8
16.3
4.5
0.1
+
0.2
32.6
1995
8.7
1.1
16.8
4.1
0.1
+
0.2
30.9
2000
7.3
1.0
16.6
3.6
0.2
+
0.2
28.8
2001
7.3
0.9
16.4
3.6
0.1
+
0.1
28.4
2002
6.8
0.8
16.4
3.5
0.1
+
0.1
27.8
2003
6.8
0.8
16.2
3.4
0.1
+
0.1
27.4
2004
7.1
0.8
15.6
3.3
0.2
+
0.1
27.1
2005
6.9
0.7
14.6
3.7
0.1
+
0.1
26.1
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq.
The estimates of C02 formation are calculated by applying a factor of 44/16, which is the ratio of molecular weight of C02 to the molecular
weight of CH4. For the purposes of the calculation, it is assumed that CH, is oxidized to C02 in the same year that it is emitted. As discussed
above, this is a simplification, because the average atmospheric lifetime of CH4 is approximately 12 years.
C02 formation can also result from the oxidation of CO and NMVOCs. However, the resulting increase of C02 in the atmosphere is
explicitly included in the mass balance used in calculating the storage and emissions from non-energy uses of fossil fuels, with the carbon
components of CO and NMVOC counted as C02 emissions in the mass balance.52
'2 See Annex 2.3 tor a more detailed discussion on accounting for indirect emissions from CO and NMVOCs.
Energy 3-59
-------
-------
4. Industrial Processes
Greenhouse gas emissions are produced as a by-product of various non-energy-related industrial activities. That is,
these emissions are produced from an industrial process itself and are not directly a result of energy consumed
during the process. For example, raw materials can be chemically transformed from one state to another. This
transformation can result in the release of greenhouse gases such as carbon dioxide (CO2), methane (CH4), or nitrous
oxide (N2O). The processes addressed in this chapter include iron and steel production, cement manufacture, ammonia
manufacture and urea application, lime manufacture, limestone and dolomite use (e.g., flux stone, flue gas desulfurization,
and glass manufacturing), soda ash manufacture and use, titanium dioxide production, phosphoric acid production, ferroalloy
production, CO2 consumption, aluminum production, petrochemical production, silicon carbide production and consumption,
lead production, zinc production, nitric acid production, and adipic acid production (see Figure 4-1).
In addition to the three greenhouse gases listed above, there are also industrial sources of man-made fluorinated compounds
called hydrofluorocarbons (HFCs),perfluorocarbons (PFCs),
and sulfur hexafluoride (SF6). The present contribution of
these gases to the radiative forcing effect of all anthropogenic
greenhouse gases is small; however, because of their
extremely long lifetimes, many of them will continue
to accumulate in the atmosphere as long as emissions
continue. In addition, many of these gases have high global
warming potentials; SF6 is the most potent greenhouse gas
the Intergovernmental Panel on Climate Change (IPCC)
has evaluated. Usage of HFCs for the substitution of ozone
depleting substances is growing rapidly, as they are the
primary substitutes for ozone depleting substances (ODSs),
which are being phased-out under the Montreal Protocol
on Substances that Deplete the Ozone Layer. In addition
to their use as ODS substitutes, HFCs, PFCs, SF6, and
other fluorinated compounds are employed and emitted by
a number of other industrial sources in the United States.
These industries include aluminum production, HCFC-22
production, semiconductor manufacture, electric power
transmission and distribution, and magnesium metal
production and processing.
In 2005, industrial processes generated emissions of
333.6 teragrams of CO2 equivalent (Tg CO2 Eq.), or 5 percent
of total U.S. greenhouse gas emissions. CO2 emissions from
Figure 4-1
2005 Industrial Processes Chapter
Greenhouse Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
HCFC-22 Production K
Ammonia Manufacture and Urea Application Hi
Nitric Acid Production •§
Lime Manufacture IH
Electrical Transmission and Distribution JH
Limestone and Dolomite Use |
Aluminum Production I
Adipic Acid Production f
Semiconductor Manufacture |
Soda Ash Manufacture and Consumption |
Petrochemical Production |
Magnesium Production and Processing \
Titanium Dioxide Production !
Ferroalloy Production :
Phosphoric Acid Production '
Carbon Dioxide Consumption
Zinc Production <0.5
Lead Production
Silicon Carbide Production and Consumption
Industrial Processes
as a Portion of
all Emissions
4.6% J
<0.5
<0.5
25
50 75
Tg CO, Eq.
100
—I
125
Industrial Processes 4-1
-------
all industrial processes were 146.8 Tg CO2 Eq. (146,825
gigagrams [Gg]) in 2005, or 2 percent of total U.S. CO2
emissions. CH4 emissions from industrial processes resulted
in emissions of approximately 2.0 Tg CO2 Eq. (97 Gg) in
2005 , which was less than 1 percent of U .S . CH4 emissions .
N2O emissions from adipic acid and nitric acid production
were 21 .7 Tg CO2 Eq. (70 Gg) in 2005 , or 5 percent of total
U.S. N2O emissions. In 2005 , combined emissions of HFCs,
PFCs and SF6 totaled 163.0 Tg CO2 Eq. Overall, emissions
from industrial processes increased by 11.2 percent from
1990 to 2005 despite decreases in emissions from several
industrial processes, such as iron and steel, aluminum
production, ammonia manufacture and urea application,
HCFC-22 production, and electrical transmission and
distribution. The increase in overall emissions was driven by
a rise in the emissions originating from cement manufacture
and, primarily, the emissions from the use of substitutes for
ozone depleting substances.
Table 4-1 summarizes emissions for the Industrial
Processes chapter in units of Tg CO2 Eq., while unweighted
native gas emissions in Gg are provided in Table 4-2.
In order to ensure the quality of the emission estimates
from industrial processes, Tier 1 quality assurance and
quality control (QA/QC) procedures and checks have
been performed on all industrial process sources. Where
Table 4-1: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
C02
Cement Manufacture
Iron and Steel Production
1990
175.5
33.3
84.9
1995
171.8
36.8
73.3
2000
166.8
41.2
65.1
2001
152.8
41.4
57.9
2002
152.0
42.9
54.6
2003
148.8
43.1
53.4
2004
152.8
45.6
51.3
2005
146.8
45.9
45.2
Ammonia Manufacture & Urea
Application 19.3 20.5 19.6 16.7 17.8 16.2 16.9 16.3
Lime Manufacture 11.3 12.8 13.3 12.9 12.3 13.0 13.7 13.7
Limestone and Dolomite Use 5.5 7.4 6.0 5.7 5.9 4.7 6.7 7.4
Soda Ash Manufacture and
Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2
Aluminum Production 6.8 5.7 6.1 4.4 4.5 4.5 4.2 4.2
Petrochemical Production 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.9
Titanium Dioxide Production 1.3 1.7 1.9 1.9 2.0 2.0 2.3 1.9
Ferroalloy Production 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4
Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4
C02 Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3
Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5
Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3
Silicon Carbide Production and
Consumption 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2
CH4 2.2 2.4 2.5 2.2 2.1 2.1 2.2 2.0
Petrochemical Production 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1
Iron and Steel Production 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0
Ferroalloy Production + + + + + + + +
Silicon Carbide Production and
Consumption + + + + + + + +
N20 33.0 37.1 25.6 20.8 23.1 22.9 21.8 21.7
Nitric Acid Production 17.8 19.9 19.6 15.9 17.2 16.7 16.0 15.7
Adipic Acid Production 15.2 17.2 6.0 4.9 5.9 6.2 5.7 6.0
HFCs, PFCs, and SF6 89.3 103.5 143.8 133.8 143.0 142.7 153.9 163.0
Substitution of Ozone Depleting
Substances 0.3 32.2 80.9 88.6 96.9 105.5 114.5 123.3
HCFC-22 Production3 35.0 27.0 29.8 19.8 19.8 12.3 15.6 16.5
Electrical Transmission and
Distribution" 27.1 21.8 15.2 15.1 14.3 13.8 13.6 13.2
Semiconductor Manufacture 2.9 5.0 6.3 4.5 4.4 4.3 4.7 4.3
Aluminum Production 18.5 11.8 8.6 3.5 5.2 3.8 2.8 3.0
Magnesium Production and
Processing" 5.4 5.6 3.0 2.4 2.4 2.9 2.6 2.7
Total
300.1
314.8
338.7 309.6
320.2
316.4
330.6 333.6
+ Does not exceed 0.05 Tg C02 Eq.
a HFC-23 emitted
b SF6 emitted
Note: Totals may not sum due to independent rounding.
Inventon; of U.S. G»penhciusi; Sav. I-urnu'u mu Sink;.: 199I]-2Q<55
-------
Table 4-2: Emissions from Industrial Processes (Gg)
Gas/Source
C02
Cement Manufacture
Iron and Steel Production
Ammonia Manufacture & Urea
Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and
Consumption
CH4
Petrochemical Production
Iron and Steel Production
Ferroalloy Production
Silicon Carbide Production and
Consumption
N20
Nitric Acid Production
Adipic Acid Production
MFCs, PFCs, and SF6
Substitution of Ozone Depleting
Substances
HCFC-22 Production3
Electrical Transmission and
Distribution"
Semiconductor Manufacture
Aluminum Production
Magnesium Production and
Processing"
NO,
CO
NMVOCs
+ Does not exceed 0.5 Gg
M (Mixture of gases)
a HFC-23 emitted
b SF6 emitted
1990
175,500
33,278
84,904
19,306
11,273
5,533
4,141
6,831
2,221
1,308
2,152
1,529
1,415
949
285
375
106
41
63
1
1
107
58
49
M
M
3
1
M
M
+
591
4,125
2,422
1995
171,832
36,847
73,333
20,453
12,844
7,359
4,304
5,659
2,750
1,670
2,036
1,513
1,423
1,013
298
329
116
52
62
1
1
120
64
56
M
M
2
1
M
M
+
607
3,959
2,642
2000
166,805
41,190
65,115
19,616
13,344
5,960
4,181
6,086
3,004
1,918
1,893
1,382
1,416
1,140
311
248
117
58
57
1
1
83
63
19
M
M
3
1
M
M
+
626
2,217
1,773
2001
152,794
41,357
57,927
16,719
12,861
5,733
4,147
4,381
2,787
1,857
1,459
1,264
825
986
293
199
103
51
51
+
+
67
51
16
M
M
2
1
M
M
+
656
2,339
1,769
2002
152,032
42,898
54,595
17,766
12,330
5,885
4,139
4,490
2,857
1,997
1,349
1,338
978
937
290
183
101
52
48
+
+
75
56
19
M
M
2
1
M
M
+
532
1,710
1,811
2003
148,767
43,082
53,370
16,173
13,022
4,720
4,111
4,503
2,777
2,013
1,305
1,382
1,310
507
289
202
101
51
49
+
+
74
54
20
M
M
1
1
M
M
+
533
1,730
1,813
2004
152,798
45,603
51,309
16,894
13,728
6,702
4,205
4,231
2,895
2,259
1,419
1,395
1,199
477
259
224
106
55
50
+
+
70
52
19
M
M
1
1
M
M
+
534
1,751
1,815
2005
146,825
45,910
45,235
16,321
13,660
7,397
4,228
4,208
2,897
1,921
1,392
1,383
1,324
465
265
219
97
51
45
+
+
70
51
19
M
M
1
1
M
M
+
535
1,772
1,818
Note: Totals may not sum due to independent rounding.
performed, Tier 2 procedures focused on the emission
factor and activity data sources and methodology used for
estimating emissions, and will be described within the QA/
QC and Verification Discussion of that source description.
In addition to the national QA/QC plan, a more detailed plan
was developed specifically for the CO2 and CH4 industrial
processes sources. This plan was based on the U.S. strategy,
but was tailored to include specific procedures recommended
for these sources.
The general method employed to estimate emissions
for industrial processes, as recommended by the IPCC,
involves multiplying production data (or activity data) for
each process by an emission factor per unit of production.
The uncertainty in the emission estimates is therefore
generally a function of a combination of the uncertainties
surrounding the production and emission factor variables.
Uncertainty of activity data and the associated probability
density functions for industrial processes CO2 sources were
Industrial Processes 4-3
-------
estimated based on expert assessment of available qualitative
and quantitative information. Uncertainty estimates and
probability density functions for the emission factors used
to calculate emissions from this source were devised based
on IPCC recommendations.
Activity data is obtained through a survey of
manufacturers conducted by various organizations
(specified within each source); the uncertainty of the
activity data is a function of the reliability of plant-level
production data and is influenced by the completeness
of the survey response. The emission factors used were
either derived using calculations that assume precise and
efficient chemical reactions, or were based upon empirical
data in published references. As a result, uncertainties in
the emission coefficients can be attributed to, among other
things, inefficiencies in the chemical reactions associated
with each production process or to the use of empirically-
derived emission factors that are biased; therefore, they
may not represent U.S. national averages. Additional
assumptions are described within each source.
The uncertainty analysis performed to quantify
uncertainties associated with the 2005 inventory estimates
from industrial processes continues a multi-year process for
developing credible quantitative uncertainty estimates for
these source categories using the IPCC Tier 2 approach.
As the process continues, the type and the characteristics
of the actual probability density functions underlying
the input variables are identified and better characterized
(resulting in development of more reliable inputs for the
model, including accurate characterization of correlation
between variables), based primarily on expert judgment.
Accordingly, the quantitative uncertainty estimates reported
in this section should be considered illustrative and as
iterations of ongoing efforts to produce accurate uncertainty
estimates. The correlation among data used for estimating
emissions for different sources can influence the uncertainty
analysis of each individual source. While the uncertainty
analysis recognizes very significant connections among
sources, a more comprehensive approach that accounts for
all linkages will be identified as the uncertainty analysis
moves forward.
4.1. Cement Manufacture (IPCC
Source Category 2A1)
Cement manufacture is an energy- and raw-material-
intensive process that results in the generation of CO2 from
both the energy consumed in making the cement and the
chemical process itself.' Cement production, at the most
recent estimation, accounted for about 2.4 percent of total
global industrial and energy-related CO2 emissions (IPCC
1996, USGS 2003). Cement is manufactured in 37 states
and Puerto Rico. CO2 emitted from the chemical process
of cement production is the largest source of industrial CO2
emissions in the United States.
During the cement production process, calcium
carbonate (CaCO3) is heated in a cement kiln at a temperature
of about 1,300 °C (2,400 °F) to form lime (i.e.. calcium
oxide or CaO) and CO2 in a process known as calcination
or calcining. A very small amount of carbonates other than
CaCO3 is also present in the raw material; however, for
calculation purposes all of the raw material is assumed to be
CaCO3. Next, the lime is combined with silica-containing
materials to produce clinker (an intermediate product), with
the earlier by-product CO2 being released to the atmosphere.
The clinker is then allowed to cool, mixed with a small
amount of gypsum, and used to make portland cement.
Additional COi emissions result from the production of
masonry cement, which accounts for approximately 6
percent of total clinker production, and is produced using
lime and portland cement. However, this additional lime
is already accounted for in the Lime Manufacture source
category in this chapter; therefore, the additional emissions
from making masonry cement from clinker are not counted
in this source category's total. They are presented here for
informational purposes only.
1 The CO2 emissions related to the consumption of energy for cement manufacture are accounted for under CO, from Fossil Fuel Combustion in the
Energy chapter.
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-3: C02 Emissions from Cement Production
(Tg C02 Eq. and Gg)*
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
Gg
33,278
36,847
41,190
41,357
42,898
43,082
45,603
45,910
* Totals exclude C02 emissions from making masonry cement from
clinker, which are accounted for under Lime Manufacture.
In 2005, U.S. clinker production —including Puerto
Rico—totaled 88,783 thousand metric tons (Van Oss 2006).
The resulting emissions of CO2 from 2005 cement production
were estimated to be 45.9 Tg CO2 Eq. (45,910 Gg) (see Table
4-3). Emissions from masonry production from clinker raw
material are accounted for under Lime Manufacture.
After falling in 1991 by two percent from 1990 levels,
cement production emissions have grown every year since.
Overall, from 1990 to 2005, emissions increased by 38
percent. Cement continues to be a critical component of the
construction industry; therefore, the availability of public
construction funding, as well as overall economic growth,
have had considerable influence on cement production.
Methodology
CO2 emissions from cement manufacture are created
by the chemical reaction of carbon-containing minerals
(i.e., calcining limestone). While in the kiln, limestone is
broken down into CO2 and lime with the CO2 released to
the atmosphere. The quantity of CO2 emitted during cement
production is directly proportional to the lime content of
the clinker. During calcination, each mole of CaCO, (i.e.,
limestone) heated in the clinker kiln forms one mole of lime
(CaO) and one mole of CO2:
Ca('<). - hojt •/ (.'at > •+ (''),
CO2 emissions were estimated by applying an emission
factor, in tons of CO2 released per ton of clinker produced,
to the total amount of clinker produced. The emission
factor used in this analysis is the product of the average
lime fraction for clinker of 64.6 percent (IPCC 2000) and
a constant reflecting the mass of CO2 released per unit of
lime. This calculation yields an emission factor of 0.507 tons
of CO2 per ton of clinker produced, which was determined
as follows: , 1
j-i-j n j >_• mole CO
During clinker production, some of the clinker
precursor materials remain in the kiln as non-calcinated,
partially calcinated, or fully calcinated cement kiln dust
(CKD). The emissions attributable to the calcinated portion
of the CKD are not accounted for by the clinker emission
factor. The IPCC recommends that these additional CKD
CO2 emissions should be estimated as two percent of the
CO2 emissions calculated from clinker production. Total
cement production emissions were calculated by adding
the emissions from clinker production to the emissions
assigned to CKD (IPCC 2000).
Masonry cement requires additional lime over and
above the lime used in clinker production. In particular,
non-plasticizer additives such as lime, slag, and shale are
added to the cement, increasing its weight by approximately
five percent. Lime accounts for approximately 60 percent of
this added weight. Thus, the additional lime is equivalent to
roughly 2.86 percent of the starting amount of the product,
since:
An emission factor for this added lime can then be
calculated by multiplying this 2.86 percent by the molecular
weight ratio of CO2 to CaO (0.785) to yield 0.0224 metric
tons of additional CO2 emitted for every metric ton of
masonry cement produced.
As previously mentioned, the CO2 emissions from the
additional lime added during masonry cement production are
accounted for in the section on CO2 emissions from Lime
Manufacture. Thus, the activity data for masonry cement
production are shown in this chapter for informational purposes
only, and are not included in the cement emission totals.
The 1990 through 2005 activity data for clinker and
masonry cement production (see Table 4-4) were obtained
through a personal communication with Hendrick Van Oss
(Van Oss 2006) of the USGS and through the USGS Mineral
Yearbook: Cement (USGS 1993 through 2005). The data
were compiled by USGS through questionnaires sent to
domestic clinker and cement manufacturing plants.
Industrial Processes 4-5
-------
Table 4-4: Cement Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Clinker
64,355
71,257
79,656
79,979
82,959
83,315
88,190
88,783
Masonry
3,209
3,603
4,332
4,450
4,449
4,737
5,000
5,514
Uncertainty
The uncertainties contained in these estimates are
primarily due to uncertainties in the lime content of clinker
and in the percentage of CKD recycled inside the clinker
kiln. Uncertainty is also associated with the amount of lime
added to masonry cement, but it is accounted for under the
Lime Manufacture source category. The lime content of
clinker varies from 64 to 66 percent. CKD loss can range
from 1.5 to 8 percent depending upon plant specifications.
Additionally, some amount of CO2 is reabsorbed when the
cement is used for construction. As cement reacts with water,
alkaline substances such as calcium hydroxide are formed.
During this curing process, these compounds may react with
CO2 in the atmosphere to create calcium carbonate. This
reaction only occurs in roughly the outer 0.2 inches of surface
area. Because the amount of CO2 reabsorbed is thought to
be minimal, it was not estimated.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-5. Cement Manufacture CO2
emissions were estimated to be between 40.1 and 52.1 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 13 percent below and 14 percent
above the emission estimate of 45.9 Tg CO2 Eq.
Recalculation:; Discussion
The historical activity data used to calculate the
emissions from cement production were updated for the
year 2004. The change resulted in a decrease of 0.04 Tg CO2
Eq. (less than one percent) in CO2 emissions from cement
production for that year.
4.2. iron arid Steel Production
(IPCC Source Category 2C1)
In addition to being an energy intensive process, the
production of iron and steel also generates process-related
emissions of CO2 and CH4. Iron is produced by first
reducing iron oxide (iron ore) with metallurgical coke in a
blast furnace to produce pig iron (impure iron containing
about 3 to 5 percent C by weight). Metallurgical coke is
manufactured using coking coal as a raw material. Iron may
be introduced into the blast furnace in the form of raw iron
ore, pellets, briquettes, or sinter. Pig iron is used as a raw
material in the production of steel, which contains about 4
percent C by weight. Pig iron is also used as a raw material
in the production of iron products in foundries. The pig iron
production process produces CO2 emissions and fugitive
CH4 emissions.
The production of metallurgical coke from coking coal
and the consumption of the metallurgical coke used as a
reducing agent in the blast furnace are considered in the
Inventory to be non-energy (industrial) processes, not energy
(combustion) processes. Metallurgical coke is produced
by heating coking coal in a coke oven in a low-oxygen
environment. The process drives off the volatile components
of the coking coal and produces coal (metallurgical) coke.
Coke oven gas and coal tar are C-containing by-products
of the coke manufacturing process. Coke oven gas is
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Cement Manufacture
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Cement Manufacture
CO,
45.9
40.1
52.1
-13%
+14%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
generally burned as a fuel within the steel mill. Coal tar is
used as a raw material to produce anodes used for primary
aluminum production and other electrolytic processes, and
also in the production of other coal tar products. The coke
production process produces CO2 emissions and fugitive
CH4 emissions.
Sintering is a thermal process by which fine iron-bearing
particles, such as air emission control system dust, are baked,
which causes the material to agglomerate into roughly one-
inch pellets that are then recharged into the blast furnace for
pig iron production. Iron ore particles may also be formed
into larger pellets or briquettes by mechanical means, and
then agglomerated by heating prior to being charged into the
blast furnace. The sintering process produces CO2 emissions
and fugitive CH4 emissions.
The metallurgical coke is a reducing agent in the blast
furnace. CO2 is produced as the metallurgical coke used in the
blast furnace process is oxidized and the iron ore is reduced.
Steel is produced from pig iron in a variety of specialized
steel-making furnaces. The majority of CO2 emissions from
the iron and steel process come from the use of coke in the
production of pig iron, with smaller amounts evolving from
the removal of C from pig iron used to produce steel. Some
C is also stored in the finished iron and steel products.
Emissions of CO2 and CH4 from iron and steel production
in 2005 were 45.2 Tg CO2 Eq. (45,235 Gg) and 1.0 Tg CO2
Eq. (45 Gg), respectively (see Table 4-6 and Table 4-7),
totaling 46.2 Tg CO2 Eq. Emissions have declined steadily
from 1990 to 2005 due to restructuring of the industry,
technological improvements, and increased scrap utilization.
In 2005, domestic production of pig iron decreased by 12.0
percent and coal coke production decreased by 1.1 percent.
Overall, domestic pig iron and coke production have declined
since the 1990s. Pig iron production in 2005 was 21 percent
lower than in 2000 and 24 percent below 1990 levels. Coke
production in 2005 was 20 percent lower than in 2000 and
39 percent below 1990 levels. Overall, emissions from iron
and steel productions have declined by 47 percent (40.0 Tg
CO2Eq.) from 1990 to 2005.
Methodology
Coking coal is used to manufacture metallurgical
(coal) coke that is used primarily as a reducing agent in
the production of iron and steel, but is also used in the
production of other metals including lead and zinc (see Lead
Production and Zinc Production in this chapter). The total
coking coal converted to coke in coke plants and the total
amount of coke produced were identified. These data were
used to estimate the emissions associated with producing
coke from coking coal and attributed to the production of
iron and steel. Additionally, the amount of coke consumed
to produce pig iron and the emissions associated with this
production were estimated. The C content of the coking
coal and coke consumed in these processes were estimated
by multiplying the energy consumption by material specific
C-content coefficients. The C content coefficients used are
presented in Annex 2.1.
Emissions from the re-use of scrap steel were also
estimated by assuming that all the associated C content
of the scrap steel, which has an associated C content of
approximately 0.5 percent, are released during the scrap
re-use process.
Lastly, emissions from C anodes, used during the
production of steel in electric arc furnaces (EAFs), were also
Table 4-6: C02 and CH4 Emissions from Iron and Steel Production (Tg C02 Eq.)
Gas
C02
CH4
Total
1990
84.9
1.3
86.2
1995
73.3
1.3
74.6
2000
65.1
1.2
66.3
2001
57.9
1.1
59.0
2002
54.6
1.0
55.6
2003
53.4
1.0
54.4
2004
51.3
1.0
52.3
2005
45.2
1.0
46.2
Table 4-7: C02 and CH4 Emissions from Iron and Steel Production (Gg)
Gas
C02
CH4
1990
84,904
63
1995
73,333
62
2000
65,115
57
2001
57,927
51
2002
54,595
48
2003
53,370
49
2004
51,309
50
2005
45,235
45
Industrie! Processes 4-7
-------
estimated. Emissions of CO2 were calculated by multiplying
the annual production of steel in EAFs by an emission factor
(4.4 kg CO2/ton steelEAF). It was assumed that the C anodes
used in the production of steel in EAFs are composed of
80 percent petroleum coke and 20 percent coal tar pitch
(DOE 1997). Since coal tar pitch is a by-product of the coke
production process and its C-related emissions have already
been accounted for earlier in the iron and steel emissions
calculation as part of the process, the emissions were reduced
by the amount of C in the coal tar pitch used in the anodes
to avoid double counting.
Emissions associated with the production of coke from
coking coal, pig iron production, the re-use of scrap steel,
and the consumption of C anodes during the production of
steel were summed.
Additionally, the coal tar pitch component of C anodes
consumed during the production of aluminum is accounted
for in the aluminum production section of this chapter. The
emissions were reduced by the amount of coal tar pitch
used in aluminum production to avoid double counting.
The amount of coal tar pitch consumed for processes other
than the aluminum production and as EAF anodes and net
imports of coal tar were also estimated. A storage factor was
applied to estimate emissions associated with other coal tar
pitch consumption and net imports.
C storage was accounted for by assuming that all
domestically manufactured steel had a C content of 0.5
percent. Furthermore, any pig iron that was not consumed
during steel production, but fabricated into finished iron
products, was assumed to have a C content of 4 percent.
The potential CO2 emissions associated with C
contained in pig iron used for purposes other than iron and
steel production, stored in the steel product, stored as coal
tar, and attributed to C anode consumption during aluminum
production were summed and subtracted from the total
emissions estimated above.
The production processes for coal coke, sinter, and pig
iron result in fugitive emissions of CH4, which are emitted
via leaks in the production equipment rather than through the
emission stacks or vents of the production plants. The fugitive
emissions were calculated by applying emission factors taken
from the 1995 IPCC Guidelines (IPCC/UNEP/OECD/IEA
1995) (see Table 4-8) to annual domestic production data for
coal coke, sinter, and pig iron.
Table 4-8: CH4 Emission Factors for Coal Coke, Sinter,
and Pig Iron Production (g/kg)
Material Produced
g Ctykg produced
Coal Coke
Pig Iron
Sinter
0.5
0.9
0.5
Source: IPCC/UNEP/OECD/IEA 1997.
Data relating to the amount of coal consumed at
coke plants, and for the production of coke for domestic
consumption in blast furnaces, were taken from the Energy
Information Administration (EIA), Quarterly Coal Report
October through December (EIA 1998. 1999, 2000, 2001,
2002,2003,2004a) and January through March (EIA 2006c).
Data on total coke consumed for pig iron production were
taken from the American Iron and Steel Institute (AISI),
Annual Statistical Report (AISI 2001, 2002, 2003, 2004,
2005,2006). Scrap steel consumption data for 1990 through
2005 \vere obtained from Annual Statistical Report (AISI
1995,2001,2002,2003,2004,2005,2006) (see Table 4-9).
Crude steel production, as well as pig iron use for purposes
other than steel production, was also obtained from Annual
Statistical Report (AISI 1996, 2001, 2002, 2004, 2005,
2006). C content percentages for pig iron and crude steel
and the CO2 emission factor for C anode emissions from
steel production were obtained from IPCC Good Practice
Guidaiice (IPCC 2000). Data on the non-energy use of coking
coal wsre obtained from EIA's Emissions of U.S. Greenhouse
Gases in the United States (EIA 2004b, 2006b). Information
on coal tar net imports was determined using data from
the U.S. Bureau of the Census's U.S. International Trade
Commission's Trade Dataweb (U.S. Bureau of the Census
2006). Coal tar consumption for aluminum production data
was estimated based on information gathered by EPA's
Voluntary Aluminum Industrial Partnership (VAIP) program
and data from USAA Primary Aluminum Statistics (USAA
2004,2005,2006) (see Aluminum Production in this chapter).
Annual consumption of iron ore used in sinter production
for 1990 through 2004 was obtained from the USGS Iron
Ore Yearbook (USGS 1994, 1995,1996,1997, 1998, 1999,
2000, 2001,2002,2003,2004) and for 2005 from the USGS
Commodity Specialist (Jorgenson 2006). The CO2 emission
factor for C anode emissions from aluminum production
was taken from the Revised 1996 IPCC Guidelines (IPCC/
UNEP/OECD/IEA 1997). Estimates for the composition of
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-9: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons)
Gas/Activity Data
C02
Coal Consumption at Coke Plants
Coke Consumption for Pig Iron
Basic Oxygen Furnace Steel
Production
Electric Arc Furnace Steel
Production
CH4
Coke Production
Iron Ore Consumption for Sinter
Domestic Pig Iron Production for
Steel
1990
35,269
25,043
56,216
33,510
25,054
12,239
49,062
1995
29,948
22,288
56,721
38,472
21,545
12,575
50,233
2000
26,254
19,307
53,965
47,860
18,877
10,784
47,400
2001
23,655
17,236
47,359
42,774
17,191
9,234
41,741
2002
21,461
15,959
45,463
46,125
15,221
9,018
39,601
2003
21,998
15,482
45,874
47,804
15,579
8,984
40,487
2004
21,473
15,068
47,714
51,969
15,340
8,047
42,292
2005
21,259
13,848
42,705
52,194
15,167
8,313
37,222
C anodes used during EAF steel and aluminum production
were obtained from Energy and Environmental Profile of the
U.S. Aluminum Industry (DOE 1997).
Uncertainty
The time series data sources for production of coal
coke, sinter, pig iron, steel, and aluminum upon which
the calculations are based are assumed to be consistent
for the entire time series. The estimates of CO2 emissions
from the production and utilization of coke are based on
consumption data, average C contents, and the fraction
of C oxidized. Uncertainty is associated with the total
U.S. coke consumption and coke consumed for pig iron
production. These data are provided by different data sources
(EIA and AISI) and comparisons between the two datasets
for net imports, production, and consumption identified
discrepancies; however, the data chosen are considered the
best available. These data and factors produce a relatively
accurate estimate of CO2 emissions. However, there are
uncertainties associated with each of these factors. For
example, C oxidation factors may vary depending on
inefficiencies in the combustion process, where varying
degrees of ash or soot can remain unoxidized.
Simplifying assumptions were made concerning the
composition of C anodes and the C contents of all pig iron
and crude steel. It was also assumed that all coal tar used
during anode production originates as a by-product of the
domestic coking process. There is also uncertainty associated
with the total amount of coal tar products produced and with
the storage factor for coal tar. Uncertainty surrounding the
CO2 emission factor for C anode consumption in aluminum
production was also estimated.
For the purposes of the CH4 calculation it is assumed
that none of the CH4 is captured in stacks or vents and that
all of the CH4 escapes as fugitive emissions. Additionally,
the CO2 emissions calculation is not corrected by subtracting
the C content of the CH4, which means there may be a slight
double counting of C as both CO2 and CH4.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-10. Iron and Steel CO2 emissions
were estimated to be between 40.4 and 57.2 Tg CO2 Eq. at
the 95 percent confidence level. This indicates a range of
approximately 11 percent below and 27 percent above the
emission estimate of 45.2 Tg CO2 Eq. Iron and Steel CH4
emissions were estimated to be between 0.9 Tg CO9 Eq.
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Iron and Steel Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eg.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Iron and Steel Production
Iron and Steel Production
C02
45.2
1.0
40.4
0.9
57.2
1.0
-11%
+ 27%
+8%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-9
-------
and 1.0 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 8 percent below and 8
percent above the emission estimate of 1.0 Tg CO2 Eq.
Recalculations Discussion
CO2 emission estimates for the iron and steel source
category were updated for the entire time series to reflect
revisions to the coal tar import/export data and the C content
of steel. These revisions resulted in a change in emissions of
less than one percent throughout the time series.
Planned Improvements
Plans for improvements to the iron and steel source
category are to include methodologies outlined in the 2006
IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC 2006). These methodologies involve the inclusion
of energy-related emissions in the iron and steel emission
estimates as well as emissions associated with metallurgical
coke production, sinter production, pellet production, and
direct reduced iron ore production in addition to iron and
steel production.
4.3. Ammonia Manufacture and
Urea Application (IPCC Source
Category 2B1)
Emissions of CO2 occur during the production of
synthetic ammonia, primarily through the use of natural gas
as a feedstock. The natural gas-based, naphtha-based, and
petroleum-coke-based processes produce CO2 and hydrogen
(H2), the latter of which is used in the production of ammonia.
One nitrogen production plant located in Kansas is producing
ammonia from petroleum coke feedstock. In some plants the
CO2 produced is captured and used to produce urea. The
brine electrolysis process for production of ammonia does
not lead to process-based CO2 emissions.
There are five principal process steps in synthetic
ammonia production from natural gas feedstock. The primary
reforming step converts CH4 to CO2, carbon monoxide (CO),
and H2 in the presence of a catalyst. Only 30 to 40 percent
of the CH4 feedstock to the primary reformer is converted
to CO and CO2. The secondary reforming step converts the
remaining CH4 feedstock to CO and CO2. The CO in the
process gas from the secondary reforming step (representing
approximately 15 percent of the process gas) is converted to
CO2 in the presence of a catalyst, water, and air in the shift
conversion step. CO2 is removed from the process gas by the
shift conversion process, and the hydrogen gas is combined
with the nitrogen (N2) gas in the process gas during the
ammonia synthesis step to produce ammonia. The CO2 is
included in a waste gas stream with other process impurities
and is absorbed by a scrubber solution. In regenerating the
scrubber solution, CO2 is released.
The conversion process for conventional steam reforming
of CH4, including primary and secondary reforming and the
shift conversion processes, is approximately as follows:
To produce synthetic ammonia from petroleum coke,
the petroleum coke is gasified and converted to CO2 and H2.
These gases are separated, and the H2 is used as a feedstock
to the ammonia production process, where it is reacted with
N2 to form ammonia.
Not all of the CO2 produced in the production of
ammonia is emitted directly to the atmosphere. Both
ammonia and CO2 are used as raw materials in the production
of urea [CO(NH2)2|, which is another type of nitrogenous
fertilizer that contains C as well as N. The chemical reaction
that produces urea is:
' NH, C •<"),- \H,rOO\)i; ->COiNH •, t HO
The C in the urea that is produced and assumed to be
subsequently applied to agricultural land as a nitrogenous
fertilizer is ultimately released into the environment as
CO2; therefore, the CO2 produced by ammonia production
and subsequently used in the production of urea does not
change overall CO2 emissions. However, the CO2 emissions
are allocated to the ammonia and urea production processes
according to the amount of ammonia and urea produced.
Net emissions of CO2 from ammonia manufacture in
2005 were 9.2 Tg CO2 Eq. (9,197 Gg), and are summarized
in Table 4-11 and Table 4-12. Emissions of CO2 from urea
application in 2005 totaled 7.1 Tg CO2 Eq. (7,124 Gg), and
are summarized in Table 4-11 and Table 4-12.
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19913-2005
-------
Table 4-11: C02 Emissions from Ammonia Manufacture and Urea Application (Tg C02 Eq.)
Source
Ammonia Manufacture
Urea Application
Total
1990
12.6
6.8
19.3
1995
13.5
6.9
20.5
2000
12.1
7.5
19.6
2001
9.3
7.4
16.7
2002
10.5
7.3
17.8
2003
8.8
7.4
16.2
2004
9.6
7.3
16.9
2005
9.2
7.1
16.3
Note: Totals may not sum due to independent rounding.
Table 4-12: C02 Emissions from Ammonia Manufacture and Urea Application (Gg)
Source
Ammonia Manufacture
Urea Application
Total
1990
12,553
6,753
19,306
1995
13,546
6,907
20,453
2000
12,128
7,488
19,616
2001
9,321
7,398
16,719
2002
10,501
7,266
17,766
2003
8,815
7,358
16,173
2004
9,571
7,323
16,894
2005
9,197
7,124
16,321
Note: Totals may not sum due to independent rounding.
Methodology
The calculation methodology for non-combustion
CO2 emissions from production of nitrogenous fertilizers
from natural gas feedstock is based on a CO2 emission
factor published by the European Fertilizer Manufacturers
Association (EFMA). The CO2 emission factor (1.2 metric
tons CO2/metric ton NH3) is applied to the percent of total
annual domestic ammonia production from natural gas
feedstock. Emissions of CO2 from ammonia production
are then adjusted to account for the use of some of the CO2
produced from ammonia production as a raw material in
the production of urea. For each ton of urea produced, 8.8
of every 12 tons of CO2 are consumed and 6.8 of every
12 tons of ammonia are consumed. The CO2 emissions
reported for ammonia production are therefore reduced by
a factor of 0.73 multiplied by total annual domestic urea
production, and that amount of CO2 emissions is allocated
to urea fertilizer application. Total CO2 emissions resulting
from nitrogenous fertilizer production do not change as a
result of this calculation, but some of the CO2 emissions
are attributed to ammonia production and some of the CO2
emissions are attributed to urea application.
The calculation of the total non-combustion CO7
emissions from nitrogenous fertilizers accounts for CO2
emissions from the application of imported and domestically
produced urea. For each ton of imported urea applied, 0.73
tons of CO2 are emitted to the atmosphere. The amount of
imported urea applied is calculated based on the net of urea
imports and exports.
All ammonia production and subsequent urea
production are assumed to be from the same process —
conventional catalytic reforming of natural gas feedstock,
with the exception of ammonia production from petroleum
coke feedstock at one plant located in Kansas. The CO2
emission factor for production of ammonia from petroleum
coke is based on plant specific data, wherein all C contained
in the petroleum coke feedstock that is not used for urea
production is assumed to be emitted to the atmosphere as
CO2 (Bark 2004). Ammonia and urea are assumed to be
manufactured in the same manufacturing complex, as both
the raw materials needed for urea production are produced
by the ammonia production process. The CO2 emission
factor (3.57 metric tons CO2/metric ton NH3) is applied to
the percent of total annual domestic ammonia production
from petroleum coke feedstock.
The emission factor of 1.2 metric tons CO2/metric ton
NH3 for production of ammonia from natural gas feedstock
was taken from the EFMA Best Available Techniques
publication, Production of Ammonia (EFMA 1995). The
EFMA reported an emission factor range of 1.15 to 1.30
metric tons CO2/metric ton NH3, with 1.2 metric tons CO2/
metric ton NH3 as a typical value. The EFMA reference also
indicates that more than 99 percent of the CH4 feedstock to
the catalytic reforming process is ultimately converted to
CO2. The emission factor of 3.57 metric tons CO2/metric
ton NH3 for production of ammonia from petroleum coke
feedstock was developed from plant-specific ammonia
production data and petroleum coke feedstock utilization
data for the ammonia plant located in Kansas (Bark 2004).
Ammonia and urea production data (see Table 4-13) were
obtained from Coffeyville Resources (Coffeyville 2005,
2006) and the Census Bureau of the U.S. Department of
-------
Table 4-13: Ammonia Production, Urea Production, and
Urea Net Imports (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Ammonia
Production
15,425
15,788
14,342
11,092
12,577
10,279
10,939
10,143
Urea
Production
8,124
7,363
6,969
6,080
7,038
5,783
5,755
5,268
Urea Net
Imports
1,086
2,055
3,241
4,008
2,870
4,250
4,230
4,447
Commerce (U.S. Census Bureau 1991, 1992, 1993, 1994,
1998, 1999, 2000, 2001a, 2001b, 2002a, 2002b, 2002c,
2003, 2004, 2005, 2006) as reported in Current Industrial
Reports Fertilizer Materials and Related Products annual
and quarterly reports. Import and export data for urea were
obtained from the U.S. Census Bureau Current Industrial
Reports Fertilizer Materials and Related Products annual and
quarterly reports for 1997 through 2005 (U.S. Census Bureau
1998,1999,2000,2001 a, 2001b, 2002a, 2002b, 2002c, 2003,
2004, 2005, 2006), The Fertilizer Institute (TFI 2002) for
1993 through 1996, and the United States International Trade
Commission Interactive Tariff and Trade DataWeb (U.S. ITC
2002) for 1990 through 1992 (see Table 4-13).
Uncertainty
The uncertainties presented in this section are primarily
due to how accurately the emission factor used represents
an average across all ammonia plants using natural gas
feedstock. Uncertainties are also associated with natural gas
feedstock consumption data for the U.S. ammonia industry
as a whole; the assumption that all ammonia production and
subsequent urea production was from the same process —
conventional catalytic reforming of natural gas feedstock,
with the exception of one ammonia production plant located
in Kansas that is manufacturing ammonia from petroleum
coke feedstock; and the assumption that 100 percent of the
urea production and net imports are used as fertilizer or in
otherwise emissive uses. It is also assumed that ammonia
and urea are produced at collocated plants from the same
natural gas raw material.
Such recovery may or may not affect the overall estimate
of CO2 emissions depending upon the end use to which the
recovered CO2 is applied. Further research is required to
determine whether byproduct CO2 is being recovered from
other ammonia production plants for application to end uses
that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-14. Ammonia Manufacture
and Urea Application CO2 emissions were estimated to
be between 15.0 and 17.6 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 8
percent below and 8 percent above the emission estimate of
16.3TgCO2Eq.
Recalculation:; Discussion
Estimates of CO2 emissions from ammonia manufacture
and urea application for the years 2002 and 2003 were revised
to reflect updated data from the U.S. Census Bureau Current
Industrial Report. These changes resulted in a decrease in
CO2 emissions from urea manufacture of 0.7 Tg CO2 Eq.
(10 percent) for 2002 and an increase of 0.9 Tg CO2 Eq. (13
percent) for 2003.
Planned Improvements
Plans for improvements to the ammonia-manufacture and
urea-application source category include updating emission
factors to include both fuel and feedstock CO2 emissions,
incorporating CO2 capture and storage, and attributing urea
application to the Agriculture sector. Methodologies will
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ammonia Manufacture and Urea
Application (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg CQ2 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Ammonia Manufacture
and Urea Application C02
16.3
15.0
17.6
+8%
> Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-12 Inventory of U.S. Greenhouse Gas i£missions and Sinks: I'J
-------
also be updated if additional ammonia-production plants
are found to use hydrocarbons other than natural gas for
ammonia production.
4,4, Lime Manufacture (IPCC
Source Category 2A2)
Lime is an important manufactured product with many
industrial, chemical, and environmental applications. Its
major uses are in steel making, flue gas desulfurization
(FGD) systems at coal-fired electric power plants,
construction, and water purification. Lime has historically
ranked fifth in total production of all chemicals in the
United States. For U.S. operations, the term "lime" actually
refers to a variety of chemical compounds. These include
calcium oxide (CaO), or high-calcium quicklime; calcium
hydroxide (Ca(OH)2), or hydrated lime; dolomitic quicklime
([CaOMgOD; and dolomitic hydrate ([Ca(OH)2-MgOl or
[Ca(OH)2»Mg(OH)2]).
Lime production involves three main processes: stone
preparation, calcination, and hydration. CO2 is generated
during the calcination stage, when limestone —mostly
calcium carbonate (CaCO3) —is roasted at high temperatures
in a kiln to produce CaO and CO2. The CO2 is given off as
a gas and is normally emitted to the atmosphere. Some of
the CO2 generated during the production process, however,
is recovered at some facilities for use in sugar refining and
precipitated calcium carbonate (PCC)2 production. It is also
important to note that, for certain applications, lime reabsorbs
CO2 during use (see Uncertainty, below).
Lime production in the United States —including
Puerto Rico—was reported to be 19,984 thousand metric
tons in 2005 (USGS 2006). This resulted in estimated CO2
emissions of 13.7 Tg CO2 Eq. (or 13,660 Gg) (see Table
4-15 and Table 4-16).
The contemporary lime market is distributed across five
end-use categories as follows: metallurgical uses, 36 percent;
environmental uses, 28 percent; chemical and industrial uses,
21 percent; construction uses, 14 percent; and refractory
dolomite, 1 percent. In the construction sector, hydrated
lime is still used to improve durability in plaster, stucco,
and mortars. In 2005, the amount of hydrated lime used for
Table 4-15: Net C02 Emissions from Lime Manufacture
(Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
11.3
12.8
13.3
12.9
12.3
13.0
13.7
13.7
Table 4-16: C02 Emissions from Lime Manufacture (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Potential
11,766
13,741
14,577
13,978
13,381
14,171
14,853
14,831
Recovered*
(493)
(896)
(1,233)
(1,118)
(1,051)
(1,149)
(1,125)
(1,171)
Net Emissions
11,273
12,844
13,344
12,861
12,330
13,022
13,728
13,660
* For sugar refining and precipitated calcium carbonate production.
Note: Totals may not sum due to independent rounding. Parentheses
indicate negative values.
traditional building increased slightly from 2004 levels to
493 metric tons (USGS 2006).
Lime production in 2005 slightly increased over 2004,
the third annual increase in production after four years of
decline. Overall, from 1990 to 2005, lime production has
increased by 26 percent. The increase in production is
attributed in part to growth in demand for environmental
applications, especially flue gas desulfurization technologies.
In 1993, EPA completed regulations under the Clean Air Act
capping sulfur dioxide (SO2) emissions from electric utilities.
Lime scrubbers' high efficiencies and increasing affordability
have allowed the flue gas desulfurization end-use to expand
significantly over the years. Phase II of the Clean Air Act
Amendments, which went into effect on January 1, 2000,
remains the driving force behind the growth in the flue gas
desulfurization market (USGS 2003).
' Precipitated calcium carbonate is a specialty filler used in premium-quality coated and uncoated papers.
industrial Processes 4-13
-------
Methodology
During the calcination stage of lime manufacture, COT
is given off as a gas and normally exits the system with
the stack gas. To calculate emissions, the amounts of high-
calcium and dolomitic lime produced were multiplied by
their respective emission factors. The emission factor is the
product of a constant reflecting the mass of CO2 released per
unit of lime and the average calcium plus magnesium oxide
(CaO + MgO) content for lime (95 percent for both types of
lime). The emission factors were calculated as follows:
For high-calcium lime:
For dolomitic lime:
Production was adjusted to remove the mass of
chemically combined water found in hydrated lime,
determined according to the molecular weight ratios of H2O
to Ca(OH)2 and [Ca(OH)2»Mg(OH)2] (IPCC 2000). These
factors set the chemically combined water content to 24.3
percent for high-calcium hydrated lime, and 27.3 percent for
dolomitic hydrated lime.
Lime production in the United States was 19,984
thousand metric tons in 2005 (USGS 2006), resulting in
potential CO2 emissions of 14.8 Tg CO2 Eq. Some of the
CO2 generated during the production process, however, was
recovered for use in sugar refining and PCC production.
Combined lime manufacture by these producers was
1,964 thousand metric tons in 2005. It was assumed that
approximately 80 percent of the CO2 involved in sugar
refining and PCC was recovered, resulting in actual CO2
emissions of 13.7 Tg CO2 Eq.
Lime production data (high-calcium- and dolomitic-
quicklime, high-calcium- and dolomitic-hydrated, and dead-
burned dolomite) for 1990 through 2005 (see Table 4-17)
were obtained from USGS (1992 through 2005). Natural
hydraulic lime, which is produced from CaO and hydraulic
calcium silicates, is not produced in the United States (USGS
2005). Total lime production was adjusted to account for the
water content of hydrated lime and is presented with lime
consumption by sugar refining and PCC production in Table
4-18 (USGS 1992 through 2005). The CaO and CaO'MgO
contents of lime were obtained from the IPCC Good Practice
Guidance (IPCC 2000). Since data for the individual lime
types I'high calcium and dolomitic) was not provided prior
to 1997, total lime production for 1990 through 1996 was
calculated according to the three year distribution from
1997 to 1999. For sugar refining and PCC, it was assumed
that 100 percent of lime manufacture and consumption was
Table 4-18: Adjusted Lime Production and Lime Use for
Sugar Refining and PCC (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
High-Calcium
12,514
14,700
15,473
15,137
14,536
15,520
15,820
15,781
Dolomitic
2,809
3,207
3,506
3,105
2,934
2,998
3,526
3,535
Use for Sugar
Refining and PCC
826
1,503
2,067
1,874
1,762
1,926
1,887
1,964
Table 4-17: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and
Dead-Burned-Dolomite Lime Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
High-Calcium
Quicklime
11,166
13,165
14,300
13,600
13,400
13,900
14,200
14,100
Dolomitic Quicklime
2,234
2,635
3,000
2,580
2,420
2,460
3,020
2,990
High-Calcium
Hydrated
1,781
2,027
1,550
2,030
1,500
2,140
2,140
2,220
Dolomitic Hydrated
319
363
421
447
431
464
421
474
Dead-Burned
Dolomite
342
308
200
200
200
200
200
200
4 inventorv of U.S Greenhouse
;:mis:-foris 3r>o: !>mi
-------
high-calcium, based on communication with the National
Lime Association (Males 2003).
Uncertainty
The uncertainties contained in these estimates can be
attributed to slight differences in the chemical composition
of these products. Although the methodology accounts for
various formulations of lime, it does not account for the
trace impurities found in lime, such as iron oxide, alumina,
and silica. Due to differences in the limestone used as a raw
material, a rigid specification of lime material is impossible.
As a result, few plants manufacture lime with exactly the
same properties.
In addition, a portion of the CO2 emitted during lime
manufacture will actually be reabsorbed when the lime is
consumed. As noted above, lime has many different chemical,
industrial, environmental, and construction applications. In
many processes, COi reacts with the lime to create calcium
carbonate (e.g., water softening). CO2 reabsorption rates
vary, however, depending on the application. For example,
100 percent of the lime used to produce precipitated calcium
carbonate reacts with CO2; whereas most of the lime used
in steel making reacts with impurities such as silica, sulfur,
and aluminum compounds. A detailed accounting of lime use
in the United States and further research into the associated
processes are required to quantify the amount of CO2 that
is reabsorbed.3
In some cases, lime is generated from calcium carbonate
by-products at pulp mills and water treatment plants.4 The
lime generated by these processes is not included in the
USGS data for commercial lime consumption. In the pulping
industry, mostly using the Kraft (sulfate) pulping process,
lime is consumed in order to causticize a process liquor
(green liquor) composed of sodium carbonate and sodium
sulfide. The green liquor results from the dilution of the smelt
created by combustion of the black liquor where biogenic
C is present from the wood. Kraft mills recover the calcium
carbonate "mud" after the causticizing operation and calcine
it back into lime—thereby generating CO2 —for reuse in the
pulping process. Although this re-generation of lime could be
considered a lime manufacturing process, the CO2 emitted
during this process is mostly biogenic in origin, and therefore
is not included in Inventory totals.5
In the case of water treatment plants, lime is used in the
softening process. Some large water treatment plants may
recover their waste calcium carbonate and calcine it into
quicklime for reuse in the softening process. Further research
is necessary to determine the degree to which lime recycling
is practiced by water treatment plants in the United States.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-19. Lime CO2 emissions
were estimated to be between 12.6 and 14.8 Tg CO2 Eq.
at the 95 percent confidence level. This indicates a range
of approximately 8 percent below and 8 percent above the
emission estimate of 13.7 Tg CO2 Eq.
Recalculations Discussion
Corrections were made to the chemically combined
water content percentages of high-calcium hydrated lime and
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lime Manufacture
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lime Manufacture
CO,
13.7
12.6
14.8
+8%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
3 Representatives of the National Lime Association estimate that C02 reabsorption that occurs from the use of lime may offset as much as a quarter of
the CO2 emissions from calcination (Males 2003).
4 Some carbide producers may also regenerate lime from their calcium hydroxide by-products, which does not result in emissions of CO2. In making
calcium carbide, quicklime is mixed with coke and heated in electric furnaces. The regeneration of lime in this process is done using a waste calcium
hydroxide (hydrated lime) [CaC2 + 2H2O -> C2H2 + Ca(OH)2|, not calcium carbonate [CaCO,]. Thus, the calcium hydroxide is heated in the kiln to
simply expel the water [Ca(OH)2 + heat -> CaO + H2O] and no CO2 is released.
* Based on comments submitted by and personal communication with Dr. Sergio F. Galeano. Georgia-Pacific Corporation.
Industrial Processes 4-15
-------
dolomitic hydrated lime. This change resulted in a 0.2 percent glass manufacture, and environmental pollution control.
increase in emissions on average throughout the time series. Limestone is widely distributed throughout the world
Estimates of CO2 from lime manufacture for the year 2004 in deposits of varying sizes and degrees of purity. Large
were revised to reflect updated data from the USGS. These depos its of limestone occur in nearly every state in the United
changes resulted in a decrease in CO2 emissions from lime States, and significant quantities are extracted for industrial
manufacture of less than one percent for 2004. applications. For some of these applications, limestone is
sufficiently heated during the process and generates CO2
Planned Improvements as a by-product. Examples of such applications include
Future inventories are anticipated to include emissions limestone used as a flux or purifier in metallurgical furnaces,
associated with lime kiln dust (LKD) in the lime emission as a sorbent in flue gas desulfurization systems for utility and
estimates. Research will be conducted to determine the industrial plants, or as a raw material in glass manufacturing
availability of LKD data in the United States for inclusion and magnesium production.
in the emission estimates. In 2Q05, approximately 12,522 thousand metric tons of
limestone and 3,953 thousand metric tons of dolomite were
4.5. LilTieStOne and DOiOnnite USe consumedduringproductionfortheseapplications.Overall,
(IPCC SOUrCe CBtenOCV 2A3) usage of limestone and dolomite resulted in aggregate CO2
emissions of 7.4Tg CO2Eq. (7,397 Gg) (see Table 4-20 and
Limestone (CaCO3) and dolomite (CaCO3MgCO3)6 Table 4-21). Emissions in 2005 increased 10 percent from
are basic raw materials used by a wide variety of industries, the previous year and have increased 34 percent overall from
including construction, agriculture, chemical, metallurgy, 1990 through 2005.
Table 4-20: C02 Emissions from Limestone & Dolomite Use (Tg C02 Eq.)
Activity
Flux Stone
Glass Making
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990
3.0
0.2
1.4
0.1
0.8
5.5
1995
4.0
0.5
1.7
0.0
1.1
7.4
2000
2.8
0.4
1.8
0.1
0.9
6.0
2001
2.5
0.1
2.6
0.1
0.5
5.7
2002
2.4
0.1
2.8
0.0
0.7
5.9
2003
2.1
0.3
1.9
0.0
0.4
4.7
2004
4.1
0.4
1.9
0.0
0.4
6.7
2005
3.3
0.4
3.0
0.0
0.7
7.4
Notes: Totals may not sum due to independent rounding. Other miscellaneous uses include chemical stone, mine dusting or acid water treatment, acid
neutralization, and sugar refining.
Table 4-21: C02 Emissions from Limestone & Dolomite Use (Gg)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990
2,999
2,554
446
217
189
28
1,433
64
819
5,533
1995
4,004
3,077
927
533
410
122
1,663
41
1,119
7,359
2000
2,830
1,810
1,020
368
368
0
1,774
73
916
5,960
2001
2,514
1,640
874
113
113
0
2,551
53
501
5,733
2002
2,405
1,330
1,075
61
61
0
2,766
0
652
5,885
2003
2,072
904
1,168
337
337
0
1,932
0
380
4,720
2004
4,112
2,023
2,088
350
350
0
1,871
0
369
6,702
2005
3,265
1,398
1,867
427
406
21
2,985
0
721
7,397
Notes: Totals may not sum due to independent rounding. Other miscellaneous uses include chemical stone, mine dusting or acid water treatment, acid
neutralization, and sugar refining.
' Limestone and dolomite are collectively referred to as limestone by the industry, and intermediate varieties are seldom distinguished.
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19!IQ-20Q5
-------
Methodology
CO2 emissions were calculated by multiplying the
quantity of limestone or dolomite consumed by the average
C content, approximately 12.0 percent for limestone and
13.2 percent for dolomite (based on stoichiometry). This
assumes that all C is oxidized and released. This methodology
was used for flux stone, glass manufacturing, flue gas
desulfurization systems, chemical stone, mine dusting or acid
water treatment, acid neutralization, and sugar refining and
then converting to CO2 using a molecular weight ratio.
Traditionally, the production of magnesium metal
was the only other use of limestone and dolomite that
produced CO2 emissions. At the start of 2001, there were
two magnesium production plants operating in the United
States and they used different production methods. One plant
produced magnesium metal using a dolomitic process that
resulted in the release of CO2 emissions, while the other
plant produced magnesium from magnesium chloride using
a CO7-emissions-free process called electrolytic reduction.
However, the plant utilizing the dolomitic process ceased its
operations prior to the end of 2001, so beginning in 2002
there were no emissions from this particular sub-use.
Consumption data for 1990 through 2005 of limestone
and dolomite used for flux stone, glass manufacturing, flue
gas desulfurization systems, chemical stone, mine dusting or
acid water treatment, acid neutralization, and sugar refining
(see Table 4-22) were obtained from personal communication
with Deborah Weaver of the USGS (Weaver 2006) and in
the USGS Minerals Yearbook: Crushed Stone Annual Report
(USGS 1993,1995a, 1995b,1996a, 1997a, 1998a, 1999a,
2000a, 2001a, 2002a, 2003a, 2004a, 2005a). The production
capacity data for 1990 through 2005 of dolomitic magnesium
metal (see Table 4-23) also came from the USGS (1995c,
1996b,1997b,1998b,1999b,2000b,2001b,2002b,2003b,
2004b, 2005b, 2006). The last plant in the United States that
used the dolomitic production process for magnesium metal
closed in 2001. The USGS does not mention this process
in the 2005 Minerals Yearbook: Magnesium', therefore, it
is assumed that this process continues to be non-existent in
the United States (USGS 2006). During 1990 and 1992, the
USGS did not conduct a detailed survey of limestone and
dolomite consumption by end-use. Consumption for 1990
was estimated by applying the 1991 percentages of total
limestone and dolomite use constituted by the individual
limestone and dolomite uses to 1990 total use. Similarly, the
1992 consumption figures were approximated by applying an
average of the 1991 and 1993 percentages of total limestone
and dolomite use constituted by the individual limestone and
dolomite uses to the 1992 total.
Additionally, each year the USGS withholds data
on certain limestone and dolomite end-uses due to
Table 4-23: Dolomitic Magnesium Metal Production
Capacity (Metric Tons)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Production Capacity
35,000
22,222
40,000
29,167
0
0
0
0
Note: Production capacity for 2002,2003,2004, and 2005 amounts to zero
because the last U.S. production plant employing the dolomitic process
shut down mid-2001 (USGS 2002b, 2003b, 2004b, 2005b, 2006).
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Other Miscellaneous Uses
Total
1990
6,738
5,804
933
489
430
59
3,258
1,835
12,319
1995
8,935
6,995
1,941
1,189
933
256
3,779
2,543
16,445
2000
6,249
4,114
2,135
836
836
0
4,031
2,081
13,197
2001
5,558
3,727
1,831
258
258
0
5,798
1,138
12,751
2002
5,275
3,023
2,252
139
139
0
6,286
1,483
13,183
2003
4,501
2,055
2,466
765
765
0
4,390
863
10,520
2004
8,971
4,599
4,373
796
796
0
4,253
840
14,859
2005
7,086
3,176
3,910
966
923
43
6,785
1,638
16,475
Notes: Other miscellaneous uses includes chemical stone, mine dusting or acid water treatment, acid neutralization, and sugar refining. Zero values for limestone
and dolomite consumption for glass making result during years when the USGS reports that no limestone or dolomite are consumed for this use.
industrial Processes 4-17
-------
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Limestone and Dolomite Use
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Limestone and Dolomite
Use C02
7.4
6.9
7.9
-6%
+ 6%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
confidentiality agreements regarding company proprietary
data. For the purposes of this analysis, emissive end-uses
that contained withheld data were estimated using one of
the following techniques: (1) the value for all the withheld
data points for limestone or dolomite use was distributed
evenly to all withheld end-uses; (2) the average percent of
total limestone or dolomite for the withheld end-use in the
preceding and succeeding years; or (3) the average fraction
of total limestone or dolomite for the end-use over the entire
time period.
Finally, there is a large quantity of crushed stone
reported to the USGS under the category "unspecified uses."
A portion of this consumption is believed to be limestone
or dolomite used for emissive end uses. The quantity listed
for "unspecified uses" was, therefore, allocated to each
reported end-use according to each end uses fraction of total
consumption in that year.7
Uncertainty
The uncertainty levels presented in this section arise
in part due to variations in the chemical composition of
limestone. In addition to calcium carbonate, limestone may
contain smaller amounts of magnesia, silica, and sulfur. The
exact specifications for limestone or dolomite used as flux
stone vary with the pyrometallurgical process, the kind of
ore processed, and the final use of the slag. Similarly, the
quality of the limestone used for glass manufacturing will
depend on the type of glass being manufactured.
The estimates below also account for uncertainty
associated with activity data. Much of the limestone consumed
in the United States is reported as "other unspecified uses;"
therefore, it is difficult to accurately allocate this unspecified
quantity to the correct end-uses. Also, some of the limestone
reported as "limestone" is believed to actually be dolomite,
which has a higher C content. Additionally, there is significant
inherent uncertainty associated with estimating withheld data
points for specific end uses of limestone and dolomite. Lastly,
the uncertainty of the estimates for limestone used in glass
making is especially high. Large fluctuations in reported
consumption exist, reflecting year-to-year changes in the
number of survey responders. The uncertainty resulting from
a shifting survey population is exacerbated by the gaps in the
time series of reports. However, since glass making accounts
for a small percent of consumption, its contribution to the
overall emissions estimate is low.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-24. Limestone and Dolomite Use
CO2 emissions were estimated to be between 6.9 and 7.9 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 6 percent below and 6 percent above
the emission estimate of 7.4 Tg CO2 Eq.
Planned Impnvements
Future improvements to the limestone and dolomite
source category involve research into the availability of
limestone and dolomite end-use data. If sufficient data are
available, limestone and dolomite used as process materials
in source categories to be included in future inventories (e.g.,
glass production, other process use of carbonates) may be
removed and the emission estimates included there.
4.5 Soda Ash Manufacture
and Consumption (IPCC Source
Category 2A4)
Soda ash (sodium carbonate, Na2CO3) is a white
crystalline solid that is readily soluble in water and strongly
alkaline. Commercial soda ash is used as a raw material
in a variety of industrial processes and in many familiar
7 This approach was recommended by USGS.
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
consumer products such as glass, soap and detergents,
paper, textiles, and food. It is used primarily as an alkali,
either in glass manufacturing or simply as a material that
reacts with and neutralizes acids or acidic substances.
Internationally, two types of soda ash are produced—-natural
and synthetic. The United States produces only natural
soda ash and is second only to China in total soda ash-
production. Trona is the principal ore from which natural
soda ash is made.
Only three states produce natural soda ash: Wyoming,
California, and Colorado. Of these three states, only net
emissions of CO2 from Wyoming were calculated due to
specifics regarding the production processes employed in
each state.8 During the production process used in Wyoming,
trona ore is treated to produce soda ash. CO2 is generated as
a by-product of this reaction, and is eventually emitted into
the atmosphere. In addition, CO2 may also be released when
soda ash is consumed.
In 2005, CO2 emissions from the manufacture of soda
ash from trona were approximately 1.7 Tg CO2 Eq. (1,655
Gg). Soda ash consumption in the United States generated 2.6
Tg CO2 Eq. (2,573 Gg) in 2005. Total emissions from soda
ash manufacture and consumption in 2005 were 4.2 Tg CO2
Eq. (4,228 Gg) (see Table 4-25 and Table 4-26). Emissions
have fluctuated since 1990. These fluctuations were strongly
related to the behavior of the export market and the U.S.
Table 4-25: C02 Emissions from Soda Ash Manufacture
and Consumption (Tg C02 Eq.)
Table 4-26: C02 Emissions from Soda Ash Manufacture
and Consumption (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Manufacture
1,431
1,607
1,529
1,500
1,470
1,509
1,607
1,655
Consumption
2,710
2,698
2,652
2,648
2,668
2,602
2,598
2,573
Total
4,141
4,304
4,181
4,147
4,139
4,111
4,205
4,228
Note: Totals may not sum due to independent rounding.
economy. Emissions in 2005 increased by approximately 0.5
percent from the previous year, and have increased overall
by approximately 2 percent since 1990.
The United States represents about one-fourth of total
world soda ash output. The approximate distribution of
soda ash by end-use in 2005 was glass making, 49 percent;
chemical production, 27 percent; soap and detergent
manufacturing, 10 percent; distributors, 5 percent; flue gas
desulfurization, 2 percent; water treatment, 1 percent; pulp
and paper production, 1 percent; and miscellaneous, 4 percent
(USGS 2006).
Although the United States continues to be a major
supplier of world soda ash, China, which surpassed the
United States in soda ash production in 2003, is the world's
leading producer. While Chinese soda ash production
appears to be stabilizing, U.S. competition in Asian markets
is expected to continue. Despite this competition, U.S. soda
ash production is expected to increase by about 0.5 percent
annually over the next five years. (USGS 2006).
During the production process, trona ore is calcined in
a rotary kiln and chemically transformed into a crude soda
ash that requires further processing. CO2 and water are
generated as by-products of the calcination process. CO2
8 In California, soda ash is manufactured using sodium carbonate-bearing brines instead of trona ore. To extract the sodium carbonate, the complex
brines are first treated with CO: in carbonation towers to convert the sodium carbonate into sodium bicarbonate, which then precipitates from the brine
solution. The precipitated sodium bicarbonate is then calcined back into sodium carbonate. Although CO: is generated as a by-product, the CO2 is
recovered and recycled for use in the carbonation stage and is not emitted.
In Colorado, the lone producer of sodium bicarbonate no longer mines trona in the state. Instead, NaHCO, is produced using soda ash feedstocks mined
in Wyoming and shipped to Colorado. Because the trona is mined in Wyoming, the production numbers given by the USGS include the feedstocks
mined in Wyoming and shipped to Colorado. In this way, the sodium bicarbonate production that takes place in Colorado is accounted for in the
Wyoming numbers.
Year
1990
1995
2000
2001
2002
2003
2004
2005
Note: Totals
Manufacture
1.4
1.6
1.5
1.5
1.5
1.5
1.6
1.7
Consumption
2.7
2.7
2.7
2.6
2.7
2.6
2.6
2.6
Total
4.1
4.3
4.2
4.1
4.1
4.1
4.2
4.2
may not sum due to independent rounding.
-------
emissions from the calcination of trona can be estimated
based on the following chemical reaction:
2(\ihliiCO ... ^|-|,o -> .^\;t,CO; ~:-iU)- CO
ItmiKi | | soda ash j
Based on this formula, approximately 10.27 metric tons
of trona are required to generate one metric ton of CO2. Thus,
the 17 million metric tons of trona mined in 2005 for soda
ash production (USGS 2006) resulted in CO2 emissions of
approximately 1.7 Tg CO2 Eq. (1,655 Gg).
Once manufactured, most soda ash is consumed in
glass and chemical production, with minor amounts in soap
and detergents, pulp and paper, flue gas desulfurization and
water treatment. As soda ash is consumed for these purposes,
additional CO2 is usually emitted. In these applications, it
is assumed that one mole of C is released for every mole of
soda ash used. Thus, approximately 0.113 metric tons of C
(or 0.415 metric tons of CO2) are released for every metric
ton of soda ash consumed.
The activity data for trona production and soda ash
consumption (see Table 4-27) were taken from USGS (1994
through 2006). Soda ash manufacture and consumption data
were collected by the USGS from voluntary surveys of the
U.S. soda ash industry.
Table 4-27: Soda Ash Manufacture and Consumption (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Manufacture*
14,700
16,500
15,700
15,400
15,100
15,500
16,500
17,000
Consumption
6,530
6,500
6,390
6,380
6,430
6,270
6,260
6,200
* Soda ash manufactured from trona ore only.
Uncertainty
Emission estimates from soda ash manufacture
have relatively low associated uncertainty levels in that
reliable and accurate data sources are available for the
emission factor and activity data. The primary source of
uncertainty, however, results from the fact that emissions
from soda ash consumption are dependent upon the type of
processing employed by each end-use. Specific information
characterizing the emissions from each end-use is limited.
Therefore, there is uncertainty surrounding the emission
factors from the consumption of soda ash.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-28. Soda Ash Manufacture and
Consumption CO2 emissions were estimated to be between
3.9 and 4.5 Tg CO2 Eq. at the 95 percent confidence level.
This indicates a range of approximately 7 percent below and
7 percent above the emission estimate of 4.2 Tg CO2 Eq.
Planned Improvements
Future inventories are anticipated to estimate emissions
from glass production and other use of carbonates. These
inventories will extract soda ash consumed for glass
production and other use of carbonates from the current
soda ash consumption emission estimates and include them
under those sources.
4,7, Titanium Dioxide Production
(IPCC Source Category 2B5)
Titanium dioxide (TiO2) is a metal oxide manufactured
from titanium ore, and is principally used as a pigment.
Titanium dioxide is a principal ingredient in white paint,
and is also used as a pigment in the manufacture of white
paper, foods, and other products. There are two processes for
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Soda Ash Manufacture and
Consumption (Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) {%)
Lower Bound Upper Bound Lower Bound Upper Bound
Soda Ash Manufacture
and Consumption
CO,
4.2
3.9
4.5
+7%
s Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-20 inventory of U.S. Greenhouse Gas Emissions arid Sinks: 1990-2005
-------
Table 4-29: C02 Emissions from Titanium Dioxide
Production (Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
1.3
1.7
1.9
1.9
2.0
2.0
2.3
1.9
Gg
1,308
1,670
1,918
1,857
1,997
2,013
2,259
1,921
making TiO2: the chloride process and the sulfate process.
The chloride process uses petroleum coke and chlorine as
raw materials and emits process-related CO2. The sulfate
process does not use petroleum coke or other forms of C as
a raw material and does not emit CO2.
The chloride process is based on the following chemical
reactions:
The C in the first chemical reaction is provided by
petroleum coke, which is oxidized in the presence of the
chlorine and FeTiO, (the Ti-containing ore) to form CO2.
The majority of U.S. TiO2 was produced in the United States
through the chloride process, and a special grade of petroleum
coke is manufactured specifically for this purpose
Emissions of CO2 in 2005 were 1.9 Tg CO2 Eq. (1,921
Gg), a decrease of 18 percent from the previous year and an
increase of 47 percent since 1990. The trend upward, due
to increasing production within the industry, was disrupted
in 2005 as a result of Hurricane Katrina (see Table 4-29),
which disrupted production of TiO2 pigment in Mississippi
(USGS 2006).
Methodology
Emissions of CO2 from TiO2 production were calculated
by multiplying annual TiO2 production by chloride-process-
specific emission factors.
Data were obtained for the total amount of TiO2 produced
each year. For years previous to 2004, it was assumed that
TiO2 was produced using the chloride process and the
sulfate process in the same ratio as the ratio of the total U.S.
production capacity for each process. As of 2004, the last
remaining sulfate-process plant in the United States had closed.
As a result, all U.S. current TiO2 production results from the
chloride process (USGS 2005). An emission factor of 0.4
metric tons C/metric ton TiO2 was applied to the estimated
chloride-process production. It was assumed that all TiO2
produced using the chloride process was produced using
petroleum coke, although some TiO2 may have been produced
with graphite or other C inputs. The amount of petroleum coke
consumed annually in TiO2 production was calculated based
on the assumption that petroleum coke used in the process is
90 percent C and 10 percent inert materials.
The emission factor for the TiO2 chloride process was
taken from the report, Everything You 've Always Wanted to
Know about Petroleum Coke (Onder and Bagdoyan 1993).
Titanium dioxide production data and the percentage of
total TiO2 production capacity that is chloride process for
1990 through 2005 (see Table 4-30) were obtained from
a personal communication with Deborah Kramer, USGS
Commodity Specialist, of the USGS (Kramer 2006) and
through the Minerals Yearbook: Titanium Annual Report
(USGS 1991 through 2005). Percentage chloride-process
data were not available for 1990 through 1993, and data from
the 1994 USGS Minerals Yearbook were used for these years.
Because a sulfate-process plant closed in September 2001,
the chloride-process percentage for 2001 was estimated based
on a discussion with Joseph Gambogi (2002). By 2002, only
one sulfate plant remained online in the United States and
this plant closed in 2004 (USGS 2005). The composition
data for petroleum coke were obtained from Onder and
Bagdoyan (1993).
Table 4-30: Titanium Dioxide Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
979
1,250
1,400
1,330
1,410
1,420
1,540
1,310
Industrial Processes 4-21
-------
Uncertainty
Although some TiO2 may be produced using graphite or
other C inputs, information and data regarding these practices
were not available. Titanium dioxide produced using graphite
inputs, for example, may generate differing amounts of CO2
per unit of TiO2 produced as compared to that generated
through the use of petroleum coke in production. While the
most accurate method to estimate emissions would be to
base calculations on the amount of reducing agent used in
each process rather than on the amount of TiO2 produced,
sufficient data were not available to do so.
Also, annual TiO2 is not reported by USGS by the
type of production process used (chloride or sulfate). Only
the percentage of total production capacity by process is
reported. The percent of total TiO2 production capacity that
was attributed to the chloride process was multiplied by total
TiO2 production to estimate the amount of TiO2 produced
using the chloride process (since, as of 2004, the last
remaining sulfate-process plant in the United States closed).
This assumes that the chloride-process plants and sulfate-
process plants operate at the same level of utilization. Finally,
the emission factor was applied uniformly to all chloride-
process production, and no data were available to account
for differences in production efficiency among chloride-
process plants. In calculating the amount of petroleum coke
consumed in chloride-process TiO2 production, literature
data were used for petroleum coke composition. Certain
grades of petroleum coke are manufactured specifically for
use in the TiO2 chloride process; however, this composition
information was not available.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-31. Titanium dioxide production
CO2 emissions were estimated to be between 1.6 and 2.2 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 16 percent below and 16 percent
above the emission estimate of 1.9 Tg CO2 Eq.
Planned !merc'vements
Future improvements to TiO2 production methodology
include researching the significance of titanium-slag
production in electric furnaces and synthetic-rutile
production using the Becher process in the United States.
Significant use of these production processes will be included
in future estimates.
1.8. Ferroallo Production SPCC
Source Category 2C2)
CO2 and CH4 are emitted from the production of several
ferroalloys. Ferroalloys are composites of iron and other
elements such as silicon, manganese, and chromium. When
incorporated in alloy steels, ferroalloys are used to alter the
material properties of the steel. Estimates from two types of
ferrosilicon (25 to 55 percent and 56 to 95 percent silicon),
silicon metal (about 98 percent silicon), and miscellaneous
alloys (36 to 65 percent silicon) have been calculated.
Emissions from the production of ferrochromium and
ferromanganese are not included here because of the small
number of manufacturers of these materials in the United
States Subsequently, government information disclosure
rules prevent the publication of production data for these
production facilities.
Similar to emissions from the production of iron and
steel, CO2 is emitted when metallurgical coke is oxidized
during a high-temperature reaction with iron and the selected
alloying element. Due to the strong reducing environment,
CO is initially produced, and eventually oxidized to CO2.
A representative reaction equation for the production of 50
percent ferrosilicon is given below:
While most of the C contained in the process materials
is released to the atmosphere as CO2, a percentage is also
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Titanium Dioxide Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Titanium Dioxide
Production
CO,
1.9
1.6
2.2
-16%
+16%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
-------
Table 4-32: C02 and CH4 Emissions from Ferroalloy Production (Tg C02 Eq.)
Year
C02
CH4
Total
1990
2.2
+
2.2
1995
2.0
+
2.0
2000
1.9
+
1.9
2001
1.5
+
1.5
2002
1.3
+
1.4
2003
1.3
+
1.3
2004
1.4
+
1.4
2005
1.4
+
1.4
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq.
Table 4-33: C02 and CH4 Emissions from Ferroalloy Production (Gg)
Year
C02
CH4
1990
2,152
0.7
1995
2,036
0.6
2000
1,893
0.5
2001
1,459
0.4
2002
1,349
0.4
2003
1,305
0.4
2004
1,419
0.4
2005
1,392
0.4
released as CH4 and other volatiles. The amount of CH4 that
is released is dependent on furnace efficiency, operation
technique, and control technology.
Emissions of CO2 from ferroalloy production in 2005
were 1.4 Tg CO2 Eq. (1,392 Gg) (see Table 4-32 and Table
4-33), which is a 2 percent decrease from the previous year
and a 35 percent reduction since 1990. Emissions of CH4
from ferroalloy production in 2005 were 0.01 Tg CO2 Eq.
(0.4 Gg), which is a 1 percent decrease from the previous
year and a 43 percent decrease since 1990.
Emissions of CO2 and CH4 from ferroalloy production
were calculated by multiplying annual ferroalloy production
by material-specific emission factors. Emission factors taken
from the 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006) were applied to ferroalloy production.
For ferrosilicon alloys containing 25 to 55 percent silicon
and miscellaneous alloys (including primarily magnesium-
ferrosilicon, but also including other silicon alloys) containing
Table 4-34: Production of Ferroalloys (Metric Tons)
32 to 65 percent silicon, an emission factor for 45 percent
silicon was applied for CO2 (2.5 metric tons CO2/metric ton of
alloy produced) and an emission factor for 65 percent silicon
was applied for CH4 (1 kg CO2/metric ton of alloy produced).
Additionally, for ferrosilicon alloys containing 56 to 95 percent
silicon, an emission factor for 75 percent silicon ferrosilicon
was applied for both CO2 and CH4 (4 metric tons CO2/metric
ton alloy produced and 1 kg CH4/metric ton of alloy produced,
respectively). The emission factors for silicon metal equaled
5 tons COVmetric ton metal produced and 1.2 kg CH4/metric
ton metal produced. It was assumed that 100 percent of the
ferroalloy production was produced using petroleum coke
using an electric arc furnace process (IPCC 2006), although
some ferroalloys may have been produced with coking coal,
wood, other biomass, or graphite C inputs. The amount of
petroleum coke consumed in ferroalloy production was
calculated assuming that the petroleum coke used is 90 percent
C and 10 percent inert material.
Ferroalloy production data for 1990 through 2005 (see
Table 4-34) were obtained from the USGS through personal
Year
1990
1995
2000
2001
2002
2003
2004
2005
Ferrosilicon
25%-55%
321,385
184,000
229,000
167,000
156,000
115,000
120,000
123,000
Ferrosilicon
56%-95%
109,566
128,000
100,000
89,000
98,600
80,500
92,300
86,100
Silicon Metal
145,744
163,000
184,000
137,000
113,000
139,000
150,000
148,000
Misc. Alloys
32%-65%
72,442
99,500
NA
NA
NA
NA
NA
NA
NA (Not Available)
-------
communications with the USGS Silicon Commodity Specialist
(Corathers 2006) and through the Minerals Yearbook: Silicon
Annual Report (USGS 1991 through 2005). Until 1999, the
USGS reported production of ferrosilicon containing 25 to 55
percent silicon separately from production of miscellaneous
alloys containing 32 to 65 percent silicon; beginning in 1999,
the USGS reported these as a single category (see Table 4-34).
The composition data for petroleum coke was obtained from
Onder and Bagdoyan (1993).
Uncertainty
Although some ferroalloys may be produced using
wood or other biomass as a C source, information and data
regarding these practices were not available. Emissions from
ferroalloys produced with wood or other biomass would not
be counted under this source because wood-based C is of
biogenic origin.9 Even though emissions from ferroalloys
produced with coking coal or graphite inputs would be
counted in national trends, they may be generated with
varying amounts of CO2 per unit of ferroalloy produced.
The most accurate method for these estimates would be to
base calculations on the amount of reducing agent used in
the process, rather than the amount of ferroalloys produced.
These data, however, were not available.
Emissions of CH4 from ferroalloy production will vary
depending on furnace specifics, such as type, operation
technique, and control technology. Higher heating temperatures
and techniques such as sprinkle charging will reduce CH4
emissions; however, specific furnace information was not
available or included in the CH4 emission estimates.
Also, annual ferroalloy production is now reported by
the USGS in three broad categories: ferroalloys containing
25 to 55 percent silicon (including miscellaneous alloys),
ferroalloys containing 56 to 95 percent silicon, and silicon
metal. It was assumed that the IPCC emission factors apply
to all of the ferroalloy production processes, including
miscellaneous alloys. Finally, production data for silvery
pig iron (alloys containing less than 25 percent silicon) are
not reported by the USGS to avoid disclosing company
proprietary data. Emissions from this production category,
therefore, were not estimated.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-35. Ferroalloy production CO2
emissions were estimated to be between 1.2 and 1.6 Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
of approximately 13 percent below and 13 percent above the
emission estimate of 1.4 Tg CO2 Eq. Ferroalloy production
CH4 emissions were estimated to be between a range of
approximately 12 percent below and 12 percent above the
emission estimate of 0.01 Tg CO2 Eq.
Recalculations; Discussion
Estimates of CO2 emissions from ferroalloy production
were revised for the entire time series to reflect updated
emission factors based on the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC 2006). This
change resulted in a 9.5 percent (0.2 Tg CO2 Eq.) increase
in emissions on average throughout the timeseries.
Planned Improvements
Future improvements to the ferroalloy production
source category include research into the data availability for
ferroalloys other than ferrosilicon and silicon metal. If data are
available, emissions will be estimated for those ferroalloys.
Additionally, research will be conducted to determine whether
data ar2 available concerning raw material consumption (e.g.,
coal coke, limestone and dolomite flux, etc.) for inclusion in
ferroalloy production emission estimates.
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Ferroalloy Production
(Tg C02 Eq. and Percent)
Source Gas
Ferroalloy Production C02
Ferroalloy Production CH4
a Range of emission estimates predicted
+ Does not exceed 0.05 Tg C02 Eq.
2005 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
1.4 1.2
Upper Bound Lower Bound
1.6 -13%
+ -12%
Upper Bound
+ 13%
+ 12%
by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
9 Emissions and sinks of biogenic carbon are accounted for in the Land-Use. Land-Use Change, and Forestry chapter.
4-24 inventory ot U.S. Greenhouse Gas Emissions and Sink:*: 199i)-20Q5
-------
4.9. Phosphoric Acid Production
(IPCC Source Category 2B5)
Phosphoric acid (H3PO4) is a basic raw material in the
production of phosphate-based fertilizers. Phosphate rock
is mined in Florida, North Carolina, Idaho, Utah, and other
areas of the United States and is used primarily as a raw
material for phosphoric acid production. The production of
phosphoric acid from phosphate rock produces byproduct
gypsum (CaSO4*2H2O), referred to as phosphogypsum.
The composition of natural phosphate rock varies
depending upon the location where it is mined. Natural
phosphate rock mined in the United States generally contains
inorganic C in the form of calcium carbonate (limestone) and
also may contain organic C. The chemical composition of
phosphate rock (francolite) mined in Florida is:
The calcium carbonate component of the phosphate rock
is integral to the phosphate rock chemistry. Phosphate rock
can also contain organic C that is physically incorporated
into the mined rock but is not an integral component of the
phosphate rock chemistry. Phosphoric acid production from
natural phosphate rock is a source of CO2 emissions, due to
the chemical reaction of the inorganic C (calcium carbonate)
component of the phosphate rock.
The phosphoric acid production process involves
chemical reaction of the calcium phosphate (Ca3(PO4)2)
component of the phosphate rock with sulfuric acid (H2SO4)
and recirculatedphosphoric acid (H3PO4) (EF MA 1997). The
primary chemical reactions for the production of phosphoric
acid from phosphate rock are:
Table 4-36: C02 Emissions from Phosphoric Acid
Production (Tg C02 Eq. and Gg)
The limestone (CaCO3) component of the phosphate rock
reacts with the sulfuric acid in the phosphoric acid production
process to produce calcium sulfate (phosphogypsum) and
CO2. The chemical reaction for the limestone-sulfuric acid
reaction is:
'.:••• . . V j *. i I i J ! I •
Total marketable phosphate rock production in 2005
was 36.0 million metric tons. Approximately 87 percent of
domestic phosphate rock production was mined in Florida
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
1.5
1.5
1.4
1.3
1.3
1.4
1.4
1.4
Gg
1,529
1,513
1,382
1,264
1,338
1,382
1,395
1,383
and North Carolina, while approximately 13 percent of
production was mined in Idaho and Utah. In addition, 2.6
million metric tons of crude phosphate rock was imported for
consumption in 2005. Marketable phosphate rock production,
including domestic production and imports for consumption,
decreased by approximately 1.0 percent between 2004 and
2005. However, over the 1990 to 2005 period, production
decreased by 12 percent. The 35.3 million metric tons
produced in 2001 was the lowest production level recorded
since 1965 and was driven by a worldwide decrease in
demand for phosphate fertilizers. Total CO2 emissions from
phosphoric acid production were 1.4 Tg CO2 Eq. (1,383 Gg)
in 2005 (see Table 4-36).
Methodology
CO2 emissions from production of phosphoric acid from
phosphate rock is calculated by multiplying the average
amount of calcium carbonate contained in the natural
phosphate rock by the amount of phosphate rock that is used
annually to produce phosphoric acid, accounting for domestic
production and net imports for consumption.
From 1993 to 2004, the USGS Mineral Yearbook:
Phosphate Rock disaggregated phosphate rock mined
annually in Florida and North Carolina from phosphate
rock mined annually in Idaho and Utah, and reported the
annual amounts of phosphate rock exported and imported
for consumption (see Table 4-37). For the years 1990, 1991,
1992, and 2005, only nationally aggregated mining data
was reported by USGS. For these years, the breakdown of
phosphate rock mined in Florida and North Carolina, and
the amount mined in Idaho and Utah, are approximated
using 1993 to 2004 data. Data for domestic production of
phosphate rock, exports of phosphate rock, and imports of
Processes
-------
Table 4-37: Phosphate Rock Domestic Production, Exports, and Imports (Gg)
Location
U.S. Production3
FL&NC
ID&UT
Exports— FL & NC
Imports — Morocco
Total U.S. Consumption
1990
49,800
42,494
7,306
6,240
451
44,011
1995
43,720
38,100
5,620
2,760
1,800
42,760
2000
37,370
31,900
5,470
299
1,930
39,001
2001
32,830
28,100
4,730
9
2,500
35,321
2002
34,720
29,800
4,920
62
2,700
37,358
2003
36,410
31,300
5,110
64
2,400
38,746
2004
36,530
31,600
4,930
2,500
39,030
2005
36,000
31,140
4,860
2,630
38,630
a USGS does not disaggregate production data regionally (FL & NC and ID & UT) for 1990 and 2005. Data for those years are estimated based on the
remaining time series distribution.
- Assumed equal to zero.
phosphate rock for consumption for 1990 through 2005 were
obtained from USGS Minerals Yearbook: Phosphate Rock
(USGS 1994 through 2006). In 2004 and 2005, the USGS
reported no exports of phosphate rock from U.S. producers
(USGS 2005,2006).
The carbonate content of phosphate rock varies
depending upon where the material is mined. Composition
data for domestically mined and imported phosphate rock
were provided by the Florida Institute of Phosphate Research
(FIPR 2003). Phosphate rock mined in Florida contains
approximately 1 percent inorganic C, and phosphate rock
imported from Morocco contains approximately 1.46 percent
inorganic C. Calcined phosphate rock mined in North
Carolina and Idaho contains approximately 0.41 percent and
0.27 percent inorganic C, respectively (see Table 4-38).
Carbonate content data for phosphate rock mined
in Florida are used to calculate the CO2 emissions from
consumption of phosphate rock mined in Florida and North
Carolina (87 percent of domestic production) and carbonate
content data for phosphate rock mined in Morocco are used
to calculate CO2 emissions from consumption of imported
phosphate rock. The CO2 emissions calculation is based
on the assumption that all of the domestic production of
phosphate rock is used in uncalcined form. At last reporting,
the USGS noted that one phosphate rock producer in Idaho
produces calcined phosphate rock; however, no production
data were available for this single producer (USGS 2005).
Carbonate content data for uncalcined phosphate rock mined
in Idaho and Utah (13 percent of domestic production) were
not available, and carbonate content was therefore estimated
from the carbonate content data for calcined phosphate rock
mined in Idaho.
The CO2 emissions calculation methodology is based
on the assumption that all of the inorganic C (calcium
carbonate) content of the phosphate rock reacts to CO2 in
the phosphoric acid production process and is emitted with
the stack gas. The methodology also assumes that: none of
the organic C content of the phosphate rock is converted
to CO2 and that all of the organic C content remains in the
phosphoric acid product.
Phosphate rock production data used in the emission
calculations are developed by the USGS through monthly
and semiannual voluntary surveys of the active phosphate
rock mines during 2005. For previous years in the timeseries,
USGS provided the data disaggregated regionally; however,
for 2005 only total U.S. phosphate rock production was
reported. Regional production for 2005 was estimated based
on regional-production data from the previous year and
Table 4-38: Chemical Composition of Phosphate Rock (percent by weight)
Composition
Total Carbon (as C)
Inorganic Carbon (as C)
Organic Carbon (as C)
Inorganic Carbon (as C02)
Central Florida
1.60
1.00
0.60
3.67
North Florida
1.76
0.93
0.83
3.43
North Carolina
(calcined)
0.76
0.41
0.35
1.50
Idaho
(calcined)
0.60
0.27
1.00
Morocco
1.56
1.46
0.10
5.00
Source: FIPR (2003)
- Assumed equal to zero.
-------
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Phosphoric Acid Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Phosphoric Acid
Production
CO,
1.4
1.1
1.6
-19%
+19%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation tor a 95 percent confidence interval.
multiplied by regionally-specific emission factors. There is
uncertainty associated with the degree to which the estimated
2005 regional-production data represents actual production
in those regions. Total U.S. phosphate rock production data
are not considered to be a significant source of uncertainty
because all the domestic phosphate rock producers report
their annual production to the USGS. Data for imports for
consumption and exports of phosphate rock used in the
emission calculation are based on international trade data
collected by the U.S. Census Bureau. These U.S. government
economic data are not considered to be a significant source
of uncertainty.
An additional source of uncertainty in the calculation
of CO, emissions from phosphoric acid production is the
carbonate composition of phosphate rock; the composition
of phosphate rock varies depending upon where the material
is mined, and may also vary over time. Another source of
uncertainty is the disposition of the organic C content of the
phosphate rock. A representative of the FIPR indicated that
in the phosphoric acid production process, the organic C
content of the mined phosphate rock generally remains in the
phosphoric acid product, which is what produces the color
of the phosphoric acid product (FIPR 2003a). Organic C is
therefore not included in the calculation of CO, emissions
from phosphoric acid production.
A third source of uncertainty is the assumption that all
domestically-produced phosphate rock is used in phosphoric
acid production and used without first being calcined.
Calcination of the phosphate rock would result in conversion
of some of the organic C in the phosphate rock into COi.
However, according to the USGS, only one producer in
Idaho is currently calcining phosphate rock, and no data were
available concerning the annual production of this single
producer (USGS 2005). For available years, total production
of phosphate rock in Utah and Idaho combined amounts to
approximately 13 percent of total domestic production on
average (USGS 1994 through 2005).
Finally, USGS indicated that 10 percent of domestically-
produced phosphate rock is used to manufacture elemental
phosphorus and other phosphorus-based chemicals, rather
than phosphoric acid (USGS 2006). According to USGS,
there is only one domestic producer of elemental phosphorus,
in Idaho, and no data were available concerning the annual
production of this single producer. Elemental phosphorus is
produced by reducing phosphate rock with coal coke, and
it is therefore assumed that 100 percent of the carbonate
content of the phosphate rock will be converted to CO, in the
elemental phosphorus production process. The calculation
for CO2 emissions is based on the assumption that phosphate
rock consumption, for purposes other than phosphoric acid
production, results in CO2 emissions from 100 percent of
the inorganic C content in phosphate rock, but none from
the organic C content. This phosphate rock, consumed for
other purposes, constitutes approximately 10 percent of total
phosphate rock consumption.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-39. Phosphoric acid production
CO2 emissions were estimated to be between 1.1 and 1.6 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 19 percent below and 19 percent
above the emission estimate of 1.4 Tg CO2 Eq.
4.10, Carbon Dioxide Consumption
(IPCC Source Category 2B5)
CO2 is used for a variety of commercial applications,
including food processing, chemical production, carbonated
beverage production, and refrigeration, and is also used in
petroleum production for enhanced oil recovery (EOR). CO2
Industrial Processes 4-27
-------
used for EOR is injected into the underground reservoirs to
increase the reservoir pressure to enable additional petroleum
to be produced.
For the most part, CO2 used in non-EOR applications
will eventually be released to the atmosphere, and for
the purposes of this analysis CO2 used in commercial
applications other than EOR is assumed to be emitted to
the atmosphere. CO2 used in EOR applications is discussed
in the Energy Chapter under "Carbon Capture and Storage,
including Enhanced Oil Recovery" and is not discussed in
this section.
CO2 is produced from naturally occurring CO2
reservoirs, as a by-product from the energy and industrial
production processes (e.g., ammonia production, fossil
fuel combustion, ethanol production), and as a by-product
from the production of crude oil and natural gas, which
contain naturally occurring CO2 as a component. Only CO2
produced from naturally occurring CO2 reservoirs and used
in industrial applications other than EOR is included in this
analysis. Neither by-product CO2 generated from energy
nor industrial production processes nor CO2 separated from
crude oil and natural gas are included in this analysis for
a number of reasons. CO2 captured from biogenic sources
(e.g., ethanol production plants) is not included in the
Inventory. CO2 captured from crude oil and gas production
is used in EOR applications and is therefore reported in
the Energy Chapter. Any CO2 captured from industrial or
energy production processes (e.g., ammonia plants, fossil fuel
combustion) and used in non-EOR applications is assumed to
be emitted to the atmosphere. The CO2 emissions from such
capture and use are therefore accounted for under Ammonia
Production, Fossil Fuel Combustion, or other appropriate
source category.
CO2 is produced as a by-product of crude oil and natural
gas production. This CO2 is separated from the crude oil and
natural gas using gas processing equipment, and may be
emitted directly to the atmosphere, or captured and reinjected
into underground formations, used for EOR, or sold for other
commercial uses. A further discussion of CO2 used in EOR
is described in the Energy Chapter under "Box 3-3: Carbon
Dioxide Transport, Injection, and Geological Storage." The
only CO, consumption that is accounted for in this analysis
is CO2 produced from naturally-occurring CO2 reservoirs that
is used in commercial applications other than EOR.
Table 4-40: C02 Emissions from C02 Consumption
(Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.3
Gg
1,415
1,423
1,416
825
978
1,310
1,199
1,324
There are currently two facilities, one in Mississippi and
one in New Mexico, producing CO2 from naturally occurring
CO2 reservoirs for use in both EOR and in other commercial
applications (e.g., chemical manufacturing, food production).
There are other naturally occurring CO2 reservoirs, mostly
located in the western United States Facilities are producing
CO2 from these natural reservoirs, but they are only producing
CO2 for EOR applications, not for other commercial
applications (Allis et al. 2000). CO2 production from these
facilities is discussed in the Energy Chapter.
In 2005, the amount of CO2 produced by the Mississippi
and New Mexico facilities for commercial applications and
subsequently emitted to the atmosphere was 1.3 Tg CO2
Eq. (1,324 Gg) (see Table 4-40). This amount represents a
increase of 10 percent from the previous year and a decrease
of 6 percent from emissions in 1990. This decrease was
due to a decrease in the percent of the Mississippi facility's
total reported production that was used for commercial
applications. During this period the Mississippi facility
dedicated more of its total production to EOR.
Methodology
CO2 emission estimates for 1990 through 2005 were based
on production data for the two facilities currently producing
CO2 from naturally-occurring CO2 reservoirs for use in non-
EOR applications (see Table 4-41). Some of the CO2 produced
by these facilities is used for EOR and some is used in other
commercial applications (e.g., chemical manufacturing,
food production). It is assumed that 100 percent of the CO2
production used in commercial applications other than EOR
is eventually released into the atmosphere.
CO2 production data for the Jackson Dome, Mississippi
facility and the percentage of total production that was used
4-28 inventory of U.S. Greenhouse Gas> Emissions and Sinks: 1990-2005
-------
Table 4-41: C02 Production (Gg C02) and the Percent Used for Non-EOR Applications for Jackson Dome and
Bravo Dome
Year
1990
1995
2000
2001
2002
2003
2004
2005
Jackson Dome C02
Production (Gg)
1,353
1,353
1,353
1,624
2,010
3,286
4,214
4,678
Jackson Dome % Used
for Non-EOR
100%
100%
100%
47%
46%
38%
27%
27%
Bravo Dome C02
Production (Gg)
6,241
7,003
6,328
6,196
5,295
6,090
6,090
6,090
Bravo Dome % Used
for Non-EOR
1%
1%
1%
1%
1%
1%
1%
1%
for EOR and in non-EOR applications were obtained from
the Advanced Resources Institute (ARI 2006) for 1990 to
2000 and from the Annual Reports for Denbury Resources
(Denbury Resources 2002, 2003, 2004, 2005, 2006) for
2001 to 2005. Denbury Resources reported the average CO2
production in units of MMCF CO2 per day for 2001 through
2005 and reported the percentage of the total average annual
production that was used for EOR. CO2 production data for
the Bravo Dome, New Mexico facility were obtained from
the New Mexico Bureau of Geology and Mineral Resources
for the years 1990 through 2003 (Broadhead 2006). The
New Mexico Bureau of Geology reported production in
billion cubic feet per year. According to the New Mexico
Bureau, the amount of CO2 produced from Bravo Dome
for use in non-EOR applications is less than one percent
of total production (Broadhead 2003a). Production data for
2004 and 2005 were not available for Bravo Dome, so it is
assumed that the production values for those years are equal
to the 2003 value.
Uncertainty
Uncertainty is associated with the number of facilities
that are currently producing CO2 from naturally occurring
CO2 reservoirs for commercial uses other than EOR, and for
which the CO2 emissions are not accounted for elsewhere.
Research indicates that there are only two such facilities,
which are in New Mexico and Mississippi; however,
additional facilities may exist that have not been identified. In
addition, it is possible that CO2 recovery exists in particular
production and end-use sectors that are not accounted for
elsewhere. Such recovery may or may not affect the overall
estimate of CO2 emissions from that sector depending upon
the end use to which the recovered CO2 is applied. Further
research is required to determine whether CO2 is being
recovered from other facilities for application to end uses
that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-42. CO2 Consumption CO2
emissions were estimated to be between 1.1 and 1.6 Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
of approximately 15 percent below to 21 percent above the
emission estimate of 1.3 Tg CO2 Eq.
Recalculations Discussion
Data for total Bravo Dome CO2 production were updated
for the entire time series based on new production data from
the facility. Data for CO2 production from Jackson Dome
Table 4-42: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from C02 Consumption
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(TgC02Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
C02 Consumption
CO,
1.3
1.1
1.6
-15%
+21%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
industrial Processes 4-29
-------
were provided for years 1990 through 2000 for the first time
during the current inventory year. These changes resulted in
an average emission increase of 70 percent for years 1990
through 2000 and an average emission increase of less than
one percent for years 2001 to 2005.
4,11, Zinc (IPCC Source
P
w
Table 4-43: C02 Emissions from Zinc Production
(Tg C02 Eq. and Gg)
Zinc production in the United States consists of both
primary and secondary processes. Primary production
techniques used in the United States are the electro-thermic
and electrolytic process while secondary techniques used
in the United States include a range of metallurgical,
hydrometallurgical, and pyrometallurgical processes.
Worldwide primary zinc production also employs a
pyrometallurgical process using the Imperial Smelting Furnace
process; however, this process is not used in the United States
(Sjardin 2003). Of the primary and secondary processes used
in the United States, the electro-thermic process results in
non-energy CO2 emissions, as does the Waelz Kiln process—a
technique used to produce secondary zinc from electric-arc
furnace (EAF) dust (Viklund-White 2000).
During the electro-thermic zinc production process,
roasted zinc concentrate and. when available, secondary
zinc products enter a sinter feed where they are burned to
remove impurities before entering an electric retort furnace.
Metallurgical coke added to the electric retort furnace reduces
the zinc oxides and produces vaporized zinc, which is then
captured in a vacuum condenser. This reduction process
produces non-energy CO2 emissions (Sjardin 2003). The
electrolytic zinc production process does not produce non-
energy CO2 emissions.
In the Waelz Kiln process. EAF dust, which is captured
during the recycling of galvanized steel, enters a kiln along
with a reducing agent—often metallurgical coke. When kiln
temperatures reach approximately 1100-1200 °C, zinc fumes
are produced, which are combusted with air entering the kiln.
This combustion forms zinc oxide, which is collected in a
baghouse or electrostatic precipitator, and is then leached
to remove chloride and fluoride. Through this process,
approximately 0.33 ton of zinc is produced for every ton of
EAF dust treated (Viklund-White 2000).
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
0.9
1.0
1.1
1.0
0.9
0.5
0.5
0.5
Gg
939
1,003
1,129
976
927
502
472
460
In 2005, U.S. primary and secondary zinc production
totaled 540,200 metric tons (Gabby 2006). The resulting
emissions of CO2 from zinc production in 2005 were
estimated to be 0.5 Tg CO2 Eq. (460 Gg) (see Table 4-
43). All 2005 CO2 emissions result from secondary zinc
production.
After a gradual increase in total emissions from 1990 to
2000, largely due to an increase in secondary zinc production,
2005 emissions have decreased by nearly half that of 1990
(49 percent) due to the closing of an electro-thermic-process
zinc plant in Monaca, PA (USGS 2004).
Methodology
Non-energy CO2 emissions from zinc production result
from those processes that use metallurgical coke or other
C-based materials as reductants. Sjardin (2003) provides an
emission factor of 0.43 metric tons CO2/ton zinc produced for
emissive zinc production processes; however, this emission
factor is based on the Imperial Smelting Furnace production
process. Because the Imperial Smelting Furnace production
process is not used in the United States, emission factors
specific to those emissive zinc production processes used
in the United States, which consist of the electro-thermic
and Waelz Kiln processes, were needed. Due to the limited
amount of information available for these electro-thermic
processes, only Waelz Kiln process-specific emission factors
were developed. These emission factors were applied to
both the Waelz Kiln process and the electro-thermic zinc
production processes. A Waelz Kiln emission factor based
on the amount of zinc produced was developed based on
the amount of metallurgical coke consumed for non-energy
4-30 Inventory of U.S. Greenhouse Ga<; Emissions and Sinks: 1990-2005
-------
purposes per ton of zinc produced, 1.19 metric tons coke/
metric ton zinc produced (Viklund-White 2000), and the
following equation:
i'.' metric tons i oke
metric ions /inc
The USGS disaggregates total U.S. primary zinc
production capacity into zinc produced using the electro-
thermic process and zinc produced using the electrolytic
process; however, the USGS does not report the amount
of zinc produced using each process, only the total zinc
production capacity of the zinc plants using each process.
The total electro-thermic zinc production capacity is divided
by total primary zinc production capacity to estimate the
percent of primary zinc produced using the electro-thermic
process. This percent is then multiplied by total primary zinc
production to estimate the amount of zinc produced using the
electro-thermic process, and the resulting value is multiplied
by the Waelz Kiln process emission factor to obtain total
CO2 emissions for primary zinc production. According to
the USGS, the only remaining plant producing primary zinc
using the electro-thermic process closed in 2003 (USGS
2004). Therefore, CO2 emissions for primary zinc production
are reported only for years 1990 through 2002.
In the United States, secondary zinc is produced through
either the electro-thermic or Waelz Kiln process. In 1997,
the Horsehead Corporation plant, located in Monaca, PA,
produced 47,174 metric tons of secondary zinc using the
electro-thermic process (Queneau et al. 1998). This is the
only plant in the United States that uses the electro-thermic
process to produce secondary zinc, which, in 1997, accounted
for 13 percent of total secondary zinc production. This
percentage was applied to all years within the time series
up until the Monaca plant's closure in 2003 (USGS 2004) to
estimate the total amount of secondary zinc produced using
the electro-thermic process. This value is then multiplied by
the Waelz Kiln process emission factor to obtain total CO2
emissions for secondary zinc produced using the electro-
thermic process.
U.S. secondary zinc is also produced by processing
recycled EAF dust in a Waelz Kiln furnace. Due to the
complexities of recovering zinc from recycled EAF dust, an
emission factor based on the amount of EAF dust consumed
rather than the amount of secondary zinc produced is believed
to represent actual CO2 emissions from the process more
accurately (Stuart 2005). An emission factor based on the
amount of EAF dust consumed was developed based on
the amount of metallurgical coke consumed per ton of
EAF dust consumed, 0.4 metric tons coke/metric ton EAF
dust consumed (Viklund-White 2000), and the following
equation:
(1.4 metric ion-, o'ke
' u ;':': metric ton-- FAF dust
O.S4 metric ton-. ('
v"
metric ion <. ok..-
The Horsehead Corporation plant, located in Palmerton,
PA, is the only large plant in the United States that produces
secondary zinc by recycling EAF dust (Stuart 2005). In
2003, this plant consumed 408,240 metric tons of EAF dust,
producing 137,169 metric tons of secondary zinc (Recycling
Today 2005). This zinc production accounted for 36 percent
of total secondary zinc produced in 2003. This percentage
was applied to the USGS data for total secondary zinc
production for all years within the time series to estimate
the total amount of secondary zinc produced by consuming
recycled EAF dust in a Waelz Kiln furnace. This value is
multiplied by the Waelz Kiln process emission factor for
EAF dust to obtain total CO2 emissions.
The 1990 through 2004 activity data for primary and
secondary zinc production (see Table 4-44) were obtained
through the USGS Mineral Yearbook: Zinc (USGS 1994
through 2005). Activity data for 2005 were obtained from
the USGS Commodity Specialist (Gabby 2006).
Industrial Processes 4-31
-------
Table 4-44: Zinc Production (Metric Tons)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Primary
262,704
231,840
227,800
203,000
181,800
186,900
188,200
191,200
Secondary
341,400
353,000
440,000
375,000
366,000
381,000
358,000
349,000
Uncertainty
The uncertainties contained in these estimates are two-
fold, relating to activity data and emission factors used.
First, there are uncertainties associated with the percent
of total zinc production, both primary and secondary, that
is attributed to the electro-thermic and Waelz Kiln emissive
zinc production processes. For primary zinc production, the
amount of zinc produced annually using the electro-thermic
process is estimated from the percent of primary-zinc
production capacity that electro-thermic production capacity
constitutes for each year of the time series. This assumes
that each zinc plant is operating at the same percentage of
total production capacity, which may not be the case and
this calculation could either overestimate or underestimate
the percentage of the total primary zinc production that is
produced using the electro-thermic process. The amount of
secondary zinc produced using the electro-thermic process is
estimated from the percent of total secondary zinc production
that this process accounted for during a single year, 2003.
The amount of secondary zinc produced using the Waelz
Kiln process is estimated from the percent of total secondary
zinc production this process accounted for during a single
year, 1997. This calculation could either overestimate or
underestimate the percentage of the total secondary zinc
production that is produced using the electro-thermic
or Waelz Kiln processes. Therefore, there is uncertainty
associated with the fact that percents of total production
data estimated from production capacity, rather than actual
production data, are used for emission estimates.
Second, there are uncertainties associated with the
emission factors used to estimate CO2 emissions from the
primary and secondary production processes. Because the
only published emission factors are based on the Imperial
Smelting Furnace, which is not used in the United States,
country-specific emission factors were developed for
the Waelz Kiln zinc production process. Data limitations
prevented the development of emission factors for the
electro-thermic process. Therefore, emission factors for the
Waelz Kiln process were applied to both electro-thermic and
Waelz Kiln production processes. Furthermore, the Waelz
Kiln emission factors are based on materials balances for
metallurgical coke and EAF dust consumed during zinc
production provided by Viklund-White (2000). Therefore,
the accuracy of these emission factors depend upon the
accuracy of these materials balances.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-45. Zinc production CO2
emissions were estimated to be between 0.4 and 0.6 Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
of approximately 21 percent below and 25 percent above the
emission estimate of 0.5 Tg CO2 Eq.
Recalculations Discussion
The historical activity data used to calculate the
emissions from zinc production were updated for the year
2004. The change resulted in a decrease of 0.03 Tg CO2
Eq. (6 percent) in CO2 emissions from zinc production for
that year.
Table 4-45: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Zinc Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Zinc Production
CO,
0.5
0.4
0.6
-21%
+25%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1930-2005
-------
4.12. Lead Production (IPCC Source
Category 2C5)
Lead production in the United States consists of both
primary and secondary processes. In the United States, primary
lead production, in the form of direct smelting, mostly occurs
at plants located in Alaska and Missouri, while secondary
production largely involves the recycling of lead acid batteries
at 14 separate smelters located in 11 states throughout the
United States (USGS 2005). Secondary lead production has
increased in the United States over the past decade while
primary lead production has decreased. In 2005, secondary
lead production accounted for approximately 89 percent of
total lead production (Gabby 2006, USGS 1995). Both the
primary lead and secondary lead production processes used
in the United States emit CO2 (Sjardin 2003).
Primary production of lead through the direct smelting
of lead concentrate produces CO2 emissions as the lead
concentrates are reduced in a furnace using metallurgical
coke (Sjardin 2003). U.S. primary lead production decreased
by 3 percent from 2004 to 2005 and has decreased by 63
percent since 1990 (Gabby 2006, USGS 1995).
In the United States, approximately 82 percent of
secondary lead is produced by recycling lead acid batteries in
either blast furnaces or reverberatory furnaces. The remaining
18 percent of secondary lead is produced from lead scrap.
Similar to primary lead production, CO2 emissions result
when a reducing agent, usually metallurgical coke, is added
to the smelter to aid in the reduction process (Sjardin 2003).
U.S. secondary lead production increased by 3 percent from
2004 to 2005, and has increased by 24 percent since 1990.
The United States is the third largest mine producer of
lead in the world, behind China and Australia, accounting
for 14 percent of world production in 2005 (USGS 2005).
In 2005, U.S. primary and secondary lead production totaled
1,288,000 metric tons (Gabby 2006). The resulting emissions
of CO2 from 2005 production were estimated to be 0.3 Tg
CO, Eq. (265 Gg) (see Table 4-46). The majority of 2005
lead production is from secondary processes, which account
for 86 percent of total 2005 CO, emissions.
After a gradual increase in total emissions from 1990
to 2000, total emissions have decreased by seven percent
since 1990, largely due a decrease in primary production
and a transition within the United States from primary lead
Table 4-46: C02 Emissions from Lead Production
(Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
Gg
285
298
311
293
290
289
259
265
production to secondary lead production, which is less
emissive than primary production (USGS 2005).
Methodology
Non-energy CO2 emissions from lead production result
from primary and secondary production processes that use
metallurgical coke or other C-based materials as reductants.
For primary lead production using direct smelting, Sjardin
(2003) provides an emission factor of 0.25 metric tons
CO2/ton lead. For secondary lead production, Sjardin (2003)
provides an emission factor of 0.2 metric tons CO2/ton lead
produced. Both factors are multiplied by total U.S. primary
and secondary lead production, respectively, to estimate
CO2 emissions.
The 1990 through 2004 activity data for primary and
secondary lead production (see Table 4-47) were obtained
through the USGS Mineral Yearbook: Lead (USGS 1994,
1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,
2005). Primary and secondary lead production data for 2005
were obtained from the USGS Lead Minerals Commodity
Specialist (Gabby 2006).
Table 4-47: Lead Production (Metric Tons)
Year
Primary
Secondary
1990
1995
404,000
374,000
922,000
1,020,000
2000
2001
2002
2003
2004
2005
341,000
290,000
262,000
245,000
148,000
143,000
1,130,000
1,100,000
1,120,000
1,140,000
1,110,000
1,145,000
Industrial Processes 4-33
-------
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lead Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lead Production
CO,
0.3
0.2
0.3
-16%
+17%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Uncertainty
Uncertainty associated with lead production relates
to the emission factors and activity data used. The direct
smelting emission factor used in primary production is taken
from Sjardin (2003) who averages the values provided by
three other studies (Dutrizac et al. 2000, Morris et al. 1983,
Ullman 1997). For secondary production, Sjardin (2003)
reduces this factor by 50 percent and adds a CO2 emissions
factor associated with battery treatment. The applicability
of these emission factors to plants in the United States
is uncertain. There is also a smaller level of uncertainty
associated with the accuracy of primary and secondary
production data provided by the USGS.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-48. Lead production CO2
emissions were estimated to be between 0.2 and 0.3 Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
of approximately 16 percent below and 17 percent above the
emission estimate of 0.3 Tg CO2 Eq.
4.13. Petrochemical Production
(IPCC Source Category 2B5)
The production of some petrochemicals results in
the release of small amounts of CH4 and CO2 emissions.
Petrochemicals are chemicals isolated or derived from
petroleum or natural gas. CH4 emissions are presented
here from the production of C black, ethylene, ethylene
dichloride, and methanol, while CO2 emissions are presented
here for only C black production. The CO2 emissions from
petrochemical processes other than C black are currently
included in the Carbon Stored in Products from Non-Energy
Uses of Fossil Fuels Section of the Energy chapter. The CO2
from C black production is included here to allow for the
direct reporting of CO2 emissions from the process and direct
accounting of the feedstocks used in the process.
C black is an intensely black powder generated by
the incomplete combustion of an aromatic petroleum or
coal-based feedstock. Most C black produced in the United
States is added to rubber to impart strength and abrasion
resistance, and the tire industry is by far the largest consumer.
Ethylene is consumed in the production processes of the
plastics industry including polymers such as high, low, and
linear low density polyethylene (HOPE, LDPE, LLDPE),
poly vinyl chloride (PVC), ethylene dichloride, ethylene
oxide, and ethylbenzene. Ethylene dichloride is one of the
first manufactured chlorinated hydrocarbons with reported
production as early as 1795. In addition to being an important
intermediate in the synthesis of chlorinated hydrocarbons,
ethylene dichloride is used as an industrial solvent and as a
fuel additive. Methanol is an alternative transportation fuel
as well as a principle ingredient in windshield wiper fluid,
paints, solvents, refrigerants, and disinfectants. In addition,
methanol-based acetic acid is used in making PET plastics
and polyester fibers.
Eimissions of CO2 and CH4 from petrochemical
production in 2005 were 2.9 Tg CO2 Eq. (2,895 Gg) and
1.1 Tg CO2 Eq. (52 Gg), respectively (see Table 4-49 and
Table 4-50), totaling 4.0 Tg CO2 Eq. Emissions of CO2 from
C black production in 2005 essentially equaled those from
the previous year. There has been an overall increase in CO2
emissions from C black production of 30 percent since 1990.
CH4 emissions from petrochemical production increased by
six percent from the previous year and increased 26 percent
since 1990.
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-49: C02 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.)
Year
C02
CH4
Total
1990
2.2 "-..
0.9 •
3.1
1995
2.8
1.1
3.8
2000
3.0
1.2
4.2
2001
2.8
1.1
3.9
2002
2.9
1.1
4.0
2003
2.8
1.1
3.9
2004
2.9
1.2
4.1
2005
2.9
1.1
4.0
Table 4-50: C02 and CH4 Emissions from Petrochemical Production (Gg)
Year
C02
CH4
1990
2,221
41 " •
1995 i-,
2,750 '.
52
2000
3,004
58
2001
2,787
51
2002
2,857
52
2003
2,777
51
2004
2,895
55
2005
2,897
51
Methodology
Emissions of CH4 were calculated by multiplying
annual estimates of chemical production by the appropriate
emission factor, as follows: 11 kg CH4/metric ton C black, 1
kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton ethylene
dichloride,10 and 2 kg CH4/metric ton methanol. Although
the production of other chemicals may also result in CH4
emissions, there were not sufficient data available to estimate
their emissions.
Emission factors were taken from the Revised 1996
IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Annual
production data for 1990 (see Table 4-51) were obtained
from the Chemical Manufacturer's Association Statistical
Handbook (CMA 1999). Production data for 1991 through
2005 were obtained from the American Chemistry Council's
Guide to the Business of Chemistry (ACC 2002, 2003,
2005,2006) and the International Carbon Black Association
(Johnson 2003, 2005, 2006).
Almost all C black in the United States is produced
from petroleum-based or coal-based feedstocks using the
"furnace black" process (European IPPC Bureau 2004).
The furnace black process is a partial combustion process
in which a portion of the C black feedstock is combusted
to provide energy to the process. C black is also produced
in the United States by the thermal cracking of acetylene-
containing feedstocks ("acetylene black process") and by
the thermal cracking of other hydrocarbons ("thermal black
process"). One U .S. C black plant produces C black using the
thermal black process, and one U.S. C black plant produces
C black using the acetylene black process (The Innovation
Group 2004).
The furnace black process produces C black from "C
black feedstock" (also referred to as "C black oil"), which
is a heavy aromatic oil that may be derived as a byproduct
of either the petroleum refining process or the metallurgical
(coal) coke production process. For the production of both
petroleum-derived and coal-derived C black, the "primary
feedstock" (i.e., C black feedstock) is injected into a furnace
that is heated by a "secondary feedstock" (generally natural
gas). Both the natural gas secondary feedstock and a portion
of the C black feedstock are oxidized to provide heat to the
production process and pyrolyze the remaining C black
feedstock to C black. The "tail gas" from the furnace black
process contains CO2, carbon monoxide, sulfur compounds,
CH4, and non-CH4 volatile organic compounds. A portion of
the tail gas is generally burned for energy recovery to heat
Table 4-51: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
Carbon Black
Ethylene
Ethylene Dichloride
Methanol
1990
1,307 • •'
16,542 ••*?
6,282 :'.
3,785 •'
1995 ,~-
1,619 '<
21,215 ==,!.
7,829 A
4,992 ,-,;
2000
1,769
24,971
9,866
4,876
2001
1,641
22,521
9,294
3,402
2002
1,682
23,623
9,288
3,289
2003
1,635
22,957
9,952
3,166
2004
1,705
25,660
12,111
2,937
2005
1,651
23,955
11,261
2,336
10 The emission factor obtained from IPCC/UNEP/OECD/IEA (1997). page 2.23, is assumed to have a misprint; the chemical identified should be
ethylene dichloride (C2H4C12) rather than dichloroethylene (C2H2C12).
Industrial Processes 4-35
-------
the downstream C black product dryers. The remaining tail
gas may also be burned for energy recovery, flared, or vented
uncontrolled to the atmosphere.
The calculation of the C lost during the production
process is the basis for determining the amount of Cd
released during the process. The C content of national C
black production is subtracted from the total amount of C
contained in primary and secondary C black feedstock to
find the amount of C lost during the production process. It
is assumed that the C lost in this process is emitted to the
atmosphere as either CH4 or CO2. The C content of the CH4
emissions, estimated as described above, is subtracted from
the total C lost in the process to calculate the amount of C
emitted as CO2. The total amount of primary and secondary
C black feedstock consumed in the process (see Table 4-52)
is estimated using a primary feedstock consumption factor
and a secondary feedstock consumption factor estimated
from U.S. Census Bureau (1999 and 2004) data. The
average C black feedstock consumption factor for U.S. C
black production is 1.43 metric tons of C black feedstock
consumed per metric ton of C black produced. The average
natural gas consumption factor for U.S. C black production is
341 normal cubic meters of natural gas consumed per metric
ton of C black produced. The amount of C contained in the
primary and secondary feedstocks is calculated by applying
the respective C contents of the feedstocks to the respective
levels of feedstock consumption (EIA 2003,2004).
For the purposes of emissions estimation, 100 percent of
the primary C black feedstock is assumed to be derived from
petroleum refining byproducts. C black feedstock derived
from metallurgical (coal) coke production (e.g., creosote
oil) is also used for C black production; however, no data
are available concerning the annual consumption of coal-
derived C black feedstock. C black feedstock derived from
petroleum refining byproducts is assumed to be 89 percent
elemental C (Srivastava et al. 1999). It is assumed that 100
percent of the tail gas produced from the C black production
process is combusted and that none of the tail gas is vented
to the atmosphere uncontrolled. The furnace black process
is assumed to be the only process used for the production of
C black because of the lack of data concerning the relatively
small amount of C black produced using the acetylene black
and thermal black processes. The C black produced from the
furnace black process is assumed to be 97 percent elemental
C(Othmeretal. 1992).
Uncertainty
The CH4 emission factors used for petrochemical
production are based on a limited number of studies. Using
plant-specific factors instead of average factors could increase
the accuracy of the emission estimates; however, such data
were not available. There may also be other significant sources
of CH4 arising from petrochemical production activities that
have not been included in these estimates.
The results of the quantitative uncertainty analysis for
the CO2 emissions from C black production calculation
are based on feedstock consumption, import and export
data, and C black production data. The composition of C
black feedstock varies depending upon the specific refinery
production process, and therefore the assumption that C
black feedstock is 89 percent C gives rise to uncertainty.
Also, no data are available concerning the consumption of
coal-derived C black feedstock, so CO2 emissions from the
utilization of coal-based feedstock are not included in the
emission estimate. In addition, other data sources indicate
that the amount of petroleum-based feedstock used in C
black Droduction may be underreported by the U.S. Census
Bureau. Finally, the amount of C black produced from the
thermal black process and acetylene black process, although
estimated to be a small percentage of the total production, is
not known. Therefore, there is some uncertainty associated
with the assumption that all of the C black is produced using
the furnace black process.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-53. Petrochemical production
CO2 emissions were estimated to be between 1.9 and 4.0 Tg
CO2 E)q. at the 95 percent confidence level . This indicates
a range of approximately 35 percent below to 39 percent
Table 4-52: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons)
Activity
Primary Feedstock
Secondary Feedstock
1990
1,864
302
1995
2,308
374
2000
2,521
408
2001
2,339
379
2002
2,398
388
2003
2,331
377
2004
2,430
393
2005
2,430
393
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-53: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Petrochemical Production
(Tg C02 Eq. and Percent)
2005 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (TgC02Eq.) (TgC02Eq.) (%)
Petrochemical
Production C02
Petrochemical
Production CH4
Lower Bound
2.9 1.9
1.1 1.0
Upper Bound
4.0
1.2
Lower Bound Upper Bound
-35% +39%
-9% +9%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
above the emission estimate of 2.9 Tg CO2 Eq. Petrochemical
production CH4 emissions were estimated to be between 1.0
and 1.2 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 9 percent below to 9
percent above the emission estimate of 1.1 Tg CO2 Eq.
Recalculations Discussion
Estimates of CH4 emissions from petrochemical
production have been revised for the entire time series to
include the removal of styrene, which has been removed
due to inconsistent information regarding its emissive use
in the United States. On average, the removal of styrene
resulted in a decrease of 0.4 Tg CO2 Eq. (27 percent) from
the previous estimate.
Planned Improvements
Future improvements to the petrochemicals source
category include research into the use of acrylonitrile in
the United States, revisions to the C black CH4 and CO2
emission factors, and research into process and feedstock
data to obtain Tier 2 emission estimates from the production
of methanol, ethylene, propylene, ethylene dichloride, and
ethylene oxide.
4.14. Silicon Carbide Production
(IPCC Source Category 2B4) and
Consumption
CO2 and CH4 are emitted from the production of silicon
carbide (SiC), a material used as an industrial abrasive.
To make SiC, quartz (SiO7) is reacted with C in the form
of petroleum coke. A portion (about 35 percent) of the C
contained in the petroleum coke is retained in the SiC. The
remaining C is emitted as Cd, CH4, or CO.
CO2 is also emitted from the consumption of SiC for
metallurgical and other non-abrasive applications. The USGS
reports that a portion (approximately 50 percent) of SiC is
used in metallurgical and other non-abrasive applications,
primarily in iron and steel production (USGS 2005a).
CO2 emissions from SiC production and consumption
in 2005 were 219 Gg (0.2 Tg CO2 Eq.). Approximately 42
percent of these emissions resulted from SiC production
while the remainder result from SiC consumption. CH4
emissions from SiC production in 2005 were 0.4 Gg CH4
(0.01 Tg CO2 Eq.) (see Table 4-54 and Table 4-55).
Table 4-54: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02
CH4
0.4
0.3
0.2
0.2
0.2
0.2
0.2
0.2
Total
0.4
0.3
0.3
0.2
0.2
0.2
0.2
0.2
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Industrial Processes 4-37
-------
Table 4-55: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02
CH4
375
1
329
1
248
1
199
183
202
224
219
+ Does not exceed 0.5 Gg.
Methodology
Emissions of CO2 and CH4 from the production of SiC
were calculated by multiplying annual SiC production by
the emission factors (2.62 metric tons CO2/metric ton SiC
for CO2 and 11.6 kg CH4/metric ton SiC for CH4) provided
by the 2006 IP CC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006).
Emissions of CO2 were calculated by multiplying the
annual SiC consumption (production plus net imports) by
the percent used in metallurgical and other non-abrasive
uses (50 percent) (USGS 2005a). The total SiC consumed in
metallurgical and other non-abrasive uses was multiplied by
the C content of SiC (31.5 percent), which was determined
according to the molecular weight ratio of SiC.
Production data for 1990 through 2005 were obtained
from the Minerals Yearbook: Manufactured Abrasives
Table 4-56: Production and Consumption of Silicon
Carbide (Metric Tons)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Production
105,000
75,400
45,000
40,000
30,000
35,000
35,000
35,000
Consumption
172,464
227,397
225,280
162,142
180,956
191,289
229,692
220,150
(USGS 1991a, 1992a, 1993a, 1994a, 1995a, 1996a, 1997a,
1998a, 1999a, 2000a, 2001a, 2002a, 2003a, 2004a, 2005a,
2006). Silicon carbide consumption by major end use was
obtained from the Minerals Yearbook: Silicon (USGS 1991 b,
1992b,1993b,1994b,1995b, 1996b, 1997b, 1998b,1999b,
2000b, 2001b, 2002b, 2003b, 2004b, 2005b) (see Table
4-56) for years 1990 through 2004 and from the USGS
Minerals Commodity Specialist for 2005 (Corathers 2006).
Net imports were obtained from the U.S. Census Bureau
(2005,2006).
Uncertainty
There is uncertainty associated with the emission factors
used because they are based on stoichiometry as opposed to
monitoring of actual SiC production plants. An alternative
would be to calculate emissions based on the quantity
of petroleum coke used during the production process
rather than on the amount of silicon carbide produced.
However, these data were not available. For CH4, there is
also uncertainty associated with the hydrogen-containing
volatile compounds in the petroleum coke (IPCC 2006).
There is also some uncertainty associated with production,
net imports, and consumption data as well as the percent of
total consumption that is attributed to metallurgical and other
non-abrasive uses.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-57. Silicon carbide
production and consumption CO2 emissions were estimated
Table 4-57: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Silicon Carbide Production
and Consumption (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate8
(TgCOjEq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Silicon Carbide Production
and Consumption
Silicon Carbide Production
and Consumption
C02
CH4
0.2
0.2 0.2
-10%
-9%
+10%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 Tg C02 Eq.
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
to be between 10 percent below and 10 percent above the
emission estimate of 0.2 Tg CO2 Eq. at the 95 percent
confidence level. Silicon carbide production CH4 emissions
were estimated to be between 9 percent below and 9 percent
above the emission estimate of 0.01 Tg CO2 Eq. at the 95
percent confidence level.
Recalculations Discussion
Emissions of CO2 from SiC production were included
for the first time during this inventory year. Overall emissions
from CO2 production and consumption increased throughout
the time series by an average of 56 percent as a result of
this change.
Planned Improvements
Future improvements to the carbide production source
category include performing research to determine if calcium
carbide production and consumption data are available
for the United States. If these data are available, calcium
carbide emission estimates will be included in this source
category.
4.15. Nitric Acid Production (IPCC
Source Category 2B2)
Nitric acid (HNO3) is an inorganic compound used
primarily to make synthetic commercial fertilizers. It is
also a major component in the production of adipic acid—a
feedstock for nylon —and explosives. Virtually all of the
nitric acid produced in the United States is manufactured
by the catalytic oxidation of ammonia (EPA 1997). During
this reaction, N2O is formed as a by-product and is released
from reactor vents into the atmosphere.
Currently, the nitric acid industry controls for emissions
of NO and NO2 (i.e., NOX). As such, the industry uses a
combination of non-selective catalytic reduction (NSCR)
and selective catalytic reduction (SCR) technologies. In the
process of destroying NOX, NSCR systems are also very
effective at destroying N,O. However, NSCR units are
generally not preferred in modern plants because of high
energy costs and associated high gas temperatures. NSCRs
were widely installed in nitric plants built between 1971
and 1977. Approximately 20 percent of nitric acid plants
use NSCR (Choe et al. 1993). The remaining 80 percent use
Table 4-58: N20 Emissions from Nitric Acid Production
(Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
17.8
19.9
19.6
15.9
17.2
16.7
16.0
15.7
Gg
58
64
63
51
56
54
52
51
SCR or extended absorption, neither of which is known to
reduce N2O emissions.
N2O emissions from this source were estimated to be
15.7 TgCO2 Eq. (51 Gg) in 2005 (seeTable4-58). Emissions
from nitric acid production have decreased by 12.1 percent
since 1990, with the trend in the time series closely tracking
the changes in production.
Methodology
N2O emissions were calculated by multiplying nitric
acid production by the amount of N2O emitted per unit of
nitric acid produced. The emission factor was determined as
a weighted average of 2 kg N2O / metric ton HNO3 for plants
using non-selective catalytic reduction (NSCR) systems
and 9.5 kg N2O/metric ton HNO3 for plants not equipped
with NSCR (Choe et al. 1993). In the process of destroying
NOX, NSCR systems destroy 80 to 90 percent of the N2O,
which is accounted for in the emission factor of 2 kg N2O/
metric ton HNO3. An estimated 20 percent of HNO3 plants
in the United States are equipped with NSCR (Choe et al.
1993). Hence, the emission factor is equal to (9.5 x 0.80) +
(2 x 0.20) = 8 kg N2O per metric ton HNO3.
Nitric acid production data for 1990 (see Table 4-59)
was obtained from Chemical and Engineering News, "Facts
and Figures" (C&EN 2001). Nitric acid production data for
1991 through 1992 (see Table 4-59) were obtained from
Chemical and Engineering News, "Facts and Figures"
(C&EN 2002). Nitric acid production data for 1993 was
obtained from Chemical and Engineering News, "Facts and
Figures" (C&EN 2004). Nitric acid production data for 1994
was obtained from Chemical and Engineering News, "Facts
and Figures" (C&EN 2005). Nitric acid production data
for 1995 through 2005 were obtained from Chemical and
Industrial Processes 4-39
-------
Table 4-59: Nitric Acid Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
7,196
8,018
7,898
6,416
6,940
6,747
6,466
6,328
Engineering News, "Facts and Figures" (C&EN 2006). The
emission factor range was taken from Choe et al. (1993).
Uncertainty
The overall uncertainty associated with the 2005 N2O
emissions estimate from nitric acid production was calculated
using the IPCC Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
N2O emissions included that of production data, the share
of U.S. nitric acid production attributable to each emission
abatement technology, and the emission factors applied to
each abatement technology type.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-60. N2O emissions from nitric acid
production were estimated to be between 13.2 and 18.5 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 16 percent below to 18 percent above
the 2005 emissions estimate of 15.7 Tg CO2 Eq.
Recalculations Discussion
The nitric acid production values for 1998, 2002, and
2004 have been updated relative to the previous Inventory-
based on revised production data presented in C&EN
(2006). The updated production data for 1998 and 2002
resulted in an increases of less than 0.0 ITg CO2 Eq. (0.01
percent), respectively, in N2O emissions from nitric acid
production for these years relative to the previous Inventory.
The updated production data for 2004 resulted in a decrease
of 0.6 Tg CO2 Eq. (3.5 percent) in N2O emissions relative
to the orevious Inventory.
Planned Imjirovements
Planned improvements are focused on assessing
the plant-by-plant implementation of NOX abatement
technologies to more accurately match plant production
capacities to appropriate emission factors, instead of using
a national profiling of abatement implementation.
4.16. Adipic Aeid Production (IPCC
Source Category 2B3)
Adipic acid production is an anthropogenic source of
N2O emissions. Worldwide, few adipic acid plants exist. The
United States is the major producer, with three companies
in four locations accounting for approximately one-third
of world production (CW 2005). Adipic acid is a white
crystalline solid used 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. Approximately 90 percent of all adipic acid
produced in the United States is used in the production of
nylon 6,6 (CMR 2001). Food-grade adipic acid is also used
to provide some foods with a "tangy" flavor (Thiemens and
Trogler 1991).
Adipic acid is produced through a two-stage process
during which N2O is generated in the second stage. The first
stage of manufacturing usually involves the oxidation of
cyclohexane to form a cyclohexanone/cyclohexanol mixture.
The second stage involves oxidizing this mixture with nitric
acid to produce adipic acid. N2O is generated as a by-product
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From Nitric Acid Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Nitric Acid Production
N,0
15.7
13.2
18.5
-16%
+18%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-61: N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
15.2
17.2
6.0
4.9
5.9
6.2
5.7
6.0
Gg
49
56
19
16
19
20
19
19
of the nitric acid oxidation stage and is emitted in the waste
gas stream (Thiemens and Trogler 1991). Process emissions
from the production of adipic acid vary with the types of
technologies and level of emission controls employed by a
facility. In 1990, two of the three major adipic acid-producing
plants had N2O abatement technologies in place and, as of
1998, the three major adipic acid production facilities had
control systems in place." Only one small plant, representing
approximately two percent of production, does not control
for N2O (Reimer 1999).
N2O emissions from adipic acid production were
estimated to be 6.0 Tg CO2 Eq. (19 Gg) in 2005 (see Table
4-61). National adipic acid production has increased by
approximately 42 percent over the period of 1990 through
2005, to approximately one million metric tons. At the same
time, emissions have been reduced by 61 percent due to the
widespread installation of pollution control measures.
Methodology
For two production plants, 1990 to 2002 emission
estimates were obtained directly from the plant engineer
and account for reductions due to control systems in place at
these plants during the time series (Childs 2002,2003). These
estimates were based on continuous emissions monitoring
equipment installed at the two facilities. Reported estimates
for 2003, 2004, and 2005 were unavailable and thus were
calculated by applying 4.4, 4.2 and 4.2 percent production
growth rates, respectively. The production for 2003 was
obtained through linear interpolation between 2002 and
2004 reported national production data. Subsequently, the
growth rate for 2004 and 2005 was based on the change
between the estimated 2003 production data and the reported
2004 production data (see discussion below on sources of
production data). For the other two plants, N2O emissions
were calculated by multiplying adipic acid production by
an emission factor (i.e., N2O emitted per unit of adipic acid
produced) and adjusting for the percentage of N2O released
as a result of plant-specific emission controls. On the basis
of experiments, the overall reaction stoichiometry for N2O
production in the preparation of adipic acid was estimated
at approximately 0.3 metric tons of N2O per metric ton
of product (Thiemens and Trogler 1991). Emissions are
estimated using the following equation:
\!
The "N2O destruction factor" represents the percentage
of N2O emissions that are destroyed by the installed abatement
technology. The "abatement system utility factor" represents
the percentage of time that the abatement equipment operates
during the annual production period. Overall, in the United
States, two of the plants employ catalytic destruction, one
plant employs thermal destruction, and the smallest plant
uses no N2O abatement equipment. The N2O abatement
system destruction factor is assumed to be 95 percent for
catalytic abatement and 98 percent for thermal abatement
(Reimer et al. 1999, Reimer 1999). For the one plant that uses
thermal destruction and for which no reported plant-specific
emissions are available, the abatement system utility factor
is assumed to be 98 percent.
For 1990 to 2003 and 2005, plant-specific production
data was estimated where direct emission measurements were
not available. In order to calculate plant-specific production
for the two plants, national adipic acid production was
allocated to the plant level using the ratio of their known
plant capacities to total national capacity for all U.S. plants.
The estimated plant production for the two plants was then
used for calculating emissions as described above. For 2004,
actual plant production data were obtained for these two
plants and used for emission calculations.
National adipic acid production data (see Table 4-62)
for 1990 through 2002 were obtained from the American
During 1997, the N2O emission controls installed by the third plant operated for approximately a quarter of the year.
Industrial Processes 4-41
-------
Table 4-62: Adipic Acid Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
735
830
925
835
921
961
1,002
1,044
Chemistry Council (ACC 2003). Production for 2003 was
estimated based on linear interpolation of 2002 and 2004
reported production. Production for 2004 was obtained from
Chemical Week, Product Focus: Adipic Acid (CW 2005).
Production for 2005 was calculated by applying a 4.2 percent
production growth rate to reported 2004 production. This
growth rate was based on the change between the estimated
2003 production and the reported 2004 production. The 4.2
percent production growth rate applied in this case is in
line with the expected growth in global adipic acid demand
of 3.2 percent per year from 2005 to 2010 (CW 2005).
Plant capacities for 1990 through 1994 were obtained from
Chemical and Engineering News, "Facts and Figures" and
"Production of Top 50 Chemicals" (C&EN 1992,1993,1994,
1995). Plant capacities for 1995 and 1996 were kept the same
as 1994 data. The 1997 plant capacities were taken from
Chemical Market Reporter "Chemical Profile: Adipic Acid"
(CMR 1998). The 1998 plant capacities for all four plants and
1999 plant capacities for three of the plants were obtained from
Chemical Week, Product Focus: Adipic Acid/Adiponitrile (CW
1999). Plant capacities for 2000 for three of the plants were
updated using Chemical Market Reporter, "Chemical Profile:
Adipic Acid" (CMR 2001). For 2001 through 2005, the plant
capacities for these three plants were kept the same as the year
2000 capacities. Plant capacity for 1999 to 2005 for the one
remaining plant was kept the same as 1998.
Uncertainty
The overall uncertainty associated with the 2005 N2O
emission estimate from adipic acid production was calculated
using the IPCC Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
N2O emissions included that of company specific production
data, industry wide estimated production growth rates,
emission factors for abated and unabated emissions, and
company-specific historical emissions estimates.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-63. N2O emissions from adipic
acid production were estimated to be between 3.2 and 8.8 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 46 percent below to 47 percent above
the 2005 emission estimate of 6.0 Tg CO2 Eq.
Planned Improvements
Improvement efforts will be focused on obtaining direct
measurement data from facilities. If they become available,
cross verification with top-down approaches will provide a
useful Tier-2-level QC check. Also, additional information
on the actual performance of the latest catalytic and thermal
abatement equipment at plants with continuous emission
monitoring may support the re-evaluation of current default
abatement values.
4.17. Substitution of Ozone Depleting
Substances (IPCC Source Category
2F)
Hydrofluorocarbons (HFCs) andperfluorocarbons (PFCs)
are used as alternatives to several classes of ozone-depleting
Table 4-63: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Adipic Acid Production
N?0
6.0
3.2
-46%
+47%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
substances (ODSs) that are being phased out under the terms
of the Montreal Protocol and the Clean Air Act Amendments
of 1990.'2 Ozone depleting substances—chlorofluorocarbons
(CFCs), halons, carbon tetrachloride, methyl chloroform, and
hydrochlorofluorocarbons (HCFCs) —are used in a variety
of industrial applications including refrigeration and air
conditioning equipment, solvent cleaning, foam production,
sterilization, fire extinguishing, and aerosols. Although HFCs
and PFCs, are not harmful to the stratospheric ozone layer,
they are potent greenhouse gases. Emission estimates for
HFCs and PFCs used as substitutes for ODSs are provided
in Table 4-64 and Table 4-65.
In 1990 and 1991, the only significant emissions of
HFCs and PFCs as substitutes to ODSs were relatively small
amounts of HFC-152a—a component of the refrigerant blend
R-500 used in chillers —and HFC-134a in refrigeration end-
uses. Beginning in 1992, HFC-134a was used in growing
amounts as a refrigerant in motor vehicle air-conditioners
and in refrigerant blends such as R-404A.13 In 1993, the use
of HFCs in foam production and as an aerosol propellant
began, and in 1994 these compounds also found applications
as solvents and sterilants. In 1995, ODS substitutes for
halons entered widespread use in the United States as halon
production was phased-out.
The use and subsequent emissions of HFCs and PFCs
as ODS substitutes has been increasing from small amounts
in 1990 to 123.3 Tg CO2 Eq. in 2005. This increase was in
large part the result of efforts to phase out CFCs and other
ODSs in the United States. In the short term, this trend is
expected to continue, and will likely accelerate over the next
decade as HCFCs, which are interim substitutes in many
applications, are themselves phased-out under the provisions
of the Copenhagen Amendments to the Montreal Protocol.
Improvements in the technologies associated with the use
Table 4-64: Emissions of HFCs and PFCs from ODS Substitutes (Tg C02 Eq.)
Gas
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-1433
HFC-236fa
CF4
Others*
Total
1990 1995
+ +
+ +
+ 3.5
+ 26.0
+ 0.9
+ 0.2
+ +
0.3 1.6
0.3 32.2
2000
+
0.3
11.2
56.3
8.3
0.7
+
4.2
80.9
2001
+
0.3
12.4
60.7
10.3
0.8
+
4.0
88.6
2002
+
0.4
13.7
64.7
12.7
0.8
+
4.5
96.9
2003
+
0.4
15.4
68.3
15.4
0.9
+
5.1
105.5
2004
+
0.5
17.3
71.8
18.4
1.0
+
5.4
114.5
2005
+
0.6
19.8
74.0
22.1
1.0
+
5.7
123.3
+ Does not exceed 0.05 Tg C02 Eq.
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and
perfluoropolyethers (PFPEs) employed for solvent applications. For estimating purposes, the GWP value used for PFC/PFPEs was based upon C6F14.
Note: Totals may not sum due to independent rounding.
Table 4-65: Emissions of HFCs and PFCs from ODS Substitution (Mg)
Gas
HFC-23
HFC-32
HFC-125
HFC-1343
HFC-1433
HFC-236f3
CF4
Others*
1990 1995
+ +
+ +
+ 1,267
+ 19,999
+ 228
+ 36
+ +
M M
2000
1
465
3,983
43,274
2,193
110
1
M
2001
2
498
4,423
46,677
2,723
123
1
M
2002
2
558
4,901
49,774
3,338
135
1
M
2003
2
645
5,484
52,521
4,045
145
1
M
2004
3
762
6,177
55,265
4,847
155
1
M
2005
3
963
7,065
56,943
5,822
163
2
M
M (Mixture of Gases)
+ Does not exceed 0.5 Mg
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, C4F10, and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and
perfluoropolyethers (PFPEs) employed for solvent applications.
I2[42U.S.C§7671.CAA§601|
13 R-404A contains HFC-125, HFC-143a, and HFC-134a.
industrial Processes 4-43
-------
of these gases and the introduction of alternative gases and
technologies, however, may help to offset this anticipated
increase in emissions.
The end-use sectors that contribute the most toward
emissions of HFCs and PFCs as ODS substitutes include
refrigeration and air-conditioning (107.8 Tg CO2 Eq., or
approximately 87 percent), aerosols (11.3 Tg CO2 Eq., or
approximately 9 percent), and solvents (1.6 Tg CO2 Eq., or
approximately 1 percent). Within the refrigeration and air-
conditioning end-use sector, motor vehicle air-conditioning
was the highest emitting end-use (53.1 Tg CO2 Eq.), followed
by retail food and refrigerated transport. In the aerosols end-
use sector, non-metered-dose inhaler (MDI) emissions make
up a majority of the end-use sector emissions.
Methodology
A detailed Vintaging Model of ODS-containing
equipment and products was used to estimate the actual —
versus potential —emissions of various ODS substitutes,
including HFCs and PFCs. The name of the model refers to
the fact that the model tracks the use and emissions of various
compounds for the annual "vintages" of new equipment
that enter service in each end-use. This Vintaging Model
predicts ODS and ODS substitute use in the United States
based on modeled estimates of the quantity of equipment
or products sold each year containing these chemicals and
the amount of the chemical required to manufacture and/or
maintain equipment and products over time. Emissions for
each end-use were estimated by applying annual leak rates
and release profiles, which account for the lag in emissions
from equipment as they leak over time. By aggregating the
data for more than 50 different end-uses, the model produces
estimates of annual use and emissions of each compound.
Further information on the Vintaging Model is contained in
Annex 3.8.
Uncertainty
Given that emissions of ODS substitutes occur from
thousands of different kinds of equipment and from millions
of point and mobile sources throughout the United States,
emission estimates must be made using analytical tools
such as the Vintaging Model or the methods outlined in
IPCC/UNEP/OECD/IEA (1997). Though the model is
more comprehensive than the IPCC default methodology,
significant uncertainties still exist with regard to the levels
of equipment sales, equipment characteristics, and end-
use emissions profiles that were used to estimate annual
emissions for the various compounds.
The Vintaging Model estimates emissions from over 50
end-uses. The uncertainty analysis, however, quantifies the
level of uncertainty associated with the aggregate emissions
resulting from the top 16 end-uses and 5 others. In an effort
to improve the uncertainty analysis, additional end-uses are
added annually, with the intention that over time uncertainty
for all emissions from the Vintaging Model will be fully
characterized. This year, one new end-use was included
in the uncertainty estimate—fire extinguishing streaming
agents. Any end-uses included in previous years' uncertainty
analysis were included in the current uncertainty analysis,
whether or not those end-uses were included in the top 95
percent of emissions from ODS Substitutes.
In order to calculate uncertainty, functional forms were
developed to simplify some of the complex "vintaging"
aspects of some end-use sectors, especially with respect to
refrigeration and air-conditioning, and to a lesser degree,
fire extinguishing. These sectors calculate emissions based
on the entire lifetime of equipment, not just equipment put
into commission in the current year, thereby necessitating
simplifying equations. The functional forms used variables that
included growth rates, emission factors, transition from ODSs,
change in charge size as a result of the transition, disposal
quantities, disposal emission rates, and either stock for the
current year or original ODS consumption. Uncertainty was
estimated around each variable within the functional forms
based on expert judgment, and a Monte Carlo analysis was
performed. The most significant sources of uncertainty for
this source category include the emission factors for mobile
air-conditioning and retail food refrigeration, as well as the
stock (MT) of retail food refrigerant.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-66. Substitution of
Ozone Depleting Substances HFC and PFC emissions were
estimated to be between 112.7 and 148.6 Tg CO2 Eq. at
the 95 percent confidence level (or in 19 out of 20 Monte
Carlo Stochastic Simulations). This indicates a range of
approximately 9 percent below to 20 percent above the
emission estimate of 123.3 Tg CO2 Eq.
4-44 inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-66: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gases (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eg.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Substitution of Ozone MFCs and
Depleting Substances PFCs 123.3
112.7
148.6
+20%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
An extensive review of the chemical substitution trends,
market sizes, growth rates, and charge sizes, together with
input from industry representatives, resulted in updated
assumptions for the Vintaging Model. These changes resulted
in an average annual net increase of 7.6 Tg CO2 Eq. (21
percent) in HFC and PFC emissions from the substitution
of ozone depleting substances for the period 1990 through
2004.
4,18 HCFC-22 Production (IPCC
Source Category 2E1)
Trifluoromethane (HFC-23 or CHF3) is generated as a
by-product during the manufacture of chlorodifluoromethane
(HCFC-22), which is primarily employed in refrigeration
and air conditioning systems and as a chemical feedstock
for manufacturing synthetic polymers. Between 1990 and
2000, U.S. production of HCFC-22 increased significantly
as HCFC-22 replaced chlorofluorocarbons (CFCs) in many
applications. Since 2000, U.S. production has fluctuated.
Because HCFC-22 depletes stratospheric ozone, its
production for non-feedstock uses is scheduled to be phased
out by 2020 under the U.S. Clean Air Act.14 Feedstock
production, however, is permitted to continue indefinitely.
HCFC-22 is produced by the reaction of chloroform
(CHC13) and hydrogen fluoride (HF) in the presence of a
catalyst, SbQ5. The reaction of the catalyst and HF produces
SbClxFv, (where x + y = 5), which reacts with chlorinated
hydrocarbons to replace chlorine atoms with fluorine.
The HF and chloroform are introduced by submerged
piping into a continuous-flow reactor that contains the
catalyst in a hydrocarbon mixture of chloroform and
partially fluorinated intermediates. The vapors leaving the
reactor contain HCFC-21 (CHC12F), HCFC-22 (CHC1F2),
HFC-23 (CHF3), HC1, chloroform, and HF. The under-
fluorinated intermediates (HCFC-21) and chloroform are
then condensed and returned to the reactor, along with
residual catalyst, to undergo further fluorination. The final
vapors leaving the condenser are primarily HCFC-22,
HFC-23, HC1 and residual HF. The HC1 is recovered as a
useful byproduct, and the HF is removed. Once separated
from HCFC-22, the HFC-23 is generally vented to the
atmosphere as an unwanted by-product, but it is sometimes
captured for use in a limited number of applications.
Emissions of HFC-23 in 2005 were estimated to be 16.5
Tg CO2 Eq. (1.3 Gg) (Table 4-67). This quantity represents
a 6 percent increase from 2004 emissions and a 53 percent
decline from 1990 emissions. The increase in 2005 emissions
is due primarily to a slight increases in the HFC-23 emission
rate (i.e., the amount of HFC-23 emitted per kilogram of
HCFC-22 manufactured), while the decline from 1990
emissions is primarily due to the large decline in the HFC-
23 emission rate between 1990 and 2005. Three HCFC-22
production plants operated in the United States in 2005, two
of which used thermal oxidation to significantly lower their
HFC-23 emissions.
Table 4-67: HFC-23 Emissions from HCFC-22
Production (Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eg.
35.0
27.0
29.8
19.8
19.8
12.3
15.6
16.5
Qg
3
2
3
2
2
1
1
1
14 As construed, interpreted, and applied in the terms and conditions of the Montreal Protocol on Substances that Deplete the Ozone Layer. [42 U.S.C.
§7671m(b),CAA§614]
industrial Processes 4-4E
-------
Methodology
The methodology employed for estimating emissions is
based upon measurements at individual HCFC-22 production
plants. Plants using thermal oxidation to abate their HFC-
23 emissions monitor the performance of their oxidizers to
verify that the HFC-23 is almost completely destroyed. The
other plants periodically measure HFC-23 concentrations
in the output stream using gas chromatography. This
information is combined with information on quantities of
critical feed components (e.g., HF) and/or products (HCFC-
22) to estimate HFC-23 emissions using a material balance
approach. HFC-23 concentrations are determined at the point
the gas leaves the chemical reactor; therefore, estimates also
include fugitive emissions.
Production data and emission estimates were prepared in
cooperation with the U.S. manufacturers of HCFC-22 (ARAP
1997,1999,2000,2001,2002,2003,2004,2005,2006; RTI
1997). Annual estimates of U.S. HCFC-22 production are
presented in Table 4-68.
Table 4-68: HCFC-22 Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
139
155
187
152
144
138
155
156
Uncertainty
A high level of confidence has been attributed to the
HFC-23 concentration data employed because measurements
were conducted frequently and accounted for day-to-day
and process variability. The results of the Tier 1 quantitative
uncertainly analysis are summarized in Table 4-69. HFC-
23 emissions from HCFC-22 production were estimated
to be between 14.9 and 18.2 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of 10 percent above
and 10 percent below the 2005 emission estimate of 16.5
TgC02Eq.
4.19. Electrical Transmission arid
Distribution (IPCC Source Category
2F7)
The largest use of SF6, both in the United States and
internationally, is as an electrical insulator and interrupter in
equipment that transmits and distributes electricity (RAND
2004) The gas has been employed by the electric power
industry in the United States since the 1950s because of its
dielectric strength and arc-quenching characteristics. It is
used in gas-insulated substations, circuit breakers, and other
switchgear. Sulfur hexafluoride has replaced flammable
insulating oils in many applications and allows for more
compact substations in dense urban areas.
Fugitive emissions of SF6 can escape from gas-insulated
substations and switch gear through seals, especially from
older equipment. The gas can also be released during
equipment manufacturing, installation, servicing, and
Table 4-69: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eg.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
HCFC-22 Production
HFC-23
16.5
14.9
18.2
-10%
+10%
1 Range of emission estimates predicted by Monte'Carlo Stochastic Simulation for a 95 percent confidence interval.
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-70: SF6 Emissions from Electric Power Systems
and Electrical Equipment Manufactures (Tg C02 Eq.)
Electric Power Electrical Equipment
Year Systems Manufacturers Total
1990
1995
2000
2001
2002
2003
2004
2005
26.8
21.3
14.5
14.4
13.7
13.2
12.9
12.5
0.3
0.5
0.7
0.7
0.7
0.7
0.7
0.7
27.1
21.8
15.2
15.1
14.3
13.8
13.6
13.2
Table 4-71: SF6 Emissions from Electric Power Systems
and Electrical Equipment Manufactures (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Emissions
1.1
0.9
0.6
0.6
0.6
0.6
0.6
0.6
disposal. Emissions of SF6 from equipment manufacturing
and from electrical transmission and distribution systems
were estimated to be 13.2 Tg CO2 Eq. (0.6 Gg) in 2005.
This quantity represents a 51 percent decrease from the
estimate for 1990 (see Table 4-70 and Table 4-71). This
decrease is believed to be a response to increases in the price
of SF6 during the 1990s and to growing awareness of the
environmental impact of SF6 emissions, through programs
such as the EPA's SF6 Emission Reduction Partnership for
Electric Power Systems.
Methodology
The estimates of emissions from electric transmission
and distribution are comprised of emissions from electric
power systems and emissions from the manufacture of
electrical equipment. The methodologies for estimating both
sets of emissions are described below.
1999 tc 2005 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to
2005 were estimated based on: (1) reporting from utilities
participating in EPA's SF6 Emission Reduction Partnership
for Electric Power Systems (partners), which began in
1999; and, (2) utilities' transmission miles as reported in the
2001 and 2004 Utility Data Institute (UDI) Directories of
Electric Power Producers and Distributors (UDI 2001,2004).
(Transmission miles are defined as the miles of lines carrying
voltages above 34.5 kV.) Over the period from 1999 to 2005,
participating utilities represented between 31 percent and 39
percent of total U.S. transmission miles. For each year, the
emissions reported by participating utilities were added to
the emissions estimated for utilities that do not participate
in the Partnership (i.e., non-partners).
Emissions from partner utilities were estimated using
a combination of reported data and, where reported data
were unavailable, interpolated or extrapolated data. If a
partner utility did not provide data for a historical year,
emissions were interpolated between years for which data
were available. For 2005, if no data was provided, estimates
were calculated based on historical trends or partner-specific
emission reduction targets (i.e., emissions were assumed to
decline linearly toward a partners' future stated goal). In
2005, non-reporting partners account for approximately 2
percent of the total emissions attributable to utilities involved
in the SF6 Emission Reduction Partnership.
Emissions from non-partners in every year since 1999
were estimated using the results of a regression analysis
that showed that the emissions of reporting utilities were
most strongly correlated with their transmission miles. The
results of this analysis are not surprising given that, in the
United States, SF6 is contained primarily in transmission
equipment rated at or above 34.5 kV. The equations were
developed based on the 1999 SF6 emissions reported by 49
partner utilities (representing approximately 31 percent of
U.S. transmission miles), and 2000 transmission mileage
data obtained from the 2001 UDI Directory of Electric Power
Producers and Distributors (UDI 2001). Two equations were
developed, one for small and one for large utilities (i.e., with
less or more than 10,000 transmission miles, respectively).
The distinction between utility sizes was made because the
regression analysis showed that the relationship between
emissions and transmission miles differed for small and
large transmission networks. The same equations were
used to estimate non-partner emissions in 1999 and every
year thereafter because non-partners were assumed not to
Industrial Processes 4-4?
-------
have implemented any changes that would have resulted in
reduced emissions since 1999.
The regression equations are:
Non-partner small utilities (less than 10.000 trunMiiission
miles, in kilograms i:
Emissions (kg) = O.S74 x Transmission Miles
Non-partner large utilities (mere than 10,000 transmission
miles, in kilograms):
Emissions (kg) = 0.558 x Transmission Miles
Data on transmission miles for each non-partner utility
for the years 2000 and 2003 were obtained from the 2001
and 2004 UDI Directories of Electric Power Producers and
Distributors, respectively (UDI 2001,2004). Given that the
U.S. transmission system grew by over 14,000 miles between
2000 and 2003, and that this increase probably occurred
gradually, transmission mileage was assumed to increase
exponentially at an annual rate of 0.7 percent between 2000
and 2003. This growth rate is assumed to have continued
through 2005.
As a final step, total emissions were determined for
each year by summing the partner emissions (reported to
the EPA's SF6 Emission Reduction Partnership for Electric
Power Systems), and the non-partner emissions (determined
using the 1999 regression equation).
1990 to 1998 Emissions from Electric Power Systems
Because most participating utilities reported emissions
only for 1999 through 2005, it was necessary to model SF6
emissions from electric power systems for the years 1990
through 1998. To do so, it was assumed that U.S. emissions
followed the same trajectory as global emissions from this
source during the 1990 to 1998 period. To estimate global
emissions, the RAND survey of global SF6 sales were used,
together with the following equation, which is derived from
the mass-balance equation for chemical emissions (Volume
3, Equation 7.3) in the IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). (Although
equation 7.3 of the IPCC Guidelines appears in the discussion
of substitutes for ozone-depleting substances, it is applicable
to emissions from any long-lived pressurized equipment that
is periodically serviced during its lifetime.)
Emissions (kilograms i -; Sl;,, purchased > rel 1! existing
equipment (kilograms) + naiteplate eao.icity ol retir IK:
equipment (kilograms
Note that the above equation holds whether the gas
from retiring equipment is released or recaptured; if the
gas is recaptured, it is used to refill existing equipment,
thereby lowering the amount of SF6 purchased by utilities
for this purpose.
Sulfur hexafluoride purchased to refill existing equipment
in a given year was assumed to be approximately equal to
the SF6 purchased by utilities in that year. Gas purchases by
utilities and equipment manufacturers from 1961 through
2003 are available from the RAND (2004) survey. 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 81.2 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 81.2 percent of
the gas purchased in 1960). The remaining 18.8 percent was
assumed to have been emitted at the time of manufacture. The
18.8 percent emission factor is an average ol'IPCC default SF6
emission rates for Europe and Japan for 1995 (IPCC 2006).
The 40-year lifetime for electrical equipment is also based on
IPCC (2006). The results of the two components of the above
equation were then summed to yield estimates of global SF6
emissions from 1990 through 1998.
U.S. emissions between 1990 and 1998 are assumed to
follow the same trajectory as global emissions during this
period. To estimate U.S. emissions, global emissions for each
year from 1990 through 1998 were divided by the estimated
global emissions from 1999. The result was a time series of
factors that express each year's global emissions as a multiple
of 1999 global emissions. Historical U.S. emissions were
estimated by multiplying the factor for each respective year
by the estimated U.S. emissions of SF6 from electric power
systems in 1999 (estimated to be 15.3 Tg CO2 Eq.).
Two factors may affect the relationship between the
RAND sales trends and actual global emission trends. One is
utilities' inventories of SF6 in storage containers. When SF6
prices rise, utilities are likely to deplete internal inventories
before purchasing new SF6 at the higher price, in which case
SF6 sales will fall more quickly than emissions. On the other
hand, when SF6 prices fall, utilities are likely to purchase
more SF6 to rebuild inventories, in which case sales will
rise more quickly than emissions. This effect was accounted
for by applying 3-year smoothing to utility SF6 sales data.
The other factor that may affect the relationship between
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
the RAND sales trends and actual global emissions is the
level of imports from and exports to Russia and China. SF6
production in these countries is not included in the RAND
survey, but may have been significant during the 1990
through 1999 period. This factor was not accounted for;
however, atmospheric studies confirmed that the downward
trend in the estimated global emissions between 1995 and
1998 was real (see the Uncertainty discussion below).
1990 to 2005 Emissions from Manufacture of Electrical
Equipment
The 1990 to 2005 emissions estimates for original
equipment manufacturers (OEMs) were derived by assuming
that manufacturing emissions equal 10 percent of the
quantity of SF6 charged into new equipment. The quantity
of SF6 charged into new equipment was estimated based on
statistics compiled by the National Electrical Manufacturers
Association (NEMA). These statistics were provided for 1990
to 2000; the quantities of SF6 charged into new equipment
for 2001 to 2005 were assumed to equal that charged into
equipment in 2000. The 10 percent emission rate is the
average of the "ideal" and "realistic" manufacturing emission
rates (4 percent and 17 percent, respectively) identified in
a paper prepared under the auspices of the International
Council on Large Electric Systems (CIGRE) in February
2002 (O'Connell et al. 2002).
Uncertainty
To estimate the uncertainty associated with emissions of
SF6 from electric transmission and distribution, uncertainties
associated with three variables were estimated: (1) emissions
from partners, (2) emissions from non-partners, and (3)
emissions from manufacturers of electrical equipment. A
Monte Carlo analysis was then applied to estimate the overall
uncertainty of the emissions estimate.
Total emissions from the SF6 Emission Reduction
Partnership include emissions from both reporting and non-
reporting partners. For reporting partners, individual partner-
reported SF6 data was assumed to have an uncertainty of 10
percent. Based on a Monte Carlo analysis, the cumulative
uncertainty of all partner reported data was estimated to be
4.9 percent. The uncertainty associated with extrapolated
or interpolated emissions from non-reporting partners was
assumed to be 20 percent.
There are two sources of uncertainty associated with
the regression equations used to estimate emissions in
2005 from non-partners: (1) uncertainty in the coefficients
(as defined by the regression standard error estimate), and
(2) the uncertainty in total transmission miles for non-
partners. In addition, there is uncertainty associated with
the assumption that the emission factor used for non-partner
utilities (which accounted for approximately 61 percent of
U.S. transmission miles) will remain at levels defined by
partners who reported in 1999. However, the last source of
uncertainty was not modeled.
Uncertainties were also estimated regarding the quantity
of SF6 charged into equipment by equipment manufacturers,
which is projected from 2000 data from NEMA, and the
manufacturers' SF6 emissions rate.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-72. Electrical Transmission and
Distribution SF6 emissions were estimated to be between 12.4
and 14.1 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 6 percent below and 7
percent above the emission estimate of 13.2 Tg CO2 Eq.
In addition to the uncertainty quantified above, there
is uncertainty associated with using global SF6 sales data
to estimate U.S. emission trends from 1990 through 1999.
However, the trend in global emissions implied by sales of
Table 4-72: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to 2005 Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Electrical Transmission
and Distribution SFB
13.2
12.4
14.1
+7%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
industrial Processes 4 49
-------
SF6 appears to reflect the trend in global emissions implied
by changing SF6 concentrations in the atmosphere. That
is, emissions based on global sales declined by 29 percent
between 1995 and 1998, and emissions based on atmospheric
measurements declined by 27 percent over the same period.
However, U.S. emission patterns may differ from global
emission patterns.
Recalculations Discussion
Relative to the previous Inventory report, SF6 emission
estimates for the period 1990 through 2004 were updated
based on (1) new data from EPA's SF6 Emission Reduction
Partnership, and (2) revisions to the assumptions used in
estimating global emissions between 1990 and 1999. For the
period 1999 through 2004, estimates have been revised to
incorporate additional data from new partners. For the period
1990 through 1998, estimates have been revised by updating
the estimated lifetime of electrical equipment and the estimated
historical emission rate during equipment manufacturing.
Previously, it was assumed that the equipment lifetime was
30 years, and that during manufacture 22.5 percent of the SF6
purchased by equipment manufacturers was emitted. These
variables have been revised to 40 years and 18.8 percent,
respectively, to reflect new data presented in IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC 2006). Based
on these revisions, SF6 emissions from electric transmission
and distribution have decreased by approximately 1 percent for
each year during the 1999 to 2004 period. Between 1990 and
1998, estimates have changed between -16 percent (decrease)
to +5 percent (increase) depending on the specific year, relative
to the previous report.
4.20. Semiconductor Manufacture
(IPCC Source Category 2F6)
The semiconductor industry uses multiple long-lived
fluorinated gases in plasma etching and plasma enhanced
chemical vapor deposition (PECVD) processes to produce
semiconductor products. The gases most commonly employed
are trifluoromethane (HFC-23 or CHF3), perfluoromethane
(CF4), perfluoroethane (C2F6), nitrogen trifluoride (NF3),
and sulfur hexafluoride (SF6), although other compounds
such as perfluoropropane (C3F8) and perfluorocyclobutane
(c-C4F8) are also used. The exact combination of compounds
is specific to the process employed.
A single 300 mm silicon wafer that yields between
400 to 500 semiconductor products (devices or chips)
may require as many as 100 distinct fluorinated-gas-using
process steps, principally to deposit and pattern dielectric
films. Plasma etching (or patterning) of dielectric films,
such as silicon dioxide and silicon nitride, is performed
to provide pathways for conducting material to connect
individual circuit components in each device. The
patterning process uses plasma-generated fluorine atoms,
which chemically react with exposed dielectric film, to
selectively remove the desired portions of the film. The
material removed as well as undissociated fluorinated gases
flow into waste streams and, unless emission abatement
systems are employed, into the atmosphere. PECVD
chambers, used for depositing dielectric films, are cleaned
periodically using fluorinated and other gases. During the
cleaning cycle the gas is converted to fluorine atoms in
plasma, which etches away residual material from chamber
walls, electrodes, and chamber hardware. Undissociated
fluorinated gases and other products pass from the chamber
to waste streams and, unless abatement systems are
employed, into the atmosphere. In addition to emissions
of unreacted gases, some fluorinated compounds can also
be transformed in the plasma processes into different
fluorinated compounds which are then exhausted, unless
abated, into the atmosphere. For example, when C2F6 is
used in cleaning or etching, CF4 is generated and emitted
as a process by-product. Besides dielectric film etching
and PECVD chamber cleaning, much smaller quantities
of fluorinated gases are used to etch polysilicon films and
refractory metal films like tungsten.
For 2005, total weighted emissions of all fluorinated
greenhouse gases by the U.S. semiconductor industry were
estimated to be 4.3 Tg CO2 Eq. Combined emissions of all
fluorinated greenhouse gases are presented in Table 4-73 and
Table 4-74. The rapid growth of this industry and the increasing
complexity (growing number of layers) of semiconductor
products led to an increase in emissions of 147 percent between
1990 and 1999. The emissions growth rate began to slow
after 1997, and emissions declined by 41 percent between
1999 and 2005. The initial implementation of PFC emission
reduction methods such as process optimization and abatement
technologies is responsible for this decline. Together, these
two trends resulted in a net increase in emissions of 47 percent
between 1990 and 2005.
4-50 inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 4-73: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.)
Gas
CF4
C2F6
63^8
C4F8
HFC-23
SF6
NF3*
Total
1990
0.7
1.5
0.0
0.0
0.2
0.5
0.0
2.9
1995
1.3
2.5
+
+
0.3
0.9
0.1
5.0
2000
1.8
3.0
0.1
0.0
0.3
1.1
0.1
6.3
2001
1.3
2.1
0.1
0.0
0.2
0.8
0.1
4.5
2002
1.1
2.2
0.1
0.0
0.2
0.7
0.3
4.4
2003
1.0
2.1
0.1
0.1
0.2
0.8
0.2
4.3
2004
1.2
2.2
0.0
0.1
0.2
0.9
0.3
4.7
2005
1.1
1.9
0.0
0.1
0.2
1.0
0.2
4.3
Note: Totals may not sum due to independent rounding.
* NF3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.
+ Does not exceed 0.05 Tg C02 Eq.
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)
Gas
CF4
C2F6
C3F8
C4F8
HFC-23
SF6
NF3
1990
115
160
0
0
15
22
3
1995
192
272
0
0
26
38
6
2000
281
324
17
0
23
46
11
2001
202
231
14
0
16
31
12
2002
175
244
9
5
15
28
32
2003
161
228
13
8
17
35
30
2004
185
245
6
9
20
38
31
2005
163
211
4
13
18
40
27
Methodology
Emissions from semiconductor manufacturing were
estimated using three distinct methods, one each for the
periods 1990 through 1994,1995 through 1999, and 2000 and
beyond. For 1990 through 1994, emissions were estimated
using the most recent version of EPA's PFC Emissions
Vintage Model (PEVM) (Burton and Beizaie 2001).l5 PFC
emissions per square centimeter of silicon increase as the
number of layers in semiconductor devices increases. Thus,
PEVM incorporates information on the two attributes of
semiconductor devices that affect the number of layers: (1)
linewidth technology (the smallest feature size, which leads
to an increasing number of layers),16 and (2) product type
(memory vs. logic).17 PEVM derives historical consumption
of silicon (i.e., square centimeters) by linewidth technology
from published data on annual wafer starts and average
wafer size (Burton and Beizaie 2001). For each linewidth
technology, a weighted average number of layers is estimated
using VLSI product-specific worldwide silicon demand data
in conjunction with complexity factors (i.e., the number
of layers per integrated circuit) specific to product type
(Burton and Beizaie 2001, ITRS 2005). The distribution of
memory/logic devices ranges over the period covered from
52 percent logic devices in 1995 to 59 percent logic devices
in 2000. These figures were used to determine emission
factors that express emissions per average layer per unit
of area of silicon consumed during product manufacture.
The per-layer emission factor was based on the total annual
emissions reported by participants in EPA's PFC Reduction/
Climate Partnership for the Semiconductor Industry in 1995
and later years.
For 1995 through 1999, total U.S. emissions were
extrapolated from the total annual emissions reported by the
Partnership participants (2005 Aggregate PFC Emissions
" The most recent version of this model is v.3.2.0506.0507, completed in September 2005.
16 By decreasing features of integrated circuit components, more components can be manufactured per device, which increases its functionality.
However, as those individual components shrink it requires more layers to interconnect them to achieve the functionality. For example, a
microprocessor manufactured with the smallest feature sizes (65 nm) might contain as many as 1 billion transistors and requires as many as 11 layers
of component interconnects to achieve functionality while a device manufactured with 130 nm feature size might contain a few hundred million
transistors and require 8 layers of component interconnects (ITRS. 2005).
17 Memory devices manufactured with the same feature sizes as microprocessors (a logic device) require approximately one-half the number of
interconnect layers (ITRS. 2005).
Industrial Processes 4-51
-------
provided to EPA by Latham & Watkins). The emissions
reported by the participants were divided by the ratio of
the total layer-weighted capacity of the plants operated by
the participants and the total layer-weighted capacity of all
of the semiconductor plants in the United States; this ratio
represents the share of layer-weighted capacity attributable
to partnership participants. The layer-weighted capacity of
a plant (or group of plants) consists of the silicon capacity
of that plant multiplied by the estimated number of layers
used to fabricate products at that plant. This method assumes
that participants and non-participants have similar capacity
utilizations and per-layer emission factors. Plant capacity,
linewidth technology, products manufactured information
is contained in the World Fab Watch (WFW) database,
which is updated quarterly (see for example, Semiconductor
Equipment and Materials Industry 2006).
The U.S. estimate for the years 2000 through 2005—the
period during which partners began the consequential
application of PFC-reduction measures —was based on a
different estimation method. The emissions reported by
Partnership participants for each year were accepted as the
quantity emitted from the share of the industry represented
by those Partners. Remaining emissions (those from non-
partners), however, were estimated using PEVM and the
method described above. (Non-partners are assumed not to
have implemented any PFC-reduction measures, and PEVM
models emissions without such measures.) The portion
of the U.S. total attributed to non-Partners is obtained by
multiplying PEVM's total U.S. figure by the non-partner
share of total layer-weighted silicon capacity for each year (as
described above). Annual updates to PEVM reflect published
figures for actual silicon consumption from VLSI Research,
Inc. as well as revisions and additions to the world population
of semiconductor manufacturing plants (see Semiconductor
Equipment and Materials Industry 2006).18'19
Two different approaches were also used to estimate
the distribution of emissions of specific PFCs. Before 1999,
when there was no consequential adoption of PFC-reducing
measures, a fixed distribution was assumed to apply to the
entire U.S. industry. This distribution was based upon the
average PFC purchases by semiconductor manufacturers
during this period and the application of IPCC default
emission factors for each gas (Burton and Beizaie 2001).
For the 2000 through 2005 period, the 1990 through 1999
distribution was assumed to apply to the non-Partners.
Partners, however, began to report gas-specific emissions
during this period. Thus, gas specific emissions for 2000
through 2005 were estimated by adding the emissions
reported by the Partners to those estimated for the non-
Partners.20
Partners estimate their emissions using a range of
methods. For 2005, we assume that most partners used
a method as least as accurate as the IPCC's Tier 2c
Methodology, recommended in the IPCC (2000), since that
has been their approach for the past several years. However,
this is expected to change with publication of the updated
IPCC (2006). The partners with relatively high emissions
typically use the more accurate IPCC 2b or 2a methods,
multiplying estimates of their PFC consumption by process-
specific emission factors that they have either measured or
obtained from tool suppliers.
Data used to develop emission estimates were prepared
in cooperation with the Partnership. Estimates of operating
plant capacities and characteristics for participants and
non-participants were derived from the Semiconductor
Equipment and Materials Industry (SEMI) World Fab Watch
(formerly International Fabs on Disk) database (1996 to
2006). Estimates of silicon consumed by line-width from
1990 through 2005 were derived from information from
VLSI Research (2005), and the number of layers per line-
18 Special attention was given to the manufacturing capacity of plants that use wafers with 300 mm diameters because the actual capacity of these
plants in 2004 is below design capacity, the figure provided in WFW. To prevent overstating estimates of partner-capacity shares from plants using 300
mm wafers, design capacities contained in WFW were replaced with estimates of actual installed capacities for 2004 published by Citigroup Smith
Barney (2005). Without this correction, the partner share of capacity would be overstated, by approximately 5 percentage points. For perspective,
approximately 95 percent of all new capacity additions in 2004 used 300 mm wafers and by year-end those plants, on average, could operate at but
approximately 70 percent of the design capacity. For 2005. actual installed capacities was estimated using an entry in the World Fab Watch database
(April 2006 Edition) called "wafers/month, 8-inch equivalent, which denotes the actual installed capacity instead of the fully-ramped capacity.
19 In 2005, the trend in co-owernship of manufacturing facilities in the industry continued. Several manufacturers, who are partners, now operate fabs
with other manufacturers, who in some cases are also partners and in other cases not partners. Special attention was given to this occurrence when
estimating the partner and non-partner shares of U.S. layer-weighted manufacturing capacity.
20 In recent years, the Partnership started reporting gas-specific emissions using GWP values from the Third Assessment Report (TAR), while in
previous years the values were taken from the Second Assessment Report (SAR). The emissions reported here are restated using GWPs from the SAR.
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1900-2005
-------
width was obtained from International Technology Roadmap
for Semiconductors: 1998-2004 (Burton and Beizaie 2001,
ITRS 2005).
Uncertainty
A quantitative uncertainty analysis of this source
category was performed using the IPCC-recommended Tier
2 uncertainty estimation methodology, the Monte Carlo
Stochastic Simulation technique. The equation used to
estimate uncertainty is:
i'.S cnnxMoii-- - Pl-.YM i-stimak- i Partnership share ••
Pi-'X M ..'vi'ink': - Fanner-hip suhmilt.il
The Monte Carlo analysis results presented below relied
on estimates of uncertainty attributed to the three variables
on the right side of the equation. Estimates of uncertainty for
the three variables were in turn developed using the estimated
uncertainties associated with the individual inputs to each
variable, error propagation analysis, and expert judgment. For
the relative uncertainty associated with the PEVM estimate in
2005, an uncertainty of ±20 percent was estimated, using the
calculus of error propagation and considering the aggregate
average emission factor, world silicon consumption, and the
U.S. share of layer-weighted silicon capacity. For the share of
U.S. layer-weighted silicon capacity accounted for by Partners,
a relative uncertainty of+10 percent was estimated based on
information from the firm that compiled the World Fab Watch
database (SMA 2003). For the aggregate PFC emissions
data supplied to the partnership, a relative uncertainty of
approximately ±10 percent was estimated (representing a 95
percent confidence interval).
Consideration was also given to the nature and
magnitude of the potential bias that PEVM might have in
its estimates of the number of layers associated with devices
manufactured at each technology node. The result of a brief
analysis indicated that PEVM overstates the average number
of layers across all product categories and all manufacturing
technologies for 2004 by 0.12 layers or 2.9 percent. This bias
is represented in the uncertainty analysis by deducting the
absolute bias value from the PEVM emission estimate when
it is incorporated into the Monte Carlo analysis.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-75. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing
were estimated to be between 3.6 and 5.4 Tg CO2 Eq. at a 95
percent confidence level. This range represents 21 percent
below to 20 percent above the 2005 emission estimate of
4.3 Tg CO2 Eq. This range and the associated percentages
apply to the estimate of total emissions rather than those of
individual gases. Uncertainties associated with individual
gases will be somewhat higher than the aggregate, but were
not explicitly modeled.
Planned Improvements
The method to estimate non-partner-related emissions
(i.e., PEVM) is not expected to change (with the exception
of possible future updates to emission factors and added
technology nodes). Future improvements to the national
emission estimates will primarily be associated with
determining the portion of national emissions to attribute to
partner report totals (about 80 percent in recent years). As
the nature of the partner reports change through time and
industry-wide reduction efforts increase, consideration will
be given to what emission reduction efforts —if any —are
likely to be occurring at non-partner facilities. (Currently
none are assumed to occur.)
Table 4-75: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate3
Gases (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate11
(TgC02Eq.)
Semiconductor
Manufacture
HFC, PFC,
and SF6
4.3
Lower Bound
3.6
Upper Bound
5.4
Lower Bound
-21%
Upper Bound
+20%
3 Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match that shown in
Table 4-73.
b Range of emissions estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-53
-------
4.21. Aluminum Production (IPCC
Source Category 2C3)
Aluminum is a light-weight, malleable, and corrosion-
resistant metal that is used in many manufactured products,
including aircraft, automobiles, bicycles, and kitchen utensils.
In 2005, the United States was the fourth largest producer of
primary aluminum, with approximately eight percent of the
world total (USGS 2006). The United States was also a major
importer of primary aluminum. The production of primary
aluminum—in addition to consuming large quantities of
electricity— results in process-related emissions of CO2 and
two perfluorocarbons (PFCs): perfluoromethane (CF4) and
perfluoroethane (C2F6).
CO2 is emitted during the aluminum smelting process
when alumina (aluminum oxide, A12O3) is reduced to
aluminum using the Hall-Heroult reduction process. The
reduction of the alumina occurs through electrolysis in a
molten bath of natural or synthetic cryolite (Na3AlF6). The
reduction cells contain a C lining that serves as the cathode. C
is also contained in the anode, which can be a C mass of paste,
coke briquettes, or prebaked C blocks from petroleum coke.
During reduction, most of this C is oxidized and released to
the atmosphere as CO2.
Process emissions of CO2 from aluminum production
were estimated to be 4.2 Tg CO2 Eq. (4,208 Gg) in 2005
(see Table 4-76). The C anodes consumed during aluminum
production consist of petroleum coke and, to a minor extent,
coal tar pitch. The petroleum coke portion of the total CO2
process emissions from aluminum production is considered
to be a non-energy use of petroleum coke, and is accounted
for here and not under the CO2 from Fossil Fuel Combustion
source category of the Energy sector. Similarly, the coal tar
pitch portion of these CO2 process emissions is accounted
for here rather than in the Iron and Steel source category of
the Industrial Processes sector.
In addition to CO2 emissions, the aluminum production
industry is also a source of PFC emissions. During the
smelting process, when the alumina ore content of the
electrolytic bath falls below critical levels required for
electrolysis, rapid voltage increases occur, which are termed
"anode effects." These anode effects cause C from the anode
and fluorine from the dissociated molten cryolite bath to
combine, thereby producing fugitive emissions of CF4 and
C2F6. In general, the magnitude of emissions for a given
level of production depends on the frequency and duration
of these anode effects. As the frequency and duration of the
anode effects increase, emissions increase.
Since 1990, emissions of CF4 and C2F6 have both
declined by 84 percent to 2.5 Tg CO2 Eq. of CF4 (0.4 Gg) and
0.4 Tg CO2 Eq. of C2F6 (0.05 Gg) in 2005, as shown in Table
4-77 and Table 4-78. This decline is due both to reductions
in domestic aluminum production and to actions taken by
Table 4-77: PFC Emissions from Aluminum Production
(Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
CF4
15.9
10.2
7.8
3.0
4.6
3.3
2.4
2.5
C2F6
2.7
1.7
0.8
0.4
0.7
0.5
0.4
0.4
Total
18.5
11.8
8.6
3.5
5.2
3.8
2.8
3.0
Note: Totals may not sum due to independent rounding.
Table 4-76: C02 Emissions from Aluminum Production
(Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
6.8
5.7
6.1
4.4
4.5
4.5
4.2
4.2
Gg
6,831
5,659
6,086
4,381
4,490
4,503
4,231
4,208
Table 4-78: PFC Emissions from Aluminum Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
CF4
2.4
1.6
1.2
0.5
0.7
0.5
0.4
0.4
C2F6
0.3
0.2
0.1
+
0.1
0.1
+
+
+ Does not exceed 0.05 Gg
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1993-2005
-------
aluminum smelting companies to reduce the frequency and
duration of anode effects. Since 1990, aluminum production
has declined by 39 percent, while the average CF4 and C2F6
emission rates (per metric ton of aluminum produced) have
each been reduced by 74 percent.
In 2005, U.S. primary aluminum production totaled
approximately 2.5 million metric tons, similar to 2004
production levels. Due to high electric power costs in
various regions of the country, aluminum production has
been curtailed at several U.S. smelters, which resulted in
2005 production levels that were approximately 34 percent
lower than the levels in 1999, the year with the highest
production over the prior decade. 1995 through 2005.
The transportation industry remained the largest domestic
consumer of primary aluminum, accounting for about 39
percent of U.S. consumption (USGS 2006).
Methodology
CO2 emissions released during aluminum production
were estimated using the combined application of process-
specific emissions estimates modeling with individual
partner reported data. These estimates are achieved through
information gathered by EPA's Voluntary Aluminum
Industrial Partnership (VAIP) program.
Most of the CO2 emissions released during aluminum
production occur during the electrolysis reaction of the C
anode, as described by the following reaction.
.":.-\i < '• M --•> i M • i(.'(i.
For prebake smelter technologies, CO2 is also emitted
during the anode baking process. These emissions can
account for approximately 10 percent of total process CO2
emissions from prebake smelters. The CO^ emission factor
employed was estimated from the production of primary
aluminum metal and the C consumed by the process.
Emissions vary depending on the specific technology
used by each plant (e.g., prebake or S0derberg). CO2
process emissions were estimated using the methodology
recommended by IPCC (2006).
The prebake process specific formula recommended by
IPCC (2006) accounts for various parameters, including net C
consumption, and the sulfur, ash, and impurity content of the
baked anode. For anode baking emissions, process formulas
account for packing coke consumption, the sulfur and ash
content of the packing coke, as well as the pitch content and
weight of baked anodes produced. The S0derberg process
formula accounts for the weight of paste consumed per metric
ton of aluminum produced, and pitch properties, including
sulfur, hydrogen, and ash content.
Through the VAIP, process data have been reported
for 1990, 2000, 2003, 2004, and 2005. Where available,
smelter-specific process data reported under the VAIP were
used; however, if the data were incomplete or unavailable,
information was supplemented using industry average values
recommended by IPCC (2006). Smelter-specific CO2 process
data were provided by 1 8 of the 23 operating smelters in
1990 and 2000, by 14 out of 16 operating smelters in 2003
and 2004, and by 14 out of 15 operating smelters in 2005.
For years where CO2 process data were not reported by
these companies, estimates were developed through linear
interpolation, and/or assuming industry default values.
In the absence of any smelter-specific process data (i.e.,
1 out of 15 smelters in 2005, and 5 out of 23 between 1990
and 2003), CO2 emission estimates were estimated using
Tier 1 S0derberg and/or prebake emission factors (metric
ton of CO2 per metric ton of aluminum produced) from
IPCC (2006).
Aluminum production data for all operating smelters
were reported under the VAIP in 2005. Between 1990 and
2004, production data were provided by 21 of the 23 U.S.
smelters that operated during at least part of that period. For
the non-reporting smelters, production was estimated based
on the difference between reporting smelters and national
aluminum production levels (USAA 2006), with allocation
to specific smelters based on reported production capacities
(USGS 2002).
PFC emissions from aluminum production were
estimated using a per-unit production emission factor that
is expressed as a function of operating parameters (anode
effect frequency and duration), as follows:
PI •( '(('(•; <)i i \lv k;j nv.-mc ;..m Al •-
s » Allude i-.lTi.-cl Mmi!K-x'(V!i H.is
where,
Anode HTo.1
Minnies
Ci.-II-l);i\ - \node Hlcr! hvquencv.'C 'ell-Din
• \nudc! tli'ci I Jurulu-N iininuicx '
Industrial Processes 4-55
-------
Smelter-specific slope coefficients that are based on
field measurements yield the most accurate results. To
estimate emissions between 1990 and 2004, smelter-specific
coefficients were available and were used for 12 out of the 23
U.S. smelters that operated during at least part of that period.
To estimate 2005 emissions, smelter-specific coefficients
were available and were used for 5 out of the 15 operating
U.S. smelters, representing approximately 33 percent of
operating 2005 U.S. production capacity. For the remaining
10 operating smelters, technology-specific slope coefficients
from IPCC (2001) were applied. The slope coefficients were
combined with smelter-specific anode effect data collected
by aluminum companies and reported under the VAIP, to
estimate emission factors overtime. In 2005, smelter-specific
anode effect data were available for all operating smelters.
Where smelter-specific anode effect data were not available
(i.e., 2 out of 23 smelters between 1990 and 2004), industry
averages were used. For all smelters, emission factors were
multiplied by annual production to estimate annual emissions
at the smelter level. In 2005, smelter-specific production data
were available for all operating smelters. Between 1990 and
2004, production data has been provided by 21 of the 23 U.S.
smelters. Emissions were then aggregated across smelters
to estimate national emissions. The methodology used to
estimate emissions is consistent with the methodologies
recommended by IPCC (2006).
National primary aluminum production data for 1990
through 2001 (see Table 4-79) were obtained from USGS,
Mineral Industry Surveys: Aluminum Annual Report (USGS
1995, 1998, 2000, 2001, 2002). For 2002 through 2005,
national aluminum production data were obtained from the
United States Aluminum Association's Primary Aluminum
Statistics (USAA 2004, 2005, 2006).
Table 4-79: Production of Primary Aluminum (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
4,048
3,375
3,668
2,637
2,705
2,705
2,517
2,478
Uncertainty
The overall uncertainties associated with the 2005 CO2,
CF4, and C2F6 emission estimates were calculated using
Approach 2, as defined by IPCC (2006). For CO2, uncertainty
was assigned to each of the parameters used to estimate CO?
emissions. Uncertainty surrounding reported production data
was assumed to be 2 percent (IPCC 2006). For additional
variables, such as net C consumption, and sulfur and
ash content in baked anodes, estimates for uncertainties
associated with reported and default data were obtained
from IPCC (2006). A Monte Carlo analysis was applied to
estimate the overall uncertainty of the CO2 emission estimate
for the U.S. aluminum industry as a whole, and the results
are provided below.
To estimate the uncertainty associated with emissions
of CF4 and C2F6, the uncertainties associated with three
variables were estimated for each smelter: (1) the quantity of
aluminum produced, (2) the anode effect minutes per cell day
(which may be reported directly or calculated as the product
of anode effect frequency and anode effect duration), and
(3) the smelter- or technology-specific slope coefficient. A
Monte Carlo analysis was then applied to estimate the overall
uncertainty of the emission estimate for each smelter or
company and for the U.S. aluminum industry as a whole.
The results of this quantitative uncertainty analysis are
summarized in Table 4-80. Aluminum production-related
CO2 emissions were estimated to be between 4.0 and 4.4 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 5 percent below to 5 percent above
the emission estimate of 4.2 Tg CO2 Eq. Also, production-
related CF4 emissions were estimated to be between 2.3
and 2.7 Tg CO2 Eq. at the 95 percent confidence level.
This indicates a range of approximately 8 percent below
to 8 percent above the emission estimate of 2.5 Tg CO2
Eq. Finally, aluminum production-related C2F6 emissions
were estimated to be between 0.4 and 0.5 Tg CO2 Eq. at
the 95 percent confidence level. This indicates a range of
approximately 15 percent below to 16 percent above the
emission estimate of 0.4 Tg CO2 Eq.
Note that the 2005 emission estimate was developed
using IPCC (2001) slope coefficients for the 10 operating
smelters without site-specific PFC measurements. If these
slope coefficients were revised to incorporate recent IPCC
(2006) slope data, overall PFC emission estimates for 2005
would be on the order of 10 percent lower than current
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19SO-2CI05
-------
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for C02 and PFC Emissions from Aluminum Production
(Tg C02 Eq. and Percent)
Source
Aluminum Production
Aluminum Production
Aluminum Production
2005 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (TgC02Eq.) (%)
C02
CF4
C2F6
4.2
2.5
0.4
Lower Bound
4.0
2.3
0.4
Upper Bound
4.4
2.7
0.5
Lower Bound
-5%
-8%
-15%
Upper Bound
+5%
+8%
+ 16%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
estimates. Additionally, since these smelters are owned
by one company, data have been reported on a company-
wide basis as totals or weighted averages. Consequently,
uncertainties in anode effect minutes per cell day, slope
coefficients, and aluminum production have been applied to
the company as a whole, and not on a smelter-specific basis.
This probably overestimates the uncertainty associated with
the cumulative emissions from these smelters, because errors
that were in fact independent were treated as if they were
correlated. It is therefore likely that uncertainties calculated
above for the total U.S. 2005 emission estimates for CF4 and
C2F6 are also high.
This Inventory may slightly underestimate greenhouse
gas emissions from aluminum production and casting
because it does not account for the possible use of SF6 as a
cover gas or a fluxing and degassing agent in experimental
and specialized casting operations. The extent of such use in
the United States is not known. Historically, SF6 emissions
from aluminum activities have been omitted from estimates
of global SF6 emissions, with the explanation that any
emissions would be insignificant (Ko et al. 1993, Victor and
MacDonald 1998). The concentration of SF6 in the mixtures
is small and a portion of the SF6 is decomposed in the process
(MacNealetal. 1990,Gariepy andDube 1992,Koetal. 1993,
Ten Eyck and Lukens 1996, Zurecki 1996).
Recalculations Discussion
Relative to the previous Inventory report, CO2 emission
estimates for the period 1990 through 2004 were updated
based on revisions to default parameters used in the
estimation methodology. Previous CO2 emission estimates
were based on default emission factors defined by IPCC/
UNEP/OED/IEA (1997) and Aluminum Sector Greenhouse
Gas Protocol (IAI 2003). Current estimates utilize default
parameters defined in IPCC (2006). Based on this revision,
CO2 emissions from aluminum production have decreased
by approximately 3 percent for each year during the 1990
to 2004 period relative to the previous report.
The default slope coefficients used to estimate PFC
emissions from two smelters that have not developed Tier 3b
site-specific estimates were revised to reflect data presented
in IPCC (2006). This change has resulted in an increase
in PFC emissions of approximately 1 percent in 1990, an
average decrease of 0.1 percent between 1991 and 1996 and
2002 through 2004, and an average decrease of 6 percent
from 1997 through 2001, relative to the estimates developed
for the 1990 to 2004 Inventory.
4.22. Magnesium Production and
Processing (IPCC Source Category
2C4)
The magnesium metal production and casting industry
uses sulfur hexafluoride (SF6) as a cover gas to prevent the
rapid oxidation of molten magnesium in the presence of air.
A dilute gaseous mixture of SF6 with dry air and/or CO2 is
blown over molten magnesium metal to induce and stabilize
the formation of a protective crust. A small portion of the
SF6 reacts with the magnesium to form a thin molecular
film of mostly magnesium oxide and magnesium fluoride.
The amount of SF6 reacting in magnesium production and
processing is assumed to be negligible and thus all SF6
used is assumed to be emitted into the atmosphere. Sulfur
hexafluoride has been used in this application around the
world for the last twenty years.
The magnesium industry emitted 2.7 Tg CO2 Eq.
(0.1 Gg) of SF6 in 2005, representing an increase of
approximately 2 percent from 2004 emissions (see Table 4-
81). A planned expansion of primary magnesium production
in the United States has been delayed due to unfavorable
market conditions. Antidumping duties imposed on Chinese
Industrial Processes 4-57
-------
Table 4-81: SF6 Emissions from Magnesium Production
and Processing (Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
5.4
5.6
3.0
2.4
2.4
2.9
2.6
2.7
Gg
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.1
imports by the U.S. International Trade Commission have
shifted the majority of U.S. demand for primary magnesium
to imports from Canada, Israel, and Russia (USGS 2006).
Die casting operations in the United States have remained
stable and are expected to increase as demand for die cast
parts for the automotive sector increases due to fuel efficiency
design objectives.
Methodology
1999 to 2005 Emissions
Emission estimates for the magnesium industry from
1999 through 2005 incorporate information provided by
industry participants in EPA's SF6 Emission Reduction
Partnership for the Magnesium Industry. The Partnership
started in 1999 and currently, participating companies
represent 100 percent of U.S. primary and secondary
production and 90 percent of the casting sector (i.e., die, sand,
permanent mold, wrought, and anode casting). Absolute
emissions for 1999 through 2005 from primary production,
secondary production (i.e., recycling), and die casting were
reported by Partnership participants. Emission factors for
2002 to 2005 for sand casting activities were also acquired
through the Partnership. The 1999 through 2005 emissions
from casting operations (other than die) were estimated by
multiplying emission factors (kg SF6 per metric ton of Mg
produced or processed) by the amount of metal produced
or consumed. U.S. magnesium metal production (primary
and secondary) and consumption (casting) data from 1990
through 2005 were available from the USGS (USGS 2002,
2003,2005a, 2005b, 2006). The emission factors for casting
activities are provided below in Table 4-82. The emission
factors for primary production, secondary production, and
sand casting are withheld to protect company-specific
production information. However, the emission factor for
primary production has not risen above the 1995 value of 1.1
kg SF(; per metric ton, and the emission factor for secondary
production is slightly lower than the industry-reported
historic value of 1 kg SF6 per metric ton.
Die casting emissions for 1999 through 2005, which
accounted for 33 to 52 percent of all SF6 emissions from the
U.S. magnesium industry during this period, were estimated
based on information supplied by industry Partners. From
2000 to 2005, Partners accounted for all U.S. die casting
that was tracked by USGS. If Partners, did not report
emissions data for a certain year, SF6 emissions data were
estimated using available information on emission factors
and production reported in prior years. Each non-reporting
Partner's production was assumed to have remained constant
since the last report, while each non-reporting Partner's
emission factor was assumed to have followed the same trend
as the emission factors for reporting die casting partners.
Emissions from non-reporting Partners are estimated to have
accounted for less than 15 percent of die-casting emissions
in all years since 1999.
In 1999, Partners did not account for all die casting
tracked by USGS, and, therefore, it was necessary to estimate
the emissions of die casters who were not Partners. Die
casters who were not Partners were assumed to be similar to
Partners who cast small parts. Due to process requirements,
these casters consume larger quantities of SF6 per metric
ton of processed magnesium than casters that process large
parts. Consequently, emission estimates from this group of
die casters were developed using an average emission factor
of 5.2 kg SF6 per metric ton of magnesium. The emission
factors for the other industry sectors (i.e., permanent mold,
Table 4-82: SF6 Emission Factors (kg SF6 per metric ton
of magnesium)
Die Permanent
Year Casting Mold Wrought Anodes
1999
2000
2001
2002
2003
2004
2005
2.14a
0.73
0.77
0.70
0.84
0.78
0.75
2
2
2
2
2
2
2
1 1
1 1
1 1
1 1
1 1
1 1
1 1
a Weighted average that includes an estimated emission factor of 5.2 kg
SF6 per metric ton of magnesium for die casters that do not participate
in the Partnership.
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 199D-2005
-------
wrought, and anode casting) were based on discussions with
industry representatives.
1990 to 1998 Emissions
To estimate emissions for 1990 through 1998, industry
emission factors were multiplied by the corresponding metal
production and consumption (casting) statistics from USGS.
The primary production emission factors were 1.2 kg per
metric ton for 1990 through 1993, and 1.1 kg per metric
ton for 1994 through 1996. These factors were based on
information reported by U.S. primary producers. For die
casting, an emission factor of 4.1 kg per metric ton was used
for the period 1990 through 1996, based on an international
survey (Gjestland & Magers 1996). For 1996 through 1998,
the emission factors for primary production and die casting
were assumed to decline linearly to the level estimated based
on Partner reports in 1999. This assumption is consistent
with the trend in SF6 sales to the magnesium sector that is
reported in the RAND survey of major SF6 manufacturers,
which shows a decline of 70 percent from 1996 to 1999
(RAND 2002). The emission factor for sand casting between
1990 and 2001 was assumed to have been the same as the
2002 emission factor provided by Partners for this process.
The emission factor for secondary production from 1990
through 1998 was similarly assumed to be constant at 1 kg
per metric ton. The emission factors for the other processes
(i.e., permanent mold, wrought, and anode casting), about
which less is known, were assumed to remain constant at
levels defined in Table 4-82.
Uncertainty
To estimate the uncertainty of the estimated 2005 SF6
emissions from magnesium production and processing, the
uncertainties associated with three variables were estimated:
(1) emissions reported by magnesium producers and
processors that participate in the Partnership, (2) emissions
estimated for magnesium producers and processors that
participate in the Partnership but did not report this year,
and (3) emissions estimated for magnesium producers and
processors that do not participate in the Partnership. In
general, where precise quantitative information was not
available on the uncertainty of a parameter, an upper-bound
value was used.
Additional uncertainties exist in these estimates,
such as the basic assumption that SF6 neither reacts nor
decomposes during use. The melt surface reactions and
high temperatures associated with molten magnesium
could potentially cause some gas degradation. Recent
measurement studies have identified SF6 cover gas
degradation at hot-chambered die casting machines on the
order of 10 percent (Bartos et al. 2003). As is the case for
other sources of SF6 emissions, total SF6 consumption data
for magnesium production and processing in the United
States were not available. Sulfur hexafluoride may also
be used as a cover gas for the casting of molten aluminum
with high magnesium content; however, to what extent this
technique is used in the United States is unknown.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-83. SF6 emissions associated with
magnesium production and processing were estimated to be
between 2.6 and 2.8 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of approximately 4 percent
below to 4 percent above the 2005 emissions estimate of
2.7 Tg CO, Eq.
Recalculations Discussion
The methodology for estimating secondary magnesium
production (recycling) emissions from 1999 to 2005 was
adjusted to rely solely on Partner-reported information,
because this was believed to yield a more accurate estimate
than adding Partner-reported emissions to the product of
USGS secondary magnesium production and a default
industry SF6 emission factor. In previous years, the "remelt"
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and Processing
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eg.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Magnesium Production
and Processing
2.7
2.6
2.8
-4%
+4%
J Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
industrial Processes 4-58
-------
activity reported by Partners was small compared to the
secondary production reported by USGS, and it was uncertain
whether this remelt activity was included in USGS totals.
Thus, emissions were estimated both for Partner-reported
remelt and for USGS-reported secondary production. With
the addition of new Partners, however, it appears that Partner-
reported remelt is actually a more complete estimate of U .S.
secondary production than the USGS value. Thus, to avoid
double-counting, only the emissions reported by the Partners
are included in the totals for the time series. The change
resulted in a decrease of 0.2 Tg CO2 Eq. (approximately 7
percent) in SF6 emissions from magnesium production and
processing for 1999 to 2002, and a decrease in SF6 emissions
of 0.1 Tg CO2 Eq. (approximately 4 percent) for 2003 to
2004 relative to the previous report.
Planned Improvements
As more work assessing the degree of cover gas
degradation and associated byproducts is undertaken and
published, results could potentially be used to refine the
emission estimates, which currently assume (per IPCC
Good Practice Guidance, IPCC 2000) that all SF6 utilized
is emitted to the atmosphere. EPA-funded measurements
of SF6 in hot chamber die casting have indicated that
the latter assumption may be incorrect, with observed
SF6 degradation on the order of 10 percent (Bartos et al.
2003). More recent EPA-funded measurement studies have
confirmed this observation for cold chamber die casting
(EPA 2004). Another issue that will be addressed in future
inventories is the likely adoption of alternate cover gases
by U.S. magnesium producers and processors. These cover
gases, which include AM-Cover™ (containing HFC-134a)
and Novec™ 612, have lower GWPs than SF6, and tend to
quickly decompose during their exposure to the molten metal.
Additionally, as more companies join the Partnership, in
particular those from sectors not currently represented such
as permanent mold and anode casting, emission factors will
be refined to incorporate these additional data.
4.23. Industrial Sources of Indirect
Greenhouse Gases
In addition to the main greenhouse gases addressed
above, many industrial processes generate emissions of
indirect greenhouse gases. Total emissions of nitrogen
oxides (NOX), carbon monoxide (CO), and non-CH4 volatile
organic compounds (NMVOCs) from non-energy industrial
processes from 1990 to 2005 are reported in Table 4-84.
Table 4-84: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source
NO,
Other Industrial Processes
Chemical & Allied Product
Manufacturing
Metals Processing
Storage and Transport
Miscellaneous*
CO
Metals Processing
Other Industrial Processes
Chemical & Allied Product
Manufacturing
Storage and Transport
Miscellaneous*
NMVOCs
Storage and Transport
Other Industrial Processes
Chemical & Allied Product
Manufacturing
Metals Processing
Miscellaneous*
1990
591
343
152
88
3
5
4,125
2,395
487
1,073
69
101
2,422
1,352
364
575
111
20
1995
607
362
143
89
5
8
3,959
2,159
566
1,110
23
102
2,642
1,499
408
599
113
23
2000
626
434
95
81
14
2
2,217
1,175
538
327
154
23
1,773
1,067
412
230
61
3
2001
656
457
97
86
15
1
2,339
1,252
558
338
162
30
1,769
1,082
381
238
65
4
2002
532
389
63
63
17
1
1,710
895
445
258
107
5
1,811
1,140
400
227
42
2
2003
533
390
63
63
17
1
1,730
906
450
261
108
5
1,813
1,142
401
227
42
2
2004
534
390
63
63
17
1
1,751
917
456
264
109
5
1,815
1,143
401
227
42
2
2005
535
391
63
63
17
1
1,772
928
461
267
111
4
1,818
1,144
402
227
42
2
* Miscellaneous includes the following categories: catastrophic/accidental release, other combustion, health services, cooling towers, and fugitive dust. It
does not include agricultural fires or slash/prescribed burning, which are accounted for under the Field Burning of Agricultural Residues source.
Note: Totals may not sum due to independent rounding.
4-60 Inventory of U.S. Greenhouse Gas Emissions arid Sinks: 1990-2005
-------
Methodology
These emission estimates were obtained from preliminary
data (EPA 2006), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emissions were calculated either for individual
categories or for many categories combined, using basic
activity data (e.g., the amount of raw material processed)
as an indicator of emissions. National activity data were
collected for individual categories from various agencies.
Depending on the category, these basic activity data may
include data on production, fuel deliveries, raw material
processed, etc.
Activity data were used in conjunction with emission
factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the
EPA's Compilation of Air Pollutant Emission Factors, AP-42
(EPA 1997). The EPA currently derives the overall emission
control efficiency of a source category from a variety of
information sources, including published reports, the 1985
National Acid Precipitation and Assessment Program
emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the
accuracy of the emission factors used and accurate estimates
of activity data. A quantitative uncertainty analysis was
not performed.
industrial Processes 4 61
-------
-------
5. Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product of various solvent and other product uses. In the United
States, emissions from Nitrous Oxide (N2O) Product Usage, the only source of greenhouse gas emissions from
this sector, accounted for less than 0.1 percent of total U.S. anthropogenic greenhouse gas emissions on a carbon
equivalent basis in 2005 (see Table 5-1). Indirect greenhouse gas emissions also result from solvent and other product use,
and are presented in Table 5-2 in teragrams of carbon dioxide equivalent (Tg CO2 Eq.) and gigagrams (Gg).
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D)
N2O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. N2O is produced by thermally decomposing
ammonium nitrate (NH4NO3), a chemical commonly used in fertilizers and explosives. The decomposition creates steam
(H2O) and N2O through a low-pressure, low-temperature (500 °F) reaction. Once the steam is removed through condensation,
the remaining N2O is purified, compressed, dried, and liquefied for storage and distribution. Two companies operate a total
of five N2O production facilities in the United States (CGA 2003).
N2O is primarily used in carrier gases with oxygen to administer more potent inhalation anesthetics for general anesthesia
and as an anesthetic in various dental and veterinary applications. As such, it is used to treat short-term pain, for sedation
in minor elective surgeries and as an induction anesthetic. The second main use of N2O is as a propellant in pressure and
aerosol products, the largest application being pressure-packaged whipped cream. Small quantities of N2O also are used
in the following applications:
• Oxidizing agent and etchant used in semiconductor manufacturing;
Table 5-1: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg)
Gas/Source
N20 Product Usage
Tg C02 Eq.
Gg
1990
4.3
14
1995
4.5
14
2000
4.8
15
2001
4.8
15
2002
4.3
14
2003
4.3
14
2004
4.3
14
2005
4.3
14
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg)
Gas/Source
NMVOCs
CO
NOX
1990
5,216
5
1
1995
5,609
5
3
2000
4,384
46
3
2001
4,547
45
3
2002
3,911
1
5
2003
3,916
1
5
2004
3,921
1
5
2005
3,926
1
5
Solvent and Other Product Use 5-1
-------
Table 5-3: N20 Emissions from N20 Product Usage
(Tg COZ Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
Gg
14
14
15
15
14
14
14
14
• Oxidizing agent used, with acetylene, in atomic
absorption spectrometry;
• Production of sodium azide, which is used to inflate
airbags;
• Fuel oxidant in auto racing; and
• Oxidizing agent in blowtorches used by jewelers and
others (Heydorn 1997).
Production of N2O in 2005 was approximately 15 Gg.
N2O emissions were 4.3 Tg CO2 Eq. (14 Gg) in 2005 (see
Table 5-3). Production of N2O stabilized during the 1990s
because medical markets had found other substitutes for
anesthetics, and more medical procedures were being
performed on an outpatient basis using local anesthetics
that do not require N2O. The use of N2O as a propellant
for whipped cream has also stabilized due to the increased
popularity of cream products packaged in reusable plastic
tubs (Heydorn 1997).
Methodology
Emissions from N2O product usage were calculated
by first multiplying the total amount of N2O produced in
the United States by the share of the total quantity of N2O
attributed to each end use. This value was then multiplied
by the associated emissions rate for each end use. After
the emissions were calculated for each end use, they were
added together to obtain a total estimate of N2O product
usage emissions. Emissions were determined using the
following equation:
N O Product l.^uiij [{missions =-
X; I'l'uUil I'.S. Production oi'N,(.)j x
| Share H'Tnia! Quant it \ u1' N >O I.'^IL'I? b\ Sc
I hmissions Kate !'or Stvlo i .
where,
The share of total quantity of N2O usage by end use
represents the share of national N2O produced that is used
by the specific subcategory (i.e., anesthesia, food processing,
etc.). In 2005, the medical/dental industry used an estimated
89.5 percent of total N2O produced, followed by food
processing propellants at 6.5 percent. All other categories
combined used the remainder of the N2O produced. This
subcategory breakdown has changed only slightly over the
past decade. For instance, the small share of N2O usage in
the production of sodium azide has declined significantly
during the decade of the 1990s. Due to the lack of information
on the specific time period of the phase-out in this market
subcategory, most of the N2O usage for sodium azide
production is assumed to have ceased after 1996, with the
majority of its small share of the market assigned to the
larger medical/dental consumption subcategory. The N2O
was allocated across these subcategories; a usage emissions
rate was then applied for each sector to estimate the amount
of N-O emitted.
Only the medical/dental and food propellant subcategories
were estimated to release emissions into the atmosphere,
and therefore these subcategories were the only usage
subcategories with emission rates. For the medical/dental
subcategory, due to the poor solubility of N2O in blood and
other tissues, approximately 97.5 percent of the N2O is not
metabolized during anesthesia and quickly leaves the body in
exhaled breath. Therefore, an emission factor of 97.5 percent
was used for this subcategory (Tupman 2002). For N2O used
as a propellant in pressurized and aerosol food products, none
of the N2O is reacted during the process and all of the N2O
is emitted to the atmosphere, resulting in an emissions factor
of 100 percent for this subcategory (Heydorn 1997). For the
remaining subcategories, all of the N2O is consumed/reacted
during the process, and therefore the emissions rate was
considered to be zero percent (Tupman 2002).
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
The 1990 through 1992 and 1996 N2O production data
were obtained from SRI Consulting's Nitrous Oxide, North
America report (Heydorn 1997). These data were provided
as a range. For example, in 1996, Heydorn (1997) estimates
N2O production to range between 13.6 and 18.1 thousand
metric tons. Tupman (2003) provided a narrower range
for 1996 that falls within the production bounds described
by Heydorn (1997). These data are considered more
industry-specific and current. The midpoint of the narrower
production range (15.9 to 18.1 thousand metric tons) was
used to estimate N2O emissions for years 1993 through 2001
(Tupman 2003). The 2002 and 2003 N2O production data
were obtained from the Compressed Gas Association Nitrous
Oxide Fact Sheet and Nitrous Oxide Abuse Hotline (CGA
2002, 2003). These data were also provided as a range. For
example, in 2003, CGA (2003) estimates N2O production to
range between 13.6 and 15.9 thousand metric tons. Due to
unavailable data, production for 2004 and 2005 were held at
the value provided for 2003. N2O production data for 1990
through 2005 are presented in Table 5-4.
The 1996 share of the total quantity of N2O used by
each subcategory was obtained from SRI Consulting's
Nitrous Oxide, North America report (Heydorn 1997). The
1990 through 1995 share of total quantity of N2O used by
each subcategory was kept the same as the 1996 number
provided by SRI Consulting. The 1997 through 2001 share
of total quantity of N2O usage by sector was obtained from
communication with a N2O industry expert (Tupman 2002).
The 2002 and 2003 share of total quantity of N2O usage
by sector was obtained from CGA (2002, 2003). Due to
unavailable data, the share of total quantity of N2O usage data
for 2004 and 2005 was assumed to equal that of 2003. The
emissions rate for the food processing propellant industry
was obtained from SRI Consulting's Nitrous Oxide, North
America report (Heydorn 1997), and confirmed by a N2O
Table 5-4: N20 Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Gg
16
17
17
17
15
15
15
15
industry expert (Tupman 2002). The emissions rate for all
other subcategories was obtained from communication with
a N2O industry expert (Tupman 2002). The emissions rate
for the medical/dental subcategory was substantiated by the
Encyclopedia of Chemical Technology (Othmer 1990).
Uncertainty
The overall uncertainty associated with the 2005 N2O
emission estimate from N2O product usage was calculated
using the Intergovernmental Panel on Climate Change
(IPCC) Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
N2O emissions included that of production data, total market
share of each end use, and the emission factors applied to
each end use, respectively.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 5-5. N2O emissions from
N2O product usage were estimated to be between 4.1 and 4.5
Tg CO2 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates a
range of approximately 4 percent below to 4 percent above
the 2005 emissions estimate of 4.3 Tg CO2 Eq.
Table 5-5: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From N20 Product Usage
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(TgC02Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
N20 Product Usage
N,0
4.3
4.1
4.5
-4%
+4%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Solvent and Other Product Use 5-3
-------
Recalculations Discussion
The N2O production values for 2002, 2003, and 2004
have been updated relative to the previous Inventory based on
revised production data presented in CGA (2003). The updated
production data resulted in a decrease of 0.5 Tg CO2 Eq. (10
percent), respectively, in N2O emissions from N2O product
usage for these years relative to the previous Inventory.
Planned Improvements
Planned improvements include a continued evaluation
of alternative production statistics for cross-verification and
a reassessment of subcategory usage to accurately represent
the latest trends in the product usage.
5.2. Indirect Greenhouse Gas
Emissions from Solvent Use
The use of solvents and other chemical products
can result in emissions of various ozone precursors
(i.e., indirect greenhouse gases).1 Non-methane volatile
organic compounds (NMVOCs), commonly referred to as
"hydrocarbons," are the primary gases emitted from most
processes employing organic or petroleum based solvents. As
some industrial applications also employ thermal incineration
as a control technology, combustion by-products, such as
carbon monoxide (CO) and nitrogen oxides (NOX), are also
reported with this source category. In the United States,
emissions from solvents are primarily the result of solvent
evaporation, whereby the lighter hydrocarbon molecules in
the solvents escape into the atmosphere. The evaporation
process varies depending on different solvent uses and
solvent types. The major categories of solvent uses include:
degreasing, graphic arts, surface coating, other industrial
uses of solvents (i.e., electronics, etc.), dry cleaning, and
non-industrial uses (i.e., uses of paint thinner, etc.).
Total emissions of NOX, NMVOCs, and CO from 1990
to 2005 are reported in Table 5-6.
Methodology
Emissions were calculated by aggregating solvent use
data based on information relating to solvent uses from
different applications such as degreasing, graphic arts, etc.
Emission factors for each consumption category were then
applied to the data to estimate emissions. For example,
emissions from surface coatings were mostly due to solvent
evaporation as the coatings solidify. By applying the
appropriate sol vent-specific emission factors to the amount of
solvents used for surface coatings, an estimate of emissions
was obtained. Emissions of CO and NOX result primarily
from thermal and catalytic incineration of solvent-laden
gas streams from painting booths, printing operations, and
oven exhaust.
These emission estimates were obtained from preliminary
data (EPA 2006), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emissions were calculated either for individual
categories or for many categories combined, using basic
activity data (e.g., the amount of solvent purchased) as an
indicator of emissions. National activity data were collected
for individual applications from various agencies.
Activity data were used in conjunction with emission
factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the
EPA's Compilation of Air Pollutant Emission Factors, AP-42
(EPA 1997). The EPA currently derives the overall emission
control efficiency of a source category from a variety of
information sources, including published reports, the 1985
National Acid Precipitation and Assessment Program
emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the
accuracy of the emission factors used and the reliability of
correlations between activity data and actual emissions.
1 Solvent usage in the United States also results in the emission of small amounts of hydrofluorocarbons (HFCs) and hydrofluoroethers (HFEs), which
are included under Substitution of Ozone Depleting Substances in the Industrial Processes chapter.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990--2005
-------
Table 5-6: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg)
Activity
NO,
Surface Coating
Degreasing
Graphic Arts
Dry Cleaning
Other Industrial Processes3
Non-Industrial Processes'1
Other
CO
Surface Coating
Degreasing
Graphic Arts
Dry Cleaning
Other Industrial Processes3
Non-Industrial Processes'1
Other
NMVOCs
Surface Coating
Non-Industrial Processes'"
Degreasing
Dry Cleaning
Graphic Arts
Other Industrial Processes3
Other
1990
1
1
+
+
+
+
+
NA
5
+
+
+
+
4
+
NA
5,216
2,289
1,724
675
195
249
85
+
1995
3
2
+
1
+
+
+
+
5
1
+
+
1
3
+
NA
5,609
2,432
1,858
716
209
307
87
+
2000
3
3
+
+
+
+
+
+
46
46
+
+
+
+
+
+
4,384
1,767
1,676
316
265
222
98
40
2001
3
3
+
+
+
+
+
+
45
45
+
+
+
+
+
+
4,547
1,863
1,707
331
272
229
103
42
2002
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,911
1,602
1,468
285
234
197
89
36
2003
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,916
1,604
1,470
285
234
197
89
36
2004
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,921
1,606
1,472
286
234
197
89
36
2005
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,926
1,608
1,474
286
235
197
89
37
a Includes rubber and plastics manufacturing, and other miscellaneous applications.
b Includes cutback asphalt, pesticide application, adhesives, consumer solvents, and other miscellaneous applications.
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg.
Solvent and Other Product Use 5-5
-------
-------
6. Agriculture
Figure 6-1
365.1
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes. This
chapter provides an assessment of non-carbon-dioxide emissions from the following source categories: enteric
fermentation in domestic livestock, livestock manure management, rice cultivation, agricultural soil management,
and field burning of agricultural residues (see Figure 6-1). Carbon dioxide (CO2) emissions and removals from agriculture-
related land-use activities, such as conversion of grassland to cultivated land, are presented in the Land Use, Land-Use
Change, and Forestry chapter. CO2 emissions from on-farm
energy use are accounted for in the Energy chapter.
In 2005, the agricultural sector was responsible for
emissions of 536.3 teragrams of CO2 equivalent (Tg CO2
Eq.), or 7 percent of total U.S. greenhouse gas emissions.
Methane (CH4) and nitrous oxide (N2O) were the primary
greenhouse gases emitted by agricultural activities. CH4
emissions from enteric fermentation and manure management
represent about 21 percent and 8 percent of total CH4
emissions from anthropogenic activities, respectively. Of all
domestic animal types, beef and dairy cattle were by far the
largest emitters of CH4. Rice cultivation and field burning of
agricultural residues were minor sources of CH4. Agricultural
soil management activities such as fertilizer application and
other cropping practices were the largest source of U.S. N2O
emissions, accounting for 78 percent. Manure management
Agricultural Soil Management
Enteric Fermentation
Manure Management
Field Burning of
Agricultural Residues
50
100 150
Tg CO, Eq.
200
Table 6-1: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural
Residues
Total
1990
154.4
115.7
30.9
7.1
0.7
375.9
366.9
8.6
0.4
530.3
1995
164.0
120.6
35.1
7.6
0.7
362.7
353.4
9.0
0.4
526.8
2000
160.5
113.5
38.7
7.5
0.8
386.9
376.8
9.6
0.5
547.4
2001
161.0
112.5
40.1
7.6
0.8
399.2
389.0
9.8
0.5
560.3
2002
161.2
112.6
41.1
6.8
0.7
376.2
366.1
9.7
0.4
537.4
2003
161.1
113.0
40.5
6.9
0.8
359.9
350.2
9.3
0.4
521.1
2004
158.7
110.5
39.7
7.6
0.9
348.7
338.8
9.4
0.5
507.4
2005
161.2
112.1
41.3
6.9
0.9
375.1
365.1
9.5
0.5
536.3
Note: Totals may not sum due to independent rounding.
Agriculture 6-1
-------
Table 6-2: Emissions from Agriculture (Gg)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural
Residues
CO
NO,
1990
7,353
5,510
1,471
339
33
1,213
1,184 .
28
1
691
28
1995
7,811
5,744
1,673
363
32
1,170
1,140
29
1
663
29
2000
7,643
5,404
1,844
357
38
1,248
1,215
31
1
792
35
2001
7,668
5,356
1,911
364
37
1,288
1,255
32
1
774
35
2002
7,678
5,361
1,959
325
34
1,213
1,181
31
1
709
33
2003
7,673
5,379
1,928
328
38
1,161
1,130
30
1
800
34
2004
7,556
5,262
1,892
360
42
1,125
1,093
30
2
879
39
2005
7,674
5,340
1,966
328
41
1,210
1,178
31
2
858
39
Note: Totals may not sum due to independent rounding.
and field burning of agricultural residues were also small
sources of N2O emissions.
Table 6-1 and Table 6-2 present emission estimates
for the Agriculture sector. Between 1990 and 2005, CH4
emissions from agricultural activities increased by 4 percent,
while N2O emissions fluctuated from year to year, but overall
decreased by less than 1 percent. In addition to CH4 and N2O,
field burning of agricultural residues was also a minor source
of the indirect greenhouse gases carbon monoxide (CO) and
nitrogen oxides (NOX).
6.1. Enteric Fermentation (IPCC
Source Category 4A)
CH4 is produced as part of normal digestive processes in
animals. During digestion, microbes resident in an animal's
digestive system ferment food consumed by the animal.
This microbial fermentation process, referred to as enteric
fermentation, produces CH4 as a by-product, which can be
exhaled or eructated by the animal. The amount of CH4
produced and excreted by an individual animal depends
primarily upon the animal's digestive system, and the amount
and type of feed it consumes.
Ruminant animals (e.g., cattle, buffalo, sheep, goats, and
camels) are the major emitters of CH4 because of their unique
digestive system. Ruminants possess a rumen, or large "fore-
stomach," in which microbial fermentation breaks down the
feed they consume into products that can be absorbed and
metabolized. The microbial fermentation that occurs in the
rumen enables them to digest coarse plant material that non-
ruminant animals cannot. Ruminant animals, consequently,
have the highest CH4 emissions among all animal types.
Non-ruminant domesticated animals (e.g., swine, horses,
and mules) also produce CH4 emissions through enteric
fermentation, although this microbial fermentation occurs in
the large intestine. These non-ruminants emit significantly
less CH4 on a per-animal basis than ruminants because the
capacity of the large intestine to produce CH4 is lower.
In addition to the type of digestive system, an animal's
feed quality and feed intake also affects CH4 emissions. In
general, lower feed quality or higher feed intake lead to higher
CH4 emissions. Feed intake is positively related to animal
size, growth rate, and production (e.g., milk production, wool
growth, pregnancy, or work). Therefore, feed intake varies
among animal types as well as among different management
practices for individual animal types.
CH4 emission estimates from enteric fermentation are
provided in Table 6-3 and Table 6-4. Total livestock CH4
emissions in 2005 were 112.1 Tg CO2 Eq. (5,340 gigagrams
[Gg]), increasing slightly since 2004 due to minor increases
in most animal populations and dairy cow milk production
in all regions. Beef cattle remain the largest contributor of
CH4 emissions from enteric fermentation, accounting for
71 percent in 2005. Emissions from dairy cattle in 2005
accounted for 25 percent, and the remaining emissions were
from horses, sheep, swine, and goats.
From 1990 to 2005, emissions from enteric fermentation
have decreased by 3 percent Generally, emissions have been
decreasing since 1995, mainly due to decreasing populations
of both beef and dairy cattle and improved feed quality for
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eq.)
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
Note: Totals may not sum due to
Table 6-4: CH4 Emissions
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
1990
81.0
28.9
1.9
1.9
1.7
0.3
115.7
independent rounding.
1995
87.4
27.7
1.9
1.5
1.9
0.2
120.6
2000
81.3
27.0
2.0
1.2
1.9
0.3
113.5
2001
80.3
26.9
2.0
1.2
1.9
0.3
112.5
2002
80.2
27.1
2.0
1.1
1.9
0.3
112.6
2003
80.5
27.3
2.0
1.1
1.9
0.3
113.0
2004
78.3
27.0
2.0
1.0
1.9
0.3
110.5
2005
79.2
27.7
2.0
1.0
1.9
0.3
112.1
from Enteric Fermentation (Gg)
1990
3,859
1,375
91
91
81
13
5,510
1995
4,160
1,320
92
72
88
12 .-••
5,744
2000
3,869
1,283
94
56
88
12
5,404
2001
3,825
1,280
95
55
88
12
5,356
2002
3,821
1,288
95
53
90
13
5,361
2003
3,832
1,299
95
51
90
13
5,379
2004
3,730
1,285
95
49
91
13
5,262
2005
3,772
1,319
95
49
91
13
5,340
Note: Totals may not sum due to independent rounding.
feedlot cattle. During this timeframe, populations of sheep
have decreased by an average annual rate of about 4 percent
per year while horse, goat, and swine populations have
remained relatively constant.
Methodology
Livestock emission estimates fall into two categories:
cattle and other domesticated animals. Cattle, due to
their large population, large size, and particular digestive
characteristics, account for the majority of CH4 emissions
from livestock in the United States. A more detailed
methodology (i.e., Intergovernmental Panel on Climate
Change [IPCC] Tier 2) was therefore applied to estimate
emissions for all cattle except for bulls. Emission estimates
for other domesticated animals (horses, sheep, swine, goats,
and bulls) were handled using a less detailed approach (i.e.,
IPCC Tier 1).
While the large diversity of animal management
practices cannot be precisely characterized and evaluated,
significant scientific literature exists that describes the
quantity of CH4 produced by individual ruminant animals,
particularly cattle. A detailed model that incorporates this
information and other analyses of livestock population,
feeding practices and production characteristics was used
to estimate emissions from cattle populations.
National cattle population statistics were disaggregated
into the following cattle sub-populations:
• Dairy Cattle
• Calves
• Heifer Replacements
• Cows
• Beef Cattle
• Calves
• Heifer Replacements
• Heifer and Steer Stackers
• Animals in Feedlots (Heifers and Steers)
• Cows
• Bulls
Calf birth rates, end of year population statistics,
detailed feedlot placement information, and slaughter
weight data were used to model cohorts of individual
animal types and their specific emissions profiles. The
key variables tracked for each of the cattle population
categories are described in Annex 3.9. These variables
include performance factors such as pregnancy and
lactation as well as average weights and weight gain.
Annual cattle population data were obtained from the U.S.
Department of Agriculture's National Agricultural Statistics
Agriculture 6-3
-------
Service (1995a,b; 1999a,c,d,f,g; 2000a,c,d,e; 2001a,c,d,f;
2002a,c,d,f; 2003a,c,d,f; 2004a,c,d,f, 2005a-d, 2006a-d).
Diet characteristics were estimated by region for U.S.
dairy, beef, and feedlot cattle. These estimates were used to
calculate Digestible Energy (DE) values and CH4 conversion
rates (Ym) for each population category. The IPCC
recommends Ym values of 3.5 to 4.5 percent for feedlot cattle
and 5.5 to 6.5 percent for other well-fed cattle consuming
temperate-climate feed types. Given the availability of
detailed diet information for different regions and animal
types in the United States, DE and Ym values unique to
the United States were developed, rather than using the
recommended IPCC values. The diet characterizations and
estimation of DE and Ym values were based on information
from state agricultural extension specialists, a review
of published forage quality studies, expert opinion, and
modeling of animal physiology. The diet characteristics for
dairy cattle were from Donovan (1999), while those for beef
cattle were derived from NRC (2000). DE and Ym for dairy
cows were calculated from diet characteristics using a model
simulating ruminant digestion in growing and/or lactating
cattle (Donovan and Baldwin 1999). For feedlot animals, DE
and Ym values recommended by Johnson (1999) were used.
Values from EPA (1993) were used for dairy replacement
heifers. For grazing beef cattle, DE values were based on
diet information in NRC (2000) and Ym values were based on
Johnson (2002). Weight data were estimated from Feedstuffs
(1998), Western Dairyman (1998), and expert opinion. See
Annex 3.9 for more details on the method used to characterize
cattle diets in the United States.
To estimate CH4 emissions from cattle, the population
was divided into region, age, sub-type (e.g., dairy cows and
replacements, beef cows and replacements, heifer and steer
stackers, and heifer and steer in feedlots), and production
(e.g., pregnant, lactating) groupings to more fully capture
differences in CH4 emissions from these animal types.
Cattle diet characteristics were used to develop regional
emission factors for each sub-category. Tier 2 equations
from IPCC (2000) were used to produce CH4 emission
factors for the following cattle types: dairy cows, beef cows,
dairy replacements, beef replacements, steer stackers, heifer
stockers, steer feedlot animals, and heifer feedlot animals.
To estimate emissions from cattle, population data were
multiplied by the emission factor for each cattle type. More
details are provided in Annex 3.9.
Emission estimates for other animal types were based on
average emission factors representative of entire populations
of each animal type. CH4 emissions from these animals
accounted for a minor portion of total CH4 emissions from
livestock in the United States from 1990 through 2005.
Also, the variability in emission factors for each of these
other animal types (e.g., variability by age, production
system, and feeding practice within each animal type) is
less than that for cattle. Annual livestock population data
for these other livestock types, except horses and goats, as
well as feedlot placement information were obtained for all
years from the U.S. Department of Agriculture's National
Agricultural Statistics Service (USDA 1994a-b, 1995a,c,
1998a-b, 1999a,b,e,f, 2000a,b,e,f, 2001 a,b,e,f, 2002 a,b,e,f,
2003 a,b,e,f, 2004a,b,e-h, 2005a,d-h, 2006a,d-h). Horse
population data were obtained from the FAOSTAT database
(FAO 2006), because USDA does not estimate U.S. horse
populations annually. Goat population data for 1992,1997,
and 2002 were obtained from the Census of Agriculture
(USDA 20051); these data were interpolated and extrapolated
to derive estimates for the other years. Information regarding
poultry turnover (i.e., slaughter) rate was obtained from
state Natural Resource Conservation Service personnel
(Lange 2000). Additional population data for different farm
size categories for dairy and swine were obtained from
the 7992 and 1997 Census of Agriculture (USDA 2005i).
CH4 emissions from sheep, goats, swine, and horses were
estimated by using emission factors utilized in Crutzen et
al. (1986, cited in 1PCC/UNEP/OECD/IEA 1997). These
emission factors are representative of typical animal sizes,
feed intakes, and feed characteristics in developed countries.
The methodology is the same as that recommended by IPCC
(IPCC/UNEP/OECD/IEA 1997, IPCC 2000).
See Annex 3.9 for more detailed information on the
methodology and data used to calculate CH4 emissions from
enteric fermentation.
Uncertainty
Quantitative uncertainty of this source category
was performed through the IPCC-recommended Tier 2
uncertainty estimation methodology, Monte Carlo Stochastic
Simulation technique as described in ICF (2003). These
estimates were developed for the 2001 inventory estimates.
No significant changes occurred in the method of data
collection, data estimation methodology, or other factors
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
that influence the uncertainty ranges around the 2005 activity
data and emission factor input variables. Consequently,
these uncertainty estimates were directly applied to the 2005
emission estimates.
A total of 185 primary input variables (177 for cattle and
8 for non-cattle) were identified as key input variables for
uncertainty analysis. The normal distribution was assumed
for almost all activity- and emission factor-related input
variables. Triangular distributions were assigned to three
input variables (specifically, cow-birth ratios for the three
most recent years included in the 2001 model run). For
some key input variables, the uncertainty ranges around
their estimates (used for inventory estimation) were collected
from published documents and other public sources. In
addition, both endogenous and exogenous correlations
between selected primary input variables were modeled. The
exogenous correlation coefficients between the probability
distributions of selected activity-related variables were
developed as educated estimates.
The uncertainty ranges associated with the activity-
related input variables were plus or minus 10 percent or lower.
However, for many emission factor-related input variables, the
lower- and/or the upper-bound uncertainty estimates were over
20 percent. The results of the quantitative uncertainty analysis
(Table 6-5) indicate that, on average, the emission estimate
range of this source is approximately 99.8 to 132.3 Tg CO2
Eq., within the range of approximately 11 percent below and
18 percent above the actual 2005 emission estimate of 112.1
Tg CO7 Eq. Among the individual sub-source categories, beef
cattle account for the largest amount of CH4 emissions as well
as the largest degree of uncertainty in the inventory emission
estimates. Consequently, the cattle sub-source categories
together contribute to the largest degree of uncertainty in the
inventory estimates of CH4 emissions from livestock enteric
fermentation. Among non-cattle, horses account for the largest
degree of uncertainty in the inventory emission estimates.
QA/QC and Verification
In order to ensure the quality of the emission estimates
from enteric fermentation, the IPCC Tier 1 and Tier 2
Quality Assurance/Quality Control (QA/QC) procedures
were implemented consistent with the U.S. QA/QC plan.
Tier 2 QA procedures included independent peer review
of emission estimates. Particular emphasis was placed this
year on cattle population and growth data, and on evaluating
the effects of data updates as described in the recalculations
discussion below.
Recalculations Discussion
While there were no changes in the methodologies used
for estimating CH4 emissions from enteric fermentation,
emissions were revised slightly due to changes in data.
US DA published revised population estimates which affected
historical emissions estimated for swine, sheep, goats, and
poultry. Recent historical emission estimates also changed for
certain beef and dairy populations as a result USDA inputs
and the calving rate described below.
The emission factor for bulls has also changed according
to IPCC (2006). Previously, the emission factor for bulls was
100 kg CH4/head/yr, which in the 2006 IPCC Guidelines was
changed to 53 kg CH4/head/yr. This change in the emission
factor resulted in an annual 47 percent decrease in emissions
from bulls.
Several changes to previously reported emissions
occurred due to revisions to population data and a change
to the emissions factor for bulls. Year 2002 total (dairy and
beef) cattle CH4 emissions decreased by 2 percent. For 2004,
beef cattle CH4 emissions decreased 2.6 percent while dairy
cattle emissions remained relatively constant. The majority
of the change in emissions from beef cattle is a result of the
change in emission factor for bulls. The decreased emission
factor in bull emissions from 1990 through 2005 resulted in a
decrease in CH4 emissions for each of those years. In 2004,
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3 b
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Enteric Fermentation
CH4
112.1
99.8
132.3
-11%
+18%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
6 Note that the relative uncertainty range was estimated with respect to the 2001 emission estimates and applied to 2005 estimates.
Agriculture 6-5
-------
this change lowered emissions by 100 Gg (2.0 percent of
total enteric fermentation emissions from all animals). Recent
historical emission estimates for swine changed (by less than
one half of one percent of respective 2004 emissions) as a
result of the US DA revisions described above.
Planned Improvements
Continued research and regular updates are necessary
to maintain a current model of cattle diet characterization,
feedlot placement data, rates of weight gain and calving,
among other data inputs. While EPA has no plans for
methodological changes in the modeling framework,
the opportunity exists to continue to refine the model's
results through identifying and improving individual data
inputs. Research is currently underway to differentiate
emissions from "dry" and lactating cows within the model.
This improvement to the model would improve inventory
estimates by taking into account the milk production for
lactating cows. Other research is currently underway to
identify updates of this nature.
6.2. Manure Management (IPCC
Source Category 46)
The management of livestock manure can produce
anthropogenic CH4 and N2O emissions. CH4 is produced by
the anaerobic decomposition of manure. N2O is produced
as part of the nitrogen cycle through the nitrification and
denitrification of the organic nitrogen in livestock manure
and urine.1
When livestock or poultry manure are stored or
treated in systems that promote anaerobic conditions (e.g.,
as a liquid/slurry in lagoons, ponds, tanks, or pits), the
decomposition of materials in the manure tends to produce
CH4. When manure is handled as a solid (e.g., in stacks or
dry lots) or deposited on pasture, range, or paddock lands,
it tends to decompose aerobically and produce little or no
CH4. Ambient temperature, moisture, and manure storage or
residency time affect the amount of CH4 produced because
they influence the growth of the bacteria responsible for
CH4 formation. For non-liquid-based manure systems, moist
conditions (which are a function of rainfall and humidity)
can promote CH4 production. Manure composition, which
varies by animal diet, growth rate, and type, including the
animal's digestive system, also affects the amount of CH4
produced. In general, the greater the energy content of the
feed, the greater the potential for CH4 emissions. However,
some higher energy feeds also are more digestible than
lower quality forages, which can result in less overall waste
excreted from the animal.
The production of N2O from livestock manure depends
on the composition of the manure and urine, the type of
bacteria involved in the process, and the amount of oxygen
and liquid in the manure system. For N2O emissions to
occur, the manure must first be handled aerobically where
ammonia or organic nitrogen is converted to nitrates and
nitrites (nitrification), and then handled anaerobically where
the nitrates and nitrites are reduced to nitrogen gas (N2),
with intermediate production of N2O and nitric oxide (NO)
(denitrification) (Groffman et al. 2000). These emissions are
most likely to occur in dry manure handling systems that
have aerobic conditions, but that also contain pockets of
anaerobic conditions due to saturation. A very small portion
of the: total nitrogen excreted is expected to convert to N2O
in the waste management system.
Estimates of CH4 emissions in 2005 were 41.3 Tg CO2
Eq. (.1,966 Gg), 34 percent higher than in 1990. Emissions
increased on average by 0.7 Tg CO2 Eq. (2 percent) annually
over this period. The majority of this increase was from swine
and dairy cow manure, where emissions increased 37 and
50 percent, respectively. Although the majority of manure
in the United States is handled as a solid, producing little
CH4, the general trend in manure management, particularly
for dairy and swine (which are both shifting towards larger
facilities), is one of increasing use of liquid systems. Also,
new regulations limiting the application of manure nutrients
have shifted manure management practices at smaller
dairies from daily spread to manure managed and stored
on sire. Although national dairy animal populations have
been generally decreasing, some states have seen increases
in their dairy populations as the industry becomes more
concentrated in certain areas of the country. These areas
1 Emissions from livestock manure and urine deposited on pasture, range, or paddock lands, indirect emissions from volatile nitrogen losses that
occur primarily in the forms of ammonia and NOX, and emissions from manure and urine spread onto fields either directly as "daily spread" or after
it is removed from manure management systems (e.g., lagoon, pit. etc.) are accounted for and discussed in the Agricultural Soil Management source
category within the Agriculture chapter.
6-6 inventory of U.S. Greenhouse Gas Emissions and Sinks: 199(1-2005
-------
of concentration, such as California, New Mexico, and
Idaho, tend to utilize more liquid-based systems to manage
(flush or scrape) and store manure. Thus the shift toward
larger facilities is translated into an increasing use of liquid
manure management systems, which have higher potential
CH4 emissions than dry systems. This shift was accounted
for by incorporating state-specific weighted CH4 conversion
factor (MCF) values in combination with the 1992, 1997,
and 2002 farm-size distribution data reported in the Census
of Agriculture (USDA2005e). From 2004 to 2005, there was
a 4 percent increase in CH4 emissions, due to minor shifts in
the animal populations and the resultant effects on manure
management system allocations.
In 2005, total N2O emissions were estimated to be 9.5 Tg
CO2 Eq. (31 Gg); in 1990,emissions were 8.6Tg CO2Eq. (28
Gg). Emissions increased on average by 0.06 Tg CO2 Eq. (0.7
percent) annually over this period, driven by beef cattle. The
10 percent increase in N2O emissions from 1990 to 2005 can
be partially attributed to a shift in the poultry industry away
from the use of liquid manure management systems in favor
of litter-based systems and high-rise houses. In addition, there
was an overall increase in the population of poultry and swine
from 1990 to 2005, although swine populations periodically
declined slightly throughout the time series. N2O emissions
showed a 0.9 percent increase from 2004 through 2005, due
to minor shifts in animal populations.
The population of beef cattle in feedlots increased
over the period of 1990 to 2005, resulting in increased N2O
emissions from this sub-category of cattle. N2O emissions
from dairy cattle increased slightly over the period 1990
through 2005, a net result of different emission trends for
dairy cows and dairy heifers. Although dairy cow populations
decreased overall for the period 1990 through 2005, the
population of dairy cows increased at dairies that manage
and store manure on-site (as opposed to using pasture, range,
or paddock or daily spread systems). The shift at dairies to
more liquid manure management systems at large operations
resulted in lower N2O emissions for dairy cows. This trend
differed from the increasing dairy heifer N2O emissions from
dairy heifers, whose populations were increasingly managed
in drylot systems.
Table 6-6 and Table 6-7 provide estimates of CH4
and N2O emissions from manure management by animal
category.
Methodology
The methodologies presented in IPCC (2006) form the
basis of the CH4 and N2O emission estimates for each animal
Table 6-6: CH4 and N20 Emissions from Manure Management (Tg C02 Eq.)
Gas/Animal Type
CH4
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Total
1990
30.9
11.9
2.5
13.1
0.1
+
2.7
0.5
8.6
2.4
4.9
0.5
0.1
+
0.5
0.2
39.5
1995
35.1
13.3
2.6
16.0
0.1
+
2.7
0.4
9.0
2.4
5.3
0.5
0.1
+
0.4
0.2
44.1
2000
38.7
15.7
2.4
17.4
0.1
+
2.6
0.5
9.6
2.5
5.9
0.5
0.1
+
0.4
0.2
48.3
2001
40.1
16.6
2.5
17.8
0.1
+
2.7
0.5
9.8
2.5
6.1
0.5
0.1
+
0.4
0.2
50.0
2002
41.1
17.2
2.4
18.3
0.1
+
2.7
0.5
9.7
2.5
6.0
0.5
0.1
+
0.4
0.2
50.8
2003
40.5
17.6
2.4
17.2
0.1
+
2.7
0.5
9.3
2.5
5.6
0.5
0.1
+
0.4
0.2
49.8
2004
39.7
17.1
2.3
17.1
0.1
+
2.6
0.5
9.4
2.5
5.7
0.5
0.1
+
0.4
0.2
49.2
2005
41.3
17.9
2.3
17.9
0.1
+
2.6
0.5
9.5
2.5
5.8
0.5
0.1
+
0.4
0.2
50.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Agriculture 6-7
-------
Table 6-7: CH4 and N20 Emissions from Manure Management (Gg)
Gas/Animal Type
CH4
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
1990
1,471
568
120
623
7
1
131
22
28
8
16
2
0
0
1
1
1995
1,673
634
122
762
5
1
128
21
29
8
17
2
0
0
1
1
2000
1,844
748
114
830
4
1
125
22
31
8
19
2
0
0
1
1
2001
1,911
789
117
849
4
1
129
22
32
8
20
1
0
0
1
1
2002
1,959
818
114
873
4
1
127
22
31
8
19
2
0
0
1
1
2003
1,928
839
113
821
4
1
127
22
30
8
18
2
0
0
1
1
2004
1,892
814
110
815
4
1
126
22
30
8
19
2
0
0
1
1
2005
1,966
851
111
852
4
1
125
22
31
8
19
2
0
0
1
1
+ Does not exceed 0.5 Gg.
Note: Totals may not sum due to independent rounding.
type. The calculation of emissions requires the following
information:
• Animal population data (by animal type and state);
• Amount of nitrogen produced (excretion rate by animal
type times animal population);
• Amount of volatile solids produced (excretion rate by
animal type times animal population);
• CH4 producing potential of the volatile solids (by animal
type);
• Extent to which the CH4 producing potential is realized
for each type of manure management system (by state
and manure management system, including the impacts
of any biogas collection efforts);
• Portion of manure managed in each manure management
system (by state and animal type); and
• Portion of manure deposited on pasture, range, or
paddock or used in daily spread systems.
This section presents a summary of the methodologies
used to estimate CH4 and N2O emissions from manure
management for this Inventory. See Annex 3.10 for
more detailed information on the methodology and data
used to calculate CH4 and N2O emissions from manure
management.
Both CH4 and N2O emissions were estimated by first
determining activity data, including animal population, waste
characteristics, and manure management system usage. For
swine and dairy cattle, manure management system usage
was determined for different farm size categories using data
from USDA (USDA 1996b, 1998c, 2000b) and EPA (ERG
2000a, EPA 2002a, 2002b). For beef cattle and poultry,
manure management system usage data were not tied to
farm size but were based on other data sources (ERG 2000a,
USDA 2000c, UEP 1999). For other animal types, manure
management system usage was based on previous estimates
(EPA 1992).
MCFs and N2O emission factors were determined for
all manure management systems. MCFs for dry systems
were set equal to default IPCC factors based on each state's
climate for each year (IPCC 2006). MCFs for liquid/slurry,
anaerobic lagoon, and deep pit systems were calculated based
on the forecast performance of biological systems relative to
temperature changes as predicted in the vari't Hoff-Arrhenius
equation. The MCF calculations model the average monthly
ambient temperature, a minimum system temperature, the
carryover of volatile solids in the system from month to
month due to long storage times exhibited by anaerobic
lagoon systems, and a factor to account for management and
design practices that result in the loss of volatile solids from
lagoon systems. N2O emission factors for all systems were
set equal to default IPCC factors (IPCC 2006).
CH4 emissions were estimated using the volatile solids
(VS) production for all livestock. For most cattle groups,
regional animal-specific VS production rates that are related
to the diet of the animal for each year of the inventory were
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19911-2005
-------
used (Pederson and Pape 2006). For all other animal groups,
VS production was calculated using a national average VS
production rate from the Agricultural Waste Management
Field Handbook (USDA 1996a), which was then multiplied
by the average weight of the animal and the state-specific
animal population. The resulting VS for each animal group
were then multiplied by the maximum CH4 producing
capacity of the waste (B0) and the state-specific MCFs.
The maximum CH4 producing capacity of the VS, or B0,
was determined based on data collected in a literature review
(ERG 2000b). B0 data were collected for each animal type
for which emissions were estimated.
Anaerobic digester reductions are estimated based on
data from the EPA AgSTAR program, including information
presented in the AgSTAR Digest (EPA 2000, 2003b, 2006).
A destruction efficiency of 99 percent was applied to CH4
recovered to estimate CH4 emissions from digesters. The
value for efficiency was selected based on the range of
efficiencies (98 to 100 percent) recommended for flares
in EPA's "AP-42 Compilation of Air Pollutant Emission
Factors, Chapter 2.4," efficiencies used to establish new
source performance standards (NSPS) for landfills, and in
recommendations for closed flares used in LMOP.
Nitrogen excretion rate data from the USDA Agricultural
Waste Management Field Handbook (USDA 1996a) were
used for all livestock except sheep, goats, and horses. Data
from the American Society of Agricultural Engineers (AS AE
1999) were used for these animal types. VS excretion rate
data from USDA (1996a) were used for swine, poultry, bulls,
and calves not on feed.
N->O emissions were estimated by determining total
Kjeldahl nitrogen (TKN)2 production for all livestock
wastes using a national average nitrogen excretion rate for
each animal group from USDA (1996a), which was then
multiplied by the average weight of the animal and the state-
specific animal population. State-specific weighted N2O
emission factors specific to the type of manure management
system were then applied to total nitrogen production to
estimate N2O emissions.
Uncertainty
An analysis was conducted for the manure management
emission estimates presented in EPA's Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2001 (EPA
2003a, ERG 2003) to determine the uncertainty associated
with estimating CH4 and N2O emissions from livestock
manure management. Because no substantial modifications
were made to the inventory methodology since the
development of these estimates, it is expected that this
analysis is applicable to the uncertainty associated with the
current manure management emission estimates.
The quantitative uncertainty analysis for this source
category was performed through the IPCC-recommended
Tier 2 uncertainty estimation methodology, the Monte Carlo
Stochastic Simulation technique. The uncertainty analysis
was developed based on the methods used to estimate CH4
and N,O emissions from manure management systems.
A normal probability distribution was assumed for each
source data category. The series of equations used were
condensed into a single equation for each animal type and
state. The equations for each animal group contained four
to five variables around which the uncertainty analysis was
performed for each state.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 6-8. Manure management CH4
emissions in 2005 were estimated to be between 33.8 and
49.5 Tg CO2 Eq. at a 95 percent confidence level, which
indicates a range of 18 percent below to 20 percent above the
actual 2005 emission estimate of 41.3 Tg CO2 Eq. At the 95
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Manure Management
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.)
Manure Management
Manure Management
CH4
N20
41.3
9.5
Lower Bound
33.8
8.0
Upper Bound
49.5
11.8
Lower Bound
-18%
-16%
Upper Bound
+20%
+24%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
2 Total Kjeldahl nitrogen is a measure of organically bound nitrogen and ammonia nitrogen.
Agriculture 69
-------
percent confidence level, N2O emissions were estimated to
be between 8.0 and 11.8 Tg CO2 Eq. (or approximately 16
percent below and 24 percent above the actual 2005 emission
estimate of 9.5 Tg CO2 Eq.).
QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted
consistent with the U.S. QA/QC plan. Tier 2 activities
focused on comparing estimates for the 2004 and 2005
Inventories for N2O emissions from managed systems and
CH4 emissions from livestock manure. All errors identified
were corrected. Order of magnitude checks were also
conducted, and corrections made where needed. Manure
nitrogen data were checked by comparing state-level data
with bottom up estimates derived at the county level and
summed to the state level. Similarly, a comparison was
made by animal and waste management system type for
the full time series, between national level estimates for
nitrogen excreted and the sum of county estimates for the
full time series.
Recalculations Discussion
A few changes have been incorporated into the overall
methodology for the manure management emission estimates.
State temperatures are now calculated using data from every
county in the state. The previous methodology linked the
temperature data to a list of counties/climate divisions that
were determined using a weather station list from the National
Climatic Data Center (NCDC). The list of weather stations,
however, did not include a match of county to climate division
for all U.S. counties. The new methodology for utilizing the
temperature data for the contiguous United States is to link
the temperature data by climate division to a complete list of
U.S. counties/climate divisions (NOAA2005). Although this
change in methodology provides a more accurate calculation
of state temperatures, it has little effect on the final temperature
calculations, MCFs, or emissions estimates.
Another major change in methodology was using
climate-specific MCFs for dry manure management systems.
In previous inventories, a "temperate" climate zone was
assumed for all U.S. states and years of the Inventory,
and the temperate MCFs for all dry manure management
systems were used in CH4 emission calculations. A climate
classification (cool, temperate, or warm) was assigned to
each state and year using the average state temperatures. New
climate-specific MCFs were incorporated into the current
Inventory for the following manure management systems:
pasture/range/paddock, daily spread, solid storage, dry
lot, burned for fuel, cattle deep bedding (<1 month and >1
month), composting—intensive windrow, and composting—
passive windrow. The change in status for some states from
temperate to cool climates and MCFs caused the most
significant changes in CH4 emissions for animal groups
that most rely on pasture/range/paddock waste management
systems (i.e., beef cattle, sheep, horses, and goats), which
showed decreased CH4 emissions for all years in the current
Inventory compared to the previous Inventory.
The percentage of dairy cattle, swine, and sheep on each
type of manure management system was also updated for the
2005 Inventory, based on farm size data from the 2002 USDA
Census of Agriculture. Liquid-based systems are in increasing
use for swine and dairy manure, due to the increasing farm
size for these animals. Sheep continue to be managed using
dry manure management systems. These manure management
system updates decreased N2O estimates and increased CH4
estimates for dairy cattle and increased N2O and CH4 estimates
for swine in the current Inventory.
Changes were also made to the current calculations
involving animal population data. Animal population data
were updated to reflect the final estimates reports from
USDA NASS, and 2002 USDA Census of Agriculture data
(USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c,2000a,2004a-
e, 2005a-d, 2006a-e). The population data in the most recent
final estimates reflect some adjustments due to USDA NASS
review. For horses, state-level populations were estimated
using the national FAO population data (FAO 2006) and the
state distributions from the 1992,1997, and 2002 Census of
Agriculture (USDA 2005e).
For the current Inventory, new VS production and
nitrogen excretion rates were calculated for poultry hens
and pullets, based on 1990 to 2004 population and VS data
and nitrogen excretion data. This change was incorporated
because USDA now reports a combined hen and pullet
population, therefore weighted average rates for the
combined population were developed.
With these recalculations, CH4 emission estimates
from manure management systems are slightly higher than
reported in the previous Inventory for the years 1999 through
2004 and slightly lower for 1990 through 1998. On average,
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
annual emissions estimates are less than those of the previous
Inventory by less than one percent.
N2O emission estimates from manure management
systems have decreased for all years of the current Inventory
compared to the previous Inventory, by 47 percent on
average, due to the use of updated emission factors published
by IPCC (2006).
Planned Improvements
Although an effort was made to introduce the variability
in VS production due to differences in diet for beef and dairy
cows, heifers, and steer, further research is needed to confirm
and track diet changes over time. A methodology to assess
variability in swine VS production would be useful in future
inventory estimates.
Research will be initiated into the estimation and
validation of the maximum CH4-producing capacity of
animal manure (B0), for the purpose of obtaining more
accurate data to develop emission estimates.
The American Society of Agricultural Engineers proposed
new standards for manure production characteristics in 2004
and finalized them in 2005. These data will be investigated
and evaluated for incorporation into future estimates.
The methodology to calculate MCFs for liquid systems
will be examined to determine how to account for a maximum
temperature in the liquid systems. It will also be evaluated
whether the lower bound estimate of temperature established
for lagoons and other liquid systems should be revised for use
with this methodology. Additionally, available research will
be investigated to develop a relationship between ambient
air temperature and temperature in liquid waste management
systems in order to improve that relationship in the MCF
methodology.
The development of the National Ammonia Emissions
Inventory for the United States (EPA 2004) used similar data
sources to the current estimates of emissions from manure
management, and through the course of development of the
ammonia inventory, updated waste management distribution
data were identified. Future inventory estimates will
incorporate these updated data.
The estimation of indirect N2O emissions associated
with manure management (e.g., ammonia NOX) is currently
included in the Agricultural Soil Management source
category. Based on IPCC (2006), a methodology to estimate
these indirect NiO emissions separately and include them in
the Manure Management source category will be evaluated
for future inventories.
The IPCC provides a suggested MCF for poultry waste
management operations of 1.5 percent. Additional study
is needed in this area to determine if poultry high-rise
houses promote sufficient aerobic conditions to warrant
a lower MCF.
A minor error was identified in the MCF calculations,
which used a value of 303.17 K instead of 303.15 K when
calculating the f factor. This error will be corrected in future
inventory estimates. This error has little impact overall on the
CH4 emission estimates. The calculated MCFs are expected
to increase up to 0.1 percent, and the overall CH4 emissions
are expected to increase by up to 0.05 percent.
6.3. Rice Cultivation (IPCC Source
Category 4C)
Most of the world's rice, and all rice in the United States,
is grown on flooded fields. When fields are flooded, aerobic
decomposition of organic material gradually depletes most
of the oxygen present in the soil, causing anaerobic soil
conditions. Once the environment becomes anaerobic, CH4
is produced through anaerobic decomposition of soil organic
matter by methanogenic bacteria. As much as 60 to 90 percent
of the CH4 produced is oxidized by aerobic methanotrophic
bacteria in the soil (some oxygen remains at the interfaces of
soil and water, and soil and root system) (Holzapfel-Pschorn
et al. 1985, Sass et al. 1990). Some of the CH4 is also leached
away as dissolved CH4 in floodwater that percolates from
the field. The remaining un-oxidized CH4 is transported
from the submerged soil to the atmosphere primarily by
diffusive transport through the rice plants. Minor amounts
of CH4 also escape from the soil via diffusion and bubbling
through floodwaters.
The water management system under which rice is
grown is one of the most important factors affecting CH4
emissions. Upland rice fields are not flooded, and therefore
are not believed to produce CH4. In deepwater rice fields
(i.e., fields with flooding depths greater than one meter),
the lower stems and roots of the rice plants are dead, so
the primary CH4 transport pathway to the atmosphere is
blocked. The quantities of CH4 released from deepwater
fields, therefore, are believed to be significantly less than
Agriculture 6-11
-------
the quantities released from areas with shallower flooding
depths. Some flooded fields are drained periodically during
the growing season, either intentionally or accidentally. If
water is drained and soils are allowed to dry sufficiently,
CH4 emissions decrease or stop entirely. This is due to soil
aeration, which not only causes existing soil CH4 to oxidize
but also inhibits further CH4 production in soils. All rice
in the United States is grown under continuously flooded
conditions; none is grown under deepwater conditions. Mid-
season drainage does not occur except by accident (e.g., due
to levee breach).
Other factors that influence CH4 emissions from flooded
rice fields include fertilization practices (especially the use of
organic fertilizers), soil temperature, soil type, rice variety,
and cultivation practices (e.g., tillage, seeding, and weeding
practices). The factors that determine the amount of organic
material available to decompose (i.e., organic fertilizer use,
soil type, rice variety,3 and cultivation practices) are the most
important variables influencing the amount of CH4 emitted
over the growing season; the total amount of CH4 released
depends primarily on the amount of organic substrate
available. Soil temperature is known to be an important
factor regulating the activity of methanogenic bacteria, and
therefore the rate of CH4 production. However, although
temperature controls the amount of time it takes to convert
a given amount of organic material to CH4, that time is short
relative to a growing season, so the dependence of total
emissions over an entire growing season on soil temperature
is weak. The application of synthetic fertilizers has also
been found to influence CH4 emissions; in particular, both
nitrate and sulfate fertilizers (e.g., ammonium nitrate and
ammonium sulfate) appear to inhibit CH4 formation.
Rice is cultivated in eight states: Arkansas, California,
Florida, Louisiana, Mississippi, Missouri, Oklahoma, and
Texas.4 Soil types, rice varieties, and cultivation practices
for rice vary from state to state, and even from farm to
farm. However, most rice farmers apply organic fertilizers
in the form of residue from the previous rice crop, which is
left standing, disked, or rolled into the fields. Most farmers
also apply synthetic fertilizer to their fields, usually urea.
Nitrate and sulfate fertilizers are not commonly used in rice
cultivation in the United States. In addition, the climatic
conditions of Arkansas, southwest Louisiana, Texas, and
Florida allow for a second, or ratoon, rice crop. CH4 emissions
from ratoon crops have been found to be considerably higher
than those from the primary crop. This second rice crop is
produced from regrowth of the stubble after the first crop
has been harvested. Because the first crop's stubble is left
Table 6-9: CH4 Emissions from Rice Cultivation (Tg C02 Eq.)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990
5.1
2.1
0.7
+
1.0
0.4
0.1
+
0.6
2.1
+
+
1.1 -
0.9
7.1
1995
5.6
2.4
0.8
0.0
1.0
0.5
0.2
0.0
0.6
2.1
0.0
0.1
1.1
0.8
7.6
2000
5.5
2.5
1.0
+
0.9
0.4
0.3
+
0.4
2.0
+
0.1
1.3
0.7
7.5
2001
5.9
2.9
0.8
+
1.0
0.5
0.4
+
0.4
1.7
+
+
1.1
0.6
7.6
2002
5.7
2.7
0.9
+
1.0
0.5
0.3
+
0.4
1.1
+
+
0.5
0.5
6.8
2003
5.4
2.6
0.9
+
0.8
0.4
0.3
+
0.3
1.5
+
+
1.0
0.5
6.9
2004
6.0
2.8
1.1
+
1.0
0.4
0.3
+
0.4
1.6
+
+
1.1
0.5
7.6
2005
6.0
2.9
0.9
+
0.9
0.5
0.4
+
0.4
0.9
+
+
0.5
0.4
6.9
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
3 The roots of rice plants shed organic material, which is referred to as "root exudate." The amount of root exudate produced by a rice plant over a
growing season varies among rice varieties.
4 Additionally, a very small amount of rice is grown on about 20 acres in South Caro ina; however, this amount was determined to be too insignificant
to warrant inclusion in national emissions estimates.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19*10-2005
-------
Table 6-10: CH4 Emissions from Rice Cultivation (Gg)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990
241
102
34
1
46
21
7
+
30
98
+
2
52
45
339
1995
265
114
40
2
48
24
10
+
27
98
+
4
54
40
363
2000
260
120
47
2
41
19
14
+
18
97
+
2
61
34
357
2001
283
138
40
1
46
22
18
+
18
81
+
2
52
27
364
2002
274
128
45
1
45
22
15
+
18
52
+
2
25
24
325
2003
255
124
43
+
38
20
15
+
15
73
+
2
50
22
328
2004
283
132
50
1
45
20
17
+
19
77
+
2
50
24
360
2005
287
139
45
1
45
22
18
+
17
41
1
2
22
17
328
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
behind in ratooned fields, and there is no time delay between
cropping seasons (which would allow the stubble to decay
aerobically), the amount of organic material that is available
for anaerobic decomposition is considerably higher than with
the first (i.e., primary) crop.
Rice cultivation is a small source of CH4 in the United
States (Table 6-9 and Table 6-10). In 2005, CH4 emissions
from rice cultivation were 6.9 Tg CO2 Eq. (328 Gg).
Although annual emissions fluctuated unevenly between the
years 1990 and 2005, ranging from an annual decrease of
11 percent to an annual increase of 17 percent, there was an
overall decrease of 3 percent over the fifteen-year period, due
to an overall decrease in primary crop area.1 The factors that
affect the rice acreage in any year vary from state to state,
although the price of rice relative to competing crops is the
primary controlling variable in most states.
Methodology
The IPCC/UNEP/OECD/IEA (1997) recommends using
harvested rice areas and area-based seasonally integrated
emission factors (i.e., amount of CH4 emitted over a
growing season per unit harvested area) to estimate annual
CH4 emissions from rice cultivation. This Inventory uses
the recommended methodology and employs U.S.-specific
emission factors derived from rice field measurements.
Seasonal emissions have been found to be much higher for
ratooned crops than for primary crops, so emissions from
ratooned and primary areas are estimated separately using
emission factors that are representative of the particular
growing season. This approach is consistent with IPCC Good
Practice Guidance (IPCC 2000).
The harvested rice areas for the primary and ratoon
crops in each state are presented in Table 6-11. Primary crop
areas for 1990 through 2005 for all states except Florida and
Oklahoma were taken from U.S. Department of Agriculture's
Field Crops Final Estimates 1987-1992 (USDA 1994),
Field Crops Final Estimates 1992-1997 (USDA 1998),
Field Crops Final Estimates 1997-2002 (USDA 2003), and
Crop Production Summary (USDA 2005, 2006). Harvested
rice areas in Florida, which are not reported by USDA,
were obtained from: Tom Schueneman (1999b, 1999c,
2000. 200la) and Arthur Kirstein (2003, 2006), Florida
agricultural extension agents; Dr. Chris Deren (2002) of the
Everglades Research and Education Centre at the University
of Florida; and Gaston Cantens (2004,2005), Vice President
of Corporate Relations of the Florida Crystals Company.
Harvested rice area in Florida for 2005 was unavailable
and set equal to the 2004 figure (Kirstein 2006, Cantens
2005). Harvested rice areas for Oklahoma, which also are
not reported by USDA, were obtained from Danny Lee of
the Oklahoma Farm Services Agency (2003, 2004, 2005,
2006). Acreages for the ratoon crops were derived from
conversations with the agricultural extension agents in each
state. In Arkansas, ratooning occurred only in 1998, 1999,
3 The 11 percent decrease occurred between 1992 and 1993 and 2001 and 2002; the 17 percent increase happened between 1993 and 1994.
Agriculture 6-13
-------
Table 6-11: Rice Areas Harvested (Hectares)
State/Crop
Arkansas
Primary
Ratoon*
California
Florida
Primary
Ratoon
Louisiana
Primary
Ratoon
Mississippi
Missouri
Oklahoma
Texas
Primary
Ratoon
Total Primary
Total Ratoon
Total
1990
485,
159,
4,
633
0
854
978
2,489
220,
66,
101,
32,
142,
57,
1,148,
125,
1,273,
558
168
174
376
617
857
143
047
799
847
1995
542
188
9
4
230
69
116
45
128
51
1,261
125
1,387
,291
0
,183
,713
,856
,676
,203
,552
,326
364
,693
,477
,796
,536
,333
2000
570,619
0
221,773
7,801
3,193
194,253
77,701
88,223
68,393
283
86,605
43,302
1,237,951
124,197
1,362,148
2001
656,010
190
4
2
220
66
102
83
87
34
1,345
104
1,449
0
,611
,562
,752
,963
,289
,388
,772
265
,414
,966
,984
,006
,991
2002
608,256
0
213,679
5,077
2,734
216,512
32,477
102,388
73,654
274
83,367
30,846
1,303,206
66,056
1,369,262
2003
588,830
0
205,180
2,369
2,369
182,113
63,739
94,699
69,203
53
72,845
27,681
1,215,291
93,790
1,309,081
2004
629,300
0
238,770
3,755
2,899
215,702
64,711
94,699
78,915
158
88,223
30,878
1,349,523
98,488
1,448,011
2005
661,675
662
212,869
3,755
2,899
212,465
27,620
106,435
86,605
271
81,344
21,963
1,365,418
53,144
1,418,562
*Arkansas ratooning occurred only in 1998,1999, and 2005.
Note: Totals may not sum due to independent rounding.
and 2005, when the ratooned area was less than 1 percent
of the primary area (Slaton 1999, 2000, 2001a; Wilson
2002, 2003, 2004, 2005, 2006). In Florida, the ratooned
area was 50 percent of the primary area from 1990 to 1998
(Schueneman 1999a), about 65 percent of the primary area in
1999 (Schueneman 2000), around 41 percent of the primary
area in 2000 (Schueneman 2001a), about 60 percent of the
primary area in 2001 (Deren 2002), about 54 percent of the
primary area in 2002 (Kirstein 2003), about 100 percent
of the primary area in 2003 (Kirstein 2004), and about 77
percent of the primary area in 2004 (Cantens 2005). Ratooned
area for 2005 was set equal to 2004, since no new data were
available. In Louisiana, the percentage of the primary area
that was ratooned was constant at 30 percent over the 1990
to 1999 period, increased to approximately 40 percent in
2000, returned to 30 percent in 2001, dropped to 15 percent
in 2002, rose to 35 percent in 2003, returned to 30 percent in
2004, and dropped to 13 percent in 2005 (Linscombe 1999,
2001a, 2002, 2003, 2004, 2005, 2006; Bollich 2000). In
Texas, the percentage of the primary area that was ratooned
was constant at 40 percent over the 1990 to 1999 period,
increased to 50 percent in 2000 due to an early primary crop,
and then decreased to 40 percent in 2001,37 percent in 2002,
38 percent in 2003, 35 percent in 2004, and 27 percent in
2005 (Klosterboer 1999, 2000, 2001a, 2002, 2003; Stansel
2004, 2005; Texas Agricultural Experiment Station 2006).
California, Mississippi, Missouri, and Oklahoma have not
ratooned rice over the period 1990-2005 (Guethle 1999,
2000,2001a, 2002,2003,2004,2005,2006; Lee 2003,2004,
2005, 2006; Mutters 2002, 2003, 2004, 2005; Street 1999,
2000, 2001a, 2002.2003; Walker 2005).
To determine what seasonal CH4 emission factors
should be used for the primary and ratoon crops, CH4 flux
information from rice field measurements in the United
States was collected. Experiments which involved atypical or
nonrepresentative management practices (e.g., the application
of nitrate or sulfate fertilizers, or other substances believed
to suppress CH4 formation), as well as experiments in which
measurements were not made over an entire flooding season
or floodwaters were drained mid-season, were excluded
from the analysis. The remaining experimental results6 were
then sorted by season (i.e., primary and ratoon) and type
of fertilizer amendment (i.e., no fertilizer added, organic
fertilizer added, and synthetic and organic fertilizer added).
6 In some of these remaining experiments, measurements from individual plots were excluded from the analysis because of the aforementioned
reasons. In addition, one measurement from the ratooned fields (i.e., the flux of 2.041 g/nr/day in Lindau and Bollich 1993) was excluded, because
this emission rate is unusually high compared to other flux measurements in the United States, as well as in Europe and Asia (IPCC/UNEP/OECD/
IEA 1997).
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
The experimental results from primary crops with added
synthetic and organic fertilizer (Bossio et al. 1999; Cicerone
etal. 1992;Sassetal. 199la, 199Ib) were averaged to derive
an emission factor for the primary crop, and the experimental
results from ratoon crops with added synthetic fertilizer
(Lindau and Bollich 1993, Lindau et al. 1995) were averaged
to derive an emission factor for the ratoon crop. The resultant
emission factor for the primary crop is 210 kg CH4/hectare-
season, and the resultant emission factor for the ratoon crop
is 780 kg CH4/hectare-season.
Uncertainty
The largest uncertainty in the calculation of CH4
emissions from rice cultivation is associated with the
emission factors. Seasonal emissions, derived from field
measurements in the United States, vary by more than
one order of magnitude. This inherent variability is due to
differences in cultivation practices, in particular, fertilizer
type, amount, and mode of application; differences in cultivar
type; and differences in soil and climatic conditions. A portion
of this variability is accounted for by separating primary from
ratooned areas. However, even within a cropping season or
a given management regime, measured emissions may vary
significantly. Of the experiments used to derive the emission
factors applied here, primary emissions ranged from 22 to
479 kg CH4/hectare-season and ratoon emissions ranged
from 481 to 1,490 kg CH4/hectare-season. The uncertainty
distributions around the primary and ratoon emission factors
were derived using the distributions of the relevant primary
or ratoon emission factors available in the literature and
described above. Variability about the rice emission factor
means was not normally distributed for either primary or
ratooned crops, but rather skewed, with a tail trailing to the
right of the mean. A lognormal statistical distribution was,
therefore, applied in the Tier 2 Monte Carlo analysis.
Other sources of uncertainty include the primary rice-
cropped area for each state, percent of rice-cropped area
that is ratooned, and the extent to which flooding outside of
the normal rice season is practiced. Expert judgment was
used to estimate the uncertainty associated with primary
rice-cropped area for each state at 1 to 5 percent, and a
normal distribution was assumed. Uncertainties were applied
to ratooned area by state, based on the level of reporting
performed by the state. No uncertainties were calculated for
the practice of flooding outside of the normal rice season
because CH4 flux measurements have not been undertaken
over a sufficient geographic range or under a broad enough
range of representative conditions to account for this source
in the emission estimates or its associated uncertainty.
To quantify the uncertainties for emissions from rice
cultivation, a Monte Carlo (Tier 2) uncertainty analysis
was performed using the information provided above. The
results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 6-12. Rice cultivation CH4 emissions
in 2005 were estimated to be between 2.1 and 18.6 Tg CO2
Eq. at a 95 percent confidence level, which indicates a range
of 70 percent below to 170 percent above the actual 2005
emission estimate of 6.9 Tg CO2 Eq.
QA/QC and Verification
A source-specific QA/QC plan for rice cultivation was
developed and implemented. This effort included a Tier 1
analysis, as well as portions of a Tier 2 analysis. The Tier 2
procedures focused on comparing trends across years, states,
and cropping seasons to attempt to identify any outliers or
inconsistencies. No problems were found.
Recalculations Discussion
An error in the spreadsheets used to calculate emissions
estimates was found during the development of the current
Inventory and corrected, resulting in a 0.06 percent decrease
in the 2004 emission estimates.
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Rice Cultivation
CH4
6.9
2.1
18.6
-70%
+ 170%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6-15
-------
6,4. Agricultural Soil Management
(IPCC Source Category 40)
Nitrous oxide is produced naturally in soils through the
microbial processes of nitrification and denitrification.7 A
number of agricultural activities increase mineral nitrogen
(N) availability in soils, thereby increasing the amount
available for nitrification and denitrification, and ultimately
the amount of N2O emitted. These activities increase soil
mineral N either directly or indirectly (see Figure 6-2).
Direct increases occur through a variety of management
practices that add or lead to greater release of mineral N
in the soil, including: fertilization; application of managed
livestock manure and other organic materials such as sewage
sludge; deposition of manure on soils by domesticated
animals in pastures, rangelands, and paddocks (PRP) (i.e.,
by grazing animals and other animals whose manure is
not managed); production of N-fixing crops and forages;
retention of crop residues; and cultivation of organic soils
(i.e., soils with a high organic matter content, otherwise
known as histosols).8 Other agricultural soil management
activities, including irrigation, drainage, tillage practices,
and fallowing of land, can influence N mineralization in
soils and thereby affect direct emissions. Mineral N is
also made available in soils through decomposition of
soil organic matter and plant litter, as well as asymbiotic
fixation of N from the atmosphere.9 Indirect emissions of
N2O occur through two pathways: (1) volatilization and
subsequent atmospheric deposition of applied N,10 and (2)
surface runoff and leaching of applied N into groundwater
and surface water. Direct emissions from agricultural lands
(i.e., croplands and grasslands) are included in this section,
while direct emissions from forest lands and settlements
are presented in the Land Use, Land-Use Change, and
Forestry chapter. In contrast, indirect N2O emissions from
all sources (agriculture, forest lands, settlements, and
managed manure) are reported in this chapter.
Agricultural soils produce the majority of N2O emissions
in the United States. Estimated emissions from this source
in 2005 were 365.1 Tg CO2 Eq. (1,178 Gg N2O) (see Table
6-13 and Table 6-14). Annual agricultural soil management
N2O emissions fluctuated between 1990 and 2005, although
overall emissions were 0.5 percent lower in 2005 than in
1990. Year-to-year fluctuations are largely a reflection of
annual variation in weather patterns, synthetic fertilizer use,
and crop production. On average, cropland accounted for
approximately 75 percent of total direct emissions, while
grassland accounted for approximately 25 percent.
Estimated direct and indirect N2O emissions by sub-
source category are provided in Table 6-15 and Table 6-16.
Figure 6-3 through Figure 6-6 show regional patterns
in N2O emissions for direct sources and regional patterns
of N losses leading to indirect N2O emissions, respectively,
for major crops and grasslands across the United States.
Direct N2O emissions tend to be high in the Corn Belt
(Illinois, Iowa, Southern Minnesota and Wisconsin, and
Eastern Nebraska). A large portion of the land in many of
these counties is covered with high input corn and N-fixing
soybean cropping, resulting in high emissions on a per
county basis. Emissions are also high in some counties in the
Dakotas, Kansas, Eastern Colorado, Oklahoma, and Texas.
High input irrigated cropping and moderate input dryland
wheat cropping are major contributors to emissions in these
counties. Emissions are high along the lower Mississippi
Valley because this area is intensively cropped and fine-
textured soils along the river facilitate denitrification and high
N2O emissions. Emissions are also high in some counties in
California where intensive, irrigated cropping is a dominant
land use. Emissions are low in the eastern United States
because a small portion of land in most of these counties is
cropped, and also low in many counties in the West where
rainfall and access to irrigation water are limited. Counties
with Isss than a minimum number of cropped acres were
not simulated by DAYCENT (white areas). Emissions from
7 Nitrification and denitrification are driven by the activity of microorganisms in soils. Nitrification is the aerobic microbial oxidation of ammonium
(NH4) to nitrate (NO,), and denitrification is the anaerobic microbial reduction of nitrate to nitrogen gas (N2). Nitrous oxide is a gaseous intermediate
product in the reaction sequence of denitrification, which leaks from microbial cells into the soil and then into the atmosphere. Nitrous oxide is also
produced during nitrification, although by a less well-understood mechanism (Nevison 2000).
8 Drainage and cultivation of organic soils in former wetlands enhances mineralization of N-rich organic matter, thereby enhancing N2O emissions
from these soils.
Q Asymbiotic N fixation is the fixation of atmospheric N2 by bacteria living in soils that do not have a direct relationship with plants.
10 These processes entail volatilization of applied N as ammonia (NH,) and oxides of N (NOX). transformation of these gases within the atmosphere
(or upon deposition), and deposition of the N primarily in the form of paniculate ammonium (NH4), nitric acid (HNO3), and NOS.
fi-16 Inventory of U.S. Greenhouse Gas
and Sinks. 13?!) -2005
-------
Figure 6-2
Agricultural Sources and Pathways of N that Result in N20 Emissions
r*~*-*"*\
N Emissions
Biomass Burning
Storage and Management
of Livestock Manure
Synthetic N Fertilizers
Organic
Amendments
Includes both commercial <
non-commercial fertilizers i
Urine and Dung from
Grazing Animals
Crop Residues
Includes above- and belowground
residues for all crops (non-N and N
crops and pastures following rer
Mineralization of
Soil Organic Matter
N-Fixing Crops
This graphic illustrates the sources and pathways of nitrogen that result in direct and indirect NjO emissions from soils in the United States. Sources of nitrogen applied to, or deposited
on, soils are represented with arrows on the left-hand side of the graphic. Emission pathways are also shown with arrows. On the lower right-hand side is a cut-away view of a
representative section of a managed soil; histosol cultivation is represented here.
Agriculture 617
-------
Table 6-13: N20 Emissions from Agricultural Soils (Tg C02 Eq.)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use Types)
Cropland
Grassland
Managed Manure3
Forest Land
Settlements
Total
1990
310.1
222.1
88.0
56.8
27.2
20.4
7.5
+
1.7
366.9
1995
292.0
214.2
77.8
61.4
27.2
24.3
8.0
0.1
1.8
353.4
2000
324.4
250.5
73.9
52.4
25.0
17.1
8.4
0.1
1.8
376.8
2001
327.4
252.6
74.8
61.6
26.1
25.1
8.5
0.1
1.8
389.0
2002
314.1
234.0
80.1
52.0
22.5
18.9
8.7
0.1
1.9
366.1
2003
297.4
226.4
71.0
52.8
25.7
16.5
8.5
0.1
1.9
350.2
2004
292.1
220.9
71.3
46.6
20.1
16.0
8.5
0.1
2.0
338.8
2005
310.5
234.2
76.4
54.6
26.2
17.8
8.5
0.1
1.9
365.1
+ Less than 0.05 Tg C02 Eq.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage, including both volatilization and leaching/runoff.
Table 6-14: N20 Emissions from Agricultural Soils (Gg N20)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use Types)
Cropland
Grassland
Managed Manure3
Forest Land
Settlements
Total
1990
1,000
716
284
183
88
66
24
+
5
1,184
1995
942
691
251
198
88
78
26
+
6
1,140
2000
1,046
808
238
169
81
55
27
+
6
1,215
2001
1,056
815
241
199
84
81
27
+
6
1,255
2002
1,013
755
259
168
72
61
28
+
6
1,181
2003
959
730
229
170
83
53
28
+
6
1,130
2004
942
712
230
150
65
52
27
+
6
1,093
2005
1,002
755
246
176
84
57
28
+
6
1,178
+ Less than 0.5 Gg N20.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage, including both volatilization and leaching/runoff.
Table 6-15: Direct N20 Emissions from Agricultural Soils by Land Use and N Input (Tg C02 Eq.)
Activity
Cropland
Mineral Soils
Synthetic Fertilizer
Organic Amendment3
Residue Nb
Other0
Organic Soils
Grassland
Synthetic Fertilizer
PRP Manure
Managed Manure"
Sewage Sludge
Residue Nb
Other0
Total
1990
222.1
219.3
83.6
10.3
15.0
110.3
2.8
88.0
2.0
16.4
0.4
0.2
34.4
34.5 •.:.:•
310.1
1995
214.2
211.4
85.1
10.9
15.8
99.6
2.8
77.8
1.7 .
15.8
0.4
0.4
29.9
29.6
292.0
2000
250.5
247.6
91.9
12.1
18.5
125.1
2.9
73.9
1.6
16.8
0.4
0.5
28.1
26.5
324.4
2001
252.6
249.7
94.2
12.9
16.6
126.0
2.9
74.8
1.7
15.3
0.4
0.5
29.9
27.0
327.4
2002
234.0
231.1
90.2
12.0
15.1
113.8
2.9
80.1
1.8
20.6
0.4
0.5
28.0
28.8
314.1
2003
226.4
223.5
84.6
11.2
18.3
109.4
2.9
71.0
1.6
15.5
0.3
0.5
27.9
25.2
297.4
2004
220.9
217.9
88.5
11.6
14.7
103.1
2.9
71.3
1.7
17.2
0.4
0.5
26.4
25.0
292.1
2005
234.2
231.2
86.9
11.7
16.0
116.6
2.9
76.4
1.7
14.3
0.4
0.5
29.8
29.7
310.5
a Organic amendment inputs include managed manure amendments and other commercial organic fertilizer (i.e., dried blood, dried manure, tankage,
compost, and other).
b Residue N inputs include unharvested fixed N from legumes as well as crop residue N.
c Other N inputs include mineralization from decomposition of soil organic matter as well as asymbiotic fixation of N from the atmosphere.
d Accounts for managed manure that is applied to grassland soils.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2(105
-------
Table 6-16: Indirect N20 Emissions from all Land-Use Types and Managed Manure Systems (Tg C02 Eq.)
Activity
Cropland
Volatilization and Atm. Deposition
Surface Leaching & Run-Off
Grassland
Volatilization and Atm. Deposition
Surface Leaching & Run-Off
Managed Manure Systems
Volatilization and Atm. Deposition3
Forest Land
Volatilization and Atm. Deposition
Surface Leaching & Run-Off
Settlements
Volatilization and Atm. Deposition
Surface Leaching & Run-Off
Total
1990
27.2
4.6
22.6
20.4
10.7
9.6
7.5
7.5
+
+
+
1.7
0.5
1.2
56.8
1995
27.2
4.9
22.3
24.3
10.3
14.0
8.0
8.0
0.1
+
+
1.8
0.6
1.2
61.4
2000
25.0
5.3
19.7
17.1
9.3
7.8
8.4
8.4
0.1
+
0.1
1.8
0.6
1.3
52.4
2001
26.1
4.9
21.2
25.1
9.4
15.7
8.5
8.5
0.1
+
0.1
1.8
0.6
1.2
61.6
2002
22.5
5.0
17.5
18.9
9.3
9.5
8.7
8.7
0.1
+
0.1
1.9
0.6
1.3
52.0
2003
25.7
5.4
20.3
16.5
9.4
7.1
8.5
8.5
0.1
+
0.1
1.9
0.6
1.3
52.8
2004
20.1
5.3
14.8
16.0
9.1
6.9
8.5
8.5
0.1
+
0.1
2.0
0.6
1.3
46.6
2005
26.2
5.4
20.7
17.8
9.9
7.9
8.5
8.5
0.1
+
0.1
1.9
0.6
1.3
54.6
+ Less than 0.05 Tg C02 Eq.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage.
these counties were calculated at the national scale using
Tier 1 methodology.
Direct emissions (Tg CO2 Eq./county/year) from
grasslands are highest in the western United States (Figure
6-4) where counties tend to be large and a high proportion of
the land in many of these counties is used for cattle grazing.
Some counties in the Great Lake states, the Northeast, and
Florida have moderate county level emissions even though
emissions from these areas tend to be high on a per unit
area basis, because the total amount of grazed land in these
counties is much less than many counties in the West.
Indirect emissions for crops and grasslands (Figure 6-5
and Figure 6-6) show patterns similar to direct emissions,
because the factors that control direct emissions (N inputs,
weather, soil type) also influence indirect emissions.
However, there are some exceptions, because the processes
that contribute to indirect emissions (NO3 leaching, N
volatilization) do not respond in exactly the same manner to
these controls as the processes that control direct emissions
(nitrification and denitrification). For example, coarse-
textured soils facilitate nitrification and moderate direct
emissions in Florida grasslands, but indirect emissions
are relatively high in Florida grasslands due to high rates
of N volatilization and NO3 leaching in coarse-textured
soils. Indirect emissions from crops in some counties in
the Carolinas are also relatively high compared to direct
emissions because these soils tend to be coarse-textured.
Methodology
The Revised 1996 1PCC Guidelines (IPCC/UNEP/
OECD/IEA 1997) divide the Agricultural Soil Management
source category into three components: (1) direct emissions
from agricultural soils due to N additions to cropland and
grassland mineral soils, planting of legumes on cropland
and grassland soils, and drainage and cultivation of organic
cropland soils; (2) direct emissions from soils due to the
deposition of manure by livestock on PRP grasslands; and
(3) indirect emissions from soils and water due to N additions
and manure deposition to soils that leads to volatilization,
leaching, or runoff of N and subsequent conversion to
N2O. Moreover, the 2006 IPCC Guidelines (IPCC 2006)
recommend reporting total emissions from managed lands,
and, therefore, this chapter includes estimates for direct
emissions due to decomposition of soil organic matter and
litter, and asymbiotic fixation of N from the atmosphere."
The methodology used to estimate emissions from
agricultural soil management in the United States is based
on a combination of IPCC Tier 1 and 3 approaches. A Tier
3, process-based model (DAYCENT) was used to estimate
direct emissions from major crops on mineral (i.e., non-
organic) soils; as well as most of the direct emissions from
grasslands. The Tier 3 approach is more refined for estimating
N2O emissions in the United States, accounting for more of
the environmental and management influences on soil N2O
emissions than the IPCC Tier 1 method (see Box 6-1 for
" N inputs from asymbiotic N fixation are not directly addressed in 2006 IPCC Guidelines, but are a component of the total emissions from managed
lands and are included in the Tier 3 approach developed for this Inventory.
Agriculture 6-19
-------
Figure 6-3
Major Crops, Average Annual Direct N20 Emissions, 1990-2005 (la C02 EqWounty/yebr)
Tg C02 Eq/County/yr
Q| Not simulated
D <0.05
D 0.05 -0.1
D 0.1-0.2
D 0.2-0.3
• >0.5
Figure 6-4
Grasslands, Average Annual Direct N20 Emissions, 11990^2005 (li C02 Eq./cpuiity/year)
Tg C02 Eq/County/yr
G Not simulated
C] <0.01
D 0.01-0.025
D 0.025-0.05
DO.05-0.1
13 0.1-0.25
H >0.25
6-20 Inventory of U.S. Greenhouse Gas h™ss>i.ns acs Sinks: 1S9ir-2eOb
-------
Figure 6-5
Major Crops, Average Annual N Losses Leading to indirect N20 Emissions, 1990-2005 (Tg C02 Eq./county/year)
Tg C02 Eq/County/yr
Q Not simulated
D< 0.0025
DO.0025-0.005
DO.005-0.01
Do.01-0.02
13 >0.04
Figure 6-6
grasslands, Average Annual N Losses Leading to indirect N20 Emissions, 1990-2005 (Tg C02 Eq./county/year)
Tg C02 Eq/County/yr
Q| Not simulated
n <0.005
D 0.005-0.01
D 0.01-0.02
D 0.02-0.05
H]0.05- 0 1
Agriculture 6
-------
Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N20 Emissions
The Tier 1 approach (IPCC 2006) is based on multiplying activity data on different N sources (e.g., synthetic fertilizer, manure, N
fixation, etc.) by the appropriate default IPCC emission factors to estimate N20 emissions on a source-by-source basis. The Tier 3 approach
developed for this Inventory employs a process-based model (i.e., DAYCENT) and is based on the interaction of N inputs and the environmental
conditions at a specific location. Consequently, it is necessary not only to know the amount of N inputs but also the conditions under which
the anthropogenic activity is increasing mineral N in a soil profile. The Tier 1 approach requires a minimal amount of activity data, readily
available in most countries (e.g., total N applied to crops); calculations are simple; and the methodology is highly transparent. The Tier
3 approach is thought to produce more accurate estimates; it accounts for land-use and management impacts and their interaction with
environmental factors (i.e., weather patterns and soil characteristics), which may enhance or dampen anthropogenic influences. However, the
Tier 3 approach requires more refined activity data (e.g., crop-specific N amendment rates, daily weather, soil types, etc.) and considerable
computational resources and programming expertise. The Tier 3 methodology is less transparent. Another important difference between
the Tier 1 and Tier 3 approaches relates to assumptions regarding N cycling. Tier 1 assumes that N added to a system is subject to N20
emissions only during that year; e.g., N added as fertilizer or through fixation contributes to N20 emissions for that year, but cannot be stored
in soils and contribute to N20 emissions in subsequent years. In contrast, the process-based model used in the Tier 3 approach includes
such legacy effects when N is mineralized from soil organic matter and emitted as N20 during subsequent years.
further elaboration). The Tier 1 IPCC methodology was used
to estimate direct emissions from non-major crops on mineral
soils, the portion of the grassland direct emissions that were
not estimated with the Tier 3 DAYCENT model, and direct
emissions from drainage and cultivation of organic cropland
soils. The Tier 1 approach was based on the 2006 IPCC
Guidelines (IPCC 2006), which was originally developed in
the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA
1997) and IPCC Good Practice Guidance Reports (IPCC 2000,
2003). A combination of DAYCENT and the IPCC Tier 1
method was used to estimate indirect emissions from soils.
The Agricultural Soil Management sector has adopted
several recommendations from IPCC (2006) that are
considered improvements over previous IPCC methods,
including: (1) estimating the contribution of N from crop
residues to indirect soil N2O emissions, (2) adopting the
revised emission factor for direct N2O emissions, (3)
removing double counting of emissions due to estimating
N-fixing crops in both the symbiotic and crop residue N
input categories, (4) using revised crop residue statistics to
compute N inputs to soil based on harvest yield data, and (5)
accounting for indirect as well as direct emissions from N
made available via mineralization of soil organic matter and
litter, in addition to asymbiotic fixation (i.e., computing total
emissions from managed land). Annex 3.11 provides more
detailed information on the methodologies and data used to
calculate N2O emissions from each component.
Direct N20 Emissions from Cropland Soils
Major Crop Types on Mineral Cropland Soils
The DAYCENT ecosystem model (Del Grosso et al.
2001. Parton et al. 1998) was used to estimate direct N2O
emissions from mineral cropland soils that are managed for
production of major crops, specifically corn, soybean, wheat,
alfalfa hay, other hay, sorghum, and cotton, representing
approximately 90 percent of total croplands in the United
States. DAYCENT simulated crop growth, soil organic
matter decomposition, greenhouse gas fluxes, and key
biogeochemical processes affecting N2O emissions, and the
simulations were driven by model input data generated from
daily weather records (Thornton et al. 1997,2000; Thornton
and Running 1999), land management surveys (see citations
below), and soil physical properties determined from national
soil surveys (Soil Survey Staff 2005).
DAYCENT simulations were conducted for each
major crop at the county scale in the United States. The
county scale was selected, because soil and weather data
were available for every county with more than 100 acres
of agricultural land. However, land management data (e.g.,
timing of planting, harvesting, intensity of cultivation) were
only available at the agricultural region level as defined by
the Agricultural Sector Model (McCarl et al. 1993). There
are 63 agricultural regions in the contiguous United States,
and most states correspond to one region, except for those
states with greater heterogeneity in agricultural practices,
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1999-2005
-------
where there are further subdivisions. While several cropping
systems were simulated for each county in an agricultural
region with county-level weather and soils data, the model
parameters that determined the influence of management
activities on soil N2O emissions (e.g., when crops were
planted/harvested) did not differ among the counties in
an agricultural region. Consequently, the results will best
represent emissions at the regional and national levels due
to the scale of management data.
Nitrous oxide emission estimates from DAYCENT
include the influence of N additions, crop type, irrigation,
and other factors in aggregate, and, therefore, it is not
possible to partition N2O emissions by anthropogenic
activity directly from model outputs (e.g., N2O emissions
from synthetic fertilizer applications cannot be distinguished
from those resulting from manure applications). Nitrous
oxide emissions from managed agricultural lands are the
result of interactions between the combined anthropogenic
interventions that are implemented (e.g., N fertilization,
manure application, tillage) and other driving variables, such
as weather and soil characteristics. These factors influence
key processes associated with N dynamics in the soil profile,
including immobilization of N by soil microbial organisms,
decomposition of organic matter, plant uptake, leaching,
runoff, and volatilization, as well as the processes leading to
N2O production (nitrification and denitrification). According
to IPCC/UNEP/OECD/IEA (1997), soil N2O inventories are
expected to report emissions from mineral soils associated
with mineral N fertilization, organic amendments, crop
residue N added to soils, and symbiotic N-fixation. In
addition, IPCC (2006) recommends reporting total N2O
emissions from managed lands, which would also include
"other N Inputs" from mineralization due to decomposition
of soil organic matter and litter, as well as asymbiotic fixation
of N from the atmosphere. To approximate emissions by
activity, the amount of mineral N added to the soil for each
of these practices was determined and then divided by the
total amount of mineral N that was made available in the
soil according to the DAYCENT model. The percentages
were then multiplied by the total N2O emissions in order
to approximate the portion attributed to key practices. This
approach is not precise because it assumes that all N made
available in soil has an equal probability of being released
as N2O, regardless of its source, which is unlikely to be the
case. Since it is not possible to track N flows from different
sources using the DAYCENT model, this approach allows
for further disaggregation by source of N, which is valuable
for reporting purposes.
Consequently, DAYCENT was used to estimate direct
NiO emissions due to mineral N available from: (1) the
application of synthetic fertilizers, (2) the application
of livestock manure, (3) the retention of crop residues
(i.e., leaving residues in the field after harvest), and (4)
mineralization of soil organic matter and litter, in addition
to asymbiotic fixation. This last source is generated
internally by the DAYCENT model. For each of the first
3 practices, annual increases in soil mineral N due to
anthropogenic activity were obtained or derived from the
following sources:
• Crop-specific N-fertilization rates: Data sources for
fertilization rates include Alexander and Smith (1990),
Anonymous (1924), Battaglin and Goolsby (1994),
Engle and Makela (1947),ERS (1994,2003), Fraps and
Asbury (1931), Ibach and Adams (1967), Ibach et al.
(1964), NFA (1946), NRIAI (2003), Ross and Mehring
(1938), Skinner (1931), Smalley et al. (1939), Taylor
(1994), USDA( 1966,1957,1954,1946). Information on
fertilizer use and rates by crop type for different regions
of the United States were obtained primarily from the
USDA Economic Research Service Cropping Practices
Survey (ERS 1997) with additional data from other
sources, including the National Agricultural Statistics
Service (NASS 1992, 1999, 2004).
• Managed manure production and application to
croplands and grasslands: Manure N amendments
applied to croplands and grasslands (not including
PRP manure) were determined using USDA Manure N
Management Databases for 1997 (Kellogg et al. 2000;
Edmonds et al. 2003). These values were scaled to
estimate values for other years based on estimates of
annual production of managed manure. The amount of
managed manure for each livestock type was calculated
by determining the population of animals that were on
feedlots or otherwise housed in order to collect and
manage the manure. Annual animal population data
for all livestock types, except horses and goats, were
obtained for all years from the U.S. Department of
Agriculture-National Agricultural Statistics Service
(USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000a,
2004a-e, 2005a-d, 2006a). Horse population data were
Agriculture 6-23
-------
obtained from the FAOSTAT database (FAO 2006).
Goat population data for 1992, 1997, and 2002 were
obtained from the Census of Agriculture (USDA
2005g); these data were interpolated and extrapolated
to derive estimates for the other years. Information
regarding the poultry turnover (i.e., slaughter) rate was
obtained from state Natural Resource Conservation
Service personnel (Lange 2000). Additional population
data for different farm size categories for dairy and
swine were obtained from the 1992 and 1997 Census
of Agriculture (USDA 2005g). These values may be
slightly high because about 5 percent of poultry manure
is used for feed (Carpenter 1992). However, poultry
manure production is relatively small compared to
other livestock categories, particularly cattle. Only a
portion of the managed manure N is applied to crop
and grassland soils according to Edmonds et al. (2003).
The difference between manure N applied to soils and
remaining N in the managed manure was assumed to
be lost through volatilization and leaching/runoff of N
species during treatment, storage, and transportation.
Instead of assuming that 20 percent of organic N
applied to soils is volatilized and 30 percent of applied
N was lost through leaching/runoff, as approximated
with IPCC (2006) methodology, volatilization and
N leaching/runoff from manure that was amended to
soils was calculated by the DAYCENT process-based
model. Frequency and rates of manure application to
cropland during the Inventory period were estimated
from data compiled by the USDA Natural Resources
Conservation Service for 1997 (Edmonds et al. 2003),
with adjustments based on managed manure N excretion
in other years of the Inventory.
• Nitrogen-fixing crops and forages, retention of crop
residue, N mineralization from soil organic matter, and
asymbiotic N fixation from the atmosphere: The IPCC
approach considers this information as separate activity
data. However, they are not considered separate activity
data for the DAYCENT simulations because residue
production, N fixation, mineralization of N from soil
organic matter, and asymbiotic fixation are internally
generated by the model. In other words, DAYCENT
accounts for the influence of N fixation, mineralization
of N from soil organic matter, and retention of crop
residue on N^O emissions, but these are not model
inputs. The total input of N from these sources is
determined during the model simulations.
• Historical and modern crop rotation and management
information (e.g., timing and type of cultivation,
timing of planting/harvest, etc.): These activity data
were derived from Hurd (1930, 1929), Latta (1938),
Iowa State College Staff Members (1946), Bogue
(1963), Hurt (1994), USDA (2004f), USDA (2000b) as
extracted by Eve (2001) and revised by Ogle (2002),
CTIC (1998), Piper et al. (1924), Hardies and Hume
(1927), Holmes (1902, 1929), Spillman (1902, 1905,
1907, 1908), Chilcott (1910), Smith (191 l),Kezer(ca.
1917), Hargreaves (1993), ERS (2002), Warren (1911),
Langston et al. (1922), Russell et al. (1922), Elliott and
Tapp (1928), Elliott (1933), Ellsworth (1929), Garey
(1929), Hodges et al. (1930), Bonnen and Elliott (1931),
Brenner et al. (2002, 2001), and Smith et al. (2002).
DAYCENT-generated per-area estimates of N2O
emissions (g N2O-N m2) from major crops were multiplied
by the cropland area data to obtain county-scale emission
estimates. Cropland area data were from NASS (USDA
2005g). The emission estimates by reported crop areas in the
county were scaled to the regions, and the national estimate
was calculated by summing results across all regions.
DAYCENT is sensitive to actual interannual variability
in weather patterns and other controlling variables, and so
emissions associated with individual activities vary through
time even if the management practices remain the same
(e.g., if N fertilization remains the same for two years). In
contrast, Tier 1 methods do not capture this variability and
rather have a linear, monotonic response that depends solely
on management practices. DAYCENT's ability to capture
these interactions between management and environmental
conditions enables it to produce more accurate estimates of
N2O emissions.
l\ion -Major Crop Types on Mineral Cropland Soils
The Tier 1 methodology (IPCC/UNEP/OECD/IEA
1997, IPCC 2006) was used to estimate direct N2O emissions
for mineral cropland soils that are managed for production
of non-major crop types. Estimates of direct N2O emissions
from N applications to non-rnajor crop types were based on
mineral soil N that was made available from the following
practices: (1) the application of synthetic commercial
fertilizers, (2) application of non-manure other commercial
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
organic fertilizers;12 and (3) the retention of above- and
below-ground crop residues. No manure amendments were
considered here because most of this material was applied
to crops simulated by DAYCENT. DAYCENT simulations
included the 5 major cropping systems (corn, hay, sorghum,
soybean, wheat), which are the land management systems
receiving the vast majority (approximately 95 percent) of
manure applications to cropped land in the United States
(Kellogg et al. 2000, Edmonds et al. 2003). Non-manure
organic amendments were not included in the DAYCENT
simulations, because county-level data for this source were
not available and this source is a very small portion of total
organic amendments. Consequently, non-manure organic
amendments were included in the Tier 1 analysis.
1. Aprocess-of-elimination approach was used to estimate
N fertilizer additions for these crops, because little
information exists on fertilizer application rates for non-
major crop types. N fertilizer additions to major crops,
grassland, forest land, and settlements were summed,
this sum was subtracted from total annual fertilizer
sales, and the difference was assumed to be applied to
non-major crop types. Non-major crop types include: (a)
fruits, nuts, and vegetables, and (b) other annual crops
not simulated by DAYCENT (barley, oats, tobacco,
sugarcane, sugar beets, sunflowers, millet, peanuts,
etc.).
2. Annual non-manure organic fertilizer additions were
based on organic fertilizer consumption statistics, which
were converted to units of N using average organic
fertilizer N content statistics (TVA 1991, 1992a, 1993.
1994;AAPFCO 1995, 1996, 1997, 1998, 1999,2000a,
2000b, 2002, 2003, 2004, 2005. 2006).
3. Crop residue N was derived by combining amounts
of above- and below-ground biomass, which were
determined based on crop production yield statistics
(1994a, 1998b, 2003,2005i, 2006b), dry matter fractions
(IPCC 2006), linear equations to estimate above-ground
biomass given dry matter crop yields (IPCC 2006), ratios
of below-to-above-ground biomass (IPCC 2006), and
N contents of the residues (IPCC 2006).
The total increase in soil mineral N from applied
fertilizers and crop residues was multiplied by the IPCC
(2006) default emission factor (Bouwman et al. 2002a,
2002b, Novoa and Tejeda 2006, Stehfest and Bouwman
2006) to derive an estimate of cropland direct N2O emissions
from non-major crop types.
Dtainage nad Cultivation oi Organic Cropland Soils
Tier 1 methods were used to estimate direct N2O
emissions from the drainage and cultivation of organic
cropland soils. Estimates of the total U.S. acreage of
drained organic soils cultivated annually for temperate and
sub-tropical climate regions were obtained for 1982, 1992,
and 1997 from the Natural Resources Inventory (USDA
2000b, as extracted by Eve 2001 and amended by Ogle
2002), using temperature and precipitation data from Daly
et al. (1994, 1998). These areas were linearly interpolated
and extrapolated to estimate areas for the missing years.
To estimate annual emissions, the total temperate area was
multiplied by the IPCC default emission factor for temperate
regions, and the total sub-tropical area was multiplied by the
average of the IPCC default emission factors for temperate
and tropical regions (IPCC 2006).
Direc! N20 Emissions from Grassland Soils
As with N7O from croplands, the Tier 3 process-based
DAYCENT model and Tier 1 methods described in the IPCC
(2006) guidelines were combined to estimate emissions
from grasslands. Grasslands include pastures and rangelands
used for grass forage production, where the primary use is
livestock grazing. Rangelands are typically extensive areas
of native grasslands that are not intensively managed, while
pastures are often seeded grasslands, possibly following tree
removal, that may or may not be improved with practices
such as irrigation and interseeding legumes.
DAYCENT was used to simulate N->O emissions
from grasslands at the county scale resulting from manure
deposited by livestock directly onto the pasture (i.e., PRP
manure, which is simulated internally within the model), N
fixation from legume seeding, managed manure amendments
(i.e., manure other than PRP manure), and synthetic fertilizer
application. The simulations used the same weather and soils
data as discussed under the section for Major Crop Types on
Mineral Cropland Soils. Managed manure N amendments
to grasslands were estimated from Edmonds et al. (2003)
i: Other commercial organic fertilizers include dried blood, dried manure, tankage, compost, other, but excludes manure and sewage sludge, which arc
used as commercial fertilizers.
Agriculture 6-25
-------
and adjusted for annual variation using managed manure N
production data according to methods described in Annex
3.11. "other N inputs" were simulated within the DAYCENT
framework, including N input from mineralization due to
decomposition of soil organic matter and plant litter, as
well as asymbiotic fixation of N from the atmosphere and
atmospheric N deposition.
DAYCENT-generated per-area estimates of N2O
emissions (g N2O-N nr2) from pasture and rangelands were
multiplied by the reported pasture and rangeland areas in the
county. Grassland area data were obtained from the National
Resources Inventory (NRI) (USDA 2000b). The 1997 NRI
area data for pastures and rangeland were aggregated to
the county level to estimate the grassland areas for 1995 to
2005, and the 1992 NRI pasture and rangeland data were
aggregated to the county level to estimate areas from 1990
to 1994. The county estimates were scaled to the regions,
and the national estimate was calculated by summing results
across all regions.
Manure N deposition from grazing animals is modeled
internally within DAYCENT. Comparisons with estimates
of total manure deposited on PRP (see Annex 3.11) showed
that DAYCENT accounted for approximately 70 percent of
total PRP manure. It is reasonable that DAYCENT did not
account for all PRP manure, because the NRI data do not
include some grassland areas such as federal grasslands.
N2O emissions from the portion of PRP manure N not
accounted for by DAYCENT were estimated using the Tier
1 method with IPCC default emission factors (de Klein
2004, IPCC 2006). Sewage sludge was assumed to be
applied on grasslands (but not included in the DAYCENT
simulations) because of the heavy metal content and
other pollutants in human waste that limit its use as an
amendment to croplands. Sewage sludge application
was estimated from data compiled by EPA (1993, 1997,
1999,2003), B astian (2002,2003,2005), and Metcalf and
Eddy (1991). Sewage sludge data on soil amendments
in agricultural lands were only available at the national
scale, and it was not possible to associate application
with specific soil conditions and weather at the county
scale. Consequently, emissions from sewage sludge were
also estimated using the Tier 1 method with IPCC default
emission factors (Bouwman et al. 2002a, 2002b, Novoa
and Tejeda 2006, Stehfest and Bouwman 2006, IPCC
2006). Emission estimates from DAYCENT and the IPCC
method were summed to provide total national emissions
for grasslands in the United States.
Annual direct emissions from major and non-major crops
on mineral cropland soils, from drainage and cultivation of
organic cropland soils, and from grassland soils were summed
to obtain total direct N2O emissions from agricultural soil
management (see Table 6-13 and Table 6-14).
Indirect N20 Emissions from Managed Soils ol al! Land-Use
Types and Managed Manure Systems
This section describes methods for estimating indirect
soil N2O emissions from all land-use types (i.e., cropland,
grassland, forest land, and settlements) and managed manure
systems based on losses of N through volatilization, leaching,
and runoff. The sources of indirect N from volatilization,
leaching, and runoff are estimated in the same manner as
direct N2O emissions from soils (i.e., using DAYCENT and
the Tier 1 method as described for direct emissions). The
indirect emissions from these N sources are estimated using
the Tier 1 method (IPCC 2006). Indirect N2O emissions
occur when mineral N made available through anthropogenic
activity is transported from the soil either in gaseous or
aqueous forms and later converted into N2O. There are two
pathways leading to indirect emissions. The first pathway
results from volatilization of N as NOX and NH3 following
application of synthetic fertilizer or organic amendments
(e.g., manure, sewage sludge); deposition of PRP manure; or
during storage, treatment, and transport of managed manure.
N made available from mineralization of soil organic matter
and asymbiotic fixation also contributes to volatilized N
emissions. Through atmospheric deposition, volatilized
N can be returned to soils, and a portion is emitted to the
atmosphere as N2O. The second pathway occurs via leaching
and runoff of soil N (primarily in the form of nitrate [NO3"])
that was made available through anthropogenic activity
on managed lands, mineralization of soil organic matter,
asymbiotic fixation, and atmospheric deposition. The nitrate
is subject to denitrification in water bodies, which leads
to additional N2O emissions. Regardless of the eventual
location of the indirect N,O emissions, the emissions
are assigned to the original source of the N for reporting
purposes, which here includes croplands, grasslands, forest
lands, and settlements.
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
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Indirect N20 Emissions from Atmospheric Deposition
of N Volatilized by Managed Soils and Managed
Manure Systems
Similar to the direct emissions calculation, several
approaches were combined to estimate the amount of
applied N that was exported from application sites through
volatilization. DAYCENT was used to simulate the amount
of N transported from land areas whose direct emissions were
simulated with DAYCENT (i.e., major croplands and most
grasslands), while the IPCC method was used for land areas
that were not simulated with DAYCENT (i.e., non-major
croplands and a small portion of grasslands) (IPCC 2006).
Manure N from managed systems assumed to be volatilized
during storage, treatment, and transport was also estimated
and included as a source of N for indirect emissions.
The N volatilized from managed agricultural, forest
land, and settlement soils, in addition to volatilization during
storage, treatment, and transport of managed manure was
summed to obtain total volatilization. N lost from storage,
treatment, and transport of managed manure is counted as
volatilized even though some of this N is likely to be leached/
runoff. This is a conservative approach because the IPCC
emission factor for volatilization is slightly higher than for
leaching/runoff (IPCC 2006). The IPCC default emission
factor (Brumme et al. 1999, Butterbach-Bahl et al. 1997,
Corre et al. 1999, Denier van der Gon and Sleeker 2005,
IPCC/UNEP/OECD/IEA 1997, IPCC 2006) was applied to
the total amount of N volatilized to estimate indirect N2O
emissions from volatilization due to the use and management
of U.S. croplands, grasslands, forest lands, settlements and
managed manure (Table 6-16).
Indirect N?0 from Leaching/Runoff
Similar to the indirect emissions calculation from
volatilized N, several approaches were combined to estimate
the amount of applied N that was transported from application
sites through leaching and surface runoff into waterbodies.
DAYCENT was used to simulate the amount of N transported
from major cropland types and most grasslands, while N
transport from non-major croplands and grasslands not
addressed in the DAYCENT model simulations (i.e., from
land areas that were not simulated with DAYCENT),
settlements, and forestland were obtained by applying the
IPCC default fractions for leaching and runoff (IPCC/UNEP/
OECD/IEA1997, IPCC 2006) to total N made available from
fertilizer applied, manure applied or deposited, above- and
below-ground crop residue retention, soil organic matter
decomposition, and asymbiotic fixation.
The N leached/runoff from managed soils, forests,
and settlements was summed to obtain total N leaching
or surface runoff. The IPCC default emission factor was
applied to the total amount of N leached/runoff to estimate
total indirect N2O emissions due to the use and management
of croplands, grasslands, forest lands, and settlements
(Table 6-16) (IPCC 2006).
Uncertainty
Uncertainty was estimated differently for each of
the following three components of N2O emissions from
agricultural soil management: (1) direct emissions calculated
by DAYCENT, (2) direct emissions not calculated by
DAYCENT, and (3) indirect emissions.
For direct emissions calculated using DAYCENT,
uncertainty in the results was attributed to model inputs
and the structure of the model (i.e., underlying model
equations and parameterization). A Monte Carlo analysis was
implemented to address these uncertainties and propagate
errors through the modeling process (Del Grosso et al.,
in prep). A Monte Carlo analysis was conducted using
probability distribution functions (PDFs) for weather, soil
characteristics, and N inputs to simulate direct N2O emissions
for each crop- or grassland type in a county. A joint PDF
was used to address the structural uncertainty for direct
N2O emissions from crops, which was derived using an
empirically-based method (Ogle et al. 2007).
County-scale PDFs for weather were based on the
variation in temperature and precipitation as represented
in DAYMET weather data grid cells (1x1 km) occurring in
croplands and grasslands in a county. The National Land
Cover Dataset (Vogelman et al. 2001) provided the data
on distribution of croplands and grasslands. Similarly,
county-scale PDFs for soil characteristics were based on
STATSGO Soil Map Units (Soil Survey Staff 2005), that
occurred in croplands and grasslands. PDFs for fertilizer
were derived from survey data for major U.S. crops, both
irrigated and rainfed (ERS 1997; NASS 2004, 1999, 1992;
Grant and Krenz 1985). State-level PDFs were developed
for each crop if a minimum of 15 data points existed for each
of the two categories (irrigated and rainfed). Where data
were insufficient at the state-level, PDFs were developed
for multi-state Farm Production Regions. Uncertainty in
Agriculture 6-2"
-------
manure applications for specific crops was incorporated into
the analysis based on total manure available for application
in each county, a weighted average application rate, and
the crop-specific land area amended with manure for 1997
(compiled from USDA data on animal numbers, manure
production, storage practices, application rates and associated
land areas receiving manure amendments; see Edmonds et
al. 2003). Together with the total area for each crop within
a county, the result yielded a probability that a given crop
in a specific county would either receive manure or not in
the Monte Carlo analysis. A ratio of manure N production
in each year of the Inventory relative to 1997 was used to
adjust the amount of area amended with manure, under
the assumption that greater or less manure N production
would lead to a proportional change in amended area (see
the section on Major Crop Types on Mineral Soils for data
sources on manure N production). If soils were amended with
manure, a reduction factor was applied to the N fertilization
rate accounting for the interaction between fertilization and
manure N amendments (i.e., producers often reduce mineral
fertilization rates if applying manure). Reduction factors
were randomly selected from probability distribution factors
based on relationships between manure N application and
fertilizer rates (ERS 1997).
An empirically-based uncertainty estimator was
developed using a method described by Ogle et al. (2007)
to assess uncertainty in model structure associated with the
algorithms and parameterization. The estimator was based
on a linear mixed-effect modeling analysis comparing N->O
emission estimates from eight agricultural experiments
with 50 treatments. Although the dataset was relatively
small, modeled emissions were significantly related to
measurements with a p-value of less than 0.01. Random
effects were included to capture the dependence in time series
and data collected from the same experimental site, which
were needed to estimate appropriate standard deviations for
parameter coefficients. The structural uncertainty estimator
accounted for bias and prediction error in the DAYCENT
model results, as well as random error associated with fine-
scale emission predictions in counties over a time series
from 1990 to 2005. Note that the current application only
addresses structural uncertainty in cropland estimates; further
development will be needed to address these uncertainties
in model estimates for grasslands, which is a planned
improvement as more soil N2O measurement data become
available for grassland sites. In general, DAYCENT tended to
underestimate emissions if the rates were above 6 g N2O m"2
(Del Grosso et al., in prep).
A simple error propagation method (IPCC 2006) was
used to estimate uncertainties for direct emissions from
mineral N inputs estimated with Tier 1 methods, including
management on croplands that were used to produce minor
crops and N inputs on grasslands that were not addressed in
the DAYCENT simulations. Similarly, indirect emissions
from agricultural soil management, which were calculated
according to the IPCC methodology, were estimated using
the simple error propagation method (IPCC 2006).
Uncertainties from Tier 3 and Tier 1 approaches were
combined using simple error propagation (IPCC 2006). The
results of the uncertainty analysis are summarized in Table
6-17. Agricultural direct soil N7O emissions in 2005 were
estimated to be between 247.5 and 380.0 Tg CO2 Eq. at a
95 percent confidence level. This indicates a range of 20
percent below and 22 percent above the actual 2005 emission
estimate of 310.5 Tg CO2 Eq. The indirect soil N2O emissions
in 2005 were estimated to range from 31.9 to 128 4 Tg CO2
Eq. at a 95 percent confidence level, indicating an uncertainty
of 42 percent below and 135 percent above the actual 2005
emission estimate of 54.6 Tg CO2 Eq.
Table 6-17: Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil Management in 2005
(Tg C02 Eq. and Percent)
2005 Emission Estimate Uncertainty Range Relative to Emission Estimate
Source Gas (TgC02Eq.) (TgC02Eq.) (%)
Direct Soil N20 Emissions N20
Indirect Soil N20 Emissions N20
310.5
54.6
Lower Bound
247.5
31.9
Upper Bound
380.0
128.4
Lower Bound
-20%
-42%
Upper Bound
+22%
+ 135%
Note: Due to lack of data, uncertainties in managed manure N production, PRP manure N production, other organic fertilizer amendments, indirect losses
of N in the DAYCENT simulations, and sewage sludge amendments to soils are currently treated as certain; every attempt will be made to include these
sources of uncertainty in future Inventories.
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19510-2005
-------
QA/QC and Verification
For quality control, DAYCENT results for N2O
emissions and NO3 leaching were compared with field data
representing various cropped/grazed systems, soils types, and
climate patterns (Del Grosso et al. 2005). N2O measurement
data were available for seven sites in the United States and
one in Canada, representing 25 different combinations
of fertilizer treatments and cultivation practices. NO3
leaching data were available for three sites in the United
States representing nine different combinations of fertilizer
amendments. Linear regressions of simulated vs. observed
emission and leaching data yielded correlation coefficients of
0.74 and 0.96 for annual NiO emissions and NO3 leaching,
respectively.
Spreadsheets containing input data and PDFs required
for DAYCENT simulations of major croplands and
grasslands and unit conversion factors were checked, as
well as the program scripts that were used to run the Monte
Carlo Analysis. There is a pending problem with timing
of management activities (e.g., planting dates, harvest)
as scheduled in the DAYCENT simulations for sorghum
production in some counties, and this issue has been
prioritized for correction. Spreadsheets containing input data
and emission factors required for the Tier 1 approach used for
non-major crops and grasslands not simulated by DAYCENT
were checked and no errors were found. Total emissions
and emissions from the different categories were compared
with inventories from previous years and differences were
reasonable given the methodological differences (see
Recalculations section for further discussion).
Recalculations Discussion
Major revisions in the Agricultural Soil Management
sector this year included (1) modifying N inputs to be
consistent with the agricultural soil C sector, (2) modeling
within-county variation in soil characteristics and weather, (3)
developing a Monte Carlo Analysis to address uncertainties
in the DAYCENT results, (4) implementing a separate
uncertainty analysis for direct emissions calculated with the
IPCC default methodology, and (5) incorporating revised
methods and emission factors from IPCC (2006).
In terms of N inputs, several changes were needed in
order to achieve consistency between the agricultural soil
N2O and soil C inventories. First, the method for simulating
mineral N fertilization was changed, so that application rates
for major crops were assumed to be stable over the Inventory
time period. Changes in the amount of fertilizer applied
to soils were assumed to be a result of changing land area
for application rather than the rate of application. Second,
manure amendment data were altered, so that the area of
application varied from year to year based on a county-scale
ratio of manure production in an Inventory year relative to
1997. Therefore, the amount of area amended with manure
varies through time as a function of the amount of manure.
Third, N2O emissions from soil application of sewage sludge
were estimated using the Tier 1 methodology (IPCC 2006)
instead of the DAYCENT model. DAYCENT simulates N2O
emissions at the county scale, but sewage sludge application
data were only available at the national scale. This created
a mismatch in the scale of the DAYCENT model analysis
compared to input data availability. The Tier 1 method was
assumed to better represent these emissions, since it was
not possible with the current dataset to associate sewage
sludge application with specific soil and weather conditions
at the county scale. Fourth, non-manure commercial organic
amendments to soils were assumed to be applied on fields
used to produce minor crops, and N2O emissions were
estimated with the IPCC default methodology. Commercial
organic fertilizers are more expensive than manure and
mineral fertilizers, and, therefore, assumed to be used on
cash crops (e.g., vegetables). Cash crops are considered
non-major crops for purposes of the Inventory calculations,
and, thus, estimated using the Tier 1 methods. Fifth, N inputs
from forage legumes not accounted for by the DAYCENT
simulations are no longer included in the emissions
calculations. In the previous Inventory, the difference
between the total N inputs from forage legumes, estimated
using an alternative approach, and the DAYCENT estimate
was included in the N2O emissions estimate. However,
it was determined that DAYCENT is likely providing a
reasonable estimate of total N inputs from forage legumes
so the additional production from the alternative approach
is no longer included.
Agriculture 6-29
-------
In last year's Inventory, weather and soils data were
based on the conditions at the centroid location of a county.
However, conditions do vary across a county, so the analysis
was modified to include sub-county scale heterogeneity in
these data. The National Land Cover Dataset (Vogelman
et al. 2001) was used to determine the overlap between
cropland and DAYMET weather records, which are produced
on a 1 x 1 km grid, as well as the soil map units from the
STATSGO database that overlap with cropland. The same
procedure was also used to determine heterogeneity in
weather and soil characteristics for grasslands. PDFs were
formed for each of these data inputs and used in a Monte
Carlo uncertainty analysis.
The methods for Agricultural Soil Management have
been revised in IPCC (2006), and key changes have been
incorporated into this year's Inventory. First, the default
emission factor for direct soil N2O emissions was lowered
from 1.25 to 1.0 percent of N inputs. Second, previously a
portion of the N inputs were removed from the calculation
of direct N2O emissions because it was assumed to be lost
through volatilization before direct emissions occurred.
However, the direct emission factor was developed based
on total N inputs, and therefore the new method has been
revised to estimate direct N2O emissions based on total N
input. Third, unlike IPCC/UNEP/OECD/IEA (1997) that
counted N fixed by legumes and transported to aboveground
biomass as N inputs, as well as N in crop residues, the
IPCC (2006) does not double-count symbiotic N fixation
separately from the crop residue N inputs. However, the
new method does incorporate crop N inputs from not only
the aboveground residues, as in IPCC/UNEP/OECD/IEA
(1997), but also the root N input to the soil as well. Fourth,
regarding indirect emissions, only N inputs from synthetic
and organic fertilizer additions were assumed to contribute
to NO3 runoff and leaching in IPCC/UNEP/OECD/IEA
(1997). IPCC (2006) assumes that N from crop residues,
which includes unharvested N that was symbolically fixed,
is also available for runoff and leaching. Sixth, the amount
of N leached out of the soil profile or run off the soil surface
that is assumed to be denitrified to N2O in aquatic systems
was lowered from 2.5 to 0.75 percent. Lastly, IPCC (2006)
recommends reporting total emissions from managed lands
because of the subjectivity with attempting to separate
anthropogenic influences from "natural" emissions in a
managed environment (i.e., all processes leading to N
mineralization in a managed environment and resulting
emissions are influenced by anthropogenic activity).
Thus, N2O emissions were not reduced by attempting to
estimate a natural background emission based on simulating
native vegetation, which had been done in the previous
Inventory.
There are two main consequences of adopting new
methods from IPCC (2006). First, total emissions are higher,
in large part because the non-anthropogenic portion was not
subtracted from total emissions. Second, indirect emissions
are lower because the amount of nitrate N leached and
runoff that is assumed to be converted to N2O in waterways
is substantially lower (0.75 versus 2.5 percent of nitrate N
in IPCC/UNEP/OECD/IEA [1997]).
The total change following recalculations ranged
from a 15 to 42 percent increase in emissions with an
average increase of 32.5 percent. As noted above, one
reason for the increase is that under the new methods
from IPCC (2006) non-anthropogenic emissions were not
subtracted from total emissions. The second main reason
is that application of the structural uncertainty estimator
described above tended to increase direct N2O estimates,
because DAYCENT under-estimated emissions when the
annual rate exceeded 6 g N2O m 2.
Planned Improvements
Two major improvements are planned for the Agricultural
Soil Management sector. The first improvement will be
to incorporate more land survey data from the National
Resources Inventory (NRI) (USDA 2000b) into the
DAYCENT simulation analysis, beyond the area estimates
for rangeland and pasture that are currently used to estimate
emissions from grasslands. NRI has a record of land-use
activities since 1982 for all U.S. agricultural land, which is
estimated at about 386 Mha. NASS is used as the basis for
land-use records in the current Inventory, and there are three
major disadvantages to this land survey. First, most crops
are grown in rotation with other crops (e.g., corn-soybean),
6-30 Inventory of U.S. Greenhouse Gas Emissions antl Sinks: 1990-2005
-------
but NASS data provide no information regarding rotation
histories. In contrast, NRI is designed to track rotation
histories, and this is important because emissions from
any particular year can be influenced by the crop that was
grown the previous year. Second, NASS does not conduct
a complete survey of cropland area each year, leading to
gaps in the land base. NRI does provide a complete history
of cropland areas for 4 out of every 5 years, and is currently
moving to an annualized inventory that will include a full
record for each year. Third, the current Inventory based on
NASS does not quantify the influence of land-use change
on emissions, which can be addressed using the NRI survey
records. NRI also provides additional information on pasture
land management that can be incorporated into the analysis
(particularly the use of irrigation). Using NRI data will also
make the Agricultural Soil Management sector methods more
consistent with the methods used to estimate C stock changes
for agricultural soils. However, the structure of model input
files that contain land management data will need to be
extensively revised to facilitate use of NRI data.
The second planned improvement is to further refine
the uncertainty analysis. New studies are being completed
and published evaluating agricultural management
impacts on soil N2O emissions, and these studies can be
incorporated into the empirical analysis, leading to a more
robust assessment of structural uncertainty in DAYCENT.
Moreover, structural uncertainty is only evaluated for
emission estimates in croplands, but it is anticipated that the
evaluation could be expanded in the near future to include
grasslands. In addition, the Monte Carlo analysis will be
expanded to address uncertainties in activity data related to
crop- and grassland areas, as well as irrigation and tillage
histories. Currently, the land-area statistics are treated as
certain because the NASS data do not include a measure of
uncertainty. Incorporating land survey data from the NRI
will facilitate the assessment of uncertainties in agricultural
activity data. Finally, uncertainties in managed manure
N production, PRP manure N production, other organic
fertilizer amendments, indirect losses of N in the DAYCENT
simulations, and sewage sludge amendments to soils are
currently treated as certain. Uncertainties in these quantities
will be derived and included in future years.
Additional improvements are more minor but will lead
to more accurate estimates, including updating DAYMET
weather for more recent years and revising manure N
application data to not include poultry manure that is used
for cattle feed. Currently, it is estimated that approximately
5 percent of poultry manure is used for feed in the United
States and, therefore, not applied to soils. Future inventories
will also create a time series of poultry manure going to
feed, since initial research indicates that the percentage may
have changed over time. In addition, some simulations for
sorghum did not run to completion. Input files for counties
where this occurred will be examined and the errors
corrected. Lastly, instead of assuming that a constant 10
percent of total fertilizer used annually in the United States
is applied to settlements, an attempt will be made in the
future to recognize that this value varies through the time
series because of increasing urbanization, particularly in
metropolitan areas. This improvement will be accomplished
by exploring the possibility of developing a database that
has county-level nitrogen fertilizer data partitioned by farm
and non-farm use.
6.5. Field Burning of Agricultural
Residues (IPCC Source Category 4F)
Farming activities produce large quantities of agricultural
crop residues, and farmers use or dispose of these residues in
a variety of ways. For example, agricultural residues can be
left on or plowed into the field, composted and then applied
to soils, landfilled, or burned in the field. Alternatively, they
can be collected and used as fuel, animal bedding material,
supplemental animal feed, or construction material. Field
burning of crop residues is not considered a net source
of CO2, because the carbon released to the atmosphere as
CO2 during burning is assumed to be reabsorbed during the
next growing season. Crop residue burning is, however, a
net source of CH4, N2O, CO, and NOX, which are released
during combustion.
Agriculture 6-31
-------
Field burning is not a common method of agricultural these crops is burned each year, except for rice." Annual
residue disposal in the United States. The primary crop emissions from this source over the period 1990 to 2005
types whose residues are typically burned in the United have remained relatively constant, averaging approximately
States are wheat, rice, sugarcane, corn, barley, soybeans, 0.9 Tg CO2 Eq. (41 Gg) of CH4,0.5 Tg CO2 Eq. (2 Gg) of
and peanuts. Less than 5 percent of the residue for each of N2O (see Table 6-18 and Table 6-19).
Table 6-18: CH4 and N20 Emissions from Field Burning of Agricultural Residues (Tg C02 Eq.)
Gas/Crop Type
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
Total
+ Less than 0.05 TgC02Eq.
1990
0.7
0.1
0.1
+
0.3
+
0.1
+
0.4
+
+
+
0.1
+
0.2
+
1.1
1995
0.7
0.1
0.1
+
0.3
+
0.2
+
0.4
+
+
+
0.1
+
0.2
+
1.0
2000
0.8
0.1
0.1
+
0.4
+
0.2
+
0.5
+
-i-
+
0.1
+
0.3
+
1.3
2001
0.8
0.1
0.1
+
0.3
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.2
2002
0.7
0.1
0.1
+
0.3
+
0.2
+
0.4
+
+
+
0.1
+
0.3
+
1.1
2003
0.8
0.1
0.1
+
0.4
+
0.2
+
0.4
+
+
+
0.1
+
0.2
+
1.2
2004
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.4
2005
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.4
Note: Totals may not sum due to independent rounding.
Table 6-19: CH4, N20, CO, and
Gas/Crop Type
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
CO
NOX
+ Less than 0.5 Gg
NOX Emissions
1990
33
7
4
1
13
1
7
+
1
+
+
+
+
+
1
+
691
28
from Field
1995
32
5
4
1
13
1
8
0
1
+
+
+
+
+
1
+
663
29
Burning of Agricultural
2000
38
5
4
1
17
1
10
+
1
+
+
+
+
+
1
+
792
35
2001
37
5
4
1
16
+
11
+
1
+
+
+
+
+
1
+
774
35
Residues
2002
34
4
3
1
15
+
10
+
1
+
+
+
+
+
1
+
709
33
(Gg)
2003
38
6
5
1
17
+
9
+
1
+
+
+
+
+
1
+
800
34
2004
42
5
4
1
20
+
11
+
2
+
+
+
+
+
1
+
879
39
2005
41
5
4
1
19
+
11
+
2
+
+
+
+
+
1
+
858
39
Note: Totals may not sum due to independent rounding.
13 The fraction of rice straw burned each year is significantly higher than that for other crops
(see "Methodology" discussion below).
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Methodology
The methodology for estimating greenhouse gas
emissions from field burning of agricultural residues is
consistent with IPCC/UNEP/OECD/IEA(1997). In orderto
estimate the amounts of C and N released during burning,
the following equations were used:14
Emissions were calculated by multiplying the amount
of C or N released by the appropriate IPCC default emission
ratio (i.e., CH4-C/C and N2O-N/N).
The types of crop residues burned in the United States
were determined from various state-level greenhouse gas
emission inventories (ILENR 1993, Oregon Department of
Energy 1995, Wisconsin Department of Natural Resources
1993) and publications on agricultural burning in the United
States (Jenkins et al. 1992, Turn et al. 1997, EPA 1992).
Crop production data for all crops except rice in
Florida and Oklahoma were taken from the USDA's Field
Crops, Final Estimates 1987-1992,1992-1997,1997-2002
(USDA 1994, 1998, 2003), and Crop Production Summary
(USDA 2005, 2006). Rice production data for Florida
and Oklahoma, which are not collected by USDA, were
estimated separately. Average primary and ratoon crop yields
Table 6-20: Agricultural Crop Production (Gg of Product)
for Florida (Schueneman and Deren 2002) were applied to
Florida acreages (Schueneman 1999b, 2001; Deren 2002;
Kirstein 2003, 2004; Cantens 2004, 2005), and crop yields
for Arkansas (USDA 1994, 1998, 2003, 2005, 2006) were
applied to Oklahoma acreages16 (Lee 2003, 2004, 2005,
2006). The production data for the crop types whose residues
are burned are presented in Table 6-20.
The percentage of crop residue burned was assumed to
be 3 percent for all crops in all years, except rice, based on
state inventory data (ILENR 1993, Oregon Department of
Energy 1995,Noller 1996, Wisconsin Department of Natural
Resources 1993, and Cibrowski 1996). Estimates of the
percentage of rice residue burned were derived from state-
level estimates of the percentage of rice area burned each year,
which were multiplied by state-level, annual rice production
statistics. The annual percentages of rice area burned in each
state were obtained from the agricultural extension agents in
each state and reports of the California Air Resources Board
(Anonymous 2006; Bollich 2000; California Air Resources
Board 1999, 2001; Cantens 2005; Deren 2002; Fife 1999;
Klosterboer 1999a, 1999b, 2000,2001,2002,2003; Lancero
2006; Lee 2005, 2006; Lindberg 2002, 2003, 2004, 2005;
Linscombe 1999a, 1999b, 2001, 2002, 2003, 2004, 2005,
2006; Najita 2000, 2001; Sacramento Valley Basinwide
Air Pollution Control Council 2005; Schueneman 1999a,
1999b, 2001; Stansel 2004, 2005; Street 2001, 2002, 2003;
Walker 2004, 2005, 2006; Wilson 2003,2004, 2005, 2006)
(see Table 6-21 and Table 6-22). The estimates provided
for Florida and Missouri remained constant over the entire
Crop
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
1990
74,292
7,114
25,525
201,534
9,192
52,416
1,635
1995
59,404
7,947
27,922
187,970
7,824
59,174
1,570
2000
60,641
8,705
32,762
251,854
6,919
75,055
1,481
2001
53,001
9,794
31,377
241,377
5,407
78,671
1,940
2002
43,705
9,601
32,253
227,767
4,940
75,010
1,506
2003
63,814
9,084
30,715
256,278
6,059
66,778
1,880
2004
58,738
10,565
26,320
299,914
6,091
85,013
1,945
2005
57,280
10,152
25,308
282,260
4,613
83,999
2,187
*Corn for grain (i.e., excludes corn for silage).
14 As is explained later in this section, the fraction of rice residues burned varies among states, so these equations were applied at the state level for rice.
These equations were applied at the national level for all other crop types.
11 Burning Efficiency is defined as the fraction of dry biomass exposed to burning that actually burns. Combustion Efficiency is defined as the fraction
of carbon in the fire that is oxidized completely to CO2. In the methodology recommended by the IPCC, the "burning efficiency" is assumed to be
contained in the "fraction of residues burned" factor. However, the number used here to estimate the "fraction of residues burned" does not account for
the fraction of exposed residue that does not burn. Therefore, a "burning efficiency factor" was added to the calculations.
16 Rice production yield data are not available for Oklahoma, so the Arkansas values are used as a proxy.
Agriculture 6-33
-------
Table 6-21: Percent of Rice Area Burned by State
State
Arkansas
California
Florida"
Louisiana
Mississippi
Missouri
Oklahoma
Texas
1990-1998
13%
Variable3
0%
6%
10%
18%
90%
1%
1999
13%
27%
0%
0%
40%
18%
90%
2%
2000
13%
27%
0%
5%
40%
18%
90%
0%
2001
13%
23%
0%
4%
40%
18%
90%
0%
2002
16%
13%
0%
3%
8%
18%
90%
0%
2003
22%
14%
0%
3%
65%
18%
100%
0%
2004
17%
11%
0%
3%
23%
18%
88%
0%
2005
22%
12%
0%
3%
23%
18%
94%
0%
a Values provided in Table 6-22.
b Although rice is cultivated in Florida, crop residue burning is illegal. Therefore, emissions remain zero throughout the time series.
1990 through 2005 period, while the estimates for all other
states varied over the time series. For California, the annual
percentages of rice area burned in the Sacramento Valley are
assumed to be representative of burning in the entire state,
because the Sacramento Valley accounts for over 95 percent
of the rice acreage in California (Fife 1999). These values
generally declined between 1990 and 2005 because of a
legislated reduction in rice straw burning (Lindberg 2002),
although there was a slight increase from 2004 to 2005 (see
Table 6-21 and Table 6-22).
All residue/crop product mass ratios except sugarcane
were obtained from Strehler and Stiitzle (1987). The datum
for sugarcane is from University of California (1977).
Table 6-22: Percent of Rice Area Burned in California,
1990-1998
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
Percentage
75%
75%
66%
60%
69%
59%
63%
34%
35%
Residue dry matter contents for all crops except soybeans
and peanuts were obtained from Turn et al. (1997). Soybean
dry matter content was obtained from Strehler and Stutzle
(1987). Peanut dry matter content was obtained through
personal communications with Jen Ketzis (1999), who
accessed Cornell University's Department of Animal
Science's computer model, Cornell Net Carbohydrate and
Protein System. The residue carbon contents and nitrogen
contents for all crops except soybeans and peanuts are from
Turn et al. (1997). The residue C content for soybeans and
peanuts is the IPCC default (IPCC/UNEP/OECD/IEA 1997).
The N content of soybeans is from Barnard and Kristoferson
(1985). The nitrogen content of peanuts is from Ketzis
(1999). These data are listed in Table 6-23. The burning
efficiency was assumed to be 93 percent, and the combustion
efficiency was assumed to be 88 percent, for all crop types
(EPA 1994). Emission ratios for all gases (see Table 6-24)
were taken from the Revised 1996 IPCC Guidelines (IPCC/
UNEP/OECD/IEA 1997).
Uncertainty
A significant source of uncertainty in the calculation
of non-CO2 emissions from field burning of agricultural
residues is in the estimates of the fraction of residue of each
Table 6-23: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues
Crop
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
Residue/Crop
Ratio
1.3
1.4
0.8
1.0
1.2
2.1
1.0
Fraction of
Residue Burned
0.03
Variable
0.03
0.03
0.03
0.03
0.03
Dry Matter
Fraction
0.93
0.91
0.62
0.91
0.93
0.87
0.86
C Fraction
0.4428
0.3806
0.4235
0.4478
0.4485
0.4500
0.4500
N Fraction
0.0062
0.0072
0.0040
0.0058
0.0077
0.0230
0.0106
Burning
Efficiency
0.93
0.93
0.93
0.93
0.93
0.93
0.93
Combustion
Efficiency
0.88
0.88
0.88
0.88
0.88
0.88
0.88
6-34 Inventory ol U.S. Greenhouse Gas Emissions and Sinks: 1980-2005
-------
Table 6-24: Greenhouse Gas Emission Ratios
Gas
Emission Ratio
coa
N20b
l\IOxb
0.005
0.060
0.007
0.121
a Mass of C compound released (units of C) relative to mass of total C
released from burning (units of C).
b Mass of N compound released (units of N) relative to mass of total N
released from burning (units of N).
crop type burned each year. Data on the fraction burned, as
well as the gross amount of residue burned each year, are
not collected at either the national or state level. In addition,
burning practices are highly variable among crops, as well
as among states. The fractions of residue burned used in
these calculations were based upon information collected by
state agencies and in published literature. Based on expert
judgment, uncertainty in the fraction of crop residue burned
ranged from zero to 100 percent, depending on the state and
crop type.
The results of the Tier 2 Monte Carlo uncertainty
analysis are summarized in Table 6-25. CH4 emissions
from field burning of agricultural residues in 2005 were
estimated to be between 0.75 and 0.97 Tg CO, Eq. at a 95
percent confidence level. This indicates a range of 13 percent
below and 13 percent above the 2005 emission estimate of
0.9 Tg CO2 Eq. Also at the 95 percent confidence level, N2O
emissions were estimated to be between 0.45 and 0.57 Tg
CO2 Eq. (or approximately 11 percent below and 12 percent
above the 2005 emission estimate of 0.5 Tg CO, Eq.).
QA/QC and Verification
A source-specific QA/QC plan for field burning of
agricultural residues was implemented. This effort included
a Tier 1 analysis, as well as portions of a Tier 2 analysis.
The Tier 2 procedures focused on comparing trends across
years, states, and crops to attempt to identify any outliers or
inconsistencies. No problems were found.
Recalculations Discussion
The crop production data for 2004 were updated
using data from USDA (2006). Data on the percentage of
rice residue burned in Missouri were revised for all years
to 17.5 percent based on new information (Anonymous
2006). Similarly, the percentage of rice residue burned in
Mississippi was revised to 22.5 percent for 2004 based on
new information provided by Walker (2006). New data for
acres of rice harvested in Arkansas in 2005 changed the
average rice yield for Arkansas for all years. Subsequently,
this change resulted in a change in the rice production data
for Oklahoma for all years, since Arkansas data are used as
a proxy to calculate rice production in Oklahoma.
These modifications resulted in a change in emissions
estimates for CH4 and N2O for all years. From 1990 to 2004,
emission estimates for CH4 increased by amounts ranging
between 0.18 and 0.51 percent. From 1990 to 2003, N2O
emission estimates increased by amounts ranging between
0.15 and 0.39 percent. In 2004, N2O emission estimates
decreased by 0.05 percent.
Planned Improvements
Preliminary research on agricultural burning in the
United States indicates that residues from several additional
crop types (e.g., grass for seed, blueberries, and fruit and nut
trees) are burned. Whether sufficient information exists for
inclusion of these additional crop types in future inventories
is being investigated. The extent of recent state crop-burning
regulations is also being investigated.
Table 6-25: Tier 2 Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of Agricultural Residues
(Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.)
Field Burning of
Agricultural Residues
Field Burning of
Agricultural Residues
CH4
NZ0
0.9
0.5
Lower Bound
0.75
0.45
Upper Bound
0.97
0.57
Lower Bound
-13%
-11%
Upper Bound
+13%
+12%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6 35
-------
-------
7. Land Use, Land-Use Change,
and Forestry
This chapter provides an assessment of the net greenhouse gas flux1 resulting from the uses and changes in land
types and forests in the United States. The Intergovernmental Panel on Climate Change (IPCC) Good Practice
Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003) recommends reporting fluxes according to
changes within and conversions between certain land-use types, termed forest land, cropland, grassland, and settlements (as
well as wetlands). The greenhouse gas flux from Forest Land Remaining Forest Land is reported using estimates of changes
in forest carbon (C) stocks, non-carbon dioxide (CO2) emissions from forest fires, and the application of synthetic fertilizers
to forest soils. The greenhouse gas flux reported in this chapter from agricultural lands (i.e., cropland and grassland) includes
changes in organic C stocks in mineral and organic soils due to land use and management, and emissions of CO2 due to the
application of crushed limestone and dolomite to managed land (i.e., soil liming). Fluxes are reported for four agricultural
land use/land-use change categories: Cropland Remaining Cropland, Land Converted to Cropland, Grassland Remaining
Grassland, and Land Converted to Grassland. Fluxes resulting from Settlements Remaining Settlements include those from
urban trees and soil fertilization. Landfilled yard trimmings and food scraps are accounted for separately under Other.
The flux estimates in this chapter, with the exception of CO2 fluxes from wood products, urban trees, and liming, are
based on activity data collected at multiple-year intervals, which are in the form of forest, land-use, and municipal solid
waste surveys. Carbon dioxide fluxes from forest C stocks (except the wood product components) and from agricultural
soils (except the liming component) are calculated on an average annual basis from data collected in intervals ranging from
1 to 10 years. The resulting annual averages are applied to years between surveys. Calculations of non-CO2 emissions from
forest fires are based on forest CO2 flux data. Agricultural mineral and organic soil C flux calculations are based primarily
on national surveys, so these results are largely constant over multi-year intervals, with large discontinuities between
intervals. For the landfilled yard trimmings and food scraps source, periodic solid waste survey data were interpolated so
that annual storage estimates could be derived. In addition, because the most recent national forest, land-use, and municipal
solid waste surveys were completed prior to 2005, the estimates of CO2 flux from forests, agricultural soils, and landfilled
yard trimmings and food scraps are based in part on extrapolation. Carbon dioxide flux from urban trees is based on neither
annual data nor periodic survey data, but instead on data collected over the period 1990 through 1999. This flux has been
applied to the entire time series, and periodic U.S. census data on changes in urban area have been used to develop annual
estimates of CO2 flux.
Land use, land-use change, and forestry activities in 2005 resulted in a net C sequestration of 828.5 Tg CO? Eq. (225.9
Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 14 percent of total U .S. CO2 emissions. Total
1 The term "flux" is used here to encompass both emissions of greenhouse gases to the atmosphere, and removal of C from the atmosphere. Removal of
C from the atmosphere is also referred to as "carbon sequestration."
Land Use, Land-Use Change, and Forestry 7-1
-------
Table 7-1: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
Forest Land Remaining Forest Land
Changes in Forest C Stocks3
Cropland Remaining Cropland
Changes in Agricultural Soil C Stocks and
Liming Emissions'1
Land Converted to Cropland
Changes in Agricultural Soil C Stocks0
Grassland Remaining Grassland
Changes in Agricultural Soil C Stocksd
Land Converted to Grassland
Changes in Agricultural Soil C Stocks6
Settlements Remaining Settlements'
Urban Trees
Other
Landfilled Yard Trimmings and Food
Scraps
Total
1990
(598.5)
(598.5)
(28.1)
(28.1)
8.7
8.7
0.1
0.1
(14.6)
(14.6)
(57.5)
(57.5)
(22.8)
(22.8)
(712.8)
1995
(717.5)
(717.5)
(37.4)
(37.4)
7.2
7.2
16.4
16.4
(16.3)
(16.3)
(67.8)
(67.8)
(13.3)
(13.3)
(828.8)
2000
(638.7)
(638.7)
(36.5)
(36.5)
7.2
7.2
16.3
16.3
(16.3)
(16.3)
(78.2)
(78.2)
(10.5)
(10.5)
(756.7)
2001
(645.7)
(645.7)
(38.0)
(38.0)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(80.2)
(80.2)
(10.6)
(10.6)
(767.5)
2002
(688.1)
(688.1)
(37.8)
(37.8)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(82.3)
(82.3)
(10.8)
(10.8)
(811.9)
2003
(687.0)
(687.0)
(38.3)
(38.3)
7.2
7.2
16.2
16.2
(16.3)
(16.3)
(84.4)
(84.4)
(9.3)
(9.3)
(811.9)
2004
(697.3)
(697.3)
(39.4)
(39.4)
7.2
7.2
16.1
16.1
(16.3)
(16.3)
(86.4)
(86.4)
(8.7)
(8.7)
(824.8)
2005
(698.7)
(698.7)
(39.4)
(39.4)
7.2
7.2
16.1
16.1
(16.3)
(16.3)
(88.5)
(88.5)
(8.8)
(8.8)
(828.5)
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
a Estimates include C stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
b Estimates include C stock changes in mineral soils and organic soils on Cropland Remaining Cropland, C stock changes in organic soils on Land Converted
to Cropland, and liming emissions from all managed land.
c Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land use/land-use change category
are reported under Cropland Remaining Cropland.
d Estimates include C stock changes in mineral soils and organic soils on Grassland Remaining Grassland, and C stock changes in organic soils on Land
Converted to Grassland. Liming emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
e Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land use/land-use change category
are reported under Grassland Remaining Grassland and Cropland Remaining Cropland, respectively.
1 Estimates include C stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming emissions for this land
use/land-use change category are reported under Cropland Remaining Cropland.
land use, land-use change, and forestry net C sequestration2
increased by approximately 16 percent between 1990
and 2005. This increase was primarily due to an increase
in the rate of net C accumulation in forest C stocks. Net
C accumulation in Settlements Remaining Settlements,
Land Converted to Grassland, and Cropland Remaining
Cropland increased, while net C accumulation in landfilled
yard trimmings and food scraps slowed over this period.
The Grassland Remaining Grassland land-use category
resulted in net C emissions in 1990 and 1991, became a
net C sink from 1992 to 1994, and then remained a fairly
constant emission source. Emissions from Land Converted
to Cropland declined between 1990 and 2005.
Non-CO2 emissions from Land Use, Land-Use Change,
and Forestry are shown in Table 7-3 and Table 7-4. The
application of synthetic fertilizers to forest and settlement
soils in 2005 resulted in direct N2O emissions of 6.2 Tg
CO2 Eq. (20 Gg N2O). Direct N2O emissions from fertilizer
application increased by approximately 19 percent between
1990 and 2005. Non-CO2 emissions from forest fires in 2005
resulted in methane (CH4) emissions of 11.6 Tg CO2 Eq. (551
Gg), and in N2O emissions of 1.2 Tg CO2 Eq. (4 Gg).
7,1. Forest Land Remaining Forest
Land
(IPCC Source Category 5A1)
For estimating C stocks or stock change (flux), C in
forest ecosystems can be divided into the following five
storage pools (IPCC 2003):
• Aboveground biomass, which includes all living
biomass above the soil including stem, stump, branches,
2 Carbon sequestration estimates are net figures. The C stock in a given pool fluctuates, due to both gains and losses. When losses exceed gains, the C
stock decreases, and the pool acts as a source. When gains exceed losses, the C stock increases, and the pool acts as a sink. This is also referred to as
net C sequestration.
72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-20C5
-------
Table 7-2: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C)
Land-Use Category
Forest Land Remaining Forest Land
Changes in Forest C Stocks3
Cropland Remaining Cropland
Changes in Agricultural Soil C Stocks and
Liming Emissions'1
Land Converted to Cropland
Changes in Agricultural Soil C Stocks0
Grassland Remaining Grassland
Changes in Agricultural Soil C Stocksd
Land Converted to Grassland
Changes in Agricultural Soil C Stocks6
Settlements Remaining Settlements'
Urban Trees
Other
Landfilled Yard Trimmings and Food
Scraps
Total
1990
(163.2)
(163.2)
(7.7)
(7.7)
2.4
2.4
0.0
0.0
(4.0)
(4.0)
(15.7)
(15.7)
(6.2)
(6.2)
(194.4)
1995
(195.7)
(195.7)
(10.2)
(10.2)
2.0
2.0
4.5
4.5
(4.5)
(4.5)
(18-5)
(18.5)
(3-6)
(3.6)
(226.0)
2000
(174.2)
(174.2)
(10.0)
(10.0)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(21.3)
(21.3)
(2.9)
(2.9)
(206.4)
2001
(176.1)
(176.1)
(10.4)
(10.4)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(21.9)
(21.9)
(2.9)
(2.9)
(209.3)
2002
(187.7)
(187.7)
(10.3)
(10.3)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(22.4)
(22.4)
(3.0)
(3.0)
(221.4)
2003
(187.4)
(187.4)
(10.4)
(10.4)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(23.0)
(23.0)
(2.5)
(2.5)
(221.4)
2004
(190.2)
(190.2)
(10.7)
(10.7)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(23.6)
(23.6)
(2.4)
(2.4)
(224.9)
2005
(190.6)
(190.6)
(10.7)
(10.7)
2.0
2.0
4.4
4.4
(4.5)
(4.5)
(24.1)
(24.1)
(2.4)
(2.4)
(225.9)
Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
a Estimates include C stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
b Estimates include C stock changes in mineral soils and organic soils on Cropland Remaining Cropland, C stock changes in organic soils on Land Converted
to Cropland, and liming emissions from all managed land.
c Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land use/land-use change category
are reported under Cropland Remaining Cropland.
d Estimates include C stock changes in mineral soils and organic soils on Grass/and Remaining Grassland, and C stock changes in organic soils on Land
Converted to Grassland. Liming emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
e Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land use/land-use change category
are reported under Grassland Remaining Grassland and Cropland Remaining Cropland, respectively.
1 Estimates include C stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming emissions for this land
use/land-use change category are reported under Crop/and Remaining Cropland.
bark, seeds, and foliage. This category includes live
understory.
• Belowground biomass, which includes all living biomass
of coarse living roots greater than 2 mm diameter.
• Dead wood, which includes all non-living woody
biomass either standing, lying on the ground (but not
including litter), or in the soil.
• Litter, which includes the litter, fumic, and humic layers,
and all non-living biomass with a diameter less than 7.5
cm at transect intersection, lying on the ground.
• Soil organic carbon (SOC), including all organic
material in soil to a depth of 1 meter but excluding the
coarse roots of the aboveground pools.
In addition, there are two harvested wood pools also
necessary for estimating C flux, which are:
• Harvested wood products in use.
• Harvested wood products in solid waste disposal sites
(SWDS).
C is continuously cycled among these storage pools and
between forest ecosystems and the atmosphere as a result
of biological processes in forests (e.g., photosynthesis,
respiration, growth, mortality, decomposition, and disturbances
such as fires or pest outbreaks) and anthropogenic activities
(e.g., harvesting, thinning, clearing, and replanting). As trees
photosynthesize and grow, C is removed from the atmosphere
and stored in living tree biomass. As trees die and otherwise
deposit litter and debris on the forest floor, C is released to
the atmosphere or transferred to the soil by organisms that
facilitate decomposition.
The net change in forest C is not equivalent to the
net flux between forests and the atmosphere because
timber harvests do not cause an immediate flux of C to the
atmosphere. Instead, harvesting transfers C to a "product
pool." Once in a product pool, the C is emitted over time as
CO2 when the wood product combusts or decays. The rate
of emission varies considerably among different product
pools. For example, if timber is harvested to produce energy,
combustion releases C immediately. Conversely, if timber
is harvested and used as lumber in a house, it may be many
decades or even centuries before the lumber decays and C is
released to the atmosphere. If wood products are disposed of
Land Use, Land-Use Change, and Forestry
-------
Table 7-3: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
Forest Land Remaining Forest Land
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
N20 Emissions from Soils3
Settlements Remaining Settlements
I\I20 Emissions from Soils"
Total
1990
7.8
7.1
0.7
0.1
5.1
5.1
13.0
1995
4.5
4.0
0.4
0.2
5.5
5.5
10.1
2000
15.7
14.0
1.4
0.3
5.6
5.6
21.3
2001
6.9
6.0
0.6
0.3
5.5
5.5
12.4
2002
11.8
10.4
1.1
0.3
5.6
5.6
17.4
2003
9.2
8.1
0.8
0.3
5.8
5.8
15.0
2004
8.0
6.9
0.7
0.3
6.0
6.0
13.9
2005
13.1
11.6
1.2
0.3
5.8
5.8
18.9
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter. Totals may not sum due to independent
rounding.
a Estimates include emissions from N fertilizer additions on both Fores/ Land Remaining Forest Land, and Land Converted to Forest Land, but not from
land-use conversion.
b Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to Settlements, but not from
land-use conversion.
Table 7-4: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Gg)
Land-Use Category
Forest Land Remaining Forest Land
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
N20 Emissions from Soils3
Settlements Remaining Settlements
N20 Emissions from Soils"
1990
337
2
0
17
1995
189
1
1
18
2000
667
5
1
18
2001
285
2
1
18
2002
494
3
1
18
2003
384
3
1
19
2004
330
2
1
19
2005
551
4
1
19
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter. Totals may not sum due to independent
rounding.
a Estimates include emissions from N fertilizer additions on both Fores? Land Remaining Forest Land, and Land Converted to Forest Land, but not from
land-use conversion.
b Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to Settlements, but not from
land-use conversion.
in SWDS, the C contained in the wood may be released many not available for the entire United States to allow results to
years or decades later, or may be stored almost permanently be partitioned in this way. Instead, net changes in all forest-
in the SWDS. related land, including non-forest land converted to forest
This section quantifies the net changes in C stocks in and fcrests converted to non-forest are reported here.
the five forest C pools and two harvested wood pools. The Forest C storage pools, and the flows between them via
net change in stocks for each pool is estimated, and then emissions, sequestration, and transfers, are shown in Figure
the changes in stocks are summed over all pools to estimate 7-1. In the figure, boxes represent forest C storage pools and
total net flux. Thus, the focus on C implies that all C-based arrows represent flows between storage pools or between
greenhouse gases are included, and the focus on stock storage pools and the atmosphere. Note that the boxes are
change suggests that specific ecosystem fluxes do not need not identical to the storage pools identified in this chapter.
to be separately itemized in this report. Disturbances from The storage pools identified in this chapter have been altered
forest fires and pest outbreaks are implicitly included in the in this graphic to better illustrate the processes that result in
net changes. For instance, an inventory conducted after fire transfers of C from one pool to another, and emissions to the
counts only trees left. The change between inventories thus atmosphere as well as uptake from the atmosphere.
accounts for the C changes due to fires; however, it may Approximately 33 percent (303 million hectares) of
not be possible to attribute the changes to the disturbance me TJ S iand area is forested, of which approximately 250
specifically. The IPCC (2003) recommends reporting C minion hectares are located in the conterminous 48 states.
stocks according to several land-use types and conversions, An additionai 52 million hectares are located in Alaska and
specifically Forest Land Remaining Forest Land and Land Hawaii, though this inventory does not currently account
Converted to Forest Land. Currently, consistent datasets are for mese stocks and fluxes due to data libations. Hawaii
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-20CI5
-------
Figure 7-1
Forest Sector Carbon Pools and Flows
Combustion from
forest fires (carbon
dioxide, methane)
Decompostion Methane
Flaring
and
i Utilization
Legend
Carbon Pool
Carbon transfer or flux
Combustion
Source: Heath etal. 2003
and U.S. territories have relatively small areas of forest land
and will probably not affect the overall C budget to a great
degree. Alaska has over 50 million hectares of forest land,
however, and more efforts will be made to account for this
area in the future (see Planned Improvements for more details).
Agroforestry systems are also not currently accounted for in
the U.S. Inventory, since they are not explicitly inventoried by
either of the two primary national natural resource inventory
programs: the Forest Inventory and Analysis (FIA) program
of the U.S. Department of Agriculture (USDA) Forest Service
and the National Resources Inventory (NRI) of the USDA
Natural Resources Conservation Service (Perry et al. 2005).
Seventy-nine percent of the 250 million hectares are
classified as timberland, meaning they meet minimum
levels of productivity and are available for timber harvest.
Historically, the timberlands in the conterminous 48 states
have been more frequently or intensively surveyed than
other forest lands. Of the remaining 51 million hectares, 16
million hectares are reserved forest lands (withdrawn by law
from management for production of wood products) and 35
million hectares are lower productivity forest lands (Smith
et al. 2004b). From the early 1970s to the early 1980s, forest
land declined by approximately 2.4 million hectares. During
the 1980s and 1990s, forest area increased by about 3.7
million hectares. These net changes in forest area represent
average annual fluctuations of only aboutO.l percent. Given
the low rate of change in U.S. forest land area, the major
influences on the current net C flux from forest land are
management activities and the ongoing impacts of previous
land-use changes. These activities affect the net flux of C
by altering the amount of C stored in forest ecosystems. For
example, intensified management of forests can increase both
the rate of growth and the eventual biomass density of the
forest, thereby increasing the uptake of C.3 Harvesting forests
removes much of the aboveground C, but trees can grow on
this area again and sequester C. The reversion of cropland to
forest land increases C storage in biomass, forest floor, and
soils. The net effects of forest management and the effects
of land-use change involving forest land are captured in the
estimates of C stocks and fluxes presented in this chapter.
1 The term "biomass density" refers to the mass of vegetation per unit area. It is usually measured on a dry-weight basis. Dry biomass is 50 percent
carbon by weight.
Land Use, Land-Use Change, and Forestry 7-5
-------
In the United States, improved forest management recently, the 1970s and 1980s saw a resurgence of federally-
practices, the regeneration of previously cleared forest areas, sponsored forest management programs (e.g., the Forestry
as well as timber harvesting and use have resulted in net Incentive Program) and soil conservation programs (e.g.,
uptake (i.e., net sequestration) of C each year from 1990 the Conservation Reserve Program), which have focused
through 2005. Due to improvements in U.S. agricultural on tree planting, improving timber management activities,
productivity, the rate of forest clearing for crop cultivation combating soil erosion, and converting marginal cropland to
and pasture slowed in the late 19th century, and by 1920, forests. In addition to forest regeneration and management,
this practice had all but ceased. As farming expanded in forest harvests have also affected net C fluxes. Because most
the Midwest and West, large areas of previously cultivated of the timber harvested from U.S. forests is used in wood
land in the East were taken out of crop production, primarily products, and many discarded wood products are disposed of
between 1920 and 1950, and were allowed to revert to in SWDS rather than by incineration, significant quantities
forests or were actively reforested. The impacts of these of C in harvested wood are transferred to long-term storage
land-use changes still affect C fluxes from forests in the pools rather than being released rapidly to the atmosphere
East. In addition, C fluxes from eastern forests have been (Skog and Nicholson 1998, Skog in preparation). The size
affected by a trend toward managed growth on private of these long-term C storage pools has increased during the
land. Collectively, these changes have nearly doubled the last century.
biomass density in eastern forests since the early 1950s. More
Table 7-5: Net Annual Changes in C Stocks (Tg C02/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic Carbon
Harvested Wood
Products in use
SWDS
Total Net Flux
1990
(466.5)
(251.8)
(63.9)
(36.7)
(65.6)
(48.5)
(132.0)
(63.1)
(68.9)
(598.5)
1995
(602.0)
(331.0)
(69.8)
(60.9)
(49.5)
(90.8)
(115.5)
(53.5)
(62.0)
(717.5)
2000
(529.4)
(347.1)
(73.9)
(48.2)
(35.8)
(24.5)
(109.3)
(46.2)
(63.1)
(638.7)
2001
(555.5)
(360.4)
(76.4)
(50.0)
(47.1)
(21.6)
(90.2)
(31.2)
(59.0)
(645.7)
2002
(595.3)
(376.4)
(79.5)
(52.4)
(52.2)
(34.8)
(92.8)
(34.1)
(58.7)
(688.1)
2003
(595.3)
(376.4)
(79.5)
(52.4)
(52.2)
(34.8)
(91.7)
(33.4)
(58.3)
(687.0)
2004
(595.3)
(376.4)
(79.5)
(52.4)
(52.2)
(34.8)
(101.9)
(43.3)
(58.7)
(697.3)
2005
(595.3)
(376.4)
(79.5)
(52.4)
(52.2)
(34.8)
(103.4)
(44.4)
(59.0)
(698.7)
Note: Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban trees, agroforestry systems).
Parentheses indicate net C sequestration (i.e., a net removal of C from the atmosphere). Total net flux is an estimate of the actual net flux between the
total forest C pool and the atmosphere. Harvested wood estimates are based on results from annual surveys and models. Totals may not sum due to
independent rounding.
Table 7-6: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic Carbon
Harvested Wood
Products in use
SWDS
Total Net Flux
1990
(127.2)
(68.7)
(17.4)
(10.0)
(17.9)
(13.2)
(36.0)
(17.2)
(18.8)
(163.2)
1995
(164.2)
(90.3)
(19.0)
(16.6)
(13.5)
(24.8)
(31.5)
(14.6)
(16.9)
(195.7)
2000
(144.4)
(94.7)
(20.1)
(13.1)
(9.8)
(6.7)
(29.8)
(12.6)
(17.2)
(174.2)
2001
(151.5)
(98.3)
(20.8)
(13.6)
(12.9)
(5.9)
(24.6)
(8.5)
(16.1)
(176.1)
2002
(162.4)
(102.7)
(21.7)
(14.3)
(14.2)
(9.5)
(25.3)
(9.3)
(16.0)
(187.7)
2003
(162.4)
(102.7)
(21.7)
(14.3)
(14.2)
(9.5)
(25.0)
(9.1)
(15.9)
(187.4)
2004
(162.4)
(102.7)
(21.7)
(14.3)
(14.2)
(9.5)
(27.8)
(11.8)
(16.0)
(190.2)
2005
(162.4)
(102.7)
(21.7)
(14.3)
(14.2)
(9.5)
(28.2)
(12.1)
(16.1)
(190.6)
Note: Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban trees, agroforestry systems).
Parentheses indicate net C sequestration (i.e., a net removal of C from the atmosphere). Total net flux is an estimate of the actual net flux between the
total forest C pool and the atmosphere. Harvested wood estimates are based on results from annual surveys and models. Totals may not sum due to
independent rounding.
7-6 inventory of U.S. Greenhouse Gas Emissions ano Sinks: 1990 2005
-------
Changes in C stocks in U.S. forests and harvested wood
were estimated to account for net sequestration of 698.7 Tg
CO2 Eq. (190.6 Tg C) in 2005 (Table 7-5, Table 7-6, and
Figure 7-2). In addition to the net accumulation of C in
harvested wood pools, sequestration is a reflection of net
forest growth and increasing forest area over this period.
though the increase in forest sequestration is due more to an
increasing C density per area than to the increase in area of
forest land. Forest land in the conterminous United States
Figure 7-2
Estimates of Net Annual Changes in Carbon Stocks
for Major Carbon Pools
so
-50 -
-100
-150
-200 -
-250 -
Soil
Harvested Wood
Forest, Nonsoil
"
Total Net Change
CMCo^irttor^eoCT>Oi-CMeo**m
CM CM CM CM CM
was approximately 246, 250, and 251 million hectares for
1987, 1997, and 2002, respectively, which amounts to only
a 2 percent increase over the period (Smith et al. 2004b).
Continuous, regular annual surveys are not available over
the period for each state; therefore, estimates for non-
survey years were derived by interpolation between known
data points. Survey years vary from state to state. National
estimates are a composite of individual state surveys. Total
sequestration increased by 17 percent between 1990 and 2005
(see Recalculations Discussion). Estimated sequestration in
the aboveground biomass C pool had the greatest effect on
total change. This was primarily due to an increase in the
rate of net C accumulation as density, or the rate of change
in metric tons of C per hectare per year, approximately a 21
percent increase over the 1990 through 2005 time series.
This increase is particularly evident for the aboveground
and belowground tree biomass pools, for which rate of C
accumulation increased by about 37 percent.
Stock estimates for forest and harvested wood C storage
pools are presented in Table 7-7. Together, the aboveground
live and forest soil pools account for a large proportion of
total forest C stocks. C stocks in all non-soil pools increased
over time. Therefore, C sequestration was greater than C
emissions from forests, as discussed above. Figure 7-3 shows
county-average C densities for live trees on forest land,
including both above- and belowground biomass.
Table 7-7: Forest area (1,000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools
Carbon Pool
Forest Area (1,000 ha)
Carbon Pools (Tg C)
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic C
Harvested Wood
Products in use
SWDS
Total C Stock
1990
242,300
39,026
14,164
2,794
2,354
4,404
15,310
1,888
1,184
704
40,914
1995
245,946
39,762
14,565 .
2,885
2,418
4,497
15,398
2,067
1,268
799
41,829
2000
250,275
40,576
15,031
2,983
2,499
4,559
15,505
2,225
1,341
884
42,801
2001
251,110
40,721
15,125
3,003
2,512
4,569
15,511
2,255
1,354
901
42,976
2002
251,977
40,872
15,224
3,024
2,526
4,582
15,517
2,287
1,368
919
43,159
2003
252,879
41,035
15,326
3,045
2,540
4,596
15,527
2,317
1,381
936
43,352
2004
253,782
41,197
15,429
3,067
2,555
4,610
15,536
2,341
1,389
952
43,538
2005
254,684
41,359
15,532
3,089
2,569
4,625
15,546
2,367
1,399
968
43,726
2006
255,587
41,522
15,634
3,110
2,583
4,639
15,555
2,395
1,411
984
43,917
Note: Forest area estimates are based on interpolation and extrapolation of inventory data as described in the text and in Annex 3.12. Forest C stocks do
not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban trees, agroforestry systems). Wood product stocks
include exports, even if the logs are processed in other countries, and exclude imports. Forest area estimates are based on interpolation and extrapolation
of inventory data as described in the text and in Annex 3.12. Harvested wood estimates are based on results from annual surveys and models. Totals may
not sum due to independent rounding. Inventories are assumed to represent stocks as of January 1 of the inventory year. Flux is the net annual change in
stock. Thus, an estimate of flux for 2005 requires estimates of C stocks for 2005 and 2006.
Land Use, Land-Use Change, and Forestry 7-7
-------
Figure 7-3
Average C Density in the Forest Tree Pool in the Conterminous United States During 2005
Live Tree
Mg C02 eq/ha
1-200
W 201-400
• over 400
Note: This graphic shows county-average carbon densities for live trees on forestland, including both above- and belowground biomass. These data
are based on the most recent forest inventory survey in each state. (See Table A-3 for the most recent inventory year for each state or substate.)
Table 7-8: Estimates of C02 (Tg/yr) Emissions for the
Lower 48 States and Alaska3
Box 7-1: C02 Emissions from Forest Fires
As stated previously, the forest inventory approach implicitly
accounts for emissions due to disturbances such as forest fires,
because only C remaining in the forest is estimated. Net C stock
change is estimated by subtracting consecutive C stock estimates.
A disturbance removes C from the forest. The inventory data on
which net C stock estimates are based already reflect this C loss.
Therefore, estimates of net annual changes in C stocks for U.S.
forestland already account for C02 emissions from forest fire, but
only for the lower 48 states. As detailed previously, Alaska is not
yet included in national estimates of forest C stocks and fluxes,
due to lack of forest inventory data at this time (see Planned
Improvements). Wildfire data is, however, available for Alaska,
so it has been included in these calculations. Because it is of
interest to quantify the magnitude of C02 emissions from fire
disturbance, these estimates are being highlighted here, using
the full extent of available data (Table 7-8). Non-C02 greenhouse
gas emissions from forest fires are also quantified in a separate
section below.
The IPCC (2003) methodology was employed to estimate C02 emissions from forest fires. C02 emissions for the lower 48 states
and Alaska in 2005 were estimated to be 126.4 Tg C02/yr. This amount is masked in the estimates of total flux for 2005, however, by
an additional 126.4 Tg C02/yr being sequestered (i.e., flux already accounts for the amount sequestered minus any emissions).
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02 emitted
in the Lower 48
States (Tg/yr)
42.7
42.9
144.6
63.0
89.7
81.4
5.0
75.9
C02 emitted
in Alaska
(Tg/yr)
34.5
0.5
8.2
2.4
23.6
6.5
70.6
50.5
Total
C02 emitted
(Tg/yr)
77.2
43.3
152.8
65.3
113.3
87.9
75.6
126.4
a Note that these emissions have already been accounted for in the net
C sequestration estimates (i.e., net flux already accounts for the amount
sequestered minus any emissions).
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Methodology
The methodology described herein is consistent
with IPCC (2003) and IPCC/UNEP/OECD/IEA (1997).
Estimates of net annual C stock change, or flux, of forest
ecosystems are derived from applying C estimation factors
to forest inventory data and interpolating between successive
inventory-based estimates of C stocks. C emissions from
harvested wood are based on factors such as the allocation
of wood to various primary and end-use products as well as
half-life (the time at which half of amount placed in use will
have been discarded from use) and expected disposition (e.g.,
product pool, SWDS, combustion). Different data sources
are used to estimate the C stocks and stock change in forest
ecosystems or harvested wood products. See Annex 3.12
for details and additional information related to the methods
described below.
Hires! Carbon Stocks and Fluxes
The first step in developing forest ecosystem estimates
is to identify useful inventory data and resolve any
inconsistencies among datasets. Forest inventory data were
obtained from the USD A Forest Service, Forest Inventory
and Analysis (FIA) program (Prayer and Furnival 1999,
USDA Forest Service 2006a). Inventories include forest
lands4 of the conterminous United States and are organized as
a number of separate datasets, each representing a complete
inventory, or survey, of an individual state at a specified time.
Forest C calculations are organized according to these state
surveys, and the frequency of surveys varies by state. To
calculate a C stock change, at least two surveys are needed
in each state. Thus, the most recent surveys for each state are
used as well as all additional consistent inventory data back
through 1990. Because C flux is based on change between
successive C stocks, consistent representation of forest land
in successive inventories is necessary. In order to achieve
accurate representation of forests from 1990 to the present,
sometimes state-level data are subdivided or additional
inventory sources are used to produce the consistent state
or sub-state inventories.
The principal FIA forest inventory datasets employed
are freely available for download at USDA Forest Service
(2006b) as the Forest Inventory and Analysis Database
(FIADB) Version 2.1. These data are identified as "snapshot"
files, also identified as FISDB 2.1, and include detailed plot
information, including individual-tree data. However, to
achieve consistent representation (spatial and temporal),
two other general sources of past FIA data are included as
necessary. Firstly, older FIA plot- and tree-level data—not
in the FIADB format—are used if available. Secondly,
Resources Planning Act Assessment (RPA) databases, which
are periodic, plot-level only, summaries of state inventories,
are used mostly to provide the data at or before 1990. A
detailed list of the specific inventory data used here is in
Table A-188 of Annex 3.12.
Forest C stocks are estimated from inventory data by a
collection of conversion factors and models referred to as
FORCARB2 (Birdsey and Heath 1995, Birdsey and Heath
2001, Heath et al. 2003, Smith et al. 2004a), which have
been formalized in an application referred to as the Carbon
Calculation Tool (CCT), (Smith et al. in preparation).
The conversion factors and model coefficients are usually
categorized by region and forest type, and forest C stock
estimates are dependent on these particular sets of factors.
Factors are applied to the data at the scale of FIA inventory
plots. The results are estimates of C density (Mg per hectare)
for the various forest pools. C density for live trees, standing
dead trees, understory vegetation, down dead wood, forest
floor, and soil organic matter are estimated. All non-soil
pools except forest floor can be separated into aboveground
and belowground components. The live tree and understory
C pools are pooled as biomass in this Inventory. Similarly,
standing dead trees and down dead wood are pooled as dead
wood in this Inventory. Definitions of ecosystem pools and
the C conversion process follow, with additional information
in Annex 3.12.
Live Biomass, Dead Wood, and Utter Carbon
Live tree C pools include aboveground and belowground
(coarse root) biomass of live trees with diameter at diameter
breast height (d.b.h.) of at least 2.54 cm at 1.37 m above
the forest floor. Separate estimates are made for full-tree
and aboveground-only biomass in order to estimate the
belowground component. If inventory plots include data
on individual trees, tree C is based on Jenkins et al. (2003)
and is a function of species and diameter. Some inventory
data do not provide measurements of individual trees; tree
4 Forest land in the United States includes land that is at least 10 percent stocked with trees of any size. Timberland is the most productive type of forest
land, which is on unreserved land and is producing or capable of producing crops of industrial wood.
Land Use, Land-Use Change, and Forestry 79
-------
C in these plots is estimated from plot-level volume of
merchantable wood, or growing-stock volume, of live trees,
which is calculated from updates of Smith et al. (2003). Some
inventory data, particularly some of the older datasets, may
not include sufficient information to calculate tree C because
of incomplete or missing tree or volume data; C estimates
for these plots are based on averages from similar, but more
complete, inventory data.
Understory vegetation is a minor component of biomass,
which is defined as all biomass of undergrowth plants in a
forest, including woody shrubs and trees less than 2.54 cm
d.b.h. In this Inventory, it is assumed that 10 percent of total
understory C mass is belowground. Estimates of C density
are based on information in Birdsey (1996).
The two components of dead wood —standing dead
trees and down dead wood —are estimated separately.
The standing dead tree C pools include aboveground and
belowground (coarse root) mass and include trees of at least
2.54 cm d.b.h. Down dead wood is defined as pieces of dead
wood greater than 7.5 cm diameter, at transect intersection,
that are not attached to live or standing dead trees. Down dead
wood includes stumps and roots of harvested trees. Ratios of
down dead wood to live tree are used to estimate this quantity.
Litter C is the pool of organic C (also known as duff, humus,
and fine woody debris) above the mineral soil and includes
woody fragments with diameters of up to 7.5 cm. Estimates
are based on equations of Smith and Heath (2002).
Forest Soil C
Soil organic carbon (SOC) includes all organic material
in soil to a depth of 1 meter but excludes the coarse roots
of the biomass or dead wood pools. Estimates of SOC are
based on the national STATSGO spatial database (USDA
1991), and the general approach described by Amichev
and Galbraith (2004). Links to FIA inventory data were
developed with the assistance of the USDA Forest Service
FIA Geospatial Service Center by overlaying FIA forest
inventory plots on the soil C map. Thus, SOC is defined by
region and forest type group.
C stocks and fluxes for Forest Land Remaining Forest
Land are reported in pools following IPCC (2003). Total forest
C stock and flux estimates start with the plot-level calculations
described above. The separate C densities are summed and
multiplied by the appropriate expansion factors to obtain
a C stock estimate for the plot. In turn, these are summed
to stare or sub-state total C stocks. Annualized estimates
of C stocks are based on interpolating or extrapolating as
necessary to assign a C stock to each year. For example, the
C stock of Alabama for 2005 is an extrapolation of the two
most recent inventory datasets for that particular state, which
are from 1999 and 2003. Flux, or net annual stock change, is
simplv the difference between two successive years with the
appropriate sign convention so that net increases in ecosystem
C are identified as negative flux. This methodological detail
accounts for the constant estimates of flux from the second
most recent Inventory to the present (see 2002 through 2005
on Table 7-5 as an example).
Harvested Wood Ciirbon
Estimates of the harvested wood product (HWP)
contribution to forest C sinks and emissions (hereafter called
"HWP Contribution") are based on methods described in
Skog (in preparation) using the WOODCARB II model.
These are based on the methods suggested in IPCC (2006)
for estimating HWP carbon. The United States uses the
production accounting approach to report HWP Contribution.
This means that C in exported wood is estimated as if it
remains in the United States, and C in imported wood is
not included in inventory estimates. Though the production
approach is used in this Inventory, estimates resulting from
use of the two alternative approaches, the stock change
and atmospheric flow approaches, are also presented for
comparison (see Annex 3.12). Annual estimates of change in
four HWP summary quantities are calculated by tracking the
additions to and removals from the pool of products held in
end uses (i.e., products in use such as housing or publications,
and the pool of products held in solid waste disposal sites
[SWDS]). These four categories of annual change of C in
wood and paper products are (1) all products in use in the
United States; (2) all products in SWDS in the United States;
(3) products in use in the United States and other countries
where the wood came from trees harvested in the United
States; and (4) products in SWDS in the United States and
other countries where the wood came from trees harvested
in the United States.
Solidwood products added to pools include lumber and
panels. End-use categories for solidwood include single and
multifamily housing, alteration and repair of housing, and
other end-uses. There is one product category and one end-use
category for paper. Additions to and removals from pools are
tracked beginning in 1900, with the exception that additions
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
of softwood lumber to housing begins in 1800. Solidwood
and paper product production and trade data are from USDA
Forest Service and other sources (Hair and Ulrich 1963;
Hair 1958; USDC Bureau of Census; 1976; Ulrich, 1985,
1989; Steer 1948; AF&PA 2006a 2006b; Howard 2003 &
forthcoming). Estimates for disposal of products reflect the
change over time in the fraction of products discarded to
SWDS (as opposed to burning or recycling) and the fraction
of SWDS that are in sanitary landfills versus dumps.
Summary categories 3 and 4 (above) are used to
estimate HWP Contribution under the production accounting
approach. A key assumption for estimating these variables
is that products exported from the United States and held in
pools in other countries have the same half lives for products
in use, the same percentage of discarded products going to
SWDS, and the same decay rates in SWDS as they would
in the United States.
Uncertainty
The forest survey data that underlie the forest C
estimates are based on a statistical sample designed to
represent the wide variety of growth conditions present over
large territories. The USDA Forest Service inventories are
designed to be accurate within 3 percent at the 67 percent
confidence level (one standard error) per 405,000 ha (1
million acres) of timberland (USDA Forest Service 2006c).
For larger areas, the uncertainty in area is concomitantly
smaller, and precision at plot levels is larger. An analysis
of uncertainty in growing stock volume data for timber
producing land in the Southeast by Phillips et al. (2000)
found that nearly all of the uncertainty in their analysis
was due to sampling rather than the regression equations
used to estimate volume from tree height and diameter. The
quantitative uncertainty analysis summarized here (and in
Table 7-9) primarily focuses on uncertainties associated with
the estimates of specific C stocks at the plot level and does
not address error in tree diameters or volumes.
Estimates for stand-level C pools are derived from
extrapolations of site-specific studies to all forest land,
because survey data on these pools are not generally
available. Such extrapolation introduces uncertainty because
available studies may not adequately represent regional or
national averages. Uncertainty may also arise due to; (1)
modeling errors (e.g., relying on coefficients or relationships
that are not well known); and (2) errors in converting
estimates from one reporting unit to another (Birdsey and
Heath 1995). An important source of uncertainty is that there
is little consensus from available data sets on the effect of
land-use change and forest management activities (such as
harvest) on soil C stocks. For example, while Johnson and
Curtis (2001) found little or no net change in soil C following
harvest, on average, across a number of studies, many of the
individual studies did exhibit differences. Heath and Smith
(2000) noted that the experimental design in a number of
soil studies limited their usefulness for determining effects
of harvesting on soil C. Because soil C stocks are large,
estimates need to be very precise, since even small relative
changes in soil C sum to large differences when integrated
over large areas. The soil C stock and stock change estimates
presented here are based on the assumption that soil C density
for each broad forest type group stays constant over time.
The state of information and modeling are improving in this
regard (Woodbury et al. 2006); the effects of land use and
of changes in land use and forest management will be better
accounted for in future estimates of soil C.
Uncertainty in estimates about the HWP Contribution
is based on Monte Carlo simulation of the production
Table 7-9: Tier 2 Quantitative Uncertainty Estimates for Net C02 Flux from Forest Land Remaining Forest Land:
Changes in Forest C Stocks (Tg C02 Eq. and Percent)
Source
Forest Ecosystem
Harvested Wood Products
Total Forest
Gas
C02
C02
C02
2005 Flux Estimate
(TgC02Eq.)
(595.3)
(103.4)
(698.7)
Uncertainty Range Relative to Flux Estimate3
(Tg C02 Eq.) (%)
Lower Bound
(785.2)
(130.2)
(889.5)
Upper Bound
(410.5)
(78.9)
(513.1)
Lower Bound
-32%
-26%
-27%
Upper Bound
+31%
+24%
+27%
Note: Parentheses indicate negative values or net sequestration.
a Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-11
-------
approach. The uncertainty analysis is based on Skog et al.
(2004). However, the uncertainty analysis simulation has
been revised in conjunction with overall revisions in the
HWP model (Skog in preparation). The analysis includes
an evaluation of the effect of uncertainty in 13 sources
including production and trade data, factors to convert
products to quantities of C, rates at which wood and paper
are discarded, and rates and limits for decay of wood and
paper in S WDS.
The 2005 flux estimate for forest C stocks is estimated
to be between -513.1 and -889.5 Tg CO2 Eq. at a 95 percent
confidence level. This includes a range of -410.5 to -785.2 Tg
CO2 Eq. in forest ecosystems and -78.9 to -130.2 Tg CO2 Eq.
for HWP. The relatively smaller range of uncertainty, in terms
of percentage, for the total relative to the two separate parts
is because the total is based on summing the two independent
uncertain parts, as discussed above.
QA/QC and Verification
As discussed above, the FIA program has conducted
consistent forest surveys based on extensive statistically-
based sampling of most of the forest land in the conterminous
United States, dating back to 1952. The main purpose of the
FIA program has been to estimate areas, volume of growing
stock, and timber products output and utilization factors. The
FIA program includes numerous quality assurance and quality
control (QA/QC) procedures, including calibration among
field crews, duplicate surveys of some plots, and systematic
checking of recorded data. Because of the statistically-based
sampling, the large number of survey plots, and the quality
of the data, the survey databases developed by the FIA
program form a strong foundation for C stock estimates. Field
sampling protocols, summary data, and detailed inventory
databases are archived and are publicly available on the
Internet (USDA Forest Service 2006b).
Many key calculations for estimating current forest C
stocks based on FIA data are based on coefficients from
the FORCARB2 model (see additional discussion in the
Methodology section above and in Annex 3.12). The model
has been used for many years to produce national assessments
of forest C stocks and stock changes. General quality control
procedures were used in performing calculations to estimate
C stocks based on survey data. For example, the derived C
datasets, which include inventory variables such as areas
and volumes, were compared with standard inventory
summaries such as Resources Planning Act (RPA) Forest
Resource Tables or selected population estimates generated
from the FIA Database (FIADB), which are available at an
FIA Internet site (USDA Forest Service 2006b). Agreement
between the C datasets and the original inventories is
important to verify accuracy of the data used. Finally, C stock
estimates were compared with previous Inventory report
estimates to ensure that any differences could be explained
by either new data or revised calculation methods (see the
"Recalculations" discussion below).
Estimates of the HWP variables and the HWP
Contribution under the production accounting approach use
data from U.S. Census and USDA Forest Service surveys of
production and trade. Factors to convert wood and paper from
original units to C units are based on estimates by industry
and Forest Service published sources. The WOODCARB
II model uses estimation methods suggested by the IPCC
(2006). Estimates of annual C change in solidwood and paper
products in use \vere verified by two independent criteria. The
first criteria is that the WOODCARB II model estimate of C
in houses standing in 2001 needs to match an independent
estimate of C in housing based on U.S. Census and USDA
Forest Service survey data. Meeting the first criteria resulted
in an estimated hall' life of about 80 years for single family
housing built in the 1920s, which is confirmed by other
U.S. Census data on housing. The second criteria is that the
WOODCARB II model estimate of wood and paper being
discarded to SWDS needs to match EPA estimates of discards
each year over the period 1990 to 2000. These criteria help
reduce uncertainty in estimates of annual change in C in
products in use in the United States and to a lesser degree
reduces uncertainty in estimates of annual change in C in
products made from wood harvested in the United States.
Recalculations Discussion
The overall scheme for developing annualized estimates
of forest ecosystem C stocks based on the individual state
surveys and the C conversion factors used are similar to
that presented in the previous Inventory (EPA 2006a).
The principal change from the previous year's methods
involves the increased use of sub-state classification of
the survey data as indicated in Table A-188 in Annex 3.12,
which details the survey data used for the current Inventory.
For the current Inventory, the emphasis was on improving
consistency between successive surveys or portions of
7-12 Inventory of U.S. Greenhouse Gas Emissions aiirS Sinks: 1980-2005
7.
-------
surveys when sub-state portions of inventory data provided
better continuity. The FIADB "snapshot" datasets were the
primary source of FIA inventory data. Secondary sources
included the plot and tree data from older, pre-FIADB,
inventories and the plot-level RPA datasets. By improving
the consistency of these datasets, substantial revisions were
made to previous estimates, which primarily affected early
years in the calculations. The new calculations of forest C
stocks in 1990 decreased the estimate of C sequestration
by 23 percent (174.9 Tg CO2 Eq.), while increasing C
sequestration estimates for forest C stocks in 2004 by 9
percent (60.1 Tg CO2 Eq.).
The change in stock and flux estimates for the period
since 1990, as compared to the estimates presented in the
previous Inventory, is based on the cumulative effects of (1)
additional inventory data, and (2) how the state or sub-state
inventories are classified. State-level inventory data changed
more dramatically for some particular states as compared to
others. As an example, stock and flux estimates for the state
of California are based on the FIA datasets specified in Table
A-188 in Annex 3.12. In past inventories (for example, EPA
2006a), chaparral ecosystems were included in forest inventory
data and, therefore, forest C stock estimates. However, much
of this ecological community type fails to meet the definition
of forestland. Current FIA forest inventory data does not
include non-forest land of this ecological community. In order
to maintain consistency across the time series, non-forest
chaparral estimates had to be removed from California's total
stock estimates in earlier inventories. This caused a dramatic
decrease in forest C stock estimates at the early part of the time
series for the state of California compared to those California
estimates used for the previous inventory submission.
The estimate of HWP contribution under the production
account approach has been revised. Estimates of the 5 HWP
variables have been added (see Annex 3.12), which allow
estimates using the alternate accounting approaches for
which the IPCC provides accounting guidance (IPCC 2006).
The basic method used to estimate the HWP variables has
not changed —tracking additions to and removals from
pools —but more detailed product and trade data are used and
discard and decay parameters have been revised. With use
of more detailed production and trade data and modification
in half lives for solidwood and paper product in use (to meet
calibration criteria), the estimates of C additions to product
in use (under the production approach) varies differently
from year to year. With calibration based on two criteria
(See Annex 3.12 for more details), the use of revised curves
to describe discards from products in use (first order decay)
did not affect recent year estimates of annual additions to
products in use, when compared to the curves previously
used. Average annual total additions due to HWP from the
period 1990 through 2004 (111 Tg CO2 Eq.) is about 47
percent less than the previous estimate of 209 Tg CO2 Eq.
Virtually all of the decrease in annual additions is due to a
decrease in estimates of annual additions to landfills and
dumps. The estimate of total C in products in use in 2004
has increased from 1344 Tg to 1389 Tg. The estimate of
total C in products in landfills and dumps in 2004 decreased
from 1369 Tg to 952 Tg. There are several revisions that
contributed to the decrease in annual additions to landfills
and dumps. Changes have been greater for estimates of C
additions to SWDS. Estimates of the fractions of discarded
wood going to landfills and dumps were revised using data
from EPA (2006b and prior years), Melosi (1981,2000) and
other sources. Estimates of the fraction of wood and paper
not subject to decay in landfills were revised, based on
Freed and Mintz (2003), using data from studies by Eleazer
et al. (1997) and Barlaz (1998). The estimated fraction of
C in wood subject to decay in landfills was revised from 3
percent to 23 percent, while the estimated fraction of C in
paper subject to decay in landfills increased from 26 percent
to 56 percent. Those fractions of wood and paper not subject
to decay, therefore, decreased. Previous estimates of wood
and paper subject to decay in landfills had been based on
Micales and Skog (1997). Estimates of the rates of decay in
landfills and dumps were also updated to 29 years and 14.5
years, respectively, using values from IPCC (2006). These
half-lives are the midpoints of the estimated ranges of decay
for wood and paper in temperate regions. The estimate of
total C additions in SWDS over the period 1990 through 2004
decreased from 630 Tg to 256 Tg. Overall, the estimate of
C additions under the production accounting approach over
the period 1990 to 2004 has decreased from 857 Tg to 455
Tg, or 47 percent.
Another change in the current Inventory is the inclusion
of estimates of C emissions caused by fire disturbance.
Although these emissions are implicitly included in total
forest C flux estimates, expert and public reviews of previous
Inventories indicated an interest in the magnitude of this flux.
An estimate of C emissions was, therefore, calculated and
Land Use, Land-Use Change, and Forestry 713
-------
included in Box 7-1 in the current Inventory. C emissions
caused by fire disturbance are still implicitly included as part
of the overall forest C flux estimate, and, thus, not treated as
a separate estimate in the current Inventory.
Non-CO2 emissions from forest fires is a new source
included in the current Inventory. CH4 and N2O emissions
resulting from forest fires were not previously calculated, but
these estimates are now included in their own subsection of
Forest Land Remaining Forest Land.
Planned Improvements
The ongoing annual surveys by the FIA Program will
improve precision of forest C estimates as new state surveys
become available (Gillespie 1999). The annual surveys will
eventually include all states. Therefore, inventory-based
estimates of net annual flux for Alaska will become available,
starting with the more productive forest in the southeastern
portion of the state. Forest inventory data is limited in
Alaska and, in the past, a net C change of zero was assumed.
Alaska has over 50 million hectares of forest land, however,
and could have a significant effect on estimates of total C
emissions and sinks. A review of the scientific literature
indicates Alaskan forests could change U.S. national forest
C flux estimates by 5 to 10 percent (not including harvested
wood). In addition, the more intensive sampling of down dead
wood, litter, and soil organic C on some of the permanent
FIA plots will substantially improve resolution of C pools
at the plot level for all U.S. forest land.
As more information becomes available about historical
land use, the ongoing effects of changes in land use and
forest management will be better accounted for in estimates
of soil C (Birdsey and Lewis 2003, Woodbury et al. 2006).
Currently, soil C estimates are based on the assumption that
soil C density depends only on broad forest type group, not
on land-use history. However, many forests in the Eastern
United States are re-growing on abandoned agricultural land.
During such regrowth, soil and forest floor C stocks often
increase substantially over many years or even decades,
especially on highly eroded agricultural land. In addition,
with deforestation, soil C stocks often decrease over many
years. A new methodology is being developed to account for
these changes in soil C over time. This methodology includes
estimates of area changes among land uses (especially forest
and agriculture), estimates of the rate of soil C stock gain
with afforestation, and estimates of the rate of soil C stock
loss with deforestation over time. This topic is important
because soil C stocks are large, and soil C flux estimates
contribute substantially to total forest C flux.
Similarly, agroforestry practices, such as windbreaks
or riparian forest buffers along waterways, are not currently
accounted for in the Inventory. In order to properly account
for the C stocks and fluxes associated with agroforestry,
research will be needed that provides the basis and tools for
including these plantings into a nation-wide inventory, as
well as the means for entity-level reporting.
An additional planned improvement is to develop
a consistent representation of the U.S. managed land
base. Currently, the forest C and the agricultural soil C
inventories are the two major analyses addressing land-use
and management impacts on C stocks. The forest inventory
relies on the activity data from the FIA Program to estimate
anthropogenic impacts on forest land, while the agricultural
soil C inventory relies on the USDA National Resources
Inventory (NRI). Recent research has revealed that the
classification of forest land is not consistent between the
FIA and NRI, leading to some double-counting and gaps in
the current forest C and agricultural soil C inventories (e.g.,
some areas classified as forest land in the FIA are considered
rangeland in the NRI). Consequently, the land bases are in
the process of being compared between the inventories to
determine where overlap or gaps occur, and then ensure that
the inventories are revised to have a consistent and complete
accounting of land-use and management impacts across all
managed land in the United States.
Non-C02 Emissions From Forest Fires
Emissions of non-CO2 gases from forest fires were
estimated using the default IPCC (2003) methodology.
Emissions from this source in 2005 were estimated to be
11.6 Tg CO2 Eq. of CH4 and 1.2 Tg CO2 Eq. of N2O, as
shown in Table 7-10 and Table 7-11. The non-CO2 estimates
of forest fire emissions account for both the lower 48
states and Alaska, while the national inventory estimates
of forest C stocks and fluxes currently include only the
conterminous states.
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 7-10: Estimated Non-C02 Emissions from Forest Fires (Tg C02 Eq.) for U.S. Forests3
Gas
1990
1995
2000 2001 2002 2003 2004
2005
CH4
N20
7.1
0.7
4.0
0.4
14.0
1.4
6.0
0.6
10.4
1.1
8.1
0.8
6.9
0.7
11.6
1.2
Total
7.8
4.4
15.4
6.6
11.4
8.9
1 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
7.6 12.8
1 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
Table 7-11: Estimated Non-C02 Emissions from Forest Fires (Gg Gas) for U.S. Forests3
Gas
CH4
N20
1990
337
2
1995
189
1 :
2000
667
5
2001
285
2
2002
494
3
2003
384
3
2004
330
2
2005
551
4
Methodology
The IPCC (2003) Tier 2 default methodology was used
to calculate non-CO2 emissions from forest fires. Estimates
for CH4 emissions were calculated by multiplying the total
estimated C emitted (see Table 7-12) from forest burned by
gas-specific emissions ratios and conversion factors. N2O
emissions were calculated in the same manner, but were also
multiplied by a N-C ratio of 0.01 as recommended by IPCC
(2003). The equations used were:
(Hi Emissions ~ (C released) % (emission ratio) x 16'12
,V<) 1 missions - (C released i x ( N'C ratio) >'
(emission ratio) v 44-2N
Estimates for C emitted from forest fires, presented in
Table 7-12 below, are the same estimates used to generate
estimates of CO^ emissions from forest fires, presented earlier
in Box 7-1. See Table A-197 and explanation in Annex 3.12
for more details on the methodology used to estimate C
emitted from forest fires.
Table 7-12: Estimated Carbon Released from Forest
Fires for U.S. Forests
Year
1990
1995
2000
2001
2002
2003
2004
2005
C Emitted (Tg/yr)
21.1
11.8
41.7
17.8
30.9
24.0
20.6
34.5
Uncertainty
Non-CO2 gases emitted from forest fires depend on
several variables, including forest area and average C density
for forest land in both Alaska and the lower 48 states, emission
ratios, and combustion factor values (proportion of biomass
consumed by fire). To quantify the uncertainties for emissions
from forest fires, a Monte Carlo (Tier 2) uncertainty analysis
was performed using the information provided above. The
results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 7-13.
Table 7-13: Tier 2 Quantitative Uncertainty Estimates of Non-C02 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Non-C02 Emissions from
Forest Fires
Non-C02 Emissions from
Forest Fires
CH4
N20
11.6
1.2
3.2
0.3
21.5
2.2
-71%
-70%
+92%
+93%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-15
-------
Direct N20 Fluxes from Forest
(IPCC Source Category 5A1)
Of the synthetic N fertilizers applied to soils in the
United States, no more than one percent is applied to forest
soils. Application rates are similar to those occurring on
cropped soils, but in any given year, only a small proportion
of total forested land receives N fertilizer. This is because
forests are typically fertilized only twice during their
approximately 40-year growth cycle (once at planting and
once approximately 20 years later). Thus, although the rate
of N fertilizer application for the area of forests that receives
N fertilizer in any given year is relatively high, average
annual applications, inferred by dividing all forest land that
may undergo N fertilization at some point during its growing
cycle by the amount of N fertilizer added to these forests
in a given year, is quite low. Nitrous oxide emissions from
forest soils are estimated to have increased by a multiple of
5.5 from 1990 to 2005. The trend toward increasing N2O
emissions is a result of an increase in the area of N fertilized
pine plantations in the southeastern United States. Total forest
soil N2O emissions are summarized in Table 7-14.
Methodology
The IPCC Tier 1 approach was used to estimate N2O
from soils within Forest Land Remaining Forest Land.
According to U.S. Forest Service statistics for 1996 (USDA
Forest Service 2001), approximately 75 percent of trees
planted were for timber, and about 60 percent of national
total harvested forest area are in the southeastern United
Table 7-14: N20 Fluxes from Soils in Fores/ Land
Remaining Forest Land (Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
0.1
0.2
0.3
0.3
0.3
0.3
0.3
0.3
Gg
<1
1
1
1
1
1
1
1
Note: These estimates include direct N20 emissions from N fertilizer
additions only. Indirect I\I20 emissions from fertilizer additions are
reported in the Agriculture chapter. These estimates include emissions
from both Forest Land Remaining Forest Land and from Land Converted
to Forest Land.
States. Consequently, it was assumed that southeastern pine
plantations represent the vast majority of fertilized forests
in the United States. Therefore, estimates of direct N2O
emissions from fertilizer applications to forests were based
on the area of pine plantations receiving fertilizer in the
southeastern United States and estimated application rates
(North Carolina State Forest Nutrition Cooperative 2002).
Not accounting for fertilizer applied to non-pine plantations
is justified because fertilization is routine for pine forests
but rare for hardwoods (Binkley et al. 1995). For each year,
the area of pine receiving N fertilizer was multiplied by the
midpoint of the reported range of N fertilization rates (150
Ibs. N per acre). Data for areas of forests receiving fertilizer
outside the southeastern United States were not available,
so N additions to non-southeastern forests are not included
here. It should be expected, however, that emissions from
the small areas of fertilized forests in other regions would
be insubstantial because the majority of trees planted and
harvested for timber are in the southeastern United States
(USDA Forest Service 2001). Area data for pine plantations
receiving fertilizer in the Southeast were not available for
2002,2003,2004, and 2005, so data from 2001 were used for
these years. The N applied to forests was multiplied by the
IPCC (2006) default emission factor of 1 percent to estimate
direct N2O emissions. The volatilization and leaching/runoff
fractions, calculated according to the IPCC default factors
of 10 percent and 30 percent, respectively, were included
with all sources of indirect emissions in the Agricultural Soil
Management source category of the Agriculture chapter.
Uncertainty
The amount of N2O emitted from forests depends not
only on N inputs, but also on a large number of variables,
including organic C availability, OT partial pressure, soil
moisture content, pH, temperature, and tree planting/
harvesting cycles. The effect of the combined interaction
of these variables on N2O flux is complex and highly
uncertain. The IPCC default methodology used here does
not incorporate any of these variables and only accounts
for variations in estimated fertilizer application rates and
estimated areas of forested land receiving N fertilizer. All
forest soils are treated equivalently under this methodology.
Furthermore, only synthetic N fertilizers are captured, so
applications of organic N fertilizers are not accounted for
here. However, the total quantity of organic N inputs to soils
7-16 Inventory of SJ.S, Greenhouse Gas Froissions and Sink;;: 199fl-2QQ5
-------
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land Remaining Forest
Land (Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Forest Land Remaining Forest
Land: N20 Fluxes from Soils N20
0.3
0.1
1.1
-59%
+211%
Note: This estimate includes direct N20 emissions from N fertilizer additions to both Forest Land Remaining Forest Land and Land Converted to Forest Land.
is accounted for in the Agricultural Soil Management and
Settlements Remaining Settlements sections.
Uncertainties exist in the fertilizer application rates, the
area of forested land receiving fertilizer, and the emission
factors used to derive emission estimates.
To quantify the uncertainties for N2O fluxes from forest
soils, a Monte Carlo (Tier 2) uncertainty analysis was performed
using the information provided above. The results of the Tier
2 quantitative uncertainty analysis are summarized in Table
7-15. N2O fluxes from soils were estimated to be between
0.1 and 1.1 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 59 percent below and 211 percent above
the 2005 emission estimate of 0.3 Tg CO9 Eq.
Recalculations Discussion
The IPCC default emission factor of 1.25 percent for
direct emissions from applied N was updated to 1 percent
based on IPCC (2006). Additionally, because the direct
emission factor was developed based on total N inputs,
the new method has been revised to estimate direct N2O
emissions based on total N input. Previously, a portion of
the N inputs were removed from the calculation of direct
N2O emissions, because it was assumed to be lost through
volatilization before direct emissions occurred.
Planned improvements
Area data for southeastern pine plantations receiving
fertilizer will be updated with more recent datasets.
7,2, Land Converted to Forest land
(IPCC Source Category 5A2)
Land-use change is constantly occurring, and areas
under a number of differing land-use types are converted to
forest each year, just as forest land is converted to other uses.
However, the magnitude of these changes is not currently
known. Given the paucity of available land-use information
relevant to this particular IPCC source category, it is not
possible to separate CO7 or NUO fluxes on Land Converted
to Forest Land from fluxes on Forest Land Remaining Forest
Land at this time.
7,3. Cropland Remaining Cropland
(IPCC Source Category 5B1)
Soils contain both organic and inorganic forms of C, but
soil organic carbon (SOC) stocks are the main source or sink
for atmospheric CCs in most soils. Changes in inorganic C
stocks are typically minor. Soil organic C is the dominant
organic C pool in cropland ecosystems, because biomass and
dead organic matter have considerably less C and those pools
are relatively ephemeral. IPCC/UNEP/OECD/IEA (1997)
recommends reporting changes in soil organic C stocks due
to agricultural land-use and management activities on mineral
soils and organic soils. In addition, the IPCC Guidelines
recommend reporting CO2 emissions that result from liming
of soils with dolomite and limestone.
Typical well-drained mineral soils contain from 1 to 6
percent organic C by weight, although some mineral soils
that are saturated with water for substantial periods during the
year may contain significantly more C (NRCS 1999). When
mineral soils undergo conversion from their native state to
agricultural uses, as much as half the SOC can be lost to the
atmosphere. The rate and ultimate magnitude of C loss will
depend on pre-conversion conditions, conversion method and
subsequent management practices, climate, and soil type. In
the tropics, 40 to 60 percent of the C loss generally occurs
within the first 10 years following conversion; C stocks
continue to decline in subsequent decades but at a much
slower rate. In temperate regions, C loss can continue for
several decades, reducing stocks by 20 to 40 percent of native
C levels. Eventually, the soil can reach a new equilibrium
Land Use, Land-Use Change, and Forestry
-------
that reflects a balance between C inputs (e.g., decayed plant
matter, roots, and organic amendments such as manure and
crop residues) and C loss through microbial decomposition
of organic matter. However, land use, management, and
other conditions may change before the new equilibrium is
reached. The quantity and quality of organic matter inputs and
their rate of decomposition are determined by the combined
interaction of climate, soil properties, and land use. Land use
and agricultural practices such as clearing, drainage, tillage,
planting, grazing, crop residue management, fertilization,
and flooding, can modify both organic matter inputs and
decomposition, and thereby result in a net flux of C to or
from the pool of soil C.
Organic soils, also referred to as histosols, include all
soils with more than 12 to 20 percent organic C by weight,
depending on clay content (NRCS 1999, Brady and Weil
1999). The organic layer of these soils can be very deep
(i.e., several meters), forming under inundated conditions,
in which minimal decomposition of plant residue occurs.
When organic soils are prepared for crop production, they
are drained and tilled, leading to aeration of the soil, which
accelerates the rate of decomposition and CO2 emissions.
Because of the depth and richness of the organic layers, C loss
from drained organic soils can continue over long periods of
time. The rate of CO2 emissions varies depending on climate
and composition (i.e.,decomposability) of the organic matter.
Also, the use of organic soils for annual crop production
leads to higher C loss rates than drainage of organic soils
in grassland or forests, due to deeper drainage and more
intensive management practices in cropland (Armentano and
Verhoeven 1990, as cited in IPCC/UNEP/OECD/IEA 1997).
C losses are estimated from drained organic soils under both
grassland and cropland management in this inventory.
The last category of the IPCC methodology addresses
emissions from lime additions (in the form of crushed
limestone (CaCO3) and dolomite (CaMg(CO3)2) to
agricultural soils. Lime and dolomite are added by
land managers to ameliorate acidification. When these
compounds come in contact with acid soils, they degrade,
thereby generating CO2. The rate and ultimate magnitude
of degradation of applied limestone and dolomite depends
on the soil conditions, climate regime, and the type of
mineral applied.
Cropland Remaining Cropland includes all areas
designated as cropland that had been cropland since 1982
according to the USDANRI land use survey (USDA-NRCS
2000). Consequently, the area of Cropland Remaining
Cropland changes through time with land-use change. For
this area, CO2 emissions and removals5 due to changes in
mineral soil C stocks are estimated using a Tier 3 approach
for the majority of annual crops. A Tier 2 IPCC method
is used for the remaining crops (vegetables, tobacco,
perennial/horticultural crops, and rice) not included in the
Tier 3 method. In addition, a Tier 2 method is used for very
gravelly, cobbly or shaley soils (i.e., classified as soils that
have greater than 35 percent of soil volume comprised
of gravel, cobbles or shale) and for additional changes in
mineral soil C stocks that were not addressed with the Tier
2 or 3 approaches (i.e., change in C stocks after 1997 due
to Conservation Reserve Program enrollment). Emissions
from organic soils are estimated using a Tier 2 IPCC' method.
Emissions from liming are estimated using a Tier 2 IPCC
method that relies on national aggregate statistics of lime
application and emissions factors developed by West and
McBride(2005).
Of the three sub-source categories, land-use and land
management of mineral soils was the most important
component of total net C stock change between 1990 and
2005 (see Table 7-16 and Table 7-17). In 2005, mineral soils
were estimated to remove about 71.1 Tg CO2 Eq. (19.4 Tg
C). This rate of C storage in mineral soils represented about
an 18 percent increase in the rate since the initial reporting
year of 1990. Emissions from organic soils had the second
largest flux, emitting about 27.7 Tg CO2 Eq. (7.5 Tg C) in
2005. Liming emitted another 4.0 Tg CO2 Eq. (1.1 Tg C) in
2005. In total, U.S. agricultural soils in Cropland Remaining
Cropland removed approximately 39.4 Tg CO2 Eq. (10.7
TgC)in2005.
The net increase in soil C stocks over the period from
1990 through 2005 was largely due to an increase in annual
cropland enrolled in the Conservation Reserve Program,
intensification of crop production by limiting the use of
bare-summer fallow in semi-arid regions, increased hay
production, and adoption of conservation tillage (i.e.,
reduced- and no-till practices). At present (2005), cropland
enrolled in the Conservation Reserve Program accounts
5 Note that removals occur through crop and forage uptake ot'COi into biomass C tha1: is later incorporated into soils pools.
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 7-16: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils
Liming of Soils3
Total Net Flux
1990
(60.2)
27.4
4.7
(28.1)
1995
(69.5)
27.7
4.4
(37.4)
2000
(68.5)
27.7
4.3
(36.5)
2001
(70.1)
27.7
4.4
(38.0)
2002
(70.4)
27.7
5.0
(37.8)
2003
(70.5)
27.7
4.6
(38.3)
2004
(71.0)
27.7
3.9
(39.4)
2005
(71.1)
27.7
4.0
(39.4)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are
based on historical data only. Totals may not sum due to independent rounding.
3 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
Table 7-17: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C)
Soil Type
Mineral Soils
Organic Soils
Liming of Soils3
Total Net Flux
1990
(16.4)
7.5
1.3
(7.7)
1995
(18.9)
7.5
1.2
(10.2)
2000
(18.7)
7.5
1.2
(10.0)
2001
(19.1)
7.5
1.2
(10.4)
2002
(19.2)
7.5
1.4
(10.3)
2003
(19.2)
7.5
1.2
(10.4)
2004
(19.4)
7.5
1.1
(10.7)
2005
(19.4)
7.5
1.1
(10.7)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are
based on historical data only. Totals may not sum due to independent rounding.
a Also includes emissions from liming in Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
for 32 percent of the increase of C stocks for Cropland
Remaining Cropland on mineral soils (Table 7-17).
The spatial variability in annual CO2 flux associated
with C stock changes in mineral and organic soils is
displayed in Figure 7-4 and Figure 7-5. The highest rates
of sequestration in mineral soils occurred in the Midwest,
where there were the largest amounts of cropland managed
with conservation tillage adoption. Rates were also high
in the Great Plains due to enrollment in the Conservation
Reserve Program. Emission rates from drained organic-
soils were highest along the southeastern coastal region, in
the northeast central United States surrounding the Great
Lakes, and along the central and northern portions of the
West Coast.
The estimates presented here are restricted to C stock
changes in agricultural soils. Agricultural soils are also
important sources of other greenhouse gases, particularly
N2O from application of fertilizers, manure, and crop
residues and from cultivation of legumes, as well as
CH4 from flooded rice cultivation. These emissions are
accounted for in the Agriculture chapter, along with
non-CO2 greenhouse gas emissions from field burning of
crop residues and CH4 and N2O emissions from livestock
digestion and manure management.
Methodology
The following section includes a description of the
methodology used to estimate changes in soil C stocks due
to: (1) agricultural land-use and management activities on
mineral soils; (2) agricultural land-use and management
activities on organic soils; and (3) CO2 emissions that
result from liming of soils with dolomite and limestone for
Cropland Remaining Cropland.
Soil C stock changes were estimated for Cropland
Remaining Cropland (as well as agricultural land falling into
the IPCC categories Land Converted to Crop/and, Grassland
Remaining Grassland, and Land Converted to Grassland)
according to land use histories recorded in the USDA
National Resources Inventory (NRI) survey (USDA-NRCS
2000). The NRI is a statistically-based sample of all non-
federal land, and includes ca. 400,000 points in agricultural
land of the conterminous United States and Hawaii.6 Each
point is associated with an "expansion factor" that allows
scaling of C stock changes from NRI points to the entire
country (i.e., each expansion factor represents the amount
of area with the same land-use/management history as the
sample point). Land-use and some management information
(e.g..crop type, soil attributes, and irrigation) were collected
for each NRI point on a 5-year cycle beginning in 1982, and
1 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-19
-------
Figure 7-4
Net Soil C Stock Change for Mineral Soils in Cropland Remaining Cropland, 2005 j
Tg C02 Eq/yr
D Oto1
D -0.1 to 0
[U-0.5 to-0.1
n -1 to -0.5
D-2to-1
III-4 to-2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
Figure 7-5
Net Soil C Stock Change for Organic Soils in Cropland Remaining Cropland, 2005
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
H 0.5 to 0.1
[H 0.1 to 0.5
n o to 0.1
Q] No organic soils
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1993-2005
-------
were subdivided into four inventory time periods, 1980-84,
1985-1989, 1990-94 and 1995-2000. Currently, the NRI is
being revised to collect data annually from a subset of points.
However, at present, no additional inventory point data are
available for years after 1997.
NRI points were classified as Cropland Remaining
Cropland for an inventory time period (e.g., 1990-1994
and 1 995-2000) if the land use had been cropland since the
first year of the NRI survey in 1982 through the end of the
respective time period. Cropland includes all land used to
produce food or fiber, as well as forage that is harvested and
used as feed (e.g., hay and silage).
iVMnerai Soil Caroon Ssoci ilhantjes
A Tier 3 model-based approach was used to estimate C
stock changes for mineral soils used to produce a majority
of annual crops in the United States (i.e., all crops except
vegetables, tobacco, perennial/horticultural crops, and rice,
in addition to lands with very gravelly, cobbly or shaley soils
(greater than 35 percent by volume)) . An IPCC Tier 2 method
(see Ogle et al. 2003) was used to estimate C stock changes
for cropland on mineral soils that were not addressed with the
Tier 3 method: vegetables, tobacco, perennial/horticultural
crops, rice, and crops rotated with these crops. The Tier 2
method was also used for very gravelly, cobbly or shaley
soils. Mineral SOC stocks were estimated using a Tier 2
method for these areas, because the Century model used
for the Tier 3 method has not been fully tested to address
its adequacy for estimating C stock changes associated
with certain crops and rotations, as well as cobbly, gravelly
or shaley soils. An additional stock change calculation
was made for mineral soils using Tier 2 emission factors.
These calculations accounted for enrollment patterns in the
Conservation Reserve Program after 1997, which was not
addressed by the Tier 3 methods.
Further elaboration on the methodology and data used
to estimate stock changes from mineral are described below
and in Annex 3.13.
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated
using the Century biogeochemical model (Parton et al. 1987,
1988, 1994; Metherell et al. 1993), which simulates the
dynamics of C and other elements in cropland, grassland,
forest, and savanna ecosystems. It uses monthly weather
data as input, along with information about soil physical
properties. Input data on land use and management can
be specified at monthly resolution and include land-use
type, crop/forage type, and management activities (e.g.,
planting, harvesting, fertilization, manure amendments,
tillage, irrigation, residue removal, grazing, and fire). The
model computes net primary productivity and C additions
to soil, temperature, and water dynamics, in addition to
turnover, stabilization, and mineralization of soil organic
matter C and nutrient (N, K, S) elements. This method is
more accurate than the Tier 1 and 2 approaches provided
by the IPCC, because the simulation model treats changes
as continuous over time rather than the simplified discrete
changes represented in the default method (see Box 7-2 for
additional information). National estimates were obtained by
simulating historical land-use and management patterns as
recorded in the USDA National Resources Inventory (NRI)
survey. Land-use and management activities were grouped
into inventory time periods (i.e., time "blocks") for 1980-84,
1985-89, 1990-94 and 1995-2000, using NRI data from
1982, 1987, 1992, and 1997, respectively.
Additional sources of activity data were used to
supplement the land-use information from NRI. The
Conservation Technology Information Center (CTIC 1998)
provided annual data on tillage activity at the county level
since 1989, with adjustments for long-term adoption of no-
till agriculture (Towery 2001). Information on fertilizer use
and rates by crop type for different regions of the United
States were obtained primarily from the USDA Economic
Research Service Cropping Practices Survey (ERS 1997)
with additional data from other sources, including the
National Agricultural Statistics Service (NASS 1992, 1999,
2004). Frequency and rates of manure application to cropland
during 1997 were estimated from data compiled by the USDA
Natural Resources Conservation Service (Edmonds et al.
2003), and adjusted based on county-level manure production
rates for other years in the Inventory. Specifically, county-
scale ratios of manure production in other years relative to
1997 were used to estimate the area amended in the other
years, essentially scaling the amendment data compiled
by USDA in 1997 across the time series (see Annex 3.13
for further details). Higher managed manure N production
relative to 1997 was, thus, assumed to increase the amount
of area amended with manure, while less managed manure
N production relative to 1997 was assumed to reduce the
amended area. The amount of managed manure produced
Land Use, Land-Use Change, and Forestry 7-21
-------
Box 7-2: Tier 3 Inventory for Soil C Stocks compared to Tier 1 or 2 Approaches
A Tier 3 model-based approach is used to inventory soil C stock changes on the majority of agricultural land with mineral soils. This
approach entails several fundamental differences compared to the IPCC Tier 1 or 2 methods, which are based on a classification of land
areas into a number of discrete states based on a highly aggregated classification of climate, soil, and management (i.e., only six climate
regions, seven soil types and eleven management systems occur in U.S. agricultural land). Input variables to the Tier 3 model, including
climate, soils, and management activities (e.g., fertilization, crop species, tillage, etc.), are represented in considerably more detail both
temporally and spatially, and exhibit multi-dimensional interactions through the more complex model structure compared with the IPCC Tier
1 or 2 approach. The spatial resolution of the analysis is also finer in the Tier 3 method compared to the lower tier methods as implemented
in the United States for previous inventories (e.g., 3,037 counties versus 181 Major Land Resource Areas (MLRAs), respectively).
In the Century model, soil C dynamics (and C02 emissions and uptake) are treated as continuous variables, which change on a monthly
time step. C emissions and removals are an outcome of plant production and decomposition processes, which are simulated in the model
structure. Thus, changes in soil C stocks are influenced by not only changes in land use and management but also inter-annual climate
variability and secondary feedbacks between management activities, climate and soils as they affect primary production and decomposition.
This latter characteristic constitutes one of the greatest differences between the methods, and forms the basis for a more complete accounting
of soil C stock changes in the Tier 3 approach compared with Tier 2 methodology.
Because the Tier 3 model simulates a continuous time period rather than as an equilibrium step change used in the IPCC methodology
(Tier 1 and 2), the Tier 3 model addresses the delayed response of the soil to management and land-use changes, which can occur due to
variable weather patterns and other environmental constraints that interact with land use and management and affect the time frame over
which stock changes occur. Moreover, the Tier 3 method also accounts for the overall effect of increasing yields and, hence, C input to soils
that have taken place across management systems and crop types within the United States. Productivity has increased by 1 to 2 percent
annually over the past 4 to 5 decades for most major crops in the United States (Reilly and Fuglie 1998), which is believed to have led to
increases in cropland soil C stocks (e.g., Allmaras et al. 2000). This is a major difference from the IPCC-based Tier 1 and 2 approaches,
in which soil C stocks change only with discrete changes in management and/or land use, rather than a longer term trend such as gradual
increases in crop productivity.
by each livestock type was calculated by determining the
population of animals that were on feedlots or otherwise
housed (requiring manure to be collected and managed).
Annual animal population data for all livestock types, except
horses and goats, were obtained for all years from the U.S.
Department of Agriculture-National Agricultural Statistics
Service (USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c,2000,
2004a-e, 2005a-e, 2006a-e). Horse population data were
obtained from the FAOSTAT database (FAO 2006). Goat
population data for 1992, 1997, and 2002 were obtained
from the Census of Agriculture (USDA 2()05f); these data
were interpolated and extrapolated to derive estimates for
the other years. Information regarding poultry turnover (i.e.,
slaughter) rate was obtained from state Natural Resource
Conservation Service personnel (Lange 2000). Additional
population data for different farm size categories for dairy
and swine were obtained from the 1992 and 1997 Census of
Agriculture (USDA2005g).
Monthly weather data, aggregated to county-scale from
the Parameter-elevation Regressions on Independent Slopes
Model (PRISM) database (Daly et al. 1994), were used
as an input in the model simulations. Soil attributes were
obtained from an NRI database, which were assigned based
on field visits and soil series descriptions. Where more than
one inventory point was located in the same county (i.e.,
same weather) and having the same land-use/management
histories and soil type, data inputs to the model were identical
and, therefore, these points were clustered for simulation
purposes. For the 370,738 NRI points representing non-
federal cropland and grassland, there were a total of 170,279
clustered points that represent the unique combinations of
climate, soils, land use, and management in the modeled
data set. Each NRI cluster point was run 100 times as part
of the uncertainty assessment, yielding a total of over 14
million simulation runs for the analysis. C stock estimates
from Century were adjusted using a structural uncertainty
estimator accounting for uncertainty in model algorithms
and parameter values (Ogle et al. 2007). Mean changes in
C stocks and 95 percent confidence intervals were estimated
for 1990 to 1994 and 1995 to 2000 (see Uncertainty section
for more details). C stock changes from 2001 to 2005 were
assumed to be similar to the 1995 to 2.000 block, because
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
no additional activity data are currently available from the
NRI for the latter years.
Tier 2 Approach
In the Tier 2 method, data on climate, soil types, land-
use and land management activity were used to classify
land area to apply appropriate stock change factors. MLRAs
formed the base spatial unit for mapping climate regions in
the United States; each MLRA represents a geographic unit
with relatively similar soils, climate, water resources, and
land uses (NRCS 1981).7 MLRAs were classified into climate
regions according to the IPCC categories using the PRISM
climate database of Daly et al. (1994).
Reference C stocks were estimated using the National
Soil Survey Characterization Database (NRCS 1997) with
cultivated cropland as the reference condition, rather than
native vegetation as used in IPCC/UNEP/OECD/IEA (1997)
and IPCC (2003). Changing the reference condition was
necessary because soil measurements under agricultural
management are much more common and easily identified in
the National Soil Survey Characterization Database (NRCS
1997) than those that are not considered cultivated cropland.
U.S.-specific stock change factors were derived from
published literature to determine the impact of management
practices on SOC storage, including changes in tillage,
cropping rotations and intensification, and land-use change
between cultivated and uncultivated conditions (Ogle et
al. 2003, Ogle et al. 2006).8 U.S. factors associated with
organic matter amendments were not estimated because of
an insufficient number of studies to analyze those impacts.
Instead, factors from IPCC (2003) were used to estimate the
effect of those activities. Euliss and Gleason (2002) provided
the data for computing the change in SOC storage resulting
from restoration of wetland enrolled in the Conservation
Reserve Program.
Similar to the Tier 3 Century method, activity data
were primarily based on the historical land-use/management
patterns recorded in the NRI. Each NRI point was classified
by land use, soil type, climate region (using PRISM data,
Daly et al. 1994) and management condition. Classification
of cropland area by tillage practice was based on data
from the Conservation Tillage Information Center (CTIC
1998, Towery 2001) as described above. Activity data on
wetland restoration of Conservation Reserve Program land
were obtained from Euliss and Gleason (2002). Manure N
amendments over the inventory time period were based on
application rates and areas amended with manure N from
Edmonds et al. (2003), in addition to the managed manure
production data discussed in the previous methodology
subsection on the Tier 3 analysis for mineral soils.
Combining information from these data sources, SOC
stocks for mineral soils were estimated 50,000 times for
1982, 1992, and 1997, using a Monte Carlo simulation
approach and the probability distribution functions for
U.S.-specific stock change factors, reference C stocks, and
land-use activity data (Ogle et al. 2002, Ogle et al. 2003).
The annual C flux for 1990 through 1992 was determined
by calculating the average annual change in stocks between
1982 and 1992; annual C flux for 1993 through 2005 was
determined by calculating the average annual change in
stocks between 1992 and 1997.
Additional Mineral C Stock Change
Annual C flux estimates for mineral soils between 1990
and 2005 were adjusted to account for additional C stock
changes associated with gains or losses in soil C after 1997
due to changes in Conservation Reserve Program enrollment.
The change in enrollment acreage relative to 1997 was based
on data from FSA (2006) for 1998 through 2005, and the
differences in mineral soil areas were multiplied by 0.5 metric
tons C per hectare per year to estimate the net effect on soil
C stocks. The stock change rate is based on estimations using
the IPCC method (see Annex 3.13 for further discussion).
Organic Soil Carbon Stock Changes
Annual C emissions from drained organic soils in
Cropland Remaining Cropland were estimated using the Tier
2 method provided in IPCC/UNEP/OECD/IEA (1997) and
IPCC (2003), which utilizes U.S.-specific C loss rates (Ogle
et al. 2003) rather than default IPCC rates. Similar to the Tier
2 analysis for mineral soils, the final estimates included a
measure of uncertainty as determined from the Monte Carlo
simulation with 50,000 iterations. Emissions were based
on the 1992 and 1997 Cropland Remaining Cropland areas
from the 7997National Resources Inventory (USDA-NRCS
1 The polygons displayed in Figure 7-7 through Figure 7-10 are the Major Land Resource Areas.
8 Stock change factors have been derived from published literature to reflect changes in tillage, cropping rotations and intensification, land-use change
between cultivated and uncultivated conditions, and drainage of organic soils.
Land Use, Land-Use Change, and Forestry 7-23
-------
2000). The annual flux estimated for 1992 was applied to
1990 through 1992, and the annual flux estimated for 1997
was applied to 1993 through 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to agricultural soils were estimated
using a Tier 2 methodology. The annual amounts of limestone
and dolomite applied (see Table 7-18) were multiplied by
CO2 emission factors from West and McBride (2005). These
emission factors (0.059 metric ton C/metric ton limestone,
0.064 metric ton C/metric ton dolomite) are lower than the
IPCC default emission factors, because they account for the
portion of agricultural lime that may leach through the soil
and travel by rivers to the ocean (West and McBride 2005).
The annual application rates of limestone and dolomite were
derived from estimates and industry statistics provided in the
Minerals Yearbook and Mineral Industry Surveys (Tepordei
1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,
2003,2004,2005,2006; USGS 2006). To develop these data,
the U.S. Geological Survey (USGS; U.S. Bureau of Mines
prior to 1997) obtained production and use information
by surveying crushed stone manufacturers. Because some
manufacturers were reluctant to provide information, the
estimates of total crushed limestone and dolomite production
and use were divided into three components: (1) production
by end-use, as reported by manufacturers (i.e., "specified"
production); (2) production reported by manufacturers
without end-uses specified (i.e., "unspecified" production);
and (3) estimated additional production by manufacturers
who did not respond to the survey (i.e., "estimated"
production).
The "unspecified" and "estimated" amounts of crushed
limestone and dolomite applied to agricultural soils were
calculated by multiplying the percentage of total "specified"
limestone and dolomite production applied to agricultural
soils by the total amounts of "unspecified" and "estimated"
limestone and dolomite production. In other words, the
proportion of total "unspecified" and "estimated" crushed
limestone and dolomite that was applied to agricultural
soils (as opposed to other uses of the stone) was assumed
to be proportionate to the amount of "specified" crushed
limestone and dolomite that was applied to agricultural
soils. In addition, data were not available for 1990, 1992,
and 2005 on the fractions of total crushed stone production
that were limestone and dolomite, and on the fractions of
limestone and dolomite production that were applied to
soils. To estimate the 1990 and 1992 data, a set of average
fractions were calculated using the 1991 and 1993 data.
These average fractions were applied to the quantity of "total
crushed stone produced or used" reported for 1990 and 1992
in the 1994 Minerals Yearbook (Tepordei 1996). To estimate
2005 data, the previous year's fractions were applied to a
2005 estimate of total crushed stone presented in the USGS
Mineral Industry Surveys: Crushed Stone and Sand and
Gravel in the First Quarter of 2006 (USGS 2006).
The primary source for limestone and dolomite activity
data is the Minerals Yearbook, published by the Bureau
of Mines through 1994 and by the USGS from 1995 to
the present. In 1994, the "Crushed Stone" chapter in the
Minerals Yearbook began rounding (to the nearest thousand)
quantities for total crushed stone produced or used. It then
reported revised (rounded) quantities for each of the years
from 1990 to 1993. In order to minimize the inconsistencies
in the activity data, these revised production numbers have
been used in all of the subsequent calculations.
Uncertainty
Uncertainty associated with the Cropland Remaining
Cropland land-use category was addressed for changes in
agricultural soil C stocks (including both mineral and organic
soils) and soil liming emissions. Uncertainty estimates are
presented in Table 7-19 for each subsource (i.e., mineral soil
C stocks, organic soil C stocks, soil liming) disaggregated to
the level of the inventory methodology employed (i.e., Tier 2
and Tier 3). A combined uncertainty estimate for changes in
soil C stocks occurring within Cropland Remaining Cropland
is also included. Uncertainty estimates from each component
Table 7-18: Applied Minerals (Million Metric Tons)
Mineral
Limestone
Dolomite
1990
19.
2.
01
36
1995
17.30
2.77
2000
15
3
.86
.81
2001
16.10
3.95
2002
20.
2.
.45
.35
2003
18.71
2.25
2004
15.50
2.33
2005
16.10
2.42
Note: These numbers represent amounts applied to all agricultural land, not just Cropland Remaining Cropland.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 2005
-------
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining Cropland
(Tg C02 Eq. and Percent)
2005 Stock uncertainty
Change Estimate unce»a|nly
Source
Mineral Soil C Stocks: Cropland Remaining Cropland,
Tier 3 Inventory Methodology
Mineral Soil C Stocks: Cropland Remaining Cropland,
Tier 2 Inventory Methodology
Mineral Soil C Stocks: Cropland Remaining Cropland
(Change in CRP enrollment relative to 1997)
Organic Soil C Stocks: Cropland Remaining Cropland,
Tier 2 Inventory Methodology
C02 Emissions from Liming
Combined Uncertainty for Agricultural Soil C
Stocks in Cropland Remaining Cropland
(Tg C02 Eq.)
(66.4)
(3.0)
(1.6)
27.7
4.0
(39.4)
(TgCO
Lower Bound
(77.0)
(6.9)
(2.5)
15.8
0.2
(56.2)
Range Relative to Stock Change Estimate
2Eq.)
Upper Bound
(55.9)
0.8
(0.8)
36.9
8.0
(24.3)
('
Lower Bound
-16%
-127%
-50%
-43%
-96%
-43%
M
Upper Bound
+ 16%
+128%
+50%
+33%
+98%
+38%
were combined using the error propagation equation in
accordance with IPCC (2006). The combined uncertainty was
calculated by taking the square root of the sum of the squares
of the standard deviations of the uncertain quantities. More
details on how the individual uncertainties were developed
appear later in this section. The combined uncertainty for soil
C stocks in Cropland Remaining Cropland ranged from 43
percent below and 38 percent above the 2005 stock change
estimate of -39.4 Tg CO2 Eq.
QA/QC and Verification
Quality control measures included checking input data.
model scripts, and results to ensure data were properly
handled through the inventory process. Errors were found
in these steps and corrective actions were taken. One of the
errors involved a subset of the transitions from full tillage
to reduced till between the late 1980s and early 1990s.
The reduced tillage transition was not occurring and the
script was revised to correct the transition. The second
error involved improved estimation of root production in
irrigated systems. Root production had been parameterized
based on rainfed crops, and so the parameters were adjusted
to better approximate C allocation to belowground growth
in irrigated lands. In addition, QA/QC activities uncovered
that the empirically-based structural uncertainty estimator
for the Century model did not address the random variation
associated with predicting soil C stock changes at the
site level in the previous Inventory, which is equivalent
to NRI points. This uncertainty is not insignificant, and,
thus, previous uncertainty estimates were unrealistically
low because the random variation was not addressed.
Adjustments were made in the current Inventory, and the
results better reflect the uncertainty in the Tier 3 approach
as implemented in the United States.
As discussed in the uncertainty sections, results were
compared to field measurements, and a statistical relationship
was developed to assess uncertainties in the model's
predictive capability. The comparisons included over 40
long-term experiments, representing about 800 combinations
of management treatments across all of the sites (Ogle et al.
2007). Inventory reporting forms and text were reviewed and
revised as needed to correct transcription errors.
Recalculations Discussion
Several adjustments were made in the current Inventory
to improve the results. First, consistency was achieved in the
N inputs data between the agricultural soil C and soil N2O
source categories (see Agricultural Soil Management section
of the Agriculture chapter). Although this improvement
required several changes to soil NUO inventory methods,
the only change to the soil C source was the scaling of
manure amendment data in 1997 based on variation in
managed manure N production during other years of the
Inventory. Second, scheduling files, (used in the model
program to determine when activities such as fertilization,
tillage, planting, and harvesting occur) were adjusted in
the Tier 3 approach, so that transitions from full tillage to
reduced till were properly modeled, and allocation of C to
roots was reduced for irrigated systems due to excessively
high root biomass discovered through QA/QC checks.
Land Use, Land-Use Change, and Forestry 7-2?
-------
Third, uncertainty was estimated in the current Inventory
for the random variation associated with Century model
estimates at the site scale. This is a significant uncertainty
in the assessment framework, which was not addressed in
the previous Inventory. Fourth, annual C emissions from
organic cropland soils are subdivided between Cropland
Remaining Cropland and Land Converted to Cropland.
In the previous Inventory, all C emissions associated with
drainage of organic soils for crop production were reported
in the Cropland Remaining Cropland category.
The quantity of applied minerals reported in the previous
Inventory for 2004 has been revised. Consequently, the
reported emissions resulting from liming in 2004 have also
changed. In the previous Inventory, to estimate 2004 data,
the previous year's fractions were applied to a 2004 estimate
of total crushed stone presented in the USGS Mineral
Industry Surveys: Crushed Stone and Sand and Gravel in
the First Quarter of 2005 (USGS 2005). Since publication
of the previous Inventory, the Minerals Yearbook has
published actual quantities of crushed stone sold or used by
producers in the United States in 2004. These values have
replaced those used in the previous Inventory to calculate
the quantity of minerals applied to soil and the emissions
from liming. Additionally, a correction was made to liming
activity data from 2003 that was inaccurately transcribed
from the original source.
Overall, the recalculations resulted in an average annual
increase in sinks of 5.3 Tg CO2 Eq. (21 percent) for soil C
stock changes in Cropland Remaining Cropland for the
period 1990 through 2004.
Planned Improvements
Several improvements are planned for the agricultural
soil C inventory. The first improvement is to incorporate
new land-use and management activity data from the NRI.
In the current Inventory, NRI data only provide land-use
and management statistics through 1997, but it is anticipated
that new statistics will be released in the coming year for
2000 through 2003. The new data will greatly improve the
accuracy of land-use and management influences on soil C
in the latter part of the time series.
The second improvement is to develop a consistent
representation of the U.S. managed land base. More details
on this planned improvement are provided in the Forest Land
Remaining Forest Land section.
The third improvement is to incorporate additional crops
into the Tier 3 approach. Currently, crops such as vegetables,
rice, and perennial and horticultural crops have not been fully
implemented in the Century model application. However,
efforts are currently underway to further develop the model
application for simulating soil C dynamics in land managed
for production of these crops.
The fourth improvement is to incorporate remote sensing
in the analysis for estimation of crop and forage production.
Specifically, the Enhanced Vegetation Index (EV1) product
that is derived from MODIS satellite imagery is being used
to refine the production estimation for the Tier 3 assessment
framework. EVI reflects changes in plant "greenness" over
the growing season and can be used to compute production
based on the light use efficiency of the crop or forage
(Potter et al. 1993). In the current framework, production is
simulated based on the weather data, soil characteristics, and
the ge netic potential of the crop. While this method produces
reasonable results, remote sensing can be used to refine the
productivity estimates and reduce biases in crop production
and subsequent C input to soil systems. It is anticipated
that precision in the Tier 3 assessment framework will be
increased by 25 percent or more with the new method.
The fifth improvement is to develop an automated
quality control system to evaluate the results from Century
model simulations. Currently, there are over 14 million
simulations, and it is not possible to manually review each
single simulation. Results are aggregated and evaluated at
larger scales such as Major Land Resource Areas and States.
QA/QC at these larger scales may not uncover errors at the
scale of individual NRI points, which is the scale at which
the Century model is used to simulate soil C dynamics.
An automated system would greatly improve QA/QC,
performing checks on the results from each simulation and
identifying errors for further refinements.
The last improvement is to further develop the
uncertainty analysis for the Tier 3 method by addressing the
uncertainty inherent in the Century model results for other
agricultural land (i.e., GrasslandRemaining Grassland,Land
Converted to Grassland, and Land Converted to Cropland).
In addition, uncertainties need to be addressed in the
simulation of soil C stocks for the pre-NRI time period (i.e.,
before 1979). In the current analysis, inventory development
focused on uncertainties in the last two decades because the
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
management activity during the most recent time periods
will likely have the largest impact on current trends in soil
C storage. However, legacy effects of past management can
also have a significant effect on current C stock trends, as well
as trajectories of those C stocks in the near future. Therefore,
a planned improvement is to revise the Inventory to address
uncertainties in management activity prior to 1979.
7.4. Land Converted to Cropland
(IPCC Source Category 5B2)
Land Converted to Cropland includes all areas
designated as cropland that had been another land use in a
prior time period according to the USDA NRI land use survey
(USDA-NRCS 2000). Consequently, the area considered
in Land Converted to Cropland changes through time with
land-use change. Lands are retained in this category for
20 years as recommended by the IPCC guidelines (IPCC
2006) unless there is another land-use change. Background
on agricultural C stock changes is provided in Cropland
Remaining Cropland and will only be summarized here for
Land Converted to Cropland. Soils are the largest pool of C
in agricultural land, and also have the greatest potential for
storage or release of C, because biomass and dead organic
matter C pools are relatively small and ephemeral compared
with soils. The IPCC/UNEP/OECD/IEA (1997) and the IPCC
(2003) recommend reporting changes in soil organic C stocks
due to: (1) agricultural land-use and management activities
on mineral soils, (2) agricultural land-use and management
activities on organic soils, and (3) CO2 emissions that result
from liming of soils with dolomite and limestone. Mineral
soil C stock changes and C emissions from drained and
cultivated organic soils are reported for Land Converted to
Cropland. It was not possible, however, to subdivide the
liming application estimates by land use/land-use change
categories (see Methodology section below for additional
discussion).
Land-use and management of mineral soils in Land
Converted to Cropland led to losses of soil C during the
early 1990s but losses declined slightly through the latter
part of the time series (Table 7-20 and Table 7-21). The rate
of change in soil C stocks was 7.2 Tg CO2 Eq. (2.0 Tg C) in
2005. Emissions from mineral soils were estimated at 4.6 Tg
CO2 Eq. (1.2 Tg C) in 2005, while drainage and cultivation
of organic soils led to annual losses of 2.6 Tg CO2 Eq. (0.7
TgC)in2005.
The spatial variability in annual CO2 flux associated
with C stock changes in mineral and organic soils for Land
Converted to Cropland is displayed in Figure 7-6 and Figure
7-7. While a large portion of the United States had net
losses in soil C for Land Converted to Cropland, there were
some notable areas with sequestration in the Intermountain
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils
Liming of Soils3
Total Net Flux
1990
6.2
2.4
8.7
1995
4.6
2.6
7.2
2000
4.6
2.6
7.2
2001
4.6
2.6
7.2
2002
4.6
2.6
7.2
2003
4.6
2.6
7.2
2004
4.6
2.6
7.2
2005
4.6
2.6
7.2
a Emissions from liming in Land Converted to Cropland are reported in Cropland Remaining Cropland.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. Totals
may not sum due to independent rounding.
Table 7-21: Net Soil C Stock Changes in Land Converted to Cropland (Tg C)
Soil Type
1990
1995
2000 2001 2002 2003 2004 2005
Mineral Soils
Organic Soils
Liming of Soils3
1.7
0.7
1.2
0.7
1.2
0.7
1.2
0.7
1.2
0.7
1.2
0.7
1.2
0.7
1.2
0.7
Total Net Flux
2.4
2.0
2.0
2.0
2.0
2.0
2.0
2.0
a Emissions from liming in Land Converted to Cropland are reported in Cropland Remaining Cropland.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. Totals
may not sum due to independent rounding.
Land Use, Land-Use Change, and Forestry 7-27
-------
Figure 7-6
Net Soil C Stock Change for Mineral Soils in Land Converted to Cropland, 2005
Tg C02 Eq/yr
D 0 to 0.5
n -0.1 toO
ll-0.3to-0.1
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
Figure 7-7
Net Soil C Stock Change for! Organic Soils in Land Converted to Cropland, 2005
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
II 0.1 to 0.2
DO to 0.1
Q| No organic soils
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1999-2CI05
-------
West and central United States. These areas were gaining
C following conversion, because croplands were irrigated
or receiving higher fertilizer inputs relative to the previous
land use. Emissions from organic soils were largest in
California, Florida and the upper Midwest, which coincided
with largest concentrations of cultivated organic soils in the
United States.
Methodology
The following section includes a brief description of the
methodology used to estimate changes in soil C stocks due to
agricultural land-use and management activities on mineral
and organic soils for Land Converted to Cropland.
Soil C stock changes were estimated for Land Converted
to Cropland according to land-use histories recorded in
the USDA NRI survey (USDA-NRCS 2000).9 Land use
and some management information (e.g., crop type, soil
attributes, and irrigation) were collected for each NRI point
on a 5-year cycle beginning in 1982, and were subdivided
into four inventory time periods, 1980-84, 1985-1989,
1990-94 and 1995-2000. NRI points were classified as Land
Converted to Cropland for an inventory time period (e.g.,
1990-1994 and 1995-2000) if the land use was cropland
at the end of the respective inventory time period but had
been another use in a prior inventory time period. Cropland
includes all land used to produce food or fiber, as well as
forage that is harvested and used as feed (e.g., hay and
silage). Further elaboration on the methodologies and data
used to estimate stock changes for mineral and organic soils
are provided in the Cropland Remaining Cropland section
and Annex 3.13.
Mineral Soil Carbon Stock Changes
A Tier 3 model-based approach was used to estimate C
stock changes for soils on Land Converted to Cropland used
to produce a majority of all crops. Exceptions, which relied on
an IPCC Tier 2 method to estimate C stock changes, included:
land used to produce vegetable, tobacco, perennial/horticultural
crops, and rice; land on very gravelly, cobbly or shaley soils
(greater than 35 percent by volume); and land converted from
forest or federal ownership (Ogle et al. 2003).I0
1'iK- J A
Mineral SOC stocks and stock changes were estimated
using the Century biogeochemical model for the Tier 3
methods. National estimates were obtained by using the
model to simulate historical land-use change patterns as
recorded in the USDA National Resources Inventory (USDA-
NRCS 2000). The methods used for Land Converted to
Cropland are the same as those described in the Tier 3 portion
of Cropland Remaining Cropland Section for mineral soils
(see Cropland Remaining Cropland Tier 3 methods section
for additional information).
For the mineral soils not included in the Tier 3 analysis,
SOC stock changes were estimated using a Tier 2 Approach
for Land Converted to Cropland as described in the Tier 2
portion of Cropland Remaining Cropland Section for mineral
soils (see Cropland Remaining Cropland Tier 2 methods
section for additional information).
Organic Son tarnon Slock Changes
Annual C emissions from drained organic soils in
Land Converted to Cropland were estimated using the
Tier 2 method provided in IPCC/UNEP/OECD/IEA(1997)
and IPCC (2003), which utilizes U.S. -specific C loss
rates (Ogle et al. 2003) rather than default IPCC rates.
The final estimates included a measure of uncertainty as
determined from the Monte Carlo simulation with 50,000
iterations. Emissions were based on the 1992 and 1997
Land Converted to Cropland areas from the 7997 National
Resources Inventory (USDA-NRCS 2000). The annual flux
estimated for 1992 was applied to 1990 through 1992, and
the annual flux estimated for 1997 was applied to 1993
through 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Land Converted to Cropland are
reported in Cropland Remaining Cropland, because it was
not possible to disaggregate liming application among land
use and land-use change categories.
'' NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
10 Federal land is not a land use, but rather an ownership designation that is treated as forest or nominal grassland for purposes of these calculations.
The specific use for federal lands is not identified in the NRI survey (USDA-NRCS 2000).
Land Use, Land-Use Change, and Forestry 7-29
-------
Uncertainty
Uncertainty associated with the Land Converted to
Cropland land-use change category includes the uncertainty
associated with changes in mineral and organic soil C
stocks. Uncertainty estimates are presented in Table 7-22
for each subsource (i.e., mineral soil C stocks and organic
soil C stocks) disaggregated to the level of the Inventory
methodology employed (i.e., Tier 2 and Tier 3). A combined
uncertainty estimate for changes in agricultural soil C
stocks occurring within Land Converted to Cropland is also
included. Uncertainty estimates from each component were
combined using the error propagation equation in accordance
with IPCC (2006). The combined uncertainty was calculated
by taking the square root of the sum of the squares of the
standard deviations of the uncertain quantities. More details
on how the individual uncertainties were developed appear
later in this section. The combined uncertainty for soil C
stocks in Land Converted to Cropland was estimated to be
33 percent below and 29 percent above the inventory estimate
of7.2TgCO2Eq.
Uncertainties in Mineral Soil Carbon Stock Changes
The uncertainty analysis for Land Converted to Cropland
using the Tier 3 and 2 approaches were based on the same
method described for Cropland Remaining Cropland, except
that the uncertainty inherent in the structure of the Century
model was not addressed.
Uncertainties in Organic Soil Carbon Stock Changes
Annual C emission estimates from drained organic soils
in Land Converted to Cropland were estimated using the
Tier 2 Approach, as described in the Cropland Remaining
Cropland section.
QA/QC and Verification
See QA/QC and Verification Section under Cropland
Remaining Cropland.
Recalculations Discussion
The specific changes in reporting in the current
Inventory for Land Converted to Cropland are the same
as those described in the Cropland Remaining Cropland
section, except that the uncertainty is not addressed for the
random variation associated with Century model estimates
at the site scale. The structural uncertainty requires further
development before it can be used to address uncertainty
inherent in the structure of the Century model for Land
Converted to Cropland. A further change affecting this
section is that organic soil emissions for the Cropland
Remaining Cropland and Land Converted to Cropland
sections were previously reported together in the Cropland
Remaining Cropland section. For the current Inventory, they
have been reapportioned between the land use categories
and, therefore, a portion of the emissions are now reported
in the Land Converted to Cropland section. Overall, these
recalculations resulted in an average annual increase in
emissions of 9.1 Tg CO2 Eq. (71.4 percent) for soil C stock
changes in Land Converted to Cropland over the time series
from 1990 through 2004. The changes also resulted in a shift
from the previous Inventory's reporting of this category as an
overall sink to the current reporting as an overall source.
Table 7-22: Quantitative Uncertainty Estimates for C Stock Changes occurring within Land Converted to Cropland
(Tg C02 Eq. and Percent)
Change Estimate Uncertainty Range Relative to Stock Change Estimate
Source
Mineral Soil C Stocks: Land Converted to Cropland,
Tier 3 Inventory Methodology
Mineral Soil C Stocks: Land Converted to Cropland,
Tier 2 Inventory Methodology
Organic Soil C Stocks: Land Converted to Cropland,
Tier 2 Inventory Methodology
Combined Uncertainty for Agricultural Soil Carbon
Stocks in Land Converted to Cropland
(TgC02Eq.)
0.4
4.1
2.6
7.2
(TgC02Eq.)
Lower Bound Upper Bound
(0.1) 0.9
2.3 5.8
1.2 3.7
4.9 9.3
tf
Lower Bound
-124%
-44%
-53%
-33%
6)
Upper Bound
+ 124%
+41%
+41%
+29%
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Planned Improvements
The empirically-based uncertainty estimator described
in the Cropland Remaining Cropland section for the Tier 3
approach has not been developed to estimate uncertainties
related to the structure of Century model for Land Converted
to Cropland, but this is a planned improvement. See Planned
Improvements section under Cropland Remaining Cropland
for additional planned improvements.
7.5. Grassland Remaining
Grassland (IPCC Source Category
5C1)
Grassland Remaining Grassland includes all areas of
grassland that had been designated as grassland since 1982
according to the USDANRI land use survey (USDA-NRCS
2000). Consequently, the area considered in Grassland
Remaining Grassland changes through time with land-use
change. Background on agricultural C stock changes is
provided in the Cropland Remaining Cropland section and
will only be summarized here for Grassland Remaining
Grassland. Soils are the largest pool of C in agricultural land,
and also have the greatest potential for storage or release of
C, because biomass and dead organic matter C pools are
relatively small and ephemeral compared to soils. IPCC/
UNEP/OECD/IEA (1997) and IPCC (2003) recommend
reporting changes in soil organic C stocks due to: (1)
agricultural land-use and management activities on mineral
soils, (2) agricultural land-use and management activities on
organic soils, and (3) CO2 emissions that result from liming
of soils with dolomite and limestone. Mineral and organic soil
C stock changes are reported here for Grassland Remaining
Grassland, but stock changes associated with liming are
reported in Cropland Remaining Cropland, because it was
not possible to subdivide those estimates by land use/land-
use change categories (see Methodology section below for
additional discussion).
Land-use and management of mineral soils in Grassland
Remaining Grassland increased soil C during the early
1990s, but this trend was reversed over the decade, with small
losses of C prevailing during the latter part of the time series
(see Table 7-23 and Table 7-24). Organic soils lost about the
same amount of C in each year of the Inventory. The overall
trend shifted from small decreases in soil C during 1990 to
larger decreases during the latter years, estimated at 16.1 Tg
CO2Eq. (4.4TgC)in2005.
The spatial variability in annual CO2 flux associated with
C stock changes in mineral and organic soils is displayed in
Figure 7-8 and Figure 7-9. Grassland is losing soil organic
C in the United States largely due to droughts that are
causing small losses of C on a per hectare basis, but are
occurring over a large land base. In areas with net gains in
Table 7-23: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C02 Eq.)
Soil Type
1990
1995
2000 2001 2002 2003 2004 2005
Mineral Soils
Organic Soils
Liming of Soils3
(3.7)
3.9
12.7
3.7
12.6
3.7
12.6
3.7
12.5
3.7
12.5
3.7
12.5
3.7
12.4
3.7
Total Net Flux
0.1
16.4
16.3 16.2 16.2 16.2 16.1 16.1
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are
based on historical data only. Totals may not sum due to independent rounding.
a Emissions from liming in Grassland Remaining Grassland are reported in Cropland Remaining Cropland.
Table 7-24: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C)
Soil Type
Mineral Soils
Organic Soils
Liming of Soils3
Total Net Flux
1990
(1.0)
1.1
0
1995
3.5
1.0
4.5
2000
3.4
1.0
4.4
2001
3.4
1.0
4.4
2002
3.4
1.0
4.4
2003
3.4
1.0
4.4
2004
3.4
1.0
4.4
2005
3.4
1.0
4.4
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are
based on historical data only. Totals may not sum due to independent rounding.
a Emissions from liming in Grassland Remaining Grassland are reported in Crop/and Remaining Cropland.
Land Use, Land-Use Change, and Forestry 7-31
-------
Figure 7-8
Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 2005
Tg C02 Eq/yr
D o to 1
n-0.1 too
n-0.5 to-0.1
BH-1 to-0-5
II -1.02 to -1
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
Figure 7-9
Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 2005
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
II 0.5 to 0.6
D 0.1 to 0.5
DO to 0.1
Q] No organic soils
7 32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
soil organic C, sequestration was driven by irrigation and
seeding legumes. Similar to Cropland Remaining Cropland,
emission rates from drained organic soils were highest along
the southeastern coastal region, in the northeast central
United States surrounding the Great Lakes, and along the
central and northern portions of the West Coast.
Methodology
The following section includes a brief description of the
methodology used to estimate changes in soil C stocks due to
agricultural land-use and management activities on mineral
and organic soils for Grassland Remaining Grassland.
Soil C stock changes were estimated for Grassland
Remaining Grassland according to land-use histories
recorded in the USDANRI survey (USDA-NRCS 2000)."
Land use and some management information (e.g., irrigation,
legume pastures) were collected for each NRI point on a 5-
year cycle beginning in 1982,1980-84,1985-1989,1990-94
and 1995-2000. NRI points were classified as Grassland
Remaining Grassland for an inventory time period (e.g.,
1990-1994 and 1995-2000) if the land use had been grassland
since the first year of the NRI survey in 1982 through the
end of the respective time period. Grassland includes pasture
and rangeland used for grass forage production, where the
primary use is livestock grazing. Rangelands are typically
extensive areas of native grassland that are not intensively
managed, while pastures are often seeded grassland, possibly
following tree removal, that may or may not be improved
with practices such as irrigation and interseeding legumes.
Further elaboration on the methodologies and data used to
estimate stock changes from mineral and organic soils are
provided in the Cropland Remaining Cropland section and
Annex 3.13.
Mineral Soil Carbon Stock Changes
A Tier 3 model-based approach was used to estimate
C stock changes for mineral soils in Grassland Remaining
Grassland, except for lands with very gravelly, cobbly or
shaley soils (greater than 35 percent by volume). An IPCC
Tier 2 method was used to estimate stock changes for the
gravelly, cobbly or shaley soils and additional changes in
C stocks in mineral soils. A Tier 2 method was also used to
estimate additional stock changes associated with sewage
sludge amendments.
Mineral soil organic C stocks and stock changes for
Grassland Remaining Grassland were estimated using the
Century biogeochemical model, as described in Cropland
Remaining Cropland. Historical land-use and management
patterns were used in the Century simulations as recorded
in the USDA National Resources Inventory (NRI) survey,
with supplemental information on fertilizer use and rates
from the USDA Economic Research Service Cropping
Practices Survey (ERS 1997) and National Agricultural
Statistics Service (NASS 1992, 1999, 2004). Frequency
and rates of manure application to grassland during 1997
were estimated from data compiled by the USDA Natural
Resources Conservation Service (Edmonds et al. 2003), and
then adjusted using county-level manure production rates
for other years in the Inventory. Specifically, county-scale
ratios of manure production in other years relative to 1997
were used to adjust the area amended with manure for other
years in the Inventory (see Annex 3.13 for further details).
Higher managed manure N production relative to 1997 was,
thus, assumed to increase the amount of area amended with
manure, while less managed manure N production relative to
1997 was assumed to reduce the amended area. The amount
of managed manure produced by each livestock type was
calculated by determining the population of animals that
were on feedlots or otherwise housed (requiring manure to be
collected and managed). Annual animal population data for
all livestock types, except horses and goats, were obtained for
all years from the U.S. Department of Agriculture-National
Agricultural Statistics Service (USDA 1994a-b, 1995a-b,
1998a-b, 1999a-c, 2000,2004a-e, 2005a-d, 2006a-e). Horse
population data were obtained from the FAOSTAT database
(FAO 2006). Goat population data for 1992, 1997, and
2002 were obtained from the Census of Agriculture (USDA
2005g); these data were interpolated and extrapolated to
derive estimates for the other years. Information regarding
poultry turnover (i.e., slaughter) rate was obtained from state
Natural Resource Conservation Service personnel (Lange
2000). Additional population data for different farm size
categories for dairy and swine were obtained from the 1992
and 1997 Census of Agriculture (USDA 2005g). Pasture/
Range/Paddock (PRP) manure N deposition was estimated
internally in the Century model, as part of the grassland
system simulations (i.e., PRP manure deposition was not
NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-33
-------
an external input into the model). See the Tier 3 methods
in Cropland Remaining Cropland section for additional
discussion on the Tier 3 methodology for mineral soils.
Tier 2 Approach
The Tier 2 approach is based on the same methods
described in the Tier 2 portion of Cropland Remaining
Cropland Section for mineral soils (see Cropland
Remaining Cropland Tier 2 methods section for additional
information).
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between
1990 and 2005 were adjusted to account for additional C
stock changes associated with sewage sludge amendments
using a Tier 2 method. Estimates of the amounts of sewage
sludge N applied to agricultural land were derived from
national data on sewage sludge generation, disposition,
and nitrogen content. Total sewage sludge generation
data for 1988, 1996, and 1998, and a projection for 2000,
in dry mass units, were obtained from EPA reports (EPA
1993, 1999), and linearly interpolated to estimate values
for the intervening years. N application rates from Kellogg
et al. (2000) were used to determine the amount of area
receiving sludge amendments. Although sewage sludge
can be added to land managed for other land uses, it was
assumed that agricultural amendments occur in grassland.
Cropland is assumed to rarely be amended with sewage
sludge due to the high metal content and other pollutants
in human waste. The soil C storage rate was estimated at
0.38 metric tons C per hectare per year for sewage sludge
amendments to grassland. The stock change rate is based
on country-specific factors and the IPCC default method
(see Annex 3.13 for further discussion).
Organic Soil Carbon Stock Changes
Annual C emissions from drained organic soils in
Grassland Remaining Grassland were estimated using the
Tier 2 method provided in IPCC/UNEP/OECD/IEA (1997)
and IPCC (2003), which utilizes U.S.-specific C loss rates
(Ogle et al. 2003) rather than default IPCC rates. The final
estimates included a measure of uncertainty as determined
from the Monte Carlo simulation with 50,000 iterations.
Emissions were based on the 1992 and 1997 Grassland
Remaining Grassland areas from the 7997 National
Resources Inventory (USDA-NRCS 2000). The annual
flux estimated for 1992 was applied to 1990 through 1992,
and the annual flux estimated for 1997 was applied to 1993
through 2005.
C02 Emission.; from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Grassland Remaining Grassland are
reported in Cropland Remaining Cropland, because it was
not possible to disaggregate liming application among land
use/land-use change categories.
Uncertainty
Uncertainty associated with the Grassland Remaining
Grassland category includes the uncertainty associated with
changes in mineral and organic soil C stocks. Uncertainty
Table 7-25: Quantitative Uncertainty Estimates for C Stock Changes occurring within Grassland Remaining
Grassland (Tg C02 Eq. and Percent)
Source
Mineral Soil C Stocks: Grassland Remaining Grassland,
Tier 3 Inventory Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
Mineral Soil C Stocks: Grassland Remaining Grassland
(Change in Soil C due to Sewage Sludge Amendments)
Organic Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
Combined Uncertainty for Agricultural Soil Carbon
Stocks in Grassland Remaining Grassland
2005 Stock
Change
Estimate
(TgC02Eq.)
13.9
(0.2)
(1.3)
3.7
16.1
Uncertainty Range Relative to Stock Change Estimate
(TgCO
Lower Bound
12.4
(0.3)
(1.9)
1.2
13.2
2Eq.)
Upper Bound
15.3
0.04
(0.6)
5.5
18.5
(%)
Lower Bound Upper Bound
-10% +10%
-89% +127%
-50% +50%
-66% +49%
-18% +15%
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
estimates are presented in Table 7-25 for each subsource
(i.e., mineral soil C stocks and organic soil C stocks)
disaggregated to the level of the inventory methodology
employed (i.e., Tier 2 and Tier 3). A combined uncertainty
estimate for changes in agricultural soil C stocks occurring
within Grassland Remaining Grassland is also included.
Uncertainty estimates from each component were combined
using the error propagation equation in accordance with
IPCC (2006). The combined uncertainty was calculated
by taking the square root of the sum of the squares of the
standard deviations of the uncertain quantities. More details
on how the individual uncertainties were developed appear
later in this section. The combined uncertainty for soil C
stocks in Grassland Remaining Grassland was estimated
to be 18 percent below and 15 percent above the inventory
estimate of 16.1 Tg CO2 Eq.
Uncertainties in Mineral Soil Carbon Stock Changes
Tier 3 Approach
The uncertainty analysis for Grassland Remaining
Grassland using the Tier 3 approach and Tier 2 approach
were based on the same method described for Cropland
Remaining Cropland, except that the uncertainty inherent in
the structure of the Century model was not addressed. See
the Tier 3 approach for mineral soils under the Cropland
Remaining Cropland section for additional discussion.
Additional Mineral Carbon Stock Change Calculations
A ±50 percent uncertainty was assumed for additional
adjustments to the soil C stocks between 1990 and 2005
to account for additional C stock changes associated with
amending grassland soils with sewage sludge.
Uncertainties in Organic Soil Carbon Stock Changes
Uncertainty in C emissions from organic soils was
estimated using country-specific factors and a Monte Carlo
analysis. PDFs for emission factors were derived from a
synthesis of 10 studies, and combined with uncertainties
in the NRI land use and management data for organic
soils in the Monte Carlo analysis. See the Tier 2 section
under minerals soils of Cropland Remaining Cropland for
additional discussion.
QA/QC and Verification
Quality control measures included checking input data,
model scripts, and results to ensure data were properly
handled through the inventory process. An error was
found in these steps and a corrective action was taken.
Specifically, the error involved improved estimation of root
production in irrigated systems. Root production had been
parameterized based on rainfed forages; the parameters
were adjusted to approximate C allocation to belowground
growth in irrigated lands.
Recalculations Discussion
The specific changes in reporting in the current
Inventory for Grassland Remaining Grassland are the same
as those described in the Cropland Remaining Cropland
section, except that the uncertainty is not addressed in the
current Inventory for the random variation associated with
Century model estimates at the site scale. The structural
uncertainty requires further development before it can be
used to address uncertainty inherent in the structure of the
Century model for Grassland Remaining Grassland. Overall,
the recalculations resulted in an average annual increase in
emissions of 7.4 Tg CO2 Eq. (46.2 percent) for soil C stock
changes in Grassland Remaining Grassland over the period
from 1990 through 2004.
Planned Improvements
The empirically-based uncertainty estimator described
in the Cropland Remaining Cropland section for the Tier 3
approach has not been developed to estimate uncertainties in
Century model results for Grassland Remaining Grassland,
but this is a planned improvement for the Inventory. See
Planned Improvements section under Cropland Remaining
Cropland for additional planned improvements.
7.6. Land Converted to Grassland
(IPCC Source Category 5C2)
Land Converted to Grassland includes all areas
designated as grassland that had been in another land use
in a prior time period according to the USDA NRI land use
Land Use, Land-Use Change, and Forestry 7-35
-------
survey (USDA-NRCS 2000). Consequently, the area of
Land Converted to Grassland changes through time with
land-use change. Lands are retained in this category for
20 years as recommended by the IPCC guidelines (IPCC
2006) unless there is another land use change. Background
on agricultural C stock changes is provided in Cropland
Remaining Cropland and will only be summarized here for
Land Converted to Grassland. Soils are the largest pool of C
in agricultural land, and also have the greatest potential for
storage or release of C because biomass and dead organic
matter C pools are relatively small and ephemeral compared
with soils. IPCC/UNEP/OECD/IEA (1997) recommends
reporting changes in soil organic C stocks due to: (1)
agricultural land-use and management activities on mineral
soils, (2) agricultural land-use and management activities on
organic soils, and (3) CO2 emissions that result from liming
of soils with dolomite and limestone. Mineral soil C stock
changes and C emissions from organic soils are reported here
for Land Converted to Grassland, but emissions from liming
are reported in Cropland Remaining Cropland, because it
was not possible to subdivide those estimates by land use
and land-use change categories (see the Methodology section
below for additional discussion).
Land-use and management of mineral soils in Land
Converted to Grassland led to an increase in soil C stocks
over the entire time series, which was largely caused by
annual cropland converted into pasture (see Table 7-26 and
Table 7-27). Stock change rates over the time series varied
from 14.6 to 16.3 Tg CO2 Eq./yr (4.0 to 4.5 Tg C). Drainage
of organic soils for grazing management led to annual losses
of0.9TgCO2Eq.in2005.
The spatial variability in annual CO2 flux associated with
C stock changes in mineral soils is displayed in Figure 7-10
and Figure 7-11. Soil C stock increased in most MLRAs for
Land Converted to Grassland. The largest gains were in the
southeast and northwest, and the amount of sequestration
increased through the 1990s. The patterns were driven by
conversion of annual cropland into continuous pasture.
Emissions from organic soils were largest in California,
Florida and the upper Midwest, which coincides with largest
concentrations of organic soils in the United States that are
used for agricultural production.
fViethodoiociv
The following section includes a brief description of
the methodology used to estimate changes in soil C stocks
due to agricultural land-use and management activities on
mineral soils for Land Converted to Grassland.
Soil C stock changes were estimated for Land Converted
to Grassland according to land-use histories recorded in
Table 7-26: Net Soil C Stock Changes for Land Converted to Grassland (Tg C02 Eq.)
Soil Type
Mineral Soils3
Organic Soils
Liming of Soils'1
Total Net Flux
1990
(15.0)
0.5
(14.6)
1995
(17.2)
0.9
(16.3)
2000
(17.2)
0.9
(16.3)
2001
(17.2)
0.9
(16.3)
2002
(17.2)
0.9
(16.3)
2003
(17.2)
0.9
(16.3)
2004
(17.2)
0.9
(16.3)
2005
(17.2)
0.9
(16-3)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are
based on historical data only. Totals may not sum due to independent rounding.
3 Stock changes due to application of sewage sludge is reported in Grassland Remaining Grassland.
b Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg C)
Soil Type
Mineral Soils3
Organic Soils
Liming of Soilsb
Total Net Flux
1990
(4.1)
0.1
(4.0)
1995
(4.7)
0.2
(4.5)
2000
(4.7)
0.2
(4.5)
2001
(4.7)
0.2
(4.5)
2002
(4.7)
0.2
(4.5)
2003
(4.7)
0.2
(4.5)
2004
(4.7)
0.2
(4.5)
2005
(4.7)
0.2
(4.5)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. /
based on historical data only. Totals may not sum due to independent rounding.
a Stock changes due to application of sewage sludge is reported in Grassland Remaining Grassland.
b Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
I other values are
7-36 Inventory of U.S. greenhouse Gas Emissions and Sink;*: 1990-2005
-------
Figure 7-10
Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 2005
Tg C02 Eq/yr
n 0 to 0.001
D-0.1 toO
n -0.5 to -0.1
• -0.8 to -0.5
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
Figure 7-11
Net Soil C Stock Change for Organic Soils in Land Converted to Grassland, 2005
Tg C02 Eq/yr
H 0.1 to 0.25
DO to 0.1
Q] No organic soils
Note: Values greater than zero represent emissions.
Lane! Use, land-Use Change, and Forestry 7-37
-------
the USDA NRI survey (USDA-NRCS 2000).l2 Land use
and some management information (e.g., legume pastures,
crop type, soil attributes, and irrigation) were collected for
each NRI point on a 5-year cycle beginning in 1982, and
were subdivided into four inventory time periods, 1980-84,
1985-1989, 1990-94 and 1995-2000. NRI points were
classified as Land Converted to Grassland for an inventory
time period (e.g., 1990-1994 and 1995-2000) if the land
use was grassland at the end of the respective inventory time
period but had been another use in a prior inventory time
period. Grassland includes pasture and rangeland used for
grass forage production, where the primary use is livestock
grazing. Rangeland are typically extensive areas of native
grassland that are not intensively managed, while pastures
are often seeded grassland, possibly following tree removal,
that may or may not be improved with practices such as
irrigation and interseeding legumes. Further elaboration on
the methodologies and data used to estimate stock changes
from mineral and organic soils are provided in the Cropland
Remaining Cropland section and Annex 3.13.
Mineral Soil Carbon Stock Changes
A Tier 3 model-based approach was used to estimate C
stock changes for Land Converted to Grassland on mineral
soils, with the exception of prior cropland used to produce
vegetables, tobacco, perennial/horticultural crops, and rice,
in addition to land areas with very gravelly, cobbly or shaley
soils (greater than 35 by volume). An IPCC Tier 2 approach
was used to estimate C stock changes for portions of the
land base for Land Converted to Grassland that were not
addressed with the Tier 3 approach (Ogle et al. 2003). A Tier
2 approach was also used to estimate additional changes in
mineral soil C stocks due to sewage sludge amendments.
However, stock changes associated with sewage sludge
amendments are reported in the Grassland Remaining
Grassland section.
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated
using the Century biogeochemical model as described for
Grassland Remaining Grassland. Historical land-use and
management patterns were used in the Century simulations
as recorded in the NRI survey, with supplemental information
on fertilizer use and rates from USDA Economic Research
Service Cropping Practices Survey (ERS 1997) and National
Agricultural Statistics Service (NASS 1992,1999,2004) (see
Grassland Remaining GrasslandTier 3 methods section for
additional information).
Tier 2 Approach
The Tier 2 Approach used for Land Converted to
Grassland on mineral soils is the same as described for
Cropland Remaining Cropland (See Cropland Remaining
Cropland Tier 2 Approach for additional information).
Organic Soil Carboti Stock Changes
Annual C emissions from drained organic soils in
Land Converted to Grassland were estimated using the
Tier 2 method provided in IPCC/UNEP/OECD/IEA (1997)
and IPCC (2003), which utilizes U.S.-specific C loss rates
(Ogle et al. 2003) rather than default IPCC rates. The final
estimates included a measure of uncertainty as determined
from a Monte Carlo simulation with 50,000 iterations.
Emissions were based on the 1992 and 1997 Land Converted
to Grassland areas from the 7997 National Resources
Inventory (USDA-NRCS 2000). The annual flux estimated
for 1992 was applied to 1990 through 1992, and the annual
flux estimated for 1997 was applied to 1993 through 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Land Converted to Grassland are
reported in Cropland Remaining Cropland, because it was
not possible to disaggregate liming application among land
use and land-use change categories.
Uncertainty
Uncertainty associated with the Land Converted to
Grassland category includes the uncertainty associated with
changes in mineral soil C stocks. Uncertainty estimates are
presented in Table 7-28 for each subsource (i.e.. mineral
soil C stocks and organic soil C stocks) disaggregated to the
level of the inventory methodology employed (i.e., Tier 2
and Tier 3). A combined uncertainty estimate for changes in
agricultural soil C stocks occurring within Land Converted
to Grassland is also included. Uncertainty estimates from
each component were combined using the error propagation
equation in accordance with IPCC (2006). The combined
uncertainty was calculated by taking the square root of the
sum of the squares of the standard deviations of the uncertain
12 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 7-28: Quantitative Uncertainty Estimates for C Stock Changes occurring within Land Converted to Grassland
(Tg C02 Eq. and Percent)
2005 StOCk lln-0,«,int,,
Change Estimate Uncertainty
Source
Mineral Soil C Stocks: Land Converted to Grassland,
Tier 3 Inventory Methodology
Mineral Soil C Stocks: Land Converted to Grassland,
Tier 2 Inventory Methodology
Organic Soil C Stocks: Land Converted to Grassland,
Tier 2 Inventory Methodology
Combined Uncertainty for Agricultural Soil Carbon
Stocks in Land Converted to Grassland
(Tg C02 Eq.)
(12.2)
(5.0)
0.9
(16.3)
(TgCO
Lower Bound
(12.5)
(7.0)
0.2
(18.4)
Range Relative to Stock Change Estimate
zEq.)
Upper Bound
(11.9)
(2.8)
1.8
(14.0)
(°/
Lower Bound
-2%
-39%
-76%
-13%
6)
Upper Bound
+ 2%
+43%
+ 104%
+14%
quantities. More details on how the individual uncertainties
were developed appear later in this section. The combined
uncertainty for soil C stocks in Land Converted to Grassland
ranged from 13 percent below and 14 percent above the 2005
estimate of 16.3 Tg CO2 Eq.
Uncertainties in Mineral Soil Carbon Stock Changes
Tier 3 Approach
The uncertainty analysis for Land Converted to
Grassland using the Tier 3 and Tier 2 approaches were
based on the same method described in Cropland Remaining
Cropland, except that the uncertainty inherent in the structure
of the Century model was not addressed.
Uncertainties in Organic Soil Carbon Stock Changes
Annual C emission estimates from drained organic soils
in Land Converted to Grassland were estimated using the
Tier 2 approach, as described in the Cropland Remaining
Cropland section.
QA/QC and Verification
See the QA/QC and Verification section under Grassland
Remaining Grassland.
Recalculations Discussion
The specific changes in reporting in the current
Inventory for Land Converted to Grassland are the same
as those described in the Cropland Remaining Cropland
section, except that the uncertainty is not addressed in the
current Inventory for the random variation associated with
Century model estimates at the site scale. The structural
uncertainty requires further development before it can be
used to address uncertainty inherent in the structure of the
Century model for other uses besides cropland. Overall, the
recalculations resulted in an average annual decrease in sinks
of 4.3 Tg CO2 Eq. (21.1 percent) for soil C stock changes in
Land Converted to Grassland for the time series from 1990
through 2004.
Planned improvements
The empirically-based uncertainty estimator described
in the Cropland Remaining Cropland section for the Tier 3
approach has not been developed to estimate uncertainties in
Century model results for Land Converted to Grassland, but
this is a planned improvement for the inventory. See Planned
Improvements section under Cropland Remaining Cropland
for additional planned improvements.
7.7. Settlements Remaining
Settlements
Changes in Carbon Stocks in Urban
Trees (IPCC Source Category 5E1)
Urban forests constitute a significant portion of the total
U.S. tree canopy cover (Dwyer et al. 2000). Urban areas
(cities, towns, and villages) are estimated to cover over
4.4 percent of the United States (Nowak et al. 2005). With
an average tree canopy cover of 27.1 percent, urban areas
account for approximately 3 percent of total tree cover in
the continental United States (Nowak et al. 2001). Trees in
urban areas of the United States were estimated to account
Land Use, Land-Use Change, and Forestry 7-39
-------
Table 7-29: Net C Flux from Urban Trees (Tg C02 Eq.
and Tg C)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
(57.5)
(67.8)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
TgC
(15.7)
(18.5)
(21.3)
(21.9)
(22.4)
(23.0)
(23.6)
(24.1)
Note: Parentheses indicate net sequestration.
for an average annual net sequestration of 73.0 Tg CO2 Eq.
(19.9 Tg C) over the period from 1990 through 2005. Total
sequestration increased by 54 percent between 1990 and 2005
due to increases in urban land area. Data on C storage and
urban tree coverage were collected throughout the 1990s.
and have been applied to the entire time series in this report.
Annual estimates of CO2 flux were developed based on
periodic U.S. Census data on urban area (Table 7-29).
Net C flux from urban trees is proportionately greater
on an area basis than that of forests. This trend is primarily
the result of different net growth rates in urban areas versus
forests —urban trees often grow faster than forest trees
because of the relatively open structure of the urban forest
(Nowak and Crane 2002). Also, areas in each case are
accounted for differently. Because urban areas contain less
tree coverage than forest areas, the C storage per hectare of
land is in fact smaller for urban areas. However, urban tree
reporting occurs on a per unit tree cover basis (tree canopy
area), rather than total land area. Urban trees, therefore.
appear to have a greater C density than forested areas (Nowak
and Crane 2002).
Methodology
The methodology used by Nowak and Crane (2002) is
based on average annual estimates of urban tree growth and
decomposition, which were derived from field measurements
and data from the scientific literature, urban area estimates
from U.S. Census data, and urban tree cover estimates
from remote sensing data. This approach is consistent with
the default IPCC methodology in IPCC (2003), although
sufficient data are not yet available to determine interannual
changes in C stocks in the living biomass of urban trees.
Annual changes in net C flux from urban trees are based
solely on changes in total urban area in the United States.
Nowak and Crane (2002) developed estimates of
annual gross C sequestration from tree growth and annual
gross C emissions from decomposition for ten U.S. cities:
Atlanta, GA; Baltimore, MD; Boston, MA; Chicago, IL;
Jersey City, NJ; New York, NY; Oakland, CA; Philadelphia,
PA; Sacramento, CA; and Syracuse, NY. The gross C
sequestration estimates were derived from field data that
were collected in these ten cities during the period from
1989 through 1999, including tree measurements of stem
diameter, tree height, crown height, and crown width, and
information on location, species, and canopy condition. The
field data were converted to annual gross C sequestration
rates for each species (or genus), diameter class, and land-use
condition (forested, park-like, and open growth) by applying
allometric equations, a root-to-shoot ratio, moisture contents,
a C content of 50 percent (dry weight basis), an adjustment
factor to account for smaller aboveground biomass volumes
(given a particular diameter) in urban conditions compared
to forests, an adjustment factor to account for tree condition
(fair to excellent, poor, critical, dying, or dead), and annual
diameter and height growth rates. The annual gross C
sequestration rates for each species (or genus), diameter class,
and land-use condition were then scaled up to city estimates
using tree population information. The field data from the
10 cities, some of which are unpublished, are described in
Nowak and Crane (2002) and references cited therein. The
allometric equations were taken from the scientific literature
(see Nowak 1994, Nowak et al. 2002), and the adjustments
to account for smaller volumes in urban conditions were
based on information in Nowak (1994). A root-to-shoot ratio
of 0.26 was taken from Cairns et al. (1997), and species- or
genus-specific moisture contents were taken from various
literature sources (see Nowak 1994). Adjustment factors
to account for tree condition were based on percent crown
dieback (Nowak and Crane 2002). Tree growth rates were
also taken from existing literature. Average diameter growth
was based on the following sources: estimates for trees in
forest stands came from Smith and Shirley (1984); estimates
for trees on land uses with a park-like structure came from
deVries (1987); and estimates for more open-grown trees
came from Nowak (1994). Formulas from Fleming (1988)
formed the basis for average height growth calculations.
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19130-2 305
-------
Annual gross C emission estimates were derived by
applying estimates of annual mortality and condition, and
assumptions about whether dead trees were removed from
the site, to C stock estimates. These values were derived
as intermediate steps in the sequestration calculations, and
different decomposition rates were applied to dead trees left
standing compared with those removed from the site. The
annual gross C emission rates for each species (or genus),
diameter class, and condition class were then scaled up to
city estimates using tree population information. Estimates of
annual mortality rates by diameter class and condition class
were derived from a study of street-tree mortality (Nowak
1986). Assumptions about whether dead trees would be
removed from the site were based on expert judgment of
the authors. Decomposition rates were based on literature
estimates (Nowak and Crane 2002).
National annual net C sequestration by urban trees was
estimated from estimates of gross and net sequestration
from seven of the ten cities, and urban area and urban tree
cover data for the United States. Annual net C sequestration
estimates were derived for seven cities by subtracting the
annual gross emission estimates from the annual gross
sequestration estimates.13 The urban areas are based on
1990 and 2000 U.S. Census data. The 1990 U.S. Census
defined urban land as "urbanized areas," which included
land with a population density greater than 1,000 people
per square mile, and adjacent ''urban places," which had
predefined political boundaries and a population total greater
than 2,500. In 2000, the U.S. Census replaced the "urban
places" category with a new category of urban land called
an "urban cluster," which included areas with more than 500
people per square mile. Urban land area has increased by
approximately 36 percent from 1990 to 2000; Nowak et al.
(2005) estimate that the changes in the definition of urban
land have resulted in approximately 20 percent of the total
reported increase in urban land area from 1990 to 2000.
Under both 1990 and 2000 definitions, urban encompasses
most cities, towns, and villages (i.e., it includes both urban
and suburban areas). The gross and net C sequestration
values for each city were divided by each city's area of tree
cover to determine the average annual sequestration rates per
unit of tree area for each city. The median value for gross
sequestration (0.30 kg C/m2-year) was then multiplied by
the estimate of national urban tree cover area to estimate
national annual gross sequestration. To estimate national
annual net sequestration, the estimate of national annual
gross sequestration was multiplied by the average of the
ratios of net to gross sequestration for those cities that had
both estimates (0.70). The urban tree cover estimates for each
of the 10 cities and the United States were obtained from
Dwyer et al. (2000) and Nowak et al. (2002). The urban area
estimates were taken from Nowak et al. (2005).
Uncertainty
Uncertainty associated with changes in C stocks in
urban trees includes the uncertainty associated with urban
area, percent urban tree coverage, and estimates of gross
and net C sequestration for the ten U.S. cities. A 10 percent
uncertainty was associated with urban area estimates, based
Table 7-30: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr), Tree Cover (Percent),
and Annual Carbon Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for Ten U.S. Cities
City
New York, NY
Atlanta, GA
Sacramento, CA
Chicago, IL
Baltimore, MD
Philadelphia, PA
Boston, MA
Syracuse, NY
Oakland, CA
Jersey City, NJ
Carbon
Stocks
1,225,200
1,220,200
1,107,300
854,800
528,700
481,000
289,800
148,300
145,800
19,300
Gross Annual
Sequestration
38,400
42,100
20,200
40,100
14,800
14,600
9,500
4,700
NA
800
Net Annual
Sequestration
20,800
32,200
NA
NA
10,800
10,700
6,900
3,500
NA
600
Tree Cover
20.9
36.7
13.0
11.0
25.2
15.7
22.3
24.4
21.0
11.5
Gross Annual
Sequestration per
Area of Tree Cover
0.23
0.34
0.66
0.61
0.28
0.27
0.30
0.30
NA
0.18
Net Annual
Sequestration per
Area of Tree Cover
0.12
0.26
NA
NA
0.20
0.20
0.22
0.22
NA
0.13
NA = not analyzed.
13 Three cities did not have net estimates.
Land Use, Land-Use Change, and Forestry 7-41
-------
Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg
C02 Eq. and Percent)
2005 Flux Estimate Uncertainty Range Relative to Flux Estimate3
Source Gas (TgC02Eq.) (TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Changes in C Stocks in
Urban Trees C02
(88.5) (108.5) (71.3) -23% +19%
Note: Parentheses indicate negative values or net sequestration.
a Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
on expert judgment. A 5 percent uncertainty was associated
with national urban tree covered area. Uncertainty associated
with estimates of gross and net C sequestration for the ten
U.S. cities was based on standard error estimates for each of
the city-level sequestration estimates as reported in Nowak et
al. (2002). These estimates are based on field data collected
in ten U.S. cities, and uncertainty in these estimates increases
as they are scaled up to the national level.
Additional uncertainty is associated with the biomass
equations, conversion factors, and decomposition assumptions
used to calculate C sequestration and emission estimates
(Nowak et al. 2002). These results also exclude changes
in soil C stocks, and there may be some overlap between
the urban tree C estimates and the forest tree C estimates.
However, both the omission of urban soil C flux and the
potential overlap with forest C are believed to be relatively
minor (Nowak 2002a). Because these factors are currently
inestimable due to data limitations, they are not quantified
as part of this analysis.
A Monte Carlo (Tier 2) uncertainty analysis was applied to
estimate the overall uncertainty of the sequestration estimate.
The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 7-31. The net C flux from changes in
C stocks in urban trees was estimated to be between -108.5
and -71.3 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 23 percent below and 19 percent above
the 2005 flux estimate of -88.5 Tg CO, Eq.
QA/QC and Verification
The net C flux resulting from urban trees was calculated
using estimates of gross and net C sequestration estimates for
urban trees and urban tree coverage area found in literature.
The validity of these data for their use in this section of the
Inventory was evaluated through correspondence established
with an author of the papers. Through the correspondence,
the methods used to collect the urban tree sequestration and
area data were further clarified and the use of these data in
the inventory was reviewed and validated (Nowak 2002a).
Recalculations Discussion
In previous Inventories, estimates of Tg C had been
rounded to 2 significant figures based on Nowak (2002b).
Since a Tier 2 uncertainty analysis was run for this source
starting from the current Inventory, this rounding step was
removed. This change resulted in a change in emission
estimates for 1990 through 2004. On average, estimates
of net C flux from urban trees decreased by less than one
percent over the period from 1990 to 2004 relative to the
previous report.
Planned Improvements
New estimates of C in urban trees based on new satellite
and field data are being developed. Once those data become
available, they will be incoiporated into estimates of net C
flux resulting from urban trees.
A consistent representation of the managed land base
in the United States is also being developed. A component
of this project will involve reconciling the overlap between
urban forest and non-urban forest GHG inventories. It is
highly likely that urban forest inventories are including
areas considered non-urban under the Forest Inventory
and Analysis (FIA) program of the USDA Forest Service,
resulting in "double-counting" of these land areas in
estimates of C stocks and fluxes for the U.S. Inventory. One
goal of the plan to develop the consistent representation of
the United States land base is to eliminate this overlap.
Direct N20 Fluxes from Settlement
Soils (IPCC Source Category 5E1)
Of the synthetic N fertilizers applied to soils in the
United States, approximately 10 percent are applied to
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 7-32: N20 Fluxes from Soils in Settlements
Remaining Settlements (Tg C02 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Tg C02 Eq.
5.1
5.5
5.6
5.5
5.6
5.8
6.0
5.8
Gg
17
18
18
18
18
19
19
19
Note: These estimates include direct N20 emissions from N fertilizer
additions only. Indirect N20 emissions from fertilizer additions are
reported in the Agriculture chapter. These estimates include emissions
from both Settlements Remaining Settlements and from Land Converted
to Settlements.
lawns, golf courses, and other landscaping occurring within
settlement areas. Application rates are less than those
occurring on cropped soils, and, therefore, account for a
smaller proportion of total U.S. soil N2O emissions per
unit area. In addition to synthetic N fertilizers, a portion of
surface applied sewage sludge is applied to settlement areas.
In 2005, N2O emissions from this source were 5.8 Tg CO2
Eq. (19 Gg). There was an overall increase of 13 percent
over the period from 1990 through 2005 due to a general
increase in the application of synthetic N fertilizers to an
expanding settlement area. Interannual variability in these
emissions is directly attributable to interannual variability
in total synthetic fertilizer consumption and sewage sludge
applications in the United States. Emissions from this source
are summarized in Table 7-32.
Methodology
For soils within Settlements Remaining Settlements,
the IPCC Tier 1 approach was used to estimate soil N2O
emissions from synthetic N fertilizer and sewage sludge
additions. Estimates of direct N2O emissions from soils
in settlements were based on the amount of N in synthetic
commercial fertilizers applied to settlement soils and the
amount of N in sewage sludge applied to non-agricultural
land and in surface disposal of sewage sludge.
Nitrogen applications to settlement soils are assumed to
be 10 percent of the total synthetic fertilizer used in the United
States (Qian 2004). Total synthetic fertilizer applications
were derived from fertilizer statistics (TVA1991,1992,1993,
1994;AAPFCO 1995,1996,1997,1998,1999,2000b, 2002,
2003, 2004, 2005, 2006) and a recent AAPFCO database
(AAPFCO 2000a). Sewage sludge applications were derived
from national data on sewage sludge generation, disposition,
and nitrogen content (see Annex 3.11 for further detail).
The total amount of N resulting from these sources was
multiplied by the IPCC default emission factor for applied
N (1 percent) to estimate direct N2O emissions (IPCC 2006).
The volatilized and leached/runoff proportions, calculated
with the IPCC default volatilization factors (10 or 20
percent, respectively, for synthetic or organic N fertilizers)
and leaching/runoff factor for wet areas (30 percent), were
included with the total N contributions to indirect emissions,
as reported in the Agricultural Soil Management source
category of the Agriculture chapter.
Uncertainty
The amount of N2O emitted from settlements depends
not only on N inputs, but also on a large number of variables,
including organic C availability, O2 partial pressure, soil
moisture content, pH, temperature, and irrigation/watering
practices. The effect of the combined interaction of these
variables on N2O flux is complex and highly uncertain. The
IPCC default methodology used here does not incorporate
any of these variables and only accounts for variations in
national fertilizer N and sewage sludge application rates.
All settlement soils are treated equivalently under this
methodology. Uncertainties exist in both the fertilizer N and
sewage sludge application rates and the emission factors
used to derive emission estimates.
The uncertainty in the amounts of sewage sludge
applied to non-agricultural lands and used in surface
disposal was based on the uncertainty of the following
data points, which were used to determine the amounts
applied in 2005: (1) N content of sewage sludge; (2) total
sludge applied in 2000; (3) wastewater existing flow in
1996 and 2000; and (4) the sewage sludge disposal practice
distributions to non-agricultural land application and
surface disposal.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 7-33. N2O emissions
from soils in Settlements Remaining Settlements in 2005
were estimated to be between 3.0 and 15.3 Tg CO2 Eq. at
a 95 percent confidence level. This indicates a range of
49 percent below to 163 percent above the 2005 emission
estimate of 5.8 Tg CO2 Eq.
Land Use, Land-Use Change, and Forestry 7 43
-------
Table 7-33: Tier 2 Quantitative Uncertainty Estimates of N20 Emissions from Soils in Settlements Remaining
Settlements (Tg C02 Eq. and Percent)
Source
Gas
2005 Emissions Uncertainty Range Relative to 2005 Emission Estimate
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Settlements Remaining Settlements:
N20 Fluxes from Soils N20
5.8
3.0
15.3
-49%
+ 163%
Note: This estimate includes direct N20 emissions from N fertilizer additions to both Settlements Remaining Settlements and from Land Converted to
Settlements.
Recalculations Discussion
There were several recalculations for the current
Inventory. The 2003 and 2004 total fertilizer application
data were updated from the APPFCO Commercial
Fertilizers 2003 Report (2004) and 2004 Report (2005).
An error in unit conversion used in the sewage sludge
calculations was corrected. Changes were made to the data
used to calculate the amount of sewage sludge applied from
2001 to 2005, as discussed in Annex 3.11. In the previous
Inventory, sewage sludge applied as commercial fertilizer
was included in total synthetic fertilizer applied, as well
as added to the total synthetic fertilizer applied, effectually
double counting the amounts of sewage sludge applied
to settlements. This error was corrected by not including
sewage sludge in total synthetic fertilizer applied. The IPCC
default emission factor of 1.25 percent for direct emissions
from applied N was updated to 1 percent based on IPCC
(2006). Additionally, because the direct emission factor was
developed based on total N inputs, the new method has been
revised to estimate direct N2O emissions based on total N
input. Previously, a portion of the N inputs were removed
from the calculation of direct N2O emissions, because it
was assumed to be lost through volatilization before direct
emissions occurred. All of these changes resulted in a 7.6
percent decrease in the emissions estimates for 2004 and
an average decrease of about 7.5 percent over the period
from 1990 to 2004.
Planned Improvements
The process-based DAYCENT model, which was used
to estimate N2O emissions from cropped soils, could also
be used to simulate direct and indirect emissions from
settlement soils using state-level settlement area data from
the National Resource Inventory.
7.8, Land Converted to Settlements
(Source Category 5E2)
Land-use change is constantly occurring, and land
under a number of uses undergoes urbanization in the
United States each year. However, data on the amount of
land converted to settlements is currently lacking. Given
the lack of available information relevant to this particular
IPCC source category, it is not possible to separate CO2 or
N2O fluxes on Land Converted to Settlements from fluxes on
Settlements Remaining Settlements at this time.
7,9. Other (IPCC Source Category 5G)
Changes in )'ard Tnmming and Food
Scrap Stocks in Land fills
In the United States, a significant change in C stocks
results from the removal of yard trimmings (i.e., grass
clippings, leaves, and branches) and food scraps from
settlements to be disposed in landfills. Yard trimmings and
food scraps account for a significant portion of the municipal
waste stream, and a large fraction of the collected yard
trimmings and food scraps are discarded in landfills. C
contained in landfilled yard trimmings and food scraps can
be stored for very long periods.
C storage is associated with particular land uses. For
example, harvested wood products are accounted for under
Forest Land Remaining Forest Land because these products
are a component of this ecosystem. C stock changes in yard
trimmings and food scraps are associated with settlements, but
removals do not occur within settlements. Yard trimming and
food scrap C storage is therefore reported under "Other."
7-44 Inventory of U.S. Greenhouse Gas; Emissions anri Sinks: 1990-2005
-------
Both the amount of yard trimmings and food scraps
collected annually and the fraction that is landfilled have
declined over the last decade. In 1990,nearly51 million metric
tons (wet weight) of yard trimmings and food scraps were
generated (i .e., put at the curb for collection or taken to disposal
or composting facilities) (EPA 2005). Since then, programs
banning or discouraging disposal have led to an increase
in backyard composting and the use of mulching mowers,
and a consequent 18 percent decrease in the amount of yard
trimmings collected. At the same time, a dramatic increase in
the number of municipal composting facilities has reduced
the proportion of collected yard trimmings that are discarded
in landfills—from 72 percent in 1990 to 35 percent in 2003
(the most recent year for which data are available; 2004 and
2005 values are assumed to equal 2003). There is considerably
less centralized composting of food scraps; generation has
grown by 32 percent since 1990, though the proportion of
food scraps discarded in landfills has decreased slightly from
81 percent in 1990 to 78 percent in 2003. Overall, there has
been a decrease in the yard trimmings and food scrap landfill
disposal rate, which has resulted in a decrease in the rate of
landfill C storage to 8.8 Tg CO2 Eq. in 2005 from 22.8 Tg CO2
Eq. in 1990 (Table 7-34 and Table 7-35).
Methodology
As empirical evidence shows, the removal of C from the
natural cycling of C between the atmosphere and biogenic
materials, which occurs when wastes of biogenic origin are
deposited in landfills, sequesters C (Barlaz 1998, 2005).
When wastes of sustainable, biogenic origin (such as yard
trimming and food scraps) are landfilled and do not completely
decompose, the C that remains is effectively removed from the
global C cycle. Estimates of net C flux resulting from landfilled
yard trimmings and food scraps were developed by estimating
the change in landfilled C stocks between inventory years,
based on methodologies presented for the Land Use, Land-Use
Change and Forestry sector in IPCC (2003) and IPCC (2006).
C stock estimates were calculated by determining the mass
of landfilled C resulting from yard trimmings or food scraps
discarded in a given year; adding the accumulated landfilled C
from previous years; and subtracting the portion of C landfilled
in previous years that decomposed.
To determine the total landfilled C stocks for a given year,
the following were estimated: (1) the composition of the yard
trimmings; (2) the mass of yard trimmings and food scraps
discarded in landfills; (3) the C storage factor of the landfilled
yard trimmings and food scraps adjusted by mass balance;
and (4) the rate of decomposition of the degradable C. The
composition of yard trimmings was assumed to be 30 percent
grass clippings, 40 percent leaves, and 30 percent branches on a
wet weight basis (Oshins and Block 2000). The yard trimmings
were subdivided, because each component has its own unique
adjusted C storage factor and rate of decomposition. The mass
of yard trimmings and food scraps disposed of in landfills was
Table 7-34: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C02 Eq.)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
1990
(20.3)
(2.4)
(8.2)
(9.7)
(2.5)
(22.8)
1995
(11.8)
(1.2)
(4.7)
(5.8)
(1.6)
(13.3)
2000
(7.5)
(0.8)
(2.9)
(3.7)
(3.0)
(10.5)
2001
(7.7)
(0.9)
(3.0)
(3.8)
(2.9)
(10.6)
2002
(7.9)
(0.9)
(3.1)
(3.9)
(2.9)
(10.8)
2003
(6.4)
(0.7)
(2.5)
(3.2)
(3.0)
(9.3)
2004
(5.5)
(0.6)
(2.1)
(2.8)
(3.2)
(8.7)
2005
(5.8)
(0.7)
(2.2)
(2.9)
(3.0)
(8.8)
Note: Totals may not sum due to independent rounding.
Table 7-35: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
Note: Totals may not sum
1990
(5.5)
(0.6)
(2.2)
(2.6)
(0.7)
(6.2)
due to independent rounding.
1995
(3.2)
(0.3)
(1.3)
(1.6)
(0.4)
(3.6)
2000
(2.0)
(0.2)
(0.8)
(1.0)
(0.8)
(2.9)
2001
(2.1)
(0.2)
(0.8)
(1.0)
(0.8)
(2.9)
2002
(2.2)
(0.3)
(0.8)
(1.1)
(0.8)
(3-0)
2003
(1.7)
(0.2)
(0.7)
(0.9)
(0.8)
(2.5)
2004
(1.5)
(0.2)
(0.6)
(0.8)
(0.9)
(2.4)
2005
(1.6)
(0.2)
(0.6)
(0.8)
(0.8)
(2.4)
Land Use, Land-Use Change, and Forestry 7-45
-------
estimated by multiplying the quantity of yard trimmings and
food scraps discarded by the proportion of discards managed in
landfills. Data on discards (i .e., the amount generated minus the
amount diverted to centralized composting facilities) for both
yard trimmings and food scraps were taken primarily from
Municipal Solid Waste Generation, Recycling, and Disposal
in the United States: 2003 Facts and Figures (EPA 2005),
which provides data for 1960, 1970, 1980, 1990, 1995, and
2000 through 2003. To provide data for some of the missing
years in the 1990 through 1999 period, two earlier reports were
used (Characterization of Municipal Solid Waste in the United
States: 1998 Update (EPA 1999), and Municipal Solid Waste
in the United States: 2001 Facts and Figures [EPA 2003]).
Remaining years in the time series for which data were not
provided were estimated using linear interpolation. Values for
2004 and 2005 are assumed to be equal to values for 2003.
The reports do not subdivide discards of individual materials
into volumes landfilled and combusted, although they provide
an estimate of the proportion of overall wastestream discards
managed in landfills and combustors (i.e., ranging from 90
percent and 10 percent respectively in 1980, to 67 percent
and 33 percent in 1960).
The amount of C disposed of in landfills each year,
starting in 1960, was estimated by converting the discarded
landfilled yard trimmings and food scraps from a wet weight
to a dry weight basis, and then multiplying by the initial (i.e.,
pre-decomposition) C content (as a fraction of dry weight).
The dry weight of landfilled material was calculated using dry
weight to wet weight ratios (Tchobanoglous et al. 1993, cited
by Barlaz 1998) and the initial C contents were determined
by Barlaz (1998, 2005) (Table 7-36).
The amount of C remaining in the landfill for each
subsequent year was tracked based on a simple model of C
fate. As demonstrated by Barlaz (1998,2005), a portion of the
initial C resists decomposition and is essentially persistent in
the landfill environment; the modeling approach applied here
builds on his findings. Barlaz (1998,2005) conducted a series
of experiments designed to measure biodegradation of yard
trimmings, food scraps, and other materials, in conditions
designed to promote decomposition (i.e., by providing ample
moisture and nutrients). After measuring the initial C content,
the materials were placed in sealed containers along with a
"seed" containing methanogenic microbes from a landfill.
Once decomposition was complete, the yard trimmings and
food scraps were re-analyzed for C content; the C remaining
in the solid sample can be expressed as a proportion of initial
C (shown in the row labeled "CS" in Table 7-36).
For purposes of simulating U.S. landfill C flows, the
proportion of C stored is assumed to persist in landfills;
the remaining portion is assumed to degrade (and results
in emissions of CH4 and CO2; the CH4 emissions resulting
from decomposition of yard trimmings and food scraps are
accounted for in the Waste chapter). The degradable portion
of the C is assumed to decay according to first order kinetics.
Grass and food scraps are assumed to have a half-life of 5
years; leaves and branches are assumed to have a half-life
of 20 years.
For each of the four materials (grass, leaves, branches,
food scraps), the stock of C in landfills for any given year is
calculated according to the following formula:
I..1-V , - IW. x i i - MC i x ICC >
where,
~ Year tor whicn {_' stocks are being estimated
- Stoc c of C' in landlills in year ;. tor waste /
•. 'jra>s. leaves brunches, foot.! snas!
Mas1, lit \\asti. / deposed in
.; . in i nits •,-! \vi t weight
— Proportion ot iriu.il C that s stored lor
v.astj ;
!(."(.', = Initial ('eonk ill of waste /
e = Natural logarithm, and
k = 1 nst order rate constant tor wast.; / which
i, equal to 0.6'M di\ idcd hv the half-lite lor
L (.-composition
For a given year t, the total stock of C in landfills (TLFCt)
is the sum of stocks across all four materials. The annual flux
of C in landfills (Ft) for year / is calculated as the change in
stock compared to the preceding year:
• -TU-T, Tl.l-C,
Thus, the C placed in a landfill in year n is tracked for
each year t through the end of the inventory period (2005).
For example, disposal of food scraps in 1960 resulted in
depositing about 1,140,000 metric tons of C. Of this amount,
16 percent (180,000 metric tons) is persistent; the remaining
7-46 Inventory of U.S. Greenhouse Gas; Emissions and Sinks: 1990-2005
-------
Table 7-36: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%), Initial C Content (%),
and Half-Life (years) for Yard Trimmings and Food Scrap Stocks in Landfills
Variable
Moisture Content (% H20)
CS, proportion of initial C stored (%)
Initial C Content (%)
Half-life (years)
Grass
70
68
45
5
Yard Trimmings
Leaves
30
72
42
20
Branches
10
77
49
20
Food Scraps
70
16
51
5
84 percent (960,000 metric tons) is degradable. By 1965, half
of the degradable portion (480,000 metric tons) decomposes,
leaving a total of 660,000 metric tons (the persistent portion,
plus the remaining half of the degradable portion).
Continuing the example, by 2005, the total food scraps
C originally disposed in 1960 had declined to 181,000 metric
tons (i.e., virtually all of the degradable C had decomposed).
By summing the C remaining from 1960 with the C remaining
from food scraps disposed in subsequent years (1961 through
2005), the total landfill C from food scraps in 2005 was 31.3
million metric tons. This value is then added to the C stock
from grass, leaves, and branches to calculate the total landfill
C stock in 2005, yielding a value of 220.6 million metric tons
(as shown in Table 7-37). In exactly the same way total net
flux is calculated for forest C and harvested wood products,
the total net flux of landfill C for yard trimmings and food
scraps for a given year (Table 7-35) is the difference in the
landfill C stock for a given year and the stock in the preceding
year. For example, the net change in 2005 shown in Table
7-35 (2.4 Tg C) is equal to the stock in 2005 (220.6 Tg C)
minus the stock in 2004 (218.2 Tg C).
When applying the C storage data reported by Barlaz
(1998), an adjustment was made to the reported values so
that a perfect mass balance on total C could be attained for
each of the materials. There are four principal elements in
the mass balance:
• Initial C content (ICC, measured),
• C output as CH4 (CH4-C. measured),
• C output as CO: (CO2-C, not measured), and
• Residual stored C (CS, measured).
In a simple system where the only C fates are CH4,
COj, and C storage, the following equation is used to attain
a mass balance:
CH4 ('-' CO. C - v '-• ~ ICC
The experiments by Barlaz and his colleagues (Barlaz
1998. Eleazer et al. 1997) did not measure CO2 outputs
in experiments. However, if the only decomposition is
anaerobic, then CH4-C = CO2-C.14 Thus, the system should
be defined by:
.: - cH,-c > ( ^ -. ice
The C outputs (= 2 x CH4-C + CS ) were less than 100
percent of the initial C mass for food scraps, leaves, and
branches (75, 86, and 90 percent, respectively). For these
materials, it was assumed that the unaccounted for C had
exited the experiment as CH4 and CO2, and no adjustment
was made to the measured value of CS.
Table 7-37: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Carbon Stocks
1990
149.8
18.2
61.3
70.3
20.3
170.1
1995
171.5
20.7
70.1
80.7
23.4
195.0
2000
181.4
21.7
74.1
85.6
27.2
208.6
2001
182.9
21.8
74.7
86.4
28.1
210.9
2002
184.4
22.0
75.3
87.1
28.9
213.3
2003
186.0
22.2
75.9
87.9
29.8
215.8
2004
187.7
22.4
76.6
88.7
30.5
218.2
2005
189.3
22.6
77.2
89.5
31.3
220.6
Note: Totals may not sum due to independent rounding.
14 The molar ratio of CH4 to CO: is 1:1 for carbohydrates (e.g.. cellulose, hemicellulose). For proteins as C, ,H5ON0 86, the molar ratio is 1.65 CH4 per
1.55 CO2 (Barlaz et al. 1989). Given the predominance of carbohydrates, for all practical purposes, the overall ratio is 1:1.
Land Use, Land-Use Change, and Forestry 7-47
-------
In the case of grass, the outputs were slightly more (103
percent) than initial C mass. To resolve the mass balance
discrepancy, it was assumed that the measurements of initial
C content and CH4 mass were accurate. Thus, the value of
CS was calculated as the residual of ICC (initial C content)
minus (2 x CH4-C). This adjustment reduced the C storage
value from the 71 percent reported by Barlaz (1998) to 68
percent (as shown in Table 7-36).
Uncertainty
The estimation of C storage in landfills is directly
related to the following yard trimming and food scrap data
and factors: disposal in landfills per year (tons of C), initial
C content, moisture content, decomposition rate (half-life),
and proportion of C stored. The C storage landfill estimates
are also a function of the composition of the yard trimmings
(i.e., the proportions of grass, leaves and branches in the yard
trimmings mixture). There are uncertainties associated with
each of these factors.
A Monte Carlo (Tier 2) uncertainty analysis was then
applied to estimate the overall uncertainty of the sequestration
estimate. The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 7-38. Total yard trimmings
and food scraps CO2 flux in 2005 was estimated to be
between -17.1 and -5.3 Tg CO2 Eq. at a 95 percent confidence
level (or 19 of 20 Monte Carlo stochastic simulations). This
indicates a range of 94 percent below to 40 percent above
the 2005 flux estimate of -8.8 Tg CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed for data gathering
and input, documentation, and calculation. The QA/QC
check revealed the need to update one of the input values,
addressed in the recalculations discussion below.
Recalculation!; Discussion
The only recalculation performed for the current
Inventory was a correction. The value for the initial C content
(ICC) of leaves was updated for the current Inventory (41.6
percent) based on updated experimental results provided
by Barlaz (2005). Although the previous Inventory used an
updated value for the carbon stored (CS) for leaves, the initial
C content had not been updated (i.e., the earlier experimental
value of 49.4 percent was used). This recalculation fixed that
problem, and has the effect of reducing the stocks of C from
leaves, and also reducing (by about 5 percent) the annual flux
for yard trimmings and food scraps.
In the previous Inventory, Changes in Yard Trimming
and Food Scrap C Stocks in Landfills was included in the
Settlements Remaining Settlements section of this chapter.
However, although C stock changes in yard trimmings and
food scraps are associated with settlements, removals do not
occur within settlements. Therefore, yard trimming and food
scrap C storage is now reported under "Other."
Planned Improvements
Future work may evaluate the potential contribution
of inorganic C to landfill sequestration, as well as the
consistency between the estimates of C storage described
in this chapter and the estimates of landfill CH4 emissions
described in the Waste chapter.
Table 7-38: Tier 2 Quantitative Uncertainty Estimates for C02 Flux from Yard Trimmings and Food Scrap Stocks in
Landfills (Tg C02 Eq. and Percent)
2005 Flux Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Flux Estimate3
(TgC02Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Yard Trimmings and
Food Scraps C02 (8.8)
(17.1) (5.3) -94% +40%
3 Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate negative values or net C sequestration.
7 48 Inventory of U.S, Greenhouse Gas Emissions arid Siiiks; 1990-2005
-------
8. Waste
Waste management and treatment activities
are sources of greenhouse gas emissions
(see Figure 8-1). Landfills accounted for
approximately 24 percent of total U.S. anthropogenic
methane (CH4) emissions in 2005,' the largest contribution of
any CH4 source in the United States. Additionally, wastewater
treatment accounts for just under 5 percent of U.S. CH4
emissions. Nitrous oxide (N2O) emissions from the discharge
of wastewater treatment effluents into aquatic environments
were estimated, as were N2O emissions from the treatment
process itself. Nitrogen oxide (NOX), carbon monoxide (CO),
and non-CH4 volatile organic compounds (NMVOCs) are
emitted by waste activities, and are addressed separately at
Table 8-1: Emissions from Waste (Tg C02 Eq.)
Figure 8-1
Landfills
Wastewater
Treatment
Waste as a Portion
of all Emissions
2.3%
/
20
40
60 80
Tg CO, Eq.
100
120
Note: Totals may not sum due to independent rounding.
Table 8-2: Emissions from Waste (Gg)
140
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Domestic Wastewater Treatment
Total
1990
185.8
161.0
24.8
6.4
6.4
192.2
1995
182.2
157.1
25.1
6.9
6.9
189.1
2000
158.3
131.9
26.4
7.6
7.6
165.9
2001
153.5
127.6
25.9
7.6
7.6
161.1
2002
156.2
130.4
25.8
7.7
7.7
163.9
2003
160.5
134.9
25.6
7.8
7.8
168.4
2004
157.8
132.1
25.7
7.9
7.9
165.7
2005
157.4
132.0
25.4
8.0
8.0
165.4
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Domestic Wastewater Treatment
NO,
CO
NMVOCs
1990
8,848
7,668
1,180
21
21
+
1
673
1995
8,674
7,479
1,195
22
22
1
2
731
2000
7,537
6,280
1,257
24
24
2
8
119
2001
7,310
6,078
1,232
25
25
2
8
122
2002
7,439
6,210
1,229
25
25
2
7
116
2003
7,645
6,425
1,220
25
25
2
7
116
2004
7,514
6,292
1,222
26
26
2
7
116
2005
7,496
6,286
1,210
26
26
2
7
116
Note: Totals may not sum due to independent rounding.
' Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land
Use. Land-Use Change, and Forestry chapter.
Waste 8-
-------
the end of this chapter. A summary of greenhouse gas and
indirect greenhouse gas emissions from the Waste chapter
is presented in Table 8-1 and Table 8-2.
Overall, in 2005, waste activities generated emissions
of 165.4 Tg CO2 Eq., or just over 2 percent of total U.S.
greenhouse gas emissions.
8.1. Landfills (IPCC Source
Category 6A1)
In 2005, landfill CH4 emissions were approximately
132 Tg CO2 Eq. (6,286 Gg), representing the largest source
of CH4 emissions in the United States. Emissions from
municipal solid waste (MSW) landfills, which received
about 64 percent of the total solid waste generated in the
United States, accounted for about 89 percent of total
landfill emissions, while industrial landfills accounted for the
remainder. Approximately 1,800 operational landfills exist in
the United States, with the largest landfills receiving most of
the waste and generating the majority of the CH4 (BioCycle
2006, adjusted to include missing data from five states).
Table 8-3: CH4 Emissions from Landfills (Tg C02 Eq.)
After being placed in a landfill, waste (such as paper,
food scraps, and yard trimmings) is initially decomposed
by aerobic bacteria. After the oxygen has been depleted, the
remaining waste is available for consumption by anaerobic
bacteria, which break down organic matter into substances
such as cellulose, amino acids, and sugars. These substances
are further broken down through fermentation into gases and
short-chain organic compounds that form the substrates for
the growth of methanogenic bacteria. These CH4-producing
anaerobic bacteria convert the fermentation products
into stabilized organic materials and biogas consisting
of approximately 50 percent carbon dioxide (CO2) and
50 percent CH4, by volume.2 Significant CH4 production
typically begins one or two years after waste disposal in a
landfill and continues for 10 to 60 years.
From 1990 to 2005, net CH4 emissions from landfills
decreased by approximately 18 percent (see Table 8-3 and
Table 8-4), with small increases occurring in some interim
years. This downward trend in overall emissions is the
result of increases in the amount of landfill gas collected
and combusted.3 which has more than offset the additional
Activity
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
1990
188.7
12.9
(17.6)
(5.0)
(17.9)
161.0
1995
204.7
13.9
(22.3)
(21.8)
(17.5)
157.1
2000
217.3
15.4
(49.0)
(37.1)
(14.7)
131.9
2001
221.4
15.6
(54.3)
(40.8)
(14.2)
127.6
2002
227.2
15.7
(54.4)
(43.7)
(14.5)
130.4
2003
234.9
15.9
(54.9)
(46.0)
(15.0)
134.9
2004
242.4
16.0
(57.1)
(54.4)
(14.7)
132.1
2005
249.6
16.1
(58.6)
(60.4)
(14.7)
132.0
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at both municipal and industrial landfills.
Table 8-4: CH4 Emissions from Landfills (Gg)
Activity
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
1990
8,985
614
(840)
(239)
(852)
7,668
1995
9,745
664
(1,061)
(1,039)
(831)
7,479
2000
10,348
731
(2,335)
(1,766)
(698)
6,280
2001
10,541
744
(2,588)
(1,943)
(675)
6,078
2002
10,820
749
(2,590)
(2,080)
(690)
6,210
2003
11,188
757
(2,614)
(2,192)
(714)
6,425
2004
11,543
761
(2,720)
(2,593)
(699)
6,292
2005
11,885
767
(2,790)
(2,877)
(698)
6,286
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at both municipal and industrial landfills.
2 The percentage of CO, in biogas released from a landfill may be smaller because some CO2 dissolves in landfill water (Bingemer and Crutzen 1987).
Additionally, less than 1 percent of landfill gas is typically composed of non-CH4 volatile organic compounds (NMVOCs).
-' The CO2 produced from combusted landfill CH4 at landfills is not counted in nation;.! inventories as it is considered part of the natural C cycle of
decomposition.
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
CH4 emissions resulting from an increase in the amount of
municipal solid waste landfilled.
Methane emissions from landfills are a function of several
factors, including: ( 1 ) the total amount of municipal solid waste
in landfills, which is related to total municipal solid waste
landfilled annually: (2) the characteristics of landfills receiving
waste (i.e., composition of waste-in-place, size, climate); (3)
the amount of CH4 that is recovered and either flared or used
for energy purposes; and (4) the amount of CH4 oxidized in
landfills instead of being released into the atmosphere. The
estimated annual quantity of waste placed in landfills increased
from about 209 Tg in 1 990 to 304 Tg in 2005, an increase of
45 percent (see Annex 3.14). During this period, the estimated
CH4 recovered and combusted from landfills increased as well .
In 1990, for example, approximately 1 ,079 Gg of CH4 were
recovered and combusted (i.e., used for energy or flared) from
landfills. In 2005. the estimated quantity of CH4 recovered
and combusted increased to 5,668 Gg, a 7 percent increase
from 2004 levels.
Over the next several years, the total amount of
municipal solid waste generated is expected to increase as the
U.S. population continues to grow. The percentage of waste
landfilled, however, may decline due to increased recycling
and composting practices. In addition, the quantity of CH4
that is recovered and either flared or used for energy purposes
is expected to increase as a result of 1 996 federal regulations
that require large municipal solid waste landfills to collect
and combust landfill gas (see 40 CFR Part 60, Subpart Cc
2005 and 40 CFR Part 60, Subpart WWW 2005), voluntary
programs encouraging CH4 recovery and use such as EPA's
Landfill Methane Outreach Program (LMOP), and federal
and state economic incentives.
Methodology
CH4 emissions from landfills were estimated to equal
the CH4 produced from municipal solid waste landfills, plus
the CH4 produced by industrial landfills, minus the CH4
recovered and combusted, minus the CH4 oxidized before
being released into the atmosphere:
where,
C'H
- CH.i emissions from solid waste
- C'H. generation from municipal
solid waste landfills
CH, ,m, = C'H| generation from industrial
landfills
R - ("II; recovered and combusted, and
Ox - C'H . o\idi/ed ironi MSWand
industrial landfills before release to
the atmosphcu-
The methodology for estimating CH4 emissions from
municipal solid waste landfills is based on the first order
decay model described by the Intergovernmental Panel on
Climate Change (IPCC 2006). Values for the CH4 generation
potential (L,,) and rate constant (k) were obtained from an
analysis of CH4 recovery rates for a database of 52 landfills
and from published studies of other landfills (RTI 2004;
EPA 1998; SWANA 1998; Peer, Thorneloe, and Epperson
1993). The rate constant was found to increase with average
annual rainfall; consequently, values of k were developed for
3 ranges of rainfall. The annual quantity of waste placed in
landfills was apportioned to the 3 ranges of rainfall based on
the percent of the U.S. population in each of the 3 ranges,
and historical census data were used to account for the
shift in population to more arid areas over time. For further
information, see Annex 3.14.
National landfill waste generation and disposal data for
1989 through 2005 were obtained from BioCycle (2006).
Because BioCvcle does not account for waste generated
in U.S. territories, waste generation for the territories was
estimated using population data obtained from the U.S.
Census Bureau (2006) and national per capita solid waste
generation from BioCycle (2006). Estimates of the annual
quantity of waste landfilled for 1960 through 1988 were
obtained from EPA's Anthropogenic Methane Emissions in
the United States, Estimates for 1990: Report to Congress
(EPA 1993) and an extensive landfill survey by the EPA's
Office of Solid Waste in 1986 (EPA 1988). Although waste
placed in landfills in the 1940s and 1950s contributes very
little to current CH4 generation, estimates for those years
were included in the first order decay model for completeness
in accounting for CH4 generation rates and are based on the
population in those years and the per capita rate for land
disposal for the 1960s.
The estimated landfill gas recovered per year was based
on updated data collected from vendors of flaring equipment,
a database of landfill gas-to-energy (LFGTE) projects
compiled by LMOP (EPA 2006), and a database maintained
by the Energy Information Administration (EIA) for the
Waste 8-3
-------
voluntary reporting of greenhouse gases (EIA 2006). The
three databases were carefully compared to identify landfills
that were in two or all three of the databases to avoid double-
counting reductions. Based on the information provided by the
EIA and flare vendor databases, the CH4 combusted by flares
in operation from 1990 to 2005 was estimated. This quantity
likely underestimates flaring because these databases do not
have information on all flares in operation. Additionally, the
EIA and LMOP databases provided data on landfill gas flow
and energy generation for landfills with LFGTE projects. If
a landfill in the EIA database was also in the LMOP and/or
the flare vendor database, the emissions avoided were based
on the EIA data because landfill owners or operators reported
the amount recovered based on measurements of gas flow
and concentration, and the reporting accounted for changes
over time. If both flare data and LMOP recovery data were
available for any of the remaining landfills (i.e., not in the
EIA database), then the emissions recovery was based on
the LMOP data, which provides reported landfill-specific
data on gas flow for direct use projects and project capacity
(i.e., megawatts) for electricity projects. The flare data, on
the other hand, only provided a range of landfill gas flow for
a given flare size. Given that each LFGTE project is likely
to also have a flare, double counting reductions from flares
and LFGTE projects in the LMOP database was avoided by
subtracting emissions reductions associated with LFGTE
projects for which a flare had not been identified from the
emissions reductions associated with flares.
A destruction efficiency of 99 percent was applied to
CH4 recovered to estimate CH4 emissions avoided. The
value for efficiency was selected based on the range of
efficiencies (98 to 100 percent) recommended for flares
in EPA's AP-42 Compilation of Air Pollutant Emission
Factors, Chapter 2.4 (EPA 1998) efficiencies used to
establish new source performance standards (NSPS) for
landfills, and in recommendations for closed flares used
in LMOP.
Emissions from industrial landfills were estimated from
activity data for industrial production, waste disposal factors,
and the first order decay model. The amount of CH4 oxidized
by the landfill cover at both municipal and industrial landfills
was assumed to be ten percent of the CH4 generated that is
not recovered (IPCC 2006, Mancinelli and McKay 1985,
Czepiel et al. 1996). To calculate net CH4 emissions, both
CH4 recovered and CH4 oxidized were subtracted from CH4
generated at municipal and industrial landfills.
Uncertainty
Several types of uncertainty are associated with the
estimates of CH4 emissions from landfills. The primary
uncertainty concerns the characterization of landfills.
Information is not available on two fundamental factors
affecting CH4 production: the amount and composition of
waste placed in every landfill for each year of its operation.
The approach used here assumes that the CH4 generation
potential and the rate of decay that produces CH4, as
determined from several studies of CH4 recovery at landfills,
are representative of U.S. landfills.
Additionally, the approach used to estimate the
contribution of industrial wastes to total CH4 generation
introduces uncertainty. Aside from uncertainty in estimating
CH4 generation potential, uncertainty exists in the estimates
of oxidation by cover soils. There is also uncertainty in
the estimates of methane that is recovered by flaring and
energy projects. The IPCC default value of 10 percent for
uncertainty in recovery estimates was used in the uncertainty
analysis when metering was in place (for about 64 percent
of the methane estimated to be recovered). For flaring
without metered recovery data (approximately 34 percent
of the methane estimated to be recovered), a much higher
uncertainty of approximately 50 percent was used (e.g.,
when recovery was estimated as 50 percent of the flare's
design capacity).
N2O emissions from the application of sewage sludge
on landfills are not explicitly modeled as part of greenhouse
gas emissions from landfills. N2O emissions from sewage
sludge applied to landfills would be relatively small because
the microbial environment in landfills is not very conducive
to the nitrification and denitrification processes that result
in N2O emissions. The total nitrogen (N) in sewage sludge
increased from 189 to 268 Gg total N between 1990 and 2005,
however; the quantity of sewage sludge applied to landfills
decreased from 28 to 10 percent from 1990 to 2005 4
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 8-5. Landfill CH4 emissions in 2005
were estimated to be between 80.5 and 174.2 Tg CO2 Eq.,
4 The methodology for estimating the quantity of N in sewage sludge disposed via incineration, land application, surface disposal, landfill, ocean
dumping, and other is described in Annex 3.11 Methodology for Estimating N20 Emissions From Agricultural Soil Management.
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg C02 Eq. and Percent)
Source
2005 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Landfills
132.0
80.5
174.2
-39%
+32%
s Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
which indicates a range of 39 percent below to 32 percent
above the actual 2005 emission estimate of 132 Tg CO2 Eq.
Recaiculations Discussion
Two recalculations affected the estimates of CH4
generation from landfills. As recommended in IPCC (2006)
for MSW landfills, the more accurate integrated form of
the first order decay model was applied (see Annex 3A.1 of
IPCC 2006), and a delay time of 6 months was incorporated.
The integrated form of the FOD model captures a constantly
changing rate of reaction, whereas the previously used
method, which was not integrated, instead assumed that the
rate of reaction remained constant throughout each year. The
6-month delay represents the time before substantial methane
generation begins at a landfill. By recalculating previous
emissions estimates using this method, estimates of CH4
generation from MSW landfills were reduced by 4 percent over
the time series. The second change was an improvement in
the estimate of CH4 generation from industrial landfills, which
was based on industrial production, waste disposal factors,
and the first order decay model. For previous Inventories,
the generation rate was estimated as simply 7 percent of
CH4 generation from MSW landfills. This change resulted
in a decrease of 2 percent in the estimated CH4 generation at
industrial landfills relative to the previous Inventory.
Another recalculation affecting estimates of CH4
recovery was associated with updating the EIA, LMOP,
and flare vendor databases. The estimates of gas recovery
by LFGTE projects and flares from 1990 to 2004 increased
by 0.7 percent based on changes to the current Inventory.
This change is due in part to updating the EIA database
and identifying additional flares installed in 2004 that were
not included in the previous Inventory. The EIA database
for 2004 did not become available until late in 2005;
consequently, the gas recovery rate for 2004 was estimated
from the 2003 data. The 2004 update showed that LFGTE
projects in the EIA 2003 database reported more gas recovery
in 2004 than 2003, and additional landfills were included in
the 2004 database, both of which increased the estimate of
CH4 recovery. A recalculation that had a minor effect was
the application of a destruction efficiency of 99 percent to
CH4 recovered to estimate CH4 emissions avoided.
The overall effect of these recalculations was an average
decrease of 5 percent in the estimated CH4 emissions from
landfills over the 1990 to 2004 time series.
Planned Improvements
For future Inventories, additional efforts will be made
to improve the estimates of CH4 generation at industrial
landfills. Improvements to the flare database will be
investigated, and an effort will be made to identify additional
landfills that have flares.
Box 8-1: Biogenic Emissions and Sinks of Carbon
C02 emissions from the combustion or decomposition of
biogenic materials (e.g., paper, wood products, and yard trimmings)
grown on a sustainable basis are considered to mimic the closed
loop of the natural carbon cycle—that is, they return to the
atmosphere C02 that was originally removed by photosynthesis.
In contrast, CH4 emissions from landfilled waste occur due to the
man-made anaerobic conditions conducive to CH4 formation that
exist in landfills, and are consequently included in this Inventory.
Depositing wastes of biogenic origin in landfills causes the
removal of carbon from its natural cycle between the atmosphere
and biogenic materials. As empirical evidence shows, some of
these wastes degrade very slowly in landfills, and the carbon they
contain is effectively sequestered in landfills over a period of time
(Barlaz 1998,2005). Estimates of carbon removals from landfilling
of forest products, yard trimmings, and food scraps are further
described in the Land Use, Land-Use Change, and Forestry chapter,
based on methods presented in IPCC (2003) and IPCC (2006).
Waste 8-5
-------
8.2. Wastewater Treatment (IPCC
Source Category 66)
Wastewater treatment processes can produce
anthropogenic CH4 and N2O emissions. Wastewater from
domestic (municipal sewage) and industrial sources is
treated to remove soluble organic matter, suspended
solids, pathogenic organisms, and chemical contaminants.
Treatment may either occur on site, most commonly through
septic systems or package plants,' or off site at centralized
treatment systems. Centralized wastewater treatment systems
may include a variety of processes, ranging from lagooning
to advanced tertiary treatment technology for removing
nutrients. In the United States, approximately 21 percent of
domestic wastewater is treated in septic systems or other on-
site systems, while the rest is collected and treated centrally
(U.S. Census Bureau 2006b).
Soluble organic matter is generally removed using
biological processes in which microorganisms consume the
organic matter for maintenance and growth. The resulting
biomass (sludge) is removed from the effluent prior to
discharge to the receiving stream. Microorganisms can
biodegrade soluble organic material in wastewater under
aerobic or anaerobic conditions, where the latter condition
produces CH4. During collection and treatment, wastewater
may be accidentally or deliberately managed under anaerobic
conditions. In addition, the sludge may be further biodegraded
under aerobic or anaerobic conditions. The generation of N2O
may also result from the treatment of domestic wastewater
during both nitrification and denitrification of the nitrogen
present, usually in the form of urea, ammonia, and proteins.
These compounds are converted to nitrate (NO3) through
the aerobic process of nitrification. Denitrification occurs
under anoxic conditions (without free oxygen), and involves
the biological conversion of nitrate into dinitrogen gas (N2).
N2O can be an intermediate product of both processes, but
is more often associated with denitrification.
The principal factor in determining the CH4 generation
potential of wastewater is the amount of degradable organic
material in the wastewater. Common parameters used to
measure the organic component of the wastewater are the
Biochemical Oxygen Demand (BOD) and Chemical Oxygen
Demand (COD). Under the same conditions, wastewater
with higher COD (or BOD) concentrations will generally
yield more CFL than wastewater with lower COD (or BOD)
concentrations. BOD represents the amount of oxygen that
would be required to completely consume the organic matter
contained in the wastewater through aerobic decomposition
processes, while COD measures the total material available
for chemical oxidation (both biodegradable and non-
biodegradable). Because BOD is an aerobic parameter, it
is preferable to use COD to estimate CH4 production. The
principal factor in determining the N2O generation potential
of wastewater is the amount of N in the wastewater.
In 2005, CH4 emissions from domestic wastewater
treatment were estimated to be 17.0 Tg CO2 Eq. (809 Gg).
Emissions fluctuated from 1990 through 1996, and have
decreased since 1997 due to decreasing percentages of
wastewater being treated in anaerobic systems, including
reduced use of on-site septic systems and central anaerobic
treatment systems. In 2005, CH4 emissions from industrial
wastewater treatment were estimated to be 8.4 Tg COi Eq.
(400 Gg). Industrial emission sources have increased across
the time series through 1999 and then slightly decreased
in keeping with production changes associated with the
treatment of wastewater from the pulp and paper; meat
and poultry; and vegetables, fruits, and juices processing
industries.6 Table 8-6 and Table 8-7 provide CH4 and N2O
emission estimates from domestic and industrial wastewater
treatment. With respect to N2O, the United States identifies
two distinct sources for N,O emissions from domestic
wastewater: emissions from centralized wastewater treatment
processes, and emissions from effluent from centralized
treatment systems that has been discharged into aquatic
environments. The 2005 emissions of N2O from centralized
wastewater treatment processes and from effluent were
estimated to be 0.2 Tg CO2 Eq. (1 Gg) and 7.8 Tg CO2 Eq.
(25 Gg), respectively. Total N2O emissions from domestic
wastewater were estimated to be 8.0 Tg CO2 Eq. (26 Gg).
N2O emissions from wastewater treatment processes
gradually increased across the time series as a result of
increasing U.S. population and protein consumption.
5 Package plants are treatment plants assembled in a factory, skid mounted, and transported to the treatment site.
6 Emissions associated with refinery wastewater are estimated in Annex 2.3 Methodology tor Estimating Carbon Emitted from Non-Energy Uses of
Fossil Fuels. Other industrial sectors include organic chemicals, starch production, alcohol refining, creameries, and textiles; however, emissions from
these sectors are considered to be insignificant.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19911-20115
-------
Table 8-6: CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.)
Activity
CH4
Domestic
Industrial*
N20
Domestic
Total
1990
24.8
17.4
7.4
6.4
6.4
31.2
1995
25.1
16.7
8.4
6.9
6.9
32.0
2000
26.4
17.7
8.7
7.6
7.6
34.0
2001
25.9
17.5
8.4
7.6
7.6
33.5
2002
25.8
17.3
8.5
7.7
7.7
33.5
2003
25.6
17.2
8.4
7.8
7.8
33.4
2004
25.7
17.1
8.5
7.9
7.9
33.6
2005
25.4
17.0
8.4
8.0
8.0
33.4
* Industrial activity includes the pulp and paper; meat and poultry; and vegetables, fruits, and juices processing industries.
Note: Totals may not sum due to independent rounding.
Table 8-7: CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
CH4
Domestic
Industrial*
N20
Domestic
1990
1,180
826
354
21
21
1995
1,195
797
398
22
22
2000
1,257
842
415
24
24
2001
1,232
832
400
25
25
2002
1,229
826
402
25
25
2003
1,220
820
400
25
25
2004
1,222
815
407
26
26
2005
1,210
809
400
26
26
* Industrial activity includes the pulp and paper; meat and poultry; and vegetables, fruits, and juices processing industries.
Note: Totals may not sum due to independent rounding.
Methodology
Domestic and industrial Wastewater CH4 Emission Estimates
Domestic wastewater CH4 emissions originate from
both septic systems and from centralized treatment systems,
such as publicly owned treatment works (POTWs). Within
these centralized systems, CH4 emissions can arise from
aerobic systems that are not well managed, anaerobic
systems (anaerobic lagoons and facultative lagoons), and
from anaerobic digesters when the captured biogas is not
completely combusted. CH4 emissions from septic systems
were estimated by multiplying the total BOD5 produced in
the United States by the percent of wastewater treated in
septic systems (21 percent), the maximum CH4-producing
capacity for domestic wastewater (0.60 kg CH4/kg BOD),
and the CH4 correction factor (MCF) for septic systems (0.5).
CH4 emissions from POTWs were estimated by multiplying
the total BOD, produced in the United States by the percent
of wastewater treated centrally (79 percent), the relative
percentage of wastewater treated by aerobic and anaerobic
systems, the maximum CH4-producing capacity of domestic
wastewater, and the relative MCFs for aerobic (zero or 0.3)
and anaerobic (0.8) systems. CH4 emissions from anaerobic
digesters were estimated by multiplying the amount of biogas
generated by wastewater sludge treated in anaerobic digesters
by the proportion of CH4 in digester biogas, the density of
CH4, and the destruction efficiency associated with burning
the biogas in an energy/thermal device.7 The methodological
equations are:
/ ;-;.'-s"!'/(•. jroin St'/i/ii Si \!i"in\ ~ .\
•'M( '!•• septic ! - i i'lAf>
/-..w/s s <(•;/; ^ in/in ( <•<;//'hi< .SY.wcw.s --- H
~(''i L(v|k'i tod/ ' (intai B( )P. j)ioducc(l) ;-. ('.;< acrohici •<
('( !i!>erat!OMs not ucll managed) •• (B,,) x
'. M< \ aoiobu'-ilo! v. ol! man) - I |0A6
/•,/.'!/.V\ '•>!!•• /I'li/ll ( \-IUI\lII\ /r, i .','<"./ \>h/l-K>l>!( ,SVA/(V/,'A =' (
~ ('•> L-Mllocli'di ' itoial BOD, piouiu od) -. ; '•< anaerobic) x
i B i > i M('!; anacr, ihu ' < 1 10-^6
loiai C'H. l-'missions ((\^i - \ + B 4- (' + I)
where,
'••< onsiii ---- l-!o\\ 10 scjitti svsiems.total tloxv
'*' i.viik''.:;etl -_- Mow to l;'()l'\\\,totalllo\\
7 Anaerobic digesters at wastewater treatment plants generated 799 Gg CH4 in 2005, 791 Gg of which was combusted in flares or energy devices
(assuming a 99% destruction efficiency).
Waste 8-7
-------
17< aerobic =
',i anaerobic =
''< operations
not \\ell
managed
Total BOD-,
produced
MCF-septic =
MCF-
aeruhicjun,
well man.
MCF-
anaerobic
DH
diiiester iia
per capita
How
0.02 S3
FRAC_.CHj
densiu of
CM;
Mow to aerobic s\ stems'total llou
to POTWs
Flow to anaerobic systems'tola I
How to POTWs
Perccni of aerobic systems that arc-
not well managed and in which
Some anaerobic dei.'rada'ion occurs
kg BOl)/capita/da> x I' S.
population x 365.2^ davv\r
Maximum C'H4 producing capacity
tor domeslic \vasL">vater (0.60 kg
CHAi:. BOD>
= ( V-iuersKin lactoi, ks.: to (iu
CH4 correction factor tor aeiohic
systems that arc not wel' rianaL'Cil
(0.3)
CM4 correction facior lor anaerobic
systems (O.S)
CM.) destruction er'ticietKA from
flaring or burning in engine (0.c'9
for enclosed Hares)
Wasteuater inlluei)' l!ov toPOTW-
that have anaerobic diuc-.'.ers (siai)
VV,iste\vater tlo\\ 10 I'OTW per
person per day • IOM gal nerson tl:i\
U.S. population data were taken from the U.S. Census
Bureau International Database (U.S. Census 2006a) and
include the populations of the United States, American
Samoa, Guam, Northern Mariana Islands, Puerto Rico,
and the Virgin Islands. Table 8-8 presents U.S. population
and total BOD, produced for 1990 through 2005. The
proportions of domestic wastewater treated onsite versus
at centralized treatment plants were based on data from the
1993, 1995, 1997, 1999, 2001, 2003, and 2005 American
Housing Surveys conducted by the U.S. Census Bureau
(U.S. Census 2006b), with data for intervening years
obtained by linear interpolation. The wastewater flow to
aerobic systems and anaerobic systems, and the wastewater
flow to POTWs that have anaerobic digesters were obtained
from the 1992, 1996, 2000, and 2004 Clean Watershed
Needs Survey, collected by EPA (EPA 1992, 1996, 2000,
and 2004a).8 Data for intervening years were obtained by
linear interpolation. The BOD5 production rate per capita
(0.09 kg/capita/day) for domestic wastewater was obtained
from Metcalf and Eddy (1991 and 2003). The CH4 emission
factor (0.6 kg CH4/kg BOD5) and the MCF data were taken
from IPCC (2006a). The CH4 destruction efficiency, 99
percent, was selected based on the range of efficiencies
(98-100 percent) recommended for flares in EPA's "AP-42
Compilation of Air Pollutant Emission Factors, Chapter
2.4,'" (EPA 1998) efficiencies used to establish new
source performance standards (NSPS) for landfills, and in
recommendations for closed flares used in the LMOP. The
Table 8-8: U.S. Population (Millions) and Domestic
Wastewater BOD5 Produced (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Population
254
271
287
289
292
295
297
300
BOD5
8,350
8,895
9,419
9,509
9,597
9,685
9,774
9,864
Source: U.S. Census Bureau (2006a); Metcalf & Eddy 1991 and 2003.
8 Aerobic and anaerobic treatment were determined based on unit processes in use at the facilities. Because the list of unit processes became
more extensive in the 2000 and 2004 surveys, the criteria used to identify aerobic and anaerobic treatment differ slightly across the time series.
Once facilities were identified as aerobic or anaerobic, they were separated by whether or not they had anaerobic digestion in place. Once these
classifications were determined, the flows associated with facilities in each category were summed.
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
cubic feet of digester gas produced per person per day (1.0
ft3/person/day) and the proportion of CH4 in biogas (0.65)
come from Metcalf and Eddy 1991. The wastewater flow
to a POTW per person per day (100 gal/person/day) was
taken from the Great Lakes-Upper Mississippi River Board
of State and Provincial Public Health and Environmental
Managers, "Recommended Standards for Wastewater
Facilities (Ten-State Standards)" (2004).
CH4 emissions estimates from industrial wastewater
were developed according to the methodology described in
IPCC (2006a). Industry categories that are likely to produce
significant CH4 emissions from wastewater treatment were
identified. High volumes of wastewater generated and a
high organic wastewater load were the main criteria. The top
three industries that meet these criteria are pulp and paper
manufacturing; meat and poultry processing; and vegetables,
fruits, and juices processing. Table 8-9 contains production
data for these industries.
CH4 emissions from these categories were estimated by
multiplying the annual product output by the average outflow,
the organics loading (in COD) in the outflow, the percentage
of organic loading assumed to degrade anaerobically, and the
emission factor. Ratios of BOD:COD in various industrial
wastewaters were obtained from the World Bank (1999) and
used to estimate COD loadings. The B0 value used for all
industries is the IPCC default value of 0.25 kg CH4/kg COD
(IPCC 2006a). The methodological equation is:
ill, MlldhMi'Mi ,. avev.ak' ~ i' \V .< (('( )|)i •
i"\ • i! , \K'i
where,
W
liulustrv output (metric ions/year)
Wastcwatcr I'enciated ( nr'/metric ton of
prod i ict I
( trsjaiiics loading in \vuste\\ater (kg/m ')
Percent ol \vasic\\,iter treated
anaerobicalK on Mte
(.'H, conei tion factor. indicatiii.L'
the exteni lo \\ nidi I he organic
eonleni inicasuivJ as ( ()!)) degrades
anaeiobict
Wastewater treatment for the pulp and paper industry
typically includes neutralization, screening, sedimentation,
and flotation/hydrocycloning to remove solids (World Bank
1999, Nemerow and Dasgupta 1991). Secondary treatment
(storage, settling, and biological treatment) mainly consists
of lagooning. In determining the percent that degrades
anaerobically, both primary and secondary treatment were
considered. Primary treatment lagoons are aerated to reduce
anaerobic activity. However, the lagoons are large and zones
of anaerobic activity may occur and, consequently, the primary
lagoons are assumed to be 1 .4 percent anaerobic (based on
expert judgment). Approximately 42 percent of the BOD passes
on to secondary treatment, which is less likely to be aerated
(EPA 1 993a,b). Twenty-five percent of the BOD in secondary
treatment lagoons was assumed to degrade anaerobically,
while 10 percent passes through to be discharged with the
effluent (EPA 1997a). Consequently, the overall percentage
of wastewater organics that degrade anaerobically was
determined to be 1 0.3 percent (i.e., 58 percent x 1 .4 percent +
42 percent x 90 percent x 25 percent). A time series of CH4
emissions for 1990 through 2001 was developed based on
Table 8-9: U.S. Pulp and Paper; Meat and Poultry; and Vegetables, Fruits, and Juices Production (Tg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Pulp and Paper
128.9
140.9
142.8
134.3
132.7
131.9
136.4
131.4
Meat
(Live Weight Killed)
27.3
30.8
32.1
31.6
32.7
32.3
31.2
31.4
Poultry
(Live Weight Killed)
14.6
18.9
22.2
22.8
23.5
23.7
24.4
25.1
Vegetables, Fruits
and Juices
40.5
49.0
52.7
46.7
49.1
46.2
49.1
43.6
Waste 8-9
-------
production figures reported in the Lockwood-Post Directory
(Lockwood-Post 2002). Published data from the American
Forest and Paper Association (AF&PA) and data published by
Paper Loop were used to estimate production for 2002 through
2005 (Pulp and Paper 2005,2006 and monthly reports from
2003-2006). The overall wastewater outflow was estimated
to be 85 m3/metric ton, and the average BOD loading entering
the secondary treatment lagoons was estimated to be 0.4 gram
BOD/liter (EPA 1997b, EPA 1993a,b, World Bank 1999).
The meat and poultry processing industry makes extensive
use of anaerobic lagoons in sequence with screening, fat traps
and dissolved air flotation when treating wastewater on site.
About 33 percent of meat processing operations (EPA 2002)
and 25 percent of poultry processing operations (U.S. Poultry
2006) perform on-site treatment in anaerobic lagoons. The
IPCC default B0 of 0.25 kg COD/kg CH4 and default MCF
of 0.8 for anaerobic lagoons were used to estimate the CH4
produced from these on-site treatment systems. Production
data, in carcass weight and live weight killed for the meat and
poultry industry, were obtained from the USDA Agricultural
Statistics Database and the Agricultural Statistics Annual
Reports (USDA 2006). Data collected by EPAs Office of
Water provided estimates for wastewater flows into anaerobic
lagoons: 5.3 and 12.5 nrVmetric ton for meat and poultry
production (live weight killed), respectively (EPA 2002). The
loadings are 2.8 and 1.5 g BOD/liter for meat and poultry,
respectively.
Treatment of wastewater from fruits, vegetables, and
juices processing includes screening, coagulation/settling and
biological treatment (lagooning). The flows are frequently
seasonal, and robust treatment systems are preferred for on-
site treatment. Effluent is suitable for discharge to the sewer.
This industry is likely to use lagoons intended for aerobic
operation, but the large seasonal loadings may develop limited
anaerobic zones. In addition, some anaerobic lagoons may
also be used (Nemerow and Dasgupta 1991). Consequently, 5
percent of these wastewater organics are assumed to degrade
anaerobically. EPA used the IPCC default B0 of 0.25 kg
COD/kg CH4 and default MCF of 0.8 for anaerobic treatment
to estimate the CH4 produced from these on-site treatment
systems. The USDA National Agricultural Statistics Service
Table 8-10: Wastewater Flow (m3/ton) and BOD Production
(g/L) for U.S. Vegetables, Fruits and Juices Production
Wastewater Outflow
Commodity (m3/ton)
Vegetables
Potatoes
Other Vegetables
Fruit
Apples
Citrus
Non-citrus
Grapes (for wine)
10.27
8.64
3.66
10.11
11.7
1.53
BOD (g/L)
1.765
0.817
1.317
0.317
0.982
2.346
(USDA 2006) provided production data for potatoes, other
vegetables, citrus fruit, non-citrus fruit, and grapes processed
for wine. Outflow and BOD data, presented in Table 8-10,
were obtained from EPA (1974) for potato, citrus fruit, and
apple processing, and from the World Bank (1999) for all
other sectors.
Domestic Wastewater N20 Emission Estimates
N2O emissions from domestic wastewater (wastewater
treatment) were estimated using the updated IPCC (2006)
methodology, including calculations that take into account N
removal with sewage sludge, non-consumption and industrial
wastewater N, and emissions from advanced centralized
wastewater treatment plants:
• In the United States, a certain amount of N is removed
with sewage sludge, which is applied to land, incinerated
or landfilled (NSLUDGE). The N disposal into aquatic
environments is reduced to account for the sewage
sludge application.9
• The IPCC methodology uses annual, per capita protein
consumption (kg protein/[person-year]). This number is
likely to underestimate the amount of protein entering
the sewer or septic system. Food (waste) that is not
consumed is often washed down the drain, as a result
of the use of garbage disposals. Also, bath and laundry
water can be expected to contribute to N loadings.
As a result, a factor of 1.4 for non-consumption N is
introduced for each year in the Inventory.10 Furthermore,
a significant quantity of industrial wastewater (N) is
9 The methodology for estimating the quantity of sewage sludge N not entering aquatic environments is described in Annex 3.11
10 Metcalf & Eddy (1991) provide a typical influent nitrogen concentration of 40 mg/L Total Kjeldahl Nitrogen (TKN) for average wastewater
from residences, which includes bathwater, laundry, and the use of garbage disposals. The factor for non-consumptive protein was estimated based
on wastewater treated in 1990, the percent of population serviced by centralized treatment systems, and the per capita TKN loading, resulting in a
factor of 1.4.
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 19UO--2005
-------
co-discharged with domestic wastewater. To account
for this, a factor of 1 .25 is used."
• Small amounts of gaseous nitrogen oxides are formed
as by-products in the conversion of nitrate to N gas in
anoxic biological treatment systems. Approximately 7
grams N2O is generated per capita per year if wastewater
treatment includes nitrification and denitrification
(Scheehle and Doom 2001). Analysis of the 2000 CWNS
shows 88 treatment plants in the United States, serving
a population of 2,636,668 persons, with denitrification
as one of their unit operations. Based on an emission
factor of 7 grams/capita/year, approximately 17.5 metric
tons of additional N2O may have been emitted via
denitrification in 2000. Similar analysis was done for
each year in the Inventory using data from CWNS on
the amount of wastewater in centralized systems treated
in denitrification units.
With the modifications described above, N2O emissions
from domestic wastewater were estimated using the
following methodology:
N .() emissions from
u ;isto\\ ator eftluent discharged
h> a|ii;itk em'irunmenls
where,
I1 S, p.tipulalinn thai is served
h\ biological Jonitrilicalion
tioni r\\ NS)
l-raeiioii ot population usiny
V\ \V"1 P i as opposed to septic
s\ sie'i's i
U.S. population data were taken from the U.S. Census
Bureau International Database (U.S. Census 2006a) and
include the populations of the United States, American
Samoa, Guam, Northern Mariana Islands, Puerto Rico,
and the Virgin Islands. The fraction of the U.S. population
using wastewater treatment plants is based on data from the
1993,1995,1997,1999,2001, and 2003 American Housing
Survey (U.S. Census 2006b). Data for intervening years
were obtained by linear interpolation. The emission factor
(EF,) to estimate emissions from wastewater treatment
was taken from IPCC (2006a). Data on annual per capita
protein intake were provided by the United Nations Food
and Agriculture Organization for the 1990 to 2003 time
frame (FAO 2006). Protein consumption data for 2004 and
11 The type, composition, and quantity of this co-discharged wastewater vary greatly between municipalities. Metcalf & Eddy (1991) provide a range
of influent nitrogen concentrations of 20 to 85 mg/L TKN (average 55) for combined residential and industrial wastewater, while residential wastewater
loading was roughly estimated at 40 mg TKN/liter (see previous footnote). Until better data become available, the amount of N in wastewater is
increased by 10 mg/L to account for industrial co-discharge (factor of 1.25).
Waste 8-11
-------
Table 8-11: U.S. Population (Millions) and Average
Protein Intake [kg/(person-year)]
Year
1990
1995
2000
2001
2002
2003
2004
2005
Population
254
271
287
289
292
295
297
300
Protein
39.2
40.0
41.6
41.3
41.3
41.7
41.9
42.1
Source: U.S. Census Bureau (2006a), FAO (2006).
2005 were extrapolated from data for 1990 through 2003.
Table 8-11 presents the data for U.S. population and average
protein intake. An emission factor to estimate emissions
from effluent (EF3) has not been specifically estimated for
the United States, thus the newly-revised default IPCC value
(0.005 kg N2O-N/kg sewage-N produced) was applied. The
fraction of N in protein (0.16 kg N/kg protein) was also
obtained from IPCC (2006). An estimate for the nitrogen
removed as sludge (NSLUDGE) was obtained by determining
the amount of sludge disposed by incineration, by land
application (agriculture or other), through surface disposal,
in landfills, or through ocean dumping.
Uncertainty
The overall uncertainty associated with both the 2005
CH4 and N2O emissions estimates from wastewater treatment
and discharge was calculated using the IPCC Good Practice
Guidance Tier 2 methodology (2000). Uncertainty associated
with the parameters used to estimate CH4 emissions included
that of numerous input variables used to model emissions
from domestic wastewater, and wastewater from the pulp
and paper industry, meat and poultry processing, as well as
from fruits, vegetables and juices processing. Uncertainty
associated with the parameters used to estimate N2O
emissions included that of sewage sludge disposal, total U.S.
population, average protein consumed per person, fraction
of N in protein, non-consumption nitrogen factor, emission
factors per capita and per mass of sewage-N, and for the
percentage of total population using centralized wastewater
treatment plants.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 8-12. CH4 emissions from
wastewater treatment were estimated to be between 15.8 and
37.3 Tg CO2 Eq. at the 95 percent confidence level (or in 19
out of 20 Monte Carlo Stochastic Simulations). This indicates
a range of approximately 38 percent below to 47 percent
above the 2005 emissions estimate of 25.4 Tg CO2 Eq. N2O
emissions from wastewater treatment were estimated to be
between 1.7 and 15.4 Tg CO2 Eq., which indicates a range
of approximately 79 percent below to 93 percent above the
actual 2005 emissions estimate of 8.0 Tg CO2 Eq.
Recalculations Discussion
The 2005 estimates for CH4 emissions from domestic
wastewater include two major methodological refinements
and one major data change. First, CH4 emissions were
estimated from four distinct source categories (septic
systems, centrally treated aerobic systems, centrally treated
anaerobic systems, and anaerobic digesters) rather than
calculating an overall percentage of wastewater treated
anaerobically from which to calculate emissions. Calculating
emissions from anaerobic digesters constitutes the second
methodological refinement to the Inventory. Emissions
from anaerobic digesters were included to account for the
increasing number of facilities that produce and use digester
Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Wastewater Treatment
(Tg C02 Eq. and Percent)
Source
Gas
2005 Emission Estimate
(Tg C02 Eg.)
Uncertainty Range Relative to Emission Estimate3
(TgC02Eq.) (%)
Wastewater Treatment
Domestic
Industrial
Domestic Wastewater
Treatment
CH4
CH4
CH4
N20
25.4
17.0
8.4
8.0
Lower Bound
15.8
8.6
4.6
1.7
Upper Bound
37.3
28.2
13.5
15.4
Lower Bound
-38%
-49%
-45%
-79%
Upper Bound
+47%
+66%
+60%
+93%
' Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
biogas. The major data adjustment for the current inventory
estimates involves the BOD per capita rate. In previous
inventories, the BOD per capita rate varied across the time
series. However, the 2005 estimates employ a standard value
for the BOD per capita rate (0.09 kg/capita/day). This change
resulted in varying differences in emissions estimates over
time, ranging from an increase of 52 percent (1990) to a
decrease of 15 percent (2004).
For industrial wastevvater, production data for the entire
time series were updated and other factors, such as wastewater
outflow, BOD, and percent of waste treated anaerobically,
were revised. Production data for potato processing, which
accounts for about 45 percent of all vegetable processing
in the United States, and about 25 percent of all fruit and
vegetable processing, had not been included in previous
inventories. However, the increase in industrial wastewater
emissions due to the inclusion of potatoes was offset by
other changes made to the Inventory. Flow and BOD data
for fruits and vegetable processing wastewater were updated
to reflect commodity-specific data, which resulted in a
decrease in emissions. In addition, the amount of meat and
poultry processing wastewater treated on site anaerobically
was substantially revised. Previously, it was assumed that
all wastewater from meat and poultry processing was
treated anaerobically. However, data from EPA's Office of
Water and from U.S. Poultry and Egg Association became
available to show that indirect dischargers do not treat
wastewater anaerobically. Therefore, the percent of waste
treated anaerobically was reduced (to 33 percent for meat
processors and 25 percent for poultry processors), which
resulted in a significant decrease in emission estimates.
These changes resulted in overall decreases of industrial
wastewater emissions between 45 and 50 percent across
the time series.
Overall, the CH4 emission estimates for wastewater
treatment are on average 17 percent lower than the previous
Inventory.
For N2O emissions from domestic wastewater, minor
changes were made to the time series to include more
specific estimates of the percent of U.S. population using
centralized wastewater treatment, and a factor was introduced
to account for the amount of biological denitrification
occurring at centralized treatment plants. The calculation
estimates for protein consumed were updated for the entire
time series. These improvements resulted in minor decreases
to the emission estimates across the time series, from 3 to
4 percent.
Finally, the default factor for N2O emissions from N
in effluent discharged to aquatic environments was updated
from 0.01 to 0.005 kg N2O -N/kg sewage-N, which resulted
in a decrease of approximately 50 percent in emission
estimates over the time series compared to the previous
Inventory. The effect of all changes was an overall decrease
in emission estimates from 50.1 to 51.4 percent across the
time series.
Overall, emissions from wastewater treatment and
discharge (CH4 and N2O) decreased by an average of 28
percent from the previous Inventory.
Planned Improvements Discussion
The methodology to estimate CH4 emissions from
domestic wastewater treatment currently utilizes estimates
for the percentage of centrally treated wastewater that is
treated by aerobic systems and anaerobic systems. These
data come from the 1992, 1996, 2000, and 2004 CWNS.
The designation of systems as aerobic or anaerobic could
be further refined to differentiate aerobic systems with the
potential to generate small amounts of CH4 (aerobic lagoons)
versus other types of aerobic systems, and to differentiate
between anaerobic systems to allow for the use of different
MCFs for different types of anaerobic treatment systems.
Currently it is assumed that all aerobic systems are well
managed and produce no CH4, and that all anaerobic systems
have an MCF of 0.8. Efforts to obtain better data are currently
being pursued.
Currently, BOD removal is not explicitly included in
inventory calculations. The appropriateness of including
a factor to account for BOD that is not removed through
treatment and therefore does not contribute to CH4 emissions
is being investigated.
The methodology to estimate emissions for industrial
wastewater currently accounts for pulp and paper, meat and
poultry processing, and fruits and vegetables processing
wastewater treatment. Information is currently being
collected on ethanol production in the United States to
determine if this should be included in future Inventories.
With respect to estimating N2O emissions, the default
emission factor for N2O from wastewater effluent has a high
uncertainty. The IPCC recently updated this factor; however,
Waste 8-13
-------
future research may identify new studies that include updated
data. The factor that accounts for non-sewage nitrogen in
wastewater (bath, laundry, kitchen, industrial components)
also has a high uncertainty. Obtaining data on the changes
in average influent nitrogen concentrations to centralized
treatment systems over the time series would improve the
estimate of total N entering the system, which would reduce
or eliminate the need for other factors for non-consumed
protein or industrial flow. In addition, more research may be
conducted to update the protein consumption data.
8.3. Waste Sources of Indirect
Greenhouse Gases
In addition to the main greenhouse gases addressed
above, waste generating and handling processes are also
sources of indirect greenhouse gas emissions. Total emissions
of NOX, CO, and NMVOCs from waste sources for the years
1990 through 2005 are provided in Table 8-13.
Methodology
These emission estimates were obtained from
preliminary data (EPA 2006), and disaggregated based on
EPA (2003), which, in its final iteration, will be published
on the National Emission Inventory (NEI) Air Pollutant
Emission Trends web site. Emission estimates of these
gases were provided by sector, using a "top down"
estimating procedure —emissions were calculated either
for individual sources or for many sources combined,
using basic activity data (e.g., the amount of raw material
processed) as an indicator of emissions. National activity
data were collected for individual source categories from
various agencies. Depending on the source category, these
basic activity data may include data on production, fuel
deliveries, raw material processed, etc.
Activity data were used in conjunction with emission
factors, which relate the quantity of emissions to the activity.
Emission factors are generally available from the EPA's
Compilation of Air Pollutant Emission Factors, AP-42 (EPA
1997). The EPA currently derives the overall emission control
efficiency of a source category from a variety of information
sources, including published reports, the 1985 National Acid
Precipitation and Assessment Program emissions inventory,
and other EPA databases.
Uncertainty
No quantitative estimates of uncertainty were calculated
for this source category. Uncertainties in these estimates,
however, are primarily due to the accuracy of the emission
factors used and accurate estimates of activity data.
Table 8-13: Emissions of NOX, CO, and NMVOC from Waste (Gg)
Gas/Source
NO,
Landfills
Wastewater Treatment
Miscellaneous3
CO
Landfills
Wastewater Treatment
Miscellaneous3
NMVOCs
Wastewater Treatment
Miscellaneous3
Landfills
1990
+
+
+
+
1
1
+
+
673
57
558
58
1995
1
1
+
1
2
2
+
1
731
61
602
68
2000
2
2
+
+
8
7
1
+
119
51
46
23
2001
2
2
+
+
8
7
1
+
122
53
46
23
2002
2
2
+
+
7
6
+
+
116
50
44
22
2003
2
2
+
+
7
6
+
+
116
50
44
22
2004
2
2
+
+
7
6
+
+
116
50
44
22
2005
2
2
+
+
7
7
+
+
116
50
44
22
a Miscellaneous includes TSDFs (Treatment, Storage, and Disposal Facilities underthe Resource Conservation and Recovery Act [42 U.S.C. § 6924, SWDA
§ 3004]) and other waste categories.
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg.
8-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
9. Other
The United States does not report any greenhouse gas emissions under the "other" Intergovernmental Panel on Climate
Change (IPCC) sector.
Other 9-1
-------
-------
10. Recalculations and
Improvements
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse
Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the use of
better methods or data, and the overall usefulness of the report. In this effort, the United States follows the
Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (IPCC 2000), which states, "It is good
practice to recalculate historic emissions when methods are changed or refined, when new source categories are included
in the national inventory, or when errors in the estimates are identified and corrected."
The results of all methodology changes and historical data updates are presented in this section; detailed descriptions of
each recalculation are contained within each source's description contained in this report, if applicable. Table I0-l summarizes
the quantitative effect of these changes on U.S. greenhouse gas emissions and Table 10-2 summarizes the quantitative effect
on U.S. sinks, both relative to the previously published U.S. Inventory (i.e., the 1990 through 2004 report). These tables
present the magnitude of these changes in units of teragrams of carbon dioxide equivalent (Tg CO2 Eq.). In addition to the
changes summarized by the tables below, the following sources and gases were added to the current Inventory:
• methane (CH4) emissions from Ferroalloy Production;
• CH4 and nitrous oxide (N2O) emissions from Forest Land Remaining Forest Land to account for emissions from
forest fires;
• CO2 emissions from Silicon Carbide Production; and
• CH4 emissions from Silicon Carbide Consumption.
The Recalculations Discussion section of each source presents the details of each recalculation. In general, when
methodological changes have been implemented, the entire time series (i.e., 1990 through 2004) has been recalculated to
reflect the change, per IPCC (2000). Changes in historical data are generally the result of changes in statistical data supplied
by other agencies.
The following emission sources, which are listed in descending order of absolute average annual change in emissions
between 1990 and 2004, underwent some of the most important methodological and historical data changes. A brief summary
of the recalculation and/or improvement undertaken is provided for each emission source.
• Agricultural Soil Management. Changes occurred as a result of (1) modifying nitrogen (N) inputs to be consistent with
the agricultural soil carbon (C) inventory, (2) modeling within-county variation in soil characteristics and weather, and
(3) incorporating revised methods and emission factors from IPCC (2006). Overall, changes resulted in an average
annual increase in N2O emissions from agricultural soil management of 90.4 Tg CO2 Eq. (33 percent) for the period
1990 through 2004.
Recalculations and Improvements 10-1
-------
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Uses of Fossil Fuels
Natural Gas Systems
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
C02 Consumption
Municipal Solid Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloy Production
Ammonia Production and Urea
Application
Phosphoric Acid Production
Petrochemical Production
Silicon Carbide Production and
Consumption
Lead Production
Zinc Production
Net C02 Flux from Land Use, Land-Use
Change, and Forestry
International Bunker Fuels3
Wood Biomass and Ethanol
Consumption*
CH4
Stationary Combustion
Mobile Combustion
Coal Mining
Abandoned Underground Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production and
Consumption
Iron and Steel Production
Ferroalloy Production"
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
Forest Land Remaining Forest Landb
Landfills
Wastewater Treatment
International Bunker Fuels3
N20
Stationary Combustion
Mobile Combustion
Adipic Acid Production
Nitric Acid Production
Manure Management
Agricultural Soil Management
Field Burning of Agricultural Residues
Wastewater Treatment
N20 Product Usage
Municipal Solid Waste Combustion
Settlements Remaining Settlements
Forest Land Remaining Forest Land
1990
56.4
27.6
0.1
27.9
NC
+
+
NC
0.6
+
NC
(0.2)
+
0.2
NC
NC
NC
0.3
NC
+
197.4
0.2
2.6
(9-0)
0.2
+
+
NC
(2.3)
+
(0.3)
NC
NC
+
(2.2)
(0.3)
NC
+
7.1
(11.3)
+
NC
87.1
+
0.3
NC
NC
(7.6)
100.8
+
(6.5)
NC
NC
(0.5)
0.7
1995
59.3
33.3
0.4
24.8
NC
+
NC
NC
0.6
+
NC
(0.2)
+
0.2
NC
NC
NC
0.2
NC
+
(213.6)
+
(5.1)
(10.3)
(0.3)
+
0.7
NC
+
+
(0.4)
NC
NC
+
(2.4)
(1.0)
NC
+
4.0
(6.2)
(4.8)
NC
30.0
(0.1)
0.3
NC
NC
(8.1)
45.3
+
(7.3)
NC
NC
(0.4)
0.4
2000
75.5
51.2
0.3
23.6
NC
+
NC
NC
0.5
+
NC
(0.2)
(0.2)
0.2
+
NC
NC
0.1
NC
+
2.8
(0.2)
1.5
(3.3)
0.1
+
(0.4)
0.1
(0.1)
+
(0.5)
NC
NC
+
(2.2)
0.7
NC
+
14.0
(7.1)
(7.9)
NC
83.6
+
0.1
NC
NC
(8.3)
98.6
+
(7.9)
NC
NC
(0.4)
1.4
2001
47.8
24.8
0.3
22.7
NC
+
NC
NC
+
(0.3)
NC
(0.1)
0.1
0.1
+
NC
NC
0.1
NC
+
0.5
(0.3)
2.7
(12.6)
0.2
(0.1)
+
0.1
(0.2)
+
(0.4)
NC
NC
+
(2.2)
1.3
NC
+
6.0
(8.5)
(8.8)
NC
89.7
+
(0.2)
NC
NC
(8.3)
106.0
+
(8.0)
NC
(0.1)
(0.4)
0.6
2002
76.9
55.5
(1.1)
23.4
NC
+
NC
NC
+
(0.3)
NC
(0.1)
+
0.1
(0.7)
NC
NC
0.1
NC
+
(43.3)
(0.4)
10.0
(10.1)
0.6
(0.1)
(0.5)
0.1
(0.4)
+
(0.4)
NC
NC
+
(2.1)
1.8
NC
+
10.4
(9.4)
(10.0)
NC
71.8
0.2
(0.4)
NC
+
(8.3)
88.3
+
(8.0)
(0.5)
(0.1)
(0.4)
1.0
2003
74.9
53.4
(2.2)
22.4
NC
+
NC
NC
+
0.1
NC
(0.1)
+
0.1
0.9
NC
NC
0.1
NC
+
(37.1)
(0.4)
7.5
(15.1)
0.5
(0.2)
(2.8)
0.1
(1.0)
(0.1)
(0.4)
NC
NC
+
(2.1)
1.3
+
+
8.1
(7.5)
(11.0)
NC
73.7
0.1
(1.0)
NC
NC
(8.2)
91.0
+
(8.0)
(0.5)
(0.1)
(0.4)
0.8
2004
76.3
56.5
(3.2)
22.2
+
+
NC
NC
+
0.8
NC
(0.1)
+
0.1
+
NC
NC
0.1
NC
+
(44.7)
2.7
13.6
(16.5)
0.7
(0.2)
(1.8)
0.1
0.2
(0.3)
(0.5)
NC
NC
+
(2.1)
0.3
+
+
6.9
(8.8)
(11.3)
+
58.5
0.2
(1.6)
NC
(0.6)
(8.3)
77.3
+
(8.1)
(0.5)
(0.1)
(0.5)
0.7
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.) (continued)
Gas/Source
International Bunker Fuels3
MFCs, PFCs, and SF6
Substitution of Ozone Depleting
Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Electrical Transmission and Distribution
Magnesium Production and Processing
Net Change in Total Emissions3
Percent Change
1990
NC
(1.4)
(0.1)
0.1
NC
NC
(1.5)
NC
133.1
6.4%
1995
we
8.6
8.1
(0.1)
NC
NC
0.6
NC
87.7
-2.1%
2000
NC
9.1
9.7
(0.4)
NC
NC
(0.1)
(0.2)
164.9
2.7%
2001
NC
8.9
9.9
(0.5)
NC
NC
(0.3)
(0.2)
133.8
2.2%
2002
NC
10.3
10.7
+
NC
NC
(0.2)
(0.2)
148.8
1.7%
2003
NC
11.6
12.0
+
NC
NC
(0.2)
(0.1)
145.1
1.7%
2004
+
10.9
11.2
+
NC
NC
(0.2)
(0.1)
129.2
1.3%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
a Totals exclude net C02 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and Wood Biomass
and Ethanol Consumption.
b New source category relative to previous Inventory.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values or net sequestration.
Table 10-2: Revisions to Net Flux of C02 to the Atmosphere from Land Use, Land-Use Change, and Forestry
(Tg C02 Eq.)
Component: Net C02 Flux From Land
Use, Land-Use Change, and Forestry
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements
Other
Net Change in Total Flux
Percent Change
1990
174.9
5.0
7.2
4.6
3.1
25.7
(22.8)
197.6
21.7%
1995
(228.9)
(11.0)
10.0
8.8
4.8
15.7
(13.3)
(213.9)
-34.8%
2000
(7.7)
(10.4)
10.0
8.8
4.8
7.7
(10.5)
2.8
0.4%
2001
(11.7)
(10.3)
10.0
8.9
4.8
9.5
(10.6)
0.5
0.1%
2002
(53.5)
(10.3)
10.0
8.9
4.8
7.6
(10.8)
(43.3)
-5.6%
2003
(51.2)
(9.6)
10.0
8.9
4.8
9.4
(9.3)
(37.1)
-4.8%
2004
(60.1)
(10.4)
10.0
8.9
4.8
10.9
(8.7)
(44.7)
-5.7%
Note: Numbers in parentheses indicate a decrease in estimated net flux of C02 to the atmosphere, or an increase in net sequestration.
Note: Totals may not sum due to independent rounding.
Net CO2 Flux from Land Use, Land-Use Change, and for the period 1990 through 2004. However, the most
Forestry. Influential changes in the Land Use, Land-Use consequential changes from these recalculations
Change, and Forestry sector occurred in calculations occurred in 1990, which saw a 197.6 Tg CO2 Eq. (21.7
for forest C stock and flux estimates. Changes for the percent) decrease in estimated sequestration.
period 1990 through 2004, as compared to the estimates . Co2frOm Fossil Fuel Combustion. The most important
presented in the previous Inventory, are based on the update mat affected the historical estimates for CO2
cumulative effects of (1) incorporating additional state emissions from fossil fuel combustion was the change
and sub-state inventory data, and (2) adjusting total to the c oxidation factor for all fuel types to 100
stock estimates used in earlier years to account for percent TMs change was made according to IPCC
inclusion or removal of different ecological community (2006) and impacted emission estimates for all fuel
types in subsequent state and sub-state inventory years. types Additionally, silicon carbide used for petroleum
Overall, these changes, in combination with adjustments coke manufacturing was reallocated to the Industrial
in the other sources/sinks within the sector, resulted in Processes chapter. Overall, changes resulted in an
an average annual decrease in net flux of CO2 to the averageannualincreaseof36.9TgCO2Eq.(0.7percent)
atmosphere from the Land Use, Land-Use Change, in cc,2 emissions from fossil fuel combustion for the
and Forestry sector of 38.3 Tg CO2 Eq. (7 percent) period 1990 through 2004
Recalculations and Improvements 103
-------
• Natural Gas Systems. The Inventory now contains
estimates for non-combustion-related (vented, fugitive,
flared) CO2 emissions from the natural gas industry.
The estimation uses the same activity and emission
factors from the CH4 emission estimates but adjusts
the emission factors for the ratio of CO2/CH4 content of
the natural gas. Efforts were made to ensure that there
was no double-accounting of CO2 emissions from other
system inventories in the overall Inventory. Overall,
changes resulted in an average annual increase in CO2
emissions from natural gas systems of 24.4 Tg CO2 Eq.
(376 percent) for the period 1990 through 2004.
• Manure Management. A few changes have been
incorporated into the overall methodology for the manure
management emission estimates. State temperatures
are now calculated using data from every county in the
state. Another major change in methodology was using
climate-specific CH4 conversion factors for dry manure
management systems. The percentage of dairy cattle, swine,
and sheep on each type of manure management system was
also updated for the current Inventory, based on farm size
data from the 2002 USDA Census of Agriculture (USD A
2005e). Changes were also made to the current calculations
involving animal population data. N2O emission estimates
from manure management systems have decreased for all
years of the current Inventory compared to the previous
Inventory due to the use of updated emission factors
from IPCC (2006). Overall, the changes resulted in an
average annual decrease in N2O emissions from manure
management of 8.1 Tg CO7 Eq. (47 percent) for the period
1990 through 2004.
• Substitution of Ozone Depleting Substances. An
extensive review of chemical substitution trends,
market sizes, growth rates, and charge sizes, together
with input from industry representatives, resulted in
updated assumptions for the Vintaging Model, which
is used to calculate emissions from this category.
These changes resulted in an average annual increase
in hydrofluorocabon (HFC) and perfluorocarbon (PFC)
emissions from the substitution of ozone depleting
substances of 7.6 Tg CO2 Eq. (21 percent) for the period
1990 through 2004.
• N2O Emissions from Wastewater Treatment. For N2O
emissions from domestic wastewater, a minor change
made to the time series was to include more specific
estimates of the percent of U.S. population that uses
centralized wastewater treatment. Also, a factor was
introduced to account for the amount of biological
denitrification used at centralized treatment plants. The
calculation estimates for protein consumed were updated
for the entire time series. Additionally, the default factor
for N2O emissions from N in effluent discharged to
aquatic environments was updated from 0.01 to 0.005
kg N2O-N/kg sewage-N. Overall, the changes resulted
in an average annual decrease in N2O emissions from
wastewater treatment of 7.5 Tg CO2 Eq. (51 percent)
for the period 1990 through 2004.
Landfills. For municipal solid waste landfills, changes
to historical data resulted from the application of a
more accurate integrated form of the first order decay
model, and incorporating a delay time of 6 months.
Another improvement was made in the estimate of CH4
generation from industrial landfills, which was based
on industrial production, waste disposal factors, and
the first order decay model. Additionally, EIA, LMOP,
and flare vendor databases were updated, affecting
estimates of CH4 recovery. Overall, changes resulted
in an average annual decrease in CH4 emissions from
landfills of 7.5 Tg CO2 Eq. (4.9 percent) for the period
1990 through 2004.
CH4 Emissions from Wastewater Treatment. Two
methodological refinements and one major data change
resulted in a decrease in CH4 emissions from wastewater
treatment for the period 1990 through 2004 relative to
the previous Inventory. First, the current estimates are
based on four distinct source categories (septic systems,
centrally treated aerobic systems, centrally treated
anaerobic systems, and anaerobic digesters), whereas in
previous inventories, emissions were calculated based on
an overall percentage of anaerobically treated wastewater.
Calculating emissions from anaerobic digesters constitutes
the second methodological refinement to this category.
The major data adjustment involves the Biochemical
Oxygen Demand (BOD) per capita rate. The current
estimates employ a standard value for the BOD per
capita rate across the time series (0.09 kg/capita/day). For
industrial wastewater, production data for the entire time
series were updated and other factors such as wastewater
outflow, BOD, and percent of waste treated anaerobically,
were revised. Overall, changes resulted in an average
10-4 Inventory of U.S. Greenhouse Gas BnissJons and Sinks: 1990-2005
-------
annual decrease in CH4 emissions from wastewater 2006). El A (2006) also reported minor changes in wood
treatment of 5.6 Tg CO, Eq. (16.7 percent) for the period consumption by the residential and industrial sectors for
1990 through 2004. the full timeseries, and in ethanol consumption for 2001
WoodBiomass and Ethanol Consumption. Commercial through 2004' Overa11' chan8es resulted in an averaSe
wood consumption values were revised for the full annual lncrease in emissi°ns from wood biomass and
timeseries, based on updated information from EIA's ethanol consumption of 2.9 Tg CO, Eq.(l percent)from
Commercial Building Energy Consumption Survey (EIA 199° through 2004.
Recalculations and improvements 10-5
-------
-------
11. References
Executive Summary
BEA (2006) 2005 Comprehensive Revision of the National
Income and Product Accounts: Current-dollar and "real"
GDP, 1929-2005. Bureau of Economic Analysis (BEA), U.S.
Department of Commerce, Washington, DC. July 29, 2006.
Available online at .
EIA (2006a) Monthly Energy Review, September 2006
and Unpublished Supplemental Tables on Petroleum
Product detail. Energy Information Administration (EIA),
U.S. Department of Energy, Washington, DC, DOE/E1A-
0035(2006/09).
EIA (2006b) International Energ\ Annual 2004. Energy
Information Administration (EIA), U.S. Department of
Energy, Washington, DC. Updated May-July 2006. Available
online at .
EPA (2006) Air Emissions Trends—Continued Progress
Through 2005. U.S. Environmental Protection Agency
(EPA), Washington, DC. December 19, 2006. Available
online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air
Pollution and the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
Hofmann, D. (2004) Long-lived Greenhouse Gas Annual
Averages for 1979-2004. NOAA/ESRL Global Monitoring
Division, Boulder, CO.
1PCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S.Eggleston,L.Buenida,K.Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestrv. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme. J. Penman, et al., eds. August 13, 2004.
Available online at .
IPCC (2001) Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change (IPCC),
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, PJ. van
der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.;
Cambridge University Press. Cambridge, U.K.
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.
IPCC (1996) Climate Change 1995: The Science of Climate
Change. Intergovernmental Panel on Climate Change, J.T.
Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A.
Kattenberg, and K. Maskell, eds. Cambridge University
Press. Cambridge, U.K.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
UNFCCC (2003) National Communications: Greenhouse
Gas Inventories from Parties included in Annex I to the
Convention, UNFCCC Guidelines on Reporting and Review.
Conference of the Parties, Eighth Session, New Delhi.
(FCCC/CP/2002/8). March 28, 2003.
U.S. Census Bureau (2006) U.S. Census Bureau International
Database (IDB). Available online at . Accessed August 15, 2006.
Introduction
Biasing and Jones (2004) Current Greenhouse Gas
Concentrations. In Trends: A Compendium of Data on Global
Change. Carbon Dioxide Information Analysis Center, Oak
Ridge National Laboratory. Oak Ridge, TN.
References 11-1
-------
EPA (2005) Air Emissions Trends—Continued Progress
Through 2003. U.S. Environmental Protection Agency,
Washington, DC. Available online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air
Pollution and the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
IPCC (2001) Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change (IPCC),
J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, PJ. van
der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.;
Cambridge University Press. Cambridge, U.K.
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.
IPCC (1999) Aviation and the Global Atmosphere.
Intergovernmental Panel on Climate Change; Penner, J .E., et
al., eds.; Cambridge University Press. Cambridge, U.K.
IPCC (1996) Climate Change 1995: The Science of Climate
Change. Intergovernmental Panel on Climate Change. J.T.
Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A.
Kattenberg, and K. Maskell, eds. Cambridge University
Press. Cambridge, U.K.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Jacobson, M.Z. (2001) "Strong Radiative Heating Due to the
Mixing State of Black Carbon in Atmospheric Aerosols."
Nature, 409:695-697.
NRC (2001) Climate Change Science: An Analysis of Some
Key Questions. Committee of the Science of Climate Change,
National Research Council (NRC). Available online at
.
UNEP/WMO (1999) Information Unit on Climate Change.
Framework Convention on Climate Change. Available online
at .
UNFCCC (2006) Updated UNFCCC reporting guidelines
on annual inventories following incorporation of the
provisions of decision 14/CP.ll. Subsidiary Body for
Scientific and Technical Advice. (FCCC/SBSTA/2006/9)
18 August 2006.
UNFCCC (2003) National Communications: Greenhouse
Gas Inventories from Parties included in Annex I to the
Convention, UNFCCC Guidelines on Reporting and Review.
Conference of the Parties, Eighth Session, New Delhi.
(FCCC/CP/2002/8) March 28,2003.
WMO (1999) Scientific Assessment of Ozone Depletion,
Global Ozone Research and Monitoring Project-Report
No. 44, World Meteorological Organization, Geneva,
Switzerland.
Trends in Greenhouse Gas Emissions
BEA (2006) 2005 Comprehensive Revision of the National
Income and Product Accounts: Current-dollar and "real"
GDP, 1929-2005. Bureau of Economic Analysis (BEA), U.S.
Department of Commerce, Washington, DC. July 29, 2006.
Available online at .
Duffield, J. (2005) Telephone and email conversations
between Lauren Flinn of ICF International and Jim Duffield,
Office' of Energy Policy and New Uses, USDA. April and
December.
EIA (2006a) Monthly Energy Review, September 2006 and
Unpublished Supplemental Tables on Petroleum Product
detail Energy Information Administration. U.S. Department
of Energy, Washington, DC, DOE/EIA-0035(2006/09).
EIA(2006b) Short-Term Energy Outlook. Energy Information
Administration, U.S. Department of Einergy, Washington,
DC. December.
EIA. (2006c) Annual Energy Review. "Appendix A. Table
A3: Approximate Heat Content of Petroleum Consumption."
Energy Information Administration. Available online at
EIA (1991 through 2005) Fuel Oil and Kerosene Sales.
"Table 22: Adjusted Sales for Farm Use: Distillate Fuel Oil
and Kerosene; Sales for Electric Power and Oil Company
Uses: Distillate Fuel Oil and Residual Fuel Oil, 2004."
Energy Information Administration. U.S. Department of
Energy, Washington, DC. Available online at .
EPA (2005) Air Emissions Trends —Continued Progress
Through 2003. U.S. Environmental Protection Agency,
Washington, DC. Available online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air
Pollution and the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
Hoffman, D. (2004) Long-lived Greenhouse Gas Annual
Averages for 1979-2004. NOAA/ESRL Global Monitoring
Division, Boulder, CO.
IPCC (2001) Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change (IPCC),
J.T. Houghton. Y. Ding, D.J. Griggs, M. Noguer, PJ. van
der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.;
Cambridge University Press. Cambridge, U.K.
11-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 199(1-2005
-------
Keeling, C.D. and T.P. Whorf (2005) "Atmospheric CO2
records from sites in the SIO air sampling network." In
Trends: A Compendium of Data on Global Change. Carbon
Dioxide Information Analysis Center, Oak Ridge National
Laboratory. U.S. Department of Energy, Oak Ridge, TN.,
U.S.A. Available online at .
U.S. Census Bureau (2006) U.S. Census Bureau International
Database (IDB). Available online at . Accessed August 15, 2006.
Energy
EIA (2006) International Energy Annual 2004. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Updated May-July 2006. Available online
at .
Carbon Dioxide Emissions from Fossil Fuel
Combustion
AAR (2005) Railroad Facts, 2002 Ed. Policy and
Economics Department, Association of American Railroads,
Washington, DC.
BEA (2006) 2005 Comprehensive Revision of the National
Income and Product Accounts: Current-dollar and "real"
GDP, 1929-2005. Bureau of Economic Analysis, U.S.
Department of Commerce, Washington, DC. July 29, 2006.
Available online at .
BEA (1991 through 2006) Unpublished BE-36 survey
data. Bureau of Economic Analysis, U.S. Department of
Commerce, Washington, DC.
Benson, D. (2002 through 2004) Personal communication.
Unpublished data developed by the Upper Great Plains
Transportation Institute, North Dakota State University and
American Short Line & Regional Railroad Association.
Corathers, L. (2006) Personal communication between Erin
Eraser of ICF International and Lisa Corathers, Commodity
Specialist, U.S. Geological Survey. October, 2006.
Dakota Gasification Company (2006) CO2 Pipeline Route
and Designation Information. Bismarck, ND. Available
online at .
DESC (2006) Unpublished data from the Defense Fuels
Automated Management System (DFAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense, Washington, DC.
DOC (1991 through 2006) Unpublished Report of Bunker
Fuel Oil Laden on Vessels Cleared for Foreign Countries.
Foreign Trade Division, Bureau of the Census, U.S.
Department of Commerce, Washington, DC. Form-563.
DOE (1993 through 2004) Transportation Energy Data
Book. Office of Transportation Technologies, Center for
Transportation Analysis, Energy Division, Oak Ridge
National Laboratory. ORNL-6959.
DOT (1991 through 2006) Fuel Cost and Consumption.
Federal Aviation Administration, U.S. Department of
Transportation, Bureau of Transportation Statistics,
Washington, DC. DAI-10.
EFMA (1995) Production of Ammonia. European Fertilizer
Manufacturers Association. March 1, 1995.
EIA (2006a) Annual Energy Review 2005. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0384(2005). July 2006.
EIA (2006b) Monthly Energy Review, December 2006 and
Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department
of Energy, Washington, DC. DOE/EIA-0035(2006/12).
EIA (2006c) Emissions of Greenhouse Gases in the United
States 2005, Draft Report. Office of Integrated Analysis
and Forecasting, Energy Information Administration,
U.S. Department of Energy, Washington, DC. DOE-EIA-
0573(2005).
EIA (2006d) ''World Petroleum Supply and Disposition.''
International Energy Annual. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
References 11-3
-------
EIA (200la) Historical Natural Gas Annual, 1930-2003.
Energy Information Administration, U.S. Department of
Energy, Washington, DC.
EIA (200Ib) U.S. Coal, Domestic and International Issues.
Energy Information Administration, U.S. Department of
Energy, Washington, DC. March 2001.
EIA (1991 through 2005) Fuel Oil and Kerosene Sales.
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0535-annual.
EPA (2005) Air Emissions Trends—Continued Progress
Through 2004. U.S. Environmental Protection Agency,
Washington, DC. August 18,2005. Available online at .
EPA (2004) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air Pollution
and the Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency. December 22, 2003.
Erickson, T. (2003) Plains CO2 Reduction (PCOR)
Partnership. Presented at the Regional Carbon Sequestration
Partnership Meeting Pittsburgh, Pennsylvania, Energy and
Environmental Research Center, University of North Dakota.
November 3, 2003. Available online at .
FHWA (1996 through 2006) Highway Statistics. Federal
Highway Administration, U .S. Department of Transportation,
Washington, DC. Report FHWA-PL-96-023-annual.
Fitzpatrick, E. (2002) The Weyburn Project: A Model
for International Collaboration. Available online at
.
FRB (2006) Industrial Production and Capacity Utilization.
Federal Reserve Board, Federal Reserve Statistical Release,
G. 17. November 7,2006 Annual Revision. Available online
at .
Gambogi, J. (2006) Personal communication between Erin
Fraser of ICF International and Joseph Gambogi, Commodity
Specialist, U.S. Geological Survey. September 2006.
Grillot, M. (2006) Personal communication between Lauren
Pederson of ICF International and Mike Grillot, Energy
Information Administration. U.S. Territories Fossil Fuel
Consumption, 1990-2005. Unpublished data developed by the
U.S. Energy Information Administration, Washington, DC.
Johnson, G. L. (2006) Personal communication between
Erin Fraser of ICF International and Greg Johnson, Liskow
& Lewis, on behalf of the International Carbon Black
Association (ICBA). October, 2006.
Kass, N. (2005) Personal communication between Erin
Fraser of ICF International and Nathaniel Kass, Energy
Information Administration, U.S. Department of Energy.
October 2005.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S.Eggleston,L.Buenida,K. Mi wa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency,
Paris, France.
Marland, G. and A. Pippin (1990) "United States Emissions
of Carbon Dioxide to the Earth's Atmosphere by Economic
Activity." Energy Systems and Policy, 14(4):323.
Onder, H. and E.A. Bagdoyan (1993) Everything You've
Alwavs Wanted to Know about Petroleum Coke. Allis Mineral
Systems.
SAIC/EIA (2001) Monte Carlo Simulations of Uncertainty
in U.S. Greenhouse Gas Emission Estimates. Final Report.
Prepared by Science Applications International Corporation
(SAIC) for Energy Information Administration (EIA), Office
of Integrated Analysis and Forecasting, U.S. Department of
Energy, Washington, DC. June 22, 2001.
USAA (2006) Primary Aluminum Statistics. Aluminum
Association, Washington, DC. January 2006.
USAF (1998) Fuel Logistics Planning. U.S. Air Force
document AFPAM23-22 I.May 1, 1998.
U.S. Census Bureau (2006) Current Industrial Reports
Fertilizer and Related Chemicals Summary: 2005. Available
online at .
U.S. Census Bureau (2005) Current Industrial Reports
Fertilizer Materials and Related Products: Fourth Quarter
Report 2004 Summary. Available online at .
U.S. Census Bureau (2004) International Data Base (IDB):
World Population Information. Washington, DC. September
30, 2006. Available online at .
U.S. Census Bureau (1991 through 1994) Current Industrial
Reports Fertilizer Materials Annual Report. Report No.
MQ28B.
USGS (1998 through 2002) Mineral Yearbook: Aluminum
Annual Report. U.S. Geological Survey, Reston, VA.
11-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
USGS (1995) Mineral Industry Surveys: Aluminum Annual
Review 1994. U.S. Geological Survey, U.S. Department of
the Interior, formerly Bureau of Mines, Washington, DC.
May 1995.
USGS (199 la through 2005a) Silicon: Annual Report. U.S.
Geological Survey, U.S. Department of the Interior, formerly
Bureau of Mines, Washington, DC.
USGS (1991b through 2005b) Mineral Yearbook: Titanium
Annual Report. U.S. Geological Survey, Reston, VA.
USITC (2006) USITC Interactive Tariff and Trade DataWeb.
United States International Trade Commission, U.S.
Department of Commerce, Washington, DC. Available online
at .
U.S. International Trade Commission (2006) HTS-
2707995010: Carbon Black Feedstock. U.S. Domestic
Exports. Available online at .
U.S. International Trade Commission (2004) HTS-2707: Oils
and Other Products of the Distillation of High Temperature
Coal Tar; Similar Products in which the Weight of Aromatic
Constituents Predominate. U.S. General Imports. Available
online at .
Carbon Emitted from Non-Energy Uses of
Fossil Fuels
ACC (2006) Guide to the Business of Chemistry, 2005.
American Chemistry Council.
ACC (2005) Guide to the Business of Chemistry, 2003.
American Chemistry Council.
Adler, B. (2001) Personal communication between Robert
Lanza of ICF International and Bob Adler, U.S. Energy
Information Administration (EIA). September 14, 2001.
APC (2006) APC Year-End Statistics for 2005. American
Plastics Council (APC) website. Available online at .
APC (2000) as reported in "Facts & Figures for the Chemical
Industry." Chemical and Engineering News, 78(26). June 26,
2000. American Plastics Council, Arlington, VA. Available
online at . Accessed July 27, 2000.
Eldredge-Roebuck, B. (2000) Personal communication
between Joe Casola of ICF International and Brandt Eldredge-
Roebuck, American Plastics Council. July 11, 2000.
References 11-5
-------
EPA (2006a) Air Emissions Trends—Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at
.
EPA (2006b) Biennial Reporting System (BRS) Database.
U.S. Environmental Protection Agency, Envirofacts
Warehouse, Washington, DC. Available online at .
EPA (2004a) Biennial Reporting System (BRS). U.S.
Environmental Protection Agency, Envirofacts Warehouse,
Washington, DC. Available online at .
EPA (2004b) Pesticides Industry Sales and Usage: 2000
and 2001 Market Estimates. U.S. Environmental Protection
Agency, Office of Prevention, Pesticides and Toxic
Substances, Washington, DC. Available online at .
EPA (2002) Pesticides Industry Sales and Usage, 1998 and
1999 Market Estimates. U.S. Environmental Protection
Agency, Office of Prevention, Pesticides and Toxic
Substances, Washington, DC. Available online at . Accessed July 2003.
EPA (2001) Inventory of U.S. Greenhouse Gas Emissions and
Sinks: 1990-1999. U.S. Environmental Protection Agency,
Office of Atmospheric Programs, Washington. DC. EPA
236-R-01-001.
EPA (2000a) Toxics Release Inventory, 1998. U.S.
Environmental Protection Agency, Office of Environmental
Information, Office of Information Analysis and Access.
Washington, DC. Available online at .
EPA (2000b) Hot Mix Asphalt Plants Emission Assessment
Report (DraftReport), AP-42. U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC. June 2000. Available online
at .
Accessed July 25,2000.
EPA (1999) Pesticides Industry Sales and Usage: 1996 and
1997 Market Estimates. U.S. Environmental Protection
Agency, Office of Prevention, Pesticides and Toxic
Substances, Washington, DC. Available online at .
EPA (1998) Pesticides Industry Sales and Usage, 1994 and
1995 Market Estimates. U.S. Environmental Protection
Agency, Office of Prevention, Pesticides and Toxic
Substances, Washington, DC. Available online at . Accessed July 2003.
EPA (1995) Asphalt Paving Operations, AP-42. U.S.
Environmental Protection Agency, Office of Air Quality
Planning and Standards, Research Triangle Park, NC.
FEE (2006) Fiber Economics Bureau, as cited in C&EN
(2006) Production: Growth in the Norm. Chemical &
Engineering News, American Chemical Society. July 10,
2006. Available online at .
FEE (2005) Fiber Economics Bureau, as cited in C&EN
(2005) Production: Growth in Most Regions. Chemical &
Engineering News, American Chemical Society. July 11,
2005. Available online at .
FEB (2003) Fiber Economics Bureau, as cited in C&EN
(2003) Production Inches Up in Most Countries. Chemical
& Engineering News, American Chemical Society July 7,
2003. Available online at .
FEB (2001) as reported in "Production: slow gains in output
of chemicals and products lagged behind U.S. economy as
a whole." Chemical and Engineering News, Vol. 79(26).
Fiber Economics Bureau, Washington, DC. June 25, 2001.
Available online at .
The Financial Planning Association (2006) Canada/US
Cross-Border Tools: US/Canada Exchange Rates. Available
from: . Accessed August 16, 2006.
Gosselin, Smith, and Hodge (1984) Clinical Toxicology of
Commercial Products. Fifth Edition, Williams & Wilkins,
Baltimore, MD.
IISRP (2003) 1ISRP Forecasts Moderate Growth in North
America to 2007. International Institute of Synthetic Rubber
Producers, Inc. New Release. Available online at .
IISRP (2000) as reported in ACS (2001) "Facts & Figures for
the Chemical Industry. Chemical and Engineering News, Vol.
78(26). June 26, 2000. International Institute of Synthetic
Rubber Producers, Houston, Texas. Available online in
IISRP's February 18, 2000, News Release: .
INEGI (2006) Produccion bruta total de las unidades
economicas manufactureras por Subsector, Rama, Subrama
y Clase de actividad. Available online at . Accessed August 15, 2006.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa,TNgara,
and K. Tanabe. eds.; Institute for Global Environmental
Strategies (IGES). Hayama. Kanagawa, Japan.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency,
Paris, France.
11-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Marland, G. and R. M. Rotty (1984) "Carbon dioxide
emissions from fossil fuels: a procedure for estimation and
results for 1950-1982." Tellus, 36B(4), 232-261.
Miller, T. (1999) Material Safety Data Sheet, Carbon Black.
Continental Carbon Company. September 1,1999. Available
online at . Accessed October 10,2003.
NPRA (2001) Selected Petrochemical Statistics- U.S. Trade,
Production and Consumption. National Petrochemical &
Refiners Association, Washington, DC.
PAN (2002) Pesticides Database. Pesticide Action Network
North America. Available online at . Accessed summer-fall 2003.
RMA (2006) Scrap Tire Markets in the United States 2005
Edition. Rubber Manufacturers Association, Washington,
DC. November 2006.
RMA (2002) U.S. Scrap Tire Markets 2001. Rubber
Manufacturers Association, Washington, DC. December
2002.
Schneider, S. (2007) E-mail communication between Sarah
Shapiro of ICF International and Shelly Schneider, Franklin
Associates, A Division of ERG. January 10, 2007.
SPI (2000) The Society of the Plastics Industry Website.
Available online at . Accessed June 28, 2000.
Statistics Canada (2006) Canadian Trade by Industry —
NAICS Codes: NAICS 3252 - Resin, Synthetic Rubber, and
Artificial and Synthetic Fibres and Filaments Manufacturing
(NAICS 3252). Available online at .
STMC (2003) Scrap Tire Facts and Figures. Scrap
Tire Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at
and . Accessed July 7, 2003.
Tooly, L. (2001) Personal communication between Robert
Lanza of ICF International and Lee Tooly, EPA's Office of
Air Quality Planning and Standards. Microsoft Access file
sent in an email. August 20, 2001.
U.S. Census Bureau (2004) Soap and Other Detergent
Manufacturing: 2002. Issued December 2004, document
number EC02-311-325611 (RV). Available online at .
U.S. Census Bureau (2003) U.S International Trade
Commission (USITC) Trade Dataweb. Available online
at . Accessed fall 2002-spring
2003.
U.S. Census Bureau (1999) 1997 Economic Census,
Manufacturing —Industry Series, Petroleum Lubricating
Oil and Grease Manufacturing and Petroleum Refining.
Document numbers EC97M-3241D and EC97M-3241A (2
reports).
U.S. International Trade Commission (2006) Available
online at . Accessed September
27,2006.
Wood, A. (2003) Compendium of Pesticide Common Names.
Alan Wood's Web Site. Available online at . Accessed summer-
fall 2003.
Stationary Combustion (excluding C02)
EIA (2006a) Monthly Energy Review, September 2006 and
Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department
of Energy, Washington, DC, DOE/EIA-0035(2006/09).
EIA (2006b) Annual Energy Review 2005. Energy
Information Administration, U.S. Department of Energy.
Washington, DC, DOE/EIA-0384(2005). July.
EPA (2005) Air Emissions Trends —Continued Progress
Through 2004. U.S. Environmental Protection Agency,
Washington DC. August 18,2005. Available online at .
EPA (2004) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between EPA OAP and EPA
OAQPS. December 22, 2003.
Grillot,M. (2006) Personal communication. U.S. Territories
Fossil Fuel Consumption, 1990-2005. Unpublished data
developed by the U.S. Energy Information Administration,
Washington, DC.
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.
References 11-7
-------
IPCC/UNEP/OECD/IEA (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.
SAIC/EIA (2001). "Monte Carlo Simulations of Uncertainty
in U.S. Greenhouse Gas Emission Estimates." Final Report.
Prepared by Science Applications International Corporation
(S AIC) for Energy Information Administration (EIA), Office
of Integrated Analysis and Forecasting, U.S. Department of
Energy, Washington, DC. 22 June.
Mobile Combustion (excluding C02)
AAR (2006) Railroad Facts, 2006 Ed. Policy and
Economics Department, Association of American Railroads,
Washington, DC.
ANL (2006) Argonne National Laboratory (2006) GREET
model Version 1.7. June 2006.
APTA (2006) Commuter Rail National Totals. American
Public Transportation Association, Washington, DC.
Available online at .
BEA(1991 through 2005) Unpublished BE-36 survey data.
Bureau of Economic Analysis (BEA), U.S. Department of
Commerce.
Benson, D. (2002 through 2004) Personal communication.
Unpublished data developed by the Upper Great Plains
Transportation Institute, North Dakota State University and
American Short Line & Regional Railroad Association.
Browning, L. (2005) Personal communication with Lou
Browning, Emission control technologies fordiesel highway
vehicles specialist, ICF International.
Browning, L. (2003) "VMT Projections for Alternative
Fueled and Advanced Technology Vehicles through 2025."
13th CRC On-Road Vehicle Emissions Workshop. April
2003.
DESC (2006) Unpublished data from the Defense Fuels
Automated Management System (DFAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense.
DOC (1991 through 2006) Unpublished Report of Bunker
Fuel Oil Laden on Vessels Cleared for Foreign Countries.
Form-563, Foreign Trade Division, Bureau of the Census,
U.S. Department of Commerce.
DOE (1993 through 2006) Transportation Energy Data
Book. Office of Transportation Technologies, Center for
Transportation Analysis, Energy Division, Oak Ridge
National Laboratory. ORNL-6959.
DOT (1991 through 2006) Fuel Cost and Consumption.
Federal Aviation Administration, U.S. Department of
Transportation, Bureau of Transportation Statistics,
Washington, DC. DAI-10.
EIA (2006a) Monthly Energy Review, December 2006 and
Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department
of Energy, Washington, DC. DOE/EIA-0035(2005/12).
EIA (2006b) International Energy Annual. World Petroleum
Supply and Disposition, Table 3.1 .Available online at .
EIA (2006c) Annual Energy Review 2005. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. July 2006. DOE/EIA-0384(2005).
EIA (2004) Natural Gas Annual 2004. Energy Information
Administration. U.S. Department of Energy, Washington,
DC.DOE/EIA-0131(04).
EIA (2002) Alternative Fuels Data Tables. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1991 through 2006) Fuel Oil and Kerosene Sales.
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0535-annual.
EPA (2006a) Annual Certification Test Results Report. Office
of Transportation and Air Quality, U.S. Environmental
Protection Agency. Available online at .
EPA (2006b) Confidential engine family sales data submitted
to EPA by manufacturers. Office of Transportation and Air
Quality, U.S. Environmental Protection Agency.
EPA (2006c) Air Emissions Trends—Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at
.
EPA (2006d) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2006e) Motor Vehicle Emission Simulator (MOVES).
Office of Transportation and Air Quality, U.S. Environmental
Protection Agency. Available online at .
EPA (2005) National Emissions Inventory Air Pollutant
Emissions Trends Data. Available online at .
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air
Pollution and the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
EPA (2000) Mobile6 Vehicle Emission Modeling Software.
Office of Mobile Sources, U.S. Environmental Protection
Agency, Ann Arbor, Michigan.
11-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
EPA (1999a) Emission Facts: The History of Reducing
Tailpipe Emissions. Office of Mobile Sources. May 1999.
EPA 420-F-99-017. Available online at .
EPA (1999b) Regulatory Announcement: EPA's Program for
Cleaner Vehicles and Cleaner Gasoline. Office of Mobile
Sources. December 1999. EPA420-F-99-051. Available
online at .
EPA (1998) Emissions of Nitrous Oxide from Highway
Mobile Sources: Comments on the Draft Inventory of U.S.
Greenhouse Gas Emissions and Sinks, 1990-1996. Office of
Mobile Sources, Assessment and Modeling Division, U.S.
Environmental Protection Agency. August 1998. EPA420-
R-98-009.
EPA (1997) Mobile Source Emission Factor Model
(MOBILESa). Office of Mobile Sources, U.S. Environmental
Protection Agency, Ann Arbor, Michigan.
EPA (1994a) Automobile Emissions: An Overview. Office of
Mobile Sources. August 1994. EPA400-F-92-007. Available
online at .
EPA (1994b) Milestones in Auto Emissions Control. Office
of Mobile Sources. August 1994. EPA 400-F-92-014.
Available online at .
EPA (1993) Automobiles and Carbon Monoxide. Office of
Mobile Sources. January 1993. EPA 400-F-92-005. Available
online at .
Esser, C. (2003 through 2004) Personal Communication with
Charles Esser, Residual and Distillate Fuel Oil Consumption
for Vessel Bunkering (Both International and Domestic) for
American Samoa, U.S. Pacific Islands, and Wake Island.
FA A (2006a). FAA Aerospace Forecasts Fiscal Years
2006-2017. Table 30 "General Aviation Aircraft Fuel
Consumption," Federal Aviation Administration. Available
online at .
FAA (2006b) Email correspondence containing aviation
emissions estimates from the System for Assessing Aviation's
Global Emissions (SAGE). August 2006.
FHWA (1996 through 2006) Highway Statistics. Federal
Highway Admini stration, U .S. Department of Transportation,
Washington, DC. Report FHWA-PL-96-023-annual.
Available online at .
ICF (2006a) Revisions to Alternative Fuel Vehicle (AFV)
Emission Factors for the U.S. Greenhouse Gas Inventory.
Memorandum from ICF International to John Davies, Office
of Transportation and Air Quality, U.S. Environmental
Protection Agency. November 2006.
ICF (2006b) Revised Gasoline Vehicle EFsfor LEV and Tier
2 Emission Levels. Memorandum from ICF International to
John Davies, Office of Transportation and Air Quality, U.S.
Environmental Protection Agency. November 2006.
ICF (2004) Update of Methane and Nitrous Oxide Emission
Factors for On-Highway Vehicles. Final Report to U.S.
Environmental Protection Agency. February 2004.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency,
Paris, France.
Lipman, T. and M. Delucchi (2002) "Emissions of Nitrous
Oxide and Methane from Conventional and Alternative Fuel
Motor Vehicles." Climate Change, 53:477-516. Available
online at .
Lou, J. (2002) Personal Communication with Joel Lou,
Residual and Distillate Fuel Oil Consumption for Vessel
(Both International and Domestic) for American Samoa,
U.S. Pacific Islands, and Wake Island.
Unnasch, S., L. Browning,and E. Kassoy (2001) Refinement
of Selected Fuel-Cycle Emissions Analyses, Final Report
to ARE.
U.S. Census Bureau (2000) Vehicle Inventory and Use
Survey. U.S. Census Bureau, Washington, DC. Database
CD-EC97-VIUS.
Whorton, D. (2006) Personal communication, Class II and III
Rail energy consumption, American Short Line and Regional
Railroad Association.
Coal Mining
AAPG (1984) Coalbed Methane Resources of the United
States. AAPG Studies in Geology Series #17.
DOE (1983) Methane Recovery from Coalbeds: A
Potential Energy Source. U.S. Department of Energy.
DOE/METC/83-76.
EIA (2006) Annual Coal Report 1991-2005 (Formerly called
Coal Industry Annual). Table 3, U.S. Department of Energy,
Energy Information Administration, Washington, DC.
EPA (1996) Evaluation and Analysis of Gas Content and
Coal Properties of Major Coal Bearing Regions of the United
States. U.S. Environmental Protection Agency. EPA/600/R-
96-065.
GRI (1988) A Geologic Assessment of Natural Gas from Coal
Seams. Topical Reports, Gas Research Institute 1986-88.
Mutmansky, Jan M. and Yanebi Wang (2000) "Analysis
of Potential Errors in Determination of Coal Mine Annual
Methane Emissions." Mineral Resources Engineering, 9(4).
December 2000.
References 11-9
-------
USBM (1986) Results of the Direct Method Determination
of the Gas Contents of U.S. Coal Basins. Circular 9067, U.S.
Bureau of Mines.
Abandoned Underground Coai Mines
EPA (2003) Methane Emissions Estimates & Methodology
for Abandoned Coal Mines in the U.S. Draft Final Report,
Washington, DC. June 2003.
Mutmansky, Jan M., and Yanbei Wang (2000) Analysis of
Potential Errors in Determination of Coal Mine Annual
Methane Emissions. Pennsylvania State University,
Department of Energy and Geo-Environmental Engineering,
University Park, PA.
U.S. Department of Labor, Mine Health & Safety
Administration (2006) Data Retrieval System. Available
online at .
Natural Gas Systems
AAPG (2004) Shale Gas Exciting Again. American
Association of Petroleum Geologists. Available online at
.
API (2005) "Table 12-Section III-Producing Oil Wells in
the United States by State." In Basic Petroleum Data Book.
American Petroleum Institute, Volume XXV, Number 1.
February 2005.
Brookhaven (2004) Natural Gas Field Subject of Interest
at Brookhaven College. Brookhaven College. Available
online at .
EIA (2006a) "Documentation of the Oil and Gas Supply
Module (OGSM)." Energy Information Administration, U.S.
Department of Energy, Washington, DC. Available online at
.
EIA (2006b) Number of Producing Gas and Gas Condensate
Wells, 1989-2004, Natural Gas Navigator. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (2006c) "Table 2 —Supply and Disposition of Dry
Natural Gas in the United States 1999-2005." Natural
Gas Monthly, Energy Information Administration, U.S.
Department of Energy, Washington, DC. Available online
at .
EIA (2006d) "Table 3—Natural Gas Consumption in the
United States." Natural Gas Monthly, Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2006e) Table 5.2. Monthly Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (2006f) "Table 7-Marketed Production of Natural
Gas by State." Natural Gas Monthly, Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2006g) U.S. Imports by Country. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2005) "Table 5-U.S. Crude Oil, Natural Gas, and
Natural Gas Liquids Reserves, 1977-2003." Energy
Information Administration, Department of Energy,
Washington, DC.
EIA (2004) US LNG Markets and Uses. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. June 2004. Available online at .
EPA (2006) Natural Gas STAR Reductions 1990-2005.
Natural Gas STAR Program.
EPA (1999) Estimates of Methane Emissions from the U.S.
Oil Industry (Draft Report). Prepared by ICF-Kaiser, Office
of Air and Radiation, U.S. Environmental Protection Agency.
October 1999.
EPA/GRI (1996) Methane Emissions from the Natural Gas
Industry. Prepared by Harrison, M.,T. Shires, J. Wessels, and
R. Cowgill, eds., Radian International LLC for National Risk
Management Research Laboratory, Air Pollution Prevention
and Control Division, Research Triangle Park, NC. EPA-
600/R-96-080a.
GRI (2001) Gas Resource Database: Unconventional Natural
Gas and Gas Composition Databases. Second Edition. GRI-
01/0136.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa. T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
Kansas (2006) Kansas Geological Survey. Oil and Gas
Production Data, All Wells, University of Kansas. Available
online at .
Lippman (2003) Rocky Mountain Region Second Quarter
2003 Production Report. Lippman Consulting, Inc.
11-10 Inventory of U.S. Greenhouse Gas; Emissions ant) Sinks: 1990-2005
-------
MMS (2006a) Gulf of Mexico Region Offshore Information.
Minerals Management Service, U.S. Department of Interior.
Available online at .
MMS (2006e) Pacific OCS Region. Minerals Management
Service, U.S. Department of Interior. Available online
at .
Montana (2006) Montana Online Oil and Gas Information
System. Montana Board of Oil and Gas Conservation,
Billing Office. Available online at .
Morgan Stanley (2005) Barnett Shale Update: None-
Core Confidence Rises. Available online at .
New Mexico (2006a) Annual Gas Well Counts by State
District. Available online at .
New Mexico (2006b) Districts. Available online at .
OGJ (1997-2006) "Worldwide Gas Processing." Oil & Gas
Journal, PennWell Corporation, Tulsa, OK.
Oklahoma (2006) Oklahoma Petroleum Information
Center—Coalbed-Methane Completions database. Oklahoma
Geological Survey. Available online at .
OPS (2006a) Natural Gas Transmission Pipeline Annual
Mileage. Office of Pipeline Safety, U.S. Department of
Transportation, Washington, DC. Available online at .
OPS (2006b) Distribution Annuals Data. Office of Pipeline
Safety, U.S. Department of Transportation, Washington, DC.
Available online at .
Texas (2006a) Gas Well Counts by County. Texas Railroad
Commission. Available online at .
Texas (2006b) Oil Well Counts by County. Texas Railroad
Commission. Available online at .
Texas (2006c) The Barnett Shale Regional Report. Foster,
Brad, Devon Energy, Texas Railroad Commission. Available
online at .
Texas (2006d) Oil and Gas District Boundaries. Texas
Railroad Commission. Available online at .
Utah (2006) Oil and Gas Data Download. Utah Division
of Oil, Gas and Mining —Department of Natural
Resources. Available online at .
World Oil Magazine (2006b) "Outlook 2006: United States
Producing oil wells." 227(2). February 2006. Available
online at .
Wyoming (2006) Wyoming Oil and Gas Conservation
Commission. Available online at .
Petroleum Systems
EIA (1995 through 2005) Annual Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1995 through 2006) Monthh Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1990 through 2005) Petroleum Supply Annual 1990-
2005 Volume I. Energy Information Administration, U.S.
Department of Energy, Washington, DC.
EIA (1990 through 2006) Refinerv Capacity Report. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EPA (2005) Incorporating the Mineral Management
Service Gi/lfwide Offshore Activities Data System (GOADS)
2000 data into the methane emissions inventories. U.S.
Environmental Protection Agency, Prepared by ICF
International. 2005.
EPA (1999) Estimates of Methane Emissions from the U.S.
Oil Industry (Draft Report). Office of Air and Radiation,
U.S. Environmental Protection Agency, Prepared by ICF
International. October 1999.
References 11-11
-------
EPA (1996) Methane Emissions from the U.S. Petroleum
Industry (Draft). U.S. Environmental Protection Agency,
Prepared by Radian. June 1996.
EPA (1995) Compilation of Air Pollutant Emission Factors
AP-42, Fifth Edition, Volume I: Stationary Point and Area
Sources. U.S. Environmental Protection Agency. Available
online at .
EPA & GRI (1996a) Methane Emissions from the Natural Gas
Industry, V7: Blow and Purge Activities. U.S. Environmental
Protection Agency, Prepared by Radian. April 1996.
EPA & GRI (1996b) Methane Emissions from the Natural
Gas Industry, VII: Compressor Driver Exhaust. U.S.
Environmental Protection Agency, Prepared by Radian.
April 1996.
EPA & GRI (1996c) Methane Emissions from the Natural
Gas Industry, VI2: Pneumatic Devices. U.S. Environmental
Protection Agency, Prepared by Radian. April 1996.
EPA & GRI (1996d) Methane Emissions from the Natural
Gas Industry, V13: Chemical Injection Pumps. U.S.
Environmental Protection Agency, Prepared by Radian.
April 1996.
MMS (2005a) OCS Platform Activity. Minerals Management
Service, U.S. Department of Interior. Available online at
.
MMS (2005b) Platform Information and Data. Minerals
Management Service, U.S. Department of Interior. Available
online at .
MMS (2001) Field and Reserve Information. Minerals
Management Service, U.S. Department of Interior. Available
online at .
OGJ (2006) Oil and Gas Journal 1990-2005. Worldwide
Refining Issue, January 1,2006.
OGJ (2005) Oil and Gas Journal 1990-2006. Pipeline
Economics Issue, August or September 2005.
United States Army Corps of Engineers (1995-2004)
Waterborne Commerce of the United States, Part 5:
National Summaries. U.S. Army Corps of Engineers,
Washington, DC.
Municipal Solid Waste Combustion
De Soete, G.G. (1993) "Nitrous Oxide from Combustion and
Industry: Chemistry, Emissions and Control." In Van Amstel,
A. R. (ed) Proc. of the International Workshop Methane and
Nitrous Oxide: Methods in National Emission Inventories and
Options for Control, Amersfoort, NL. February 3-5,1993.
DeZan, D. (2000) Personal communication between Joe
Casola of ICF Internationa] and Diane DeZan, Fiber
Economics Bureau. August 4, 2000.
EPA (2006a) Solid Waste Management and Greenhouse
Gases: A Life-Cycle Assessment of Emissions and Sinks.
Office of Solid Waste and Emergency Response, U.S.
Environmental Protection Agency, Washington, DC.
EPA (2006b) Municipal Solid Waste in the United States:
Facts and Figures for 2005. Office of Solid Waste and
Emergency Response, U.S. Environmental Protection
Agency, Washington, DC. Available online at .
EPA (2005a) Municipal Solid Waste Generation, Recycling,
and Disposal in the United States: Facts and Figures for
2003. Office of Solid Waste and Emergency Response,
U.S. Environmental Protection Agency, Washington, DC.
Available online at .
EPA (2003) Characterization of Municipal Solid Waste in the
United States: 200J Update (Draft}. Office of Solid Waste
and Emergency Response, U.S. Environmental Protection
Agency, Washington, DC.
EPA (2002) Characterization of Municipal Solid Waste
in the United States: 2000 Update. Office of Solid Waste
and Emergency Response, U.S. Environmental Protection
Agency, Washington, DC. EPA530-R-02-001.
EPA (2000a) Characterization of Municipal Solid Waste in
the United States: 1999 Update Fact Sheet (andData Tables).
Office of Solid Waste, U.S. Environmental Protection
Agency, Washington, DC. EPA530-F-00-024.
EPA (2000b) Characterization of Municipal Solid Waste in
the United States: Source Data on the 1999 Update. Office
of Solid Waste, U.S. Environmental Protection Agency,
Washington, DC. EPA530-F-00-024.
EPA (1999) Characterization of Municipal Solid Waste in
the United States: 1998 Update. Report No. EPA530-R-99-
021. Office of Solid Waste, U.S. Environmental Protection
Agency, Washington, DC.
EPA (1998) Characterization of Municipal Solid Waste
in the United States: 1997 Update. Office of Solid Waste,
U.S. Environmental Protection Agency, Washington, DC.
EPA530-R-98-007.
EPA (1997) Characterization of Municipal Solid Waste
in the United States: 1996 Update. Office of Solid Waste,
U.S. Environmental Protection Agency, Washington, DC.
EPA530-R-97-015.
11-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
EPA (1996) Characterization of Municipal Solid Waste in
the United States: 1995 Update. Office of Solid Waste, U.S.
Environmental Protection Agency, Washington, DC.
EPA (1995) Compilation of Air Pollutant Emission Factors,
AP-42. Fifth Edition, Volume I: Stationary Point and Area
Sources, Introduction, Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency, Research
Triangle Park, NC. October 1995.
FEE (2006) Fiber Economics Bureau, as cited in C&EN
(2006) "Production: Growth in Most Regions," Chemical
& Engineering News, American Chemical Society, July 11,
2006. Available online at .
Glenn, Jim (1999) "11th Annual BioCycle Nationwide
Survey: The State of Garbage in America." BioCycle, JG
Press, Emmaus, PA. April 1999.
Goldstein, N. and C. Madtes (2001) "13"1 Annual BioCycle
Nationwide Survey: The State of Garbage in America."
BioCycle, JG Press, Emmaus, PA. December 2001.
Goldstein, N. and C. Madtes (2000) "12th Annual BioCycle
Nationwide Survey: The State of Garbage in America, Part
I." BioCycle, JG Press, Emmaus, PA. November 2000.
1PCC (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.
Johnke (1999) as cited in Good Practice Guidance and
Uncertainty Management in National Greenhouse Gas
Inventories. Intergovernmental Panel on Climate Change,
2000.
Kaufman, et al. (2004a) "14th Annual BioCycle Nationwide
Survey: The State of Garbage in America 2004" BioCvcle,
JG Press, Emmaus, PA. January, 2004.
Kaufman, et al. (2004b) "Corrections to State of Garbage
2004" BioCycle, JG Press, Emmaus, PA. April, 2004.
Miller, T. (1999) Material Safety Data Sheet, Carbon Black.
Continental Carbon Company. September 1,1999. Available
online at
and . Accessed January 3,2007.
STMC (2003) Scrap Tire Facts and Figures. Scrap
Tire Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at
and . Accessed July 7,2003.
STMC (2002) Scrap Tire Facts and Figures. Scrap Tire
Management Council of the Rubber Manufacturers
Association. Washington, DC. Available online at . Accessed
October 22, 2002.
STMC (2001) Scrap Tire Facts and Figures. Scrap Tire
Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at . Accessed
September 5, 2001.
STMC (2000) Scrap Tire Facts and Figures. Scrap Tire
Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at . Accessed July 26, 2000.
UK: Environment Agency (1999) as cited in Good Practice
Guidance and Uncertainty Management in National
Greenhouse Gas Inventories. Intergovernmental Panel on
Climate Change, 2000.
Yasuda (1993) as cited in Good Practice Guidance
and Uncertainty Management in National Greenhouse
Gas Inventories. Intergovernmental Panel on Climate
Change, 2000.
Energy Sources of Indirect Greenhouse
Gas Emissions
EPA (2006) Air Emissions Trends —Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19. 2006. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air Pollution
and the Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency (EPA). December 22,
2003.
EPA (1997) Compilation of Air Pollutant Emission Factors,
AP-42. U.S. Environmental Protection Agency, Office of Air
Quality Planning and Standards, Research Triangle Park,
NC. October 1997.
References 11-13
-------
International Bunker Fuels
ASTM (1989) Military Specification for Turbine Fuels,
Aviation, Kerosene Types, NATO F-34 (JP-8), and NATO
F-35. February 10, 1989. Available online at .
BEA (1991 through 2006) Unpublished BE-36 survey data.
Bureau of Economic Analysis (BEA), U.S. Department of
Commerce, Washington, DC.
Chevron (2000) Aviation Fuels Technical Review (FTR-3).
Chevron Products Company, Chapter 2. Available online at
.
DESC (2006) Unpublished data from the Defense Fuels
Automated Management System (DFAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense, Washington, DC.
DOC (1991 through 2006) Unpublished Report of Bunker
Fuel Oil Laden on Vessels Cleared for Foreign Countries.
Foreign Trade Division, Bureau of the Census, U.S.
Department of Commerce, Washington, DC. Form-563.
DOT (1991 through 2006) Fuel Cost and Consumption.
Airline Information, Bureau of Transportation Statistics, U.S.
Department of Transportation, Washington, DC.
EIA (2006) Monthly Energy Review, December 2006 and
Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department
of Energy, Washington, DC. DOE/EIA-0035(2006/12).
IPCC (2006) 20061PCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa, T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme. Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
USAF (1998) Fuel Logistics Planning. U.S. Air Force
pamphlet AFPAM23-221, May 1,1998.
Wood Biomass and Ethanol Consumption
EIA (2006) Annual Energy Review 2005. Energy Information
Administration, U .S. Department of Energy. Washington, DC,
Tables 10.2a and 10.2b. July 2006. DOE/EIA-0384(2005).
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Lindstrom, P. (2006) Personal communication between
Jean Kim of ICF International and Perry Lindstrom, Energy
Information Administration.
Industrial Processes
Cement Manufacture
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 (1996) Climate Change 1995: The Science of Climate
Change. Intergovernmental Panel on Climate Change, J.T.
Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A.
Kattenberg, and K. Maskell, (eds); Cambridge University
Press, Cambridge, U.K.
USGS (2005) Minerals Yearbook: Cement Annual Report
2004. U.S. Geological Survey. Reston, VA.
USGS (2004) Minerals Yearbook: Cement Annual Report
2003. U.S. Geological Survey. Reston, VA.
USGS (2003) Minerals Yearbook: Cement Annual Report
2002. U.S. Geological Survey. Reston, VA.
USGS (2002) Minerals Yearbook: Cement Annual Report
2001. U.S. Geological Survey. Reston, VA.
USGS (2001) Minerals Yearbook: Cement Annual Report
2000. U.S. Geological Survey. Reston, VA.
USGS (2000) Minerals Yearbook: Cement Annual Report
1999. U.S. Geological Survey. Reston, VA.
USGS (1999) Minerals Yearbook: Cement Annual Report
1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Mineral Industrial Survey: Cement 1997. U.S.
Geological Survey, Reston, VA.
USGS (1997) Mineral Industrial Survey: Cement 1996. U.S.
Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Cement Annual Report
1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Cement Annual Report
1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Cement Annual Report
1993. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Cement Annual Report
1992. U.S. Geological Survey, Reston, VA.
Van Oss (2006) Personal communication between Hendrik
Van Oss, Commodity Specialist of the U.S. Geological
Survey and Erin Fraser of ICF International. September
20,2006.
11-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Iron and Steel Production
AISI (2006) 2005 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (2005) 2004 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (2004) 2003 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (2003) 2002 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (2002) 2007 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (2001) 2000 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (1996) 7995 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
AISI (1995) 1994 Annual Statistical Report, American Iron
and Steel Institute, Washington, DC.
DOE (1997) Energy and Environmental Profile of the U.S.
Aluminum Industry. Office of Industrial Technologies. U.S.
Department of Energy. July 1997.
El A (2006a) Annual Energy Review 2005. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/ EIA-0384.
EIA (2006b) Emissions of Greenhouse Gases in the United
States 2005. Energy Information Administration, U.S.
Department of Energy, Washington, DC. DOE/EIA-0573
(2005).
EIA (2006c) Quarterly Coal Report January-March 2006,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (2004a) Quarterly Coal Report October-December
2003, Energy Information Administration, U.S. Department
of Energy, Washington, DC. DOE/EIA-0121.
EIA (2004b) Emissions of Greenhouse Gases in the United
States 2003. Energy Information Administration, U.S.
Department of Energy. Washington. DC. DOE/EIA-0573.
EIA (2003) Quarterly Coal Report October-December 2002,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (2002) Quarterly Coal Report October-December 2001,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (2001) Quarterly Coal Report October-December 2000,
Energy Information Administration. U.S. Department of
Energy, Washington. DC. DOE/EIA-0121.
EIA (2000) Quarterly Coal Report October-December 1999,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121 (2000/4Q).
EIA (1999) Quarterly Coal Report October-December 1998,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
El A (1998) Quarterly Coal Report October-December 1997,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa.T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
IPCC/UNEP/OECD/IEA (1995) IPCC Guidelines
for National Greenhouse Gas Inventories, Volume 3,
Greenhouse Gas Inventory Reference Manual. Table 2-2.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
IPCC WG1 Technical Support Unit, UK.
Jorgenson, J. (2006) Telephone conversation between Chris
Steuer of ICF International and John Jorgenson, Commodity
Specialist, USGS. 20 September 2006.
US AA(2Q06) Primary Aluminum Statistics. U.S. Aluminum
Association, Washington, DC. January 2006.
US AA (2005) Primary Aluminum Statistics. U.S. Aluminum
Association, Washington, DC. January 2005.
US AA (2004) Primanc Aluminum Statistics. U.S. Aluminum
Association, Washington, DC. January 2004.
U.S. Census Bureau (2006) U.S International Trade
Commission (USITC) Trade Dataweb. Available online at
. Accessed Fall 2006.
USGS (2006) Minerals Yearbook: Iron Ore Report 2005.
U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook: Iron Ore Report 2004.
U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Iron Ore Report 2003.
U.S. Geological Survey. Reston, VA.
USGS (2003) Minerals Yearbook: Iron Ore Report 2002.
U.S. Geological Survey, Reston, VA.
References 11-15
-------
USGS (2002) Minerals
U.S. Geological Survey,
USGS (2001) Minerals
U.S. Geological Survey,
USGS (2000) Minerals
U.S. Geological Survey,
USGS (1999) Minerals
U.S. Geological Survey,
USGS (1998) Minerals
U.S. Geological Survey,
USGS (1997) Minerals
U.S. Geological Survey,
USGS (1996) Minerals
U.S. Geological Survey,
USGS (1995) Minerals
U.S. Geological Survey,
USGS (1994) Minerals
U.S. Geological Survey,
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Yearbook: Iron
Reston, VA.
Ore Report 2001.
Ore Report 2000.
Ore Report 1999.
Ore Report 1998.
Ore Report 1997.
Ore Report 1996.
Ore Report 1995.
Ore Report 1994.
Ore Report 1993.
Ammonia Manufacture and Urea
Application
Bark (2004) Coffeyville Nitrogen Plant. Available online at
Accessed: December 15, 2004.
Coffeyville Resources Nitrogen Fertilizers, LLC
(2006) Business Data. Available online at Accessed
September 7, 2006.
Coffeyville Resources Nitrogen Fertilizers, LLC
(2005) Business Data. Available online at Accessed
September 12,2005.
EFMA (1995) Production of Ammonia. European Fertilizer
Manufacturers Association. March 1, 1995.
EIA (1998) Manufacturing Energy Consumption Survey
(MECS) U.S. Department of Energy, Energy Information
Administration, Washington, DC. Available online at .
U.S. Census Bureau (2005) Current Industrial Reports
Fertiliser Materials and Related Products: Fourth Quarter
Report 2004 Summary. Available online at .
U.S. Census Bureau (2004) Current Industrial Reports
Fertilizer Materials and Related Products: Fourth Quarter
Report 2003 Summary. Available online at .
U.S. Census Bureau (2003) Current Industrial Reports
Fertilizer Materials and Related Products: Annual Reports
2002 Summary. Available online at .
U.S. Census Bureau (2002a) Current Industrial Reports
Fertilizer Materials and Related Products: First Quarter
2002. June 2002. Available online at .
U.S. Census Bureau (2002b) Current Industrial Reports
Fertilizer Materials and Related Products: Fourth Quarter
2001. March 2002. Available online at .
U.S. Census Bureau (2002c) Current Industrial Reports
Fertilizer Materials and Related Products: Third Quarter
2001. January 2002. Available online at .
U.S. Census Bureau (2001a) Current Industrial Reports
Fertilizer Materials and Related Products: Second Quarter
2001. September 2001. Available online at .
U.S. Census Bureau (2001b) Current Industrial Reports
Fertilizer Materials and Related Products: Annual Report
2000. Available online at .
U.S. Census Bureau (2000) Current Industrial Reports
Fertilizer Materials and Related Products: Annual Report
1999. Available online at .
U.S. Census Bureau (1999) Current Industrial Reports
Fertilizer Materials and Related Products: Annual Report
1998. Available online at .
U.S. Census Bureau (1998) Current Industrial Reports
Fertilizer Materials and Related Products: Annual Report
1997. Available online at .
11-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
U.S. Census Bureau (1994) Current Industrial Reports
Fertilizer Materials Annual Report 1993. Report No.
MQ28B. U.S. Census Bureau, Washington, DC.
U.S. Census Bureau
Fertilizer Materials
MQ28B. U.S. Census
U.S. Census Bureau
Fertilizer Materials
MQ28B. U.S. Census
U.S. Census Bureau
Fertilizer Materials
MQ28B. U.S. Census
(1993) Current Industrial Reports
Annual Report 1992. Report No.
Bureau, Washington, DC.
(1992) Current Industrial Reports
Annual Report 1991. Report No.
Bureau, Washington, DC.
(1991) Current Industrial Reports
Annual Report 1990. Report No.
Bureau, Washington, DC.
U.S. ITC (2002) United States International Trade
Commission Interactive Tariff and Trade Data Web, Version
2.5.0. Available online at . Accessed August 2002.
Lime Manufacture
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.
Males, E. (2003) Public review comments received in a
memorandum from Eric Males, National Lime Association to
Mr. William N. Irving & Mr. Leif Hockstad, Environmental
Protection Agency. March 6, 2003.
USGS (2006) Minerals Yearbook: Lime Annual Report 2005.
U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook: Lime Annual Report 2004.
U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Lime Annual Report 2003.
U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Lime Annual Report 2002.
U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Lime Annual Report 2001.
U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Lime Annual Report 2000.
U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Lime Annual Report 1999.
U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Lime Annual Report 1998.
U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Lime Annual Report 1997.
U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Lime Annual Report 1996.
U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Lime Annual Report 1995.
U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Lime Annual Report 1994.
U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Lime Annual Report 1993.
U.S. Geological Survey, Reston, VA.
USGS (1992) Minerals Yearbook: Lime Annual Report 1991.
U.S. Geological Survey, Reston, VA.
Limestone and Dolomite Use
USGS (2006) Minerals Yearbook: Magnesium Annual Report
2005. U.S. Geological Survey, Reston, VA.
USGS (2005a) Minerals Yearbook: Magnesium Annual
Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2005b) Minerals Yearbook: Magnesium Annual
Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004a) Minerals Yearbook: Crushed Stone Annual
Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2004b) Minerals Yearbook: Magnesium Annual
Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003a) Minerals Yearbook: Crushed Stone Annual
Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2003b) Minerals Yearbook: Magnesium Annual
Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002a) Minerals Yearbook: Crushed Stone Annual
Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2002b) Minerals Yearbook: Magnesium Annual
Report 2001. U.S. Geological Survey, Reston, VA.
USGS (200la) Minerals Yearbook: Crushed Stone Annual
Report 2000. U.S. Geological Survey, Reston, VA.
USGS (200Ib) Minerals Yearbook: Magnesium Annual
Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000a) Minerals Yearbook: Crushed Stone Annual
Report 1999. U.S. Geological Survey, Reston, VA.
USGS (2000b) Minerals Yearbook: Magnesium Annual
Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999a) Minerals Yearbook: Crushed Stone Annual
Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1999b) Minerals Yearbook: Magnesium Annual
Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998a) Minerals Yearbook: Crushed Stone Annual
Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1998b) Minerals Yearbook: Magnesium Annual
Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997a) Minerals Yearbook: Crushed Stone Annual
Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1997b) Minerals Yearbook: Magnesium Annual
Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996a) Minerals Yearbook: Crushed Stone Annual
Report 1995. U.S. Geological Survey, Reston, VA.
References 11-17
-------
USGS (1996b) Minerals Yearbook: Magnesium Annual
Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995a) Minerals Yearbook: Crushed Stone Annual
Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1995b) Minerals Yearbook: Crushed Stone Annual
Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1995c) Minerals Yearbook: Magnesium Annual
Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Crushed Stone Annual
Report 1991. U.S. Geological Survey, Reston, VA.
Weaver, S. (2006) Electronic mail from Susan Weaver,
Commodity Specialist, U.S. Geological Survey, to Erin
Eraser of ICE International. September 14,2006.
Soda Ash Manufacture and Consumption
USGS (2006) Minerals Yearbook: Soda Ash Annual Report
2005. U.S. Geological Survey, Reston. VA.
USGS (2005) Minerals Yearbook: Soda Ash Annual Report
2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Soda Ash Annual Report
2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Soda Ash Annual Report
2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Soda Ash Annual Report
2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Soda Ash Annual Report
2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Soda Ash Annual Report
1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Soda Ash Annual Report
1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Soda Ash Annual Report
1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Soda Ash Annual Report
1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Soda Ash Annual Report
1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Soda Ash Annual Report
1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Soda Ash Annual Report
1993. U.S. Geological Survey, Reston, VA.
Titanium Dioxide Production
Gambogi, J. (2002) Telephone conversation between Philip
Groth of ICE International and Joseph Gambogi, Commodity
Specialist, U.S. Geological Survey. November 2002.
Kramer, D. (2006) Telephone conversation between Erin
Eraser of ICE International and Deborah Kramer, Commodity
Specialist, U.S. Geological Survey. September 2006.
Onder, H, and E.A. Bagdoyan (1993) Everything You've
Always Wanted to Know about Petroleum Coke. Allis
Mineral Systems.
USGS (2006) Minerals Commodity Summaries: Titanium
Mineral Concentrates 2005. U.S. Geological Survey.
Reston, VA.
USGS (2005) Mineral Yearbook: Titanium Annual Report
2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Mineral Yearbook: Titanium Annual Report
2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Mineral Yearbook: Titanium Annual Report
2002. U.S. Geological Survey, Reston. VA.
USGS (2002) Mineral Yearbook: Titanium Annual Report
2001. U.S. Geological Survey, Reston. VA.
USGS (2001) Mineral Yearbook: Titanium Annual Report
2000. U.S. Geological Survey, Reston: VA.
USGS (2000) Mineral Yearbook: Titanium Annual Report
1999. U.S. Geological Survey, Reston. VA.
USGS (1999) Mineral Yearbook: Titanium Annual Report
1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Mineral Yearbook: Titanium Annual Report
1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Mineral Yearbook: Titanium Annual Report
1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Mineral Yearbook: Titanium Annual Report
1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Mineral Yearbook: Titanium Annual Report
1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Mineral Yearbook: Titanium Annual Report
1993 U.S. Geological Survey, Reston, VA.
USGS (1993) Mineral Yearbook: Titanium Annual Report
1992, U.S. Geological Survey, Reston, VA.
USGS (1992) Mineral Yearbook: Titanium Annual Report
1991. U.S. Geological Survey, Reston, VA.
USGS (1991) Mineral Yearbook: Titanium Annual Report
1990. U.S. Geological Survey, Reston, VA.
Ferroalloy Production
Corathers, L. (2006) Personal communication between Lisa
Corathers, Commodity Specialist, U.S. Geological Survey
and Erin Eraser of ICE International. October 2006.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston,L. Buenida, K. Miwa,T Ngara,
and K. Tanabe (eds.); Institute for Global Environmental
Strategies (ICES). Hayama, Kanagawa, Japan.
Onder, H., and E.A. Bagdoyan (1993) Everything You've
Always Wanted to Know about Petroleum Coke. Allis Mineral
Systems.
11-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 191)0-2005
-------
USGS (2005) Minerals Yearbook: Silicon Annual Report
2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Silicon Annual Report
2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Mineral* Yearbook: Silicon Annual Report
2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Silicon Annual Report
2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Silicon Annual Report
2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Silicon Annual Report
1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Silicon Annual Report
1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Silicon Annual Report
1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Silicon Annual Report
1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Silicon Annual Report
1995. U.S. Geological Survey, Reston. VA.
USGS (1995) Minerals Yearbook: Silicon Annual Report
1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Silicon Annual Report
1993. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Silicon Annual Report
1992. U.S. Geological Survey, Reston, VA.
USGS (1992) Minerals Yearbook: Silicon Annual Report
1991. U.S. Geological Survey, Reston, VA.
USGS (1991) Minerals Yearbook: Silicon Annual Report
1990. U.S. Geological Survey, Reston, VA.
Phosphoric Acid Production
EFMA (2000) Production of Phosphoric Acid. Booklet No.
4 of 8 in the series "Best Available Techniques for Pollution
Prevention and Control in the European Fertilizer Industry,"
European Fertilizer Manufacturers Association. Available
online at .
F1PR (2003) "Analyses of Some Phosphate Rocks."
Facsimile from Gary Albarelli of the Florida Institute of
Phosphate Research, Bartovv, Florida, to Robert Lanza of
ICF International, July 29, 2003.
FIPR (2003a) Florida Institute of Phosphate Research,
personal communication between Mr. Michael Lloyd,
Laboratory Manager, FIPR, Barlow, Florida, and Mr. Robert
Lanza, ICF International, August 2003.
USGS (2006) Minerals Yearbook. Phosphate Rock Annual
Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook. Phosphate Rock Annual
Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook. Phosphate Rock Annual
Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Electronic mails from Mr. Stephen M Jasinski,
USGS Commodity Specialist, Phosphate Rock to Mr. Robert
Lanza, ICF International, July-August, 2003.
USGS (2002) Minerals Yearbook. Phosphate Rock Annual
Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook. Phosphate Rock Annual
Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook. Phosphate Rock Annual
Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook. Phosphate Rock Annual
Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook. Phosphate Rock Annual
Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook. Phosphate Rock Annual
Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook. Phosphate Rock Annual
Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook. Phosphate Rock Annual
Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook. Phosphate Rock Annual
Report 1993. U.S. Geological Survey, Reston, VA.
Carbon Dioxide Consumption
Allis, R. et al. (2000) Natural CO2 Reservoirs on the Colorado
Plateau and Southern Rocky Mountains: Candidates for CO2
Sequestration. Utah Geological Survey and Utah Energy and
Geoscience Institute, Salt Lake City, Utah.
ARI (2006) CO2-EOR: An Enabling Bridge for the Oil
Transition. Presented to: Modeling the Oil Transition —a
DOE/EPA Workshop on the Economic and Environmental
Implications of Global Energy Transitions. Washington, DC.
April 20-21,2006.
Broadhead, R. (2006) Electronic mail from Mr. Ron Broadhead,
New Mexico Bureau of Geology and Mineral Resources to
Mr. Erin Eraser, ICF International, September 2006.
Denbury Resources Inc. (2006) Annual Report, 2004, 34.
Denbury Resources Inc. (2005) Annual Report, 2004, 32.
Denbury Resources Inc. (2004) Annual Report, 2003,41.
Denbury Resources Inc. (2003) Annual Report, 2002, 14.
Denbury Resources Inc. (2002) Annual Report, 2001,22.
Zinc Production
Gabby, P. (2006) Telephone conversation between Erin
Eraser of ICF International and Peter Gabby, Commodity
Specialist, U.S. Geological Survey. 29 September 2006.
References 11-19
-------
Queneau P.B., James S.E.,Downey J.P.,Livelli G.M. (1998)
Recycling Lead and Zinc in the United States. Zinc and Lead
Processing. The Metallurgical Society of CIM.
Recycling Today (2005) Horsehead Sales Complete. Available
at . January 5,2005.
Sjardin (2003) CO2 Emission Factors for Non-Energy Use in
the Non-Ferrous Metal, Ferroalloys and Inorganics Industry.
Copernicus Institute, Utrecht, the Netherlands.
Stuart (2005) Telephone conversation between Christopher
Steuer of ICF International and Eric Stuart of the Steel
Manufacturers Association. October 31, 2005.
USGS (2005) Minerals Yearbook: Zinc Annual Report 2004.
U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Zinc Annual Report 2003.
U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Zinc Annual Report 2002.
U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Zinc Annual Report 2001.
U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Zinc Annual Report 2000.
U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Zinc Annual Report 1999.
U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Zinc Annual Report 1998.
U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Zinc Annual Report 1997.
U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Zinc Annual Report 1996.
U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Zinc Annual Report 1995.
U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Zinc Annual Report 1994.
U.S. Geological Survey, Reston, VA.
Viklund-White C. (2000) The Use of LCA for the
Environmental Evaluation of the Recycling of Galvanized
Steel. ISIJ International. Volume 40 No. 3: 292-299.
Lead Production
Dutrizac, J.E., V. Ramachandran, and J.A. Gonzalez (2000)
Lead-Zinc 2000. The Minerals, Metals, and Materials
Society.
Gabby, P. (2006) Telephone conversation between Erin
Fraser of ICF International and Peter Gabby, Commodity
Specialist, USGS, 29 September 2006.
Morris, D., F.R. Steward, and P. Evans (1983) Energy
Efficiency of a Lead Smelter. Energy 8(5):337-349.
Sjardin, M. (2003) CO2 Emission Factors for Non-Energy
Use in the Non-Ferrous Metal, Ferroalloys and Inorganics
Industry. Copernicus Institute, Utrecht, the Netherlands.
Ullman 's Encyclopedia of Industrial Chemistry: Fifth Edition
(1997) Volume A5. John Wiley and Sons.
USGS (2005) Minerals Yearbook: Lead Annual Report 2004.
U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Lead Annual Report 2003.
U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Lead Annual Report 2002.
U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Lead Annual Report 2001.
U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Lead Annual Report 2000.
U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Lead Annual Report 1999.
U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Lead Annual Report 1998.
U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Lead Annual Report 1997.
U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Lead Annual Report 1996.
U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Lead Annual Report 1995.
U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Lead Annual Report 1994.
U.S. Geological Survey, Reston, VA.
Petrochemical Production
ACC (2006) Guide to the Business of Chemistry 2005.
American Chemistry Council, Arlington, VA.
ACC (2005) Guide to the Business of Chemistry 2005.
American Chemistry Council, Arlington, VA.
ACC (2003) Guide to the Business of Chemistry 2003.
American Chemistry Council, Arlington, VA.
ACC (2002) Guide to the Business of Chemistry 2002.
American Chemistry Council, Arlington, VA.
CMA (1999) US. Chemical Industry Statistical Handbook.
Chemical Manufacturer's Association. Washington, DC.
EIA (2004) Annual Energy Review 2003. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. DOE/EIA-0384(2003). September 2004.
EIA (2003) Emissions of Greenhouse Gases in the United
States 2002. Office of Integrated Analysis and Forecasting,
Energy Information Administration, U.S. Department
of Energy, Washington, DC. DOE-EIA-0573(2002).
February 2003.
European IPPC Bureau (2004) Draft Reference Document on
Best Available Techniques in the Large Volumen Inorganic
Chemicals—Solid and Others Industry, Table 4.21. European
Commission, 224. August 2004.
11-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
The Innovation Group (2004) Carbon Black Plant Capacity.
Available online at .
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Johnson, G. L. (2006) Personal communication between Erin
Eraser of ICE International and Greg Johnson of Liskow
& Lewis, on behalf of the International Carbon Black
Association (ICBA). October 2006.
Johnson, G. L. (2005) Personal communication between Erin
Eraser of ICE International and Greg Johnson of Liskow
& Lewis, on behalf of the International Carbon Black
Association (ICBA). October 2005.
Johnson, G. L. (2003) Personal communication between
Caren Mintz of ICE International and Greg Johnson of
Liskow & Lewis, on behalf of the International Carbon Black
Association (ICBA). November 2003.
Othmer, K. (1992) Carbon (Carbon Black), Vol. 4,1045.
Srivastava, Manoj, I.D. Singh, and Himmat Singh (1999)
"Structural Characterization of Petroleum Based Feedstocks
for Carbon Black Production," Table-1. Petroleum Science
and Technology 17(1&2):67-80.
U.S. Census Bureau (2006) U.S International Trade
Commission (USITC) Trade DataWeb. Available online at
. Accessed Fall 2006.
U.S. Census Bureau (2004) 2002 Economic Census:
Manufacturing—Industry Series: Carbon Black Manufacturing.
Department of Commerce, Washington, DC. EC02-311-
325182. September 2004.
U.S. Census Bureau (1999) 7997 Economic Census:
Manufacturing—Industry Series: Carbon Black Manufacturing.
Department of Commerce, Washington, DC. EC97M-3251F.
August 1999.
Silicon Carbide Production
Corathers, L. (2006) Personal communication between Lisa
Corathers, Commodity Specialist, U.S. Geological Survey
and Erin Fraser of ICE International. October 2006.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa, T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
U.S. Census Bureau (2006) U.S International Trade
Commission (USITC) Trade DataWeb. Available online at
. Accessed Fall 2006.
U.S. Census Bureau (2005) U.S International Trade
Commission (USITC) Trade DataWeb. Available online at
. Accessed Fall 2005.
USGS (2006) Minerals Yearbook: Manufactured Abrasives
Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2005a) Minerals Yearbook: Manufactured Abrasives
Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2005b) Minerals Yearbook: Silicon Annual Report
2004. U.S. Geological Survey, Reston, VA.
USGS (2004a) Minerals Yearbook: Manufactured Abrasives
Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2004b) Minerals Yearbook: Silicon Annual Report
2003. U.S. Geological Survey, Reston, VA.
USGS (2003a) Minerals Yearbook: Manufactured Abrasives
Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2003b) Minerals Yearbook: Silicon Annual Report
2002. U.S. Geological Survey, Reston, VA.
USGS (2002a) Minerals Yearbook: Manufactured Abrasives
Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2002b) Minerals Yearbook: Silicon Annual Report
2001. U.S. Geological Survey, Reston, VA.
USGS (200 la) Minerals Yearbook: Manufactured Abrasives
Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (200 Ib) Minerals Yearbook: Silicon Annual Report
2000. U.S. Geological Survey, Reston, VA.
USGS (2000a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (2000b) Minerals Yearbook: Silicon Annual Report
1999. U.S. Geological Survey, Reston, VA.
USGS (1999a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1999b) Minerals Yearbook: Silicon Annual Report
1998. U.S. Geological Survey, Reston, VA.
USGS (1998a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1998b) Minerals Yearbook: Silicon Annual Report
1997. U.S. Geological Survey, Reston, VA.
USGS (1997a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1997b) Minerals Yearbook: Silicon Annual Report
1996. U.S. Geological Survey, Reston, VA.
USGS (1996a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1996b) Minerals Yearbook: Silicon Annual Report
1995. U.S. Geological Survey, Reston, VA.
USGS (\995a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1995b) Minerals Yearbook: Silicon Annual Report
1994. U.S. Geological Survey, Reston, VA.
References 11-21
-------
USGS (1994a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1994b) Minerals Yearbook: Silicon Annual Report
1993. U.S. Geological Survey, Reston, VA.
USGS (1993a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1992. U.S. Geological Survey, Reston, VA.
USGS (1993b) Minerals Yearbook: Silicon Annual Report
1992. U.S. Geological Survey, Reston, VA.
USGS (1992a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1991. U.S. Geological Survey, Reston, VA.
USGS (1992b) Minerals Yearbook: Silicon Annual Report
1991. U.S. Geological Survey, Reston, VA.
USGS (1991a) Minerals Yearbook: Manufactured Abrasives
Annual Report 1990. U.S. Geological Survey, Reston, VA.
USGS (1991b) Minerals Yearbook: Silicon Annual Report
1990. U.S. Geological Survey, Reston, VA.
Nitric Acid Production
C&EN (2006) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 84(28):64. July 10, 2006.
C&EN (2005) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 83(28):72. July 11, 2005.
C&EN (2004) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 82(27):54. July 5, 2004.
C&EN (2003) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 81(30):56. July 28. 2003.
C&EN (2002) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 80(25):62. June 24, 2002.
C&EN (2001) "Facts and Figures in the Chemical Industry."
Chemical & Engineering News, 79(26):46. June 25, 2001.
Choe, J.S.,P.J. Cook, and P.P. Petrocelli (1993) "Developing
N2O Abatement Technology for the Nitric Acid Industry."
Prepared for presentation at the 1993 ANPSG Conference.
Air Products and Chemicals, Inc., Allentown, PA.
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), 3.35. May 2000.
EPA (1997) Compilation of Air Pollutant Emission Factors,
AP-42, Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park,
NC. October 1997.
Adipic Acid Production
ACC (2003) "Adipic Acid Production." Table 3.12-
Production of the Top 100 Chemicals. American Chemistry
Council Guide to the Business of Chemistry. August 2003.
C&EN (1995) "Production of Top 50 Chemicals Increased
Substantially in 1994." Chemical & Engineering News,
73(15):17. April 10,1995.
C&EN (1994) "Top 50 Chemicals Production Rose Modestly
Last Year." Chemical & Engineering News, 72( 15): 13. April
11, 1994.
C&EN (1993) "Top 50 Chemicals Production Recovered
Last Year." Chemical & Engineering News, 71 (15): 11. April
12, 1993.
C&EN (1992) "Production of Top 50 Chemicals Stagnates
in 1991." Chemical & Engineering News, 70(15): 17. April
13, 1992.
Childs, D. (2003) Personal communication between Dave
Childs of DuPont, USA and Duncan Rotherham of ICF
International. August 7, 2003.
Childs, D. (2002) Personal communication between Dave
Childs of DuPont, USA and Laxmi Palreddy of ICF,
Consulting, USA. August 8, 2002.
CMR (2001) "Chemical Profile: Adipic Acid." Chemical
Market Reporter. July 16, 2001.
CMR (1998) "Chemical Profile: Adipic Acid." Chemical
Market Reporter. June 15, 1998.
CW (2005) "Product Focus: Adipic Acid." Chemical Week.
May 4, 2005.
CW (1999) "Product Focus: Adipic Acid/Adiponitrile."
Chemical Week, p. 31. March 10, 1999.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, National
Greenhouse Gas Inventories Programme, Montreal, 1PCC-
XVI/Doc. 10 (1.IV.2000). May. Pg 3.34.
Reimer, R. (1999) Personal communication between Ron
Reimsr of DuPont, USA and Heike Mainhardt of ICF
International. May 19, 1999.
Thiemens, M.H., and W.C. Trogler (1991) "Nylon production;
an unknown source of atmospheric nitrous oxide." Science
251:932-934.
Subsitutior ot Ozone Depleting
Substances
IPCC/UNEP/OECD/1EA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
11-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
HCFC-22 Production
ARAP (2006) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental
Protection Agency. July 11, 2006.
ARAP (2005) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S.
Environmental Protection Agency. August 9, 2005.
ARAP (2004) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S.
Environmental Protection Agency. June 3, 2004.
ARAP (2003) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental
Protection Agency. August 18. 2003.
ARAP (2002) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S.
Environmental Protection Agency. August 7, 2002.
ARAP (2001) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S.
Environmental Protection Agency. August 6, 2001.
ARAP (2000) Electronic mail communication from Dave
Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental
Protection Agency. August 13, 2000.
ARAP (1999) Facsimile from Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy
to Deborah Ottinger Schaefer of the U.S. Environmental
Protection Agency. September 23, 1999.
ARAP (1997) Letter from Dave Stirpe, Director, Alliance
for Responsible Atmospheric Policy to Elizabeth Dutrow
of the U.S. Environmental Protection Agency. December
23. 1997.
Rand, S., M. Branscome, and D. Ottinger (1999)
"Opportunities for the Reduction of HFC-23 Emissions from
the Production of HCFC-22." In: Proceedings from the Joint
IPCC/TEAP Expert Meeting On Options for the Limitation
of Emissions of MFCs and PFCs. Petten, the Netherlands,
26-28 May 1999.
RTI (1997) "Verification of Emission Estimates of HFC-23
from the Production of HCFC-22: Emissions from 1990
through 1996." Report prepared by Research Triangle
Institute for the Cadmus Group. November 25,1997; revised
February 16, 1998.
Electrical Transmission and Distribution
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S.Eggleston,L.Buenida,K.Miwa,TNgara,
and K. Tanabe, eds.: Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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.
Maiss, M. and C.A.M. Brenninkmeijer (2000) "A reversed
trend in emissions of SF6 to the atmosphere?" Non-CO2
Greenhouse Gases: Scientific Understanding, Control, and
Implementation, Proceedings of the Second International
Symposium, Noordvvijkerhout, the Netherlands, September
8-10, 1999, Kluvver Academic Publishers, 2000, 199.
O'Connell. P., F. Heil, J. Henriot, G. Mauthe, H. Morrison, L.
Neimeyer, M. Pittroff, R. Probst, J.P. Tailebois (2002) SFfi in
the Electric Industry, Status 2000, Cigre. February 2002.
RAND (2004) Katie D. Smythe, RAND Environmental
Science and Policy Center, "Trends in SF6 Sales and End-
Use Applications: 1961 -2003," International Conference on
SF6 and the Environment: Emission Reduction Strategies,
Scottsdale, AZ, December 1-3, 2004.
UDI (2004) 2004 UDl Directory of Electric Power Producers
and Distributors, 112"' Edition, Platts.
UDI (2001) 2001 UDI Directory of Electric Power Producers
and Distributors, 109'1' Edition, Platts.
Semiconductor Manufacture
Burton, C.S., and R. Beizaie (2001) "EPA's PFC
Emissions Model (PEVM) v. 2.14: Description and
Documentation" prepared for Office of Global Programs,
U. S. Environmental Protection Agency, Washington, DC.
20001 November 2001.
Burton, C.S., and H. Mallya (2005) "PFC Reduction/Climate
Partnership for the Semiconductor Industry: Trends in
Emissions and Documentation," Draft Report, prepared
for Office of Atmospheric Programs, U. S. Environmental
Protection Agency, Washington, DC. 20001. August 2005.
Citigroup Smith Barney (2005) Global Supply/Demand
Model for Semiconductors. March 2005.
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.
References 11-23
-------
ITRS (2005) International Technology Roadmap for
Semiconductors: 2004 Update. January 2005. This and
earlier editions and updates are available at Information about the number of interconnect
layers for years 1990-2010 is contained in Burton and
Beizaie, 2001. PEVM is updated using new editions and
updates of the ITRS, which are published annually.
Semiconductor Equipment and Materials Industry (2006)
World Fab Watch, April 2006 Edition.
Strategic Marketing Associates (2003) Personal
communication between C. S. Burton and George Burns,
President of Strategic Marketing Associates, Santa Cruz,
C A. September 5,2003.
VLSI Research, Inc. (2005) Document 327202, V5.061-
Worldwide Silicon Demand by Wafer Size, by Linewidth and
by Device Type. June 2005. Available online at .
VSLI Research, Inc. (2003) Personal communication
between C. S. Burton and Marta Hernandez, Analyst at VLSI
Research Inc., San Jose, CA. September 5,2003.
Aluminum Production
Gariepy, B. and G. Dube (1992) "Treating Aluminum with
Chlorine." U.S. Patent 5,145,514. Issued September 8,
1992.
IAI (2003) Aluminum Sector Greenhouse Gas Protocol:
Greenhouse Gas Emissions Monitoring and Reporting by
the Aluminum Industry, International Aluminum Institute,
May 2003. Available at .
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa, T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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.
Kantamaneni R. and D. Pape (2001) "2000 Aluminum
Inventory — Uncertainty Analysis", Under EPA Contract No.
68-W6-0029, Task Order 408. Memorandum to EPA from
ICE International. October, 18,2001.
Ko, M.K.W., N.D. Sze, W.-C. Wang, G. Shia, A. Goldman,
F.J. Murcray, D.G. Murcray, and C.P. Rinsland (1993)
"Atmospheric Sulfur Hexafluoride: Sources, Sinks, and
Greenhouse Warming." Journal of Geophysical Research,
98:10499-10507.
MacNeal, J., T. Rack, and R. Corns (1990) "Process for
Degassing Aluminum Melts with Sulfur Hexafluoride." U.S.
Patent 4,959,101. Issued September 25, 1990.
Ten Eyck, N. and M. Lukens (1996) "Process for
Treating Molten Aluminum with Chlorine Gas and Sulfur
Hexafluoride to Remove Impurities." U.S. Patent 5,536,296.
Issued July 16, 1996.
US A A (2006) Primary Aluminum Statistics. U.S. Aluminum
Association, Washington, DC. January 2006.
USAA(2005) Primary Aluminum Statistics. U.S. Aluminum
Association, Washington, DC. January 2005.
US AA (2004) Primary Aluminum Statistics .U.S. Aluminum
Association, Washington, DC. January 2004.
USGS (2006) Mineral Commodity Summaries. U.S. Geological
Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Aluminum Annual Report
2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Aluminum Annual Report
2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Aluminum Annual Report
1999. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Aluminum Annual Report
1997. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Aluminum Annual Report
1994. U.S. Geological Survey, Reston. VA.
Victor, D.G. and GJ. MacDonald (1998) "A Model for
Estimating Future Emissions of Sulfur Hexafluoride and
Perfluorcarbons." Interim Report for the International
Institute for Applied Systems Analysis (IIASA). July, 1998.
Available online at . Accessed May
23,2000.
Zurecki, Z. (1996) "Effect of Atmosphere Composition on
Homogenizing Al-Mg and Al-Li Alloys." Gas Interactions
in Nonferrous Metals Processing—Proceedings of the 1996
125"' The Minerals, Metals & Materials Society (TMS)
Annual Meeting, Anaheim, CA, 77-93.
Magnesium Production and Processing
Bartos S., J. Marks, R. Kantamaneni, C. Laush (2003)
"Measured SF6 Emissions from Magnesium Die Casting
Operations," Magnesium Technology 2003, Proceedings of
The Minerals, Metals & Materials Society (TMS) Conference.
March 2003.
EPA (2004) Characterization of Cover Gas Emissions from
US. Magnesium Die Casting, Office of Air and Radiation, U.S.
Environmental Protection Agency. EPA430-R-04-004.
Gjestland, H. and D. Magers (1996) "Practical Usage of
Sulphur Hexafluoride for Melt Protection in the Magnesium
Die Casting Industry." #13, International Magnesium
Association 1996 Annual Conference Proceedings, Ube
City, Japan.
11-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
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.
RAND (2002) Katie D. Smythe, RAND Environmental
Science and Policy Center, "Production and Distribution of
SF6 by End-Use Application." International Conference on
SF6 and the Environment: Emission Reduction Strategies,
San Diego, CA. November 21-22.
USGS (2006) Minerals Yearbook: Magnesium Annual Report
2005. U.S. Geological Survey, Reston, VA. Available online
at .
USGS (2005a) Minerals Yearbook: Magnesium Annual
Report 2004. U.S. Geological Survey, Reston, VA.
Available online at .
USGS (2005b) Personal communication between Jeremy
Scharfenberg of ICF International and Deborah A. Kramer of
the U.S. Geological Survey, Reston, VA. September, 2005.
USGS (2003) Minerals Yearbook: Magnesium Annual Report
2002. U.S. Geological Survey, Reston, VA. Available online
at .
USGS (2002) Minerals Yearbook: Magnesium Annual Report
2001 .U.S. Geological Survey, Reston, VA. Available online
at .
industrial Sources of Indirect
Greenhouse Gases
EPA (2006) Air Emissions Trends —Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air Pollution
and the Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency. December 22, 2003.
EPA (1997) Compilation of Air Pollutant Emission Factors,
AP-42. Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park,
NC. October 1997.
Solvent and Other Product Use
Nitrous Oxide Product Usage
CGA (2003) "CGA Nitrous Oxide Abuse Hotline."
Compressed Gas Association. November 3,2003. Available
online at .
CGA (2002) "CGA/NWSA Nitrous Oxide Fact Sheet."
Compressed Gas Association. March 25, 2002.
Heydorn, B. (1997) "Nitrous Oxide —North America."
Chemical Economics Handbook, SRI Consulting. May 1997.
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.IV2000). May 2000.
Kirt-Otthmer (1990) "Anesthetics." Kirk-Otthmer Encyclopedia
of Chemical Technology, Volume 2,781-782.
Tupman, M. (2003) Personal communication between Martin
Tupman of Airgas Nitrous Oxide and Daniel Lieberman of
ICF International. August 8, 2003.
Tupman, M. (2002) Personal communication between Martin
Tupman of Airgas Nitrous Oxide and Laxmi Palreddy of ICF
International. July 3, 2002.
Indirect Greenhouse Gas Emissions from
Solvent Use
EPA (2006) Air Emissions Trends —Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air Pollution
and the Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency. December 22, 2003.
EPA (1997) Compilation of Air Pollutant Emission Factors,
AP-42. Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park,
NC. October 1997.
References 11-25
-------
Agriculture
Enteric Fermentation
Crutzen, P.J., I. Aselmann, and W. Seller (1986) "Methane
Production by Domestic Animals, Wild Ruminants, Other
Herbivores, Fauna, and Humans." Tellux 386:271-284.
Donovan, K. (1999) Personal Communication between
Kacey Donovan of the University of California at Davis and
staff at ICF International.
Donovan, K. and L. Baldwin (1999) Results of the
AAMOLLY model runs for the Enteric Fermentation Model.
University of California, Davis.
EPA(2000) Draft Enteric Fermentation Model Documentation.
Office of Air and Radiation, U.S. Environmental Protection
Agency, Washington, DC. J une 13, 2000.
EPA (1993) Anthropogenic Methane Emissions in the United
States: Estimates for 1990. Report to Congress. Office of
Air and Radiation, U.S. Environmental Protection Agency,
Washington, DC.
FAO (2006) FAOSTAT Statistical Database. Food and
Agriculture Organization of the United Nations. Available
online at .
Feedstuffs (1998) "Nutrient requirements for pregnant
replacement heifers." Feedstuffs, Reference Issue, p. 50.
ICF (2006) Cattle Enteric Fermentation Model: Model
Documentation. Prepared by ICF International for the
Environmental Protection Agency. June 2006.
ICF (2003) Uncertainty Analysis of 2001 Inventory Estimates
of Methane Emissions from Livestock Enteric Fermentation in
the U.S. Memo from ICF International to the Environmental
Protection Agency. May 2003.
1PCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston,L. Buenida, K. Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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.
1PCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Johnson, D. (2002) Personal Communication between Don
Johnson of Colorado State University, Fort Collins, and ICF
International.
Johnson, D. (2000) Enteric Fermentation Model Progress and
Changes. Comments prepared by Don Johnson of Colorado
State University. Fort Collins, for ICF International.
Johnson, D. (1999) Personal Communication between Don
Johnson of Colorado State University, Fort Collins, and
David Conneely of ICF International.
Lange, J. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and John Lange, Agricultural Statistician, U.
S. Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
NRC 12000) Nutrient Requirements of Beef Cattle: Seventh
Revised Edition: Update 2000. Table 11-1, Appendix Table
1. National Research Council.
NRC (1999) 1996 Beef NRC, Appendix Table 22. National
Research Council.
USDA (2()06a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 2,2006. Available online at .
USDA (2006b) Livestock Slaughter. National Agriculture
Statistics Service. U.S. Department of Agriculture,
Washington, DC. August 2,2006. Available online at
USDA (2()06c) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. August 2,2006. Available online at .
USDA(2006d) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 2,2006. Available online at .
USDA (2006f) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 2, 2006. Available online at .
USDA (2005a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 8, 2005. Available online at .
USDA (2005b) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington,DC. August 8,2005. Available online at .
USDA (2005c) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture.
Washington, DC. August 8,2005. Available online at .
11-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
USDA (2005d) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 8, 2005. Available online at .
USDA (2005e) Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. August 8,2005. Available online at .
USDA (2005f) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
August 8, 2005. Available online at .
USDA (20051) Census of Agriculture. National Agriculture
Statistics Service. U.S. Department of Agriculture,
Washington, DC. Data for 1992, 1997, and 2002 accessed
from in June
2005.
USDA (2004a) Cattle. National Agriculture Statistics
Service. U.S. Department of Agriculture, Washington, DC.
July 1, 2004. Available online at .
USDA (2004b) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
June 27, 2003. Available online at .
USDA (2004c) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. July 6-7,2004. Available online at .
USDA (2004d) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. July 1, 2004. Available online at .
USDA (2004e) Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 31, 2003. Available online at
.
USDA (2004f) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
July 1, 2004. Available online at .
USDA (2004g) Chicken and Eggs-Final Estimates
1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004h) Poultry Production and Value-Final
Estimates 1998-2002. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 2004. Available online at .
USDA (2003a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 31,2003. Available online at .
USDA (2003b) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
June 27, 2003. Available online at .
USDA (2003c) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 24-June 20,2003. Available online
at .
USDA (2003d). Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington. DC. February 14, 2003. Available online at
.
USDA (2003e) Sheep and Goats, U.S. Department of
Agriculture, National Agriculture Statistics Service,
Washington, DC. January 31. 2003. Available online at
.
USDA(2003f) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 14, 2003. Available online at .
USDA (2002a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 1,2002. Available online at .
\JSDA(2002b) Hogs tind Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
June 28. 2002. Available online at .
USDA (2002c) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 25-June 21,2002. Available online
at .
USDA (2002d) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 15, 2002. Available online at
.
USDA (2()02e) Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 1, 2002. Available online at
.
USDA (2002f) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 15, 2002. Available online at .
USDA (200la) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 26,2001 .Available online at .
References 11-27
-------
USD A (2001 b) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
December 28, 2001. Available online at .
USDA (200Ic) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 19-December 21,2001. Available
online at .
USDA (200Id) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 16, 2001. Available online at
.
USDA (200le) Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 26, 2001. Available online at
.
USDA (200 If) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 16, 2001. Available online at .
USDA (2000a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 28,2000. Available online at .
USDA (2000b) Chicken and Eggs-Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . Accessed May 3,2000.
USDA (2000c) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 21-December 22,2000. Available
online at .
USDA (2000d) Milk Production. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 16, 2000. Available online at
.
USDA(2000e) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 18, 2000. Available online at .
USDA (2000f) Chicken and Eggs-Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . Accessed May 3,2000.
USDA (1999a) Cattle, Final Estimates 1994-1998.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at .
USDA (1999b) Poultry Production and Value-Final
Estimates 1994-97. National Agriculture Statistics Service,
U.S. Department of Agriculture, Washington, DC. March
1999. Available online at .
USDA (1999c) Livestock Slaughter. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 22-December 23,1999. Available
online at .
USDA (1999d) Milk Cows and Milk Production-Final
Estimates 1993-1997. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 1999. Available online at .
USDA (1999e) Sheep and Goats, Final Estimates 1994-98.
U.S. Department of Agriculture, National Agriculture
Statistics Service, Washington, DC. Available online at
.
USD A (1999f) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington,
DC. Available online at .
USDA (1999g) Miscellaneous Livestock and Animal
Specialties Inventory and Sales: 1997 and 1992, Table 25.
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. . Accessed
May 2000.
USDA (1998a) Hogs and Pigs, Final Estimates 1993-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at .
USD A (1998b) Chicken and Eggs -Final Estimates 1994-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998. Available online
at .
USDA (1996) Beef Cow I Calf Health and Productivity
Audit (CHAPA): Forage Analyses from Cow/Calf Herds
in 18 States. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. March 1996.
Available online at .
USDA (1995a) Cattle, Final Estimates 1989-93. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington,DC. January 1995. Available online
at .
USDA(1995b) Dairy Outlook. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
February 27, 1995. Available online at .
11-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
USD A (1995c) Poultry Production and Value-Final
Estimates 1988-1993. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 1995. Available online at .
USDA (1994a) Hogs and Pigs, Final Estimates 1988-92.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1994. Available
online at .
USDA (1994b) Sheep and Goats, Final Estimates 1988-93.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 31, 1994. Available
online at .
USDA:APHIS:VS (2002) Reference of 2002 Dairy
Management Practices. National Animal Health Monitoring
System, Fort Collins, CO. Available online at .
USDA: APHIS: VS (1998) Beef '97. National Animal Health
Monitoring System, Fort Collins, CO. Available online at
.
USDA:APHIS:VS (1996) Reference of 1996 Dairy
Management Practices. National Animal Health Monitoring
System, Fort Collins, CO. Available online at .
USDA:APHIS:VS (1994) Beef Cow/Calf Health and
Productivity Audit. National Animal Health Monitoring
System, Fort Collins, CO. Available online at .
USDA:APHIS:VS (1993) Beef Cow/Calf Health and
Productivity Audit. National Animal Health Monitoring
System, Fort Collins, CO. August 1993. Available online at
.
Western Dairyman (1998) "How Big Should Heifers Be at
Calving?" The Western Dairyman, p. 12. September 1998.
Manure Management
Anderson, S. (2000) Telephone conversation between
Lee-Ann Tracy of ERG and Steve Anderson, Agricultural
Statistician, National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. May 31,
2000.
AS AE (1999) ASAE Standards 1999,46"' Edition. American
Society of Agricultural Engineers, St. Joseph, MI.
Bryant, M.P., V.H. Varel, R.A. Frobish, and H.R. Isaacson
(1976) In H.G. Schlegel (ed.); Seminar on Microbial Energy
Conversion. E. Goltz KG, Gottingen, Germany.
Deal, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Peter B. Deal, Rangeland Management
Specialist, Florida Natural Resource Conservation Service.
June 21,2000.
EPA (2006) AgSTAR Digest. Office of Air and Radiation,
U.S. Environmental Protection Agency, Washington, DC.
Winter 2006. Available online at Accessed July 2006.
EPA (2004) National Emission Inventory —Ammonia
Emissions from Animal Husbandry Operations. Office of
Air and Radiation, U.S. Environmental Protection Agency,
Washington, DC. Available online at .
EPA (2003a) Inventory of U.S. Greenhouse Gas Emissions and
Sinks: 1990-2001. EPA 430-R-03-004. U.S. Environmental
Protection Agency, Washington, DC. April 15, 2003.
EPA (2003b) AgSTAR Digest. Office of Air and Radiation,
U.S. Environmental Protection Agency, Washington, DC.
Winter 2003. Accessed July 2006.
EPA (2002a) Development Document for the Final Revisions
to the National Pollutant Discharge Elimination System
(NPDES) Regulation and the Effluent Guidelines for
Concentrated Animal Feeding Operations (CAFOS). U.S.
Environmental Protection Agency. EPA-821-R-03-001.
December 2002.
EPA (2002b) Cost Methodology for the Final Revisions
to the National Pollutant Discharge Elimination System
Regulation and the Effluent Guidelines for Concentrated
Animal Feeding Operations. U.S. Environmental Protection
Agency. EPA-821-R-03-004. December 2002.
EPA (2000) AgSTAR Digest. Office of Air and Radiation, U.S.
Environmental Protection Agency, Washington, DC.
EPA (1992) Global Methane Emissions from Livestock and
Poultry Manure, U.S. Environmental Protection Agency,
Office of Air and Radiation. February 1992.
ERG (2003) "Methodology for Estimating Uncertainty for
Manure Management Greenhouse Gas Inventory." Contract
No, GS-10F-0036, Task Order 005. Memorandum to EPA
from ERG, Lexington, MA. September 26, 2003.
ERG (2001) Summary of development of MDP Factor for
methane conversion factor calculations. ERG, Lexington,
MA. September 2001.
ERG (2000a) Calculations: Percent Distribution of Manure
for Waste Management Systems. ERG, Lexington, MA.
August 2000.
ERG (2000b) Discussion of Methodology for Estimating
Animal Waste Characteristics (Summary of Bo Literature
Review). ERG, Lexington, MA. June 2000.
FAO (2006) Yearly U.S. total horse population data from the
Food and Agriculture Organization of the United Nations
database. Available online at .
Accessed May 2006.
References 11-29
-------
Garrett, W.N. and D.E. Johnson (1983) "Nutritional
energetics of ruminants." Journal of Animal Science,
57(suppl.2):478^97. July 1983.
Groffman, P.M., R. Brumme, K. Butterbach-Bahl, K.E.
Dobbie, A.R. Mosier, D. Ojima, H. Papen, WJ. Parton.
K.A. Smith, and C. Wagner-Riddle (2000) "Evaluating
annual nitrous oxide fluxes at the ecosystem scale." Global
Biogeochemcial Cycles, 14(4):1061-1070.
Hashimoto. A.G. (1984) "Methane from Swine Manure:
Effect of Temperature and Influent Substrate Composition on
Kinetic Parameter (k)." Agricultural Wastes, 9:299-308.
Hashimoto, A.G., V.H. Varel, and Y.R. Chen (1981)
"Ultimate Methane Yield from Beef Cattle Manure; Effect
of Temperature, Ration Constituents, Antibiotics and Manure
Age." Agricultural Wastes, 3:241-256.
Hill, D.T. (1984) "Methane Productivity of the Major Animal
Types." Transactions oftheASAE, 27(2):530-540.
Hill, D.T. (1982) "Design of Digestion Systems for
Maximum Methane Production." Transactions of the ASAE,
25(1):226-230.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston,L. Buenida. K. Miwa,T. Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagavva. Japan.
Johnson, D. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Dan Johnson, State Water Management
Engineer, California Natural Resource Conservation Service.
June 23,2000.
Lange, J. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and John Lange, Agricultural Statistician, U.S.
Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
Miller, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Paul Miller, Iowa Natural Resource
Conservation Service. June 12, 2000.
Milton, B. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Bob Milton, Chief of Livestock Branch,
U.S. Department of Agriculture, National Agriculture
Statistics Service. May 1, 2000.
Morris, G.R. (1976) Anaerobic Fermentation of Animal
Wastes: A Kinetic and Empirical Design Fermentation. M.S.
Thesis. Cornell University.
NOAA (2005) National Oceanic and Atmospheric
Administration (NOAA), National Climate Data Center
(NCDC) Available online at (for all states except Alaska and Hawaii) and
(for Alaska
and Hawaii). Accessed June 2005.
Pederson, L. and D. Pape. (2006) 1990-2005 Volatile Solids
and Nitrogen Excretion Rates, Deliverable Under EPA
Contract GS-10F-0124J,Task Order 056-01. Memorandum
to EPA from ICE International. August 5, 2006.
Poe, G.. N. Bills, B. Bellows. P. Crosscombe, R. Koelsch,
M. Kreher, and P. Wright (1999) Staff Paper Documenting
the Status of Dairy Manure Management in New York:
Current Practices and Willingness to Participate in Voluntary
Programs, Department of Agricultural, Resource, and
Managerial Economics, Cornell University, Ithaca. New
York, September.
Safley, L.M., Jr. (2000) Telephone conversation between
Deb EJartram of ERG and L .M. Safley, President, Agri-Waste
Technology. June and October 2000.
Safley, L.M., Jr. and P.W. Westerman (1990) "Psychrophilic
Anaerobic Digestion of Animal Manure: Proposed Design
Methodology." Biological Wastes., 34:133-148.
Stettler, D. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Don Stettler, Environmental Engineer,
National Climate Center, Oregon Natural Resource
Conservation Service. June 27, 2000.
Sweeten, J. (2000) Telephone conversation between Indra
Mitra of ERG and John Sweeten, Texas A&M University.
June 2000.
UEP (1999) Voluntary Survey Results — Estimated Percentage
Participation/Activity, Caged Layer Environmental
Management Practices, Industry data submissions for EPA
profile development, United Egg Producers and National
Chicken Council. Received from John Thorne, Capitolink.
June 2000.
USDA (2006a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 2006. Available online at .
USDA(2006b) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 2006. Available online at .
USDA (2006c) Chicken and Eggs 2005 Summary,
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. February 2006. Available
online at .
USDA (2006d) Poultry-Production and Value 2005
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2006.
Available online at .
USDA (2006e) Published Estimates Database. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . Accessed May 2006.
11-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
LJSDA (2005a) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 21, 2005. Available online at .
USDA (2005b) Poultry Production and Value Annual
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington. DC. April 28,
2005. Available online at .
USDA (2005c) Quarterly Hogs and Pigs. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 2005. Available
online at .
USDA (2005d) Sheep ami Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 28, 2005. Available online at
.
USDA(2005e) 1992,1997,and 2002 Census of Agriculture.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . Accessed March 2006.
USDA (2004a) Cattle-Final Estimates 1999-2003, U.S.
Department of Agriculture, National Agriculture Statistics
Service. Washington. DC. April 2004. Available online at
.
USDA (2004b) Hogs and Pigs-Final Estimates 1998-2002.
National Agriculture Statistics Service. U.S. Department of
Agriculture, Washington. DC. March 2004. Available online
at .
USDA (2004c) Chicken and Eggs-Final Estimates
1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004d) Poultry Production and Value-Final
Estimates 1998-2002. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 2004. Available online at .
USDA (20()4e) Sheep and Goats-Final Estimates
1999-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2000a) Chicken and Eggs-Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . May 3,2000.
USDA (2000b) Re-aggregated data from the National
Animal Health Monitoring System's (NAHMS) Dairy '96
study provided by Stephen L. Ott of the U.S. Department
of Agriculture, Animal and Plant Health Inspection Service.
June 19,2000.
USDA (2000c) Layers '99-Parl 11: References of 1999
Table Egg Layer Management in the U.S. U.S. Department
of Agriculture, Animal and Plant Health Inspection Service
(APHIS), National Animal Health Monitoring System
(NAHMS). January 2000.
USDA(1999a) Cattle-Final Estimates 1994-98. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1999. Available online
at .
USDA (1999b) Poultry Production and Value-Final
Estimates 1994-97. National Agriculture Statistics Service,
U.S. Department of Agriculture. Washington, DC. March
1999. Available online at .
USDA (1999c) Sheep and Goats-Final Estimates
1994-1998. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January 1999.
Available online at .
USDA (1998a) Hogs and Pigs-Final Estimates 1993-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998. Available
online at .
USDA (1998b) Chicken and Eggs-Final Estimates 1994-
97. National Agriculture Statistics Service, U.S. Department
of Agriculture. Washington, DC. December 1998. Available
online at .
USDA (1998c) Re-aggregated data from the National Animal
Health Monitoring System's (NAHMS) Swine '95 study
aggregated by Eric Bush of the Centers for Epidemiology
and Animal Health , U.S. Department of Agriculture.
USDA (1996a) Agricultural Waste Management Field
Handbook, National Engineering Handbook (NEH),
Part 651. Natural Resources Conservation Service, U.S.
Department of Agriculture. July 1996.
USDA (1996b) Swine '95: Grower/Finisher Part II:
Reference of 1995 U.S. Grower/Finisher Health &
Management Practices. Animal Plant Health and Inspection
Service, U.S. Department of Agriculture, Washington, DC.
June 1996.
USDA (1995a) Cattle-Final Estimates 1989-93. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1995. Available online
at .
References 11-31
-------
USDA (1995b) Poultry Production and Value-Final
Estimates 1988-1993. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 1995. Available online at .
USDA (1994a) Hogs and Pigs-Final Estimates 1988-92.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1994. Available
online at .
USDA (1994b) Sheep and Goats-Final Estimates
1989-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January 31,
1994. Available online at .
Wright, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Peter Wright, Cornell University, College
of Agriculture and Life Sciences. June 23,2000.
Rice Cultivation
Bollich, P. (2000) Telephone conversation between Payton
Deeks of ICF International and Pat Bollich, Professor with
Louisiana State University Agriculture Center. May 17,
2000.
Bossio, D.A., W. Horwath, R.G. Mutters, and C. van
Kessel (1999) "Methane pool and flux dynamics in a rice
field following straw incorporation." Soil Biology and
Biochemistry, 31:1313-1322.
Cantens, G. (2005) Telephone conversation between Lauren
Flinn of ICF International and Janet Lewis, Assistant to
Gaston Cantens, Vice President of Corporate Relations,
Florida Crystals Company. August 4,2005.
Cantens, G. (2004) Telephone conversation between Lauren
Flinn of ICF International and Janet Lewis, Assistant to
Gaston Cantens, Vice President of Corporate Relations,
Florida Crystals Company. July 30, 2004.
Cicerone R.J., C .C. Delwiche, S .C. Tyler, and P.R. Zimmerman
(1992) "Methane Emissions from California Rice Paddies
with Varied Treatments." Global Biogeochemical Cycles
6:233-248.
Deren, C. (2002) Telephone conversation between Caren Mintz
and Dr. Chris Deren, Everglades Research and Education
Centre at the University of Florida. August 15, 2002.
Guethle, D. (2006) Telephone conversation between Lauren
Flinn of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. July
2005.
Guethle, D. (2005) Email correspondence between Lauren
Flinn of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. July
2005.
Guethle, D. (2004) Telephone conversation between Lauren
Flinn of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. June
23,2004.
Guethle, D. (2003) Telephone conversation between Caren
Mintz of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. June
19,2003.
Guethle, D. (2002) Telephone conversation between Caren
Mintz of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. August
19,2002.
Guethle, D. (2001 a) Telephone conversation between Caren
Mintz of ICF International and David Guethle, Agronomy
Specialist at Missouri Cooperative Extension Service. July
31,2001.
Guethle, D. (200 Ib) Telephone conversation between Caren
Mintz of ICF International and David Guethle, Agronomy
Specialist at Missouri Cooperative Extension Service.
September 4,2001.
Guethle, D. (2000) Telephone conversation between Payton
Deeks of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. May
17,2000.
Guethle, D. (1999) Telephone conversation between Payton
Deeks of ICF International and David Guethle, Agronomy
Specialist, Missouri Cooperative Extension Service. August
6,1999.
Holzapfel-Pschorn, A., R. Conrad, and W. Seller (1985)
"Production, Oxidation, and Emissions of Methane in Rice
Paddies." FEMS Microbiology Ecology, 31:343-351.
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/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Kirstein, A. (2006) Telephone conversation between Lauren
Flinn of ICF International and Arthur Kirstein, Coordinator,
Agricultural Economic Development Program, Palm Beach
County Cooperative Extension Service, FL. August 17,
2006.
Kirstein, A. (2004) Telephone conversation between Lauren
Flinn of ICF International and Arthur Kirstein, Coordinator,
Agricultural Economic Development Program, Palm Beach
County Cooperative Extension Service, FL. June 30, 2004.
11-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Kirstein, A. (2003) Telephone conversation between Caren
Mintz of ICF International and Arthur Kirstein, Coordinator,
Agricultural Economic Development Program, Palm Beach
County Cooperative Extension Service, FL. August 13,
2003.
Klosterboer, A. (2003) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
retired Extension Agronomist, Texas A&M University. July
7,2003.
Klosterboer, A. (2002) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. August 19,
2002.
Klosterboer, A. (200la) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. August
6,2001.
Klosterboer, A. (2001b) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. October
8,2001.
Klosterboer, A. (2000) Telephone conversation between
Payton Decks of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. May 18,
2000.
Klosterboer, A. (1999) Telephone conversation between
Catherine Leining of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. June 10,
1999.
Klosterboer, A. (1997) Telephone conversation between
Holly Simpkins of ICF Incorporated and Arlen Klosterboer,
Texas A&M University. December 1, 1997.
Lee, D. (2006) Email correspondence between Lauren Flinn
of ICF International and Danny Lee, OK Farm Service
Agency. July 13,2006.
Lee, D. (2005) Email correspondence between Lauren Flinn
of ICF International and Danny Lee, OK Farm Service
Agency, Stillwater, OK. July and September 2005.
Lee, D. (2004) Telephone conversation between Lauren
Flinn of ICF International and Danny Lee, OK Farm Service
Agency, Stillwater, OK. July 23, 2004.
Lee, D. (2003) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Danny Lee, OK Farm Service Agency, Stillwater, OK.
July 2,2003.
Lindau, C.W. and P.K. Bollich (1993) "Methane Emissions
from Louisiana First and Ratoon Crop Rice." Soil Science,
156:42-48.
Lindau, C.W., P.K Bollich, and R.D. DeLaune (1995) "Effect
of Rice Variety on Methane Emission from Louisiana Rice."
Agriculture, Ecosystems and Environment, 54:109-114.
Linscombe, S. (2006) Email correspondence between Lauren
Flinn of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. Slinscombe@agctr.lsu.edu. August 15,
2006.
Linscombe, S. (2005) Email correspondence between Lauren
Flinn of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. July 2005.
Linscombe, S. (2004) Telephone conversation between
Lauren Flinn of ICF International and Steve Linscombe,
Professor with the Rice Research Station at Louisiana State
University Agriculture Center. June 23,2004.
Linscombe, S. (2003) Telephone conversation between Caren
Mintz of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. June 10, 2003.
Linscombe, S. (2002) Telephone conversation between Caren
Mintz of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. August 21, 2002.
Linscombe, S. (200la) Telephone conversation between
Caren Mintz of ICF International and Steve Linscombe,
Research Agronomist, Rice Research Station in Crowley,
LA. July 30-August 1,2001.
Linscombe, S. (200Ib) Email correspondence between
Caren Mintz of ICF International and Steve Linscombe,
Research Agronomist, Rice Research Station in Crowley,
LA. October 4, 2001.
Linscombe, S. (1999) Telephone conversation between
Catherine Leining of ICF International and Steve Linscombe,
Research Agronomist, Rice Research Station in Crowley,
LA. June 3,1999.
Mayhew, W. (1997) Telephone conversation between
Holly Simpkins of ICF Incorporated and Walter Mayhew,
University of Arkansas, Little Rock. November 24, 1997.
Mutters, C. (2005) Email correspondence between Lauren
Flinn of ICF International and Mr. Cass Mutters, Rice Farm
Advisor for Butte, Glen, and Tehama Counties. University
of California Cooperative Extension Service. July 2004.
Mutters, C. (2004) Telephone conversation between Lauren
Flinn of ICF International and Mr. Cass Mutters, Rice Farm
Advisor for Butte, Glen, and Tehama Counties. University of
California Cooperative Extension Service. June 25,2004.
Mutters, C. (2003) Telephone conversation between Caren
Mintz of ICF International and Mr. Cass Mutters, Rice Farm
Advisor for Butte, Glen, and Tehama Counties. University of
California Cooperative Extension Service. June 23, 2003.
Mutters, C. (2002) Telephone conversation between Caren
Mintz of ICF International and Mr. Cass Mutters, Rice Farm
Advisor for Butte, Glen, and Tehama Counties. University
of California Cooperative Extension Service. August 27,
2002.
References 11-33
-------
Mutters, C. (2001) Telephone conversation between Caren
Mintz of ICF International and Mr. Cass Mutters, Rice Farm
Advisor for Butte, Glen, and Tehama Counties, University
of California Cooperative Extension Service. September 5,
2001.
Saichuk, J. (1997) Telephone conversation between Holly
Simpkins of ICF Incorporated and John Saichuk of Louisiana
State University. November 24,1997.
Sass, R.L., F.M Fisher, P.A. Harcombe, and F.T. Turner
(1991a) "Mitigation of Methane Emissions from Rice Fields:
Possible Adverse Effects of Incorporated Rice Straw." Global
Biogeochemical Cycles, 5:275-287.
Sass, R.L., F.M. Fisher, F.T. Turner, and M.F. Jund (1991b)
"Methane Emissions from Rice Fields as Influenced by Solar
Radiation, Temperature, and Straw Incorporation." Global
Biogeochemical Cycles, 5:335-350.
Sass, R.L., F.M. Fisher, P.A. Harcombe, and F.T. Turner
(1990) "Methane Production and Emissions in a Texas Rice
Field." Global Biogeochemical Cycles, 4:47-68.
Schueneman, T. (200la) Telephone conversation between
Caren Mintz of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
July 30,2001.
Schueneman, T. (2001b) Telephone conversation between
Caren Mintz of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
October 9,2001.
Schueneman, T. (2000) Telephone conversation between
Pay ton Decks of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
May 16,2000.
Schueneman, T. (1999a) Telephone conversation between
Catherine Leining of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL. June
7,1999.
Schueneman, T. (1999b) Telephone conversation between
Payton Deeks of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
August 10,1999.
Schueneman, T. (1999c) Telephone conversation between
John Venezia of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
August 7,1999.
Schueneman, T. (1997) Telephone conversation between
Barbara Braatz of ICF Incorporated and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
November 7,1997.
Slaton, N. (2001a) Telephone conversation between Caren
Mintz of ICF International and Nathan Slaton, Extension
Agronomist—Rice, University of Arkansas Division of
Agriculture Cooperative Extension Service. August 23,
2001.
Slaton, N. (2001b) Telephone conversation between Caren
Mintz of ICF International and Nathan Slaton, Extension
Agronomist—Rice, University of Arkansas Division of
Agriculture Cooperative Extension Service. October 3,
2001.
Slaton, N. (2000) Telephone conversation between Payton
Deeks of ICF International and Nathan Slaton, Extension
Agronomist-Rice, University of Arkansas Division of
Agriculture Cooperative Extension Service. May 20,2000.
Slaton, N. (1999) Telephone conversation between
Catherine Leining of ICF International and Nathan Slaton,
Extension Agronomist —Rice, University of Arkansas
Division of Agriculture Cooperative Extension Service.
June 3, 1999.
Stansel, J. (2005) Email correspondence between Lauren
Flinn of ICF International and Dr. Jim Stansel, Resident
Director and Professor Emeritus, Texas A&M University
Agricultural Research and Extension Center. July 2005.
Stansel, J. (2004) Telephone conversation between Lauren
Flinn of ICF International and Dr. Jim Stansel, Resident
Director and Professor Emeritus, Texas A&M University
Agricultural Research and Extension Center. July 12,
2004,
Stevens, G. (1997) Telephone conversation between Holly
Simpkins of ICF Incorporated and Gene Stevens, Extension
Specialist, Missouri Commercial Agriculture Program, Delta
Research Center. December 17,1997.
Street, J. (2003) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Joe Street, Rice Specialist, Mississippi State University,
Delta Research Center. June 19, 2003.
Street, J. (2002) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Joe Street, Rice Specialist, Mississippi State University,
Delta Research Center. August 19, 2002.
Street, J. (200la) Telephone conversation between Caren
Mintz of ICF International and Dr. Joe Street, Mississippi
State University, Delta Research and Extension Center and
Delta Branch Station. August 1,2001.
Street, J. (2001b) Telephone conversation between Caren
Mintz of ICF International and Dr. Joe Street, Mississippi
State University, Delta Research and Extension Center and
Delta Branch Station. October 3,2001.
Street, J. (2000) Telephone conversation between Payton
Deeks of ICF International and Joe Street, Rice Specialist,
Mississippi State University, Delta Research Center. May
17,2000.
Street, J. (1999) Telephone conversation between Catherine
Leining of ICF International and Joe Street, Rice Specialist,
Mississippi State University, Delta Research Center. June
8,1999.
11-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Street, J. (1997) Telephone conversation between Holly
Simpkins of ICF Incorporated and Dr. Joe Street, Mississippi
State University, Delta Research and Extension Center and
Delta Branch Station. December 1,1997.
Texas Agricultural Experiment Station (2006) 2005-Texas
Rice Crop Statistics Report. Agricultural Research and
Extension Center, Texas Agricultural Experiment Station,
Texas A&M University System, p. 8. Available online at
.
USDA (2006) Crop Production 2005 Summary, National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at .
USDA (2005) Crop Production 2004 Summary. National
Agricultural Statistics Service, U.S. Department of
Agriculture. Available online at . Accessed June 2005.
USDA (2003) Field Crops, Final Estimates 1997-2002.
Statistical Bulletin No. 982. National Agricultural Statistics
Service, Agricultural Statistics Board, U.S. Department
of Agriculture, Washington, DC. Available online at
.
Accessed September 2005.
USDA (1998) Field Crops Final Estimates 1992-97.
Statistical Bulletin Number 947 a. National Agricultural
Statistics Service, U.S. Department of Agriculture. Available
online at . Accessed July
2001.
USDA (1994) Field Crops Final Estimates 1987-1992.
Statistical Bulletin Number 896. National Agricultural
Statistics Service,U.S. Department of Agriculture. Available
online at . Accessed July
2001.
Walker, T. (2005) Email correspondence between Lauren
Flinn of ICF International and Tim Walker, Assistant
Research Professor, Mississippi State University Delta
Branch Exp. Station. July 2005.
Wilson, C. (2006) Email coorespondence between Lauren
Flinn of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. (870) 673-2661. Wilson@uamont.edu.
August 8, 2006.
Wilson, C. (2005) Email correspondence between Lauren
Flinn of ICF Internationa] and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. August 2005.
Wilson, C. (2004) Telephone conversation between Lauren
Flinn of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. June 23, 2004.
Wilson, C. (2003) Telephone conversation between Caren
Mintz of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. June 11, 2003.
Wilson, C. (2002) Telephone conversation between Caren
Mintz of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. August 23, 2002.
Agricultural Soil Management
AAPFCO (2006) Commercial Fertilizers 2005. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2005) Commercial Fertilizers 2004. Association
of American Plant Food Control Officials and The Fertilizer
Institute University of Kentucky, Lexington, KY.
AAPFCO (2004) Commercial Fertilizers 2003. Association
of American Plant Food Control Officials and The Fertilizer
Institute University of Kentucky, Lexington, KY.
AAPFCO (2003) Commercial Fertilizers 2002. Association
of American Plant Food Control Officials and The Fertilizer
Institute University of Kentucky, Lexington, KY.
AAPFCO (2002) Commercial Fertilizers 2001. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2000a) 1999-2000 Commercial Fertilizers
Data, ASCII files. Available from David Terry, Secretary,
Association of American Plant Food Control Officials.
AAPFCO (2000b) Commercial Fertilizers 2000. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1999) Commercial Fertilizers 1999. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1998) Commercial Fertilizers 1998. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1997) Commercial Fertilizers 1997. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1996) Commercial Fertilizers 1996. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1995) Commercial Fertilizers 1995. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
Alexander, R.B. and R.A. Smith (1990) County-Level
Estimates of Nitrogen and Phosphorous Fertilizer Use in
the United States, 1945-1985. U.S. Geological Survey Open
File Report 90-130.
References 11-35
-------
Anderson, S. (2000) Telephone conversation between
Lee-Ann Tracy of ERG and Steve Anderson, Agricultural
Statistician, U.S. Department of Agriculture, National
Agriculture Statistics Service, Washington, DC. May 31,
2000.
Anonymous (1924) Fertilizer Used on Cotton, 1923-1924.
"Miscellaneous Agricultural Statistics," Table 753. 7924
Yearbook of the Department of Agriculture, 1171.
AS AE (1999) ASAE Standards 1999,46"' Edition. American
Society of Agricultural Engineers, St. Joseph, MI.
Bastian, R. (2006) Telephone conversation between Lauren
Flinn of ICF International and Robert Bastian, Office of
Water, U .S. Environmental Protection Agency, Washington,
DC. July 17,2006.
Bastian,R. (2005) Telephone conversation between Lauren
Flinn of ICF International and Robert Bastian, Office of
Water, U .S. Environmental Protection Agency, Washington,
DC. September 2005.
Bastian, R. (2003) Telephone conversation between Caren
Mintz of ICF International and Robert Bastian, Office of
Water, U.S. Environmental Protection Agency, Washington,
DC. August 13,2003.
Bastian, R. (2002) Telephone conversation between Caren
Mintz of ICF International and Robert Bastian, Office of
Water, U.S. Environmental Protection Agency, Washington,
DC. August 23,2002.
Battaglin, W.A., and D.A. Goolsby (1994) Spatial Data in
Geographic Information System Format on Agricultural
Chemical Use, Land Use, and Cropping Practices in the
United States. U.S. Geological Survey Water-Resources
Investigations Report 94-4176.
Bogue A.G. (1963) From Prairie to Corn Belt: Farming on
the Illinois and Iowa prairies in the Nineteenth Century. The
University of Chicago Press, Chicago, 1L.
Bonnen C.A., and F.F. Elliott (1931) Type of Farming
Areas in Texas. Bulletin Number 427, Texas Agricultural
Experiment Station, Agricultural and Mechanical College
of Texas.
Bouwman, A.F., L.J.M. Boumans, and N.H. Batjes. (2002a)
"Emissions of N2O and NO from fertilised fields: Summary
of available measurement data." Glob. Biogeochem. Cycles,
16(4), art. no. 1058.
Bouwman, A.F., L.J.M. Boumans, and N.H, Batjes (2002b)
"Modeling global annual N2O and NO emissions from
fertilised fields." Glob. Biogeochem. Cycles, 16(4), art. no.
1080.
Brenner, J., K. Paustian, G. Bluhm, J. Cipra, M. Easter, R.
Foulk, K. Killian, R. Moore, J. Schuler, P. Smith, and S.
Williams (2002) Quantifying the Change in Greenhouse Gas
Emissions Due to Natural Resource Conservation Practice
Application in Nebraska. Colorado State University Natural
Resource Ecology Laboratory and USD A Natural Resources
Conservation Service, Fort Collins, CO.
Brenner, J.,K. Paustian.,G. Bluhm, J. Cipra, M. Easter, E.T.
Elliott, T. Koutza,K. Killian, J. Schuler, S. Williams (2001)
Quantifying the Change in Greenhouse Gas Emissions Due
to Natural Resource Conservation Practice Application in
Iowa. Final report to the Iowa Conservation Partnership.
Colorado State University Natural Resource Ecology
Laboratory and U.S. Department of Agriculture Natural
Resources Conservation Service, Fort Collins, CO.
Brumme,R.,Borken, W., andFinke, S. (1999) "Hierarchical
control on nitrous oxide emission in forest ecosystems."
Global Biochem. Cycles 13:1137-1148.
Butterbach-Bahl, K., R. Gasche, L. Breuer, and H. Papen.
(1997) "Fluxes of NO and N2O from temperate forest soils:
impact of forest type, N deposition and of liming on the NO
and N2O emissions." Nutr. Cycl. Agroecosyst. 48:79-90.
Carpenter, G.H. (1992) "Current Litter Practices and Future
Needs." In 7992 National Poultry Waste Management
Symposium Proceedings. J.P. Blake, J.O. Donald, and
P.H. Patterson (eds.); Auburn University Printing Service,
Auburn, AL, 268-273.
Chilcott B.C. (1910) A Study of Cultivation Methods and
Crop Rotations for the Great Plains Area. U.S. Department
of Agriculture Bureau of Plant Industry Bulletin Number 187.
Government Printing Office, Washington, DC.
Clough, T., J.E. Bertram, R.R. Sherlock, R.L. Leonard, and
B.L. Nowicki (2006) "Comparison of measured and EF5-r-
derived N2O fluxes from a spring-fed river." Glob. Change
Bioi. 12:477-488.
Corre, M.D., D.J. Pennock, C. van Kessel, and O.K. Elliott
(1999) "Estimation of annual nitrous oxide emissions from
a transitional grassland-forest region in Saskatchewan.
Canada. Biogeochem. 44:29-49.
CTIC (1998) 7998 Crop Residue Management Executive
Summary. Conservation Technology Information Center.
Data available online at .
Daly, C., R.P. Neilson, and D.L. Phillips (1994) "A statistical-
topographic model for mapping climatological precipitation
over mountainous terrain." Journal of Applied Meteorology,
33:140-158.
Daly, C., G.H. Taylor, W.P. Gibson, T. Parzybok, G.L.
Johnson, and P.A. Pasteris (1998) "Development of high-
quality spatial datasets for the United States." Proc., 1st
International Conference on Geospatial Information in
Agriculture and Forestry, Lake Buena Vista, FL, 1-512-1-
519. June 1-3,1998.
DAYMET (No date) Daily Surface Weather and
Climatological Summaries. Numerical Terradynamic
Simulation Group (NTSG), University of Montana. Available
online at .
11-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Deal, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Peter B. Deal, Rangeland Management
Specialist, Florida Natural Resource Conservation Service.
June 21,2000.
de Klein, C.A.M (2004) "Review of the N2O emission
factor for excreta deposited by grazing animals (EF3PRP)."
Paper prepared as part of the 2006 Revised Guidelines for
Greenhouse Gas Inventories of IPCC.
Del Grosso, S.J., A.R. Mosier, W.J. Parton, and D.S.
Ojima (2005) "DAYCENT Model Analysis of Past and
Contemporary Soil N9O and Net Greenhouse Gas Flux for
Major Crops in the USA." Soil Tillage and Research, 83:
9-24. doi: 10.1016/j.still.2005.02.007.
Del Grosso, S.J., S.M. Ogle, and F.J. Breidt (in prep.)
''Uncertainty in estimating nitrous oxide emissions from
cropped and grazed soils in the USA." Manuscript in
preparation.
Del Grosso, S.J., W.J. Parton, A.R. Mosier, M.D. Hartman,
J. Brenner, D.S. Ojima, and D.S. Schimel (2001) "Simulated
Interaction of Carbon Dynamics and Nitrogen Trace Gas
Fluxes Using the DAYCENT Model." In Schaffer, M., L.
Ma, S. Hansen, (eds.); Modeling Carbon and Nitrogen
Dynamics for Soil Management. CRC Press, Boca Raton,
Florida. 303-332.
Denier van der Gon, H., and A. Bleeker (2005) "Indirect
N2O emission due to atmospheric N deposition for the
Netherlands." Atmos. Environ. 39:5827-5838.
Dong, L.F., D.B. Nedwell, I. Colbeck, and J. Finch (2004)
"Nitrous oxide emission from some English and Welsh rivers
and estuaries." Water Air Soil Pollution: Focus 4:127-134.
Edmonds, L., N. Gollehon, R.L. Kellogg, B. Kintzer, L.
Knight, C. Lander, J.Lemunyon.D. Meyer, D.C.Moffitt, and
J. Schaeffer (2003) "Costs Associated with Development and
Implementation of Comprehensive Nutrient Management
Plans." Part 1. Nutrient Management, Land Treatment,
Manure and Wastewater Handling and Storage, and
Recordkeeping. Natural Resource Conservation Service,
U.S. Department of Agriculture.
Elliott, F.F. (1933) Types of Farming in the United States.
U.S. Department of Commerce. Government Printing Office,
Washington, DC.
Elliott, F.F. and J.W. Tapp (1928) Types of Farming in North
Dakota. U.S. Department of Agriculture Technical Bulletin
Number 102.
Ellsworth, J.O. (1929) Types of Farming in Oklahoma.
Agricultural Experiment Station Bulletin Number 181.
Oklahoma Agricultural and Mechanical College.
Engle, R.H. and B.R. Makela (1947) "Where is All the
Fertilizer Going?" The Fertilizer Review. The National
Fertilizer Association, Vol. XXII, 6:7-10.
EPA (2003) Clean Watersheds Needs Survey 2000-Report
to Congress, U.S. Environmental Protection Agency,
Washington, DC. Available online at .
EPA (2002) Cost Methodology for the Final Revisions to the
National Pollutant Discharge Elimination System Regulation
and the Effluent Guidelines for Concentrated Animal Feeding
Operations. EPA-821-R-03-004. December 2002.
EPA (1999) Biosolids Generation, Use and Disposal in the
United States. Office of Solid Waste, U.S. Environmental
Protection Agency. Available online at .
EPA (1997) 1996 Clean Watersheds Needs Survey Report
to Congress—Assessment of Needs for Publicly Owned
Wastewater Treatment Facilities, Correction of Combined
Sewer Overflows, and management of Storm Water and
Nonpoint Source Pollution in the United States, U.S.
Environmental Protection Agency, Washington, DC.
Available online at .
EPA (1993) Federal Register. Part II. Standards for the
Use and Disposal of Sewage Sludge; Final Rules. U.S.
Environmental Protection Agency, 40 CFR Parts 257, 403,
and 503.
EPA (1992) Global Methane Emissions from Livestock
and Poultry Manure. Office of Air and Radiation, U.S.
Environmental Protection Agency. February 1992.
ERG (2003) Methodology for Estimating Uncertainty for
Manure Management Greenhouse Gas Inventory. Contract
No. GS-10F-0036, Task Order 005. Memorandum to EPA
from ERG. September 26, 2003.
ERS (2003) Ag Chemical and Production Technology.
Economic Research Service, U.S. Department of
Agriculture.
ERS (2002) Economic Research Service, U.S. Department
of Agriculture. Available online at .
ERS (1997) Cropping Practices Survey Data-1995.
Economic Research Service, U.S. Department of Agriculture.
Available online at .
ERS (1994) Fertilizer Use and Price Statistics. Stock
#86012. Economic Research Service, U.S. Department of
Agriculture.
ERS (1988) Agricultural Resources—Inputs Situation and
Outlook Report. AR-9. Economic Research Service, U.S.
Department of Agriculture.
Eve, M. (2001) E-mail from Marlen Eve of the Natural
Resources Ecology Laboratory to Barbara Braatz and Caren
Mintz of ICF International, containing statistics on U.S.
organic soil areas cultivated in 1982,1992, and 1997, which
were extracted from the 1997 National Resources Inventory.
September 21,2001.
References 11-37
-------
FAO (2006) Yearly U.S. total horse population data from the
Food and Agriculture Organization of the United Nations
database. Available online at .
Fraps, G.S. and S.E. Asbury (1931) Commercial Fertilizers
in 1930-1931 and Their Uses. Agricultural Experiment
Station Bulletin Number 434. Agricultural and Mechanical
College of Texas.
Hardies, E.W. and A.N. Hume (1927) Wheat in South
Dakota. Agronomy Department Bulletin Number 222.
Agricultural Experiment Station, South Dakota State College
of Agriculture and Mechanical Arts, Brookings, SD.
Garey, L.F. (1929) Types of Farming in Minnesota.
Agricultural Experiment Station Bulletin Number 257.
University of Minnesota, St. Paul, MN.
Grant, W.R. and R.D. Krenz (1985) U. S. grain sorghum
production practices and costs. Staff Report No. AGES
851024. National Economics Division, Economics Research
Service, U.S. Department of Agriculture.
Hargreaves, M.W.M. (1993) Dry Farming in the Northern
Great Plains: Years of Readjustment, 192 0-1990. University
Press of Kansas, Lawrence, KS.
Hiscock, K.M., A.S. Bateman, T. Fukada, and P.F. Dennis
(2002) "The concentration and distribution of groundwater
N2O in the Chalk aquifer of eastern England." In J. Van Ham,
A.P.M. Baede, R. Guicherit, and J.G.F.M Williams-Jacobse
(eds.); Proc. 3rdInternal. Symp.Non-CO2 Greenhouse Gases,
Maastricht, The Netherlands, 185-190.
Hiscock, K.M., A.S. Bateman, I. H. Muhlherr, T. Fukada,
and P.F. Dennis (2003) "Indirect emissions of nitrous oxide
from regional aquifers in the United Kingdom." Environ.
Sci.Technol. 37:3507-3512.
Hodges, J.A., F.F. Elliott, and W.E. Grimes (1930) Types
of Farming in Kansas. Agricultural Experiment Station
Bulletin Number 251. Kansas State Agricultural College,
Manhattan, KS.
Holmes C.L. (1929) Types of Farming in Iowa. Agricultural
Experiment Station Bulletin Number 259. Iowa State College
of Agriculture and Mechanic Arts, Ames, IA.
Holmes O.K. (1902) "Practices in Crop Rotation." Yearbook
of the Department ofAgriculture, 519-532.
Hurd E.B. (1930) Cropping Systems in Iowa Past and
Present. Agricultural Experiment Station Bulletin Number
268. Iowa State College of Agriculture and Mechanic Arts,
Ames, IA.
Hurd E .B. (1929) The Corn Enterprise in Iowa. Agricultural
Experiment Station Bulletin Number 268. Iowa State College
of Agriculture and Mechanic Arts, Ames, IA.
Hurt, R.D. (1994) American Agriculture: A Brief History.
Iowa State University Press, Ames, IA.
Ibach, D.B. and J.R. Adams (1967) Fertilizer Use in the
United States by Crops and Areas, 1964 Estimates. Statistical
Bulletin Number 408, U.S. Department of Agriculture.
Ibach, D.B., J.R. Adams, and E.I. Fox (1964) Commercial
Fertilizer used on Crops and Pasture in the United States,
1959 Estimates. U.S. Department of Agriculture Statistical
Bulletin Number 348.
Iowa State College Staff Members (1946) A Century of
Farming in Iowa 1846-1946. The Iowa State College Press,
Ames, IA.
IPCC (2006) 2006IPCC Guide lines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa,T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change. National Greenhouse Gas Inventories
Programme, J. Penman, et al., eds. August 13, 2004.
Available online at .
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/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Johnson, D. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Dan Johnson, State Water Management
Engineer, California Natural Resource Conservation Service.
June 23,2000.
Kellogg R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon
(2000) Manure Nutrients Relative to Capacity of Cropland
and Pastureland to Assimilate Nutrients: Spatial and
Temporal Trends for the United States. U.S. Department of
Agriculture Publication Number npsOO-0579.
Kezer A. (ca 1917) Dry Farming in Colorado. Colorado
State Board of Immigration, Denver, CO.
Klemedtsson, L., A. Kasimir Klemedtsson, M. Escala, and
A. Kulmala (1999) "Inventory of N2O emission from farmed
European peatlands." In A. Freibauer and M. Kaltschmitt
(eds.); Approaches to Greenhouse Gas Inventories of
Biogenic Sources in Agriculture, Proc. Workshop at
Lokeberg, Sweden, 79-91. 9-10 July 1998.
Kuchler, AW. (1964) "The Potential Natural Vegetation of
the Conterminous United States." Amer. Geographical Soc.
NY, Special Publication No. 36.
Lange, J. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and John Lange, Agricultural Statistician, U .S.
Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
11-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1090-2005
-------
Langston C.W., L.M. Davis, C.A. Juve, O.C. Stine, A.E.
Wight, A.J. Pistor, and C.F. Langworthy (1922) "The Dairy
Industry." Yearbook of the Department of Agriculture.
Latta, W.C. (1938) Outline History of Indiana Agriculture.
Alpha Lambda Chapter of Epsilon Sigma Phi, Purdue
University, West Lafayette, IN.
McCarl, B.A., C.C. Chang, J.D. Atwood, and W.I. Nayda
(1993) Documentation of ASM: The U.S. Agricultural Sector
Model, Technical Report TR-93. Agricultural Experimental
Station, College Station, TX.
Metcalf and Eddy, Inc. (1991) Wastewater Engineering:
Treatment, Disposal, and Re use, Third Edition. McGraw-Hill
Publishing Company, New York, 772.
Miller, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Paul Miller, Iowa Natural Resource
Conservation Service. June 12, 2000.
Milton, B. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Bob Milton, Chief of Livestock Branch,
U.S. Department of Agriculture, National Agriculture
Statistics Service. May 1,2000.
Mosier, A.R. (2004) E-mail correspondence between Arvin
Mosier of Agricultural Research Service, USDA and Stephen
Del Grosso of Natural Resource Ecology Laboratory,
Colorado State University, regarding the uncertainty in
estimates of N application rates for specific crops (+/-20).
September 20, 2004.
NASS (2004) Agricultural Chemical Usage: 2003 Field
Crops Summary. Report AgCh 1 (04)a, National Agricultural
Statistics Service, U.S.Department of Agriculture. Available
online at .
NASS (1999) Agricultural Chemical Usage: 1998 Field
Crops Summary. Report AgCH 1(99). National Agricultural
Statistics Service, U.S.Department of Agriculture. Available
online at .
NASS (1992) Agricultural Chemical Usage: 1991 Field
Crops Summary. Report AgChl(92). National Agricultural
Statistics Service, U.S.Department of Agriculture. Available
online at .
NFA (1946) Charting the Fertilizer Course: Results ofNFA 's
Third Practice Survey. National Fertilizer Association. The
Fertilizer Review. Vol. XXI, 2:7-13.
Novoa, R. and H.R. Tejeda (2006) Evaluation of the
N2O emissions from N in plant residues as affected by
environmental and management factors. Nutr. Cycl.
Agroecosyst. (in press; available on-line).
NRAES (1992) On-Farm Composting Handbook (NRAES-
54). Natural Resource, Agriculture, and Engineering
Service. Available online at .
NRIAI (2003) Regional Budget and Cost Information. Natural
Resources Inventory and Analysis Institute, Natural Resources
Conservation Service. U.S. Department of Agriculture.
Ogle, S. (2002) E-mail from Stephen Ogle of the Natural
Resources Ecology Laboratory to Barbara Braatz of ICF
International, containing revised statistics on U.S. histosol
areas cultivated in 1982,1992, and 1997, which were extracted
from the 1997 National Resources Inventory by Marlen Eve,
January 9,2002.
Ogle, S.M.,FJ. Breidt,M. Easter, S. Williams, and K. Paustian.
(2007) "Empirically-Based Uncertainty Associated with
Modeling Carbon Sequestration Rates in Soils." Ecological
Modeling, accepted for publication, but not yet published.
Parton, W.J., M.D. Hartman, D.S. Ojima, and D.S. Schimel
(1998) "DAYCENT: Its Land Surface Submodel: Description
and Testing". Glob. Planet. Chang. 19: 35^18.
Piper C.V., R.A. Oakley, H.N. Vinall, A.J. Pieters, W.J.
Morse, W.J. Spillman, O.C. Stine, J.S. Cotton., G.A. Collier,
M.R Cooper, B.C. Parker, E.W. Sheets, and A.T. Semple
(1924) "Hay." Yearbook of the Department of Agriculture,
285-376.
Poe, G., N. Bills, B. Bellows, P. Crosscombe, R. Koelsch, M.
Kreher, and P. Wright (1999) Documenting the Status of Dairy
Manure Management in New York: Current Practices and
Willingness to Participate in Voluntary Programs. Staff Paper,
Dept. of Agricultural, Resource, and Managerial Economics,
Cornell University, Ithaca, NY, September 1999.
Reay, D.S., K.A. Smith, and A.C. Edwards (2004) "Nitrous
oxide in agricultural drainage waters following field
fertilisation." Water Air Soil Pollution: Focus, 4:437-451.
Reay, D., K.A. Smith, A.C. Edwards, K.M. Hiscock, L.F.
Dong, and D. Nedwell (2005) "Indirect nitrous oxide
emissions: revised emission factors." Environ. Sciences,
2:153-158.
Rochette, R, D.A. Angers, G. Belanger, M.H. Chantigny, D.
Prevost, G. Levesque, (2004) "Emissions of N2O from alfalfa
and soybean crops in eastern Canada." Soil Sci. Soc. Am. J.
68:493-506.
Ross W.H. and A.L. Mehring (1938) "Mixed Fertilizers." In
Soils and Men. Agricultural Yearbook 1938. U.S. Department
of Agriculture.
Russell E.Z., S.S. Buckley, C.E. Baker, C.E. Gibbons, R.H.
Wilcox, H.W. Hawthorne, S.W. Mendum, O.C. Stine, O.K.
Holmes, A.V. Swarthout, W.B. Bell, G.S. Jamieson, C.W.
Warburton, and C .F. Langworthy (1922) Hog Production and
Marketing. Yearbook of the U.S. Department of Agriculture.
Safley, L.M. (2000) Telephone conversation between Deb
Bartram of ERG and L.M. Safley, President, Agri-Waste
Technology. June 2000.
Safley, L.M., M.E. Casada, J.W. Woodbury, and J.F. Roos
(1992) Global Methane Emissions from Livestock and Poultry
Manure. EPA/400/1-91/048, Office of Air and Radiation, U.S.
Environmental Protection Agency. February 1992.
References 11-39
-------
Sawamoto, T.. Y. Nakajima, M. Kasuya, H. Tsuruta, and
K. Yagi (2005) "Evaluation of emission factors for indirect
N2O emission due to nitrogen leaching in agro-ecosystems."
Geophys. Res. Lett. 32(3), doi:10.1029/2004GL021625.
Saxton,K.E.,W.J.Rawls,J.S.Romberger,andR.I.Papendick
(1986) "Estimating Generalized Soil-Water Characteristics
From Texture." Soil Sci. Soc. Am. J. 50:1031-1036.
Skinner, J .J. (1931) Fertilizers/or Cotton Soils. Miscellaneous
Publication Number 126. U.S. Department of Agriculture.
Smalley, H.R., R.H. Engle, and H. Willett (1939) American
Fertilizer Practices: Second Survey. The National Fertilizer
Association.
Smith C.B. (1911) Rotations in the Corn Belt. Yearbook of
the Department of Agriculture, pp.325-336.
Smith, P., J. Brenner, K. Paustian, G. Bluhm, J. Cipra, M.
Easter, E.T. Elliott, K. Killian, D. Lamm, J. Schuler, and S.
Williams (2002) Quantifying the Change in Greenhouse
Gas Emissions Due to Natural Resource Conservation
Practice Application in Indiana. Final Report to the Indiana
Conservation Partnership, Colorado State University Natural
Resource Ecology Laboratory and U.S. Department of
Agriculture Natural Resources Conservation Service, Fort
Collins, CO.
Soil Survey Staff, Natural Resources Conservation Service,
United States Department of Agriculture (2005) State Soil
Geographic (STATSGO) Database for State. Available
online at .
USDA (2005a) Cattle. National Agricultural Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 28, 2005. Available online at .
USDA (2005b) Cattle on Feed. National Agricultural
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 21, 2005. Available online at
.
USDA(2005c) Hogs and Pigs. National Agricultural Statistics
Service, U.S. Department of Agriculture, Washington, DC.
March 24,2005. Available online at .
11-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
USDA (2005d) Chicken and Eggs Annual Summary.
National Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. February 2005. Available online
at .
USDA (2005e) Poultry Production and Value Annual
Summary. National Agricultural Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 28,2005.
Available online at .
USDA (2005f) Sheep and Goats. National Agricultural
Statistics Service, U .S. Department of Agriculture, Washington,
DC. January 28,2005. Available online at .
USDA (2005g) 1992,1997, and 2002 Census of Agriculture.
National Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at .
USDA (2005h) Agriculture Statistics 2005. National
Agricultural Statistics Service, U.S. Department of Agriculture,
Washington, DC. Available online at or .
USDA (2005i) Crop Production 2004 Summary. National
Agricultural Statistics Service, U.S. Department of Agriculture,
Washington, DC. Available online at .
USDA(2004a) Cattle-Final Estimates 1999-2003. National
Agricultural Statistics Service, U.S. Department of Agriculture,
Washington, DC. April 2004. Available online at .
USDA (2004b) Hogs and Pigs-Final Estimates 1998-2002.
National Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. March 2004. Available online
at .
USDA (2004c) Chicken and Eggs-Final Estimates
1998-2003. National Agricultural Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004d) Poultry Production and Value-Final
Estimates 1998-2002. National Agricultural Statistics Service,
U.S. Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA(2004e) Sheep and Goats-Final Estimates 1999-2003.
National Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. April 2004. Available online at
.
USDA (2004f) Statistics on county level total crop area data
for 1990-2003, extracted from the Agricultural Statistics
Database. National Agricultural Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at .
USDA (2003) Crop Production 2002 Summary. National
Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . Accessed May 2003.
USDA(2000a) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 14, 2000. Data also available online at .
USDA (2000b) 7997 National Resources Inventory.
National Agricultural Statistics Service, U.S. Department
of Agriculture, Washington, DC. Available online at .
USDA (2000c) Agricultural Statistics 2000. National
Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at .
USDA (1999a) Cattle-Final Estimates 1994-98. National
Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1999. Data also
available online at .
USDA (1999b) Poultry Production and Value-Final
Estimates 1994-97. National Agricultural Statistics Service,
U.S. Department of Agriculture, Washington, DC. March.
USDA (1999c) Sheep and Goats-Final Estimates
1994-1998. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January
1999.
USDA (1998a) Chicken and Eggs-Final Estimates 1994-
97. National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. December 1998.
USDA (1998b) Field Crops Final Estimates 1992-97.
Statistical Bulletin Number 947a. National Agricultural
Statistics Service, U.S. Department of Agriculture,
Washington, DC. Available online at . Accessed July 2001.
USDA (1998c) Hogs and Pigs-Final Estimates 1993-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998. Data also
available online at .
USDA (1996) Agricultural Waste Management Field
Handbook, National Engineering Handbook (NEH),
Part 651. Natural Resources Conservation Service, U.S.
Department of Agriculture. July 1996.
References 11-41
-------
USDA (1995a) Cattle-Final Estimates 1989-93. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1995. Data also
available online at .
USDA (1995b) Poultry Production and Value-Final
Estimates 1989-1993. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
USDA (1994a) Field Crops: Final Estimates, 1987-1992.
Statistical Bulletin Number 896, National Agriculture
Statistics Service, U.S. Department of Agriculture.
Washington, DC. Available online at .
USDA (1994b) Hogs and Pigs-Final Estimates 1988-92.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1994. Data also
available online at .
USDA (1994c) Sheep and Goats-Final Estimates
1989-1993, National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January
1994.
USDA. (1966) Consumption of Commercial Fertilizers and
Primary Plant Nutrients in the United States, 1850-1964
and By States, 1945-1964. Statistical Bulletin Number
375, Statistical Reporting Service, U.S. Department of
Agriculture.
USDA .(1957) Fertilizer Used on Crops and Pastures in the
United States—1954 Estimates. Statistical Bulletin Number
216, Agricultural Research Service, U.S. Department of
Agriculture.
USDA. (1954) Fertilizer Use and Crop Yields in the United
States. Agricultural Handbook Number 68, the Fertilizer
Work Group, U.S. Department of Agriculture.
USDA. (1946) Fertilizers and Lime in the United States.
Miscellaneous Publication Number 586, U.S. Department
of Agriculture.
VEMAP (1995) Members (J.M. Melillo, J. Borchers, J.
Chancy, H. Fisher, S. Fox, A. Haxeltine, A. Janetos, D.W.
Kicklighter, T.G.F. Kittel, A.D. McGuire, R. McKeown,
R. Neilson, R. Nemani, D.S. Ojima, T. Painter, Y. Pan,
W.J. Parton, L. Pierce, L. Pitelka, C. Prentice, B. Rizzo,
N.A. Rosenbloom, S. Running, D.S. Schimel, S. Sitch, T.
Smith, I. Woodward). "Vegetation/Ecosystem Modeling and
Analysis Project (VEMAP): Comparing Biogeography and
Biogeochemistry Models in a Continental-Scale Study of
Terrestrial Ecosystem Responses to Climate Change and CO2
Doubling." Global Biogeochemical Cycles, 9:407^-37.
Vogelmann, J.E., S.M. Howard, L. Yang, C. R. Larson, B.
K. Wylie, and J. N. Van Driel (2001) "Completion of the
1990's National Land Cover Data Set for the conterminous
United States." Photogrammetric Engineering and Remote
Sensing, 61': 650-662.
Warren J.A. (1911) Agriculture in the Central Part of the
Semiarid Portion of the Great Plains. Bulletin Number 215,
Bureau of Plant Industry, U.S. Department of Agriculture.
Williams, S.A. (2006) From an unpublished manuscript
and data compiled for the Consortium for Agricultural
Soils Mitigation of Greenhouse Gases (CASMGS). Natural
Resource Ecology Laboratory, Colorado State University.
Williams-Jacobse, J.G.F.M. (ed.) (2002) Proceedings 3rd
International Symposium Non-CO2 Greenhouse Gases,
Maastricht, the Netherlands, 185-190.
Wright, P. (2000) Telephone conversation between Lee-Ann
Tracy of ERG and Peter Wright, Cornell University, College
of Agriculture and Life Sciences. June 23, 2000.
Field Burning of Agricultural Residues
Anonymous (2006) Telephone conversation with Lauren
Flinn of ICF International. August 11, 2006.
Barnard, G., and L. Kristoferson (1985) Agricultural
Residues as Fuel in the Third World. Earthscan Energy
Information Programme and the Beijer Institute of the Royal
Swedish Academy of Sciences, London, England.
Bollich, P. (2000) Telephone conversation between Payton
Deeks of ICF International and Pat Bollich, Professor with
Louisiana State University Agriculture Center. May 17,
2000.
California Air Resources Board (2001) Progress Report on
the Phase Down and the 1998-2000 Pause in the Phase
Down of Rice Straw Burning in the Sacramento Valley
Air Basin, Proposed 2001 Report to the Legislature. June
2001.
California Air Resources Board (1999) Progress Report on
the Phase Down of Rice Straw Burning in the Sacramento
Valley Air Basin, Proposed 1999 Report to the Legislature.
December 1999.
Cantens.G. (2005) Telephone conversation between Lauren
Flinn of ICF International and Janet Lewis, Assistant to
Gaston Cantens, Vice President of Corporate Relations,
Florida Crystals Company. July 2005.
Cantens, G. (2004) Telephone conversation between Lauren
Flinn of ICF International and Janet Lewis, Assistant to
Gaston Cantens, Vice President of Corporate Relations,
Florida Crystals Company. July 30,2004.
Cibrowski, P. (1996) Telephone conversation between
Heike Mainhardt of ICF Incorporated and Peter Cibrowski,
Minnesota Pollution Control Agency. July 29, 1996.
Deren, C. (2002) Telephone conversation between Caren
Mintz of ICF International and Dr. Chris Deren, Everglades
Research and Education Centre at the Lfniversity of Florida.
August 15,2002.
11-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
EPA (1994) International Anthropogenic Methane Emissions:
Estimates for 1990, Report to Congress. EPA 230-R-93-010.
Office of Policy Planning and Evaluation, U.S. Environmental
Protection Agency. Washington, DC.
EPA (1992) Prescribed Burning Background Document and
Technical Information Document for Prescribed Burning
Best Available Control Measures. Office of Air Quality
Planning and Standards, U.S. Environmental Protection
Agency. Research Triangle Park, NC. EPA-450/2-92-003.
Fife, L. (1999) Telephone conversation between Catherine
Leining of ICF International and Les Fife, President and
General Manager, Fife Environmental. June 9, 1999.
ILENR (1993) Illinois Inventory of Greenhouse Gas
Emissions and Sinks: 1990. Office of Research and Planning,
Illinois Department of Energy and Natural Resources.
Springfield, IL.
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 (1.1V.2000). May 2000.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Jenkins, B.M., S.Q. Turn, and R.B. Williams (1992)
"Atmospheric emissions from agricultural burning in
California: determination of burn fractions, distribution
factors, and crop specific contributions." Agriculture,
Ecosystems and Environment 38:313-330.
Ketzis, J. (1999) Telephone conversation between Marco
Alcaraz of ICF International and Jen Ketzis of Cornell
University. June/July 1999.
Kirstein, A. (2004) Telephone conversation between Lauren
Flinn of ICF International and Arthur Kirstein, Coordinator,
Agricultural Economic Development Program, Palm Beach
County Cooperative Extension Service, Florida. June 30,
2004.
Kirstein, A. (2003) Telephone conversation between Caren
Mintz of ICF International and Arthur Kirstein, Coordinator,
Agricultural Economic Development Program, Palm Beach
County Cooperative Extension Service, Florida. August 13,
2003.
Klosterboer, A. (2003) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
retired Extension Agronomist, Texas A&M University. July
7,2003.
Klosterboer, A. (2002) Telephone conversation between Caren
Mintz of ICF International and Arlen Klosterboer, Extension
Agronomist, Texas A&M University. August 19, 2002.
Klosterboer, A. (2001) Telephone conversation between
Caren Mintz of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. August
6,2001.
Klosterboer, A. (2000) Telephone conversation between
Payton Deeks of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. May 18,
2000.
Klosterboer, A. (1999a) Telephone conversation between
Catherine Leining of ICF International and Arlen
Klosterboer, Extension Agronomist, Texas A&M
University. June 10, 1999.
Klosterboer, A. (1999b) Telephone conversation between
Payton Deeks of ICF International and Arlen Klosterboer,
Extension Agronomist, Texas A&M University. August
12,1999.
Lancero, J. (2006) Email correspondence between Lauren
Flinn of ICF International and Jeff Lancero, California Air
Resources Board. August 11, 2006.
Lee, D. (2006) Email correspondence between Lauren Flinn
of ICF Internationa] and Danny Lee, OK Farm Service
Agency. July 13,2006.
Lee, D. (2005) Email correspondence between Lauren Flinn
of ICF International and Danny Lee, OK Farm Service
Agency, Stillwater, OK. July and September 2005.
Lee, D. (2004) Telephone conversation between Lauren
Flinn of ICF International and Danny Lee, OK Farm Service
Agency, Stillwater, OK. July 23, 2006.
Lee, D. (2003) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Danny Lee, OK Farm Service Agency, Stillwater, OK.
July 2, 2003.
Lindberg, J. (2005) Email correspondence between Lauren
Flinn of ICF International and Jeff Lindberg, California Air
Resources Board. July 2005.
Lindberg, J. (2004) Email correspondence between Lauren
Flinn of ICF International and Jeff Lindberg, California Air
Resources Board. June-July 2004.
Lindberg, J. (2003) Email correspondence between Caren
Mintz of ICF International and Jeff Lindberg, California
Air Resources Board. June-July 2003.
Lindberg, J. (2002) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Jeff Lindberg, California Air Resources Board.
September 12-13,2002.
Linscombe, S. (2006) Email correspondence between
Lauren Flinn of ICF International and Steve Linscombe,
Professor with the Rice Research Station at Louisiana State
University Agriculture Center. August 15, 2006.
References 11-43
-------
Linscombe, S. (2005) Email correspondence between Lauren
Flinn of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. July 2005.
Linscombe, S. (2004) Telephone conversation between
Lauren Flinn of ICF International and Steve Linscombe,
Professor with the Rice Research Station at Louisiana State
University Agriculture Center. June 23, 2004.
Linscombe, S. (2003) Telephone conversation between Caren
Mintz of ICF International and Steve Linscombe, Professor
with the Rice Research Station at Louisiana State University
Agriculture Center. June 10,2003.
Linscombe, S. (2002) Email correspondence between Caren
Mintz of ICF International and Steve Linscombe, Research
Agronomist, Louisiana State University Agricultural Center.
August 21,2002.
Linscombe, S. (2001) Email correspondence between Caren
Mintz of ICF International and Steve Linscombe, Research
Agronomist, Louisiana State University Agricultural Center.
July 30-August 1,2001.
Linscombe, S. (1999a) Telephone conversation between
Catherine Leining of ICF International and Steve Linscombe,
Research Agronomist,Louisiana State University Agricultural
Center. June 3,1999.
Linscombe, S. (1999b) Telephone conversation between
Payton Decks of ICF International and Steve Linscombe,
Research Agronomist,Louisiana State University Agricultural
Center. August 9,1999.
Najita, T. (2001) Telephone conversation between Caren
Mintz of ICF International and Theresa Najita, Air Pollution
Specialist, California Air Resources Board. July 31,2001.
Najita, T. (2000) Telephone conversation between Payton
Deeks of ICF International and Theresa Najita, Air Pollution
Specialist, California Air Resources Board. August 17,2000.
Noller, J. (1996) Telephone conversation between Heike
Mainhardt of ICF Incorporated and John Noller, Missouri
Department of Natural Resources. July 30,1996.
Oregon Department of Energy (1995) Report on Reducing
Oregon's Greenhouse Gas Emissions: Appendix D Inventory
and Technical Discussion. Oregon Department of Energy.
Salem, OR.
Sacramento Valley Basinwide Air Pollution Control Council
(2005) Report on the Conditional Rice Straw Burning Permit
Program. May 25, 2005. Available online at .
Schueneman, T. (2001) Telephone conversation between
Caren Mintz of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
July 30,2001.
Schueneman, T. (1999a) Telephone conversation between
Catherine Leining of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL. June
7,1999.
Schueneman, T. (1999b) Telephone conversation between
Payton Deeks of ICF International and Tom Schueneman,
Agricultural Extension Agent, Palm Beach County, FL.
August 10,1999.
Schueneman, T.J. and C.W. Deren (2002) "An Overview
of the Florida Rice Industry" SS-AGR-77, Agronomy
Department, Florida Cooperative Extension Service, Institute
of Food and Agricultural Sciences, University of Florida.
Revised November 2002.
Stansel, J. (2005) Email correspondence between Lauren
Flinn of ICF International and Dr. Jim Stansel, Resident
Director and Professor Emeritus, Texas A&M University
Agricultural Research and Extension Center. July 2005.
Stansel, J. (2004) Telephone conversation between Lauren
Flinn of ICF International and Dr. Jim Stansel, Resident
Director and Professor Emeritus, Texas A&M University
Agricultural Research and Extension Center. July 12,
2004.
Street, J. (2003) Telephone conversation between Caren
Mintz of ICF International and Joe Street, Rice Specialist,
Mississippi State University, Delta Research Center. June
19,2003.
Street, J. (2002) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Joe Street, Rice Specialist, Mississippi State University,
Delta Research Center. August 19,2002.
Street, J. (2001) Telephone conversation and email
correspondence between Caren Mintz of ICF International
and Joe Street, Rice Specialist, Mississippi State University,
Delta Research Center. August 1,2001.
Strehler, A., and W. Stiitzle (1987) "Biomass Residues." In
Hall, D.O. and Overend, R.P. (eds.) Biomass. John Wiley
and Sons, Ltd. Chichester, UK.
Turn, S.Q., B.M. Jenkins, J.C. Chow, L.C. Pritchett, D.
Campbell, T. Cahill, and S.A. Whalen (1997) "Elemental
characterization of particulate matter emitted from biomass
burning: Wind tunnel derived source profiles for herbaceous
and wood fuels." Journal of Geophysical Research
102(D3):3683-3699.
University of California (1977) Emission Factors From
Burning of Agricultural Waste Collected in California.
University of California. Davis.
USDA (2006) Crop Production 2005 Summary. National
Agricultural Statistics Service, U.S. Department of
Agriculture. Available online at . Accessed July 2006.
11-44 Inventory of U.S. Greenhouse! Gas Emissions and Sinks: 1990-2005
-------
USDA (2005) Crop Production 2004 Summary. National
Agricultural Statistics Service, U.S. Department of
Agriculture. Available online at . Accessed June 2005.
USDA (2003) Field Crops, Final Estimates 1997-2002.
Statistical Bulletin No. 982. National Agricultural Statistics
Service, Agricultural Statistics Board, U.S. Department
of Agriculture, Washington, DC. Available online at
.
Accessed September 2005.
USDA (1998) Field Crops, Final Estimates 1992-1997.
Statistical Bulletin No. 947a. National Agricultural
Statistics Service, Agricultural Statistics Board, U.S.
Department of Agriculture, Washington, DC. Available
online at .
Walker, T. (2006) Telephone conversation between Lauren
Flinn of ICF International and Tim Walker, Assistant
Research Professor, Mississippi State University Delta
Branch Exp. Station. August 17, 2006.
Walker, T. (2005) Email correspondence between Lauren
Flinn of ICF International and Tim Walker, Assistant
Research Professor, Mississippi State University Delta
Branch Exp. Station. July 2005.
Walker, T. (2004) Telephone conversation between Lauren
Flinn of ICF International and Tim Walker, Assistant
Research Professor, Mississippi State University Delta
Branch Exp. Station. July 12, 2004.
Wilson, C. (2006) Email coorespondence between Lauren
Flinn of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. (870) 673-2661. Wilson@uamont.edu.
August 8, 2006.
Wilson, C. (2005) Email correspondence between Lauren
Flinn of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. July 2005.
Wilson, C. (2004) Telephone conversation between Lauren
Flinn of ICF International and Dr. Chuck Wilson, Rice
Specialist at the University of Arkansas Cooperative
Extension Service. June 23, 2004.
Wilson, C. (2003) Telephone conversation between Caren
Mintz of ICF International and Dr. Chuck Wilson, Rice
Specialist, University of Arkansas Cooperative Extension
Service. June 11,2003.
Wisconsin Department of Natural Resources (1993)
Wisconsin Greenhouse Gas Emissions: Estimates for 1990.
Bureau of Air Management, Wisconsin Department of
Natural Resources, Madison, WI.
Land Use, Land-Use Change, and
Forestry
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme, J. Penman, et al., eds. August 13, 2004.
Available online at .
Forest Land Remaining Forest Land:
Changes in Forest Carbon Stocks
AF&PA. (2006a) (and earlier). Statistical roundup. (Monthly).
Washington, DC: American Forest & Paper Association.
AF&PA. (2006b) (and earlier). Statistics of paper, paperboard
and wood pulp. Washington, DC: American Forest & Paper
Association.
Amichev, B. Y. and J. M. Galbraith (2004) "A Revised
Methodology for Estimation of Forest Soil Carbon from
Spatial Soils and Forest Inventory Data Sets." Environmental
Management 33(Suppl. 1):S74-S86.
Barlaz, M.A. (1998) "Carbon storage during biodegradation
of municipal solid waste components in laboratory-scale
landfills." Global Biogeochemical Cycles 12 (2):373-380.
Birdsey, R. (1996) "Carbon Storage for Major Forest Types
and Regions in the Conterminous United States." In R.N.
Sampson and D. Hair, (eds); Forest and Global Change,
Volume 2: Forest Management Opportunities for Mitigating
Carbon Emissions. American Forests, Washington, DC, 1-26
and 261-379 (appendices 262 and 263).
Birdsey, R., and L. S. Heath (2001) "Forest Inventory Data,
Models, and Assumptions for Monitoring Carbon Flux." In
Soil Carbon Sequestration and the Greenhouse Effect. Soil
Science Society of America, Madison, WI, 125-135.
Birdsey, R.A., and L.S. Heath (1995) "Carbon Changes
in U.S. Forests." In Productivity of America's Forests and
Climate Change. Gen. Tech. Rep. RM-271. Rocky Mountain
Forest and Range Experiment Station, Forest Service, U.S.
Department of Agriculture, Fort Collins, CO, 56-70.
Birdsey, R. A., and G. M. Lewis (2003) "Current and
Historical Trends in Use, Management, and Disturbance
of U.S. Forestlands." In J. M. Kimble, L. S. Heath, R. A.
Birdsey, and R. Lai, editors. The Potential of U.S. Forest
Soils to Sequester Carbon and Mitigate the Greenhouse
Effect. CRC Press, New York, 15-34.
References 11-45
-------
Eleazer, W.E., W.S. Odle, III, Y.S. Wang, and M.A.
Barlaz (1997) "Biodegradability of municipal solid waste
components in laboratory-scale landfills." Env. Sci. Tech.
31(3):911-917.
EPA (2006a) Inventory of U. S. Greenhouse Gas Emissions
and Sinks: 1990-2004. EPA, Office of Atmospheric
Programs, Washington, DC.
EPA (2006b) Municipal solid waste in the United States:
2005 Facts and figures. Office of Solid Waste, U.S.
Environmental Protection Agency, Washington, DC. (5306P)
EPA530-R-06-011. Available online at .
Frayer, W.E., and G.M. Furnival (1999) "Forest Survey
Sampling Designs: A History." Journal of Forestry 97(12):
4-10.
Freed, R. (2004) Open-dump and Landfill timeline
spreadsheet (unpublished). ICF International. Washington,
DC.
Gillespie, A.J.R. (1999) "Rationale for a National Annual
Forest Inventory Program." Journal of Forestry 97(12):
16-20.
Hair, D. (1958) "Historical forestry statistics of the United
States." Statistical Bull. 228. U.S. Department of Agriculture
Forest Service, Washington, DC.
Hair. D. and A.H. Ulrich (1963) The Demand and price
situation for forest products—1963. U.S. Department of
Agriculture Forest Service, Misc Publication No. 953,
Washington, DC.
Heath, L.S. (2006a) E-mail correspondence between Linda
Heath of the U.S. Department of Agriculture Forest Service
and Kimberly Klunich of the U.S. Environmental Protection
Agency regarding the 95 percent CI for forest area estimates
(+1-0.24%) and average carbon density for Lower 48 States
(+/-0. 4%). October 26, 2006.
Heath, L.S. (2006b) E-mail correspondence between Linda
Heath of the U.S. Department of Agriculture Forest Service
and Kimberly Klunich of the U.S. Environmental Protection
Agency regarding the 95 percent CI for average carbon
density for Alaska (+/-1.2%). October 27, 2006.
Heath,L. S.,andJ.E. Smith (2000) "Soil Carbon Accounting
and Assumptions for Forestry and Forest-related Land Use
Change." In The Impact of Climate Change on America's
Forests. Joyce, L.A., and Birdsey, R.A. Gen. Tech. Rep.
RMRS-59. Rocky Mountain Research Station, Forest
Service, U.S. Department of Agriculture, Fort Collins, CO,
89-101.
Heath, L.S., J.E., Smith, and R.A. Birdsey (2003) Carbon
Trends in U. S. Forestlands: A Context for the Role of
Soils in Forest Carbon Sequestration. In J. M. Kimble, L.
S. Heath, R. A. Birdsey, and R. Lai, editors. The Potential
of U. S. Forest Soils to Sequester Carbon and Mitigate the
Greenhouse Effect. Lewis Publishers (CRC Press), Boca
Raton, FL, 35^5.
Howard, James L. (forthcoming) U.S. timber production,
trade, consumption, and price statistics 1965 to 2005. Res.
Pap. FPL-RP-XXX. Madison, WI: USDA, Forest Service,
Forest Products Laboratory.
Howard, James L. (2003) U.S. timber production, trade,
consumption, and price statistics 1965 to 2002. Res. Pap.
FPL-RP-615. Madison, WI: USDA, Forest Service, Forest
Products Laboratory. Available online at .
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston,L. Buenida,K.Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme, J. Penman, et al., eds. August 13, 2004.
Available online at .
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Jenkins, J,C., D.C. Chojnacky, L.S. Heath, and R.A. Birdsey
(2003) "National-scale biomass estimators for United States
tree species." Forest Science 49(1): 12-35.
Johnson, D. W., and P. S. Curtis (2001) "Effects of Forest
Management on Soil C and N Storage: Meta Analysis."
Forest Ecology and Management 140:227-238.
Melosi. M. (2000) The Sanitary City. Johns Hopkins
University Press, Baltimore, MD.
Melosi, M. (1981) Garbage in The Cities: Refuse Reform and
the Environment: 1880-1980. Texas A&M Press.
Micales, J.A. and K.E. Skog (1997) "The decomposition of
forest products in landfills." International Biodeterioration
& Biodegradation. 39(2-3): 145-158.
Perry, C.H., C.W. Woodall, and M. Schoeneberger (2005)
Inventorying trees in agricultural landscapes: towards an
accounting of "working trees". In: B rooks, K.N. and Ffolliott,
P.F. (eds); "Moving Agroforestry into the Mainstream." Proc.
9"' N. Am. Agroforestry Con/., 12-15 June 2005, Rochester,
MN [CD-ROM]. Dept. of Forest Resources, Univ. Minnesota,
St. Paul, MN, 12 p. Available online at (verified 23 Sept 2006).
Ph ill ips, D .L., S .L. B ro wn, P.E. Schroeder, and R. A. Birdsey
(2000) "Toward Error Analysis of Large-Scale Forest Carbon
Budgets." Global Ecology and Biogeography 9:305-313.
11-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Skog, K.E., and G.A. Nicholson (1998) "Carbon Cycling
Through Wood Products: The Role of Wood and Paper
Products in Carbon Sequestration." Forest Products Journal
48:75-83.
Skog, K.E., K. Pingoud, and J.E. Smith (2004) "A method
countries can use to estimate changes in carbon stored
in harvested wood products and the uncertainty of such
estimates." Environmental Management 33(Suppl. 1):
S65-S73.
Skog, K. E. (in preparation) "Sequestration of carbon in
harvested wood products for the United States."
Smith, James E., Linda S. Heath, and Michael C. Nichols
(In preparation). U.S. Forest Carbon Calculation Tool User's
Guide: Forestland Carbon Stocks and Net Annual Stock
Change. Gen Tech Report, U.S. Department of Agriculture
Forest Service, Northern Research Station.
Smith, J.E., and L.S. Heath (2002) "A model of forest floor
carbon mass for United States forest types." Res. Paper NE-
722. US DA Forest Service, Northeastern Research Station,
Newtowne Square, PA.
Smith, J. E., L. S. Heath, and J. C. Jenkins (2003) Forest
Volume-to-Biomass Models and Estimates of Mass for Live
and Standing Dead Trees of U.S. Forests. General Technical
Report NE-298, USDA Forest Service, Northeastern
Research Station, Nevvtown Square, PA.
Smith, J. E., L. S. Heath, and P. B. Woodbury (2004 a) "How
to estimate forest carbon for large areas from inventory data."
Journal of Forestrv 102:25—31.
Smith, W.B., P.O. Miles, J.S. Vissage,andS.A.Pugh(2004b)
Forest Resources of the United States, 2002. General Technical
Report NC-241, U.S. Department of Agriculture Forest
Service, North Central Research Station. St. Paul, MN.
Steer, Henry B. (1948) Lumber production in the United
States. Misc. Pub. 669, U.S. Department of Agriculture
Forest Service, Washington, DC.
Ulrich, A.H. (1989) U.S. Timber Production, Trade,
Consumption, and Price Statistics, 1950-1987. USDA
Miscellaneous Publication No. 1471, U.S. Department of
Agriculture, Forest Service, Washington, DC, 77.
Ulrich, Alice (1985) U.S. Timber Production, Trade,
Consumption, and Price Statistics 1950-1985. Misc. Pub.
1453, U.S. Department of Agriculture Forest Service,
Washington, DC.
USDAForest Service. (2006a) Forest Inventory and Analysis
National Program, FIA library. Available online at .
Accessed September 20,2006.
USDAForest Service. (2006b) Forest Inventory and Analysis
Data Center. Available online at . Accessed September 20, 2006.
USDA Forest Service. (2006c) FIA Data Mart: Download.
Available online at .
References 11-47
-------
Cropland Remaining Cropland, Land
Converted to Cropland, Grassland
Remaining Grassland, and Land Converted
to Grassland: Changes in Agricultural Soil
Carbon Stocks
Allmaras, R .R., H .H. Schotnberg, C .L. Douglas, Jr., and T.H.
Dao (2000) "Soil organic carbon sequestration potential of
adopting conservation tillage in U.S. croplands." J Soil Water
Conserv 55:365-373.
Armentano,T.V.andJ.T.A.Verhoeven(1990)"Biogeochemical
Cycles: Global." In B.C. Patten, et al. (eds.); Wetlands and
Shallow Continental Water Bodies. SPB Academic Publishing,
The Hague, the Netherlands, Vol. 1,281-311.
Barbarika, A. (2006) Conservation Reserve Program Summary
and Enrollment Statistics - 2005. Farm Service Agency, U.S.
Department of Agriculture, Washington, DC.
Brady, N.C. and R.R. Weil (1999) The Nature and Properties
of Soils. Prentice Hall, Upper Saddle River,NJ, 881.
CTIC (1998) "1998 Crop Residue Management Executive
Summary." Conservation Technology Information Center,
West Lafayette, IN.
Daly, C., R.P. Neilson, and D.L. Phillips (1994) "A Statistical-
Topographic Model for Mapping Climatological Precipitation
Over Mountainous Terrain." Journal of Applied Meteorology
33:140-158.
Edmonds, L., R. L. Kellogg, B. Kintzer, L. Knight, C. Lander,
J. Lemunyon, D. Meyer, D.C. Moffitt, and J. Schaefer (2003)
"Costs associated with development and implementation of
Comprehensive Nutrient Management Plans." Part I-Nutrient
management, land treatment, manure and wastewater
handling and storage, and recordkeeping. Natural Resources
Conservation Service, U.S. Department of Agriculture.
Available online at .
EPA (1999) Biosolids Generation, Use and Disposal in the
United States. Office of Solid Waste, U.S. Environmental
Protection Agency. Available online at .
EPA (1993) Federal Register. Part II. Standards for the Use and
Disposal of Sewage Sludge; Final Rules. U.S. Environmental
Protection Agency, 40 CFR Parts 257,403, and 503.
ERS (1997) Cropping Practices Survey Data-1995.
Economic Research Service, United States Department of
Agriculture. Available online at .
Euliss, N., and R. Gleason (2002) Personal communication
between Ned Euliss and Robert Gleason of the U .S. Geological
Survey, Jamestown, ND, to Stephen Ogle of the National
Resource Ecology Laboratory, Fort Collins, CO on wetland
restoration factor estimates and restoration activity data.
August 2002.
FAO (2006) Yearly U.S. total horse population data from the
Food and Agriculture Organization of the United Nations
database. Available online at .
Accessed July 2006.
FSA (2006) Conservation Reserve Program: Summary and
Enrollment Statistics—2005. U.S. Department of Agriculture,
Farm Services Agency, Washington, DC.
IPCC (2006) 20061PCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa, T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC: (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Prog ramme, J. Penman, et al., eds. August 13,2004. Available
online at .
NASS (1999) Agricultural Chemical Usage: 1998 Field Crops
Summary. Report AgCH 1(99). National Agricultural Statistics
Service, U.S. Department of Agriculture, Washington, DC.
Available online at .
NASS (1992) Agricultural Chemical Usage: 1991 Field Crops
Summary. Report AgChl(92). National Agricultural Statistics
Service, U.S. Department of Agriculture, Washington, DC.
Available online at .
11-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
NRCS (1999) "Soil Taxonomy: A basic system of soil
classification for making and interpreting soil surveys, 2nd
Edition." Agricultural Handbook Number 436, Natural
Resources Conservation Service, U.S. Department of
Agriculture, Washington, DC.
NRCS (1997) "National Soil Survey Laboratory
Characterization Data," Digital Data, Natural Resources
Conservation Service, U.S. Department of Agriculture,
Lincoln, NE.
NRCS (1981) "Land Resource Regions and Major Land
Resource Areas of the United States," USD A Agriculture
Handbook 296, United States Department of Agriculture,
Natural Resources Conservation Service, National Soil
Survey Center, Lincoln, NE, pp. 156.
Ogle, S.M., F.J. Breidt, M. Easter, S. Williams and K.
Paustian. (2007) "Empirically-Based Uncertainty Associated
with Modeling Carbon Sequestration Rates in Soils."
Ecological Modeling, accepted.
Ogle, S.M., F.J. Breidt, and K. Paustian. (2006) "Bias
and variance in model results due to spatial scaling of
measurements for parameterization in regional assessments."
Global Change Biology 12:516-523.
Ogle, S.M., M.D. Eve, F.J. Breidt, and K. Paustian (2003)
"Uncertainty in estimating land use and management impacts
on soil organic carbon storage for U.S. agroecosystems between
1982 and 1997." Global Change Biology 9:1521-1542.
Ogle, S., M. Eve, M. Sperrow, F.J. Breidt, and K. Paustian
(2002) Agricultural Soil C Emissions, 1990-2001:
Documentation to Accompany EPA Inventory Tables.
Natural Resources Ecology Laboratory, Fort Collins, CO,
Provided in an e-mail from Stephen Ogle of NREL to Barbara
Braatz of ICF International. September 23,2002.
Parton, W.J., D.S. Ojima, C.V. Cole, and D.S. Schimel
(1994) "A General Model for Soil Organic Matter Dynamics:
Sensitivity to litter chemistry, texture and management." In
Quantitative Modeling of Soil Forming Processes. Special
Publication 39, Soil Science Society of America, Madison,
WI, 147-167.
Parton, W.J., D.S. Schimel, C.V. Cole, D.S. Ojima (1987)
"Analysis of factors controlling soil organic matter levels
in Great Plains grasslands." Soil Science Society of America
Journal 51:1173-1179.
Parton, W.J., J.W.B. Stewart, C.V. Cole. (1988) "Dynamics of
C, N, P, and S in grassland soils: a model." Biogeochemistry
5:109-131.
Potter, C. S., J.T. Randerson, C.B. Fields, PA. Matson,
P.M. Vitousek, H.A. Mooney, and S.A. Klooster. (1993)
"Terrestrial ecosystem production: a process model based
on global satellite and surface data." GlobalBiogeochemical
Cycles 7:811-841.
Reilly, J.M. and K.O. Fuglie. (1998) "Future yield growth
in field crops: What evidence exists?" Soil Till Res
47:275-290.
Tepordei, V.V. (2006) "Crushed Stone," In Minerals
Yearbook 2004. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2006.
Tepordei, V.V. (2005) "Crushed Stone," In Minerals
Yearbook 2003. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2005.
Tepordei, V.V. (2004) "Crushed Stone," In Minerals
Yearbook 2002. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2004. Accessed
August 2004.
Tepordei, V.V. (2003) "Crushed Stone," In Minerals
Yearbook 2001. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed June 2003.
Tepordei, V.V. (2002) "Crushed Stone," In Minerals
Yearbook 2000. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed September 2002.
Tepordei, V.V. (2001) "Crushed Stone," In Minerals
Yearbook 1999. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2001.
Tepordei, V.V. (2000) "Crushed Stone," In Minerals
Yearbook 1998. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2000.
Tepordei, V.V. (1999) "Crushed Stone," In Minerals
Yearbook 1997. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2000.
Tepordei, V.V. (1998) "Crushed Stone," In Minerals
Yearbook 1996. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online at
. Accessed August 2000.
Tepordei, V.V. (1997) "Crushed Stone," In Minerals Yearbook
1995. U.S. Department of the Interior/U.S. Geological
Survey, Washington, DC. pp. 783-809. Available online
at .
References 11-49
-------
Tepordei. V.V. (1996) "Crushed Stone," In Minerals
Yearbook 1994. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. Available online at . Accessed August 2000.
Tepordei, V.V. (1995) "Crushed Stone," In Minerals
Yearbook 1993. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1107-1147.
Tepordei, V. V. (1994) "Crushed Stone," In Minerals
Yearbook 1992. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1279-1303.
Tepordei, V.V. (1993) "Crushed Stone," In Minerals
Yearbook 1991. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1469-1511.
Towery, D. (2001) Personal communication between Dan
Towery of the Conservation Technology Information Center,
West Lafayette, IN, and Marlen Eve of the National Resource
Ecology Laboratory, Fort Collins, CO regarding adjustments
to the CTIC (1998) tillage data to reflect long-term trends.
February 2001.
USDA (2006a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 2006. Available online at .
USDA (2006b) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 2006. Available online at .
USDA (2006c) Chicken and Eggs 2005 Summary.
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. February 2006. Available
online at .
USDA (2006d) Poultry - Production and Value 2005
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2006.
Available online at .
USDA (2006e) Published Estimates Database. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . Accessed May 2006.
USDA (2005a) Cattle. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 28, 2005. Available online at .
USDA (2005b) Cattle on Feed. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
January 21, 2005. Available online at .
USDA (2005c) Hogs and Pigs. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
March 24,2005. Available online at .
USDA (2005e) Poultry Production and Value Annual
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 28,
2005. Available online at .
USDA (20051") Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. January 28, 2005. Available online at
.
USDA(2005g) Census of Agriculture. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. Data for 1992, 1997, and 2002 available
from in June 2005.
USDA (2004a) Cattle-Final Estimates 1999-2003.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. April 2004. Available online
at .
USDA (2004b) Hogs andPigs-Final Estimates 1998-2002.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. March 2004. Available online
at .
USDA (2004c) Chicken and Eggs-Final Estimates
1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004d) Poultry Production and Value-Final
Estimates 1998-2002. National Agriculture Statistics
Service, U.S. Department of Agriculture, Washington, DC.
April 2004. Available online at.
USDA (2004e) Sheep and Goats-Final Estimates
1999-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2000) Chicken and Eggs-Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . May 3,2000.
USDA (1999a) Cattle-Final Estimates 1994-98. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1999. Available online
at .
USDA (1999b) Poultry Production and Value-Final
Estimates 1994-97. National Agriculture Statistics Service,
U.S. Department of Agriculture, Washington, DC. March
1999.
11-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
USDA (1999c) Sheep and Goats-Final Estimates
1994-1998. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January
1999.
USDA (1998a) Chicken and Eggs-Final Estimates 1994-
97. National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. December 1998.
USDA (1998b) Hogs and Pigs-Final Estimates 1993-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998. Available
online at .
USDA (1995a) Cattle-Final Estimates 1989-93. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. January 1995. Available online
at .
USDA (1995b) Poultry Production and Value-Final
Estimates 1989-1993. National Agriculture Statistics
Service. U.S. Department of Agriculture, Washington, DC.
USDA (1994a) Hogs and Pigs-Final Estimates 1988-92.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1994. Available
online at .
USDA (1994b) Sheep and Goats-Final Estimates
1989-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. January
1994.
USDA-NRCS (2000) Digital Data And Summary Report:
1997 National Resources Inventory. Revised December
2000. Resources Inventory Division, Natural Resources
Conservation Service, United States Department of
Agriculture, Beltsville, MD.
USGS (2005) Mineral Industry Surveys: Crushed Stone
and Sand and Gravel in the First Quarter of 2005. U.S.
Geological Survey, Reston, VA. Available online at .
West, T.O., and A.C. McBride (2005) "The contribution
of agricultural lime to carbon dioxide emissions in the
United States: dissolution, transport, and net emissions,"
Agricultural Ecosystems & Environment 108:145-154.
Settlements Remaining Settlements:
Changes in Carbon Stocks in Urban Trees
Cairns, M.A.,S. Brown, E.H.Helmer, and G.A.Baumgardner
(1997) "Root Biomass Allocation in the World's Upland
Forests." Oceologia 111: 1-11.
deVries, R.E. (1987) A Preliminary Investigation of the
Growth and Longevity of Trees in Central Park. New
Brunswick, NJ: Rutgers University, M.S. thesis.
Dwyer, J.F., D.J. Nowak, M.H. Noble, and S.M Sisinni
(2000) Connecting People with Ecosystems in the 21''
Century: An Assessment of Our Nation's Urban Forests.
General Technical Report PNW-GTR-490. U.S. Department
of Agriculture, Forest Service, Pacific Northwest Research
Station, Portland, OR.
Fleming, L.E. (1988) Growth Estimation of Street Trees in
Central New Jersey. M.S. thesis, Rutgers University. New
Brunswick, NJ.
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme, J. Penman, et al., eds. August 13, 2004.
Available online at .
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change. United Nations
Environment Programme, Organization for Economic Co-
Operation and Development, International Energy Agency.
Paris, France.
Nowak, D.J. (2002a) E-mail from David Nowak of the
USDAForest Service to Barbara Braatz at ICE International,
containing information on possible urban tree carbon and
forest carbon overlap, January 10, 2002.
Nowak, D.J. (2002b) E-mail from David Nowak of the
USDA Forest Service to Barbara Braatz at ICF International,
regarding significant digits. October 29, 2002.
Nowak, D.J. (1994) "Atmospheric Carbon Dioxide Reduction
by Chicago's Urban Forest." In: E.G. McPherson, D.J.
Nowak, and R.A. Rowntree (eds.); Chicago's Urban Forest
Ecosystem: Results of the Chicago Urban Forest Climate
Project. U.S. Department of Agriculture Forest Service
General Technical Report NE-186, Radnor, PA, 83-94.
Nowak, D.J., (1986) "Silvics of an Urban Tree Species:
Norway Maple (Acerplatanoides L.)." M.S. thesis, College
of Environmental Science and Forestry, State University of
New York, Syracuse, NY.
Nowak, D.J. and D.E. Crane (2002) "Carbon Storage
and Sequestration by Urban Trees in the United States."
Environmental Pollution 116(3): 381-389.
Nowak, D.J., D.E. Crane, J.C. Stevens, and M. Ibarra (2002)
Brooklyn '.v Urban Forest. General Technical Report NE-290,
U.S. Department of Agriculture Forest Service, Newtown
Square, PA.
Nowak, D.J., M.H. Noble, S.M. Sisinni, and J.F. Dwyer
(2001) "Assessing the U.S. Urban Forest Resource. "Journal
of Forestry 99(3):37^2.
Nowak, D.J., J.T.Walton, E.G. Kaya, and J.F. Dwyer (2005)
"The Increasing Influence of Urban Environments on U.S.
Forest Management." Journal of Forestry.
References 11-51
-------
Smith, W.B. and S.R. Shifley (1984) Diameter Growth,
Survival, and Volume Estimates for Trees in Indiana and
Illinois. Res. Pap. NC-257. North Central Forest Experiment
Station, U.S. Department of Agriculture Forest Service, St.
Paul,MN.
Settlements Remaining Settlements:
Oirect N20 Fluxes from Settlement Soils
AAPFCO (2006) Commercial Fertilizers 2005. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2005) Commercial Fertilizers 2004. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2004) Commercial Fertilizers 2003. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2003) Commercial Fertilizers 2002. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2002) Commercial Fertilizers 2001. Association
of American Plant Food Control Officials and The Fertilizer
Institute, University of Kentucky, Lexington, KY.
AAPFCO (2000a) 1999-2000 Commercial Fertilizers Data.
ASCII files. Available: David Terry, Secretary, AAPFCO,
Lexington, KY.
AAPFCO (2000b) Commercial Fertilizers 2000. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1999) Commercial Fertilizers 1999. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1998) Commercial Fertilizers 1998. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1997) Commercial Fertilizers 7997. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1996) Commercial Fertilizers 7996. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
AAPFCO (1995) Commercial Fertilizers 7995. Association
of American Plant Food Control Officials, University of
Kentucky, Lexington, KY.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston,L. Buenida, K. Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
Qian, Y. (2004) Meeting between Yaling Qian of
Horticulture and Landscape Architecture Department,
Colorado State University and William Patron and Stephen
Del Grosso of Natural Resource Ecology Laboratory,
Colorado State University, regarding the percentage of
national fertilizer applied to turf grass (10% of national N)
and the confidence interval for this estimate (-50 to +20%).
September 17, 2004.
TVA (1994) Commercial Fertilizers 1994. Tennessee Valley
Authority, Muscle Shoals, AL.
TVA(1993) Commercial Fertilizers 1993. Tennessee Valley
Authority, Muscle Shoals, AL.
TVA (1992) Commercial Fertilizers 1992. Tennessee Valley
Authority, Muscle Shoals, AL.
TVA (1991) Commercial Fertilizers 1991. Tennessee Valley
Authority, Muscle Shoals, AL.
Other: Changes in Yard Trimming and
Food Scrap Stocks in Landfills
Barlaz, M.A. (2005) "Decomposition of Leaves in Simulated
Landfill." Letter report to Randall Freed, ICF International.
June 29,2005.
Barlaz,M.A. (1998) "Carbon Storage during Biodegradation
of Municipal Solid Waste Components in Laboratory-Scale
Landfills." Global Biogeochemical Cycles 12:373-380.
Eleazer, W.E., W.S. Odle, Y. Wang, and M. Barlaz (1997)
"Biodegradability of Municipal Solid Waste Components
in Laboratory-Scale Landfills" Environmental Science
Technology, 31:911-917.
EPA (2005) Municipal Solid Waste Generation. Recycling,
and Disposal in the United States: 2003 Facts and Figures.
U.S. Environmental Protection Agency, Office of Solid Waste
and Emergency Response, Washington, DC. Available online
at .
EPA (2005a) Municipal Solid Waste in the United States:
2003 Data Tables. U.S. Environmental Protection Agency,
Office of Solid Waste and Emergency Response, Washington,
DC. Available online at .
EPA (2003) Characterization of Municipal Solid Waste in
the United States: 2001 Update. (Draft) U.S. Environmental
Protection Agency, Office of Solid Waste and Emergency
Response. Washington, DC.
EPA (1999) Characterization of Municipal Solid Waste in the
United States: 1998 Update. U.S. Environmental Protection
Agency, Office of Solid Waste and Emergency Response,
Washington, DC.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme,H.S.Eggleston,L.Buenida,K. Miwa,T.Ngara,
and K. Tanabe (eds.); Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
11-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme, J. Penman, et al., (eds). August 13, 2004.
Available online at .
Oshins, C., and D. Block (2000) "Feedstock Composition at
Composting Sites." Biocycle 41(9):31-34.
Schneider, S. (2007) E-mail between Shelly Schneider of
Franklin Associates, a Division of ERG and Sarah Shapiro
of ICF International. January 10,2007.
Tchobanoglous, G., H. Theisen, and S.A. Vigil (1993)
Integrated Solid Waste Management, 1st edition. McGraw-
Hill, NY. Cited by Barlaz (1998).
Waste
Landfills
40 CFR Part 60, Subpart Cc (2005) Emission Guidelines
and Compliance Times for Municipal Solid Waste Landfills,
60.30c--60.36c, Code of Federal Regulations, Title 40.
Available online at .
40 CFR Part 60, Subpart WWW (2005) Standards of
Performance for Municipal Solid Waste Landfills, 60.750-
-60.759, Code of Federal Regulations, Title 40. Available
online at .
Barlaz, M.A. (2005) "Decomposition of Leaves in Simulated
Landfill." Letter report to Randall Freed, ICF International.
June 29, 2005.
Barlaz, M.A. (1998) "Carbon Storage during Biodegradation
of Municipal Solid Waste Components in Laboratory-Scale
Landfills." Global Biogeochemical Cycles 12:373-380.
Bingemer, H. and J. Crutzen (1987) "The Production of
Methane from Solid Wastes," Journal of Geophysical
Research, 92:2181-2187.
BioCycle (2006) "15th Annual BioCycle Nationwide Survey:
The State of Garbage in America" By P. Simmons, N.
Goldstein, S. Kaufman, N. Goldstein, N. Themelis, and J.
Thompson. BioCycle. April 2006.
Czepiel, P., B. Mosher, P. Crill, and R. Harriss (1996)
"Quantifying the Effect of Oxidation on Landfill
Methane Emissions." Journal of Geophysical Research,
101(D11):16721-16730.
Energy Information Agency (EIA) (2006) Voluntary
Greenhouse Gas Reports for EIA Form 1605B (Reporting
Year 2004). Available online at .
EPA (2006) Landfill Gas-to-Energy Project Database.
Landfill Methane and Outreach Program. July 2006.
EPA (2005) Municipal Solid Waste in the United States:
2003 Facts and Figures. Office of Solid Waste and
Emergency Response, U.S. Environmental Protection
Agency, Washington, DC. Available at .
EPA (1998) Compilation of Air Pollution Emission Factors,
Publication AP-42, Section 2.4 Municipal Solid Waste
Landfills. November 1998.
EPA (1993) Anthropogenic Methane Emissions in the
United States, Estimates for 1990: Report to Congress,
U.S. Environmental Protection Agency, Office of Air and
Radiation, Washington, DC. EPA/430-R-93-003. April
1993.
EPA (1988) National Survey of Solid Waste (Municipal)
Landfill Facilities, U.S. Environmental Protection Agency,
Washington, DC. EPA/530-SW-88-011. September 1988.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S.Eggleston,L.Buenida,K. Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
IPCC (2003) Good Practice Guidance for Land Use, Land-
Use Change, and Forestry. The Intergovernmental Panel
on Climate Change, National Greenhouse Gas Inventories
Programme, J. Penman, et al., eds. August 13, 2004.
Available online at .
Mancinelli,R. and C. McKay (1985) "Methane-Oxidizing
Bacteria in Sanitary Landfills." Proc. First Symposium on
Biotechnical Advances in Processing Municipal Wastes
for Fuels and Chemicals, Minneapolis, MN, 437-450.
August 1984.
Peer, R., S. Thorneloe, and D. Epperson (1993) "AComparison
of Methods for Estimating Global Methane Emissions from
Landfills." Chemo sphere, 26(l-4):387-400.
RTI (2004) Documentation for Changes to the Methodology
for the Inventory of Methane Emissions from Landfills.
September 2004.
Solid Waste Association of North America (SWANA) (1998)
Comparison of Models for Predicting Landfill Methane
Recovery. Publication No. GR-LG 0075. March 1998.
U.S. Bureau of Census (2006) International Data Base. April
2006. Available online at
-------
Doom, M. and E. Scheehle (2002) "Estimate of U.S.
Methane Emissions from Industrial Wastewater; Enhancing
Completeness of the Annual National Greenhouse Gas
Inventory." Third Int. Symposium on Non- CO2 Greenhouse
Gases (NCGG-3), Maastricht, Netherlands. January 21-23,
2002.
Eckenfelder, W.W. (1980) Principles of Water Quality
Management. CBI Publishing Company, Inc. Boston MA.
EPA (2004a) Clean Watersheds Needs Survey 2004-Report
to Congress. U.S. Environmental Protection Agency, Office
of Wastewater Management, Washington, DC.
EPA (2004b) Technical Development Document for the Final
Effluent Limitations Guidelines and Standards for the Meat
and Poultry Products Point Source Category (40 CFR 432).
Office of Water, U.S. Environmental Protection Agency,
Washington. DC, EPA-821-R-04-011. July 2004.
EPA (2002) Development Document for the Proposed
Effluent Limitations Guidelines and Standards for the Meat
and Poultry Products Industry Point Source Category (40
CFR 432). Office of Water, U.S. Environmental Protection
Agency, Washington, DC, EPA-821-B-01-007. January
2002.
EPA (2000) Clean Watersheds Needs Survey 2000-Report
to Congress. Office of Wastewater Management, U.S.
Environmental Protection Agency, Washington, DC.
Available online at .
EPA (1998) "AP-42 Compilation of Air Pollutant Emission
Factors." Chapter 2.4, Table 2.4-3, page 2.4-13. Available
online at .
EPA (1997a) Estimates of Global Greenhouse Gas Emissions
from Industrial and Domestic Wastewater Treatment. Office
of Policy, Planning, and Evaluation, U.S. Environmental
Protection Agency, Washington, DC, EPA-600/R-97-091.
September 1997.
EPA (1997b) Supplemental Technical Development Document
for Effluent Guidelines and Standards (Subparts B & E).
EPA-821-R-97-011. Office of Water, U.S. Environmental
Protection Agency, Washington, DC. October 1997.
EPA (1996) 7996 Clean Water Needs Survey Report
to Congress. Assessment of Needs for Publicly Owned
Wastewater Treatment Facilities, Correction of Combined
Sewer Overflows, and Management of Storm Water and
Nonpoint Source Pollution in the United States. Office of
Wastewater Management, U.S. Environmental Protection
Agency, Washington, DC. Available online at .
EPA (1993a) Anthropogenic Methane Emissions in the
U.S.: Estimates for 1990, Report to Congress. Office of
Air and Radiation, U.S. Environmental Protection Agency,
Washington, DC. April 1993.
EPA (1993b) Development Document for the Proposed
Effluent Limitations Guidelines and Standards for the Pulp,
Paper and Paperboard Point Source Category. EPA-821-
R-93-019. Office of Water, U.S. Environmental Protection
Agency, Washington, DC. October 1993.
EPA (1992) Clean Watersheds Needs Survey 1992-Report
to Congress. Office of Wastewater Management, U.S.
Environmental Protection Agency, Washington, DC.
EPA (1974) Development Document for Effluent Limitations
Guidelines and New Source Performance Standards for the
Apple, Citrus, and Potato Processing Segment of the Canned
and Preserved Fruits and Vegetables Point Source Category.
Office of Water, U.S. Environmental Protection Agency,
Washington, DC, EPA-440/l-74-027-a. March 1974.
FAO (2006) FAOSTAT Statistical Database, United
Nations Food and Agriculture Organization. Available
online at . Accessed August 21, 2006.
Great Lakes-Upper Mississippi River Board of State and
Provincial Public Health and Environmental Managers.
(2004) Recommended Standards for Wastewater Facilities
(Ten-State Standards).
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida, K. Miwa,T Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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 (1.1V.2000). May 2000.
Lockwood-Post (2002) Lockwood-Post's Directory of Pulp,
Paper and Allied Trades, Mi Her-Free man Publications, San
Francisco, CA.
Metcalf & Eddy, Inc. (2003) Wastewater Engineering:
Treatment, Disposal and Reuse, 4th ed. McGraw Hill
Publishing.
Metcalf & Eddy, Inc. (1991) Wastewater Engineering:
Treatment, Disposal and Reuse, 3rd ed. McGraw Hill
Publishing.
Nemerow, N.L. and A. Dasgupta (1991) Industrial and
Hazardous Waste Treatment. Van Nostrand Reinhold. NY.
ISBN 0-442-31934-7.
Pulp and Paper (2006) "AF&PAprojects more capacity losses
this year, small gains in 2007-08." April 2006.
Pulp and Paper (2005) "U.S. paper/board production rises
in 2004 to 91.47 million tons." April 2005.
Pulp and Paper (2003-2006) "Month in Statistics." January
2003-June 2006.
11-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2QD5
-------
Scheehle, E.A., and Doom, M.R. (2001) "Improvements to
the U.S. Wastewater Methane and Nitrous Oxide Emissions
Estimate."July 2001.
U.S. Census Bureau (2006a) International Database. Available
online at
and .
U.S. Census Bureau (2006b) "American Housing Survey."
Table 1A-4: Selected Equipment and Plumbing—All Housing
Units. From 1989, 1991,1993, 1995,1997,1999,2001,2003
and 2005 reports. Available online at .
USDA (2006) National Agricultural Statistics Service.
Washington, DC. Available online at and .
USPoultry (2006) Email from John Starkey, USPOULTRY
to D. Bartram, ERG. 30 August 2006.
World Bank (1999) Pollution Prevention and Abatement
Handbook 1998, Toward Cleaner Production. The
International Bank for Reconstruction and Development,
The World Bank, Washington, DC. ISBN 0-8213-3638-X.
Waste Sources of Indirect Greenhouse
Gases
EPA (2006) Air Emissions Trends— Continued Progress
Through 2005. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data between the Office of Air Pollution
and the Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency (EPA). December 22,
2003.
EPA (1997) Compilation of Air Pollutant Emission Factors,
AP-42. Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency, Research Triangle Park,
NC. October 1997.
Recalculations and Improvements
EIA (2006) Annual Energy Review 2005. Energy Information
Administration, U.S. Department of Energy. Washington, DC,
Tables 10.2aand 10.2b. July 2006. DOE/EIA-0384(2005).
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buenida,K. Miwa,TNgara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
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.
USDA (2005e) 1992,1997, and 2002 Census of Agriculture.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . Accessed March 2006.
References 11-55
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Methane Emissions from Landfills
Landfills are the largest single anthropogenic soiirce
environment where the oxygen content is low or nonexistent
waste, household waste, food waste, and paper are
methane. Emissions from this source have decreased
and combustion of landfill gas.
Carbon Dioxide Emissions from Mobile Combustion:
Fossil fuel combustion in airplanes and other aircraft
gas emissions in 2005.
Kerosene jet fuel is the primary fuel used for civil avi ition (
is most commonly used in general aviation (i.e.,
this source have increased 3 percent since 1990.
. The main types of fuel burned in aircraft are kerosene
. Almost all of the energy cons imed for transport
Carbon Dioxide Emissions from Mobile Combustion:
Fossil fuel combustion in road and non-road vehicles
gas emissions in 2005.
products. Since the 1970s, the number of highway v
than the overall population; the number of miles dri'
United States have increased steadily since the 198(
since 1990.
Carbon Dioxide Emissions from Stationary Combusti >n: Coal
Carbon dioxide emissions from combustion of natural gas in stationary appl
29 percent of U.S. greenhouse gas emissions in 200:
consumed in electric power generation. Coal is also u
and commercial applications. Emissions from this
of methane emissions in the United States. In an
(i.e. anaerobic), organic materials such as yard
decomposed by bacteria, resulting in the generation of
18 percent since 1990, due mostly to greater collection
Aviation
resulted in approximately 3 percent of U.S. greenhouse
-type jet fuel and aviation gasoline.
.e., most commercial aircraft) and aviation gasoline
recreational and corporate aircraft). Emissions from
sr lall
Road & Other
ccounted for approximately 23 percent of U.S. greenhouse
:ation was supplied by petroleum-based
hides registered in the United States has increased faster
en and the gallons of gasoline consumed each year in the
's. Emissions from this source have increased 33 percent
ications accounted for approximately
i. The vast majority of coal burned in the United States is
ed in industrial boilers, and in small amounts in residential
source have increased 23 percent since 1990.
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v/EPA
United States
Enviromental Protection
Agency
EPA 430-R-07-002 April 2007
Office of Atmospheric Programs (6207J)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
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