v»EPA Inventory of U.S. Greenhouse Gas
Emissions and Sinks: 1990-2007
-------
INVENTORY OF U.S. GREENHOUSE GAS
EMISSIONS AND SINKS:
199O-2OO7
April 15,2009
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
U.S.A.
-------
-------
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 and transportation.
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, Randy Freed, and their staff at ICF International's Energy, Climate
and Transportation Practice, including Don Robinson, Diana Pape, Susan Asam, Michael Grant, Mark Flugge, Rubab Bhangu,
Robert Lanza, Chris Steuer, Lauren Pederson, Kamala Jayaraman, Jeremy Scharfenberg, Mollie Averyt, Stacy Hetzel,
Lauren Smith, Zachary Schaffer, Vineet Aggarwal, Colin McGroarty, Hemant Mallya, Victoria Thompson, Jean Kim,
Erin Gray, Tristan Kessler, Sarah Menassian, Katrin Moffroid, Veronica Kennedy, Aaron Beaudette, Nikhil Nadkarni,
Joseph Herr, 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.
-------
-------
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(l)(a) of the United Nations Framework Convention on Climate Change .
2 See .
iii
-------
-------
Table of Contents
Acknowledgments i
Table of Contents v
List of Tables, Figures, and Boxes viii
Tables viii
Figures xvii
Boxes xix
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-12
ES.4. Other Information ES-15
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 1-14
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 2-17
2.3. Indirect Greenhouse Gas Emissions (CO, NOX, NMVOCs, and SO2) 2-28
3. Energy 3-1
3.1. Fossil Fuel Combustion (IPCC Source Category 1A) 3-4
3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-31
3.3. Coal Mining (IPCC Source Category IBla) 3-36
3.4. Abandoned Underground Coal Mines (IPCC Source Category IB la) 3-38
3.5. Natural Gas Systems (IPCC Source Category lB2b) 3-42
3.6. Petroleum Systems (IPCC Source Category lB2a) 3-46
3.7. Incineration of Waste (IPCC Source Category 1A5) 3-51
3.8. Energy Sources of Indirect Greenhouse Gas Emissions 3-54
-------
3.9. International Bunker Fuels (IPCC Source Category 1: Memo Items) 3-55
3.10. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A) 3-59
4. Industrial Processes 3-1
4.1. Cement Production (IPCC Source Category 2A1) 4-5
4.2. Lime Production (IPCC Source Category 2A2) 4-7
4.3. Limestone and Dolomite Use (IPCC Source Category 2A3) 4-10
4.4. Soda Ash Production and Consumption (IPCC Source Category 2A4) 4-13
4.5. Ammonia Production (IPCC Source Category 2B1) and Urea Consumption 4-15
4.6. Nitric Acid Production (IPCC Source Category 2B2) 4-19
4.7. Adipic Acid Production (IPCC Source Category 2B3) 4-20
4.8. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption 4-23
4.9. Petrochemical Production (IPCC Source Category 2B5) 4-25
4.10. Titanium Dioxide Production (IPCC Source Category 2B5) 4-28
4.11. Carbon Dioxide Consumption (IPCC Source Category 2B5) 4-30
4.12. Phosphoric Acid Production (IPCC Source Category 2B5) 4-32
4.13. Iron and Steel Production (IPCC Source Category 2C1) and Metallurgical Coke Production 4-35
4.14 Ferroalloy Production (IPCC Source Category 2C2) 4-44
4.15 Aluminum Production (IPCC Source Category 2C3) 4-46
4.16 Magnesium Production and Processing (IPCC Source Category 2C4) 4-50
4.17. Zinc Production (IPCC Source Category 2C5) 4-53
4.18. Lead Production (IPCC Source Category 2C5) 4-56
4.19. HCFC-22 Production (IPCC Source Category 2E1) 4-57
4.20. Substitution of Ozone Depleting Substances (IPCC Source Category 2F) 4-59
4.21. Semiconductor Manufacture (IPCC Source Category 2F6) 4-63
4.22. Electrical Transmission and Distribution (IPCC Source Category 2F7) 4-69
4.23. Industrial Sources of Indirect Greenhouse Gases 4-74
5. Solvent and Other Product Use 5-1
5.1. Nitrous Oxide from Product Uses (IPCC Source Category 3D) 5-1
5.2. Indirect Greenhouse Gas Emissions from Solvent Use 5-3
6. Agriculture 6-1
6.1. Enteric Fermentation (IPCC Source Category 4A) 6-2
6.2. Manure Management (IPCC Source Category 4B) 6-7
6.3. Puce Cultivation (IPCC Source Category 4C) 6-13
6.4. Agricultural Soil Management (IPCC Source Category 4D) 6-18
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F) 6-32
7. Land Use, Land-Use Change, and Forestry 7-1
7.1. Representation of the U.S. Land Base 7-4
7.2. Forest Land Remaining Forest Land 7-13
7.3. Land Converted to Forest Land (IPCC Source Category 5A2) 7-27
7.4. Cropland Remaining Cropland (IPCC Source Category 5B1) 7-27
vi
-------
7.5. Land Converted to Cropland (IPCC Source Category 5B2) 7-38
7.6. Grassland Remaining Grassland (IPCC Source Category 5C1) 7-42
7.7. Land Converted to Grassland (IPCC Source Category 5C2) 7-47
7.8. Wetlands Remaining Wetlands (IPCC Source Category 5D1) 7-52
7.9. Settlements Remaining Settlements 7-56
7.10. Land Converted to Settlements (Source Category 5E2) 7-61
7.11. Other (IPCC Source Category 5G) 7-61
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. Composting (IPCC Source Category 6D) 8-17
8.4. Waste Sources of Indirect Greenhouse Gases 8-19
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 CLLj, N2O, and Indirect Greenhouse Gases from Stationary Combustion
3.2. Methodology for Estimating Emissions of CLL,, N2O, and Indirect Greenhouse Gases from Mobile Combustion
and Methodology for and Supplemental Information on Transportation-Related GHG Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CFL, and CO2 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CFL, and CO2 Emissions from Petroleum Systems
3.6. Methodology for Estimating CO2 and N2O Emissions from the Incineration of Waste
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
3.10. Methodology for Estimating CFL, 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 Cropland
and Grassland
3.14. Methodology for Estimating CH4 Emissions from Landfills
vii
-------
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 Analyses 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
Fuel Consuming End-Use Sector (Tg CO2 Eq.) ES-9
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg CO2 Eq.) ES-13
Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) ES-14
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) ES-15
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.) ES-16
Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with
Electricity-Related Emissions Distributed (Tg CO2 Eq.) ES-17
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100) ES-18
Table ES-10: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) ES-19
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
Table 1-4: Key Categories for the United States (1990-2007) 1-12
Table 1-5: Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent) 1-14
Table 1-6: IPCC Sector Descriptions 1-16
Table 1-7: List of Annexes 1-17
viii
-------
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) 2-4
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-6
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg CO2 Eq.) 2-8
Table 2-4: Emissions from Energy (Tg CO2 Eq.) 2-10
Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 2-11
Table 2-6: Emissions from Industrial Processes (Tg CO2 Eq.) 2-13
Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.) 2-13
Table 2-8: Emissions from Agriculture (Tg CO2 Eq.) 2-14
Table 2-9: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-15
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-16
Table 2-11: Emissions from Waste (Tg CO2 Eq.) 2-17
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors
(Tg CO2 Eq. and Percent of Total in 2007) 2-18
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-21
Table 2-14: U.S Greenhouse Gas Emissions by Economic Sector and Gas with
Electricity-Related Emissions Distributed (Tg CO2 Eq.) and Percent of Total in 2007 2-22
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-24
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100) 2-27
Table 2-17: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) 2-29
Table 3-1: CO2, CFL,, 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, CK4, and N2O Emissions from Fossil Fuel Combustion (Tg CO2 Eq.) 3-4
Table 3-4: CO2, CK4, and N2O Emissions from Fossil Fuel Combustion (Gg) 3-4
Table 3-5: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.) 3-5
Table 3-6: Annual Change in CO2 Emissions from Fossil Fuel Combustion for
Selected Fuels and Sectors (Tg CO2 Eq. and Percent) 3-6
Table 3-7: CO2, CH4, and N2O Emissions from Fossil Fuel Combustion by Sector (Tg CO2 Eq.) 3-8
Table 3-8: CO2, CK4, and N2O Emissions from Fossil Fuel Combustion by
End-Use Sector (Tg CO2 Eq.) 3-9
Table 3-9: CO2 Emissions from Stationary Combustion (Tg CO2 Eq.) 3-10
Table 3-10: CFL, Emissions from Stationary Combustion (Tg CO2 Eq.) 3-11
Table 3-11: N2O Emissions from Stationary Combustion (Tg CO2 Eq.) 3-12
Table 3-12: CO2 Emissions from Fossil Fuel Combustion in Transportation
End-Use Sector (Tg CO2 Eq.) 3-15
Table 3-13: CK4 Emissions from Mobile Combustion (Tg CO2 Eq.) 3-17
Table 3-14: N2O Emissions from Mobile Combustion (Tg CO2 Eq.) 3-18
Table 3-15: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu) 3-21
Table 3-16: Carbon Intensity from All Energy Consumption by Sector (Tg CO2 Eq./QBtu) 3-22
Table 3-17: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-related
Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent) 3-24
ix
-------
Table 3-18: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Energy-Related Stationary Combustion, Including Biomass (Tg CO2 Eq. and Percent) 3-26
Table 3-19: Tier 2 Quantitative Uncertainty Estimates for CFLj and N2O Emissions from
Mobile Combustion (Tg CO2 Eq. and Percent) 3-29
Table 3-20: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.) 3-31
Table 3-21: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-32
Table 3-22: 2007 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-33
Table 3-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Non-Energy Uses
of Fossil Fuels (Tg CO2 Eq. and Percent) 3-35
Table 3-24: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses
of Fossil Fuels (Percent) 3-35
Table 3-25: CK4 Emissions from Coal Mining (Tg CO2 Eq.) 3-36
Table 3-26: CH4 Emissions from Coal Mining (Gg) 3-36
Table 3-27: Coal Production (Thousand Metric Tons) 3-37
Table 3-28: Tier 2 Quantitative Uncertainty Estimates for CFLj Emissions from
Coal Mining (Tg CO2 Eq. and Percent) 3-38
Table 3-29: CK4 Emissions from Abandoned Underground Coal Mines (Tg CO2 Eq.) 3-39
Table 3-30: CK4 Emissions from Abandoned Underground Coal Mines (Gg) 3-39
Table 3-31: Number of Gas sy Abandoned Mines Occurring in U. S. Basins Grouped by
Class According to Post-abandonment State 3-41
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CFLj Emissions from
Abandoned Underground Coal Mines (Tg CO2 Eq. and Percent) 3-42
Table 3-33: CK4 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-42
Table 3-34: CK4 Emissions from Natural Gas Systems (Gg) 3-42
Table 3-35: Non-combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-43
Table 3-36: Non-combustion CO2 Emissions from Natural Gas Systems (Gg) 3-43
Table 3-37: Tier 2 Quantitative Uncertainty Estimates for CFLj and Non-energy CO2 Emissions from
Natural Gas Systems (Tg CO2 Eq. and Percent) 3-45
Table 3-38: CK4 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-47
Table 3-39: CK4 Emissions from Petroleum Systems (Gg) 3-47
Table 3-40: CO2 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-47
Table 3-41: CO2 Emissions from Petroleum Systems (Gg) 3-47
Table 3-42: Tier 2 Quantitative Uncertainty Estimates for CFLj and CO2 Emissions from
Petroleum Systems (Tg CO2 Eq. and Percent) 3-49
Table 3-43: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.) 3-50
Table 3-44: Potential Emissions from CO2 Capture and Transport (Gg) 3-50
Table 3-45: CO2 and N2O Emissions from the Incineration of Waste (Tg CO2 Eq.) 3-52
Table 3-46: CO2 and N2O Emissions from the Incineration of Waste (Gg) 3-52
Table 3-47: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-53
Table 3-48: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from the
Incineration of Waste (Tg CO2 Eq. and Percent) 3-53
-------
Table 3-49: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg) 3-54
Table 3-50: CO2, CLL,, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.) 3-56
Table 3-51: CO2, CLL,, and N2O Emissions from International Bunker Fuels (Gg) 3-56
Table 3-52: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-57
Table 3-53: Marine Fuel Consumption for International Transport (Million Gallons) 3-57
Table 3-54: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.) 3-60
Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Gg) 3-60
Table 3-56: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq.) 3-60
Table 3-57: CO2 Emissions from Ethanol Consumption (Gg) 3-60
Table 3-58: Woody Biomass Consumption by Sector (Trillion Btu) 3-61
Table 3-59: Ethanol Consumption by Sector (Trillion Btu) 3-61
Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.) 4-3
Table 4-2: Emissions from Industrial Processes (Gg) 4-4
Table 4-3: CO2 Emissions from Cement Production (Tg CO2 Eq. and Gg) 4-5
Table 4-4: Clinker Production (Gg) 4-6
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Cement Production (Tg CO2 Eq. and Percent) 4-6
Table 4-6: CO2 Emissions from Lime Production (Tg CO2 Eq. and Gg) 4-7
Table 4-7: Potential, Recovered, and Net CO2 Emissions from Lime Production (Gg) 4-7
Table 4-8: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and
Dead-Burned-Dolomite Lime Production (Gg) 4-8
Table 4-9: Adjusted Lime Production (Gg) 4-9
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Lime Production (Tg CO2 Eq. and Percent) 4-10
Table 4-11: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.) 4-11
Table 4-12: CO2 Emissions from Limestone & Dolomite Use (Gg) 4-11
Table 4-13: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-12
Table 4-14: Dolomitic Magnesium Metal Production Capacity (Metric Tons) 4-12
Table 4-15: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Limestone and Dolomite Use (Tg CO2 Eq. and Percent) 4-13
Table 4-16: CO2 Emissions from Soda Ash Production and Consumption (Tg CO2 Eq.) 4-14
Table 4-17: CO2 Emissions from Soda Ash Production and Consumption (Gg) 4-14
Table 4-18: Soda Ash Production and Consumption (Gg) 4-15
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Soda Ash Production and Consumption (Tg CO2 Eq. and Percent) 4-15
Table 4-20: CO2 Emissions from Ammonia Production and Urea Consumption (Tg CO2 Eq.) 4-16
Table 4-21: CO2 Emissions from Ammonia Production and Urea Consumption (Gg) 4-16
Table 4-22: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg) 4-17
Table 4-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Ammonia Production and Urea Consumption (Tg CO2 Eq. and Percent) 4-18
Table 4-24: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg) 4-19
xi
-------
Table 4-25: Nitric Acid Production (Gg) 4-20
Table 4-26: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from
Nitric Acid Production (Tg CO2 Eq. and Percent) 4-20
Table 4-27: N2O Emissions from Adipic Acid Production (Tg CO2 Eq. and Gg) 4-21
Table 4-28: Adipic Acid Production (Gg) 4-22
Table 4-29: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from
Adipic Acid Production (Tg CO2 Eq. and Percent) 4-23
Table 4-30: CO2 and CFLj Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.) 4-23
Table 4-31: CO2 and CFLj Emissions from Silicon Carbide Production and Consumption (Gg) 4-23
Table 4-32: Production and Consumption of Silicon Carbide (Metric Tons) 4-24
Table 4-33: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from
Silicon Carbide Production and Consumption (Tg CO2 Eq. and Percent) 4-24
Table 4-34: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.) 4-25
Table 4-35: CO2 and CFLj Emissions from Petrochemical Production (Gg) 4-25
Table 4-36: Production of Selected Petrochemicals (Thousand Metric Tons) 4-26
Table 4-37: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock
(Secondary Feedstock) Consumption (Thousand Metric Tons) 4-27
Table 4-38: Tier 2 Quantitative Uncertainty Estimates for CO2 and CK4 Emissions from Petrochemical
Production and CO2 Emissions from Carbon Black Production (Tg CO2 Eq. and Percent) 4-27
Table 4-39: CO2 Emissions from Titanium Dioxide (Tg CO2 Eq. and Gg) 4-28
Table 4-40: Titanium Dioxide Production (Gg) 4-29
Table 4-41: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Titanium Dioxide Production (Tg CO2 Eq. and Percent) 4-29
Table 4-42: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg) 4-30
Table 4-43: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for
Jackson Dome and Bravo Dome 4-31
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
CO2 Consumption (Tg CO2 Eq. and Percent) 4-32
Table 4-45: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. and Gg) 4-33
Table 4-46: Phosphate Rock Domestic Production, Exports, and Imports (Gg) 4-33
Table 4-47: Chemical Composition of Phosphate Rock (Percent by Weight) 4-34
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Phosphoric Acid Production (Tg CO2 Eq. and Percent) 4-35
Table 4-49: CO2 and CH4 Emissions from Metallurgical Coke Production (Tg CO2 Eq.) 4-37
Table 4-50: CO2 and CK4 Emissions from Metallurgical Coke Production (Gg) 4-37
Table 4-51: CO2 Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-38
Table 4-52: CO2 Emissions from Iron and Steel Production (Gg) 4-38
Table 4-53: CFLj Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-38
Table 4-54: CFLj Emissions from Iron and Steel Production (Gg) 4-38
xii
-------
Table 4-55: Material Carbon Contents for Metallurgical Coke Production 4-39
Table 4-56: CFL, Emission Factor for Metallurgical Coke Production (g CFL/metric ton) 4-39
Table 4-57: Production and Consumption Data for the Calculation of CO2 and CFL, Emissions from
Metallurgical Coke Production (Thousand Metric Tons) 4-39
Table 4-58: Production and Consumption Data for the Calculation of CO2 Emissions from
Metallurgical Coke Production (million ft3) 4-40
Table 4-59: CO2 Emission Factors for Sinter Production and Direct Reduced Iron Production 4-40
Table 4-60: Material Carbon Contents for Iron and Steel Production 4-40
Table 4-61: CFL, Emission Factors for Sinter and Pig Iron Production 4-41
Table 4-62: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from
Iron and Steel Production (Thousand Metric Tons) 4-41
Table 4-63: Production and Consumption Data for the Calculation of CO2 Emissions from Iron and
Steel Production (million ft3 unless otherwise specified) 4-42
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for CO2 and CFL, Emissions from Iron and
Steel Production (Tg CO2 Eq. and Percent) 4-43
Table 4-65: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.) 4-44
Table 4-66: CO2 and CK4 Emissions from Ferroalloy Production (Gg) 4-44
Table 4-67: Production of Ferroalloys (Metric Tons) 4-45
Table 4-68: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from
Ferroalloy Production (Tg CO2 Eq. and Percent) 4-46
Table 4-69: CO2 Emissions from Aluminum Production (Tg CO2 Eq. and Gg) 4-47
Table 4-70: PFC Emissions from Aluminum Production (Tg CO2 Eq.) 4-47
Table 4-71: PFC Emissions from Aluminum Production (Gg) 4-47
Table 4-72: Production of Primary Aluminum (Gg) 4-49
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from
Aluminum Production (Tg CO2 Eq. and Percent) 4-50
Table 4-74: SF6 Emissions from Magnesium Production and Processing (Tg CO2 Eq. and Gg) 4-50
Table 4-75: SF6 Emission Factors (kg SF6 per metric ton of Magnesium) 4-51
Table 4-76: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from
Magnesium Production and Processing (Tg CO2 Eq. and Percent) 4-52
Table 4-77: CO2 Emissions from Zinc Production (Tg CO2 Eq. and Gg) 4-53
Table 4-78: Zinc Production (Metric Tons) 4-55
Table 4-79: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Zinc Production (Tg CO2 Eq. and Percent) 4-56
Table 4-80: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg) 4-56
Table 4-81: Lead Production (Metric Tons) 4-57
Table 4-82: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Lead Production (Tg CO2 Eq. and Percent) 4-57
Table 4-83: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg) 4-58
Table 4-84: HCFC-22 Production (Gg) 4-59
xiii
-------
Table 4-85: Quantitative Uncertainty Estimates for HFC-23 Emissions from
HCFC-22 Production (Tg CO2 Eq. and Percent) 4-59
Table 4-86: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) 4-60
Table 4-87: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-60
Table 4-88: Emissions of FfFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) by Sector 4-61
Table 4-89: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from
ODS Substitutes (Tg CO2 Eq. and Percent) 4-63
Table 4-90: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.) 4-64
Table 4-91: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-64
Table 4-92: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from
Semiconductor Manufacture (Tg CO2 Eq. and Percent) 4-68
Table 4-93: SF6 Emissions from Electric Power Systems and Electrical Equipment
Manufacturers (Tg CO2 Eq.) 4-69
Table 4-94: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg) 4-69
Table 4-95: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission
and Distribution (Tg CO2 Eq. and Percent) 4-72
Table 4-96: 2007 Potential and Actual Emissions of HFCs, PFCs, and SF6 from
Selected Sources (Tg CO2 Eq.) 4-73
Table 4-97: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-74
Table 5-1: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg) 5-1
Table 5-2: N2O Production (Gg) 5-2
Table 5-3: N2O Emissions from N2O Product Usage (Tg CO2 Eq. and Gg) 5-2
Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From N2O Product Usage
(Tg CO2 Eq. and Percent) 5-3
Table 5-5: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg) 5-4
Table 6-1: Emissions from Agriculture (Tg CO2 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: CK4 Emissions from Enteric Fermentation (Gg) 6-3
Table 6-5: Tier 2 Quantitative Uncertainty Estimates for CK4 Emissions from
Enteric Fermentation (Tg CO2 Eq. and Percent) 6-5
Table 6-6: CFLj and N2O Emissions from Manure Management (Tg CO2 Eq.) 6-8
Table 6-7: CH4 and N2O Emissions from Manure Management (Gg) 6-9
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O (Direct and Indirect)
Emissions from Manure Management (Tg CO2 Eq. and Percent) 6-12
Table 6-9: CH4 Emissions from Puce Cultivation (Tg CO2 Eq.) 6-14
Table 6-10: CH4 Emissions from Puce Cultivation (Gg) 6-15
Table 6-11: Puce Areas Harvested (Hectares) 6-16
Table 6-12: Ratooned Area as Percent of Primary Growth Area 6-16
Table 6-13: Non-USDA Data Sources for Puce Harvest Information 6-17
xiv
-------
Table 6-14: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Rice CultivationManure Management (Tg CO2 Eq. and Percent) 6-17
Table 6-15: N2O Emissions from Agricultural Soils (Tg CO2 Eq.) 6-20
Table 6-16: N2O Emissions from Agricultural Soils (Gg) 6-20
Table 6-17: Direct N2O Emissions from Agricultural Soils by Land Use Type and
N Input Type (Tg CO2 Eq.) 6-20
Table 6-18: Indirect N2O Emissions from all Land-Use Types (Tg CO2 Eq.) 6-21
Table 6-19: Quantitative Uncertainty Estimates of N2O Emissions from
Agricultural Soil Management in 2007 (Tg CO2 Eq. and Percent) 6-30
Table 6-20: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.) 6-33
Table 6-21: CK4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg) 6-33
Table 6-22: Agricultural Crop Production (Gg of Product) 6-35
Table 6-23: Percent of Rice Area Burned by State 6-35
Table 6-24: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-36
Table 6-25: Greenhouse Gas Emission Ratios and Conversion Factors 6-36
Table 6-26: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Field Burning of Agricultural Residues (Tg CO2 Eq. and Percent) 6-37
Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use,
Land-Use Change, and Forestry (Tg CO2 Eq.) 7-2
Table 7-2: Net CO2 Flux from Carbon Stock Changes in Land Use,
Land-Use Change, and Forestry (Tg C) 7-2
Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 7-3
Table 7-4: Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-3
Table 7-5: Land Use, Land-Use Change, and Forestry on Managed Land (Thousands of Hectares) 7-5
Table 7-6: Net Annual Changes in C Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools 7-16
Table 7-7: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools 7-16
Table 7-8: Forest Area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools 7-17
Table 7-9: Estimates of CO2 (Tg/yr) Emissions for the Lower 48 States and Alaska 7-18
Table 7-10: 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) 7-21
Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. Forests 7-24
Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (Gg) for U.S. Forests 7-24
Table 7-13: Estimated Carbon Released from Forest Fires for U.S. Forests 7-24
Table 7-14: Quantitative Uncertainty Estimates of Non-CO2 Emissions from
Forest Fires in Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent) 7-25
Table 7-15: N2O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Gg N2O) 7-26
Table 7-16: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in
Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent) 7-27
Table 7-17: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.) 7-29
Table 7-18: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C) 7-29
XV
-------
Table 7-19: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within
Cropland Remaining Cropland (Tg CO2 Eq. and Percent) 7-33
Table 7-20: CO2 Emissions from Liming of Agricultural Soils (Tg CO2 Eq.) 7-35
Table 7-21: CO2 Emissions from Liming of Agricultural Soils (Tg C) 7-35
Table 7-22: Applied Minerals (Million Metric Tons) 7-35
Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Liming of Agricultural Soils (Tg CO2 Eq. and Percent) 7-36
Table 7-24: CO2Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.) 7-37
Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C) 7-37
Table 7-26: Applied Urea (Million Metric Tons) 7-37
Table 7-27: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Urea Fertilization (Tg CO2 Eq. and Percent) 7-38
Table 7-28: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.) 7-39
Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-39
Table 7-30: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within
Land Converted to Cropland (Tg CO2 Eq. and Percent) 7-42
Table 7-31: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.) 7-43
Table 7-32: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-43
Table 7-33: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within
Grassland Remaining Grassland (Tg CO2 Eq. and Percent) 7-46
Table 7-34: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.) 7-48
Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-48
Table 7-36: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within
Land Converted to Grassland (Tg CO2 Eq. and Percent) 7-51
Table 7-37: Emissions from Lands Undergoing Peat Extraction (Tg CO2 Eq.) 7-53
Table 7-38: Emissions from Lands Undergoing Peat Extraction (Gg) 7-53
Table 7-39: Peat Production of Lower 48 States (in thousands of Metric Tons) 7-53
Table 7-40: Peat Production of Alaska (in thousands of Cubic Meters) 7-54
Table 7-41: Tier-2 Quantitative Uncertainty Estimates for CO2 and N2O Emissions from
Lands Undergoing Peat Extraction 7-55
Table 7-42: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C) 7-56
Table 7-43: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover (Percent),
and Annual C Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for 15 U.S. Cities 7-58
Table 7-44: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from
Changes in C Stocks in Urban Trees (Tg CO2 Eq. and Percent) 7-59
Table 7-45: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg N2O) 7-60
Table 7-46: Quantitative Uncertainty Estimates of N2O Emissions from Soils in
Settlements Remaining Settlements (Tg CO2 Eq. and Percent) 7-61
Table 7-47: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.) 7-62
Table 7-48: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C) 7-62
xvi
-------
Table 7-49: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%),
Initial C Content (%), and Half-Life (years) for Landfilled Yard Trimmings and
Food Scraps in Landfills 7-63
Table 7-50: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-64
Table 7-51: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and
Food Scraps in Landfills (Tg CO2 Eq. and Percent) 7-65
Table 8-1: Emissions from Waste (Tg CO2 Eq.) 8-1
Table 8-2: Emissions from Waste (Gg) 8-2
Table 8-3: CFL, Emissions from Landfills (Tg CO2 Eq.) 8-3
Table 8-4: CH4 Emissions from Landfills (Gg) 8-3
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CK4 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: CFL, 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) 8-9
Table 8-9: Industrial Wastewater CH4 Emissions by Sector for 2007 8-9
Table 8-10: U.S. Pulp and Paper; Meat and Poultry; Vegetables, Fruits and Juices Production;
and Fuels Production (Tg) 8-10
Table 8-11: Variables Used to Calculate Percent Wastewater Treated Anaerobically by Industry 8-11
Table 8-12: Wastewater How (m3/ton) and BOD Production (g/L) for U.S. Vegetables,
Fruits and Juices Production 8-12
Table 8-13: U.S. Population (Millions), Available Protein [kg/(person-year)], and
Protein Consumed [kg/(person-year)] 8-15
Table 8-14: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from
Wastewater Treatment (Tg CO2 Eq. and Percent) 8-16
Table 8-15: CFL, and N2O Emissions from Composting (Tg CO2 Eq.) 8-18
Table 8-16: CFL, and N2O Emissions from Composting (Gg) 8-18
Table 8-17: U.S. Waste Composted (Gg) 8-19
Table 8-18: Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting
(Tg CO2 Eq. and Percent) 8-19
Table 8-19: Emissions of NOX, CO, and NMVOCs from Waste (Gg) 8-19
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.) 10-3
Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from Land Use,
Land-Use Change, and Forestry (Tg CO2 Eq.) 10-5
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: 2007 Greenhouse Gas Emissions by Gas ES-7
Figure ES-5: 2007 Sources of CO2 Emissions ES-7
Figure ES-6: 2007 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type ES-8
xvii
-------
Figure ES-7: 2007 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion ES-8
Figure ES-8: 2007 Sources of CFL, Emissions ES-10
Figure ES-9: 2007 Sources of N2O Emissions ES-11
Figure ES-10: 2007 Sources of HFCs, PFCs, and SF6 Emissions ES-12
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector ES-12
Figure ES-12: 2007 U.S. Energy Consumption by Energy Source ES-13
Figure ES-13: Emissions Allocated to Economic Sectors ES-16
Figure ES-14 Emissions with Electricity Distributed to Economic Sectors ES-17
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product ES-18
Figure ES-16: 2007 Key Categories ES-20
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 Annual U.S. Greenhouse Gas Emissions Relative to 1990 2-2
Figure 2-4: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector 2-8
Figure 2-5: 2007 Energy Chapter Greenhouse Gas Sources 2-8
Figure 2-6: 2007 U.S. Fossil Carbon Hows (Tg CO2 Eq.) 2-9
Figure 2-7: 2007 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-9
Figure 2-8: 2007 End-Use Sector Emissions from Fossil Fuel Combustion 2-10
Figure 2-9: 2007 Industrial Processes Chapter Greenhouse Gas Sources 2-12
Figure 2-10: 2007 Agriculture Chapter Greenhouse Gas Emision Sources 2-14
Figure 2-11: 2007 Waste Chapter Greenhouse Gas Emission Sources 2-16
Figure 2-12: Emissions Allocated to Economic Sectors 2-18
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors 2-21
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-27
Figure 3-1: 2007 Energy Chapter Greenhouse Gas Emission Sources 3-1
Figure 3-2: 2007 U.S. Fossil Carbon Hows (Tg CO2 Eq.) 3-2
Figure 3-3: 2007 U.S. Energy Consumption by Energy Source 3-6
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu) 3-6
Figure 3-5: 2007 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-6
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2007) 3-7
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2007) 3-7
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the
United States (1974-2007) 3-7
Figure 3-9: Electricity Generation Retail Sales by End-Use Sector (1974-2007) 3-11
Figure 3-10: Industrial Production Indices (Index 2002=100) 3-13
Figure 3-11: Sales-Weighted Fuel Economy of New Passenger Cars and Light-Duty Trucks, 1990-2007 .... 3-16
Figure 3-12: Sales of New Passenger Cars and Light-Duty Trucks, 1990-2007 3-16
Figure 3-13: Mobile Source CFLj and N2O Emissions 3-17
Figure 3-14: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita
and Per Dollar GDP 3-22
xviii
-------
Figure 4-1: 2007 Industrial Processes Chapter Greenhouse Gas Emission Sources 4-1
Figure 6-1: 2007 Agriculture Chapter Greenhouse Gas Emission Sources 6-1
Figure 6-2: Sources and Pathways of N that Result in N2O Emissions from
Agricultural Soil Management 6-19
Figure 6-3: Major Crops, Average Annual Direct N2O Emissions by State,
Estimated Using the DAYCENT Model, 1990-2007 (Tg CO2 Eq./year) 6-22
Figure 6-4: Grasslands, Average Annual Direct N2O Emissions by State,
Estimated Using the DAYCENT Model, 1990-2007 (Tg CO2 Eq./year) 6-22
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions by State,
Estimated Using the DAYCENT Model, 1990-2007 (Gg N/year) 6-23
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions, by State,
Estimated Using the DAYCENT Model, 1990-2007 (Gg N/year) 6-23
Figure 6-7: Comparison of Measured Emissions at Field Sites with Modeled Emissions
Using the DAYCENT Simulation Model 6-31
Figure 7-1: Percent of Total Land Area in the General Land Use Categories for 2007 7-6
Figure 7-2: Forest Sector Carbon Pools and Hows 7-14
Figure7-3: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools 7-15
Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States, 2008 7-17
Figure 7-5: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States,
2007, Cropland Remaining Cropland 7-29
Figure 7-6: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States,
2007, Cropland Remaining Cropland 7-30
Figure 7-7: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States,
2007, Land Converted to Cropland 7-40
Figure 7-8: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States,
2007, Land Converted to Cropland 7-40
Figure 7-9: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States,
2007, Grassland Remaining Grassland 7-44
Figure 7-10: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States,
2007, Grassland Remaining Grassland 7-44
Figure 7-11: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States,
2007, Land Converted to Grassland 7-49
Figure 7-12: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States,
2007, Land Converted to Grassland 7-49
Figure 8-1: 2007 Waste Chapter Greenhouse Gas Emission 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-18
Box 1-1: The IPCC Fourth Assessment Report and Global Warming Potentials 1-8
Box 1-2: IPCC Reference Approach 1-10
xix
-------
Box 2-1: Methodology for Aggregating Emissions by Economic Sector 2-26
Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data 2-27
Box 2-3: Sources and Effects of Sulfur Dioxide 2-28
Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends 3-7
Box 3-2: Carbon Intensity of U.S. Energy Consumption 3-21
Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage 3-50
Box 4-1: Potential Emission Estimates of FfFCs, PFCs, and SF6 4-73
Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions 6-24
Box 6-2: Comparison of Tier 2 U.S. Inventory Approach and IPCC (2006) Default Approach 6-36
Box 7-1: CO2 Emissions from Forest Fires 7-18
Box 7-2: Tier 3 Inventory for Soil C Stocks Compared to Tier 1 or 2 Approaches 7-32
Box 8-1: Biogenic Emissions and Sinks of Carbon 8-6
XX
-------
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
2007. 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 1996IPCC 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. emissions 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).
2Article 2 of the UNFCCC published by the UNEP/WMO Information Unit on Climate Change. See .
3 Article 4(l)(a) of the UNFCCC (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
-------
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 2006) 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 (CK4), 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.
5 Emission estimates of CFCs, HCFCs, halons and other ozone depleting
substances are included in the annexes of this Inventory for informational
purposes.
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-CFLj 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, CK4, 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 2005, concentrations
of these greenhouse gases have increased globally by 36,148,
and 18 percent, respectively (IPCC 2007).
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 2007).
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Global Warming Potentials
Gases in the atmosphere can contribute to the greenhouse
effect both directly and indirectly. Direct effects occur when
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 CO2, and therefore GWP-weighted
emissions are measured in teragrams (or million metric
tons) of CO2 equivalents (Tg CO2 Eq.).7'8 All gases in this
Executive Summary are presented in units of Tg CO2 Eq.
The UNFCCC reporting guidelines for national
inventories were updated in 2006,9 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 2007 are consistent with estimates developed prior to the
publication of the IPCC Third Assessment Report (TAR)
and the IPCC Fourth Assessment Report (AR4). 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 and AR4 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 in Table ES-1.
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-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^FIO
CeF-14
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.
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).
ES.2. Recent Trends in
U.S. Greenhouse Gas Emissions
and Sinks
6 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 comprises 12/44'hs of carbon dioxide by weight.
8 One teragram is equal to 1012 grams (g) or one million metric tons.
9 See .
In 2007, total U.S. greenhouse gas emissions were
7,150.1 Tg CO2 Eq. Overall, total U.S. emissions have risen
by 17 percent from 1990 to 2007. Emissions rose from 2006
to 2007, increasing by 1.4 percent (99.0 Tg CO2 Eq.). The
following factors were primary contributors to this increase:
(1) cooler winter and warmer summer conditions in 2007
than in 2006 increased the demand for heating fuels and
contributed to the increase in the demand for electricity, (2)
increased consumption of fossil fuels to generate electricity
and (3) a significant decrease (14.2 percent) in hydropower
generation used to meet this demand.
Executive Summary ES-3
-------
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 2007.
Figure ES-4 illustrates the relative contribution of the
direct greenhouse gases to total U.S. emissions in 2007.
The primary greenhouse gas emitted by human activities
in the United States was CO2, representing approximately
85.4 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
declined from 1990 levels, resulted primarily from
enteric fermentation associated with domestic livestock,
decomposition of wastes in landfills, and natural gas
systems. Agricultural soil management and mobile source
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 as a by-product of primary aluminum production
and from semiconductor manufacturing.
Overall, from 1990 to 2007, total emissions of CO2
increased by 1,026.7 Tg CO2 Eq. (20.2 percent), while CH4
and N2O emissions decreased by 31.2 Tg CO2 Eq. (5.1
percent) and 3.1 Tg CO2 Eq. (1.0 percent), respectively.
During the same period, aggregate weighted emissions
of FfFCs, PFCs, and SF6 rose by 59.0 Tg CO2 Eq. (65.2
percent). From 1990 to 2007, FfFCs increased by 88.6 Tg
CO2 Eq. (240.0 percent), PFCs decreased by 13.3 Tg CO2 Eq.
(64.0 percent), and SF6 decreased by 16.3 Tg CO2 Eq. (49.8
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 14.9 percent of total emissions in 2007.
The following sections describe each gas's contribution to
total U.S. greenhouse gas emissions in more detail.
Figure ES-1
U.S. Greenhouse Gas Emissions by Gas
HFCs, PFCs, & SFt
Nitrous Oxide
8,000 -
7,000 -
6,000 -
S 5,000 -
o
m 4,000 -
3,000 -
2,000 -
1,000-
o-
Methane
Carbon Dioxide
to CN TT J2 0 ^
i- CM co -^ in to r-
Figure ES-2
Annual Percent Change in U.S. Greenhouse Gas Emissions
0%
-2% J
2.1%
1.7% H 1.7%
iliiil Mill I
iiiliiiiiiiiiiiii
Figure ES-3
Cumulative Change in U.S. Greenhouse Gas
Emissions Relative to 1990
1,100
1,000
900
800
S 700
o~ 600
m 500
400
300
200
100
0
-100
1,051
966
952
-45
iiiliiiiiiiiiiiii
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 5,076.7 5,407.9
Fossil Fuel Combustion 4,708.9 5,013.9
Electricity Generation 1,809.71 1,938.9
Transportation 1,484.51 1,598.7
Industrial 834.2 862.6
Residential 337.7 354.4
Commercial 214.5 224.4
U.S. Territories 28.3 35.0
Non-Energy Use of Fuels 117.0 137.5
Iron and Steel Production &
Metallurgical Coke Production 109.8 103.1
Cement Production 33.3 36.8
Natural Gas Systems 33.7 33.8
Incineration of Waste 10.9 15.7
Lime Production 11.5 13.3
Ammonia Production and Urea Consumption 16.8 17.8
Cropland Remaining Cropland 7.11 7.0
Limestone and Dolomite Use 5.11 6.7
Aluminum Production 6.8 5.7
Soda Ash Production and Consumption 4.11 4.3
Petrochemical Production 2.2 2.8
Titanium Dioxide Production 1.2 1.5
Carbon Dioxide Consumption 1.4 1.4
Ferroalloy Production 2.2 2.0
Phosphoric Acid Production 1.5 1.5
Wetlands Remaining Wetlands 1.0 1.0
Zinc Production 0.91 1.0
Petroleum Systems 0.41 0.3
Lead Production 0.31 0.3
Silicon Carbide Production and Consumption 0.41 0.3
Land Use, Land-Use Change,
and Forestry (Sink)3 (841.4) (851.0)
Biomass—Wood 215.2 229.1
International Bunker Fuels" 114.3 101.6
Biomass—Ethanol13 4.2M 7.7
CH4 616.6 615.8
Enteric Fermentation 133.2 143.6
Landfills 149.2 144.3
Natural Gas Systems 129.6 132.6
Coal Mining 84.1 67.1
Manure Management 30.4 34.5
Forest Land Remaining Forest Land 4.61 6.1
Petroleum Systems 33.9 32.0
Wastewater Treatment 23.5 24.8
Stationary Combustion 7.41 7.1
Rice Cultivation 7.11 7.6
Abandoned Underground Coal Mines 6.0 8.2
Mobile Combustion 4.7B 4.3
5,955.2
5,561.5
2,283.2
1,800.3
844.6
370.4
226.9
36.2
144.5
95.1
41.2
29.4
17.5
14.1
16.4
7.5
5.1
6.1
4.2
3.0
1.8
1.4
1.9
1.4
1.2
1.1
0.3
0.3
0.2
(717.5)
218.1
99.0
9.2
591.1
134.4
122.3
130.8
60.5
37.9
20.6
30.3
25.2
6.6
7.5
7.4
3.4
6,090.8
5,723.5
2,381.0
1,881.5
828.0
358.0
221.8
53.2
138.1
73.2
45.9
29.5
19.5
14.4
12.8
7.9
6.8
4.1
4.2
2.8
1.8
1.3
1.4
1.4
1.1
0.5
0.3
0.3
0.2
(1,122.7)
208.9
111.5
22.6
561.7
136.0
127.8
106.3
57.1
41.8
14.2
28.3
24.3
6.7
6.8
5.6
2.5
6,014.9
5,635.4
2,327.3
1,880.9
844.5
321.9
206.0
54.8
145.1
76.1
46.6
29.5
19.8
15.1
12.3
7.9
8.0
3.8
4.2
2.6
1.9
1.7
1.5
1.2
0.9
0.5
0.3
0.3
0.2
(1,050.5)
209.9
110.5
30.5
582.0
138.2
130.4
104.8
58.4
41.9
31.3
28.3
24.5
6.3
5.9
5.5
2.4
6,103.4
5,735.8
2,397.2
1,887.4
845.4
340.6
214.4
50.8
133.9
77.4
44.5
28.7
20.8
14.6
13.8
8.0
6.2
4.3
4.1
2.6
1.9
1.9
1.6
1.2
1.0
0.5
0.3
0.3
0.2
(1,062.6)
209.8
108.8
38.0
585.3
139.0
132.9
104.7
57.6
44.0
29.0
28.8
24.4
6.6
6.2
5.7
2.3
Executive Summary ES-5
-------
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.) (continued)
Gas/Source
1990
1995
2000
2005
2006
Total
6,098.7
6,463.3
7,008.2
2007
Composting 0.31 0.71 1.3 1.6 1.6 1.7
Petrochemical Production 0.91 1.11 1.2 1.1 1.0 1.0
Field Burning of Agricultural Residues 0.71 0.71 0.81 0.9 0.8 0.9
Iron and Steel Production &
Metallurgical Coke Production 1.0 1.0l 0.9 • 0.7 0.7 0.7
Ferroalloy Production +1 +1 +1 + + +
Silicon Carbide Production and Consumption +1 +1 +1 + + +
International Bunker Fuels6 0.2 H 0.71 0.71 0.1 0.1 0.1
N20 315.0 334.1 329.2 315.9 312.1 311.9
Agricultural Soil Management 200.3 202.3 204.5 210.6 208.4 207.9
Mobile Combustion 43.7 53.7 52.8 36.7 33.5 30.1
Nitric Acid Production 20.0 22.3 21.9 18.6 18.2 21.7
Manure Management 12.1 12.9 14.0 14.2 14.6 14.7
Stationary Combustion 12.8 13.3 14.5 14.8 14.5 14.7
Adipic Acid Production 15.3 17.3 6.2 5.9 5.9 5.9
Wastewater Treatment 3.71 4.01 4.51 4.8 4.8 4.9
N20 from Product Uses 4.41 4.61 4.91 4.4 4.4 4.4
Forest Land Remaining Forest Land 0.51 0.81 2.4l 1.8 3.5 3.3
Composting 0.4l 0.81 1.41 1.7 1.8 1.8
Settlements Remaining Settlements 1.0 1.2 1.2 1.5 1.5 1.6
Field Burning of Agricultural Residues 0.4l 0.4l 0.51 0.5 0.5 0.5
Incineration of Waste 0.51 0.51 0.4l 0.4 0.4 0.4
Wetlands Remaining Wetlands +1 +1 +1 + + +
International Bunker Fuels6 7.71 0.91 0.91 1.0 1.0 1.0
MFCs 36.9 61.8 100.1 116.1 119.1 125.5
Substitution of Ozone Depleting Substances0 0.31 28.5 71.2 100.0 105.0 108.3
HCFC-22 Production 36.4 33.0 28.6 15.8 13.8 17.0
Semiconductor Manufacture 0.2! 0.31 0.31 0.2 0.3 0.3
PFCs 20.8 15.6 13.5 6.2 6.0 7.5
Aluminum Production 18.5 11.8 8.61 3.0 2.5 3.8
Semiconductor Manufacture 2.2 3.8 4.91 3.2 3.5 3.6
SF6 32.8 28.1 19.2 17.9 17.0 16.5
Electrical Transmission and Distribution 26.8 21.6 15.1 14.0 13.2 12.7
Magnesium Production and Processing 5.41 5.6 3.0 2.9 2.9 3.0
Semiconductor Manufacture 0.51 0.91 1.11 1.0 1.0 0.8
7,108.6 7,051.1 7,150.1
Net Emissions (Sources and Sinks)
5,257.3
5,612.3
6,290.7
5,985.9 6,000.6 6,087.5
+ 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.
c Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure ES-4
Figure ES-5
2007 Greenhouse Gas Emissions by Gas
MFCs, PFCs, & SF6
N,0
2.1%
4.4%
8.2%
CO
85.4%
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 36 percent (IPCC
2007), principally due to the combustion of fossil fuels.
Within the United States, fuel combustion accounted for 94
percent of CO2 emissions in 2007. Globally, approximately
29,195 Tg of CO2 were added to the atmosphere through the
combustion of fossil fuels in 2006, of which the United States
accounted for about 20 percent.10 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, CO2 from fossil fuel combustion has accounted
for approximately 79 percent of GWP-weighted emissions
since 1990, growing slowly from 77 percent of total
GWP-weighted emissions in 1990 to 80 percent in 2007.
Emissions of CO2 from fossil fuel combustion increased at
an average annual rate of 1.3 percent from 1990 to 2007.
10 Global CO2 emissions from fossil fuel combustion were taken from
Energy Information Administration International Energy Annual 2006
(EIA2008b).
2007 Sources of CO? Emissions
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Production
& Metallurgical Coke Production
Cement Production
Natural Gas Systems
Incineration of Waste
Lime Production
Ammonia Production and
Urea Consumption
Cropland Remaining Cropland
Limestone and Dolomite Use
Aluminum Production
Soda Ash Production and Consumption
Petrochemical Production
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Phosphoric Acid Production
Wetlands Remaining Wetlands
Zinc Production
Petroleum Systems | <0.5
Lead Production
5,735.8
Silicon Carbide Production and
Consumption
<0.5
<0.5
75 100
TgCO,Eq.
125 150
The fundamental factors influencing this trend include
(1) a generally growing domestic economy over the last 17
years, and (2) significant overall growth in emissions from
electricity generation and transportation activities. Between
1990 and 2007, CO2 emissions from fossil fuel combustion
increased from 4,708.9 Tg CO2 Eq. to 5,735.8 Tg CO2 Eq.
—a 21.8 percent total increase over the eighteen-year period.
From 2006 to 2007, these emissions increased by 100.4 Tg
CO2Eq. (1.8 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
Executive Summary ES-7
-------
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 five major fuel consuming sectors contributing to
CO2 emissions from fossil fuel combustion are electricity
generation, transportation, industrial, residential, and
commercial. CO2 emissions are produced by the electricity
generation sector as they consume fossil fuel to provide
electricity to one of the other four sectors, or "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 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
2007.n Virtually all of the energy consumed in this end-use
sector came from petroleum products. Nearly 60 percent
of the emissions resulted from gasoline consumption for
personal vehicle use. The remaining emissions came from
other 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 2007. Just over half of these emissions
resulted from direct fossil fuel combustion to produce steam
and/or heat for industrial processes. The remaining emissions
11 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 2007.
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 2007. Both sectors relied heavily
on electricity for meeting energy demands, with 72 and
79 percent, respectively, of their emissions attributable to
electricity consumption for lighting, heating, cooling, and
Figure ES-6
2007 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
2,500 -|
2,000 -
1,500 -
1,000 -
500 -
0 -1
Natural Gas
Petroleum
I Coal
Relative Contribution
by Fuel Type
31 |
1 1
.2 o ••= o
i= '•= « '•=
W TO ^ TO
= I si
2
Note: Electricity generation also includes emissions of less than 0.5 Tg C02 Eq. from geothermal-based
electricity generation.
Figure ES-7
2,500 -
2,000 -
S 1,500 -
o
1,000 -
500 -
0 J
""007 End-Use Sector Emissions of C02
from Fossil Fuel Combustion
From Electricity
Consumption
I From Direct Fossil
Fuel Combustion
U.S. Commercial Residential Industrial Transportation
Territories
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-3: C02 Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories3
Total
Electricity Generation
a Fuel consumption by U.S. territories (i.e., American Samoa
included in this report.
1990
1,487.5 1
1,484.5 1
3.0
1,516.8 1
834.2
682.6
927.1
337.7
589.4
749.2
214.5
534.7
28.3
4,708.9 5
1,809.7 1
, Guam, Puerto Rico
1995
,601.7
,598.7
3.0 1
,575.5
862.6
712.9 1
993.3
354.41
638.8
808.5
224.41
584.1
35.0
,013.9
,938.9
2000
1,803.7
1,800.3
3.4l
1,629.6
844.6
785.0
1,128.2
370.4
757.9
963.8
226.9
736.8
36.2
5,561.5
2,283.2
, U.S. Virgin Islands, Wake Island,
2005
1,886.2
1,881.5
4.7
1,558.5
828.0
730.5
1,207.2
358.0
849.2
1,018.4
221.8
796.6
53.2
5,723.5
2,381.0
and other U.
Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated
national electricity consumption by each end-use sector.
2006
1,885.4
1,880.9
4.5
1,550.7
844.5
706.2
1,145.9
321.9
824.1
998.6
206.0
792.5
54.8
5,635.4
2,327.3
,S. Pacific Islands)
2007
1,892.2
1,887.4
4.8
1,553.4
845.4
708.0
1,198.0
340.6
857.4
1,041.4
214.4
827.1
50.8
5,735.8
2,397.2
is
based on aggregate
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 42 percent of the
CO2 from fossil fuel combustion in 2007. 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 94
percent of all coal consumed for energy in the United States
in 2007. 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 16.9 Tg CO2 Eq. (14.5 percent) from 1990 to
2007. Emissions from non-energy uses of fossil fuels
were 133.9 Tg CO2 Eq. in 2007, which constituted 2.2
percent of total national CO2 emissions, approximately
the same proportion as in 1990.
CO2 emissions from iron and steel production and
metallurgical coke production increased slightly from
2006 to 2007 (1.3 Tg CO2 Eq.), but have decreased by
29.5 percent to 77.4 Tg CO2 Eq. from 1990 to 2007,
due to restructuring of the industry, technological
improvements, and increased scrap utilization.
In 2007, CO2 emissions from cement production
decreased slightly by 2.0 Tg CO2 Eq. (4.4 percent) from
2006 to 2007. This decrease occurs despite the overall
increase over the time series. After falling in 1991 by two
percent from 1990 levels, cement production emissions
grew every year through 2006. Overall, from 1990 to
2007, emissions from cement production increased by
34 percent, an increase of 11.2 Tg CO2 Eq.
CO2 emissions from incineration of waste (20.8 Tg CO2
Eq. in 2007) increased by 9.8 Tg CO2 Eq. (90 percent) from
1990 to 2007, as the volume of plastics and other fossil
carbon-containing materials in the waste stream grew.
Net CO2 sequestration from Land Use, Land-Use
Change, and Forestry increased by 221.1 Tg CO2 Eq. (26
percent) from 1990 to 2007. This increase was primarily
due to an increase in the rate of net carbon accumulation
Executive Summary ES-9
-------
in forest carbon stocks, particularly in aboveground and
below ground 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 148 percent (IPCC 2007).
Anthropogenic sources of CH^ include landfills, natural gas
and petroleum systems, agricultural 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:
• Enteric fermentation is the largest anthropogenic source
of CH4 emissions in the United States. In 2007, enteric
fermentation CFL, emissions were 139.0 Tg CO2 Eq.
(approximately 24 percent of total CH4 emissions),
which represents an increase of 5.8 Tg CO2 Eq., or 4.3
percent, since 1990.
• Landfills are the second largest anthropogenic source
of CH4 emissions in the United States, accounting
for approximately 23 percent of total CFL, emissions
(132.9 Tg CO2 Eq.) in 2007. From 1990 to 2007, net
CH4 emissions from landfills decreased by 16.3 Tg
CO2 Eq. (11 percent), with small increases occurring
in some interim years, including 2007. This downward
trend in overall emissions is the result of increases in
the amount of landfill gas collected and combusted,12
which has more than offset the additional CH4
emissions resulting from an increase in the amount of
municipal solid waste landfilled.
• CFLj emissions from natural gas systems were 104.7
Tg CO2 Eq. in 2007; emissions have declined by 24.9
Tg CO2 Eq. (19 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
2007 Sources of CH* Emissions
Enteric Fermentation
Landfills
Natural Gas Systems
Coal Mining
Manure Management
Forest Land Remaining Forest Land
Petroleum Systems
Wastewater Treatment
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal Mines
Mobile Combustion
Composting
Petrocbemical Production
Field Burning of Agricultural Residues
Iron and Steel Production
& Metallurgical Coke Production
Ferroalloy Production
Silicon Carbide Production and Consumption
<0.5
<0.5
20 40 60 80 100 120 140
Tg CO, Eq.
In 2007, CH4 emissions from coal mining were 57.6 Tg
CO2 Eq., a 0.8 Tg CO2 Eq. (1.3 percent) decrease over
2006 emission levels. The overall decline of 26.4 Tg CO2
Eq. (31 percent) from 1990 results from the mining of less
gassy coal from underground mines and the increased use
of CFLj collected from degasification systems.
CH4 emissions from manure management increased by
44.7 percent for CFL,, from 30.4 Tg CO2 Eq. in 1990 to
44.0 Tg CO2 Eq. in 2007. The majority of this increase
was from swine and dairy cow manure, since the general
trend in manure management is one of increasing use
of liquid systems, which tends to produce greater CFL,
emissions. The increase in liquid systems is the combined
result of a shift to larger facilities, and to facilities in
the West and Southwest, all of which tend to use 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 site.
12 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.
ES-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 2007). The
main anthropogenic activities producing N2O in the United
States are agricultural soil management, fuel combustion
in motor vehicles, nitric acid production, stationary
fuel combustion, manure management, and adipic acid
production (see Figure ES-9).
Some significant trends in U.S. emissions of N2O include
the following:
• Agricultural soils produced approximately 67 percent of
N2O emissions in the United States in 2007. Estimated
emissions from this source in 2007 were 207.9 Tg
CO2 Eq. Annual N2O emissions from agricultural soils
fluctuated between 1990 and 2007, although overall
emissions were 3.8 percent higher in 2007 than in
1990. 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, and to
weather patterns and crop type.
Figure ES-9
2007 Sources of N,0 Emissions
207.9
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Manure Management
Stationary Combustion
Adipic Acid Production ^|
Wastewater Treatment ^|
N20 from Product Uses ^|
Forest Land Remaining Forest Land |
Composting |
Settlements Remaining Settlements |
Field Burning of Agricultural Residues |
-------
Figure ES-10
Figure ES-11
2007 Sources of MFCs, PFCs, and SF6 Emissions
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Electrical Transmission
and Distribution
108.3
Aluminum Production
Magnesium Production
and Processing
10
20 30
Tg CO, Eq.
40
50
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.
• HFC emissions from the production of HCFC-22
decreased by 53 percent (19.4 Tg CO2 Eq.) from
1990 to 2007, 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.
• SF6 emissions from electric power transmission and
distribution systems decreased by 53 percent (14.1
Tg CO2 Eq.) from 1990 to 2007, primarily because of
higher purchase prices for SF6 and efforts by industry
to reduce emissions.
• PFC emissions from aluminum production decreased by
79 percent (14.7 Tg CO2 Eq.) from 1990 to 2007, due
to both industry emission reduction efforts and lower
domestic aluminum production.
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
Reporting and Review (UNFCCC 2003), Figure ES-11 and
Table ES-4 aggregate emissions and sinks by these chapters.
U.S. Greenhouse Gas Emissions and Sinks
by Chapter/IPCC Sector
Industrial Processes
Waste
7,500
7,000
6,500
6,000
5,500
5,000
4,500
4,000
" 3,500
, 3,000
2,500
2,000
1,500
1,000
500
0
(500) -
(1,000)-
(1,500)-I
Land Use, Land-Use Change and Forestry (sinks)
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and
Other Product Use sectors.
Emissions of all gases can be summed from each source
category from Intergovernmental Panel on Climate Change
(IPCC) guidance. Over the eighteen-year period of 1990 to
2007, total emissions in the Energy, Industrial Processes, and
Agriculture sectors climbed by 976.7 Tg CO2 Eq. (19 percent),
28.5Tg CO2 Eq. (9 percent), and28.9Tg CO2 Eq. (8 percent),
respectively. Emissions decreased in the Waste and Solvent
and Other Product Use sectors by 11.5 Tg CO2 Eq. (6 percent)
and less than 0.1 Tg CO2 Eq. (0.4 percent), respectively. Over
the same period, estimates of net C sequestration in the Land
Use, Land-Use Change, and Forestry sector increased by
192.5 Tg CO2 Eq. (23 percent).
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 2007. In 2007, approximately
85 percent of the energy consumed in the United States (on
a Btu basis) was produced through the combustion of fossil
fuels. The remaining 15 percent came from other energy
sources such as hydropower, biomass, nuclear, wind, and
solar energy (see Figure ES-12). Energy-related activities are
also responsible for CFL, and N2O emissions (35 percent and
14 percent of total U.S. emissions of each gas, respectively).
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
1990
1995
2000
2005
2006
2007
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and
Forestry (Emissions)
Waste
6,059.9
356.3
4.9
399.4
33.0
154.6
6,169.2
337.6
4.4
410.8
26.4
160.2
6,084.4
343.9
4.4
410.3
45.1
163.0
6,170.3
353.8
4.4
413.1
42.9
165.6
Total Emissions
6,098.7
6,463.3
7,008.2
7,108.6 7,051.1 7,150.1
Net C02 Flux from Land Use, Land-Use
Change, and Forestry (Sinks)3
(841.4)
(851.0)
(717.5)
(1,122.7) (1,050.5) (1,062.6)
Net Emissions (Sources and Sinks)
5,257.3
5,612.3
6,290.7
5,985.9 6,000.6 6,087.5
aThe 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.
Figure ES-12
2007 U.S. Energy Consumption by Energy Source
Renewable
Nuclear
Natural Gas
Coal
Petroleum
7%
22%
22%
39%
Overall, emission sources in the Energy chapter account
for a combined 86.3 percent of total U.S. greenhouse gas
emissions in 2007.
Industrial Processes
The Industrial Processes chapter contains byproduct
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, CLL,, and N2O. These processes include iron
and steel production and metallurgical coke production, cement
production, ammonia production and urea consumption,
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, silicon carbide production and consumption,
aluminum production, petrochemical production, nitric acid
production, adipic acid production, lead production, and zinc
production. Additionally, emissions from industrial processes
release HFCs, PFCs, and SF6. Overall, emission sources in the
Industrial Processes chapter account for 4.9 percent of U.S.
greenhouse gas emissions in 2007.
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 from product uses, 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 2007.
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
Executive Summary ES-13
-------
primary greenhouse gases emitted by agricultural activities.
CH4 emissions from enteric fermentation and manure
management represented about 24 percent and 8 percent
of total CH4 emissions from anthropogenic activities,
respectively, in 2007. Agricultural soil management
activities such as fertilizer application and other cropping
practices were the largest source of U.S. N2O emissions in
2007, accounting for 67 percent. In 2007, emission sources
accounted for in the Agriculture chapter were responsible
for 6 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 CK4 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 86
percent of total 2007 net CO2 flux, urban trees accounted
for 9 percent, mineral and organic soil carbon stock changes
accounted for 4 percent, and landfilled yard trimmings
and food scraps accounted for 1 percent of the total net
flux in 2007. 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 and
organic soils sequester approximately 70 percent more
C than is emitted through these soils, liming, and urea
fertilization, combined. 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 2007 resulted in a net C sequestration of 1,062.6
Tg CO2 Eq. (Table ES-5). This represents an offset of
approximately 17.4 percent of total U.S. CO2 emissions,
or 14.9 percent of total greenhouse gas emissions in 2007.
Between 1990 and 2007, total land use, land-use change,
and forestry net C flux resulted in a 26.3 percent increase
in CO2 sequestration, 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
Table ES-5: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2005
2006
2007
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements
Other (Landfilled Yard Trimmings and
Food Scraps)
(975.7)
(18.3)
5.9
(4.6)
(26.7)
(93.3)
(900.3)
(19.1)
5.9
(4.6)
(26.7)
(95.5)
(23.5)
(13.9)
(11.3)
(10.2) (10.4)
(9.8)
Total
(841.4)
(851.0)
(717.5)
(1,122.7) (1,050.5) (1,062.6)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
ES-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Source Category
1990
1995
2000
2005
2006
2007
C02 8.1
Crop|and Remaining Cropland: Liming of
Agricultural Soils 4.7
Cropland Remaining Cropland: Urea Fertilization 2.4
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands 1.0
CH4 4.6
Forest Land Remaining Forest Land: Forest Fires 4.6
N20 1.5
Forest Land Remaining Forest Land: Forest Fires 0.5
Forest Land Remaining Forest Land: Forest Soils 0.0
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands +
Settlements Remaining Settlements:
Settlement Soils 1.0
8.1
4.4
2.7
1.0
6.1
6.1
2.0
0.6
1.2
8.8
4.3
3.2
1.2
20.6
20.6
3.6
2.1
0.3
1.2
8.9
4.3
3.5
1.1
14.2
14.2
3.3
1.4
0.3
1.5
8.8
4.2
3.7
0.9
31.3
31.3
5.0
3.2
0.3
1.5
9.0
4.1
4.0
1.0
29.0
29.0
4.9
2.9
0.3
1.6
Total
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
33.0
26.4
45.1
42.9
scraps slowed over this period, while the rate of annual C
accumulation increased in urban trees.
Emissions from Land Use, Land-Use Change, and
Forestry are shown in Table ES-6. The application of crushed
limestone and dolomite to managed land (i.e., soil liming) and
urea fertilization resulted in CO2 emissions of 8.0 Tg CO2
Eq. in 2007, an increase of 13 percent relative to 1990. The
application of synthetic fertilizers to forest and settlement
soils in 2007 resulted in direct N2O emissions of 1.6 Tg
CO2 Eq. Direct N2O emissions from fertilizer application
increased by approximately 61 percent between 1990 and
2007. Non-CO2 emissions from forest fires in 2007 resulted
in CILj emissions of 29.0 Tg CO2 Eq., and in N2O emissions
of 2.9 Tg CO2 Eq. CO2 and N2O emissions from peatlands
totaled 1.0 Tg CO2 Eq. and less than 0.01 Tg CO2 Eq. in
2007, respectively.
Waste
The Waste chapter contains emissions from waste
management activities (except incineration of waste,
which is addressed in the Energy chapter). Landfills were
the largest source of anthropogenic CH4 emissions in the
Waste chapter, accounting for 23 percent of total U.S. CH4
emissions.13 Additionally, wastewater treatment accounts
for 4 percent of U.S. CH4 emissions. N2O emissions from
the discharge of wastewater treatment effluents into aquatic
environments were estimated, as were N2O emissions from
the treatment process itself. Emissions of CFL, and N2O
from composting grew from 1990 to 2007, and resulted
in emissions of 1.7 Tg CO2 Eq. and 1.8 Tg CO2 Eq.,
respectively. Overall, in 2007, emission sources accounted
for in the Waste chapter generated 2.3 percent of total U. S.
greenhouse gas emissions.
ES.4. Other Information
Emissions by Economic Sector
Throughout the Inventory of U.S. Greenhouse Gas
Emissions and Sinks 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
13 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.
Executive Summary ES-15
-------
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
1,859.1
1, 543.6 1
1,496.0
428.5
392.9
344.51
34.1
6,098.7
(841.4)
5,257.3
1995
1,989.0
1,685.2
1,524.5
453.7
401.0
368.8
41.1
6,463.3
(851.0)
5,612.3
2000
2,329.3
1,919.7
1,467.5
470.2
388.2
386.0
47.3
7,008.2
(717.5)
6,290.7
2005
2,429.4
1,998.9
1,364.9
482.6
401.8
370.5
60.5
7,108.6
(1,122.7)
5,985.9
2006
2,375.5
1,994.4
1,388.4
502.9
392.6
334.9
62.3
7,051.1
(1,050.5)
6,000.6
2007
2,445.1
1,995.2
1,386.3
502.8
407.6
355.3
57.7
7,150.1
(1,062.6)
6,087.5
Note: Totals may not sum due to independent rounding. Emissions include C02, CH4, N20, MFCs, PFCs, and SF6. See Table 2-12 for more detailed data.
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, 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 2007.
Using this categorization, emissions from electricity
generation accounted for the largest portion (34 percent)
of U.S. greenhouse gas emissions in 2007. Transportation
activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted
for 20 percent of U.S. greenhouse gas emissions in 2007.
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 18 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 CO2 emissions from fossil fuel combustion. Activities
related to agriculture accounted for roughly 7 percent of
U.S. emissions; unlike other economic sectors, agricultural
sector emissions were dominated by N2O emissions from
agricultural soil management and CH^ emissions from enteric
fermentation, rather than CO2 from fossil fuel combustion.
Figure ES-13
Emissions Allocated to Economic Sectors
2,500 -
2,000 -
1,500-
1,000-
500-
Electricity Generation
•^
Transportation
Industry
Agriculture
^Commercial
Residential
00000000
Note: Does not include U.S. Territories.
The commercial sector accounted for about 6 percent of
emissions, while U.S. territories accounted for approximately
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 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
ES-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions
Distributed (Tg C02 Eq.)
Implied Sectors
Industry
Transportation
Commercial
Residential
Agriculture
U.S. Territories
Total Emissions
Land Use, Land-Use Change,
and Forestry (Sinks)
Net Emissions (Sources and Sinks)
See Table 2-14 for more detailed data.
Figure ES-14
1990 1995 2000 2005 2006 2007
2,166.5 2,219.8 2,235.5 2,081.2 2,082.3 2,081.2
1,546.7 1,688.3 1, 923.21 2,003.6 1,999.0 2,000.1
942.2 1,000.21 1,140.0 1,214.6 1,201.5 1,251.2
950.0 1,024.21 1,159.21 1,237.0 1,176.1 1,229.8
459.2 489.7 503.2 511.7 530.0 530.1
34.1 41.1 47.3 60.5 62.3 57.7
6,098.7 6,463.3 7,008.2 7,108.6 7,051.1 7,150.1
(841.4) (851.0) (717.5) (1,122.7) (1,050.5) (1,062.6)
5,257.3 5,612.3 6,290.7 5,985.9 6,000.6 6,087.5
CO2 and N2O from incineration of waste, CH^ and N2O from
stationary sources, and SF6 from electrical transmission and
to Economic Sectors
2,500 -
-^~- ' ^^
2,000 -
S 1,500- *^"
o1 ^--"-'
o ^---^
™ *^^-
1,000- - * -—__.
° 0
distribution systems.
Industrial
~-
^
Transportation
^---Residential
-"
.Commercial
Agriculture
IIH
Note: Does not include U.S. Territories.
When emissions from electricity are distributed among
these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (30 percent) in 2007. 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, primarily from the
combustion of fossil fuels. Figure ES-14 shows the trend in
these emissions by sector from 1990 to 2007.
generation were allocated to the residential, commercial,
industry, transportation, and agriculture economic sectors
according to retail sales of electricity.14 These source
categories include CO2 from fossil fuel combustion and the
use of limestone and dolomite for flue gas desulfurization,
Indirect Greenhouse Gases (CO, NOX,
NMVOCs, and S02)
The reporting requirements of the UNFCCC15 request
that information be provided on indirect greenhouse gases,
which include CO, NOX, NMVOCs, and SO2. These gases do
not have a direct global warming effect, but indirectly affect
terrestrial radiation absorption by influencing the formation
14Emissions 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.
15 See .
Executive Summary ES-17
-------
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 2007; (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 0.9 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
1995
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Populationd
Greenhouse Gas Emissions6
a Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2008)
c Energy content-weighted values (EIA 2008a)
11 U.S. Census Bureau (2008)
e GWP-weighted values
2000
2005
2006
2007
Growth
Rate3
138
155
127| 134
117 119
117 119
1131 118
115 V\l_
159
135
117
118
119
115
162
137
119
120
120
117
2.9%
1.9%
1.1%
1.1%
1.1%
0.9%
Figure ES-15
U.S. Greenhouse Gas Emissions Per Capita and
Per Dollar of Gross Domestic Product
Real GDP
Population
Emissions
per capita
Emissions
per $GDP
iiiiliiiiiiiiiiiii
Source: BEA (2008), U.S. Census Bureau (2008), and emission estimates in this report.
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table ES-10: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
1990
1995
2000
2005
2006
2007
NO,
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Oil and Gas Activities
Incineration of Waste
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Incineration of Waste
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
Incineration of Waste
Waste
Agricultural Burning
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Incineration of Waste
Waste
Solvent Use
Agricultural Burning
NA
NA
15,612
8,757
5,857
534
321
98
39
5
2
71,672
62,519
4,778
1,744
1,439
860
324
7
2
14,562
6,292
3,881
2,035
1,450
545
243
115
NA
13,348
11,641
852
600
233
22
1
0
NA
14,701
8,271
5,445
527
316
98
38
5
2
67,453
58,322
4,792
1,743
1,438
825
323
7
2
14,129
5,954
3,867
1,950
1,470
535
239
113
NA
12,259
10,650
845
520
221
22
1
0
NA
14,250
7,831
5,445
520
314
97
37
5
2
63,875
54,678
4,792
1,743
1,438
892
323
7
2
13,747
5,672
3,855
1,878
1,470
526
234
111
NA
11,725
10,211
839
442
210
22
1
0
NA
NA (Not Available)
Note: Totals may not sum due to independent rounding.
Source: EPA (2008), disaggregated based on EPA (2003), except for estimates from field burning of agricultural residues.
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
2008),16 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.
16 NOX and CO emission estimates from field burning of agricultural residues
were estimated separately, and therefore not taken from EPA (2008).
Executive Summary ES-19
-------
Figure ES-16
2007 Key Categories
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
Direct N20 Emissions from Agricultural Soil Management
CH, Emissions from Enteric Fermentation
C02 Emissions from Non-Energy Use of Fuels
CH, Emissions from Landfills
Emissions from Substitutes for Ozone Depleting Substances
Fugitive CH, Emissions from Natural Gas Systems
C02 Emissions from Iron and Steel Production & Metallurgical Coke Production
Fugitive CH, Emissions from Coal Mining
C02 Emissions from Mobile Combustion: Marine
C02 Emissions from Cement Production
CH, Emissions from Manure Management
Indirect N20 Emissions from Applied Nitrogen
Fugitive CH, Emissions from Petroleum Systems
C02 Emissions from Natural Gas Systems
Non-C02 Emissions from Stationary Combustion
Key Categories as a
Portion of all Emissions
I I I I I I I I I I I I
0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200
Tg C02 Eq.
Notes: For a complete discussion of the key source analysis, see Annex 1. Darker bars indicate a Tier 1 level assessment key category. Lighter bars indicate a Tier 2 level assessment key category.
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."17 By
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 2007 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 the Inventory. For more
information regarding key categories, see Section 1.5 and
Annex 1 of the Inventory.
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
17 See Chapter 7 "Methodological Choice and Recalculation" in IPCC
(2000).
ES-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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-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-21
-------
1, Introduction
This report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions
and sinks for the years 1990 through 2007. A summary of these estimates is provided in Table 2-1 and Table 2-2
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.1 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/IEA1997) 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. In addition, this Inventory is in accordance with the IPCC Good Practice Guidance and Uncertainty
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 1-1
-------
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 2006IPCC 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 ozone 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. They can affect the
absorptive characteristics of the atmosphere. Comparatively,
however, the level of scientific understanding of aerosols is
still very low (IPCC 2001).
5 For more on the science of climate change, see NRC (2001).
6 Emission 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: 1990-2007
-------
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 concentration
Rate of concentration change
Atmospheric lifetime0
C02
278 ppm
379 ppm
1 .4 ppm/yr
50-200d
CH4
0.71 5 ppm
1.774 ppm
0.005 ppm/yra
12e
N20
0.270 ppm
0.31 9 ppm
0.26% yr
114e
SF6
Oppt
5.6 ppt
Linear"
3,200
CF4
40 ppt
74 ppt
Linear"
>50,000
a The growth rate for atmospheric CH4 has been decreasing from 14 ppb/yr in 1984 to almost 0 ppb/yr in 2001, 2004, and 2005 (IPCC 2007).
b IPCC (2007) identifies the rate of concentration change for SF6 and CF4 as linear.
c Source: IPCC (1996).
11 No single lifetime can be defined for C02 because of the different rates of uptake by different removal processes.
e This lifetime has been defined as an "adjustment time" that takes into account the indirect effect of the gas on its own residence time.
Source: Pre-industrial atmospheric concentrations, current atmospheric concentrations, and rate of concentration changes for all gases are from IPCC (2007).
Note: ppt (parts per thousand), ppm (parts per million), ppb (parts per billion).
Carbon dioxide, CH^, 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. Carbon dioxide concentrations
in the atmosphere increased from approximately 280 parts
per million by volume (ppmv) in pre-industrial times to
379 ppmv in 2005, a 35 percent increase (IPCC 2007 and
Hofmann 2004).78 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, other biomass burning, and some non-
energy production processes (e.g., cement production) also
emit notable quantities of CO2.
7The pre-industrial period is considered as the time preceding the year
1750 (IPCC 2001).
8 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 1-3
-------
In its second assessment, the IPCC also stated that" [t]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. Methane 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. Methane 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 CH^ have increased by about 143 percent
since 1750, from a pre-industrial value of about 722 ppb to
1,774 ppb in 2005, although the rate of increase has been
declining. The IPCC has estimated that slightly more than half
of the current CH^ flux to the atmosphere is anthropogenic,
from human activities such as agriculture, fossil fuel use,
and waste disposal (IPCC 2007).
Methane 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 incineration; and biomass burning. The atmospheric
concentration of N2O has increased by 18 percent since 1750,
from a pre-industrial value of about 270 ppb to 319 ppb in
2005, a concentration that has not been exceeded during
the last thousand years. Nitrous oxide is primarily removed
from the atmosphere by the photolytic action of sunlight in
the stratosphere (IPCC 2007).
Ozone. 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 [HFCs])
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
stratospheric ozone depletion, which itself is an important
greenhouse gas in addition to shielding the earth from
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 11 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 U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 511 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 also 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-CFLj 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
from an increase in airborne aerosols. The second effect
"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 of
ten additional years in the phase-out of ozone depleting substances.
12 NOX emissions injected higher in the stratosphere, primarily from fuel
combustion emissions from high altitude supersonic aircraft, can lead to
stratospheric ozone depletion.
Introduction 1-5
-------
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
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
SO2 and other sulfur compounds into the stratosphere, which can result in
a longer negative forcing effect (i.e., a few years) (IPCC 1996).
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:
Tg
Tg CO2 Eq. = (Gg of gas) x (GWP) x
1,000 Gg
where,
Tg CO2 Eq.
Gg
GWP
Tg
Teragrams of CO2 Equivalents
Gigagrams (equivalent to a
thousand metric tons)
Global Warming Potential
Teragrams
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
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
15 Carbon comprises 12/44'hs 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).
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 1-2: Global Warming Potentials and Atmospheric
Lifetimes (Years) Used in this Report
Gas
C02
CH4b
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4Fio
CeF-|4
SF6
Atmospheric
Lifetime
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
a 100-year time horizon
b 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.
Source: (IPCC 1996)
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.
1.2. 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 (OAP)
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
OAP 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
calculations for individual sources are the responsibility of
individual source leads, who are most familiar with each
Introduction 1-7
-------
Box 1-1: The IPCC Fourth Assessment Report and Global Warming Potentials
In 2007, the IPCC published its Fourth Assessment Report (AR4), 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 SAR and the IPCC's Third
Assessment Report (TAR) (IPCC 2001). Thus the GWPs used in this report have been updated twice by the IPCC; although the SAR GWPs
are used throughout this report, it is interesting to review the changes to the GWPs and the impact such improved understanding has on the
total GWP-weighted emissions of the United States. Since the SAR and TAR, the IPCC has applied an improved calculation of C02 radiative
forcing and an improved C02 response function. The GWPs are drawn from IPCC/TEAP (2005) and the TAR, with updates for those cases
where new laboratory or radiative transfer results have been published. Additionally, the atmospheric lifetimes of some gases have been
recalculated. In addition, the values for radiative forcing and lifetimes have been recalculated 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
CH4a
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4Fio
C6F14
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
AR4
1
25
298
14,800
675
3,500
1,430
4,470
124
3,220
9,810
1,640
7,390
12,200
8,860
9,300
22,800
Change
TAR
NC
2
(14)
300
(100)
600
NC
500
(20)
600
3,100
200
(800)
2,700
1,600
1,600
(1,700)
from SAR
AR4
0
4
(12)
3,100
25
700
130
670
(16)
320
3,510
340
890
3,000
1,860
1,900
(1,100)
NC (No Change)
aThe 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.
Note: Parentheses indicate negative values.
Source: IPCC (2001, 2007)
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 2006 are consistent and comparable with
estimates developed prior to the publication of the TAR and AR4. For informational purposes, emission estimates that use the updated GWPs
are presented in detail in Annex 6.1 of this report. All estimates provided throughout this report are also presented in unweighted units.
17 See .
source category and the unique characteristics of its coordinating with researchers and contractors familiar
emissions profile. The individual source leads determine with the sources. A multi-stage process for collecting
the most appropriate methodology and collect the best information from the individual source leads and
activity data to use in the emission calculations, based producing the Inventory is undertaken annually to compile
upon their expertise in the source category, as well as all information and data.
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 CRF, conducting
quality assurance and quality control (QA/QC) checks, and
uncertainty analyses.
Summary Spreadsheet Compilation and
Data Storage
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.
National 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 Format 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 1-9
-------
QA/QC and Uncertainty
QA/QC and uncertainty analyses are supervised by the
QA/QC and Uncertainty coordinators, who have 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). These coordinators work
closely with the source leads to ensure that 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 and IPCC.
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
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.
Box 1-2: IPCC Reference Approach
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: 1990-2007
-------
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
and uncertainties 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. Following the Tier 1 approach, a Tier 2 approach,
as defined in the IPCC's Good Practice Guidance (IPCC
2000), was then implemented to identify any additional key
categories not already identified in the Tier 1 assessment. This
analysis, which includes each source cateogory's uncertainty
assessments in its calculations, was also performed twice to
include or exclude LULUCF sources.
In addition to conducting Tier 1 and 2 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,
which would qualify it as a key category according to the
Tier 2 approach.
Table 1-4 presents the key categories for the United
States (including and excluding LULUCF categories) using
emissions and uncertainty data in this report, and ranked
according to their sector and global warming potential-
weighted emissions in 2007. The table also indicates the
criteria used in identifying these categories (i.e., level, trend,
Tier 1, Tier 2, 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 and 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;
18 See Chapter 7 "Methodological Choice and Recalculation" in IPCC
(2000).
Introduction 1-11
-------
Table 1-4: Key Categories for the United States (1990-2007)
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
C02 Emissions from Mobile Combustion: Marine
C02 Emissions from Natural Gas Systems
C02 Emissions from Incineration of Waste
Fugitive CH4 Emissions from Natural Gas Systems
Fugitive CH4 Emissions from Coal Mining
Fugitive CH4 Emissions from Petroleum Systems
Non-C02 Emissions from Stationary Combustion
N20 Emissions from Mobile Combustion:
Road & Other
Non-C02 Emissions from Stationary Combustion
International Bunker Fuels"
Industrial Processes
C02 Emissions from Iron and Steel Production &
Metallurgical Coke Production
C02 Emissions from Cement Production
C02 Emissions from Ammonia Production and
Urea Consumption
N20 Emissions from Adipic Acid Production
Emissions from Substitutes for Ozone
Depleting Substances
HFC-23 Emissions from HCFC-22 Production
SF6 Emissions from Electrical Transmission
and Distribution
PFC Emissions from Aluminum Production
Agriculture
CH4 Emissions from Enteric Fermentation
CH4 Emissions from Manure Management
CH4 Emissions from Rice Cultivation
Direct N20 Emissions from Agricultural
Soil Management
Indirect N20 Emissions from Applied Nitrogen
Waste
CH4 Emissions from Landfills
CH4 Emissions from Wastewater Treatment
Gas
C02
C02
C02
C02
C02
C02
C02
C02
C02
CH4
CH4
CH4
CH4
N20
N20
Several
r*n
C02
C02
rn
L*U2
N20
Several
MFCs
SF6
PFCs
CH4
CH4
CH4
N20
N20
CH4
CH4
iu.
ŁŁ
3 =
0 =
09
_1
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Tie
o
±±o
=?=
•03
09
1^
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
r1
^
^^
S =
09—1
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
f
^^
|3
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
0
;=o
^ =
0 =
O9
_1
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
Tie
o
±±o
^=
•03
09
1^
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
r2
^
^^
S =
09—1
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
f
^
|3
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
/
ra
a
/
= =»•
r~im
§ So
S~"
"Ł
2,086.5
1,649.1
1,181.1
580.4
187.5
133.9
50.8
28.7
20.8
104.7
57.6
28.8
6.6
27.9
14.7
109.9
~7~7 A
77.4
44.5
-10 Q
1 O.O
5.9
108.3
17.0
12.7
3.8
139.0
44.0
6.2
172.0
35.9
132.9
24.4
1-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 1-4: Key Categories for the United States (1990-2007) (continued)
IPCC Source Categories
Land Use, Land Use Change, and Forestry
C02 from Changes in Forest Carbon Stocks
C02 Emissions from Urban Trees
C02 Emissions from Cropland Remaining Cropland
C02 Emissions from Landfilled Yard Trimmings
and Food Scraps
C02 Emissions from Grassland Remaining Grassland
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
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
CH4
N20
•5
i=
«3
O9
Tie
O
53
•03
09
r1
.=
5",
/
/
/
/
s
Is
S3
/
/
/
/
/
/
0
i=
o
Tie
O
53
•03
09
r2
.=
5",
/
/
/
/
/
/
s
Is
S3
/
/
/
/
/
/
/
ra
a
w"5
Iji
mt
-910.1
-97.6
-11.6
-9.8
-4.7
29.0
2.9
6,972.3
7,107.2
98%
5,991.9
6,087.5
98%
3 Qualitative criteria.
b Emissions from this source not included in totals.
• 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
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 each greenhouse gas emissions source
or sink included in 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.
Introduction 1-13
-------
The quality 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.
The QA/QC plan guides 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 7996IPCC 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.
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
Table 1-5: Estimated Overall Inventory Quantitative Uncertainty (Tg C02 Eq. and Percent)
2007 Emission
Estimate
Gas (Tg C02 Eq.)
C02
CH4
N20
PFCs, HFCs&SF6d
Total
Net Emissions
(Sources and Sinks)
6,103.4
585.3
311.9
149.5
7,150.1
6,087.5
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound0
5,974.9
527.0
278.7
141.6
7,047.8
5,917.7
Upper Bound0
6,390.0
689.0
440.6
160.3
7,525.1
6,503.9
Lower Bound0
-2%
-10%
-11%
-5%
-1%
-3%
Upper Bound0
+5%
+ 18%
+41%
+7%
+5%
+7%
Standard
Mean" Deviation
(Tg C02 Eq.)
6,181.5
599.3
352.4
148.1
7,281.3
6,205.6
106.8
41.3
42.8
4.7
121.9
150.1
aThe emission estimates correspond to 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.
cThe low and high estimates for total emissions were separately calculated through simulations and, hence, the low and high emission estimates for the
sub-source categories do not sum to total emissions.
11 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 2007.
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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. An estimate of
the overall quantitative uncertainty is shown in Table 1-5.
The 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.
1.8. Completeness
This report, along with its accompanying CRE 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 2007. 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 foil owing 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.
Introduction 1-15
-------
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.
Byproduct 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 uses.
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)
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 necessitate 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.
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.
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 and C02 Emissions from Petroleum Systems
3.6. Methodology for Estimating C02 and N20 Emissions from Incineration of Waste
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 Analyses by Source
Introduction 1-17
-------
2. Trends in Greenhouse Gas
Emissions
2.1. Recent Trends in U.S. Greenhouse Gas Emissions
In 2007, total U.S. greenhouse gas emissions were 7,150.1 teragrams of carbon dioxide equivalents (Tg CO2 Eq.).1
Overall, total U.S. emissions have risen by 17 percent from 1990 to 2007. Emissions increased from 2006 to 2007
by 1.4 percent (99.0 Tg CO2 Eq.). The following factors were primary contributors to this increase: (1) cooler
winter and warmer summer conditions in 2007 than in 2006 increased the demand for heating fuels and contributed to the
increase in the demand for electricity; (2) increased consumption of fossil fuels to generate electricity; and (3) a significant
decrease (14.2 percent) in hydropower generation used to meet this demand. 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 79 percent of global warming potential (GWP) weighted emissions since 1990, growing slowly from 77
percent of total GWP-weighted emissions in 1990 to 80 percent in 2007. Emissions from this source category grew by 21.8
percent (1,026.9 Tg CO2 Eq.) from 1990 to 2007 and were
Figure 2-1
U.S. Greenhouse Gas Emissions by Gas
MFCs, PFCs, & SFt
Nitrous Oxide
8,000 -
7,000 -
6,000 -
S 5,000 -
o
m 4,000 -
3,000 -
2,000 -
1,000-
o-
Methane
I Carbon Dioxide
in °> T- °
<° 3! 5 E = Ł ^
S S. "- S- E- S- C-
responsible for most of the increase in national emissions
during this period. From 2006 to 2007, these emissions
increased by 1.8 percent (100.4 Tg CO2 Eq.). 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
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, Executive Summary.)
2 See the following section for an analysis of emission trends by general U.S. economic sector.
Trends in Greenhouse Gas Emissions 2-1
-------
Figure 2-2
Annual Percent Change in
U.S. Greenhouse Gas Emissions
4%-,
-1%
-2%
"li'iil lili •
-1.6%
i— CM co ^ m co r-
Figure 2-3
Cumulative Change in Annual U.S. Greenhouse Gas
Emissions Relative to 1990
1,100
1,000
900
800
700
~ 600
500
400
300
200
100
0
-100
1051
966
952
-45
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
instead of coal, for example, can reduce the CO2 emissions
because of the lower C content of natural gas.
Emissions from fuel combustion increased in 2003 at
about the average annual growth rate since 1990 (1.4 percent).
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 continued to
increase at about the average annual growth rate since 1990.
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 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
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
From 2005 to 2006, emissions from fuel combustion
decreased for the first time since 2000 to 2001. This
decrease occurred primarily in the electricity generation,
transportation, residential, and commercial sectors due
to a number of factors. The decrease in emissions from
electricity generation is a result of a smaller share of
electricity generated by coal and a greater share generated by
natural gas. Coal and natural gas consumption for electricity
generation increased by 1.3 percent and 5.9 percent in 2006,
respectively, and nuclear power increased by less than 1
percent. The transportation decrease is primarily a result
of the restraint on fuel consumption caused by rising fuel
prices, which directly resulted in a decrease of petroleum
consumption within this sector of less than one percent in
2006. The decrease in emissions from the residential sector
is primarily a result of decreased electricity consumption
due to increases in the price of electricity, and warmer
winter weather conditions. The increase in emissions in the
industrial sector is a result of a increased emissions from
fossil fuel combustion for this sector. A moderate increase
in the industrial sector is a result of growth in industrial
output and growth in the U.S. economy. Renewable fuels
used to generate electricity increased in 2006, with the
greatest growth occurring in wind.
After experiencing a decrease from 2005 to 2006,
emissions from fuel combustion grew from 2006 to 2007
at a rate slightly higher than the average growth rate since
1990. There were a number of factors contributing to this
increase. Unfavorable weather conditions in both the winter
and summer resulted in an increase in consumption of heating
fuels, as well as an increase in the demand for electricity.
This demand for electricity was met with an increase in coal
consumption of 1.8 percent, and with an increase in natural
gas consumption of 10.3 percent. This increase in fossil
fuel consumption, combined with a 14.2 percent decrease
in hydropower generation from 2006 to 2007, resulted in an
increase in emissions in 2007. The increase in emissions from
the residential and commercial sectors is a result of increased
electricity consumption due to warmer summer conditions
and cooler winter conditions compared to 2006. In addition
to these unfavorable weather conditions, electricity prices
remained relatively stable compared to 2006, and natural
gas prices decreased slightly. Emissions from the industrial
sector increased slightly compared to 2006 as a result of a 1.7
percent increase in industrial production and the increase in
fossil fuels used for electricity generation. Despite an overall
decrease in electricity generation from renewable energy in
2007 driven by decreases in hydropower generation, wind
and solar generation increased significantly.
Overall, from 1990 to 2007, total emissions of CO2
increased by 1,026.7 Tg CO2 Eq. (20.2 percent), while
CtLj and N2O emissions decreased by 31.2 Tg CO2 Eq.
(5.1 percent) and 3.1 Tg CO2 Eq. (1 percent) respectively.
During the same period, aggregate weighted emissions of
HFCs, PFCs, and SF6 rose by 59 Tg CO2 Eq. (65.2 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 14.9 percent of
total emissions in 2007.
Table 2-1 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 2-2.
Trends in Greenhouse Gas Emissions 2-3
-------
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 5,076.7 5,407.9 5,955.2 6,090.8 6,014.9 6,103.4
Fossil Fuel Combustion 4,708.9 5,013.9 5,561.51 5,723.5 5,635.4 5,735.8
Electricity Generation 1,809.7 1,938.9 2,283.21 2,381.0 2,327.3 2,397.2
Transportation 1,484.51 1,598.7 1,800.3 1,881.5 1,880.9 1,887.4
Industrial 834.2 862.6 844.6 828.0 844.5 845.4
Residential 337.7 354.4 370.4 358.0 321.9 340.6
Commercial 214.5 224.4 226.9 221.8 206.0 214.4
U.S. Territories 28.3 35.0 36.2 53.2 54.8 50.8
Non-Energy Use of Fuels 117.0 137.5 144.5 138.1 145.1 133.9
Iron and Steel Production & Metallurgical
Coke Production 109.8 103.1 95.1 73.2 76.1 77.4
Cement Production 33.3 36.8 41.2 45.9 46.6 44.5
Natural Gas Systems 33.7 33.8 29.4 29.5 29.5 28.7
Incineration of Waste 10.9 15.7 17.5 19.5 19.8 20.8
Lime Production 11.5 13.3 14.1 14.4 15.1 14.6
Ammonia Production and Urea Consumption 16.8 17.8 16.4 12.8 12.3 13.8
Cropland Remaining Cropland 7.11 7.01 7.51 7.9 7.9 8.0
Limestone and Dolomite Use 5.11 6.71 5.11 6.8 8.0 6.2
Aluminum Production 6.81 5.71 6.11 4.1 3.8 4.3
Soda Ash Production and Consumption 4.11 4.31 4.21 4.2 4.2 4.1
Petrochemical Production 2.2 2.8 3.01 2.8 2.6 2.6
Titanium Dioxide Production 1.2 1.51 1.81 1.8 1.9 1.9
Carbon Dioxide Consumption 1.4 1.4 1.4 1.3 1.7 1.9
Ferroalloy Production 2.2 2.01 1.91 1.4 1.5 1.6
Phosphoric Acid Production 1.51 1.51 1.4 1.4 1.2 1.2
Wetlands Remaining Wetlands 1.01 1.01 1.2 1.1 0.9 1.0
Zinc Production O.gl 1.0 1.11 0.5 0.5 0.5
Petroleum Systems 0.4l 0.31 0.31 0.3 0.3 0.3
Lead Production 0.31 0.31 0.31 0.3 0.3 0.3
Silicon Carbide Production and Consumption 0.4! 0.31 0.2! 0.2 0.2 0.2
Land Use, Land-Use Change, and
Forestry (Sink)3 (841.4) (851.0) (717.5) (1,122.7) (1,050.5) (1,062.6)
Biomass—Woodb 215.2 229.1 218.1 208.9 209.9 209.8
International Bunker Fuels" 114.3 101.6 99.0 111.5 110.5 108.8
Biomass—Ethanol" 4.2U 7.71 9.2! 22.6 30.5 38.0
CH4 616.6 615.8 591.1 561.7 582.0 585.3
Enteric Fermentation 133.2 143.6 134.4 136.0 138.2 139.0
Landfills 149.2 144.3 122.3 127.8 130.4 132.9
Natural Gas Systems 129.6 132.6 130.8 106.3 104.8 104.7
Coal Mining 84.1 67.1 60.5 57.1 58.4 57.6
Manure Management 30.4 34.5 37.9 41.8 41.9 44.0
Forest Land Remaining Forest Land 4.el 6.11 20.6 14.2 31.3 29.0
Petroleum Systems 33.9 32.0 30.3 28.3 28.3 28.8
Wastewater Treatment 23.5 24.8 25.2 24.3 24.5 24.4
Stationary Combustion 7.4l 7.11 6.61 6.7 6.3 6.6
Rice Cultivation 7.11 7.61 7.51 6.8 5.9 6.2
Abandoned Underground Coal Mines 6.0 8.2 7.41 5.6 5.5 5.7
Mobile Combustion 4.71 4.31 3.41 2.5 2.4 2.3
Composting O.sl 0.71 1.3 1.6 1.6 1.7
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.) (continued)
Gas/Source
1990
1995
2000
2005
2006
Total
6,098.7
6,463.3
7,008.2
2007
Petrochemical Production 0.91 1.1| 1.2 1.1 1.0 1.0
Field Burning of Agricultural Residues 0.71 0.71 0.81 0.9 0.8 0.9
Iron and Steel Production & Metallurgical 1 Q 1 Q Q g Q7 Q7 Q7
Ferroalloy Production +1 +1 +1 + + +
Silicon Carbide Production and Consumption +1 +1 +1 + + +
International Bunker Fuels6 0.2! 0.71 0.71 0.1 0.1 0.1
N20 315.0 334.1 329.2 315.9 312.1 311.9
Agricultural Soil Management 200.3 202.3 204.5 210.6 208.4 207.9
Mobile Combustion 43.7 53.7 52.8 36.7 33.5 30.1
Nitric Acid Production 20.0 22.3 21.9 18.6 18.2 21.7
Manure Management 12.1 12.9 14.0 14.2 14.6 14.7
Stationary Combustion 12.8 13.3 14.5 14.8 14.5 14.7
Adipic Acid Production 15.3 17.3 6.2 5.9 5.9 5.9
Wastewater Treatment 3.71 4.01 4.51 4.8 4.8 4.9
N20 from Product Uses 4.41 4.61 4.91 4.4 4.4 4.4
Forest Land Remaining Forest Land 0.51 0.81 2.4l 1.8 3.5 3.3
Composting 0.4l 0.81 1.41 1.7 1.8 1.8
Settlements Remaining Settlements 1.0 1.2 1.2 1.5 1.5 1.6
Field Burning of Agricultural Residues 0.4l 0.4l 0.51 0.5 0.5 0.5
Incineration of Waste 0.51 0.51 0.4l 0.4 0.4 0.4
Wetlands Remaining Wetlands +1 +1 +1 + + +
International Bunker Fuels6 7.71 0.91 0.91 1.0 1.0 1.0
MFCs 36.9 61.8 100.1 116.1 119.1 125.5
Substitution of Ozone Depleting Substances0 0.31 28.5 71.2 100.0 105.0 108.3
HCFC-22 Production 36.4 33.0 28.6 15.8 13.8 17.0
Semiconductor Manufacture 0.2! 0.31 0.31 0.2 0.3 0.3
PFCs 20.8 15.6 13.5 6.2 6.0 7.5
Aluminum Production 18.5 11.8 8.61 3.0 2.5 3.8
Semiconductor Manufacture 2.2 3.81 4.91 3.2 3.5 3.6
SF6 32.8 28.1 19.2 17.9 17.0 16.5
Electrical Transmission and Distribution 26.8 21.6 15.1 14.0 13.2 12.7
Magnesium Production and Processing 5.41 5.61 3.0 2.9 2.9 3.0
Semiconductor Manufacture 0.51 0.91 1.1 1.0 1.0 0.8
7,108.6 7,051.1 7,150.1
Net Emissions (Sources and Sinks)
5,257.3
5,612.3
6,290.7
5,985.9 6,000.6 6,087.5
+ Does not exceed 0.05 Tg C02 Eq.
aThe 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.
c Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Emissions of all gases can be summed from each source
category from Intergovernmental Panel on Climate Change
(IPCC) guidance (see Table 2-3 and Figure 2-4). Over the
eighteen-year period of 1990 to 2007, total emissions in
the Energy, Industrial Processes, and Agriculture sectors
grew by 976.7 Tg CO2 Eq. (19 percent), 28.5 Tg CO2 Eq.
(9 percent), and 28.9 Tg CO2 Eq. (8 percent), respectively.
Emissions decreased in the Waste and Solvent and Other
Product Use sectors by 11.5 Tg CO2 Eq. (6 percent) and less
than 0.1 Tg CO2 Eq. (less than 0.4 percent), respectively.
Over the same period, estimates of net C sequestration in the
Land Use, Land-Use Change, and Forestry sector increased
by 192.5 Tg CO2 Eq. (23 percent).
Trends in Greenhouse Gas Emissions 2-5
-------
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 5,076,694
Fossil Fuel Combustion 4,708,918
Electricity Generation 1,809,685
Transportation 1,484,485
Industrial 834,204
Residential 337,715
Commercial 214,544
U.S. Territories 28,285
Non-Energy Use of Fuels 116,977
Iron and Steel Production & Metallurgical
Coke Production 109,760
Cement Production 33,278
Natural Gas Systems 33,733
Incineration of Waste 10,950
Lime Production 11,533
Ammonia Production and Urea Consumption 16,831
Cropland Remaining Cropland 7,084
Limestone and Dolomite Use 5,127
Aluminum Production 6,831
Soda Ash Production and Consumption 4,141
Petrochemical Production 2,221
Titanium Dioxide Production 1,195
Carbon Dioxide Consumption 1,416
Ferroalloy Production 2,152
Phosphoric Acid Production 1,529
Wetlands Remaining Wetlands 1,033
Zinc Production 949
Petroleum Systems 376
Lead Production 285
Silicon Carbide Production and Consumption 375
Land Use, Land-Use Change, and
Forestry (Sink)3 (841,430)
Biomass—Wooo* 215,186
International Bunker Fuels" 114,330
Biomass—Ethanolb 4,155
CH4 29,360
Enteric Fermentation 6,342
Landfills 7,105
Natural Gas Systems 6,171
Coal Mining 4,003
Manure Management 1,447
Forest Land Remaining Forest Land 218
Petroleum Systems 1,613
Wastewater Treatment 1,120
Stationary Combustion 352
5,407,885
5,013,910
1,938,862
1,598,668
862,5571
354,4431
I 224,4001
34,978
137,4601
5,407,885
5,013,910
1,938,862
1,598,668
862,557
354,443
224,400
34,978
137,460
103,116
36,847
33,810
15,712
13,325
17,796
7,049
6,651
5,659
4,304
2,750
1,526
1,422
2,036
1,513
1,018
1,013
341
298
329
(850,952)
229,091
101,620
7,683
29,325
6,837
6,871
6,314
3,193
1,642
293
1,524
1,183
340
5,955,177
5,561,515
2,283,177
1,800,305
844,554
370,352
226,932
36,195
144,473
95,062
41,190
29,394
17,485
14,088
16,402
7,541
5,056
6,086
4,181
3,004
1,752
1,421
1,893
1,382
1,227
1,140
325
311
248
(717,506)
218,088
98,966
9,188
28,148
6,398
5,825
6,231
2,881
1,804
983
1,441
1,200
315
6,090,838
5,723,477
2,381,002
1,881,470
828,008
358,036
221,761
53,201
138,070
73,190
45,910
29,463
19,532
14,379
12,849
7,854
6,768
4,142
4,228
2,804
1,755
1,321
1,392
1,386
1,079
465
287
266
219
(1,122,745)
208,927
111,487
22,554
26,748
6,474
6,088
5,062
2,719
1,991
676
1,346
1,159
318
6,014,871
5,635,418
2,327,313
1,880,874
844,505
321,852
206,049
54,824
145,137
76,100
46,562
29,540
19,824
15,100
12,300
7,889
8,035
3,801
4,162
2,573
1,876
1,709
1,505
1,167
879
529
288
270
207
(1,050,541)
209,926
110,520
30,459
27,713
6,580
6,211
4,991
2,780
1,993
1,489
1,346
1,165
300
6,103,408
5,735,789
2,397,191
1,887,403
845,416
340,625
214,351
50,803
133,910
77,370
44,525
28,680
20,786
14,595
13,786
8,007
6,182
4,251
4,140
2,636
1,876
1,867
1,552
1,166
1,010
530
287
267
196
(1,062,566)
209,785
108,756
38,044
27,872
6,618
6,327
4,985
2,744
2,093
1,381
1,370
1,160
315
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) (continued)
Gas/Source
1990
1995
2000
2005
2006
2007
Rice Cultivation 339 363 357 326 282 293
Abandoned Underground Coal Mines 2881 3921 3501 265 263 273
Mobile Combustion 22sl 2071 16sl 121 115 109
Composting 151 351 601 75 75 79
Petrochemical Production 411 52 591 51 48 48
Field Burning of Agricultural Residues 331 321 38 41 39 42
Iron and Steel Production & Metallurgical
Coke Production 46 471 441 34 35 33
Ferroalloy Production
Silicon Carbide Production and Consumption
International Bunker Fuels'3
N20
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Manure Management
Stationary Combustion
Adipic Acid Production
Wastewater Treatment
N20 from Product Uses
Forest Land Remaining Forest Land
Composting
Settlements Remaining Settlements
Field Burning of Agricultural Residues
Incineration of Waste
Wetlands Remaining Wetlands
International Bunker Fuels'3
MFCs
Substitution of Ozone Depleting Substances0
HCFC-22 Production
Semiconductor Manufacture
PFCs
Aluminum Production
Semiconductor Manufacture
SF6
Electrical Transmission and Distribution
Magnesium Production and Processing
Semiconductor Manufacture
+ Does not exceed 0.5 Gg.
M Mixture of multiple gases
aThe 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.
c Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
7
1,007
672
108
59
47
47
19
15
14
11
6
5
2
1
3
M
M
1
M
M
M
1
1
7
1,006
671
97
70
47
47
19
16
14
11
6
5
2
1
3
M
M
1
M
M
M
1
1
Trends in Greenhouse Gas Emissions 2-7
-------
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
1990
1995
2000
2005
2006
2007
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and
Forestry (Emissions)
Waste
5,520.1
345.8
4.6
402.0
16.2
174.7
6,059.9
356.3
4.9
399.4
1399.41
_ 33.0
154.6
6,169.2
337.6
4.4
410.8
26.4
160.2
6,084.4
343.9
4.4
410.3
45.1
163.0
6,170.3
353.8
4.4
413.1
42.9
165.6
Total Emissions
6,098.7
6,463.3
7,008.2
7,108.6 7,051.1 7,150.1
Net C02 Flux from Land Use, Land-Use Change,
and Forestry (Sinks)3 (841.4)
(851.0)
(717.5)
(1,122.7) (1,050.5) (1,062.6)
Net Emissions (Sources and Sinks)
5,257.3
5,612.3
6,290.7
5,985.9 6,000.6 6,087.5
aThe 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.
Figure 2-4
Figure 2-5
U.S. Greenhouse Gas Emissions and Sinks
by Chapter/IPCC Sector
7,500 -|
7,000 -
6,500 -
6,000 -
5,500 -
5,000
. 4,500-
4,000 -
" 3,500-
, 3,000-
2,500 -
2,000 -
1,500-
1,000-
500-
0
(500) -
(1,000)-
(1,500)-I
Industrial Processes
Agriculture
Waste
LULUCF (sources)
_1L_
Land Use, Land-Use Change and Forestry (sinks)
CM co -^ in to r-
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and
Other Product Use sector.
Energy
Energy-related activities, primarily fossil fuel
combustion, accounted for the vast majority of U.S. CO2
emissions for the period of 1990 through 2007. In 2007,
approximately 85 percent of the energy consumed in the
United States (on a Btu basis) was produced through the
combustion of fossil fuels. The remaining 15 percent came
from other energy sources such as hydropower, biomass,
nuclear, wind, and solar energy (see Figure 2-5 and Figure
2-6). A discussion of specific trends related to CO2 as well as
other greenhouse gas emissions from energy consumption is
presented in the Energy chapter. Energy-related activities are
2007 Energy Chapter Greenhouse Gas Sources
5,735.8
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion
Incineration of Waste
Abandoned Underground
Coal Mines
Energy as a Portion
of all Emissions
25
50 75 100
Tg C02 Eq.
125 150
also responsible for CH4 and N2O emissions (35 percent and
14 percent of total U.S. emissions of each gas, respectively).
Table 2-4 presents greenhouse gas emissions from the Energy
chapter, by source and gas.
CO2 emissions from fossil fuel combustion are presented
in Table 2-5 based on the underlying U.S. energy consumer
data collected by EIA. Estimates of CO2 emissions from
fossil fuel combustion are calculated from these EIA "end-
use sectors" based on total consumption and appropriate
fuel properties (any additional analysis and refinement of
the EIA data is further explained in the Energy chapter of
this report). EIA's fuel consumption data for the electric
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure 2-6
2007 U.S. Fossil Carbon Flows (Tg C02 Eq.)
Fossil Fuel
Energy Exports
340
NEU Emissions 122
Non-Energy Use
Carbon Seguestered
227
Fossil Fuel Stock
Non-Energy Consumption Changes
Use Imports U.S. ^
55 Territories
51
25
Non-Energy
Use U.S.
Territories
Note: Totals may not sum dueto independent rounding.
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
power sector comprises electricity-only and combined-heat-
and-power (CHP) plants within the NAICS 22 category
whose primary business is to sell electricity, or electricity
and heat, to the public (nonutility power producers can be
included in this sector as long as they meet the electric power
sector definition). EIA statistics for the industrial sector
include fossil fuel consumption that occurs in the fields of
manufacturing, agriculture, mining, and construction. EIA's
fuel consumption data for the transportation sector consists
of all vehicles whose primary purpose is transporting people
and/or goods from one physical location to another. EIA's
fuel consumption data for the industrial sector consists of
all facilities and equipment used for producing, processing,
or assembling goods (EIA includes generators that produce
electricity and/or useful thermal output primarily to support
on-site industrial activities in this sector). EIA's fuel
consumption data for the residential sector consists of living
quarters for private households. EIA's fuel consumption
data for the commercial sector consists of service-
providing facilities and equipment from private and public
organizations and businesses (EIA includes generators that
produce electricity and/or useful thermal output primarily to
support the activities at commercial establishments in this
sector). Table 2-5, Figure 2-7, and Figure 2-8 summarize CO2
emissions from fossil fuel combustion by end-use sector.
The main driver of emissions in the energy sector is
CO2 from fossil fuel combustion. The transportation end-
Figure 2-7
2,500 -i
2,000 -
1,500 -
3
1,000 -
500 -
0 -1
2007 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
Natural Gas
Petroleum
I Coal
Relative Contribution
by Fuel Type
ij
Note: Electricity generation also includes emissions of less than 0.5 Tg C02 Eq. from geothermal-based
electricity generation.
Trends in Greenhouse Gas Emissions 2-9
-------
Table 2-4: Emissions from Energy (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
Total
5,193.6
5,520.1
6,059.9
2007
C02 4,871.0 5,201.2 5,753.2 5,910.8 5,830.2 5,919.5
Fossil Fuel Combustion 4,708.9 5,013.91 5,561.5 5,723.5 5,635.4 5,735.8
Electricity Generation 1,809.7 1,938.9 2,283.21 2,381.0 2,327.3 2,397.2
Transportation 1,484.5 1,598.7 1,800.3 1,881.5 1,880.9 1,887.4
Industrial 834.2 862.6 844.6 828.0 844.5 845.4
Residential 337.7 354.4 370.4 358.0 321.9 340.6
Commercial 214.5 224.4 226.9 221.8 206.0 214.4
U.S. Territories 28.3 35.0 36.2 53.2 54.8 50.8
Non-Energy Use of Fuels 117.0 137.5 144.5 138.1 145.1 133.9
Natural Gas Systems 33.7 33.8 29.4 29.5 29.5 28.7
Incineration of Waste 10.9 15.7 17.5 19.5 19.8 20.8
Petroleum Systems 0.41 0.31 0.31 0.3 0.3 0.3
Wood Biomass and Ethanol Consumption3 219.3 236.8 227.3 231.5 240.4 247.8
International Bunker Fuels* 114.3 101.6 99.0 111.5 110.5 108.8
CH4 265.7 251.4 239.0 206.5 205.7 205.7
Natural Gas Systems 129.6 132.6 130.8 106.3 104.8 104.7
Coal Mining 84.1 67.1 60.5 57.1 58.4 57.6
Petroleum Systems 33.9 32.0 30.3 28.3 28.3 28.8
Stationary Combustion 7.4l 7.11 6.6 6.7 6.3 6.6
Abandoned Underground Coal Mines 6.0 8.2 7.41 5.6 5.5 5.7
Mobile Combustion 4.71 4.31 3.41 2.5 2.4 2.3
International Bunker Fuels3 0.2 H 0.71 0.71 0.7 0.7 0.7
N20 57.0 67.5 67.7 51.9 48.5 45.2
Mobile Combustion 43.7 53.7 52.8 36.7 33.5 30.1
Stationary Combustion 12.8 13.3 14.5 14.8 14.5 14.7
Incineration of Waste 0.51 0.51 0.4l 0.4 0.4 0.4
International Bunker Fuels3 1.1 0.9U 0.9U 1.0 1.0 1.0
6,169.2 6,084.4 6,170.3
a 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.
use sector accounted for 1,892.2 Tg CO2 Eq. in 2007, or
approximately 33 percent of total CO2 emissions from fossil
fuel combustion, the largest share of any end-use economic
sector.3 The industrial end-use sector accounted for 27 percent
of CO2 emissions from fossil fuel combustion. 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 72 and 79 percent
of emissions from the residential and commercial end-use
sectors, respectively. Significant trends in emissions from
3 Note that electricity generation is the largest emitter of CO2 when electricity
is not distributed among end-use sectors.
Figure 2-8
2,500 -i
2,000 -
S
1,500 -
1,000 -
500 -
0 J
2007 End-Use Sector Emissions
from Fossil Fuel Combustion
From Electricity
Consumption
| From Direct Fossil
Fuel Combustion
U.S. Commercial Residential
Territories
Industrial Transportation
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-5: 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
1,487,
1,484,
3,
1,516,
834,
682
927,
337,
589,
749,
214,
534,
28,
4,708,
1,809,
.5
.5
.0
.8
.2
.6
.1
.7
.4
.2
.5
.7
.3
.9
.7
1995
1,601,
1,598,
3,
1,575,
862
712,
993,
354,
638
808,
224,
584,
35,
5,013,
1,938,
.7
.7
.0
.5
.6
.9
.3
.4
.8
.5
.4
.1
.0
.9
.9
2000
1,803,
1,800,
3,
1,629,
844,
785,
1,128,
370,
757,
963,
226
736,
36,
5,561,
2,283,
.7
.3
.4
.6
.6
.0
.2
i
.2
.5
.2
2005
1,886.2
1,881.5
4.7
1,558.5
828.0
730.5
1,207.2
358.0
849.2
1,018.4
221.8
796.6
53.2
5,723.5
2,381.0
2006
1,885.4
1,880.9
4.5
1,550.7
844.5
706.2
1,145.9
321.9
824.1
998.6
206.0
792.5
54.8
5,635.4
2,327.3
2007
1,892.2
1,887.4
4.8
1,553.4
845.4
708.0
1,198.0
340.6
857.4
1,041.4
214.4
827.1
50.8
5,735.8
2,397.2
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.
energy source categories over the eighteen-year period from
1990 through 2007 included the following:
• Total CO2 emissions from fossil fuel combustion
increased from 4,708.9 Tg CO2 Eq. to 5,735.8 Tg CO2
Eq. —a 22 percent total increase over the eighteen-year
period. From 2006 to 2007, these emissions increased
by 100.4 Tg CO2 Eq. (1.8 percent).
• CO2 emissions from non-energy use of fossil fuels have
increased 16.9 Tg CO2 Eq. (14.5 percent) from 1990
through 2007. Emissions from non-energy uses of fossil
fuels were 133.9 Tg CO2 Eq. in 2007, which constituted
2.2 percent of total national CO2 emissions.
• CH4 emissions from natural gas systems were 104.7
Tg CO2 Eq. in 2007; emissions have declined by 24.9
Tg CO2 Eq. (19 percent) since 1990. This decline
has been due to improvements in technology and
management practices, as well as some replacement of
old equipment.
• CH4 emissions from coal mining were 57.6 Tg CO2
Eq. This decline of 26.4 Tg CO2 Eq. (31 percent)
from 1990 results from the mining of less gassy coal
from underground mines and the increased use of CH4
collected from degasification systems.
• In 2007, N2O emissions from mobile combustion were
30.1 Tg CO2 Eq. (approximately 10 percent of U.S. N2O
emissions). From 1990 to 2007, N2O emissions from
mobile combustion decreased by 31 percent. However,
from 1990 to 1998 emissions increased by 26 percent,
due to control technologies that reduced NOX emissions
while increasing N2O emissions. Since 1998, newer
control technologies have led to a steady decline in N2O
from this source.
• CO2 emissions from incineration of waste (20.8 Tg CO2
Eq. in 2007) increased by 9.8 Tg CO2 Eq. (90 percent)
from 1990 through 2007, as the volume of plastics and
other fossil carbon-containing materials in municipal
solid waste grew.
Industrial Processes
Emissions are produced as a byproduct 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 and
metallurgical coke production, cement production, ammonia
production 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, silicon carbide production
and consumption, aluminum production, petrochemical
production, nitric acid production, adipic acid production,
lead production, and zinc production (see Figure 2-9).
Trends in Greenhouse Gas Emissions 2-11
-------
Figure 2-9
2007 Industrial Processes Chapter
Greenhouse Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production &
Metallurgical Coke Production
Cement Production
Nitric Acid Production f
HCFC-22 Production f
Lime Production |
Ammonia Production and Urea Consumption |
Electrical Transmission and Distribution |
Aluminum Production |
Limestone and Dolomite Use |
Adipic Acid Production |
Semiconductor Manufacture |
Soda Asb Production and Consumption
Petrocbemical Production
Magnesium Production and Processing
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Pbospboric Acid Production
Zinc Production
Lead Production | <0.5
Silicon Carbide Production and Consumption I <0.5
Industrial Processes
as a Portion of
all Emissions
0
25
50 75 100
Tg CO, Eq.
125
Additionally, emissions from industrial processes release
HFCs, PFCs and SF6. Table 2-6 presents greenhouse gas
emissions from industrial processes by source category.
Overall, emissions from industrial processes increased
by 8.8 percent from 1990 to 2007 despite decreases in
emissions from several industrial processes, such as iron
and steel production and metallurgical coke production,
aluminum production, 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.
Significant trends in emissions from industrial processes
source categories over the eighteen-year period from 1990
through 2007 included the following:
• HFC emissions from ODS substitutes have been
increasing from small amounts in 1990 to 108.3 Tg CO2
Eq. in 2007. This increase results from 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
phased out under the provisions of the Copenhagen
Amendments to the Montreal Protocol.
• Carbon dioxide and CH4 emissions from iron and steel
production and metallurgical coke production increased
by 1.6 percent to 78.1 Tg CO2 Eq. in 2007, but have
declined overall by 32.6 Tg CO2 Eq. (29.5 percent)
from 1990 through 2007, due to restructuring of the
industry, technological improvements, and increased
scrap utilization.
• PFC emissions from aluminum production decreased by
79 percent (14.7 Tg CO2 Eq.) from 1990 to 2007, due
to both industry emission reduction efforts and lower
domestic aluminum production.
• Nitrous oxide emissions from adipic acid production
were 5.9 Tg CO2 Eq. in 2007, and have decreased
significantly in recent years from the widespread
installation of pollution control measures. Emissions
from adipic acid production have decreased 61 percent
since 1990, and emissions from adipic acid production
have fluctuated by less than 1.2 Tg CO2 Eq. annually
since 1998.
• Carbon dioxide emissions from ammonia production
and urea application (13.8 Tg CO2 Eq. in 2007) have
decreased by 3.0 Tg CO2 Eq. (18 percent) since 1990,
due to a decrease in domestic ammonia production.
This decrease in ammonia production can be attributed
to market fluctuations and high natural gas prices.
Solvent and Other Product Use
Greenhouse gas emissions are produced as a byproduct
of various solvent and other product uses. In the United
States, N2O Emissions from Product Uses, the only source of
greenhouse gas emissions from this sector, accounted for 4.4
Tg CO2 Eq., or less than 0.1 percent of total U.S. emissions
in 2007 (see Table 2-7).
In 2007, N2O emissions from product uses constituted
1 percent of US.N2O emissions. From 1990 to 2007, emissions
from this source category decreased by less than 0.5 percent,
though slight increases occurred in intermediate years.
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-6: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
Total
325.2
345.8
356.3
337.6
2006
343.9
2007
C02 197.6 198.6 193.2 171.1 175.9 174.9
Iron and Steel Production & Metallurgical
Coke Production 109.8 103.1 95.1 73.2 76.1 77.4
Cement Manufacture 33.3 36.8 41.2 45.9 46.6 44.5
Lime Manufacture 11.5 13.3 14.1 14.4 15.1 14.6
Ammonia Production & Urea Application 16.8 17.8 16.4 12.8 12.3 13.8
Limestone and Dolomite Use 5.11 6.71 5.11 6.8 8.0 6.2
Aluminum Production 6.8 5.71 6.11 4.1 3.8 4.3
Soda Ash Manufacture and Consumption 4.11 4.sB 4.2! 4.2 4.2 4.1
Petrochemical Production 2.2 2.8 3.01 2.8 2.6 2.6
Titanium Dioxide Production 1.2 1.51 1.81 1.8 1.9 1.9
Carbon Dioxide Consumption 1.4 1.4 1.4 1.3 1.7 1.9
Ferroalloy Production 2.2 2.01 1.91 1.4 1.5 1.6
Phosphoric Acid Production 1.51 1.51 1.4 1.4 1.2 1.2
Zinc Production 0.91 1.01 1.11 0.5 0.5 0.5
Lead Production 0.31 0.31 0.31 0.3 0.3 0.3
Silicon Carbide Production and Consumption 0.4! 0.31 0.2! 0.2 0.2 0.2
Petrochemical Production 0.91 1.11 1.2 1.1 1.0 1.0
Iron and Steel Production & Metallurgical
Coke Production 1.0 1.0 0.9 0.7 0.7 0.7
Ferroalloy Production +1 +1 +1 + + +
Silicon Carbide Production and Consumption +1 +1 +1 + + +
N20 35.3 39.6 28.1 24.6 24.2 27.6
Nitric Acid Production 20.0 22.3 21.9 18.6 18.2 21.7
Adipic Acid Production 15.3 17.3 6.2 5.9 5.9 5.9
MFCs 36.9 61.8 100.1 116.1 119.1 125.5
Substitution of Ozone Depleting Substances3 0.31 28.5 71.2 100.0 105.0 108.3
HCFC-22 Production 36.4 33.0 28.6 15.8 13.8 17.0
Semiconductor Manufacture 0.2! 0.31 0.31 0.2 0.3 0.3
PFCs 20.8 15.6 13.5 6.2 6.0 7.5
Aluminum Production 18.5 11.8 8.6 3.0 2.5 3.8
Semiconductor Manufacture 2.2 3.8 4.91 3.2 3.5 3.6
SF6 32.8 28.1 19.2 17.9 17.0 16.5
Electrical Transmission and Distribution 26.8 21.6 15.1 14.0 13.2 12.7
Magnesium Production and Processing 5.41 5.eB 3.0 2.9 2.9 3.0
Semiconductor Manufacture 0.51 0.91 1.1 1.0 1.0 0.8
353.8
+ Does not exceed 0.05 Tg C02 Eq.
a Small amounts of RFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Table 2-7: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq.)
Gas/Source
N20
N20 from Product Uses
Total
1990
4.4
4.4
4.4
1995
4.6
4.6
4.6
2000
4.9
4.9
4.9
2005
4.4
4.4
4.4
2006
4.4
4.4
4.4
2007
4.4
4.4
4.4
Trends in Greenhouse Gas Emissions 2-13
-------
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 (see Figure 2-10).
In 2007, agricultural activities were responsible for
emissions of 413.1 Tg CO2 Eq., or 5.8 percent of total U.S.
greenhouse gas emissions (see Table 2-8). Methane and N2O
were the primary greenhouse gases emitted by agricultural
activities. Methane emissions from enteric fermentation
and manure management represented about 24 percent
and 8 percent of total CH4 emissions from anthropogenic
activities, respectively, in 2007. Agricultural soil management
activities, such as fertilizer application and other cropping
Figure 2-10
2007 Agriculture Chapter Greenhouse Gas
Emision Sources
207.9
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
Agriculture
as a Portion of
all Emissions
50 100
Tg C02 Eq.
150
practices, were the largest source of U.S. N2O emissions in
2007, accounting for 67 percent.
Some significant trends in U.S. emissions from
agriculture include the following:
• Agricultural soils produced approximately 67 percent of
N2O emissions in the United States in 2007. Estimated
emissions from this source in 2007 were 207.9 Tg
CO2 Eq. Annual N2O emissions from agricultural soils
fluctuated between 1990 and 2007, although overall
emissions were 3.8 percent higher in 2007 than in
1990. 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, and to
weather patterns and crop type.
• Enteric fermentation was the largest source of CH4
emissions in 2007, at 139.0 Tg CO2 Eq. Although
emissions from enteric fermentation have increased by
4 percent between 1990 and 2007, emissions increased
about 8 percent between 1990 and 1995 and decreased
about 7 percent from 1995 to 2004, mainly due to
decreasing populations of both beef and dairy cattle
and improved feed quality for feedlot cattle. The last
three years have shown an increase in emissions. During
this timeframe, populations of sheep have decreased
46 percent since 1990 while horse populations have
increased over 80 percent, mostly over the last 6 years.
Goat and swine populations have increased 1 percent
and 21 percent, respectively, during this timeframe.
• Overall, emissions from manure management increased
38 percent between 1990 and 2007. This encompassed
Table 2-8: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source
1990
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural Residues
1995
2000
2005
185.5
136.0
41.8
6.8
0.9
225.3
210.6
14.2
0.5
2006
186.8
138.2
41.9
5.9
0.8
223.5
208.4
14.6
0.5
2007
190.0
139.0
44.0
6.2
0.9
223.1
207.9
14.7
0.5
Total
384.2
402.0
399.4
410.8
410.3
413.1
Note: Totals may not sum due to independent rounding.
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
an increase of 45 percent for CH4, from 30.4 Tg
CO2 Eq. in 1990 to 44.0 Tg CO2 Eq. in 2007; and an
increase of 22 percent for N2O, from 12.1 Tg CO2 Eq.
in 1990 to 14.7 Tg CO2 Eq. in 2007. The majority of
this increase was from swine and dairy cow manure,
since the general trend in manure management is one
of increasing use of liquid systems, which tends to
produce greater CR4 emissions.
Land Use, Land-Use Change, 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 an uptake (sequestration) of
carbon in the United States, which offset about 14.9 percent
of total U.S. greenhouse gas emissions in 2007. Forests
(including vegetation, soils, and harvested wood) accounted
for approximately 86 percent of total 2007 net CO2 flux,
urban trees accounted for 9 percent, mineral and organic soil
carbon stock changes accounted for 4 percent, and landfilled
yard trimmings and food scraps accounted for 1 percent of
the total net flux in 2007. The net forest sequestration is a
result of net forest growth, increasing forest area, and a net
accumulation of carbon stocks in harvested wood pools.
The net sequestration in urban forests is a result of net tree
growth and increased urban forest size. In agricultural soils,
mineral and organic soils sequester approximately 70 percent
more C than is emitted from these soils through liming, urea
fertilization, or both. The mineral soil C sequestration is
largely due to the conversion of cropland to hay production
fields, the limited use of bare-summer fallow areas in semi-
arid areas, and an increase in the adoption of conservation
tillage practices. 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
2007 resulted in a net C sequestration of 1,062.6 Tg CO2
Eq. (Table 2-9). This represents an offset of approximately
17.4 percent of total U.S. CO2 emissions, or 14.9 percent of
total greenhouse gas emissions in 2007. Between 1990 and
2007, total land use, land-use change, and forestry net C flux
resulted in a 26.3 percent increase in CO2 sequestration.
Land use, land-use change, and forestry source categories
also resulted in emissions of CO2, CFL,, and N2O that are
not included in the net flux estimates presented in Table
2-10. The application of crushed limestone and dolomite
to managed land (i.e., soil liming) and urea fertilization
resulted in CO2 emissions of 8.0 Tg CO2 Eq. in 2007, an
increase of 13 percent relative to 1990. Lands undergoing
peat extraction resulted in CO2 emissions of 1.0 Tg CO2 Eq.
(1,010 Gg), andN2O emissions of less than 0.01 Tg CO2Eq.
N2O emissions from the application of synthetic fertilizers
to forest soils have increased from 1990 to 0.3 Tg CO2 Eq.
in 2007. Settlement soils in 2007 resulted in direct N2O
emissions of 1.6 Tg CO2 Eq., a 61 percent increase relative to
1990. Non-CO2 emissions from forest fires in 2007 resulted
in CH4 emissions of 29 Tg CO2 Eq., and in N2O emissions
of 2.9 Tg CO2 Eq.
Other significant trends from 1990 to 2007 in land use,
land-use change, and forestry emissions include:
• Net C sequestration by forest land has increased 38
percent. This is primarily due to increased forest
Table 2-9: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2005
2006
2007
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements
Other (Landfilled Yard Trimmings and
Food Scraps)
(23.5)
(13.9)
(11.3)
(975.7)
(18.3)
5.9
(4.6)
(26.7)
(93.3)
(900.3)
(19.1)
5.9
(4.6)
(26.7)
(95.5)
(10.2) (10.4)
(910.1)
(19.7)
5.9
(4.7)
(26.7)
(97.6)
(9.8)
Total
(841.4)
(851.0)
(717.5)
(1,122.7) (1,050.5) (1,062.6)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Trends in Greenhouse Gas Emissions 2-15
-------
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
C02
Cropland Remaining Cropland:
Liming of Agricultural Soils
Cropland Remaining Cropland:
Urea Fertilization
Wetlands Remaining Wetlands:
Peatlands Remaining Peatlands
CH4
Forest Land Remaining Forest Land:
Forest Fires
N20
Forest Land Remaining Forest Land:
Forest Fires
Forest Land Remaining Forest Land:
Forest Soils
Wetlands Remaining Wetlands:
Peatlands Remaining Peatlands
Settlements Remaining Settlements:
Settlement Soils
8.1
4.7
2.4
1.0
4.61
4.6
1.51
0.5
0.0
8.1
4.4
2.7
1.0
6.1
6.1
2.01
0.6
1
1.2
8.8
4.3
3.2
1.2
20.6
20.6
3.6
2.1
0.3
8.9
4.3
3.5
1.1
14.2
14.2
3.3
1.4
0.3
+
1.5
8.8
4.2
3.7
0.9
31.3
31.3
5.0
3.2
0.3
+
1.5
9.0
4.1
4.0
1.0
29.0
29.0
4.9
2.9
0.3
+
1.6
Total
14.2
16.2
33.0
26.4
45.1
42.9
+ Less than 0.05 TgC02Eq.
Note: Totals may not sum due to independent rounding.
management and the effects of previous reforestation.
The increase in intensive forest management resulted in
higher growth rates and higher biomass density. The tree
planting and conservation efforts of the 1970s and 1980s
continue to have a significant impact on sequestration
rates. Finally, the forested area in the United States
increased over the past 18 years, although only at an
average rate of 0.25 percent per year.
• Net sequestration of C by urban trees has increased by
61 percent over the period from 1990 to 2007. This is
primarily due to an increase in urbanized land area in
the United States.
• Annual C sequestration in landfilled yard trimmings
and food scraps has decreased by 58 percent since 1990.
This is due in part to a decrease in the amount of yard
trimmings and food scraps generated. In addition, the
proportion of yard trimmings and food scraps landfilled
has decreased, as there has been a significant rise in
the number of municipal composting facilities in the
United States.
Waste
Waste management and treatment activities are sources
of greenhouse gas emissions (see Figure 2-11). In 2007,
landfills were the second largest source of anthropogenic
CH4 emissions, accounting for 23 percent of total U.S. CH4
emissions.4 Additionally, wastewater treatment accounts
for 4 percent of U.S. CH4 emissions, and 2 percent of N2O
Figure 2-11
2007 Waste Chapter Greenhouse Gas Emission Sources
Landfills
Composting
0 20
40
60 80 100
Tg C02 Eq.
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.
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-11: Emissions from Waste (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Landfills
Wastewater Treatment
Composting
N20
Wastewater Treatment
Composting
153.8
127.8
24.3
1.6
6.5
4.8
1.7
156.5
130.4
24.5
1.6
6.6
4.8
1.8
158.9
132.9
24.4
1.7
6.7
4.9
1.8
Total
177.1
174.7
154.6
160.2
163.0
165.6
Note: Totals may not sum due to independent rounding.
emissions. Emissions of CH4 and N2O from composting grew
from 1990 to 2007, and resulted in emissions of 3.5 Tg CO2
Eq. in 2007. A summary of greenhouse gas emissions from
the Waste chapter is presented in Table 2-11.
Overall, in 2007, waste activities generated emissions
of 165.6 Tg CO2 Eq., or 2.3 percent of total U.S. greenhouse
gas emissions.
Some significant trends in U.S. emissions from waste
include the following:
• From 1990 to 2007, net CFL, emissions from landfills
decreased by 16.3 Tg CO2 Eq. (11 percent), with small
increases occurring in 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.
• From 1990 to 2007, CH4 and N2O emissions from
wastewater treatment increased by 0.8 Tg CO2 Eq. (4
percent) and 1.2 Tg CO2 Eq. (32 percent), respectively.
• Methane and N2O emissions from composting each
increased by less than 0.1 Tg CO2 Eq. (4 percent) from
2006 to 2007. Emissions from composting have been
continually increasing since 1990, from 0.7 Tg CO2
Eq. to 3.5 Tg CO2 Eq. in 2007, a four-fold increase
over the time series.
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.
2.2. Emissions by Economic Sector
Throughout this report, emission estimates are grouped
into six sectors (i.e., chapters) defined by the IPCC and
detailed above: 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 U.S. 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 2007. Transportation
activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted for
about 20 percent of U.S. greenhouse gas emissions in 2007. 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 efficiency improvements. The remaining 18
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 5 percent, and primarily consisted of CO2
emissions from fossil fuel combustion. Activities related to
agriculture accounted for roughly 7 percent of U.S. emissions;
Trends in Greenhouse Gas Emissions 2-17
-------
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 roughly 6 percent of emissions, while
U.S. territories accounted for about 1 percent.
Carbon dioxide 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 landfilling of yard trimmings.
Table 2-12 presents a detailed breakdown of emissions
from each of these economic sectors by source category, as
they are defined in this report. Figure 2-12 shows the trend
in emissions by sector from 1990 to 2007.
Figure 2-12
Emissions Allocated to Economic Sectors
2,500 -i
2,000 -
1,500-
1,000-
500-
Electricity Generation
Transportation
Industry
Agriculture
'Commercial
Residential
Note: Does not include U.S. Territories.
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors
(Tg C02 Eq. and Percent of Total in 2007)
Sector/Source
1990
1995
2000
2005
2006
2007 Percent3
Electric Power Industry
C02from Fossil Fuel Combustion
Incineration of Waste
1,859.1
1, 809.7 1
11.4
11,989.0
1,938.9
16.2
2,329.3
2,283.2
17.9
2,429.4
2,381.0
19.9
2,375.5
2,327.3
20.2
2,445.1
2,397.2
21.2
34.2%
33.5%
0.3%
Electrical Transmission and
Distribution 26.8
Stationary Combustion 8.6
Limestone and Dolomite Use 2.6
Transportation 1,543.6
C02 from Fossil Fuel Combustion 1,484.5
Substitution of Ozone Depleting
Substances +
Mobile Combustion 47.3
Non-Energy Use of Fuels 11.9
Industry 1,496.0
C02 from Fossil Fuel Combustion 803.4
Natural Gas Systems 163.3
Non-Energy Use of Fuels 99.4
Iron and Steel & Metallurgical
Coke Production 110.7
Coal Mining 84.1
Cement Production 33.3
Petroleum Systems 34.2
Nitric Acid Production 20.0
HCFC-22 Production 36.4
Lime Production 11.5
Ammonia Production and Urea
Consumption 16.81
Aluminum Production 25.4
Substitution of Ozone Depleting
Substances
Adipic Acid Production 15.3
104.1
67.1
36.8
32.3
22.3
33.0
13.3
17.8
17.5
1.2
17.3
96.0
60.5
41.2
30.6
21.9
28.6
14.1
16.4
14.7
3.1
6.2
73.9
57.1
45.9
28.6
18.6
15.8
14.4
12.8
7.1
5.2
5.9
76.8
58.4
46.6
28.6
18.2
13.8
15.1
12.3
6.3
5.7
5.9
78.1
57.6
44.5
29.1
21.7
17.0
14.6
13.8
8.1
6.1
5.9
0.2%
0.2%
+
27.9%
26.4%
0.9%
0.4%
0.1%
19.4%
11.2%
1.9%
1.6%
1.1%
0.8%
0.6%
0.4%
0.3%
0.2%
0.2%
0.2%
0.1%
0.1%
0.1%
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (continued)
(Tg C02 Eq. and Percent of Total in 2007)
Sector/Source
1990
1995
2000
2005
2006
2007 Percent3
Abandoned Underground Coal
Mines
Semiconductor Manufacture
Stationary Combustion
N20 from Product Uses
Soda Ash Production and
Consumption
Petrochemical Production
Limestone and Dolomite Use
Magnesium Production and
Processing
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Mobile Combustion
Phosphoric Acid Production
Zinc Production
Lead Production
Silicon Carbide Production and
Consumption
Agriculture
N20 from Agricultural Soil
Management
Enteric Fermentation
Manure Management
C02from Fossil Fuel Combustion
CH4 and N20 from Forest Fires
Rice Cultivation
Liming of Agricultural Soils
Urea Fertilization
Field Burning of Agricultural
Residues
C02 and N20 from Managed
Peatlands
Mobile Combustion
N20 from Forest Soils
Stationary Combustion
Commercial
C02from Fossil Fuel Combustion
Landfills
Substitution of Ozone Depleting
Substances
Wastewater Treatment
Human Sewage
Composting
Stationary Combustion
Residential
C02from Fossil Fuel Combustion
Substitution of Ozone Depleting
Substances
6.0
2.9
4.7
4.4
4.1
3.1
2.6
5.4
1.2
1.4
2.2
0.9
1.5
0.9
0.3
0.4
428.5
200.3
133.2
42.4
30.8
5.1
7.1
4.7
2.4
1.1
8.2
4.9
4.9
4.6
4.3
3.8
3.3
5.6
1.5
1.4
2.0
1.0
1.5
1.0
0.3
0.3
453.7
202.3
143.6
47.4
36.3
6.8
7.6
4.4
2.7
1.0
7.4
6.2
4.8
4.9
4.2
4.2
2.5
3.0
1.8
1.4
1.9
1.1
1.4
1.1
0.3
0.3
470.2
204.5
134.4
51.9
38.4
22.7
7.5
4.3
3.2
1.3
1.2
0.4
0.3
+
388.2
226.9
122.3
5.5
25.2
4.5
2.6
1.2
386.0
370.4
10.1
5.6
4.4
4.5
4.4
4.2
3.9
3.4
2.9
1.8
1.3
1.4
1.3
1.4
0.5
0.3
0.2
482.6
210.6
136.0
56.0
46.4
15.6
6.8
4.3
3.5
1.4
1.1
0.5
0.3
+
401.8
221.8
127.8
18.5
24.3
4.8
3.3
1.2
370.5
358.0
6.5
5.5
4.7
4.6
4.4
4.2
3.6
4.0
2.9
1.9
1.7
1.5
1.3
1.2
0.5
0.3
0.2
502.9
208.4
138.2
56.4
48.6
34.4
5.9
4.2
3.7
1.3
0.9
0.5
0.3
+
392.6
206.0
130.4
22.4
24.5
4.8
3.3
1.1
334.9
321.9
7.5
5.7
4.7
4.5
4.4
4.1
3.7
3.1
3.0
1.9
1.9
1.6
1.3
1.2
0.5
0.3
0.2
502.8
207.9
139.0
58.7
47.9
31.9
6.2
4.1
4.0
1.4
1.0
0.5
0.3
+
407.6
214.4
132.9
26.6
24.4
4.9
3.5
1.2
355.3
340.6
8.6
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
7.0%
2.9%
1.9%
0.8%
0.7%
0.4%
0.1%
0.1%
0.1%
5.7%
3.0%
1.9%
0.4%
0.3%
0.1%
5.0%
4.8%
0.1%
Trends in Greenhouse Gas Emissions 2-19
-------
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors
(Tg C02 Eq. and Percent of Total in 2007) (continued)
Sector/Source
Stationary Combustion
Settlement Soil Fertilization
U.S. Territories
C02from Fossil Fuel Combustion
Non-Energy Use of Fuels
Stationary Combustion
Total Emissions
Sinks
C02 Flux from Forests
Urban Trees
C02 Flux from Agricultural Soil
Carbon Stocks
Landfilled Yard Trimmings and
Food Scraps
Net Emissions
(Sources and Sinks)
1990
5.5
6,098.7
(841.4)
(661.1)
(60.6)
(96.3)
(23.5)
5,257.3
1995
5.0
41.1
35.0
6.0
0.1
6,463.3
(851.0)
(686.6)
(71.5)
(78.9)
(13.9)
5,612.3
2000
4.3
47.3
36.2
10.9
0.1
7,008.2
(717.5)
(512.6)
(82.4)
(111.2)
(11.3)
6,290.7
2005
4.5
1.5
60.5
53.2
7.1
0.2
7,108.6
(1,122.7)
(975.7)
(93.3)
(43.6)
(10.2)
5,985.9
2006
4.0
1.5
62.3
54.8
7.3
0.2
7,051.1
(1,050.5)
(900.3)
(95.5)
(44.5)
(10.4)
6,000.6
2007
4.4
1.6
57.7
50.8
6.7
0.2
7,150.1
(1,062.6)
(910.1)
(97.6)
(45.1)
(9.8)
6,087.5
Percent3
0.1%
+
0.8%
0.7%
0.1%
0.0%
100.0%
(14.9)%
(12.7)%
(1.4)%
(0.6)%
(0.1)%
85.1%
+ Does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
'Percent of total emissions for year 2007.
Note: Includes all emissions of C02, CH4, N20, MFCs, PFCs, and SFe. Parentheses indicate negative values or sequestration. Totals may not sum due to
independent rounding.
Emissions with Electricity Distributed to
Economic Sectors
It can also be useful to view 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). The generation,
transmission, and distribution of electricity, which is the
largest economic sector in the United States, accounted for
34 percent of total U.S. greenhouse gas emissions in 2007.
Emissions increased by 28 percent since 1990, as electricity
demand grew and fossil fuels remained the dominant
energy source for generation. Electricity generation-related
emissions increased from 2006 to 2007 by 3 percent,
primarily due to increased CO2 emissions from fossil fuel
combustion. The electricity generation sector in the United
States is composed of traditional electric utilities as well as
other entities, such as power marketers and non-utility 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 2-13 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 (ElA 2008a 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 (30 percent), followed closely by
emissions from transportation activities, which account for
28 percent of total emissions. Emissions from the residential
6Emissions 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.
2-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Fuel Type or Source
1990
1995
2000
2005
2006
Total
1,859.1
1,989.0
2,329.3
2007
C02 1,823.2 1,957.9 2,303.2 2,403.9 2,351.2 2,421.1
C02 from Fossil Fuel Combustion 1,809.7 1,938.9 2,283.21 2,381.0 2,327.3 2,397.2
Coal 1,531.1 1,648.6 1,909.5 1,958.4 1,932.4 1,967.6
Natural Gas 176.5 229.2 281.8 319.9 338.9 373.8
Petroleum 101.8 60.7 91.5 102.3 55.6 55.3
Geottiermal 0.4U 0.31 0.41 0.4 0.4 0.4
Incineration of Waste 10.9 15.7 17.5 19.5 19.8 20.8
Limestone and Dolomite Use 2.6 3.31 2.51 3.4 4.0 3.1
CH4 0.61 0.61 0.7 0.7 0.7 0.7
Stationary Combustion3 0.61 0.61 0.71 0.7 0.7 0.7
N20 8.5 9.01 10.4 10.7 10.5 10.7
Stationary Combustion3 8.11 8.61 10.0 10.3 10.1 10.3
Incineration of Waste 0.51 0.51 0.4l 0.4 0.4 0.4
SF6 26.8 21.6 15.1 14.0 13.2 12.7
Electrical Transmission and Distribution 26.8 21.6 15.1 14.0 13.2 12.7
2,429.4 2,375.5 2,445.1
'Includes only stationary combustion emissions related to the generation of electricity.
Note: Totals may not sum due to independent rounding.
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 2-14 presents a detailed breakdown of emissions
from each of these economic sectors, with emissions from
electricity generation distributed to them. Figure 2-13 shows
the trend in these emissions by sector from 1990 to 2007.
Figure 2-13
Emissions with Electricity Distributed to Economic Sectors
Industry
2,500 -
2,000 -
1,500-
1,000-
500-
0-
Industrial
Transportation
Residential
•
Commercial
Agriculture
O)O)O)O)O)O)O)O)O)O)OOOOOOOO
Note: Does not include U.S. Territories.
The industrial end-use sector includes CO2 emissions
from fossil fuel combustion from all manufacturing facilities,
in aggregate. This sector also includes emissions that are
produced as a byproduct of the non-energy-related industrial
process activities. The variety of activities producing these
non-energy-related emissions, includes, among others,
fugitive CtLj emissions from coal mining, byproduct CO2
emissions from cement manufacture, and HFC, PFC, and
SF6 byproduct emissions from semiconductor manufacture.
Overall, direct industry sector emissions have declined
since 1990, while electricity-related emissions have risen. 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 are also affected by weather conditions.
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.
Transportation
When electricity-related emissions are distributed
to economic end-use sectors, transportation activities
Trends in Greenhouse Gas Emissions 2-21
-------
Table 2-14: U.S Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related
Emissions Distributed (Tg C02 Eq.) and Percent of Total in 2007
Sector/Gas
Industry
Direct Emissions
C02
CH4
N20
MFCs, PFCs, and SF6
Electricity-Related
C02
CH4
N20
SF6
Transportation
Direct Emissions
C02
CH4
N20
HFCsb
Electricity-Related
C02
CH4
N20
SF6
Commercial
Direct Emissions
C02
CH4
N20
MFCs
Electricity-Related
C02
CH4
N20
SF6
Residential
Direct Emissions
C02
CH4
N20
MFCs
Electricity-Related
C02
CH4
N20
SF6
1990
2,166.5
1,496.0
1,097.9
291.1
43.6
63.3
670.6
657.6
0.2
3.1 1
9.7
1,546.7
1,543.6
1,496.3
4.5
42.7
::
+
942.2
392.9
214.5
173.9
4.4
+
549.3
538.7
0.2
Ł
950.0
344.5
337.7
4.4
2.1 1
0.3
605.5
593.8
0.2l
2.8
8.7
1995
2,219.8
1,524.5
1,141.7
277.8
48.4
56.6
695.3
684.4
0.2l
3.2
7.5
1,688.3
1,685.2
1,610.0
4.1 1
52.5
18.6
I
+
1,000.2
401.0
224.4
170.8
5.2
0.7
599.2
589.8
0.2
2.7
6.5
1,024.2
368.8
354.4
4.0
2.2l
655.4
645.1
0.2l
3.0
7.1
2000
2,235.5
1,467.5
1,118.3
262.5
37.2
49.6
767.9
759.3
0.2
3.4 1
5.0 1
1,923.2
_._
5.5
751.7
743.3
0.2l
3.3
4.9 1
1,159.2
386.0
370.4
3.4
10.1
773.2
764.5
0.2
3.4
5.0
2005
2,081.2
1,364.9
1,070.1
230.4
33.1
31.3
716.3
708.8
0.2
3.2
4.1
2,003.6
1,998.9
1,891.7
2.2
35.2
69.7
4.8
4.7
+
+
+
1,214.6
401.8
221.8
154.6
6.8
18.5
812.8
804.3
0.2
3.6
4.7
1,237.0
370.5
358.0
3.5
2.4
6.5
866.5
857.4
0.3
3.8
5.0
2006
2,082.3
1,388.4
1,095.8
230.2
32.8
29.6
693.8
686.7
0.2
3.1
3.9
1,999.0
1,994.4
1,890.8
2.1
32.0
69.5
4.6
4.5
+
+
+
1,201.5
392.6
206.0
157.3
6.9
22.4
808.9
800.6
0.2
3.6
4.5
1,176.1
334.9
321.9
3.2
2.4
7.5
841.2
832.5
0.3
3.7
4.7
2007
2,081.2
1,386.3
1,086.4
229.1
36.2
34.7
694.9
688.0
0.2
3.0
3.6
2,000.1
1,995.2
1,897.6
2.0
28.6
67.0
4.9
4.8
+
+
+
1,251.2
407.6
214.4
159.7
7.0
26.6
843.6
835.3
0.3
3.7
4.4
1,229.8
355.3
340.6
3.5
2.5
8.6
874.5
865.9
0.3
3.8
4.5
Percent3
29.1%
19.4%
15.2%
3.2%
0.5%
0.5%
9.7%
9.6%
+
+
0.1%
28.0%
27.9%
26.5%
+
0.4%
0.9%
0.1%
0.1%
+
+
+
17.5%
5.7%
3.0%
2.2%
0.1%
0.4%
11.8%
11.7%
+
0.1%
0.1%
17.2%
5.0%
4.8%
+
+
0.1%
12.2%
12.1%
+
0.1%
0.1%
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-14: U.S Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related
Emissions Distributed (Tg C02 Eq.) and Percent of Total in 2007 (continued)
Sector/Gas
1990
1995
2000
2005
2006
2007 Percent3
Agriculture
Direct Emissions
C02
CH4
N20
Electricity-Related
C02
CH4
N20
SF6
U.S. Territories
47.3
511.7
482.6
55.3
199.8
227.5
29.0
28.7
+
0.1
0.2
60.5
530.0
502.9
57.3
218.2
227.4
27.0
26.8
+
0.1
0.2
62.3
530.1
502.8
56.9
219.2
226.7
27.3
27.0
+
0.1
0.1
57.7
7.4%
7.0%
0.8%
3.1%
3.2%
0.4%
0.4%
0.8%
Total
6,098.7
6,463.3
7,008.2
7,108.6 7,051.1 7,150.1 100.0%
+ Does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
'Percent of total emissions for year 2007.
b Includes primarily HFC-134a.
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.
accounted for 28 percent of U.S. greenhouse gas emissions
in 2007. The largest sources of transportation GHGs in 2007
were passenger cars (33 percent), light duty trucks, which
include sport utility vehicles, pickup trucks, and minivans
(28 percent), freight trucks (21 percent) and commercial
aircraft (8 percent). These figures include direct emissions
from fossil fuel combustion, as well as HFC emissions from
mobile air conditioners and refrigerated transport allocated
to these vehicle types. Table 2-15 provides a detailed
summary of greenhouse gas emissions from transportation-
related activities with electricity-related emissions included
in the totals.
From 1990 to 2007, transportation emissions rose by 29
percent due, in large part, to increased demand for travel and
the stagnation of fuel efficiency across the U.S. vehicle fleet.
The number of vehicle miles traveled by light-duty motor
vehicles (passenger cars and light-duty trucks) increased
40 percent from 1990 to 2007, as a result of a confluence
of factors including population growth, economic growth,
urban sprawl, and low fuel prices over much of this period.
A similar set of social and economic trends has led to a
significant increase in air travel and freight transportation
by both air and road modes during the time series.
Although average fuel economy over this period
increased slightly due primarily to the retirement of older
vehicles, average fuel economy among new vehicles sold
annually gradually declined from 1990 to 2004. The decline
in new vehicle fuel economy between 1990 and 2004
reflected the increasing market share of light duty trucks,
which grew from about one-fifth of new vehicle sales in the
1970s to slightly over half of the market by 2004. Increasing
fuel prices have since decreased the momentum of light
duty truck sales, and average new vehicle fuel economy has
improved since 2005 as the market share of passenger cars
increased. VMT growth among all passenger vehicles has
also been impacted, growing an average annual rate of 0.6
percent from 2004 to 2007, compared to an annual rate of
2.6 percent over the period 1990 to 2004.
Almost all of the energy consumed for transportation
was supplied by petroleum-based products, with more than
half being related to gasoline consumption in automobiles
and other highway vehicles. Other fuel uses, especially diesel
fuel for freight trucks and jet fuel for aircraft, accounted for
the remainder. The primary driver of transportation-related
emissions was CO2 from fossil fuel combustion, which
increased by 29 percent from 1990 to 2007. This rise in
CO2 emissions, combined with an increase in HFCs from
virtually no emissions in 1990 to 67.0 Tg CO2 Eq. in 2007,
led to an increase in overall emissions from transportation
activities of 28 percent.
Trends in Greenhouse Gas Emissions 2-23
-------
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Vehicle Type/Gas
1990
1995
2000
2005
2006
2007
Passenger Cars 656.9 644.1 694.6 705.8 678.3 664.6
C02 628.8 604.9 643.5 658.4 634.4 625.0
N20 25.4 26.9 25.2 17.8 15.7 13.7
MFCs +1 10.1 24.3 28.5 27.2 24.9
Light-Duty Trucks 336.2 434.7 508.3 544.8 557.1 561.7
C02 320.7 405.0 466.2 502.8 515.5 522.0
Medium- and Heavy-Duty Trucks 228.8 272.7 344.2 395.1 404.5 410.8
C02 227.8 271.2 341.3 391.6 401.1 407.4
Buses 8.3 9.11 11.1 12.1 12.4 12.4
Motorcycles 1.81 1.81 1.9 1.6 1.9 2.1
Commercial Aircraft" 136.9 143.1 167.8 159.8 155.5 155.2
C02 135.5 141.6 166.0 158.2 153.9 153.6
Other Aircraft" 44.4 32.3 32.9 34.5 33.8 34.2
C02 43.9 32.0 32.5 34.1 33.4 33.9
Ships and Boats0 46.9 56.6 65.1 50.7 54.1 56.3
C02 46.5 55.5 61.0 45.4 48.7 50.8
Rail 38.6 44.1 50.1 56.7 58.9 58.0
C02 38.1 42.2 45.1 49.8 51.8 50.8
MFCs +1 1.4l 4.61 6.4 6.5 6.6
Other Emissions from Electricity Generation 0.11 0.11 0.11 0.1 0.1 0.1
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.) (continued)
Vehicle Type/Gas
Pipelines6
C02
Lubricants
C02
Total Transportation
International Bunker Fuels'
1990
36.2
36.2
11.9
11.9
1,546.7
115.6
1995
38.5
38.5
11.3
11.3
1,688.3
102.7
2000
35.2
35.2
12.1
12.1
1,923.2
100.0
2005
32.4
32.4
10.2
10.2
2,003.6
112.7
2006
32.6
32.6
9.9
9.9
1,999.0
111.7
2007
34.6
34.6
10.2
10.2
2,000.1
109.9
+ Does not exceed 0.05 Tg C02 Eq.
'Consists of emissions from jet fuel consumed by domestic operations of commercial aircraft (no bunkers).
b Consists of emissions from jet fuel and aviation gasoline consumption by general aviation and military aircraft.
c Fluctuations in emission estimates are associated with fluctuations in reported fuel consumption, and may reflect data collection problems.
11 Other emissions from electricity generation are a result of waste incineration (as the majority of municipal solid waste is combusted in "trash-to-
steam" electricity generation plants), electrical transmission and distribution, and a portion of limestone and dolomite use (from pollution control
equipment installed in electricity generation plants).
e C02 estimates reflect natural gas used to power pipelines, but not electricity. While the operation of pipelines produces CH4 and N20, these emissions
are not directly attributed to pipelines in the US Inventory.
'Emissions from International Bunker Fuels include emissions from both civilian and military activities; these emissions are not included in the
transportation totals.
Note: Totals may not sum due to independent rounding. Passenger cars and light-duty trucks include vehicles typically used for personal travel and less
than 8500 Ibs; medium- and heavy-duty trucks include vehicles 8501 Ibs and above.
HFC emissions primarily reflect HFC-134a.
Commercial
The commercial sector is heavily reliant on electricity
for meeting energy needs, with electricity consumption for
lighting, heating, air conditioning, and operating appliances.
The remaining emissions were largely due to the direct
consumption of natural gas and petroleum products, primarily
for heating and cooking needs. Energy-related 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.
Landfills and wastewater treatment are included in this
sector, with landfill emissions decreasing since 1990, while
wastewater treatment emissions have increased slightly.
Residential
The residential sector is heavily reliant on electricity
for meeting energy needs, with electricity consumption for
lighting, heating, air conditioning, and operating appliances.
The remaining emissions were largely due to the direct
consumption of natural gas and petroleum products, primarily
for heating and cooking needs. Emissions from the residential
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. In the long-term, this sector
is also affected by population growth, regional migration
trends, and changes in housing and building attributes (e.g.,
size and insulation).
Agriculture
The agricultural sector includes a variety of processes,
including enteric fermentation in domestic livestock,
livestock manure management, and agricultural soil
management. In 2007, enteric fermentation was the largest
source of CH^ emissions in the United States, and agricultural
soil management was the largest source of N2O emissions in
the United States. This sector also includes small amounts
of CO2 emissions from fossil fuel combustion by motorized
farm equipment such as tractors.
Electricity Generation
The process of generating electricity, for consumption in
the above sectors, is the single largest source of greenhouse
gas emissions in the United States, representing 34 percent
of total U.S. emissions. Electricity generation also accounted
for the largest share of CO2 emissions from fossil fuel
combustion, approximately 42 percent in 2007. Electricity
was consumed primarily in the residential, commercial,
and industrial end-use sectors for lighting, heating, electric
motors, appliances, electronics, and air-conditioning.
Trends in Greenhouse Gas Emissions 2-25
-------
Box 2-1: Methodology for Aggregating Emissions by Economic Sector
In presenting the Economic Sectors in the annual Inventory of U.S. Greenhouse Gas Emissions and Sinks, EPA expands upon the
standard IPCC sectors common for UNFCCC reporting. EPA believes that discussing greenhouse gas emissions relevant to U.S.-specific
sectors improves communication of the report's findings.
Electricity Generation: Carbon dioxide emissions from the combustion of fossil fuels included in the EIA electric-utility fuel-consuming
sector are apportioned to this economic sector. Stationary combustion emissions of CH4 and N20 are also based on the EIA electric-utility
sector. Additional sources include C02 and N20 from waste incineration, as the majority of municipal solid waste is combusted in "trash-to-
steam" electricity generation plants. The Electricity Generation economic sector also includes SF6 from electrical transmission and distribution,
and a portion of C02 from limestone and dolomite use (from pollution control equipment installed in electricity generation plants).
Transportation: Carbon dioxide emissions from the combustion of fossil fuels included in the EIA transportation fuel-consuming sector
are apportioned to this economic sector (additional analyses and refinement of the EIA data is further explained in the Energy chapter of this
report). Additional emissions are apportioned from CH4 and N20 from mobile combustion, based on the EIA transportation sector. Substitutes
for ozone depleting substances are apportioned to this economic sector based on their specific end-uses within the source category, along
with emissions from transportation refrigeration/air-conditioning systems. Finally, C02 emissions from non-energy uses of fossil fuels identified
as lubricants for transportation vehicles are included in the Transportation economic sector.
Industry: Carbon dioxide emissions from the combustion of fossil fuels included in the EIA industrial fuel-consuming sector, minus the
agricultural use of fuel explained below, are apportioned to this economic sector. Stationary and mobile combustion emissions of CH4 and
N20 are also based on the EIA industrial sector, minus emissions apportioned to the Agriculture economic sector described below. Substitutes
for ozone depleting substances are apportioned based on their specific end-uses within the source category, with most emissions falling
within the Industry economic sector (emissions from the other economic sectors are subtracted to avoid double-counting). Additionally, all
process-related emissions from sources with methods considered within the IPCC Industrial Process guidance have been apportioned to
this economic sector. This includes the process-related emissions (i.e., emissions resulting from the processes used to make materials, and
not from burning fuels to provide power or heat) from such activities as cement production, iron and steel production and metallurgical coke
production, and ammonia production. Additionally, fugitive emissions from energy production sources, such as natural gas systems, coal
mining, and petroleum systems are included in the Industry economic sector. A portion of C02 emissions from limestone and dolomite use
(from pollution control equipment installed in large industrial facilities) are also included in the Industry economic sector. Finally, all remaining
C02 emissions from non-energy uses of fossil fuels are assumed to be industrial in nature (besides the lubricants for transportation vehicles
specified above), and are attributed to the Industry economic sector.
Agriculture: As agricultural equipment is included in ElA's industrial fuel-consuming sector surveys, additional data is used to separate
out the fuel used by agricultural equipment, to allow for accurate reporting in the Agriculture economic sector from all sources of emissions,
such as motorized farming equipment. Energy consumption estimates are obtained from Department of Agriculture survey data, in combination
with separate EIA fuel sales reports. This supplementary data is used to apportion C02 emissions from fossil fuel combustion and CH4 and
N20 emissions from stationary and mobile combustion (this data is subtracted from the Industry economic sector to avoid double-counting).
The other emission sources included in this economic sector are non-combustion sources of emissions that are included in the Agriculture
and Land Use, Land-Use Change and Forestry chapters: N20 emissions from agricultural soils, CH4from enteric fermentation (i.e., exhalation
from the digestive tracts of domesticated animals), CH4 and N20 from manure management, CH4 from rice cultivation, C02 emissions from
liming of agricultural soils and urea application, and CH4 and N20 from forest fires. Nitrous oxide emissions from the application of fertilizers
to tree plantations (termed "forest land" by the IPCC) are also included in the Agriculture economic sector.
Residential: This economic sector includes the C02 emissions from the combustion of fossil fuels reported forthe EIA residential sector.
Stationary combustion emissions of CH4 and N20 are also based on the EIA residential fuel-consuming sector. Substitutes for ozone depleting
substances are apportioned based on their specific end-uses within the source category, with emissions from residential air-conditioning
systems distributed to this economic sector. Nitrous oxide emissions from the application of fertilizers to developed land (termed "settlements"
by the IPCC) are also included in the Residential economic sector.
Commercial: This economic sector includes the C02 emissions from the combustion of fossil fuels reported in the EIA commercial
fuel-consuming sector data. Stationary combustion emissions of CH4 and N20 are also based on the EIA commercial sector. Substitutes for
ozone depleting substances are apportioned based on their specific end-uses within the source category, with emissions from commercial
refrigeration/air-conditioning systems distributed to this economic sector. Public works sources including direct CH4 from landfills and CH4
and N20 from wastewater treatment and composting are included in this economic sector.
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Box 2-2: 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 non-utilities combined—was the largest source of U.S.
greenhouse gas emissions in 2007; (4) emissions per unit of total gross domestic product as a measure of national economic activity; or
(5) emissions per capita.
Table 2-16 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 0.9 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 2-14).
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100)
Growth
Variable 1990 1995 2000 2005 2006 2007 Rate"
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Populationd
Greenhouse Gas Emissions6
'Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2008)
c Energy content-weighted values (EIA 2008a)
11 U.S. Census Bureau (2008)
e GWP-weighted values
155
134
119
119
118
117
159
135
117
118
119
115
162
137
119
120
120
117
2.9%
1.9%
1.1%
1.1%
1.1%
0.9%
Figure 2-14
U.S. Greenhouse Gas Emissions Per Capita and
Per Dollar of Gross Domestic Product
Real GDP
Population
Emissions
per capita
Emissions
per $GDP
Source: BEA (2008), U.S. Census Bureau (2008), and emission estimates in the this report.
Trends in Greenhouse Gas Emissions 2-27
-------
2.3. Indirect Greenhouse Gas
Emissions (CO, NOX, NMVOCs,
and S02)
The reporting requirements of the UNFCCC7 request
that information be provided on indirect greenhouse gases,
which include CO, NOX, NMVOCs, and SO2. These gases
do not have a direct global warming effect, but indirectly
affect 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.
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
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 CH^ 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
2-17 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.
Box 2-3: Sources and Effects of Sulfur Dioxide
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 87 percent in
2007. 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.
7 See .
8 NO,, and CO emission estimates from field burning of agricultural residues
were estimated separately, and therefore not taken from EPA (2008).
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 2-17: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
1990
1995
2000
2005
2006
2007
NO,
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Oil and Gas Activities
Incineration of Waste
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Incineration of Waste
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
Incineration of Waste
Waste
Agricultural Burning
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Incineration of Waste
Waste
Solvent Use
Agricultural Burning
NA
NA
15,612
8,757
5,857
534
321
98
39
5
2
71,672
62,519
4,778
1,744
1,439
860
324
7
2
14,562
6,292
3,881
2,035
1,450
545
243
115
NA
13,348
11,641
852
600
233
22
1
0
NA
14,701
8,271
5,445
527
316
98
38
5
2
67,453
58,322
4,792
1,743
1,438
825
323
7
2
14,129
5,954
3,867
1,950
1,470
535
239
113
NA
12,259
10,650
845
520
221
22
1
0
NA
14,250
7,831
5,445
520
314
97
37
5
2
63,875
54,678
4,792
1,743
1,438
892
323
7
2
13,747
5,672
3,855
1,878
1,470
526
234
111
NA
11,725
10,211
839
442
210
22
1
0
NA
NA (Not Available)
Note: Totals may not sum due to independent rounding.
Source: EPA (2005) except for estimates from field burning of agricultural residues.
Trends in Greenhouse Gas Emissions 2-29
-------
3. Energy
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting
for 86.3 percent of total emissions on a carbon dioxide (CO2) equivalent basis in 2007. This included 97,
35, and 14 percent of the nation's CO2, methane (CFL,), and nitrous oxide (N2O) emissions, respectively.
Energy-related CO2 emissions alone constituted 83 percent of national emissions from all sources on a CO2 equivalent
basis, while the non-CO2 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 29,195 teragrams (Tg) of CO2 were added to the atmosphere
through the combustion of fossil fuels in 2006, of which the United States accounted for about 20 percent.1 Due to their
relative importance, fossil fuel combustion-related CO2 emissions 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 of biomass and biomass-based fuels also
emits greenhouse gases. Carbon dioxide emissions from these
activities, however, are not included in national emis sions 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 separately
within the Land Use, Land-Use Change, and Forestry chapter.
Emissions of other greenhouse gases from the combustion
Figure 3-1
2007 Energy Chapter Greenhouse Gas Emission Sources
5,735.8
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion
Incineration of Waste
Energy as a Portion
of all Emissions
Abandoned Underground
Coal Mines
25
50 75 100
Tg CO, Eq.
125 150
1 Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy Annual 2006
EIA (2008).
Energy 3-1
-------
Figure 3-2
2007 U.S. Fossil Carbon Flows (Tg C02 Eq.)
NED Emissions
3
Coal Emissions
2,090
Natural Gas Emissions
1,225
NEU Emissions 122
Non-Energy Use
Carbon Sequestered
227
Fossil Fuel Stock Non-Energy
Non-Enerav Consumption Changes Use U.S.
Use Imports U.S. 25 Territories
55 Territories 8
51
Note: Totals may not sum due to independent rounding.
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
of biomass 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 Tg 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 6,170.3 Tg CO2 Eq. in 2007, an increase of 19 percent
since 1990.
Table 3-1: C02, CH4, and N20 Emissions from Energy (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 4,871.0 5,201.2
Fossil Fuel Combustion 4,708.9 5,013.9
Electricity Generation 1,809.7 1,938.9
Transportation 1,484.5 1,598.7
Industrial 834.2 862.6
Residential 337.7 354.4
Commercial 214.5 224.4
U.S. Territories 28.3 35.0
Non-Energy Use of Fuels 117.0 137.5
Natural Gas Systems 33.7 33.8
Incineration of Waste 10.9 15.7
Petroleum Systems 0.41 0.3
Wood Biomass and Ethanol Consumption3 219.3 236.8
International Bunker Fuels3 114.3 101.6
5,753.2
5,561.5
2,283.2
1,800.3
844.6
370.4
226.9
36.2
144.5
29.4
17.5
0.3
227.3
99.0
5,910.8
5,723.5
2,381.0
1,881.5
828.0
358.0
221.8
53.2
138.1
29.5
19.5
0.3
23?. 5
111.5
5,830.2
5,635.4
2,327.3
1,880.9
844.5
321.9
206.0
54.8
145.1
29.5
19.8
0.3
240.4
110.5
5,919.5
5,735.8
2,397.2
1,887.4
845.4
340.6
214.4
50.8
133.9
28.7
20.8
0.3
247.8
108.8
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-1: C02, CH4, and N20 Emissions from Energy (Tg C02 Eq.) (continued)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
International Bunker Fuels3
N20
Mobile Combustion
Stationary Combustion
Incineration of Waste
International Bunker Fuels3
265.7
129.6
84.1
33.9
7.4
6.0
4.7
0.2
57.0
43.7
12.8
0.5
1.1
251.4
132.6
67.1
32.0
7.1
8.2
4.3
0.1
67.5
53.7
13.3
0.5
0.9
239.0
130.8
60.5
30.3
6.6
7.4
3.4
0.1
67.7
52.8
14.5
0.4
0.9
206.5
106.3
57.1
28.3
6.7
5.6
2.5
0.1
51.9
36.7
14.8
0.4
1.0
205.7
104.8
58.4
28.3
6.3
5.5
2.4
0.1
48.5
33.5
14.5
0.4
1.0
205.7
104.7
57.6
28.8
6.6
5.7
2.3
0.1
45.2
30.1
14.7
0.4
1.0
Total
5,193.6
5,520.1
6,059.9
6,169.2 6,084.4 6,170.3
a 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.
Table 3-2: C02, CH4, and N20 Emissions from Energy (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 4,870,953 5,201,233 5,753,192
Fossil Fuel Combustion 4,708,918 5,013,910 5,561,515
Non-Energy Use of Fuels 116,9771 137,4601 144,473
Natural Gas Systems 33,733 33,810 29,394
Incineration of Waste 10,950 15,712 17,485
Petroleum Systems 3761 341 325
Wood Biomass and Ethanol Consumption3 219,341U 236J75U 227,276
International Bunker Fuels3 114,330 101,620 98,966
CH4 12,651 11,970 11,381
Natural Gas Systems 6,171 6,314 6,231
Coal Mining 4,003 3,193 2,881
Petroleum Systems 1,613 1,524 1,441
Stationary Combustion 3521 3401 315
Abandoned Underground Coal Mines 2881 3921 350
Mobile Combustion 2251 2071 163
International Bunker Fuels3 8 6 6\
N20 184 218 219
Mobile Combustion 141 1731 170
Stationary Combustion 411 431 47
Incineration of Waste 2 11 1
International Bunker Fuels3 333
5,910,830
5,723,477
138,070
29,463
19,532
287
231,481
111,487
9,832
5,062
2,719
1,346
318
265
121
7
167
118
48
1
3
5,830,206
5,635,418
145,137
29,540
19,824
288
240,386
110,520
9,795
4,991
2,780
1,346
300
263
115
7
156
108
47
1
3
5,919,452
5,735,789
133,910
28,680
20,786
287
247,829
108,756
9,796
4,985
2,744
1,370
315
273
109
7
146
97
47
1
3
a 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.
Energy 3-3
-------
3.1. Fossil Fuel Combustion (IPCC
Source Category 1 A)
Emissions from the combustion of fossil fuels for energy
include the gases CO2, CH4, and N2O. Given that CO2 is
the primary gas emitted from fossil fuel combustion and
represents the largest share of U.S. total emissions, CO2
emissions from fossil fuel combustion are discussed at the
beginning of this section. Following that is a discussion of
emissions of all three gases from fossil fuel combustion
presented by sectoral breakdowns. Methodologies for
estimating CO2 from fossil fuel combustion also differ from
the estimation of CH4 and N2O emissions from stationary
combustion and mobile combustion. Thus, three separate
descriptions of methodologies, uncertainties, recalculations,
and planned improvements are provided at the end of this
section. Total CO2, CH4, and N2O emissions from fossil fuel
combustion are presented in Table 3-3 and Table 3-4.
CO2 from Fossil Fuel Combustion
Carbon dioxide is the primary gas emitted from fossil
fuel combustion and represents the largest share of U.S.
total greenhouse gas emissions. Carbon dioxide emissions
from fossil fuel combustion are presented in Table 3-5.
In 2007, CO2 emissions from fossil fuel combustion
increased by 1.8 percent relative to the previous year. This
increase is primarily a result of an increase in electricity
demand, combined with a significant decrease (14.2
percent) in hydropower generation used to meet this
demand. Additionally, cooler winter and warmer summer
conditions in 2007 increased the demand for heating fuels
and contributed to the increase in the demand for electricity.
In 2007, CO2 emissions from fossil fuel combustion were
5,735.8 Tg CO2 Eq., or 22 percent above emissions in 1990
(see Table 3-5).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.
Table 3-3: C02, CH4, and N20 Emissions from Fossil Fuel Combustion (Tg C02 Eq.)
Gas
C02
CH4
N20
Total
1990
4,708.9
12.1
56.5
4,777.6
1995
5,013.9
11.5
67.0
5,092.4
2000
5,561.5
10.0
67.4
5,638.9
2005
5,723.5
9.2
51.5
5,784.2
2006
5,635.4
8.7
48.1
5,692.2
2007
5,735.8
8.9
44.8
5,789.5
Note: Totals may not sum due to independent rounding.
Table 3-4: C02, CH4, and N20 Emissions from Fossil Fuel Combustion (Gg)
Gas
1990
1995
2000
2005
2006
2007
C02
CH4
N20
4,708,918 5,013,910 5,561,515 5,723,477 5,635,418 5,735,789
578 5471 478 439 415 424
182 2161 2171 166 155 145
Note: Totals may not sum due to independent rounding.
2 An additional discussion of fossil fuel emission trends is presented in the
Trends in U.S. Greenhouse Gas Emissions chapter.
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-5: C02 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.)
Fuel/Sector
1990
1995
2000
2005
2006
2007
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
Geothermal3
1,695.9
2.9
11.8
149.5
NE
1,531.1
0.6
1,001.7
237.4
141.5
410.1
36.2
176.5
NO
2,010.9
97.4
61.2
274.6
1,448.3
101.8
27.6
0.40
1,801.9
1.7
11.1
139.6
NE
1,648.6
0.9
1,159.1
262.3
164.0
465.0
38.6
229.2
NO
2,052.6
90.5
49.3
257.9
1,560.1
60.7
34.0
0.34
12,046.4
I
126.8
2,046.4
1.0
8.2
126.8
NE
1,909.5
0.9
1,210.8
268.8
171.6
452.3
35.6
281.8
0.7
2,303.9
100.5
47.2
265.5
1,764.7
91.5
34.6
0.36
2,088.2
0.8
9.1
116.2
NE
1,958.4
3.7
1,161.4
262.0
163.1
381.8
33.2
319.9
1.3
2,473.5
95.2
49.6
330.0
1,848.2
102.3
48.2
0.38
2,057.2
0.5
6.2
114.1
NE
1,932.4
4.0
1,140.7
236.8
153.8
376.2
33.5
338.9
1.4
2,437.2
84.5
46.0
354.2
1,847.4
55.6
49.4
0.37
2,086.5
0.6
6.8
107.4
NE
1,967.6
4.1
1,216.5
256.9
163.4
385.6
35.4
373.8
1.4
2,432.4
83.2
44.2
352.5
1,852.0
55.3
45.3
0.38
Total
4,708.9
5,013.9
5,561.5
5,723.5 5,635.4 5,735.8
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.
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, size of houses, and number 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).
Carbon dioxide emissions also depend on the source of
energy and its carbon (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 as much 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
3 Based on national aggregate carbon content of all coal, natural gas, and
petroleum fuels combusted in the United States.
using nuclear or renewable energy sources (e.g., wind) can
essentially eliminate emissions (see Box 3-2). Table 3-6 shows
annual changes in emissions during the last five years for coal,
petroleum, and natural gas in selected sectors.
In the United States, 85 percent of the energy consumed
in 2007 was produced through the combustion of fossil fuels
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 (7 percent), primarily hydroelectric power and biofuels
(FJA 2008a). Specifically, petroleum supplied the largest share
of domestic energy demands, accounting for an average of 42
percent of total fossil-fuel-based energy consumption in 2007.
Natural gas and coal followed in order of importance, accounting
for 30 and 28 percent of total consumption, respectively.
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 consumed in all end-use
sectors except transportation (see Figure 3-5) (ElA 2008a).
Energy 3-5
-------
Table 3-6: 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"
2003 to 2004
11.4
18.4
2.0
51.1
-13.7
-5.1
1.2
-17.8
64.4
0.6%
6.6%
2.0%
2.9%
-4.9%
-2.9%
1.0%
-4.2%
1.1%
2004 to 2005
40.8
22.7
2.2
19.9
-0.5
-5.7
-2.4
-28.3
54.2
2.1%
7.6%
2.2%
1.1%
-0.2%
-3.4%
-2.0%
-6.9%
1.0%
2005 to 2006
-26.0
19.0
-46.7
-0.8
-25.2
-9.3
-2.1
-5.6
-88.1
-1.3%
5.9%
-45.6%
0.0%
-9.6%
-5.7%
-1.8%
-1.5%
-1.5%
2006(02007
35.3
34.9
-0.3
4.6
20.1
9.6
-6.7
9.4
100.4
1.8%
10.3%
-0.6%
0.2%
8.5%
6.2%
-5.9%
2.5%
1.8%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
Figure 3-3
2007 U.S. Energy Consumption by Energy Source
Renewable
Nuclear
Natural Gas
Coal
Petroleum
7%
22%
22%
39%
Figure 3-4
U.S. Energy Consumption (Quadrillion Btu)
120-1
100-
.2
S
60-
20-
O-1
Total Energy
Fossil Fuels
Renewable & Nuclear
Note: Expressed as gross calorific values.
Figure 3-5
2007 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
2,500 -|
2,000 -
1,500 -
3
' 1,000 -
500 -
0 -1
Natural Gas
Petroleum
I Coal
Relative Contribution
by Fuel Type
•=
1
Note: Electricity generation also includes emissions of less than 0.5 Tg C02 Eq. from
geothermal-based electricity generation.
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-
CO2 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
of the C in fossil fuels used to produce energy is eventually
converted to atmospheric CO2.
4 See the sections entitled Stationary Combustion and Mobile Combustion
in this chapter for information on non-CO2 gas emissions from fossil fuel
combustion.
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Box 3-1: Weather and Non-Fossil Energy Effects on C02 from Fossil Fuel Combustion Trends
In 2007, weather conditions became much cooler in the winter and slightly warmer in the summer, compared to 2006. Although winter
conditions were cooler in 2007 compared to 2006, the winter was warmer than normal, with heating degree days in the United States 6
percent below normal (see Figure 3-6). Cooler winter conditions compared to 2006 led to an increase in demand for heating fuels. Although
summer conditions were slightly warmer in 2007 compared to 2006, summer temperatures were substantially warmer than usual, with
cooling degree days 13 percent above normal (see Figure 3-7) (EIA 2008f).5 As a result, the demand for electricity increased due to warmer
summer conditions compared to 2006.
Figure 3-6
Annual Deviations from Normal Heating Degree Days for the United States (1950-2007)
15 -i
Si 10-
;i 5-
»E
it o
*l -5 -
IS -10 -
o^
-15 -
Normal (4,524 Heating Degree Days)
• I •• _•-••
99% Confidence
nn ™
CO CO O CM
Note: Climatological normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1971 through 1990.
Figure 3-7
Annual Deviations from Normal Cooling Degree Days for the United States (1950-2007)
99% Confidence
11 '' I Normal (1,242 Cooling Degree Days)
Note: Climatological normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1971 through 1990.
s s s s
Although no new U.S. nuclear power plants have been
constructed in recent years, the utilization (i.e., capacity factors6)
of existing plants in 2007 remained high at just over 90 percent.
Electricity output by hydroelectric power plants decreased in 2007
by approximately 14 percent. Electricity generated by nuclear plants
in 2007 provided almost 3 times as much of the energy consumed
in the United States as hydroelectric plants (EIA 2008a). 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 (1974-2007)
80-1
60-
40-
20-
0J
§ s s s
& & & &
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 effect 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 2008a).
Energy 3-7
-------
Fossil Fuel Combustion Emissions
by Sector
In addition to the CO2 emitted from fossil fuel
combustion, CK4 and N2O are emitted from stationary and
mobile combustion as well. Table 3-7 provides an overview
of the CO2, CH4, and N2O emissions from fossil fuel
combustion by sector.
Other than CO2, gases emitted from stationary combustion
include the greenhouse gases CtLj and N2O and the indirect
greenhouse gases NOX, CO, and NMVOCs.7 CJ^ and N2O
emissions from stationary combustion sources depend
upon fuel characteristics, size and vintage, along with
combustion technology, pollution control equipment, ambient
environmental conditions, and operation and maintenance
practices. Nitrous oxide 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. Methane emissions from
stationary combustion are primarily a function of the CH^
content of the fuel and combustion efficiency.
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 from mobile combustion
are closely related to fuel characteristics, air-fuel mixes,
combustion temperatures, and the use of pollution control
equipment. Nitrous oxide from mobile sources, 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. Methane and
Table 3-7: C02, CH4, and N20 Emissions from Fossil Fuel Combustion by Sector (Tg C02 Eq.)
End-Use Sector/Gas
1990
1995
2000
2005
2006
2007
Electricity Generation
C02
CH4
N20
Transportation
C02
CH4
N20
Industrial
C02
CH4
N20
Residential
C02
CH4
N20
Commercial
C02
CH4
N20
U.S. Territories3
1,818.3
1,809.7
0.6
8.1
1,532.9
1,484.5
4.7
43.7
838.9
834.2
1.5
3.2
343.2
337.7
4.4
1.1
215.8
214.5
0.9
0.4
28.4
1,938.9 2,283.2
0.61 0.71
Rfi mn
1,948.0
1,938.9
0.6
8.6
1,656.7
1,598.7
4.3
53.7
867.5
862.6
1.6
3.3
359.4
354.4
4.0
1.0
225.7
224.4
0.9
0.4
35.1
2,293.8
2,283.2
0.7
10.0
1,856.5
1,800.3
3.4
52.8
849.4
844.6
1.6
3.2
374.7
370.4
3.4
0.9
228.2
226.9
0.9
0.3
36.3
2,392.1
2,381.0
0.7
10.3
1,920.7
1,881.5
2.5
36.7
832.5
828.0
1.5
3.1
362.5
358.0
3.5
0.9
223.0
221.8
0.9
0.3
53.4
2,338.1
2,327.3
0.7
10.1
1,916.8
1,880.9
2.4
33.5
849.2
844.5
1.5
3.2
325.9
321.9
3.2
0.8
207.2
206.0
0.8
0.3
55.0
2,408.2
2,397.2
0.7
10.3
1,919.8
1,887.4
2.3
30.1
849.9
845.4
1.5
3.1
345.1
340.6
3.5
0.9
215.5
214.4
0.8
0.3
51.0
Total
4,777.6
5,092.4
5,638.9
5,784.2 5,692.2 5,789.5
aU.S. Territories are not apportioned by sector, and emissions are total greenhouse gas emissions from all fuel combustion sources.
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.
7 Sulfur dioxide (SO2) emissions from stationary combustion are addressed
in Annex 6.3.
3-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
NMVOC emissions from motor vehicles are a function of the
CtLj 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).
An alternative method of presenting combustion
emissions is to allocate emissions associated with electricity
generation to the sectors in which it is used. Four end-use
sectors were defined: industrial, transportation, residential,
and commercial. In Table 3-8, electricity generation emissions
have been distributed to each end-use sector based upon the
sector's share of national electricity consumption, with the
exception of CH4 and N2O from transportation.8 Emissions
from U.S. territories are also calculated separately due to a
lack of end-use-specific consumption data. This method of
distributing emissions assumes that each sector consumes
electricity generated from an equally carbon-intensive mix
of fuels and other energy sources. Table 3-7 and Table 3-8
summarize CO2, CH4, and N2O emissions from direct fossil
fuel combustion and pro-rated electricity generation emissions
from electricity consumption by end-use sector. The following
discussions for stationary combustion sources focus on direct
emissions, as presented in Table 3-7, while the discussion of
transportation and mobile combustion sources focuses on the
alternative method as presented in Table 3-8.
Stationary Combustion
The direct combustion of fuels by stationary sources
in the electricity generation, industrial, commercial, and
residential sectors represent the greatest share of U.S.
greenhouse gas emissions. Table 3-9 presents CO2 emissions
from fossil fuel combustion by stationary sources. The CO2
emitted is closely linked to the type of fuel being combusted
in each sector (see Methodology section for CO2 from
fossil fuel combustion). Other than CO2, gases emitted
from stationary combustion include the greenhouse gases
CH4 and N2O. Table 3-10 and Table 3-11 present CH4 and
N2O emissions from the combustion of fuels in stationary
sources. Methane and N2O emissions from stationary
Table 3-8: C02, CH4, and N20 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)a
End-Use Sector/Gas
Transportation
C02
CH4
N20
Industrial
C02
CH4
N20
Residential
C02
CH4
N20
Commercial
C02
CH4
N20
U.S. Territories"
Total
1990
1,536.0
1,487.5
;l
43.7
1,524.7
1,516.8
1.7
6.2!
935.4
927.1
4.6
3.7
753.0
749.2
1
2.8
28.4
4,777.6
1995
1,659.7
1,601.7
4.3
53.7
1,583.8
1,575.5
1.8
6.5l
1,001.3
993.3
4.2
3.8
812.5
808.5
1.ll
2.9 1
35.1
5,092.4
2000
1,860.0
1,803.7
3.4
52.8
1,638.1
1,629.6
1.8
6.7
1,136.1
1,128.2
3.6 1
42|
968.5
963.8
1.ll
3.6 1
36.3
5,638.9
2005
1,925.4
1,886.2
2.5
36.7
1,566.4
1,558.5
1.7
6.2
1,215.6
1,207.2
3.8
4.6
1,023.3
1,018.4
1.1
3.8
53.4
5,784.2
2006
1,921.3
1,885.4
2.4
33.6
1,558.7
1,550.7
1.7
6.2
1,153.8
1,145.9
3.4
4.4
1,003.4
998.6
1.1
3.7
55.0
5,692.2
2007
1,924.6
1,892.2
2.3
30.1
1,561.2
1,553.4
1.7
6.1
1,206.4
1,198.0
3.8
4.6
1,046.4
1,041.4
1.1
3.9
51.0
5,789.5
'Electricity generation emissions have been distributed to each end-use sector based upon the sector's share of national electricity consumption.
bU.S. Territories are not apportioned by sector, and emissions are total greenhouse gas emissions from all fuel combustion sources.
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.
8 Separate calculations were performed for transportation-related CH4 and
N2O. The methodology used to calculate these emissions are discussed in
the mobile combustion section.
Energy 3-9
-------
Table 3-9: C02 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
1990
1995
2000
2005
2006
2007
Electricity Generation
Coal
Natural Gas
Fuel Oil
Geothermal
Industrial
Coal
Natural Gas
Fuel Oil
Commercial
Coal
Natural Gas
Fuel Oil
Residential
Coal
Natural Gas
Fuel Oil
U.S. Territories3
Coal
Natural Gas
Fuel Oil
1,809.7
1,531.1
176.5
101.8
0.4
834.2
149.5
410.1
274.6
214.5
11.8
141.5
61.2
337.7
2.9
237.4
97.4
28.3
0.6
NO
27.6
1,938.9
1,648.6
229.2
60.7
0.3
862.6
139.6
465.0
257.9
224.4
11.1
164.0
49.3
354.4
1.7
262.3
90.5
35.0
0.9
NO
34.0
2,283.2
1,909.5
281.8
91.5
0.4
844.6
126.8
452.3
265.5
226.9
8.2
171.6
47.2
370.4
1.0
268.8
100.5
36.2
0.9
0.7
34.6
2,381.0
1,958.4
319.9
102.3
0.4
828.0
116.2
381.8
330.0
221.8
9.1
163.1
49.6
358.0
0.8
262.0
95.2
53.2
3.7
1.3
48.2
2,327.3
1,932.4
338.9
55.6
0.4
844.5
114.1
376.2
354.2
206.0
6.2
153.8
46.0
321.9
0.5
236.8
84.5
54.8
4.0
1.4
49.4
2,397.2
1,967.6
373.8
55.3
0.4
845.4
107.4
385.6
352.5
214.4
6.8
163.4
44.2
340.6
0.6
256.9
83.2
50.8
4.1
1.4
45.3
Total
4,708.9
5,013.9
5,561.5
5,723.5 5,635.4 5,735.8
NO (Not Occurring)
aU.S. Territories are not apportioned by sector, and emissions from all fuel combustion sources are presented in this table.
Note: Totals may not sum due to independent rounding.
combustion sources depend upon fuel characteristics, size
and vintage, along with combustion technology, pollution
control equipment, ambient environmental conditions,
and operation and maintenance practices. Nitrous oxide
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. Methane emissions from stationary combustion
are primarily a function of the CK4 content of the fuel and
combustion efficiency. Please refer to Table 3-7 for the
corresponding presentation of all direct emission sources of
fuel combustion.
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. Methane
and N2O accounted for a small portion of emissions from
electricity generation, representing less than 0.1 percent
and 0.4 percent, respectively. Electricity generation also
accounted for the largest share of CO2 emissions from
fossil fuel combustion, approximately 42 percent in 2007.
Methane and N2O from electricity generation represented 8
and 23 percent of emissions from fossil fuel combustion in
2007. 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 3-9).
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) places 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
3-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-10: CH4 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
1990
1995
2000
2005
2006
2007
Electricity Generation
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
0.6
0.3
0.1
0.1
0.1
1.5
0.3
0.2
0.2
0.9
0.91
0.2
0.3
0.4
4.4
0.2
0.3
0.4
3.5
7.4
6.7
0.7
0.4
+
0.1
0.1
1.5
0.3
0.2
0.1
0.9
0.8
+
0.1
0.3
0.4
3.2
+
0.3
0.4
2.5
0.1
+
0.1
6.3
0.7
0.4
+
0.1
0.1
1.5
0.2
0.2
0.1
0.9
0.8
+
0.1
0.3
0.4
3.5
+
0.3
0.5
2.8
0.1
+
0.1
6.6
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
the production of electricity,9 while the other sectors consist
of those producers that indicate their primary business is
something other than the production of electricity.
The industrial, residential, and commercial end-use
sectors, as presented in Table 3 -8, were reliant on electricity for
meeting energy needs. The residential and commercial end-use
sectors were especially reliant on electricity consumption for
lighting, heating, air conditioning, and operating appliances.
Electricity sales to the residential and commercial end-use
sectors in 2007 increased about 3 percent in the residential
and 3.3 percent in the commercial sectors. The trend in the
commercial sector can largely be attributed to the growing
economy (2.0 percent), which led to increased demand for
electricity. The increase is also attributed to an increase in air
9 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).
conditioning-related electricity consumption in the residential
and commercial sectors that occurred as a result of the warmer
summer compared to 2006. In 2007, the amount of electricity
Figure 3-9
Electricity Generation Retail Sales by
End-Use Sector (1974-2007)
1,600 -i
1,400 -
1,200 -
1,000 -
800-
600-
400-
Residential
Industrial
r-r-r-ooooooooooo>
a>a>oooo
0>0>OOOO
Note: The transportation end-use sector consumes minor qualities of electricity.
Energy 3-11
-------
Table 3-11: N20 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
1990
1995
2000
2005
2006
2007
Electricity Generation
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
8.1
7.6
0.2
0.1
0.2
3.2
0.7
0.5
0.2
1.7
0.4
0.1
0.2
a!
0.3
8.6
8.1
0.1
0.1
0.1
3.31
0.7
0.4
0.3
1.9
0.4
0.1
0.1
a!
"
0.2
0.1
0.6
10.0
9.4
0.2
0.2
0.2
3.2
0.6
0.4
0.3
1.9
0.3
,1
a!
0.9
0.3
0.1
0.5
10.3
9.7
0.2
0.2
0.2
3.1
0.6
0.6
0.2
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
10.1
9.5
0.1
0.2
0.2
3.2
0.6
0.6
0.2
1.8
0.3
+
0.1
0.1
0.1
0.8
+
0.2
0.1
0.5
0.1
+
0.1
10.3
9.7
0.1
0.2
0.2
3.1
0.5
0.6
0.2
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.2
0.1
0.5
0.1
+
0.1
Total
13.3
14.5
14.8
14.5
14.7
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
generated (in kWh) increased by 2.1 percent from the previous
year. This growth is due to the growing economy, expanding
industrial production, and warmer summer conditions
compared to 2006. As a result, CO2 emissions from the electric
power sector increased by 3.0 percent as the consumption
of coal and natural gas for electricity generation increased.
Coal and natural gas consumption for electricity generation
increased by 1.8 percent and 10.3 percent, respectively, in
2007, and nuclear power increased by just over 2 percent. As
a result of the significant increase in natural gas consumption,
C intensity from direct fossil fuel combustion decreased
slightly overall in 2007 (see Table 3-15). Coal is consumed
primarily by the electric power sector in the United States,
which accounted for 94 percent of total coal consumption for
energy purposes in 2007. Spurred by a 14.2-percent decrease
in hydropower, total renewable electricity generation fell by
8.9 percent in 2007. However non-hydropower renewable
generation grew by 6.8 percent, thus preventing an even greater
increase in emissions.
Industrial End-Use Sector
The industrial sector accounted for 15 percent of CO2
emissions from fossil fuel combustion, 17 percent of CH^
emissions from fossil fuel combustion, and 7 percent of N2O
emissions from fossil fuel combustion. Carbon dioxide, CH4,
and N2O emissions resulted from the direct consumption of
fossil fuels for steam and process heat production.
The industrial sector, per the underlying energy
consumption data from EIA, 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 2008a and EIA 2005).
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
In theory, emissions from the industrial sector should be
highly correlated with economic growth and industrial output,
but heating of industrial buildings and agricultural energy
consumption are also affected by weather conditions.10 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 2006 to 2007, total industrial production and
manufacturing output increased by 1.7 and 1.8 percent,
respectively (FRB 2007). Over this period, output increased
for chemicals, and food, but decreased for petroleum
refineries, paper, primary metals, and nonmetallic mineral
products (see Figure 3-10).
Despite the growth in industrial output (60 percent)
and the overall U.S. economy (62 percent) from 1990 to
2007, CO2 emissions from the industrial sector increased
Figure 3-10
Industrial Production Indices (Index 2002=100)
120
110
100
70
60
120
110
100
90
120-,
110-
100-
70-1
120-|
110-
100-
90-
Total
Industrial
Incli
Paper
Total excluding Computers,
Communications Equipment,
and Semiconductors
Stone, Clay & Glass Products
Chemicals
Primary Metals
S S S
Petroleum Refineries
S 5 S S S S
10 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.
by only 1.3 percent over that time. A number of factors are
believed to have caused this disparity between rapid growth
in industrial output and only minor growth 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 2007, CO2, CH4, and N2O emissions from fossil
fuel combustion and electricity use within the industrial
end-use sectors totaled 1,561.2 Tg CO2 Eq., or 0.2 percent
above 2006 emissions.
Residential and Commercial End-Use Sectors
The residential and commercial sectors accounted for
an average 6 and 4 percent of CO2 emissions from fossil
fuel combustion, 40 and 9 percent of CH4 emissions from
fossil fuel combustion, and 2 and 1 percent of N2O emissions
from fossil fuel combustion, respectively. Emissions from
these sectors were largely due to the direct consumption of
natural gas and petroleum products, primarily for heating and
cooking needs. Coal consumption was a minor component
of energy use in both of these end-use sectors. In 2007, CO2,
CH4, and N2O emissions from fossil fuel combustion and
electricity use within the residential and commercial end-
use sectors were 1,206.4 Tg CO2 Eq. and 1,046.4 Tg CO2
Eq., respectively. Total CO2, CH4, and N2O emissions from
the residential sector increased by 4.4 percent in 2007, with
emissions in 2007 from the commercial sector 4.1 percent
higher than in 2006.
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. In the long-term, both
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
75 and 76 percent of the direct fossil fuel CO2 emissions from
the residential and commercial sectors, respectively. In 2007,
natural gas CO2 emissions increased by 8.5 percent and 6
percent, respectively, in each of these sectors. The increase
in emissions in both sectors is a result of cooler winter
conditions in the United States compared to 2006.
Energy 3-13
-------
U.S. Territories
Emissions from U.S. territories are based on the fuel
consumption in American Samoa, Guam, Puerto Rico, U.S.
Virgin Islands, Wake Island, and other U.S. Pacific Islands.
As described in the Methodology section for CO2 from fossil
fuel combustion, this data is collected separately from the
sectoral-level data available for the general calculations. As
sectoral information is not available for U.S. Territories, CO2,
CH4, and N2O emissions are presented in Table 3-7 through
3-11, though the emissions will include some transportation
and mobile combustion sources.
Transportation and Mobile Combustion
This discussion of transportation emissions follows the
alternative method of presenting combustion emissions by
allocating emissions associated with electricity generation to
the transportation end-use sector, as presented in Table 3-8.
For direct emissions from transportation (i.e., not including
electricity consumption), please see Table 3-7.
Transportation End-Use Sector
The transportation end-use sector accounted for 1,924.6
Tg CO2 Eq. in 2007, which represented 33 percent of CO2
emissions from fossil fuel combustion, 26 percent of CH4
emissions from fossil fuel combustion, and 67 percent of N2O
emissions from fossil fuel combustion, respectively. Fuel
purchased in the U.S. for international aircraft and marine
travel accounted for an additional 108.8 Tg CO2 in 2007;
these emissions are recorded as international bunkers and are
not included in U.S. totals according to UNFCCC reporting
protocols. Among domestic transportation sources, light duty
vehicles (including passenger cars and light-duty trucks)
represented 61 percent of CO2 emissions, medium- and
heavy-duty trucks 22 percent, commercial aircraft 8 percent,
and other sources 10 percent. See Table 3-12 for a detailed
breakdown of CO2 emissions by mode and fuel type.
From 1990 to 2007, transportation emissions rose by 29
percent due, in large part, to increased demand for travel and
the stagnation of fuel efficiency across the U.S. vehicle fleet.
The number of vehicle miles traveled by light-duty motor
vehicles (passenger cars and light-duty trucks) increased
40 percent from 1990 to 2007, as a result of a confluence
of factors including population growth, economic growth,
urban sprawl, and low fuel prices over much of this period.
A similar set of social and economic trends has led to a
significant increase in air travel and freight transportation
by both air and road modes during the time series.
Almost all of the energy consumed for transportation
was supplied by petroleum-based products, with more than
half being related to gasoline consumption in automobiles
and other highway vehicles. Other fuel uses, especially diesel
fuel for freight trucks and jet fuel for aircraft, accounted for
the remainder. The primary driver of transportation-related
emissions was CO2 from fossil fuel combustion, which
increased by 29 percent from 1990 to 2007. This rise in
CO2 emissions, combined with an increase in HFCs from
virtually no emissions in 1990 to 67.0 Tg CO2 Eq. in 2007,
led to an increase in overall emissions from transportation
activities of 28 percent.
Fossil Fuel Combustion C02 Emissions
from Transportation
Domestic transportation CO2 emissions increased by
27 percent (404.7 Tg CO2 Eq.) between 1990 and 2007, an
annualized increase of 1.5 percent. Since 2005, the growth
rate of emissions has slowed considerably; transportation
CO2 emissions increased by just 0.3 percent in total between
2005 and 2007. Almost all of the energy consumed by the
transportation sector is petroleum-based, including motor
gasoline, diesel fuel, jet fuel, and residual oil. Transportation
sources also produce CFLj and N2O; these emissions are
included in Table 3-13 and Table 3-14 in the "Mobile
Combustion" section. Annex 3.2 presents total emissions
from all transportation and mobile sources, including CO2,
N20, CFl4, and HFCs.
Carbon dioxide emissions from passenger cars and light-
duty trucks totaled 1,147.0 Tg CO2 Eq. in 2007, an increase
of 21 percent (197.5 Tg CO2 Eq.) from 1990. CO2 emissions
from passenger cars and light-duty trucks peaked at 1,181.3 Tg
CO2 Eq.in 2004, and since then have declined about 3 percent.
Over the 1990s through early this decade, growth in vehicle
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-12: C02 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg C02 Eq.)a
Fuel/Vehicle Type
1990
1995
2000
2005
2006
2007
Gasoline
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty Trucks"
Buses
Motorcycles
Recreational Boats
Distillate Fuel Oil (Diesel)
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty Trucks"
Buses
Rail
Recreational Boats
Ships and Other Boats
International Bunker Fuels0
Jet Fuel
Commercial Aircraft
Military Aircraft
General Aviation Aircraft
International Bunker Fuels0
Aviation Gasoline
General Aviation Aircraft
Residual Fuel Oil
Ships and Other Boatsd
International Bunker Fuels0-"
Natural Gas
Passenger Cars
Light-Duty Trucks
Buses
Pipelines
LPG
Light-Duty Trucks
Medium- and Heavy-Duty Trucks"
Buses
Electricity
Rail
982.7
621.0
308.9
38.7
0.3
1.7
12.1
261.2
7.8
11.3
188.3
7.9
35.1
1.9
8.8
11.6
176.2
135.5
34.4
6.4
46.4
3.1
3.1
23.7
23.7
56.4
36.2
36.2
1.4
0.5
0.8
3.0
3.0
1,038.9
597.0
389.9
35.8
0.4
1.8
14.1
315.9
7.7
14.7
234.9
8.6
39.2
2.3
8.6
9.2
170.9
141.6
23.9
5.4
51.2
2.7
2.7
30.5
30.5
41.2
38.6
"
0.1
38.5
1.1
0.5
0.5
3.0
3.0
1,135.7
639.9
446.0
36.0
0.4
1.8
11.6
394.7
3.6
19.8
305.1
10.1
41.7
2.7
11.7
6.3
196.1
166.0
20.7
9.3
57.7
2.5
2.5
34.9
34.9
35.0
35.6
0.4
35.2
0.7
0.4
0.2
3.4
1181.1
654.2
476.0
34.7
0.4
1.6
14.2
453.0
4.2
25.5
356.5
10.6
45.1
3.1
8.0
9.3
189.9
158.2
17.8
13.9
56.4
2.4
2.4
20.2
20.2
45.8
33.2
0.8
32.4
1.7
1.3
0.4
+
4.7
4.7
1,169.7
630.3
487.9
35.3
0.4
1.9
14.0
464.7
4.1
26.4
365.4
10.9
47.3
3.2
7.4
8.7
185.0
153.9
16.1
15.0
54.6
2.3
2.3
24.1
24.1
47.2
33.5
0.8
32.6
1.6
1.2
0.5
+
4.5
4.5
1,166.7
620.9
493.9
35.6
0.4
2.0
13.8
470.6
4.1
26.9
371.3
10.9
46.0
3.3
8.1
8.1
185.3
153.6
15.8
15.8
52.7
2.2
2.2
25.6
25.6
47.9
35.4
0.8
34.6
1.6
1.2
0.5
+
4.8
4.8
Total
Total (Including Bunkers)0
1,487.5
1,601.7
1,703.3
1,803.7
1,902.7
1,886.2 1,885.4 1,892.2
1,997.6 1,995.9 2,000.9
+ Less than 0.05 Tg C02 Eq.
aThis table does not include emissions from non-transportation mobile sources, such as agricultural equipment and construction/mining 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 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.
11 Fluctuations in emission estimates from the combustion of residual fuel oil are associated with fluctuations in reported fuel consumption and may reflect
data collection problems.
Note: Totals may not sum due to independent rounding.
Energy 3-15
-------
travel substantially outweighed improvements in vehicle fuel
economy; however, the rate of Vehicle Miles Traveled (VMT)
growth slowed considerably starting in 2005 while average
vehicle fuel economy increased. Among new vehicles sold
annually, average fuel economy gradually declined from 1990
to 2004 (Figure 3-11), reflecting substantial growth in sales of
light-duty trucks—in particular, growth in the market share
of sport utility vehicles—relative to passenger cars (Figure
3-12). New vehicle fuel economy improved beginning in 2005,
largely due to higher light-duty truck fuel economy standards,
which have risen each year since 2005. The overall increase in
fuel economy is also due to a slightly lower light-duty truck
market share, which peaked in 2004 at 52 percent and declined
to 48 percent in 2007.
Medium- and heavy-duty truck11 CO2 emissions
increased by 79 percent (179.9 Tg CO2 Eq.) from 1990 to
2007, representing the largest percentage increase of any
major transportation mode. This increase was largely due to
a substantial increase in truck freight movement, as medium-
Figure 3-11
Sales-Weighted Fuel Economy of New Passenger Cars
and Light-Duty Trucks, 1990-2007
25-
24-
23-
= 22-
_o
I 21-
» 20'
18-
17-
16-
15-
Figure3-12
Sales of New Passenger Cars and
Light-Duty Trucks, 1990-2007
and heavy-duty truck VMT increased by 55 percent. Carbon
dioxide from the domestic operation of commercial aircraft
increased by 13 percent (18.2 Tg CO2 Eq.) from 1990 to
2007, well below the growth in travel activity. The operational
efficiency of commercial aircraft improved substantially
because of a growing percentage of seats occupied per flight,
improvements in the fuel efficiency of new aircraft, and the
accelerated retirement of older, less fuel efficient aircraft.
Across all categories of aviation,12 CO2 emissions increased
by 5.1 percent (9.0 Tg CO2 Eq.) between 1990 and 2007.
This overall increase includes a 57 percent (18.6 Tg CO2 Eq.)
decrease in emissions from domestic military operations. For
further information on all greenhouse gas emissions from
transportation sources, please refer to Annex 3.2.
Fossil Fuel Combustion CH4 and N20 Emissions
from Mobile Sources
Mobile combustion includes emissions of CH4 and
N2O from all transportation sources identified in the U.S.
Inventory with the exception of pipelines, which are
stationary; mobile sources also include non-transportation
sources such as construction/mining equipment, agricultural
equipment, vehicles used off-road, and other sources (e.g.,
snowmobiles, lawnmowers, etc.). Annex 3.2 includes a
11 Includes "medium- and heavy-duty trucks" fueled by gasoline, diesel
and LPG.
12 Includes consumption of jet fuel and aviation gasoline. Does not include
aircraft bunkers, which are not accounted for in national emission totals.
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-13: CH4 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel/Vehicle Type3
1990
1995
2000
2005
2006
2007
Gasoline On-Road 4.2
Passenger Cars 2.6
Light-Duty Trucks 1.4
Medium- and Heavy-Duty Trucks and Buses 0.2
Motorcycles +
Diesel On-Road +
Passenger Cars +
Light-Duty Trucks +
Medium- and Heavy-Duty Trucks and Buses +
Alternative Fuel On-Road +
Non-Road 0.5
Ships and Other Boats 0.1
Rail 0.1
Agricultural Equipment" 0.1
Construction/Mining Equipment0 +
Aircraft 0.2
Otherd 0.1
3.8
2.1
1.4
0.2
j
0.51
0.1
0.1
0.1
0.1
0.1
0.1
2.8
1.6
1.1
0.6 1
0.1
0.1
0.1
0.1
0.2
0.1
1.9
1.1
0.7
0.1
0.1
0.6
0.1
0.1
0.1
0.1
0.2
0.1
1.7
1.0
0.6
0.1
0.1
0.6
0.1
0.1
0.1
0.1
0.1
0.1
1.6
0.9
0.6
0.1
0.1
0.6
0.1
0.1
0.1
0.1
0.1
0.1
Total
4.7
4.3
3.4
2.5
2.4
2.3
+ Less than 0.05 Tg C0? Eq.
aSee Annex 3.2 for definitions of on-road vehicle types.
b Includes equipment, such as tractors and combines, as well as fuel consumption from trucks that are used off-road in agriculture.
c Includes equipment, such as cranes, dumpers, and excavators, as well as fuel consumption from trucks that are used off-road in construction.
11 "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment, as well as fuel consumption from trucks that are used off-road for commercial/industrial purposes.
Note: Totals may not sum due to independent rounding.
summary of all emissions from both transportation and
mobile sources. Table 3-13 and Table 3-14 provide CK4 and
N2O emission estimates in Tg CO2 Eq.13
Mobile combustion was responsible for a small portion
of national CH4 emissions (0.4 percent) but was the second
largest source of U.S. N2O emissions (10 percent). From 1990
to 2007, mobile source CFLj emissions declined by 52 percent,
to 2.3 Tg CO2 Eq. (109 Gg), due largely to control technologies
employed in on-road vehicles since the mid-1990s to reduce
CO, NOX, NMVOC, and CH4 emissions. Mobile source
emissions of N2O decreased by 31 percent, to 30.1 Tg CO2
Eq. (97 Gg). 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 45 percent decrease in mobile source N2O emissions from
Figure 3-13
Mobile Source CH,, and N,0 Emissions
60-
50-
40-
30-
20-
10-
0-
CH4
i— CM eo
1998 to 2007 (Figure 3-13). Overall, CFLj and N2O emissions
were predominantly from gasoline-fueled passenger cars and
light-duty trucks.
13 See Annex 3.2 for a complete time series of emission estimates for 1990
through 2007.
Energy 3-17
-------
Table 3-14: N20 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel/Vehicle Type3
1990
1995
2000
2005
2006
2007
Gasoline On-Road 40.1 49.8 48.4
Passenger Cars 25.4 26.9 25.2
Light-Duty Trucks 14.1 22.1 22.4
Medium-and Heavy-Duty Trucks and Buses 0.6 0.71 0.9
Diesel On-Road 0.2 0.3 0.3
Passenger Cars +1 +1 +
Light-Duty Trucks +1 +1 +
Medium-and Heavy-Duty Trucks and Buses 0.2 0.2 0.3
Alternative Fuel On-Road 0.11 0.11 0.1
Non-Road 3.4 3.61 4.0
Ships and Other Boats 0.4! 0.4! 0.5
Agricultural Equipment" 0.2! 0.31 0.3
Construction/Mining Equipment0 0.3 0.41 0.4
Otherd 0.4l O.sl 0.5
32.1
17.7
13.6
0.8
+
0.3
0.3
0.2
4.1
0.4
0.4
0.4
0.5
1.9
0.6
29.0
15.7
12.5
0.7
+
0.3
0.3
0.2
4.1
0.4
0.4
0.4
0.5
1.8
0.6
25.5
13.7
11.1
0.7
+
0.3
0.3
0.2
4.1
0.4
0.4
0.4
0.5
1.8
0.6
Total
43.7
53.7
52.8
36.7
33.5
30.1
+ Less than 0.05 Tg C0? Eq.
aSee Annex 3.2 for definitions of on-road vehicle types.
b Includes equipment, such as tractors and combines, as well as fuel consumption from trucks that are used off-road in agriculture.
c Includes equipment, such as cranes, dumpers, and excavators, as well as fuel consumption from trucks that are used off-road in construction.
11 "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment,
commercial equipment, and industrial equipment, as well as fuel consumption from trucks that are used off-road for commercial/industrial purposes.
Note: Totals may not sum due to independent rounding.
CO2 from Fossil Fuel Combustion
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 published supplemental
tables on petroleum product detail (EIA 2008b). The
EIA does not include territories in its national energy
statistics, so fuel consumption data for territories were
collected separately from Grillot (2008).14
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, andlosses). The resulting
quantities are referred to as "apparent consumption."
The data collected in the United States by EIA on an
annual basis and used in this Inventory are predominantly
from mid-stream or conversion energy consumers
such as refiners and electric power generators. These
annual surveys are supplemented with end-use energy
consumption surveys, such as the Manufacturing Energy
Consumption Survey, that are conducted on a periodic
14Fuel 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 51 Tg CO2
Eq. in 2007.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
basis (every 4 years). These consumption data sets help
inform the annual surveys to arrive at the national total
and sectoral breakdowns for that total.15
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 standards, which
are to report energy statistics in terms of net calorific
values (NCV) (i.e., lower heating values).16
2. Subtract uses accounted for in the Industrial
Processes chapter. Portions of the fuel consumption
data for seven fuel categories—coking coal, distillate
fuel, 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 AISI (1995 through 2008), CVR
Energy (2008), Corathers (2008), U.S. Census Bureau
(2008), EIA (2008g), EIA (2001), Smith, G. (2007),
USGS (2008), USGS (1995, 1998, 2000 through
2002), USGS (1995), USGS (1991a through 2007a),
USGS (1991b through 2007b), USGS (1991 through
2005), and USGS (1995 through 2006).17
3. Adjust for biofuels, conversion offossilfuels, 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
industrial coal, and is currently included in EIA statistics
for both coal and natural gas. Therefore, synthetic natural
15 See IPCC Reference Approach for estimating CO2 emissions from fossil
fuel combustion in Annex 4 for a comparison of U.S. estimates using top-
down and bottom-up approaches.
16 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.
17 See sections on Iron and Steel Production and Metallurgical Coke
Production, Ammonia Production and Urea Consumption, Petrochemical
Production, Titanium Dioxide Production, Ferroalloy Production, Aluminum
Production, and Silicon Carbide Production and Consumption in the
Industrial Processes chapter.
gas is subtracted from energy consumption statistics.18
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 (2008b) and data for synthetic natural
gas were collected from EIA (2008e), and data for CO2
exports were collected from the Dakota Gasification
Company (2006), Fitzpatrick (2002), Erickson (2003),
and EIA (2006).
4. Adjust Sectoral Allocation of Distillate Fuel Oil and
Motor Gasoline. EPA had conducted a separate bottom-up
analysis of transportation fuel consumption based on the
Federal Highway Administration's (FHWA) VMT that
indicated that the amount of distillate and motor gasoline
consumption allocated to the transportation sector in the EIA
statistics should be adjusted. Therefore, for these estimates,
the transportation sector's distillate fuel and motor gasoline
consumption was adjusted upward 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.
Similarly, as the total motor gasoline consumption estimate
is considered to be accurate at the national level, the motor
gasoline consumption totals for commercial and industrial
sectors were adjusted downward proportionately. The data
sources used in the bottom-up analysis of transportation
fuel consumption include AAR (2008), Benson (2002
through 2004), DOE (1993 through 2008), HA (2008a),
EIA (1991 through 2005), EPA (2006), and FHWA (1996
through 2008).
5. Adjust for fuels consumed for non-energy uses. U.S.
aggregate energy statistics include consumption of fossil
fuels for non-energy purposes. These are fossil fuels
that are manufactured into plastics, asphalt, lubricants,
or other products. 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 (since the C in these fuels ends up in
18 These adjustments are explained in greater detail in Annex 2.1.
Energy 3-19
-------
products instead of being combusted), 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 El A (2008b).
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).19 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 2008) supplied data on military jet fuel and marine
fuel use. Commercial jet fuel use was obtained from FAA
(2006); residual and distillate fuel use for civilian marine
bunkers was obtained from DOC (1991 through 2008) for
1990 through 2001, and 2007, and DHS (2008) for 2003
through 2006. Consumption of these fuels was subtracted
from the corresponding fuels in the transportation end-use
sector. Estimates of international bunker fuel emissions
for the United States are discussed in detail later in the
International Bunker Fuels section of this chapter.
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 2007 (EIA
2008c) and EIA's Monthly Energy Review and published
supplemental tables on petroleum product detail EIA (EIA
2008b). They are presented in Annexes 2.1 and 2.2.
8. Estimate CO2 Emissions. Total CO2 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 on-road vehicles, annual estimates of combined
motor gasoline and diesel fuel consumption by vehicle
category were obtained from FHWA (1996 through
2008); for each vehicle category, the percent gasoline,
diesel, and other (e.g., CNG, LPG) fuel consumption are
estimated using data from DOE (1993 through 2008).
• For non-road vehicles, activity data were obtained from
AAR (2008), APTA (2007 through 2008), BEA (1991
through 2008), Benson (2002 through 2004), DOE
(1993 through 2008), DESC (2008), DOC (1991 through
2008), DOT (1991 through 2007), EIA (2008a), EIA
(2008d), EIA (2007), EIA (2002), EIA (1991 through
2005), EPA (2006), FAA (2008), and Gaffney (2007).
• 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.20 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
(2008a) and USAF (1998).21
19 See International Bunker Fuels section in this chapter for a more detailed
discussion.
20FAA'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 .
21 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.
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.22
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.23 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.24 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 3-15 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.
Table 3-15: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg C02 Eq./QBtu)
Sector 1990 1995 2000 2005 2006 2007
Residential3 57.4 56.7 56.7 56.6 56.6 56.3
Commercial3 59.3 57.8 57.1 57.6 57.2 57.0
Industrial3 63.7 62.7 62.5 64.0 64.2 63.9
Transportation3 71.0 71.0 71.0 71.1 71.1 71.1
Electricity Generation" 86.7 86.0 85.6 85.0 84.6 84.0
U.S. Territories0 74J 74J 73.2 74.6 74.6 74.7
All Sectors0 72J 72.2 72J 73.1 73.1 72.8
aDoes 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 3-15, Table 3-16 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.25 This table, therefore, provides a more complete picture of
22 Small quantities of C02, 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.
23 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
24 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.
25 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.
Energy 3-21
-------
Box 3-2: Carbon Intensity of U.S. Energy Consumption (continued)
the actual C intensity of each end-use sector per unit of energy consumed. The transportation end-use sector in Table 3-16 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
Table 3-16: Carbon Intensity from All Energy Consumption by Sector (Tg C02 Eq./QBtu)
Sector
1995
2000
2005
2006
2007
Transportation3
Other End-Use Sectors3'1
Electricity Generation0
All Sectors"
70.6
57.7
59.9
70.1
58.1
59.9
69.8
57.5
58.9
69.4
57.5
59.3
61.1
60.3
61.4
61.6
61.1
61.0
'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.
11 Includes nuclear and renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
from the scenario in Table 3-15, 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.
By comparing the values in Table 3-15 and Table 3-16, 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
eighteen-year period of 1990 through 2007, 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 3-14). 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 2008).
Figure 3-14
U.S. Energy Consumption and Energy-Related C02
Emissions Per Capita and Per Dollar GDP
Energy
Consumption/
Capita
Uncertainty
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
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 2007. 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 EIA. 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
Simulation technique, with @RISK software. For this
uncertainty estimation, the inventory estimation model for
CO2 from fossil fuel combustion was integrated with the
relevant 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.26 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.27
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).28 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 3-17. Fossil fuel combustion CO2
emissions in 2007 were estimated to be between 5,622.3 and
6,029.3 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 2 percent below to 6 percent above the
2007 emission estimate of 5,735.8 Tg CO2 Eq.
26 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.
27 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.
28 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.
Energy 3-23
-------
Table 3-17: 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
2007 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
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
Total (excluding Geothermal)"
Geothermal
Total (including Geothermal)"'"
2,086.5
0.6
6.8
107.4
NE
1,967.6
4.1
1,216.5
256.9
163.4
385.6
35.4
373.8
1.4
2,432.4
83.2
44.2
352.5
1,852.0
55.3
45.3
5,735.4
0.4
5,735.8
Lower Bound
2,015.7
0.5
6.4
103.3
NE
1,890.6
3.6
1,226.2
249.7
158.9
396.1
34.4
363.1
1.2
2,279.1
78.8
42.1
306.4
1,710.8
53.3
41.8
5,621.9
NE
5,622.3
Upper Bound
2,284.1
0.7
7.8
125.4
NE
2,157.3
4.9
1,295.9
275.0
174.9
436.0
37.9
393.0
1.7
2,553.7
87.4
46.0
411.5
1,947.9
58.8
50.4
6,028.9
NE
6,029.3
Lower Bound
-3%
-6%
-5%
-4%
NA
-4%
-12%
+ 1%
-3%
-3%
+ 3%
-3%
-3%
-12%
-6%
-5%
-5%
-13%
-8%
-4%
-8%
-2%
NE
-2%
Upper Bound
+9%
+ 15%
+ 15%
+ 17%
NA
+ 10%
+ 19%
+7%
+7%
+7%
+ 13%
+7%
+5%
+ 17%
+5%
+5%
+4%
+ 17%
+5%
+6%
+ 11%
+5%
NE
+6%
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.
Note: Totals may not sum due to independent rounding.
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.
Recalculations Discussion
Estimates of CO2 from the industrial sector have
been revised for the years 1990 through 2006 to subtract
non-energy related consumption of coal, distillate fuel,
and natural gas used in iron and steel and metallurgical
coke production. A discussion of the methodology used
to estimate non-energy related consumption is contained
in the Iron and Steel Production and Metallurgical Coke
Production section of the Industrial Processes chapter. In
addition, the Energy Information Administration (EIA
2008b) updated energy consumption data for all years.
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
These revisions primarily impacted the emission estimates
for 2006. Overall, these changes resulted in an average
annual decrease of 17 Tg CO2 Eq. (0.3 percent) in CO2
emissions from fossil fuel combustion for the period 1990
through 2006.
Planned Improvements
An analysis is being undertaken to update the carbon
content factors for fossil fuels, as presented in the annexes
of this report. To reduce uncertainty of CO2 from fossil fuel
combustion estimates, efforts will be taken to work with
El A 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. In
addition, further expert elicitation may be conducted to better
quantify the total uncertainty associated with emissions from
this source.
CH4 and N20 from Stationary
Combustion
Methodology
CH4 and N2O emissions from stationary combustion
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, electricity generation, 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 detail (ElA 2008a). Wood consumption data for
the United States was obtained from EIA's Annual Energy
Review (EIA 2008b). Because the United States does not
include territories in its national energy statistics, fuel
consumption data for territories were provided separately
by Grillot (2008).29 Fuel consumption for the industrial
sector was adjusted to subtract out construction and
agricultural use, which is reported under mobile sources.30
Construction and agricultural fuel use was obtained from EPA
(2006). 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 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006). 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.
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/
29U.S. territories data also include combustion from mobile activities
because data to allocate territories' energy use were unavailable. For this
reason, CH4 and N2O emissions from combustion by U.S. territories are
only included in the stationary combustion totals.
30 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.
Energy 3-25
-------
EIA (2001) report.31 For these variables, the uncertainty The uncertainties associated with the emission
ranges were assigned to the input variables based on the estimates of CH4 and N2O are greater than those associated
data reported in SAIC/EIA (2001).32 However, the CH4 with estimates of CO2 from fossil fuel combustion, which
emission factors differ from those used by EIA. Since these mainly rely on the carbon content of the fuel combusted.
factors were obtained from IPCC/UNEP/OECD/IEA (1997), Uncertainties in both CH4 and N2O estimates are due to the
uncertainty ranges were assigned based on IPCC default fact that emissions are estimated based on emission factors
uncertainty estimates (IPCC 2000). representing only a limited subset of combustion conditions.
Theresultsof the Tier 2 quantitative uncertainty analysis For the indirect greenhouse gases, uncertainties are partly
are summarized in Table 3-18. Stationary combustion CH4 due to assumptions concerning combustion technology
emissions in 2007 (including biomass) were estimated to be ^P68' a§e of equipment, emission factors used, and activity
between 4.3 and 15.1 Tg CO2 Eq. at a 95 percent confidence ^^ projections.
level. This indicates a range of 34 percent below to 128
percent above the 2007 emission estimate of 6.6 TgCO2Eq.33 QA/QC 311(1 Verification
Stationary combustion N2O emissions in 2007 (including A source-specific QA/QC plan for stationary combustion
biomass) were estimated to be between 11.2 and 42.1 Tg was developed and implemented. This effort included a
CO2 Eq. at a 95 percent confidence level. This indicates a Tier 1 analysis, as well as portions of a Tier 2 analysis. The
range of 24 percent below to 187 percent above the 2007 Tier 2 procedures that were implemented involved checks
emissions estimate of 14.7 Tg CO2 Eq. specifically focusing on the activity data and emission factor
sources and methodology used for estimating CH4, N2O, and
Table 3-18: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg C02 Eq. and Percent)
2007 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg C02 Eq.) (Tg C02 Eq.) (%)
Stationary Combustion
Stationary Combustion
CH4
N20
6.6
14.7
Lower Bound
4.3
11.2
Upper Bound
15.1
42.1
Lower Bound
-34%
-24%
Upper Bound
+ 128%
+ 187%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
31 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.
32 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.
33 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.
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
Recalculations Discussion
Historical CH4 and N2O emissions from stationary
sources (excluding CO2) were revised due to a couple of
changes. Slight changes to emission estimates for sectors
are due to revised data from EIA (2008a). 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 (2008b) were revised for the
residential, industrial, and electric power sectors. The
combination of the methodological and historical data
changes resulted in an average annual increase of less than
0.1 Tg CO2 Eq. (less than 0.1 percent) in CFLj emissions from
stationary combustion and an average annual decrease of less
than 0.1 Tg CO2 Eq. (0.2 percent) in N2O emissions from
stationary combustion for the period 1990 through 2006.
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 made 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.
CH4 and N20 from Mobile Combustion
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 miles traveled (VMT) for 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 CH4 and N2O emissions from mobile combustion
and the emission factors used in the calculations is provided
in Annex 3.2.
On-Road Vehicles
Estimates of CH4 and N2O emissions from gasoline
and diesel on-road vehicles are based on VMT and emission
factors by vehicle type, fuel type, model year, and emission
control technology. Emission estimates for alternative fuel
vehicles (AFVs)34 are based on VMT and emission factors
by vehicle and fuel type.
Emission factors for gasoline and diesel on-road
vehicles utilizing Tier 2 and Low Emission Vehicle (LEV)
technologies were developed by ICF (2006b); all other
gasoline and diesel on-road vehicle emissions factors were
developed by ICF (2004). These factors were derived
from EPA, California Air Resources Board (CARB) and
Environment Canada laboratory test results of different
vehicle and control technology types. The EPA, CARB and
Environment Canada tests were designed following the
Federal Test Procedure (FTP), which covers three separate
driving segments, since vehicles emit varying amounts of
GHGs depending on the driving segment. These driving
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 emission
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, an EPA emission factor model that
predicts gram per mile emissions of CO2, CO, HC, NOX, and
PM from vehicles under various conditions, to approximate
average driving characteristics.35
34Alternative fuel and advanced technology vehicles are those that can
operate using a motor fuel other than gasoline or diesel. This includes
electric or other bi-fuel or dual-fuel vehicles that may be partially powered
by gasoline or diesel.
35 Additional information regarding the model can be found online at http: //
www.epa.gov/OMS/m6.htm.
Energy 3-27
-------
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 2007 were obtained
from the Federal Highway Administration's (FHWA)
Highway Performance Monitoring System database as
reported in Highway Statistics (FHWA 1996 through 2008).
VMT estimates were 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 2008) and
information on total motor vehicle fuel consumption by fuel
type from FHWA (1996 through 2008). VMT for AFVs were
taken from Browning (2003). The age distributions of the
U.S. vehicle fleet were obtained from EPA (2007c, 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 on-road
vehicles were obtained from EPA's Office of Transportation
and Air Quality (EPA 2007a, 2007b, 2000,1998, and 1997) and
Browning (2005). These technologies and standards are defined
in Annex 3.2, and were compiled from EPA (1993, 1994a,
1994b, 1998,1999a) and IPCC/UNEP/OECD/IEA (1997).
Non-Road Vehicles
To estimate emissions from non-road 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).36 Activity
data were obtained from AAR (2008), APTA (2007 through
2008), APTA (2006), BEA (1991 through 2005), Benson
(2002 through 2004), DHS (2008), DOC (1991 through
36 The consumption of international bunker fuels is not included in these
activity data, but is estimated separately under the International Bunker
Fuels source category.
2008), DOE (1993 through 2008), DESC (2008), DOT
(1991 through 2008), EIA (2008b, 2007a, 2007b, 2002),
EIA (2007 through 2008), EIA (1991 through 2007), EPA
(2006b), Esser (2003 through 2004), FAA (2008 and 2006),
Gaffney (2007), and Whorton (2006 through 2007). Emission
factors for non-road modes were taken from IPCC/UNEP/
OECD/IEA(1997).
Uncertainty
A quantitative uncertainty analysis was conducted
for the on-road 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
2007 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.
Uncertainty analyses were not conducted for NOX, CO,
or NMVOC emissions. Emission factors for these gases have
been extensively researched since emissions of these gases
from motor vehicles are regulated in the United States, and
the uncertainty in these emission estimates is believed to be
relatively low. However, a much higher level of uncertainty
is associated with CIL, and N2O emission factors, because
emissions of these gases are not regulated in the United States
(and, therefore, there are not adequate emission test data),
and because, unlike CO2 emissions, the emission pathways
of CH4 and N2O are highly complex.
The results of the Tier 2 quantitative uncertainty analysis
for the mobile source CIL, and N2O emissions from on-road
vehicles are summarized in Table 3-19. As noted above, an
uncertainty analysis was not performed for CIL, and N2O
emissions from non-road vehicles. Mobile combustion CH4
emissions (from on-road vehicles) in 2007 were estimated to
be between 1.5 and 1.8 Tg CO2 Eq. at a 95 percent confidence
level. This indicates a range of 8 percent below to 8 percent
above the corresponding 2007 emission estimate of 1.7
Tg CO2 Eq. Also at a 95 percent confidence level, mobile
combustion N2O emissions from on-road vehicles in 2007
were estimated to be between 21.1 and 30.8 Tg CO2 Eq.,
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-19: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Mobile Combustion
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3'"
(Tg C02 Eq.) (%)
Mobile Combustion
Mobile Combustion
CH4
N20
1.7
26.0
Lower Bound
1.5
21.1
Upper Bound
1.8
30.8
Lower Bound
-8%
-19%
Upper Bound
+ 8%
+ 19%
a 2007 Emission estimates and the uncertainty range presented in this table correspond to on-road vehicles, comprising conventional and alternative fuel
vehicles. Because the uncertainty associated with the emissions from non-road vehicles were not estimated, they were excluded in the estimates reported
in this table.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
indicating a range of 19 percent below to 19 percent above the
corresponding 2007 emission estimate of 26.0 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 IPCC Tier 2 approach to
uncertainty analysis. As a result, as new information becomes
available, uncertainty characterization of input variables
may be improved and revised. For additional information
regarding uncertainty in emission estimates for CH4 and N2O
please refer to the Uncertainty Annex.
QA/QC and Verification
A source-specific QA/QC plan for mobile combustion
was developed and implemented. This plan is based on the
IPCC-recommended QA/QC Plan. The specific plan used
for mobile combustion was updated prior to collection and
analysis of this current year of data. 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 methodologies used
in calculating emissions in the current Inventory relative to
the previous Inventory report.
New estimates of VMT by alternative fueled vehicles
are now calculated using an updated method. The original
VMT for alternative fuels was determined from energy use
data obtained from EIA and projected. The new update uses
actual energy use for 2005 through 2007 and improved
estimations for future years.
Several changes were also made in the calculation
of emissions from non-road vehicles. Commercial aircraft
activity data for 1990 through 1999 is now calculated as
the result of estimating DOT (1991 through 2008) data
based upon the average difference between FAA (2006)
and DOT (1991 through 2008) datasets for the years 2000
through 2005. For 2006 and 2007 commercial aircraft
activity data, DOT (1991 through 2008) data is multiplied
by the percentage difference between 2005 (the most recent
available SAGE datapoint) and the respective year.
International jet fuel bunkers are now calculated by
assigning the difference between the sum of domestic activity
data (in TBtu) and the EIA transportation jet fuel allotment
to the jet fuel bunkers category. Previously, international jet
Energy 3-29
-------
fuel bunkers were calculated based upon DOT (1991 through
2008) and BEA (1991 through 2005) data for the years 1990
through 1999 and 2006 through 2007 and estimated by FAA
(2006) for 2000 through 2005.
Categories of non-road sources for which activity data
are supplied from EPA's NONROAD model (EPA 2006) now
include all Source Classification Codes available within the
model, rather than a subset of all sources. This change results
in an increase in emissions estimates from farm equipment,
construction equipment, and other non-road sources.
As a result of these changes, average estimates of CH4
and N2O emissions from mobile combustion were slightly
higher relative to the previous Inventory—showing an
increase of no more than 2.5 percent in a given year—for the
period 1990 through 2007. The greatest increase in absolute
terms, 0.48 Tg CO2 Eq. (1.4 percent), occurs with the 2006
N,O estimate.
Planned Improvements
While the data used for this report represent the most
accurate information available, six areas have been identified
that could potentially be improved in the short-term given
available resources.
1. Develop updated emissions factors for diesel vehicles,
motorcycles, and biodiesel vehicles. Previous emission
factors were based upon extrapolations from other
vehicle classes and new test data from Environment
Canada will allow for better estimation of emission
factors for these vehicles.
2. Develop updated emissions factors for ships and boats.
Prior emission factors were derived from AP-42 for
combustion of diesel and residual fuel. The new factors
will take into account new data obtained from the
Swedish Methodology for Environmental Data.
3. Develop new emis sion factors for non-road equipment.
The current Inventory estimates for non-CO2 emissions
from non-road sources are based on emission factors
from IPCC guidelines published in 1996. Recent data
on non-road sources from Environment Canada and the
California Air Resources Board will be investigated in
order to assess the feasibility of developing new N2O and
CH4 emissions factors for non-road equipment.
4. Examine the feasibility of estimating aircraft N2O
and CH4 emissions by the number of takeoffs and
landings, instead of total fuel consumption. Various
studies have indicated that aircraft N2O and CH4
emissions are more dependent on aircraft takeoffs
and landings than on total aircraft fuel consumption;
however, aircraft emissions are currently estimated
from fuel consumption data. FAA's SAGE database
contains detailed data on takeoffs and landings for each
calendar year starting in 1999, and could potentially be
used to conduct a Tier II analysis of aircraft emissions.
This methodology will require a detailed analysis of
the number of takeoffs and landings by aircraft type
on domestic trips and development of procedures to
develop comparable estimates for years prior to 1999.
The feasibility of this approach will be explored.
5. Develop improved estimates of domestic waterborne
fuel consumption. The Inventory estimates for residual
fuel used by ships and boats is based in part on data on
bunker fuel use from the U.S. Department of Commerce.
The Department of Homeland Security (DHS) maintains
an electronic reporting system that automatically registers
monthly sales of bunker fuel at ports, which should
provide a more accurate and comprehensive estimate
of residual bunker fuel use by reducing the amount of
non-reporting. This system has been used to collect data
since 2002, and these data could be incorporated into the
development of inventory figures. The DHS figures will
need to be reconciled with figures from the current sources
of data and a methodology will need to be developed to
produce updated estimates for prior years.
6. Continue to examine the use of 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. As
MOVES goes through additional testing and refinement,
the use of MOVES will be further explored.
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
3.2. Carbon Emitted from
Non-Energy Uses of Fossil Fuels
(IPCC Source Category 1A)
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).
Carbon dioxide 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 63 percent of the total C consumed for
non-energy purposes was stored in products, and not released
to the atmosphere; the remaining 37 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 EIA 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 3-20, fossil fuel emissions in 2007
from the non-energy uses of fossil fuels were 133.9 Tg CO2
Eq., which constituted approximately 2 percent of overall
fossil fuel emissions. In 2007, the consumption of fuels for
non-energy uses (after the adjustments described above) was
5,219.2 TBtu, an increase of 16 percent since 1990(see Table
3-21). About 62.0 Tg of the C (227.2 Tg CO2 Eq.) in these
fuels was stored, while the remaining 36.5 Tg C (133.9 Tg
CO2 Eq.) was emitted. The proportion of C emitted as CO2
has remained about constant since 1990, at about 37 to 40
percent of total non-energy consumption (see Table 3-20).
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 (2007) (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 3-21 and Table
Table 3-20: C02 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg C02 Eq.)
Type
Potential Emissions
C Stored
Emissions as a % of Potential
Emissions
1995
137.5
2000
2005
2006
2007
375.9
237.8
37%
383.4
238.3
38%
361.1
227.2
37%
144.5
138.1
145.1
133.9
Energy 3-31
-------
Table 3-21: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Sector/Fuel Type
1990
1995
2000
2005
2006
2007
Industry 4,222.3
Industrial Coking Coal +
Industrial Other Coal 8.2
Natural Gas to Chemical Plants, Other Uses 276.0
Asphalt & Road Oil 1,170.2
LPG 1,119.0
Lubricants 186.3
Pentanes Plus 77.3
Naphtha (<401°F) 325.7
Other Oil (>401°F) 677.2
Still Gas 21.3
Petroleum Coke 82.1
Special Naphtha 100.9
Distillate Fuel Oil 7.0
Waxes 33.3
Miscellaneous Products 137.8
Transportation 176.0
Lubricants 176.0
U.S. Territories 86.7
Lubricants 0.7
Other Petroleum (Misc. Prod.) 86.0
4,804.4
75.0
11.3
330.4
1,178.2
1,484.7
177.8
285.3
350.6
612.7
40.1
45.5
66.9
8.0
40.6
97.1
167.9
167.9
90.8
2.0
15,278.9
82.2
194!
5,278.9
82.2
12.4
420.7
1,275.7
1,603.1
189.9
228.5
592.3
553.8
12.6
49.4
94.3
11.7
33.1
119.2
179.4
179.4
165.5
16.4
149.1
5,153.4
53.3
11.9
390.0
1,323.2
1,440.9
160.2
145.9
678.2
518.3
67.7
147.2
60.8
11.7
31.4
112.8
151.3
151.3
107.7
5.2
102.4
5,245.8
74.7
12.4
403.2
1,261.2
1,492.0
156.1
105.7
619.4
572.9
123.9
181.5
69.1
11.7
26.1
136.0
147.4
147.4
110.3
5.4
105.0
4,966.4
33.0
12.4
396.0
1,197.0
1,483.2
161.0
132.4
543.3
511.7
88.4
165.4
75.6
11.7
21.9
133.5
152.0
152.0
100.9
4.9
96.0
Total
4,485.0
5,063.1
5,623.7
5,412.4 5,503.6 5,219.2
+ Less than 0.05 TBtu.
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.
3-22 have been adjusted to subtract non-energy uses that are
included in the source categories of the Industrial Processes
chapter.37 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
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
37 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.
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 Incineration
of Waste 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 3-20).
More detail on the methodology for calculating storage
and emissions from each of these sources is provided in
Annex 2.3.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-22: 2007 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Adjusted Carbon
Non-Energy Content
Usea Coefficient
Sector/Fuel Type (TBtu) (Tg C/QBtu)
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
4,966.4
33.0
12.4
396.0
1,197.0
1,483.2
161.0
132.4
543.3
511.7
88.4
165.4
75.6
11.7
21.9
133.5
152.0
152.0
100.9
4.9
96.0
5,219.2
-
31.00
25.63
14.47
20.62
16.76
20.24
18.24
18.14
19.95
17.51
27.85
19.86
19.95
19.81
20.33
-
20.24
-
20.24
20.00
Potential
Carbon
(TgC)
93.4
1.0
0.3
5.7
24.7
24.9
3.3
2.4
9.9
10.2
1.5
4.6
1.5
0.2
0.4
2.7
3.1
3.1
2.0
0.1
1.9
98.5
Storage
Factor
-
0.10
0.61
0.61
1.00
0.61
0.09
0.61
0.61
0.61
0.61
0.30
0.61
0.50
0.58
0.00
-
0.09
-
0.09
0.10
Carbon Carbon Carbon
Stored Emissions Emissions
(TgC) (TgC) (Tg C02 Eq.)
61.5
0.1
0.2
3.5
24.7
15.3
0.3
1.5
6.0
6.3
1.0
1.4
0.9
0.1
0.3
0.0
0.3
0.3
0.2
0.0
0.2
62.0
31.9
0.9
0.1
2.2
+
9.6
3.0
0.9
3.8
3.9
0.6
3.2
0.6
0.1
0.2
2.7
2.8
2.8
1.8
0.1
1.73
36.5
117.0
3.4
0.4
8.1
+
35.2
10.8
3.4
14.0
14.5
2.2
11.8
2.1
0.4
0.7
9.9
10.2
10.2
6.7
0.3
6.3
133.9
+ Less than 0.05 TBtu.
- Not applicable.
aTo avoid double counting, exports have been deducted.
Note: Totals may not sum due to independent rounding.
Where 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 Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data (EPA
2008), Toxics Release Inventory, 1998 (2000a), Biennial
Reporting System (EPA 2004a, 2006b, 2007), 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
(SPI 2000); Bank of Canada (2006); Financial Planning
Association (2006); INEGI (2006); Statistics Canada
(2006); the United States International Trade Commission
(2006 through 2008); 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 through 2007); the Material Safety Data Sheets
(Miller 1999); the Chemical Manufacturer's Association
Energy 3-33
-------
(CMA 1999); and the American Chemistry Council (ACC
2005 through 2008) Specific data sources are listed in full
detail in Annex 2.3.
Uncertainty
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.-specific 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 3-23 (emissions) and Table 3-24
(storage factors). Carbon emitted from non-energy uses of
fossil fuels in 2007 was estimated to be between 107.0 and
144.6 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 20 percent below to 8 percent above the
2007 emission estimate of 133.9 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 3-24, 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
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 and for imports and exports. 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.
For petrochemical import and export data, special
attention was paid to NAICS numbers and titles to verify
that none had changed or been removed. Import and export
totals were compared for 2007 as well as their trends across
the time series.
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-23: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Non-Energy Uses of Fossil Fuels
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Feedstocks
Asphalt
Lubricants
Waxes
Other
Total
C02
C02
C02
C02
C02
C02
79.9
0.0
21.4
0.7
31.9
133.9
Lower Bound
64.4
0.2
17.7
0.5
13.7
107.0
Upper Bound
95.9
0.8
24.9
1.1
33.0
144.6
Lower Bound
-19%
NA
-17%
-24%
-57%
-20%
Upper Bound
+20%
NA
+ 16%
+64%
+ 3%
+8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
NA (Not Applicable)
Table 3-24: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent)
Source
2007 Storage Factor
Gas (%)
Uncertainty Range Relative to Emission Estimate3
(%) (%, Relative)
Feedstocks
Asphalt
Lubricants
Waxes
Other
C02
C02
C02
C02
C02
61%
100%
9%
58%
17%
Lower Bound Upper Bound
59% 63%
99% 100%
4% 17%
44% 70%
17% 64%
Lower Bound
-4%
-1%
-57%
-25%
+ 2%
Upper Bound
+ 3%
+ 0%
+89%
+20%
+273%
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).
Recalculations Discussion
Non-energy end uses for petroleum coke (other than
in the industrial processing sectors, where it is accounted
for separately) had not been identified in the past. Huurman
(2006) suggests that in the Netherlands petroleum coke is
used in some pigments, and identifies its corresponding
storage factor as 0.3. This year,itwas assumed that petroleum
coke used for non-energy purposes (and not accounted for
in the Industrial Processes chapter, viz., for production of
primary aluminum anodes, electric arc furnace anodes,
titanium dioxide, ammonia, urea, and ferroalloys) is used in
pigments, with a storage factor of 0.3 (rather than the value
of 0.5 used previously). This resulted in an average 1.4%
increase in NEU emissions across the time series.
Planned Improvements
There are several improvements planned for the
future:
• Future updates in line with the 2006 IPCC Guidelines.
These changes could 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 wastewaters, 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).
Energy 3-35
-------
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 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. 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 CH^ emissions. In
2007,233 coal mines, (including all 131 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 CH^ to the
atmosphere in low concentrations. Additionally, 20 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 2007,15
coal mines collected CH^ from degasification systems and
utilized this gas, thus reducing emissions to the atmosphere.
Of these mines, 13 coal mines sold CK4 to the natural gas
pipeline, one coal mine generated electricity, and one coal
mine used CH^ from its degasification system to heat mine
ventilation air on site. On addition, one of the coal mines that
sold gas to pipelines also used CK4 to 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 CFLj retained in the coal after mining is released during
processing, storage, and transport of the coal.
Total CH4 emissions in 2007 were estimated to be
57.6 Tg CO2 Eq. (2,744 Gg), a decline of 31 percent since
1990 (see Table 3-25 and Table 3-26). Of this amount,
Table 3-25: CH4 Emissions from Coal Mining (Tg C02 Eq.)
Activity
1990
1995
2000
2005
2006
2007
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
62.3
67.9
(5.6)
12.0
7.7
2.0
I 59.2 54.4
(12.4) (14.9)
11.5 12.3
I 6.9 6.71
35.2
50.1
(14.9)
13.3
6.4
2.2
35.8
54.5
(18.6)
14.0
6.3
2.3
35.5
47.7
(12.3)
13.8
6.1
2.2
Total
84.1
67.1
60.5
57.1
58.4
57.6
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-26: CH4 Emissions from Coal Mining (Gg)
Activity
1990
1995
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
2,968
3,234
(266)
574
368
93
I 2,817
(592)
330
2005
1,677
2,387
(710)
633
306
103
2006
1,705
2,593
(888)
668
298
109
2007
1,689
2,273
(584)
659
290
107
Total
4,003
3,193
2,881
2,719 2,780
2,744
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
underground mines accounted for 62 percent, surface
mines accounted for 24 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 CH^ recovered and
used. Since that time, underground coal production and the
associated methane emissions have remained fairly level,
while surface coal production and its associated emissions
have generally increased.
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.
Undergro und mines. Total CFLj 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
detectable38 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 mines using these systems,
depending on available data. For example, some mines report
to EPA the amount of CFLj 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 CFLj recovered by degasification
systems and then used (i.e., not vented) was estimated. In
2007,13 active coal mines sold recovered CK4 into the local
gas pipeline networks, one used recovered CH4 to generate
electricity while one coal mine used recovered CFLj on site for
heating. 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 CFLj emissions were estimated by
multiplying basin-specific coal production, obtained from the
Energy Information Administration's Annual Coal Report
(see Table 3-27) (EIA 2006), by basin-specific emission
factors. Surface mining emission factors were developed by
assuming that surface mines emit two times as much CH4
as the average in situ CK4 content of the coal. Revised data
on in situ CH4 content and emissions factors are taken from
EPA (2005), 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.
Table 3-27: Coal Production (Thousand Metric Tons)
Year Underground Surface
Total
384,250
^H
359,477
546,818
577,638
931,068
937,115
2000
^
2005
2006
2007
338,173
635,592
973,765
334,404
325,703
319,145
691,460
728,459
720,035
1,025,864
1,054,162
1,039,179
38 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 3-37
-------
Table 3-28: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Coal Mining
CH,
57.6
48.6
71.2
-16%
+24%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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
CtLj emissions (Mutmansky and Wang 2000). Estimates of
CH4 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 vary if the drainage area is
found to be larger or smaller 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 3-28. Coal
mining CH^ emissions in 2007 were estimated to be between
48.6 and 71.2 Tg CO2 Eq. at a 95 percent confidence level.
This indicates a range of 16 percent below to 24 percent
above the 2007 emission estimate of 57.6 Tg CO2 Eq.
Recalculations Discussion
In 2007, calculations of emissions avoided at the four
Jim Walters Resources (JWR) coal mines in Alabama were
performed using the previous EPA method. This was done
in order to take a better documented approach and to track
the four coal mines individually rather than as a group.
Emissions avoided calculations for any pre-drainage wells
at JWR coal mines are based on publicly-available data
records from the Alabama State Oil & Gas Board. Emission
reductions are calculated for pre-drainage wells that are
located inside the mine plan boundaries and are declared
"shut-in" by the O&G Board. The total production for a
well is claimed in the year that the well was shut-in and
mined through.
3.4. Abandoned Underground Coal
Mines (IPCC Source Category 1B1 a)
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
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 CtLj that may find its way to surface structures through
overburden fractures. As work stops within the mines, the
CtLj liberation decreases but it does not stop completely.
Following an initial decline, abandoned mines can liberate
CtLj 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 CK4 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;
• CtLj flow capacity of the mine;
• Mine flooding;
• Presence of vent holes; and
• Mine seals.
Gross abandoned mine CR4 emissions ranged from
6.0 to 9.1 Tg CO2 Eq. from 1990 through 2007, 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. Gross 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 2007, with only three closures in 2007. By 2007,
gross abandoned mine emissions increased to 9.0 Tg CO2
Eq. (see Table 3-29 and Table 3-30). Gross emissions are
reduced by CFLj recovered and used at 27 mines, resulting
in net emissions in 2007 of 5.7 Tg CO2 Eq.
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. A well or a mine which produces
gas from a coal seam and the surrounding strata will produce
less gas through time as the reservoir of gas is depleted.
Depletion of a reservoir will follow a predictable pattern
depending on the interplay of a variety of natural physical
Table 3-29: CH4 Emissions from Abandoned Underground Coal Mines (Tg C02 Eq.)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990
6.0
0.0
6.0
1995
8.9
0.7
8.2
2000
8.9
1.5
7.4
2005
7.0
1.4
5.6
2006
7.5
2.0
5.5
2007
9.0
3.3
5.7
Note: Totals may not sum due to independent rounding.
Table 3-30: CH4 Emissions from Abandoned Underground Coal Mines (Gg)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990
288
0
288
1995
424
32
392
2000
422
72
350
2005
334
68
265
2006
359
96
263
2007
428
155
273
Note: Totals may not sum due to independent rounding.
Energy 3-39
-------
conditions imposed on the reservoir. The depletion of a
reservoir is commonly modeled by mathematical equations
and mapped as a type curve. Type curves which are referred
to as decline curves have been developed for abandoned
coal mines. 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 CR4 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). Arate-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:
where,
q = Gas rate at time t in thousand cubic feet
per day (mcfd)
q; = Initial gas rate at time zero (t0) in mcfd
b = The hyperbolic exponent, dimensionless
D; = Initial decline rate, 1/yr
t = Elapsed time from t0 (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 created to model the gas emission
rate of coal mines must account for factors that decrease
the rate of emission after mining activities cease, such as
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 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 = Gas flow rate at time t in mcfd
q; = Initial gas flow rate at time zero (t0) in mcfd
D = Decline rate, 1/yr
t = Elapsed time from t0 (years)
Seals have an inhibiting effect on the rate of flow of
CH4 into the atmosphere compared to the rate that would be
emitted if the mine had an open vent. The total volume emitted
will be the same, but will occur over a longer period. The
methodology, therefore, treats the emissions prediction from
a sealed mine similar to emissions from a vented mine, but
uses a lower initial rate depending on the degree of sealing.
The computational fluid dynamics simulator was again
used with the conceptual abandoned mine model to predict
the decline curve for inhibited flow. The percent sealed is
defined as 100 x [1 - (initial emissions from sealed mine /
emission rate at abandonment prior to sealing)]. Significant
differences are seen between 50 percent, 80 percent, and 95
percent closure. These decline curves were therefore used as
the high, middle, and low values for emissions from sealed
mines (EPA 2003).
For active coal mines, those mines producing over 100
mcfd account for 98 percent of all CK4 emissions. This
same relationship is assumed for abandoned mines. It was
determined that 448 abandoned mines closing after 1972
produced emissions greater than 100 mcfd when active.
Further, the status of 267 of the 448 mines (or 60 percent) is
known to be either: (1) vented to the atmosphere; (2) sealed
to some degree (either earthen or concrete seals); or,
(3) flooded (enough to inhibit CH4 flow to the atmosphere).
The remaining 40 percent of the mines were placed in one
of the three categories by applying a probability distribution
analysis based on the known status of other mines located in
the same coal basin (EPA 2003).
Inputs to the decline equation require the average
emission rate and the date of abandonment. Generally this
data is available for mines abandoned after 1972; however,
such data are largely unknown for mines closed before 1972.
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Information that is readily available such as coal production
by state and county is helpful, but does not provide enough
data to directly employ the methodology used to calculate
emissions from mines abandoned after 1971. It is assumed
that pre-1972 mines are governed by the same physical,
geologic, and hydrologic constraints that apply to post-1972
mines; thus, their emissions may be characterized by the
same decline curves.
During the 1970s, 78 percent of CH4 emissions from
coal mining came from seventeen counties in seven states.
In addition, mine closure dates were obtained for two states,
Colorado and Illinois, for the hundred year period extending
from 1900 through 1999. The data were used to establish a
frequency of mine closure histogram (by decade) and applied
to the other five states with gassy mine closures. As a result,
basin-specific decline curve equations were applied to 145
gassy coal mines estimated to have closed between 1920
and 1971 in the United States, representing 78 percent of
the emissions. State-specific, initial emission rates were used
based on average coal mine CFLj emissions rates during the
1970s (EPA 2003).
Abandoned mines emission estimates are based on all
closed mines known to have active mine CH4 ventilation
emission rates greater than 100 mcfd at the time of
abandonment; a list by region is shown in Table 3-31. For
example, for 1990 the analysis included 145 mines closed
before 1972 and 258 mines closed between 1972 and 1990.
Initial emission rates based on MSHA reports, time of
abandonment, and basin-specific decline curves influenced by
a number of factors were used to calculate annual emissions for
each mine in the database. Coal mine degasification data are
not available for years prior to 1990, thus the initial emission
rates used reflect ventilation emissions only for pre-1990
closures. Methane degasification amounts were added to the
quantity of CH4 ventilated for the total CH4 liberation rate for
fifteen mines that closed between 1992 and 2007. Since the
sample of gassy mines (with active mine emissions greater
than 100 mcfd) is assumed to account for 78 percent of the
pre-1971 and 98 percent of the post-1971 abandoned mine
emissions, the modeled results were multiplied by 1.22 and
1.02 to account for all U.S. abandoned mine emissions.
From 1993 through 2007, 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 CFLj 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.
Table 3-31: Number of Gassy Abandoned Mines Occurring in U.S. Basins Grouped by Class According to
Post-abandonment State
Basin
Central Appalachia
Illinois
Northern Appalachia
Warrior Basin
Western Basins
Total
Sealed
24
28
42
0
25
119
Vented
25
3
22
0
3
53
Flooded
48
14
16
15
2
95
Total Known
97
45
79
15
30
267
Unknown
115
25
32
0
9
181
Total Mines
212
70
112
15
39
448
Energy 3-41
-------
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal Mines
(Tg C02 Eq. and Percent)
2007 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Abandoned Underground
Coal Mines CH4 57 4.6 7J -19% +23%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Once the low, mid, and high values are selected, they are 35 |\|gtural G3S SySteiTIS (IPCC
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 The U.S. natural gas system encompasses hundreds
emissions in 2007 were estimated to be between 4.6 and 7.1 of thousands of wells, hundreds of processing facilities,
Tg CO2 Eq. at a 95 percent confidence level. This indicates and over a million miles of transmission and distribution
a range of 19 percent below to 23 percent above the 2007 pipelines. Overall, natural gas systems emitted 104.7 Tg CO2
emission estimate of 5.7 Tg CO2 Eq. One of the reasons for Eq. (4,985 Gg) of CH4 in 2007, a 19 percent decrease over
the relatively narrow range is that mine-specific data is used 1990 emissions (see Table 3-33 and Table 3-34), and 28.7
in the methodology. The largest degree of uncertainty is Tg CO2 Eq. (28,680 Gg) of non-combustion CO2 in 2007,
associated with the unknown status mines (which account for a 15 percent decrease over 1990 emissions (see Table 3-35
40 percent of the mines), with a +53 percent uncertainty. and Table 3-36). Improvements in management practices and
Table 3-33: CH4 Emissions from Natural Gas Systems (Tg C02 Eq.)a
Stage 1990 1995 2000 2005 2006 2007
Field Production 34.2 38.7 40.3 26.4 27.8 22.4
Processing 15.0 15.1 14.5 11.6 11.6 12.3
Transmission and Storage 47.0 46.4 44.6 39.1 38.4 40.4
Distribution 33.4 32.4 31.4 29.3 27.0 29.6
Total 129.6 132.6 130.8 106.3 104.8 104.7
'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)a
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
1,629
7141
2,237
1,591
6,171
1995
1,842
717
2,212
1,543
6,314
2000
1,918
692
2,123
1,498
6,231
2005
1,256
550
1,862
1,393
5,062
2006
1,323
555
1,828
1,285
4,991
2007
1,066
584
1,926
1,409
4,985
'Including CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-35: Non-combustion 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 1
+
33.7
1995
24.6
0.1 1
+
33.8
2000
6.0
23.3
0.1 1
+
29.4
2005
7.6
21.7
0.1
+
29.5
2006
8.2
21.2
0.1
+
29.5
2007
7.4
21.2
0.1
+
28.7
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 3-36: Non-combustion C02 Emissions from Natural Gas Systems (Gg)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
5,877
27,752
59
46
33,733
1995
9,084
24,621
61
45
33,810
2000
5,956
23,332
61
44
29,394
2005
7,625
21,736
61
41
29,463
2006
8,235
21,204
60
40
29,540
2007
7,389
21,189
61
41
28,680
Note: Totals may not sum due to independent rounding.
technology, along with the replacement of older equipment,
have helped to stabilize emissions. Methane emissions
decreased since 2006 despite an increase in production
and production wells due to a decrease in 73 offshore
platforms and an increase of 25 percent in Natural Gas STAR
production sector emissions reductions.
Methane and non-combustion 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. Below is a characterization
of the four major stages of the natural gas system. Each of
the stages is described and the different factors affecting CH4
and non-combustion CO2 emissions are discussed.
Field Production. In this initial stage, wells are used to
withdraw raw gas from underground formations. Emissions
arise from the wells themselves, gathering pipelines, and
well-site gas treatment facilities such as dehydrators and
separators. Fugitive emissions and emissions from pneumatic
devices account for the majority of CH4 emissions. Flaring
emissions account for the majority of the non-combustion
CO2 emissions. Emissions from field production accounted
for approximately 21 percent of CK4 emissions and about
26 percent of non-combustion CO2 emissions from natural
gas systems in 2007.
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-combustion CO2 emissions come
from acid gas removal units, which are designed to remove
CO2 from natural gas. Processing plants account for about 12
percent of CFLj emissions and approximately 74 percent of
non-combustion 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
powerplants 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 CR4 emissions from these compressor
stations and from metering and regulating stations account
for the majority of the emissions from this stage. Pneumatic
Energy 3-43
-------
devices and engine uncombusted exhaust are also sources of
j 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.
Methane emissions from the transmission and storage sector
account for approximately 39 percent of emissions from
natural gas systems, while CO2 emissions from transmission
and storage account for less than 1 percent of the non-
combustion 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 1,190,000 miles of distribution
mains in 2007, an increase from just over 944,000 miles in
1990 (OPS 2007b). Distribution system emissions, which
account for approximately 28 percent of CH4 emissions
from natural gas systems and less than 1 percent of non-
combustion CO2 emissions, result mainly from fugitive
emissions from gate stations and pipelines. 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 2007 were 1 1 .4 percent lower than
1990 levels.
Methodology
The primary basis for estimates of CH4 and non-
combustion-related CO2 emissions from the U.S. natural gas
industry is a detailed study by the Gas Research Institute
(GRI) 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 CK4 and
non-combustion CO2 emissions. However, the CH4 emission
factors were adjusted for CO2 content when estimating fugitive
and vented non-combustion 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, except where direct
activity data was available (e.g., offshore platform counts,
processing plant counts, transmission pipeline miles, and
distribution pipelines). 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 CK4 and non-
combustion CO2 emissions from natural gas systems.
Activity factor data were taken from the following
sources: American Gas Association (AGA 1991-1998);
Minerals and Management Service (MMS 2008a-d); Monthly
Energy Review (EIA 20081); Natural Gas Liquids Reserves
Report (EIA 2005); Natural Gas Monthly (EIA 2008b,c,e);
the Natural Gas STAR Program annual emissions savings
(EPA 2008); Oil and Gas Journal (OGJ 1997-2008);
Office of Pipeline Safety (OPS 2008a-b) and other Energy
Information Administration publications (EIA 2001, 2004,
2008a,d); World Oil Magazine (2008a-b). Data for estimating
emissions from hydrocarbon production tanks were
incorporated (EPA 1999). Coalbed CH4 well activity factors
were taken from the Wyoming Oil and Gas Conservation
Commission (Wyoming 2008) and the Alabama State Oil
and Gas Board (Alabama 2008). Other state well data was
taken from: American Association of Petroleum Geologists
(AAPG 2004); Brookhaven College (Brookhaven 2004);
Kansas Geological Survey (Kansas 2008); Montana Board
of Oil and Gas Conservation (Montana 2008); Oklahoma
Geological Survey (Oklahoma 2008); Morgan Stanley
(Morgan Stanley 2005); Rocky Mountain Production Report
(Lippman (2003); New Mexico Oil Conservation Division
(New Mexico 2008a,b); Texas Railroad Commission (Texas
2008a-d); Utah Division of Oil, Gas and Mining (Utah 2008).
Emission factors were taken from EPA/GRI (1996). GTI's
Unconventional Natural Gas and Gas Composition Databases
(GTI2001) were used to adapt the CFLj emission factors into
non-combustion related CO2 emission factors. Additional
information about CO2 content in transmission-quality
natural gas was obtained via the internet from numerous
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
U.S. transmission companies to help further develop the
non-combustion 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 2007 were
estimated to be between 79.7 and 150.2 Tg CO2 Eq. at a 95
percent confidence level. Natural gas systems non-energy
CO2 emissions in 2007 were estimated to be between 21.8
and 41.1 Tg CO2 Eq. at 95 percent confidence level.
Recalculations Discussion
In the previous Inventory, all activity factors were
estimated using base year activity factors and activity drivers
even if activity data was publicly available for all years in
the time series. This was done to maintain consistency of
methodology across all sources. However, this resulted in
discrepancy in the activity factors in outer years. This is
because activity data in the base year have been revised since
the GPJ activity factors were developed. Additionally, the
oil and gas industry has undergone changes that do not get
reflected in the outer years, if the base year activity factors
are driving the entire time series.
Therefore, where direct activity data were available for
activity factors, the activity factors were replaced with the
direct data for all years to adapt the natural gas Inventory to
publicly available data and adjust the current Inventory to
better reflect emissions from these sources. Direct activity
data are available for shallow water gas platforms, deep
water gas platforms, gas processing plants, transmission
pipeline miles, distribution mains pipeline miles (by pipeline
material), and distribution services (by pipeline material).
This substitution resulted in a 3.5 to 4 percent increase in
CH4 emissions in the inventory time series.
The second recalculation is a result of changing several
base year (1992) activity factors to re-estimated EPA/GPJ
(1996). Methane Emissions from the Natural Gas Industry
report base year activity factors. The GPJ study consists of
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
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Natural Gas Systems
Natural Gas Systems"
CH4
C02
104.7
28.7
Lower Bound0
79.7
21.8
Upper Bound0
150.2
41.1
Lower Bound0
-24%
-24%
Upper Bound0
+43%
+43%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
bAn 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.
c All reported values are rounded after calculation. As a result, lower and upper bounds may not be duplicable from other rounded values as shown in table.
Energy 3-45
-------
direct activity factors and derived activity factors. Direct
activity factors refer to publicly available data, whereas
derived activity factors were obtained by extrapolating
sample data collected from the surveys to national estimates
using direct factors such as gas production, gas throughput,
etc. The base year derived activity factors were re-estimated
by updating the 1992 direct activity factor with the publicly
available data discussed in the previous paragraph.
All other recalculations are the result of updating the
previous Inventory activity data with revised values.
Planned Improvements
Most of the activity factors and emission factors in the
natural gas model are from the EPA/GRI (1996) study. A
study is currently underway to review selected emission
factors in the natural gas industry, and as appropriate, conduct
measurement-based studies to develop updated emission
factors to better reflect current national circumstances.
Results from these studies are expected in the next few
years, and will be incorporated into the Inventory, pending
a peer review.
3.6. Petroleum Systems (IPCC
Source Category 1B2a)
j emissions from petroleum systems are primarily
associated with crude oil production, transportation,
and refining operations. During each of these activities,
CH4 emissions are released to the atmosphere as fugitive
emissions, vented emissions, emissions from operational
upsets, and emissions from fuel combustion. Fugitive and
vented CO2 emissions from petroleum systems are primarily
associated with crude oil production and are negligible in
the transportation and refining operations. Combusted CO2
emissions are already accounted for in the Fossil Fuels
Combustion source category, and hence have not been taken
into account in the Petroleum Systems source category. Total
CFLj and CO2 emissions from petroleum systems in 2007
were 28.8 Tg CO2 Eq. (1,370 Gg CH4) and 0.3 Tg CO2 (287
Gg), respectively. Since 1990, CH4 emissions have declined
by 15 percent, due to industry efforts to reduce emissions
and a decline in domestic oil production (see Table 3-38 and
Table 3-39). Carbon dioxide emissions have also declined
by 24 percent since 1990 due to similar reasons (see Table
3-40 and Table 3-41).
Production Field Operations. Production field operations
account for almost 98 percent of total CFLj emissions from
petroleum systems. Vented CF^ from field operations account
for 91.5 percent of the emissions from the production
sector, unburned CH4 combustion emissions account for 5.2
percent, fugitive emissions are 3.2 percent, and process upset
emissions are slightly over two-tenths of a percent. The most
dominant sources of emissions, in order of magnitude, are
shallow water offshore oil platforms, natural-gas-powered
pneumatic devices (low bleed and high bleed), field storage
tanks, gas engines, chemical injection pumps and deep water
offshore platforms. These seven sources alone emit over 95
percent of the production field operations emissions. Offshore
platform emissions are a combination of fugitive, vented,
and unburned fuel combustion emissions from all equipment
housed on oil platforms producing oil and associated gas.
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. Emissions from storage tanks occur when the CFLj
entrained in crude oil under pressure volatilizes once the
crude oil is put into storage tanks at atmospheric pressure.
Emissions from gas engines are due to unburned CH4 that
vents with the exhaust. Emissions from chemical injection
pumps are due to the 25 percent that use associated gas to
drive pneumatic pumps. The remaining five percent of the
emissions are distributed among 26 additional activities
within the four categories: vented, fugitive, combustion and
process upset emissions. For more detailed, source-level
data on CFLj emissions in production field operations, refer
to Annex 3.5.
Vented CO2 associated with natural gas emissions
from field operations account for 99 percent of the total
CO2 emissions from this source category, while fugitive
and process upsets together account for 1 percent of the
emissions. The most dominant sources of vented emissions
are field storage tanks, pneumatic devices (high bleed and low
bleed), shallow water offshore oil platforms, and chemical
injection pumps. These five sources together account for
98.5 percent of the non-combustion CO2 emissions from
this source category, while the remaining 1.5 percent of the
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-38: CH4 Emissions from Petroleum Systems (Tg C02 Eq.)
Stage
1990
1995
2000
2005
2006
2007
Production Field Operations
Pneumatic Device Venting
Tank Venting
Combustion & Process Upsets
Misc. Venting & Fugitives
Wellhead Fugitives
Crude Oil Transportation
Refining
27.6
8.3
2.8
1.5
14.5
0.4
0.1
0.6
27.6
8.3
2.8
1.5
14.6
0.4
0.1
0.6
28.1
8.4
2.8
1.5
15.0
0.4
0.1
0.6
Total
33.9
32.0
30.3
Note: Totals may not sum due to independent rounding.
Table 3-39: CH4 Emissions from Petroleum Systems (Gg)
28.3
28.3
28.8
Stage
1990
2000
Production Field Operations
Pneumatic Device Venting
Tank Venting
Combustion & Process Upsets
Misc. Venting & Fugitives
Wellhead Fugitives
Crude Oil Transportation
Refining
25
Total
1,613
2005
2006
1,314
396
135
71
694
17
5
28
1,346 1,346
2007
1,338
398
135
72
716
18
5
27
1,370
Note: Totals may not sum due to independent rounding.
Table 3-40: C02 Emissions from Petroleum Systems (Tg C02 Eq.)
Stage
Production Field Operations
Pneumatic Device Venting
Tank Venting
Misc. Venting & Fugitives
Wellhead Fugitives
Total
1990
0.4
0.3
+
+
0.4
1995
0.3
0.3 1
+ 1
+
0.3
2000
0.3
0.3 1
+ 1
+
0.3
2005
0.3
+
0.2
+
+
0.3
2006
0.3
+
0.2
+
+
0.3
2007
0.3
+
0.2
+
+
0.3
+ Less than 0.05 Tg C02 Eq.
Table 3-41: C02 Emissions from Petroleum Systems (Gg)
Stage
1990
2000
Production Field Operations
Pneumatic Device Venting
Tank Venting
Misc. Venting & Fugitives
Wellhead Fugitives
2005
287
22
248
16
1
2006
288
22
249
16
1
2007
287
22
247
16
1
Total
376
341
325
287
288
287
Note: Totals may not sum due to independent rounding.
Energy 3-47
-------
emissions is distributed among 24 additional activities within
the three categories: vented, fugitive and process upsets.
Crude Oil Transportation. Crude oil transportation
activities account for less than one half of one percent of
total CH4 emissions from the oil industry. Venting from tanks
and marine vessel loading operations accounts for 62 percent
of CH4 emissions from crude oil transportation. Fugitive
emissions, almost entirely from floating roof tanks, account
for 19percent. The remaining 19percentis distributed among
six 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 less than two percent of total
CH4 emissions from the oil industry because most of the
CtLj in crude oil is removed or escapes before the crude oil
is delivered to the refineries. There is an insignificant amount
of CtLj 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 blow downs for maintenance and the process of asphalt
blowing—with air, to harden the asphalt—are the primary
venting contributors. Most of the fugitive CK4 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 1996, EPA 1999). 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
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 three EPA studies (1996, 1999 and 2005). 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 and field storage tanks. 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 2004). 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 2007. 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 2008a-c).
For oil storage tanks, the emissions factor was calculated
from API TankCalc data as the total emissions per barrel of
crude charge (EPA 1999).
The methodology for estimating CO2 emissions from
petroleum systems combines vented, fugitive and process
upset emissions sources from 29 activities for crude oil
production field operations. Emissions are estimated for
each activity by multiplying emission factors by their
corresponding activity factors. The emission factors for CO2
are estimated by multiplying the CH4 emission factors by
a conversion factor, which is the ratio of CO2 content and
CH4 content in produced associated gas. The only exceptions
to this methodology are the emission factors for crude
oil storage tanks, which are obtained from API TankCalc
simulation runs.
Activity factors for the years 1990 through 2007 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
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 wells and production
were used, along with the ratios developed for EPA (1996).
In other cases, the activity factor was held constant from
1990 through 2007 based on EPA(1999). Lastly, the previous
year's data were used when data for the current year were
unavailable. The CK4 and CO2 sources in the production
sector share common activity factors. 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 (EIA 1990 through 2007, 1990
through 2008, 1995 through 2008a-b), 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,
2008a-c), analysis of MMS data (EPA 2005, MMS 2004),
the Oil & Gas Journal (OGJ 2008a,b), the Interstate Oil and
Gas Compact Commission (IOGCC 2008), and the United
States Army Corps of Engineers (1995-2008).
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 to
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 the seven major sources, which account for
93.1 percent of the total methane emissions, the uncertainty
surrounding these seven 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 3-42. Because the top
emission sources have not changed from 2006, the relative
uncertainty ranges computed for 2006 and published in the
previous Inventory were taken as valid and applied to the
2007 inventory emission estimates. Petroleum systems CH^
emissions in 2007 were estimated to be between 20.7 and
70.2 Tg CO2 Eq., while CO2 emissions were estimated to be
Table 3-42: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Petroleum Systems
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Petroleum Systems
Petroleum Systems
CH4
C02
28.8
0.3
Lower Bound"
20.7
0.2
Upper Bound"
70.2
0.7
Lower Bound"
-28%
-28%
Upper Bound"
+ 144%
+ 144%
a Range of 2006 relative uncertainty predicted by Monte Carlo Stochastic Simulation, based on 1995 base year activity factors, for a 95 percent confidence
interval.
b All reported values are rounded after calculation. As a result, lower and upper bounds may not be duplicable from other rounded values as shown in table.
Energy 3-49
-------
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, 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 natural 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 Production sections of the Inventory,
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. However, IPCC (2006) notes that if a national regulatory process exists, emissions information
available through that process may support development of C02 emissions estimates for geologic storage.
In October 2007, the U.S. EPA announced plans to develop regulations for geologic sequestration of C02 under the EPA Underground
Injection Control Program. Given that the regulatory process is in its early phases, and site-specific emissions estimates are not yet available,
emissions estimates from C02 capture, transport, injection and geologic storage are not yet included in national totals. Preliminary estimates
indicate that the amount of C02 captured from industrial and natural sites, as well as fugitive emissions from pipelines is 40.0 Tg C02 (40,044
Gg C02) (see Table 3-43 and Table 3-44). 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.
Table 3-43: Potential Emissions from C02 Capture and Transport (Tg C02 Eq.)
Stage
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
22.5
0.7 B
0.0
26.9
2000
2.3
23.2
0.7 B
0.0
26.1
2005
6.0
28.3
0.7
0.0
34.9
2006
6.4
30.2
0.7
0.0
37.3
2007
6.3
33.1
0.7
0.0
40.0
Table 3-44: Potential Emissions from C02 Capture and Transport (Gg)
Stage
Acid Gas Removal Plants
Naturally Occurring C02
Ammonia Production Plants
Pipelines Transporting C02
Total
1990
4,832
20,811
0
8
25,643
1995
3,672
22,547
676
8
26,896
2000
2,264
23,208
676
8
26,149
2005
5,992
8,267
676
7
34,935
2006
6,417
30,224
676
8
37,318
2007
6,282
33,086
676
8
40,044
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
between 0.2 and 0.7 Tg CO2 Eq. at a 95 percent confidence
level. This indicates a range of 28 percent below to 144
percent above the 2007 emission estimates of 28.8 and 0.3
Tg CO2 Eq. for CFL, and CO2, respectively.
Recalculations Discussion
All revisions were due to updating previous years' data
with revised data from existing data sources.
Planned Improvements
As noted above, nearly all emission factors used in the
development of the petroleum systems estimates were taken
from EPA (1995, 1996, 1999), with the remaining emission
factors taken from EPA default values (EPA 2005) and a
consensus of industry peer review panels. These emission
factors will be reviewed as part of future inventory work.
Results of this review and analysis will be incorporated into
future Inventories, as appropriate.
3.7. Incineration of Waste (IPCC
Source Category 1A5)
Incineration is used to manage about 7 to 19 percent of
the solid wastes 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,
ArSova et al. 2008). In the context of this section, waste
includes all municipal solid waste (MSW) as well as tires. In
the United States, almost all incineration of MSW occurs at
waste-to-energy facilities where useful energy is recovered,
and thus emissions from waste incineration are accounted
for in the Energy chapter. Similarly, tires are combusted for
energy recovery in industrial and utility boilers. Incineration
of waste results in conversion of the organic inputs to CO2.
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
incineration 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. As noted above, tires
(which contain rubber and carbon black) are also considered
a "non-hazardous" waste and are included in the waste
incineration estimate, though waste disposal practices for
tires differ from municipal solid waste (viz., most incineration
occurs outside of MSW combustion facilities).
Approximately 32 million metric tons of waste was
incinerated in the United States in 2007 (EPA 2008). Carbon
dioxide emissions from incineration of waste rose 91 percent
since 1990, to an estimated 20.8 Tg CO2 Eq. (20,786 Gg)
in 2007, as the volume of synthetic fibers and other fossil
C-containing materials in waste increased (see Table 3-45
and Table 3-46). Waste incineration is also a source of N2O
emissions (De Soete 1993). Nitrous oxide emissions from
the incineration of waste were estimated to be 0.4 Tg CO2
Eq. (1 Gg N2O) in 2007, and have not changed significantly
since 1990.
Methodology
Emissions of CO2 from the incineration of waste include
CO2 generated by the incineration of plastics, synthetic
fibers, and synthetic rubber, as well as the incineration of
synthetic rubber and carbon black in tires. These emissions
were estimated by multiplying the amount of each material
incinerated by the C content of the material and the fraction
oxidized (98 percent). Plastics incinerated in municipal solid
wastes were categorized into seven plastic resin types, each
Energy 3-51
-------
Table 3-45: C02 and N20 Emissions from the Incineration of Waste (Tg C02 Eq.)
Gas/Stage
1990
1995
2000
2005
2006
2007
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
19.5
12.8
1.2
1.6
1.8
2.2
0.4
19.8
12.9
1.2
1.6
1.8
2.3
0.4
20.8
13.6
1.2
1.6
2.0
2.4
0.4
Total
16.2
17.9
19.9
20.2
21.2
Table 3-46: C02 and N20 Emissions from the Incineration of Waste (Gg)
Gas/Stage
1990
1995
2000
2005
2006
2007
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N20
19,532
12,782
1,207
1,579
1,752
2,212
1
19,824
12,920
1,207
1,579
1,788
2,330
1
20,786
13,622
1,207
1,579
2,000
2,378
1
material 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 incineration sources is
provided in Annex 3.6.
For each of the methods used to calculate CO2 emissions
from the incineration of waste, 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 municipal solid wastes and its portion incinerated
were taken from the Characterization of Municipal Solid
Waste in the United States (EPA2000b, 2002, 2003, 2005a,
2006b, 2007,2008) 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 through 2003, 2006). For 2006
and 2007, synthetic rubber data is set equal to 2005 due to a
lack of more recently available data.
Average C contents for the "Other" plastics category,
synthetic rubber in municipal solid wastes, 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 waste incineration categories for CO2
emissions) was reported in EPA's life cycle analysis of
greenhouse gas emissions and sinks from management of
solid waste (EPA 2006a).
Incineration of waste also results in emissions of N2O.
These emissions were calculated as a function of the total
estimated mass of waste incinerated and an emission factor.
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-47: Municipal Solid Waste Generation (Metric
Tons) and Percent Combusted
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
2007
Waste Generation
266,365,714
296,390,405
^^^^^^^^^^^H
371,071,109
353,086,962a
335,102,816
343,482,645"
351,862,474
363,274,720
374,686,965
374,686,965C
Incinerated (%)
11.5
10.0
^^^^^^^^^B
^^^^^^^^^H
7.0
7.4a
7.7
7.6b
7.4
7.2
6.9
6.9C
'Interpolated between 2000 and 2002 values.
b Interpolated between 2002 and 2004 values.
c Assumed equal to 2006 value.
Source: ArSova et al. (2008).
The N2O emission estimates are based on different data
sources than the CO2 emission estimates. As noted above,
N2O emissions are a function of total waste incinerated in
each year; for 1990 through 2006, these data were derived
from the information published in BioCycle (ArSova et al.
2008). Data on total waste incinerated was not available for
2007, so this value was assumed to equal the most recent
value available (2006). Table 3-47 provides data on municipal
solid waste generation and percentage combusted for the
total waste stream. The emission factor of N2O emissions per
quantity of municipal solid waste combusted is an average of
values from IPCC's Good Practice Guidance (2000).
Uncertainty
ATier 2 Monte Carlo analysis was performed to determine
the level of uncertainty surrounding the estimates of CO2
emissions and N,O emissions from the incineration of waste.
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 incineration emission
estimates arise from both the assumptions applied to
the data and from the quality of the data. Key factors
include MSW incineration rate; fraction oxidized; missing
data on waste composition; average C content of waste
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 3-48. Waste incineration
CO2 emissions in 2007 were estimated to be between 15.2
and 25.0 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 27 percent below to 20 percent above
the 2007 emission estimate of 20.8 Tg CO2 Eq. Also at a 95
percent confidence level, Waste incineration N2O emissions
in 2007 were estimated to be between 0.1 and 1.2 Tg CO2
Table 3-48: Tier 2 Quantitative Uncertainty Estimates for C02 and N20 from the Incineration of Waste
(Tg C02 Eq. and Percent)
Source
Incineration of Waste
Incineration of Waste
2007 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
C02
N20
20.8
0.4
Lower Bound
15.2
0.1
Upper Bound
25.0
1.2
Lower Bound
-27%
-71%
Upper Bound
+20%
+ 191%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Energy 3-53
-------
Eq. This indicates a range of 71 percent below to 191 percent
above the 2007 emission estimate of 0.4 Tg CO2 Eq.
QA/QC and Verification
A source-specific QA/QC plan was implemented for
incineration of waste. 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 incineration of waste. Trends
across the time series were analyzed to determine whether
any corrective actions were needed. Actions were taken to
streamline the activity data throughout the incineration of
waste calculations.
Recalculations Discussion
This emissions source was previously known as
Municipal Solid Waste Combustion.
Planned Improvements
Additional data sources for calculating an N2O emission
factor for U.S. incineration of waste may be investigated. In
conjunction with its efforts to develop methods for reporting
GHG emissions from various sources, the use of new
techniques using radiochemistry methods to directly measure
the fossil C content of flue gas from the incineration of waste
may also be investigated.
3.8. 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-CH^ volatile organic
compounds (NMVOCs) from energy-related activities from
1990 to 2007 are reported in Table 3-49.
Methodology
These emission estimates were obtained from preliminary
data (EPA 2008), 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
Table 3-49: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
NO,
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Incineration of Waste
International Bunker Fuels3
CO
Mobile Combustion
Stationary Combustion
Incineration of Waste
Oil and Gas Activities
International Bunker Fuels3
NMVOCs
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Incineration of Waste
International Bunker Fuels3
20,829
10,920
9,689
139
82
2,020
125,640
119,360
5,000
978
302
130
12,620
10,932
912
554
222
61
20,429
10,622
9,619
100
14,129
8,271
5,445
316
98
1,719
64,876
58,322
4,792
1,438
323
130
8,198
5,954
1,470
535
239
54
13,687
7,831
5,445
314
97
1,712
61,231
54,678
4,792
1,438
323
127
7,903
5,672
1,470
526
234
54
a 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.
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
3.9. International Bunker
Fuels (IPCC Source Category 1:
Memo Items)
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
Intergovernmental Negotiating Committee in establishing the
Framework Convention on Climate Change.39 These decisions
are reflected in the Revised 1996 IPCC Guidelines, as well as
the 2006 IPCC 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).40
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.41 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.42
Emissions of CO2 from aircraft are essentially a
function of fuel use. Methane and N2O emissions also
depend upon engine characteristics, flight conditions,
and flight phase (i.e., take-off, climb, cruise, decent, and
landing). Methane 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,
39 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. Ic).
40 Note that the definition of international bunker fuels used by the UNFCCC
differs from that used by the International Civil Aviation Organization.
41 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).
42 Naphtha-type jet fuel was used in the past by the military in turbojet and
turboprop aircraft engines.
Energy 3-55
-------
international bunker fuels are solely related to cargo and
passenger carrying vessels, which is the largest of the four Emissions of CO2 were estimated by applying C
categories, and military vessels. Two main types of fuels content ^ fraction oxidized factors to fuel consumption
are used on sea-going vessels: distillate diesel fuel and actiyity data This approach is analogous to that described
residual fuel oil. Carbon dioxide is the primary greenhouse under ^ from Fossil Fud Combustion. Carbon content
gas emitted from marine shipping. aad fraction oxidized factors for jet fuel, distillate fuel oil,
Overall, aggregate greenhouse gas emissions in 2007 and residual fuel oil were taken directly from EIA and are
from the combustion of international bunker fuels from presented in Annex 2.1, Annex 2.2, and Annex 3.7 of this
both aviation and marine activities were 109.9 Tg CO2 Eq., Inventory. Density conversions were taken from Chevron
or five percent below emissions in 1990 (see Table 3-50 (2000), ASTM (1989), and USAF (1998). Heat content
and Table 3-51). Although emissions from international for distillate fuel oil and residual fuel oil were taken from
flights departing from the United States have increased (14 EIA (2008) and USAF (1998), and heat content for jet fuel
percent), emissions from international shipping voyages was taken from EIA (2008). A complete description of the
departing the United States have decreased by 18 percent methodology and a listing of the various factors employed
since 1990. The majority of these emissions were in the can be found in Annex 2.1. See Annex 3.7 for a specific
form of CO2; however, small amounts of CH^ and N2O were discussion on the methodology used for estimating emissions
also emitted. from international bunker fuel use by the U.S. military.
Table 3-50: C02, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.)
Gas/Mode 1990 1995 2000 2005 2006 2007
C02 114.3 101.6 99.0 111.5 110.5 108.8
Aviation 46.4 51.2 57.7 56.4 54.6 52.7
Marine 68.0 50.4 41.3 55.1 56.0 56.0
CH4 0.2 0.11 0.11 0.1 0.1 0.1
Aviation +1 +1 +1 + + +
Marine 0.11 0.11 0.11 0.1 0.1 0.1
N20 1.11 0.9 0.9 1.0 1.0 1.0
Aviation 0.51 0.61 0.61 0.6 0.6 0.6
Marine 05 04 03 0.4 0.4 0.4
Total 115.6 102.7 100.0 112.7 111.7 109.9
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-51: C02, CH4, and N20 Emissions from International Bunker Fuels (Gg)
Gas/Mode 1990 1995 2000 2005 2006 2007
C02
Aviation
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Emission estimates for CK4 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 CELj and N2O emissions were obtained from
the Revisedl 996IPCC Guidelines (IPCCIUNEPIOECDIIEA
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 CELj 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 CFLj 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 derived
from FAA's System for assessing Aviation Global Emissions
(SAGE) Model (FAA 2006). International aviation bunker
fuel consumption from 1990-2007 was calculated by
assigning the difference between the sum of domestic
activity data (in TBtu) from SAGE and the reported EIA
transportation jet fuel consumption to the international
bunker fuel category for jet fuel from EIA (2008). 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
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 2008). 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 3-52. 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 2008) for 1990 through 2001, and 2007, and
the Department of Homeland Security's Bunker Report for
2003 through 2006 (DHS 2008). Fuel consumption data for
2002 was interpolated due to inconsistencies in reported
fuel consumption data. Activity data on distillate diesel
consumption by military vessels departing from U.S. ports
were provided by DESC (2008). 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 3-53.
Table 3-52: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
1990
1995
2000
2005
2006
2007
U.S. and Foreign Carriers
U.S. Military
4,932
862
5,462
581
6,158
480
6,022
462
5,823
400
5,629
410
Total
5,794
6,043
6,638
6,484
6,223
6,039
Note: Totals may not sum due to independent rounding.
Table 3-53: 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
61/1
522
5,920
1995
3,495
5731
334
4,402
2000
2,967
290 1
329
3,586
2005
3,881
444
471
4,796
2006
4,004
446
414
4,864
2007
4,059
358
444
4,861
Note: Totals may not sum due to independent rounding.
Energy 3-57
-------
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.43
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.
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, emission 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 estimates 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 1996IPCC 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 COj.44
There is also concern as to the reliability of the existing
DOC (1991 through 2008) data on marine vessel fuel
consumption reported at U.S. customs stations due to the
significant degree of inter-annual variation.
43 See uncertainty discussions under CO2 Emissions from Fossil Fuel
Combustion.
44U.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 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.
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
Recalculations Discussion
Historical activity data for aviation was revised for both
U.S. and foreign carriers. International jet fuel bunkers are
now calculated in tandem with the domestic jet fuel estimates.
EPA performs the analysis for domestic activity data (in
TBtu), as described in the CO2 from fossil fuel combustion
section, and, using that calculated total for domestic in
comparison with EIA's total consumption activity data,
assigns the remainder to the jet fuel bunkers consumption.
The previous method for international jet fuel bunkers were
calculated based upon DOT (1991 through 2008) and BEA
(1991 through 2005) data for the years 1990-1999 and
2006-2007 and estimated by FAA (2006) for 2000-2005.
That data is still collected and used to quality assure the
new method. The new method is understood to reduce
the uncertainty of the domestic emissions calculation, as
it relies on one dataset, rather than the multiple datasets
that were used in the previous method for international jet
fuel bunkers. Distillate and residual fuel oil consumption
by cargo or passenger carrying marine vessels from 2003
through 2006 was revised using DHS (2008), and 2002
distillate and residual fuel oil consumption was interpolated
to adjust inconsistencies in reported fuel consumption data.
These historical data changes resulted in changes to the
emission estimates for 1990 through 2006, which averaged
to an annual increase in emissions from international bunker
fuels of 6.6 Tg CO2 Eq. (7.0 percent) in CO2 emissions, an
annual increase of less than 0.1 Tg CO2 Eq. (14 percent) in
CH4 emissions, and an annual increase of 0.1 Tg CO2 Eq.
(12 percent) in N2O emissions.
3.10. Wood Biomassand
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 2007, total CO2 emissions from the burning of woody
biomass in the industrial, residential, commercial, and
electricity generation sectors were approximately 209.8 Tg
CO2 Eq. (209,785 Gg) (see Table 3-54 and Table 3-55). As
the largest consumer of woody biomass, the industrial sector
was responsible for 65 percent of the CO2 emissions from this
source. The residential sector was the second largest emitter,
constituting 23 percent of the total, while the commercial and
electricity generation sectors accounted for the remainder.
Biomass-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
cleaner than gasoline (i.e., lower in NOX and hydrocarbon
Energy 3-59
-------
Table 3-54: 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 1
13.3
215.2
1995
155.1
53.6
7.5l
12.9
229.1
2000
153.6
43.3
7.4
13.9
218.1
2005
136.3
46.4
7.2
19.1
208.9
2006
142.2
42.3
6.7
18.7
209.9
2007
136.7
47.4
6.7
18.9
209.8
Note: Totals may not sum due to independent rounding.
Table 3-55: C02 Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
135,
59,
6,
13,
215,
348
808
779
252
186
1995
155,
53,
7,
12,
229,
075
621
463
932
091
2000
153,
43,
7,
13,
218,
559
309
370
851
088
2005
136
,269
46,402
7
19
208
,182
,074
,927
2006
142
42
6
18
209
,226
,278
,675
,748
,926
2007
136,729
47,434
6,675
18,947
209,785
Note: Totals may not sum due to independent rounding.
emissions), and have been employed in urban areas with poor
air quality. However, because ethanol is a hydrocarbon fuel,
its combustion emits CO2.
In 2007, the United States consumed an estimated
577 trillion Btu of ethanol, and as a result, produced
approximately 38.0 Tg CO2 Eq. (38,044 Gg) (seeTable 3-56
and Table 3-57) 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 EIA gross heat contents (Lindstrom 2006) to U.S.
consumption data (EIA 2008) (see Table 3-58), 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
(15432359 MMBtu/MT wood and wood waste) was applied
to the consumption data for the other sectors. An EIA
Table 3-56: C02 Emissions from Ethanol Consumption (Tg C02 Eq.)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990
4.1
0.1
+
4.2
1995
7.6
0.1 1
+
7.7
2000
9.1
°l
9.2
2005
22.0
0.5
0.1
22.6
2006
29.8
0.6
0.1
30.5
2007
37.2
0.8
0.1
38.0
+ Less than 0.05 Tg C02 Eq.
Table 3-57: C02 Emissions from Ethanol Consumption (Gg)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990
4,066
55
33
4,155
1995
7,570
1041
9
7,683
2000
9,077
85 1
25
9,188
2005
22,034
460
59
22,554
2006
29,758
622
80
30,459
2007
37,168
111
100
38,044
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 3-58: Woody Biomass Consumption by Sector (Trillion Btu)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
Table 3-59: Ethanol
End-Use Sector
Transportation
Industrial
Commercial
Total
1990
1,442
580 1
eel
129
2,216
Consumption by Sector (Trillion Btu)
1990
61.7
0.8 1
0.5
63.0
1995
1,652
520 1
72 1
125
2,370
1995
114.8
1.6
0.1
116.5
2000
1,636
420 1
134
2,262
2000
137.6
1.3
0.4
139.3
2005
1,452
450
70
185
2,156
2005
334.1
7.0
0.9
342.0
2006
1,515
410
65
182
2,172
2006
451.2
9.4
1.2
461.9
2007
1,457
460
65
184
2,165
2007
563.6
11.8
1.5
576.9
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
factor of 17.99 Tg C/QBtu (Lindstrom 2006) to U.S. ethanol
consumption estimates that were provided in energy units
(EIA 2008) (see Table 3-59).
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 decrease 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.
Recalculations Discussion
Wood consumption values were revised in 2001 through
2003, and 2005 through 2006 based on updated information
from EIA's Annual Energy Review (EIA 2008). EIA (2008)
also reported minor changes in wood consumption for
all sectors in 2006. This adjustment of historical data for
wood biomass consumption resulted in an average annual
increase in emissions from wood biomass consumption
of 0.6 Tg CO2 Eq. (0.3 percent) from 1990 through 2006.
Slight adjustments were made to ethanol consumption based
on updated information from EIA (2008), which slightly
decreased estimates for ethanol consumed. As a result of
these adjustments, average annual emissions from ethanol
consumption decreased by less than 0.1 Tg CO2 Eq. (less
than 0.1 percent).
Energy 3-61
-------
4. Industrial Processes
Greenhouse gas emissions are produced as the byproducts 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 production, lime production,
ammonia production and urea consumption, limestone and dolomite use (e.g., flux stone, flue gas desulfurization, and
glass manufacturing), soda ash production and use, aluminum production, titanium dioxide production, CO2 consumption,
ferroalloy production, phosphoric acid production, zinc production, lead production, petrochemical production, silicon
carbide production and consumption, 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 2007, industrial processes generated emissions of 353.8
teragrams of CO2 equivalent (Tg CO2 Eq.), or 5 percent of
Figure 4-1
2007 Industrial Processes Chapter
Greenhouse Gas Emission Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production &
Metallurgical Coke Production
Cement Production
Nitric Acid Production |
HCFC-22 Production f
Lime Production |
Ammonia Production and Urea Consumption |
Electrical Transmission and Distribution |
Aluminum Production |
Limestone and Dolomite Use |
Adipic Acid Production |
Semiconductor Manufacture |
SodaAsb Production and Consumption
Petrocbemical Production
Magnesium Production and Processing
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Pbospboric Acid Production
Zinc Production
Lead Production | <0.5
Silicon Carbide Production and Consumption I <0.5
Industrial Processes
as a Portion of
all Emissions
0
25
50 75
TgCO,Eq.
100 125
Industrial Processes 4-1
-------
total U.S. greenhouse gas emissions. Carbon dioxide emissions
from all industrial processes were 174.9 Tg CO2 Eq. (174,939
Gg) in 2007, or 3 percent of total U.S. CO2 emissions. CH4
emissions from industrial processes resulted in emissions of
approximately 1.7 Tg CO2 Eq. (82 Gg) in 2007, which was less
than 1 percent of U.S. CFLj emissions. Nitrous oxide emissions
from adipic acid and nitric acid production were 27.6 Tg CO2
Eq. (89 Gg) in 2007, or 9 percent of total U.S. N2O emissions.
In 2007, combined emissions of HFCs, PFCs and SF6 totaled
149.5 Tg CO2 Eq. Overall, emissions from industrial processes
increased by 9 percent from 1990 to 2007 despite decreases in
emissions from several industrial processes, such as cement
production, lime production, limestone and dolomite use, soda
ash production and consumption, and electrical transmission
and distribution. The increase in overall emissions was
driven by a rise in the emissions originating from HCFC-
22 production 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. The
source descriptions that follow in the chapter are presented
in the order as reported to the UNFCCC in the common
reporting format tables, corresponding generally to: mineral
products, chemical production, metal production, and
emissions from the uses of HFCs, PFCs, and SF6.
QA/QC and Verification Procedures
Tier 1 quality assurance and quality control procedures
have been performed for all industrial process sources. For
industrial process sources of CO2 and CH4 emissions, a
detailed plan was developed and implemented. This plan
was based on U.S. strategy, but was tailored to include
specific procedures recommended for these sources. Two
types of checks were performed using this plan: (1) general,
or Tier 1, procedures that focus on annual procedures and
checks to be used when gathering, maintaining, handling,
documenting, checking and archiving the data, supporting
documents, and files, and (2) source-category specific, or
Tier 2, procedures that focus on procedures and checks of the
emission factors, activity data, and methodologies used for
estimating emissions from the relevant Industrial Processes
sources. Examples of these procedures include, among
others, checks to ensure that activity data and emission
estimates are consistent with historical trends; that, where
possible, consistent and reputable data sources are used
across sources; that interpolation or extrapolation techniques
are consistent across sources; and that common datasets and
factors are used where applicable.
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
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 datais 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 2007 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
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-1: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
1990
1995
2000
Total
325.2
345.8
356.3
2005
337.6
2006
343.9
2007
C02 197.6 198.6 193.2 171.1 175.9 174.9
Iron and Steel Production and Metallurgical
Coke Production 109.8 103.1 95.1 73.2 76.1 77.4
Iron and Steel Production 104.3 98.1 90.7 69.3 72.4 73.6
Metallurgical Coke Production 5.sl 5.ol 4.^1 3.8 3.7 3.8
Cement Production 33.3 36.8 41.2 45.9 46.6 44.5
Ammonia Production & Urea Consumption 16.8 17.8 16.4 12.8 12.3 13.8
Lime Production 11.5 13.3 14.1 14.4 15.1 14.6
Limestone and Dolomite Use 5.11 6.71 5.11 6.8 8.0 6.2
Aluminum Production 6.8 5.71 6.11 4.1 3.8 4.3
Soda Ash Production and Consumption 4.11 4.sB 4.2! 4.2 4.2 4.1
Petrochemical Production 2.2 2.8 3.01 2.8 2.6 2.6
Titanium Dioxide Production 1.2 1.51 1.81 1.8 1.9 1.9
Carbon Dioxide Consumption 1.4 1.4 1.4 1.3 1.7 1.9
Ferroalloy Production 2.2 2.01 1.91 1.4 1.5 1.6
Phosphoric Acid Production 1.51 1.51 1.4 1.4 1.2 1.2
Zinc Production 0.91 1.01 1.11 0.5 0.5 0.5
Lead Production 0.31 0.31 0.31 0.3 0.3 0.3
Silicon Carbide Production and Consumption 0.4! 0.31 0.2! 0.2 0.2 0.2
Petrochemical Production 0.91 1.11 1.2 1.1 1.0 1.0
Iron and Steel Production and Metallurgical
Coke Production 1.0 1.0 0.9 0.7 0.7 0.7
Iron and Steel Production 7.ol 7.ol O.sl 0.7 0.7 0.7
Metallurgical Coke Production +1 +1 +1 + + +
Ferroalloy Production +1 +1 +1 + + +
Silicon Carbide Production and Consumption + +1 +1 + + +
N20 35.3 39.6 28.1 24.6 24.2 27.6
Nitric Acid Production 20.0 22.3 21.9 18.6 18.2 21.7
Adipic Acid Production 15.3 17.3 6.2 5.9 5.9 5.9
MFCs 36.9 61.8 100.1 116.1 119.1 125.5
Substitution of Ozone Depleting Substances3 0.31 28.5 71.2 100.0 105.0 108.3
HCFC-22 Manufacture 36.4 33.0 28.6 15.8 13.8 17.0
Semiconductor Manufacturing MFCs 0.2! 0.31 0.31 0.2 0.3 0.3
PFCs 20.8 15.6 13.5 6.2 6.0 7.5
Aluminum Production 18.5 11.8 8.6 3.0 2.5 3.8
Semiconductor Manufacturing PFCs 2.2 3.8 4.91 3.2 3.5 3.7
SF6 32.8 28.1 19.2 17.9 17.1 16.5
Electrical Transmission and Distribution 26.8 21.6 15.1 14.0 13.2 12.7
Magnesium Production and Processing 5.41 5.eB 3.0 2.9 2.9 3.0
Semiconductor Manufacturing SF6 0.51 0.91 1.11 1.0 1.0 0.8
353.8
+ Does not exceed 0.05 Tg C02 Eq.
a Small amounts of RFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
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.
Industrial Processes 4-3
-------
Table 4-2: Emissions from Industrial Processes (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
C02 197,623
Iron and Steel Production and Metallurgical
Coke Production
Iron and Steel Production
Metallurgical Coke Production
Cement Production
Ammonia Production & Urea Consumption
Lime Production
Limestone and Dolomite Use
Aluminum Production
Soda Ash Production and Consumption
Petrochemical Production
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Phosphoric Acid Production
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
CH4
Petrochemical Production
Iron and Steel Production and Metallurgical
Coke Production
Iron and Steel Production
Metallurgical Coke Production
Ferroalloy Production
Silicon Carbide Production and Consumption
N20
Nitric Acid Production
Adipic Acid Production
MFCs
Substitution of Ozone Depleting Substances3
HCFC-22 Manufacture
Semiconductor Manufacturing MFCs
PFCs
Aluminum Production
Semiconductor Manufacturing PFCs
SF6
Electrical Transmission and Distribution
Magnesium Production and Processing
Semiconductor Manufacturing SF6
+ Does not exceed 0.5 Gg.
M (Mixture of gases).
a Small amounts of RFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
198,584
103,116
98,078
5,037
36,847
17,796
13,325
6,651
193,217
95,062
90,680
4,381
41,190
16,402
14,088
5,056
171,075 175,897 174,939
73,190
69,341
3,849
45,910
12,849
14,379
6,768
4,142
4,228
2,804
1,755
1,321
1,392
1,386
465
266
219
86
51
34
34
79
60
19
M
M
1
M
M
M
1
1
76,100
72,418
3,682
46,562
12,300
15,100
8,035
3,801
4,162
2,573
1,876
1,709
1,505
1,167
529
270
207
83
48
35
35
78
59
19
M
M
1
M
M
M
1
1
77,370
73,564
3,806
44,525
13,786
14,595
6,182
4,251
4,140
2,636
1,876
1,867
1,552
1,166
530
267
196
82
48
33
33
89
70
19
M
M
1
M
M
M
1
1
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
4.1. Cement Production
(IPCC Source Category 2A1)
Cement production 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.1 Cement is produced in 37 states
and Puerto Rico. Carbon dioxide emitted from the chemical
process of cement production is the second largest source of
industrial CO2 emissions in the United States.
During the cement production proces s, calcium carbonate
(CaCO3) is heated in a cement kiln at a temperature of about
1,450°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 and non-
carbonates are 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 byproduct CO2 being released to the atmosphere.
The clinker is then allowed to cool, mixed with a small
amount of gypsum, and potentially other materials (e.g.,
slag) and used to make portland cement.2
In 2007, U.S. clinker production—including Puerto
Puco—totaled 86,106 thousand metric tons (van Oss 2008b).
The resulting emissions of CO2 from 2007 cement production
were estimated to be 44.5 Tg CO2 Eq. (44,525 Gg) (see
Table 4-3).
After falling in 1991 by 2 percent from 1990 levels,
cement production emissions grew every year through 2006,
and then decreased slightly from 2006 to 2007. Overall, from
1990 to 2007, emissions increased by 34 percent. Cement
continues to be a critical component of the construction
industry; therefore, the availability of public construction
Table 4-3: C02 Emissions from Cement Production
(Tg C02 Eq. and Gg)
1 The CO2 emissions related to the consumption of energy for cement
manufacture are accounted for under CO2 from Fossil Fuel Combustion
in the Energy chapter.
2 Approximately six percent of total clinker production is used to produce
masonry cement, which is produced using plasticizers (e.g., ground
limestone, lime) and portland cement. Carbon dioxide emissions that result
from the production of lime used to create masonry cement are included in
the Lime Manufacture source category (van Oss 2008c).
Year
Tg C02 Eq.
Gg
1990
33.3
33,278
2005
2006
2007
45,910
46,562
44,525
funding, as well as overall economic growth, have had
considerable influence on cement production.
Methodology
Carbon dioxide emissions from cement production
are created by the chemical reaction of carbon-containing
minerals (i.e., calcining limestone) in the cement kiln. 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 CaCO3 (i.e., limestone) heated in the clinker kiln forms
one mole of lime (CaO) and one mole of CO2:
CaCO3 + heat -» CaO + CO2
Carbon dioxide 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 65 percent (van Oss
2008c) and a constant reflecting the mass of CO2 released
per unit of lime. This calculation yields an emission factor
of 0.51 tons of CO2 per ton of clinker produced, which was
determined as follows:
EFQlnker = 0.65 CaO x
44.01 g/mole CO2
56.08 g/mole CaO
= 0.51 tons CO2/ton clinker
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
Industrial Processes 4-5
-------
Table 4-4: Clinker Production (Gg)
Uncertainty
Year
Clinker
88,783
90,045
86,106
are not accounted for by the clinker emission factor. The IPCC
recommends that these additional CKD CO2 emissions should
be estimated as 2 percent of the CO2 emissions calculated from
clinker production.3 Total cement production emissions were
calculated by adding the emissions from clinker production
to the emissions assigned to CKD (IPCC 2006)4
The 1990 through 2007 activity data for clinker
production (see Table 4-4) were obtained through a personal
communication with Hendrik van Oss (van Oss 2008b) of the
USGS and through the USGS Minerals Yearbook: Cement
Annual Report (US Bureau of Mines 1990 through 1993,
USGS 1995 through 2006). The data were compiled by
USGS through questionnaires sent to domestic clinker and
cement manufacturing plants.
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 cement
kiln. Uncertainty is also associated with the assumption
that all calcium-containing raw material is CaCO3 when a
small percentage likely consists of other carbonate and non-
carbonate raw materials. The lime content of clinker varies
from 60 to 67 percent (van Oss 2008b). 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 CaCO3. 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 Production CO2
emissions were estimated to be between 38.8 and 50.5 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 44.5 Tg CO2 Eq.
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Cement Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Cement Production
CO,
44.5
38.8
50.5
-13%
+ 13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
3 Default IPCC clinker and CKD emission factors were verified through
expert consultation with the Portland Cement Association (PCA 2008) and
van Oss (2008a).
4 The 2 percent CO2 addition associated with CKD is included in the
emission estimate for completeness. The cement emission estimate also
includes an assumption that all raw material is limestone (CaCO3) when
in fact a small percentage is likely composed of non-carbonate materials.
Together these assumptions may result in a small emission overestimate
(van Oss 2008c).
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Recalculations
Estimates of CO2 emissions from cement production
were revised for 2006 to reflect updates to the clinker
production data for that year.
Planned Improvements
Future improvements to the cement source category
involve continued research into emission factors for clinker
production and CKD. Research has been conducted into the
accuracy and appropriateness of default emission factors
and reporting methodology used by other organizations. As
these methodologies continue to develop, the cement source
category will be updated with any improvements to IPCC
assumptions for clinker and CKD emissions.
4.2. Lime Production
(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. 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 ([CaOMgO]); and dolomitic hydrate
([Ca(OH)2»MgO] or [Ca(OH)2»Mg(OH)2]).
Lime production involves three main processes:
stone preparation, calcination, and hydration. Carbon
dioxide 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) production.5 In certain additional applications, lime
reabsorbs CO2 during use.
Lime production in the United States—including Puerto
Rico—was reported to be 20,192 thousand metric tons in 2007
Table 4-6: C02 Emissions from Lime Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
11.5
11,533
2005
2006
2007
14,379
15,100
14,595
Table 4-7: Potential, Recovered, and Net C02 Emissions
from Lime Production (Gg)
Year
Potential
Recovered3 Net Emissions
1990
12,004
471
11,533
2005
2006
2007
15,131
15,825
15,264
752
725
669
14,379
15,100
14,595
5 PCC is obtained from the reaction of CO2 with calcium hydroxide. It is
used as a filler and/or coating in the paper, food, and plastic industries.
Note: Totals may not sum due to independent rounding.
aFor sugar refining and PCC production.
(USGS 2008). This resulted in estimated CO2 emissions of 14.6
Tg CO2 Eq. (or 14,595 Gg) (see Table 4-6 and Table 4-7).
The contemporary lime market is distributed across five
end-use categories as follows: metallurgical uses, 36 percent;
environmental uses, 29 percent; chemical and industrial uses,
22 percent; construction uses, 12 percent; and refractory
dolomite, 1 percent. In the construction sector, lime is used
to improve durability in plaster, stucco, and mortars, as
well as to stabilize soils. In 2007, the amount of lime used
for construction decreased by 8 percent from 2006 levels.
This is most likely a result of increased prices for lime and
the downturn in new home construction; total construction
spending decreased by 3 percent and residential construction
spending decreased by nearly 18 percent compared with
2006 (USGS 2008).
Lime production in 2007 decreased by 4 percent
compared to 2006, owing to a downturn in major markets
including construction, mining, and steel (USGS 2008).
Overall, from 1990 to 2007, lime production has increased
by 28 percent. Annual consumption for industrial/chemical
Industrial Processes 4-7
-------
and environmental lime consumption decreased by 1
percent and 4 percent, respectively (USGS 2008). The
decrease in environmental production for environmental
uses is attributed to a decrease in lime consumption for
drinking water treatment, sludge treatment, and the utility
power-plant market for flue gas desulfurization (USGS
2008). Lime production also decreased for metallurgical
consumption, owing to a shift in steel production from basic
oxygen furnaces (BOF) to electric arc furnaces (EAF). EAFs
use iron and steel scrap as their primary iron source which
contains fewer impurities and requires less than one-half
of the lime per ton of steel produced than pig iron used by
BOFs (USGS 2008).
Methodology
During the calcination stage of lime production, CO2
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) (IPCC 2006). The emission factors were calculated
as follows:
For high-calcium lime:
[(44.01 g/mole CO2) •*- (56.08 g/mole CaO)] x
(0.95 CaO/lime) = 0.75 g CO2/g lime
For dolomitic lime:
[(88.02 g/mole CO2) •*- (96.39 g/mole CaO)] x
(0.95 CaO/lime) = 0.87 g CO2/g 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 emission estimates were multiplied by a factor of
1.02 to account for lime kiln dust (LKD), which is produced
as a byproduct during the production of lime (IPCC 2006).
Lime emission estimates were further adjusted to account
for PCC producers and sugar refineries that recover CO2
emitted by lime production facilities and use the captured
CO2 as an input into production or refining processes.
For CO2 recovery by sugar refineries, lime consumption
estimates from USGS were multiplied by a CO2 recovery
factor to determine the total amount of CO2 recovered from
lime production facilities. According to industry surveys,
sugar refineries use captured CO2 for 100 percent of their
CO2 input (Lutter 2008). Carbon dioxide recovery by PCC
producers was determined by multiplying estimates for the
percentage CO2 of production weight for PCC production
at lime plants, by a CO2 recovery factor of 93 percent for
2007 (Prillaman 2008). As data were only available for
2007, CO2 recovery for the period 1990 through 2006 were
extrapolated by determining a ratio of PCC production at
lime facilities to lime consumption for PCC (USGS 2002
through 2007, 2008).
Lime production data (high-calcium- and dolomitic-
quicklime, high-calcium- and dolomitic-hydrated, and dead-
burned dolomite) for 1990 through 2007 (see Table 4-8) were
obtained from USGS (1992 through 2007). Natural hydraulic
Table 4-8: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated,
and Dead-Burned-Dolomite Lime Production (Gg)
Year
High-Calcium
Quicklime
Dolomitic
Quicklime
High-Calcium
Hydrated
Dolomitic
Hydrated
Dead-Burned
Dolomite
2005
2006
2007
14,100
15,000
14,700
2,990
2,950
2,700
2,220
2,370
2,240
474
409
352
200
200
200
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-9: Adjusted Lime Production3 (Gg)
Year
High-Calcium Dolomitic
1990
1995
2000
12,514
^H
14,700
^^^^^^^^H
15,473
2,809
3,207
^^^^^^^H
3,506
2005
2006
2007
15,781
16,794
16,396
3,535
3,448
3,156
a Minus water content of hydrated lime.
lime, which is produced from CaO and hydraulic calcium
silicates, is not produced in the United States (USGS 2008).
Total lime production was adjusted to account for the water
content of hydrated lime by converting hydrate to oxide
equivalent, based on recommendations from the IPCC Good
Practice Guidance and is presented in Table 4-9 (USGS
1992 through 2007, IPCC 2000). The CaO and CaOMgO
contents of lime were obtained from IPCC (2006). Since data
for the individual lime types (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. Lime consumed by
PCC producers and sugar refineries was obtained from USGS
(1992 through 2007).
Uncertainty
The uncertainties contained in these estimates can be
attributed to slight differences in the chemical composition
of these products and recovery rates for sugar refineries and
PCC manufacturers located at lime plants. 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 produce lime
with exactly the same properties.
In addition, a portion of the CO2 emitted during lime
production 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, CO2 reacts with the lime
to create calcium carbonate (e.g., water softening). Carbon
dioxide reabsorption rates vary, however, depending on the
application. For example, 100 percent of the lime used to
produce PCC 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.6
In some cases, lime is generated from calcium carbonate
byproducts at pulp mills and water treatment plants.7 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 (Miner and
Upton 2002).
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.
Uncertainties also remain surrounding recovery rates
used for sugar refining and PCC production. The recovery rate
for sugar refineries is based on two sugar beet processing and
refining facilities located in California that use 100 percent
recovered CO2 from lime plants (Lutter 2008). This analysis
assumes that all sugar refineries located on-site at lime plants
6 Representatives of the National Lime Association estimate that CO2
reabsorption that occurs from the use of lime may offset as much as a quarter
of the CO2 emissions from calcination (Males 2003).
7 Some carbide producers may also regenerate lime from their calcium
hydroxide byproducts, 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 [CaCO3]. 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.
Industrial Processes 4-9
-------
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lime Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lime Production
CO,
14.6
13.5
15.9
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
also use 100 percent recovered CO2. The recovery rate for
PCC producers located on-site at lime plants is based on the
2007 value for PCC manufactured at commercial lime plants,
given by the National Lime Association (Prillaman 2008).
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-10. Lime CO2 emissions
were estimated to be between 13.5 and 15.9 Tg CO2 Eq.
at the 95 percent confidence level. This indicates a range
of approximately 8 percent below and 9 percent above the
emission estimate of 14.6 Tg CO2 Eq.
Recalculations Discussion
Estimates of CO2 emissions from lime production were
revised for years 1990 through 2006 to include estimates of
CO2 recovery from PCC production and sugar refining. On
average, these revisions resulted in an annual decrease in
emissions of approximately 13 percent.
Planned Improvements
Future improvements to the lime source category involve
continued research into CO2 recovery associated with lime use
during sugar refining and PCC production. Two sugar refining
facilities in California have been identified that capture CO2
produced in lime kilns located on the same site as the sugar
refinery (Lutter, 2008). Currently, data on CO2 production by
these lime facilities is unavailable. Future work will include
research to determine the number of sugar refineries that
employ the carbonation technique, the percentage of these
that use captured CO2 from lime production facilities, and the
amount of CO2 recovered per unit of lime production. Future
research will also aim to improve estimates of CO2 recovered
as part of the PCC production process using estimates of PCC
production and CO2 inputs rather than lime consumption by
PCC facilities.
4.3. Limestone and Dolomite Use
(IPCC Source Category 2A3)
Limestone (CaCO3) and dolomite (CaCO3MgCO3)8
are basic raw materials used by a wide variety of industries,
including construction, agriculture, chemical, metallurgy,
glass production, and environmental pollution control.
Limestone is widely distributed throughout the world
in deposits of varying sizes and degrees of purity. Large
deposits of limestone occur in nearly every state in the United
States, and significant quantities are extracted for industrial
applications. For some of these applications, limestone is
sufficiently heated during the process and generates CO2 as a
byproduct. Examples of such applications include limestone
used as a flux or purifier in metallurgical furnaces, as a
sorbent in flue gas desulfurization systems for utility and
industrial plants, or as a raw material in glass manufacturing
and magnesium production.
In 2007, approximately 13,075 thousand metric tons of
limestone and 1,827 thousand metric tons of dolomite were
consumed during production for these applications. Overall,
usage of limestone and dolomite resulted in aggregate CO2
emissions of 6.2 Tg CO2 Eq. (6,182 Gg) (see Table 4-11 and
Table 4-12). Emissions in 2007 decreased 23 percent from
the previous year and have increased 21 percent overall from
1990 through 2007.
Methodology
Carbon dioxide emissions were calculated by multiplying
the quantity of limestone or dolomite consumed by the
average C content, approximately 12.0 percent for limestone
8 Limestone and dolomite are collectively referred to as limestone by the
industry, and intermediate varieties are seldom distinguished.
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-11: C02 Emissions from Limestone & Dolomite Use (Tg C02 Eq.)
Activity
Flux Stone
Glass Making
Flue Gas Desulfurization
Magnesium Production
Other Miscellaneous Uses
Total
1990
1""
0.8
5.1
1995
•„„
1.2
6.7
2000
•„.
""•
0.1
0.7
5.1
2005
2.7
0.4
3.0
0.0
0.7
6.8
2006
4.5
0.7
2.1
0.0
0.7
8.0
2007
2.0
0.3
3.2
0.0
0.7
6.2
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 4-12: C02 Emissions from Limestone & Dolomite Use (Gg)
Activity
1990
1995
2000
2005
2006
2007
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
Flue Gas Desulfurization
Magnesium Production
Other Miscellaneous Uses
2,593
2,304
289
217
189
28
1,433
64
819
3,198
2,027
1,171
525
421
103
1,719
41
1,168
2,104
1,374
730
371
371
°
1,787
73
722
2,650
1,096
1,554
425
405
20
2,975
0
718
4,492
1,917
2,575
747
717
31
2,061
0
735
1,959
1,270
689
333
333
0
3,179
0
711
Total
5,127
6,651
5,056
6,768 8,035
6,182
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.
and 13.2 percent for dolomite (based on stoichiometry), and
converting this value to CO2. 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. Flux stone
used during the production of iron and steel was deducted
from the Limestone and Dolomite Use estimate and attributed
to the Iron and Steel Production estimate.
Traditionally, the production of magnesium metal was
the only other significant 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 CO2-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 2007 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 4-13) were obtained from the USGS Minerals
Yearbook: Crushed Stone Annual Report (USGS 1993,
1995a through 2007a, 2008a). The production capacity
data for 1990 through 2007 of dolomitic magnesium metal
(see Table 4-14) also came from the USGS (1995b through
2007b, 2008b). 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 2007 Minerals Yearbook: Magnesium; therefore, it
is assumed that this process continues to be non-existent in
the United States (USGS 2008b). During 1990 and 1992, the
Industrial Processes 4-11
-------
Table 4-13: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
1990
1995
2000
2005
2006
2007
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
Flue Gas Desulfurization
Other Miscellaneous Uses
7,022
3,165
3,857
962
920
43
6,761
1,632
11,030
5,208
5,822
1,693
1,629
64
4,683
1,671
5,305
3,477
1,827
757
757
0
7,225
1,616
Total
12,319
16,321
12,826
16,377 19,078 14,903
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.
Table 4-14: Dolomitic Magnesium Metal Production
Capacity (Metric Tons)
Year
Production Capacity
1990
35,000
2005
2006
2007
Note: Production capacity for 2002, 2003, 2004, 2005, 2006, and 2007
amounts to zero because the last U.S. production plant employing the
dolomitic process shut down mid-2001 (USGS 2002b through 2008b).
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
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.
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-use's fraction of total consumption
in that year.9
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,
among other minerals. The exact specifications for limestone
or dolomite used as flux stone vary with the pyrometallurgical
process and the kind of ore processed. 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. 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. The accuracy of distribution by
end use is also uncertain because this value is reported by
the manufacturer and not the end user. Additionally, there is
'This approach was recommended by USGS.
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-15: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Limestone and Dolomite Use
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Limestone and Dolomite
Use CO?
6.2
5.4
7.2
-12%
+ 16%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
significant inherent uncertainty associated with estimating
withheld data points for specific end uses of limestone and
dolomite. The uncertainty of the estimates for limestone
used in glass making is especially high; however, since
glass making accounts for a small percent of consumption,
its contribution to the overall emissions estimate is low.
Lastly, 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.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-15. Limestone and Dolomite Use
CO2 emissions were estimated to be between 5.4 and 7.2 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 12 percent below and 16 percent
above the emission estimate of 6.2 Tg CO2 Eq.
Recalculations Discussion
Estimates of CO2 emissions from Limestone and
Dolomite Use have been revised for the entire time series to
accommodate minor revisions to the "unspecified uses" of
limestone and dolomite identified by the USGS. On average,
these revisions resulted in an annual decrease in emissions of
0.1 percent. Additionally, limestone and dolomite consumption
data were updated to attribute emissions from limestone and
dolomite used for iron and steel production to the Iron and
Steel Production estimate. On average, this resulted in an
additional decrease in emissions of 10 percent.
Planned Improvements
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 included in future Inventories (e.g., glass
production, other process use of carbonates) may be removed
from this section and will be reported under the appropriate
source categories.
4.4. Soda Ash Production 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 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 two states produce natural soda ash: Wyoming
and California. Of these two states, only net emissions
of CO2 from Wyoming were calculated due to specifics
regarding the production processes employed in the state.10
10 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 CO2 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 CO2 is generated as a byproduct,
the CO2 is recovered and recycled for use in the carbonation stage and is
not emitted. A third state, Colorado, produced soda ash until the plant was
idled in 2004. The lone producer of sodium bicarbonate no longer mines
trona in the state. For a brief time, NaHCO3 was 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 included
the feedstocks mined in Wyoming and shipped to Colorado. In this way, the
sodium bicarbonate production that took place in Colorado was accounted
for in the Wyoming numbers.
Industrial Processes 4-13
-------
Table 4-16: C02 Emissions from Soda Ash Production
and Consumption (Tg C02 Eq.)
Year
Production Consumption
Total
1990
1.4
2.7
2005
2006
2007
1.7
1.6
1.7
2.6
2.5
2.5
4.2
4.2
4.1
Note: Totals may not sum due to independent rounding.
Table 4-17: C02 Emissions from Soda Ash Production
and Consumption (Gg)
Year
Production Consumption Total
1990
1,431
2,710
4,228
4,162
4,140
Note: Totals may not sum due to independent rounding.
During the production process used in Wyoming, trona ore
is treated to produce soda ash. Carbon dioxide is generated
as a byproduct of this reaction, and is eventually emitted
into the atmosphere. In addition, CO2 may also be released
when soda ash is consumed.
In 2007, CO2 emissions from the production of soda ash
from trona were approximately 1.7 Tg CO2 Eq. (1,675 Gg).
Soda ash consumption in the United States generated 2.5
Tg CO2 Eq. (2,465 Gg) in 2007. Total emissions from soda
ash production and consumption in 2007 were 4.1 Tg CO2
Eq. (4,140 Gg) (see Table 4-16 and Table 4-17). Emissions
have fluctuated since 1990. These fluctuations were strongly
related to the behavior of the export market and the U.S.
economy. Emissions in 2007 decreased by approximately 0.5
percent from the previous year, and have decreased overall
by less than 0.5 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 2007 was glass making, 49 percent;
chemical production, 30 percent; soap and detergent
manufacturing, 8 percent; distributors, 5 percent; flue gas
desulfurization, 2 percent; water treatment, 2 percent; pulp
and paper production, 2 percent; and miscellaneous, 3 percent
(USGS 2008).
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).
Methodology
During the production process, trona ore is calcined in
a rotary kiln and chemically transformed into a crude soda
ash that requires further processing. Carbon dioxide and
water are generated as byproducts of the calcination process.
Carbon dioxide emissions from the calcination of trona can
be estimated based on the following chemical reaction:
2(Na3(CO3)(HCO3)»2H2O) -> 3Na2CO3 + 5H2O + CO2
[trona] [soda ash]
Based on this formula, approximately 10.27 metric tons
of trona are required to generate one metric ton of CO2, or
an emission factor of 0.097 metric tons CO2 per metric ton
trona (IPCC 2006). Thus, the 17.2 million metric tons of
trona mined in 2007 for soda ash production (USGS 2008)
resulted in CO2 emissions of approximately 1.7 Tg CO2 Eq.
(1,675 Gg).
Once produced, 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 4-18) were taken from USGS (1994
through 2008). Soda ash production and consumption data
were collected by the USGS from voluntary surveys of the
U.S. soda ash industry.
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-18: Soda Ash Production and Consumption (Gg) Planned Improvements
Year
Production3
Consumption
2005
2006
2007
17,000
16,700
17,200
6,200
6,110
5,940
aSoda ash produced from trona ore only.
Uncertainty
Emission estimates from soda ash production 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 4-19. Soda Ash Production and
Consumption CO2 emissions were estimated to be between
3.8 and 4.4 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 4.1 Tg CO2 Eq.
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.
4.5. Ammonia Production (IPCC
Source Category 2B1) and Urea
Consumption
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 N 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
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Soda Ash Production and Consumption
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Soda Ash Production
and Consumption
CO?
4.1
3.8
4.4
+7%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-15
-------
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. Carbon dioxide 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:
(catalyst)
0.88CH4 + 1.26Air + 1.24H2O -> 0.88CO2 + N2 + 3H2
N2 + 3H2 -» 2NH3
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:
2NH3 + CO2 -» NH2COONH4 -» CO(NH2)2 + H2O
Urea is consumed for a variety of uses, including as a
nitrogenous fertilizer, in urea-formaldehyde resins, and as
a deicing agent (TIG 2002). The C in the consumed urea is
assumed to be released into the environment as CO2 during
use. Therefore, the CO2 produced by ammonia production
that is subsequently used in the production of urea is still
emitted during urea consumption. The majority of CO2
emissions associated with urea consumption are those
that result from its use as a fertilizer. These emissions are
accounted for in the Cropland Remaining Cropland section
of the Land Use, Land-Use Change, and Forestry chapter.
Carbon dioxide emissions associated with other uses of urea
are accounted for in this chapter. Net emissions of CO2 from
ammonia production in 2007 were 13.8 Tg CO2 Eq. (13,786
Gg), and are summarized in Table 4-20 and Table 4-21.
Emissions of CO2 from urea consumed for non-fertilizer
purposes in 2007 totaled 4.7 Tg CO2 Eq. (4,750 Gg), and
are summarized in Table 4-20 and Table 4-21. The decrease
in ammonia production in recent years is due to several
factors, including market fluctuations and high natural gas
prices. Ammonia production relies on natural gas as both a
feedstock and a fuel, and as such, domestic producers are
competing with imports from countries with lower gas prices.
If natural gas prices remain high, it is likely that domestically
Table 4-20: C02 Emissions from Ammonia Production and Urea Consumption (Tg C02 Eq.)
Source
Ammonia Production
Urea Consumption3
Total
1990
13.0
3.8
16.8
1995
13.5
4.3
17.8
2000
12.2
4.2
16.4
2005
9.2
3.7
12.8
2006
8.8
3.5
12.3
2007
9.0
4.7
13.8
allrea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.
Note: Totals may not sum due to independent rounding.
Table 4-21: C02 Emissions from Ammonia Production and Urea Consumption (Gg)
Source
Ammonia Production
Urea Consumption3
Total
1990
13,047
3,784
16,831
1995
13,541
4,255
17,796
2000
12,172
4,231
16,402
2005
9,196
3,653
12,849
2006
8,781
3,519
12,300
2007
9,036
4,750
13,786
aUrea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.
Note: Totals may not sum due to independent rounding.
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
produced ammonia will continue to decrease with increasing
ammonia imports (EEA 2004).
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 selected EFMA factor is based on
ammonia production technologies that are similar to those
employed in the U.S. 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 from fuels consumed for energy purposes during
the production of ammonia are accounted for in the Energy
chapter. 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 (European Fertilizer Manufacturers Association
2000). The CO2 emissions reported for ammonia production
are therefore reduced by a factor of 0.73 multiplied by total
annual domestic urea production. 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 consumption. Those
CO2 emissions that result from the use of urea as a fertilizer
are accounted for in the Land Use, Land-Use Change, and
Forestry chapter.
The total amount of urea consumed for non-agricultural
purposes is estimated by deducting the quantity of urea
fertilizer applied to agricultural lands, which is obtained
directly from the Land Use, Land-Use Change, and Forestry
Chapter and is reported in Table 4-22, from the total U.S.
production. Total urea production is estimated based on the
amount of urea produced plus the sum of net urea imports
and exports CO2 emissions associated with urea that is used
for non-fertilizer purposes are estimated using a factor of
0.73 tons of CO2 per ton of urea consumed.
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 ton 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
Table 4-22: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg)
Year
Ammonia
Production
Urea Production
Urea Applied
as Fertilizer
Urea Imports
Urea Exports
2005
2006
2007
10,143
9,962
10,386
5,270
5,410
5,630
4,779
4,985
5,389
5,026
5,029
6,546
536
656
310
Industrial Processes 4-17
-------
EFMA reported an emission factor range of 1.15 to 1.30
metric ton CO2/metric ton NH3, with 1.2 metric ton CO2/
metric ton NH3 as a typical value. Technologies (e.g.,
catalytic reforming process) associated with this factor
are found to closely resemble those employed in the
United States for use of natural gas as a feedstock. The
EFMA reference also indicates that more than 99 percent
of the CtLj feedstock to the catalytic reforming process is
ultimately converted to CO2. The emission factor of 3.57
metric ton 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). As noted earlier, emissions from
fuels consumed for energy purposes during the production
of ammonia are accounted for in the Energy chapter.
Ammonia production data (see Table 4-22) was obtained
from Coffeyville Resources (Coffeyville 2005,2006,2007a,
2007b) and the Census Bureau of the U.S. Department of
Commerce (U.S. Census Bureau 1991 through 1994, 1998
through 2007) as reported in Current Industrial Reports
Fertilizer Materials and Related Products annual and
quarterly reports. Urea-ammonia nitrate production was
obtained from Coffeyville Resources (Coffeyville 2005,
2006, 2007a). Urea production data for 1990 through 2007
were obtained from the Minerals Yearbook: Nitrogen (USGS
1994 through 2007). Import 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 2007 (U.S. Census Bureau 1998 through
2007), 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 4-22). Urea export data for
1990 through 2007 were taken from U.S. Fertilizer Import/
Exports from USDA Economic Research Service Data Sets
(U.S. Department of Agriculture 2008).
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. 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.
Additional uncertainty is associated with the estimate
of urea consumed for non-fertilizer purposes. Emissions
associated with this consumption are reported in this
source category, while those associated with consumption
as fertilizer are reported in Cropland Remaining Cropland
section of the Land Use, Land-Use Change, and Forestry
chapter. The amount of urea used for non-fertilizer purposes
is estimated based on estimates of urea production, net urea
imports, and the amount of urea used as fertilizer. There is
uncertainty associated with the accuracy of these estimates
as well as the fact that each estimate is obtained from a
different data source.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-23. Ammonia Production
and Urea Consumption CO2 emissions were estimated to
be between 12.1 and 15.2 Tg CO2 Eq. at the 95 percent
Table 4-23: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ammonia Production and
Urea Consumption (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Ammonia Production
and Urea Consumption
CO?
13.8
12.1
15.2
-12%
+11%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
confidence level. This indicates a range of approximately 12
percent below and 11 percent above the emission estimate
of 13.8TgC02Eq.
Recalculations Discussion
Urea export data were revised for 1990 through 2006
using the U.S. Department of Agriculture's Economic
Research Service Data Set for U.S. Fertilizer Exports. These
data were used because the previous data source discontinued
publication of urea export data. On average, revisions to
the exported urea dataset resulted in a decrease in annual
emission estimates of less than one percent. Urea production
data were revised for 1990 through 2006. These data were
used in place of estimating urea production based on quantity
of urea applied to agricultural lands and an estimated percent
of urea consumed for agricultural purposes. On average, the
new data resulted in a decrease in annual emission estimates
of less than half of one percent.
Planned Improvements
Planned improvements to the Ammonia Production and
Urea Consumption source category include updating emission
factors to include both fuel and feedstock CO2 emissions and
incorporating CO2 capture and storage. Methodologies will
also be updated if additional ammonia-production plants
are found to use hydrocarbons other than natural gas for
ammonia production. Additional efforts will be made to find
consistent data sources for urea consumption and to report
emissions from this consumption appropriately as defined
by the 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006).
4.6. 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 byproduct and is released
from reactor vents into the atmosphere.
Table 4-24: N20 Emissions from Nitric Acid Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
20.0
64
2005
2006
2007
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 N2O. 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. Less than 5 percent of nitric acid plants use NSCR and
they represent 0.6 percent of estimated national production
(EPA 2008). The remaining 95 percent of the facilities use
SCR or extended absorption, neither of which is known to
reduce N2O emissions.
Nitrous oxide emissions from this source were estimated
to be 21.7 Tg CO2 Eq. (70 Gg) in 2007 (see Table 4-24).
Emissions from nitric acid production have increased by 8.5
percent since 1990, with the trend in the time series closely
tracking the changes in production. Emissions increased
19 percent between 2006 and 2007, which resulted from
an increase in nitric acid production driven by increased
synthetic fertilizer demand by farmers taking advantage of
high grain prices by expanding crop planting (ICIS 2008).
Emissions have decreased by 8.8 percent since 1997, the
highest year of production in the time series.
Methodology
Nitrous oxide 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
Industrial Processes 4-19
-------
Table 4-25: Nitric Acid Production (Gg)
Year
Gg
produced at plants using non-selective catalytic reduction
(NSCR) systems and 9 kg N2O/metric ton HNO3 produced at
plants not equipped with NSCR (IPCC 2006). 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. Less than 5 percent of HNO3 plants
in the United States are equipped with NSCR representing
0.6 percent of estimated national production (EPA 2008).
Hence, the emission factor is equal to (9 x 0.994) + (2 x
0.006) = 9.0 kg N2O per metric ton HNO3.
Nitric acid production data for 1990 through 2002 were
obtained from the U.S. Census Bureau Current Industrial
Reports (2006), and for 2003 through 2007 from the U.S.
Census Bureau Current Industrial Reports (2008) (see
Table 4-25).
Uncertainty
The overall uncertainty associated with the 2007
N2O emissions estimate from nitric acid production
was calculated using the IPCC Guidelines for National
Greenhouse Gas Inventories (2006) 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 4-26. Nitrous oxide emissions from
nitric acid production were estimated to be between 12.7
and 31.3 Tg CO2 Eq. at the 95 percent confidence level.
This indicates a range of approximately 42 percent below
to 44 percent above the 2007 emissions estimate of 21.7 Tg
CO2 Eq.
Recalculations Discussion
Changes to the weighted N2O emission factor resulted in
an increase in emissions across the time series. The weighted
N2O emission factor was previously based on the percentage
of facilities equipped and not equipped with NSCR systems.
The emission factor used for the current estimate is based
on the percentage of HNO3 produced at plants with NCSR
systems and HNO3 produced at plants without NSCR
systems. Additionally, the nitric acid production value for
2006 has also been updated relative to the previous Inventory
based on revised production data published by the U.S.
Census Bureau (2008). Revised production data reduced
emissions for 2006by 0.2TgCO2Eq. (l.Opercent). Overall,
these changes resulted in an average annual increase in N2O
emissions of 3.1 Tg CO2 Eq. (17.8 percent) for the period
1990 through 2006 relative to the previous Inventory.
4.7. Adipic Acid Production (IPCC
Source Category 2B3)
Adipic acid production is an anthropogenic source of
N2O emissions. Worldwide, few adipic acid plants exist.
The United States and Europe are the major producers.
Table 4-26: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Nitric Acid Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Nitric Acid Production
N,0
21.7
12.7
31.3
-42%
+44%
a 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 and Sinks: 1990-2007
-------
The United States has three companies in four locations
accounting for 34 percent of world production, and eight
European producers account for a combined 38 percent
of world production (CW 2007). Adipic acid is a white
crystalline solid used in the manufacture of synthetic fibers,
plastics, coatings, urethane foams, elastomers, and synthetic
lubricants. Commercially, it is the most important of the
aliphatic dicarboxylic acids, which are used to manufacture
polyesters. Eighty-four percent of all adipic acid produced
in the United States is used in the production of nylon 6,6;
9 percent is used in the production of polyester polyols; 4
percent is used in the production of plasticizers; and the
remaining 4 percent is accounted for by other uses, including
unsaturated polyester resins and food applications (ICIS
2007). Food grade adipic acid is 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. Nitrous oxide is generated as a
byproduct 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 (Reimer et al. 1999).n
Only one small plant, representing approximately two percent
of production, does not control for N2O (ICIS 2007; VA
DEQ 2006).
Nitrous oxide emissions from adipic acid production
were estimated to be 5.9 Tg CO2 Eq. (19 Gg) in 2007 (see
Table 4-27). National adipic acid production has increased
by approximately 26 percent over the period of 1990 through
2007, to approximately one million metric tons. Over the
same period, emissions have been reduced by 61 percent due
to the widespread installation of pollution control measures
in the late 1990s.
Table 4-27: N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
15.3
49
2005
2006
2007
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 emission
estimates for 2003 to 2007 were unavailable. Emission
estimates for 2003 and 2004 were calculated by applying 4.4
and 4.2 percent national production growth rates, respectively.
Emission estimates for 2005 to 2007 were kept the same as
2004. National production for 2003 was calculated through
linear interpolation between 2002 and 2004 reported national
production data. 2005 national production was calculated
through linear interpolation between 2004 and 2006 reported
national production. 2007 national production was kept
the same as 2006. 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 (IPCC 2006). Emissions are estimated using the
following equation:
N2O emissions = {production of adipic acid
[metric tons (MT) of adipic acid]} x
(0.3 MT N2O /MT adipic acid) x
[1-(N2O destruction factor x abatement system utility factor)]
"During 1997, the N2O emission controls installed by the third plant
operated for approximately a quarter of the year.
Industrial Processes 4-21
-------
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. For the one plant that
uses thermal destruction and for which no reported plant-
specific emissions are available, the N2O abatement system
destruction factor is assumed to be 98.5 percent, and the
abatement system utility factor is assumed to be 97 percent
(IPCC 2006).
For 1990 to 2003, 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 and
2006, actual plant production data were obtained for these
two plants and used for emission calculations. For 2005,
interpolated national production was used for calculating
emissions. For 2007, production was kept the same as 2006,
as described above.
National adipic acid production data (see Table 4-28)
for 1990 through 2002 were obtained from the American
Chemistry Council (ACC 2003). Production for 2003 was
estimated based on linear interpolation of 2002 and 2004
reported production. Production for 2004 and 2006 were
obtained from Chemical Week, "Product Focus: Adipic Acid"
(CW 2005, 2007). 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 through 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
Table 4-28: Adipic Acid Production (Gg)
Year
Gg
1990
^m
1995
2000
^H
2005
2006
2007
735
830
925
^B
1,002
1,002
1,002
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. For 2004 to 2007, although plant capacity data
are available (CW 1999, CMR 2001, ICIS 2007), they are
not used to calculate plant-specific production for these years
because plant-specific production data for 2004 and 2006 are
also available and are used in our calculations instead (CW
2005, CW 2007).
Uncertainty
The overall uncertainty associated with the 2007 N2O
emission estimate from adipic acid production was calculated
using the IPCC Guidelines for National Greenhouse
Gas Inventories (2006) 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 4-29. Nitrous oxide
emissions from adipic acid production were estimated to be
between 4.9 and 7.1 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of approximately 18 percent
below to 20 percent above the 2007 emission estimate of
5.9 Tg CO2 Eq.
Planned Improvements
Improvement efforts will be focused on obtaining direct
measurement data from facilities. If they become available,
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-29: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Adipic Acid Production N20
5.9
4.9
7.1
-18%
+20%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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.
4.8. Silicon Carbide Production
(IPCC Source Category 2B4) and
Consumption
Carbon dioxide and CtLj are emitted from the production12
of silicon carbide (SiC), a material used as an industrial
abrasive. To make SiC, quartz (SiO2) 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 CO2, CH4, or CO.
Carbon dioxide 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).
Carbon dioxide emissions from SiC production and
consumption in 2007 were 0.2 Tg CO2 Eq. (196 Gg).
Approximately 47 percent of these emissions resulted
from SiC production while the remainder results from SiC
consumption. CH^ emissions from SiC production in 2007
were 0.01 Tg CO2 Eq. CH4 (0.4 Gg) (see Table 4-30 and
Table 4-31).
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
Table 4-30: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.)
Gas
1990
2000
2005
C02
CH4
0.4
0.2
0.2
2006
2007
0.2
0.2
Total
0.4
0.3
0.3
0.2
0.2
0.2
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-31: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)
Gas
1990
1995
2000
2005
2006
2007
C02
CH4
+ Does not exceed 0.5 Gg.
12 Silicon carbide is produced for both abrasive and metallurgical applications
in the United States. Production for metallurgical applications is not available
and therefore both CH4 and CO2 estimates are based solely upon production
estimates of silicon carbide for abrasive applications.
207
+
196
+
Industrial Processes 4-23
-------
for CO2 and 11.6 kg CH4/metric ton SiC for CH4) provided
by the 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006).
Emissions of CO2 from silicon carbide consumption
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 2007 were obtained
from the Minerals Yearbook: Manufactured Abrasives (USGS
1991a through 2005a, 2006). Silicon carbide consumption
by major end use was obtained from the Minerals Yearbook:
Silicon (USGS 1991b through 2005b) (see Table 4-32) for
Table 4-32: Production and Consumption of Silicon
Carbide (Metric Tons)
Year
Production
Consumption
1990
^m
1995
^^g
2000
2005
2006
2007
105,000
^H
75,400
45,000
^H
35,000
35,000
35,000
172,465
^M
227,395
225,070
^H
220,149
199,937
179,741
years 1990 through 2004 and from the USGS Minerals
Commodity Specialist for 2005 and 2006 (Corathers 2006,
2007). Silicon carbide consumption by major end use data
for 2007 are proxied using 2006 data due to unavailability
of data at time of publication. Net imports for the entire time
series were obtained from the U.S. Census Bureau (2005
through 2008).
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 CtLj, 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 4-33. Silicon carbide
production and consumption CO2 emissions were estimated
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
Table 4-33: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Silicon Carbide Production
and Consumption (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Silicon Carbide Production
and Consumption
Silicon Carbide Production
C02 0.2
CH4 +
Lower Bound Upper Bound Lower Bound
0.18 0.22 -10%
+ + -9%
Upper Bound
+10%
+ 10%
+ Does not exceed 0.05 Tg C02 Eq. or 0.5 Gg.
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
were estimated to be between 9 percent below and 10
percent above the emission estimate of 0.01 Tg CO2 Eq. at
the 95 percent confidence level.
Recalculations Discussion
Estimates of CO2 emissions from silicon carbide
consumption were revised for all years due to the availability
of more precise import and export data from the United
States International Trade Commission. On average, these
revisions resulted in a decrease in annual emissions of less
than 1 percent.
Planned Improvements
Future improvements to the carbide production source
category include continued 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.
4.9. Petrochemical Production
(IPCC Source Category 2B5)
The production of some petrochemicals results in
the release of small amounts of CH^ 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.
Carbon black is an intense 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),
polyvinyl 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.
Emissions of CO2 and CH4 from petrochemical
production in 2007 were 2.6 Tg CO2 Eq. (2,636 Gg) and 1.0
Tg CO2 Eq. (48 Gg), respectively (see Table 4-34 and Table
4-35), totaling 3.7 Tg CO2 Eq. Emissions of CO2 from C
Table 4-34: C02 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.)
Gas
C02
CH4
Total
1990
2.2
0.9
3.1
1995
2.8
1.1
3.8
2000
3.0
1.2
4.2
2005
2.8
1.1
3.9
2006
2.6
1.0
3.6
2007
2.6
1.0
3.7
Table 4-35: C02 and CH4 Emissions from Petrochemical Production (Gg)
Gas
C02
CH4
1990
2,221
41
1995
2,750
52
2000
3,004
59 |
2005
2,804
51
2006
2,573
48
2007
2,636
48
Industrial Processes 4-25
-------
black production remained constant at 2.6 Tg CO2 Eq. (2,573
Gg) in 2006 and 2007. There has been an overall increase
in CO2 emissions from C black production of 18 percent
since 1990. CK4 emissions from petrochemical production
increased by approximately 17 percent since 1990.
Methodology
Emissions of CH4 were calculated by multiplying
annual estimates of chemical production by the appropriate
emission factor, as follows: 11 kg CtLj/metric ton C black, 1
kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton ethylene
dichloride,13 and 2 kg CELj/metric ton methanol. Although
the production of other chemicals may also result in CH4
emissions, insufficient data were available to estimate their
emissions.
Emission factors were taken from the Revised 1996
IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Annual
production data (see Table 4-36) were obtained from the
American Chemistry Council's Guide to the Business of
Chemistry (ACC 2002, 2003, 2005 through 2008) and the
International Carbon Black Association (Johnson 2003,2005
through 2008).
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,
CELj, and non-CELj volatile organic compounds. A portion of
the tail gas is generally burned for energy recovery to heat
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 CO2
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 CK4 or CO2. The C content of the CK4
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 4-37)
is estimated using a primary feedstock consumption factor
Table 4-36: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
Carbon Black
Ethylene
Ethylene Dichloride
Methanol
1990
1,307
16,541
6,282
3,785
1995
1,619
21,214
7,829
4,992
2000
1,769
24,970
9,866
5,221 1
2005
1,651
23,954
11,260
2,336
2006
1,515
25,000
9,736
1,123
2007
1,552
25,392
9,566
1,068
13 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).
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-37: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons)
Activity
1990
2000
Primary Feedstock
Secondary Feedstock
1,864
302
2005
2006
2007
2,353
381
2,159
350
2,212
358
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 (Othmer et al. 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 production 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 4-38. Petrochemical production
Table 4-38: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Petrochemical Production
and C02 Emissions from Carbon Black Production (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Petrochemical Production
Petrochemical Production
C02
CH4
2.6
1.0
Lower Bound
1.7
0.7
Upper Bound
3.7
1.3
Lower Bound
-34%
-31%
Upper Bound
+40%
+31%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-27
-------
CO2 emissions were estimated to be between 1.7 and 3.7 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 34 percent below to 40 percent
above the emission estimate of 2.6 Tg CO2 Eq. Petrochemical
production CH4 emissions were estimated to be between 0.7
and 1.3 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 31 percent below to 31
percent above the emission estimate of 1.0 Tg CO2 Eq.
Recalculations Discussion
Estimates of CH4 emissions from petrochemical
production were revised to account for small changes in
ethylene, ethylene dichloride, and methanol production
for years 1990 through 2006. On average, these revisions
resulted in an annual increase in CH4 emissions of
approximately 1.5 percent.
Table 4-39: C02 Emissions from Titanium Dioxide
(Tg C02 Eq. and Gg)
Planned Improvements
Future improvements to the Petrochemical Production
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.
4.10. 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
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:
2FeTi03 + 7C12 + 3C -» 2TiCl4 + 2FeCl3 + 3CO2
2TiCl4 + 202 -» 2Ti02 + 4C12
Year
Tg C02 Eq.
Gg
1990
1.2
1,195
2005
2006
2007
The C in the first chemical reaction is provided by
petroleum coke, which is oxidized in the presence of the
chlorine and FeTiO3 (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
"calcined" petroleum coke is manufactured specifically for
this purpose.
Emissions of CO2 in 2007 were 1.9 Tg CO2 Eq. (1,876
Gg), which represents an increase of 57 percent since 1990
(see Table 4-39).
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 the calcined
petroleum coke used in the process is 98.4 percent C and 1.6
percent inert materials (Nelson 1969).
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-40: Titanium Dioxide Production (Gg)
Year
Gg
1990
1995
2000
^H
2005
2006
2007
979
•
1,250
^m
1,400
^m
1,310
1,400
1,400
The emission factor for the TiO2 chloride process
was taken from the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). Titanium dioxide
production data and the percentage of total TiO2 production
capacity that is chloride process for 1990 through 2006 (see
Table 4-40) were obtained through the Minerals Yearbook:
Titanium Annual Report (USGS 1991 through 2008). Because
2007 production and capacity data were unavailable, 2006
production data were used. 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).
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. As of 2004, the last remaining sulfate-
process plant in the United States closed; therefore, 100
percent of post-2004 production uses the chloride process.
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 4-41. Titanium dioxide consumption
CO2 emissions were estimated to be between 1.6 and 2.1 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 12 percent below and 13 percent
above the emission estimate of 1.9 Tg CO2 Eq.
Table 4-41: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Titanium Dioxide Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Titanium Dioxide Production CO?
1.9
1.6
2.1
-12%
+13%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-29
-------
Planned Improvements
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.
4.11. Carbon Dioxide Consumption
(IPCC Source Category 2B5)
Carbon dioxide 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). Carbon dioxide 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. Carbon dioxide 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.
Carbon dioxide is produced from naturally occurring
CO2 reservoirs, as a byproduct from energy and industrial
production processes (e.g., ammonia production, fossil
fuel combustion, ethanol production), and as a byproduct
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 byproduct 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. Carbon dioxide captured from biogenic
sources (e.g., ethanol production plants) is not included in
the inventory. Carbon dioxide 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.14
Carbon dioxide is produced as a byproduct 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
the text box titled "Carbon Dioxide Transport, Injection,
and Geological Storage." The only CO2 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.
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). Carbon dioxide production
from these facilities is discussed in the Energy chapter.
In 2007, the amount of CO2 produced by the Mississippi
and New Mexico facilities for commercial applications and
subsequently emitted to the atmosphere was 1.9 Tg CO2
Eq. (1,867 Gg) (see Table 4-42). This amount represents an
increase of 9 percent from the previous year and an increase
Table 4-42: C02 Emissions from C02 Consumption
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
2000
^m
2005
2006
2007
1.4
•
1.3
1.7
1.9
1,421
M
1,321
1,709
1,867
14There are currently four known electric power plants operating in the
United States that capture CO2 for use as food-grade CO2 or other industrial
processes; however, insufficient data prevents estimating emissions from
these activities as part of Carbon Dioxide Consumption.
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
of 32 percent since 1990. This increase was due to an increase
in production at the Mississippi facility, despite the decrease
in the percent of the facility's total reported production that
was used for commercial applications.
Methodology
Carbon dioxide emission estimates for 1990 through 2007
were based on production data for the two facilities currently
producing CO2 from naturally-occurring CO2 reservoirs for
use in non-EOR applications. 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.
Carbon dioxide production data for the Jackson Dome,
Mississippi facility and the percentage of total production
that was used for EOR and in non-EOR applications
were obtained from the Advanced Resources Institute
(ARI 2006, 2007) for 1990 to 2000 and from the Annual
Reports for Denbury Resources (Denbury Resources 2002
through 2007) for 2001 to 2007 (see Table 4-43). Denbury
Resources reported the average CO2 production in units of
MMCF CO2 per day for 2001 through 2007 and reported
the percentage of the total average annual production that
was used for EOR. Carbon dioxide production data for the
Bravo Dome, New Mexico facility were obtained from the
Advanced Resources International, Inc. (Godec 2008). The
percentage of total production that was used for EOR and in
non-EOR applications were obtained from the New Mexico
Bureau of Geology and Mineral Resources (Broadhead
2003 and New Mexico Bureau of Geology and Mineral
Resources 2006).
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.
Table 4-43: C02 Production (Gg C02) and the Percent Used for Non-EOR Applications for Jackson Dome
and Bravo Dome
Year
Jackson Dome C02
Production (Gg)
Jackson Dome % Used
for Non-EOR
Bravo Dome C02
Production (Gg)
Bravo Dome % Used
for Non-EOR
2005
2006
2007
4,677
6,610
9,529
27%
25%
19%
5,799
5,613
5,605
1%
1%
1%
Industrial Processes 4-31
-------
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from C02 Consumption
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
C02 Consumption
CO,
1.9
1.5
2.3
-18%
+22%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-44. Carbon dioxide consumption
CO2 emissions were estimated to be between 1.5 and 2.3 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 18 percent below to 22 percent above
the emission estimate of 1.9 Tg CO2 Eq.
Recalculations Discussion
Estimates of CO2 emissions from CO2 Consumption
have been revised for 2006 based on revised CO2 production
data from Jackson Dome. The revision resulted in an increase
in emissions of approximately 8 percent for 2006.
Planned Improvements
Future improvements to the Carbon Dioxide Consumption
source category include research into CO2 capture for
industrial purposes at electric power plants. Currently,
four plants have been identified that capture CO2 for these
purposes, but insufficient data prevents including them in
the current emission estimate.
4.12. 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:
Ca10_x_y Nax Mgy (PO4)6_x(CO3)xF2+0.4x
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 recirculated phosphoric acid (H3PO4) (EFMA 2000). The
primary chemical reactions for the production of phosphoric
acid from phosphate rock are:
Ca3(PO4)2 + 4H3PO4 -» 3Ca(H2PO4)2
3Ca(H2P04)2 + 3H2S04 + 6H2O -»
3CaS04 • 6H20 + 6H3PO4
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:
CaCO,
H2SO4 + H2O
CaSO4 • 2H2O + CO2
Total marketable phosphate rock production in 2007
was 29.7 million metric tons. Approximately 87 percent of
domestic phosphate rock production was mined in Florida
and North Carolina, while approximately 13 percent of
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-45: C02 Emissions from Phosphoric Acid
Production (Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
1.5
1,529
2005
2006
2007
production was mined in Idaho and Utah. In addition, 2.7
million metric tons of crude phosphate rock was imported
for consumption in 2007. The vast majority, 99 percent, of
imported phosphate rock is sourced from Morocco (USGS
2005). Marketable phosphate rock production, including
domestic production and imports for consumption, decreased
by less than 1 percent between 2006 and 2007. However,
over the 1990 to 2007 period, production has decreased
by 26 percent. Total CO2 emissions from phosphoric acid
production were 1.2 Tg CO2 Eq. (1,166 Gg) in 2007 (see
Table 4-45).
Methodology
Carbon dioxide emissions from production of phosphoric
acid from phosphate rock are 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.
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.
From 1993 to 2004, the USGS Minerals 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 4-46). For the years 1990,1991,
1992, 2005, 2006, and 2007 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
(primarily from Florida and North Carolina), and imports of
phosphate rock for consumption for 1990 through 2007 were
obtained from USGS Minerals Yearbook: Phosphate Rock
(USGS 1994 through 2008). From 2004-2007, the USGS
reported no exports of phosphate rock from U.S. producers
(USGS 2005 through 2008).
Table 4-46: Phosphate Rock Domestic Production, Exports, and Imports (Gg)
Location
U.S. Production3
Florida & North Carolina
Idaho & Utah
Exports — Florida & North Carolina
Imports— Morocco
Total U.S. Consumption
1990
49,800
42,4941
7,306 1
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
2005
36,100
31,227
4,874
2,630
38,730
2006
30,100
26,037
4,064
2,420
32,520
2007
29,700
25,691
4,010
2,670
32,370
- Assumed equal to zero.
aUSGS does not disaggregate production data regionally (Florida & North Carolina and Idaho & Utah) for 1990, 2005, 2006, and 2007. Data for those years are
estimated based on the remaining time series distribution.
Industrial Processes 4-33
-------
Table 4-47: 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
- Assumed equal to zero.
Source: FIPR (2003).
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 4-47).
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. As of 2006, 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 2006).
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.
Uncertainty
Phosphate rock production data used in the emission
calculations were developed by the USGS through monthly
and semiannual voluntary surveys of the active phosphate
rock mines during 2007. For previous years in the time
series, USGS provided the data disaggregated regionally;
however, beginning in 2006 only total U.S. phosphate rock
production was reported. Regional production for 2007 was
estimated based on regional production data from previous
years and multiplied by regionally specific emission factors.
There is uncertainty associated with the degree to which
the estimated 2007 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 exports of phosphate rock used in the emission
calculation are reported by phosphate rock producers and
are not considered to be a significant source of uncertainty.
Data for imports for consumption 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 CO2 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 CO2 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 CO2.
However, according to the USGS, only one producer in
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Phosphoric Acid Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Phosphoric Acid Production C02
1.2
1.0
1.4
-18%
+18%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 approximately 7 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 CO2 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.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-48. Phosphoric acid production
CO2 emissions were estimated to be between 1.0 and 1.4 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of approximately 18 percent below and 18 percent
above the emission estimate of 1.2 Tg CO2 Eq.
Planned Improvements
Currently, data sources for the carbonate content of the
phosphate rock are limited. If additional data sources are found,
this information will be incorporated into future estimates.
4.13. Iron and Steel Production
(IPCC Source Category 2C1) and
Metallurgical Coke Production
The production of iron and steel is an energy-intensive
process that also generates process-related emissions of CO2
and CH4. Metallurgical coke, which is manufactured using
coking coal as a raw material, is used widely during the
production of iron and steel. According to the 2006 IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC
2006), the production of metallurgical coke from coking
coal is considered to be an energy use of fossil fuel and
the use of coke in iron and steel production is considered
to be an industrial process source, so emissions from these
are reported separately. Emission estimates presented in
this chapter are based on the methodologies provided by
the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006), which call for a mass balance
accounting of the carbonaceous inputs and outputs during
the iron and steel production process and the metallurgical
coke production process. The methodologies also call for
reporting emissions from metallurgical coke production in
the Energy sector; however, the approaches and emission
estimates for both metallurgical coke production and iron and
steel production are presented separately here because the
activity data used to estimate emissions from metallurgical
coke production have significant overlap with activity data
used to estimate iron and steel production emissions. Further,
some byproducts (e.g., coke oven gas) of the metallurgical
coke production process are consumed during iron and
steel production, and some byproducts of the iron and steel
production process (e.g., blast furnace gas) are consumed
during metallurgical coke production. Emissions associated
Industrial Processes 4-35
-------
with the consumption of these byproducts are attributed
to point of consumption. As an example, CO2 emissions
associated with the combustion of coke oven gas in the blast
furnace during pig iron production are attributed to pig iron
production. Emissions associated with fuel consumption
downstream of the iron and steelmaking furnaces, such as
natural gas used for heating and annealing purposes, are
reported in the Energy chapter.
The production of metallurgical coke from coking
coal occurs both on-site at "integrated" iron and steel
plants and off-site at "merchant" coke plants. 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. Carbon-containing byproducts of the
metallurgical coke manufacturing process include coke
oven gas, coal tar, coke breeze (small-grade coke oven coke
with particle size <5mm). Coke oven gas is recovered and
used for underfiring the coke ovens and within the iron and
steel mill. Small amounts of coke oven gas are also sold as
synthetic natural gas outside of the iron and steel mills and
are accounted for in the Energy chapter. Coal tar is used as a
raw material to produce anodes used for primary aluminum
production, electric arc furnace (EAF) steel production, and
other electrolytic processes, and also used in the production
of other coal tar products. Light oil is sold to petroleum
refiners who use the material as an additive for gasoline.
The metallurgical coke production process produces CO2
emissions and fugitive CH4 emissions.
Iron is produced by first reducing iron oxide (iron ore)
with metallurgical coke in a blast furnace to produce pig iron
(impure or crude iron containing about 3 to 5 percent carbon
by weight). Inputs to the blast furnace include natural gas,
fuel oil, and coke oven gas. The carbon in the metallurgical
coke used in the blast furnace combines with oxides in the
iron ore in a reducing atmosphere to produce blast furnace
gas containing carbon monoxide (CO) and CO2. The CO is
then converted and emitted as CO2 when combusted to either
pre-heat the blast air used in the blast furnace or for other
purposes at the steel mill. Iron may be introduced into the
blast furnace in the form of raw iron ore, pellets (9-16mm
iron-containing spheres), briquettes, or sinter. Pig iron is used
as a raw material in the production of steel, which contains
about 1 percent carbon 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 CK4 emissions.
Iron can also be produced through the direct reduction
process; wherein, iron ore is reduced to metallic iron in the
solid state at process temperatures less than 1000°C. Direct
reduced iron production results in process emissions of CO2
and emissions of CH4 through the consumption of natural
gas used during the reduction process.
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. The
agglomerate is then crushed and screened to produce an
iron-bearing feed that is charged into the blast furnace. The
sintering process produces CO2 and fugitive CK4 emissions
through the consumption of carbonaceous inputs (e.g., coke
breeze) during the sintering process.
Steel is produced from pig iron in a variety of specialized
steel-making furnaces, including EAFs and basic oxygen
furnaces (BOFs). Carbon inputs to steel-making furnaces
include pig iron and scrap steel as well as natural gas, fuel oil,
and fluxes (e.g., limestone, dolomite). In a BOF, the carbon
in iron and scrap steel combines with high-purity oxygen to
reduce the carbon content of the metal to the amount desired
for the specified grade of steel. EAFs use carbon electrodes,
charge carbon and other materials (e.g., natural gas) to aid in
melting metal inputs (primarily recycled scrap steel), which
are refined and alloyed to produce the desired grade of steel.
Carbon dioxide emissions occur in BOFs occur through the
reduction process. In EAFs, CO2 emissions result primarily
from the consumption of carbon electrodes and also from
the consumption of supplemental materials used to augment
the melting process.
In addition to the production processes mentioned above,
CO2 is also generated at iron and steel mills through the
consumption of process byproducts (e.g., blast furnace gas,
coke oven gas) used for various purposes including heating,
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
annealing, and electricity generation.15 Process byproducts
sold for use as synthetic natural gas are deducted and reported
in the Energy chapter. Emissions associated with natural gas
and fuel oil consumption for these purposes are reported in
the Energy chapter.
The majority of CO2 emissions from the iron and steel
production process come from the use of metallurgical coke in
the production of pig iron and from the consumption of other
process byproducts at the iron and steel mill, with smaller
amounts evolving from the use of flux and from the removal
of carbon from pig iron used to produce steel. Some carbon
is also stored in the finished iron and steel products.
Metallurgical Coke Production
Emissions of CO2 and CH4 from metallurgical coke
production in 2007 were 3.8 Tg CO2 Eq. (3,806 Gg) and
less than 0.05 Tg CO2 Eq. (less than 0.5 Gg), respectively
(see Table 4-49 and Table 4-50), totaling 3.8 Tg CO2 Eq.
Emissions increased in 2007, but have decreased overall
since 1990. In 2007, domestic coke production decreased
by 1.2 percent and has decreased overall since 1990. Coke
production in 2007 was 22 percent lower than in 2000 and 41
percent below 1990. Overall, emissions from metallurgical
coke production have declined by 31 percent (1.7 Tg CO2
Eq.) from 1990 to 2007.
Iron and Steel Production
Emissions of CO2 and CELj from iron and steel production
in 2007 were 73.6 Tg CO2 Eq. (73,564 Gg) and 0.7 Tg CO2
Eq. (33.2 Gg), respectively (seeTable 4-51, Table 4-52,Table
4-53, and Table 4-54), totaling 74.3 Tg CO2 Eq. Emissions
increased in 2007, but have decreased overall since 1990 due
to restructuring of the industry, technological improvements,
and increased scrap utilization. Carbon dioxide emission
estimates include emissions from the consumption of
carbonaceous materials in the blast furnace, EAF, and BOF
as well as blast furnace gas and coke oven gas consumption
for other activities at the steel mill.
Table 4-49: C02 and CH4 Emissions from Metallurgical Coke Production (Tg C02 Eq.)
Gas
C02
CH4
Total
1990
5.5
+
5.5
1995
5.0 1
+
5.0
2000
4.4
+
4.4
2005
3.8
+
3.8
2006
3.7
+
3.7
2007
3.8
+
3.8
+ Does not exceed 0.05 Tg C02 Eq.
Table 4-50: C02 and CH4 Emissions from Metallurgical Coke Production (Gg)
Gas
2005
2006
2007
C02
CH4
+ Does not exceed 0.5 Gg.
15 Emissions resulting from fuel consumption for the generation of electricity
are reported in the Energy chapter. Some integrated iron and steel mills have
on-site electricity generation for which fuel is used. Data are not available
concerning the amounts and types of fuels used in iron and steel mills to
generate electricity. Therefore all of the fuel consumption reported at iron and
steel mills is assumed to be used within the iron and steel mills for purposes
other than electricity consumption, and the amounts of any fuels actually
used to produce electricity at iron and steel mills are not subtracted from the
electricity production emissions value used in the Energy chapter, therefore
some double-counting of electricity-related CO2 emissions may occur.
Industrial Processes 4-37
-------
Table 4-51: C02 Emissions from Iron and Steel Production (Tg C02 Eq.)
Process
Sinter Production
Iron Production
Steel Production
Other Activities3
Total
1990
I"'
,-,.,
39.3
104.3
1995
I"
,„.„
40.9
98.1
2000
•""
,-,.„
39.9
90.7
2005
1.7
19.6
14.0
34.2
69.3
2006
1.4
24.0
14.4
32.6
72.4
2007
1.4
26.9
14.3
31.0
73.6
'Includes emissions from blast furnace gas and coke oven gas combustion for activities at the steel mill other than consumption in blast furnace,
EAFs, or BOFs.
Note: Totals may not sum due to independent rounding.
Table 4-52: C02 Emissions from Iron and Steel Production (Gg)
Process
Sinter Production
Iron Production
Steel Production
Other Activities3
Total
1990
2,448
47,886
14,672
39,256
104,262
1995
2,512
38,791
15,925
40,850
98,078
2000
2,158
33,808
14,837
39,877
90,680
2005
1,663
19,576
13,950
34,152
69,341
2006
1,418
24,026
14,392
32,583
72,418
2007
1,383
26,948
14,270
30,964
73,564
'Includes emissions from blast furnace gas and coke oven gas combustion for activities at the steel mill other than consumption in blast furnace,
EAFs, or BOFs.
Note: Totals may not sum due to independent rounding.
Table 4-53: CH4 Emissions from Iron and Steel Production (Tg C02 Eq.)
Process
Sinter Production
Iron Production
Total
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-54: CH4 Emissions from Iron and Steel
Process
Sinter Production
Iron Production
Total
1990
+
0.9
1.0
Production
1990
0.9 1
44.7
45.6
1995
+
1.0
1.0
(Gg)
1995
0.9 1
45.8
46.7
2000
+
0.9
0.9
2000
0.7
43.1
43.8
2005
+
0.7
0.7
2005
0.6
33.5
34.1
2006
+
0.7
0.7
2006
0.5
34.1
34.6
2007
+
0.7
0.7
2007
0.5
32.7
33.2
Note: Totals may not sum due to independent rounding.
In 2007, domestic production of pig iron decreased by 4 M 6t h 0 d 010 Q V
percent. Overall, domestic pig iron production has declined
since the 1990s. Pig iron production in 2007 was 24 percent Metallurgical Coke Production
lower than in 2000 and 26 percent below 1990. Carbon Coking coal is used to manufacture metallurgical
dioxide emissions from steel production have decreased by (coal) coke mat is used primarily as a reducing agent in
3 percent (4Tg CO2 Eq.) since 1990. Overall, CO2 emissions the production of iron and steel, but is also used in the
from iron and steel production have declined by 29 percent production of other metals including lead and zinc (see Lead
(30 7 Tg CO Eq ) from 1990 to 2007 Production and Zinc Production in this chapter). Emissions
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
associated with producing metallurgical coke from coking
coal are estimated and reported separately from emissions
that result from the iron and steel production process. To
estimate emission from metallurgical coke production, a Tier
2 method provided by the 20051PCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) was utilized. The
amount of carbon contained in materials produced during
the metallurgical coke production process (i.e., coke, coke
breeze, coke oven gas, and coal tar) is deducted from the
amount of carbon contained in materials consumed during
the metallurgical coke production process (i.e., natural
gas, blast furnace gas, coking coal). Light oil, which is
produced during the metallurgical coke production process,
is excluded from the deductions due to data limitations. The
amount of carbon contained in these materials is calculated
by multiplying the material-specific carbon content by the
amount of material consumed or produced (see Table 4-55).
Table 4-55: Material Carbon Contents for
Metallurgical Coke Production
Material
Coal Tar
Coke
Coke Breeze
Coking Coal
Material
Coke Oven Gas
Blast Furnace Gas
kg C/kg
0.62
0.83
0.83
0.73
kg C/GJ
12.1
70.8
Source: IPCC (2006), Table 4.3. Coke Oven Gas and Blast Furnace Gas,
Table 1.3.
Table 4-56: CH4 Emission Factor for
Metallurgical Coke Production (g CH^metric ton)
Material Produced
g CH4/metric ton
Metallurgical Coke
0.1
Source: IPCC (2006), Table 4.2.
The amount of coal tar produced was approximated using a
production factor of 0.03 tons of coal tar per ton of coking
coal consumed. The amount of coke breeze produced was
approximated using a production factor of 0.075 tons of
coke breeze per ton of coking coal consumed. Data on the
consumption of carbonaceous materials (other than coking
coal) as well as coke oven gas production were available for
integrated steel mills only (i.e., steel mills with co-located
coke plants). Therefore, carbonaceous material (other than
coking coal) consumption and coke oven gas production
were excluded from emission estimates for merchant coke
plants. Carbon contained in coke oven gas used for coke-
oven underfiring was not included in the deductions to avoid
double-counting.
The production processes for metallurgical coke
production results 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
the Tier 1 emission factor (0.1 g CH4/metric ton) taken from
the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006) for metallurgical coke production
(see Table 4-56).
Data relating to the mass of coking coal consumed
at metallurgical coke plants and the mass of metallurgical
coke produced at coke plants were taken from the Energy
Information Administration (EIA), Quarterly Coal Report
October through December (EIA 1998 through 2004a) and
January through March (EIA 2006a, 2007,2008a) (see Table
4-57). Data on the volume of natural gas consumption, blast
furnace gas consumption, and coke oven gas production for
metallurgical coke production at integrated steel mills were
obtained from the American Iron and Steel Institute (AISI),
Annual Statistical Report (AISI 2004 through 2008a) and
through personal communications with AISI (2008b) (see
Table 4-57: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from Metallurgical
Coke Production (Thousand Metric Tons)
Source/Activity Data
Metallurgical Coke Production
Coking Coal Consumption at Coke Plants
Coke Production at Coke Plants
Coal Tar Production
Coke Breeze Production
1990
35,269
25,054
7521
1,879
1995
29,948
21,545
646 1
1,616
2000
26,254
18,877
566
1,416
2005
21,259
15,167
455
1,138
2006
20,827
14,882
446
1,116
2007
20,607
14,698
441
1,102
Industrial Processes 4-39
-------
Table 4-58: Production and Consumption Data for the Calculation of C02 Emissions from Metallurgical
Coke Production (million ft3)
Source/Activity Data
Metallurgical Coke Production
Coke Oven Gas Production3
Natural Gas Consumption
Blast Furnace Gas Consumption
1990
59gl
24,602
1995
1 66,750 1
1841
29,423
2000
149,47/1
180
26,075 |
2005
114,213
2,996
4,460
2006
114,386
3,277
5,505
2007
109,912
3,309
5,144
'Includes coke oven gas used for purposes other than coke oven underfiring only.
Table 4-58). The factor for the quantity of coal tar produced per
ton of coking coal consumed was provided by AISI (2008b).
The factor for the quantity of coke breeze produced per ton of
coking coal consumed was obtained through Table 2-1 of the
report Energy and Environmental Profile of the U.S. Iron and
Steel Industry (DOE 2000). Data on natural gas consumption
and coke oven gas production at merchant coke plants were
not available and were excluded from the emission estimate.
Carbon contents for coking coal, metallurgical coke, coal tar,
coke oven gas, and blast furnace gas were provided by the 2006
IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC 2006). The carbon content for coke breeze was assumed
to equal the carbon content of coke.
Iron and Steel Production
Emissions of CO2 from sinter production and direct
reduced iron production were estimated by multiplying
total national sinter production and the total national direct
reduced iron production by Tier 1 CO2 emission factors (see
Table 4-59). Because estimates of sinter production and direct
reduced iron production were not available, production was
assumed to equal consumption.
To estimate emissions from pig iron production in the
blast furnace, the amount of carbon contained in the produced
pig iron and blast furnace gas were deducted from the amount
of carbon contained in inputs (i.e., metallurgical coke, sinter,
natural ore, pellets, natural gas, fuel oil, coke oven gas,
direct coal injection). The carbon contained in the pig iron,
blast furnace gas, and blast furnace inputs was estimated
Table 4-59: C02 Emission Factors for Sinter Production
and Direct Reduced Iron Production
Material Produced
Metric Ton C02/Metric Ton
Sinter
Direct Reduced Iron
0.2
0.7
by multiplying the material-specific carbon content by each
material type (see Table 4-60). Carbon in blast furnace gas
used to pre-heat the blast furnace air is combusted to form
CO2 during this process.
Emissions from steel production in EAFs were estimated
by deducting the carbon contained in the steel produced
from the carbon contained in the EAF anode, charge carbon,
and scrap steel added to the EAF. Small amounts of carbon
from direct reduced iron, pig iron, and flux additions to the
EAFs were also included in the EAF calculation. For BOFs,
estimates of carbon contained in BOF steel were deducted
from carbon contained in inputs such as natural gas, coke
oven gas, fluxes, and pig iron. In each case, the carbon was
calculated by multiplying material-specific carbon contents
by each material type (see Table 4-60). For EAFs, the amount
of EAF anode consumed was approximated by multiplying
total EAF steel production by the amount of EAF anode
consumed per metric ton of steel produced (0.002 metric tons
EAF anode per metric ton steel produced (AISI 2008b)). The
amount of flux (e.g., limestone and dolomite) used during
Table 4-60: Material Carbon Contents for Iron
and Steel Production
Material
Coke
Direct Reduced Iron
Dolomite
EAF Carbon Electrodes
EAF Charge Carbon
Limestone
Pig Iron
Steel
Material
Coke Oven Gas
Blast Furnace Gas
kg C/kg
0.83
0.02
0.13
0.82
0.83
0.12
0.04
0.01
kg C/GJ
12.1
70.8
Source: IPCC (2006), Table 4.1.
Source: IPCC (2006), Table 4.3. Coke Oven Gas and Blast Furnace Gas,
Table 1.3.
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
steel manufacture was deducted from the Limestone and
Dolomite Use source category to avoid double-counting.
Carbon dioxide emissions from the consumption of blast
furnace gas and coke oven gas for other activities occurring
at the steel mill were estimated by multiplying the amount of
these materials consumed for these purposes by the material-
specific C content (see Table 4-60).
Carbon dioxide emissions associated with the sinter
production, direct reduced iron production, pig iron
production, steel production, and other steel mill activities
were summed to calculate the total CO2 emissions from iron
and steel production (see Table 4-51 and Table 4-52).
The production processes for sinter and pig iron result in
fugitive emissions of CK4, 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 Tier 1 emission factors taken
Table 4-61: CH4 Emission Factors for Sinter and
Pig Iron Production
Material Produced
Factor
Unit
Pig Iron
Sinter
0.9
0.07
g CHVkg
kg CH^metric ton
Source: Sinter (IPCC 2006, Table 4.2), Pig Iron (IPCC/UNEP/OECD/IEA
1995, Table 2.2).
from the 2006 IPCC Guidelines for National Greenhouse
Gas Inventories (IPCC 2006) for sinter production and the
1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) (see
Table 4-61) for pig iron production. The production of direct
reduced iron also results in emissions of CH4 through the
consumption of fossil fuels (e.g., natural gas); however, these
emissions estimates are excluded due to data limitations.
Sinter consumption and direct reduced iron consumption
data were obtained from AISI' s Annual Statistical Report (AISI
2004 through 2008a) and through personal communications
withAISI (2008b) (see Table 4-62). Data on direct reduced iron
consumed in EAFs were not available for the years 1990,1991,
1999, 2006, and 2007. EAF direct reduced iron consumption
in 1990 and 1991 was assumed to equal consumption in
1992, consumption in 1999 was assumed to equal the average
of 1998 and 2000, and consumption in 2006 and 2007 was
assumed to equal consumption in 2005. Data on direct reduced
iron consumed in BOFs were not available for the years 1990
through 1994,1999,2006, and 2007. EOF direct reduced iron
consumption in 1990 through 1994 was assumed to equal
consumption in 1995, consumption in 1999 was assumed to
equal the average of 1998 and 2000, and consumption in 2006
and 2007 was assumed to equal consumption in 2005. The
Tier 1 CO2 emission factors for sinter production and direct
reduced iron production were obtained through the 2006 IPCC
Table 4-62: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from
Iron and Steel Production (Thousand Metric Tons)
Source/Activity Data
Sinter Production
Sinter Production
Direct Reduced Iron Production
Direct Reduced Iron Production
Pig Iron Production
Coke Consumption
Pig Iron Production
Direct Injection Coal Consumption
EAF Steel Production
EAF Anode and Charge Carbon Consumption
Scrap Steel Consumption
Flux Consumption
EAF Steel Production
BOF Steel Production
Pig Iron Consumption
Scrap Steel Consumption
Flux Consumption
BOF Steel Production
1990
12,239
936 1
24,946
49,669
1,485
67 1
35,743
319
33,511
46,564
14,548
576 1
43,973
1995
12,562
989
22,198
50,891
1,509
77 1
39,010
267 1
38,472
49,896
15,967
1,259
56,721
2000
10,788
1,914
19,215
47,888
3,012
96
43,001
654
47,860
46,993
14,969
978
53,965
2005
8,315
1,633
13,832
37,222
2,573
104
37,558
695
52,194
32,115
11,612
582
42,705
2006
7,088
1,633
14,684
37,904
2,526
112
37,558
671
56,071
32,115
11,612
610
42,119
2007
6,914
1,633
15,039
36,337
2,734
114
37,558
567
57,004
32,115
11,612
408
41,099
Industrial Processes 4-41
-------
Guidelines for National Greenhouse Gas Inventories (IPCC
2006). Data for pig iron production, coke, natural gas, fuel
oil, sinter, and pellets consumed in the blast furnace; pig iron
production; and blast furnace gas produced at the iron and steel
mill and used in the metallurgical coke ovens and other steel
mill activities were obtained from AISI's Annual Statistical
Report (AISI 2004 through 2008a) and through personal
communications with AISI (2008b) (see Table 4-63). Data for
EAF steel production, flux, EAF charge carbon, direct reduced
iron, pig iron, scrap steel, and natural gas consumption as well
as EAF steel production were obtained from AISI's Annual
Statistical Report (AISI 2004 through 2008a) and through
personal communications with AISI (2008b). The factor for
the quantity of EAF anode consumed per ton of EAF steel
produced was provided by AISI (AISI 2008b). Data for EOF
steel production, flux, direct reduced iron, pig iron, scrap steel,
natural gas, natural ore, pellet sinter consumption as well as
BOF steel production were obtained from AISI's Annual
Statistical Report (AISI 2004 through 2008a) and through
personal communications with AISI (2008b). Because data on
pig iron consumption and scrap steel consumption in BOFs
and EAFs were not available for 2006 and 2007, 2005 data
were used. Because pig iron consumption in EAFs was also
not available in 2003 and 2004, the average of 2002 and 2005
pig iron consumption data were used. Data on coke oven gas
and blast furnace gas consumed at the iron and steel mill other
than in the EAF, BOF, or blast furnace were obtained from
AISI's Annual Statistical Report (AISI 2004 through 2008a)
and through personal communications with AISI (2008b).
Data on blast furnace gas and coke oven gas sold for use as
synthetic natural gas were obtained through EIA's Natural
Gas Annual 2007 (EIA 2008b). C contents for direct reduced
iron, EAF carbon electrodes, EAF charge carbon, limestone,
dolomite, pig iron, and steel were provided by the 2006 IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC
2006). The C contents for natural gas, fuel oil, and direct
injection coal as well as the heat contents for the same fuels
were provided by EIA (2008b). Heat contents for coke oven
gas and blast furnace gas were provided in Table 2-2 of the
report Energy and Environmental Profile of the U.S. Iron and
Steel Industry (DOE 2000).
Uncertainty
The estimates of CO2 emissions from metallurgical coke
production are based on material production and consumption
data and average carbon contents. Uncertainty is associated
with the total U.S. coking coal consumption, total U.S. coke
production and materials consumed during this process.
Data for coking coal consumption and metallurgical coke
production are from different data sources (EIA) than data
for other carbonaceous materials consumed at coke plants
(AISI), which does not include data for merchant coke plants.
There is uncertainty associated with the fact that coal tar
and coke breeze production were estimated based on coke
Table 4-63: Production and Consumption Data for the Calculation of C02 Emissions from Iron and Steel Production
(million ft3 unless otherwise specified)
Source/Activity Data
Pig Iron Production
Natural Gas Consumption
Fuel Oil Consumption (thousand gallons)
Coke Oven Gas Consumption
Blast Furnace Gas Production3
EAF Steel Production
Natural Gas Consumption
BOF Steel Production
Natural Gas Consumption
Coke Oven Gas Consumption
Other Activities
Coke Oven Gas Consumption
Blast Furnace Gas Consumption
1990
56,
163,
22,
1,439,
9,
6,
3,
224,
1,414,
,273
,397
,033
,380
,604
,301
,851
,883
,778
1995
106,
108,
10,
1,559,
11,
16,
1,
155,
1,530,
,514
,196
,097
,795
,026
,546
,284
,369
,372
2000
91,
120,
,798
,921
13,702
1,524,
13,
6,
135,
1,498,
,891
,135
,816
2005
59,
16,
16,
1,299,
14,
5,
97,
1,295,
844
170
557
980
959
026
524
132
520
2006
58,344
87,702
16,649
1,236,526
16,070
5,827
559
97,178
1,231,021
2007
56,112
84,498
16,239
1,173,588
16,337
11,740
525
93,148
1,168,444
'Includes blast furnace gas used for purposes other than in the blast furnace only.
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
production because coal tar and coke breeze production data
were not available.
The estimates of CO2 emissions from iron and steel
production are based on material production and consumption
data and average carbon contents. There is uncertainty
associated with the assumption that direct reduced iron
and sinter consumption are equal to production. There is
uncertainty associated with the assumption that all coal used
for purposes other than coking coal is for direct injection
coal. Some of this coal may be used for electricity generation.
There is also uncertainty associated with the carbon contents
for pellets, sinter, and natural ore, which are assumed to equal
the carbon contents of direct reduced iron. For EAF steel
production there is uncertainty associated with the amount of
EAF anode and charge carbon consumed due to inconsistent
data throughout the timeseries. Uncertainty is also associated
with the use of process gases such as blast furnace gas
and coke oven gas. Data are not available to differentiate
between the use of these gases for processes at the steel
mill versus for energy generation (e.g., electricity and steam
generation); therefore, all consumption is attributed to iron
and steel production. These data and carbon contents produce
a relatively accurate estimate of CO2 emissions. However,
there are uncertainties associated with each.
For the purposes of the CH4 calculation it is assumed
that all of the CFLj escapes as fugitive emissions and that
none of the CH4 is captured in stacks or vents. 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 an
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-64 for iron and steel production.
Iron and Steel Production CO2 emissions were estimated
to be between 57.0 and 87.9 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 22
percent below and 20 percent above the emission estimate of
73.6 Tg CO2 Eq. Iron and Steel Production CK4 emissions
were estimated to be between 0.6 Tg CO2 Eq. and 0.8 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 0.7 Tg CO2 Eq.
Recalculations Discussion
Estimates of CO2 from iron and steel production have
been revised for the years 1990 through 2006 to adhere to the
methods presented in the 2006IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). Previously the
estimates focused primarily on the consumption of coking
coal to produce metallurgical coke and the consumption of
metallurgical coke, carbon anodes, and scrap steel to produce
iron and steel. The revised estimates differentiate between
emissions associated with metallurgical coke production and
those associated with iron and steel production and include
CO2 emissions from the consumption of other materials such
as natural gas, fuel oil, flux (e.g. limestone and dolomite
use), direction injection goal, sinter, pellets, and natural
ore during the iron and steel production process as well
as the metallurgical coke production process. Currently,
CO2 emissions from iron and steel production are reported
separately from CO2 emissions from metallurgical coke
production. On average, revisions to the Iron and Steel
Production estimate resulted in an annual increase of CO2
emissions of 26.1 Tg CO2 Eq. (40.7 percent).
Estimates of CH4 emissions from iron and steel
production have been revised based on revisions to the
CH4 emission factor from sinter production and to report
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Iron and Steel Production
(Tg C02 Eq. and Percent)3
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Iron and Steel Production
Iron and Steel Production
C02
CH4
73.6
0.7
57.0
0.6
87.9
0.8
-22%
+20%
+8%
aThe emission estimates and the uncertainty range presented in this table correspond to iron and steel production only. Uncertainty associated with
emissions from metallurgical coke production were not estimated due to data limitations and were excluded from the uncertainty estimates presented in
this table.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-43
-------
emissions from metallurgical coke production separately. On
average, revisions to the Iron and Steel Production estimate
resulted in an annual decrease of CH4 emissions of 0.3 Tg
CO2 Eq. (24.6 percent).
Planned Improvements
Plans for improvements to the Iron and Steel Production
source category include attributing emissions estimates for
the production of metallurgical coke to the Energy chapter
as well as identifying the amount of carbonaceous materials,
other than coking coal, consumed at merchant coke plants.
Additional improvements include identifying the amount of
coal used for direct injection and the amount of coke breeze,
coal tar, and light oil produced during coke production.
Efforts will also be made to identify inputs for preparing
Tier 2 estimates for sinter and direct reduced iron production,
as well as to identify information to better characterize
emissions from the use of process gases and fuels within the
Energy and Industrial Processes chapters.
4.14 Ferroalloy Production (IPCC
Source Category 2C2)
Carbon dioxide and CK4 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. Consequently, 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:
Fe203 + 2Si02 + 7C -» 2FeSi + 7CO
While most of the C contained in the process materials
is released to the atmosphere as CO2, a percentage is also
released as CK4 and other volatiles. The amount of CK4 that
is released is dependent on furnace efficiency, operation
technique, and control technology.
Emissions of CO2 from ferroalloy production in 2007
were 1.6 Tg CO2 Eq. (1,552 Gg) (see Table 4-65 and Table
4-66), which is a 3 percent increase from the previous year
and a 28 percent reduction since 1990. Emissions of CK4
from ferroalloy production in 2007 were 0.01 Tg CO2 Eq.
(0.448 Gg), which is also a 3 percent increase from the
previous year and a 28 percent decrease since 1990.
Table 4-65: C02 and CH4 Emissions from Ferroalloy Production (Tg C02 Eq.)
Gas
1990
1995
2000
2005 2006
2007
C02
CH4
2.2
2.o
1.9
1.4
1.5
1.6
Total
2.2
2.0
1.9
1.4
1.5
1.6
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-66: C02 and CH4 Emissions from Ferroalloy Production (Gg)
Gas
1990
1995
2000
2005
2006
2007
C02
CH4
1,505
+
1,552
+
+ Does not exceed 0.5 Gg.
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Methodology
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 2006 IPCC 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 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 CH4/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 CtLj (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 metric tons CO2/
metric 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 biomas s, 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 2007 (see
Table 4-67) were obtained from the USGS through personal
communications with the USGS Silicon Commodity Specialist
(Corathers 2008) and through the Minerals Yearbook: Silicon
Annual Report (USGS 1991 through 2007). Because USGS
does not provide estimates of silicon metal production for
2006 and 2007,2005 production data are used. 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 4-67).
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.16 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
Table 4-67: Production of Ferroalloys (Metric Tons)
Year
Ferrosilicon
25%-55%
Ferrosilicon
56%-95%
Silicon Metal
Misc. Alloys
32%-65%
1990
M
1995
^
2000
NA (Not Available).
321,385
^H
184,000
^^H
229,000
109,566
^M
128,000
^^m
100,000
145,744
^H
163,000
184,000
72,442
^m
99,500
•
NA
2005
2006
2007
123,000
164,000
180,000
86,100
88,700
90,600
148,000
148,000
148,000
NA
NA
NA
16 Emissions and sinks of biogenic carbon are accounted for in the Land
Use, Land-Use Change, and Forestry chapter.
Industrial Processes 4-45
-------
Table 4-68: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Ferroalloy Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Ferroalloy Production
Ferroalloy Production
C02
CH4
1.6
Lower Bound Upper Bound Lower Bound
1.4 1.7 -12%
+ + -12%
Upper Bound
+ 12%
+ 12%
+ Does not exceed 0.05 Tg C02 Eq.
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 4-68. Ferroalloy production CO2
emissions were estimated to be between 1.4 and 1.7 Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
of approximately 12 percent below and 12 percent above the
emission estimate of 1.6 Tg CO2 Eq. Ferroalloy production
CFLj 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.
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 are available concerning raw material consumption (e.g.,
coal coke, limestone and dolomite flux, etc.) for inclusion in
ferroalloy production emission estimates.
4.15 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. As of last reporting, the United States was the fourth
largest producer of primary aluminum, with approximately
seven percent of the world total (USGS 2008). 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).
Carbon dioxide 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 4.3 Tg CO2 Eq. (4,251 Gg) in 2007
(see Table 4-69). 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
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-69: C02 Emissions from Aluminum Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
6.8
6,831
2005
2006
2007
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 carbon 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
smelter and 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 declined
by 80 percent and 76 percent, respectively, to 3.2 Tg CO2
Eq. of CF4 (0.5 Gg) and 0.64 Tg CO2 Eq. of C2F6 (0.07
Gg) in 2007, as shown in Table 4-70 and Table 4-71. This
decline is due both to reductions in domestic aluminum
production and to actions taken by aluminum smelting
companies to reduce the frequency and duration of anode
effects. (Note, however, that production and the frequency
and duration of anode effects increased in 2007 compared
to 2006.) Since 1990, aluminum production has declined by
37 percent, while the combined CF4 and C2F6 emission rate
(per metric ton of aluminum produced) has been reduced
by 67 percent.
In 2007, U.S. primary aluminum production totaled
approximately 2.6 million metric tons, a 12 percent increase
from 2006 production levels. In December 2006, production
resumed at the 265,000-t/y smelter in Hannibal, OH, owned
by Ormet Corp (USGS 2007). In 2007, Columbia Falls
Aluminum Co. announced it was restarting additional
Table 4-70: PFC Emissions from Aluminum Production
(Tg C02 Eq.)
Year
CF4
C2F6
Total
1990
15.9
2.7
18.5
2005
2006
2007
Note: Totals may not sum due to independent rounding.
Table 4-71: PFC Emissions from Aluminum Production
(Gg)
Year
CF4
C2F6
2005
2006
2007
+ Does not exceed 0.05 Gg.
potlines (USAA 2007), and Alcoa Intalco Works reported
increased production from a re-energized potline at their
Ferndale operation (Alcoa Inc. 2007).
Methodology
Carbon dioxide 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 based
on 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:
2A12O3
3C -» 4A1 + 3CO,
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.
Industrial Processes 4-47
-------
Depending on the availability of smelter-specific data,
the CO2 emitted from electrolysis at each smelter was
estimated from: (1) the smelter's annual anode consumption;
(2) the smelter's annual aluminum production and rate of
anode consumption (per ton of aluminum produced) for
previous and /or following years, or; (3) the smelter's annual
aluminum production and IPCC default CO2 emission
factors. The first approach tracks the consumption and carbon
content of the anode, assuming that all carbon in the anode
is converted to CO2. Sulfur, ash, and other impurities in the
anode are subtracted from the anode consumption to arrive
at a carbon consumption figure. This approach corresponds
to either the IPCC Tier 2 or Tier 3 method, depending on
whether smelter-specific data on anode impurities are used.
The second approach interpolates smelter-specific anode
consumption rates to estimate emissions during years for
which anode consumption data are not available. This
avoids substantial errors and discontinuities that could be
introduced by reverting to Tier 1 methods for those years.
The last approach corresponds to the IPCC Tier 1 method
(2006) and is used in the absence of present or historic anode
consumption data.
The equations used to estimate CO2 emissions in the
Tier 2 and 3 methods vary depending on smelter type (IPCC
2006). For Prebake cells, the process formula accounts for
various parameters, including net anode consumption, and
the sulfur, ash, and impurity content of the baked anode. For
anode baking emissions, the formula accounts 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. For S0derberg cells, the 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, anode consumption (and some
anode impurity) data have been reported for 1990, 2000,
2003, 2004, 2005, 2006, and 2007. 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 18 of the 23 operating smelters in 1990
and 2000, by 14 out of 16 operating smelters in 2003 and
2004, 14 out of 15 operating smelters in 2005, and 13 out
of 14 operating smelters in 2006 and 2007. 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 14 smelters in 2007 and 2006,1 out of 15 smelters in
2005, and 5 out of 23 smelters 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 13 out of 14 operating
smelters were reported under the VAIP in 2007. Between
1990 and 2006, 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 (US AA 2008), 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:
PFC (CF4 or C2F6) kg/metric ton Al =
S x Anode Effect Minutes/Cell-Day
where,
S = Slope coefficient (kg PFC/metric ton
Al)/(Anode Effect Minute/Cell-Day)
Anode Effect
Minutes/
Cell-Day = Anode Effect Frequency/Cell-Day x
Anode Effect Duration (Minutes)
This approach corresponds to either the Tier 3 or the Tier
2 approach in the 2006 IPCC Guidelines, depending upon
whether the slope-coefficient is smelter-specific (Tier 3) or
technology-specific (Tier 2). For 1990 through 2007, smelter-
specific slope coefficients were available and were used for
smelters representing between 30 and 94 percent of U.S.
primary aluminum production. The percentage changed from
year to year as some smelters closed or changed hands and as
the production at remaining smelters fluctuated. For smelters
that did not report smelter-specific slope coefficients, IPCC
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
technology-specific slope coefficients were applied (IPCC
2000, 2006). The slope coefficients were combined with
smelter-specific anode effect data collected by aluminum
companies and reported under the VAIP, to estimate emission
factors over time. For 1990 through 2007, smelter-specific
anode effect data were available for smelters representing
between 80 and 100 percent of U.S. primary aluminum
production. Where smelter-specific anode effect data were
not available, industry averages were used.
For all smelters, emission factors were multiplied by
annual production to estimate annual emissions at the smelter
level. For 1990 through 2007, smelter-specific production
data were available for smelters representing between 30 and
100 percent of U.S. primary aluminum production. (For the
years after 2000, this percentage was near the high end of the
range.) Production at non-reporting smelters was estimated
by calculating the difference between the production reported
under VAIP and the total U.S. production supplied by USGS
or US AA and then allocating this difference to non-reporting
smelters in proportion to their production capacity. Emissions
were then aggregated across smelters to estimate national
emissions.
National primary aluminum production data for 2007
were obtained via USAA (USAA 2008). For 1990 through
2001, and 2006 (see Table 4-72) data were obtained from
USGS Mineral Industry Surveys: Aluminum Annual Report
(USGS 1995, 1998, 2000, 2001, 2002, 2007). For 2002
through 2005, national aluminum production data were
Table 4-72: Production of Primary Aluminum (Gg)
Year
Gg
2005
2006
2007
2,478
2,284
2,560
obtained from the United States Aluminum Association's
Primary Aluminum Statistics (USAA 2004, 2005, 2006).
Uncertainty
The overall uncertainties associated with the 2007 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 CO2
emissions. Uncertainty surrounding reported production data
was assumed to be 1 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 and for
the U.S. aluminum industry as a whole.
The results of this quantitative uncertainty analysis are
summarized in Table 4-73. Aluminum production-related
CO2 emissions were estimated to be between 4.1 and 4.4 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 4 percent below to 4 percent above
the emission estimate of 4.3 Tg CO2 Eq. Also, production-
related CF4 emissions were estimated to be between 2.9
and 3.5 Tg CO2 Eq. at the 95 percent confidence level.
This indicates a range of approximately 10 percent below
to 9 percent above the emission estimate of 3.2 Tg CO2
Eq. Finally, aluminum production-related C2F6 emissions
were estimated to be between 0.5 and 0.8 Tg CO2 Eq. at
Industrial Processes 4-49
-------
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for C02 and PFC Emissions from Aluminum Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Aluminum Production
Aluminum Production
Aluminum Production
C02
CF4
C2F6
4.3
3.2
0.6
Lower Bound
4.1
2.9
0.5
Upper Bound
4.4
3.5
0.8
Lower Bound
-4%
-10%
-27%
Upper Bound
+4%
+ 9%
+32%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
the 95 percent confidence level. This indicates a range of
approximately 27 percent below to 32 percent above the
emission estimate of 0.6 Tg CO2 Eq.
The 2007 emission estimate was developed using
site-specific PFC slope coefficients for all but 1 of the 14
operating smelters where default IPCC (2006) slope data
was used.
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,GariepyandDube 1992,Koetal. 1993,
Ten Eyck and Lukens 1996, Zurecki 1996).
Recalculations Discussion
There were no recalculations in the historical timeseries
for this source category.
4.16 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-five years.
The magnesium industry emitted 3.0 Tg CO2 Eq. (0.1
Gg) of SF6 in 2007, representing an increase of approximately
4 percent from 2006 emissions (see Table 4-74). The increase
is attributed to higher production by the sand casting sector
in 2007 (USGS 2008a). Counter to the increase in production
from sand casting, a combination of high magnesium prices
and reduced demand from the American auto industry has
adversely impacted die casting operations in the United
States (USGS 2008b).
Table 4-74: SF6 Emissions from Magnesium Production
and Processing (Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
5.4
0.2
1995
2000
^m
2005
2006
2007
5.6
3.0
•
2.9
2.9
3.0
0.1
0.1
0.1
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Methodology
Emission estimates for the magnesium industry
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 production (i.e., die, sand, permanent
mold, wrought, and anode casting). Absolute emissions for
1999 through 2007 from primary production, secondary
production (i.e., recycling), and die casting were generally
reported by Partnership participants. Partners reported their
SF6 consumption, which was assumed to be equivalent to
emissions. When a partner did not report emissions, they
were estimated based on the metal processed and emission
rate reported by that partner in previous and (if available)
subsequent years. Where data for subsequent years was
not available, metal production and emissions rates were
extrapolated based on the trend shown by partners reporting
in the current and previous years.
Emission factors for 2002 to 2006 for sand casting
activities were also acquired through the Partnership.
For 2007, the sand casting partner did not report and the
reported emission factor from 2005 was utilized as being
representative of the industry. The 1999 through 2007
emissions from casting operations (other than die) were
estimated by multiplying emission factors (kg SF6 per metric
ton of magnesium produced or processed) by the amount of
metal produced or consumed. The emission factors for casting
activities are provided below in Table 4-75. The emission
Table 4-75: SF6 Emission Factors (kg SF6 per metric ton
of Magnesium)
Die Permanent
Year Casting Mold Wrought Anodes
1999
2000
2001
2002
2003
2004
2005
2006
2007
2.14a
0.72
0.72
0.71
0.81
0.81
0.76
0.86
0.67
2 1
2 1
2 1
2 1
2 1
2 1
2 1
2 1
2 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.
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 average 1995
partner value of 1.1 kg SF6 per metric ton.
Die casting emissions for 1999 through 2007, which
accounted for 19 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 2007, partners accounted for all U.S. die casting
that was tracked by USGS. 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, wrought, and anode casting) were based
on discussions with industry representatives.
Data used to develop SF6 emission estimates were
provided by the Magnesium Partnership participants and
the USGS. U.S. magnesium metal production (primary
and secondary) and consumption (casting) data from 1990
through 2007 were available from the USGS (USGS 2002,
2003,2005,2006,2007,2008a). Emission factors from 1990
through 1998 were based on a number of sources. Emission
factors for primary production were available from U.S.
primary producers for 1994 and 1995, and an emission
factor for die casting of 4.1 kg per metric ton was available
for the mid-1990s from an international survey (Gjestland
& Magers 1996).
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 1997. For die casting, an emission
factor of 4.1 kg per metric ton was used for the period 1990
through 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
Industrial Processes 4-51
-------
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).
Sand casting emission factors for 2002 through 2007 were
provided by the Magnesium Partnership participants, and
1990 through 2001 emission factors for this process were
assumed to have been the same as the 2002 emission factor.
The emission factor for secondary production from 1990
through 1998 was assumed to be constant at the 1999 average
partner value. 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 4-75.
Uncertainty
To estimate the uncertainty surrounding the estimated
2007 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 SF6
Emission Reduction 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. An uncertainty of 5 percent
was assigned to the data reported by each participant in the
Partnership. If partners did not report emissions data during
the current reporting year, SF6 emissions data were estimated
using available emission factors and production information
reported in prior years; the extrapolation was based on the
average trend for partners reporting in the current reporting
year and the year prior. The uncertainty associated with the
SF6 usage estimate generated from the extrapolated emission
factor and production information was estimated to be 30
percent; the lone sand casting partner did not report in the
current reporting year and its activity and emission factor was
held constant at 2006 and 2005 levels, respectively, and given
an uncertainty of 30 percent. For those industry processes that
are not represented in Partnership, such as permanent mold
and wrought casting, SF6 emissions were estimated using
production and consumption statistics reported by USGS
and estimated process-specific emission factors (see Table
4-75). The uncertainties associated with the emission factors
and USGS-reported statistics were assumed to be 75 percent
and 25 percent, respectively. Emissions associated with
sand casting activities utilized a partner-reported emission
factor with an uncertainty of 75 percent. In general, where
precise quantitative information was not available on the
uncertainty of a parameter, a conservative (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 in die casting
applications on the order of 20 percent (Bartos et al. 2007).
Sulfur hexafluoride may also be used as a cover gas for the
casting of molten aluminum with high magnesium content;
however, the extent to which this technique is used in the
United States is unknown.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 4-76. Sulfur hexafluoride
emissions associated with magnesium production and
processing were estimated to be between 2.6 and 3.4Tg CO2
Eq. at the 95 percent confidence level. This indicates a range
Table 4-76: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and Processing
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Magnesium Production SF6
3.0
2.6
3.4
-12%
+13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
of approximately 12 percent below to 13 percent above the
2007 emission estimate of 3.0 Tg CO2 Eq.
Recalculations Discussion
Newly reported historical data from a secondary remelt
partner led to revised SF6 emission estimates in the years
2001 to 2006; the new data resulted in an average decrease
of 0.3 Tg CO2 Eq. in emissions for the 2004 to 2006 period,
or about 10 percent of total emissions.
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 the 2006
IPCC Guidelines, IPCC 2006) that all SF6 utilized is emitted
to the atmosphere. EPA-funded measurements of SF6 in die
casting applications have indicated that the latter assumption
may be incorrect, with observed SF6 degradation on the
order of 20 percent (Bartos et al. 2007). 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. Magnesium producers and
processors have already begun using these cover gases for
2006 and 2007 in a limited fashion; because the amounts are
currently negligible these emissions are only being monitored
and recorded at this time.
4.17. Zinc Production
(IPCC Source Category 2C5)
Zinc production in the United States consists of both
primary and secondary processes. Primary production
techniques used in the United States are the electrothermic
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 electrothermic 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 electrothermic 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).
In 2007, U.S. primary and secondary zinc production
totaled 519,221 metric tons (Tokin 2009). The resulting
emissions of CO2 from zinc production in 2007 were
estimated to be 0.5 Tg CO2 Eq. (530 Gg) (see Table
4-77). All 2007 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,
emissions have decreased in recent years due to the closing of
an electrothermic-process zinc plant in Monaca, PA (USGS
Table 4-77: C02 Emissions from Zinc Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
0.9
949
2005
2006
2007
Industrial Processes 4-53
-------
2004). Emissions for 2007, which are nearly half that of 1990
(44 percent), remained constant from 2006 due to the use of
proxied data for secondary zinc production.
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 electrothermic
and Waelz Kiln processes, were needed. Due to the limited
amount of information available for these electrothermic
processes, only Waelz Kiln process-specific emission factors
were developed. These emission factors were applied to
both the Waelz Kiln process and the electrothermic 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
purposes per ton of zinc produced, 1.19 metric tons coke/
metric ton zinc produced (Viklund-White 2000), and the
following equation:
1.19 metric tons coke
Waelz Kiln —
metric tons zinc
0.84 metric tons C
metric tons coke
3.67 metric tons CO2
metric tons C
3.66 metric tons CO2
metric tons zinc
The USGS disaggregates total U.S. primary zinc
production capacity into zinc produced using the
electrothermic 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 electrothermic zinc production capacity is
divided by total primary zinc production capacity to estimate
the percent of primary zinc produced using the electrothermic
process. This percent is then multiplied by total primary zinc
production to estimate the amount of zinc produced using the
electrothermic 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 electrothermic 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 electrothermic or Waelz Kiln process. In 1997,
the Horsehead Corporation plant, located in Monaca, PA,
produced 47,174 metric tons of secondary zinc using the
electrothermic process (Queneau et al. 1998). This is the
only plant in the United States that uses the electrothermic
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 electrothermic process. This value is then multiplied
by the Waelz Kiln process emission factor to obtain total
CO2 emissions for secondary zinc produced using the
electrothermic 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:
EFF
0.4 metric tons coke
metric tons EAF dust
0.84 metric tons C
metric tons coke
3.67 metric tons CO2
metric tons C
1.23 metric tons CO2
metric tons EAF dust
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-78: Zinc Production (Metric Tons)
Year
Primary
Secondary
191,120
113,000
121,221
349,000
397,000
398,000
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 2006 activity data for primary and
secondary zinc production (see Table 4-78) were obtained
through the USGS Mineral Yearbook: Zinc (USGS 1994
through 2008). Preliminary data for 2007 primary production
and production from scrap were obtained from the USGS
Mineral Commodity Specialist (Tolcin 2009). Because data
for 2007 secondary zinc production were unavailable, 2006
data were used.
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 electrothermic and Waelz Kiln emissive
zinc production processes. For primary zinc production, the
amount of zinc produced annually using the electrothermic
process is estimated from the percent of primary zinc
production capacity that electrothermic 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 electrothermic process. The amount of
secondary zinc produced using the electrothermic 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 electrothermic 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
electrothermic process. Therefore, emission factors for the
Waelz Kiln process were applied to both electrothermic 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 4-79. Zinc production CO2
Industrial Processes 4-55
-------
Table 4-79: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Zinc Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Zinc Production
CO,
0.5
0.4
0.7
-21%
+25%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
emissions were estimated to be between 0.4 and 0.7 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.
4.18. Lead Production
(IPCC Source Category 2C5)
Lead production in the United States consists of both
primary and secondary processes—both of which emit CO2
(Sjardin 2003). Primary lead production, in the form of
direct smelting, mostly occurs at plants located in Alaska
and Missouri, though to a lesser extent in Idaho, Montana,
and Washington. Secondary production largely involves the
recycling of lead acid batteries at approximately 18 separate
smelters located in 11 states (USGS 2008 and 2009). Secondary
lead production has increased in the United States over the past
decade while primary lead production has decreased. In 2007,
secondary lead production accounted for approximately 91
percent of total lead production (USGS 2009).
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 20 percent from 2006 to 2007 and has decreased by 68
percent since 1990 (USGS 2009, USGS 1995).
At last reporting, approximately 93 percent of refined
lead production is produced primarily from scrapped
lead acid batteries (USGS 2009). 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 decreased from 2006 to 2007 by 2 percent,
and has increased by 28 percent since 1990 (USGS 2009,
USGS 1995).
At last reporting, the United States was the third largest
mine producer of lead in the world, behind China and Australia,
accounting for 12 percent of world production in 2007 (USGS
2009). In 2007, U.S. primary and secondary lead production
totaled 1,303,000 metric tons (USGS 2009). The resulting
emissions of CO2 from 2007 production were estimated to
be 0.3 Tg CO2 Eq. (267 Gg) (see Table 4-80). The majority
of 2007 lead production is from secondary processes, which
account for 88 percent of total 2007 CO2 emissions.
After a gradual increase in total emissions from 1990 to
2000, total emissions have decreased by six percent since 1990,
largely due to a decrease in primary production (68 percent
since 1990) and a transition within the United States from
primary lead production to secondary lead production, which
is less emissive than primary production, although the sharp
decrease leveled off in 2005 (USGS 2009, Smith 2007).
Table 4-80: C02 Emissions from Lead Production
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
0.3
285
2005
2006
2007
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-81: Lead Production (Metric Tons)
Year
Primary
Secondary
143,000
153,000
123,000
922,000
1,020,000
1,130,000
^^^H
1,150,000
1,160,000
1,180,000
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) and the IPCC (2006) provide an emission factor of
0.25 metric tons CO2/ton lead. For secondary lead production,
Sjardin (2003) and IPCC (2006) provide 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 2007 activity data for primary and
secondary lead production (see Table 4-81) were obtained
through the USGS Minerals Yearbook: Lead (USGS 1994
through 2009).
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 emission
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 4-82. 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.
4.19. HCFC-22 Production
(IPCC Source Category 2E1)
Trifluoromethane (HFC-23 or CHF3) is generated as a
byproduct 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 but
has generally remained above 1990 levels. Because HCFC-22
depletes stratospheric ozone, its production for non-feedstock
uses is scheduled to be phased out by 2020 under the U.S.
Table 4-82: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lead Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lead Production
CO,
0.3
0.2
0.3
-16%
+17%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-57
-------
Clean Air Act.17 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
SbClxFy, (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 may be released
to the atmosphere, recaptured for use in a limited number of
applications, or destroyed.
Emissions of HFC-23 in 2007 were estimated to be
17.0 Tg CO2 Eq. (1.5 Gg) (Table 4-83). This quantity
represents a 23 percent increase from 2006 emissions and
a 53 percent decline from 1990 emissions. The increase
from 2006 emissions was caused by a 5 percent increase in
HCFC-22 production and a 17 percent increase in the HFC-
23 emission rate. The decline from 1990 emissions is due
to a 60 percent decrease in the HFC-23 emission rate since
1990. The decrease is primarily attributable to four factors:
(a) five plants that did not capture and destroy the HFC-23
generated have ceased production of HCFC-22 since 1990;
(b) one plant that captures and destroys the HFC-23 generated
began to produce HCFC-22; (c) one plant implemented and
documented a process change that reduced the amount of
HFC-23 generated; and (d) the same plant began recovering
HFC-23, primarily for destruction and secondarily for sale.
Three HCFC-22 production plants operated in the United
States in 2008, two of which used thermal oxidation to
significantly lower their HFC-23 emissions.
Table 4-83: HFC-23 Emissions from HCFC-22
Production (Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
36.4
2005
2006
2007
17 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].
Methodology
To estimate their emissions of HFC-23, five of the eight
HCFC-22 plants that have operated in the U.S. since 1990
use (or, for those plants that have closed, used) methods
comparable to the Tier 3 methods in the 2006 IPCC
Guidelines (IPCC 2006). The other three plants, the last of
which closed in 1993, used methods comparable to the Tier 1
method in the 2006 IPCC Guidelines. Emissions from these
three plants have been recalculated using the recommended
emission factor for unoptimized plants operating before
1995 (0.04 kg HCFC-23/kg HCFC-22 produced). (This
recalculation was reflected in the 1990 through 2006
inventory submission.)
The five plants that have operated since 1994 measured
concentrations of HFC-23 to estimate their emissions of HFC-
23. 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. Plants that
release (or historically have released) some of their byproduct
HFC-23 periodically measure HFC-23 concentrations in the
output stream using gas chromatography. This information is
combined with information on quantities of products (e.g.,
HCFC-22) to estimate HFC-23 emissions.
In most years, including 2008, an industry association
aggregates and reports to EPA country-level estimates of
HCFC-22 production and HFC-23 emissions (ARAP 1997,
1999,2000,2001,2002,2003,2004,2005,2006,2007,2008).
However, in 1997 and 2008, EPA (through a contractor)
performed comprehensive reviews of plant-level estimates
of HFC-23 emissions and HCFC-22 production (RTI 1997;
RTI 2008). These reviews enabled EPA to review, update,
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-84: HCFC-22 Production (Gg)
Year
Gg
1990
1995
2000
^H
2005
2006
2007
139
•
155
•
186
•
156
154
162
and where necessary, correct U.S. totals, and also to perform
plant-level uncertainty analyses (Monte-Carlo simulations)
for 1990, 1995, 2000, 2005, and 2006. Estimates of annual
U.S. HCFC-22 production are presented in Table 4-84.
Uncertainty
The uncertainty analysis presented in this section was
based on a plant-level Monte Carlo simulation for 2006. The
Monte Carlo analysis used estimates of the uncertainties in
the individual variables in each plant's estimating procedure.
This analysis was based on the generation of 10,000 random
samples of model inputs from the probability density
functions for each input. A normal probability density
function was assumed for all measurements and biases
except the equipment leak estimates for one plant; a log-
normal probability density function was used for this plant's
equipment leak estimates. The simulation for 2006 yielded
a 95-percent confidence interval for U.S. emissions of 6.8
percent below to 9.6 percent above the reported total.
Because EPA did not have access to plant-level
emissions data for 2007, the relative errors yielded by the
Monte Carlo simulation for 2006 were applied to the U.S.
emission estimate for 2007. The resulting estimates of
absolute uncertainty are likely to be accurate because (1) the
methods used by the three plants to estimate their emissions
are not believed to have changed significantly since 2006;
(2) the distribution of emissions among the plants is not
believed to have changed significantly since 2006 (one plant
continues to dominate emissions); and (3) the country-level
relative errors yielded by the Monte Carlo simulations for
2005 and 2006 were very similar, implying that these errors
are not sensitive to small, year-to-year changes.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-85. HFC-23 emissions from
HCFC-22 production were estimated to be between 15.8
and 18.6 Tg CO2 Eq. at the 95-percent confidence level. This
indicates a range of approximately 7 percent below and 10
percent above the emission estimate of 17.0 Tg CO2 Eq.
4.20. Substitution of Ozone
Depleting Substances (IPCC Source
Category 2F)
Hydrofluorocarbons (HFCs) andperfluorocarbons (PFCs)
are used as alternatives to several classes of ozone depleting
substances (ODSs) that are being phased out under the terms
of the Montreal Protocol and the Clean Air Act Amendments
of 1990.ls 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 4-86 and Table 4-87.
Table 4-85: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
HCFC-22 Production
HFC-23
17.0
15.8
18.6
+ 10%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
8 [42 U.S.C § 7671, CAA § 601].
Industrial Processes 4-59
-------
Table 4-86: Emissions of MFCs and PFCs from ODS Substitutes (Tg C02 Eq.)
Gas
1990
1995
2000
2005
2006
2007
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-236fa
CF4
Others3
;
0.3
0.4
10.3
70.5
12.2
0.8
+
5.9
0.6
12.3
70.7
14.4
0.8
+
6.2
0.9
14.7
68.6
16.7
0.9
+
6.5
Total
0.3
28.5
71.2
100.0
105.0
108.3
+ 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 4-87: Emissions of MFCs and PFCs from ODS Substitution (Mg)
Gas
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-236fa
CF4
Others3
1990
+
+
\
M
1995
+
+ 1
291
19,537
1321
36 1
+ 1
M
2000
1
44l
1,873
44,011
1,089
85 1
ll
M|
2005
1
562
3,675
54,226
3,200
125
2
M
2006
1
913
4,394
54,362
3,782
131
2
M
2007
1
1,325
5,253
52,782
4,402
136
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.
In 1990 and 1991, the only significant emissions of
HFCs and PFCs as substitutes to ODSs were relatively small
amounts of HFC-152a—used as an aerosol propellant and
also 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.19 In 1993, the use of HFCs in
foam production 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 108.3 Tg CO2 Eq. in 2007. This increase was in
9 R-404A contains HFC-125, HFC-143a, and HFC-134a.
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
of these gases and the introduction of alternative gases and
technologies, however, may help to offset this anticipated
increase in emissions.
Table 4-88 presents HFCs and PFCs emissions by end-
use sector for 1990 through 2007. The end-use sectors that
contributed the most toward emissions of HFCs and PFCs
as ODS substitutes in 2007 include refrigeration and air-
conditioning (97.5 Tg CO2 Eq., or approximately 90 percent),
aerosols (6.2 Tg CO2 Eq., or approximately 6 percent), and
foams (2.6 Tg CO2 Eq., or approximately 2 percent). Within
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-88: Emissions of MFCs and PFCs from ODS Substitutes (Tg C02 Eq.) by Sector
Gas
1990
1995
2000
2005
2006
2007
Refrigeration/Air-conditioning
Aerosols
Foams
Solvents
Fire Protection
j
+
119.31 58.6
8.11 10.1
0.9 2.1 I
90.1
5.9
2.2
1.3
0.5
94.6
6.1
2.4
1.3
0.6
97.5
6.2
2.6
1.3
0.7
Total
28.5
71.2
100.0
105.0
108.3
+ Does not exceed 0.05 Tg C02 Eq.
the refrigeration and air-conditioning end-use sector, motor
vehicle air-conditioning was the highest emitting end-use
(52.9 Tg CO2 Eq.), followed by refrigerated transport and
retail food. Each of the end-use sectors is described in more
detail below.
Refrigeration/Air-conditioning
The refrigeration and air-conditioning sector includes a
wide variety of equipment types that have historically used
CFCs or HCFCs. End-uses within this sector include motor
vehicle air-conditioning, retail food refrigeration, refrigerated
transport (e.g., ship holds, truck trailers, railway freight cars),
household refrigeration, residential and small commercial
air-conditioning/heat pumps, chillers (large comfort
cooling), cold storage facilities, and industrial process
refrigeration (e.g., systems used in food processing, chemical,
petrochemical, pharmaceutical, oil and gas, and metallurgical
industries). As the ODS phaseout is taking effect, most
equipment is being or will eventually be retrofitted or
replaced to use HFC-based substitutes. Common HFCs in
use today in refrigeration/air-conditioning equipment are
HFC- 134a, R-410A, R-404A, and R-507A. These HFCs are
emitted to the atmosphere during equipment manufacture
and operation (as a result of component failure, leaks, and
purges), as well as at servicing and disposal events.
Aerosols
Aerosol propellants are used in metered dose inhalers
(MDIs) and a variety of personal care products and technical/
specialty products (e.g., duster sprays and safety horns).
Many pharmaceutical companies that produce MDIs—a
type of inhaled therapy used to treat asthma and chronic
obstructive pulmonary disease—have committed to replace
the use of CFCs with HFC-propellant alternatives. The
earliest ozone-friendly MDIs were produced with HFC- 134a,
but eventually, the industry expects to use HFC-227ea as well.
Conversely, since the use of CFC propellants was banned in
1978, most consumer aerosol products have not transitioned
to HFCs, but to "not-in-kind" technologies, such as solid or
roll-on deodorants and finger-pump sprays. The transition
away from ODS in specialty aerosol products has also led
to the introduction of non-fluorocarbon alternatives (e.g.,
hydrocarbon propellants) in certain applications, in addition
to HFC-134a or HFC-152a. These propellants are released
into the atmosphere as the aerosol products are used.
Foams
CFCs and HCFCs have traditionally been used as foam
blowing agents to produce polyurethane (PU), polystyrene,
polyolefin, and phenolic foams, which are used in a wide
variety of products and applications. Since the Montreal
Protocol, flexible PU foams as well as other types of
foam, such as polystyrene sheet, polyolefin, and phenolic
foam, have transitioned almost completely away from
fluorocompounds, into alternatives such as CO2, methylene
chloride, and hydrocarbons. The majority of rigid PU foams
have transitioned to HFCs—primarily HFC- 134a and HFC-
245fa. Today, these HFCs are used to produce polyurethane
appliance foam, PU commercial refrigeration, PU spray, and
PU panel foams—used in refrigerators, vending machines,
roofing, wall insulation, garage doors, and cold storage
applications. In addition, HFC-152a is used to produce
polystyrene sheet/board foam, which is used in food
packaging and building insulation. Emissions of blowing
agents occur when the foam is manufactured as well as
during the foam lifetime and at foam disposal, depending
on the particular foam type.
Solvents
CFCs, methyl chloroform (1,1,1-trichloroethane or
TCA), and to a lesser extent carbon tetrachloride (CC14)
were historically used as solvents in a wide range of cleaning
Industrial Processes 4-61
-------
applications, including precision, electronics, and metal
cleaning. Since their phaseout, metal cleaning end-use
applications have primarily transitioned to non-fluorocarbon
solvents and not-in-kind processes. The precision and
electronics cleaning end-uses have transitioned in part to
high-GWP gases, due to their high reliability, excellent
compatibility, good stability, low toxicity, and selective
solvency. These applications rely on HFC-43 lOmee, HFC-
365mfc, HFC-245fa, and to a lesser extent, PFCs. Electronics
cleaning involves removing flux residue that remains after
a soldering operation for printed circuit boards and other
contamination-sensitive electronics applications. Precision
cleaning may apply to either electronic components or to
metal surfaces, and is characterized by products, such as disk
drives, gyroscopes, and optical components, that require a
high level of cleanliness and generally have complex shapes,
small clearances, and other cleaning challenges. The use of
solvents yields fugitive emissions of these HFCs and PFCs.
Fire Protection
Fire protection applications include portable fire
extinguishers ("streaming" applications) that originally used
halon 1211, and total flooding applications that originally
used halon 1301, as well as some halon 2402. Since the
production and sale of halons were banned in the United
States in 1994, the halon replacement agent of choice in the
streaming sector has been dry chemical, although HFC-236ea
is also used to a limited extent. In the total flooding sector,
HFC-227ea has emerged as the primary replacement for
halon 1301 in applications that require clean agents. Other
FfFCs, such as HFC-23, FfFC-236fa, andHFC-125, are used
in smaller amounts. The majority of HFC-227ea in total
flooding systems is used to protect essential electronics, as
well as in civil aviation, military mobile weapons systems,
oil/gas/other process industries, and merchant shipping. As
fire protection equipment is tested or deployed, emissions of
these HFCs are released.
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
(2006). 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 19 end-uses, comprising over 97
percent of the total emissions, and 5 other end-uses. 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, two new end-uses were
included in the uncertainty estimate—polyurethane flexible
integral skin foam and residential unitary air conditioners.
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 97 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
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 4-89: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)a
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Substitution of Ozone MFCs and
Depleting Substances PFCs
105.9
97.5
115.2
+ 9%
a2007 Emission estimates and the uncertainty range presented in this table correspond to aerosols, foams, solvents, fire extinguishing agents, and
refrigerants, but not for other remaining categories. Therefore, because the uncertainty associated with emissions from "other" ODS substitutes was not
estimated, they were exclude in the estimates reported in this table.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 refrigerated transport,
as well as the percent of non-MDI aerosol propellant that is
HFC-152a.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-89. Substitution of ozone
depleting substances HFC and PFC emissions were estimated
to be between 97.5 and 115.2 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 8
percent below to 9 percent above the emission estimate of
105.9 Tg CO2 Eq.
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 decrease of 1.2
Tg CO2 Eq. (1.2 percent) in HFC and PFC emissions from
the substitution of ozone depleting substances for the period
1990 through 2007. The primary change was a revision in
the non-MDI aerosol sector, where a fraction of the market
formerly assumed to use HFC- 134a (with a GWP of 1,300)
was discovered to be transitioning more quickly to HFC-
152a (with a GWP of 140).
4.21. 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
Industrial Processes 4-63
-------
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 byproduct.
Besides dielectric film etching andPECVD chamber cleaning,
much smaller quantities of fluorinated gases are used to etch
polysilicon films and refractory metal films like tungsten.
For 2007, total weighted emissions of all fluorinated
greenhouse gases by the U.S. semiconductor industry were
estimated to be 4.7 Tg CO2 Eq. Combined emissions of all
fluorinated greenhouse gases are presented in Table 4-90
and Table 4-91 below for years 1990, 1995, 2000 and the
period 2005 to 2007. The rapid growth of this industry and
the increasing complexity (growing number of layers)20 of
semiconductor products led to an increase in emissions of
150 percent between 1990 and 1999, when emissions peaked
at 7.2 Tg CO2 Eq. The emissions growth rate began to slow
after 1998, and emissions declined by 35 percent between
1999 and 2007. Together, industrial growth and adoption of
emissions reduction technologies, including but not limited
to abatement technologies, resulted in a net increase in
emissions of 63 percent between 1990 and 2007.
Table 4-90: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.)
Gas
1990
1995
2000
2005
2006
2007
CF4
C2F6
CsFs
c-C4F8
HFC-23
SFB
1.1
2.0
0.0
0.1
0.2
1.0
0.4
1.2
2.2
0.0
0.1
0.3
1.0
0.7
1.3
2.3
0.0
0.1
0.3
0.8
0.5
Total
2.9
4.9
6.2
4.4
4.7
4.7
aNF3 emissions are presented for informational purposes, using the AR4 GWP of 17,200, and are not included in totals.
Note: Totals may not sum due to independent rounding.
Table 4-91: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)
Gas
CF4
C2F6
C^FS
c-C4F8
HFC-23
SF6
NF3
1990
1995
2000
2005
168
216
5
13
18
40
26
2006
181
240
5
13
22
40
40
2007
195
246
6
7
22
34
30
20 Complexity is a term denoting the circuit required to connect the active
circuit elements (transistors) on a chip. Increasing miniaturization, for the
same chip size, leads to increasing transistor density, which, in turn, requires
more complex interconnections between those transistors. This increasing
complexity is manifested by increasing the levels (i.e., layers) of wiring, with
each wiring layer requiring fluorinated gas usage for its manufacture.
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Methodology
Emissions are based on Partner reported emissions
data received through the EPA's PFC Reduction/Climate
Partnership and the EPA's PFC Emissions Vintage Model
(PEVM), a model which estimates industry emissions in
the absence of emission control strategies (Burton and
Beizaie 2001).21 The availability and applicability of Partner
data differs across the 1990 through 2007 time series.
Consequently, emissions from semiconductor manufacturing
were estimated using four distinct methods, one each for
the periods 1990 through 1994, 1995 through 1999, 2000
through 2006, and 2007.
1990 through 1994
From 1990 through 1994, Partnership data was
unavailable and emissions were modeled using the PEVM
(Burton and Beizaie 2001).22 1990 to 1994 emissions are
assumed to be uncontrolled, since reduction strategies such as
chemical substitution and abatement were yet developed.
PEVM is based on the recognition that PFC emissions
from semiconductor manufacturing vary with (1) the number
of layers that comprise different kinds of semiconductor
devices, including both silicon wafer and metal interconnect
layers, and (2) silicon consumption (i.e., the area of
semiconductors produced) for each kind of device. The
product of these two quantities, Total Manufactured Layer
Area (TMLA), constitutes the activity data for semiconductor
manufacturing. PEVM also incorporates an emission factor
that expresses emissions per unit of layer-area. Emissions are
estimated by multiplying TMLA by this emission factor.
PEVM incorporates information on the two attributes
of semiconductor devices that affect the number of layers:
(1) linewidth technology (the smallest manufactured
21A Partner refers to a participant in the U.S. EPA PFC Reduction/Climate
Partnership for the Semiconductor Industry. Through a Memorandum
of Understanding (MoU) with the EPA, Partners voluntarily report their
PFC emissions to the EPA by way of a third party which aggregates the
emissions.
22 Various versions of the PEVM exist to reflect changing industrial practices.
From 1990 to 1994 emissions estimates are from PEVM vl.O, completed
in September 1998. The emission factor used to estimate 1990 to 1994
emissions is an average of the 1995 and 1996 emissions factors, which were
derived from Partner reported data for those years.
feature size),23 and (2) product type (discrete, memory
or logic).24 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 (1C)) specific to product type (Burton and Beizaie
2001, ITRS 2007). PEVM derives historical consumption
of silicon (i.e., square inches) by linewidth technology from
published data on annual wafer starts and average wafer
size (VLSI Research, Inc. 2007).
The emission factor in PEVM is the average of four
historical emission factors, each derived by dividing the total
annual emissions reported by the Partners for each of the four
years between 1996 and 1999 by the total TMLA estimated
for the Partners in each of those years. Over this period,
the emission factors varied relatively little (i.e., the relative
standard deviation for the average was 5 percent). Since
Partners are believed not to have applied significant emission
reduction measures before 2000, the resulting average
emission factor reflects uncontrolled emissions. The emission
factor is used to estimate world uncontrolled emissions using
publicly available data on world silicon consumption.
1995 through 1999
For 1995 through 1999, total U.S. emissions were
extrapolated from the total annual emissions reported by the
Partners (1995 through 1999). Partner-reported emissions are
considered more representative (e.g., in terms of capacity
utilization in a given year) than PEVM estimated emissions,
and are used to generate total U.S. emissions when applicable.
The emissions reported by the Partners were divided by the
ratio of the total capacity of the plants operated by the
23 By decreasing features of 1C 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 require 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 2007).
24 Memory devices manufactured with the same feature sizes as
microprocessors (a logic device) require approximately one-half the number
of interconnect layers, whereas discrete devices require only a silicon base
layer and no interconnect layers (ITRS 2007). Since discrete devices did
not start using PFCs appreciably until 2004, they are only accounted for in
the PEVM emissions estimates from 2004 onwards.
Industrial Processes 4-65
-------
Partners and the total capacity of all of the semiconductor
plants in the United States; this ratio represents the share
of capacity attributable to the Partnership. This method
assumes that Partners and non-Partners have identical
capacity utilizations and distributions of manufacturing
technologies. Plant capacity data is contained in the World
Fab Forecast (WFF) database and its predecessors, which is
updated quarterly (Semiconductor Equipment and Materials
Industry 2007).
2000 through 2006
The emission estimate for the years 2000 through
2006 —the period during which Partners began the
consequential application of PFC-reduction measures—was
estimated using a combination of Partner-reported emissions
and PEVM modeled emissions. The emissions reported
by Partners 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,
were estimated using PEVM and the method described
above. This is because 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. emissions figure by the
non-Partner share of U. S. total silicon capacity for each
year as described above.25 26 Annual updates to PEVM
reflect published figures for actual silicon consumption from
VLSI Research, Inc., revisions and additions to the world
population of semiconductor manufacturing plants, and
changes in 1C fabrication practices within the semiconductor
25 This approach assumes that the distribution of linewidth technologies is the
same between Partners and non-Partners. As discussed in the description of
the method used to estimate 2007 emissions, this is not always the case.
26 Generally 5 percent or less of the fields needed to estimate TMLA shares
are missing values in the World Fab Watch databases. In the 2007 World
Fab Watch database used to generate the 2006 non-Partner TMLA capacity
share, these missing values were replaced with the corresponding mean
TMLA across fabs manufacturing similar classes of products. However,
the impact of replacing missing values on the non-Partner TMLA capacity
share was inconsequential.
industry (see, ITRS, 2007 and Semiconductor Equipment
and Materials Industry 2008).27<28<29
2007
For the year 2007, emissions were also estimated using
a combination of Partner reported emissions and PEVM
modeled emissions; however, two improvements were
made to the estimation method employed for the previous
years in the time series. First, the 2007 emission estimates
account for the fact that Partners and non-Partners employ
different distributions of manufacturing technologies, with
the Partners using manufacturing technologies with greater
transistor densities and therefore greater numbers of layers.
Had the method used to estimate the 2000 through 2006
emissions (described above) been employed, the emissions
estimated for 2007 would have been 1.5 percent higher
27 Special attention was given to the manufacturing capacity of plants that
use wafers with 300 mm diameters because the actual capacity of these
plants is ramped up to design capacity, typically over a 2-3 year period. 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
approximately 70 percent of the design capacity. For 2005, actual installed
capacities were estimated using an entry in the World Fab Watch database
(April 2006 Edition) called "wafers/month, 8-inch equivalent," which
denoted the actual installed capacity instead of the fully-ramped capacity.
For 2006, actual installed capacities of new fabs were estimated using an
average monthly ramp rate of 1100 wafer starts per month (wspm) derived
from various sources such as semiconductor fabtech, industry analysts,
and articles in the trade press. The monthly ramp rate was applied from
the first-quarter of silicon volume (FQSV) to determine the average design
capacity over the 2006 period.
28 In 2006, the industry trend in co-ownership of manufacturing facilities
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. manufacturing capacity.
29Two versions of PEVM are used to model non-Partner emissions during
this period. For the years 2000 to 2003 PEVM v3.2.0506.0507 was used to
estimate non-Partner emissions. During this time, discrete devices did not
use PFCs during manufacturing and therefore only memory and logic devices
were modeled in the PEVM v3.2.0506.0507. From 2004 onwards, discrete
device fabrication started to use PFCs, hence PEVM v4.0.0701.0701, the
first version of PEVM to account for PFC emissions from discrete devices,
was used to estimate non-Partner emissions for this time period.
4-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
because the estimate of uncontrolled non-Partner emissions
would have been overstated by 2.5 percent.30
Second, the scope of the 2007 estimate is expanded
relative to the estimates for the years 2000 through 2006 to
include emissions from Research and Development fabs.
This was feasible through the use of more detailed data
published in the World Fab Forecast. PEVM databases are
updated annually as described above. The published world
average capacity utilization for 2007 was used for production
fabs while for R&D fabs, a 20 percent figure was assumed.
Inclusion of R&D fabs increased the estimated emissions
by less than 1 percent.
Gas-Specific Emissions
Two different approaches were also used to estimate
the distribution of emissions of specific fluorinated gases.
Before 1999, when there was no consequential adoption
of fluorinated-gas-reducing measures, a fixed distribution
of fluorinated-gas-use was assumed to apply to the entire
U.S. industry. This distribution was based upon the average
fluorinated-gas purchases by semiconductor manufacturers
during this period and the application of IPCC default emission
factors for each gas (Burton andBeizaie 2001). For the 2000
through 2007 period, the 1990 through 1999 distribution was
assumed to apply to the non-Partners. Partners, however,
began reporting gas-specific emissions during this period.
Thus, gas-specific emissions for 2000 through 2007 were
estimated by adding the emissions reported by the Partners
to those estimated for the non-Partners.
Data Sources
Partners estimate their emissions using a range of
methods. For 2007, it is assumed that most Partners
used a method at least as accurate as the IPCC's Tier 2a
Methodology, recommended in the IPCC Guidelines for
National Greenhouse Inventories (2006). The Partners with
relatively high emissions use leading-edge manufacturing
technology, the newest process equipment. When purchased,
30 EPA considered applying this change to years before 2007, but found
that it would be difficult due to the large amount of data (i.e., technology-
specific global and non-Partner TMLA) that would have to be examined
and manipulated for each year. This effort did not appear to be justified
given the relatively small impact of the improvement on the total estimate
for 2007 and the fact that the impact of the improvement would likely be
lower for earlier years because the estimated share of emissions accounted
for by non-Partners is growing as Partners continue to implement emission-
reduction efforts.
this equipment is supplied with fluorinated-gas emission
factors, measured using industry standard guidelines
(International Sematech 2006). The larger emitting Partners
likely use these process-specific emission factors instead of
the somewhat less representative default emission factors
provided in the IPCC guidelines. Data used to develop
emission estimates are attributed in part to estimates provided
by the members of the Partnership, and in part from data
obtained from PEVM estimates. Estimates of operating
plant capacities and characteristics for Partners and non-
Partners were derived from the Semiconductor Equipment
and Materials Industry (SEMI) World Fab Forecast (formerly
World Fab Watch) database (1996 through 2008). Estimates
of world average capacity utilizations for 2007 were obtained
from Semiconductor International Capacity Statistics
(SICAS). Estimates of silicon consumed by linewidth
from 1990 through 2007 were derived from information
from VLSI Research (2008), and the number of layers per
linewidth was obtained from International Technology
Roadmap for Semiconductors: 2006 Update (Burton and
Beizaie 2001, ITRS 2007, ITRS 2008).
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:
U.S. emissions = ^Partnership gas-specific submittals +
[(non-Partner share of world TMLA) x
(PEVM emission factor x world TMLA)]
The Monte Carlo analysis results presented below relied
on estimates of uncertainty attributed to the four quantities
on the right side of the equation. Estimates of uncertainty
for the four quantities were in turn developed using the
estimated uncertainties associated with the individual inputs
to each quantity, error propagation analysis, Monte Carlo
simulation and expert judgment. The relative uncertainty
associated with World TMLA estimate in 2007 is +9
percent, based on the uncertainty estimate obtained from
discussions with VLSI, Inc. For the share of World layer-
weighted silicon capacity accounted for by non-Partners,
a relative uncertainty of +8 percent was estimated based
Industrial Processes 4-67
-------
on a separate Monte Carlo simulation to account for the
random occurrence of missing data in the World Fab Watch
database. For the aggregate PFC emissions data supplied
to the partnership, a relative uncertainty of +50 percent
was estimated for each gas-specific PFC emissions value
reported by an individual Partner, and error propagation
techniques were used to estimate uncertainty for total
Partnership gas-specific submittals.31 A relative error of
approximately 10 percent was estimated for the PEVM
emission factor, based on the standard deviation of the 1996
to 1999 emission factors.32 All estimates of uncertainties
are given at 95-percent confidence intervals.
In developing estimates of uncertainty, consideration
was also given to the nature and magnitude of the potential
bias that World activity data (i.e., World TMLA) 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 U.S. TMLA overstates the
average number of layers across all product categories and
all manufacturing technologies for 2004 by 0.12 layers or 2.9
percent. The same upward bias is assumed for World TMLA,
and is represented in the uncertainty analysis by deducting the
absolute bias value from the World activity estimate when it
is incorporated into the Monte Carlo analysis.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-92. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing
were estimated to be between 4.7 and 5.7 Tg CO2 Eq. at a
95 percent confidence level. This range represents 9 percent
below to 9 percent above the 2007 emission estimate of
5.2 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
With the exception of possible future updates to emission
factors, the method to estimate non-Partner related emissions
(i.e., PEVM) is not expected to change. 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)
and improvements in estimates of non-Partner totals. 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.
Another point of consideration for future national
emissions estimates is the inclusion of PFC emissions from
heat transfer fluid (HTF) loss to the atmosphere and the
production of photovoltaic cells (PVs). Heat transfer fluids,
of which some are liquid perfluorinated compounds, are used
during testing of semiconductor devices and, increasingly, are
used to manage heat during the manufacture of semiconductor
devices. Evaporation of these fluids is a source of emissions
(EPA 2006). PFCs are also used during manufacture of PV
cells that use silicon technology, specifically, crystalline,
polycrystalline and amorphous silicon technologies. PV
Table 4-92: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)a
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Semiconductor
Manufacture
HFC, PFC,
and SF6
5.2
Lower Bound0
4.7
Upper Bound0
5.7
Lower Bound
-9%
Upper Bound
+ 9%
'Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match that shown in Table 4-90.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
c Absolute lower and upper bounds were calculated using the corresponding lower and upper bounds in percentages.
31 Error propagation resulted in Partnership gas-specific uncertainties ranging
from 18 to 36 percent.
32The average of 1996 to 1999 emission factor is used to derive the PEVM
emission factor.
4-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
manufacture is growing in the United States, and therefore
may be expected to constitute a growing share of U.S. PFC
emissions from the electronics sector.
4.22. Electrical Transmission
and 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 switchgear through seals, especially from
older equipment. The gas can also be released during
equipment manufacturing, installation, servicing, and
disposal. Emissions of SF6 from equipment manufacturing
and from electrical transmission and distribution systems
were estimated to be 12.7 Tg CO2 Eq. (0.5 Gg) in 2007. This
quantity represents a 53 percent decrease from the estimate
for 1990 (see Table 4-93 and Table 4-94). This decrease is
Table 4-93: SF6 Emissions from Electric Power Systems
and Electrical Equipment Manufacturers (Tg C02 Eq.)
Year
Electric Power
Systems
Electrical Equipment
Manufacturers Total
2005
2006
2007
13.2
12.4
12.0
0.8
0.8
0.7
14.0
13.2
12.7
Table 4-94: SF6 Emissions from Electric Power Systems
and Electrical Equipment Manufacturers (Gg)
Year
Emissions
1990
1.1
2005
2006
2007
believed to have two causes: a sharp increase in the price
of SF6 during the 1990s and a growing awareness of the
environmental impact of SF6 emissions through programs
such as 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 through 2007 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to
2007 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) the relationship between emissions and
utilities' transmission miles as reported in the 2001, 2004
and 2007 Utility Data Institute (UDI) Directories of Electric
Power Producers and Distributors (UDI 2001, 2004, 2007).
(Transmission miles are defined as the miles of lines carrying
voltages above 34.5 kV.) Over the period from 1999 to 2007,
partner utilities, which for inventory purposes are defined as
utilities that either currently are or previously have been part
of the Partnership, represented between 42 percent and 47
percent of total U.S. transmission miles. For each year, the
emissions reported by or estimated for partner utilities were
Industrial Processes 4-69
-------
added to the emissions estimated for utilities that have never
participated in the Partnership (i.e., non-partners).33
Partner utilities estimated their emissions using a Tier
3 utility-level mass balance approach (IPCC 2006). If a
partner utility did not provide data for a particular year,
emissions were interpolated between years for which data
were available or extrapolated based on partner-specific
transmission mile growth rates. In 2007, non-reporting
partners accounted for approximately 8 percent of the total
emissions attributed to partner utilities.
Emissions from non-partners in every year since 1999
were estimated using the results of a regression analysis
that showed that the emissions from 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 43
partner utilities (representing approximately 24 percent of
U.S. transmission miles), and 2000 transmission mileage
data obtained from the 2001UDI Directory of Electric Power
Producers and Distributors (UDI 2001). Two equations
were developed, one for small and one for large utilities
(i.e., with fewer 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
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 transmission
miles, in kilograms):
Emissions (kg) = 0.89 x Transmission Miles
Non-Partner large utilities (more than 10,000 transmission
miles, in kilograms):
Emissions (kg) = 0.58 x Transmission Miles
Data on transmission miles for each non-partner utility
for the years 2000, 2003, and 2006 were obtained from the
2001, 2004, and 2007 UDI Directories of Electric Power
Producers and Distributors, respectively (UDI 2001, 2004,
2007). The U.S. transmission system grew by over 22,000
miles between 2000 and 2003 and by over 55,000 miles
between 2003 and 2006. These periodic increases are assumed
to have occurred gradually, therefore transmission mileage
was assumed to increase at an annual rate of 1.2 percent
between 2000 and 2003 and 2.8 percent between 2003 and
2006. Transmission miles in 2007 were then extrapolated
from 2006 based on the 2.8 percent growth rate.
As a final step, total emissions were determined for
each year by summing the partner reported and estimated
emissions (reported data was available through the EPA's SF6
Emission Reduction Partnership for Electric Power Systems),
and the non-partner emissions (determined using the 1999
regression equations).
1990 through 1998 Emissions from Electric Power Systems
Because most participating utilities reported emissions
only for 1999 through 2007, modeling was used to estimate
SF6 emissions from electric power systems for the years 1990
through 1998. To perform this modeling, U.S. emissions were
assumed to follow the same trajectory as global34 emissions
from this source during the 1990 to 1999 period. To estimate
global emissions, the PsAND survey of global SF6 sales were
used, together with the following equation for estimating
emissions, 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.)
33 Partners in EPA's SF6 Emission Reduction Partnership reduced their
emissions by approximately 54% from 1999 to 2007.
34Ideally sales to utilities in the U.S. between 1990 and 1999 would be
used as a model. However, this information was not available. There are
only two U.S. manufacturers of SF6, so sensitive sales information is not
concealed by aggregation.
4-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Emissions (kilograms SF6) = SF6 purchased to refill
existing equipment (kilograms) + SF6 nameplate capacity35
of retiring 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.
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 of 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 1999.
U.S. emissions between 1990 and 1999 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 15.1 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
35 Nameplate capacity is defined as the amount of SF6 within fully charged
electrical equipment.
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 the
PvAND sales trends and actual global emissions is the level
of imports from and exports to Russia and China. Sulfur
hexafluoride production in these countries is not included
in the RAND survey and is not accounted for in any other
manner by RAND. However, atmospheric studies confirm
that the downward trend in estimated global emissions
between 1995 and 1998 was real (see the Uncertainty
discussion below).
1990 through 2007 Emissions from Manufacture of
Electrical Equipment
The 1990 to 2007 emission estimates for original
equipment manufacturers (OEMs) were derived by assuming
that manufacturing emissions equal 10 percent of the quantity
of SF6 provided with new equipment. The quantity of SF6
provided with 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 provided with new equipment
for 2001 to 2007 were estimated using partner-reported data
and the total industry SF6 nameplate capacity estimate (131.8
Tg CO2 Eq. in 2007). Specifically, the ratio of new nameplate
capacity to total nameplate capacity of a subset of partners
for which new nameplate capacity data was available from
1999 to 2007 was calculated. This ratio was then multiplied
by the total industry nameplate capacity estimate to derive
the amount of SF6 provided with new equipment for the
entire industry. 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'Connelletal. 2002).
Uncertainty
To estimate the uncertainty associated with emissions of
SF6 from electric transmission and distribution, uncertainties
associated with three quantities were estimated: (1) emissions
Industrial Processes 4-71
-------
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
3.6 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 2007
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 58 percent of U.S. transmission
miles in 2007) 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 supplied with equipment by equipment manufacturers,
which is projected from partner provided nameplate capacity
data and industry SF6 nameplate capacity estimates, and the
manufacturers' SF6 emissions rate.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-95. Electrical Transmission and
Distribution SF6 emissions were estimated to be between 10.0
and 15.5 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 21 percent below and 22
percent above the emission estimate of 12.7 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
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.
Several pieces of evidence indicate that U.S. SF6
emissions were reduced as global emissions were reduced.
First, the decreases in sales and emissions coincided with a
sharp increase in the price of SF6 that occurred in the mid-
1990s and that affected the United States as well as the rest of
the world. A representative from Dilo, a major manufacturer
of SF6 recycling equipment, stated that most U.S. utilities
began recycling rather than venting SF6 within two years of
the price rise. Finally, the emissions reported by the one U.S.
utility that reported 1990 through 1999 emissions to EPA
showed a downward trend beginning in the mid-1990s.
Recalculations Discussion
Sulfur hexafluoride emission estimates for the period
1990 through 2006 were updated based on (1) new data from
EPA's SF6 Emission Reduction Partnership; (2) revisions
to interpolated and extrapolated non-reported partner data;
and (3) a revised regression equation coefficient for non-
partner small utilities (fewer than 10,000 transmission
miles). The new regression coefficient resulted from a
revised 1999 emission estimate from a Partner of EPA's SF6
Emission Reduction Partnership. This new emission estimate
changed the regression coefficient from 0.88 to 0.89. Based
on the revisions listed above, SF6 emissions from electric
transmission and distribution increased 1 percent or less for
each year from 1990 through 2006.
Table 4-95: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Electrical Transmission
and Distribution SFfi
12.7
10.0
15.5
-21%
+22%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Box 4-1: Potential Emission Estimates of MFCs, PFCs, and SF6
Emissions of MFCs, PFCs and SF6 from industrial processes can be estimated in two ways, either as potential emissions or as actual
emissions. Emission estimates in this chapter are "actual emissions," which are defined by the Revised 1996IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) as estimates that take into account the time lag between consumption and
emissions. In contrast, "potential emissions" are defined to be equal to the amount of a chemical consumed in a country, minus the amount
of a chemical recovered for destruction or export in the year of consideration. Potential emissions will generally be greater for a given year
than actual emissions, since some amount of chemical consumed will be stored in products or equipment and will not be emitted to the
atmosphere until a later date, if ever. Although actual emissions are considered to be the more accurate estimation approach for a single
year, estimates of potential emissions are provided for informational purposes.
Separate estimates of potential emissions were not made for industrial processes that fall into the following categories:
• Byproduct emissions. Some emissions do not result from the consumption or use of a chemical, but are the unintended byproducts
of another process. For such emissions, which include emissions of CF4 and C2F6 from aluminum production and of HFC-23 from
HCFC-22 production, the distinction between potential and actual emissions is not relevant.
• Potential emissions that equal actual emissions. For some sources, such as magnesium production and processing, no delay
between consumption and emission is assumed and, consequently, no destruction of the chemical takes place. In this case, actual
emissions equal potential emissions.
Table 4-96 presents potential emission estimates for MFCs and PFCs from the substitution of ozone depleting substances, MFCs, PFCs,
and SF6 from semiconductor manufacture, and SF6 from magnesium production and processing and electrical transmission and distribution.36
Potential emissions associated with the substitution for ozone depleting substances were calculated using the EPA's Vintaging Model.
Estimates of MFCs, PFCs, and SF6 consumed by semiconductor manufacture were developed by dividing chemical-by-chemical emissions
by the appropriate chemical-specific emission factors from the IPCC Good Practice Guidance (Tier 2c). Estimates of CF4 consumption were
adjusted to account for the conversion of other chemicals into CF4 during the semiconductor manufacturing process, again using the default
factors from the IPCC Good Practice Guidance. Potential SF6 emissions estimates for electrical transmission and distribution were developed
using U.S. utility purchases of SF6 for electrical equipment. From 1999 through 2007, estimates were obtained from reports submitted by
participants in EPA's SF6 Emission Reduction Partnership for Electric Power Systems. U.S. utility purchases of SF6 for electrical equipment
from 1990 through 1998 were backcasted based on world sales of SF6 to utilities. Purchases of SF6 by utilities were added to SF6 purchases
by electrical equipment manufacturers to obtain total SF6 purchases by the electrical equipment sector.
Table 4-96:2007 Potential and Actual Emissions of MFCs, PFCs, and SF6
from Selected Sources (Tg C02 Eq.)
Source
Substitution of Ozone Depleting Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Magnesium Production and Processing
Electrical Transmission and Distribution
Potential
185.5
-
-
7.6
3.0
20.9
Actual
108.3
3.8
17.0
4.7
3.0
12.7
-Not applicable.
36 See Annex 5 for a discussion of sources of SF6 emissions excluded from the actual emissions estimates in this report.
Industrial Processes 4-73
-------
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 2007 are reported in Table 4-97.
Methodology
These emission estimates were obtained from preliminary
data (EPA 2008), 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.
Table 4-97: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
NOX 591 607 626 534 527 520
Other Industrial Processes 3431 3621 435 389 382 375
Chemical & Allied Product Manufacturing 1521 14sl 951 64 64 64
Metals Processing 881 891 811 63 63 63
Storage and Transport 3 5 14 17 17 17
CO 4,125 3,959 2,216 1,744 1,743 1,743
Metals Processing 2,395 2,159 1,175 895 895 894
Other Industrial Processes 4871 5661 5371 445 444 444
Chemical & Allied Product Manufacturing 1,073 1,110 3271 258 258 258
Storage and Transport 691 231 1531 107 107 107
Miscellaneous3 101 1021 231 39 40 40
NMVOCs 2,422 2,642 1,773 2035 1950 1878
Storage and Transport 1,352 1,499 1,067 1346 1280 1228
Other Industrial Processes 3641 408 4121 401 388 376
Chemical & Allied Product Manufacturing 5751 5991 2301 226 221 216
Metals Processing 111 1131 611 42 42 42
Miscellaneous3 201 231 3 20 19 17
'Miscellaneous includes the following categories: catastrophic/accidental release, other combustion
It does not include agricultural fires or slash/prescribed burning, which are accounted for under the
Note: Totals may not sum due to independent rounding.
, health services, cooling towers, and fugitive dust.
Field Burning of Agricultural Residues source.
4-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 2007 (see Table 5-1). Indirect greenhouse gas emissions also result from solvent and other product use,
and are presented in Table 5-5 in gigagrams (Gg).
Table 5-1: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg)
Gas/Source
N20 from Product Uses
Tg C02 Eq.
eg
1990
4.4l
u|
1995
4.6 1
15
2000
4.9 1
ie|
2005
4.4
14
2006
4.4
14
2007
4.4
14
5.1. Nitrous Oxide from Product Uses (IPCC Source Category 3D)
N2O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. Two companies operate a total of five N2O
production facilities in the United States (Airgas 2007; FTC 2001). 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;
• 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 2007 was approximately 15 Gg (Table 5-2). N2O emissions were 4.4 Tg CO2 Eq. (14 Gg) in
2007 (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).
Solvent and Other Product Use 5-1
-------
Table 5-2: N20 Production (Gg)
Year
Gg
2005
2006
2007
Table 5-3: N20 Emissions from N20 Product Usage
(Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
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 emission 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:
N2O Product Usage Emissions =
2, [Total U.S. Production of N2O] x
[Share of Total Quantity of N2O Usage by Sector i] x
[Emissions Rate for Sector i],
where,
i = sector.
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 2007, 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 (Heydorn 1997).
The N2O was allocated across the following categories:
medical applications, food processing propellant, and sodium
azide production (pre-1996). A usage emissions rate was
then applied for each sector to estimate the amount of N2O
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, none of the N2O is assumed to be metabolized
during anesthesia and quickly leaves the body in exhaled
breath. Therefore, an emission factor of 100 percent was
used for this subcategory (IPCC 2006). 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 emission factor
of 100 percent for this subcategory (IPCC 2006). For the
remaining subcategories, all of the N2O is consumed/reacted
during the process, and therefore the emission rate was
considered to be zero percent (Tupman 2002).
The 1990 through 1992 N2O production data were
obtained from SRI Consulting's Nitrous Oxide, North
America report (Heydorn 1997). N2O production data for
1993 through 1995 were not available. Production data for
1996 was specified as a range in two data sources (Heydorn
1997, Tupman 2002). In particular, for 1996, Heydorn (1997)
estimates N2O production to range between 13.6 and 18.1
thousand metric tons. Tupman (2003) provided a narrower
range (i.e., 15.9 to 18.1 thousand metric tons) for 1996 that
falls within the production bounds described by Heydorn
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From N20 Product Usage
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
N20 Product Usage
N,0
4.4
4.3
4.5
-2%
+ 2%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
(1997). Tupman (2003) data are considered more industry-
specific and current. Therefore, the midpoint of the narrower
production range 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, 2005, 2006, and 2007 were held at the 2003 value.
The 1996 share of the total quantity of N2O used by
each subcategory was obtained from SRI Consul ting'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, 2005, 2006, and 2007 was assumed to equal
the 2003 value. The emissions rate for the food processing
propellant industry was obtained from SRI Consul ting's
Nitrous Oxide, North America report (Heydorn 1997), and
confirmed by a N2O 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
obtained from the 2006IPCC Guidelines.
Uncertainty
The overall uncertainty associated with the 2007 N2O
emission estimate from N2O product usage was calculated
using the IPCC Guidelines for National Greenhouse
Gas Inventories (2006) 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 5-4. N2O emissions from
N2O product usage were estimated to be between 4.3 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 2 percent below to 2 percent above
the 2007 emissions estimate of 4.4 Tg CO2 Eq.
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, and investigation
of production and use cycles and the potential need to
incorporate a time lag between production and ultimate
product use and resulting release of N2O. Additionally,
planned improvements include considering imports and
exports of N2O for product uses.
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
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.
Solvent and Other Product Use 5-3
-------
most processes employing organic or petroleum based
solvents. As some industrial applications also employ
thermal incineration as a control technology, combustion
byproducts, 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 2007 are reported in Table 5-5.
Table 5-5: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg)
Activity
1990
1995
2000
2005
2006
2007
NO,
Surface Coating
Graphic Arts
Degreasing
Dry Cleaning
Other Industrial Processes3
Non-Industrial Processes"
Other
CO
Surface Coating
Other Industrial Processes3
Dry Cleaning
Degreasing
Graphic Arts
Non-Industrial Processes"
Other
NMVOCs
Surface Coating
Non-Industrial Processes"
Degreasing
Dry Cleaning
Graphic Arts
Other Industrial Processes3
Other
j
NA
j
NA
5,216
2,289
1,724
675
195
249
85
3
I
NA
5,609
2,432
1,858
716
209
307
87
3
I
I
4,384
1,766
1,676
316
265
222
98
40
3,881
1,590
1,457
283
232
195
88
36
3,867
1,584
1,452
282
231
194
88
36
3,855
1,579
1,447
281
230
194
88
36
+ Does not exceed 0.5 Gg.
'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.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 solvent-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 2009), 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.
Solvent and Other Product Use 5-5
-------
6. Agriculture
Figure 6-1
2007 Agriculture Chapter Greenhouse Gas
Emission Sources
207.9
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. Carbon dioxide
emissions from on-farm energy use are accounted for in the
Energy chapter.
In 2007, the Agricultural sector was responsible for
emissions of 413.1 teragrams of CO2 equivalents (Tg CO2
Eq.), or 6 percent of total U.S. greenhouse gas emissions.
Methane (CFL,) and nitrous oxide (N2O) were the primary
greenhouse gases emitted by agricultural activities. Methane
emissions from enteric fermentation and manure management
represent about 24 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 CK4. Rice cultivation and field burning of
agricultural residues were minor sources of CH4. Agricultural
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
Agriculture
as a Portion of
all Emissions
50
100
Tg CO, Eq.
150
Table 6-1: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural Residues
Total
402.0
399.4
185.5
136.0
41.8
6.8
0.9
225.5
210.6
14.2
0.5
410.8
186.8
138.2
41.9
5.9
0.8
223.5
208.4
14.6
0.5
410.3
190.0
139.0
44.0
6.2
0.9
223.1
207.9
14.7
0.5
413.1
Note: Totals may not sum due to independent rounding.
Agriculture 6-1
-------
Table 6-2: Emissions from Agriculture (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural Residues
8,833
6,474
1,991
326
41
727
679
46
2
8,894
6,580
1,993
282
39
721
672
47
2
9,047
6,618
2,093
293
42
720
671
47
2
Note: Totals may not sum due to independent rounding.
soil management activities such as fertilizer application and
other cropping practices were the largest source of U. S. N2O
emissions, accounting for 67 percent. Manure management
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 2007, CH4
emissions from agricultural activities increased by 11 percent,
while N2O emissions fluctuated from year to year, but overall
increased by 5 percent.
6.1. Enteric Fermentation (IPCC
Source Category 4A)
Methane 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 CK4 as a byproduct, which
can be exhaled or eructated by the animal. The amount of
CtLj produced and emitted 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 CK4 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 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 and/or higher feed intake leads
to higher CH4 emissions. Feed intake is positively correlated
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
(e.g., animals in feedlots or grazing on pasture).
Methane emission estimates from enteric fermentation
are provided in Table 6-3 and Table 6-4. Total livestock
CH4 emissions in 2007 were 139.0 Tg CO2 Eq. (6,618 Gg).
Beef cattle remain the largest contributor of CH4 emissions
from enteric fermentation, accounting for 72 percent in
2007. Emissions from dairy cattle in 2007 accounted for
23 percent, and the remaining emissions were from horses,
sheep, swine, and goats.
From 1990 to 2007, emissions from enteric fermentation
have increased by 4.3 percent. Generally, emissions
decreased from 1995 to 2004, though with slight increases
in 2002 and 2003. This trend was mainly due to decreasing
populations of both beef and dairy cattle and increased
digestibility of feed for feedlot cattle. Emissions have
increased from 2004 through 2007, as both dairy and
beef populations have undergone increases. During the
timeframe of this analysis, populations of sheep have
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eq.)
1995
Livestock Type
1990
2005
2006
2007
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
94.6
32.8
1.9
1.9
1.7
0.3
106.7
Total
133.2
143.6
136.0
100.0
31.4
3.5
1.0
1.9
0.3
138.2
100.2
31.9
3.5
1.0
2.0
0.3
139.0
Note: Totals may not sum due to independent rounding.
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg)
Livestock Type
1990
1995
2000
2005
2006
2007
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
4,762
1,497
166
50
93
13
6,474 6,580
4,772
1,521
166
49
98
13
6,618
Note: Totals may not sum due to independent rounding.
decreased 46 percent since 1990 while horse populations
have increased over 80 percent, mostly since 1999. Goat and
swine populations have increased 1 percent and 21 percent,
respectively, during this timeframe.
Methodology
Livestock emission estimate methodologies 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., 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 provides the necessary data to
estimate cattle emissions using the IPCC Tier 2 approach.
The Cattle Enteric Fermentation Model (CEFM), developed
by EPA and used to estimate cattle CH4 emissions from
enteric fermentation, incorporates this information and other
analyses of livestock population, feeding practices, and
production characteristics.
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 create a transition matrix that models cohorts of
Agriculture 6-3
-------
individual animal types and their specific emission 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 (USDA) National Agricultural Statistics
Service Quick Stats database (USDA 2008).
Diet characteristics were estimated by region for U.S.
dairy, beef, and feedlot cattle. These estimates were used to
calculate Digestible Energy (DE) values (expressed as the
percent of gross energy intake digested by the animal) and
CELj conversion rates (Ym) (expressed as the fraction of gross
energy converted to CK4) for each population category. The
IPCC recommends Ym values of 3.0+1.0 percent for feedlot
cattle and 6.5+1.0 percent for other well-fed cattle consuming
temperate-climate feed types (IPCC 2006). 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). Values from
EPA (1993) were used for dairy replacement heifers. For
feedlot animals, DE and Ym values recommended by Johnson
(1999) were used. For grazing beef cattle, DE values were
based on diet information in NRC (2000) and Ym values were
based on Johnson (2002). Weight and weight gains for cattle
were estimated from Enns (2008), Patton et al. (2008), Lippke
et al. (2000), Pinchack et al., (2004), Platter et al. (2003),
Skogerboe et al. (2000), and expert opinion. See Annex 3.9
for more details on the method used to characterize cattle
diets and weights in the United States.
To estimate CH4 emissions from all cattle types except
bulls and calves younger than 7 months,1 the population
was divided into state, age, sub-type (i.e., dairy cows and
replacements, beef cows and replacements, heifer and steer
stackers, and heifer and steer in feedlots), and production
(i.e., pregnant, lactating) groupings to more fully capture
differences in CH4 emissions from these animal types. The
transition matrix was used to simulate the age and weight
structure of each sub-type on a monthly basis, to more
accurately reflect the fluctuations that occur throughout the
year. Cattle diet characteristics were then used in conjunction
with Tier 2 equations from IPCC (2006) to produce CFLj
emission factors for the following cattle types: dairy
cows, beef cows, dairy replacements, beef replacements,
steer stackers, heifer stackers, steer feedlot animals, and
heifer feedlot animals. To estimate emissions from cattle,
population data from the transition matrix were multiplied
by the calculated 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. Methane emissions from these animals
accounted for a minor portion of total CH4 emissions from
livestock in the United States from 1990 through 2007. 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 2008). Horse population data were
obtained from the FAOSTAT database (FAO 2008), because
USDA does not estimate U.S. horse populations annually.
Goat population data were obtained for 1992,1997, and 2002
(USDA 2008); these data were interpolated and extrapolated
to derive estimates for the other years. Methane emissions
1 Emissions from bulls are estimated using a Tier 1 approach because it is
assumed there is minimal variation in population and diets; because calves
younger than 7 months consume mainly milk and the IPCC recommends the
use of methane conversion factor of zero for all juveniles consuming only
milk, this results in no methane emissions from this subcategory of cattle.
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
from sheep, goats, swine, and horses were estimated by
using emission factors utilized in Crutzen et al. (1986, cited
in IPCC 2006). 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 (2006).
See Annex 3.9 for more detailed information on the
methodology and data used to calculate CH4 emissions from
enteric fermentation.
Uncertainty
Quantitative uncertainty analysis for 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 uncertainty estimates were developed for the 1990
through 2001 Inventory report. No significant changes
occurred in the method of data collection, data estimation
methodology, or other factors that influence the uncertainty
ranges around the 2007 activity data and emission factor
input variables used in the current submission. Consequently,
these uncertainty estimates were directly applied to the 2007
emission estimates.
A total of 185 primary input variables (177 for cattle
and 8 for non-cattle) were identified as key input variables
for the uncertainty analysis. A 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) to
capture the fact that these variables cannot be negative. For
some key input variables, the uncertainty ranges around their
estimates (used for inventory estimation) were collected
from published documents and other public sources; others
were based on expert opinion and our best estimates. 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 through expert judgment.
The uncertainty ranges associated with the activity data-
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 123.7 to 164.0
Tg CO2 Eq., calculated as 11 percent below and 18 percent
above the actual 2007 emission estimate of 139.0 Tg CO2 Eq.
Among the individual cattle 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. Among non-cattle, horses account for the largest
degree of uncertainty in the inventory emission estimates
because there is a higher degree of uncertainty among the
FAO population estimates used for horses than for the USDA
population estimates used for swine, goats, and sheep.
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
Table 6-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3'b
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Enteric Fermentation
CH4
139.0
123.7
164.0
-11%
+ 18%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b Note that the relative uncertainty range was estimated with respect to the 2001 emission estimates submitted in 2003 and applied to the 2007 estimates.
Agriculture 6-5
-------
emission estimates. As described below, particular emphasis
this year was placed on revising CEFM weight assumptions
and modifications of the stacker population estimates in the
transition matrix, which required further QA/QC to ensure
consistency of estimates generated by the updated model.
Recalculations Discussion
There were several modifications to the estimates
relative to the previous Inventory that had an effect on
emission estimates, including the following:
• During the QA/QC process, it was noted that a portion
of the steer and heifer populations that were held aside
(e.g., not eligible to be placed in feedlots) to establish
the stacker population for the following January were
inadvertently left out of the emissions calculations. These
heifer and steer stacker populations are now included.
• An additional adjustment was made to the CEFM to
allow feedlot placements for the 700-800 Ibs category
to use excess animals from the over 800 Ibs category
if insufficient animals are available to place in a
given month at 700-800 Ibs. This process reduced the
discrepancy in the model between actual placement
numbers by weight category from USDA and available
animals within the transition matrix.
• Calf weight at 7 months was adjusted to be equal for
all months, as current research indicated that evidence
was not sufficient to suggest that calf weight at weaning
differs by birth month.
• Mature weight for beef cows was revised based on
annual data collected from 1989 through 2007, as was
replacement weight at 15 and 24 months.
• Mature weight for dairy cows was adjusted to 1,550 for
all years, and replacement weight at 15 and 24 months
was adjusted accordingly.
• Monthly weight gain for stackers was increased to 1.83
Ibs per day starting in 2000, and a linear function was
used to determine adjustments from previous estimates
between 1989 and 2000.
• Bulls were added to the CEFM calculations for the first
time, as previously they had been calculated separately;
however, the estimates are still carried out with the Tier 1
approach, so this change did not result in any changes
in emissions from previous years.
• The USDA published revised population estimates that
affected historical emissions estimated for swine in
2006. In addition, some historical population estimates
for certain beef and dairy populations were also updated
as a result of changes in USDA inputs.
• As a result of these changes, dairy cattle emissions
increased an average of 65 Gg (4.6 percent) per year and
beef cattle increased an average of 423 Gg (9.7 percent)
per year over the entire time series relative to the previous
Inventory. Historical emission estimates for swine in 2006
increased by less than one half of one percent as a result
of the USDA 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. Research is currently underway to
update the diet assumptions. There are a variety of models
available to predict CH4 production from cattle. Four of
these models (two mechanistic, and two empirical) are
being evaluated to determine appropriate Ym and DE values
for each cattle type and state. In addition to the model
evaluation, separate research is being conducted to update
the assumptions used for cattle diet components for each
animal type. At the conclusion of both of these updates, it
is anticipated that a peer-reviewed article will be published
and will serve as the basis for future emission estimates for
enteric fermentation.
In addition to the diet characteristics research discussed
above several revisions will be investigated, including:
• Estimating bull emissions using the IPCC Tier
2 approach;
• Updating input variables that are from older data
sources, such as beef births by month and beef cow
lactation rates;
• Continue to evaluate and improve the CEFM handling
of the differences between the USDA feedlot placement
data by weight category and the number of animals that
are available for placement by weight class according
to the CEFM transition matrix;
• The possible breakout of other animal types (i.e., sheep,
swine, goats, horses) from national estimates to state-
level estimates; and
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
• Including bison in the estimates for other domesticated
animals.
These updates may result in significant changes to
some of the activity data used in generating emissions.
Additionally, since these revised inputs will be state-
specific and peer-reviewed, uncertainty ranges around these
variables will likely decrease. As a consequence, the current
uncertainty analysis will become outdated, and a revision of
the quantitative uncertainty surrounding emission estimates
from this source category will be initiated.
6.2. Manure Management (IPCC
Source Category 4B)
The management of livestock manure can produce
CH4 and N2O emissions. Methane is produced by the
anaerobic decomposition of manure. Direct N2O emissions
are produced as part of the N cycle through the nitrification
and denitrification of the organic N in livestock manure and
urine.2 Indirect N2O emissions are produced as result of the
volatilization of N as ammonia (NH3) and oxides of nitrogen
(NOX) and runoff and leaching of N during treatment, storage
and transportation.
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
drylots) 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,
2 Direct and indirect N2O 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.) and from livestock manure
and urine deposited on pasture, range, or paddock lands are accounted for
and discussed in the Agricultural Soil Management source category within
the Agriculture sector.
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 direct N2O emissions 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 direct
N2O emissions to occur, the manure must first be handled
aerobically where NH3 or organic N 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 N excreted is expected to convert
to N2O in the waste management system (WMS). Indirect
N2O emissions are produced when N is lost from the system
through volatilization (as NH3 or NOX) or through runoff
and leaching. The vast majority of volatilization losses from
these operations are NH3. Although there are also some small
losses of NOX, there are no quantified estimates available
for use, so losses due to volatilization are only based on
NH3 loss factors. Runoff losses would be expected from
operations that house animals or store manure in a manner
that results in exposure to weather. Runoff losses are also
specific to the type of animal housed on the operation due
to differences in manure characteristics. Little information
is known about leaching from manure management systems
as most research focuses on leaching from land application
systems. Since leaching losses are expected to be minimal,
leaching losses are coupled with runoff losses and the runoff/
leaching estimate does not include any leaching losses.
Estimates of CH4 emissions in 2007 were 44.0 Tg CO2
Eq. (2,093 Gg), 45 percent higher than in 1990. Emissions
increased on average by 0.8 Tg CO2 Eq. (2.5 percent)
annually over this period. The majority of this increase
was from swine and dairy cow manure, where emissions
increased 51 and 60 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
Agriculture 6-7
-------
the application of manure nutrients have shifted manure
management practices at smaller dairies from daily spread
to manure managed and stored on site. 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 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 and WMS-specific CH4 conversion factor (MCF)
values in combination with the 1992,1997, and 2002 farm-
size distribution data reported in the Census of Agriculture
(USDA 2005). Methane emissions from horses have nearly
doubled since 1990 (an 82 percent increase from 1990 to
2007); however, this is due to population increases rather
than changes in manure management practices. Overall,
horses contribute only 2 percent of CH4 emissions from
animal manure management. From 2006 to 2007, there was
a 5 percent increase in total CH4 emissions, due to minor
shifts in the animal populations and the resultant effects on
manure management system allocations.
In 2007, total N2O emissions were estimated to be 14.7
Tg CO2 Eq. (47 Gg); in 1990, emissions were 12.1 Tg CO2
Eq. (39 Gg). These values include both direct and indirect
N2O emissions from manure management. Nitrous oxide
emissions have remained fairly steady since 1990. Small
changes in N2O emissions from individual animal groups
exhibit the same trends as the animal group populations,
with the overall net effect that N2O emissions showed a 22
percent increase from 1990 to 2007 and a 1 percent increase
from 2006 through 2007.
Table 6-6 and Table 6-7 provide estimates of CH^ and N2O
emissions from manure management by animal catagory.
Methodology
The methodologies presented in IPCC (2006) form
the basis of the CH4 and N2O emission estimates for
each animal type. This section presents a summary of the
methodologies used to estimate CH4 and N2O emissions
Table 6-6: CH4 and N20 Emissions from Manure Management (Tg C02 Eq.)
Gas/Animal Type
1990
1995
2000
2005
2006
2007
CH4a
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20"
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Total
30.4
11.3
2.6
13.1
"
2.8
0.5
12.1
3.5
5.5
1.2
"
1.5
0.2
42.5
34.5
12.5
2.6
16.0
"
2.7
0.4
12.9
3.5
6.0
1.4
0.2
0.2
47.4
37.9
14.7
2.5
17.5
"
2.6
0.5
14.0
3.6
6.7
1.4
0.3
0.2
51.9
41.8
17.2
2.4
18.6
0.1
+
2.7
0.8
14.2
3.7
6.5
1.5
0.3
+
1.7
0.4
56.0
+ Less than 0.05 Tg C02 Eq.
a Includes CH4 emission reductions due to CH4 collection and combustion by anaerobic digestion utilization systems.
b Includes both direct and indirect N20 emissions.
Note: Totals may not sum due to independent rounding.
41.9
17.5
2.5
18.3
0.1
+
2.7
0.8
14.6
3.8
6.7
1.5
0.4
+
1.8
0.4
56.4
44.0
18.1
2.4
19.7
0.1
2.7
0.8
14.7
3.9
6.7
1.6
0.3
1.8
0.4
58.7
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-7: CH4 and N20 Emissions from Manure Management (Gg)
Gas/Animal Type
1990
1995
2000
2005
2006
2007
CH4a
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20"
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
1,447
538
124
624
7
1
131
22
39
11
18
4
1,642
597
125
764
128
21
42
1,804
701
118
832
126
22
45
12
22
5
1,991
820
114
887
4
1
127
39
46
12
21
5
1
+
6
1
1,993
833
119
870
4
1
128
39
47
12
22
5
1
+
6
1
2,093
863
116
940
4
1
130
39
47
13
22
5
1
+
6
1
+ Less than 0.5 Gg.
a Includes CH4 emission reductions due to CH4 collection and combustion by anaerobic digestion utilization systems.
b Includes both direct and indirect N20 emissions.
Note: Totals may not sum due to independent rounding.
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.
Methane Calculation Methods
The following inputs were used in the calculation of
j emissions:
Animal population data (by animal type and state);
Typical Animal Mass (TAM) data (by animal type);
Portion of manure managed in each Waste Management
System (WMS), by state and animal type;
Volatile solids (VS) production rate (by animal type and
state or U.S.);
CtLj producing potential (B0) of the volatile solids (by
animal type); and
Methane Conversion Factors (MCF), representing the
extent to which the CFLj producing potential is realized
for each type of WMS (by state and manure management
system, including the impacts of any biogas collection/
utilization efforts).
Methane emissions were estimated by first determining
activity data, including animal population, TAM, WMS
usage, and waste characteristics. The activity data sources
are described below:
• Annual animal population data for 1990 through 2007
for all livestock types, except horses and goats were
obtained from the USDA National Agricultural Statistics
Service (NASS). Horse population data were obtained
from the Food and Agriculture Organization (FAO)
FAOSTAT database (FAO 2008). Goat population data
for 1992,1997, and 2002 were obtained from the Census
of Agriculture (USDA 2005).
• The TAM is an annual average weight which was obtained
for each animal type from information in USDA's
Agricultural Waste Management Field Handbook (USDA
1996a), the American Society of Agricultural Engineers,
Standard D384.1 (ASAE 1999) and others (EPA 1992,
Shuyler 2000, and Safley 2000).
• WMS usage was estimated for swine and dairy cattle
for different farm size categories using data from
USDA (USDA 1996b, 1998, 2000a) and EPA (ERG
2000a, EPA 2002a, 2002b). For beef cattle and poultry,
Agriculture 6-9
-------
manure management system usage data were not tied
to farm size but were based on other data sources (ERG
2000a, USDA 2000b, UEP 1999). For other animal
types, manure management system usage was based on
previous estimates (EPA 1992).
• VS production rates for all cattle except for bulls and
calves were calculated for each state and animal type
in the CEFM, which is described in section 6.1, Enteric
Fermentation. VS production rates for all other animals
were determined using data from USDA's Agricultural
Waste Management Field Handbook (USDA 1996a)
and data from the American Society of Agricultural
Engineers, Standard D384.1 (ASAE 1999).
• The maximum CFLj producing capacity of the VS (B0)
was determined for each animal type based on literature
values (Morris 1976, Bryant et al, 1976, Hashimoto 1981,
Hashimoto 1984, EPA 1992, Hill 1982, and Hill 1984).
• MCFs for dry systems were set equal to default IPCC
factors based on state 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 van't Hoff-
Arrhenius equation which is consistent with IPCC 2006
Tier 2 methodology.
• Anaerobic digestion system data were obtained from
the EPA AgSTAR Program, including information
presented in the AgSTAR Digest (EPA 2000, 2003b,
2006).
• Emissions from anaerobic digestion systems were
estimated based on the methodology described in EPA's
Climate Leaders Greenhouse Gas Inventory Protocol
Offset Project Methodology for Project Types Managing
Manure with Biogas Recovery Systems (EPA 2008).
To estimate CH4 emissions, first the annual amount of
VS (kg per year) from manure that is excreted in each WMS
for each animal type, state, and year was calculated. This
calculation multiplied the animal population (head) by the VS
excretion rate (kg VS per 1,000 kg animal mass per day), the
TAM (kg animal mass per head) divided by 1,000, the WMS
distribution (percent), and the number of days per year.
The estimated amount of VS managed in each WMS was
used to estimate the CH4 emissions (kg CH4 per year) from
each WMS. The amount of VS (kg per year) was multiplied
by the maximum CH4 producing capacity of the VS (B0) (m3
CH4 per kg VS), the MCF for that WMS (percent), and the
density of CH4 (kg CH4 per m3 CH4).
For anaerobic digestion systems, the maximum CFLj
producing capacity of the VS (B0) (m3 CH4 per kg VS) was
multiplied by an estimated CH4 production value (percent),
assumed values of the system collection efficiency (CE)
(percent), an assumed value of the system destruction
efficiency (DE) (percent), and the density of CH4 (kg CH4
per m3 CH4) (ERG 2008). Anaerobic digestion systems
were assumed to produce 90 percent of the maximum CH4
producing capacity of the VS (B0). The CH4 CE of covered
lagoon systems was estimated to be 75 percent, and the
CH4 CE of complete mix and plug flow anaerobic digestion
systems was assumed to be 99 percent (EPA 2008). Any CH4
that was not collected was assumed to be emitted as leakage.
A DE from flaring or burning in an engine is estimated to
be 98 percent; therefore, the amount of CH4 that would not
be flared or combusted and would be emitted is 2 percent
(EPA 2008).
The CH4 emissions for each WMS (including anaerobic
digestion systems), state, and animal type were summed to
determine the total U.S. Methane emissions from manure
management.
Nitrous Oxide Calculation Methods
The following inputs were used in the calculation of
direct and indirect N2O emissions:
• Animal population data (by animal type and state);
• TAM data (by animal type);
• Portion of manure managed in each WMS (by state and
animal type);
• Total Kjeldahl N excretion rate (Nex);
• Direct N2O emission factor (EFWMS);
• Indirect N2O emission factor for volatilization
(-tiTvolitalization)'
• Indirect N2O emission factor for runoff and leaching
• Fraction of N loss from volatilization of ammonia and
NOX (Fracgas); and
• Fraction of N loss from runoff and leaching
(Frac,
'runoff/le:
:ach)-
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
N2O emissions were estimated by first determining
activity data, including animal population, TAM, WMS
usage, and waste characteristics. The activity data sources
(except for population, TAM, and WMS, which were
described above) are described below:
• N excretion rates from the USDA Agricultural Waste
Management Field Handbook (USDA 1996a) were used
for all animal types except sheep, goats, and horses. Data
from the American Society of Agricultural Engineers
(ASAE1999) were used for these animal types.
• All N2O emissions factors (direct and indirect) were
from IPCC (IPCC 2006).
• Country-specific estimates for the fraction of N loss from
volatilization (Fracgas) and runoff and leaching (Frac^^i
leach) were developed. Fracgas values were based on
WMS-specific volatilization values as estimated from
U.S. EPA's National Emission Inventory—Ammonia
Emissions from Animal Agriculture Operations (EPA
2005). Frac,
'runoff/leaching
values were based on regional
cattle runoff data from EPA's Office of Water (EPA
2002b; see Annex 3.1).
To estimate N2O emissions, first the amount of Nexcreted
(kg per year) in manure in each WMS for each animal type,
state, and year was calculated. The population (head) for
each state and animal was multiplied by TAM (kg animal
mass per head) divided by 1,000, the N excretion rate (Nex,
in kg N per 1000 kg animal mass per day), WMS distribution
(percent), and the number of days per year.
Direct N2O emissions were calculated by multiplying
the amount of Nexcreted (kg per year) in each WMS by the
N2O direct emission factor for that WMS (EFWMS, in kg
N2O-N per kg N) and the conversion factor of N2O-N to
N2O. These emissions were summed over state, animal and
WMS to determine the total direct N2O emissions (kg of
N2O per year).
Then, indirect N2O emissions from volatilization (kg
N2O per year) were calculated by multiplying the amount
of N excreted (kg per year) in each WMS by the fraction of
N lost through volatilization (Fracgas) divided by 100, and
the emission factor for volatilization (EFvolatilization, in kg N2O
per kg N), and the conversion factor of N2O-N to N2O. Next,
indirect N2O emissions from runoff and leaching (kg N2O
per year) were calculated by multiplying the amount of N
excreted (kg per year) in each WMS by the fraction of N lost
through runoff and leaching (Frac^^,!,,^) divided by 100,
and the emission factor for runoff and leaching (EFrunoff/leach,
in kg N2O per kg N), and the conversion factor of N2O-N
to N2O. The indirect N2O emissions from volatilization and
runoff and leaching were summed to determine the total
indirect N2O emissions.
The direct and indirect N2O emissions were summed to
determine total N2O emissions (kg N2O per year).
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. The quantitative uncertainty analysis
for this source category was performed in 2002 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 N2O 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.
No significant changes occurred in the methods, data or other
factors that influence the uncertainty ranges around the 2007
activity data. Consequently, these uncertainty estimates were
directly applied to the 2007 emission estimates.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 6-8. Manure management CH4
emissions in 2007 were estimated to be between 36.0 and
52.8 Tg CO2 Eq. at a 95 percent confidence level, which
indicates a range of 18 percent below to 20 percent above the
actual 2007 emission estimate of 44.0 Tg CO2 Eq. At the 95
percent confidence level, N2O emissions were estimated to
be between 12.3 and 18.2 Tg CO2 Eq. (or approximately 16
percent below and 24 percent above the actual 2007 emission
estimate of 14.7 Tg CO2 Eq.).
Agriculture 6-11
-------
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 (Direct and Indirect) Emissions from
Manure Management (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Manure Management
Manure Management
CH4
N20
44.0
14.7
Lower Bound
36.0
12.3
Upper Bound
52.8
18.2
Lower Bound
-18%
-16%
Upper Bound
+20%
+24%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 previous and
current inventories for CH^ and N2O emissions from manure
management. All errors identified were corrected. Order of
magnitude checks were also conducted, and corrections made
where needed. Manure N 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 WMS type for the full
time series, between national level estimates for N excreted
and the sum of county estimates for the full time series.
Recalculations Discussion
For the current Inventory, anaerobic digester systems were
incorporated into the WMS distributions in the CtLj estimates
using the existing WMS distributions and EPA AgSTAR data.
Emissions for anaerobic digestion systems were also calculated
using an assumed CH4 production rate, collection efficiency,
and combustion efficiency (ERG 2008).
Using the APHIS 2001 Sheep report, the WMS
distribution for sheep was updated. The APHIS report
presents regional percentages of sheep and lambs that are
primarily managed in open range/pasture, fenced range/
pasture, farms, or feedlots in 2001 (USDA 2003). WMS
data for sheep were previously obtained from USDA NASS
sheep report for years 1990 through 1993 (USDA 1994).
The WMS data for years 1994 through 2000 were calculated
assuming a linear progression from 1993 to 2001. Due to
lack of additional data, data for years 2002 and beyond were
assumed to be the same as 2001.
The CEFM produces volatile solids data for cattle that
are used in the manure management estimates. The CEFM
team implemented methodological changes to the VS
estimation, which created changes in VS data and changes
in the amount of methane estimated for manure management
(see Section 6.1, Enteric Fermentation).
With these recalculations, CH4 emission estimates
from manure management systems are slightly higher than
reported in the previous Inventory for swine and slightly
lower for dairy cattle. On average, annual CH4 emission
estimates are less than those of the previous Inventory by
1.7 percent.
Nitrous oxide emission estimates from manure
management systems have increased for all years for beef
cattle and since 1994 for sheep in the current Inventory as
compared to the previous Inventory due to the recalculations.
Overall the total emission estimates for the current Inventory
increased by 1.2 percent, relative to the previous Inventory.
Planned Improvements
The manure management emission estimates will
be updated to reflect changes in the Cattle Enteric
Fermentation Model (CEFM). In addition, efforts will
be made to ensure that the manure management emission
estimates and CEFM are using the same data sources and
variables where appropriate.
An updated version of the USDA Agricultural Waste
Management Field Handbook became available in March
2008. This reference will be reviewed to determine if updates
should be made to any of the inventory activity data.
The current inventory estimates take into account
anaerobic digestion systems for only dairy and swine
operations. Data from the AgSTAR Program will also be
reviewed and anaerobic digestions systems that exist for
other animal types will be incorporated.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
The uncertainty analysis will be updated in the future to
more accurately assess uncertainty of emission calculations.
This update is necessary due to changes in emission
calculation methodology in the current Inventory, including
estimation of emissions at the WMS level and the use of new
calculations and variables for indirect N2O emissions.
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 CtLj 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 CK4 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 CtLj 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 CH^ transport pathway to the atmosphere is
blocked. The quantities of CH4 released from deepwater
fields, therefore, are believed to be significantly less than
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 CH^ 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 CH^ 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 CH^ 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 CH^ production. However, although
temperature controls the amount of time it takes to convert
a given amount of organic material to CK4, 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 CK4 emissions; in particular, both
nitrate and sulfate fertilizers (e.g., ammonium nitrate and
ammonium sulfate) appear to inhibit CH^ formation.
Rice is cultivated in seven states: Arkansas, California,
Florida, Louisiana, Mississippi, Missouri, and Texas.4 Until
2006, rice was also cultivated in Oklahoma, but as of 2007
rice cultivation in the state ceased (Anderson 2008). 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
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.
4A very small amount of rice is grown on about 20 acres in South Carolina;
however, this amount was determined to be too insignificant to warrant
inclusion in national emissions estimates.
Agriculture 6-13
-------
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
southwest Louisiana, Texas, and Florida often allow for a
second, or ratoon, rice crop. Ratoon crops are much less
common or non-existent in Arkansas, California, Mississippi,
Missouri, Oklahoma, and northern areas of Louisiana.
Methane 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 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 ( and Table 6-10). In 2007, CIL, emissions from rice
cultivation were 6.2 Tg CO2 Eq. (293 Gg). Although annual
emissions fluctuated unevenly between the years 1990 and
2007, ranging from an annual decrease of 14 percent to an
annual increase of 17 percent, there was an overall decrease
of 14 percent over the seventeen-year period, due to an
overall decrease in primary crop area.5 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
IPCC (2006) recommends using harvested rice areas,
area-based daily emission factors (i.e., amount of CH4 emitted
per day per unit harvested area), and length of growing season
to estimate annual CH4 emissions from rice cultivation. This
Inventory uses the recommended methodology and employs
Tier 2 U.S.-specific emission factors derived from rice field
measurements. State-specific and daily emission factors were
not available, however, so average U.S. seasonal emission
factors were used. 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 (2006).
Table 6-9: CH4 Emissions from Rice Cultivation (Tg C02 Eq.)
State
1990
1995
2000
2005
2006
2007
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
5.1
2.1
1.0
0.4
"
0.6
"
»
0.9
5.6
2.4
0.8
0.5
0.2
0.6
"
"
0.8
5.5
2.5
0.9
0.4
0.3
0.4
2.0 1
0+
6.0
2.9
0.9
+
0.9
0.5
0.4
+
0.4
0.8
0.5
0.4
5.1
2.5
0.9
+
0.6
0.3
0.4
+
0.3
0.9
0.5
0.4
4.9
2.4
1.0
+
0.7
0.3
0.3
0.0
0.3
1.2
0.9
0.3
Total
7.1
7.6
7.5
6.8
5.9
6.2
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
5The 14 percent decrease occurred between 2005 and 2006; the 17 percent
increase happened between 1993 and 1994.
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-10: CH4 Emissions from Rice Cultivation (Gg)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
1990
2005
2006
241
119
44
1
29
16
18
+
13
41
+
1
22
18
2007
234
113
45
1
32
16
15
+
12
59
+
1
42
16
Total
339
363
357
326
282
293
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
The harvested rice areas for the primary and ratoon crops
in each state are presented in Table 6-11, and the area of
ratoon crop area as a percent of primary crop area is shown
in Table 6-12. Primary crop areas for 1990 through 2007 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 through 2008). Source data for non-USDA
sources of primary and ratoon harvest areas are shown in
Table 6-13. California, Mississippi, Missouri, and Oklahoma
have not ratooned rice over the period 1990 through 2007
(Guethle 1999, 2000, 2001a, 2002 through 2008; Lee 2003
through 2007; Mutters 2002 through 2005; Street 1999
through 2003; Walker 2005, 2007, 2008).
To determine what CH4 emission factors should be used
for the primary and ratoon crops, CJL, flux information from
rice field measurements in the United States was collected.
Experiments that 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).
The experimental results from primary crops with added
synthetic and organic fertilizer (Bossio et al. 1999; Cicerone
etal. 1992;Sassetal. 1991a, 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
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 1,490 kg CH4/hectare-season 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 IPCC (2006) default
emission factors.
Agriculture 6-15
-------
Table 6-11: Rice Areas Harvested (Hectares)
State/Crop
Arkansas
Primary
Ratoon3
California
Florida
Primary
Ratoon
Louisiana
Primary
Ratoon
Mississippi
Missouri
Oklahoma
Texas
Primary
Ratoon
Total Primary
Total Ratoon
Total
1990
485,
159,
4,
2,
220,
66,
101,
32,
142,
57,
1,148,
125,
1,273,
633
0
854
978
489
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,
221,
7,
3,
194,
77,
88,
68,
86,
43,
1,237,
124,
1,362,
619
0
773
801
193
253
701
223
393
283
605
302
951
197
148
2005
661,675
662
212,869
4,565
0
212,465
27,620
106,435
86,605
271
81,344
21,963
1,366,228
50,245
1,416,473
2006
566,572
6
211,655
4,575
1,295
139,620
27,924
76,487
86,605
17
60,704
23,675
1,146,235
52,899
1,199,135
2007
536,220
5
215,702
4,199
840
152,975
53,541
76,487
72,036
0
58,681
21,125
1,116,299
75,511
1,191,810
'Arkansas ratooning occurred only in 1998,1999, 2005, and 2006 and was assumed to occur in 2007.
Note: Totals may not sum due to independent rounding.
Table 6-12: Ratooned Area as Percent of Primary Growth Area
State
1990
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Arkansas
Florida
Louisiana
Texas
0%
50%
30%
40%
+ 0%
65% 41% 60% 54% 100% 77%
40% 30% 15% 35% 30%
50% 40% 37% 38% 35%
13%
27%
20%
20% 35%
39% 36%
+ Indicates ratooning rate less than 0.5 percent.
to derive an emission factor for the ratoon crop. The resultant
emission factor for the primary crop is 210 kg CtLj/hectare-
season, and the resultant emission factor for the ratoon crop
is 780 kg CHVhectare-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 CtLj/hectare-season. The uncertainty
distributions around the primary and ratoon emission factors
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-13: Non-USDA Data Sources for Rice Harvest Information
State/Crop
Arkansas
Ratoon
Florida
Primary
Ratoon
Louisiana
Ratoon
Oklahoma
Primary
Texas
Ratoon
1990 1999 2000
2001
2002 2003 2004 2005 2006 2007
Wilson (2002-2007)
Scheuneman
(1999b, 1999c, 2000, 2001 a)
Scheuneman
(1999a)
Bollich (2000)
Deren
(2002)
Deren
(2002)
Kirstein
(2003, 2006)
Kirstein Cantens
(2003-2004) (2005)
Linscombe (1999, 2001 a, 2002 through
l_66
(2003-2007)
Klosterboer
(1999-2003)
Gonzales
(2006-2008)
Gonzales
(2006-2008)
2008)
Anderson
(2008)
Stansel Texas Ag Experiment Station
(2004-2005) (2006-2008)
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 CK4 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 6-14. Rice cultivation CH^ emissions
in 2007 were estimated to be between 2.1 and 16.3 Tg CO2
Eq. at a 95 percent confidence level, which indicates a range
of 66 percent below to 164 percent above the actual 2007
emission estimate of 6.2 Tg CO2 Eq.
Table 6-14: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation
Manure Management (Tg C02 Eq. and Percent)
Source
2007 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
6.2
2.1
16.3
-66%
+ 164%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6-17
-------
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.
Planned Improvements
A possible future improvement is to create region-
specific emission factors for rice cultivation. The current
methodology uses a nationwide average emission factor,
derived from several studies done in a number of states.
The prospective improvement would take the same studies
and average them by region, presumably resulting in more
spatially-specific emission factors.
6.4. Agricultural Soil Management
(IPCC Source Category 4D)
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 to 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 drainage and cultivation of organic cropland
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, which are influenced
by agricultural management through impacts on moisture
and temperature regimes in soils. These additional sources
of mineral N are included at the recommendation of IPCC
(2006) for complete accounting of management impacts on
greenhouse gas emissions, as discussed in the Methodology
section.9 Indirect emissions of N2O occur through two
pathways: (1) volatilization and subsequent atmospheric
deposition of applied/mineralized N,10 and (2) surface runoff
and leaching of applied/mineralized 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. However, indirect N2O emissions from all land-use
types (cropland, grassland, forest lands, and settlements) are
reported in this section.
Agricultural soils produce the majority of N2O
emissions in the United States. Estimated emissions
from this source in 2007 were 207.9 Tg CO2 Eq. (671
Gg N2O) (see Table 6-15 and Table 6-16). Annual N2O
emissions from agricultural soils fluctuated between 1990
and 2007, although overall emissions were 3.8 percent
higher in 2007 than in 1990. Year-to-year fluctuations
are largely a reflection of annual variation in weather
patterns, synthetic fertilizer use, and crop production. On
7 Nitrification and denitrification are driven by the activity of microorganisms
in soils. Nitrification is the aerobic microbial oxidation of ammonium (NH4+)
to nitrate (NO3~), and denitrification is the anaerobic microbial reduction of
nitrate to 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.
9 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 or mineralized N as NH3
and NO,,, transformation of these gases within the atmosphere (or upon
deposition), and deposition of the N primarily in the form of particulate
ammonium (NH4+), nitric acid (HNO3), and NO,,.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure 6-2
Sources and Pathways of N that Result in N20 Emissions from Agricultural Soil Management
Synthetic N Fertilizers
Synthetic N fettilizet applied to soil
Organic
Amendments
Urine and Dung from
Grazing Animals
Manute deposited on pastute, tange,
and paddock
Includes above- and belowgtound
tesidues fot all ctops (non-N and in-
fixing (and from petennial fotage
ctops and pastutes following tenewal
Mineralization of
Soil Organic Matter
Includes N convetted to minetal fc
upon decomposition of soil otganic
Asymbiotic Fixation
Fixation of atmosphetic N2 by bactetia
living in soils that do not have a ditect
telationship with plants
This graphic illustrates the sources and pathways of nitrogen that result
in direct and indirect N20 emissions from soils using the methodologies
described in this Inventory. Emission pathways are 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.
average, cropland accounted for approximately 69 percent
of total direct emissions, while grassland accounted for
approximately 31 percent. These percentages are about
the same for indirect emissions since forest lands and
settlements account for such a small percentage of total
indirect emissions. Estimated direct and indirect N2O
emissions by sub-source category are shown in Table
6-17 and Table 6-18.
Agriculture 6-19
-------
Table 6-15: N20 Emissions from Agricultural Soils (Tg C02 Eq.)
Activity
1990
1995
2000
2005
2006
2007
Direct
Cropland
Grassland
Indirect (All Land-Use Types)
Cropland
Grassland
Forest Land
Settlements
174.4
122.2
52.1
36.3
25.0
10.5
0.1
0.6
170.7
119.9
50.8
37.7
26.7
10.3
0.1
0.6
172.0
121.9
50.1
35.9
24.9
10.3
0.1
0.6
Total
200.3
202.3
204.5
+ Less than 0.05 Tg C02 Eq.
Table 6-16: N20 Emissions from Agricultural Soils (Gg)
210.6
208.4
207.9
Activity
1990
Direct
Cropland
Grassland
Indirect (All Land-Use Types)
Cropland
Grassland
Forest Land
Settlements
1995
2000
2005
562
394
168
117
81
34
2006
551
387
164
122
86
33
2007
555
393
162
116
80
33
Total
646
653
660
679
672
671
+ Less than 0.5 Gg N20
Table 6-17: Direct N20 Emissions from Agricultural Soils by Land Use Type and N Input Type (Tg C02 Eq.)
Activity
1990
1995
2000
2005
2006
2007
Cropland
Mineral Soils
Synthetic Fertilizer
Organic Amendments3
Residue Nb
Mineralization and Asymbiotic Fixation
Organic Soils
Grassland
Synthetic Fertilizer
PRP Manure
Managed Manure0
Sewage Sludge
Residue Nd
Mineralization and Asymbiotic Fixation
106.3
103.5
41.0
7.6
7.0
47.8
2.9
52.5
1.0
10.3
1.0
0.3
12.0
27.9
114.2
111.3
46.6
8.3
7.7
48.7
2.9
51.6
1.0
10.9
0.9
0.3
11.9
26.6
119.4
116.5
45.4
8.8
7.7
54.6
2.9
49.9
0.9
10.2
0.9
0.4
11.1
26.3
122.2
119.3
48.3
9.2
7.5
54.3
2.9
52.1
0.9
10.7
1.0
0.5
11.8
27.3
119.9
117.0
46.5
9.3
7.6
53.7
2.9
50.8
0.9
10.5
1.0
0.5
11.5
26.4
121.9
119.0
47.3
9.8
7.6
54.4
2.9
50.1
0.9
10.4
1.0
0.5
11.3
26.0
Total
158.9
165.8
169.2
174.4
170.7
172.0
'Organic amendment inputs include managed manure amendments, daily spread manure amendments, and commercial organic fertilizers (i.e.
blood, dried manure, tankage, compost, and other).
b Cropland residue N inputs include N in unharvested legumes as well as crop residue N.
c Accounts for managed manure and daily spread manure amendments that are applied to grassland soils.
11 Grassland residue N inputs include N in ungrazed legumes as well as ungrazed grass residue N.
, dried
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-18: Indirect N20 Emissions from all Land-Use Types (Tg C02 Eq.)
Activity
1990
2005
2006
2007
Cropland
Volatilization & Atm. Deposition
Surface Leaching & Run-Off
Grassland
Volatilization & Atm. Deposition
Surface Leaching & Run-Off
Forest Land
Volatilization & Atm. Deposition
Surface Leaching & Run-Off
Settlements
Volatilization & Atm. Deposition
Surface Leaching & Run-Off
29.1
7.8
21.3
12.0
5.6
6.4
0.4
0.1
0.2
24.8
8.9
15.9
11.2
5.6
5.6
0.5
0.2
0.3
25.6
9.0
16.6
9.1
5.0
4.0
0.1
0.5
0.2
0.3
25.0
9.2
15.8
10.5
5.2
5.3
0.1
+
0.1
0.6
0.2
0.4
26.7
10.1
16.6
10.3
5.2
5.1
0.1
+
0.1
0.6
0.2
0.4
24.9
8.9
16.0
10.3
5.3
5.0
0.1
+
0.1
0.6
0.2
0.4
Total
41.5
36.5
35.3
36.3
37.7
35.9
+ Less than 0.05 Tg C02 Eq.
Figure 6-3 through Figure 6-6 show regional patterns
in direct N2O emissions, and also show N losses from
volatilization, leaching, and runoff that lead to indirect N2O
emissions. Average annual emissions and N losses from
croplands that produce major crops and from grasslands are
shown for each state. Direct N2O emissions from croplands
tend to be high in the Corn Belt (Illinois, Iowa, Indiana, Ohio,
southern Minnesota, and eastern Nebraska), where a large
portion of the land is used for growing highly fertilized corn
and N-fixing soybean crops. Direct emissions are also high
in North Dakota, Kansas, and Texas, primarily from irrigated
cropping and dryland wheat. Direct emissions are low in many
parts of the eastern United States because a small portion of
land is cultivated, and also low in many western states where
rainfall and access to irrigation water are limited.
Direct emissions (Tg CO2 Eq./state/year) from grasslands
are highest in the central and western United States (Figure
6-4) where a high proportion of the land is used for cattle
grazing. Some areas in the Great Lake states, the Northeast,
and Southeast have moderate emissions even though emissions
from these areas tend to be high on a per unit area basis,
because the total amount of grazed land is much lower than
states in the central and western United States.
Indirect emissions from croplands 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 as the processes that control direct emissions
(nitrification and denitrification). For example, coarser-
textured soils facilitate relatively high indirect emissions in
Florida grasslands due to high rates of N volatilization and
NO3~ leaching, even though they have only moderate rates
of direct N2O emissions.
Agriculture 6-21
-------
Figure 6-3
Major Crops, Average Annual Direct N20 Emissions by State, Estimated Using the DAYCENT Model,
1990-2007 (Tg C02 Eq./year)
Figure 6-4
Grasslands, Average Annual Direct N20 Emissions by State, Estimated Using the DAYCENT Model,
1990-2007 (Tg C02 Eq./year)
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure 6-5
Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions by State,
Estimated Using the DAYCENT Model, 1990-2007 (Gg N/year)
Gg N/state/year
D< 10
D 10-20
• 20-50
D50-100
D 100-200
D 200-400
D 400-692.9
Figure 6-6
Grasslands, Average Annual N Losses Leading to Indirect N20 Emissions, by State,
Estimated Using the DAYCENT Model, 1990-2007 (Gg N/year)
Gg N/state/year
D< 10
D 10-20
• 20-50
D 50-100
D 100-200
D 200-400
D 400-872.3
Agriculture 6-23
-------
Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N20 Emissions
The IPCC (2006) Tier 1 approach is based on multiplying activity data on different N inputs (e.g., synthetic fertilizer, manure, N fixation,
etc.) by the appropriate default IPCC emission factors to estimate N20 emissions on a input-by-input basis. 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. In contrast, the Tier 3 approach developed for this Inventory employs a process-based model (i.e., DAYCENT) that
represents the interaction of N inputs and the environmental conditions at specific locations. Consequently, the Tier 3 approach is likely
to produce more accurate estimates; it accounts more comprehensively 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), additional data inputs (e.g., daily weather, soil
types, etc.), and considerable computational resources and programming expertise. The Tier 3 methodology is less transparent, and thus it
is critical to evaluate the output of Tier 3 methods against measured data in order to demonstrate the adequacy of the method for estimating
emissions (IPCC 2006). 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 and cannot be stored in soils and contribute to
N20 emissions in subsequent years. This is a simplifying assumption that is likely to create bias in estimated N20 emissions for a specific
year. In contrast, the process-based model used in the Tier 3 approach includes such legacy effects when N added to soils is re-mineralized
from soil organic matter and emitted as N20 during subsequent years.
Methodology
The 2006 IPCC Guidelines (IPCC 2006) divide the
Agricultural Soil Management source category into four
components: (1) direct emissions due to N additions to
cropland and grassland mineral soils, including synthetic
fertilizers, sewage sludge applications, crop residues, organic
amendments, and biological nitrogen fixation associated with
planting of legumes on cropland and grassland soils; (2) direct
emissions from drainage and cultivation of organic cropland
soils; (3) direct emissions from soils due to the deposition
of manure by livestock on PRP grasslands; and (4) indirect
emissions from soils and water due to N additions and manure
deposition to soils that lead to volatilization, leaching, or
runoff of N and subsequent conversion to N2O.
The United States has adopted recommendations from
IPCC (2006) on methods for agricultural soil management.
These recommendations include (1) estimating the contribution
of N from crop residues to indirect soil N2O emissions; (2)
adopting a revised emission factor for direct N2O emissions
to the extent that Tier 1 methods are used in the Inventory
(described later in this section); (3) removing double counting
of emissions from N-fixing crops associated with the biological
N fixation and crop residue N input categories; (4) using revised
crop residue statistics to compute N inputs to soils based on
harvest yield data; (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 fixation11
(i.e., computing total emissions from managed land); (6)
reporting all emissions from managed lands, largely because
management affects all processes leading to soil N2O emissions.
One recommendation from IPCC (2006) has not been adopted:
accounting for emissions from pasture renewal, which involves
occasional plowing to improve forage production. This practice
is not common in the United States, and is not estimated.
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 has been specifically designed and tested
to estimate 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 further elaboration). The Tier 1 IPCC (2006) methodology
was used to estimate (1) direct emissions from non-major
crops on mineral soils (e.g., barley, oats, vegetables, and other
crops); (2) the portion of the grassland direct emissions that
were not estimated with the Tier 3 DAYCENT model (i.e.,
federal grasslands); and (3) direct emissions from drainage
11N 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 source.
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
and cultivation of organic cropland soils. Indirect emissions
were also estimated with a combination of DAY CENT and
the IPCC Tier 1 method.
In past inventory reports, attempts were made to subtract
"background" emissions that would presumably occur if the
lands were not managed. However, this approach is likely
to be inaccurate for estimating the anthropogenic influence
on soil N2O emissions. Moreover, if background emissions
could be measured or modeled based on processes unaffected
by anthropogenic activity, they would be a very small
portion of the total emissions, due to the high inputs of N
to agricultural soils from fertilization and legume cropping.
Given the recommendation from IPCC (2006) and the
influence of management on all processes leading to N2O
emissions from soils in agricultural systems, the decision
was made to report total emissions from managed lands for
this source category. 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 DAY CENT 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, soybeans,
wheat, alfalfa hay, other hay, sorghum, and cotton-
representing approximately 90 percent of total croplands in
the United States. For these croplands, DAY CENT was used
to simulate 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). Note that the influence of land-
use change on soil N2O emissions was not addressed in this
analysis, but is a planned improvement.
DAY CENT simulations were conducted for each major
crop at the county scale in the United States. Simulating
N2O emissions at the county scale was facilitated by soil and
weather data that were available for every county with more
than 100 acres of agricultural land, and by land management
data (e.g., timing of planting, harvesting, intensity of
cultivation) that were available at the agricultural-region
level as defined by the Agricultural Sector Model (McCarl et
al. 1993). ASM has 63 agricultural regions in the contiguous
United States. Most regions correspond to one state, except
for those states with greater heterogeneity in agricultural
practices; in such cases, more than one region is assigned
to a state. While cropping systems were simulated for each
county, the results best represent emissions at regional
(i.e., state) and national levels due to the regional scale of
management data, which include model parameters that
determined the influence of management activities on soil
N2O emissions (e.g., when crops were planted/harvested).
Nitrous oxide emissions from managed agricultural lands
are the result of interactions among anthropogenic activities
(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). It is not possible to partition N2O emissions
by anthropogenic activity directly from model outputs due to
the complexity of the interactions (e.g., N2O emissions from
synthetic fertilizer applications cannot be distinguished from
those resulting from manure applications). To approximate
emissions by activity, the amount of mineral N added to
the soil for each of these sources was determined and then
divided by the total amount of mineral N that was made
available in the soil according to the DAY CENT model.
The percentages were then multiplied by the total of direct
N2O emissions in order to approximate the portion attributed
to key practices. This approach is only an approximation
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. However, this
approach allows for further disaggregation of emissions by
source of N, which is valuable for reporting purposes and is
analogous to the reporting associated with the IPCC (2006)
Tier 1 method, in that it associates portions of the total soil
N2O emissions with individual sources of N.
DAY CENT was used to estimate direct N2O emissions
due to mineral N available from: (1) the application of
Agriculture 6-25
-------
synthetic fertilizers; (2) the application of livestock manure;
(3) the retention of crop residues (i.e., leaving residues in the
field after harvest instead of burning or collecting residues);
and (4) mineralization of soil organic matter and litter, in
addition to asymbiotic fixation. Note that commercial organic
fertilizers are addressed with the Tier 1 method because
county-level application data would be needed to simulate
applications in the DAY CENT, and currently data are only
available at the national scale. The third and fourth sources
are generated internally by the DAY CENT model. For the
first two practices, annual changes 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), NEA (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
and daily spread 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). Amendment data for 1997 were scaled to
estimate values for other years based on the availability
of managed manure N for application to soils in 1997
relative to other years. The amount of available nitrogen
from managed manure for each livestock type was
calculated as described in the Manure Management
section (Section 6.2) and Annex 3.10.
• Retention of crop residue, N mineralization from soil
organic matter, and asymbiotic N fixation from the
atmosphere: The IPCC approach considers crop residue
N and N mineralized from soil organic matter as activity
data. However, they are not treated as activity data in
DAY CENT 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, DAY CENT accounts for the
influence of N fixation, mineralization of N from soil
organic matter, and retention of crop residue on N2O
emissions, but these are not model inputs.
• 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 (2000a) 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). Approximately 3 percent of
the crop residues were assumed to be burned based on
state inventory data (ILENR 1993, Oregon Department
of Energy 1995, Noller 1996, Wisconsin Department
of Natural Resources 1993, and Cibrowski 1996), and
therefore did not contribute to soil N2O emissions.
DAY CENT simulations produced per-area estimates
of N2O emissions (g N2O-N/m2) for major crops in each
county, which were multiplied by the cropland areas in each
county to obtain county-scale emission estimates. Cropland
area data were from NASS (USDA 2008a,b). 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. DAY CENT is sensitive
to interannual variability in weather patterns and other
controlling variables, 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. DAY CENT's
ability to capture these interactions between management and
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
environmental conditions produces more accurate estimates
of N2O emissions than the Tier 1 method.
Non-Major Crop Types on Mineral Cropland Soils
The IPCC (2006) Tier 1 methodology was used to
estimate direct N2O emissions for mineral cropland soils
that are managed for production of non-major crop types,
including barley, oats, tobacco, sugarcane, sugar beets,
sunflowers, millet, rice, peanuts, and other crops that were
not included in the DAY CENT simulations. Estimates of
direct N2O emissions from N applications to non-major 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 managed manure
and non-manure commercial organic fertilizers;12 and (3)
the retention of above- and below-ground crop residues in
agricultural fields (i.e., crop biomass that is not harvested).
Non-manure organic amendments were not included in
the DAY CENT simulations because county-level data
were not available. Consequently, non-manure organic
amendments, as well as manure amendments not included
in the DAY CENT simulations, were included in the Tier 1
analysis. The influence of land-use change on soil N2O
emissions from non-major crops has not been addressed in
this analysis, but is a planned improvement. The following
sources were used to derive activity data:
• A process-of-elimination approach was used to estimate
synthetic N fertilizer additions for non-major crops,
because little information exists on their fertilizer
application rates. The total amount of fertilizer used
on farms has been estimated by the USGS from sales
records (Ruddy et al. 2006), and these data were
aggregated to obtain state-level N additions to farms.
After subtracting the portion of fertilizer applied to
major crops and grasslands (see sections on Major
Crops and Grasslands for information on data sources),
the remainder of the total fertilizer used on farms was
assumed to be applied to non-major crops.
• A process-of-elimination approach was used to estimate
manure N additions for non-major crops, because
12 Commercial organic fertilizers include dried blood, tankage, compost,
and other; dried manure and sewage sludge that are used as commercial
fertilizer have been excluded to avoid double counting. The dried manure
N is counted with the non-commercial manure applications, and sewage
sludge is assumed to be applied only to grasslands.
little information exists on application rates for these
crops. The amount of manure N applied to major crops
and grasslands was subtracted from total manure N
available for land application (see sections on Major
Crops and Grasslands for information on data sources),
and this difference was assumed to be applied to non-
major crops.
• Non-manure, non-sewage-sludge commercial organic
fertilizer additions were based on organic fertilizer
consumption statistics, which were converted to
units of N using average organic fertilizer N content
(TVA 1991 through 1994; AAPFCO 1995 through
2008). Manure and sewage sludge components were
subtracted from total commercial organic fertilizers to
avoid double counting.
• Crop residue N was derived by combining amounts
of above- and below-ground biomass, which were
determined based on crop production yield statistics
(USDA 1994, 1998, 2003, 2005, 2006, 2008a), dry
matter fractions (IPCC 2006), linear equations to
estimate above-ground biomass given dry matter crop
yields from harvest (IPCC 2006), ratios of below-to-
above-ground biomass (IPCC 2006), and N contents
of the residues (IPCC 2006). Approximately 3 percent
of the crop residues were burned and therefore did
not contribute to soil N2O emissions, based on state
inventory data (ILENR 1993, Oregon Department of
Energy 1995, Noller 1996, Wisconsin Department of
Natural Resources 1993, and Cibrowski 1996).
The total increase in soil mineral N from applied
fertilizers and crop residues was multiplied by the IPCC
(2006) default emission factor to derive an estimate of direct
N2O emissions from non-major crop types.
Drainage and Cultivation of Organic Cropland Soils
The IPCC (2006) Tier 1 methods were used to estimate
direct N2O emissions due to drainage and cultivation of
organic soils at a state scale. State-scale estimates of the
total area of drained and cultivated organic soils were
obtained from the National Resources Inventory (NRI)
(USDA 2000a, as extracted by Eve 2001 and amended by
Ogle 2002). Temperature data from Daly et al. (1994, 1998)
were used to subdivide areas into temperate and tropical
climates using the climate classification from IPCC (2006).
Agriculture 6-27
-------
Data were available for 1982, 1992 and 1997. 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).
Direct N20 Emissions from Grassland Soils
As with N2O from croplands, the Tier 3 process-based
DAY CENT model and Tier 1 method described in IPCC
(2006) 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, which
may or may not be improved with practices such as irrigation
and interseeding legumes.
DAY CENT was used to simulate county-scale N2O
emissions from non-federal grasslands resulting from manure
deposited by livestock directly onto pastures and rangelands
(i.e., PRPmanure), N fixation from legume seeding, managed
manure amendments (i.e., manure other than PRP manure),
and synthetic fertilizer application. Other N inputs were
simulated within the DAY CENT framework, including
N input from mineralization due to decomposition of soil
organic matter and N inputs from senesced grass litter, as
well as asymbiotic fixation of N from the atmosphere. The
simulations used the same weather, soil, and synthetic N
fertilizer 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) and adjusted for annual variation using data on the
availability of managed manure N for application to soils,
according to methods described in the Manure Management
section (Section 6.2) and annex (Annex 3.10). Biological N
fixation is simulated within DAY CENT and therefore was
not an input to the model.
Manure N deposition from grazing animals (i.e., PRP
manure) was an input to the DAY CENT model (see Annex
3.10), and included approximately 91 percent of total PRP
manure. The remainder of the PRP manure N excretions in
each county was assumed to be excreted on federal grasslands
(i.e., DAY CENT simulations were only conducted for non-
federal grasslands), and the N2O emissions were estimated
using the IPCC (2006) Tier 1 method with IPCC default
emission factors. The amounts of PRP manure N applied on
non-federal and federal grasslands in each county were based
on the proportion of non-federal grassland area according
to data from the NRI (USDA 2000a), relative to the area of
federal grasslands from the National Land Cover Dataset
(Vogelman et al. 2001).
Sewage sludge was assumed to be applied on grasslands
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, 1999, 2003), McFarland (2001), and
NEBPsA (2007). Sewage sludge data on soil amendments on
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. Therefore,
DAY CENT could not be used to simulate the influence of
sewage sludge amendments on N2O emissions from grassland
soils, and consequently, emissions from sewage sludge were
estimated using the IPCC (2006) Tier 1 method.
DAY CENT simulations produced per-area estimates of
N2O emissions (g N2O-N/m2) for pasture and rangelands,
which were multiplied by the reported pasture and rangeland
areas in each county. Grassland area data were obtained
from the NPJ (USDA 2000a). The 1997 NPJ area data for
pastures and rangeland were aggregated to the county level
to estimate the grassland areas for 1995 to 2007, and the
1992 NPJ pasture and rangeland data were aggregated to
the county level to estimate areas from 1990 to 1994. The
county estimates were scaled to the 63 agricultural regions,
and the national estimate was calculated by summing results
across all regions. Tier 1 estimates of N2O emissions for
the PRP manure N applied to non-federal lands and sewage
sludge N were produced by multiplying the N input by the
appropriate emission factor.
Total Direct N20 Emissions from Cropland and
Grassland Soils
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 the total direct N2O emissions from agricultural soil
management (see Table 6-15 and Table 6-16).
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Indirect N20 Emissions from Managed Soils of all
Land-Use Types
This section describes the methods used for estimating
indirect soil N2O emissions from all land-use types (i.e.,
croplands, grasslands, forest lands, and settlements). 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, organic
amendments (e.g., manure, sewage sludge), and deposition
of PRP manure. Nitrogen made available from mineralization
of soil organic matter and asymbiotic fixation also contributes
to volatilized N emissions. Volatilized N can be returned
to soils through atmospheric deposition, 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, and asymbiotic fixation. The nitrate is
subj ect to denitrification in water bodies, which leads to N2O
emissions. Regardless of the eventual location of the indirect
N2O emissions, the emissions are assigned to the original
source of the N for reporting purposes, which here includes
croplands, grasslands, forest lands, and settlements.
Indirect N20 Emissions from Atmospheric Deposition
of Volatilized N from Managed Soils
Similarly to the direct emissions calculation, the
Tier 3 DAYCENT model and IPCC (2006) Tier 1 methods
were combined to estimate the amount of N that was
transported from croplands, grasslands, forest lands, and
settlements through volatilization, and eventually emitted
as N2O. DAYCENT was used to estimate N volatilization
for land areas whose direct emissions were simulated with
DAYCENT (i.e., major croplands and most grasslands). The
N inputs included are the same as described for direct N2O
emissions in the sections on major crops and grasslands.
The Tier 1 method and default IPCC fractions for N subject
to volatilization were used for areas and N applications
that were not simulated with DAYCENT (i.e., N inputs on
non-major croplands, PRP manure N excretion on federal
grasslands, sewage sludge application on grasslands).
The Tier 1 method and default fractions were also used
to estimate N subject to volatilization from N inputs on
settlements and forest lands (see the Land Use, Land-Use
Change, and Forestry chapter). With the DAYCENT and Tier
1 approaches, the IPCC (2006) default emission factor was
used to estimate indirect N2O emissions associated with the
amount of volatilized N (Table 6-18).
Indirect N20 from Leaching/Runoff
As with the calculations of indirect emissions from
volatilized N, the Tier 3 DAYCENT model and IPCC (2006)
Tier 1 method were combined to estimate the amount of N
that was transported from croplands, grasslands, forest lands,
and settlements through leaching and surface runoff into
water bodies, and eventually emitted as N2O. DAYCENT
was used to simulate the amount of N transported from lands
used to produce major crops and most grasslands. Nitrogen
transport from all other areas was estimated using the Tier 1
method and the IPCC (2006) default factor for the proportion
of N subject to leaching and runoff. This N transport estimate
includes N applications on croplands that produce non-maj or
crops, sewage sludge amendments on grasslands, PRP
manure N excreted on federal grasslands, and N inputs on
settlements and forest lands. For both the DAYCENT and
IPCC (2006) Tier 1 methods, nitrate leaching was assumed
to be an insignificant source of indirect N2O in cropland and
grassland systems where the amount of precipitation plus
irrigation did not exceed the potential evapotranspiration, as
recommended by IPCC (2006). With both the DAYCENT
and Tier 1 approaches, the IPCC (2006) default emission
factor was used to estimate indirect N2O emissions associated
with N losses through leaching and runoff (Table 6-18).
Uncertainty
Uncertainty was estimated for each of the following
five components of N2O emissions from agricultural soil
management: (1) direct emissions calculated by DAYCENT;
(2) the components of indirect emissions (N volatilized
and leached or runoff) calculated by DAYCENT; (3) direct
emissions calculated with the IPCC (2006) Tier 1 method;
(4) the components of indirect emissions (N volatilized and
leached or runoff) calculated with the IPCC (2006) Tier 1
method; and (5) indirect emissions calculated with the IPCC
(2006) Tier 1 method. Uncertainty in direct emissions, which
Agriculture 6-29
-------
Table 6-19: Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil Management in 2007
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Direct Soil N20 Emissions
Indirect Soil N20 Emissions
N20
N20
172.0
35.9
Lower Bound
126.2
20.6
Upper Bound
265.2
84.8
Lower Bound
-27%
-43%
Upper Bound
+54%
+ 136%
Note: Due to lack of data, uncertainties in areas for major crops, 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; these sources of
uncertainty will be included in future Inventories.
account for the majority of N2O emissions from agricultural
management, as well as the components of indirect emissions
calculated by DAYCENT were estimated with a Monte
Carlo Analysis, addressing uncertainties in model inputs and
structure (i.e., algorithms and parameterization). Uncertainties
in direct emissions calculated with the IPCC (2006) Tier 1
method, the proportion of volatilization and leaching or runoff
estimated with the IPCC (2006) Tier 1 method, and indirect
N2O emissions were estimated with a simple error propagation
approach (IPCC 2006). Additional details on the uncertainty
methods are provided in Annex 3.11.
Uncertainties from the Tier 1 and Tier 3 (i.e., DAYCENT)
estimates were combined using simple error propagation
(IPCC 2006), and the results are summarized in Table
6-19. Agricultural direct soil N2O emissions in 2007 were
estimated to be between 126.2 and 265.2 Tg CO2 Eq. at a 95
percent confidence level. This indicates a range of 27 percent
below and 54 percent above the 2007 emission estimate of
172.0 Tg CO2 Eq. The indirect soil N2O emissions in 2007
were estimated to range from 20.5 to 84.8 Tg CO2 Eq. at
a 95 percent confidence level, indicating an uncertainty of
43 percent below and 136 percent above the 2007 emission
estimate of 35.9 Tg CO2 Eq.
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, soil
types, and climate patterns (Del Grosso et al. 2005, Del
Grosso et al. 2008), and further evaluated by comparing to
emission estimates produced using the IPCC (2006) Tier 1
method for the same sites. Nitrous oxide measurement data
were available for 11 sites in the United States and one in
Canada, representing 30 different combinations of fertilizer
treatments and cultivation practices. DAYCENT estimates
of N2O emissions were closer to measured values at all
sites except for Colorado dryland cropping (Figure 6-7). In
general, IPCC Tier 1 methodology tends to over-estimate
emissions when observed values are low and under-estimate
emissions when observed values are high, while DAYCENT
estimates are less biased. This is not surprising because
DAYCENT accounts for site-level factors (weather, soil
type) that influence N2O emissions. 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 0.89 and 0.94 for
annual N2O emissions and NO3~ leaching, respectively.
This comparison demonstrates that DAYCENT provides
relatively high predictive capability for N2O emissions and
NO3~ leaching, and is an improvement over the IPCC Tier 1
method (see additional information in Annex 3.11).
Spreadsheets containing input data and probability
distribution functions 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 uncertainty analysis.
Several errors were identified following re-organization
of the calculation spreadsheets, and corrective actions
have been taken. In particular, some of the links between
spreadsheets were missing or needed to be modified.
Spreadsheets containing input data, emission factors, and
calculations required for the Tier 1 approach were checked
and no errors were found.
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure 6-7
Comparison of Measured Emissions at Field Sites with Modeled Emissions Using the DAYCENT Simulation Model
40 -1
30 -
20 -
10 -
I Measured
DAYCENT
IPCC
I
CO
Dryland
Wheat
CO
Dryland
Cropping
NE
Dryland
Wheat
NE
Grass
CO
Grass
Ontario
Corn
I •
PA
Crop
I
PA
Grass
Average
Recalculations Discussion
Several revisions were made in the Agricultural Soil
Management Section for the current Inventory.
First, a new version of the DAYCENT model was made
operational for the Inventory. This version of DAYCENT
has several improvements, including elimination of the
influence of labile (i.e., easily decomposable by microbes) C
availability on surface litter denitrification rates, incorporation
of precipitation events as a controlling variable on surface
litter denitrification, and allowing the wettest soil layer within
the rooting zone to control plant transpiration.
Second, given a new operational version of DAYCENT,
the structural uncertainty in the model was re-evaluated and
estimates were revised from the previous Inventory. In the
current application, residual error from the linear mixed-effect
model was also included as a component of the structural
uncertainty, and this led to a larger uncertainty in the N2O
emission estimates from DAYCENT. This component was
not addressed in the previous Inventory because it was
considered measurement error. However, some of the residual
error is likely associated with the structure of the model. In
addition, structural uncertainty was evaluated in the grassland
predictions from DAYCENT, which had not been included
in the previous Inventory.
Third, PRP manure N deposition on non-federal
grasslands was estimated from county-level grazing animal
population data, instead of using estimates of N deposition
computed internally in the DAYCENT model. Quality
control on the previous Inventory suggested that DAYCENT
over-estimated PRP manure N deposition in some states.
This improvement ensures that the data on PRP manure
N in the DAYCENT model simulations is consistent with
N excretion data from the Manure Management section of
this Inventory.
Fourth, nitrate leaching was assumed to be an
insignificant source of indirect N2O in cropland and grassland
systems where the amount of precipitation plus irrigation did
not exceed the potential evapotranspiration, as recommended
by IPCC (2006). These areas are typically semi-arid to arid,
and nitrate leaching to groundwater is a relatively uncommon
event. Adopting this recommendation reduced indirect N2O
emissions.
The recalculations associated with these changes
reduced emissions by about 23 percent on average, primarily
due to the new operational version of DAYCENT, revised
structural uncertainty associated with the model, and reduced
impact of N leaching on indirect N2O emissions in arid and
semi-arid regions. Earlier versions of DAYCENT tended to
over-estimate emissions above 6 g N2O/m2, and although
these emissions were adjusted using the structural uncertainty
estimator, there was considerable uncertainty in those
adjustments. The new operational version of DAYCENT
does not overestimate N2O emissions for the majority of
crops, with the exception of small grains.
Including residual error from the linear mixed-effect
model as a component of the structural uncertainty and
structural uncertainty in the grassland predictions from
DAYCENT resulted in wider 95 percent confidence intervals
compared to the previous Inventory. Of these changes,
including structural uncertainty in the grassland predictions
Agriculture 6-31
-------
from DAY CENT was responsible for most of the increase
in uncertainty.
Planned Improvements
Several improvements are planned for the Agricultural
Soil Management sector. The first improvement is to
incorporate more land-use survey data from the NRI (USDA
2000a) into the DAY CENT 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 1979 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. First, most
crops are grown in rotation with other crops (e.g., corn-
soybean), but NASS data provide no information regarding
rotation histories. In contrast, NRI is designed to track
rotation histories, which 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 provides a complete history of cropland
areas for four out of every five years from 1979 to 1997,
and then every year after 1998. 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 methods
more consistent with the methods used to estimate C stock
changes for agricultural soils. The structure of model input
files that contain land management data will need to be
extensively revised to facilitate use of the annualized NRI
data. This improvement is planned to take place over the
next several years.
Other planned improvements are minor but will lead
to more accurate estimates, including updating DAYMET
weather data for more recent years, setting the PRP emission
factor for horse, sheep and goats to 0.01 in accordance with
guidance from IPCC (2006) and using a rice-crop-specific
EF for N amendments to rice areas.
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 C 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.
Field burning is not a common method of agricultural
residue disposal in the United States. The primary crop types
whose residues are typically burned in the United States are
wheat, rice, sugarcane, corn, barley, soybeans, and peanuts.
It is assumed that 3 percent of the residue for each of these
crops is burned each year, except for rice.13 In 2007, CK4
and N2O emissions from field burning were 0.9 Tg CO2 Eq.
(42 Gg) and 0.5 Tg. CO2 Eq. (2 Gg), respectively. Annual
emissions from this source over the period 1990 to 2007 have
remained relatively constant, averaging approximately 0.8
Tg CO2 Eq. (37 Gg) of CH4 and 0.4 Tg CO2 Eq. (1 Gg) of
N2O (see Table 6-20 and Table 6-21).
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: 1990-2007
-------
Table 6-20: CH4 and N20 Emissions from Field Burning of Agricultural Residues (Tg C02 Eq.)
Gas/Crop Type
1990
1995
2000
2005
2006
2007
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
"
0.3
0.4 1
I
0.2
"
0.3
0.2
0.41
I
0.2
0.8
0.1
"
0.4
0.2
0.51
I
0.3
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
+
0.1
+
0.3
0.8
0.1
0.1
+
0.4
+
0.2
+
0.5
0.1
+
0.3
0.9
0.1
0.1
+
0.5
+
0.2
+
0.5
0.1
+
0.2
Total
1.1
1.0
1.3
1.4
1.3
1.4
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-21: CH4, N20, CO, and NO, Emissions from Field Burning of Agricultural Residues (Gg)
Gas/Crop Type
1990
1995
2000
2005
2006
2007
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
CO
NO,
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
39
4
4
1
18
+
12
+
2
1
+
825
38
42
5
4
1
22
+
9
+
2
1
+
892
37
Agriculture 6-33
-------
Methodology
The Tier 2 methodology used for estimating greenhouse
gas emissions from field burning of agricultural residues in
the United States is consistent with IPCC (2006) (for more
details, see Box 6-2). In order to estimate the amounts of
C and nitrogen (N) released during burning, the following
equation was used:14
C or N released = Ł over all crop types
(Crop Production x Residue/Crop Ratio x
Dry Matter Fraction x Fraction of Residue Burned x
Burning Efficiency x Combustion Efficiency x
Fraction of C or N)
where,
Crop Production = Annual production of crop
inGg
Residue/Crop
Ratio = Amount of residue produced
per unit of crop production
Fraction of
Residue Burned = Amount of residue that is
burned per unit of total
residue
Dry Matter Fraction = Amount of dry matter per
unit of biomass
Fraction of C or N = Amount of C or N per unit
of dry matter
Burning Efficiency = The proportion of prefire
fuel biomass consumed15
Combustion
Efficiency = The proportion of C or N
released with respect to the
total amount of C or N avail-
able in the burned material,
respectively15
The amount C or N released was used in the following
equation to determine the CH4, CO, N2O and NOX emissions
from the field burning of agricultural residues:
CH4 and CO, or N2O and NOX Emissions from Field
Burning of Agricultural Residues = (C or N Released) x
(Emissions Ratio for C or N) x (Conversion Factor)
where,
14As 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.
15 In IPCC/UNEP/OECD/IEA (1997), the equation for C or N released
contains the variable 'fraction oxidized in burning.' This variable is
equivalent to (burning efficiency x combustion efficiency).
Emissions Ratio = g CH4-C or CO-C/g C
released, or g N2O-N or
NOx-N/g N released
Conversion Factor = conversion, by molecular
weight ratio, of CH4 to
C (16/12), or CO to
C(28/12),orN2Oto
N (44/28), or NOX to
N (30/14)
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 through 2008). Rice production data for Florida
and Oklahoma, which are not collected by USDA, were
estimated separately. Average primary and ratoon crop yields
for Florida (Schueneman and Deren 2002) were applied to
Florida acreages (Schueneman 1999b, 2001; Deren 2002;
Kirstein 2003, 2004; Cantens 2004, 2005; Gonzalez 2007a,
2008), and crop yields for Arkansas (USDA 1994, 1998,
2003,2005,2006) were applied to Oklahoma acreages16 (Lee
2003 through 2006; Anderson 2008). The production data
for the crop types whose residues are burned are presented
in Table 6-22.
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 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; Guethle 2007, 2008; Klosterboer
16 Rice production yield data are not available for Oklahoma, so the Arkansas
values are used as a proxy.
6-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
1999a, 1999b, 2000 through 2003; Lancero 2006 through
2008; Lee 2005 through 2007; Lindberg 2002 through
2005; Linscombe 1999a, 1999b, 2001 through 2008; Najita
2000, 2001; Sacramento Valley Basinwide Air Pollution
Control Council 2005, 2007; Schueneman 1999a, 1999b,
2001; Stansel 2004, 2005; Street 2001 through 2003;
Texas Agricultural Experiment Station 2006 through 2008;
Walker 2004 through 2008; Wilson 2003 through 2007) (see
Table 6-23). The estimates provided for Florida remained
constant over the entire 1990 through 2007 period. While
the estimates for all other states varied over the time series,
estimates for Missouri remained constant through 2005,
dropped in 2006, and remained constant at the 2006 value
in 2007. 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 2007 because of a legislated
reduction in rice straw burning (Lindberg 2002), although
there was a slight increase from 2004 to 2005 and from
2006 to 2007 (see Table 6-23).
Table 6-22: Agricultural Crop Production (Gg of Product)
All residue/crop product mass ratios except sugarcane
were obtained from Strehler and Stiitzle (1987). The data for
sugarcane is from University of California (1977). 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 Stiitzle (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 C contents and N 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 N
content of peanuts is from Ketzis (1999). These data are
listed in Table 6-24. 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 and conversion factors for all gases (see Table 6-25)
were taken from the Revised 1996 IPCC Guidelines (IPCC/
UNEP/OECD/IEA 1997).
Crop
Wheat
Rice
Sugarcane
Corn3
Barley
Soybeans
Peanuts
a Corn for grain
(i.e., excludes corn for silage).
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
2005
57,280
10,150
24,137
282,311
4,613
83,368
2,209
2006
49,316
8,813
26,820
267,598
3,923
86,770
1,571
2007
56,247
8,979
27,972
332,092
4,612
70,358
1,697
Agriculture 6-35
-------
Box 6-2: Comparison of Tier 2 U.S. Inventory Approach
and IPCC (2006) Default Approach
This Inventory calculates emissions from Burning of
Agricultural Residues using a Tier 2 methodology that is based on
IPCC/UNEP/OECD/IEA (1997) and incorporates crop- and country-
specific emission factors and variables. The equation used in this
Inventory varies slightly in form from the one presented in the IPCC
(2006) guidelines, but both equations rely on the same underlying
variables. The IPCC (2006) equation was developed to be broadly
applicable to all types of biomass burning, and, thus, is not specific
to agricultural residues. IPCC (2006) default factors are provided
only for four crops (wheat, corn, rice, and sugarcane), while this
Inventory analyzes emissions from seven crops. A comparison of
the methods and factors used in (1) the current Inventory and (2)
the default IPCC (2006) approach was undertaken to determine
the magnitude of the difference in overall estimates resulting from
the two approaches. Since the default IPCC (2006) approach calls
for area burned data that are currently unavailable for the United
States, estimates of area burned were developed using USDA data
on area harvested for each crop multiplied by the estimated fraction
of residue burned for that crop (see Table 6-24).
The IPCC (2006) default approach resulted in 19 percent
higher emissions of CH4 and 35 percent higher emissions of N20
than the current estimates in this Inventory. It is reasonable to
maintain the current methodology, since the IPCC (2006) defaults
are only available for four crops and are worldwide average
estimates, while current inventory estimates are based on U.S.-
specific, crop-specific, published data.
Table 6-25: Greenhouse Gas Emission Ratios and
Conversion Factors
Gas
CH4:C
CO:C
N20:N
NOX:N
Emission Ratio
0.0053
0.0603
0.007b
0.121b
Conversion Factor
16/12
28/12
44/28
30/14
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).
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 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 and 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 6-26. Methane emissions
Table 6-24: 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
6-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 6-26: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of
Agricultural Residues (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Field Burning of
Agricultural Residues
Field Burning of
Agricultural Residues
CH4
N20
0.9
0.5
Lower Bound
0.2
0.1
Upper Bound
1.7
0.9
Lower Bound
-73%
-73%
Upper Bound
+94%
+85%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
from field burning of agricultural residues in 2007 were
estimated to be between 0.2 and 1.7 Tg CO2 Eq. at a 95
percent confidence level. This indicates a range of 73 percent
below and 94 percent above the 2007 emission estimate of
0.9 Tg CO2 Eq. Also at the 95 percent confidence level, N2O
emissions were estimated to be between 0.1 and 0.9 Tg CO2
Eq. (or approximately 73 percent below and 85 percent above
the 2007 emission estimate of 0.5 Tg CO2 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 2006 and 2007 were
updated using data from USDA (2008). This change resulted
in an increase in the CK4 emission estimate for 2006 of 0.01
percent, and an increase in the N2O emission estimate for
2006 of 0.002 percent, relative to the previous Inventory.
Planned Improvements
The estimated 3 percent of crop residue burned for all
crops, except rice, is based on data gathered from several
state greenhouse gas inventories. This fraction is the most
statistically significant input to the emissions equation, and
an important area for future improvement. More crop- and
state-specific information on the fraction burned will be
investigated by literature review and/or by contacting state
departments of agriculture.
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.
Agriculture 6-37
-------
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 2006 Guidelines for
National Greenhouse Gas Inventories (IPCC 2006) 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) and urea fertilization. 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 estimates in this chapter, with the exception of CO2 fluxes from wood products and urban trees, and CO2 emissions
from liming and urea fertilization, are based on activity data collected at multiple-year intervals, which are in the form of
forest, land-use, and municipal solid waste surveys. CO2 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. For the landfilled yard trimmings and food scraps
source, periodic solid waste survey data were interpolated so that annual storage estimates could be derived. 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 2007 resulted in a net C sequestration of 1,062.6 Tg CO2 Eq. (289.8
Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 17.4 percent of total U.S. CO2 emissions. Total land
use, land-use change, and forestry net C sequestration2 increased by approximately 26 percent between 1990 and 2007. This
increase was primarily due to an increase in the rate of net C accumulation in forest C stocks. Net C accumulation in Forest
Land Remaining Forest Land, Land Converted to Grassland, and Settlements Remaining Settlements increased, while net C
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."
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 act as a sink. This is also referred to as net
C sequestration.
Land Use, Land-Use Change, and Forestry 7-1
-------
Table 7-1: Net C02 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2005
2006
2007
Forest Land Remaining Forest Land3
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements"
Other (Landfilled Yard Trimmings
and Food Scraps)
(975.7)
(18.3)
5.9
(4.6)
(26.7)
(93.3)
(900.3)
(19.1)
5.9
(4.6)
(26.7)
(95.5)
(23.5)
(13.9)
(11.3)
(10.2) (10.4)
(910.1)
(19.7)
5.9
(4.7)
(26.7)
(97.6)
(9.8)
Total
(841.4)
(851.0)
(717.5)
(1,122.7) (1,050.5) (1,062.6)
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 on both Settlements Remaining Settlements and Land Converted to Settlements.
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
Table 7-2: Net C02 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg C)
Sink Category
1990
1995
2000
2005
2006
2007
Forest Land Remaining Forest Land3
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements"
Other (Landfilled Yard Trimmings
and Food Scraps)
(180.3)
(8.0)
0.6
(12.7)
(6.1)
(16.5)
(6.4)
(187.2)
(6.3)
0.8
(9.9)
(6.1)
(19.5)
I 0.8 0.61
(9.9) (14.0)
(6.1) (8.7)
• (19.5) (22.5)
(139.8)
(8.2)
0.6
(14.0)
(8.7)
(22.5)
(3.8)
(3.1)
(266.1)
(5.0)
1.6
(1.3)
(7.3)
(25.4)
(2.8)
(245.5)
(5.2)
1.6
(1.3)
(7.3)
(26.0)
(2.8)
(248.2)
(5.4)
1.6
(1.3)
(7.3)
(26.6)
(2.7)
Total
(229.5)
(232.1)
(195.7)
(306.2) (286.5) (289.8)
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 on both Settlements Remaining Settlements and Land Converted to Settlements.
Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
accumulation in Cropland Remaining Cropland, Grassland
Remaining Grassland, and landfilled yard trimmings and
food scraps slowed over this period. Emissions from Land
Converted to Cropland increased between 1990 and 2007.
Emissions from Land Use, Land-Use Change, and
Forestry are shown in Table 7-3 and Table 7-4. Liming of
agricultural soils and urea fertilization in 2007 resulted in
CO2 emissions of 4.1 Tg CO2 Eq. (4,055 Gg) and 4.0 Tg
CO2 Eq. (3,952 Gg), respectively. Lands undergoing peat
extraction (i.e., Peatlands Remaining Peatlands) resulted
in CO2 emissions of 1.0 Tg CO2 Eq. (1,010 Gg), and N2O
emissions of less than 0.01 Tg CO2 Eq. The application of
synthetic fertilizers to forest and settlement soils in 2007
resulted in direct N2O emissions of 1.9 Tg CO2 Eq. (6 Gg).
Direct N2O emissions from fertilizer application to forest
soils have increased by a multiple of 6.7 since 1990, but still
account for a relatively small portion of overall emissions at
0.3 Tg CO2 Eq. (1 Gg) in 2007. Forest fires in 2007 resulted
in methane (CFL,) emissions of 29.0 TgCO2Eq. (1,381 Gg),
and in N2O emissions of 2.9 Tg CO2 Eq. (9 Gg).
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Source Category
1990
1995
2000
2005
2006
2007
CO,
Crop|and Remaining Cropland: Liming of
Agricultural Soils
Urea Fertilization
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands
CH4
Forest Land Remaining Forest Land:
Forest Fires
N,0
Forest Land Remaining Forest Land:
Forest Fires
Forest Land Remaining Forest Land:
Forest Soils3
Settlements Remaining Settlements:
Settlement Soils"
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands
Total
8.8
4.3
3.2
1.2
20.6
20.6
3.6
2.1
0.3
1.2
8.9
4.3
3.5
1.1
14.2
14.2
3.3
1.4
0.3
1.5
8.8
4.2
3.7
0.9
31.3
31.3
5.0
3.2
0.3
1.5
9.0
4.1
4.0
1.0
29.0
29.0
4.9
2.9
0.3
1.6
14.2
33.0
26.4
45.1
42.9
+ Less than 0.05 Tg C02 Eq.
a Estimates include emissions from N fertilizer additions on both Forest 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.
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter.
Totals may not sum due to independent rounding.
Table 7-4: Emissions from Land Use, Land-Use Change, and Forestry (Gg)
Source Category
1990
1995
2000
2005
2006
2007
CO,
Cropjand Remaining Cropland: Liming of
Agricultural Soils
Urea Fertilization
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands
CH4
Forest Land Remaining Forest Land:
Forest Fires
N,0
8,117
4,667
2,417
1,033
218
218
5
8,067
4,392
2,657
1,018
293
293
6
8,768
4,328
3,214
1,227
983
983
8,933 8,768
Forest Land Remaining Forest Land:
Forest Fires
Forest Land Remaining Forest Land:
Forest Soils3
Settlements Remaining Settlements:
Settlement Soils"
Wetlands Remaining Wetlands: Peatlands
Remaining Peatlands
3
4
4,349
3,504
1,079
676
676
11
5
1
5
4,233
3,656
879
1,489
1,489
16
10
1
5
9,018
4,055
3,952
1,010
1,381
1,381
16
9
1
5
+ Less than 0.5 Gg
a Estimates include emissions from N fertilizer additions on both Forest 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.
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter.
Totals may not sum due to independent rounding.
Land Use, Land-Use Change, and Forestry 7-3
-------
7.1. Representation of the
U.S. Land Base
A national land-use categorization system that is
consistent and complete both temporally and spatially is
needed in order to assess land use and land-use change
status and the associated greenhouse gas fluxes over the
inventory time series. This system should be consistent with
IPCC (2006), such that all countries reporting on national
greenhouse gas fluxes to the UNFCCC should (1) describe the
methods and definitions used to determine areas of managed
and unmanaged lands in the country, (2) describe and apply
a consistent set of definitions for land-use categories over
the entire national land base and time series associated with
the greenhouse gas inventory, such that increases in the
land areas within particular land use categories are balanced
by decreases in the land areas of other categories, and (3)
account for greenhouse gas fluxes on all managed lands.
The implementation of such a system helps to ensure that
estimates of greenhouse gas fluxes are as accurate as possible.
This section of the National Greenhouse Gas Inventory has
been developed in order to comply with this guidance.
Multiple databases are utilized to track land management
in the United States, which are also used as the basis to
categorize the land area into the six IPCC land-use categories
(i.e., Forest Land Remaining Forest Land, Cropland
Remaining Cropland, Grassland Remaining Grassland,
Wetlands Remaining Wetlands, Settlements Remaining
Settlements and Other Land Remaining Other Land) and
thirty land-use change categories (e.g., Cropland Converted
to Forest Land, Grassland Converted to Forest Land,
Wetlands Converted to Forest Land, Settlements Converted
to Forest Land, Other Land Converted to Forest Lands)3
(IPCC 2006). The primary databases are the U.S. Department
of Agriculture (USDA) National Resources Inventory (NPJ)4
and the USDA Forest Service (USFS) Forest Inventory and
Analysis (FTA)5 Database. The U.S. Geological Survey
(USGS) National Land Cover Dataset (NLCD)6 is also
used to identify land uses in regions that were not included
in the NPJ or FIA. The total land area included in the U.S.
Inventory is 786 million hectares, and this entire land base is
considered managed.7 In 1990, the United States had a total
of 244 million hectares of Forest Land, 171 million hectares
of Cropland, 288 million hectares of Grassland, 28 million
hectares of Wetlands, 40 million hectares of Settlements, and
14 million hectares in the Other Land8 category (Table 7-5).
By 2007, the total area in Forest Land had increased by 3.7
percent to 253 million hectares, Cropland had declined by
4.0 percent to 163 million hectares, Grassland declined by
3.5 percent to 278 million hectares, Wetlands decreased by
2.4 percent to 28 million hectares, Settlements increased by
22.6 percent to 49 million hectares, and Other Land remained
at about 14 million hectares.
Dominant land uses vary by region, largely due to
climate patterns, soil types, geology, proximity to coastal
regions, and historical settlement patterns, although all
land-uses occur within each of the fifty states (Figure
7-1). Forest Land tends to be more common in the eastern
states, mountainous regions of the western United States,
and Alaska. Cropland is concentrated in the mid-continent
region of the United States, and Grassland is more common
in the western United States. Wetlands are fairly ubiquitous
throughout the United States, though they are more common
in the upper Midwest and eastern portions of the country.
Settlements are more concentrated along the coastal margins
and in the eastern states.
3 Land-use category definitions are provided in the Methodology section.
4NRI data is available at .
5 FIA data is available at .
6NLCD data is available at .
7The current land representation does not include areas from Alaska, U.S.
territories or federal lands in Hawaii, but there are planned improvements
to include these regions in future reports.
8 Other Land is a miscellaneous category that includes lands that are not
classified into the other five land-use categories. It also allows the total of
identified land areas to match the national area.
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-5: Land Use, Land-Use Change, and Forestry on Managed Land (Thousands of Hectares)
Land Use, Land-Use Change Categories
1990
1995
2000
2005
2006
2007
Total Forest Land 243,160
Forest Land Remaining Forest Land 238,088
Cropland Converted to Forest Land 1,147
Grassland Converted to Forest Land 3,401
Wetlands Converted to Forest Land 58
Settlements Converted to Forest Land 98
Other Lands Converted to Forest Land 368
Total Cropland 170,677
Cropland Remaining Cropland 155,478
Forest Land Converted to Cropland 1,105
Grassland Converted to Cropland 13,298
Wetlands Converted to Cropland 163
Settlements Converted to Cropland 470
Other Lands Converted to Cropland 162
Total Grassland 289,333
Grassland Remaining Grassland 279,318
Forest Land Converted to Grassland 1,514
Cropland Converted to Grassland 7,873
Wetlands Converted to Grassland 233
Settlements Converted to Grassland 133
Other Lands Converted to Grassland 262
Total Wetlands 28,545
Wetlands Remaining Wetlands 27,892
Forest Land Converted to Wetlands 140
Cropland Converted to Wetlands 139
Grassland Converted to Wetlands 322
Settlements Converted to Wetlands < 1
Other Land Converted to Wetlands 51
Total Settlements 39,548
Settlements Remaining Settlements 34,772
Forest Land Converted to Settlements 1,842
Cropland Converted to Settlements 1,373
Grassland Converted to Settlements 1,498
Wetlands Converted to Settlements 3
Other Land Converted to Settlements 60
Total Other Land 14,425
Other Land Remaining Other Land 13,437
Forest Land Converted to Other Land 193
Cropland Converted to Other Land 279
Grassland Converted to Other Land 458
Wetlands Converted to Other Land 55
Settlements Converted to Other Land 3
246,363
237,767
1,804
5,802
125
179
686
168,501
149,353
1,289
16,517
249
869
223
284,622
270,985
2,129
10,506
352
237
413
28,266
27,298
253
233
456
• z,wz
18,691
1.135
• 359|
Ł
248,993
235,855
2,842
8,691
193
278
1,135
163,914
143,816
1,027
17,623
267
889
293
281,748
262,679
3,136
14,585
359
276
712
28,456
26,907
406
371
726
3
43
48,160
33,999
5,777
3,738
4,397
31
218
14,427
12,171
545
473
1,105
123
11
251,441
238,335
2,863
8,574
192
288
1,188
163,236
145,573
806
15,514
234
825
283
279,282
261,555
2,858
13,517
345
270
738
28,151
26,591
415
363
736
3
43
49,285
35,011
5,873
3,673
4,479
32
217
14,304
12,061
560
499
1,058
114
12
252,252
239,111
2,871
8,600
193
289
1,188
163,195
145,533
805
15,513
234
825
283
278,762
261,105
2,846
13,463
344
269
735
27,960
26,408
412
360
734
3
43
49,255
34,982
5,873
3,673
4,479
32
217
14,275
12,033
559
499
1,057
114
12
252,927
239,755
2,878
8,623
194
290
1,188
163,183
145,522
805
15,513
234
825
283
278,273
260,676
2,837
13,415
343
268
734
27,817
26,272
409
358
732
3
43
49,248
34,975
5,873
3,672
4,479
32
217
14,250
12,009
559
499
1,057
114
12
Grand Total"
785,687
785,687
785,698
785,698 785,698 785,698
aThe total land changes over time because there is a net transfer of land from federal to non-federal ownership in Hawaii. Federal lands in Hawaii are not
currently included in the U.S. Land Representation, leading to a change in the land base overtime. There is a planned improvement to include land-use
data for federal lands in Hawaii, which will resolve the issue with a changing land base over time. In addition, area data for Hawaii are currently only
available through 1997 leading to no change in the federal land base after 1997.
Note: Managed and unmanaged lands are not differentiated in the current U.S. Land Representation Assessment. In addition, U.S. Territories along
with federal lands in Hawaii have not been classified into land uses and are not included in the U.S. land representation assessment. See planned
improvements for discussion on plans to include Alaska, territories and federal lands in Hawaii in future Inventories.
Land Use, Land-Use Change, and Forestry 7-5
-------
Figure 7-1
Percent of Total Land Area in the General Land Use Categories for 2007
Croplands
Grasslands
Wetlands
r\
r~A
Forest Lands
Settlements
Other Lands
D<10% •11%-30% D31%-50% D>50%
Note: Land use/land-use change categories were aggregated into the 6 general land-use categories based on the current use in 2007.
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Methodology
IPCC Approaches for Representing Land Areas
IPCC (2006) describes three approaches for representing
land areas. Approach 1 provides data on the total area for
each individual land-use category, but does not provide
detailed information on changes of area between categories
and is not spatially explicit other than at the national or
regional level. With Approach 1, total net conversions
between categories can be detected, but not the individual
changes between the land-use categories that led to those
net changes. Approach 2 introduces tracking of individual
land-use changes between the categories (e.g., forest
land to cropland, cropland to forest land, grassland to
cropland, etc.), using surveys or other forms of data that
do not provide location data on specific parcels of land.
Approach 3 extends Approach 2 by providing location data
on specific parcels of land, such as maps, along with the
land-use history. The three approaches are not presented as
hierarchical tiers and are not mutually exclusive.
According to IPCC (2006), the approach or mix of
approaches selected by an inventory agency should reflect
the calculation needs and national circumstances. For this
analysis, the NRI, FIA, and the NLCD have been combined
to provide a complete representation of land use for managed
lands. These data sources are described in more detail later in
this section. All of these datasets have a spatially-explicit time
series of land-use data, and therefore Approach 3 is used to
provide a full representation of land use in the U.S. Inventory.
Lands are treated as remaining in the same category (e.g.,
Cropland Remaining Cropland) if a land-use change has not
occurred in the last 20 years. Otherwise, the land is classified
in a land-use change category based on the current use and
most recent use before conversion to the current use (e.g.,
Cropland Converted to Forest Land).
Definitions of Land Use in the United States
Managed and Unmanaged Land
The U.S. definitions of managed and unmanaged lands
are similar to the basic IPCC (2006) definition of managed
land, but with some additional elaboration to reflect national
circumstances. Based on the following definitions, most lands
in the United States are classified as managed:
• Managed Land: Land is considered managed if direct
human intervention has influenced its condition.
Direct intervention includes altering or maintaining
the condition of the land to produce commercial or
non-commercial products or services; to serve as
transportation corridors or locations for buildings,
landfills, or other developed areas for commercial
or non-commercial purposes; to extract resources or
facilitate acquisition of resources; or to provide social
functions for personal, community or societal objectives.
Managed land also includes legal protection of lands
(e.g., wilderness, preserves, parks, etc.) for conservation
purposes (i.e., meets societal objectives).9
• Unmanaged Land: All other land is considered
unmanaged. Unmanaged land is largely comprised of
areas inaccessible to human intervention due to the
remoteness of the locations, or lands with essentially
no development interest or protection due to limited
personal, commercial or social value. Though these
lands may be influenced indirectly by human actions
such as atmospheric deposition of chemical species
produced in industry, they are not influenced by a direct
human intervention.10
Land-Use Categories
As with the definition of managed lands, IPCC
(2006) provides general non-prescriptive definitions for
the six main land-use categories: Forest Land, Cropland,
Grassland, Wetlands, Settlements and Other Land. In order
to reflect U.S. circumstances, country-specific definitions
have been developed, based predominantly on criteria used
in the land-use surveys for the United States. Specifically,
the definition of Forest Land is based on the FIA definition
of forest,11 while definitions of Cropland, Grassland, and
Settlements are based on the NPJ.12 The definitions for
9 Wetlands are an exception to this general definition, because these lands, as
specified by IPCC (2006), are only considered managed if they are created
through human activity, such as dam construction, or the water level is
artificially altered by human activity. Distinguishing between managed and
unmanaged wetlands is difficult, however, due to limited data availability.
Wetlands are not characterized by use within the NRI. Therefore, unless
wetlands are managed for cropland or grassland, it is not possible to know
if they are artificially created or if the water table is managed based on the
use of NRI data.
10 There will be some areas that qualify as forest land or grassland according
to the land use criteria, but are classified as unmanaged land due to the
remoteness of their location.
11 See .
12 See .
Land Use, Land-Use Change, and Forestry 7-7
-------
Other Land and Wetlands are based on the IPCC (2006)
definitions for these categories.
• Forest Land: A land-use category that includes land
that is at least 10 percent stocked13 by forest trees
of any size, or land formerly having such tree cover,
and not currently developed for a non-forest use. The
minimum area for classification as Forest Land is one
acre (0.40 ha). Roadside, stream-side, and shelterbelt
strips of timber must be at least 120 feet (36.58 m) wide
to qualify as Forest Land. Unimproved roads and trails,
streams and other bodies of water, or natural clearings
in forested areas are classified as Forest Land, if less
than 120 feet (36.58 m) in width or one acre (0.40 ha)
in size. Improved roads within Forest Land, however,
are extracted from forest area estimates and included
in Settlements. Grazed woodlands, fields reverting to
forest, and pastures that are not actively maintained are
included if the above qualifications are satisfied. Forest
Land consists of three main subcategories: timberland,
reserved forest land, and other forest land.14 Forest Land
also includes woodlands, which describes forest types
consisting primarily of species that have their diameter
measured at root collar, and for which there are no
site index equations, nor stocking guides. These may
include areas with degrees of stocking between 5 and
9.9 percent. The FIA regions with woodland areas are,
however, considering new definitions that should result
in all Forest Land meeting the minimum 10 percent
stocking threshold.
• Cropland: A land-use category that includes areas used
for the production of adapted crops for harvest, this
category includes both cultivated and non-cultivated
lands. Cultivated crops include row crops or close-
grown crops and also hay or pasture in rotation with
cultivated crops. Non-cultivated cropland includes
continuous hay, perennial crops (e.g., orchards) and
horticultural cropland. Cropland also includes land
with alley cropping and windbreaks,15 as well as lands
13 The percentage stocked refers to the degree of occupancy of land by trees,
measured either by basal area or number of trees by size and spacing or
both, compared to a stocking standard.
14 These subcategory definitions are fully described in the Forest Land
Remaining Forest Land section.
15 Currently, there is no data source to account for biomass C stock change
associated with woody plant growth and losses in alley cropping systems
and windbreaks in cropping systems, although these areas are included in
the cropland land base.
in temporary fallow or enrolled in conservation reserve
programs (i.e., set-asides16). Roads through Cropland,
including interstate highways, state highways, other
paved roads, gravel roads, dirt roads, and railroads are
excluded from Cropland area estimates and are, instead,
classified as Settlements.
• Grassland: A land-use category on which the plant cover
is composed principally of grasses, grass-like plants,
forbs, or shrubs suitable for grazing and browsing,
and includes both pastures and native rangelands. This
includes areas where practices such as clearing, burning,
chaining, and/or chemicals are applied to maintain the
grass vegetation. Savannas, some wetlands and deserts,
in addition to tundra are considered Grassland.17 Woody
plant communities of low forbs and shrubs, such as
mesquite, chaparral, mountain shrub, and pinyon-
juniper, are also classified as Grassland if they do not
meet the criteria for Forest Land. Grassland includes
land managed with agroforestry practices such as
silvipasture and windbreaks, assuming the stand or
woodlot does not meet the criteria for Forest Land.
Roads through Grassland, including interstate highways,
state highways, other paved roads, gravel roads, dirt
roads, and railroads are excluded from Grassland area
estimates and are, instead, classified as Settlements.
• Wetlands: Aland-use category that includes land covered
or saturated by water for all or part of the year. Managed
Wetlands are those where the water level is artificially
changed, or were created by human activity. Certain
areas that fall under the managed Wetlands definition
are covered in other areas of the IPCC guidance and/or
the inventory, including Cropland (e.g., rice cultivation),
Grassland, and Forest Land (including drained or
undrained forested wetlands).
• Settlements: A land-use category representing developed
areas consisting of units of 0.25 acres (0.1 ha) or
more that includes residential, industrial, commercial,
and institutional land; construction sites; public
administrative sites; railroad yards; cemeteries; airports;
golf courses; sanitary landfills; sewage treatment plants;
16A set-aside is cropland that has been taken out of active cropping and
converted to some type of vegetative cover, including, for example, native
grasses or trees.
17 IPCC (2006) guidelines do not include provisions to separate desert and
tundra as land categories.
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
water control structures and spillways; parks within
urban and built-up areas; and highways, railroads, and
other transportation facilities. Also included are tracts of
less than 10 acres (4.05 ha) that may meet the definitions
for Forest Land, Cropland, Grassland, or Other Land
but are completely surrounded by urban or built-up
land, and so are included in the settlement category.
Rural transportation corridors located within other land
uses (e.g., Forest Land, Cropland) are also included in
Settlements.
• Other Land: A land-use category that includes bare soil,
rock, ice, non-settlement transportation corridors, and
all land areas that do not fall into any of the other five
land-use categories. It allows the total of identified land
areas to match the managed national area.
Land Use Data Sources: Description
and Application to U.S. Land Area
Classification
U.S. Land Use Data Sources
The three main data sources for land area and use data
in the United States are the NRI, FIA, and the NLCD. For
the Inventory, the NRI is the official source of data on all
land uses on non-federal lands (except forest land), and is
also used as the resource to determine the total land base
for the conterminous United States and Hawaii. The NRI is
conducted by the USDA Natural Resources Conservation
Service and is designed to assess soil, water, and related
environmental resources on non-federal lands. The NRI
has a stratified multi-stage sampling design, where primary
sample units are stratified on the basis of county and township
boundaries defined by the U.S. Public Land Survey (Nusser
and Goebel 1997). Within a primary sample unit (typically
a 160-acre (64.75 ha) square quarter-section), three sample
points are selected according to a restricted randomization
procedure. Each point in the survey is assigned an area
weight (expansion factor) based on other known areas and
land-use information (Nusser and Goebel 1997). The NRI
survey utilizes data derived from remote sensing imagery and
site visits in order to provide detailed information on land
use and management, particularly for croplands, and is used
as the basis to account for C stock changes in agricultural
lands (except federal Grasslands). The NRI survey was
conducted every 5 years between 1982 and 1997, but
shifted to annualized data collection in 1998. This Inventory
incorporates data through 2003 from the NRI.
The FIA program, conducted by the USFS, is the official
source of data on Forest Land area and management data
for the Inventory. FIA engages in a hierarchical system of
sampling, with sampling categorized as Phases 1 through 3,
in which sample points for phases are subsets of the previous
phase. Phase 1 refers to collection of remotely-sensed data
(either aerial photographs or satellite imagery) primarily
to classify land into forest or non-forest and to identify
landscape patterns like fragmentation and urbanization.
Phase 2 is the collection of field data on a network of ground
plots that enable classification and summarization of area,
tree, and other attributes associated with forest land uses.
Phase 3 plots are a subset of Phase 2 plots where data on
indicators of forest health are measured. Data from all three
phases are also used to estimate C stock changes for forest
land. Historically, FIA inventory surveys had been conducted
periodically, with all plots in a state being measured at a
frequency of every 5 to 14 years. A new national plot design
and annual sampling design was introduced by FIA about
ten years ago. Most states, though, have only recently been
brought into this system. Annualized sampling means that a
portion of plots throughout each state is sampled each year,
with the goal of measuring all plots once every 5 years. See
Annex 3.12 to see the specific survey data available by state.
The most recent year of available data varies state by state
(2002 through 2007).
Though NRI provides land-area data for both federal
and non-federal lands, it only includes land-use data on
non-federal lands, and FIA only records data for forest
land.18 Consequently, major gaps exist when the datasets
are combined, such as federal grassland operated by the
Bureau of Land Management (BLM), USDA, and National
Park Service, as well as most of Alaska.19 Consequently, the
NLCD is used as a supplementary database to account for
land use on federal lands that are not included in the NRI
and FIA databases. The NLCD is a land-cover classification
scheme, available for 1992 and 2001, that has been applied
over the conterminous United States. For this analysis, the
18 FIA does collect some data on non-forest land use, but these are held in
regional databases versus the national database. The status of these data is
being investigated.
19The survey programs also do not include U.S. Territories with the exception
of non-federal lands in Puerto Rico, which are included in the NRI survey.
Furthermore, NLCD does not include coverage for U.S. Territories.
Land Use, Land-Use Change, and Forestry 7-9
-------
NLCD Retrofit Land Cover Change Product was used in
order to represent both land use and land-use change for
federal lands. It is based primarily on Landsat Thematic
Mapper imagery. The NLCD contains 21 categories of land
cover information, which have been aggregated into the
IPCC land-use categories, and the data are available at a
spatial resolution of 30 meters. The federal land portion of
the NLCD was extracted from the dataset using the federal
land area boundary map from the National Atlas.20 This map
represents federal land boundaries in 2005, so as part of the
analysis, the federal land area was adjusted annually based on
the NRI federal land area estimates (i.e., land is periodically
transferred between federal and non-federal ownership).
Consequently, the portion of the land base categorized with
NLCD data varied from year to year, corresponding to an
increase or decrease in the federal land base. The NLCD is
strictly a source of land-cover information, however, and
does not provide the necessary site conditions, crop types,
and management information from which to estimate C stock
changes on those lands.
Another step in the analysis is to address gaps, as well
as overlaps, in the representation of the U.S. land base
between the Agricultural Carbon Stock Inventory (Cropland
Remaining Cropland, Land Converted to Cropland, Grassland
Remaining Grassland, Land Converted to Grassland) and
Forest Land Carbon Stock Inventory (Forest Land Remaining
Forest Land and Land Converted to Forest Land), which
are based on the NRI and FIA databases, respectively.
NRI and FIA have different criteria for classifying forest
land, leading to discrepancies in the resulting estimates of
Forest Land area on non-federal land. Similarly, there are
discrepancies between the NLCD and FIA data for defining
and classifying Forest Land on federal lands. Moreover,
dependence exists between the Forest Land area and the
amount of land designated as other land uses in both the
NRI as well as the NLCD, such as the amount of Grassland,
Cropland and Wetland, relative to the Forest Land area.
This results in inconsistencies among the three databases for
estimated Forest Land area, as well as for the area estimates
for other land-use categories. FIA is the main database for
forest statistics, and consequently, the NRI and NLCD were
adjusted to achieve consistency with FIA estimates of Forest
Land. The adjustments were made at a state scale, and it was
assumed that the majority of the discrepancy in forest area
was associated with an under- or over-prediction of grassland
and wetland area in the NRI and NLCD due to differences in
Forest Land definitions. Specifically, the Forest Land area for
a given state according to the NRI and NLCD was adjusted to
match the FIA estimates of Forest Land for non-federal and
federal land, respectively. In a second step, corresponding
increases or decreases were made in the area estimates of
Grassland and Wetland from the NRI and NLCD, in order to
balance the change in forest area, and therefore not change the
overall amount of managed land within an individual state.
The adjustments were based on the proportion of land within
each of these land-use categories at the state level, (i.e., a
higher proportion of Grassland led to a larger adjustment in
Grassland area and vice versa).
As part of Quality Assurance/Quality Control (QA/QC),
the land base derived from the NRI, FIA, and NLCD was
compared to the U.S. Census Survey.21 The U.S. Census
Bureau gathers data on the U.S. population and economy,
and has a database of land areas for the country. The land
area estimates from the U.S. Census Bureau differ from
those provided by the land-use surveys used in the Inventory
because of discrepancies in the reporting approach for the
census and the methods used in the NRI, FIA and NLCD.
The area estimates of land-use categories, based on NRI, FIA
and NLCD, are derived from remote sensing data instead of
the land survey approach used by the U.S. Census Survey.
More importantly, the U.S. Census Survey does not provide
a time series of land-use change data or land management
information, which is critical for conducting emission
inventories and is provided from the NRI and FIA surveys.
Consequently, the U.S. Census Survey was not adopted as
the official land-area estimate for the Inventory. Rather the
NRI data were adopted given that this database provides full
coverage of land area for the conterminous United States and
Hawaii. Regardless, the total difference between the U.S.
Census Survey and the data sources used in the Inventory
is about 25 million hectares for the total land base of about
785 million hectares currently included in the Inventory, or a
3.1 percent difference. Much of this difference is associated
with open waters in coastal regions and the Great Lakes.
NRI does not include as much of the area of open waters in
these regions as the U.S. Census Survey.
20 See . 21 See .
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Approach for Combining Data Sources
The managed land base in the United States has been
classified into the six IPCC land-use categories using
definitions22 developed to meet national circumstances, while
adhering to IPCC (2006). In practice, the land was initially
classified into a variety of land-use categories using the NRI,
FIA and NLCD, and then aggregated into the thirty-six broad
land use and land use change categories identified in IPCC
(2006). Details on the approach used to combine data sources
for each land use are described below as are the gaps that will »
be reconciled as part of ongoing planned improvements:
• Forest Land: Both non-federal and federal forest lands
on both the continental United States and coastal Alaska
are covered by FIA. FIA is used as the basis for both
Forest Land area data as well as to estimate C stocks and
fluxes on Forest Land. Interior Alaska is not currently
surveyed by FIA, but NLCD has a new product for
Alaska that will be incorporated into the assessment as a
planned improvement for future reports. Forest Land in »
U.S. territories are currently excluded from the analysis,
but FIA surveys are currently being conducted on U.S.
territories and will become available in the future. NRI
is being used in the current report to provide Forest Land
areas on non-federal lands in Hawaii. Federal forest land
in Hawaii is currently excluded, but FIA data will be
collected in Hawaii in the future.
• Cropland: Cropland is classified using the NRI, which
covers all non-federal lands, within 49 states (excluding
Alaska), including state and local government-owned
land as well as tribal lands. NRI is used as the basis for
both Cropland area data as well as to estimate C stocks
and fluxes on Cropland. Cropland in U.S. territories
are excluded from both NRI data collection and the
NLCD. NLCD has a new product for Alaska that will
be incorporated into the assessment as a planned »
improvement for future reports.
• Grassland: Grassland on non-federal lands is classified
using the NRI within 49 states (excluding Alaska),
including state and local government-owned land as
well as tribal lands. NRI is used as the basis for both
Grassland area data as well as to estimate C stocks
and fluxes on Grassland. U.S. territories are excluded
from both NRI data collection and the current release
of the NLCD product. Grassland on federal Bureau of
Land Management lands, Department of Defense lands,
National Parks and within USFS lands are covered by
the NLCD, with the exception of federal grasslands in
Hawaii, which will be added as a planned improvement in
the future. In addition, federal and non-federal grasslands
in Alaska are currently excluded from the analysis,
but NLCD has a new product for Alaska that will be
incorporated into the assessment for future reports.
Wetlands: NRI captures wetlands on non-federal lands
within 49 states (excluding Alaska), while federal
wetlands are covered by the NLCD, with the exception
of federal lands in Hawaii, which will be added as a
planned improvement in the future. Alaska and U.S.
territories are excluded. This currently includes both
managed and unmanaged wetlands as no database has
yet been applied to make this distinction. See Planned
Improvements for details.
Settlements: The NRI captures non-federal settlement
area in 49 states (excluding Alaska). If areas of
Forest Land or Grassland under 10 acres (4.05 ha) are
contained within settlements or urban areas, they are
classified as Settlements (urban) in the NRI database.
If these parcels exceed the 10 acre (4.05 ha) threshold
and are Grassland, they will be classified as such by
NRI. Regardless of size, a forested area is classified as
nonforest by FIA if it is located within an urban area.
Settlements on federal lands are covered by NLCD,
with the exception of federal lands in Hawaii, which
will be added as a planned improvement in the future.
Settlements in U.S. territories are currently excluded
from NRI and NLCD. NLCD has a new product for
Alaska that will be incorporated into the assessment
as a planned improvement for future reports.
Other Land: Any land not falling into the other five land
categories and, therefore, categorized as Other Land
is classified using the NRI for non-federal areas in the
49 states (excluding Alaska) and NLCD for the federal
lands, with the exception of federal lands in Hawaii,
which will be added as a planned improvement in the
future. Other land in U.S. territories is excluded from
the NLCD. NLCD has a new product for Alaska that
will be incorporated into the assessment as a planned
improvement for future reports.
22 Definitions are provided in the previous section.
Land Use, Land-Use Change, and Forestry 7-11
-------
Some lands can be classified into one or more categories
due to multiple uses that meet the criteria of more than
one definition. However, a ranking has been developed for
assignment priority in these cases. The ranking process is
initiated by distinguishing between managed and unmanaged
lands. The managed lands are then assigned, from highest to
lowest priority, in the following manner:
Settlements > Cropland > Forest Land > Grassland >
Wetlands > Other Land
Settlements are given the highest assignment priority
because they are extremely heterogeneous with a mosaic
of patches that include buildings, infrastructure and travel
corridors, but also open grass areas, forest patches, riparian
areas, and gardens. The latter examples could be classified as
Grassland, Forest Land, Wetlands, and Cropland, respectively,
but when located in close proximity to settlement areas they
tend to be managed in a unique manner compared to non-
settlement areas. Consequently, these areas are assigned to
the Settlements land-use category. Cropland is given the
second assignment priority, because cropping practices tend
to dominate management activities on areas used to produce
food, forage or fiber. The consequence of this ranking is that
crops in rotation with grass will be classified as Cropland,
and land with woody plant cover that is used to produce
crops (e.g., orchards) is classified as Cropland, even though
these areas may meet the definitions of Grassland or Forest
Land, respectively. Similarly, Wetlands that are used for rice
production are considered Croplands. Forest Land occurs
next in the priority assignment because traditional forestry
practices tend to be the focus of the management activity in
areas with woody plant cover that are not croplands (e.g.,
orchards) or settlements (e.g., housing subdivisions with
significant tree cover). Grassland occurs next in the ranking,
while Wetlands and Other Land complete the list.
Priority does not reflect the level of importance for
reporting greenhouse gas emissions and removals on
managed land, but is intended to classify all areas into a single
land use. Currently, the IPCC does not make provisions in the
guidelines for assigning land to multiple uses. For example, a
Wetland is classified as Forest Land if the area has sufficient
tree cover to meet the stocking and stand size requirements.
Similarly, Wetlands are classified as Cropland if they are used
to produce a crop, such as rice. In either case, emissions from
Wetlands are included in the Inventory if human interventions
are influencing emissions from Wetlands, in accordance with
the guidance provided in IPCC (2006).
Recalculations/Revisions
Three major revisions were made in the current
Inventory for land representation.
• First, land uses were further disaggregated by land
use and land-use change categories as recommended
by IPCC (2006), which was possible with the new
NLCD Retrofit Product in combination with the NPJ
data. This change provides additional information on
land-use trends in the United States, and is expected to
improve estimation of greenhouse gas emissions and
transparency of the report.
• Second, rural transportation corridors were re-classified
as Settlements, instead of including these areas in the
Other Land category. Transportation corridors are
managed in a manner more similar to land use practices
typically associated with Settlements, and therefore
more aligned with this land-use category.
• Finally, the NPJ was adopted as the official land area
estimate for the U.S. Inventory. This change led to a
decline in the managed land base for the United States
because the NPJ does not include some of the open
water areas in the Great Lakes and ocean coastal regions.
Currently, there is no estimation of greenhouse gas
emissions associated with open waters of these regions
from the perspective of land use, and so this change
has no consequences on the estimates of anthropogenic
greenhouse gas emissions for the Inventory.
Planned Improvements
Area data by land-use category are not estimated for
major portions of Alaska, federal lands in Hawaii, or any
of the U.S. territories. A key planned improvement is to
incorporate land-use data from these areas in the National
Greenhouse Gas Emissions Inventory. For Alaska, a new
NLCD 2001 data product will be used to cover those land
areas presently omitted. Fortunately, most of the managed
land in the United States is included in the current land-use
statistics, but a complete accounting is a key goal for the near
future. Data sources will also be evaluated for representing
land use on federal lands in Hawaii and federal and non-
federal lands in U.S. territories.
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Additional work will be done to reconcile differences in
Forest Land estimates between the NRI and FIA, evaluating
the assumption that the majority of discrepancies in Forest
Land areas are associated with an over- or under-estimation
of Grassland and Wetland area. In some regions of the United
States, a discrepancy in Forest Land areas between NRI and
FIA may be associated with an over- or under-prediction of
other land uses.
There are also other databases that may need to be
reconciled with the NRI and NLCD datasets, particularly
for Settlements and Wetlands. Urban area estimates, used
to produce C stock and flux estimates from urban trees, are
currently based on population data (1990 and 2000 U.S.
Census data). Using the population statistics, "urban clusters"
are defined as areas with more than 500 people per square
mile. The USFS is currently moving ahead with an urban
forest inventory program so that urban forest area estimates
will be consistent with FIA forest area estimates outside of
urban areas, which would be expected to reduce omissions
and overlap of forest area estimates along urban boundary
areas. For Wetlands, the Army Corps of Engineers National
Inventory of Dams (NID) (ACE 2005) and the U.S. Fish
and Wildlife Service National Wetlands Inventory (NWI)23
databases are being evaluated and will be compared against
the NRI and NLCD. The NID and NWI may be used to refine
wetland area estimates for the U.S. Land Representation
assessment, including disaggregation of managed and
unmanaged wetlands.
7.2. Forest Land Remaining
Forest Land
Changes in Forest Carbon Stocks
(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, bark, seeds, and foliage. This category
includes live understory.
• Below ground 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 C (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
necessary for estimating C flux:
• Harvested wood products in use.
• Harvested wood products in solid waste disposal
sites (SWDS).
Carbon 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 in SWDS, the C contained
in the wood may be released many years or decades later, or
may be stored almost permanently in the SWDS.
This section quantifies the net changes in C stocks in
the five forest C pools and two harvested wood pools. The
3 See .
Land Use, Land-Use Change, and Forestry 7-13
-------
net change in stocks for each pool is estimated, and then the
changes in stocks are summed over all pools to estimate total
net flux. The focus on C implies that all C-based greenhouse
gases are included, and the focus on stock change suggests
that specific ecosystem fluxes do not need to be separately
itemized in this report. Disturbances from forest fires and
pest outbreaks are implicitly included in the net changes.
For instance, an inventory conducted after fire counts only
trees left. The change between inventories thus accounts for
the C changes due to fires; however, it may not be possible
to attribute the changes to the disturbance specifically. The
IPCC (2003) recommends reporting C stocks according to
several land-use types and conversions, specifically Forest
Land Remaining Forest Land and Land Converted to Forest
Land. Currently, consistent datasets are not available for the
entire United States to allow results to be partitioned in this
way. Instead, net changes in all forest-related land, including
non-forest land converted to forest and forests converted to
non-forest are reported here.
Forest C storage pools, and the flows between them via
emissions, sequestration, and transfers, are shown in Figure
7-2. In the figure, boxes represent forest C storage pools and
arrows represent flows between storage pools or between
storage pools and the atmosphere. Note that the boxes are
not identical to the storage pools identified in this chapter.
The storage pools identified in this chapter have been altered
in this graphic to better illustrate the processes that result in
transfers of C from one pool to another, and emissions to the
atmosphere as well as uptake from the atmosphere.
Approximately 33 percent (304 million hectares)
of the U.S. land area is forested (Smith et al. 2008). The
current forest inventory includes 250 million hectares in
the conterminous 48 states (USDA Forest Service 2008a,
2008b) that are considered managed and are included in this
Inventory. The additional forest lands are located in Alaska
and Hawaii. This Inventory includes approximately 3.8
million hectares of Alaska forest, which are in the southeast
and south central regions of Alaska and represent the majority
of the state's managed forest land. Survey data are not yet
available from Hawaii. While Hawaii and U.S. territories
have relatively small areas of forest land and will probably
not affect the overall C budget to a great degree, these
areas will be included as sufficient data becomes available.
Agroforestry systems are also not currently accounted for
in the Inventory, since they are not explicitly inventoried by
either of the two primary national natural resource inventory
Figure 7-2
Forest Sector Carbon Pools and Flows
Combustion from
forest fires (carbon
dioxide, methane)
Combustion from forest fires
(carbon dioxide, methane)
Processing
^^Consu
/ ^^
Legend
Carbon Pool
Carbon transfer or flux
Combustion
Source: Heath et al. 2003
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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).
Sixty-eight percent of U.S. forests (208 million hectares)
are classified as timberland, meaning they meet minimum
levels of productivity and are available for timber harvest.
Nine percent of Alaska forests andSl percent of forests in the
conterminous United States are classified as timberlands. Of
the remaining nontimberland forests, 30 million hectares are
reserved forest lands (withdrawn by law from management
for production of wood products) and 66 million hectares
are lower productivity forest lands (Smith et al. 2008).
Historically, the timberlands in the conterminous 48 states
have been more frequently or intensively surveyed than
other forest lands.
Forest land declined by approximately 10 million
hectares over the period from the early 1960s to the late
1980s. Since then, forest area has increased by about 8
million hectares. Current trends in forest area represent
average annual change of less than 0.2 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 that leads to an increased
rate of growth increases the eventual biomass density of
the forest, thereby increasing the uptake of C.24 Though
harvesting forests removes much of the aboveground C,
there is a positive growth to harvest ratio on U. S. timberlands
(AF&PA 2001). 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.
In the United States, improved forest management
practices, the regeneration of previously cleared forest areas,
as well as timber harvesting and use have resulted in net
uptake (i.e., net sequestration) of C each year from 1990
through 2007. The rate of forest clearing begun in the 17th
century following European settlement had slowed by the
late 19th century. Through the later part of the 20th century
many areas of previously forested land in the United States
were allowed to revert to forests or were actively reforested.
The impacts of these land-use changes still affect C fluxes
from these forest lands. More recently, the 1970s and 1980s
saw a resurgence of federally-sponsored forest management
programs (e.g., the Forestry Incentive Program) and soil
conservation programs (e.g., the Conservation Reserve
Program), which have focused on tree planting, improving
timber management activities, combating soil erosion, and
converting marginal cropland to forests. In addition to forest
regeneration and management, forest harvests have also
affected net C fluxes. Because most of the timber harvested
from U.S. forests is used in wood products, and many
discarded wood products are disposed of in SWDS rather than
by incineration, significant quantities of C in harvested wood
are transferred to long-term storage pools rather than being
released rapidly to the atmosphere (Skog and Nicholson
1998, Skog 2008). The size of these long-term C storage
pools has increased during the last century.
Changes in C stocks in U.S. forests and harvested wood
were estimated to account for net sequestration of 910.1 Tg
C02 Eq. (248.2 Tg C) in 2007 (Table 7-6, Table 7-7, Figure
7-3 and Table 7-8). 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
Figure 7-3
Estimates of Net Annual Changes in Carbon Stocks
for Major Carbon Pools
50 n
24 The term "biomass density" refers to the mass of live vegetation per
unit area. It is usually measured on a dry-weight basis. Dry biomass is 50
percent C by weight.
-300-
-350 J
Soil
i- CM co
if> to r-
Land Use, Land-Use Change, and Forestry 7-15
-------
Table 7-6: 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
(529.3)
(321.5)
(61.8)
(15.4)
(67.8)
(62.8)
(131.8)
(64.8)
(67.0)
(661.1)
1995
(568.
(390.
(78.
2)
9)
2)
(27.3)
(37.2)
(34.6)
(118.4)
(55.
(63.
(686.
.2)
2)
6)
2000
(399.
(352.
(71.
7)
1)
5)
(18.2)
(14.8)
56.9
(112.9)
(47.
(65.
(512.
0)
9)
6)
2005
(871.7)
(469.4)
(93.3)
(39.4)
(79.6)
(190.1)
(103.9)
(44.1)
(59.8)
(975.7)
2006
(791.7)
(442.7)
(88.9)
(35.6)
(68.7)
(155.9)
(108.6)
(45.2)
(63.3)
(900.3)
2007
(809.6)
(452.4)
(90.7)
(36.8)
(70.8)
(158.9)
(100.4)
(36.9)
(63.5)
(910.1)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, western Texas 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 7-7: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools
Carbon Pool 1990 1995 2000 2005 2006 2007
Forest (144.3) (155.0) (109.0) (237.7) (215.9) (220.8)
Aboveground Biomass (87.7) (106.6) (96.0) (128.0) (120.7) (123.4)
Belowground Biomass (16.8) (21.3) (19.5) (25.5) (24.2) (24.7)
Dead Wood (4.2) (7.4) (5.0) (10.7) (9.7) (10.0)
Litter (18.5) (10.1) (4.0) (21.7) (18.7) (19.3)
Soil Organic Carbon (17.1) (9.4) 15.5 (51.9) (42.5) (43.3)
Harvested Wood (35.9) (32.3) (30.8) (28.3) (29.6) (27.4)
Products in use (17.7) (15.1) (12.8) (12.0) (12.3) (10.1)
SWDS (18.3) (17.2) (18.0) (16.3) (17.3) (17.3)
Total Net Flux (180.3) (187.2) (139.8) (266.1) (245.5) (248.2)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, western Texas 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.
period. Overall, average C in forest ecosystem biomass sequestration over the interval 1990 to 2007 are the result
(aboveground and belowground) increased from 70 to 76 Mg of the sequences of new inventories for each state. C in
C/ha between 1990 and 2008 (see Annex 3-12 for average C forest ecosystem biomass had the greatest effect on total
densities by specific regions and forest types). Continuous, change through increases in C density and total forest land.
regular annual surveys are not available over the period for Management practices that increase C stocks on forest land,
each state; therefore, estimates for non-survey years were as well as afforestation and reforestation efforts, influence
derived by interpolation between known data points. Survey the trends of increased C densities in forests and increased
years vary from state to state, and national estimates are a forest land in the United States.
composite of individual state surveys. Therefore, changes in
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Stock estimates for forest and harvested wood C storage
pools are presented in Table 7-8. 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 7-4 shows
county-average C densities for live trees on forest land,
including both above- and belowground biomass.
Table 7-8: Forest Area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools
Forest Area (1000 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
245,697
40,011
14,378
2,860
2,541
4,558
15,675
1,783
1,193
590
41,794
1995
249,240
40,762
14,845
2,950
2,567
4,651
15,748
1,963
1,280
683
42,724
2000
251,732
41,475
15,365
3,055
2,597
4,690
15,767
2,124
1,355
769
43,599
2005
255,358
42,488
15,974
3,177
2,640
4,772
15,925
2,271
1,413
857
44,759
2006
256,227
42,726
16,102
3,203
2,651
4,794
15,977
2,296
1,423
873
45,023
2007
257,001
42,942
16,222
3,227
2,660
4,813
16,019
2,325
1,436
890
45,267
2008
257,787
43,163
16,346
3,252
2,670
4,832
16,063
2,353
1,446
907
45,515
Note: Forest area estimates include portions of Alaska. Forest C stocks do not include forest stocks in U.S. territories, Hawaii, western Texas, a large
portion of Alaska, 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
Smith et al. (2007, in press) 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 2006 requires estimates of C stocks for 2006 and 2007.
Figure 7-4
Average C Density in the Forest Tree Pool in the Conterminous United States, 2008
Live Tree
Mg C02 Eq./ha
D1-200
D 201^100
PI 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.)
Land Use, Land-Use Change, and Forestry 7-17
-------
Box 7-1: C02 Emissions from Forest Fires
Table 7-9: Estimates of C02 (Tg/yr) Emissions for the Lower 48 States
and Alaska3
Year
1990
C02 Emitted from C02 Emitted from C02 Emitted from
Wildfires in Prescribed Fires in Wildfires in Total C02
Lower 48 States Lower 48 States Alaska Emitted
(Tg/yr) (Tg/yr) (Tg/yr) (Tg/yr)
38.6
46.4
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 fires occurring in the
lower 48 states as well as in the proportion
of Alaska's managed forest land captured
in this Inventory. 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. Non-C02 greenhouse gas emissions from forest fires are also quantified in a
separate section below.
The IPCC (2003) methodology and IPCC (2006) default combustion factor for wildfire were employed to estimate C02 emissions from
forest fires. C02 emissions for wildfires and prescribed fires in the lower 48 states and wildfires in Alaska in 2007 were estimated to be 293.7
Tg C02/yr. This amount is masked in the estimate of net annual forest carbon stock change for 2007, however, because this net estimate
accounts for the amount sequestered minus any emissions.
2005
2006
2007
120.9
289.5
262.3
22.9
27.0
31.4
+ 143.8
+ 316.6
+ 293.7
+ Does not exceed 0.05 Tg C02 Eq.
a Note that these emissions have already been accounted for in the estimates of net annual
changes in C stocks, which account for the amount sequestered minus any emissions.
Methodology and Data Sources
The methodology described herein is consistent with
IPCC (2003, 2006) and IPCC/UNEP/OECD/IEA (1997).
Forest ecosystem C stocks and net annual C stock change
are determined according to stock-difference methods, which
involve applying C estimation factors to forest inventory
data and interpolating between successive inventory-based
estimates of C stocks. Harvested wood C estimates 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). An overview of the different methodologies
and data sources used to estimate the C in forest ecosystems
or harvested wood products is provided here. See Annex
3.12 for details and additional information related to the
methods and data.
Forest Ecosystem Carbon from Forest Inventory
Forest ecosystem stock and flux estimates are based on
the stock-difference method and calculations for all estimates
are in units of C. Separate estimates are made for the five
IPCC C storage pools described above. All estimates are
based on data collected from the extensive array of permanent
forest inventory plots in the United States as well as models
employed to fill gaps in field data. Carbon conversion factors
are applied at the disaggregated level of each inventory plot
and then appropriately expanded to population estimates. A
combination of tiers as outlined by Eggleston et al. (2006) is
used. The Tier 3 biomass C values are from forest inventory
tree-level data. The Tier 2 dead organic and soil C pools are
based on empirical or process models from the inventory
data. All carbon conversion factors are specific to regions or
individual states within the United States, which are further
classified according to characteristic forest types within
each region.
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 USDA Forest Service FIA program (Prayer
andFurnival 1999, USDAForest Service 2008a). Inventories
include data collected on permanent inventory plots on forest
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
lands25 and are organized as a number of separate datasets,
each representing a complete inventory, or survey, of an
individual state at a specified time. Some of the more recent
annual inventories reported for some states include "moving
averages" which means that a portion—but not all—of the
previous year's inventory is updated each year (USDA
Forest Service 2008d). Forest C calculations are organized
according to these state surveys, and the frequency of surveys
varies by state. All available datasets are identified for each
state starting with pre-1990 data where possible and including
all surveys since then. Since C stock change is based on
differences between successive surveys within each state,
accurate estimates of net C flux thus depend on consistent
representation of forest land between these successive
inventories. In order to achieve this consistency from 1990
to the present, state-level data are sometimes subdivided in
cases where the sum of sub-state inventories produces the
best whole-state represention of C change as discussed in
Smith et al. (2007).
The principal FIA datasets employed are freely available
for download at USDA Forest Service (2008b) as the
Forest Inventory and Analysis Database (FIADB) Version
3.0. However, to achieve consistent representation (spatial
and temporal), two other general sources of past FIA data
are included as necessary. First, older FIA plot- and tree-
level data—not in the current FIADB format—are used
if available. Second, 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. See USDA Forest Service (2008a)
for information on current and older data as well as additional
FIA Program features. A detailed list of the specific inventory
data used in this Inventory is in 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 FIADB-to-carbon calculator (Smith
et al. 2007, in press). The conversion factors and model
coefficients are categorized by region and forest type, and
forest C stock estimates are calculated from application of
25 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.
these factors at the scale of FIA inventory plots. The results
are estimates of C density (Mg C per hectare) for six forest
ecosystem pools: live trees, standing dead trees, understory
vegetation, down dead wood, forest floor, and soil organic
matter. The six carbon pools used in the FIADB-to-carbon
calculator are aggregated to the 5 carbon pools defined by
IPCC (2006): abovegroundbiomass,belowgroundbiomass,
dead wood, litter and soil organic matter. All non-soil pools
except forest floor are separated into aboveground and
below ground components. The live tree and understory C
pools are pooled as biomass, and standing dead trees and
down dead wood are pooled as dead wood, in accordance
with IPCC (2006).
Once plot-level C stocks are calculated as C densities
on Forest Land Remaining Forest Land for the five IPCC
(2006) reporting pools, the stocks are expanded to population
estimates according to methods appropriate to the respective
inventory data (for example, see USDA Forest Service
(2008d)). These expanded C stock estimates are summed to
state or sub-state total C stocks. Annualized estimates of C
stocks are developed by using available FIA inventory data
and interpolating or extrapolating to assign a C stock to each
year in the 1990 through 2008 time series. Flux, or net annual
stock change, is estimated by calculating the difference
between two successive years and applying the appropriate
sign convention; net increases in ecosystem C are identified
as negative flux. By convention, inventories are assigned to
represent stocks as of January 1 of the inventory year; an
estimate of flux for 1996 requires estimates of C stocks for
1996 and 1997, for example. For this Inventory, 2008 stock
and 2007 flux are based on extrapolation of the average of
the most recent three years of interpolated flux in the time
series. Additional discus sion of the use of FIA inventory data
and the C conversion process is in Annex 3.12.
Carbon in Biomass
Live tree C pools include aboveground and below ground
(coarse root) biomass of live trees with diameter at 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
below ground 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 C in these
plots is estimated from plot-level volume of merchantable
Land Use, Land-Use Change, and Forestry 7-19
-------
wood, or growing-stock volume, of live trees, which is
calculated from updates of Smith et al. (2003). These biomass
conversion and expansion factors (BCEFs) are applied to
about 5 percent of the inventory records, all of which are
pre-1998 data. 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.
This applies to an additional 3 percent of inventory records,
which represent older (pre-1998) non-timberlands.
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). Understory
frequently represents over 1 percent of C in biomass, but its
contribution rarely exceeds 2 percent of the total.
Carbon in Dead Organic Matter
Dead organic matter is initially calculated as three
separate pools with C stocks modeled from inventory data.
Estimates are specific to regions and forest types within each
region, and stratification of forest land for dead organic matter
calculations is identical to that used for biomass through the
state and sub-state use of FIA data as discussed above. 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.
Calculations are BCEF-like factors based on updates of Smith
et al. (2003). 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).
Carbon in Forest Soil
Soil organic C 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), which includes
region and soil type information. SOC determination is based
on the general approach described by Amichev and Galbraith
(2004). Links to FIA inventory data were developed with the
assistance of the USDAForest Service FIA Geospatial Service
Center by overlaying FIA forest inventory plots on the soil C
map. This method produced mean SOC densities stratified
by region and forest type group. It did not provide separate
estimates for mineral or organic soils but instead weighted their
contribution to the overall average based on the relative amount
of each within forest land. Thus, forest SOC is a function of
species and location, and net change also depends on these
two factors as total forest area changes. In this respect, SOC
provides a country-specific reference stock for 1990-present,
but it does not reflect effects of past land use.
Harvested Wood Carbon
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
(2008) using the WOODCARBII model. These methods are
based on IPCC (2006) guidance for estimating HWP C.
IPCC (2006) provides methods that allow Parties to report
HWP Contribution using one of several different accounting
approaches: production, stock change and atmospheric flow,
as well as a default method that assumes there is no change in
HWP C stocks (see Annex 3.12 for more details about each
approach). The United States uses the production accounting
approach to report HWP Contribution. Under the production
approach, 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 reported U.S. HWP estimates
are based on the production approach, 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
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).
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
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
the exception that additions 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, 2007). 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.
There are 5 annual HWP variables that are used in varying
combinations to estimate HWP Contribution using any one of
the three main approaches listed above. These are:
(1A) annual change of C in wood and paper products in
use in the United States,
(IB) annual change of C in wood and paper products in
SWDS in the United States,
(2A) annual change of C in wood and paper products
in use in the United States and other countries
where the wood came from trees harvested in the
United States,
(2B) annual change of C in wood and paper products
in SWDS in the United States and other countries
where the wood came from trees harvested in the
United States,
(3) C in imports of wood, pulp, and paper to the United
States,
(4) C in exports of wood, pulp and paper from the
United States, and
(5) C in annual harvest of wood from forests in the
United States.
The sum of variables 2A and 2B yields the estimate
for 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
A quantitative uncertainty analysis placed bounds
on current flux for forest ecosystems as well as carbon in
harvested wood products through Monte Carlo simulation
of the methods described above and probabilistic sampling
of carbon conversion factors and inventory data. See Annex
3.12 for additional information. The 2007 flux estimate for
forest C stocks is estimated to be between -736 and -1083
Tg CO2 Eq. at a 95 percent confidence level. (See Table
7-10). This includes a range of -638 to -981 Tg CO2 Eq.
in forest ecosystems and -76 to -127 Tg CO2 Eq. for HWP.
The relatively smaller range of uncertainty, in terms of
percentage, for the total relative to the two separate parts in
because the total is based on summing the two independent
uncertain parts.
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,
Table 7-10: 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
2007 Flux Estimate Uncertainty Range Relative to Flux Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
(809.6)
(100.4)
(910.1)
Lower Bound
(980.9)
(127.0)
(1,083.1)
Upper Bound
(637.5)
(76.2)
(735.6)
Lower Bound
-21%
-26%
-19%
Upper Bound
+21%
+24%
19%
a Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate negative values or net sequestration.
Land Use, Land-Use Change, and Forestry 7-21
-------
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 2008c).
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 2008d). 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 IPCC (2006).
Estimates of annual C change in solidwood and paper
products in use were 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 half 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 basic models used to estimate forest ecosystem and
HWP C stocks and change are largely unchanged from the
previous Inventory (Smith et al. 2007, Skog 2008). Most of
the estimates for 1990-present are relatively similar to the
values previously reported (EPA 2008). However, changes in
underlying FIA data have driven some changes in estimates
across the time series. Most states have added new inventory
data or modified some of the information in previously existing
surveys and the FIADB format changed to version 3.0 (USDA
Forest Service 2008b). The change to FIADB 3.0 resulted in
three broad changes to the carbon calculation methods of Smith
et al. (2007), affecting: (1) expansion of plot-level carbon to
total carbon stocks; (2) the more complete use of the moving
averages; and (3) the method of extrapolating stock and stock
change, which is related to the use of the moving averages.
See Smith et al. (2007, in press) for further discussion. The
plot-level carbon conversion process is essentially unchanged.
However, the process for expanding carbon to the totals used
for determining net stock change is modified somewhat from
Smith et al. (2007) according to methods described in the
current FIADB user's guide (USDA Forest Service 2008d,
Smith et al. in press).
The increasing number of annual inventory reports
from moving averages (USDA Forest Service 2008b),
especially in the eastern U.S., are incorporated into this
year's Inventory (see Annex 3.12). The newly available
annual inventory data necessitated the second broad update
to the carbon calculator, which was to incorporate the use of
all of these annual data summaries. Their use was minimized
in previous forest carbon inventories (Smith et al. 2007, in
press). Moving averages have the potential for greater inter-
annual variability in stocks for some states, which in turn can
have an even greater effect on carbon change because of the
greater sensitivity in change (Smith et al. 2007). That is, a
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
very small change in stock can have a tremendous effect on
stock change, which is based on a small difference between
two very large values. The use of the moving averages and
the related sensitivity of stock change led to the third general
change in the calculator, which is the method of extrapolation
applied. Extrapolated values are based on short-term trends
rather than being subject to a single year.
Most of these changes in data sources or methodology
had only minor effects on estimates for 1990-present. A
notable exception is the spike in net annual changes in C
stocks for forest ecosystem C after 2000; this spike occurs
in all five forest ecosystem pools to different degrees.
Carbon change estimates generated for 2002 through 2006
are notably greater than the corresponding values from the
previous Inventory. At the same time, the three previous
years (1999, 2000, and 2001) show a slight decrease
relative to values reported in the 1990-2006 Inventory.
This combined effect is largely associated with forest areas
reported by surveys over that interval and is a product of the
interpolated stock differences from the FIADB. Comparing
the relative rates of change in area versus overall C density
for all forest carbon pools for 1990-2007 illustrates that the
rate of change for carbon density is relatively steady, but the
rate of change for area fluctuates considerably. Extrapolated
portions of the 1990-present estimates are subject to change
as new data become available and they generally include
greater uncertainty. However, most of the increased carbon
sequestration over 2000-2003 is based on interpolation
between stocks because only 6 percent of the carbon change
reported for 2003 is based on extrapolated values.
The uncertainty analysis for forest ecosystem carbon
stock change has been revised. It is now possible to estimate
sampling errors associated with each of the specific carbon
pools reported here; this has been incorporated into the
current uncertainty analysis (see Annex 3.12).
Planned Improvements
The ongoing annual surveys by the FIA Program will
improve precision of forest C estimates as new state surveys
become available (USDAForest Service 2008a). The annual
surveys will eventually include all states. To date, four
states are not yet reporting any data from the annualized
sampling design of FIA: Hawaii, Oklahoma, New Mexico,
and Wyoming. Estimates for these states are currently based
on older, periodic data. Hawaii and U.S. territories will also
be included when appropriate forest C data are available. In
addition, the more intensive sampling of down dead wood,
litter, and soil organic C on some of the permanent FIA plots
continues and will substantially improve resolution of C pools
at the plot level for all U. S. forest land when this information
becomes available. Improved resolution, incorporating more
of Alaska's forests, and using annualized sampling data as
it becomes available for those states currently not reporting
are planned for future reporting.
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, Woodbury
et al. 2007). 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, but long-term residual
effects on soil and forest floor C stocks are likely after land-
use change. Estimates of such effects depend on identifying
past land use changes associated with forest lands.
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 in a nation-wide inventory, as well
as the means for entity-level reporting.
Non-C02 Emissions from Forest Fires
Emissions of non-CO2 gases from forest fires were
estimated using the default IPCC (2003) methodology
and default IPCC (2006) combustion factor for wildfires.
Emissions from this source in 2007 were estimated to be
29.0 Tg CO2 Eq. of CH4 and 2.9 Tg CO2 Eq. of N2O, as
shown in Table 7-11 and Table 7-12. The estimates of non-
CO2 emissions from forest fires account for wildfires in the
lower 48 states and Alaska as well as prescribed fires in the
lower 48 states.
Land Use, Land-Use Change, and Forestry 7-23
-------
Table 7-11: Estimated Non-C02 Emissions from Forest Fires (Tg C02 Eq.) for U.S. Forests3
Gas
1990
1995
2000
2005
2006
2007
CH4
N20
4.6
0.5
Total
5.1
14.2
1.4
15.6
'Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003, 2006).
31.3
3.2
34.4
29.0
2.9
31.9
'Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003, 2006).
Table 7-12: Estimated Non-C02 Emissions from Forest Fires (Gg) for U.S. Forests3
Gas
CH4
N20
1990
218
2
1995
293
2
2000
983
y|
2005
676
5
2006
1,489
10
2007
1,381
9
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 (Table 7-13) from forest burned by
gas-specific emissions ratios and conversion factors. N2O
emissions were calculated in the same manner, but were also
multiplied by an N-C ratio of 0.01 as recommended by IPCC
(2003). The equations used were:
CtLj Emissions = (C released) x (emission ratio) x 16/12
N2O Emissions = (C released) x (N/C ratio) x
(emission ratio) x 44/28
Estimates for C emitted from forest fires are the same
estimates used to generate estimates of CO2 emissions from
forest fires, presented earlier in Box 7-1. Estimates for C
emitted include emissions from wildfires in both Alaska
and the lower 48 states as well as emissions from prescribed
fires in the lower 48 states only (based on expert judgment
that prescribed fires only occur in the lower 48 states)
(Smith 2008a). The IPCC (2006) default combustion factor
of 0.45 for "all 'other' temperate forests" was applied in
estimating C emitted from both wildfires and prescribed fires.
See the explanation in Annex 3.12 for more details on the
methodology used to estimate C emitted from forest fires.
Table 7-13: Estimated Carbon Released from
Forest Fires for U.S. Forests
Year
C Emitted (Tg/yr)
2000
2005
2006
2007
61.4
^
42.3
93.0
86.3
Uncertainty
Non-CO2 gases emitted from forest fires depend on
several variables, including: forest area for Alaska and the
lower 48 states; average carbon densities for wildfires in
Alaska, wildfires in the lower 48, and prescribed fires in
the lower 48; 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
information about the uncertainty surrounding each of these
variables. The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 7-14.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-14: Quantitative Uncertainty Estimates of Non-C02 Emissions from Forest Fires in Forest Land Remaining
Forest Land (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Non-C02 Emissions
from Forest Fires
Non-C02 Emissions
from Forest Fires
CH4
N20
29.0
2.9
Lower Bound
7.7
0.8
Upper Bound
73.9
7.4
Lower Bound
-73%
-73%
Upper Bound
+ 155%
+ 152%
QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted
consistent with the U.S. QA/QC plan. Source-specific quality
control measures for forest fires included checking input data,
documentation, and calculations to ensure data were properly
handled through the inventory process. Errors that were found
during this process were corrected as necessary.
Recalculations Discussion
Based on new data from the FIA National Program,
average carbon density for Alaska was updated from 331 Mg/
ha to 179 Mg/ha and for the lower 48 states from 89 Mg/ha to
91 Mg/ha. The previous value of 331 Mg/ha for Alaska was
from a much smaller subset of Alaskan forest. The updated
density values correspond directly to the forest land that the
U.S. Forest Service uses to report carbon. Emissions from
prescribed fires were included in the totals this year. Reported
area burned for prescribed fires was taken from the National
Interagency Fire Center and an average carbon density value
of 30 Mg/ha was used based on expert judgment within the
U.S. Forest Service. The IPCC (2006) default combustion
factor for "all 'other' temperate forests" of 0.45 was used
in place of the 0.40 factor previously used. Data for land
area under wildland fire protection for the year 2006 was
obtained from the National Association of State Foresters
State Forestry Statistics 2006 Report. This affected emission
estimates across the time series. See explanation in Annex
3.12 for more details on the methodology used to estimate
land area under wildland fire protection for the time series.
Based on expert judgment, new uncertainty parameters were
applied, including updated uncertainty percentages and
distributions surrounding the variables used in estimating
emissions. These changes resulted in a wider uncertainty
range relative to the previous Inventory.
Planned Improvements
The default combustion factor of 0.45 from IPCC
(2006) was applied in estimating C emitted from both
wildfires and prescribed fires. Additional research into the
availability of a combustion factor specific to prescribed
fires will be conducted.
Direct N20 Fluxes from Forest Soils
(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. N2O emissions from forest soils are
estimated to have increased by a multiple of 5.7 from 1990 to
2007. 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 7-15.
Land Use, Land-Use Change, and Forestry 7-25
-------
Table 7-15: N20 Fluxes from Soils in Forest Land
Remaining Forest Land (Tg C02 Eq. and Gg N20)
Year
Tg C02 Eq.
Gg
1990
0.0
0.2
2005
2006
2007
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 Forest Land Remaining Forest Land and from
Land Converted to Forest Land.
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 is in the southeastern United
States. 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 (Albaugh et al., 2007).
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
weighted average of the reported range of N fertilization
rates (121 Ibs. N per acre). Datafor areas of forests receiving
fertilizer outside the southeastern United States were not
available, so N additions to non-southeastern forests are
not included here. Area data for pine plantations receiving
fertilizer in the Southeast were not available for 2005, 2006
and 2007, so data from 2004 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, oxygen gas 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.
IPCC (2006) does not incorporate any of these variables into
the default methodology 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 estimated. However, the
total quantity of organic N inputs to soils is included in the
Agricultural Soil Management and Settlements Remaining
Settlements sections.
Uncertainties exist in the fertilization rates, annual
area of forest lands receiving fertilizer, and the emission
factors. Fertilization rates were assigned a default level26
of uncertainty at +50 percent, and area receiving fertilizer
was assigned a +20 percent according to expert knowledge
(Binkley 2004). IPCC (2006) provided estimates for the
uncertainty associated with the direct N2O emission factor
for synthetic N fertilizer application to soils. Quantitative
uncertainty of this source category was estimated through
the IPCC-recommended Tier 2 uncertainty estimation
methodology. The uncertainty ranges around the 2005
activity data and emission factor input variables were directly
applied to the 2007 emissions estimates. The results of the
quantitative uncertainty analysis are summarized in Table
7-16. N2O fluxes from soils were estimated to be between
0.1 and 1.0 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 59 percent below and 211 percent above
the 2007 emission estimate of 0.3 Tg CO2 Eq.
26 Uncertainty is unknown for the fertilization rates so a conservative value
of ±50% was used in the analysis.
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-16: Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land Remaining Forest Land
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (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
1.0
-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.
Recalculations Discussion
Number of acres fertilized and fertilizer application
rate data for plantations in the southeastern United States
receiving N fertilizer were updated based on Albaugh et al.
(2007) from the previous Inventory. This resulted in a small
decrease (less than 10 percent on average) in emissions
compared to the previous Inventory.
Planned Improvements
State-level area data will be acquired for southeastern
pine plantations receiving fertilizer to estimate soil N2O
emission by state and provide information about regional
variation in emission patterns.
7.3. 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 CO2 or N2O fluxes on Land Converted
to Forest Land from fluxes on Forest Land Remaining Forest
Land at this time.
7.4. Cropland Remaining Cropland
(IPCC Source Category 5B1)
Mineral and Organic Soil Carbon
Stock Changes
Soils contain both organic and inorganic forms of C, but
soil organic C (SOC) stocks are the main source and sink
for atmospheric CO2 in most soils. Changes in inorganic C
stocks are typically minor. In addition, SOC 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 (2006) recommends
reporting changes in SOC stocks due to agricultural land-use
and management activities on mineral and organic soils.27
Typical well-drained mineral soils contain from 1 to
6 percent organic C by weight, although 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 of 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
27 CO2 emissions associated with liming are also estimated but are included
in a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-27
-------
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
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.
Cropland Remaining Cropland includes all cropland
in an inventory year that had been cropland for the last 20
years28 according to the USDA NRI land use survey (USDA-
NRCS 2000). Consequently, the area of Cropland Remaining
Cropland changes through time with land-use change. CO2
emissions and removals29 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 2003 due to Conservation Reserve Program
enrollment). Emissions from organic soils are estimated using
a Tier 2 IPCC method.
Of the two 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
2007 (see Table 7-17 and Table 7-18). In 2007, mineral
soils were estimated to remove 47.3 Tg CO2 Eq. (12.9 Tg
C). This rate of C storage in mineral soils represented about
a 17 percent decrease in the rate since the initial reporting
year of 1990. Emissions from organic soils were 27.7 Tg
CO2 Eq. (7.5 Tg C) in 2007. In total, U.S. agricultural soils
in Cropland Remaining Cropland removed approximately
19.7 Tg C02 Eq. (5.4 Tg C) in 2007.
The net reduction in soil carbon accumulation over the
time series (33 percent for 2007, relative to 1990) was largely
due to the declining influence of annual cropland enrolled
in the Conservation Reserve Program, which began in the
late 1980s. However, there were still positive increases
in C stocks from land enrolled in the reserve program, as
well as 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).
The spatial variability in annual CO2 flux associated with
C stock changes in mineral and organic soils is displayed
in Figure 7-5 and Figure 7-6. The highest rates of net C
accumulation in mineral soils occurred in the Midwest, which
is the area with the largest amounts of cropland managed with
conservation tillage. Rates were also high in the Great Plains
due to enrollment in the Conservation Reserve Program.
28 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began, and consequently the classifications
were based on less than 20 years from 1990 to 2001.
29 Note that removals occur through crop and forage uptake of CO2 into
biomass C that is later incorporated into soil pools.
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-17: Net C02 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C02 Eq.)
Soil Type
1990
1995
2000
2005
2006
2007
Mineral Soils3
Organic Soils
(56.8)
27.4
(50.6)
27.7
(57.9)
27.7
(45.9)
27.7
(46.8)
27.7
(47.3)
27.7
Total Net Flux3
(29.4)
(22.9)
(30.2)
(18.3) (19.1) (19.7)
'Preliminary estimates that will be finalized after public review period following completion of quality control measures.
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.
Table 7-18: Net C02 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C)
Soil Type
1990
1995
2000
2005
2006 2007
Mineral Soils3
Organic Soils
(15.5)
7.5
(13.8)
7.5
(15.8)
7.5
(12.5)
7.5
(12.8)
7.5
(12.9)
7.5
Total Net Flux3
(8.0)
(6.3)
(8.2)
(5.0)
(5.2) (5.4)
'Preliminary estimates that will be finalized after public review period following completion of quality control measures.
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.
Figure 7-5
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States,
2007, Cropland Remaining Cropland
Tg C02 Eq./year
D>0
D-0.1 too
O ^-^-^ ^ / \ j D-0.5to-0.1
D-1to-0.5
D-2to-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.
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 description of the
methodology used to estimate changes in soil C stocks due
to: (1) agricultural land-use and management activities on
Land Use, Land-Use Change, and Forestry 7-29
-------
Figure 7-6
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States,
2007, Cropland Remaining Cropland
Tg C02 Eq./year
>2
• lto2
D0.5to1
D0.1to0.5
DO to 0.1
O No organic soils
Note: Values greater than zero represent emissions.
mineral soils; and (2) agricultural land-use and management
activities on organic soils 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 Cropland,
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 approximately
260,000 points in agricultural land for the conterminous
United States and Hawaii.30 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 originally collected for each NRI point on
a 5-year cycle beginning in 1982. For cropland, data were
collected for 4 out of 5 years in the cycle (i.e., 1979-1982,
1984-1987, 1989-1992, and 1994-1997). However, the
NRI program began collecting annual data in 1998, and
data are currently available through 2003. NRI points were
classified as Cropland Remaining Cropland in a given year
between 1990 and 2007 if the land use had been cropland
for 20 years.31 Cropland includes all land used to produce
food and fiber, or forage that is harvested and used as feed
(e.g., hay and silage).
Mineral Soil Carbon Stock Changes
An IPCC 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. The remaining
crops on mineral soils were estimated using an IPCC Tier
2 method (Ogle et al. 2003), including 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 (greater than 35 percent by
30 NRI points were classified as agricultural if under grassland or cropland
management between f 990 and 2003.
31 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began. Therefore, the classification prior to
2002 was based on less than 20 years of recorded land-use history for the
time series.
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
volume). 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,
accounting for enrollment patterns in the Conservation
Reserve Program after 2003, which was not addressed by
the Tier 3 methods.
Further elaboration on the methodology and data used
to estimate stock changes from mineral soils 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 an input, along with information about soil physical
properties. Input data on land use and management are
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, 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
(NPJ) survey.
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 then adjusted using county-level estimates of
manure available for application in other years. Specifically,
county-scale ratios of manure available for application to
soils in other years relative to 1997 were used to adjust
the area amended with manure (see Annex 3.13 for further
details). Greater availability of managed manure N relative to
1997 was, thus, assumed to increase the area amended with
manure, while reduced availability of manure N relative to
1997 was assumed to reduce the amended area. The amount
of manure produced by each livestock type was calculated for
managed and unmanaged waste management systems based
on methods described in the Manure Management section
(Section 6.2) and annex (Annex 3.10).
Manure amendments were an input to the Century
Model based on manure N available for application from
all managed or unmanaged systems except Pasture/Range/
Paddock.32 Data on the county-level N available for
application were estimated for managed systems based on
the total amount of N excreted in manure minus N losses
and including the addition of N from bedding materials. N
losses include direct nitrous oxide emissions, volatilization of
ammonia and NOX, runoff and leaching, and poultry manure
used as a feed supplement. More information on these losses
is available in the description of the Manure Management
source category. Animal-specific bedding factors were set
equal to IPCC default factors (IPCC 2006). For unmanaged
systems, it is assumed that no N losses or additions occur.
Monthly weather data were used as an input in the model
simulations, based on an aggregation of gridded weather data
to the county scale from the Parameter-elevation Regressions
on Independent Slopes Model (PRISM) database (Daly et
al. 1994). Soil attributes, which were obtained from an NRI
database, were assigned based on field visits and soil series
descriptions. Each NRI point was run 100 times as part of
the uncertainty assessment, yielding a total of over 18 million
32 Pasture/Range/Paddock manure additions to soils are addressed in
the Grassland Remaining Grassland and Land Converted to Grassland
categories.
Land Use, Land-Use Change, and Forestry 7-31
-------
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 classes 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 under the IPCC classification). 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. Delayed responses 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 trends in soil C stocks only capture discrete changes in management and/or land use, rather than a longer term trend
such as gradual increases in crop productivity.
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). C stocks and 95 percent confidence
intervals were estimated for each year between 1990 and
2003, but C stock changes from 2004 to 2007 were assumed
to be similar to 2003 because no additional activity data are
currently available from the NRI for the latter years.
Tier 2 Approach
In the IPCC 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). 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 (2003,2006). 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). 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
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 2007 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 2007 were adjusted to account for additional C stock
changes associated with gains or losses in soil C after 2003
due to changes in Conservation Reserve Program enrollment.
The change in enrollment acreage relative to 2003 was based
on data from USDA-FSA (2007) for 2004 through 2007,
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 (2003, 2006), with 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 1997
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 2007.
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). Uncertainty estimates are presented in Table 7-19 for
Table 7-19: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Cropland Remaining
Cropland (Tg C02 Eq. and Percent)
2007 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source (Tg C02 Eq.) (Tg C02 Eq.) (%)
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 2003)
Organic Soil C Stocks: Cropland Remaining Cropland,
Tier 2 Inventory Methodology
(42.3)
(3.0)
(2.0)
27.7
Lower
Bound
(69.6)
(6.9)
(3.0)
15.8
Upper
Bound
(15.1)
0.8
(1.0)
36.9
Lower
Bound
-64%
-127%
-50%
-43%
Upper
Bound
+64%
+ 128%
+50%
+33%
Combined Uncertainty for Flux Associated with
Agricultural Soil Carbon Stock Change in Cropland
Remaining Cropland
(19.7)
(49.6)
9.4
-152% +148%
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
Land Use, Land-Use Change, and Forestry 7-33
-------
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). Uncertainty for the portions of the
Inventory estimated with Tier 2 and 3 approaches was derived
using a Monte Carlo approach (see Annex 3.13 for further
discussion). A combined uncertainty estimate for changes in
soil C stocks 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 are in Annex 3.13. The combined uncertainty
for soil C stocks in Cropland Remaining Cropland ranged
from 152 percent below to 148 percent above the 2007 stock
change estimate of -19.7 Tg CO2 Eq.
QA/QC and Verification
Quality control measures included checking input data,
model scripts, and results to ensure data were properly
handled throughout the inventory process. Several errors
were found in the implementation of the new annual
NRI data, mostly involving problems in scheduling crops
and practices with the more detailed histories; corrective
actions were taken to deal with the errors. As discussed
in the uncertainty section, 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
Annual survey data from the USDA National Resources
Inventory (NRI) were incorporated into this year's estimates.
This resulted in several changes to the inventory methods:
First, the availability of new data extended the time
series of activity data beyond 1997 to 2003,33 In previous
Inventories, activity data were only available through 1997,
and so subsequent years were treated as the same land use
practice occurring in 1997.
Second, annual area data, rather than area data that had
been collected in 5-year increments, were used to estimate
soil C stock changes, leading to more accurate estimates.
Third, each NRI point was simulated separately, instead
of simulating clusters of points that had common cropping
rotation histories and soil characteristics in a county. More
importantly, the exact cropping histories were simulated,
instead of generalized cropping rotations (e.g., wheat-fallow,
corn-soybean).
Overall, the recalculations resulted in an average annual
decline in soil organic C stocks of 12.5 Tg CO2 Eq. for
the period 1990 through 2006, compared to the previous
Inventory. Uncertainties were also higher in this year's
Inventory because soil C stock changes were estimated for
each year from new annual NRI data. Previous Inventories
took an average of changes over 5-year periods.
CO2 Emissions from Liming of
Agricultural Soils
IPCC (2006) recommends reporting CO2 emissions from
lime additions (in the form of crushed limestone (CaCO3)
and dolomite (CaMg(CO3)2) to agricultural soils. Limestone
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. Emissions from liming have
fluctuated over the past sixteen years, ranging from 3.8 Tg
CO2 Eq. to 5.0 Tg CO2 Eq. In 2007, liming of agricultural
soils in the United States resulted in emissions of 4.1 Tg CO2
Eq. (1.1 Tg C), representing about a 13 percent decrease
in emissions since 1990 (see Table 7-20 and Table 7-21).
The trend is driven entirely by the amount of lime and
dolomite estimated to have been applied to soils over the
time period.
33 Note that the new NRI data were only used in the Tier 3 estimates. The
Tier 2 estimates still use data from the 1997 National Resources Inventory,
but will be updated in the future.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-20: C02 Emissions from Liming of Agricultural Soils (Tg C02 Eq.)
Source
1990
1995
2000
2005
2006
2007
Liming of Agricultural Soils3
4.7
4.4
4.3
4.3
4.2
4.1
a Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland, and Settlements
Remaining Settlements.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only.
Table 7-21: C02 Emissions from Liming of Agricultural Soils (Tg C)
Source
1990
1995
2000
2005
2006
2007
Liming of Agricultural Soils3
1.3
1.2
1.2
1.2
1.2
1.1
a Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland, and Settlements
Remaining Settlements.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only.
Methodology
CO2 emissions from degradation of limestone and
dolomite applied to agricultural soils were estimated using a
Tier 2 methodology consistent with IPCC (2006). The annual
amounts of limestone and dolomite applied (see Table 7-22)
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). This analysis of lime dissolution is based on
liming occurring in the Mississippi Pviver basin, where the
vast maj ority of all U. S. liming takes place (West 2008) .U.S.
liming that does not occur in the Mississippi Pviver basin tends
to occur under similar soil and rainfall regimes, and, thus,
the emission factor is appropriate for use across the United
States (West 2008). 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 through 2006; Willett
2007a, b; USGS 2007,2008). 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
Table 7-22: Applied Minerals (Million Metric Tons)
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 2007 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.
Source
Limestone
Dolomite
1990
19.01
2.36
1995
17.30
2.77
2000
15.86
3.81
2005
18.09
1.85
2006
17.14
2.24
2007
16.42
2.14
Note: These numbers represent amounts applied to Cropland Remaining Cropland, Land Converted to Cropland, Grassland Remaining Grassland,
Land Converted to Grassland, and Settlements Remaining Settlements.
Land Use, Land-Use Change, and Forestry 7-35
-------
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 2007 data,
the previous year's fractions were applied to a 2007 estimate
of total crushed stone presented in the USGS Mineral
Industry Surveys: Crushed Stone and Sand and Gravel in
the First Quarter of 2008 (USGS 2008).
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
metric tons) 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.
Since limestone and dolomite activity data are also available
at the state level, the national-level estimates reported here
were broken out by state, although state-level estimates are
not reported here.
Uncertainty
Uncertainty regarding limestone and dolomite activity
data inputs was estimated at +15 percent and assumed to
be uniformly distributed around the inventory estimate
(Tepordei 2003b). Analysis of the uncertainty associated with
the emission factors included the following: the fraction of
agricultural lime dissolved by nitric acid versus the fraction
that reacts with carbonic acid, and the portion of bicarbonate
that leaches through the soil and is transported to the ocean.
Uncertainty regarding the time associated with leaching and
transport was not accounted for, but should not change the
uncertainty associated with CO2 emissions (West 2005). The
uncertainty associated with the fraction of agricultural lime
dissolved by nitric acid and the portion of bicarbonate that
leaches through the soil were each modeled as a smoothed
triangular distribution between ranges of 0 percent to 100
percent. The uncertainty surrounding these two components
largely drives the overall uncertainty estimates reported
below. More information on the uncertainty estimates
for liming of agricultural soils is contained within the
Uncertainty Annex.
A Monte Carlo (Tier 2) uncertainty analysis was applied
to estimate the uncertainty of CO2 emissions from liming.
The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 7-23. CO2 emissions from liming of
agricultural soils in 2007 were estimated to be between 0.22
and 8.30 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of 95 percent below to 105 percent above
the 2007 emission estimate of 4.05 Tg CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and
input, documentation, and calculation. The QA/QC analysis
did not reveal any inaccuracies or incorrect input values.
Recalculations Discussion
Several adjustments were made in the current Inventory
to improve the results. The quantity of applied minerals
reported in the previous Inventory for 2006 has been revised.
Consequently, the reported emissions resulting from liming
in 2006 have also changed. In the previous Inventory, to
estimate 2006 data, the previous year's fractions were
Table 7-23: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Liming of Agricultural Soils
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Liming of Agricultural Soils"
C02
4.1
0.2
8.3
-95%
+ 105%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland, and
Settlements Remaining Settlements.
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
applied to a 2006 estimate of total crushed stone presented
in the USGS Mineral Industry Surveys: Crushed Stone and
Sand and Gravel in the First Quarter of 2007 (USGS 2007).
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 2006. These
values have replaced those used in the previous Inventory
to calculate the quantity of minerals applied to soil and the
emissions from liming.
CO2 Emissions from Urea Fertilization
The use of urea (CO(NH2)2) as fertilizer leads to
emissions of CO2 that was fixed during the industrial
production process. Urea in the presence of water and urease
enzymes is converted into ammonium (NH4+), hydroxyl
ion (OH), and bicarbonate (HCO3 ). The bicarbonate then
evolves into CO2 and water. Emissions from urea fertilization
in the United States totaled 4.0 Tg CO2 Eq. (1.1 Tg C) in
2007 (Table 7-24 and Table 7-25). Emissions from urea
fertilization have fluctuated over the past sixteen years,
ranging from 2.3 Tg CO2 Eq. to 4.0 Tg CO2 Eq.
Methodology
Carbon dioxide emissions from the application of urea
to agricultural soils were estimated using the IPCC (2006)
Tier 1 methodology. The annual amounts of urea fertilizer
applied (see Table 7-26) were derived from state-level
fertilizer sales data provided in Commercial Fertilizers (TVA
1991, 1992, 1993, 1994; AAPFCO 1995 through 2008)
and were multiplied by the default IPCC (2006) emission
factor of 0.20, which is equal to the C content of urea on
an atomic weight basis. Because fertilizer sales data are
reported in fertilizer years (July through June), a calculation
was performed to convert the data to calendar years (January
through December). According to historic monthly fertilizer
use data (TVA 1992b), 65 percent of total fertilizer used
in any fertilizer year is applied between January through
June of that calendar year, and 35 percent of total fertilizer
used in any fertilizer year is applied between July through
December of the previous calendar year. Fertilizer sales
data for the 2008 fertilizer year were not available in time
for publication. Accordingly, July through December 2007
fertilizer consumption was estimated by calculating the
percent change in urea use from January through June 2006
Table 7-24: C02 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C02 Eq.)
Source
1990
1995
2000
2005
2006
2007
Urea Fertilization3
2.4
2.7
3.2
3.5
3.7
4.0
a Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland,
Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only.
Table 7-25: C02 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C)
Source
1990
2000
2005
2006
2007
Urea Fertilization3
0.7
0.7
0.9
1.0
1.0
1.1
a Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland,
Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only.
Table 7-26: Applied Urea (Million Metric Tons)
1990
1995
2000
2005
2006
2007
Urea Fertilization3
3.30
3.62
4.38
4.78
4.98
5.39
a Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, Land Converted to Grassland,
Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only.
Land Use, Land-Use Change, and Forestry 7-37
-------
to July through December 2006. This percent change was
then multiplied by the January through June 2007 data to
estimate July through December 2007 fertilizer use. State-
level estimates of CO2 emissions from the application of urea
to agricultural soils were summed to estimate total emissions
for the entire United States.
Uncertainty
Uncertainty estimates are presented in Table 7-27 for Urea
Fertilization. A Tier 2 Monte Carlo analysis was completed.
The largest source of uncertainty was the default emission
factor, which assumes that 100 percent of the C applied to
soils is ultimately emitted into the environment as CO2. This
factor does not incorporate the possibility that some of the C
may be retained in the soil. The emission estimate is, thus,
likely to be high. In addition, each urea consumption data
point has an associated uncertainty. Urea for non-fertilizer
use, such as aircraft deicing, may be included in consumption
totals; it was determined through personal communication
with Fertilizer Regulatory Program Coordinator David L.
Terry (2007), however, that this amount is most likely very
small. Research into aircraft deicing practices also confirmed
that urea is used minimally in the industry; a 1992 survey
found a known annual usage of approximately 2,000 tons
of urea for deicing; this would constitute 0.06 percent of the
1992 consumption of urea (EPA 2000). Similarly, surveys
conducted from 2002 to 2005 indicate that total urea use
for deicing at U.S. airports is estimated to be 3,740 MT
per year, or less than 0.07 percent of the fertilizer total for
2007 (Itie 2009). Lastly, there is uncertainty surrounding the
assumptions behind the calculation that converts fertilizer
years to calendar years. CO2 emissions from urea fertilization
of agricultural soils in 2007 were estimated to be between 2.3
and 4.1 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of 43 percent below to 4 percent above the
2006 emission estimate of 4.0 Tg CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and
input, documentation, and calculation. Inventory reporting
forms and text were reviewed. No errors were found.
Recalculations Discussion
July to December 2006 urea application was updated
with newly available data for fertilizer year 2007, and the
2006 emission estimate was revised accordingly. (In the
previous Inventory, the application for this period was
calculated based on application during July to December
2005.) No other recalculations were needed, and the rest
of the time series remains the same as estimated in the
previous Inventory.
Planned Improvements
The primary planned improvement is to investigate
using a Tier 2 or Tier 3 approach, which would utilize
country-specific information to estimate a more precise
emission factor.
7.5. Land Converted to Cropland
(IPCC Source Category 5B2)
Land Converted to Cropland includes all cropland in an
inventory year that had been another land use at any point
during the previous 20 years34 according to the USDA NRI
land use survey (USDA-NRCS 2000). Consequently, lands
are retained in this category for 20 years as recommended
Table 7-27: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Urea Fertilization (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Urea Fertilization
C02
4.0
2.3
4.1
-43%
+4%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland Remaining Grassland,
Land Converted to Grassland, Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
34 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began, and consequently the classifications
were based on less than 20 years from 1990 to 2001.
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 (2006)
recommends reporting changes in soil organic C stocks due
to: (1) agricultural land-use and management activities on
mineral soils, and (2) agricultural land-use and management
activities on organic soils.35
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 7-28 and Table 7-29). The
total rate of change in soil C stocks was 5.9 Tg CO2 Eq.
(1.6 Tg C) in 2007. Mineral soils were estimated to lose
3.3 Tg CO2 Eq. (0.9 Tg C) in 2007, while drainage and
cultivation of organic soils led to annual losses of 2.6 Tg
C02 Eq. (0.7 Tg C) in 2007.
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 7-7 and
Figure 7-8. 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 net C accumulation in the Great
Plains, Midwest, and mid-Atlantic states. These areas were
gaining C following conversion, because the land had been
brought into hay production, including grass and legume hay,
leading to enhanced plant production relative to the previous
land use, and thus higher C input to the soil. 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.
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.
Soil C stock changes were estimated for Land Converted
to Cropland according to land-use histories recorded in the
USDANPJ survey (USDA-NRCS 2000). Land-use and some
management information (e.g., crop type, soil attributes, and
irrigation) were originally collected for each NPJ point on a
Table 7-28: Net C02 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990
(0.3)
2.4
2.2
1995
0.3
2.6
2.9
2000
(0.3)
2.6
2.4
2005
3.3
2.6
5.9
2006
3.3
2.6
5.9
2007
3.3
2.6
5.9
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.
Table 7-29: Net C02 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C)
1995
Soil Type
1990
2000
2005
2006 2007
Mineral Soils
Organic Soils
(0.1)
0.7
0.1
0.7
(0.1)
0.7
0.9
0.7
0.9
0.7
0.9
0.7
Total Net Flux
0.6
0.8
0.6
1.6
1.6
1.6
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.
35 CO2 emissions associated with liming are also estimated but included in
a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-39
-------
Figure 7-7
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States,
2007, Land Converted to Cropland
o
Tg C02 Eq./year
D>0
D-0.1 toO
D -0.5 to -0.1
• -1to-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 7-8
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States,
2007, Land Converted to Cropland
• a
Note: Values greater than zero represent emissions.
Tg C02 Eq./year
• 0.5 to 1
D 0.1 to 0.5
DO to 0.1
EH No organic soils
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
5-year cycle beginning in 1982. However, the NRI program
initiated annual data collection in 1998, and the annual
data are currently available through 2003. NRI points were
classified as Land Converted to Cropland in a given year
between 1990 and 2007 if the land use was cropland but had
been another use during the previous 20 years.36 Cropland
includes all land used to produce food or fiber, or forage that
is harvested and used as feed (e.g., hay and silage).
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. Soil C stock changes
on the remaining soils were estimated with the IPCC Tier 2
method (Ogle et al. 2003), including land used to produce
vegetables, 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.37
Tier 3 Approach
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 US DA 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
and Annex 3.13 for additional information).
Tier 2 Approach
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
36 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began. Therefore, the classification prior to
2002 was based on less than 20 years of recorded land-use history for the
time series.
37 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).
soils (see Cropland Remaining Cropland Tier 2 methods
section for additional information).
Organic Soil Carbon Stock Changes
Annual C emissions from drained organic soils in Land
Converted to Cropland were estimated using the Tier 2
method provided in IPCC (2003, 2006), with 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 1997 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 2007.
Uncertainty
Uncertainty analysis for mineral soil C stock changes
using the Tier 3 and Tier 2 approaches was 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. The uncertainty for
annual C emission estimates from drained organic soils
in Land Converted to Cropland was estimated using the
Tier 2 approach, as described in the Cropland Remaining
Cropland section.
Uncertainty estimates are presented in Table 7-30 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). Uncertainty
for the portions of the Inventory estimated with Tier 2 and 3
approaches was derived using a Monte Carlo approach (see
Annex 3.13 for further discussion). A combined uncertainty
estimate for changes in agricultural soil C stocks is also
included. Uncertainty estimates from each component were
combined using the error propagation equation in accordance
with IPCC (2006), i.e., by taking the square root of the sum
of the squares of the standard deviations of the uncertain
quantities. The combined uncertainty for soil C stocks in
Land Converted to Cropland was estimated to be 40 percent
below and 36 percent above the inventory estimate of 5.9
Tg CO2 Eq.
Land Use, Land-Use Change, and Forestry 7-41
-------
Table 7-30: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Land Converted to
Cropland (Tg C02 Eq. and Percent)
2007 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source (Tg C02 Eq.) (Tg C02 Eq.) (%)
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
(0.8)
4.1
2.6
Lower
Bound
(1.5)
2.3
1.2
Upper
Bound
(0.1)
5.8
3.7
Lower
Bound
-84%
-44%
-53%
Upper
Bound
+84%
+41%
+41%
Combined Uncertainty for Flux Associated with
Soil Carbon Stock Change in Land Converted
to Cropland
5.9
3.5
8.1
-40%
+36%
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
QA/QC and Verification
See QA/QC and Verification section under Cropland
Remaining Cropland.
Recalculations Discussion
Annual survey data from the USDA National Resources
Inventory (NRI) were incorporated into the current Inventory.
This resulted in several changes to the inventory methods:
First, the availability of new data extended the time
series of activity data beyond 1997 to 2003,38 In previous
Inventories, activity data were only available through 1997,
and so subsequent years were treated as the same land use
practice occurring in 1997.
Second, annual area data, rather than area data that had
been collected in 5-year increments, were used to estimate
soil C stock changes, leading to more accurate estimates.
Third, each NRI point was simulated separately, instead
of simulating clusters of points that had common land use/
cropping rotation histories and edaphic characteristics in a
county. More importantly, the exact cropping histories were
simulated, instead of generalized cropping rotations (e.g.,
wheat-fallow, corn-soybean).
Fourth, NRI area data were reconciled with the forest
area estimates in the Forest Inventory and Analysis (FIA)
dataset, and were incorporated into the estimation of soil
C stock changes. The reconciliation led to adjustments
in the grassland areas in the NRI dataset, including Land
Converted to Cropland39 (i.e., Grassland and Wetlands
Converted to Cropland).
Overall, these recalculations resulted in an average
annual increase in soil C stocks of 8.5 Tg CO2 Eq. for
soil C stock changes in Land Converted to Cropland over
the time series from 1990 through 2006, compared to the
previous Inventory.
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 the Century model for Land
Converted to Cropland, but this is a planned improvement.
This improvement will produce a more rigorous assessment of
uncertainty. See Planned Improvements section under Cropland
Remaining Cropland for additional planned improvements.
7.6. Grassland Remaining Grassland
(IPCC Source Category 5C1)
Grassland Remaining Grassland includes all grassland
in an inventory year that had been grassland for the previous
38 Note that the new NRI data were only used in the Tier 3 inventory. The Tier
2 portion of the inventory still used data from the 1997 National Resources
Inventory, but will be updated in the future.
39 NRI area data for forest lands was adjusted the match the forest area
estimates in the Forest Inventory and Analysis dataset. In order to maintain
the same total area, the area data for grasslands and wetlands in the NRI
were adjusted to offset the increase or decrease in the forest land area (see
section on Representation of U.S. Land Base for more information).
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
20 years40 according to the USDA NRI land use survey
(USDA-NRCS 2000). 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 (2006) recommends reporting changes in
soil organic C stocks due to: (1) agricultural land-use and
management activities on mineral soils, and (2) agricultural
land-use and management activities on organic soils.41
Land-use and management of mineral soils in Grassland
Remaining Grassland increased soil C, while organic soils
lost relatively small amounts of C in each year 1990 through
2007. Due to the pattern for mineral soils, the overall trend
were gains in soil C over the time series although the rates
varied from year to year, with a net removal of 4.7 Tg CO2
Eq. (5.4 Tg C) in 2007 (Table 7-31 and Table 7-32). However,
there was considerable variation driven by variability in
weather patterns over the time series. Overall, flux rates
declined by 42.1 Tg CO2 Eq. (11.5 Tg C) when comparing
the net change in soil C for 1990 and 2007.
The spatial variability in annual CO2 flux associated
with C stock changes in mineral and organic soils is
displayed in Figure 7-9 and Figure 7-10. Grassland gained
soil organic C in several regions during 2007, including
the Northeast, Midwest, Southwest, and far western
states; although these were relatively small increases in
C on a per-hectare basis. 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.
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.
Table 7-31: Net C02 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C02 Eq.)
Soil Type
1990
1995
2000
2005
2006
2007
Mineral Soils
Organic Soils
(50.6)
3.9
(40.1)
I
(55.1)
3.7
(8.3)
3.7
(8.3)
3.7
(8.4)
3.7
Total Net Flux
(46.7)
(36.4)
(51.4)
(4.6)
(4.6) (4.7)
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.
Table 7-32: Net C02 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C)
Soil Type
1990
1995
2000
2005
2006
2007
Mineral Soils
Organic Soils
(13.8)
1.1
(10.9)
1.0
(15.0)
1.0
(2.3)
1.0
(2.3)
1.0
(2.3)
1.0
Total Net Flux
(12.7)
(9.9)
(14.0)
(1.3)
(1.3) (1.3)
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.
40 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began, and consequently the classifcations
were based on less than 20 years from 1990 to 2001.
41CO2 emissions associated with liming are also estimated but included in
a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-43
-------
Figure 7-9
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States,
2007, Grassland Remaining Grassland
• o
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 7-10
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States,
2007, Grassland Remaining Grassland
Note: Values greater than zero represent emissions.
Tg C02 Eq./year
• lto2
D0.5to1
DO.1 to 0.5
Do to 0.1
I | No organic soils
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Soil C stock changes were estimated for Grassland
Remaining Grassland according to land-use histories
recorded in the USDA NRI survey (USDA-NRCS 2000).
Land-use and some management information (e.g., crop
type, soil attributes, and irrigation) were originally collected
for each NRI point on a 5-year cycle beginning in 1982.
However, the NRI program initiated annual data collection
in 1998, and the annual data are currently available through
2003. NRI points were classified as Grassland Remaining
Grassland in a given year between 1990 and 2007 if the land
use had been grassland for 20 years.42 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.
Mineral Soil Carbon Stock Changes
An IPCC Tier 3 model-based approach was used to
estimate C stock changes for most mineral soils in Grassland
Remaining Grassland. The C stock changes for the remaining
soils were estimated with an IPCC Tier 2 method (Ogle et
al. 2003), including gravelly, cobbly or shaley soils (greater
than 35 percent by volume) and additional stock changes
associated with sewage sludge amendments.
Tier 3 Approach
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
42 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began. Therefore, the classification prior to
2002 was based on less than 20 years of recorded land-use history for the
time series.
Resources Conservation Service (Edmonds, et al. 2003),
and then adjusted using county-level estimates of manure
available for application in other years. Specifically, county-
scale ratios of manure available for application to soils in
other years relative to 1997 were used to adjust the area
amended with manure (see Annex 3.13 for further details).
Greater availability of managed manure N relative to 1997
was, thus, assumed to increase the area amended with
manure, while reduced availability of manure N relative to
1997 was assumed to reduce the amended area.
The amount of manure produced by each livestock
type was calculated for managed and unmanaged waste
management systems based on methods described in the
Manure Management Section (Section 6.2) and Annex
(Annex 3.10). In contrast to manure amendments, 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
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 and Annex 3.13 for
additional information).
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between 1990
and 2007 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, in dry mass units, were obtained from an EPA
report (EPA 1999) and estimates for 2004 were obtained
from an independent national biosolids survey (NEBRA
2007). These values were 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
Land Use, Land-Use Change, and Forestry 7-45
-------
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 (2003,2006), which utilizes
U.S.-specific C loss rates (Ogle et al. 2003) rather than
default IPCC rates. Emissions were based on the 1992 and
1997 Grassland Remaining Grassland areas from the 1997
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 2007.
Uncertainty
Uncertainty estimates are presented in Table 7-33 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). Uncertainty
for the portions of the Inventory estimated with Tier 2 and 3
approaches was derived using a Monte Carlo approach (see
Annex 3.13 for further discussion). A combined uncertainty
estimate for changes in agricultural soil C stocks is also
included. Uncertainty estimates from each component were
combined using the error propagation equation in accordance
with IPCC (2006), i.e., by taking the square root of the sum
of the squares of the standard deviations of the uncertain
quantities. The combined uncertainty for soil C stocks in
Grassland Remaining Grassland was estimated to be 54
percent below and 41 percent above the inventory estimate
of -4.7 Tg CO2 Eq.
Uncertainties in Mineral Soil Carbon Stock Changes
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.
A +50 percent uncertainty was assumed for additional
adjustments to the soil C stocks between 1990 and 2007
to account for additional C stock changes associated with
amending grassland soils with sewage sludge.
Table 7-33: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Grassland Remaining
Grassland (Tg C02 Eq. and Percent)
2007 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source (Tg C02 Eq.) (Tg C02 Eq.) (%)
Mineral Soil C Stocks Grassland Remaining Grassland,
Tier 3 Methodology
Mineral Soil C Stocks: Grassland Remaining Grassland,
Tier 2 Methodology
Mineral Soil C Stocks: Grassland Remaining Grassland,
Tier 2 Methodology (Change in Soil C due to Sewage
Sludge Amendments)
Organic Soil C Stocks: Grassland Remaining Grassland,
Tier 2 Methodology
(7.0)
(0.2)
(1.2)
3.7
Lower
Bound
(7.2)
(0.3)
(1.8)
1.2
Upper
Bound
(6.8)
0.0
(0.6)
5.5
Lower
Bound
-2%
-89%
-50%
-66%
Upper
Bound
+2%
+ 127%
+50%
+49%
Combined Uncertainty for Flux Associated with
Agricultural Soil Carbon Stock Change in Grassland
Remaining Grassland
(4.7)
(7.2)
(2.7)
-54% +41%
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Uncertainties in Soil Carbon Stock Changes for Organic Soils
Uncertainty in C emissions from organic soils was
estimated using country-specific factors and a Monte Carlo
analysis. Probability distribution functions 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. Several errors were
found in the implementation of the new annual NRI data,
mostly involving problems in scheduling crops and practices
with the more detailed histories; corrective actions were taken
to deal with the errors.
Recalculations Discussion
Annual survey data from the USDA National Resources
Inventory (NRI) were incorporated into this year's Inventory.
This resulted in several changes to the inventory methods:
First, the availability of new data extended the time
series of activity data beyond 1997 to 2003,43 In previous
Inventories, activity data were only available through 1997,
and so subsequent years were treated as the same land use
practice occurring in 1997.
Second, annual area data, rather than area data that had
been collected in 5-year increments, were used to estimate
soil C stock changes, leading to more accurate estimates.
Third, each NRI point was simulated separately, instead
of simulating clusters of points that had common land use
histories and edaphic characteristics in a county.
Fourth, NRI area data were reconciled with the forest
area estimates in the Forest Inventory and Analysis (FIA)
dataset, and were incorporated into the estimation of soil
C stock changes. The reconciliation led to adjustments in
the grassland areas in the NRI dataset, including Grassland
Remaining Grassland.44
Overall, the recalculations resulted in an average annual
increase in soil C stocks of 31 Tg CO2 Eq. for the time series
over the period from 1990 through 2006, compared to the
previous Inventory.
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. This
improvement will produce a more rigorous assessment
of uncertainty. See Planned Improvements section under
Cropland Remaining Cropland for additional planned
improvements.
7.7. Land Converted to Grassland
(IPCC Source Category 5C2)
Land Converted to Grassland includes all grassland in an
inventory year that had been in another land use at any point
during the previous 20 years45 according to the USDA NRI
land use survey (USDA-NRCS 2000). Consequently, lands
are retained in this category for 20 years as recommended
by 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 (2006) recommend
reporting changes in soil organic C stocks due to: (1)
agricultural land-use and management activities on mineral
43 Note that the new NRI data were only used in the Tier 3 estimates. The Tier
2 portion of the estimates still used data from the 1997 National Resources
Inventory, but will be updated in the future.
44 NRI area data for forest lands was adjusted the match the forest area
estimates in the Forest Inventory and Analysis dataset. In order to maintain
the same total area, the area data for grasslands and wetlands in the NRI
were adjusted to offset the increase or decrease in the forest land area (see
section on Representation of U.S. Land Base for more information).
45 NRI points were classified according to land-use history records starting
in 1982 when the NRI survey began, and consequently the classifcations
were based on less than 20 years from 1990 to 2001.
Land Use, Land-Use Change, and Forestry 7-47
-------
soils, and (2) agricultural land-use and management activities
on organic soils.46
Land-use and management of mineral soils in Land
Converted to Grassland led to an increase in soil C stocks
from 1990 through 2007, which was largely due to annual
cropland conversion to pasture (see Table 7-34 and Table
7-35). For example, the stock change rates were estimated
to remove 22.7 Tg CO2 Eq./yr (6.2 Tg C) and 27.6 Tg
CO2 Eq./yr (7.5 Tg C) from mineral soils in 1990 and
2007, respectively. Drainage of organic soils for grazing
management led to losses varying from 0.5 to 0.9 Tg CO2
Eq./yr (0.1 to 0.2 TgC).
The spatial variability in annual CO2 flux associated with
C stock changes in mineral soils is displayed in Figure 7-11
and Figure 7-12. Soil C stock increased in most states for
Land Converted to Grassland. The largest gains were in the
South-Central region, Midwest, and northern Great Plains.
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,
coinciding with largest concentrations of organic soils in the
United States that are used for agricultural production.
Methodology
This 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. 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.
Soil C stock changes were estimated for Land Converted
to Grassland according to land-use histories recorded in
the USDA NRI survey (USDA-NRCS 2000). Land-use
and some management information (e.g., crop type, soil
attributes, and irrigation) were originally collected for each
NRI point on a 5-year cycle beginning in 1982. However,
the NRI program initiated annual data collection in 1998,
and the annual data are currently available through 2003.
NRI points were classified as Land Converted to Grassland
in a given year between 1990 and 2007 if the land use was
grassland, but had been another use in the previous 20
years. Grassland includes pasture and rangeland used for
grass forage production, where the primary use is livestock
grazing. Rangeland typically includes extensive areas of
Table 7-34: Net C02 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C02 Eq.)
Soil Type
Mineral Soils3
Organic Soils
Total Net Flux
1990
(22.7)
0.5
(22.3)
1995
(23.4)
0.9
(22.5)
2000
(32.8)
0.9
(32.0)
2005
(27.6)
0.9
(26.7)
2006
(27.6)
0.9
(26.7)
2007
(27.6)
0.9
(26.7)
a Stock changes due to application of sewage sludge are reported in Grassland Remaining Grassland.
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.
Table 7-35: Net C02 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C)
Soil Type
Mineral Soils3
Organic Soils
Total Net Flux
1990
(6.2)
(6.1)
1995
(6.4)
0.2
(6.1)
2000
(9.0)
0.2
(8.7)
2005
(7.5)
0.2
(7.3)
2006
(7.5)
0.2
(7.3)
2007
(7.5)
0.2
(7.3)
a Stock changes due to application of sewage sludge are reported in Grassland Remaining Grassland.
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.
46 CO2 emissions associated with liming are also estimated but included in
a separate section of the report.
7-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Figure 7-11
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States,
2007, Land Converted to Grassland
Tg C02 Eq./year
D-0.1 too
D-0.5 to-0.1
D-1to-0.5
• -2to-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 7-12
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States,
2007, Land Converted to Grassland
Tg C02 Eq./year
• 0.5 to 1
D 0.1 to 0.5
DO to 0.1
CH No organic soils
Note: Values greater than zero represent emissions.
Land Use, Land-Use Change, and Forestry 7-49
-------
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.
Mineral Soil Carbon Stock Changes
An IPCC Tier 3 model-based approach was used to
estimate C stock changes for Land Converted to Grassland
on most mineral soils. C stock changes on the remaining soils
were estimated with an IPCC Tier 2 approach (Ogle et al.
2003), including prior cropland used to produce vegetables,
tobacco, perennial/horticultural crops, and rice; land areas
with very gravelly, cobbly or shaley soils (greater than 35
percent by volume); and land converted from forest or federal
ownership.47 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 the US DA Economic Research
Service Cropping Practices Survey (ERS 1997) and the
National Agricultural Statistics Service (NASS 1992, 1999,
2004) (see Grassland Remaining Grassland Tier 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 CroplandTier
2 Approach and Annex 3.13 for additional information).
Organic Soil Carbon Stock Changes
Annual C emissions from drained organic soils in Land
Converted to Grassland were estimated using the Tier 2
method provided in IPCC (2003,2006), which utilizes U. S. -
specific C loss rates (Ogle et al. 2003) rather than default
IPCC rates. Emissions were based on the 1992 and 1997
Land Converted to Grassland areas from the 1997 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 2007.
Uncertainty
Uncertainty analysis for mineral soil C stock changes
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. The uncertainty or
annual C emission estimates from drained organic soils
in Land Converted to Grassland was estimated using the
Tier 2 approach, as described in the Cropland Remaining
Cropland section.
Uncertainty estimates are presented in Table 7-36 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). Uncertainty
for the portions of the Inventory estimated with Tier 2 and 3
approaches was derived using a Monte Carlo approach (see
Annex 3.13 for further discussion). A combined uncertainty
estimate for changes in agricultural soil C stocks is also
included. Uncertainty estimates from each component were
combined using the error propagation equation in accordance
with IPCC (2006), (i.e., by taking the square root of the sum
of the squares of the standard deviations of the uncertain
quantities). The combined uncertainty for soil C stocks in
Land Converted to Grassland ranged from 8 percent below
to 9 percent above the 2007 estimate of -26.7 Tg CO2 Eq.
47 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).
7-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-36: Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Land Converted to
Grassland (Tg C02 Eq. and Percent)
2007 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source (Tg C02 Eq.) (Tg C02 Eq.) (%)
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
(22.6)
(5.0)
0.9
Lower
Bound
(23.1)
(7.0)
0.2
Upper
Bound
(22.1)
(2.8)
1.8
Lower
Bound
-2%
-39%
-76%
Upper
Bound
+2%
+43%
+ 104%
Combined Uncertainty for Flux Associated with
Agricultural Soil Carbon Stocks in Land Converted
to Grassland
(26.7)
(28.8)
(24.3)
+9%
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
QA/QC and Verification
See the QA/QC and Verification section under Grassland
Remaining Grassland.
Recalculations Discussion
Annual survey data from the USDA National Resources
Inventory (NRI) were incorporated into this year's Inventory.
This resulted in several changes to the inventory methods:
First, the availability of new data extended the time
series of activity data beyond 1997 to 2003,48 In previous
Inventories, activity data were only available through 1997,
and so subsequent years were treated as the same land use
practice occurring in 1997.
Second, annual area data, rather than area data that had
been collected in 5-year increments, were used to estimate
soil C stock changes, leading to more accurate estimates.
Third, each NRI point was simulated separately, instead
of simulating clusters of points that had common land use
histories and edaphic characteristics in a county.
Fourth, NRI area data were reconciled with the forest
area estimates in the Forest Inventory and Analysis (FIA)
dataset, and were incorporated into the estimation of soil C
stock changes. The reconciliation led to adjustments in the
grassland areas in the NRI dataset, including Land Converted
to Grassland.49
Overall, the recalculations resulted in an average annual
increase in soil C stocks of 9.4 Tg CO2 Eq. for the time
series from 1990 through 2006, compared to the previous
Inventory.
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. This improvement
will produce a more rigorous assessment of uncertainty. See
Planned Improvements section under Cropland Remaining
Cropland for additional planned improvements.
48 Note that the new NRI data were only used in the Tier 3 inventory. The Tier
2 portion of the inventory still used data from the 1997 National Resources
Inventory, but will be updated in the future.
49 NRI area data for forest lands was adjusted the match the forest area
estimates in the Forest Inventory and Analysis dataset. In order to maintain
the same total area, the area data for grasslands and wetlands in the NRI
were adjusted to offset the increase or decrease in the forest land area (see
section on Representation of U.S. Land Base for more information).
Land Use, Land-Use Change, and Forestry 7-51
-------
7.8. Wetlands Remaining Wetlands
(IPCC Source Category 5D1)
Peatlands Remaining Peatlands
Emissions from Managed Peatlands
Managed peatlands are peatlands which have been
cleared and drained for the production of peat. The
production cycle of a managed peatland has three phases:
land conversion in preparation for peat extraction (e.g.,
draining, and clearing surface biomass); extraction (which
results in the emissions reported under Peatlands Remaining
Peatlands); and abandonment, restoration or conversion of
the land to another use.
CO2 emissions from the removal of biomass and the
decay of drained peat constitute the major greenhouse gas
flux from managed peatlands. Managed peatlands may also
emit CH4 and N2O. The natural production of CH4 is largely
reduced but not entirely shut down when peatlands are
drained in preparation for peat extraction (Strack et al., 2004);
however, methane emissions are assumed to be insignificant
under Tier 1 IPCC (2006) methods. N2O emissions from
managed peatlands depend on site fertility. In addition,
abandoned and restored peatlands continue to release GHG
emissions, and at present no methodology is provided by
IPCC (2006) to estimate GHG emissions or removals from
restored peatlands. This Inventory estimates both CO2 and
N2O emissions from lands undergoing peat extraction in
accordance with Tier 1 IPCC (2006) guidelines.
C02 and N20 Emissions from Lands Undergoing
Peat Extraction
IPCC (2006) recommends reporting CO2 and N2O
emissions from lands undergoing peat extraction (i.e.,
Peatlands Remaining Peatlands) as part of the estimate
for emissions from managed wetlands. Peatlands occur in
wetland areas where plant biomass has sunk to the bottom
of water bodies and water-logged areas and exhausted the
oxygen supply below the water surface during the course of
decay. Due to these anaerobic conditions, much of the plant
matter does not decompose but instead forms layers of peat
over the course of many decades and centuries. In the United
States, peat is extracted for horticulture and landscaping
growing media, and for a wide variety of industrial, personal
care, and other products. It has not been used for fuel in
the United States for many decades. Peat is harvested from
two types of peat deposits in the United States: sphagnum
bogs in northern states and wetlands in states further south.
The peat from sphagnum bogs in northern states, which is
nutrient-poor, is generally corrected for acidity and mixed
with fertilizer. Production from more southerly states is
relatively coarse but nutrient-rich.
IPCC (2006) recommends considering both on-site and
off-site emissions when estimating CO2 emissions from
lands undergoing peat extraction using the Tier 1 approach.
Current methodologies estimate only on-site N2O emissions,
since off-site N2O estimates are complicated by the risk of
double-counting emissions from nitrogen fertilizers added to
horticultural peat. On-site emissions from managed peatlands
occur as the land is cleared of vegetation and the underlying
peat is exposed to sun and weather. As this occurs, some peat
deposit is lost and CO2 is emitted from the oxidation of the
peat. On-site N2O is emitted during draining depending on
site fertility and if the deposit contains significant amounts
of organic nitrogen in inactive form. Draining land in
preparation for peat extraction allows bacteria to convert the
nitrogen into nitrates which leach to the surface where they
are reduced to N2O.
Off-site CO2 emissions from managed peatlands occur
from the horticultural and landscaping use of peat. CO2
emissions occur as the nutrient-poor (but now fertilizer-
enriched) peat is used in bedding plants, other greenhouse
and plant nursery production, and by consumers, and as
nutrient-rich (but relatively coarse) peat is used directly in
landscaping, athletic fields, golf courses, and plant nurseries.
Most of the CO2 emissions from peat occur off-site, as the
peat is processed and sold to firms which, in the United
States, use it predominately for horticultural purposes. The
magnitude of the CO2 emitted from peat depends on whether
the peat has been extracted from nutrient-rich or nutrient-
poor peat deposits.
Total emissions from lands undergoing peat extraction
have fluctuated between 0.9 and 1.2 Tg CO2 Eq. across the
time series with a gentle decrease until 1996 followed by
an increase though 2000. Since 2000, total emissions have
decreased with some fluctuations. Carbon dioxide emissions
from lands undergoing peat extraction have fluctuated
7-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-37: Emissions from Lands Undergoing Peat Extraction (Tg C02 Eq.)
Gas
1990
1995
2000
2005
2006
2007
C02
N20
1.0
1.0
1.1
0.9
1.0
Total
1.0
1.0
1.2
1.1
0.9
Table 7-38: Emissions from Lands Undergoing Peat Extraction (Gg)
Gas
1990
2000
2005
2006
C02
N20
+ Does not exceed 0.5 Gg.
Note: These numbers are based on U.S. production data in accordance with Tier 1 guidelines, which does not take into account imports,
exports and stockpiles (i.e., apparent consumption).
1.0
+ Does not exceed 0.05 Tg C02 Eq.
Note: These numbers are based on U.S. production data in accordance with Tier 1 guidelines, which does not take into account imports,
exports and stockpiles (i.e., apparent consumption).
2007
between 0.9 and 1.2 Tg CO2 Eq. in recent years and have
driven the trends in total emissions. Nitrous oxide emissions
remained close to zero in recent years, with a decreasing
trend until 1995 followed by an overall increase with
fluctuations until around 2000. Since 2000, N2O emissions
have fluctuated but shown an overall decrease. (See Table
7-37 and Table 7-38).
Methodology
Off-site C02 Emissions
Carbon dioxide emissions from domestic peat production
were estimated using a Tier 1 methodology consistent with
IPCC (2006). Off-site CO2 emissions from lands undergoing
peat extraction were calculated by apportioning the annual
weight of peat produced in the United States (Table 7-39) into
peat extracted from nutrient-rich deposits and peat extracted
from nutrient-poor deposits using annual percentage by
weight figures. These nutrient-rich and nutrient-poor
production values were then multiplied by the appropriate
default carbon fraction conversion factor taken from IPCC
(2006) in order to obtain off-site emission estimates. Both
annual percentages of peat type by weight and domestic
peat production data were sourced from estimates and
industry statistics provided in the Minerals Yearbook and
Mineral Industry Surveys from the U.S. Geological Survey
(USGS 1990 through 2008). 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
domestic peat producers. The USGS often receives a response
to the survey from most of the smaller peat producers, but
fewer of the larger ones. For example, of the four active
operations producing 23,000 or more metric tons per year,
two did not respond to the survey in 2007. As a result, the
USGS estimates production from the nonrespondent peat
producers based on responses to previous surveys (responses
from 2004 and 2005, in the case above) or other sources.
Estimates were made separately for Alaska, because the state
conducts its own mineral survey and reports peat production
Table 7-39: Peat Production of Lower 48 States (in thousands of Metric Tons)
Type of Deposit
Nutrient-Rich
Nutrient-Poor
Total Production
1990
595.1
55.4
692.0
1995
531.4
116.6
648.0
2000
728.6
63.4
792.0
2005
657.6
27.4
685.0
2006
529.0
22.0
551.0
2007
581.0
54.0
635.0
Source: USGS (1990-2008) Minerals Yearbook and Mineral Industry Surveys.
Land Use, Land-Use Change, and Forestry 7-53
-------
Table 7-40: Peat Production of Alaska (in thousands of Cubic Meters)
1990
1995
2000
2005
2006
2007
Total Production
49.7
26.8
27.2
47.8
50.8
51.0
Source: Szumigala, D.J. and R.A. Hughes (1990-2007) Alaska's Mineral Industry Reports. Alaska Department of Natural Resources.
by volume, rather than by weight (Table 7-40). However,
volume production data was used to calculate off-site CO2
emissions from Alaska applying the same methodology but
with volume-specific carbon fraction conversion factors
from IPCC (2006).50
The apparent consumption of peat in the United States,
which includes production plus imports minus exports plus
the decrease in stockpiles, is over two-and-a-half times the
amount of domestic peat production. Therefore, off-site
CO2 emissions from the use of all horticultural peat within
the United States are not accounted for using the Tier 1
approach. The United States has increasingly imported peat
from Canada for horticultural purposes; in 2007, imports
of sphagnum moss (nutrient-poor) peat from Canada
represented 97 percent of total U.S. peat imports (USGS
2008). Most peat produced in the United States is reed-sedge
peat, generally from southern states, which is classified as
nutrient rich by IPCC (2006). Higher-tier calculations of
CO2 emissions from apparent consumption would involve
consideration of the percentages of peat types stockpiled
(nutrient-rich versus nutrient-poor) as well as the percentages
of peat types imported and exported.
On-site C02 Emissions
IPCC (2006) suggests basing the calculation of on-site
emissions estimates on the area of peatlands managed for
peat extraction differentiated by the nutrient type of the
deposit (rich versus poor). Information on the area of land
managed for peat extraction is currently not available for
the United States, but in accordance with IPCC (2006), an
average production rate for the industry was applied to derive
an area estimate. In a mature industrialized peat industry,
such as exists in the United States and Canada, the vacuum
method51 can extract up to 100 metric tons per hectare per
year (Cleary 2005). The area of land managed for peat
extraction in the United States was estimated using nutrient-
rich and nutrient-poor production data and the assumption
that 100 metric tons of peat are extracted from a single hectare
in a single year. The annual land area estimates were then
multiplied by the appropriate nutrient-rich or nutrient-poor
IPCC (2006) default emission factor in order to calculate on-
site CO2 emission estimates. Production data is not available
by weight for Alaska. In order to calculate on-site emissions
resulting from land undergoing peat extraction in Alaska, the
production data by volume were converted to weight using
annual peat density values, and then converted to land area
estimates using the assumption that a single hectare yields
100 metric tons. The IPCC (2006) on-site emissions equation
also includes a term which accounts for emissions resulting
from the change in carbon stocks that occurs during the
clearing of vegetation prior to peat extraction. Area data on
land undergoing conversion to peatlands for peat extraction
is also unavailable for the United States. However, USGS
records show that the number of active operations in the
United States has been declining since 1990. Since vacuum-
harvested peatlands have an average lifespan of thirty-five
years (Cleary 2005), it seems reasonable to assume that no
new areas are being cleared of vegetation for peat extraction.
Other changes in carbon stocks in living biomass on managed
peat lands are also assumed to be zero under the Tier 1
methodology (IPCC 2006).
On-site N20 Emissions
IPCC (2006) suggests basing the calculation of on-
site N2O emissions estimates on the area of nutrient-rich
peatlands managed for peat extraction. These data are not
available for the United States, but the on-site CO2 emissions
methodology above details the calculation of area data from
production data. In order to estimate N2O emissions, the
50 Peat produced from Alaska was assumed to be nutrient poor; as is the case
in Canada, "where deposits of high-quality [but nutrient poor] sphagnum
moss are extensive" (USGS 2008).
51 The vacuum method is one type of extraction that annually "mills" or
breaks up the surface of the peat into particles, which then dry during the
summer months. The air-dried peat particles are then collected by vacuum
harvesters and transported from the area to stockpiles (IPCC 2006).
7-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
area of nutrient rich land undergoing peat extraction was
multiplied by the appropriate default emission factor taken
from IPCC (2006).
Uncertainty
The uncertainty associated with peat production data was
estimated to be + 25 percent (Apodaca 2008) and assumed to
be normally distributed. The uncertainty associated with peat
production data stems from the fact that the USGS receives
data from the smaller peat producers but estimates production
from some larger peat distributors. This same uncertainty
and distribution was assumed for the peat type production
percentages. The uncertainty associated with the Alaskan
reported production data was assumed to be the same as the
lower 48 states, or + 25 percent with a normal distribution.
It should be noted that the Alaskan Department of Natural
Resources estimate that around half of producers do not
respond to their survey with peat production data; therefore,
the production numbers reported are likely to underestimate
Alaska peat production. The uncertainty associated with the
average bulk density values was estimated to be + 25 percent
with a normal distribution (Apodaca 2008). IPCC (2006)
gives uncertainty values for the emission factors for the
area of peat deposits managed for peat extraction based on
the range of underlying data used to determine the emission
factors. The uncertainty associated with the emission factors
was assumed to be triangularly distributed. The uncertainty
values surrounding the carbon fractions were based on IPCC
(2006) and the uncertainty was assumed to be uniformly
distributed. Based on these values and distributions, a
Monte Carlo (Tier 2) uncertainty analysis was applied to
estimate the uncertainty of CO2 and N2O emissions from
land undergoing peat extraction. The results of the Tier 2
quantitative uncertainty analysis are summarized in Table
7-41. CO2 emissions from lands undergoing peat extraction
in 2007 were estimated to be between 0.70 and 1.30 Tg
CO2 Eq. at the 95 percent confidence level. This indicates
a range of 31 percent below to 29 percent above the 2007
emission estimate of 0.99 Tg CO2 Eq. N2O emissions from
lands undergoing peat extraction in 2007 were estimated to
be between 0.001 and 0.007 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of 73 percent below
to 37 percent above the 2007 emission estimate of 0.005 Tg
CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and
input, documentation, and calculation. The QA/QC analysis
did not reveal any inaccuracies or incorrect input values.
Recalculations Discussion
This is the first year that emissions from Lands
Undergoing Peat Extraction are included in the Inventory
of U.S. Greenhouse Gas Emissions and Sinks.
Planned Improvements
In order to further improve estimates of CO2 and N2O
emissions from lands undergoing peat extraction, future
efforts will consider options for obtaining better data on
the quantity of peat harvested per hectare and the total area
undergoing peat extraction.
Table 7-41: Tier-2 Quantitative Uncertainty Estimates for C02 and N20 Emissions from Lands Undergoing
Peat Extraction
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lands Undergoing
Peat Extraction
Lands Undergoing
Peat Extraction
C02
N20
Lower Bound
1.0 0.7
+ +
Upper Bound
1.3
+
Lower Bound
-31%
-73%
Upper Bound
+29%
+37%
+ Does not exceed 0.05 Tg C02 Eq.
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-55
-------
7.9. 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 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
for an average annual net sequestration of 79.1 Tg CO2 Eq.
(22 Tg C) over the period from 1990 through 2007. Total
sequestration increased by 61 percent between 1990 and
2007 due to increases in urban land area. Data on C storage
and urban tree coverage were collected since the early
1990s and have been applied to the entire time series in this
report. Annual estimates of CO2 flux were developed based
on periodic (1990 and 2000) U.S. Census data on urban
area (Table 7-42). Net C flux from urban trees in 2007 was
estimated to be -97.6 Tg CO2 Eq. (-26.6 Tg C).
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
Table 7-42: Net C Flux from Urban Trees
(Tg C02 Eq. and Tg C)
Year
Tg C02 Eq.
TgC
1990
(60.6)
(25.4)
(26.0)
(26.6)
(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 (2006), although
sufficient data are not yet available to determine interannual
gains and losses 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.
Most of the field data were analyzed using the U.S.
Forest Service's Urban Forest Effects (UFORE) model.52 The
UFOPsE model is a computer model that uses standardized
field data from random plots in each city and local air
pollution and meteorological data to quantify urban forest
structure, values of the urban forest, and environmental
effects, including total C stored and annual C sequestration
(Nowak et al. 2007a).
Nowak and Crane (2002) developed estimates of annual
gross C sequestration from tree growth and annual gross C
emissions from decomposition for 10 U.S. cities. Subsequent
studies have developed estimates for 5 more cities, resulting
in estimates for the following 15 cities: Atlanta, GA;
Baltimore, MD; Boston, MA; Chicago, IE; Freehold, NJ;
Jersey City, NJ; Minneapolis, MN; Moorestown, NJ; New
York, NY; Oakland, CA; Philadelphia, PA; San Francisco,
CA; Syracuse, NY; Washington, DC; and Woodbridge, NJ.
' J ' ' & ' ' & '
Field data was collected for a sample of trees in each of
the 15 cities during the period from 1989 through 2006,
Note: Parentheses indicate net sequestration.
52 Oakland and Chicago estimates were based on prototypes to the UFORE
model.
7-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
including tree measurements of stem diameter, tree height,
crown height, and crown width, and information on location,
species, and canopy condition. The data for each tree was
converted into C storage by applying allometric equations
to estimate aboveground biomass, a root-to-shoot ratio
to convert aboveground biomass estimates to whole tree
biomass, moisture contents, a C content of 50 percent (dry
weight basis), and an adjustment factor to account for urban
trees having less aboveground biomass than predicted by
allometric equations based on forest trees. Carbon storage
estimates for deciduous trees were structured to include
only carbon stored in wood. These calculations were then
used to form an estimation equation for each species of tree,
encompassing a range of diameters.
Tree growth was estimated using annual height
growth and diameter growth rates for specific land uses
and diameter classes. Growth calculations were adjusted
by a factor to account for tree condition (fair to excellent,
poor, critical, dying, or dead). For each tree, the difference
in carbon storage estimates between year 1 and year x + 1
gave the gross amount of C sequestered. These annual gross
C sequestration rates for each species (or genus), diameter
class, and land-use condition (parks, transportation, vacant,
golf courses, etc.) were then scaled up to city estimates
using tree population information.
Gross C emissions result from tree death and removals.
These emissions were derived by applying estimates of annual
mortality and condition and assumptions about whether dead
trees were removed from the site to the total C stock estimate
for each city. Estimates of annual mortality rates by diameter
class and condition class were derived from a study of street-
tree mortality (Nowak 1986). Different decomposition rates
were applied to dead trees left standing compared with those
removed from the site. For removed trees, different rates were
applied to the removed/aboveground biomass in contrast to
the below ground biomass. The estimated 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.
The field data from the 15 cities, some of which are
unpublished (Nowak 2007c), are described in Nowak and
Crane (2002), Nowak et al. (2007a), and references cited
therein. The allometric equations applied to the field data
for each tree were taken from the scientific literature (see
Nowak 1994, Nowak et al. 2002), but if no allometric
equation could be found for the particular species, the
average result for the genus was used. The adjustment (0.8)
to account for less live tree biomass in urban trees was 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). Tree growth rates were
taken from existing literature. Average diameter growth was
based on the following sources: estimates for trees in forest
stands came from Smith and Shifley (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.
Growth rates were adjusted to account for tree condition.
Growth factors for Atlanta, Boston, Chicago, Freehold,
Jersey City, Moorestown, New York, Oakland, Philadelphia,
and Woodbridge were adjusted based on the typical growth
conditions of different land-use categories (e.g., forest stands,
park-like stands). Growth factors for the more recent studies
in Baltimore, Minneapolis, San Francisco, Syracuse, and
Washington were adjusted using an updated methodology
based on the condition of each individual tree, which is
determined using tree competition factors (depending on
whether it is open grown or suppressed) (Nowak 2007b).
Assumptions for which dead trees would be removed versus
left standing were developed specific to each land use and
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
calculated based on estimates of gross and net sequestration
from 13 of the 15 cities (Table 7-43), and urban area and
urban tree cover data for the United States. Annual net
C sequestration estimates53 were derived for 13 cities
by subtracting the annual gross emission estimates from
the annual gross sequestration estimates. The urban area
estimates were based on 1990 and 2000 U.S. Census data.
53 Net estimates were not available for two cities (Chicago and Oakland).
Land Use, Land-Use Change, and Forestry 7-57
-------
Table 7-43: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover (Percent), and
Annual C Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for 15 U.S. Cities
City
Atlanta, GA
Baltimore, MD
Boston, MA
Chicago, IL
Freehold, NJ
Jersey City, NJ
Minneapolis, MN
Moorestown, NJ
New York, NY
Oakland, CA
Philadelphia, PA
San Francisco, CA
Syracuse, NY
Washington, DC
Woodbridge, NJ
NA = not analyzed.
Sources: Nowakand
Carbon
Stocks
1,219,256
541,589
289,392
NA
18,144
19,051
226,796
106,141
1,224,699
NA
480,808
175,994
156,943
477,179
145,150
Crane (2002) and
Gross Annual
Sequestration
42,093
14,696
9,525
NA
494
807
8,074
3,411
38,374
NA
14,606
4,627
4,917
14,696
5,044
Nowak(2007a,c).
Net Annual
Sequestration
32,169
9,261
6,966
NA
318
577
4,265
2,577
20,786
NA
10,530
4,152
4,270
11,661
3,663
Tree
Cover
36.7%
21.0%
22.3%
11.0%
34.4%
11.5%
26.4%
28.0%
20.9%
21.0%
15.7%
11.9%
23.1%
28.6%
29.5%
Gross Annual
Sequestration per
Area of Tree Cover
0.34
0.35
0.30
0.61
0.28
0.18
0.20
0.32
0.23
NA
0.27
0.33
0.33
0.32
0.28
Net Annual
Sequestration per
Area of Tree Cover
0.26
0.22
0.22
NA
0.18
0.13
0.11
0.24
0.12
NA
0.20
0.29
0.29
0.26
0.21
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 (0.31 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 (0.72). The urban tree cover
estimates for each of the 15 cities and the United States were
obtained from Dwyer et al. (2000), Nowak et al. (2002), and
Nowak (2007a). 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 13 of the 15 U.S. cities. A 10 percent
uncertainty was associated with urban area estimates while a
5 percent uncertainty was associated with percent urban tree
coverage. Both of these uncertainty estimates were based on
expert judgment. Uncertainty associated with estimates of
gross and net C sequestration for 13 of the 15U.S. cities was
based on standard error estimates for each of the city-level
sequestration estimates reported by Nowak (2007c). These
estimates are based on field data collected in 13 of the 15
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
7-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-44: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees
(Tg C02 Eq. and Percent)
Source
Changes in C Stocks
in Urban Trees
Gas
C02
2007 Flux Estimate
(Tg C02 Eq.)
(97.6)
Uncertainty Range Relative to Flux Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
(115.3) (77.3)
Lower Bound Upper Bound
-18% +21%
Note: Parentheses indicate net sequestration.
(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. Due
to data limitations, urban soil flux is not quantified as part of
this analysis, while reconciliation of urban tree and forest tree
estimates will be addressed through the land representation
effort described at the beginning of this chapter.
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 7-44. The net C flux from changes in
C stocks in urban trees in 2007 was estimated to be between
-115.3 and-77.3 Tg CO2 Eq. at a 95 percent confidence level.
This indicates a range of 18 percent below and 21 percent
above the 2007 flux estimate of -97.6 Tg CO2 Eq.
QA/QC and Verification
The net C flux resulting from urban trees was calculated
using estimates of gross and net C sequestration 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 this
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, 2007b).
Planned Improvements
A consistent representation of the managed land base
in the United States is being developed. A component
of this effort, which is discussed at the beginning of the
LULUCF chapter, will involve reconciling the overlap
between urban forest and non-urban forest greenhouse gas
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 Inventory. Planned
improvements to the FIA program include the development
of a long-term dataset that will define urban area boundaries
and make it possible to identify what area is forested. Once
those data become available, they will be incorporated into
estimates of net C flux resulting from urban trees.
Urban forest data for additional cities is expected in
the near future, and the use of this data will further refine
the estimated median sequestration value. It may also be
possible to report C losses and gains separately in the future.
It is currently not possible, since existing studies estimate
rather than measure natality or mortality; net sequestration
estimates are based on assumptions about whether dead trees
are being removed, burned, or chipped. There is an effort
underway to develop long-term data on permanent plots in
at least two cities, which would allow for direct calculation
of C losses and gains from observed rather than estimated
natality and mortality of trees.
Direct N20 Fluxes from Settlement
Soils (IPCC Source Category 5E1)
Of the synthetic N fertilizers applied to soils in the
United States, approximately 2.5 percent are currently
applied to lawns, golf courses, and other landscaping
occurring within settlement areas. Application rates are lower
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 2007, N2O emissions from this source were 1.6 Tg CO2
Eq. (5.2 Gg). There was an overall increase of 61 percent
over the period from 1990 through 2007 due to a general
Land Use, Land-Use Change, and Forestry 7-59
-------
Table 7-45: N20 Fluxes from Soils in Settlements
Remaining Settlements (Tg C02 Eq. and Gg N20)
Year
Tg C02 Eq.
Gg
1990
1.0
3.2
2005
2006
2007
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.
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 7-45.
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 (see Annex 3.11
for a detailed discussion of the methodology for estimating
sewage sludge application).
Nitrogen applications to settlement soils are estimated
using data compiled by the USGS (Ruddy et al. 2006). The
USGS estimated on-farm and non-farm fertilizer use based
on sales records at the county level from 1982 through 2001
(Ruddy et al. 2006). Non-farm N fertilizer was assumed to be
applied to settlements and forests and values for 2002 through
2007 were based on 2001 values adjusted for annual total N
fertilizer sales in the United States. Settlement application
was calculated by subtracting forest application from total
non-farm fertilizer use. Sewage sludge applications were
derived from national data on sewage sludge generation,
disposition, and N 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 directN2O 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, oxygen gas 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 does not incorporate any of
these variables and only accounts for variations in 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 in addition to the emission factors.
Uncertainty in fertilizer N application was assigned a
default level54 of +50 percent. Uncertainty in the amounts
of sewage sludge applied to non-agricultural lands and used
in surface disposal was derived from variability in several
factors, including: (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. Uncertainty in the emission factors was provided
by the IPCC (2006).
Quantitative uncertainty of this source category was
estimated through the IPCC-recommended Tier 2 uncertainty
estimation methodology. The uncertainty ranges around the
2005 activity data and emission factor input variables were
directly applied to the 2007 emission estimates. The results of
the quantitative uncertainty analysis are summarized in Table
7-46. N2O emissions from soils in Settlements Remaining
Settlements in 2007 were estimated to be between 0.8 and 4.2
54 No uncertainty is provided with the USGS application data (Ruddy et al.
2006) so a conservative ±50% was used in the analysis.
7-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-46: Quantitative Uncertainty Estimates of N20 Emissions from Soils in Settlements Remaining Settlements
(Tg C02 Eq. and Percent)
Source
Gas
2007 Emissions
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Settlements Remaining Settlements:
N20 Fluxes from Soils N20
1.6
0.8
4.2
-49%
+163%
Note: This estimate includes direct N20 emissions from N fertilizer additions to both Settlements Remaining Settlements and from Land Converted
to Settlements.
Tg CO2 Eq. at a 95 percent confidence level. This indicates
a range of 49 percent below to 163 percent above the 2007
emission estimate of 1.6 Tg CO2 Eq.
Recalculations Discussion
The total amount of fertilizer in non-agricultural uses
has been estimated by the USGS for 1990 through 2001
on a county scale from fertilizer sales data (Ruddy et al.
2006). In previous Inventories, data for 2001 was used for
subsequent years without adjustment. For subsequent years in
the current Inventory (2002 though 2007), county-level data
on non-farm fertilizer use for 2001 were adjusted based on
annual fluctuations in total U.S. fertilizer sales. This change
resulted in a small (less than 1 percent on average) increase
in emissions relative to the previous Inventory.
Planned Improvements
A minor improvement is to update the uncertainty
analysis for direct emissions from settlements to be consistent
with the most recent activity data for this source.
7.10. 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.
7.11. Other
(IPCC Source Category 5G)
Changes in Yard Trimming and Food
Scrap Carbon Stocks in Landfills
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. Carbon
contained in landfilled yard trimmings and food scraps can
be stored for very long periods.
Carbon storage estimates are associated with particular
land uses. For example, harvested wood products are
accounted for under Forest Land Remaining Forest Land
because these wood products are a component of the forest
ecosystem. The wood products serve as reservoirs to which
C resulting from photosynthesis in trees is transferred, but
the removals in this case occur in the forest. Carbon stock
changes in yard trimmings and food scraps are associated
with settlements, but removals in this case do not occur within
settlements. To address this complexity, yard trimming and
food scrap C storage is therefore reported under the "Other"
source category.
Both the amount of yard trimmings collected annually
and the fraction that is landfilled have declined over the last
decade. In 1990, over 50 million metric tons (wet weight)
of yard trimmings and food scraps were generated (i.e.,
Land Use, Land-Use Change, and Forestry 7-61
-------
put at the curb for collection to be taken to disposal sites
or to composting facilities) (EPA 2008; Schneider 2007,
2008). Since then, programs banning or discouraging yard
trimmings disposal have led to an increase in backyard
composting and the use of mulching mowers, and a
consequent 7 percent decrease in the tonnage generated (i.e.,
collected for composting or disposal). 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 29 percent in 2007. The net effect of the reduction
in generation and the increase in composting is a 62 percent
decrease in the quantity of yard trimmings disposed in
landfills since 1990.
Food scraps generation has grown by 52 percent since
1990, but the proportion of food scraps discarded in landfills
has decreased slightly from 81 percent in 1990 to 79 percent
in 2007. Overall, the decrease in the yard trimmings landfill
disposal rate has more than compensated for the increase
in food scrap disposal in landfills, and the net result is a
decrease in annual landfill carbon storage from 23.5 Tg
CO2 Eq. in 1990 to 9.8 Tg CO2 Eq. in 2007 (Table 7-47 and
Table 7-48).
Methodology
When wastes of sustainable, biogenic origin (such as
yard trimmings and food scraps) are landfilled and do not
completely decompose, the C that remains is effectively
removed from the global C cycle. Empirical evidence
indicates that yard trimmings and food scraps do not
completely decompose in landfills (Barlaz 1998, 2005,
2008), and thus the stock of carbon in landfills can increase,
with the net effect being a net atmospheric removal of
carbon. 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). Carbon
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
Table 7-47: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C02 Eq.)
Carbon Pool
1990
1995
2000
2005
2006
2007
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
(21.2)
(1.9)
(9.7)
(9.7)
(2.2)
IOZ.5) (8.2)
(0.8) (0.4)
(6.0) (4.0)
(5.8) (3.7)
(6.6)
(0.4)
(3.3)
(3.0)
(3.5)
(6.8)
(0.5)
(3.3)
(3.0)
(3.6)
(6.3)
(0.4)
(3.1)
(2.8)
(3.5)
Total Net Flux
(23.5)
(13.9)
(11.3)
(10.2) (10.4)
(9.8)
Note: Totals may not sum due to independent rounding.
Table 7-48: 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
1990
(5.8)
(0.5)
(2.7)
(2.6)
(0.6)
(6.4)
1995
(3.4)
(0.2)1
(1.6)
(1.6)
(0.4)
(3.8)
2000
(2.2)
(0-1)1
(1.1)
(1.0)
(0.9)
(3-D
2005
(1.8)
(0.1)
(0.9)
(0.8)
(1.0)
(2.8)
2006
(1.8)
(0.1)
(0.9)
(0.8)
(1.0)
(2.8)
2007
(1.7)
(0.1)
(0.8)
(0.8)
(0.9)
(2.7)
Note: Totals may not sum due to independent rounding.
7-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
landfilled yard trimmings and food scraps; 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 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:
2007 Facts and Figures (EPA 2008), which provides data
for 1960, 1970, 1980, 1990, 2000, 2002, and 2004 through
2007. To provide data for some of the missing years, detailed
backup data was obtained from Schneider (2007, 2008).
Remaining years in the time series for which data were not
provided were estimated using linear interpolation. The
EPA (2008) report does not subdivide discards of individual
materials into volumes landfilled and combusted, although it
provides an estimate of the proportion of overall waste stream
discards managed in landfills and combustors (i.e., ranging
from 92 percent and 8 percent respectively in 1984—86, 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 and the C
storage factors were determined by Barlaz (1998, 2005,
2008) (Table 7-49).
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, 2008), a
portion of the initial C resists decomposition and is essentially
persistent in the landfill environment. Barlaz (1998, 2005,
2008) 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 7-49).
The modeling approach applied to simulate U.S. landfill
C flows builds on the findings of Barlaz (1998,2005,2008).
The proportion of C stored is assumed to persist in landfills.
The remaining portion is assumed to degrade, resulting in
emissions of CK4 and CO2 (the CK4 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. Food scraps are assumed to have a half-life of 3.7
years; grass is assumed to have a half-life of 5 years; leaves
are assumed to have a half-life of 20 years; and branches
are assumed to have a half-life of 23.1 years. The half-life
of food scraps is consistent with analysis for landfill CK4 in
the Waste chapter.
Table 7-49: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%), Initial C Content (%),
and Half-Life (years) for Landfilled Yard Trimmings and Food Scraps in Landfills
Variable
Moisture Content (% H20)
CS, proportion of initial C stored (%)
Initial C Content (%)
Half-life (years)
Grass
70
53
45
5
Yard Trimmings
Leaves
30
85
46
20
Branches
10
77
49
23
Food Scraps
70
16
51
4
Land Use, Land-Use Change, and Forestry 7-63
-------
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:
LFC u = Ł Wu x (1 - MQ) x ICQ x
n
{[CS; x ICQ] + [(1 - (CS; x ICQ)) x e-k(t-n)]}
where,
= Year for which C stocks are being estimated
(year)
i = Waste type for which C stocks are being
estimated (grass, leaves, branches, food
scraps)
LFQ t = Stock of C in landfills in year t, for waste i
(metric tons)
W; n = Mass of waste i disposed in landfills in year
n (metric tons, wet weight)
n = Year in which the waste was disposed (year,
where 1960 < n < t)
MQ = Moisture content of waste i (percent of water)
CSj = Proportion of initial C that is stored for
waste i (percent)
ICQ = Initial C content of waste i (percent),
e = Natural logarithm
k = First order rate constant for waste i, which
is equal to 0.693 divided by the half-life for
decomposition (year"1)
For a given year t, the total stock of C in landfills (TLFQ)
is the sum of stocks across all four materials (grass, leaves,
branches, food scraps). The annual flux of C in landfills (Ft)
for year t is calculated as the change in stock compared to
the preceding year:
Ft = TLFQ - TLFQ _ 1
Thus, the C placed in a landfill in year n is tracked for
each year t through the end of the inventory period (2007). For
example, disposal of food scraps in 1960 resulted in depositing
about 1,135,000 metric tons of C. Of this amount, 16 percent
(179,000 metric tons) is persistent; the remaining 84 percent
(956,000 metric tons) is degradable. By 1964, more than half
of the degradable portion (500,000 metric tons) decomposes,
leaving a total of 635,000 metric tons (the persistent portion,
plus the remainder of the degradable portion).
Continuing the example, by 2007, the total food scraps
C originally disposed in 1960 had declined to 179,000 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
2007), the total landfill C from food scraps in 2007 was 30.6
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 2007, yielding a value of 240.4 million metric tons
(as shown in Table 7-50). 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 7-48) is the difference in the
landfill C stock for that year and the stock in the preceding
year. For example, the net change in 2007 shown in Table
7-48 (2.7 Tg C) is equal to the stock in 2007 (240.4 Tg C)
minus the stock in 2006 (237.7 Tg C).
The C stocks calculated through this procedure are
shown in Table 7-50.
Uncertainty
The uncertainty analysis for landfilled yard trimmings
and food scraps includes an evaluation of the effects of
uncertainty for the following 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).
Table 7-50: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
1990
1995
2000
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
160.3
16.2
71.7
72.5
18.4
20.9
24.3
2005
206.2
19.2
93.6
93.4
28.7
2006
208.0
19.4
94.5
94.2
29.7
2007
209.7
19.5
95.3
94.9
30.6
Total Carbon Stocks
178.7
204.4
220.3
234.9
237.7
240.4
Note: Totals may not sum due to independent rounding.
7-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 7-51: Tier 2 Quantitative Uncertainty Estimates for C02 Flux from Yard Trimmings and Food Scraps in Landfills
(Tg C02 Eq. and Percent)
Source
Yard Trimmings
and Food Scraps
Gas
C02
2007 Flux Estimate
(Tg C02 Eq.)
(9.8)
Uncertainty Range Relative to Flux Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
(17.9) (5.5)
Lower Bound Upper Bound
-84% +44%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate net sequestration.
There are respective uncertainties associated with each of
these factors.
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 7-51. Total yard trimmings
and food scraps CO2 flux in 2007 was estimated to be between
-17.9 and -5.5 Tg CO2 Eq. at a 95 percent confidence level (or
19 of 20 Monte Carlo stochastic simulations). This indicates
a range of 84 percent below to 44 percent above the 2007
flux estimate of -9.8 Tg CO2 Eq. More information on the
uncertainty estimates for Yard Trimmings and Food Scraps
in Landfills is contained within the Uncertainty Annex.
QA/QC and Verification
A QA/QC analysis was performed for data gathering
and input, documentation, and calculation.
Recalculations Discussion
The current Inventory uses updated data from
Municipal Solid Waste Generation, Recycling, and
Disposal in the United States: 2007 Facts and Figures
(EPA 2008), which provides updated data through 2007
including revisions to the amount of food scraps generated
in 2000 and 2004 through 2007. This update results in 4.6
and 0.5 percent decreases in carbon storage on average
across the time series for food scraps and yard trimmings,
respectively. This translates to an average 1.0% decrease
in carbon storage on average across the time series for the
entire source category.
Planned Improvements
Future work is planned to develop improved estimates
of the decay rates for the individual materials. Additional
analysis may also be performed to evaluate the potential
contribution of inorganic C, primarily in the form of
carbonates, to landfill sequestration, as well as the consistency
between the estimates of C storage described in this chapter
and the estimates of landfill CFL, emissions described in the
Waste chapter.
Land Use, Land-Use Change, and Forestry 7-65
-------
8. Waste
Figure 8-1
2007 Waste Chapter Greenhouse Gas Emission Sources
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 8-1).
Landfills accounted for approximately 23 percent of total U.S. anthropogenic methane (CH4) emissions
in 2007,: the second largest contribution of any CtLj source in the United States. Additionally, wastewater
treatment and composting of organic waste accounted for approximately 4 percent and less than 1 percent of U.S. CH4
emissions, respectively. 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. N2O emissions from composting
were also estimated. Together, these waste activities account
for approximately 2 percent of total U.S. N2O emissions.
Nitrogen oxide (NOX), carbon monoxide (CO), andnon-CH4
volatile organic compounds (NMVOCs) are emitted by waste
activities, and are addressed separately at the end of this
chapter. A summary of greenhouse gas emissions from the
Waste chapter is presented in Table 8-1 and Table 8-2.
Overall, in 2007, waste activities generated emissions
of 165.6 teragrams of carbon dioxide equivalents (Tg CO2
Eq.) or just over 2 percent of total U.S. greenhouse gas
emissions.
Landfills
Composting
20
60 80
Tg C02 Eq.
100
120
140
Table 8-1: Emissions from Waste (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Landfills
Wastewater Treatment
Composting
N20
Domestic Wastewater Treatment
Composting
153.8
127.8
24.3
1.6
6.5
4.8
1.7
156.5
130.4
24.5
1.6
6.6
4.8
1.8
158.9
132.9
24.4
1.7
6.7
4.9
1.8
Total
177.1
174.7
154.6
160.2
163.0
165.6
Note: Totals may not sum due to independent rounding.
1 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 8-1
-------
Table 8-2: Emissions from Waste (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
CH4
Landfills
Wastewater Treatment
Composting
N20
Domestic Wastewater Treatment
Composting
Note: Totals may not sum due to independent rounding.
7,322
6,088
1,159
75
21
15
6
7,451
6,211
1,165
75
21
15
6
7,566
6,327
1,160
79
22
16
6
8.1. Landfills (IPCC Source
Category 6A1)
In 2007, landfill CK4 emissions were approximately
132.9 Tg CO2 Eq. (6,327 Gg of CH4), representing the second
largest source of CH^ emissions in the United States, behind
enteric fermentation. Emissions from municipal solid waste
(MSW) landfills, which received about 64.5 percent of the
total solid waste generated in the United States, accounted for
about 90 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 CH^ (BioCycle 2006, adjusted to include
missing data from five states).
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 CELrproducing
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 CELj production
typically begins one or two years after waste disposal in a
landfill and continues for 10 to 60 years or longer.
From 1990 to 2007, net CH4 emissions from landfills
decreased by approximately 10 percent (see Table 8-3 and
Table 8-4). This net CH4 emissions decrease is the result
of increases in the amount of landfill gas collected and
combusted,3 which has more than offset the additional
CH4 generation resulting from an increase in the amount of
municipal solid waste landfilled over the past 17 years. Over
the past 6 years, however, the net CH4 emissions have slowly
increased, but have remained relatively steady since 2005.
While the amount of landfill gas collected and combusted
continues to increase every year, the rate of increase no longer
exceeds that rate of additional CK4 generation resulting from
an increase in the amount of municipal solid waste landfill ed
as the U.S. population grows.
Methane emissions from landfills are a function of
several factors, including: (1) the total amount of waste in
MSW landfills, which is related to total waste landfilled
annually; (2) the characteristics of landfills receiving waste
(i.e., composition of waste-in-place, size, climate); (3) the
amount of CELj 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 MSW landfills
increased from about 209 Tg in 1990 to 291 Tg in 2007, an
increase of 28 percent (see Annex 3.14). During this period, the
estimated CELj recovered and combusted from MSW landfills
increased as well. In 1990, for example, approximately 878 Gg
of CELj were recovered and combusted (i.e., used for energy
or flared) from landfills, while in 2007, 5,812 Gg CH4 was
combusted. In 2007, an estimated 59 new landfill gas-to-energy
(LFGTE) projects and 55 new flares began operation, resulting
2 The percentage of CO2 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
NMVOCs.
3 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.
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 8-3: CH4 Emissions from Landfills (Tg C02 Eq.)
Activity
1990
1995
2000
2005
2006
2007
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
172.6
11.6
(13.3)
(5.1)
(16.6)
191.8
12.9
(22.3)
(22.0)
(16.0)
206.9
14.4
(49.3)
(36.2)
(13.6)
241.2
15.3
(56.8)
(57.6)
(14.2)
248.1
15.3
(59.2)
(59.3)
(14.6)
254.2
15.4
(64.3)
(57.7)
(14.8)
Total
149.2
144.3
122.3
127.8
130.4
132.9
'Includes oxidation at both municipal and industrial landfills.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 8-4: CH4 Emissions from Landfills (Gg)
Activity
1990
2000
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
(1,064)
(1,048)
(763)
(2,348)
(1,722)
(647)
2005
2006
11,486
728
(2,707)
(2,743)
(676)
11,813
730
(2,819)
(2,822)
(690)
2007
12,107
735
(3,062)
(2,750)
(703)
Total
7,105
'Includes oxidation at both municipal and industrial landfills.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
5,825
6,088
6,211
6,327
in a 3 percent increase in the quantity of CH^ recovered and
combusted from 2006 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 CH^ that
is recovered and either flared or used for energy purposes is
expected to continue to increase as a result of 1996 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 CH^ recovery and use such as EPA's
Landfill Methane Outreach Program (LMOP), and federal and
state incentives that promote renewable energy (e.g. tax credits,
low interest loans, and Renewable Portfolio Standards).
Methodology
A detailed description of the methodology used to
estimate CH4 emissions from landfills can be found in
Annex 3.14.
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 CH^
recovered and combusted, minus the CH4 oxidized before
being released into the atmosphere:
CH
-4, Solid Waste
- [CH4
MSW
CH4ind - R] - Ox
where,
R
Ox
CH4 Soiid waste = CH4 emissions from solid waste
= CH^ generation from municipal solid
waste landfills,
= CH^ generation from industrial landfills,
= CH4 recovered and combusted, and
= GIL, oxidized from MSW and
industrial landfills before release to
the atmosphere.
The methodology for estimating CH^ 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 (L0) and rate constant (k) were obtained from an
Waste 8-3
-------
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
2007 was extrapolated based on BioCycle data and the U.S.
Census population from 2006. Data for 1989 through 2006
were obtained from BioCycle (2006). Because BioCycle
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
(2007) 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. For calculations in this Inventory, wastes landfilled
prior to 1980 were broken into two groups: wastes disposed
in landfills (CH4 correction factor, or MCF, of 1) and those
disposed in dumps (MCF of 0.6). Please see Annex 3.14 for
more details.
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 2008), and a database
maintained by the Energy Information Administration (El A)
for the voluntary reporting of greenhouse gases (EIA 2007).
As the EIA database only included data through 2006, 2007
recovery for projects included in the EIA database were
assumed to be the same as in 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 2007 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 CFL, 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 (ERG 2008), waste
disposal factors, and the first order decay model. As over
99 percent of the organic waste placed in industrial landfills
originated from the food processing (meat, vegetables,
fruits) and pulp and paper industries, estimates of industrial
landfill emissions focused on these two sectors (EPA 1993).
The amount of CFL, oxidized by the landfill cover at both
municipal and industrial landfills was assumed to be ten
percent of the CFL, generated that is not recovered (IPCC
2006, Mancinelli and McKay 1985, Czepiel et al. 1996). To
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
calculate net CH4 emissions, both CH4 recovered and CH4
oxidized were subtracted from CFL, 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 CK4 production: the amount and composition of
waste placed in every landfill for each year of its operation.
The approach used here assumes that the CFL, 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 CH4 estimated to be recovered).
For flaring without metered recovery data (approximately
34 percent of the CH4 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. Furthermore, the 2006 IPCC Guidelines
(IPCC 2006) did not include a methodology for estimating
N2O emissions from solid waste disposal sites "because they
are not significant." Therefore, any uncertainty or bias caused
by not including N2O emissions from landfills is expected
to be minimal.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 8-5. Landfill CK4 emissions in 2007
were estimated to be between 80.6 and 176.2 Tg CO2 Eq.,
which indicates a range of 39 percent below to 33 percent
above the 2007 emission estimate of 132.9 Tg CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and
input, documentation, and calculation. A primary focus of the
QA/QC checks was to ensure that CFL, recovery estimates
were not double-counted. Both manual and electronic checks
were made to ensure that emission avoidance from each
landfill was calculated only in one of the three databases.
The primary calculation spreadsheet is tailored from the
IPCC waste model and has been verified previously using the
original, peer-reviewed IPCC waste model. All model input
values were verified by secondary QA/QC review.
Recalculations Discussion
In developing the current Inventory, the data that formed
the basis of the industrial food processing waste DOC values
were re-analyzed. Based on the re-analysis of the available
data for industrial food processing waste, the DOC value for
industrial food waste was revised from 0.29 to 0.26 (Coburn
2008). This decrease in food industries' DOC value led to a
slight decrease in CK4 generation and CK4 emissions from
food industry landfills.
Planned Improvements
For future Inventories, additional efforts will be made
to improve the estimates of the amount of waste placed in
MSW landfills. Improvements to the flare database will be
investigated, and an effort will be made to identify additional
landfills that have flares.
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Landfills
CH4
132.9
80.6
176.2
-39%
+33%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Waste 8-5
-------
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).
8.2. Wastewater Treatment (IPCC
Source Category 6B)
Wastewater treatment processes can produce
anthropogenic CtLj, N2O, and in some cases, CO2, emissions.4
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,5 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 2007b).
Soluble organic matter is generally removed using
biological processes in which microorganisms consume the
organic matter for maintenance and growth. The resulting
4 Wastewater treatment at petroleum refineries can produce anthropogenic
CO2. Estimates of these emissions are found in the Petroleum Systems
section of the Energy chapter.
5 Package plants are treatment plants assembled in a factory, skid mounted,
and transported to the treatment site.
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 N 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 CK4 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 CH4 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 CH^ production. The
principal factor in determining the N2O generation potential
of wastewater is the amount of N in the wastewater.
In 2007, CH4 emissions from domestic wastewater
treatment were 15.8 Tg CO2 Eq. (755 Gg). Emissions
gradually increased from 1990 through 1996, but have
decreased since that time 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 2007, CH4 emissions from industrial
wastewater treatment were estimated to be 8.5 Tg CO2 Eq.
(405 Gg). Industrial emission sources have increased across
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 8-6: CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.)
Activity
1990
1995
2000
2005
2006
2007
CH4
Domestic
Industrial3
N20
Domestic
23.5
16.4
7.1
3.7
3.7
I 24.8 25.2
16.9 16.8
8.01 8.4
4.0 4.5
24.3
16.2
8.2
4.8
4.8
24.5
16.0
8.5
4.8
4.8
24.4
15.8
8.5
4.9
4.9
Total
27.2
28.9
29.6
29.1
29.3
Table 8-7: CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
1990
1995
2005
CH4
Domestic
Industrial3
N20
Domestic
1,120
782
338
12
12
2006
1,165
762
403
15
15
29.2
a Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, starch-based ethanol
production, and petroleum refining industries.
Note: Totals may not sum due to independent rounding.
2007
1,160
755
405
16
16
a Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, starch-based ethanol
production, and petroleum refining industries.
Note: Totals may not sum due to independent rounding.
the time series through 1999 and then fluctuated up and down
with production changes associated with the treatment of
wastewater from the pulp and paper manufacturing, meat and
poultry processing, fruit and vegetable processing, starch-
based ethanol production, and petroleum refining industries.6
Table 8-6 and Table 8-7 provide CfLj and N2O emission
estimates from domestic and industrial wastewater treatment.
With respect to N2O, the United States identifies two distinct
sources for N2O 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 2007 emissions of N2O from centralized wastewater
treatment processes and from effluent were estimated to
be 0.3 Tg CO2 Eq. (1 Gg) and 4.6 Tg CO2 Eq. (15 Gg),
respectively. Total N2O emissions from domestic wastewater
were estimated to be 4.9 Tg CO2 Eq. (16 Gg). N2O emissions
from wastewater treatment processes gradually increased
across the time series as a result of increasing U.S. population
and protein consumption.
6 Other industrial sectors include organic chemicals, starch production,
alcohol refining, creameries, seafood processing, steam electric power
generation, fertilizer manufacturing, and textiles; however, emissions from
these sectors are considered to be insignificant.
Methodology
Domestic Wastewater CH4 Emission Estimates
Domestic wastewater CK4 emissions originate from both
septic systems and from centralized treatment systems, such
as publicly owned treatment works (POTWs). Within these
centralized systems, CELj emissions can arise from aerobic
systems that are not well managed or that are designed to have
periods of anaerobic activity (e.g., constructed wetlands),
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 (20 percent), the maximum CELj
producing capacity for domestic wastewater (0.60 kg CH4/kg
BOD), and the MCF for septic systems (0.5). CELj emissions
from POTWs were estimated by multiplying the total BOD5
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
relative percentage of wastewater facilities with primary
treatment, the percentage of BOD5 treated after primary
treatment (67.5 percent), the maximum CH4-producing
Waste 8-7
-------
capacity of domestic wastewater (0.6), 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 (0.65), the density of CH4 (662 g
CtLj/m3 CFy,7 and the destruction efficiency associated with
burning the biogas in an energy/thermal device (0.99).8 The
methodological equations are:
Emissions from Septic Systems = A
= (% onsite) x (total BOD5 produced) x (B0) x
(MCF-septic)xl/106
Emissions from Centrally Treated Aerobic Systems = B
= [(% collected) x (total BOD5 produced) x (% aerobic) x
(% aerobic w/out primary) + (% collected) x
(total BOD5 produced) x (% aerobic) x
(% aerobic w/primary) x
(1-% BOD removed in prim, treat.)] x
(% operations not well managed) x (B0) x
(MCF-aerobic_not_well_man.) x 1/106
Emissions from Centrally Treated Anaerobic Systems = C
= [(% collected) x (total BOD5 produced) x
(% anaerobic) x (% anaerobic w/out primary) +
(% collected) x (total BOD5 produced) x
(% anaerobic) x (% anaerobic w/primary) x
(1-%BOD removed in prim, treat.)] x (B0) x
(MCF-anaerobic) x 1/106
Emissions from Anaerobic Digesters = D
= [(POTW_flow_AD) x (digester gas)/(per capita flow)] x
conversion to m3 x (FRACJZF^) x (365.25) x
(density of CH4) x (1-DE) x 1/109
Total CFLj Emissions (Gg) =A + B + C + D
where,
% onsite
% collected =
% aerobic =
% anaerobic =
How to septic systems/total flow
How to POTWs/total flow
How to aerobic systems/total flow
to POTWs
How to anaerobic systems/total
flow to POTWs
w/out
primary
% aerobic
w/primary
%BOD
removed in
prim, treat.
% operations
not well
managed
% anaerobic
w/out
primary
% anaerobic
w/primary
Total BOD5
produced
MCF-septic =
1/106
MCF-aerobic_
not_
well man. :
MCF-
anaerobic
DE
POTW_
flow_AD
digester gas =
Percent of aerobic systems that do
not employ primary treatment
Percent of aerobic systems that
employ primary treatment
Percent of aerobic systems that are
not well managed and in which
some anaerobic degradation occurs
Percent of anaerobic systems that
do not employ primary treatment
Percent of anaerobic systems that
employ primary treatment
kg BOD/capita/day x U.S.
population x 365.25 days/yr
Maximum CH4-producing capacity
for domestic wastewater (0.60 kg
CH4/kg BOD)
CH4 correction factor for septic
systems (0.5)
= Conversion factor, kg to Gg
7 Based on air at 70° F and 1 atm.
8 Anaerobic digesters at wastewater treatment plants generated 798 Gg
CH4 in 2006, 790 Gg of which was combusted in flares or energy devices
(assuming a 99% destruction efficiency).
j correction factor for aerobic
systems that are not well managed
(0.3)
CFLj correction factor for anaerobic
systems (0.8)
CFLj destruction efficiency from
flaring or burning in engine (0.99
for enclosed flares)
Wastewater influent flow to POTWs
that have anaerobic digesters (gal)
Cubic feet of digester gas produced
per person per day (1.0 ft3/person/
day) (Metcalf and Eddy 1991)
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
per capita
flow
conversion
torn3
FRAC_CH4
density of
CH4
1/109
= Wastewater flow to POTW per
person per day (100 gal/person/day)
= Conversion factor, ft3 to m3
(0.0283)
= Proportion CH4 in biogas (0.65)
= 662 (g CH4/m3 CH4)
= Conversion factor, g to Gg
Table 8-8: U.S. Population (Millions) and Domestic
Wastewater BOD5 Produced (Gg)
U.S. population data were taken from the U.S. Census
Bureau International Database (U.S. Census 2008a) and
include the populations of the United States, American
Samoa, Guam, Northern Mariana Islands, Puerto Puco, and
the U.S. Virgin Islands. Table 8-8 presents U.S. population
and total BOD5 produced for 1990 through 2007. The
proportions of domestic wastewater treated onsite versus
at centralized treatment plants were based on data from the
1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, and 2005
American Housing Surveys conducted by the U.S. Census
Bureau (U.S. Census 2008b), with data for intervening
years obtained by linear interpolation. The wastewater flow
to aerobic 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 (EPA 1992, 1996, 2000, and 2004a).9 Data
for intervening years were obtained by linear interpolation.
The BOD5 production rate (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 MCFs were taken from IPCC (2006). The GIL, destruction
efficiency, 99 percent, was selected based on the range of
efficiencies (98 to 100 percent) recommended for flares
in AP-42 Compilation of Air Pollutant Emission Factors,
Chapter 2.4 (EPA 1998), efficiencies used to establish NSPS
for landfills, and in recommendations for closed flares used
by the LMOP The cubic feet of digester gas produced per
person per day (1.0 ft3/person/day) and the proportion of
j in biogas (0.65) come from Metcalf and Eddy (1991).
9 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.
Year
Population
BODS
1990
254
8,350
1995
271
8,895
2000
2001
2002
2003
2004
2005
2006
2007
287
289
292
295
297
300
303
306
9,419
9,509
9,597
9,685
9,774
9,864
9,954
10,043
Source: U.S. Census Bureau (2008a); Metcalf & Eddy 1991 and 2003.
The wastewater flow to a POTW (100 gal/person/day) was
taken from the Great Lakes-Upper Mississippi Paver Board
of State and Provincial Public Health and Environmental
Managers (2004), "Recommended Standards for Wastewater
Facilities (Ten-State Standards)."
Industrial Wastewater CH4 Emission Estimates
CH4 emissions estimates from industrial wastewater
were developed according to the methodology described in
IPCC (2006). 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 five industries that meet these criteria are pulp and paper
manufacturing; meat and poultry processing; vegetables,
fruits, and juices processing; starch-based ethanol production;
and petroleum refining. Wastewater treatment emissions for
these sectors for 2007 are displayed in Table 8-9.
Table 8-10 contains production data for these industries.
Table 8-9: Industrial Wastewater CH4 Emissions by
Sector for 2007
Pulp & Paper
Meat & Poultry
Petroleum Refineries
Fruit & Vegetables
Ethanol Refineries
Total
CH4 Emissions
(Tg C02 Eq.)
4.1
3.6
0.6
0.1
0.1
8.5
% of Industrial
Wastewater CH4
48%
43%
7%
1%
1%
100%
Waste 8-9
-------
Table 8-10: U.S. Pulp and Paper; Meat and Poultry; Vegetables, Fruits and Juices Production; and Fuels
Production (Tg)
Meat Poultry Vegetables,
Petroleum
Year Pulp and Paper (Live Weight Killed) (Live Weight Killed) Fruits and Juices Ethanol Refining
1990 128.9 27.3 14.6 38.7
1995 140.9 30.8 18.9 46.9
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^H
2000 142.8 32.1 22.2 50.9
2001 134.3 31.6 22.8 45.0
2002 132.7 32.7 23.5 47.7
2003 131.9 32.3 23.7 44.7
2004 136.4 31.2 24.4 47.8
2005 131.4 31.4 25.1 42.7
2006 137.4 32.5 25.5 43.5
2007 135.9 33.4 26.0 43.5
CH4 emissions from these categories were estimated W
by multiplying the annual product output by the average
outflow, the organics loading (in COD) in the outflow, COD
the percentage of organic loading assumed to degrade
anaerobically, and the emission factor. Ratios of BOD:COD TA
in various industrial wastewaters were obtained from EPA
(1997a) and used to estimate COD loadings. The B0 value %Plants0
used for all industries is the IPCC default value of 0.25 kg
CH4/kg COD (IPCC 2006). %WWap
For each industry, the percent of plants in the industry
that treat wastewater on site, the percent of plants that have a P
primary treatment step prior to biological treatment, and the
percent of plants that treat wastewater anaerobically were /oPlantsa
defined. The percent of wastewater treated anaerobically onsite
(TA) was estimated for both primary treatment and secondary /oPlantst
treatment. For plants that have primary treatment in place, an
estimate of COD that is removed prior to wastewater treatment a s
in the anaerobic treatment units was incorporated.
The methodological equations are: 07 ww
/c vv vv a Ł
CH4 (industrial wastewater) =
PxWxCODxTAxB0xMCF
2.7 702.4
^^^^^^^^^^^^^^^^^^^m
^^^^^^^^^^^^^^^^^^^H
4.2 735.6
^^^^^^^^^^^^^^^^^^^m
4.9 795.2
5.3 794.9
6.4 794.4
8.4 804.2
10.2 821.5
11.7 818.6
14.5 826.7
19.4 827.6
Wastewater generated (m3/metric
ton of product)
Organics loading in wastewater
(kg/m3)
Percent of wastewater treated
anaerobically on site
percent of plants with onsite
treatment
percent of wastewater treated an-
aerobically in primary treatment
percent of COD entering primary
treatment
percent of plants with anaerobic
secondary treatment
percent of plants with other
secondary treatment
percent of wastewater treated
anaerobically in anaerobic
secondary treatment
percent of wastewater treated
anaerobically in other secondary
treatment
TA = (%Plants0 x %WWap x %CODp) +
(%Plantsa x %WWa s x %CODS) +
(%Plantst x %WW t x %CODS)
where,
CH4
(industrial
wastewater) = Total CH4 emissions from industrial
wastewater (kg/year)
P = Industry output (metric tons/year)
%CODS
MCF
percent of COD entering secondary
treatment
Maximum CK4 producing potential
of industrial wastewater (default
value of 0.25 kg CHVkg COD)
CFLj correction factor, indicating the
extent to which the organic con-
tent (measured as COD) degrades
anaerobically
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 8-11: Variables Used to Calculate Percent Wastewater Treated Anaerobically by Industry
Variable
%TAP
%TAS
%Plants0
%Plantsa
%Plants,
%WW3ip
%wwaiS
%wwa,t
%CODP
%CODS
Pulp and
Paper
0
10.5
60
25
35
0
100
0
100
42
Meat
Processing
0
33
100
33
67
0
100
0
100
100
Poultry
Processing
0
25
100
25
75
0
100
0
100
100
Industry
Fruit/Vegetable
Processing
0
5.5
11
5.5
5.5
0
100
0
100
100
Ethanol
Production
—Wet Mill
0
33.3
100
33.3
66.7
0
100
0
100
100
Ethanol
Production
—Dry Mill
0
75
100
75
25
0
100
0
100
100
Petroleum
Refining
0
100
100
100
0
0
100
0
100
100
As described below, the values presented in Table 8-11
were used in the inventory calculations.
Pulp and Paper. 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. In the United States,
primary treatment is focused on solids removal, equalization,
neutralization, and color reduction (EPA 1993). The vast
majority of pulp and paper mills with on-site treatment
systems use mechanical clarifiers to remove suspended solids
from the wastewater. About 10 percent of pulp and paper
mills with treatment systems use settling ponds for primary
treatment and these are more likely to be located at mills that
do not perform secondary treatment (EPA 1993). However,
because the vast majority of primary treatment operations at
U.S. pulp and paper mills use mechanical clarifiers, and less
than 10 percent of pulp and paper wastewater is managed in
primary settling ponds that are not expected to have anaerobic
conditions, negligible emissions are assumed to occur during
primary treatment.
Approximately 42 percent of the BOD passes on to
secondary treatment, which consists of activated sludge,
aerated stabilization basins, or non-aerated stabilization
basins. No anaerobic activity is assumed to occur in
activated sludge systems or aerated stabilization basins
(note: although IPCC recognizes that some CH4 can be
emitted from anaerobic pockets, they recommend an MCF
of zero). However, about 25 percent of the wastewater
treatment systems used in the United States are non-aerated
stabilization basins. These basins are typically 10 to 25
feet deep. These systems are classified as anaerobic deep
lagoons (MCF = 0.8).
A time series of CH4 emissions for 1990 through 2001
was developed based on production figures reported in the
Lockwood-Post Directory (Lockwood-Post 2002). Published
data from the American Forest and Paper Association, data
published by Paper Loop, and other published statistics were
used to estimate production for 2002 through 2007 (Pulp and
Paper 2005, 2006 and monthly reports from 2003 through
2006; Paper 360° 2007). The overall wastewater outflow
was estimated to be 85 m3/metric ton, and the average BOD
concentrations in raw wastewater was estimated to be 0.4 gram
BOD/liter (EPA 1997b, EPA 1993, World Bank 1999).
Meat and Poultry Processing. 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.
Waste 8-11
-------
The IPCC default B0 of 0.25 kg CH4/kg COD 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 2008a). Data collected by
EPA's Office of Water provided estimates for wastewater
flows into anaerobic lagoons: 5.3 and 12.5 m3/metric
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.
Vegetables, Fruits, and Juices Processing. 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, 4.2
percent of these wastewater organics are assumed to degrade
anaerobically. The IPCC default B0 of 0.25 kg CHVkg COD
and default MCF of 0.8 for anaerobic treatment were used
to estimate the CH4 produced from these on-site treatment
systems. The USDA National Agricultural Statistics Service
(USDA 2008a) provided production data for potatoes, other
vegetables, citrus fruit, non-citrus fruit, and grapes processed
for wine. Outflow and BOD data, presented in Table 8-12, were
obtained from EPA (1974) for potato, citrus fruit, and apple
processing, and from EPA (1975) for all other sectors.
Ethanol Production. Ethanol, or ethyl alcohol, is
produced primarily for use as a fuel component, but is
also used in industrial applications and in the manufacture
of beverage alcohol. Ethanol can be produced from the
fermentation of sugar-based feedstocks (e.g., molasses
and beets), starch- or grain-based feedstocks (e.g., corn,
sorghum, and beverage waste), and cellulosic biomass
feedstocks (e.g., agricultural wastes, wood, and bagasse).
Ethanol can also be produced synthetically from ethylene or
hydrogen and carbon monoxide. However, synthetic ethanol
comprises only about 2 percent of ethanol production, and
Table 8-12: Wastewater Flow (m3/ton) and BOD
Production (g/L) for U.S. Vegetables, Fruits and
Juices Production
«„__„ j!(1, Wastewater Outflow
Commodity (m3/,on)
Vegetables
Potatoes
Other Vegetables
Fruit
Apples
Citrus
Non-citrus
Grapes (for wine)
10.27
8.81
3.66
10.11
12.42
2.78
BOD
(g/L)
1.765
0.808
1.371
0.317
1.204
1.831
although the Department of Energy predicts cellulosic
ethanol to greatly increase in the coming years, currently
it is only in an experimental stage in the United States.
According to the Renewable Fuels Association, 82 percent
of ethanol production facilities use corn as the sole feedstock
and 7 percent of facilities use a combination of corn and
another starch-based feedstock. The fermentation of corn is
the principal ethanol production process in the United States
and is expected to increase for at least the next 6 years,
and potentially more; therefore, emissions associated with
wastewater treatment at starch-based ethanol production
facilities were estimated (ERG 2006).
Ethanol is produced from corn (or other starch-based
feedstocks) primarily by two methods: wet milling and dry
milling. Historically, the majority of ethanol was produced
by the wet milling process, but now the majority is produced
by the dry milling process. The wastewater generated at
ethanol production facilities is handled in a variety of
ways. Dry milling facilities often combine the resulting
evaporator condensate with other process wastewaters,
such as equipment wash water, scrubber water, and boiler
blowdown and anaerobically treat this wastewater using
various types of digesters. Wet milling facilities often treat
their steepwater condensate in anaerobic systems followed by
aerobic polishing systems. Wet milling facilities may treat the
stillage (or processed stillage) from the ethanol fermentation/
distillation process separately or together with steepwater
and/or wash water. CH4 generated in anaerobic digesters is
commonly collected and either flared or used as fuel in the
ethanol production process (ERG 2006).
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Available information was compiled from the industry
on wastewater generation rates, which ranged from 1.25
gallons per gallon ethanol produced (for dry milling) to
10 gallons per gallon ethanol produced (for wet milling)
(Ruocco 2006a,b; Merrick 1998; Donovan 1996; andNRBP
2001). COD concentrations were also found to be about
3 g/L (Ruocco 2006a; Merrick 1998; White and Johnson
2003). The amount of wastewater treated anaerobically
was estimated, along with how much of the methane is
recovered through the use of biomethanators (ERG 2006).
CH4 emissions were then estimated as follows:
Methane = {Production x Flow x COD x 3.785 x
[(%Plants0 x %WWap x %CODp) +
(%Plantsa x %WWa s x %CODS) +
(%Plantst x %WWa t x %CODS)] x
B0 x MCF x % Not Recovered} +
{Production x How x 3.785 x COD x
[(%Plants0 x %WWap x %CODp) +
(%Plantsa x %WWa s x %CODS) +
(%Plantst x %WW3jt x %CODS)] x
B0 x MCF x % Recovered x (1-DE)} x 1/109
where,
Production
How
COD
3.785
%Plantsn
%WW
a,p
%COD
%Plantsa
%Plantst
= gallons ethanol produced
(wet milling or dry milling)
= gallons wastewater generated per
gallon ethanol produced (1.25 dry
milling, 10 wet milling)
= COD concentration in influent (3
g/1)
= conversion, gallons to liters
= percent of plants with onsite treat-
ment (100%)
= percent of wastewater treated
anaerobically in primary treatment
(0%)
= percent of COD entering primary
treatment (100%)
= percent of plants with anaerobic
secondary treatment (33.3% wet,
75% dry)
= percent of plants with other second-
ary treatment (66.7% wet, 25% dry)
= percent of wastewater treated an-
aerobically in anaerobic secondary
treatment (100%)
%WW3jt
%CODS
B0
MCF
% Recovered =
%Not
Recovered =
DE
1/109
percent of wastewater treated
anaerobically in other secondary
treatment (0%)
percent of COD entering secondary
treatment (100%)
maximum methane producing
capacity (0.25 g CH4/g COD)
methane conversion factor (0.8 for
anaerobic systems)
percent of wastewater treated in
system with emission recovery
1 - percent of wastewater treated in
system with emission recovery
= destruction efficiency of recovery
system (99%)
= conversion factor, g to Gg
A time series of CFLj emissions for 1990 through 2007
was developed based on production data from the Renewable
Fuels Association (REA 2005).
Petroleum Refining. Petroleum refining wastewater
treatment operations produce CH4 emissions from anaerobic
wastewater treatment. The wastewater inventory section
includes CFLj emissions from petroleum refining wastewater
treated on site under intended or unintended anaerobic
conditions. Most facilities use aerated biological systems,
such as trickling filters or rotating biological contactors; these
systems can also exhibit anaerobic conditions that can result
in the production of methane. Oil/water separators are used
as a primary treatment method; however, it is unlikely that
any COD is removed in this step.
Available information from the industry was compiled.
The wastewater generation rate, from CARB 2007 and
Timm 1985, was determined to be 35 gallons per barrel of
finished product. An average COD value in the wastewater
was estimated at 0.45 kg/m3 (Benyahia et al.).
The equation used to calculate CH4 generation at
petroleum refining wastewater treatment systems is presented
below:
Methane = How x COD x Bn x MCF
Where:
How
= Annual flow treated through
anaerobic treatment system (m3/year)
Waste 8-13
-------
COD = COD loading in wastewater entering
anaerobic treatment system (kg/m3)
B0 = maximum methane producing
potential of industrial wastewater
(default value of 0.25 kg CH4 /
kg COD)
MCF = methane conversion factor (0.3)
A time series of CH4 emissions for 1990 through 2007
was developed based on production data from the Energy
Information Association (EIA 2008).
Domestic Wastewater N20 Emission Estimates
N2O emissions from domestic wastewater (wastewater
treatment) were estimated using thelPCC (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.10
• The IPCC methodology uses annual, per capita
protein consumption [kg protein/(person-year)]. For
this Inventory, the amount of protein available to be
consumed is estimated based on per capita annual food
availability data and its protein content, and then adjusts
that data using a factor to account for the fraction of
protein actually consumed.11
• Small amounts of gaseous nitrogen oxides are
formed as byproducts in the conversion of nitrate
to N2 gas in anoxic biological treatment systems.
Approximately 7 grams NO is generated per capita
per year if wastewater treatment includes intentional
nitrification and denitrification (Scheehle and Doom
10 The methodology for estimating the quantity of sewage sludge N not
entering aquatic environments is described in Annex 3.11.
11 ERG identified two data sources needed to determine the consumption
factor. The first source is Table 7 of USDA's Nutrient Content of the U.S.
Food Supply, 1909-2004 Summary Report, which presents a time series
percentage of protein contributed by major food groups to the U.S. food
supply. The second source is Table 1 from Kantor (1997), which presents
the percentage of loss from the edible food supply by major food groups.
Using data from these two sources, one can calculate a time series of factors
of protein loss.
2001) Analysis of the 2000 CWNS shows there are
88 treatment plants in the United States, serving a
population of 2.6 million people, 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 analyses were
completed for each year in the Inventory using data
from CWNS on the amount of wastewater in centralized
systems treated in denitrification units. Plants without
intentional nitrification/ denitrification are assumed to
generate 3.2 grams N2O per capita per year.
With the modifications described above, N2O emissions
from domestic wastewater were estimated using the
following methodology:
N2OTOTAL = N2OPLANT + N2OEFFLUENT
= N2ONIT/DENIT + N2OWOUT NIT/DENIT
N2O
2NIT/DENIT =
N20
2WOUT NIT/DENIT
EF2 x FIND_COM] x 1/10
= {[(USp0p x WWTP) - USP
-coMlxEFJxl/109
N,O
2^EFFLUENT
NPR
= {[((USp0p - (0.9 x USPOPND)) x Protein x
where,
N2OTOTAL
N,0P
N2ONIT/DENIT
ON-CON x FIND-COM) ~~ NS
EF3x44/28}xl/106
= Annual emissions of N2O (kg)
= N2O emissions from centralized
wastewater treatment plants (kg)
= N2O emissions from centralized
wastewater treatment plants with
nitrification/denitrification (kg)
N2OWOuT NIT/DENIT = N2O emissions from centralized
wastewater treatment plants
without nitrification/denitrifica-
tion (kg)
N2OEFFLUENT
USp
= N2O emissions from wastewater
effluent discharged to aquatic
environments (kg)
= U.S. population
= U.S. population that is served by
biological denitrification (from
CWNS)
8-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
WWTP
EF2
Protein
NPR
Ns
SLUDGE
EF,
44/28
= Fraction of population using
WWTP (as opposed to septic
systems)
= Emission factor (3.2 g N2O/
person-year)
= Emission factor (7 g N2O/
person-year)
= Annual per capita protein
consumption (kg/person/year)
= Fraction of N in protein, default =
0.16 (kg N/kg protein)
= Factor for non-consumed protein
added to wastewater (1.4)
= Factor for industrial and commer-
cial co-discharged protein into
the sewer system (1.25)
= N removed with sludge, kg N/yr
= Emission factor (0.005 kg N2O
-N/kg sewage-N produced)
= Molecular weight ratio of N2O to
N2
U.S. population data were taken from the U.S. Census
Bureau International Database (U.S. Census 2008a) and
include the populations of the United States, American
Samoa, Guam, Northern Mariana Islands, Puerto Puco, and
the U.S. Virgin Islands. The fraction of the U.S. population
using wastewater treatment plants is based on data from
the 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, and
2005 American Housing Survey (U.S. Census 2008b). Data
for intervening years were obtained by linear interpolation.
The emission factor (EF:) used to estimate emissions from
wastewater treatment was taken from IPCC (2006). Data
on annual per capita protein intake were provided by U.S.
Department of Agriculture Economic Research Service
(USDA 2008b). Protein consumption data for 2005 through
2007 were extrapolated from data for 1990 through 2004.
Table 8-13 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 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). Sludge generation was obtained from EPA (1999)
Table 8-13: U.S. Population (Millions), Available Protein
[kg/(person-year)], and Protein Consumed
[kg/(person-year)j
Year
Population
Available
Protein
Protein
Consumed
2000
2001
2002
2003
2004
2005
2006
2007
287
289
292
295
297
300
303
306
41.3
42.0
40.9
40.9
41.3
41.7
41.9
42.1
31.6
32.1
31.3
31.3
31.6
32.1
32.1
32.2
Source: U.S. Census Bureau (2008a), USDA (2008b).
for 1988, 1996, and 1998 and from Beecher et al. (2007)
for 2004. Intervening years were interpolated, and estimates
for 2005 through 2007 were forecasted from the rest of the
time series. 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. In 2007, 266 Tg N was removed with sludge.
Uncertainty
The overall uncertainty associated with both the 2007
CFLj 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 include
that of numerous input variables used to model emissions
from domestic wastewater, and wastewater from pulp and
paper manufacture, meat and poultry processing, fruit and
vegetable processing, ethanol production, and petroleum
refining. Uncertainty associated with the parameters used
to estimate N2O emissions include 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.
Waste 8-15
-------
Table 8-14: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Wastewater Treatment
(Tg C02 Eq. and Percent)
Source
2007 Emission Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Wastewater Treatment
Domestic
Industrial
Domestic Wastewater
Treatment
CH4
CH4
CH4
N20
24.4
15.8
8.5
4.9
Lower Bound
15.1
7.7
5.1
1.2
Upper Bound
36.3
27.0
13.1
9.4
Lower Bound
-38%
-51%
-40%
-75%
Upper Bound
+49%
+70%
+54%
+94%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 8-14. CK4 emissions from
wastewater treatment were estimated to be between 15.1 and
36.3 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 49 percent
above the 2007 emissions estimate of 24.4 Tg CO2 Eq. N2O
emissions from wastewater treatment were estimated to be
between 1.2 and 9.4 Tg CO2 Eq., which indicates a range
of approximately 75 percent below to 94 percent above the
actual 2007 emissions estimate of 4.9 Tg CO2 Eq.
QA/QC and Verification
A QA/QC analysis was performed on activity data,
documentation, and emission calculations. This effort
included a Tier 1 analysis, including the following checks:
• Checked for transcription errors in data input;
• Ensured references were specified for all activity data
used in the calculations;
• Checked a sample of each emission calculation used for
the source category;
• Checked that parameter and emission units were
correctly recorded and that appropriate conversion
factors were used;
• Checked for temporal consistency in time series input
data for each portion of the source category;
• Confirmed that estimates were calculated and reported
for all portions of the source category and for all
years;
• Investigated data gaps that affected emissions estimates
trends; and
• Compared estimates to previous estimates to identify
significant changes.
All transcription errors identified were corrected. The
QA/QC analysis did not reveal any systemic inaccuracies or
incorrect input values.
Recalculations Discussion
The estimates of CH4 emissions from industrial
wastewater treatment increased across the time series as
petroleum refining wastewater treatment was added to the
Inventory. The addition of this industrial sector increased
industrial wastewater estimates by 9.0 to 9.8 percent across
the time series.
For treatment of the fruit and vegetable processing
industry, a factor to account for the removal of organics as
sludge prior to anaerobic treatment was added. Based on
data collected by EPA (1975), BOD is typically reduced by
17 to 30 percent, so a removal rate of 23 percent was used
in the Inventory.
Finally, the calculations of the percent of industrial
wastewater treated anaerobically (%TA) were revised. A
general calculation for each industry defines the percent
of plants in the industry that treat wastewater on site, the
percent of plants that have a primary treatment step prior
to biological treatment, and the percent of plants that treat
wastewater anaerobically. The %TA was estimated for both
primary treatment and secondary treatment.
Overall, the CH4 emission estimates for wastewater
treatment are on average 0.5 percent greater than the previous
Inventory.
For N2O emissions from domestic wastewater, a major
refinement to the calculation was the reestimation of per
8-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
capita protein consumption to account for the amount
consumed, not simply all protein available for consumption.
In addition, the N2O emission calculation was updated.
The (US pop) component of the N2OEFFLUENT equation was
replaced with [USPOP - (0.9xUSpOPND)] to more accurately
represent the nitrogen loading of wastewater discharged to
aquatic environments. By making that replacement, the N lost
as N2O from centralized treatment systems was subtracted
from the estimate of nitrogen discharged to the environment
to account for loss from nitrification/denitrification systems.
Overall, the N2O emissions estimates for wastewater
treatment are on average 41 percent lower than the previous
Inventory.
Overall, emissions from wastewater treatment and
discharge (CH4 and N2O) decreased by an average of
approximately 9 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 has
been 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, all aerobic
systems that have some anaerobic activity have an MCF
of 0.3, and that all anaerobic systems have an MCF of
0.8. Efforts to obtain better data reflecting emissions from
various types of municipal treatment systems are currently
being pursued.
For the current Inventory, an attempt was made to refine
the designation of unit operations from aerobic and anaerobic
to include an aerobic/anaerobic designation for some of the
treatment systems that were previously designated anaerobic.
However, the available data are not sufficiently detailed
across the time series to complete this designation.
Other potential sources of CH4 and CO2 emissions
from wastewater treatment at petroleum refineries will be
investigated. Also, available data on wastewater treatment
emissions at organic chemical manufacturers will be
reviewed to determine if this is a significant source to be
included in future versions of the Inventory.
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,
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 there is uncertainty
associated with the N2O emission factors for direct emissions
from centralized wastewater treatment facilities. Efforts to
gain greater confidence in these emission factors are currently
being pursued.
8.3. Composting (IPCC Source
Category 6D)
Composting of organic waste, such as food waste,
garden (yard) and park waste and sludge, is common in the
United States. Advantages of composting include reduced
volume in the waste material, stabilization of the waste, and
destruction of pathogens in the waste material. The end product
of composting, depending on its quality, can be recycled as
fertilizer and soil amendment, or be disposed of in a landfill.
Composting is an aerobic process and a large fraction
of the degradable organic carbon in the waste material is
converted into CO2. Methane is formed in anaerobic sections
of the compost, but it is oxidized to a large extent in the
aerobic sections of the compost. Anaerobic sections are
created in composting piles when there is excessive moisture
or inadequate aeration (or mixing) of the compost pile. The
estimated CH4 released into the atmosphere ranges from
less than 1 percent to a few percent of the initial C content
in the material (IPCC 2006). Composting can also produce
emissions of N2O. The range of the estimated emissions
varies from less than 0.5 percent to 5 percent of the initial
nitrogen content of the material (IPCC 2006).
Waste 8-17
-------
Table 8-15: CH4 and N20 Emissions from Composting (Tg C02 Eq.)
Activity
CH4
N20
Total
1990
0.3 1
0.4
0.7
1995
0.7 1
0.8
1.5
2000
1.3
1.4
2.6
2005
1.6
1.7
3.3
2006
1.6
1.8
3.3
2007
1.7
1.8
3.5
Table 8-16: CH4 and N20 Emissions from Composting (Gg)
Activity
CH4
N20
1990
15!
1
1995
35
3
2000
60
4
2005
75
6
2006
75
6
2007
79
6
From 1990 to 2007, the amount of material composted
in the United States has increased from 3,810 Gg to 19,695
Gg, an increase of approximately 400 percent. Emissions
of CH4 and N2O from composting have increased by the
same percentage (see Table 8-15 and Table 8-16). In
2007, CH4 emissions from composting were 1.7 Tg CO2
Eq. (79 Gg), and N2O emissions from composting were
1.8 Tg CO2 Eq. (6 Gg). The wastes that are composted
include primarily yard trimmings (grass, leaves, and tree
and brush trimmings) and food scraps from residences
and commercial establishments (such as grocery stores,
restaurants, and school and factory cafeterias). The
composting waste quantities reported here do not include
backyard composting. The growth in composting is
attributable primarily to two factors: (1) steady growth
in population and residential housing, and (2) state and
local governments enacting legislation that discouraged
the disposal of yard trimmings in landfills. In 1992, 11
states and the District of Columbia had legislation in effect
that banned or discouraged disposal of yard trimmings in
landfills. In 2005, 21 states and the District of Columbia,
representing about 50 percent of the nation's population,
had enacted such legislation (EPA 2006).
Methodology
CH4 and N2O emissions from composting depend on
factors such as the type of waste composted, the amount
and type of supporting material (such as wood chips and
peat) used, temperature, moisture content and aeration
during the process.
The emissions shown in Table 8-15 and Table 8-16 were
estimated using the IPCC default (Tier 1) methodology (IPCC
2006), which is the product of an emission factor and the
mass of organic waste composted (note: no CK4 recovery is
expected to occur at composting operations):
where,
E; = CH4 or N2O emissions from composting,
M
mass of organic waste composted in Gg,
emission factor for composting, 4 g
kg of waste treated (wet basis) and 0.3 g
N2O/kg of waste treated (wet basis), and
i = designates either CK4 or N2O.
Estimates of the quantity of waste composted (M) are
presented in Table 8-17. Estimates of the quantity composted
for 1990 and 1995 were taken from the Characterization of
Municipal Solid Waste in the United States: 1996 Update
(Franklin Associates 1997); estimates of the quantity
composted for 2000, 2005,2006, and 2007 were taken from
EPA's Municipal Solid Waste In The United States: 2007
Facts and Figures (EPA 2008).
8-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 8-17: U.S. Waste Composted (Gg)
Activity
1990
1995
2000
2005
2006
2007
Waste Composted
3,810
8,682
14,923
18,643 18,852 19,695
Source: Franklin Associates (1997) and EPA (2008).
Table 8-18: Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg C02 Eq. and Percent)
2007 Emission Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Composting CH4, N20 3.5
1.7 5.2 -50% +50%
Uncertainty
The estimated uncertainty from the 2006 1PCC
Guidelines (IPCC 2006) is +50 percent for the Tier 1
methodology. Emissions from composting in 2007 were
estimated to be between 1.7 and 5.2 Tg CO2 Eq., which
indicates a range of 50 percent below to 50 percent above
the actual 2007 emission estimate of 3.5 Tg CO2 Eq. (see
Table 8-18).
Planned Improvements
For future Inventories, additional efforts will be made
to improve the estimates of CH4 and N2O emissions from
composting. For example, a literature search may be conducted
to determine if emission factors specific to various composting
systems and composted materials are available.
8.4. 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 2007 are provided in Table 8-19.
Methodology
These emission estimates were obtained from preliminary
data (EPA 2008), 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
Table 8-19: Emissions of NOX, CO, and NMVOCs from Waste (Gg)
Gas/Source
1990
1995
2000
2005
2006
2007
N08
Landfills
Wastewater Treatment
Miscellaneous3
CO
Landfills
Wastewater Treatment
Miscellaneous3
NMVOCs
Wastewater Treatment
Miscellaneous3
Landfills
2
\
119
22
51
46
115
22
50
44
113
21
49
43
+ Does not exceed 0.5 Gg.
a Miscellaneous includes TSDFs (Treatment, Storage, and Disposal Facilities under the 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.
111
21
48
42
Waste 8-19
-------
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.
8-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
9. Other
T
I he United States does not report any greenhouse gas emissions under the Intergovernmental Panel on Climate
Change (IPCC) "Other" sector.
Other 9-1
-------
1O. 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 10-1
summarizes the quantitative effect of these changes on U. S. greenhouse gas emissions and Table 10-2 provides greater detail
regarding the quantitative effect of these changes in the Land Use, Land-Use Change, and Foresty sector, both relative to
the previously published U.S. Inventory (i.e., the 1990 through 2006 report). These tables present the magnitude of these
changes in units of teragrams of carbon dioxide equivalent (Tg CO2 Eq.).
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 2006) 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 2006, 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.
• Net CO2 Flux from Land Use, Land- Use Change, and Forestry. Changes in the Land Use, Land-Use Change, and Forestry
sector occurred primarily in calculations for forest and grassland carbon (C) stock and flux estimates. The most significant
changes were in forest aboveground biomass and soil organic carbon within the Forest Land Remaining Forest Land land-
use category and in the Grassland Remaining Grassland land-use category. In the estimation of forest C stocks within the
Forest Land Remaining Forest Land land-use category, newly available state data contributed to the recalculations in the
flux of carbon dioxide to the atmosphere. Changes in calculation methodology for state-lev el estimates, particularly in
the scaling up of plot-level stock estimates and in extrapolating C stock and stock change, resulted in significant change
in the net forest C flux. With regard to C stock recalculation for Grassland Remaining Grassland, several changes to
historical estimates resulted from the incorporation of annual survey data from the USDA National Resources Inventory
(NRI) in the 1990-2007 Inventory. These changes included: (1) the availability of new data extended the time series
of activity data beyond 1997 to 2003; (2) annual area data were used to estimate soil C stock changes, rather than data
collected in 5-year increments; (3) each NRI point was simulated separately, instead of simultaneously; and, (4) NRI
Recalculations and Improvements 10-1
-------
area data were reconciled with Forest Inventory and •
Analysis (FIA) area data, which led to adjustments in the
NRI dataset. Overall, these changes, in combination with
smaller adjustments in the other sources/sinks within the
sector, resulted in an average annual decrease in net flux
of CO2 to the atmosphere from the Land Use, Land-Use
Change, and Forestry sector of 117.3 Tg CO2 Eq. (14.1
percent) for the period 1990 through 2006, as compared
to estimates presented in the previous Inventory.
• Agricultural Soil Management. Changes in the estimates
of N2O emissions from Agricultural Soil Management
occurred primarily due to a new operational version of
the DAYCENT model and revised structural uncertainty
associated with the model. Improvements to the
DAYCENT model include elimination of the influence
of labile (i.e., easily decomposable by microbes)
C availability on surface litter denitrification rates, •
incorporation of precipitation events as a controlling
variable on surface litter denitrification, and allowing the
wettest soil layer within the rooting zone to control plant
transpiration. Overall, changes resulted in an average
annual decrease in nitrous oxide (N2O) emissions from
Agricultural Soil Management of 61.3 Tg CO2 Eq. (22.7
percent) for the period 1990 through 2006.
• Iron and Steel Production. Estimates of CO2 from iron
and steel production have been revised to adhere to
the 2006 IPCC Guidelines for National Greenhouse
Gas Inventories (IPCC 2006). Previously the estimates
focused primarily on the consumption of coking coal
to produce metallurgical coke and the consumption
of metallurgical coke, carbon anodes, and scrap steel
to produce iron and steel. The revised estimates
differentiate between emissions associated with
metallurgical coke production and those associated with •
iron and steel production and include CO2 emissions
from the consumption of other materials such as natural
gas, fuel oil, flux (e.g. limestone and dolomite use),
direction injection goal, sinter, pellets, and natural ore
during the iron and steel production process as well
as the metallurgical coke production process. Overall,
changes to the Iron and Steel Production estimate
resulted in an average annual increase in CO2 emissions
of 26.1 Tg CO2 Eq. (40.7 percent) for the period 1990 .
through 2006.
Fossil Fuel Combustion. Estimates of CO2 from
the industrial sector have been revised for the years
1990 through 2006 to subtract for non-energy related
consumption of coal, distillate fuel, and natural gas used
to produce pig iron in iron and steel and metallurgical
coke production. A discussion of the methodology used
to estimate non-energy related consumption is contained
in the Iron and Steel Production and Metallurgical Coke
Production section of the Industrial Processes chapter.
Additionally, the Energy Information Administration
(EIA 2008b) updated energy consumption data for all
years. These revisions primarily impacted the emission
estimates for 2006. Overall, changes resulted in an
average annual decrease in CO2 emissions from Fossil
Fuel Combustion of 17 Tg CO2 Eq. (0.3 percent) for the
period 1990 through 2006.
Enteric Fermentation. Changes in the estimates of
methane (CFL,) emissions from Enteric Fermentation
occurred as a result of (1) including additional heifer
and steer stacker populations; (2) adjusting the Cattle
Enteric Fermentation Model (CEFM) to allow feedlot
placements for the 700-800 Ibs category to use excess
animals from the over 800 Ibs category if insufficient
animals are available to place in a given month at
700-800 Ibs; (3) adjusting animal weights used in
calculations; (4) using revised USDA population
estimates that affected historical emissions estimated
for swine in 2006; and (5) some historical population
estimates for certain beef and dairy populations were
also updated as a result of changes in USDA inputs.
Overall, changes resulted in an average annual increase
in CFLj emissions from Enteric Fermentation of 10.2 Tg
CO2 Eq. (8.1 percent) from 1990 through 2006.
Natural Gas Systems. Changes in the estimates of CFL,
emissions from this source category resulted primarily
from the substitution of activity factors with direct
data for all years to adapt the natural gas inventory to
publicly available data and adjust the current inventory
to better reflect emissions from these sources. Overall,
changes resulted in an average annual increase in CFL,
emissions from Natural Gas Systems of 4.3 Tg CO2 Eq.
(3.5 percent) for the period 1990 through 2006.
Non-Energy Use of Fuels. Changes in CO2 emissions
estimates from Non-Energy Use of Fuels resulted from
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
changes in assumptions pertaining to petroleum coke.
Non-energy end uses for petroleum coke (other than in
the industrial processing sectors, where it is accounted
for separately) had not been identified in the past.
This year, it was assumed that petroleum coke used
for non-energy purposes (and not accounted for in the
industrial processes chapter, viz., for production of
primary aluminum anodes, electric arc furnace anodes,
titanium dioxide, ammonia, urea, and ferroalloys) is used
in pigments, with a storage factor of 0.3 (rather than
the value of 0.5 used previously). Overall, the changes
resulted in an average annual increase in CO2 emissions
from Non-Energy Use of Fuels of 3.9 Tg CO2 Eq. (2.9
percent) for the period 1990 through 2006.
Nitric Acid Production. Changes in the estimates of N2O
emissions from Nitric Acid Production were mostly
due to adjusting the weighted N2O emission factor (kg
N2O/metric ton HNO3), which resulted in an increase
in emissions across the time series. The weighted N2O
emission factor was previously based on the percentage
of facilities equipped and not equipped with non-
selective catalytic reduction (NSCR) systems. The
emission factor used for the current estimate is based on
the percentage of HNO3 produced at plants with NSCR
systems and HNO3 produced at plants without NSCR
systems. Overall, changes resulted in an average annual
increase in N2O emissions from Nitric Acid Production
of 3.1 Tg CO2 Eq. (17.8 percent) for the period 1990
through 2006.
Wastewater Treatment. Changes in N2O emissions
estimates from domestic wastewater resulted primarily
from a major refinement to the calculation—per capita
protein consumption was reestimated to account for
the amount consumed, not simply all protein available
for consumption. In addition, the N2O emission
calculation was updated to more accurately represent
the N loading of wastewater discharged to aquatic
environments. Overall, changes resulted in an average
annual decrease in N2O emissions from Wastewater
Treatment of 3.0 Tg CO2 Eq. (41.0 percent) for the
period 1990 through 2006.
Forest Land Remaining Forest Land. Changes in
CH4 emissions from Forest Land Remaining Forest
Land resulted primarily from updated carbon density
values, combustion factors, and the inclusion of
prescribed fires. The carbon density for Alaska was
revised to reflect the entire area that the U.S. Forest
Service uses to report carbon, and the default IPCC
combustion factor for forests was used to replace
the previous combustion factor. Emissions from
prescribed fires in the United States were included
in this year's estimates. Finally, data for land area
under wildland fire protection were updated. Overall,
changes resulted in an average annual increase in CH4
emissions from Forest Land Remaining Forest Land
of 1.8 Tg CO2 Eq. (20.0 percent) for the period 1990
through 2006.
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2004
2005
2006
C02
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
US Territories
Non-Energy Use of Fuels
Iron and Steel Production &
Metallurgical Coke Production
Cement Production
Natural Gas Systems
Incineration of Waste
Lime Production
8.2
(15.2)
0.1
(0.6)
(10.7)
(2.4)
(1.6)
NC
(0.2)
23.5
NC
NC
(0.5)
13.7
(18.5)
(0.4)
(0.7)
(13.9)
(2.1)
(1.4)
NC
4.2
28.4
NC
NC
(0.7)
15.5
(15.6)
0.9
2.1
(15.8)
(1.7)
(1.1)
NC
3.0
28.5
NC
(0.8)
9.9
(12.0)
0.4
4.0
(13.1)
(2.0)
(1.3)
NC
0.4
23.3
NC
+
(1.5)
(0.7)
16.5
(7.6)
0.8
11.6
(19.3)
(0.5)
(0.2)
+
(1.0)
26.6
NC
+
(1.1)
(0.8)
31.8
(2.5)
(0.8)
24.8
(17.7)
(4.7)
(4.1)
(0.1)
7.2
27.0
0.8
1.0
(1.1)
(0.7)
Recalculations and Improvements 10-3
-------
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.) (continued)
Gas/Source
1990
1995
2000
2004
2005
2006
Ammonia Production and Urea Consumption (0.1) +• +• + + (0.1)
Cropland Remaining Cropland Ncl Ncl Ncl NC NC (0.1)
Limestone and Dolomite Use (0.4) (0.7) (0.9) (0.8) (0.6) (0.6)
Aluminum Production NC NC NC NC (0.1) (0.1)
Soda Ash Production and Consumption NC NC NC NC NC NC
Petrochemical Production NC NC NC NC NC NC
Titanium Dioxide Production NC NC NC NC NC NC
Carbon Dioxide Consumption NC NC NC NC NC 0.1
Ferroalloy Production NC NC NC NC NC NC
Phosphoric Acid Production NC NC NC NC NC NC
Wetlands Remaining Wetlands3 1.01 1.01 1.2 1.2 1.1 0.9
Zinc Production NC NC NC NC NC NC
Petroleum Systems +1 +1 +1 + + +
Lead Production NC NC NC NC NC NC
Silicon Carbide Production and Consumption +1 +1 +1 + + +
and Forestry (Sink)b ' (103.8) (75.6) (43.9) (420.9) (244.1) (166.9)
Wood Biomass and Ethanol Consumption6 NCU +1 +1 + 4.1 5.7
International Bunker Fuels" 0.61 7.01 (2.2) (4.1) (11.1) (16.6)
CH4 10.5 16.9 16.8 17.2 22.0 26.7
Enteric Fermentation 6.31 11.2 9.81 11.4 11.5 12.0
Landfills (0.4) 0.2! 1.51 3.6 4.2 4.8
Natural Gas Systems 4.91 4.51 4.31 4.0 3.8 2.4
Coal Mining NC NC 0.11 (1.6) + (0.1)
Manure Management (0.6) (0.7) (0.9) (0.3) 0.1 0.4
Forest Land Remaining Forest Land 0.11 1.51 1.71 (0.3) 1.9 6.7
Petroleum Systems +1 +1 +1 + + (0.1)
Wastewater Treatment 0.51 0.51 0.61 0.6 0.6 0.6
Stationary Combustion +1 +1 +1 + 0.2 0.1
Rice Cultivation NC NC NC NC NC NC
Abandoned Underground Coal Mines NC NC NC + + 0.1
Mobile Combustion +1 +1 +1 + + 0.1
Composting NC NC NC NC NC NC
Petrochemical Production +1 +1 +1 0.1 + +
Field Burning of Agricultural Residues NC NC NC NC NC +
Iron and Steel Production &
Metallurgical Coke Production (0.4) (0.3) (0.3) (0.2) (0.2) (0.2)
Ferroalloy Production NC NC NC NC NC NC
Silicon Carbide Production and Consumption NC NC NC NC NC NC
International Bunker Fuels'3 +1 +1 +1 + + +
N20 (68.4) (61.5) (56.7) (35.7) (54.1) (55.8)
Agricultural Soil Management (69.0) (62.5) (57.6) (35.7) (54.6) (56.5)
Mobile Combustion 0.2! 0.2! 0.31 0.3 0.4 0.5
Nitric Acid Production 3.01 3.41 3.31 2.7 2.8 2.6
Manure Management +1 0.11 0.31 0.3 0.3 0.3
Stationary Combustion +1 +1 (0.1) (0.1) + +
Adipic Acid Production NC NC NC NC NC NC
Wastewater Treatment (2.6) (2.8) (3.1) (3.2) (3.2) (3.3)
N20 from Product Uses NC NC NC NC NC NC
Forest Land Remaining Forest Land + 0.1 0.2! (0.1) 0.2 0.6
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.) (continued)
Gas/Source
1990
1995
2000
2004
2005
2006
Composting
Settlements Remaining Settlements
Field Burning of Agricultural Residues
Incineration of Waste
Wetlands Remaining Wetlands3
International Bunker Fuels"
MFCs
Substitution of Ozone Depleting Substances
HCFC-22 Production
Semiconductor Manufacture
PFCs
Aluminum Production
Semiconductor Manufacture
SF6
Electrical Transmission and Distribution
Magnesium Production and Processing
Semiconductor Manufacture
Net Change in Total Emissions0
NC
NC
NC
0.7
NC
NC
+
0.1
0.1
NO
NC
NC
NC
NC
NC
«
0.1
NO
NC
+
NC
NC
(4.2)
(4.2)
NC
NC
+
(0.2)
0.1
(0.3)
NC
+
NC
(0.1)
(5.3)
(5.3)
NC
(0.3)
0.1
(0.4)
(30.7)
(24.4)
(13.0) (21.3)
NC
0.1
(0.1)
(5.5)
(5.5)
NC
NC
+
(0.3)
+
(0.3)
(3.1)
Percent Change
-0.8%
-0.5%
-0.2%
-0.3%
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements
Other
(408.7)
22.7
(3.4)
(20.9)
(10.4)
NC
(0.3)
(232.1)
22.7
(3.4)
(20.9)
(10.4)
NC
(0.2)
0.0%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
aNew source category relative to previous Inventory.
b Not included in emissions total.
c Excludes net C02 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and Wood Biomass and
Ethanol Consumption.
Note: Totals may not sum due to independent rounding.
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 1990 1995 2000 2004 2005 2006
(155.2)
22.7
(3.4)
(20.9)
(10.4)
NC
0.2
Net Change in Total Flux
(103.8)
(75.6)
(43.9)
(420.9) (244.1) (166.9)
Percent Change
-14.1%
-9.8
-6.5%
-48.2% -27.8% -18.9%
NC (No Change)
Note: Numbers in parentheses indicate a decrease in estimated net flux of C02 to the atmosphere or an increase in net sequestration.
Totals may not sum due to independent rounding.
Recalculations and Improvements 10-5
-------
11, References
Executive Summary
BEA (2008) "Current Dollar and Real Gross Domestic
Product." National Economic Accounts. Bureau of
Economic Analysis (BEA), U.S. Department of Commerce,
Washington, DC. July 29, 2008. Available online at .
EIA (2008a) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, September 2008.
Unpublished. Energy Information Administration (EIA),
U.S. Department of Energy. Washington, DC, DOE/EIA-
0035(2008/09).
EIA (2008b) International Energy Annual 2005. Energy
Information Administration (EIA), U.S. Department of
Energy. Washington, DC. Updated June-October 2007.
Available online at .
EPA (2008) "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards. Available online at
.
EPA (2003) E-mail correspondence. Air pollutant data. Office
of Air Pollution to the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
IPCC (2007) Climate Change 2007: The Physical Science
Basis. Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on
Climate Change. S. Solomon , D. Qin, M. Manning, Z.
Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller
(eds.). Cambridge University Press, Cambridge, United
Kingdom 996 pp.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC (2003) Good Practice Guidance for Land Use,
Land- Use Change, and Forestry. National Greenhouse Gas
Inventories Programme, The Intergovernmental Panel on
Climate Change, J. Penman, et al. (eds.). Available online
at . August 13, 2004.
IPCC (2001) Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change, J.T. Houghton,
Y. Ding, D.J. Griggs, M. Noguer, PJ. van derLinden, X. Dai,
C.A. Johnson, andK. Maskell (eds.). Cambridge University
Press, Cambridge, United Kingdom.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.2000).
IPCC (1996) Climate Change 1995: The Science of Climate
Change. Intergovernmental Panel on Climate Change, J.T.
Houghton, E.G. Meira Filho, B.A. Callander, N. Harris, A.
Kattenberg, and K. Maskell. (eds.). Cambridge University
Press, Cambridge, United Kingdom.
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 (2008) U.S. Census Bureau International
Database (IDE). Available online at . August 15, 2008.
References 11-1
-------
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.
EPA (2008) Air Emissions Trends—Continued Progress
Through 2006. U.S. Environmental Protection Agency.
Washington, DC. Available online at .
EPA (2003) E-mail correspondence. Air pollutant data. Office
of Air Pollution to 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, 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, United Kingdom.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change. Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.2000).
IPCC (1999) Aviation and the Global Atmosphere.
Intergovernmental Panel on Climate Change, J.E. Penner, et
al. (eds.). Cambridge University Press. Cambridge, United
Kingdom.
IPCC (1996) Climate Change 1995: The Science of Climate
Change. Intergovernmental Panel on Climate Change, J.T.
Houghton, E.G. Meira Filho, B.A. Callander, N. Harris, A.
Kattenberg, and K. Maskell. (eds.). Cambridge University
Press. Cambridge, United Kingdom.
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. Note by the secretariat.
(FCCC/SBSTA/2006/9). United Nations Office at Geneva,
Geneva.
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 (2008) 2007 Comprehensive Revision of the National
Income and Product Accounts: Current-dollar and "real"
GDP, 1929-2006. Bureau of Economic Analysis (BEA),
U.S. Department of Commerce, Washington, DC. July 29,
2008. Available online at .
Duffield, J. (2006) Personal communication. Jim Duffield,
Office of Energy Policy and New Uses, USDA and Lauren
Hinn, ICF International. April and December.
EIA (2008a) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, September 2008. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035(2008/09).
EIA (2008b) Short-Term Energy Outlook. Energy Information
Administration, U.S. Department of Energy, Washington,
DC.
EPA (2008) Air Emissions Trends—Continued Progress
Through 2006. U.S. Environmental Protection Agency.
Washington, DC. Available online at .
Heydorn, B. (1997) "Nitrous Oxide—North America."
Chemical Economics Handbook, SRI Consulting. May
1997.
IPCC (2001) Climate Change 2001: The Scientific Basis.
Intergovernmental Panel on Climate Change, J.T. Houghton,
Y. Ding, D.J. Griggs, M. Noguer, PJ. van der Linden, X. Dai,
C.A. Johnson, andK. Maskell (eds.). Cambridge University
Press. Cambridge, United Kingdom.
U.S. Census Bureau (2008) U.S. Census Bureau International
Database (IDE). Available online at . August 15, 2008.
11-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Energy
EIA (2008) International Energy Annual 2007. Energy
Information Administration, U.S. Department of Energy.
Washington, DC. Updated June-October 2007. Available
online at .
Carbon Dioxide Emissions from Fossil Fuel
Combustion
AAR (2008) Railroad Facts, 2008 Ed. Policy and Economics
Department, Association of American Railroads, Washington,
DC.
AISI (1995 through 2008) Annual Statistical Report.
American Iron and Steel Institute, Washington, DC.
APIA (2007 through 2008) Public Transportation Fact Book.
American Public Transportation Association, Washington,
DC. Available online at .
APTA (2006) Commuter Rail National Totals. American
Public Transportation Association, Washington, DC.
Available online at .
BEA (2008) 2007 Comprehensive Revision of the National
Income and Product Accounts: Current-dollar and "real"
GDP, 1929-2007. Bureau of Economic Analysis (BEA),
U.S. Department of Commerce, Washington, DC. July 29,
2008. Available online at .
BEA (1991 through 2008) Unpublished BE-36 survey
data. Bureau of Economic Analysis, U.S. Department of
Commerce. Washington, DC.
Benson, D. (2002 through 2004) Unpublished data. Upper
Great Plains Transportation Institute, North Dakota State
University and American Short Line & Regional Railroad
Association.
CVR Energy (2008) Coffeyville Resources Nitrogen
Fertilizers. Nitrogen Fertilizer Operations. Available online
at
September 2008.
Corathers, L. (2008) Personal communication. LisaCorathers,
Commodity Specialist, U.S. Geological Survey and Sarah
Menassian, ICF International. September 16, 2008.
Dakota Gasification Company (2006) CO2 Pipeline Route
and Designation Information. Bismarck, ND. Available
online at .
DHS (2008) Email Communication. Elissa Kay, Department
of Homeland Security and Joe Aamidor, ICF International.
January 11,2008.
DESC (2008) Unpublished data from the Defense Fuels
Automated Management System (DEAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense, Washington, DC.
DOC (1991 through 2008) 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, Washington, DC.
DOE (1993 through 2008) Transportation Energy Data
Book. Office of Transportation Technologies, Center for
Transportation Analysis, Energy Division, Oak Ridge
National Laboratory. ORNL-5198.
DOT (1991 through 2007) Fuel Cost and Consumption.
Federal Aviation Administration, Bureau of Transportation
Statistics, U.S. Department of Transportation, Washington,
DC. DAI-10.
EIA (2008a) Annual Energy Review 2007. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0384(2007). June 2008.
EIA (2008b) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, September 2008. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035(2008/09).
EIA (2008c) Emissions of Greenhouse Gases in the United
States 2007, Draft Report. Office of Integrated Analysis
and Forecasting, Energy Information Administration,
U.S. Department of Energy, Washington, DC. DOE-
EIA-0573(2007).
EIA (2008d) "Table 3.1: World Petroleum Supply and
Disposition." International Energy Annual. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (2008e) Natural Gas Annual 2006. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. DOE/EIA-0131(06). November 2007.
EIA (2008f) Short-Term Energy Outlook. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. December 2008.
EIA (2008g) Quarterly Coal Report. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. DOE/EIA-0121.
EIA (2007) Personal Communication. Joel Lou, Energy
Information Administration, and Aaron Beaudette, ICF
International. Residual and Distillate Fuel Oil Consumption
for Vessel Bunkering (Both International and Domestic) for
American Samoa, U.S. Pacific Islands, and Wake Island.
October 24, 2007.
EIA (2006) Historical Natural Gas Annual, 1930-2006.
Energy Information Administration, U.S. Department of
Energy, Washington, DC.
References 11-3
-------
El A (2005) Manufacturing Consumption of Energy 2002.
Energy Information Administration, U.S. Department of
Energy, Washington, DC.
EIA (2002) Alternative Fuels Data Tables. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (2001) 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 (2006) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
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 .
FAA (2008). FAA Aerospace Forecasts Fiscal Years
2008-2025. Table 30 "General Aviation Aircraft Fuel
Consumption," Federal Aviation Administration. Available
online at .
FAA (2006). System for assessing Aviation's Global
Emission (SAGE) Model. Federal Aviation Administration's
Office of Aviation Policy, Planning, and Transportation
Topics, 2006.
Fitzpatrick, E. (2002) The Weyburn Project: A Model
for International Collaboration. Available online at
.
FHWA (1996 through 2008) Highway Statistics. Federal
Highway Administration, U. S. Department of Transportation,
Washington, DC. Report FHWA-PL-96-023-annual.
Available online at .
FRB (2007) Industrial Production and Capacity Utilization.
Federal Reserve Statistical Release, G. 17, Federal Reserve
Board. Available online at November 7, 2008.
Gaffney, J. (2007) Email Communication. John Gaffney,
American Public Transportation Association and Joe
Aamidor, ICF International. December 17, 2007.
Grillot, M. (2008) Personal communication. Mike Grillot,
Energy Information Administration and Rubab Bhangu, ICF
International. U.S. Territories Fossil Fuel Consumption,
1990-2007. Unpublished. U.S. Energy Information
Administration, Washington, DC.
IPCC (2006) 2006IPCC Guidelines for National Green-
house Gas Inventories. The National Greenhouse Gas
Inventories Programme, The Intergovernmental Panel on
Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T.
Ngara, and K. Tanabe (eds.). 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.
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 Office of Integrated Analysis and Forecasting,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. June 22, 2001.
Smith, G. (2007) Personal communication. Gerald Smith,
Commodity Specialist, USGS and Toby Krasney, ICF
International. 7 October 2007.
USAF (1998) Fuel Logistics Planning. U.S. Air Force:
AFPAM23-221. May 1, 1998.
U.S. Bureau of the Census (2008) Current Industrial Reports
Fertilizers and Related Chemicals Quarterly Summaries:
2007. June 2008. Available online at . Accessed in 9/2008.
USGS (2008) Mineral Commodity Summaries: Aluminum.
U.S. Geological Survey, Reston, VA.
USGS (1995,1998,2000 through 2002) Mineral Yearbook:
Aluminum Annual Report. U.S. Geological Survey, Reston,
VA.
USGS (1995 through 2008) Minerals Yearbook: Lead Annual
Report. U.S. Geological Survey, Reston, VA.
USGS (1995) Mineral Industry Surveys: Aluminum Annual
Review 1994. U.S. Geological Survey, U.S. Department of
the Interior, Washington, DC. May 1995.
USGS (1991a through 2007a) Silicon: Annual Report.
U.S. Geological Survey, U.S. Department of the Interior,
Washington, DC.
USGS (1991b through 2007b) Minerals Yearbook:
Manufactured Abrasives Annual Report 2005. U.S.
Geological Survey, Reston, VA.
USGS (1991 through 2005) Mineral Yearbook: Titanium
Annual Report. U.S. Geological Survey, Reston, VA.
11-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Stationary Combustion (Excluding C02)
EIA (2008a) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, December 2008. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035(2008/12).
EIA (2008b) Annual Energy Review 2007. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0384(2007). June 2007.
EPA (2006) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2003) E-mail correspondence. Air pollutant data. Office
of Air Pollution to the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
Grillot, M. (2008) Personal communication. Mike Grillot,
Energy Information Administration and Rubab Bhangu, ICE
International. U.S. Territories Fossil Fuel Consumption,
1990-2007. Unpublished. U.S. Energy Information
Administration, Washington, DC.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.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.
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 Office of Integrated Analysis and Forecasting,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. June 22, 2001.
Mobile Combustion (Excluding C02)
AAR (2008) Railroad Facts, 2008 Ed. Policy and
Economics Department, Association of American Railroads,
Washington, DC.
ANL (2006) Argonne National Laboratory (2006) GREET
model Version 1.7. June 2006.
APIA (2007 through 2008) Public Transportation Fact Book.
American Public Transportation Association, Washington,
DC. Available online at .
APTA (2006) Commuter Rail National Totals. American
Public Transportation Association, Washington, DC.
Available online at .
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.
BEA (1991 through 2005) Unpublished BE-36 survey data.
Bureau of Economic Analysis (BEA), U.S. Department of
Commerce.
Browning, L. (2005) Personal communication with Lou
Browning, emission control technologies for diesel 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.
DHS (2008) Email Communication. ElissaKay, Department
of Homeland Security and Joe Aamidor, ICF International.
January 11,2008.
DESC (2008) Unpublished data from the Defense Fuels
Automated Management System (DEAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense, Washington, DC.
DOC (1991 through 2008) 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, Washington, DC.
DOE (1993 through 2008) Transportation Energy Data
Book. Office of Transportation Technologies, Center for
Transportation Analysis, Energy Division, Oak Ridge
National Laboratory. ORNL-5198.
DOT (1991 through 2008) Fuel Cost and Consumption.
Federal Aviation Administration, U.S. Department of
Transportation, Bureau of Transportation Statistics,
Washington, DC. DAI-10.
EIA (2008a) Annual Energy Review 2007. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. July 2006. DOE/EIA-0384(2005).
EIA (2008b) "Table 3.1: World Petroleum Supply and
Disposition." International Energy Annual. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
References 11-5
-------
EIA (2007a) Personal Communication. Joel Lou, Energy
Information Administration and Aaron Beaudette, ICF
International. Residual and Distillate Fuel Oil Consumption
for Vessel Bunkering (Both International and Domestic) for
American Samoa, U.S. Pacific Islands, and Wake Island.
October 24, 2007.
EIA (2007b) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, December 2007. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035(2007/12).
EIA (2007 through 2008) Natural Gas Annual. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0131(06).
EIA (2002) Alternative Fuels Data Tables. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1991 through 2008) Fuel Oil and Kerosene Sales.
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0535-annual.
EPA (2008). "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards,
EPA (2007a) Annual Certification Test Results Report. Office
of Transportation and Air Quality, U.S. Environmental
Protection Agency. Available online at .
EPA (2007b) Confidential engine family sales data submitted
to EPA by manufacturers. Office of Transportation and Air
Quality, U.S. Environmental Protection Agency.
EPA (2007c) Motor Vehicle Emission Simulator (MOVES).
Office of Transportation and Air Quality, U.S. Environmental
Protection Agency. Available online at .
EPA (2006) NONROAD Model. Office of Transportation
and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2000) Mobile6 Vehicle Emission Modeling Software.
Office of Mobile Sources, U.S. Environmental Protection
Agency, Ann Arbor, Michigan.
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. EPA 400-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. EPA400-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.
FAA (2008). FAA Aerospace Forecasts Fiscal Years
2008-2025. Table 30 "General Aviation Aircraft Fuel
Consumption," Federal Aviation Administration. Available
online at .
FAA (2006) Email correspondence containing aviation
emissions estimates from the System for Assessing Aviation's
Global Emissions (SAGE). August 2006.
FHWA (1996 through 2008) Highway Statistics. Federal
Highway Administration, U.S. Department of Transportation,
Washington, DC. Report FHWA-PL-96-023-annual.
Available online at .
Gaffney, J. (2007) Email Communication. John Gaffney,
American Public Transportation Association and Joe
Aamidor, ICF International. December 17, 2007.
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.
11-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
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 through 2008) Personal communication,
Class II and III Rail energy consumption, American Short
Line and Regional Railroad Association.
Carbon Emitted from Non-Energy Uses of
Fossil Fuels
ACC (2005 through 2008) Guide to the Business of
Chemistry, 2007. American Chemistry Council.
American Gas Association (1974) Gas Engineer's Handbook.
Industrial Press, New York, NY, pp. 3/71, 3.87.
APC (2004 through 2006) APC Year-End Statistics
for 2005. April 2006. Available online at .
API (1990 through 2005) Sales of Natural Gas Liquids and
Liquefied Refinery Gases. American Petroleum Institute.
API (1988) Alcohols and Ethers: A Technical Assessment of
Their Applications as Fuels and Fuel Components. American
Petroleum Institute, API 4261.
Applied Systems Corporation (1976) Compilation of
Oil Shale Test Results. Submitted to the Office of Naval
Research, April 1976, p. 3-2.
ASTM (1985) ASTMand Other Specifications for Petroleum
Products and Lubricants. American Society for Testing and
Materials, Philadelphia, PA.
Black, F and L. High (1979) "Methodology for Determining
Particulate and Gaseous Diesel Emissions," in The
Measurement and Control of Diesel Particulate Emissions.
Society of Automotive Engineers, p. 128.
Boldt, K. and B.R. Hall (1977) Significance of Tests for
Petroleum Products. American Society for Testing and
Materials, Philadelphia, PA, p. 30.
C.R. Martel and E.G. Angello (1977) "Hydrogen Content as
a Measure of the Combustion Performance of Hydrocarbon
Fuels," in Current Research in Petroleum Fuels, Volume L
MSS Information Company, New York, NY, p. 116.
Da vie, I.N. (1993) "Compostability of Petroleum Wax-based
Coatings." Technical Association for the Pulp and Paper
Industry Journal. 76(2): 167-170.
Davie, I. N., Winter, J. P., Varoney, R.P. (1995) "Decomposition
of Coated Papers from a Quick-service Restaurant."
Technical Association for the Pulp and Paper Industry
Journal. 78(5): 127-130.
DeLuchi (1993) Emissions of Greenhouse Gases from the
Use of Transportation Fuels and Electricity, Volume 2, ANL/
ESD/TM-22, Vol. 2. Argonne National Laboratory. Chicago,
IL, Appendix C, pp. C-l to C-8.
DOC (1929) Thermal Properties of Petroleum Products, U.S.
Department of Commerce, National Bureau of Standards.
Washington, DC. pp. 16-21.
EIA (1995 through 2007) Petroleum Supply Annual, Energy
Information Administration, U.S. Department of Energy,
Washington, DC.
EIA (2006) 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 (2005) Monthly Energy Review, September 2005 and
Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department
of Energy, Washington, DC, DOE/EIA-0035(2005/09).
EIA (2003) State Energy Data 2000: Consumption. U.S.
Energy Information Administration, U.S. Department of
Energy, Washington, DC. August 2003. Available online
at .
EIA (2002) Coal Industry Annual U.S. Department of Energy,
Energy Information Administration, Washington, DC.
EIA (2001a) Annual Energy Review 1999. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0384(99).
EIA (2001b) Cost and Quality of Fuels for Electric
Utility Plants 2000. Energy Information Administration,
Washington, DC. August 2001. Available online at .
EIA (1994) Emissions of Greenhouse Gases in the United
States 1987-1992. Energy Information Administration, U.S.
Department of Energy, Washington, DC. November, 1994.
DOE/EIA0573.
EPA (2007a) Biennial Reporting System (BRS) Database.
U.S. Environmental Protection Agency, Envirofacts
Warehouse, Washington, DC. Available online at .
EPA (2007b) Municipal Solid Waste in the United States:
Facts and Figures for 2006. Office of Solid Waste and
Emergency Response, U.S. Environmental Protection
Agency, Washington, DC. Available online at .
References 11-7
-------
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 (2004) Biennial Reporting System (BRS). U.S.
Environmental Protection Agency, Envirofacts Warehouse,
Washington, DC. Available online at .
EPA (2000a) Biennial Reporting System (BRS). U.S.
Environmental Protection Agency, Envirofacts Warehouse,
Washington, DC. Available online at .
EPA (2000b) Toxics Release Inventory, 1998. U.S.
Environmental Protection Agency, Office of Environmental
Information, Office of Information Analysis and Access,
Washington, DC. Available online at .
FEE (2007) Fiber Economics Bureau, as cited in C&EN
(2007) "Gains in Chemical Output Continue." Chemical &
Engineering News. American Chemical Society. July 2,2007.
Available online at .
FEB, (2005) Fiber Economics Bureau, as cited in C&EN
(2005) "Production: Growth in Most Regions" Chemical
& Engineering News. American Chemical Society, 11 July.
Available online at .
Funkenbush, E.F, D.G. Leddy, and J.H. Johnson (1979)
"The Organization of the Soluble Organic Fraction of
Diesel Particulate Matter," in The Measurement and Control
of Diesel Particulate Emissions. Society of Automotive
Engineers, p. 128.
Gas Technology Institute (1992) Database as documented in
W.E. Liss, W.H. Thrasher, G.F Steinmetz, P. Chowdiah, and
A. Atari, Variability of Natural Gas Composition in Select
Major Metropolitan Areas of the United States. GRI-92/0123.
March 1992.
Guerra, C.R., K. Kelton, and DC Nielsen (1979) "Natural
Gas Supplementation with Refinery Gases and Hydrogen,"
in New Fuels and Advances in Combustion Technologies.
Institute of Gas Technology, Chicago, IE, June 1979.
Guthrie, V. (ed.) (1960) Petroleum Products Handbook.
McGraw-Hill, New York, NY.
Hadaller, O.J. andA.M. Momenthy (1990) The Characteristics
of Future Fuels, Part 1, "Conventional Heat Fuels." Boeing
Corp., Seattle, WA, September 1990. pp. 46-50.
Hare, C.T. and R.L. Bradow (1979) "Characterization of
Heavy-Duty Diesel Gaseous and Particulate Emissions,
and the Effects of Fuel Composition," in The Measurement
and Control of Diesel Particulate Emissions. Society of
Automotive Engineers, p. 128.
Hare, C.T., K.J. Springer, and R.L. Bradow (1979) "Fuel
and Additive Effects on Diesel Particulate—Development
and Demonstration of Methodology," in The Measurement
and Control of Diesel Particulate Emissions. Society of
Automotive Engineers, p. 179.
Hong, B.D. and E.R. Slatnick (1994) "Carbon Dioxide
Emission Factors for Coal," Quarterly Coal Report. U.S.
Energy Information Administration, Washington, DC.
January-March 1994.
Howard (1993). Handbook of Environmental Fate and
Exposure Data for Organic Chemicals: Vol. II Solvents 2,
Phillip H Howard, Ed. CRC Lewis Publishers, 1993
Hunt, J.M. (1979) Petroleum Geochemistry and Geology.
W.H. Freeman and Company, San Francisco, CA, pp.
31-37.
Huurman, J.W.F (2006) Recalculation of Dutch Stationary
Greenhouse Gas Emissions Based on sectoral Energy
Statistics 1990-2002. Statistics Netherlands, Voorburg, The
Netherlands.
IGI (2002) 100 Industry Applications. The International
Group Inc. Available online at . Toronto, Ontario.
IISRP (2003) IISRP Forecasts Moderate Growth in North
America to 2007. International Institute of Synthetic
Rubber Producers, Inc. Available online at .
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
James, A. (2000) Personal communication. Alan James, Akzo
Nobel Coatings, Inc. and Suzanne Bratis, ICF International.
July 2000. (Tel: 614-294-3361).
Longwell, J.P (1991) "Interface Between Fuels and
Combustion," in Fossil Fuel Combustion: A Sourcebook.
New York, NY, John Wiley & Sons.
Maguire, J. (2004) National Petrochemicals and Refiners
Association Wax Contact. Personal Communication
(August-September, 2004)
Martin, S.W. (1960) "Petroleum Coke," in Petroleum
Processing Handbook, Virgil Guthrie (ed.). McGraw-Hill,
New York, NY. pp. 14-15.
Mason, R.L. (1981) "Developing Prediction Equations
for Fuels and Lubricants," SAE Paper 811218, p.34.
October 1981.
Mosby, F, G.B. Hoekstra, T.A. Kleinhenz, and J.M. Sokra
(1976) "Pilot Plant Proves Resid Process," in Chemistry of
Petroleum Processing and Extraction. MSS Information
Corporation, p.227.
11-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
National Institute for Petroleum and Energy Research
(1990 through 2004) Motor Gasolines, Summer and Motor
Gasolines, Winter.
National Institute for Petroleum and Energy Research (1992)
Fuel Oil Surveys, Bartlesville, OK.
NPRA (2002) North American Wax—A Report Card. Report
presented at the National Petrochemicals and Refiners
Association Lubricants and Waxes Meeting (11/15/2002).
NPRA (LW-02-126). Washington, DC.
Rinehart, T. (2000) Personal communication. Thomas
Rinehart, U.S. Environmental Protection Agency, Office
of Solid Waste, and Randall Freed, ICF International. July
2000. (Tel: 703-308-4309).
Ringen, S., J. Lanum, and FP Miknis (1979) "Calculating
Heating Values from the Elemental Composition of Fossil
Fuels," Fuel, Vol. 58, January 1979, p.69.
RMA (2006) Scrap Tire Markets in the United States 2005
Edition. Rubber Manufacturers Association, Washington,
DC. November 2006.
Rose, J.W. and J.R. Cooper (1977) Technical Data on Fuel.
The British National Committee, World Energy Conference,
London, England.
SAIC (2005) Analysis prepared by Science Applications
International Corporation for EPA, Office of Air and
Radiation, Market Policies Branch.
SAIC (1992) Analysis of the Relationship Between Heat and
Carbon Content of U.S. Fuels: Final Task Report. Science
Applications International Corporation, prepared for the U.S.
Energy Information Administration, Office of Coal, Nuclear,
Electric and Alternative Fuels, Washington, DC.
Schneider, S. (2007) E-mail communication. Shelly
Schneider, Franklin Associates (a division of ERG) and Sarah
Shapiro, ICF International, January 10, 2007.
U.S. Bureau of the Census (2004) Soap and Other Detergent
Manufacturing: 2002, Issued December 2004, EC02-
311-325611 (RV). Available online at .
U.S. National Research Council (1927) International
Critical Tables of Numerical Data, Physics, Chemistry, and
Technology, McGraw-Hill, New York, NY.
Unzelman, G.H. (1992) "A Sticky Point for Refiners: FCC
Gasoline and the Complex Model." Fuel Reformulation.
July/August 1992, p. 29.
USGS (1998) CoalQual Database Version 2.0, U.S.
Geological Survey.
Vorum, D.A. (1974) "Fuel and Synthesis Gases from Gaseous
and Liquid Hydrocarbons," in Gas Engineer's Handbook.
American Gas Association, New York, NY, Industrial Press,
p. 3/71.
Ward, C.C. (1978) "Petroleum and Other Liquid Fuels,"
in Marks' Standard Handbook for Mechanical Engineers.
McGraw-Hill, New York, NY, pp. 7-14.
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 (2008) Annual Coal Report 1991-2007 (Formerly
called Coal Industry Annual). Table 3. Energy Information
Administration, U.S. Department of Energy,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 Yanbei Wang (2000) "Analysis
of Potential Errors in Determination of Coal Mine Annual
Methane Emissions." Mineral Resources Engineering, 9(4).
December 2000.
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 Coal 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. Department of Energy and Geo-
Environmental Engineering, Pennsylvania State University,
University Park, PA.
U.S. Department of Labor, Mine Health & Safety
Administration (2007) Data Retrieval System. Available
online at .
Natural Gas Systems
AAPG (2004) Shale Gas Exciting Again. American
Association of Petroleum Geologists. Available online at
.
AGA (1991 through 1998) Gas Facts. American Gas
Association, Washington, DC.
References 11-9
-------
API (2005) "Table 12-Section Ill-Producing Oil Wells in
the United States by State." In Basic Petroleum Data Book.
American Petroleum Institute, Volume XXV, Number 1.
February 2005.
Alabama (2008) Alabama State Oil and Gas Board. Available
online at .
Brookhaven (2004) Natural Gas Field Subject of Interest
at Brookhaven College. Brookhaven College. Available
online at .
EIA (2008a) Number of Producing Gas and Gas Condensate
Wells, 1989-2006, Natural Gas Navigator. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2008b) "Table 1—Summary of Natural Gas Supply
and Disposition in the United States 1999-2008." Natural
Gas Monthly, Energy Information Administration, U.S.
Department of Energy, Washington, DC. Available online
at .
EIA (2008c) "Table 2—Natural Gas Consumption in the
United States." Natural Gas Monthly, Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2008d) Table 5.2. Monthly Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (2008e) "Table 6—Marketed Production of Natural
Gas by State." Natural Gas Monthly, Energy Information
Administration, U.S. Department of Energy, Washington,
DC. Available online at .
EIA (2008f) 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 .
EIA (2001) "Documentation of the Oil and Gas Supply
Module (OGSM)." Energy Information Administration,
U.S. Department of Energy, Washington, DC. Available
online at .
EIA (1996) "Emissions of Greenhouse Gases in the
United States" Carbon Dioxide Emissions. Energy
Information Administration, U.S. Department of Energy,
Washington, DC.
EPA (2008) Natural Gas STAR Reductions 1990-2007.
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 EEC for National Risk
Management Research Laboratory, Air Pollution Prevention
and Control Division, Research Triangle Park, NC. EPA-
600/R-96-080a.
GTI (2001) Gas Resource Database: Unconventional
Natural Gas and Gas Composition Databases. Second
Edition. GRI-01/0136.
IPCC (2007) 2007IPCC 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 (2008) "Oil and Gas Production Data, All Wells,"
Kansas Geological Surveys. University of Kansas. Available
online at .
Lippman (2003) Rocky Mountain Region Second Quarter
2003 Production Report. Lippman Consulting, Inc.
MMS (2008a) Gulf of Mexico Region Offshore Information.
Minerals Management Service, U.S. Department of Interior.
Available online at .
MMS (2008b) Gulf of Mexico Region Products/Free Data.
Minerals Management Service, U.S. Department of Interior.
Available online at .
MMS (2008c) OCS Platform Activity. Minerals Management
Service, U.S. Department of Interior. Available online at
.
MMS (2008d) Pacific OCS Region. Minerals Management
Service, U.S. Department of Interior. Available online
at .
MMS (2004) Gulfwide Emission Inventory Study for the
Regional Haze and Ozone Modeling Effort. OCS Study
MMS 2004-072.
Montana (2008) Montana Online Oil and Gas Information
System. Montana Board of Oil and Gas Conservation,
Billings Office. Available online at .
11-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Morgan Stanley (2005) "Barnett Shale Update: None-
Core Confidence Rises." Available online at .
New Mexico (2008a) "Annual Gas Well Counts by State
District." Available online at .
New Mexico (2008b) "Districts." Available online at.
OGJ (1997-2008) "Worldwide Gas Processing." Oil & Gas
Journal, PennWell Corporation, Tulsa, OK.
Oklahoma (2008) Oklahoma Petroleum Information
Center—Coalbed-Methane Completions database. Oklahoma
Geological Survey. Available online at .
OPS (2008a) Natural Gas Transmission Pipeline Annual
Mileage. Office of Pipeline Safety, U.S. Department of
Transportation, Washington, DC. Available online at .
OPS (2008b) Distribution Annuals Data. Office of Pipeline
Safety, U.S. Department of Transportation, Washington, DC.
Available online at .
Texas (2008a) Gas Well Counts by County. Texas Railroad
Commission. Available online at .
Texas (2008b) Oil Well Counts by County. Texas Railroad
Commission. Available online at .
Texas (2008c) The Barnett Shale Regional Report. Foster,
Brad, Devon Energy, Texas Railroad Commission. Available
online at .
Texas (2008d) Oil and Gas District Boundaries. Texas
Railroad Commission. Available online at .
Utah (2008) Oil and Gas Data Download. Utah Division
of Oil, Gas and Mining —Department of Natural
Resources. Available online at .
World Oil Magazine (2008a) "Outlook 2008: Producing Gas
Wells." 228(2). February 2008. Available online at .
World Oil Magazine (2008b) "Outlook 2008: Producing Oil
Wells." 228(2). February 2008. Available online at .
Wyoming (2008) "Wyoming Oil and Gas Conservation
Commission." Available online at .
Petroleum Systems
EIA (1990 through 2008) Refinery Capacity Report. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1995 through 2008a) Annual Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
EIA (1995 through 2008b) Monthly Energy Review. Energy
Information Administration, U.S. Department of Energy,
Washington, DC. Available online at .
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 (1996) Methane Emissions from the U.S. Petroleum
Industry (Draft). Prepared by Radian. U.S. Environmental
Protection Agency. June 1996.
EPA (1999) Estimates of Methane Emissions from the U.S.
Oil Industry (Draft Report). Prepared by ICF International.
Office of Air and Radiation, U.S. Environmental Protection
Agency. October 1999.
EPA (2005) Incorporating the Mineral Management Service
Gulfwide Offshore Activities Data System (GOADS) 2000
data into the methane emissions inventories. Prepared by ICF
International. U.S. Environmental Protection Agency. 2005.
EPA/GRI (1996a) Methane Emissions from the Natural Gas
Industry, V7: Blow and Purge Activities. Prepared by Radian.
U.S. Environmental Protection Agency. April 1996.
EPA/GRI (1996b) Methane Emissions from the Natural Gas
Industry, VII: Compressor Driver Exhaust. Prepared by
Radian. U.S. Environmental Protection Agency. April 1996.
EPA/GRI (1996c) Methane Emissions from the Natural Gas
Industry, VI2: Pneumatic Devices. Prepared by Radian. U.S.
Environmental Protection Agency. April 1996.
EPA/GRI (1996d) Methane Emissions from the Natural
Gas Industry, VIS: Chemical Injection Pumps. Prepared
by Radian. U.S. Environmental Protection Agency. April
1996.
IOGCC (2008) Marginal Wells: fuel for economic growth
2007 Report. Interstate Oil & Gas Compact Commission.
Available online at .
MMS (2001) Field and Reserve Information. Minerals
Management Service, U.S. Department of Interior. Available
online at .
References 11-11
-------
MMS (2004). Gulfwide Emission Inventory Study for
the Regional Haze and Ozone Modeling Effort. Minerals
Management Service, U.S. Department of Interior. OCS
Study MMS 2004-072.
MMS (2008a) OCS Platform Activity. Minerals Management
Service, U.S. Department of Interior. Available online at
.
MMS (2008b) Platform Information and Data. Minerals
Management Service, U.S. Department of Interior. Available
online at .
MMS (2008c) Pacific OCS Region. Minerals Management
Service, U.S. Department of Interior. Available online
at .
OGJ (2008a) Oil and Gas Journal 1990-2008. Pipeline
Economics Issue, September 2008.
OGJ (2008b) Oil and Gas Journal 1990-2008. Worldwide
Refining Issue, January 1, 2008.
United States Army Corps of Engineers (1995-2008)
Waterborne Commerce of the United States, Part 5:
National Summaries. U.S. Army Corps of Engineers,
Washington, DC.
Incineration of Waste
De Soete, G.G. (1993) "Nitrous Oxide from Combustion
and Industry: Chemistry, Emissions and Control." In A.
R. Van Amstel, (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. Diane DeZan,
Fiber Economics Bureau and Joe Casola, ICF International.
August 4, 2000.
EPA (2007 through 2008) Municipal Solid Waste in the United
States: Facts and Figures for 2006. Office of Solid Waste
and Emergency Response, U.S. Environmental Protection
Agency. Washington, DC. Available online at .
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 (2005) 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: 2001 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 (1996 through 1999) Characterization of Municipal
Solid Waste in the United States. 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) "13th 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.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.2000).
Kaufman, et al. (2004a) "14th Annual BioCycle Nationwide
Survey: The State of Garbage in America 2004" Biocycle,
JG Press, Emmaus, PA. January, 2004.
11-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 . October 10, 2003.
RMA (2006) U.S. Scrap Tire Markets in the United
States 2005 Edition. Rubber Manufacturers Association,
Washington, DC. November 2006.
Schneider, S. (2007) E-mail communication. Shelly
Schneider, Franklin Associates and Sarah Shapiro, ICE
International. January 10, 2007.
Simmons, et al. (2006) "15th Nationwide Survey of Municipal
Solid Waste Management in the United States: The State
of Garbage in America" BioCycle, JG Press, Emmaus, PA.
April 2006.
STMC (2003, 2006) Scrap Tire Facts and Figures. Scrap
Tire Management Council of the Rubber Manufacturers
Association. Washington, DC. Available online at and .
STMC (2001, 2002) Scrap Tire Facts and Figures. Scrap
Tire Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at .
STMC (2000) Scrap Tire Facts and Figures. Scrap Tire
Management Council of the Rubber Manufacturers
Association, Washington, DC. Available online at . July 26, 2000.
Energy Sources of Indirect Greenhouse
Gas Emissions
EPA (2008) "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards. Available online at
.
EPA (2003) E-mail correspondence. Air pollutant data. Office
of Air Pollution to the Office of Air Quality Planning and
Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
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 2008) 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
.
DHS (2008). Personal Communication with Elissa Kay,
Residual and Distillate Fuel Oil Consumption (International
Bunker Fuels). Department of Homeland Security, Bunker
Report. January 11, 2008.
DESC (2008) Unpublished data from the Defense Fuels
Automated Management System (DEAMS). Defense Energy
Support Center, Defense Logistics Agency, U.S. Department
of Defense, Washington, DC.
DOC (1991 through 2008) 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, Washington, DC.
DOT (1991 through 2008) Fuel Cost and Consumption.
Airline Information, Bureau of Transportation Statistics, U.S.
Department of Transportation, Washington, DC.
EIA (2008) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, September 2008, Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035(2008/09).
FAA (2006). System for assessing Aviation's Global Emission
(SAGE) Model. Federal Aviation Administration's Office
of Aviation Policy, Planning, and Transportation Topics,
2006.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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 (2008) Annual Energy Review 2007. Energy Information
Administration, U.S. Department of Energy, Washington,
DC. DOE/EIA-0384(2007). June 2008.
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.
References 11-13
-------
Lindstrom, P. (2006) Personal communication. Perry
Lindstrom, Energy Information Administration and Jean
Kim, ICF International.
Industrial Processes
Cement Production
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and
K. Tanabe (eds.). Hayama, Kanagawa, Japan.
USGS (1995 through 2008) Minerals Yearbook: Cement
Annual Report. U.S. Geological Survey, Reston, VA.
U.S. Bureau of Mines (1990, 1992, 1993) Minerals
Yearbook: Cement Annual Report. U.S. Department of the
Interior, Washington, DC.
van Oss (2008a) Personal communication. Hendrik van Oss,
Commodity Specialist of the U.S. Geological Survey and
Erin Gray, ICF International. December 16, 2008.
van Oss (2008b) Personal communication. Hendrik van Oss,
Commodity Specialist of the U.S. Geological Survey and
Tristan Kessler, ICF International. October 20, 2008.
van Oss (2008c) Personal communication. Hendrik van Oss,
Commodity Specialist of the U.S. Geological Survey and
Chris Steuer, ICF International. February 7, 2008.
Lime Production
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.2000).
Lutter (2008). Personal communication. Karen Lutter,
California Air Resources Board and Mausami Desai, EPA.
October 28, 2008.
Males, E. (2003) Memorandum from Eric Males, National
Lime Association to Mr. William N. Irving & Mr. Leif
Hockstad, Environmental Protection Agency. March 6,2003.
Miner, R. and B. Upton (2002). Methods for estimating
greenhouse gas emissions from lime kilns at kraft pulp mills.
Energy. Vol. 27 (2002), p. 729-738.
Prillaman (2008). Personal communication. Hunter
Prillaman, National Lime Association and Mausami Desai,
EPA. November 5, 2008.
USGS (2008). 2007 Minerals Yearbook: Lime (Advance
Release). U.S. Geological Survey, Reston, VA.
USGS (1992 through 2007) Minerals Yearbook: Lime Annual
Report. U.S. Geological Survey, Reston, VA.
Limestone and Dolomite Use
USGS (2008a). Minerals Yearbook: Crushed Stone Annual
Report 2007 (Advanced Copy). U.S. Geological Survey,
Reston, VA.
USGS (2008b). Minerals Yearbook: Magnesium Annual
Report 2007 (Advanced Copy). U.S. Geological Survey,
Reston, VA.
USGS (1995 through 2007a) Minerals Yearbook: Crushed
Stone Annual Report. U.S. Geological Survey, Reston, VA.
USGS (1995 through 20ff7b) Minerals Yearbook: Magnesium
Annual Report. U.S. Geological Survey, Reston, VA.
U.S. Bureau of Mines (1991 & 1993) Minerals Yearbook:
Crushed Stone Annual Report. U.S. Department of the
Interior, Washington, DC.
Soda Ash Production and Consumption
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
USGS (2008) Minerals Yearbook: Soda Ash Annual Report.
(Advanced Data) U.S. Geological Survey, Reston, VA.
USGS (1994 through 2007) Minerals Yearbook: Soda Ash
Annual Report. U.S. Geological Survey, Reston, VA.
Ammonia Production and
Urea Consumption
Bark (2004) Coffeyville Nitrogen Plant. Available online at
December 15, 2004.
Coffeyville Resources Nitrogen Fertilizers, LLC (2005
through 2007a) Business Data. Available online at
Coffeyville Resources Nitrogen Fertilizers (2007b).
Nitrogen Fertilizer Operations. Available online at .
EEA (2004) Natural Gas Issues for the U.S. Industrial
and Power Generation Sectors. Submitted to National
Commission on Energy Policy.
EFMA (1995) Production of Ammonia. European Fertilizer
Manufacturers Association. March 1, 1995.
TFI (2002) U.S. Nitrogen Imports/Exports Table. The
Fertilizer Institute. Available online at . August 2002.
11-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
TIG (2002) Chemical Profiles - Urea. The Innovation Group.
Available online at . September 2007.
U.S. Census Bureau (2008), Current Industrial Reports
Fertilizer Materials and Related Products: 2007 Summary.
Available online at .
U.S. Census Bureau (2007) Current Industrial Reports
Fertilizer Materials and Related Products: 2006 Summary.
Available online at .
U.S. Census Bureau (2006) Current Industrial Reports
Fertilizer Materials and Related Products: 2005 Summary.
Available online at .
U.S. Census Bureau (2002, 2004, 2005) Current Industrial
Reports Fertilizer Materials and Related Products: Fourth
Quarter Report Summary. Available online at .
U.S. Census Bureau (1998 through 2002b, 2003) Current
Industrial Reports Fertilizer Materials and Related Products:
Annual Reports 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 (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 (1991 through 1994) Current Industrial
Reports Fertilizer Materials Annual Report. Report No.
MQ28B. U.S. Census Bureau, Washington, DC.
U.S. Department of Agriculture (2008) Economic Research
Service Data Sets, U.S. Fertilizer Imports/Exports. Available
online at .
U.S. ITC (2002) United States International Trade
Commission Interactive Tariff and Trade DataWeb, Version
2.5.0. Available online at . August 2002.
Nitric Acid Production
EPA (2008) Draft Nitric Acid Database. U.S. Environmental
Protection Agency, Office of Air and Radiation. September,
2008.
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.
ICIS (2008) Chemical Profile: Nitric Acid. ICIS Chemical
Business. May 16, 2008.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
US Census Bureau (2008) Current Industrial Reports.
Fertilizers and Related Chemicals: 2007. "Table 1:
Shipments and Production of Principal Fertilizers and Related
Chemicals: 2003 to 2007." June, 2008. MQ325B(07)-5.
Available online at .
US Census Bureau (2006) Current Industrial Reports.,
"Table 995: Inorganic Chemicals and Fertilizers." August,
2006. Series MAQ325A Available online at .
AdipicAcid Production
ACC (2003) "Adipic Acid Production." Table
3.12—Production of the Top 100 Chemicals. Guide to
the Business of Chemistry. American Chemistry Council.
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. Dave Childs,
DuPont, USA and Duncan Rotherham, ICF International.
August 7, 2003.
Childs, D. (2002) Personal communication. Dave Childs,
DuPont, USA and Laxmi Palreddy, ICF Consulting. 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 (2007) "ProductFocus: AdipicAcid." Chemical Week.
August 1-8, 2007.
References 11-15
-------
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.
ICIS (2007) "Adipic Acid." ICIS Chemical Business
Americas. July 9, 2007.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Reimer, R.A., Slaten, C.S., Seapan, M., Koch, T.A. and
Triner, V.G. (1999) "Implementation of Technologies for
Abatement of N2O Emissions Associated with Adipic Acid
Manufacture." Proceedings of the 2nd Symposium on Non-
CO2 Greenhouse Gases (NCGG-2), Noordwijkerhout, The
Netherlands, 8-10 Sept. 1999, Ed. J. van Ham et al., Kluwer
Academic Publishers, Dordrecht, pp. 347-358.
Thiemens, M.H., andW.C. Trogler (1991) "Nylon production;
an unknown source of atmospheric nitrous oxide." Science
251:932-934.
VADEQ (2006) Virginia Title VOperating Permit. Honeywell
International Inc. Hopewell Plant. Virginia Department of
Environmental Quality. Permit No. PRO50232. Effective
January 1,2007.
Silicon Carbide Production
Corathers, L. (2007) Personal communication, Lisa
Corathers, Commodity Specialist, U.S. Geological Survey
and Michael Obeiter, ICF International. September
2007.
Corathers, L. (2006) Personal communication. Lisa
Corathers, Commodity Specialist, U.S. Geological Survey
and Erin Fraser, ICF International. October 2006.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
U.S. Census Bureau (2005 through 2008) U.S International
Trade Commission (USITC) Trade DataWeb. Available
online at .
USGS (2006) Minerals Yearbook: Manufactured Abrasives
Annual Report 2005. U.S. Geological Survey, Reston, VA.
USGS (199la through 2005a) Minerals Yearbook:
Manufactured Abrasives Annual Report 2004. U.S.
Geological Survey, Reston, VA.
USGS (1991b through 2005b) Minerals Yearbook: Silicon
Annual Report 2004. U.S. Geological Survey, Reston, VA.
Petrochemical Production
ACC (2002,2003,2005 through 2008) Guide to the Business
of Chemistry. American Chemistry Council, Arlington, VA.
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.
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. (2008) Personal communication. Greg
Johnson of Liskow & Lewis, on behalf of the International
Carbon Black Association (ICBA) and Jean Y. Kim, ICF
International. November 2008.
Johnson, G. L. (2007) Personal communication. Greg
Johnson of Liskow & Lewis, on behalf of the International
Carbon Black Association (ICBA) and Tristan Kessler, ICF
International. November 2007.
Johnson, G. L. (2006) Personal communication. Greg
Johnson of Liskow & Lewis, on behalf of the International
Carbon Black Association (ICBA) and Erin Fraser, ICF
International. October 2006.
Johnson, G. L. (2005) Personal communication. Greg
Johnson of Liskow & Lewis, on behalf of the International
Carbon Black Association (ICBA) and Erin Fraser, ICF
International. October 2005.
Johnson, G. L. (2003) Personal communication. Greg
Johnson of Liskow & Lewis, on behalf of the International
Carbon Black Association (ICBA) and Caren Mintz, ICF
International 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.
The Innovation Group (2004) Carbon Black Plant Capacity.
Available online at .
11-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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.
Titanium Dioxide Production
Gambogi, J. (2002) Telephone communication. Joseph
Gambogi, Commodity Specialist, U.S. Geological Survey
and Philip Groth, ICF International. November 2002.
IPCC (2006) 20061PCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Nelson, H.W. (1969) Petroleum Coke Handling Problems.
Great Lakes Carbon Corporation.
USGS (1991 through 2008) Mineral Yearbook: Titanium
Annual Report. 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 (2007). CO2-EOR: An Enabling Bridge for the Oil
Transition. Presented at "Modeling the Oil Transition—a
DOE/EPA Workshop on the Economic and Environmental
Implications of Global Energy Transitions." Washington,
DC. April 20-21,2007.
ARI (2006) CO2-EOR: An Enabling Bridge for the Oil
Transition. Presented at "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 (2003). Personal communication. RonBroadhead,
Principal Senior Petroleum Geologist and Adjunct faculty,
Earth and Environmental Sciences Department, New Mexico
Bureau of Geology and Mineral Resources, and Robin
Pestrusak, ICF International. September 5, 2003.
Denbury Resources Inc. (2002 through 2008) Annual Report:
Form 10-K.p, 6.
Godec (2008). Personal communication. Mike Godec, Vice
President of the Advanced Resources International and
Robert Lanza, ICF International. August 26, 2008.
New Mexico Bureau of Geology and Mineral Resources
(2006). Natural Accumulations of Carbon Dioxide
in New Mexico and Adjacent Parts of Colorado and
Arizona: Commercial Accumulation of CO2. Available
online at .
Phosphoric Acid Production
EFMA (2000) "Production of Phosphoric Acid." Best
Available Techniques for Pollution Prevention and Control
in the European Fertilizer Industry. Booklet 4 of 8. European
Fertilizer Manufacturers Association. Available online at
.
FIPR (2003) "Analyses of Some Phosphate Rocks."
Facsimile from Gary Albarelli, the Florida Institute of
Phosphate Research, Bartow, Florida, to Robert Lanza, ICF
International. July 29, 2003.
FIPR (2003a) Florida Institute of Phosphate Research.
Personal communication. Mr. Michael Lloyd, Laboratory
Manager, FIPR, Bartow, Florida, to Mr. Robert Lanza, ICF
International. August 2003.
USGS (1994 through 2002, 2004 through 2008) Minerals
Yearbook. Phosphate Rock Annual Report. U.S. Geological
Survey, Reston, VA.
Iron and Steel Production and
Metallurgical Coke Production
AISI (2004 through 2008a) Annual Statistical Report,
American Iron and Steel Institute, Washington, DC.
AISI (2008b) Personal communication, Mausami Desai,
US EPA, and the American Iron and Steel Institute, October
2008.
DOE (2000) Energy and Environmental Profile of the U.S.
Iron and Steel Industry. Office of Industrial Technologies,
U.S. Department of Energy. August 2000. DOE/EE-0229.
EIA (2008a) Quarterly Coal Report: January-March 2008,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (2008b) "Supplemental Tables on Petroleum Product
detail." Monthly Energy Review, December 2008, Energy
Information Administration, U.S. Department of Energy,
Washington, DC. DOE/EIA-0035 (2008/12).
EIA (2007) Quarterly Coal Report: January-March 2007,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (2006a) Quarterly Coal Report: January-March 2006,
Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0121.
EIA (1998 through 2004a) Quarterly Coal Report: October-
December, Energy Information Administration, U.S.
Department of Energy. Washington, DC. DOE/EIA-0121.
References 11-17
-------
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC/UNEP/OECD/IEA (1995) "Volume 3: Greenhouse Gas
Inventory Reference Manual. Table 2-2." 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. IPCC WG1
Technical Support Unit, United Kingdom.
Ferroalloy Production
Corathers, L. (2008) Personal communication. LisaCorathers,
Commodity Specialist, U.S. Geological Survey and Sarah
Menassian, ICE International. September 16, 2008.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Onder, H., and E.A. Bagdoyan (1993) Everything You've
Always Wanted to Know about Petroleum Coke. Allis Mineral
Systems.
USGS (1991 through 2007) Minerals Yearbook: Silicon
Annual Report. U.S. Geological Survey, Reston, VA.
Aluminum Production
Alcoa Inc. (2007) "Re-Energized Potline Produces
Employment and Stability at Alcoa Ferndale Operations."
News release posted: February 5, 2007. Available online
at . Last accessed: October 31, 2008.
Gariepy, B. and G. Dube (1992) "Treating Aluminum with
Chlorine." U.S. Patent 5,145,514. Issued September 8,
1992.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.2000).
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.
USAA (2004, 2005, 2006) Primary Aluminum Statistics.
U.S. Aluminum Association, Washington, DC.
USAA (2007) "Glencore Restarts Potline at Montana." U.S.
Aluminum Association, Washington, DC. News archive
posted: January 25, 2007. Last accessed: October 31, 2008.
Available online at .
USAA (2008) U.S. Primary Aluminum Production. U.S.
Aluminum Association, Washington, DC.
USGS (2007) 2006 MineralYeabook: Aluminum. U.S.
Geological Survey, Reston, VA.
USGS (1995,1998,2000,2001,2002) Minerals Yearbook:
Aluminum Annual Report. U.S. Geological Survey,
Reston, VA.
Victor, D.G. and G.J. 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 . 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
125th The Minerals, Metals & Materials Society (TMS)
Annual Meeting, Anaheim, CA, 77-93.
Magnesium Production and Processing
Bartos S., C. Laush, J. Scharfenberg, and R. Kantamaneni
(2007) "Reducing greenhouse gas emissions from
magnesium die casting," Journal of Cleaner Production,
15: 979-987, March.
Gjestland, H. and D. Magers (1996) "Practical Usage of
Sulphur [Sulfur] Hexafluoride for Melt Protection in the
Magnesium Die Casting Industry," #13, 7996 Annual
Conference Proceedings, International Magnesium
Association. Ube City, Japan.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
RAND (2002) RAND Environmental Science and Policy
Center, "Production and Distribution of SF6 by End-Use
Applications" Katie D. Smythe. International Conference
on SF6 and the Environment: Emission Reduction Strategies.
San Diego, CA. November 21-22, 2002.
11-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
USGS (2002,2003,2005 through 2008a) Minerals Yearbook:
Magnesium Annual Report. U.S. Geological Survey, Reston,
VA. Available online at .
USGS (2008b) Mineral Industry Surveys: Magnesium in
the Second Quarter. U.S. Geological Survey, Reston, VA.
Available online at .
Zinc Production
Queneau P.B., S.E. James, J.R Downey, and G.M. Livelli
(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) Personal communication. Eric Stuart, Steel
Manufacturers Association and Christopher Steuer, ICF
International. October 31, 2005.
Tolcin, A. (2009) Personal communication. Amy Tolcin,
Commodity Specialist, U.S. Geological Survey and Sarah
Menassian, ICF International. January 22, 2009.
USGS (1994 through 2008) Minerals Yearbook: Zinc Annual
Report. U.S. Geological Survey, Reston, VA.
USGS (2008b) Mineral Commodity Summary: Zinc. 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 40(3):292-299.
Lead Production
Dutrizac, J.E., V Ramachandran, and J.A. Gonzalez (2000)
Lead-Zinc 2000. The Minerals, Metals, and Materials
Society.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
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.
Smith, G. (2007) Personal communication. Gerald Smith,
Commodity Specialist, USGS and Toby Krasney, ICF
International. October 7, 2007.
Ullman 's Encyclopedia of Industrial Chemistry: Fifth Edition
(1997) Volume A5. John Wiley and Sons.
USGS (1994 through 2009) Minerals Yearbook: Lead Annual
Report. U.S. Geological Survey, Reston, VA.
HCFC-22 Production
ARAP (2008) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
October 17, 2008.
ARAP (2007) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
October 2, 2007.
ARAP (2006) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Sally Rand, U.S. Environmental Protection Agency. July
11,2006.
ARAP (2005) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
August 9, 2005.
ARAP (2004) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
June 3, 2004.
ARAP (2003) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Sally Rand, U.S. Environmental Protection Agency. August
18, 2003.
ARAP (2002) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
August 7, 2002.
ARAP (2001) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Deborah Ottinger, U.S. Environmental Protection Agency.
August 6, 2001.
ARAP (2000) E-mail communication. Dave Stirpe, Executive
Director, Alliance for Responsible Atmospheric Policy and
Sally Rand, 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, U.S. Environmental Protection
Agency. September 23, 1999.
ARAP (1997) Letter from Dave Stirpe, Director, Alliance for
Responsible Atmospheric Policy to Elizabeth Dutrow, U.S.
Environmental Protection Agency. December 23, 1997.
References 11-19
-------
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
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.
RTI (2008) "Verification of Emission Estimates of HFC-23
from the Production of HCFC-22:Emissions from 1990
through 2006." Report prepared by RTI International for the
Climate Change Division. March, 2008.
Substitution of Ozone Depleting Substances
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
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.
2000 I.November 2001.
Burton, C.S., and N. Kshetry (2007) "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. July 2007.
Citigroup Smith Barney (2005) Global Supply/Demand
Model for Semiconductors. March 2005.
International S ematech (2006)' 'Guideline for Characterization
of Semiconductor Process Equipment," International
Sematech, Technology Transfer # 06124825A-ENG,
December 22, 2006. Note that this is an update to
previous guideline, TT from International Sematech #
01104197A-XFR, December 2001.
ITRS (2007, 2008) International Technology Roadmapfor
Semiconductors: 2006 Update;. January 2007; International
Technology Roadmap for Semiconductors: 2007 Edition,
January 2008; Available online at . These 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.
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 (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe, eds.; Institute for Global Environmental
Strategies (IGES). Hayama, Kanagawa, Japan.
Semiconductor Equipment and Materials Industry (2008)
World Fab Forecast, May 2008 Edition.
US EPA (2006) Uses and Emissions of Liquid PFC
Heat Transfer Fluids from the Electronics Sector. U.S.
Environmental Protection Agency, Washington, DC. EPA-
430-R-06-901.
VLSI Research, Inc. (2007) Document 327028, V6.12.l-
Worldwide Silicon Demand by Wafer Size, by Linewidth and
by Device Type. January 2007. Available online at .
Electrical Transmission and Distribution
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
O'Connell, P., F Heil, J. Henriot, G. Mauthe, H. Morrison, L.
Neimeyer, M. Pittroff, R. Probst, J.P Tailebois (2002) SF6 in
the Electric Industry, Status 2000, CIGRE. February 2002.
RAND (2004) "Trends in SF6 Sales and End-Use Applications:
1961-2003," Katie D. Smythe. International Conference on
SF6 and the Environment: Emission Reduction Strategies.
RAND Environmental Science and Policy Center, Scottsdale,
AZ. December 1-3, 2004.
UDI (2007) 2007 UDIDirectory of Electric Power Producers
and Distributors, 115th Edition, Platts.
UDI (2004) 2004 UDI Directory of Electric Power Producers
and Distributors, 112th Edition, Platts.
UDI (2001) 2007 UDI Directory of Electric Power Producers
and Distributors, 109th Edition, Platts.
Industrial Sources of Indirect
Greenhouse Gases
EPA (2008). "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards. Available online at
11 -20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data. 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 from Product Uses
Airgas (2007) Airgas, INC. Form 10-K. Annual Report
Pursuant to Section 13 or 15 (d) of the SEC Act of 1934. Fiscal
year ended March, 31,2007. Available online at .
CGA (2003) "CGA Nitrous Oxide Abuse Hotline: CGA/
NWSA Nitrous Oxide Fact Sheet." Compressed Gas
Association. Novembers, 2003.
CGA (2002) "CGA/NWSA Nitrous Oxide Fact Sheet."
Compressed Gas Association. March 25, 2002.
FTC (2001) Federal Trade Commission: Analysis of Agreement
Containing Consent Order To Aid Public Comment. FTC File
No. 001-0040. October, 2001. Available online at .
Heydorn, B. (1997) "Nitrous Oxide—North America."
Chemical Economics Handbook, SRI Consulting. May 1997.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Tupman, M. (2003) Personal communication. Martin
Tupman, Airgas Nitrous Oxide and Daniel Lieberman, ICF
International. August 8, 2003.
Tupman, M. (2002) Personal communication. Martin
Tupman of Airgas Nitrous Oxide and Laxmi Palreddy, ICF
International. July 3, 2002.
Solvent Use
EPA (2008). "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data. 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.
Agriculture
Enteric Fermentation
Baldwin R.L. (1995) Modeling Ruminant Digestion and
Metabolism. Chapman & Hall, London, UK.
Crutzen, P.J., I. Aselmann, and W. Seiler (1986) "Methane
Production by Domestic Animals, Wild Ruminants, Other
Herbivores, Fauna, and Humans." Tellus, 38B:271-284.
Donovan, K. (1999) Personal Communication. Kacey
Donovan, 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.
Ellis J.L., Kebreab E., Odongo N.E., McBride B.W., Okine
E.K. and France J. (2007) "Prediction of methane production
from dairy and beef cattle." J. Dairy Sci. 90:3456-3467.
Enns, M. (2008) Personal Communication. Dr. Mark Enns,
Colorado State University and staff at ICF International.
EPA (2000) Draft Enteric Fermentation Model Documentation.
Office of Air and Radiation, U.S. Environmental Protection
Agency, Washington, DC. June 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 (2008) FAOSTAT Statistical Database. Food and
Agriculture Organization of the United Nations. Available
online at .
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. Memorandum from ICF International to the
Environmental Protection Agency. May 2003.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
References 11-21
-------
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change, Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.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. (2002) Personal Communication. Don
Johnson, 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. Don Johnson,
Colorado State University, Fort Collins, and David Conneely,
ICF International.
Kebreab E., Mills J.A.N., Crompton L.A., Bannink A.,
Dijkstra J., Gerrits W. J. J. and France J. (2004) "An integrated
mathematical model to evaluate nutrient partition in dairy
cattle between animal and environment." Anim. Feed Sci.
Technol. 112:131-154.
Lange, J. (2000) Personal Communication. Lee-Ann Tracy,
ERG and John Lange, Agricultural Statistician, U. S.
Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
Lippke, PL, T. D. Forbes, and W. C. Ellis. (2000) "Effect of
supplements on growth and forage intake by stacker steers
grazing wheat pasture." J. Anim. Sci. 78:1625-1635
Mills J. A.N., Dijkstra J., Bannink A., Cammell S .B., Kebreab
E. and France J., (2001) "A mechanistic model of whole-tract
digestion and methanogenesis in the lactating dairy cow:
model development, evaluation, and application." J. Anim.
Sci. 79: 1584-1597.
Molly (2007) Version 3.0 available from .
NRC (2000) Nutrient Requirements of Beef Cattle: Seventh
Revised Edition: Update 2000. Table 11-1, Appendix Table
1. National Research Council.
NRC (1999) 7996 Beef NRC: Appendix Table 22. National
Research Council.
Patton, J., J. J. Murphy, F P. O'Mara and S. T. Butler (2008).
"A comparison of energy balance and metabolic profiles of
the New Zealand and North American strains of Holstein
Friesian dairy cow." Animal 2(6):969-978.
Pinchak, W.E., D. R. Tolleson, M. McCloy, L. J. Hunt, R. J.
Gill, R. J. Ansley, and S. J. Bevers (2004) "Morbidity effects
on productivity and profitability of stacker cattle grazing in
the southern plains." J. Anim. Sci. 82:2773-2779.
Platter, W. J., J. D. Tatum, K. E. Belk, J. A. Scanga, and G. C.
Smith (2003) "Effects of repetitive use of hormonal implants
on beef carcass quality, tenderness, and consumer ratings of
beef palatability." J. Anim. Sci. 81:984-996.
Skogerboe, T. L., L. Thompson, J. M. Cunningham, A. C.
Brake, V. K. Karle (2000) "The effectiveness of a single
dose of doramectin pour-on in the control of gastrointestinal
nematodes in yearling stacker cattle." Vet. Parasitology
87:173-181.
USDA (2008) Quick Stats: Agricultural Statistics Database.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . June 27, 2008.
USDA (1996) Beef Cow/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. Available
online at .
March 1996.
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
.
Manure Management
Anderson, S. (2000) Personal Communication. Lee-Ann
Tracy, ERG and Steve Anderson, Agricultural Statistician,
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. May 31, 2000.
ASAE (1999) ASAE Standards 1999,46th 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.
11 -22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Deal, P. (2000) Personal Communication. Lee-Ann
Tracy, ERG and Peter B. Deal, Rangeland Management
Specialist, Florida Natural Resource Conservation
Service. June 21,2000.
EPA (2008) Climate Leaders Greenhouse Gas Inventory
Protocol Offset Project Methodology for Project Type
Managing Manure with Biogas Recovery Systems. Available
online at .
EPA (2006) AgSTAR Digest. Office of Air and Radiation,
U.S. Environmental Protection Agency, Washington, DC.
Winter 2006. Available online at July 2006.
EPA (2005) National Emission Inventory—Ammonia
Emissions from Animal Agricultural Operations, Revised
Draft Report. U.S. Environmental Protection Agency,
Washington, DC. April 22, 2005. Available online at August 2007.
EPA (2003a) Inventory of U.S. Greenhouse Gas Emissions and
Sinks: 1990-2001. EPA430-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. Available online at 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/or 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, Office of Air and Radiation, U.S.
Environmental Protection Agency. February 1992.
ERG (2008) "Methodology for Improving Methane
Emissions Estimates and Emission Reductions from
Anaerobic Digestion System for the 1990-2007 Greenhouse
Gas Inventory for Manure Management." Memorandum to
EPA from ERG. August 18, 2008.
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 (2008) Yearly U.S. total horse population data from the
Food and Agriculture Organization of the United Nations
database. Available online at . June
2008.
Garrett, W.N. and D.E. Johnson (1983) "Nutritional
energetics of ruminants." Journal of Animal Science,
57(suppl.2):478^97.
Groffman, P.M., R. Brumme, K. Butterbach-Bahl, K.E.
Dobbie, A.R. Mosier, D. Ojima, H. Papen, W.J. Parton,
K.A. Smith, and C. Wagner-Riddle (2000) "Evaluating
annual nitrous oxide fluxes at the ecosystem scale." Global
Biogeochemical 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 oftheASAE,
25(1):226-230.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Johnson, D. (2000) Personal Communication. Lee-Ann
Tracy, ERG and Dan Johnson, State Water Management
Engineer, California Natural Resource Conservation Service.
June 23, 2000.
Lange, J. (2000) Personal Communication. Lee-Ann
Tracy, ERG and John Lange, Agricultural Statistician, U.S.
Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
Miller, P. (2000) Personal Communication. Lee-Ann Tracy,
ERG and Paul Miller, Iowa Natural Resource Conservation
Service. June 12, 2000.
References 11-23
-------
Milton, B. (2000) Personal Communication. Lee-Ann Tracy,
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 (2008) National Climate Data Center (NCDC).
Available online at
(for all states except Alaska and Hawaii) and (for Alaska and Hawaii).
June 2008.
Pape, D. andK. Moffroid (2008) 1990-2007 Volatile Solids
and Nitrogen Excretion Rates. Dataset to EPA from ICE
International. August 2008.
Pederson, L., D. Pape and K. Moffroid (2007) 1990-2006
Volatile Solids and Nitrogen Excretion Rates, EPA Contract
GS-10F-0124J, Task Order 056-01. Memorandum to EPA
from ICE International. August 2007.
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. andPW. Westerman (1990) "Psychrophilic
anaerobic digestion of animal manure: proposed design
methodology." Biological Wastes, 34:133-148.
Safley, L.M., Jr. (2000) Personal Communication. Deb
Bartram, ERG and L.M. Safley, President, Agri-Waste
Technology. June and October 2000.
Stettler, D. (2000) Personal Communication. Lee-Ann Tracy,
ERG and Don Stettler, Environmental Engineer, National
Climate Center, Oregon Natural Resource Conservation
Service. June 27, 2000.
Sweeten, J. (2000) Personal Communication. Indra
Mitra, ERG and John Sweeten, Texas A&M University.
June 2000.
UEP (1999) Vo luntary 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 (2008a) Published Estimates Database. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online . June 2008.
USDA (2008b) Chicken and Eggs 2007 Summary. National
Agriculture Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 2008. Available online at .
USDA (2008c) Poultry - Production and Value 2007
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2008.
Available online at .
USDA (2008d) Sheep and Goats. National Agriculture
Statistics Service, U.S. Department of Agriculture,
Washington, DC. February 2008. Available online at.
USDA (2005) 7992, 7997, and 2002 Census of Agriculture.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . March 2006.
USDA (2004a) Chicken and Eggs-Final Estimates
1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004b) 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 (2003) APHIS Sheep 2001, Parts I and IV. Available
online at .
USDA (2000a) National Animal Health Monitoring System's
(NAHMS) Dairy '96 Study. Stephen L. Ott, Animal and Plant
Health Inspection Service, U.S. Department of Agriculture.
June 19, 2000.
USDA (2000b) Layers '99-Part II: References of 1999
Table Egg Layer Management in the U.S. Animal and
Plant Health Inspection Service (APHIS), National Animal
Health Monitoring System (NAHMS), U.S. Department of
Agriculture. January 2000.
USDA (1999) 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 (1998a) Chicken and Eggs-Final Estimates 1994-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998. Available online
at .
USDA (1998b) National Animal Health Monitoring
System's (NAHMS) Swine '95 Study. Eric Bush, 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.
11 -24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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) Chicken and Eggs—Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . January 1995.
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 (1994) 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) Personal Communication. Lee-Ann Tracy,
ERG and Peter Wright, Cornell University, College of
Agriculture and Life Sciences. June 23, 2000.
Rice Cultivation
Anderson, M. (2008) Email correspondence. Monte
Anderson, Oklahoma Farm Service Agency and Sarah
Menassian, ICE International. August 5, 2008.
Bollich, P. (2000) Personal Communication. Pat Bollich,
Professor with Louisiana State University Agriculture Center
and Payton Decks, ICE International. 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) Personal Communication. Janet Lewis,
Assistant to Gaston Cantens, Vice President of Corporate
Relations, Florida Crystals Company and Lauren Flinn, ICE
International. August 4, 2005.
Cantens, G. (2004) Personal Communication. Janet Lewis,
Assistant to Gaston Cantens, Vice President of Corporate
Relations, Florida Crystals Company and Lauren Flinn of
ICE International. July 30, 2004.
Cicerone R.J., C.C. Delwiche, S.C. Tyler, and PR. Zimmerman
(1992) "Methane Emissions from California Rice Paddies
with Varied Treatments." Global Biogeochemical Cycles,
6:233-248.
Deren, C. (2002) Personal Communication and Dr. Chris
Deren, Everglades Research and Education Centre at the
University of Florida and Caren Mintz, ICF International.
August 15, 2002.
Gonzalez, R. (2008) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Sarah
Menassian, ICF International. July 12, 2008.
Gonzalez, R. (2007a) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Sarah
Menassian, ICF International. August 29, 2007.
Gonzalez, R. (2007b) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Victoria
Thompson, ICF International. August 2007.
Guethle, D. (2008) Email correspondence. David Guethle,
Agronomy Specialist, Missouri Cooperative Extension Service
and Sarah Menassian, ICF International. June 30, 2008.
Guethle, D. (2007) Email correspondence. David Guethle,
Agronomy Specialist, Missouri Cooperative Extension
Service and Victoria Thompson, ICF International. July
30, 2007.
Guethle, D. (2006) Personal Communication. David Guethle,
Agronomy Specialist, Missouri Cooperative Extension
Service and Lauren Flinn, ICF International. July 2006.
Guethle, D. (2005) Personal Communication. David Guethle,
Agronomy Specialist, Missouri Cooperative Extension
Service and Lauren Flinn, ICF International. July 2005.
Guethle, D. (2004) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Lauren Flinn, ICF International.
June 23, 2004.
Guethle, D. (2003) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Caren Mintz, ICF International.
June 19, 2003.
Guethle, D. (2002) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Caren Mintz, ICF International.
August 19, 2002.
Guethle, D. (200la) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Caren Mintz, ICF International. July
31,2001.
Guethle, D. (200Ib) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Caren Mintz, ICF International.
September 4, 2001.
Guethle, D. (2000) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Payton Decks, ICF International.
May 17, 2000.
Guethle, D. (1999) Personal Communication. David
Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Payton Decks, ICF International.
August 6, 1999.
References 11-25
-------
Holzapfel-Pschorn, A., R. Conrad, and W. Seller (1985)
"Production, Oxidation, and Emissions of Methane in Puce
Paddies." FEMS Microbiology Ecology, 31:343-351.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
IPCC (2000) Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories.
National Greenhouse Gas Inventories Programme,
Intergovernmental Panel on Climate Change. Montreal. May
2000. IPCC-XVI/Doc. 10 (1.IV.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) Personal Communication. ArthurKirstein,
Coordinator, Agricultural Economic Development Program,
Palm Beach County Cooperative Extension Service, FL and
Lauren Flinn, ICF International. August 17, 2006.
Kirstein,A. (2004) Personal Communication. Arthur Kirstein,
Coordinator, Agricultural Economic Development Program,
Palm Beach County Cooperative Extension Service, FL and
Lauren Flinn, ICF International. June 30, 2004.
Kirstein,A. (2003) Personal Communication. Arthur Kirstein,
Coordinator, Agricultural Economic Development Program,
Palm Beach County Cooperative Extension Service, FL and
Caren Mintz, ICF International. August 13, 2003.
Klosterboer, A. (2003) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. July 7,2003.
Klosterboer, A. (2002) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. August
19, 2002.
Klosterboer, A. (2001a) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. August
6, 2001.
Klosterboer, A. (200Ib) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. October
8,2001.
Klosterboer, A. (2000) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Pay ton Decks, ICF International. May
18, 2000.
Klosterboer, A. (1999) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Catherine Leining, ICF International. June
10, 1999.
Klosterboer, A. (1997) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Holly Simpkins, ICF Incorporated. December
1, 1997.
Lancero, J. (2008) Email correspondence. Jeff Lancero,
California Air Resources Board and Sarah Menassian, ICF
International. July 24, 2008.
Lancero, J. (2007) Email correspondence. Jeff Lancero,
California Air Resources Board and Victoria Thompson,
ICF International. July 24, 2007.
Lancero, J. (2006) Email correspondence. Jeff Lancero,
California Air Resources Board and Lauren Flinn, ICF
International. August 11, 2006.
Lee, D. (2007) Email correspondence. Danny Lee, OK Farm
Service Agency and Victoria Thompson, ICF International.
July 30, 2007.
Lee, D. (2006) Email correspondence. Danny Lee, OK Farm
Service Agency and Lauren Flinn, ICF International. July
13, 2006.
Lee, D. (2005) Email correspondence. Danny Lee, OK Farm
Service Agency and Lauren Flinn, ICF International. July
and September 2005.
Lee, D. (2004) Personal Communication. Danny Lee, OK
Farm Service Agency and Lauren Flinn, ICF International
July 23, 2004.
Lee, D. (2003) Personal Communication. Danny Lee, OK
Farm Service Agency and Caren Mintz, ICF International.
July 2, 2003.
Lindau, C.W. and PK. Bollich (1993) "Methane Emissions
from Louisiana First and Ratoon Crop Rice." Soil Science,
156:42^18.
Lindau, C.W., PK Bollich, andR.D. DeLaune (1995) "Effect
of Rice Variety on Methane Emission from Louisiana Rice."
Agriculture, Ecosystems and Environment, 54:109-114.
Linscombe, S. (2008) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Sarah
Menassian, ICF International. June 30, 2008.
Linscombe, S. (2007) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Victoria
Thompson, ICF International. July 24, 2007.
Linscombe, S. (2006) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Fh'nn, ICF International. August 15, 2006.
11 -26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Linscombe, S. (2005) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Flinn, ICF International. July 2005.
Linscombe, S. (2004) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Flinn, ICF International.. June 23, 2004.
Linscombe, S. (2003) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Caren
Mintz, ICF International. June 10, 2003.
Linscombe, S. (2002) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Caren
Mintz, ICF International. August 21, 2002.
Linscombe, S. (2001a) Personal Communication. Steve
Linscombe, Research Agronomist, Rice Research Station
in Crowley, LA and Caren Mintz, ICF International. July
30-August 1,2001.
Linscombe, S. (200Ib) Email correspondence. Steve
Linscombe, Research Agronomist, Rice Research Station in
Crowley, LA and Caren Mintz, ICF International. October
4,2001.
Linscombe, S. (1999) Personal Communication. Steve
Linscombe, Research Agronomist, Rice Research Station
in Crowley, LA and Catherine Leining, ICF International
June3, 1999.
Mayhew, W. (1997) Personal Communication. Walter
Mayhew, University of Arkansas, Little Rock and Holly
Simpkins, ICF Incorporated. November 24, 1997.
Mutters, C. (2005) Email correspondence. Mr. Cass Mutters,
Rice Farm Advisor for Butte, Glen, and Tehama Counties
University of California, Cooperative Extension Service and
Lauren Flinn, ICF International. July 2004.
Mutters, C. (2004) Personal Communication. Mr. Cass
Mutters, Rice Farm Advisor for Butte, Glen, and Tehama
Counties University of California, Cooperative Extension
Service and Lauren Flinn, ICF International. June 25,
2004.
Mutters, C. (2003) Personal Communication. Mr. Cass
Mutters, Rice Farm Advisor for Butte, Glen, and Tehama
Counties University of California, Cooperative Extension
Service and Caren Mintz, ICF International. June 23,
2003.
Mutters, C. (2002) Personal Communication. Mr. Cass
Mutters, Rice Farm Advisor for Butte, Glen, and Tehama
Counties University of California, Cooperative Extension
Service and Caren Mintz, ICF International. August 27,
2002.
Mutters, C. (2001) Personal Communication. Mr. Cass
Mutters, Rice Farm Advisor for Butte, Glen, and Tehama
Counties University of California, Cooperative Extension
Service and Caren Mintz, ICF International. September 5,
2001.
Sacramento Valley Basinwide Air Pollution Control Council
(2007) Report on the Conditional Rice Straw Burning Permit
Program. June 1, 2007. Available online at .
Sacramento Valley Basinwide Air Pollution Control Council
(2005) Report on the Conditional Rice Straw Burning Permit
Program. May 25, 2005. Available online at .
Saichuk, J. (1997) Personal Communication. John Saichuk,
Louisiana State University and Holly Simpkins, ICF
Incorporated. November 24, 1997.
Sass, R.L., EM Fisher, PA. Harcombe, and FT. 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., FM. Fisher, FT. 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., FM. Fisher, PA. Harcombe, and FT. Turner
(1990) "Methane Production and Emissions in a Texas Rice
Field." Global Biogeochemical Cycles, 4:47-68.
Schueneman, T. (2001a) Personal Communication.
Tom Schueneman, Agricultural Extension Agent, Palm
Beach County, FL and Caren Mintz, ICF International.
July 30, 2001.
Schueneman, T. (200 Ib) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Caren Mintz, ICF International. October
9,2001.
Schueneman, T. (2000) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Payton Decks, ICF International. May 16,
2000.
Schueneman, T. (1999a) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Catherine Leining, ICF International. June
7, 1999.
Schueneman, T. (1999b) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Payton Decks, ICF International. August
10, 1999.
Schueneman, T. (1999c) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and John Venezia, ICF International. August
7, 1999.
References 11-27
-------
Schueneman, T. (1997) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Barbara Braatz, ICF Incorporated. November
7, 1997.
Slaton, N. (200la) Personal Communication. Nathan Slaton,
Extension Agronomist—Rice, University of Arkansas
Division of Agriculture Cooperative Extension Service and
Caren Mintz, ICF International. August 23, 2001.
Slaton, N. (200 Ib) Personal Communication. Nathan Slaton,
Extension Agronomist—Rice, University of Arkansas
Division of Agriculture Cooperative Extension Service and
Caren Mintz, ICF International. October 3, 2001.
Slaton, N. (2000) Personal Communication. Nathan Slaton,
Extension Agronomist—Rice, University of Arkansas
Division of Agriculture Cooperative Extension Service and
Payton Decks, ICF International. May 20, 2000.
Slaton, N. (1999) Personal Communication. Nathan Slaton,
Extension Agronomist—Rice, University of Arkansas
Division of Agriculture Cooperative Extension Service and
Catherine Leining, ICF International. June 3, 1999.
Stansel, J. (2005) Email correspondence. Dr. Jim Stansel,
Resident Director and Professor Emeritus, Texas A&M
University Agricultural Research and Extension Center and
Lauren Flinn, ICF International. July 2005.
Stansel, J. (2004) Personal Communication. Dr. Jim Stansel,
Resident Director and Professor Emeritus, Texas A&M
University Agricultural Research and Extension Center and
Lauren Flinn, ICF International. July 12, 2004.
Stevens, G. (1997) Personal Communication. Gene Stevens,
Extension Specialist, Missouri Commercial Agriculture
Program, Delta Research Center and Holly Simpkins, ICF
Incorporated. December 17, 1997.
Street, J. (2003) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. June 19, 2003.
Street, J. (2002) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. August 19,
2002.
Street, J. (2001a) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. August 1,
2001.
Street, J. (200 Ib) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. October 3,
2001.
Street, J. (2000) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Payton Decks, ICF International. May 17,
2000.
Street, J. (1999) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Catherine Leining, ICF International June 8,
1999.
Street, J. (1997) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Holly Simpkins, ICF Incorporated. December
1, 1997.
Texas Agricultural Experiment Station (2008) 2007 - Texas
Rice Acreage by Variety. Agricultural Research and Extension
Center, Texas Agricultural Experiment Station, Texas A&M
University System. Available online at .
Texas Agricultural Experiment Station (2007) 2006 - Texas
Rice Acreage by Variety. Agricultural Research and Extension
Center, Texas Agricultural Experiment Station, Texas A&M
University System. Available online at .
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 (2008) Crop Production 2007 Summary. National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at .
USDA (2007) Crop Production 2006 Summary. National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at .
USDA (2005 through 2006) Crop Production Summary.
National Agricultural Statistics Service,Agricultural Statistics
Board, U.S. Department of Agriculture, Washington, DC.
Available online at .
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 .
September 2005.
USDA (1998) Field Crops Final Estimates 1992-97.
Statistical Bulletin Number 947 a. National Agricultural
Statistics Service, Agricultural Statistics Board, U.S.
Department of Agriculture, Washington, DC. Available
online at . July 2001.
USDA (1994) Field Crops Final Estimates 1987-1992.
Statistical Bulletin Number 896. National Agricultural
Statistics Service, Agricultural Statistics Board, U.S.
Department of Agriculture, Washington, DC. Available
online at . July 2001.
11 -28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Walker, T. (2008) Email correspondence. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Sarah Menassian, ICE
International. July 25, 2008.
Walker, T. (2007) Personal Communication. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Victoria Thompson, ICE
International. August 15, 2007.
Walker, T. (2005) Email correspondence. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Lauren Flinn, ICE International.
July 2005.
Wilson, C. (2007) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Victoria Thompson, ICE
International. August 22, 2007.
Wilson, C. (2006) Email correspondence. Dr. Chuck Wilson,
Rice Specialist at the University of Arkansas Cooperative
Extension Service and Lauren Flinn, ICF International.
August 8, 2006.
Wilson, C. (2005) Email correspondence. Dr. Chuck Wilson,
Rice Specialist at the University of Arkansas Cooperative
Extension Service and Lauren Flinn, ICF International.
August 2005.
Wilson, C. (2004) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Lauren Flinn, ICF
International. June 23, 2004.
Wilson, C. (2003) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Caren Mintz, ICF
International. June 11, 2003.
Wilson, C. (2002) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Caren Mintz, ICF
International. August 23, 2002.
Agricultural Soil Management
AAPFCO (1995 through 2000b, 2002 through 2008)
Commercial Fertilizers. Association of American Plant Food
Control Officials. 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.
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.
Anonymous (1924) Fertilizer Used on Cotton, 1923-1924.
"Miscellaneous Agricultural Statistics," Table 753. 1924
Yearbook of the Department of Agriculture, 1171.
Bastian, R. (2007) Personal Communication. Robert Bastian,
Office of Water, U.S. Environmental Protection Agency,
Washington, DC and Victoria Thompson, ICF International.
July 20, 2007.
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 andlowaprairies in the Nineteenth Century. The
University of Chicago Press, Chicago, IL.
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.
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 Natural Resources
Conservation Service, U.S. Department of Agriculture, 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.
ChilcottE.C. (1910) A Study of Cultivation Methods and Crop
Rotations for the Great Plains Area. Bureau of Plant Industry
Bulletin Number 187, U.S. Department of Agriculture,
Government Printing Office. Washington, DC.
Cibrowski, P. (1996) Personal Communication. Peter
Cibrowski, Minnesota Pollution Control Agency and Heike
Mainhardt, ICF Incorporated. July 29, 1996.
Cochran, W.G. (1977) Sampling Techniques, Third Edition.
Wiley Publishing, New York.
CTIC (1998) 7998 Crop Residue Management Executive
Summary. Conservation Technology Information Center.
Available online at .
Daly, C., G.H. Taylor, W.P Gibson, T. Parzybok, G.L.
Johnson, and PA. 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, I-512-I-519.
June 1-3, 1998.
References 11-29
-------
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.
DAYMET (No date) Daily Surface Weather and
Climatological Summaries. Numerical Terradynamic
Simulation Group (NTSG), University of Montana. Available
online at .
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., T. Wirth, S.M. Ogle, W.J. Parton (2008)
Estimating agricultural nitrous oxide emissions. EOS 89,
529-530.
Del Grosso, S.J., A.R. Mosier, W.J. Parton, and D.S.
Ojima (2005) "DAYCENT Model Analysis of Past and
Contemporary Soil N2O 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., W.J. Parton, A.R. Mosier, M.D. Hartman,
J. Brenner,D.S. Ojima, andD.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.
Del Grosso, S.J., W.J. Parton,A.R. Mosier,D.S. Ojima,A.E.
Kulmala and S. Phongpan (2000) General model for N2O and
N2 gas emissions from soils due to denitrification. Global
Biogeochem. Cycles, 14:1045-1060.
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 National Fertilizer Association. The
Fertilizer Review, 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 (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 (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 correspondence. Marl en Eve, Natural
Resources Ecology Laboratory, Colorado State University
and Barbara Braatz and Caren Mintz, ICF International.
Statistics on U.S. organic soil areas cultivated in 1982,1992,
and 1997, which were extracted from the 7997 National
Resources Inventory. September 21, 2001.
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, 1920-1990. University
Press of Kansas, Lawrence, KS.
11 -30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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 G.K. (1902) "Practices in Crop Rotation." Yearbook
of the Department of Agriculture, 519-532.
HurdE.B. (1929) The Corn Enterprise in Iowa. Agricultural
Experiment Station Bulletin Number 268. Iowa State College
of Agriculture and Mechanic Arts, Ames, IA.
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, I A.
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.
ILENR (1993) Illinois Inventory of Greenhouse Gas
Emissions andSinks: 1990. Office of Research and Planning,
Illinois Department of Energy and Natural Resources,
Springfield, IE.
Iowa State College Staff Members (1946) A Century of
Farming in Iowa 1846-1946. The Iowa State College Press,
Ames, I A.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
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.
Kuchler, AW. (1964) "The Potential Natural Vegetation of
the Conterminous United States." Amer. Geographical Soc.
NY, Special Publication No. 36.
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.
McFarland, M.J. (2001) Biosolids Engineering, McGraw-
Hill, p. 2.12. New York.
Mosier, A.R. (2004) E-mail correspondence. Arvin Mosier,
U.S. Department of Agriculture, Agricultural Research
Service and Stephen Del Grosso, 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 AgChl(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 AgCh 1(92). National Agricultural
Statistics Service, U.S. Department of Agriculture. Available
online at .
NEBRA (2007) A National Biosolids Regulation, Quality,
End Use & Disposal Survey. North East Biosolids and
Residuals Association, July 21, 2007
NEA (1946) "Charting the Fertilizer Course: Results of NEA's
Third Practice Survey." National Fertilizer Association. The
Fertilizer Review. Vol. XXI, 2:7-13.
Noller, J. (1996) Personal Communication. John Noller,
Missouri Department of Natural Resources and Heike
Mainhardt, ICF Incorporated. July 30, 1996.
NRAES (1992) On-Farm Composting Handbook
(NRAES-54). Natural Resource, Agriculture, and Engineering
Service. Available online at .
NRIAI (2003) Regional Budget and Cost Information. U.S.
Department of Agriculture, Natural Resources Conservation
Service, Natural Resources Inventory and Analysis Institute.
Available online at
References 11-31
-------
Ogle, S. (2002) E-mail correspondence. Stephen Ogle,
Natural Resources Ecology Laboratory, Colorado State
University and Barbara Braatz, ICE International, concerning
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., F.J. Breidt, M. Easter, S. Williams, and K.
Paustian. (2007) "Empirically-Based Uncertainty Associated
with Modeling Carbon Sequestration in Soils." Ecological
Modeling 205:453^63.
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.
Parton, W.J., M.D. Hartman, D.S. Ojima, andD.S. Schimel
(1998) "DAYCENT: Its Land Surface Submodel: Description
and Testing." Glob. Planet. Chang. 19:35^8.
Parton, W.J., E.A. Holland, S.J. Del Grosso, M.D. Hartman,
R.E. Martin, A.R. Mosier, D.S. Ojima, and D.S. Schimel
(2001) Generalized model for NOX and N2O emissions from
soils. Journal of Geophysical Research. 106 (D15): 17403-
17420.
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, E.G. Parker, E.W. Sheets, and A.T. Semple
(1924) "Hay." Yearbook of the Department of Agriculture,
285-376.
Ruddy B.C., D.L. Lorenz, and O.K. Mueller (2006) County-
level estimates of nutrient inputs to the land surface of
the conterminous United States, 1982-2001. Scientific
Investigations Report 2006-5012. US Department of the
Interior.
Ross W.H. and A.L. Mehring (1938) "Mixed Fertilizers." In
So Us 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, G.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.
Saxton, K.E., W.J. Rawls, J.S. Romberger, and R.I. Papendick
(1986) "Estimating Generalized Soil-Water Characteristics
From Texture." Soil Sci. Soc. Am. J. 50:1031-1036.
Skinner, J.J. (1931) Fertilizers for 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 .
Spillman W.J. (1908) Types of Farming in the United States.
Yearbook of the Department of Agriculture, 351-366.
Spillman W.J. (1907) Cropping Systems for Stock Farms.
Yearbook of the Department of Agriculture, 385-398.
Spillman W.J. (1905) Diversified Farming in the Cotton Belt.
Yearbook of the Department of Agriculture, 193-218.
Spillman W.J. (1902) Systems of Farm Management in the
United States. Yearbook of the Department of Agriculture,
343_364.
Taylor, H.H. (1994) Fertilizer Use and Price Statistics:
1960-93. Resources and Technology Division, Economic
Research Service, U.S. Department of Agriculture, Statistical
Bulletin Number 893.
Thornton, P.E., H. Hasenauer, and M.A. White (2000)
"Simultaneous Estimation of Daily Solar Radiation and
Humidity from Observed Temperature and Precipitation: An
Application Over Complex Terrain in Austria." Agricultural
and Forest Meteorology 104:255-271.
Thornton, PE. and S.W. Running (1999) "An Improved
Algorithm for Estimating Incident Daily Solar Radiation from
Measurements of Temperature, Humidity, and Precipitation."
Agriculture and Forest Meteorology. 93: 211-228.
Thornton, P.E., S.W. Running, and M.A. White (1997)
"Generating Surfaces of Daily Meteorology Variables Over
Large Regions of Complex Terrain." Journal of Hydrology.
190:214-251.
TVA(1991 through 1992a, 1993 through 1994) Commercial
Fertilizers. Tennessee Valley Authority, Muscle Shoals,
AL.
TVA (1992b) Fertilizer Summary Data 1992. Tennessee
Valley Authority, Muscle Shoals, AL.
USDA (2008a) Crop Production 2007 Summary, National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at ,
11 -32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
USDA (2008b) Quick Stats: U.S. & All States Data - Crops.
National Agricultural Statistics Service, U.S. Department
of Agriculture. Washington, DC. U.S. Department of
Agriculture, National Agricultural Statistics Service,
Washington, DC, Available online at
USDA (2006) Crop Production 2005 Summary. National
Agricultural Statistics Service, 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, 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) 7997 National Resources Inventory.
National Agricultural Statistics Service, U.S. Department
of Agriculture, Washington, DC. Available online at .
USDA (2000b) Agricultural Statistics 2000. National
Agricultural Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at .
USDA (1998) 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 (1996) Agricultural Waste Management Field
Handbook, National Engineering Handbook (NEH),
Part 651. Natural Resources Conservation Service, U.S.
Department of Agriculture. July 1996.
USDA (1994) 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 (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, 9:407-437.
Vogelman, 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, 67:650-662.
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) Data compiled for the Consortium
for Agricultural Soils Mitigation of Greenhouse Gases
(CASMGS) from an unpublished manuscript. Natural
Resource Ecology Laboratory, Colorado State University.
Wisconsin Department of Natural Resources (1993)
Wisconsin Greenhouse Gas Emissions: Estimates for 1990.
Bureau of Air Management, Wisconsin Department of
Natural Resources, Madison, WI.
Field Burning of Agricultural Residues
Anderson, M. (2008) Email correspondence. Monte
Anderson, Oklahoma Farm Service Agency and Sarah
Menassian, ICF International. August 5, 2008.
Anonymous (2006) Personal communication with Lauren
Flinn, ICF International. August 11, 2006.
Barnard, G., and L. Kristoferson (1985) Agricultural
Residues as Fuel in the Third World. Ear thscan Energy
Information Programme and the Beijer Institute of the Royal
Swedish Academy of Sciences. London, England.
Bollich, P. (2000) Personal Communication. Pat Bollich,
Professor with Louisiana State University Agriculture Center
and Payton Decks, ICF International. 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.
References 11-33
-------
Cantens, G. (2005) Personal Communication. Janet Lewis,
Assistant to Gaston Cantens, Vice President of Corporate
Relations, Florida Crystals Company and Lauren Flinn, ICF
International. July 2005.
Cantens, G. (2004) Personal Communication. Janet Lewis,
Assistant to Gaston Cantens, Vice President of Corporate
Relations, Florida Crystals Company and Lauren Flinn, ICF
International. July 30, 2004.
Cibrowski, P. (1996) Personal Communication. Peter
Cibrowski, Minnesota Pollution Control Agency and Heike
Mainhardt, ICF Incorporated. July 29, 1996.
Deren, C. (2002) Personal communication. Dr. Chris Deren,
Everglades Research and Education Centre at the University
of Florida and Caren Mintz, ICF International. August 15,
2002.
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) Personal Communication. Les Fife, President
and General Manager, Fife Environmental and Catherine
Leining, ICF International. June 9, 1999.
Gonzalez, R. (2008) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Sarah
Menassian, ICF International. July 12, 2008.
Gonzalez, R. (2007a) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Sarah
Menassian, ICF International. August 29, 2007.
Gonzalez, R. (2007b) Email correspondence. Rene Gonzalez,
Plant Manager, Sem-Chi Rice Company and Victoria
Thompson, ICF International. August 2007.
Guethle, D. (2008) Email correspondence. David Guethle,
Agronomy Specialist, Missouri Cooperative Extension
Service and Sarah Menassian, ICF International. June 30,
2008.
Guethle, D. (2007) Email correspondence David Guethle,
Agronomy Specialist, Missouri Cooperative Extension
Service and Victoria Thompson, ICF International. July 30,
2007.
ILENR (1993) Illinois Inventory of Greenhouse Gas
Emissions andSinks: 1990. Office of Research and Planning,
Illinois Department of Energy and Natural Resources,
Springfield, IL.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and
K. Tanabe (eds.). 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.
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) Personal Communication. Jen Ketzis,
Cornell University and Marco Alcaraz, ICF International.
June/July 1999.
Kirstein, A. (2004) Personal Communication. Arthur Kirstein,
Coordinator, Agricultural Economic Development Program,
Palm Beach County Cooperative Extension Service, Florida
and Lauren Hinn, ICF International. June 30, 2004.
Kirstein, A. (2003) Personal communication. Arthur Kirstein,
Coordinator, Agricultural Economic Development Program,
Palm Beach County Cooperative Extension Service, Florida
and Caren Mintz, ICF International. August 13, 2003.
Klosterboer, A. (2003) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. July 7,
2003.
Klosterboer, A. (2002) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. August 19,
2002.
Klosterboer, A. (2001) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. August 6,
2001.
Klosterboer, A. (2000) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Payton Decks, ICF International. May 18,
2000.
Klosterboer, A. (1999a) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Catherin Leining, ICF International. June
10, 1999.
11 -34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Klosterboer, A. (1999b) Personal Communication. Arlen
Klosterboer, retired Extension Agronomist, Texas A&M
University and Payton Decks, ICF International. August
12, 1999.
Lancero, J. (2008) Email correspondence. Jeff Lancero,
California Air Resources Board and Sarah Menassian, ICF
International. July 24, 2008.
Lancero, J. (2007) Email correspondence. Jeff Lancero,
California Air Resources Board and Victoria Thompson,
ICF International. July 24, 2007.
Lancero, J. (2006) Email correspondence. Jeff Lancero,
California Air Resources Board and Lauren Flinn, ICF
International. August 11, 2006.
Lee, D. (2007) Email correspondence. Danny Lee, OK Farm
Service Agency and Victoria Thompson, ICF International.
July 30, 2007.
Lee, D. (2006) Email correspondence. Danny Lee, OK Farm
Service Agency and Lauren Flinn, ICF International. July
13, 2006.
Lee, D. (2005) Email correspondence. Danny Lee, OK Farm
Service Agency and Lauren Flinn, ICF International July
and September 2005.
Lee, D. (2004) Email correspondence. Danny Lee, OK Farm
Service Agency and Lauren Flinn, ICF International. July
23, 2006.
Lee, D. (2003) Personal Communication. Danny Lee, OK
Farm Service Agency and Caren Mintz, ICF International.
July 2, 2003.
Lindberg, J. (2005) Email correspondence. Jeff Lindberg,
California Air Resources Board and Lauren Flinn, ICF
International. July 2005.
Lindberg, J. (2004) Email correspondence. Jeff Lindberg,
California Air Resources Board and Lauren Flinn, ICF
International. June-July 2004.
Lindberg, J. (2003) Email correspondence. Jeff Lindberg,
California Air Resources Board and Caren Mintz, ICF
International. June-July 2003.
Lindberg, J. (2002) Personal Communication. Jeff Lindberg,
California Air Resources Board and Caren Mintz, ICF
International September 12-13, 2002.
Linscombe, S. (2008) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Sarah
Menassian, ICF International. June 30, 2008.
Linscombe, S. (2007) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Victoria
Thompson, ICF International. July 24, 2007.
Linscombe, S. (2006) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Flinn, ICF International. August 15, 2006.
Linscombe, S. (2005) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Flinn, ICF International. July 2005.
Linscombe, S. (2004) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Lauren
Flinn, ICF International. June 23, 2004.
Linscombe, S. (2003) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Caren
Mintz, ICF International. June 10, 2003.
Linscombe, S. (2002) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Caren
Mintz, ICF International. August 21, 2002.
Linscombe, S. (2001) Email correspondence. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Caren
Mintz, ICF International. July 30-August 1, 2001.
Linscombe, S. (1999a) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Catherine
Leining, ICF International. June 3, 1999.
Linscombe, S. (1999b) Personal Communication. Steve
Linscombe, Professor with the Rice Research Station at
Louisiana State University Agriculture Center and Payton
Decks, ICF International. August 9, 1999.
Najita, T. (2001) Personal Communication. Theresa Najita,
Air Pollution Specialist, California Air Resources Board and
Caren Mintz, ICF International. July 31, 2001.
Najita, T. (2000) Personal Communication. Theresa Najita,
Air Pollution Specialist, California Air Resources Board and
Payton Decks, ICF International. August 17, 2000.
Noller, J. (1996) Personal Communication. John Noller,
Missouri Department of Natural Resources and Heike
Mainhardt, ICF Incorporated. 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
(2007) Report on the Conditional Rice Straw Burning Permit
Program. June 1, 2007. Available online at: .
Sacramento Valley Basinwide Air Pollution Control Council
(2005) Report on the Conditional Rice Straw Burning Permit
Program. May 25, 2005. Available online at .
References 11-35
-------
Schueneman, T. (2001) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Caren Mintz, ICF International. July 30,
2001.
Schueneman, T. (1999a) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Catherine Leining, ICF International. June
7, 1999.
Schueneman, T. (1999b) Personal Communication. Tom
Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Payton Decks, ICF International. 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. Dr. Jim Stansel,
Resident Director and Professor Emeritus, Texas A&M
University Agricultural Research and Extension Center and
Lauren Flinn, ICF International. July 2005.
Stansel, J. (2004) Personal Communication. Dr. Jim Stansel,
Resident Director and Professor Emeritus, Texas A&M
University Agricultural Research and Extension Center and
Lauren Flinn, ICF International. July 12, 2004.
Street, J. (2003) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. June 19, 2003.
Street, J. (2002) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. August 19,
2002.
Street, J. (2001) Personal Communication. Joe Street, Rice
Specialist, Mississippi State University, Delta Research
Center and Caren Mintz, ICF International. August 1,
2001.
Strehler, A., and W. Stutzle (1987) "Biomass Residues." In
Hall, D.O. and Overend, R.P (eds.) Biomass. John Wiley
and Sons, Ltd., Chichester, UK.
Texas Agricultural Experiment Station (2008) 2007— Texas
Rice Acreage by Variety. Agricultural Research and Extension
Center, Texas Agricultural Experiment Station, Texas A&M
University System. Available online at .
Texas Agricultural Experiment Station (2007) 2006— Texas
Rice Acreage by Variety. Agricultural Research and Extension
Center, Texas Agricultural Experiment Station, Texas A&M
University System. Available online at .
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.
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 (2008) Crop Production 2007 Summary. National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at .
USDA (2007) Crop Production 2006 Summary. National
Agricultural Statistics Service, Agricultural Statistics Board,
U.S. Department of Agriculture, Washington, DC. Available
online at .
USDA (2006) Crop Production 2005 Summary. National
Agricultural Statistics Service, U.S. Department of
Agriculture. Available online at . Accessed July 2006.
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 .
USDA (1994) Field Crops, Final Estimates 1987-1992.
Statistical Bulletin No. 896. National Agricultural Statistics
Service, Agricultural Statistics Board, U.S. Department of
Agriculture, Washington, DC. Available online at.
Walker, T. (2008) Email correspondence. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Sarah Menassian, ICF
International. July 25, 2008.
11 -36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Walker, T. (2007) Personal Communication. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Victoria Thompson, ICF
International. August 15, 2007.
Walker, T. (2006) Personal Communication. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Lauren Fh'nn, ICF International.
August 17, 2006.
Walker, T. (2005) Email correspondence. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Lauren Flinn, ICF International.
July 2005.
Walker, T. (2004) Personal Communication. Tim Walker,
Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Lauren Flinn, ICF International.
July 12, 2004.
Wilson, C. (2007) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Victoria Thompson, ICF
International. August 22, 2007.
Wilson, C. (2006) Email correspondence. Dr. Chuck Wilson,
Rice Specialist at the University of Arkansas Cooperative
Extension Service and Lauren Flinn, ICF International.
August 8, 2006.
Wilson, C. (2005) Email correspondence. Dr. Chuck Wilson,
Rice Specialist at the University of Arkansas Cooperative
Extension Service and Lauren Flinn, ICF International. July
2005.
Wilson, C. (2004) Personal Communication. Dr. Chuck
Wilson, Rice Specialist at the University of Arkansas
Cooperative Extension Service and Lauren Flinn, ICF
International. June 23, 2004.
Wilson, C. (2003) Personal Communication. Dr. Chuck
Wilson, Rice Specialist, University of Arkansas Cooperative
Extension Service and Caren Mintz, ICF International. June
11,2003.
Wisconsin Department of Natural Resources (1993)
Wisconsin Greenhouse Gas Emissions: Estimates for 1990.
ureau 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 .
Representation of the U.S. Land Base
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Nusser, S.M. and J.J. Goebel (1997) "The national
resources inventory: a long-term multi-resource monitoring
programme." Environmental and Ecological Statistics
4:181-204.
Forest Land Remaining Forest Land:
Changes in Forest Carbon Stocks
Barlaz, M.A. (1998) "Carbon storage during biodegradation
of municipal solid waste components in laboratory-scale
landfills." Global Biogeochemical Cycles 12 (2):373-380.
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 (2006) 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 .
Freed, R. (2004) Open-dump and Landfill timeline spreadsheet
(unpublished). ICF International, Washington, DC.
Melosi, M. (1981) Garbage in The Cities: Refuse Reform and
the Environment: 1880-1980. Texas A&M Press.
Melosi, M. (2000) The Sanitary City. Johns Hopkins
University Press, Baltimore, MD.
Micales, J.A. and K.E. Skog (1997) "The decomposition of
forest products in landfills." International Biodeterioration
& Biodegradation. 39(2-3): 145-158.
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. American Forest & Paper Association,
Washington, DC.
AF&PA. 2001. U.S. Forests Facts and Figures. American
Forest & Paper Association, Washington, DC.
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.
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.
References 11-37
-------
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 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.
EPA (2006) Inventory of U. S. Greenhouse Gas Emissions
and Sinks: 1990-2004. EPA, Office of Atmospheric
Programs, Washington, DC.
Prayer, W.E., and G.M. Furnival (1999) "Forest Survey
Sampling Designs: A History." Journal of Forestry
97(12):4-10.
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.
Hair, D. (1958) "Historical forestry statistics of the United
States." Statistical Bull. 228. U.S. Department of Agriculture
Forest Service, Washington, DC.
Heath, L. (2007) Email communication between Kim
Klunich, EPA, and Linda Heath, U.S. Forest Service.
November 9, 2007.
Heath, L.S. (2006a) Email correspondence. Linda Heath,
U.S. Department of Agriculture Forest Service and Kimberly
Klunich, 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) Email correspondence. Linda Heath,
U.S. Department of Agriculture Forest Service and Kimberly
Klunich, U.S. Environmental Protection Agency regarding
the 95 percent CI for average carbon density for Alaska (+/-
1.2%). October 27, 2006.
Heath, L.S., I.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.
Heath, L. S., and I.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.
Howard, James L. (2003) U.S. timber production, trade,
consumption, and price statistics 1965 to 2002. Res. Pap.
FPL-RP-615. USDA, Forest Service, Forest Products
Laboratory, Madison, WI. Available online at .
Howard, James L. (2007) U.S. timber production, trade,
consumption, and price statistics 1965 to 2005. Res. Pap.
FPL-RP-637. USDA, Forest Service, Forest Products
Laboratory, Madison, WI.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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.
National Interagency Fire Center (2008) "Fire Information—
Wildland Fire Statistics. Total Wildland Fires and Acres
(1960-2006)." Available online at March 2008.
National Association of State Foresters (2007a) State Forestry
Statistics 1998 Report. Available online at March 2008.
National Association of State Foresters (2007b) State
Forestry Statistics 2002 Report. Available online at March 2008.
11 -38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
National Association of State Foresters (2007c) State
Forestry Statistics 2004 Report. Available online at
March 2008.
Perry, C.H., C.W. Woodall, and M. Schoeneberger (2005)
Inventorying trees in agricultural landscapes: towards an
accounting of "working trees". In: "Moving Agroforestry
into the Mainstream." Proc. 9th N. Am. Agroforestry Cow/.,
Brooks, K.N. and Ffolliott, P.P. (eds). 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).
Phillips, D.L., S.L. Brown, PE. Schroeder, andR.A. Birdsey
(2000) "Toward Error Analysis of Large-Scale Forest Carbon
Budgets." Global Ecology and Biogeography 9:305-313.
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 I.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. (2008) "Sequestration of carbon in harvested
wood products for the United States." Forest Products
Journal 58:56-72.
Smith, I.E., and L.S. Heath (2002) "A model of forest floor
carbon mass for United States forest types." Res. Paper NE-
722. USDA 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, Newtown Square, PA.
Smith, J. E., L. S. Heath, and P. B. Woodbury (2004a) "How
to estimate forest carbon for large areas from inventory data."
Journal of Forestry 102:25-31.
Smith, W. B., P. D. Miles, J. S. Vissage, and S. 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.
Smith, W. B., P. D. Miles, J. S. Vissage, and S. A. Pugh (In
press) Forest Resources of the United States, 2007. General
Technical Report, U.S. Department of Agriculture Forest
Service.
Smith, I.E., L.S. Heath, andM.C. Nichols (2007). U.S. Forest
Carbon Calculation Tool User's Guide: Forestland Carbon
Stocks and Net Annual Stock Change. General Technical
Report NRS-13, U.S. Department of Agriculture Forest
Service, Northern Research Station.
Smith, I.E., L.S. Heath, and M.C. Nichols (In preparation).
U.S. Forest Carbon Calculator and User's Guide, for use
with FIADB 3.0
Steer, Henry B. (1948) Lumber production in the United
States. Misc. Pub. 669, U.S. Department of Agriculture
Forest Service, Washington, DC.
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.
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.
USDC Bureau of Census (1976) Historical Statistics
of the United States, Colonial Times to 1970, Vol. 1.
Washington, DC.
USDAForest Service (1992) "1984-1990 Wildfire Statistics."
Prepared by State and Private Forestry Fire and Aviation
Management Staff. Facsimile from Helene Cleveland, USDA
Forest Service, to ICF International. January 30, 2008.
USDAForest Service (2008a) Forest Inventory andAnalysis
National Program: User Information. U.S. Department of
Agriculture Forest Service, Washington, DC. Available
online at .
Accessed 15 October 2008.
USDA Forest Service. (2008b) FIA Data Mart. U.S.
Department of Agriculture Forest Service, Washington, DC.
Available online at . Accessed 15 October 2008.
USDAForest Service. (2008c) Forest Inventory andAnalysis
National Program, FIA library: Field Guides, Methods and
Procedures. U.S. Department of Agriculture Forest Service.
Washington, DC. Available online at . Accessed October
15, 2008.
USDAForest Service (2008d) Forest Inventory and Analysis
National Program, FIA library: Database Documentation.
U. S. Department of Agriculture, Forest Service, Washington
Office. Available online at .
Accessed 15 October 2008.
USDA (1991) State Soil Geographic (STATSGO) Data Base
Data use information. Miscellaneous Publication Number
1492, National Soil Survey Center, Natural Resources
Conservation Service, U.S. Department of Agriculture, Fort
Worth, TX.
Woodbury, P.B., Heath, L.S., and Smith, I.E. (2006) "Land
Use Change Effects on Forest Carbon Cycling Throughout
the Southern United States." Journal of Environmental
Quality, 35:1348-1363.
References 11-39
-------
Woodbury, P.B., L.S. Heath, and I.E. Smith (2007) Effects of
land use change on soil carbon cycling in the conterminous
United States from 1900 to 2050, Global Biogeochem.
Cycles, 21, GB3006, doi:10.1029/2007GB002950.
Forest Land Remaining Forest Land:
Non-C02 Emissions from Forest Fires
Alaska Department of Natural Resources (2008). Divison of
Forestry. "Fire Statistics." Available online at . October 2008.
Heath, L. (2008) Phone communication between Kim
Klunich, EPA, and Linda Heath, U.S. Forest Service.
November 24, 2008.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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 .
National Interagency Fire Center (2008) "Fire Information—
Wildland Fire Statistics. Total Wildland Fires and Acres
(1960-2006)." Available online at October 2008.
National Association of State Foresters (1998) State Forestry
Statistics 1998 Report. Available online at October
2008.
National Association of State Foresters (2002) State Forestry
Statistics 2002 Report. Available online at October 2008.
National Association of State Foresters (2004) State Forestry
Statistics 2004 Report. Available online at October
2008.
National Association of State Foresters (2008) State Forestry
Statistics 2006 Report. Available online at February 2009.
Smith, J. (2008a) Email correspondence. Jim Smith, U.S.
Forest Service and Jean Kim, ICF International. December
3, 2008.
Smith, J. (2008b) Email correspondence. Jim Smith, U.S.
Forest Service and Jean Kim, ICF International. December
8, 2008.
Smith, J. (2008c) Email correspondence. Jim Smith, U.S.
Forest Service and Jean Kim, ICF International. December
16, 2008.
Smith, J. (2009) Email correspondence. Jim Smith, U.S.
Forest Service and Jean Kim, ICF International. January
30, 2009.
USDAForest Service (2008a) Forest Inventory andAnalysis
National Program: User Information. U.S. Department of
Agriculture Forest Service, Washington, DC. Available
online at .
Accessed 15 October 2008.
USDA Forest Service. (2008b) FIA Data Mart. U.S.
Department of Agriculture Forest Service, Washington, DC.
Available online at . Accessed 15 October 2008.
USDAForest Service. (2008c) Forest Inventory andAnalysis
National Program, FIA library: Field Guides, Methods and
Procedures. U.S. Department of Agriculture Forest Service,
Washington, DC. Available online at . Accessed October
15, 2008.
USDAForest Service (2008d) Forest Inventory and Analysis
National Program, FIA library: Database Documentation.
U. S. Department of Agriculture, Forest Service, Washington
Office. Available online at .
Accessed 15 October 2008.
USDAForest Service (1992) "1984-1990 Wildfire Statistics."
Prepared by State and Private Forestry Fire and Aviation
Management Staff. Facsimile from Helene Cleveland, USDA
Forest Service, to ICF International. January 30, 2008.
Forest Land Remaining Forest Land: N20
Fluxes from Soils
Albaugh, T.J., Allen, H.L., Fox, T.R. (2007) "Historical
Patterns of Forest Fertilization in the Southeastern United
States from 1969 to 2004." Southern Journal of Applied
Forestry, 31, 129-137(9).
Binkley, D. (2004) Email correspondence regarding the 95%
CI for area estimates of southern pine plantations receiving
N fertilizer (+20%) and the rate applied for areas receiving N
fertilizer (100 to 200 pounds/acre). Dan Binkley, Department
of Forest, Rangeland, and Watershed Stewardship, Colorado
State University and Stephen Del Grosso, Natural Resource
Ecology Laboratory, Colorado State University. September
19, 2004.
Binkley, D., R. Carter, and H.L. Allen (1995) "Nitrogen
Fertilization Practices in Forestry." Nitrogen Fertilization
in the Environment, PE. Bacon (ed.), Marcel Decker, Inc.,
New York.
11 -40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
USDA Forest Service (2001) U.S. Forest Facts and
Historical Trends. FS-696. U.S. Department of Agriculture
Forest Service, Washington, DC. Available online at .
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. Schomberg, C.L. Douglas, Jr., andT.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. and J.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.
Brady,NC. 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.
Easter, M. , S. Williams, and S. Ogle. (2008) Gap-filling
NRI data for the Soil C Inventory. Natural Resource Ecology
Laboratory, Colorado State University, Fort Collins, CO.
Report provided to the US Environmental Protection Agency,
Tom Wirth.
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
regarding wetland restoration factor estimates and restoration
activity data. 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.
August 2002.
FAO (2008) Yearly U.S. Total Horse Population Data from
the Food and Agriculture Organization of the United Nations
database. Available online at .
Accessed July 2008.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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.
Kellogg, R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon
(2000) Manure Nutrients Relative to the Capacity of
Cropland and Pastureland to Assimilate Nutrients:
Spatial and Temporal Trends for the United States. U.S.
Department of Agriculture, Washington, DC. Publication
number npsOO-0579.
Lange, J. (2000) Personal Communication Lee-Ann Tracy,
ERG and John Lange, Agricultural Statistician, U. S.
Department of Agriculture, National Agriculture Statistics
Service, Washington, DC. May 8, 2000.
Metherell, A.K., L.A. Harding, C.V. Cole, and W.J.
Parton (1993) "CENTURY Soil Organic Matter Model
Environment." Agroecosystem version 4.0. Technical
documentation, GPSR Tech. Report No. 4, USDA/ARS, Ft.
Collins, CO.
References 11-41
-------
NASS (2004) Agricultural Chemical Usage: 2003 Field
Crops Summary. Report AgChl(04)a. National Agricultural
Statistics Service, U.S. Department of Agriculture,
Washington, DC. 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 AgCh 1(92). National Agricultural
Statistics Service, U.S. Department of Agriculture,
Washington, DC. Available online at .
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 205:453^63.
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, andK. 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, NREL to Barbara
Braatz, ICF International. September 23, 2002
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." Bio geochemistry
5:109-131.
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.
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." Global Biogeochemical
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.
Towery, D. (2001) Personal Communication. Dan Towery
regarding adjustments to the CTIC (1998) tillage data
to reflect long-term trends, Conservation Technology
Information Center, West Lafayette, IN, and Marlen Eve,
National Resource Ecology Laboratory, Fort Collins, CO.
February 2001.
USDA-FS A (2007) Conservation Reserve Program Summary
and Enrollment Statistics FY 2006. U.S. Department of
Agriculture, Farm Service Agency, Washington, DC,
Available online at .
USDA (2008a) Published Estimates Database. National
Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. Available online at . June 2008.
USDA (2008b) Chicken and Eggs 2007 Summary.
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. February 2008. Available
online at .
USDA (2008c) Poultry - Production and Value 2007
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2008.
Available online at .
USDA (2006a) Chicken and Eggs 2005 Summary.
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. February 2006. Available
online at .
USDA (2006b) Poultry - Production and Value 2005
Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2006.
Available online at .
11 -42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
USDA (2005a) Chicken and Eggs Annual Summary.
National Agriculture Statistics Service, U.S. Department
of Agriculture, Washington, DC. February 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) Census of Agriculture. National Agriculture
Statistics Service, U.S. Department of Agriculture, Washington,
DC. Datafor 1992,1997,and2002. Available online at in June 2005.
USDA (2004a) Chicken and Eggs-Final Estimates
1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. April 2004.
Available online at .
USDA (2004b) 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 (1999) 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 (1998) Chicken and Eggs-Final Estimates 1994-97.
National Agriculture Statistics Service, U.S. Department of
Agriculture, Washington, DC. December 1998.
USDA (1995a) Chicken and Eggs—Final Estimates
1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture, Washington, DC. Available
online at . January 1995.
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-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.
Peatlands Remaining Peatlands: C02 and
N20 Emissions from Lands Undergoing
Peat Extraction
Apodaca, L. (2008) Email correspondence. Lori Apodaca,
Peat Commodity Specialist, USGS and Emily Rowan, ICE
International. October and November.
Cleary, J., N. Roulet and T.R. Moore (2005) "Greenhouse
gas emissions from Canadian peat extraction, 1990-2000: A
life-cycle analysis." Ambio 34:456^161.
Szumigala, D.J. and R.A. Hughes (1990-2007) Alaska's
Mineral Industry Reports. Alaska Department of Natural
Resources. Available online at .
United States Geological Survey (USGS) (1990-2008)
Annual Mineral Industry Surveys: Peat. Available online at
.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and
K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Liming and Urea
AAPFCO (1995 through 2000, 2002 through 2008)
Commercial Fertilizers. Association of American Plant Food
Control Officials. University of Kentucky, Lexington, KY.
AAPFCO (2000) 1999-2000 Commercial Fertilizers
Data, ASCII files. Available from David Terry, Secretary,
AAPFCO.
IPCC (2006) 2006 IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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.
Me, Cortney (2009). Email correspondence. Cortney
Itle, ERG and Tom Wirth, U.S. Environmental Protection
Agency on the amount of urea used in aircraft deicing.
January 7, 2009.
References 11-43
-------
Tepordei, V.V. (1997 through 2006) "Crashed Stone," In
Minerals Yearbook. U.S. Department of the Interior/U.S.
Geological Survey, Washington, DC. Available online
at .
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.
Terry, D. (2007) Email correspondence. David Terry,
Fertilizer Regulatory program, University of Kentucky and
David Berv, ICF International. September 7, 2007.
TVA(1991 through 1994) Commercial Fertilizers. Tennessee
Valley Authority, Muscle Shoals, AL.
U.S. EPA. (2000) Preliminary Data Summary: Airport
Deicing Operations (Revised). EPA-821-R-00-016. August
2000.
USGS (2008) Mineral Industry Surveys: Crushed Stone
and Sand and Gravel in the First Quarter of 2008, U.S.
Geological Survey, Reston, VA. Available online at .
USGS (2007) Mineral Industry Surveys: Crushed Stone
and Sand and Gravel in the First Quarter of 2007. 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.
West, Tristram O. (2008). Email correspondence. Tristram
West, Environmental Sciences Division, Oak Ridge National
Laboratory, U.S. Department of Energy and Nikhil Nadkarni,
ICF International on suitability of liming emission factor for
the entire United States. June 9, 2008.
Willett, J.C. (2007a) "Crashed Stone," In Minerals Yearbook
2005. U.S. Department of the Interior/U.S. Geological
Survey, Washington, DC. Available online at . Accessed August 2007.
Willett, J.C. (2007b) "Crashed Stone," In Minerals Yearbook
2006. U.S. Department of the Interior/U.S. Geological
Survey, Washington, DC. Available online at . Accessed August 2008.
Settlements Remaining Settlements:
Changes in Carbon Stocks in Urban Trees
Cairns, M.A., S. Brown, E.H. Helmer, andG.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. M.S. thesis,
Rutgers University, New Brunswick, NJ.
Dwyer, J.F, D.J. Nowak, M.H. Noble, and S.M Sisinni
(2000) Connecting People with Ecosystems in the 21st
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 (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Nowak, D.J. (2007a) "New York City's Urban Forest."
Newtown Square, PA: USDA Forest Service, Feb 2007.
Nowak, D.J. (2007b) Personal Communication. David
Nowak, USDA Forest Service and Susan Asam, ICF
International. September 25, 2007.
Nowak, D.J. (2007c) E-mail correspondence regarding
revised sequestration values and standard errors for
sequestration values. David Nowak, USDA Forest Service
to Susan Asam, ICF International. October 31, 2007.
Nowak, D.J. (2002a) E-mail correspondence containing
information on possible urban tree carbon and forest carbon
overlap. David Nowak, USDA Forest Service to Barbara
Braatz, ICF International. January 10, 2002.
Nowak, D.J. (2002b) E-mail correspondence regarding
significant digits. David Nowak, USDA Forest Service to
Barbara Braatz, ICF International. 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.
11 -44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
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's 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.
Smith, W.B. and S.R. Shirley (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:
N20 Fluxes from Soils
Albaugh, T.J., Allen, H.L., Fox, T.R. (2007) "Historical
Patterns of Forest Fertilization in the Southeastern United
States from 1969 to 2004." Southern Journal of Applied
Forestry, 31, 129-137(9)
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and
K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Ruddy B.C., D.L. Lorenz, and O.K. Mueller (2006)
County-level estimates of nutrient inputs to the land
surface of the conterminous United States, 1982-
2001. Scientific Investigations Report 2006-5012. US
Department of the Interior.
Other: Changes in Yard Trimming and
Food Scrap Carbon Stocks in Landfills
Barlaz, M.A. (2008) "Re: Corrections to Previously
Published Carbon Storage Factors." Memorandum to Randall
Freed, ICF International. February 28, 2008.
Barlaz, M.A. (2005) "Decomposition of Leaves in Simulated
Landfill." Letter report to Randall Freed, ICF Consulting.
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 (2006 through 2008) Municipal Solid Waste in the
United States: Facts and Figures. U.S. Environmental
Protection Agency, Office of Solid Waste and Emergency
Response, Washington, DC. Available online at .
EPA (2005) Municipal Solid Waste Generation, Recycling,
and Disposal in the United States: Facts and Figures for
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, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). 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 .
Oshins, C, andD. Block (2000) "Feedstock Composition at
Composting Sites." Biocycle 41(9):31-34.
Schneider, S. (2007, 2008) Email correspondence. Shelly
Schneider, Franklin Associates, ADivision of ERG and Sarah
Shapiro, ICF International.
Tchobanoglous, G., H. Theisen, and S.A. Vigil (1993)
Integrated Solid Waste Management, 1st edition. McGraw-
Hill, New York, NY. Cited by Barlaz (1998).
References 11-45
-------
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 . HH
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 .
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.
Coburn, J. (2008) "Analysis of DOC Values for Industrial
Solid Waste for the Pulp and Paper Industry and the Food
Industry." Memorandum to M. Weitz (EPA), October 13,
2008.
Czepiel, P., B. Mosher, P. Grill, and R. Harriss (1996)
"Quantifying the Effect of Oxidation on Landfill
Methane Emissions." Journal of Geophysical Research,
101(D11): 16721-16730.
El A (2007) Voluntary Greenhouse Gas Reports for EIA Form
1605B (Reporting Year 2006). Available online at.
EPA (2008) Landfill Gas-to-Energy Project Database.
Landfill Methane and Outreach Program. July 2008.
EPA (2005) Municipal Solid Waste 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 (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.
ERG (2008). Production Data Supplied by ERG for
1990-2007 for Pulp and Paper, Fruits and Vegetables, and
Meat. July.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Jensen, J.E.F, and R. Pipatti (2002) "CH4 Emissions from
Solid Waste Disposal." Background paper for the Good
Practice Guidance and Uncertainty Management in National
Greenhouse Gas Inventories.
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.
Minz C., R. Feed, and M. Walsh (2003) "Timeline of
Anaerobic Land Disposal of Solid Waste." Memorandum to
T. Wirth (EPA) and K. Skog (USDA), December 31, 2003.
Peer, R., S. Thorneloe, andD. Epperson (1993) "A Comparison
of Methods for Estimating Global Methane Emissions from
Landfills." Chemosphere, 26(1^.):387-^00.
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 (2007) International Data Base.
July 2007. Available online at .
U.S. Department of Agriculture (2003) U.S. Timber
Production, Trade, Consumption, and Price Statistics
1965-2002. Research Paper FPL-RP-615. Available online
at . December.
Weitz, K. and M. Banner (2006) "Methane Emissions for
Industrial Landfills." Memorandum to M. Weitz (EPA),
September 5, 2006.
Wastewater Treatment
ARCADIS (2004) "Response to ERG Review and New US
M&P estimates." Memorandum from M. Doom, ARCADIS
to D. Pape, ICF International and E. Scheehle, U.S.
Environmental Protection Agency. August 16, 2004.
Beecher et al. (2007) "A National Biosolids Regulation,
Quality, End Use & Disposal Survey, Preliminary Report."
Northeast Biosolids and Residuals Association, April 14,
2007.
11 -46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
Benyahia, E, M. Abdulkarim, A. Embaby, and M. Rao.
Refinery Wastewater Treatment: A true Technological
Challenge. Presented at the Seventh Annual U.A.E.
University Research Conference.
GARB (2007) Attachments C TO F - Supplemental Materials
Document for Staff Report: Initial Statement of Reasons
for Rulemaking, Mandatory Reporting of Greenhouse
Gas Emissions Pursuant to the California Global Warming
Solutions Act of 2006 (Assembly Bill 32), Attachment
E: Technical Attachment on Development of Emissions
Reporting Requirements for Oil Refineries and Hydrogen
Plants. California Environmental Protection Agency Air
Resources Board, dated October 19, 2007. Available online
at .
Donovan (1996) Siting an Ethanol Plant in the Northeast.
C.T. Donovan Associates, Inc. Report presented to Northeast
Regional Biomass Program (NRBP). (April). Available
online at . Accessed
October 2006.
EIA. (2008) Energy Information Administration. U.S.
Refinery and Blender Net Production of Crude Oil and
Petroleum Products (Thousand Barrels). Available online
at .
Accessed: August 2008.
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.
EPA (1975) Development Document for Interim Final
and Proposed Effluent Limitations Guidelines and New
Source Performance Standards for the Fruits, Vegetables,
and Specialties Segment of the Canned and Preserved
Fruits and Vegetables Point Source Category. United
States Environmental Protection Agency, Office of Water,
Washington, DC. EPA-440/1-75-046. October 1975.
EPA (1992) Clean Watersheds Needs Survey 1992-Report
to Congress. Office of Wastewater Management, U.S.
Environmental Protection Agency, Washington, DC.
EPA (1993) 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 (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
.
Accessed July 2007.
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 E & E).
EPA-821-R-97-011. Office of Water, U.S. Environmental
Protection Agency, Washington, DC. October 1997.
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 (1999) Biosolids Generation, Use and Disposal in
the United States. Office of Solid Waste and Emergency
Response, U.S. Environmental Protection Agency,
Washington, DC. EPA530-R-99-009. September 1999.
EPA (2000) Clean Watersheds Needs Survey 2000-Report
to Congress. Office of Wastewater Management, U.S.
Environmental Protection Agency, Washington, DC.
Available online at . Accessed July 2007.
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 (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.
ERG (2006) Memorandum: Assessment of Greenhouse
Gas Emissions from Wastewater Treatment of U.S. Ethanol
Production Wastewaters. Prepared for Melissa Weitz, EPA.
10 October 2006.
ESE (1975) Draft Development Document for Effluent
Limitations Guidelines and new Source Performance
Standards for the Miscellaneous Foods and Beverages Point
Source Category. Prepared by Environmental Science and
Engineering, Inc. for U.S. EPA. February 1975.
References 11-47
-------
Great Lakes-Upper Mississippi River Board of State and
Provincial Public Health and Environmental Managers.
(2004) Recommended Standards for Wastewater Facilities
(Ten-State Standards).
Holman (2006a) Personal Communication. Steven Williams,
Iowa Department of Natural Resources, Wastewater
Division, NPDES Permits and Sarah Holman, ERG. "Ethanol
Production Facilities - VeraSun Energy Corp., NPDES ID
No. IA0079227." August 31, 2006.
Holman (2006b) Personal Communication. Kelly Buscher,
South Dakota Department of Environment and Natural
Resources, Surface Water Discharge Permits and Sarah
Holman, ERG. "South Dakota Ethanol Production
Facilities—Dakota Ethanol, NPDES ID No. SD0027847."
September 1, 2006.
Holman (2006c) Personal Communication. Dr. Joe
Ruocco, Phoenix Bio-Systems and Sarah Holman, ERG.
"Bio-Methanator Units at Ethanol Production Facilities."
September 5, 2006.
Holman (2006d) Personal Communication. Peggi Badten,
City of Aberdeen, South Dakota and Sarah Holman, ERG.
"South Dakota Ethanol Production Facilities - Heartland
Grain Fuels, LP" September 6, 2006.
Holman (2006e) Personal Communication. Ron Ash,
Nebraska Department of Environmental Quality, Water
Division, NPDES Program and Sarah Holman, ERG.
"Nebraska Ethanol Production Facilities - Chief Ethanol,
NPDES ID No. NE0114243." September 7, 2006.
Holman (2006f) Personal Communication. Matt Gluckman,
U.S. EPA, Region 5, WN-16J and Sarah Holman, ERG.
"Region 5 Ethanol Production Facilities - New Energy Corp.
and MGPI." September 19, 2006.
Holman (2006g) Personal Communication. Dr. Ann Wilkie,
University of Florida, Soil and Water Science Department
and Sarah Holman, ERG. "Wastewater stillage from ethanol
production facilities." September 20, 2006.
Holman (2006h) Personal Communication. Mike Pring,
ERG and Sarah Holman, ERG. "Emissions from ethanol
production facilities." September 7, 2006.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara,
and K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Kantor, L.S., Lipton, L., Manchester, A., & Oliveira, V.
Estimating and Addressing America's Food Losses, Food
Review, January-April 1997.
Lockwood-Post (2002) Lockwood-Post's Directory of Pulp,
Paper and Allied Trades, Miller-Freeman Publications, San
Francisco, CA.
Merrick (1998) "Wastewater Treatment Options for the
Biomass-to-Ethanol Process." Report presented to National
Renewable Energy Laboratory (NREL). Merrick & Company.
Subcontract No. AXE-8-18020-01. October 22, 1998.
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.
NRBP (2001) Northeast Regional Biomass Program.
An Ethanol Production Guidebook for Northeast States.
Washington, DC (May 3). Available online at . Accessed October 2006.
Paper 360° (2007) "U.S. production rises slightly in
December." March 2007. Available online at . Accessed June 2007.
PBS (2006) General Project Experience: Anaerobic. Phoenix
Bio-Systems. Available online at . Accessed October 2006.
Pulp and Paper (2006) "AF&PA projects 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.
Renewable Fuels Association (2005) Historic U.S. Fuel
Ethanol Production. Available online at . Accessed July 2008.
Ruocco (2006a) Email correspondence. Dr. Joe Ruocco,
Phoenix Bio-Systems to Sarah Holman, ERG. "Capacity of
Bio-Methanators (Dry Milling)." October 6, 2006.
Ruocco (2006b) Email correspondence. Dr. Joe Ruocco,
Phoenix Bio-Systems to Sarah Holman, ERG. "Capacity of
Bio-Methanators (Wet Milling)." October 16, 2006.
Scheehle, E.A., and Doom, M.R. (2001) "Improvements to
the U.S. Wastewater Methane and Nitrous Oxide Emissions
Estimate. "July 2001.
Timm, C.M. (1985) Water use, conservation and wastewater
treatment alternatives for oil refineries in New Mexico.
NMERDI-2-72-4628.
U.S. Census Bureau (2008a) International Database.
Available online at and .
Accessed August 2008.
11 -48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007
-------
U.S. Census Bureau (2008b) "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 . Accessed August 2008.
USDA (2008a) National Agricultural Statistics Service.
Washington, DC. Available online at and . Accessed
July 2008.
USDA (2008b) U.S. Food Supply: Nutrients and Other
Food Components, Per Capita Per Day. USDA Economic
Research Service, Washington DC. Available online
at . Accessed August
2008.
USPoultry (2006) Email correspondence. John Starkey,
USPOULTRY to D. Bartram, ERG. 30 August 2006.
White and Johnson (2003) White, PJ. and Johnson, L.A.
Editors. Corn: Chemistry and Technology. 2nd ed. AACC
Monograph Series. American Association of Cereal
Chemists, St. Paul, MN.
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.
Composting
EPA (2008) Municipal Solid Waste in the United States: 2007
Facts and Figures. Office of Solid Waste and Emergency
Response, U.S. Environmental Protection Agency,
Washington, DC. Available online at .
EPA (2006) Municipal Solid Waste in the United States: 2005
Facts and Figures. Office of Solid Waste and Emergency
Response, U.S. Environmental Protection Agency,
Washington, DC. Available online at .
Franklin Associates (1997) Characterization of Municipal
Solid Waste in the United States: 1996 Update. Report
prepared for the U.S. Environmental Protection Agency,
Municipal and Industrial Solid Waste Division by Franklin
Associates, Ltd., Prairie Village, KS. EPA530-R-97-015.
June 1997.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse
Gas Inventories. The National Greenhouse Gas Inventories
Programme, The Intergovernmental Panel on Climate
Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and
K. Tanabe (eds.). Hayama, Kanagawa, Japan.
Waste Sources of Indirect Greenhouse
Gas Emissions
EPA (2008). "1970-2007 Average annual emissions, all
criteria pollutants in MS Excel." National Emissions
Inventory (NEI) Air Pollutant Emissions Trends Data. Office
of Air Quality Planning and Standards. Available online at
.
EPA (2003) E-mail correspondence containing preliminary
ambient air pollutant data. 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 11-49
-------
How to Obtain Copies
You can electronically download this document on the U.S. EPA's homepage at . To request free copies of this report, call the National Service Center for Environmental Publications
(NSCEP) at (800) 490-9198, or visit the web site above and click on "order online" after selecting an edition.
All data tables of this document are available for the full time series 1990 through 2007, inclusive, at the internet site
mentioned above.
For Further Information
Contact Mr. Leif Hockstad, Environmental Protection Agency, (202) 343-9432, hockstad.leif@epa.gov.
Or Ms. Melissa Weitz, Environmental Protection Agency, (202) 343-9897, weitz.melissa@epa.gov.
For more information regarding climate change and greenhouse gas emissions, see the EPA web site at .
Released for printing: April 15, 2009
Greenhouse Gases
The photos on the front and back cover of this report depict the types of greenhouse gases covered in the 1990-2007 Inventory.
This Inventory presents emissions of carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and sulfur
hexafluoride. Of these, carbon dioxide is emitted in the largest quantities in the United States, so three of the pictures below
depict sources and sinks of carbon dioxide, while sources of each of the other gases are represented in one picture each.
Carbon Dioxide: Land Use, Land-Use Change, and Forestry
Forests and soils in the United States are a net sink for carbon dioxide, offsetting about 17 percent of emissions in
2007. The sink has increased by about 26 percent since 1990. Soils can also be a source of carbon dioxide: liming
of agricultural soils and urea application to cropland both lead to a small amount of carbon dioxide emissions.
Methane
Methane is a greenhouse gas that is approximately 21 times stronger than carbon dioxide and is emitted from
numerous sources in the United States. The four largest sources of methane are enteric fermentation in domestic
animals, landfills, natural gas systems, and coal mining. Since 1990, emissions of methane have decreased 5
percent in the United States.
Perfluorocarbons (PFCs)
A family of synthetic fluorinated chemicals, PFCs are used in semiconductor manufacture and also emitted
during the electrolysis phase of aluminum production. PFCs generally have long atmospheric lifetimes as well
as very high global warming potentials, so that even though they are emitted in relatively small quantities, their
global warming impact is significant. Since 1990, PFC emissions have decreased 64 percent.
Carbon Dioxide: Industrial Processes
Some industrial processes emit carbon dioxide as part of the process itself rather than from energy inputs.
The two largest industrial emitters of carbon dioxide are iron and steel production and cement production,
each accounting for 1 percent of all carbon dioxide emissions in 2007. Industrial emissions of this gas have
decreased 11 percent since 1990.
-------
Nitrous Oxide
Nitrous oxide is approximately 310 times stronger than carbon dioxide at trapping heat, and is emitted from
a variety of sources. In the United States, the largest source of this gas is agricultural soil management,
responsible for approximately 67 percent of nitrous oxide emissions. Other significant sources include mobile
and stationary combustion, adipic acid production, waste water treatment, and manure management. Emissions
of nitrous oxide have decreased 1 percent since 1990.
Carbon Dioxide: Fossil Fuel Combustion
Carbon dioxide is the most common and important greenhouse gas, and fossil fuel combustion is the largest
source of carbon dioxide emissions in the United States, accounting for 80 percent of all emissions in 2007.
In order of decreasing size, the contributors to these emissions were electricity generation, transportation,
industry, and the residential and commercial sectors. Emissions from fossil fuel combustion have increased
22 percent since 1990.
Sulfur Hexafluoride
Sulfur hexafluoride is a very inert synthetic chemical with an extremely high global warming potential and a
long atmospheric lifetime, giving it a greenhouse gas impact larger than its relatively small emissions would
suggest. Because of its inert properties, it is used in electrical transmission and distribution as an insulator
and interrupter, as a cover gas in magnesium production and processing, and in semiconductor manufacture.
Emissions have decreased 50 percent since 1990.
Hydrofluorocarbons (MFCs)
HFCs are a class of synthetic chemicals used as alternatives to ozone depleting substances being phased out
under the Montreal Protocol. These substitution uses include refrigeration and air conditioning, semiconductor
manufacture, aerosols, and solvents. In addition, some is emitted during the production of another fluorochemical,
HCFC-22. Emissions of this gas have increased 240 percent since 1990, mostly due to the phaseout of ozone
depleting substances over that period. HFCs generally have high global warming potentials compared to the
naturally occurring greenhouse gases (carbon dioxide, methane, and nitrous oxide).
-------
United States
Environmental Protection
Agency
EPA 430-R-09-004 April 2009
Office of Atmospheric Programs (6207J)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
------- |