EPA 430-R-08-005
INVENTORY OF U.S. GREENHOUSE GAS EMISSIONS AND SINKS:
1990-2006
APRIL 15, 2008
FINAL
U.S. Environmental Protection Agency
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
U.S.A.
-------
-------
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 2006, 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, 2008
-------
-------
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 and
Resources Practice, including Don Robinson, Diana Pape, Susan Asam, Michael Grant, Ravi Kantamaneni, Robert
Lanza, Chris Steuer, Lauren Pederson, Kamala Jayaraman, Jeremy Scharfenberg, Mollie Averyt, Sarah Shapiro,
Nina Kshetry, Pankaj Kumar, Stacy Hetzel, Brian Gillis, Zachary Schaffer, Vineet Aggarwal, Colin McGroarty,
Hemant Mallya, Victoria Thompson, Jean Kim, Tristan Kessler, Sarah Menassian, Katrin Moffroid, Veronica
Kennedy, Joseph Aamidor, Aaron Beaudette, Dylan Harrison-Atlas, 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.
-------
-------
Preface
The United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas
Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention on
Climate Change (UNFCCC).1 Under decision 3/CP.5 of the UNFCCC Conference of the Parties, national
inventories for UNFCCC Annex I parties should be provided to the UNFCCC Secretariat each year by April 15.
In an effort to engage the public and researchers across the country, the EPA has instituted an annual public review
and comment process for this document. The availability of the draft document is announced via Federal Register
Notice and is posted on the EPA web site.2 Copies are also mailed upon request. The public comment period is
generally limited to 30 days; however, comments received after the closure of the public comment period are
accepted and considered for the next edition of this annual report.
1 See Article 4(1 )(a) of the United Nations Framework Convention on Climate Change .
2 See .
ill
-------
-------
Table of Contents
ACKNOWLEDGMENTS I
TABLE OF CONTENTS V
LIST OF TABLES, FIGURES, AND BOXES VIM
Tables viii
FIGURES XVI
Boxes xix
EXECUTIVE SUMMARY ES-1
Background Information ES-2
Recent Trends in U.S. Greenhouse Gas Emissions and Sinks ES-4
Overview of Sector Emissions and Trends ES-12
Other Information ES-15
1. INTRODUCTION 1-1
1.1. Background Information 1 -2
1.2. Institutional Arrangements 1-9
1.3. Inventory Process 1-9
1.4. Methodology and Data Sources 1-11
1.5. Key Categories 1-12
1.6. Quality Assurance and Quality Control (QA/QC) 1-14
1.7. Uncertainty Analysis of Emission Estimates 1-15
1.8. Completeness 1-16
1.9. Organization of Report 1-16
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 2-16
2.3. Indirect Greenhouse Gas Emissions (CO, NOx, NMVOCs, and SO2) 2-26
3. ENERGY 3-1
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source Category 1A) 3-3
3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-19
3.3. Stationary Combustion (excluding CO2) (IPCC Source Category 1A) 3-24
3.4. Mobile Combustion (excluding CO2) (IPCC Source Category 1A) 3-29
3.5. Coal Mining (IPCC Source Category IBla) 3-37
3.6. Abandoned Underground Coal Mines (IPCC Source Category IB la) 3-40
3.7. Natural Gas Systems (IPCC Source Category lB2b) 3-44
-------
3.8.
3.9.
3.10.
3.11.
3.12.
4.
4.1.
4.2.
4.3.
4.4.
4.5.
4.6.
4.7.
4.8.
4.9.
4.10.
4.11.
4.12.
4.13.
4.14.
4.15.
4.16.
4.17.
4.18.
4.19.
4.20.
4.21.
4.22.
4.23.
5.
5.1.
5.2.
6.
6.1.
6.2.
6.3.
Petroleum Systems (IPCC Source Category lB2a)
Municipal Solid Waste Combustion (IPCC Source Category 1A5)
Energy Sources of Indirect Greenhouse Gas Emissions
International Bunker Fuels (IPCC Source Category 1 : Memo Items)
Wood Biomass and Ethanol Consumption (IPCC Source Category 1A)
INDUSTRIAL PROCESSES
Cement Manufacture (IPCC Source Category 2A1)
Lime Manufacture (IPCC Source Category 2A2)
Limestone and Dolomite Use (IPCC Source Category 2A3)
Soda Ash Manufacture and Consumption (IPCC Source Category 2A4)
Ammonia Manufacture (IPCC Source Category 2B1) and Urea Consumption
Nitric Acid Production (IPCC Source Category 2B2)
Adipic Acid Production (IPCC Source Category 2B3)
Silicon Carbide Production (IPCC Source Category 2B4) and Consumption
Petrochemical Production (IPCC Source Category 2B5)
Titanium Dioxide Production (IPCC Source Category 2B5)
Carbon Dioxide Consumption (IPCC Source Category 2B5)
Phosphoric Acid Production (IPCC Source Category 2B5)
Iron and Steel Production (IPCC Source Category 2C1)
Ferroalloy Production (IPCC Source Category 2C2)
Aluminum Production (IPCC Source Category 2C3)
Magnesium Production and Processing (IPCC Source Category 2C4)
Zinc Production (IPCC Source Category 2C5)
Lead Production (IPCC Source Category 2C5)
HCFC-22 Production (IPCC Source Category 2E1)
Substitution of Ozone Depleting Substances (IPCC Source Category 2F)
Semiconductor Manufacture (IPCC Source Category 2F6)
Electrical Transmission and Distribution (IPCC Source Category 2F7)
Industrial Sources of Indirect Greenhouse Gases
SOLVENT AND OTHER PRODUCT USE
Nitrous Oxide from Product Uses (IPCC Source Category 3D)
Indirect Greenhouse Gas Emissions from Solvent Use
AGRICULTURE
Enteric Fermentation (IPCC Source Category 4A)
Manure Management (IPCC Source Category 4B)
Rice Cultivation (IPCC Source Category 4C)
3-48
3-53
3-56
3-57
3-61
4-1
4-4
4-7
4-10
4-13
4-16
4-19
4-21
4-24
4-26
4-29
4-31
4-34
4-37
4-41
4-43
4-47
4-50
4-53
4-55
4-57
4-61
4-66
4-72
5-1
5-1
5-4
6-1
6-2
6-7
6-13
vi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
6.4. Agricultural Soil Management (IPCC Source Category 4D) 6-18
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F) 6-29
7. LAND USE, LAND-USE CHANGE, AND FORESTRY 7-1
7.1. Representation of the U.S. Land Base 7-3
7.2. Forest Land Remaining Forest Land 7-11
7.3. Land Converted to Forest Land (IPCC Source Category 5A2) 7-23
7.4. Cropland Remaining Cropland (IPCC Source Category 5B1) 7-23
7.5. Land Converted to Cropland (IPCC Source Category 5B2) 7-35
7.6. Grassland Remaining Grassland (IPCC Source Category 5C1) 7-38
7.7. Land Converted to Grassland (IPCC Source Category 5C2) 7-43
7.8. Settlements Remaining Settlements 7-46
7.9. Land Converted to Settlements (Source Category 5E2) 7-52
7.10. Other (IPCC Source Category 5G) 7-53
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
Vll
-------
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-4
Table ES-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg CO2 Eq.) ES-8
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.)ES-
12
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-14
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.) ES-15
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed
(TgCO2Eq.) ES-16
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100) ES-17
Table ES-10: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) ES-18
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 (1990-2006) Based on Tier 1 Approach 1-12
Table 1-5. Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent) 1-15
Table 1-6: IPCC Sector Descriptions 1-16
Table 1-7: List of Annexes 1-17
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) 2-3
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-5
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.) 2-7
Table 2-4: Emissions from Energy (Tg CO2 Eq.) 2-8
Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 2-9
Table 2-6: Emissions from Industrial Processes (Tg CO2 Eq.) 2-10
Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.) 2-12
Table 2-8: Emissions from Agriculture (Tg CO2 Eq.) 2-12
Table 2-9: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-13
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-14
Table 2-11: Emissions from Waste (Tg CO2 Eq.) 2-15
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq. and Percent of Total in
2006) 2-16
viii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-19
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 2006 2-20
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-22
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100) 2-26
Table 2-17: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) 2-27
Table 3 -1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.) 3-1
Table 3 -2: CO2, CH4, and N2O Emissions from Energy (Gg) 3 -2
Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.) 3-3
Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg CO2
Eq. and Percent) 3-4
Table 3-5: CO2 Emissions from International Bunker Fuels (Tg CO2 Eq.)* 3-7
Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 3-7
Table 3-7: CO2 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO2 Eq.)a 3-9
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu) 3-15
Table 3 -9: Carbon Intensity from all Energy Consumption by Sector (Tg CO2 Eq./QBtu) 3-16
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-related Fossil Fuel
Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent) 3-18
Table 3-11: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.) 3-20
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-21
Table 3-13: 2006 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-21
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Non-Energy Uses of Fossil Fuels
(Tg CO2 Eq. and Percent) 3-23
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent) 3-23
Table 3-16: CH4 Emissions from Stationary Combustion (Tg CO2 Eq.) 3-25
Table 3-17: N2O Emissions from Stationary Combustion (Tg CO2 Eq.) 3-25
Table 3-18: CH4 Emissions from Stationary Combustion (Gg) 3-26
Table 3-19: N2O Emissions from Stationary Combustion (Gg) 3-26
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg CO2 Eq. and Percent) 3-28
Table 3-21: CH4 Emissions from Mobile Combustion (Tg CO2 Eq.) 3-30
Table 3 -22: N2O Emissions from Mobile Combustion (Tg CO2 Eq.) 3 -31
Table 3-23: CH4 Emissions from Mobile Combustion (Gg) 3-31
Table 3-24: N2O Emissions from Mobile Combustion (Gg) 3-32
Table 3-25. Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Mobile Sources (Tg CO2
Eq. and Percent) 3-34
Table 3-26: CH4 Emissions from Coal Mining (Tg CO2 Eq.) 3-37
Table 3-27: CH4 Emissions from Coal Mining (Gg) 3-37
IX
-------
Table 3 -28: Coal Production (Thousand Metric Tons) 3-38
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg CO2 Eq. and
Percent) 3-39
Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg CO2 Eq.) 3-40
Table 3-31: CH4 Emissions from Abandoned Coal Mines (Gg) 3-41
Table 3-32: Number of gassy abandoned mines occurring in U.S. basins grouped by class according to post-
abandonment state 3-42
Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal
Mines (Tg CO2 Eq. and Percent) 3-43
Table 3-34. CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.)* 3-45
Table 3-35. CH4 Emissions from Natural Gas Systems (Gg)* 3-45
Table 3-36. Non-combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-45
Table 3-37. Non-combustion CO2 Emissions from Natural Gas Systems (Gg) 3-45
Table 3-38: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-combustion CO2 Emissions from Natural
Gas Systems (Tg CO2 Eq. and Percent) 3-46
Table 3-39: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-48
Table 3-40: CH4 Emissions from Petroleum Systems (Gg) 3-49
Table 3-41: CO2 Emissions from Petroleum Systems (TgCO2 Eq.) 3-49
Table 3-42: CO2 Emissions from Petroleum Systems (Gg) 3-49
Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg CO2 Eq. and
Percent) 3-51
Table 3-44: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.) 3-52
Table 3-45: Potential Emissions from CO2 Capture and Transport (Gg) 3-52
Table 3-46: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Tg CO2 Eq.) 3-53
Table 3-47: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Gg) 3-53
Table 3-48: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-54
Table 3-49: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from Municipal Solid Waste Combustion
(Tg CO2 Eq. and Percent) 3-55
Table 3-50: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg) 3-56
Table 3-51: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.) 3-58
Table 3-52: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg) 3-58
Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-59
Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons) 3-59
Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.) 3-61
Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Gg) 3-62
Table 3-57: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq.) 3-62
Table 3-58: CO2 Emissions from Ethanol Consumption (Gg) 3-62
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu) 3-63
Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 3 -60: Ethanol Consumption (Trillion Btu) 3-63
Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.) 4-1
Table 4-2: Emissions from Industrial Processes (Gg) 4-2
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 Manufacture (Tg CO2 Eq.
and Percent) 4-6
Table 4-6: CO2 Emissions from Lime Manufacture (Tg CO2 Eq. and Gg) 4-7
Table 4-7: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and Dead-Burned-
Dolomite Lime Production (Gg) 4-8
Table 4-8: Adjusted Lime Production3 (Gg) 4-8
Table 4-9: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Manufacture (Tg CO2 Eq. and
Percent) 4-10
Table 4-10: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.) 4-10
Table 4-11: CO2 Emissions from Limestone & Dolomite Use (Gg) 4-11
Table 4-12: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-12
Table 4-13: Dolomitic Magnesium Metal Production Capacity (Metric Tons) 4-12
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Limestone and Dolomite Use (Tg
CO2 Eq. and Percent) 4-13
Table 4-15: CO2 Emissions from Soda Ash Manufacture and Consumption (Tg CO2Eq.) 4-14
Table 4-16: CO2 Emissions from Soda Ash Manufacture and Consumption (Gg) 4-14
Table 4-17: Soda Ash Manufacture and Consumption (Gg) 4-15
Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Soda Ash Manufacture and
Consumption (Tg CO2 Eq. and Percent) 4-16
Table 4-19: CO2 Emissions from Ammonia Manufacture and Urea Consumption (Tg CO2 Eq.) 4-17
Table 4-20: CO2 Emissions from Ammonia Manufacture and Urea Consumption (Gg) 4-17
Table 4-21: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg) 4-18
Table 4-22: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ammonia Manufacture and Urea
Consumption (Tg CO2 Eq. and Percent) 4-19
Table 4-23: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg) 4-20
Table 4-24: Nitric Acid Production (Gg) 4-20
Table 4-25: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From Nitric Acid Production (Tg CO2
Eq. and Percent) 4-21
Table 4-26: N2O Emissions from Adipic Acid Production (Tg CO2 Eq. and Gg) 4-22
Table 4-27: Adipic Acid Production (Gg) 4-23
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from Adipic Acid Production (Tg CO2
Eq. and Percent) 4-24
Table 4-29: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.) 4-24
Table 4-30: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg) 4-25
XI
-------
Table 4-31: Production and Consumption of Silicon Carbide (Metric Tons) 4-25
Table 4-32: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from Silicon Carbide Production
and Consumption (Tg CO2 Eq. and Percent) 4-26
Table 4-33: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.) 4-26
Table 4-34: CO2 and CH4 Emissions from Petrochemical Production (Gg) 4-27
Table 4-35: Production of Selected Petrochemicals (Thousand Metric Tons) 4-27
Table 4-36: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons) 4-28
Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and CO2
Emissions from Carbon Black Production (Tg CO2 Eq. and Percent) 4-29
Table 4-38: CO2 Emissions from Titanium Dioxide (Tg CO2 Eq. and Gg) 4-29
Table 4-39: Titanium Dioxide Production (Gg) 4-30
Table 4-40: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Titanium Dioxide Production (Tg
CO2 Eq. and Percent) 4-31
Table 4-41: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg) 4-32
Table 4-42: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for Jackson Dome and
Bravo Dome 4-33
Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and
Percent) 4-33
Table 4-44: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. and Gg) 4-34
Table 4-45: Phosphate Rock Domestic Production, Exports, and Imports (Gg) 4-35
Table 4-46: Chemical Composition of Phosphate Rock (percent by weight) 4-35
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Phosphoric Acid Production (Tg
CO2 Eq. and Percent) 4-36
Table 4-48: CO2 and CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-38
Table 4-49: CO2 and CH4 Emissions from Iron and Steel Production (Gg) 4-38
Table 4-50: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg) 4-39
Table 4-51: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons) 4-39
Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from Iron and Steel Production
(Tg. CO2 Eq. and Percent) 4-40
Table 4-53: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.) 4-41
Table 4-54: CO2 and CH4 Emissions from Ferroalloy Production (Gg) 4-41
Table 4-55: Production of Ferroalloys (Metric Tons) 4-42
Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ferroalloy Production (Tg CO2 Eq.
and Percent) 4-43
Table 4-57: CO2 Emissions from Aluminum Production (Tg CO2 Eq. and Gg) 4-43
Table 4-58: PFC Emissions from Aluminum Production (Tg CO2 Eq.) 4-44
Table 4-59: PFC Emissions from Aluminum Production (Gg) 4-44
Table 4-60: Production of Primary Aluminum (Gg) 4-46
xii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 4-61: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from Aluminum Production (Tg
CO2 Eq. and Percent) 4-47
Table 4-62: SF6 Emissions from Magnesium Production and Processing (Tg CO2 Eq. and Gg) 4-48
Table 4-63: SF6 Emission Factors (kg SF6 per metric ton of magnesium) 4-49
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
Processing (Tg CO2 Eq. and Percent) 4-50
Table 4-65: CO2 Emissions from Zinc Production (Tg CO2 Eq. and Gg) 4-51
Table 4-66: Zinc Production (Metric Tons) 4-52
Table 4-67: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Zinc Production (Tg CO2 Eq. and
Percent) 4-53
Table 4-68: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg) 4-54
Table 4-69: Lead Production (Metric Tons) 4-54
Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lead Production (Tg CO2 Eq. and
Percent) 4-55
Table 4-71: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg) 4-56
Table 4-72: HCFC-22 Production (Gg) 4-56
Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and
Percent) 4-57
Table 4-74: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) 4-58
Table 4-75: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-58
Table 4-76: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) by Sector 4-59
Table 4-77: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg CO2
Eq. and Percent) 4-61
Table 4-78: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.) 4-62
Table 4-79: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-62
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg CO2 Eq. and Percent) 4-66
Table 4-81: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Tg CO2 Eq.) 4-
67
Table 4-82: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg) 4-67
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg CO2 Eq. and Percent) 4-70
Table 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF6 from Selected Sources (Tg CO2 Eq.)4-72
Table 4-85: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-72
Table 5-1: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg) 5-1
Table 5-2: N2O Emissions from N2O Product Usage (Tg CO2 Eq. and Gg) 5-1
Table 5-3: N2O Production (Gg) 5-3
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
Xlll
-------
Table 6-1: Emissions from Agriculture (Tg CO2 Eq.) 6-1
Table 6-2: Emissions from Agriculture (Gg) 6-1
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg CO2 Eq.) 6-3
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg) 6-3
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg CO2 Eq. and
Percent) 6-5
Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2 Eq.) 6-9
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) 6-11
Table 6-9: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.) 6-14
Table 6-10: CH4 Emissions from Rice Cultivation (Gg) 6-15
Table 6-11: Rice Areas Harvested (Hectares) 6-16
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg CO2 Eq. and
Percent) 6-17
Table 6-13: N2O Emissions from Agricultural Soils (Tg CO2 Eq.) 6-18
Table 6-14: N2O Emissions from Agricultural Soils (Gg N2O) 6-19
Table 6-15: Direct N2O Emissions from Agricultural Soils by Land-Use and N Input (Tg CO2 Eq.) 6-19
Table 6-16: Indirect N2O Emissions from all Land Use Types (Tg CO2 Eq.) 6-19
Table 6-17: Quantitative Uncertainty Estimates of N2O Emissions from Agricultural Soil Management in 2006 (Tg
CO2 Eq. and Percent) 6-27
Table 6-18: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.) 6-29
Table 6-19: CH4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg) 6-30
Table 6-20: Agricultural Crop Production (Gg of Product) 6-32
Table 6-21: Percent of Rice Area Burned by State 6-32
Table 6-22: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-33
Table 6-23: Greenhouse Gas Emission Ratios 6-33
Table 6-24: Tier 2 Uncertainty Estimates for CH4 and N2O Emissions from Field Burning of Agricultural Residues
(Tg CO2 Eq. and Percent) 6-33
Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 7-
1
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.) 7-2
Table 7-4: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-3
Table 7-5. Land use areas during the inventory reporting period (millions of hectares) 7-4
Table 7-6. Net Annual Changes in C Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools 7-13
Table 7-7. Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools 7-13
Table 7-8. Forest area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools 7-14
xiv Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 7-9: Estimates of CO2 (Tg/yr) emissions for the lower 48 states and Alaska1 7-14
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) 7-18
Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. forests1 7-20
Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (Gg Gas) for U.S. forests1 7-20
Table 7-13: Estimated Carbon Released from Forest Fires for U.S. Forests 7-20
Table 7-14: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg CO2 Eq. and Percent) 7-21
Table7-15. N2O Fluxes from Soils in Forest Land Remaining Forest Land (TgCO2Eq. and Gg) 7-21
Table 7-16: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in Forest Land Remaining Forest Land
(Tg CO2 Eq. and Percent) 7-22
Table 7-17: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.) 7-24
Table 7-18: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C) 7-24
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining
Cropland (Tg CO2 Eq. and Percent) 7-29
Table 7-20: Emissions from Liming of Agricultural Soils (Tg CO2 Eq.) 7-31
Table 7-21: Emissions from Liming of Agricultural Soils (Tg C) 7-31
Table 7-22: Applied Minerals (Million Metric Tons) 7-32
Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of Agricultural Soils (Tg
CO2 Eq. and Percent) 7-33
Table 7-24: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.) 7-33
Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C) 7-34
Table 7-26: Applied Urea (Million Metric Tons) 7-34
Table 7-27: Quantitative Uncertainty Estimates for CO2 Emissions from Urea Fertilization (Tg CO2 Eq. and
Percent) 7-35
Table 7-28: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.) 7-36
Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-36
Table 7-30: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Land Converted to
Cropland (Tg CO2 Eq. and Percent) 7-38
Table 7-31: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.) 7-39
Table 7-32: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-39
Table 7-33: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Grassland Remaining
Grassland (Tg CO2 Eq. and Percent) 7-42
Table 7-34: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.) 7-43
Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-43
Table 7-36: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Land Converted to
Grassland (Tg CO2 Eq. and Percent) 7-45
Table 7-37: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C) 7-47
Table 7-38: 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/m2cover-yr) for 15 U.S. Cities 7-48
xv
-------
Table 7-39: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg
CO2 Eq. and Percent) 7-49
Table 7-40: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg) 7-51
Table 7-41: Quantitative Uncertainty Estimates of N2O Emissions from Soils in Settlements Remaining Settlements
(Tg CO2 Eq. and Percent) 7-52
Table 7-42: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.) 7-53
Table 7-43: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C) 7-53
Table 7-44: 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 7-56
Table 7-45: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-56
Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and Food Scraps in
Landfills (Tg CO2 Eq. and Percent) 7-56
Table 8-1: Emissions from Waste (Tg CO2 Eq.) 8-1
Table 8-2: Emissions from Waste (Gg) 8-1
Table 8-3: CH4 Emissions from Landfills (Tg CO2 Eq.) 8-2
Table 8-4: CH4 Emissions from Landfills (Gg) 8-3
Table 8-5. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg CO2 Eq. and Percent) 8-
5
Table 8-6. CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.) 8-7
Table 8-7. CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg) 8-7
Table 8-8. U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg) 8-10
Table 8-9. U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg) 8-10
Table 8-10. Wastewater Flow (nrVton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices
Production 8-12
Table 8-11. U.S. Population (Millions) and Average Protein Intake [kg/(person-year)] 8-15
Table 8-12. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg CO2 Eq.
and Percent) 8-15
Table 8-13: CH4 and N2O Emissions from Composting (Tg CO2 Eq.) 8-18
Table 8-14: CH4 and N2O Emissions from Composting (Gg) 8-18
Table 8-15: U. S. Waste Composted (Gg) 8-19
Table 8-16 : Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg CO2 Eq. and Percent)8-
19
Table 8-17: Emissions of NOX, CO, and NMVOC 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
C02 Eq.) 10-4
Figures
IFigureES-l: U.S. Greenhouse Gas Emissions by Gas ES-4
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions ES-4
xvi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 ES-4
Figure ES-4: 2006 Greenhouse Gas Emissions by Gas (percents based on Tg CO2 Eq.) ES-6
Figure ES-5: 2006 Sources of CO2 ES-7
Figure ES-6: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type ES-8
Figure ES-7: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion ES-8
Figure ES-8: 2006 Sources of CH4 ES-10
Figure ES-9: 2006 Sources of N2O ES-11
Figure ES-10: 2006 Sources of MFCs, PFCs, and SF6 ES-11
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector ES-12
Figure ES-12: 2006 U.S. Energy Consumption by Energy Source ES-13
Figure ES-13: Emissions Allocated to Economic Sectors ES-15
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-17
Figure ES-16: 2006 Key Categories—Tier 1 Level Assessment ES-19
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas 2-1
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 2-1
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 2-1
Figure 2-4: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector 2-7
Figure 2-5: 2006 Energy Chapter Greenhouse Gas Sources 2-7
Figure 2-6: 2006 U.S. Fossil C Flows (Tg CO2 Eq.) 2-7
Figure 2-7: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-9
Figure 2-8: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 2-9
Figure 2-9: 2006 Industrial Processes Chapter Greenhouse Gas Sources 2-10
Figure 2-10: 2006 Agriculture Chapter Greenhouse Gas Sources 2-12
Figure 2-11: 2006 Waste Chapter Greenhouse Gas Sources 2-15
Figure 2-12: Emissions Allocated to Economic Sectors 2-16
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors 2-20
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-26
Figure 3-1: 2006 Energy Chapter Greenhouse Gas Sources 3-1
Figure 3-2: 2006 U.S. Fossil Carbon Flows (TgCO2Eq.) 3-1
Figure 3-3: 2006 U.S. Energy Consumption by Energy Source 3-5
Figure 3-4: U.S. Energy Consumption (QuadrillionBtu) 3-5
Figure 3-5: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-5
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2006) 3-6
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2006) 3-6
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States (1974-2006) 3-
6
xvn
-------
Figure 3-9: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 3-7
Figure 3-10: Sales-Weighted Fuel Economy of New Passenger Cars and Light-Duty Trucks, 1990-2006 3-8
Figure 3-11: Sales of New Passenger Cars and Light-Duty Trucks, 1990-2006 3 -8
Figure 3-12: Industrial Production Indices (Index 2002=100) 3-10
Figure 3-13: Electricity Generation Retail Sales by End-Use Sector 3-11
Figure 3-14: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and Per Dollar GDP 3-16
Figure 3-15: Mobile Source CH4 and N2O Emissions 3-30
Figure 4-1: 2006 Industrial Processes Chapter Greenhouse Gas Sources 4-1
Figure 6-1: 2006 Agriculture Chapter Greenhouse Gas Emission Sources 6-1
Figure 6-2: Agricultural Sources and Pathways of N that Result in N2O Emissions 6-18
Figure 6-3: Major Crops, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-
2006 (Tg CO2 Eq./state/year) 6-20
Figure 6-4: Grasslands, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-2006
(Tg CO2 Eq./state/year) 6-20
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT
Model, 1990-2006 (Gg N/state/year) 6-20
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT
Model, 1990-2006 (Gg N/state/year) 6-20
Figure 6-7: Comparison of measured emissions at field sites with modeled emissions using the DAYCENT
simulation model 6-27
Figure 7-1. Percent of Total Land Area in Each Land-Use Category by State 7-4
Figure 7-2: Forest Sector Carbon Pools and Flows 7-12
Figure 7-3: Estimates of Net Annual Changes in C Stocks for Major C Pools 7-14
Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States, 2007 7-14
Figure 7-5: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland 7-25
Figure 7-6: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland 7-25
Figure 7-7: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Land Converted to Cropland 7-36
Figure 7-8: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-2006
Land Converted to Cropland 7-36
Figure 7-9: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Grassland Remaining Grassland 7-39
Figure 7-10: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-
2006 Grassland Remaining Grassland 7-40
Figure 7-11: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-
2006 Land Converted to Grassland 7-44
Figure 7-12: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-
2006 Land Converted to Grassland 7-44
Figure 8-1: 2006 Waste Chapter Greenhouse Gas Sources 8-1
xviii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Boxes
BoxES-l: Recalculations of Inventory Estimates ES-1
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data ES-17
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials 1-8
Box 1 -2: IPCC Reference Approach 1-11
Box 2-1: Methodology for Aggregating Emissions by Economic Sector 2-24
Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data 2-25
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 3-5
Box 3-2: Carbon Intensity of U.S. Energy Consumption 3-14
Box 3-3. Carbon Dioxide Transport, Injection, and Geological Storage 3-52
Box 4-1: Potential Emission Estimates of HFCs, PFCs, and SF6 4-71
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions 6-21
Box 6-2: ComparsionofTier2U.S. Inventory Approach and IPCC (2006) Default Approach 6-31
Box 7-1: CO2 Emissions from Forest Fires 7-14
Box 7-2: Tier 3 Inventory for Soil C Stocks compared to Tier 1 or 2 Approaches 7-26
Box 8-1: Biogenic Emissions and Sinks of Carbon 8-6
xix
-------
-------
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 2006. 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.
emission inventory has begun to incorporate new methodologies and data from the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC 2006). The structure of this report is consistent with the UNFCCC
guidelines for inventory reporting.4 For most source categories, the Intergovernmental Panel on Climate Change
(IPCC) methodologies were expanded, resulting in a more comprehensive and detailed estimate of emissions.
[BEGIN BOX]
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
1 The term "anthropogenic", in this context, refers to greenhouse gas emissions and removals that are a direct result of human
activities or are the result of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
2 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate
Change. See .
3 Article 4(1 )(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent
decisions by the Conference of the Parties elaborated the role of Annex I Parties in preparing national inventories. See
.
4 See .
Executive Summary ES-1
-------
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 2005) 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.
[END BOX]
Background Information
Naturally occurring greenhouse gases include water vapor, carbon dioxide (CO2), methane (CH4), nitrous oxide
(N2O), and ozone (O3). Several classes of halogenated substances that contain fluorine, chlorine, or bromine are
also greenhouse gases, but they are, for the most part, solely a product of industrial activities. Chlorofluorocarbons
(CFCs) and hydrochlorofluorocarbons (HCFCs) are halocarbons that contain chlorine, while halocarbons that
contain bromine are referred to as bromofluorocarbons (i.e., halons). As stratospheric ozone depleting substances,
CFCs, HCFCs, and halons are covered under the Montreal Protocol on Substances that Deplete the Ozone Layer.
The UNFCCC defers to this earlier international treaty. Consequently, Parties to the UNFCCC are not required to
include these gases in their national greenhouse gas emission inventories.5 Some other fluorine-containing
halogenated substances—hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)—do
not deplete stratospheric ozone but are potent greenhouse gases. These latter substances are addressed by the
UNFCCC and accounted for in national greenhouse gas emission inventories.
There are also several gases that do not have a direct global warming effect but indirectly affect terrestrial and/or
solar radiation absorption by influencing the formation or destruction of greenhouse gases, including tropospheric
and stratospheric ozone. These gases include carbon monoxide (CO), oxides of nitrogen (NOX), and non-CH4
volatile organic compounds (NMVOCs). Aerosols, which are extremely small particles or liquid droplets, such as
those produced by sulfur dioxide (SO2) or elemental carbon emissions, can also affect the absorptive characteristics
of the atmosphere.
Although the direct greenhouse gases CO2, CH4, and N2O occur naturally in the atmosphere, human activities have
changed their atmospheric concentrations. From the pre-industrial era (i.e., ending about 1750) to 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 OD S 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).
5 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in the annexes of the
Inventory report for informational purposes.
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 of CO2 equivalent (Tg CO2Eq.).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 2002,9 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 2006 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 below in Table ES-1.
Table ES-1 : Global Warming Potentials (100-Year Time Horizon) Used in this Report
Gas
C02
CH4*
N2O
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4F10
C.
Executive Summary ES-3
-------
* 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 CO2 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).
Recent Trends in U.S. Greenhouse Gas Emissions and Sinks
In 2006, total U.S. greenhouse gas emissions were 7,054.2 Tg CO2 Eq. Overall, total U.S. emissions have risen by
14.7 percent from 1990 to 2006, while the U.S. gross domestic product has increased by 59 percent over the same
period (BEA 2007). Emissions fell from 2005 to 2006, decreasing by 1.1 percent (75.7 Tg CO2 Eq.). The
following factors were primary contributors to this decrease: (1) compared to 2005, 2006 had warmer winter
conditions, which decreased consumption of heating fuels, as well as cooler summer conditions, which reduced
demand for electricity, (2) restraint on fuel consumption caused by rising fuel prices, primarily in the transportation
sector and (3) increased use of natural gas and renewables in the electric power sector.
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 2006.
Figure ES-1: U.S. Greenhouse Gas Emissions by Gas
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Natural Gas Systems
Municipal Solid Waste
Combustion
Lime Manufacture
Ammonia Manufacture and
Urea Consumption
Limestone and Dolomite
Use
1990^
5,068.5^
4,724.1^
1,809.6^
1,485.1 =
844.9^
340.1^
216.1 =
28.3^
117.2 =
86.2^
33.3^
33.7^
10.9J
12.0 =
16.9JJ
m 1995^
m 5,394.2m
JH 5,032. 4m
1 1.939.3P
1 1.599.4=
1 876.5p
H 356. sm
1 225. 8p
1 35. Op
1 133.2P
H i4.im
1 36.8P
^ 33.8m
^ i5.im
i 14. om
1
1
i 2000
i 5,939.7
3 5 577 1
i 2,282.3
i 1,798.2
i 860.3
1 372.1
i 228-°
i 36.2
1 141.4
i 66.6
i 41.2
1 29-4
1 17.5
1 I4-9
1 16-4
1 6.0
2001
5,846.2
55074
2,244.3
1,775.6
852.5
363.6
222.3
49.0
131.9
59.2
41.4
28.8
18.0
14.3
13.3
5.7
2002
5,908.6
5 5648
2,253.7
1,828.9
854.8
360.5
222.8
44.0
135.9
55.9
42.9
29.6
18.5
13.7
14.2
5.9
2003
5,952.7
5617
2,283
1,807
856
382
236
51
131
54
43
28
19
14
12
4
0
.1
.6
.0
.9
.5
.0
.8
.7
.1
.4
.1
.5
.5
.8
2004
6,038,
5681
2,314
1,856
857
368
230
53
148
52
45
28
20
15
13
6
.2
4
.9
.4
.7
.3
.6
.5
.9
.8
.6
.1
.1
.2
.2
.7
2005
6,074.3
5731 0
2,380.2
1,869.8
847.3
358.5
221.9
53.2
139.1
46.6
45.9
29.5
20.7
15.1
12.8
7.4
2006
5,983.1
56379
2,328.2
1,856.0
862.2
326.5
210.1
54.9
138.0
49.1
45.7
28.5
20.9
15.8
12.4
8.6
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Cropland Remaining
Cropland
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide
Production
Carbon Dioxide
Consumption
Ferroalloy Production
Phosphoric Acid Production
Zinc Production
Petroleum Systems
Lead Production
Silicon Carbide Production
and Consumption
Land Use, Land-Use
Change, and Forestry
(Sink)"
Biomass — Woodb
International Bunker Fuelsb
Biomass — Ethanof
CH4
Enteric Fermentation
Landfills
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Forest Land Remaining
Forest Land
Wastewater Treatment
Stationary Combustion
Rice Cultivation
Abandoned Underground
Coal Mines
Mobile Combustion
Composting
Petrochemical Production
Iron and Steel Production
Field Burning of
Agricultural Residues
Ferroalloy Production
Silicon Carbide Production
and Consumption
International Bunker Fuelsb
N20
Agricultural Soil
Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
7.
4.
6.
2.
1.
1.
2.
1.
0.
0.
0.
0.
1 =
iB
8^
2^
2^
4^
2^
5^
9^
4M
3^
4JJI
(737. 7)M
215.
113.
4.
606.
126.
149.
124.
84.
31.
33.
4.
23.
7.
7.
6.
4.
0.
0.
1.
0.
a
383.
269.
43.
17.
12.
12.
6.
2=
7iH
2=
iiH
9m
6JJJ:
7M
iM
van
9M
5Ji
OWi
4^
1M
7M
3^
9^
3^
+jjjjjj.
+B
2^
4^
4^
0^
8^
1^
3H
= 7.0^
1
1
1 2.8^
1
1
1
i 1.5^
1
1
1
1
1 (775.3)m
1 229. im
=k 100.6^
1
1 598.9P
1 132.3P
| 144.0P
1 128.1^
1 67. im
| 35.2^
i 32.0^
1
1 24.3^
1
1
1 8.2^
1
1 0.7p
1
1
1
i +p
1 +p
1
1 395.6P
| 264.8P
3 53.4^
1 18.9^
1 13. 4p
1
1
1 7.5
1 4.2
i 6.1
i 3.0
1 1-8
1 1.4
i 1.9
1 I-4
i 1.1
1 °-3
1 0-3
1 0-2
1 (tf73.
-------
Adipic Acid Production 15.3^^ 17 6.2 5.1 6.1 6.3 5.9 5.9 5.9
N2O from Product Uses 4.9 4.9 4.4 4.4 4.4 4.4 4.4
Forest Land Remaining ^
Forest Land 2.2 1.3 2.0 1.2 1.1 1.6 2.8
Composting 1.4 1.4 1.4 1.6 1.7 1.7 1.8
Settlements Remaining
Settlements 1.2 1.4 1.5 1.5 1.6 1.5 1.5
Field Burning of
Agricultural Residues 0.5 0.5 0.4 0.4 0.5 0.5 0.5
Municipal Solid Waste
Combustion 0.4 0.4 0.4 0.4 0.4 0.4 0.4
International Bunker Fuels* 0.9 0.9 0.8 0.9 1.1 1.1 1.1
HFCs 100.1 97.9 106.3 104.5 116.6 121.4 124.5
Substitution of Ozone
Depleting Substances' 71.2 78.0 85.0 92.0 99.1 105.4 110.4
HCFC-22 Production 36-4^ 28-6 19-7 2L1 12-3 17-2 15-8 13-8
Semiconductor Manufacture 0.3 0.2 0.2 0.2 0.2 0.2 0.3
PFCs 20-8^ 13-5 7.0 8-7 7.1 6-1 6-2 6-°
Semiconductor Manufacture 4.9 3.5 3.5 3.3 3.3 3.2 3.6
Aluminum Production 18-5^ 8.6 3.5 5.2 3.8 2.8 3.0 2.5
SF6 32.7^ 19.1 18.7 18.0 18.1 18.0 18.2 17.3
Electrical Transmission and
Distribution 26.7^ 15.1 15.0 14.4 13.8 13.9 14.0 13.2
Magnesium Production and ^
Processing 3.0 2.9 2.9 3.4 3.2 3.3 3.2
Semiconductor Manufacture 1.1 0.7 0.7 0.8 0.8 1.0 1.0
Total 6,148.3||| 6,494.0^ 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2
Net Emissions (Sources and
Sinks) 5,410.6^ 5,718.7^ 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5
+ Does not exceed 0.05 Tg CO2 Eq.
a Parentheses indicate negative values or sequestration. The net CO2 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.
0 Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Note: One teragram (Tg) equals one million metric tons.
Figure ES-4 illustrates the relative contribution of the direct greenhouse gases to total U.S. emissions in 2006. The
primary greenhouse gas emitted by human activities in the United States was CO2, representing approximately 84.8
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 fossil fuel combustion were the major sources of N2O emissions.
The emissions of substitutes for ozone depleting substances and emissions of HFC-23 during the production of
HCFC-22 were the primary contributors to aggregate HFC emissions. Electrical transmission and distribution
systems accounted for most SF6 emissions, while PFC emissions resulted from semiconductor manufacturing and as
a by-product of primary aluminum production.
Figure ES-4: 2006 Greenhouse Gas Emissions by Gas (percents based on Tg CO2 Eq.)
Overall, from 1990 to 2006, total emissions of CO2 increased by 914.6 Tg CO2 Eq. (18.0 percent), while CH4 and
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
N2O emissions decreased by 50.8 Tg CO2 Eq. (8.4 percent) and 15.5 Tg CO2 Eq. (4.0 percent), respectively. During
the same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 57.6 Tg CO2 Eq. (63.7 percent).
From 1990 to 2006, HFCs increased by 87.6 Tg CO2 Eq. (237.3 percent), PFCs decreased by 14.7 Tg CO2 Eq. (70.9
percent), and SF6 decreased by 15.3 Tg CO2 Eq. (47.0 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 12.5 percent of
total emissions in 2006. The following sections describe each gas' contribution to total U.S. greenhouse gas
emissions in more detail.
Carbon Dioxide Emissions
The global carbon cycle is made up of large carbon flows and reservoirs. Billions of tons of carbon in the form of
CO2 are absorbed by oceans and living biomass (i.e., sinks) and are emitted to the atmosphere annually through
natural processes (i.e., sources). When in equilibrium, carbon fluxes among these various reservoirs are roughly
balanced. Since the Industrial Revolution (i.e., about 1750), global atmospheric concentrations of CO2 have risen
about 36 percent (IPCC 2007), principally due to the combustion of fossil fuels. Within the United States, fuel
combustion accounted for 94.2 percent of CO2 emissions in 2006. Globally, approximately 28,193 Tg of CO2 were
added to the atmosphere through the combustion of fossil fuels in 2005, 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).
Figure ES-5: 2006 Sources of CO2
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 2006. Emissions of CO2 from fossil fuel combustion increased at an
average annual rate of 1.1 percent from 1990 to 2006. The fundamental factors influencing this trend include (1) a
generally growing domestic economy over the last 16 years, and (2) significant overall growth in emissions from
electricity generation and transportation activities. Between 1990 and 2006, CO2 emissions from fossil fuel
combustion increased from 4,724.1 Tg CO2 Eq. to 5,637.9 Tg CO2 Eq.—a 19.3 percent total increase over the
sixteen-year period. From 2005 to 2006, these emissions decreased by 93.1 Tg CO2 Eq. (1.6 percent).
Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S.
emission trends. Changes in CO2 emissions from fossil fuel combustion are influenced by many long-term and
short-term factors, including population and economic growth, energy price fluctuations, technological changes, and
seasonal temperatures. On an annual basis, the overall consumption of fossil fuels in the United States generally
fluctuates in response to changes in general economic conditions, energy prices, weather, and the availability of
non-fossil alternatives. For example, in a year with increased consumption of goods and services, low fuel prices,
severe summer and winter weather conditions, nuclear plant closures, and lower precipitation feeding hydroelectric
dams, there would likely be proportionally greater fossil fuel consumption than a year with poor economic
performance, high fuel prices, mild temperatures, and increased output from nuclear and hydroelectric plants.
10 Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Annual 2005 (EIA 2007b).
Executive Summary ES-7
-------
Figure ES-6: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Figure ES-7: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
The four major fuel consuming end-use sectors contributing to CO2 emissions from fossil fuel combustion are
industrial, transportation, residential, and commercial. Electricity generation also emits CO2, although these
emissions are produced as they consume fossil fuel to provide electricity to one of the four end-use sectors. For the
discussion below, electricity generation emissions have been distributed to 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.
Table ES-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg CO2 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990 =
1,488.1 =
1,485.1 =
3.0=
1,527.5 =
844.9 =
682.5 =
929.5^
340.1 =
589.4^
750.8^
216.1 =
534.7^
28.3=
4,724.1^
1,809.6 =
=
1 1,602.5=
= 1,599.4=
=
1 1,589.5=
=
1 713.1 =
=
=
1 639.0jji
1 810.0^
1 225.8^
1 584.2^
=
1 5,032.4^
1 1,939.3=
= 2000
1 1,801.6
= 1,798.2
= 3.4
1 1,645.1
= 860.3
= 784.7
1 1,129.7
= 372.1
1 757.6
1 964.6
1 228.0
1 736.6
= 36.2
1 5,577.1
= 2,282.3
2001
1,779.2
1,775.6
3.6
1,583.9
852.5
731.4
1,121.8
363.6
758.1
973.5
222.3
751.1
49.0
5,507.4
2,244.3
2002
1,832.3
1,828.9
3.4
1,572.5
854.8
717.7
1,145.6
360.5
785.1
970.3
222.8
747.5
44.0
5,564.8
2,253.7
2003
1,811.8
1,807.6
4.2
1,592.1
856.0
736.1
1,178.3
382.9
795.4
983.8
236.5
747.3
51.0
5,617.0
2,283.1
2004
1,860.9
1,856.4
4.5
1,596.8
857.7
739.0
1,173.1
368.3
804.9
997.1
230.6
766.5
53.5
5,681.4
2,314.9
2005
1,874.5
1,869.8
4.7
1,579.6
847.3
732.3
1,206.4
358.5
847.9
1,017.3
221.9
795.4
53.2
5,731.0
2,380.2
2006
1,861.0
1,856.0
4.9
1,567.1
862.2
704.9
1,151.9
326.5
825.4
1,003.0
210.1
792.9
54.9
5,637.9
2,328.2
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.
Transportation End-Use Sector. Transportation activities (excluding international bunker fuels) accounted for 33
percent of CO2 emissions from fossil fuel combustion in 2006.!! Virtually all of the energy consumed in this end-
use sector came from petroleum products. Over 60 percent of the emissions resulted from gasoline consumption for
personal vehicle use. The remaining emissions came from other 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
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 2006.
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
indirectly from the generation of electricity that is consumed by industry, accounted for 28 percent of CO2 from
fossil fuel combustion in 2006. Just over hah0 of these emissions resulted from direct fossil fuel combustion to
produce steam and/or heat for industrial processes. The remaining emissions resulted from consuming electricity
for motors, electric furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The residential and commercial end-use sectors accounted for 20
and 18 percent, respectively, of CO2 emissions from fossil fuel combustion in 2006. 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 operating appliances. The remaining emissions were due
to the consumption of natural gas and petroleum for heating and cooking.
Electricity Generation. The United States relies on electricity to meet a significant portion of its energy demands,
especially for lighting, electric motors, heating, and air conditioning. Electricity generators consumed 36 percent of
U.S. energy from fossil fuels and emitted 41 percent of the CO2 from fossil fuel combustion in 2006. 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 2006. 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 20.8 Tg CO2 Eq. (18 percent) from 1990
through 2006. Emissions from non-energy uses of fossil fuels were 138.0 Tg CO2 Eq. in 2006, which
constituted 2.4 percent of overall fossil fuel CO2 emissions and 2.3 percent of total national CO2 emissions,
approximately the same proportion as in 1990.
• CO2 emissions from iron and steel production increased by 5.3 percent to 49.1 Tg CO2 Eq. in 2006, but have
declined overall by 37.1 Tg CO2 Eq. (43 percent) from 1990 through 2006, due to restructuring of the industry,
technological improvements, and increased scrap utilization.
• In 2006, CO2 emissions from cement manufacture decreased slightly by 0.2 Tg CO2 Eq. (0.4 percent) from
2005 to 2006. 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 2005. Overall, from 1990
to 2006, emissions from cement manufacture increased by 37 percent, an increase of 12.5 Tg CO2 Eq..
• CO2 emissions from municipal solid waste combustion (20.9 Tg CO2 Eq. in 2006) increased by 10.0 Tg CO2
Eq. (91 percent) from 1990 through 2006, as the volume of plastics and other fossil carbon-containing materials
in municipal solid waste grew.
• CO2 emissions from ammonia manufacture and urea consumption (12.4 Tg CO2 Eq. in 2006) have decreased by
4.5 Tg CO2 Eq. (27 percent) since 1990. The decrease in emissions from ammonia manufacture and urea
consumption is associated with an overall decrease in domestic ammonia manufacture, and is due to several
factors including market fluctuations and high natural gas prices.
• Net CO2 sequestration from Land Use, Land-Use Change, and Forestry increased by 146.0 Tg CO2 Eq. (20
percent) from 1990 through 2006. This increase was primarily due to an increase in the rate of net carbon
accumulation in forest carbon stocks, particularly in aboveground and belowground tree biomass. Annual
carbon accumulation in landfilled yard trimmings and food scraps slowed over this period, while the rate of
carbon accumulation in urban trees increased.
Methane Emissions
According to the IPCC, CH4 is more than 20 times as effective as CO2 at trapping heat in the atmosphere. Over the
last two hundred and fifty years, the concentration of CH4 in the atmosphere increased by 148 percent (IPCC 2007).
Anthropogenic sources of CH4 include landfills, natural gas and petroleum systems, agricultural activities, coal
Executive Summary ES-9
-------
mining, wastewater treatment, stationary and mobile combustion, and certain industrial processes (see Figure ES-8).
Figure ES-8: 2006 Sources of CH4
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 2006,
enteric fermentation CH4 emissions were 126.2 Tg CO2 Eq. (approximately 22.7 percent of total CH4
emissions), which represents a decline of 0.7 Tg CO2 Eq., or 0.6 percent, since 1990. Despite this overall
decline in emissions, the last two years have shown a slight increase in emissions.
• Landfills are the second largest anthropogenic source of CH4 emissions in the United States, accounting for
approximately 22.6 percent of total CH4 emissions (125.7 Tg CO2 Eq.) in 2006. From 1990 to 2006, net CH4
emissions from landfills decreased by 23.9 Tg CO2 Eq. (16 percent), with small increases occurring in some
interim years, including 2006. 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.
• CH4 emissions from natural gas systems were 102.4 Tg CO2 Eq. in 2006; emissions have declined by 22.3 Tg
CO2 Eq. (18 percent) since 1990. This decline has been due to improvements in technology and management
practices, as well as some replacement of old equipment.
• In 2006, CH4 emissions from coal mining were 58.5 Tg CO2 Eq., a 1.4 Tg CO2 Eq. (2.5 percent) increase over
2005 emission levels. The overall decline of 25.6 Tg CO2 Eq. (30 percent) from 1990 results from the mining
of less gassy coal from underground mines and the increased use of CH4 collected from degasification systems.
• CH4 emissions from manure management increased by 34 percent for CH4, from 31.0 Tg CO2 Eq. in 1990 to
41.4 Tg CO2 Eq. in 2006. 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
CH4 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.
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
wastewater treatment (see Figure ES-9).
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: 1990-2006
-------
Figure ES-9: 2006 Sources of N2O
Some significant trends in U.S. emissions of N2O include the following:
• Agricultural soils produced approximately 72 percent of N2O emissions in the United States in 2006. Estimated
emissions from this source in 2006 were 265.0 Tg CO2 Eq. Annual N2O emissions from agricultural soils
fluctuated between 1990 and 2006, although overall emissions were 1.6 percent lower in 2006 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.
• In 2006, N2O emissions from mobile combustion were 33.1 Tg CO2 Eq. (approximately 9 percent of U. S. N2O
emissions). From 1990 to 2006, N2O emissions from mobile combustion decreased by 24 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.
• N2O emissions from adipic acid production were 5.9 Tg CO2 Eq. in 2006, 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 Tg CO2 Eq. annually since 1998.
HFC, RFC, and SF6 Emissions
HFCs and PFCs are families of synthetic chemicals that are used as alternatives to the ODSs, which are being
phased out under the Montreal Protocol and Clean Air Act Amendments of 1990. HFCs and PFCs do not deplete
the stratospheric ozone layer, and are therefore acceptable alternatives under the Montreal Protocol.
These compounds, however, along with SF6, are potent greenhouse gases. In addition to having high global
warming potentials, SF6 and PFCs have extremely long atmospheric lifetimes, resulting in their essentially
irreversible accumulation in the atmosphere once emitted. Sulfur hexafluoride is the most potent greenhouse gas
the IPCC has evaluated.
Other emissive sources of these gases include HCFC-22 production, electrical transmission and distribution
systems, semiconductor manufacturing, aluminum production, and magnesium production and processing (see
Figure ES-10).
Figure ES-10: 2006 Sources of HFCs, PFCs, and SF6
Some significant trends in U.S. HFC, PFC, and SF6 emissions include the following:
• Emissions resulting from the substitution of ozone depleting substances (e.g., CFCs) have been increasing from
small amounts in 1990 to 110.4 Tg CO2 Eq. in 2006. Emissions from substitutes for ozone depleting
substances are both the largest and the fastest growing source of HFC, PFC, and SF6 emissions. These
emissions have been increasing as phase-outs required under the Montreal Protocol come into effect, especially
after 1994 when full market penetration was made for the first generation of new technologies featuring ODS
substitutes.
• HFC emissions from the production of HCFC-22 decreased by 62 percent (22.6 Tg CO2 Eq.) from 1990
through 2006, 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
Executive Summary ES-11
-------
emissions.
• SF6 missions from electric power transmission and distribution systems decreased by 51 percent (13.5 Tg CO2
Eq.) from 1990 to 2006, primarily because of higher purchase prices for SF6 and efforts by industry to reduce
emissions.
• PFC emissions from aluminum production decreased by 87 percent (16.1 Tg CO2 Eq.) from 1990 to 2006, due
to both industry emission reduction efforts and lower domestic aluminum production.
Overview of Sector Emissions and Trends
In accordance with the Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), and the 2003 UNFCCC Guidelines on Reporting and Review (UNFCCC 2003),
the Inventory of U.S. Greenhouse Gas Emissions and Sinks report is segregated into six sector-specific chapters.
Figure ES-11 and Table ES-4 aggregate emissions and sinks by these chapters. Emissions of all gases can be
summed from each source category from Intergovernmental Panel on Climate Change (IPCC) guidance. Over the
sixteen-year period of 1990 to 2006, total emissions in the Energy, Industrial Processes, and Agriculture sectors
climbed by 873.0 Tg CO2 Eq. (17 percent), 21.0 Tg CO2Eq. (7 percent), and 6.6 Tg CO2Eq. (1 percent),
respectively. Emissions decreased in the Waste and Solvent and Other Product Use sectors by 18.6 Tg CO2 Eq. (10
percent) and less than 0.1 Tg CO2 Eq. (less than 1 percent), respectively. Over the same period, estimates of net C
sequestration in the Land Use, Land-Use Change, and Forestry sector increased by 122.2 Tg CO2Eq. (17 percent).
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
Table ES-4: Recent Trends in U.S. Greenhouse Gas
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change,
and Forestry (Emissions)
Waste
Total Emissions
1990!
5,203.91
299.9 =
4.4 =
447.5 =
13.11
179.6 =
6,148.31
E 19951
i 5,529.61
\ 315.71
i 4.61
i 453.81
i 13.6s
i 176.8s
i 6,494.01
Emissions and Sinks by Chapter/IPCC Sector
1 2000
1 6,067.8
i 326.5
i 4.9
i 447.9
1 30.0
i 155.6
1 7,032.6
2001
5,982
297
4
463
20
152
6,921
.8
.9
.9
.7
.0
.1
.3
2002
6,036.3
308.6
4.4
449.0
28.4
154.5
6,981.2
2003
6,078
301
4
434
19
160
6,998
o
.5
.2
A
o
.J
.7
.3
.2
2004
6,150.9
315.9
4.4
432.1
17.1
157.7
7,078.0
(Tg C02
2005
6,174.4
315.5
4.4
453.6
23.2
158.7
7,129.9
Eq.)
2006
6,076.9
320.9
4.4
454.1
36.9
161.0
7,054.2
Net CO2 Flux from Land Use, f| ^
Land-Use Change, and I| j
Forestry (Sinks)* (737.7)11 (775.3)g (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)
Net Emissions (Sources and jjj, ^
Sinks) 5,410.6J 5,718.7J1 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5
* The net CO2 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.
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 2006. In 2006,
approximately 83 percent of the energy consumed in the United States (on a Btu basis) was produced through the
combustion of fossil fuels. The remaining 17 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 CH4
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
and N2O emissions (37 percent and 13 percent of total U.S. emissions of each gas, respectively). Overall, emission
sources in the Energy chapter account for a combined 86.1 percent of total U.S. greenhouse gas emissions in 2006.
Figure ES-12: 2006 U.S. Energy Consumption by Energy Source
Industrial Processes
The Industrial Processes chapter contains by-product or fugitive emissions of greenhouse gases from industrial
processes not directly related to energy activities such as fossil fuel combustion. For example, industrial processes
can chemically transform raw materials, which often release waste gases such as CO2, CH4 and N2O. These
processes include iron and steel production, cement manufacture, ammonia manufacture 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 Process chapter
account for 4.5 percent of U.S. greenhouse gas emissions in 2006.
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 2006.
Agriculture
The Agricultural chapter contains anthropogenic emissions from agricultural activities (except fuel combustion,
which is addressed in the Energy chapter, and agricultural CO2 fluxes, which are addressed in the Land Use, Land-
Use Change, and Forestry Chapter). Agricultural activities contribute directly to emissions of greenhouse gases
through a variety of processes, including the following source categories: enteric fermentation in domestic livestock,
livestock manure management, rice cultivation, agricultural soil management, and field burning of agricultural
residues. CH4 and N2O were the primary greenhouse gases emitted by agricultural activities. CH4 emissions from
enteric fermentation and manure management represented about 23 percent and 7 percent of total CH4 emissions
from anthropogenic activities, respectively, in 2006. Agricultural soil management activities such as fertilizer
application and other cropping practices were the largest source of U.S. N2O emissions in 2006, accounting for 72
percent. In 2006, emission sources accounted for in the Agricultural chapters were responsible for 6.4 percent of
total U.S. greenhouse gas emissions.
Land Use, Land-Use Change, and Forestry
The Land Use, Land-Use Change, and Forestry chapter contains emissions of CH4 and N2O, and emissions and
removals of CO2 from forest management, other land-use activities, and land-use change. Forest management
practices, tree planting in urban areas, the management of agricultural soils, and the landfilling of yard trimmings
and food scraps have resulted in a net uptake (sequestration) of C in the United States. Forests (including
vegetation, soils, and harvested wood) accounted for approximately 84 percent of total 2006 net CO2flux, urban
trees accounted for 11 percent, mineral and organic soil carbon stock changes accounted for 5 percent, and
landfilled yard trimmings and food scraps accounted for 1 percent of the total net flux in 2006. 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
Executive Summary ES-13
-------
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 2006 resulted in a net C sequestration of 883.7 Tg CO2 Eq.
(Table ES-5). This represents an offset of approximately 14.8 percent of total U.S. CO2 emissions, or 12.5 percent
of total greenhouse gas emissions in 2006. Between 1990 and 2006, total land use, land-use change, and forestry
net C flux resulted in a 20 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 scraps slowed over this period, while the rate of annual C
accumulation increased in urban trees.
Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)
Sink Category
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)
Total
1990^
(621.7)(
(30.1)(
14-7B
(1.9)(
(14.3)(
(23. 9) •
(737.7)^
1
1 (659-9)l
1 (39-4)l
1
| 16.6M
1 <16-3)1
1 (7L5)1
1 (14.1)1
1 (775.3) =
1 2000
1 (550.7)
1 (38'4)
1 9-4
1 16-4
1 <16'3)
1 (82'4)
1 (11.5)
S (673.6)
2001
(623.4)
(40.0)
9.4
16.4
(16.3)
(84.6)
(11.6)
(750.2)
2002
(697.3)
(40.3)
9.4
16.4
(16.3)
(86.8)
(11.8)
(826.8)
2003
(730.9)
(40.5)
9.4
16.4
(16.3)
(88.9)
(10.0)
(860.9)
2004
(741.4)
(40.9)
9.4
16.3
(16.3)
(91.1)
(9.6)
(873.7)
2005
(743.6)
(41.0)
9.4
16.3
(16.3)
(93.3)
(10.0)
(878.6)
2006
(745.1)
(41.8)
9.4
16.2
(16.3)
(95.5)
(10.5)
(883.7)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
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 2006, and increase of 13 percent relative to 1990. The application of synthetic fertilizers to forest and
settlement soils in 2006 resulted in direct N2O emissions of 1.8 Tg CO2 Eq. Direct N2O emissions from fertilizer
application increased by approximately 74 percent between 1990 and 2006. Non-CO2 emissions from forest fires in
2006 resulted in CH4 emissions of 24.6 Tg CO2 Eq., and in N2O emissions of 2.5 Tg CO2 Eq.
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)
Source Category 2000 2001 2002 2003 2004 2005 2006
CO2 7.5 7.8 8.5 8.3 7.6 7.9 8.0
Cropland Remaining Cropland:
Liming of Agricultural Soils &
Urea Fertilization 7.5 7.8 8.5 8.3 7.6 7.9 8.0
CH4 19.0 9.4 16.4 8.7 6.9 12.3 24.6
Forest Land Remaining Forest
Forest Fires 19.0 9.4 16.4 8.7 6.9 12.3 24.6
2.7 3.5 2.7 2.6 3.1 4.3
Forest Land Remaining Forest
Forest Fires 1.9 1.0 1.7 0.9 0.7 1.2 2.5
ES-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Forest Land Remaining Forest =
Land: ^
Forest Soils 0.1^
Settlements Remaining Settlements: ^
Settlement Soils
Total 13.1^
=
1
1
i 0.3
1 1.2
1 30.0
0.3
1.4
20.0
0.3
1.5
28.4
0.3
1.5
19.7
0.3
1.6
17.1
0.3
1.5
23.2
0.3
1.5
36.9
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Waste
The Waste chapter contains emissions from waste management activities (except waste incineration, 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 CH4 and N2O
from composting grew from 1990 to 2006, and resulted in emissions of 1.6 Tg CO2 Eq. and 1.8 Tg CO2 Eq.,
respectively. Overall, in 2006, emission sources accounted for in the Waste chapter generated 2.3 percent of total
U.S. greenhouse gas emissions.
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 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 2006.
Figure ES-13: Emissions Allocated to Economic Sectors
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.)
Implied Sectors
Electric Power Industry
Transportation
Industry
Agriculture
Commercial
Residential
U.S. Territories
Total Emissions
Land Use, Land-Use Change,
and Forestry (Sinks)
1990^
1,859.1^
1,544.1^
1,460.3^
506.8^
396.9^
346.9^
34.1^
6,148.3p
(737.7)B
= 1995 =
= 1.989.7 =
= 1,478.0 =
ji 524.1^
M 404.5^
HI 310.9M
M 41.1 =
= 6,494.0 =
• (775.3)1
= 2
= 1
= ]
= 7
• ('
2000
,328.9
,917.5
,432.9
528.0
390.3
387.7
47.3
,032.6
673.6)
2001
2,290.9
1,895.8
1,384.3
533.4
383.0
379.3
54.5
6,921.3
(750.2)
2002
2,300.4
1,948.5
1,384.9
529.3
388.1
376.6
53.3
6,981.2
(826.8)
2003
2,329.4
1,925.9
1,375.5
498.0
410.2
399.6
59.7
6,998.2
(860.9)
2004
2,363.4
1,975.4
1,388.9
499.2
404.6
385.5
61.0
7,078.0
(873.7)
2
1
1
7
0
2005
,430.0
,987.2
,354.3
521.3
400.4
376.0
60.5
,129.9
878.6)
2006
2,377.8
1,969.5
1,371.5
533.6
394.6
344.8
62.4
7,054.2
(883.7)
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 of the Inventory report.
Executive Summary ES-15
-------
Net 5,410.6^=5,718.7^6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5
Note: Totals may not sum due to independent rounding. Emissions include CO2, CH4, N2O, HFCs, PFCs, and SF6.
See Table 2-12 for more detailed data.
Using this categorization, emissions from electricity generation accounted for the largest portion (34 percent) of
U.S. greenhouse gas emissions in 2006. Transportation activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted for 19 percent of U.S. greenhouse gas emissions in 2006.
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 19 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 8 percent of U.S. emissions; unlike other economic sectors, agricultural sector emissions
were dominated by N2O emissions from agricultural soil management and CH4 emissions from enteric fermentation,
rather than CO2 from fossil fuel combustion. The commercial sector accounted for about 6 percent of emissions,
while U.S. territories accounted for 1 percent.
CO2 was also emitted and sequestered by a variety of activities related to forest management practices, tree planting
in urban areas, the management of agricultural soils, and landfilling of yard trimmings.
Electricity is ultimately consumed in the economic sectors described above. Table ES-8 presents greenhouse gas
emissions from economic sectors with emissions related to electricity generation distributed into end-use categories
(i.e., emissions from electricity generation are allocated to the economic sectors in which the electricity is
consumed). To distribute electricity emissions among end-use sectors, emissions from the source categories
assigned to electricity generation were allocated to the residential, commercial, industry, transportation, and
agriculture economic sectors according to retail sales of electricity.14 These source categories include CO2 from
fossil fuel combustion and the use of limestone and dolomite for flue gas desulfurization, CO2 and N2O from waste
combustion, CH4 and N2O from stationary sources, and SF6 from electrical transmission and distribution systems.
When emissions from electricity are distributed among these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (29 percent) in 2006. 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 2006.
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed
(TgC02Eq.)
Implied Sectors
Industry
Transportation
Commercial
Residential
Agriculture
U.S. Territories
Total Emissions
1990^
2,100.4p
l,547.2p
946.3p
952.4p
567.9m
34.1P
6,148.3p
^ 1995 =
^2,141.1 =
^1,688.9 =
^1,003.8 =
^1,026.5 =
m 592.5 =
m 41.1 =
^6,494.0^
= 2000 2001 2002 2003 2004 2005 2006
^2,174.3 2,061.1 2,051.6 2,064.0 2,075.4 2,038.3 2,029.2
^1,921.0 1,899.4 1,952.0 1,930.2 1,980.0 1,992.0 1,974.5
= 1,141.9 1,149.8 1,151.1 1,172.7 1,187.2 1,212.5 1,204.4
= 1,160.7 1,153.2 1,178.0 1,211.2 1,207.2 1,241.7 1,187.8
= 587.4 603.2 595.1 560.5 567.2 584.9 595.8
= 47.3 54.5 53.3 59.7 61.0 60.5 62.4
M 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2
14 Emissions were not distributed to U.S. territories, since the electricity generation sector only includes emissions related to the
generation of electricity in the 50 states and the District of Columbia.
ES-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Land Use, Land-Use Change, H
and Forestry (Sinks) (737.7)P
Net Emissions (Sources and H
Sinks) 5,410.6p
^(775.3) =
^5,718.7^
= (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)
M 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5
See Table 2-14 for more detailed data.
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors
[BEGIN BOX]
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 2006; (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 2000 2001 2002 2003 2004 2005 2006 h Rate3
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Population"1
Greenhouse Gas Emissions6
100 =
100 =
100^
100 =
100^
100^
1
1
| 107^
1
I
| 106^
i 138
i 127
\ H7
i 116
1 113
1 114
139
125
115
112
114
113
141
128
116
115
115
114
145
129
116
115
116
114
150
131
119
118
117
115
155
134
119
118
118
116
159
135
117
117
119
115
3.0%
1.9%
1.0%
1.0%
1.1%
0.9%
a Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2007)
0 Energy content-weighted values (EIA 2007b)
d U.S. Census Bureau (2007)
e GWP-weighted values
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product
Source: BEA (2007), U.S. Census Bureau (2007), and emission estimates in this report.
[END BOX]
Executive Summary ES-17
-------
Indirect Greenhouse Gases (CO, NOX, NMVOCs, and S02)
The reporting requirements of the UNFCCC 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.
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.
Table ES-10: Emissions of NOX, CO, NMVOCs, and SO2 (Gg)
Gas/Activity
NOX
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Oil and Gas Activities
Municipal Solid Waste
Combustion
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Municipal Solid Waste
Combustion
Agricultural Burning
Oil and Gas Activities
Waste
Solvent Use
NMVOCs
Mobile Fossil Fuel Combustion
Solvent Use
Industrial Processes
Stationary Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
Waste
Agricultural Burning
1990^= 1995^
21,645p
10,920p
9,883p_
591^
139m
m
82p
im
op
130,461p
119,360p
5,000m
4,125m
m
691m
302m
im
5m
20,930p
10,932p
5,216m
2,422^
9i2m
554p.
mi
222mi
613m
NA^
21
10
9
,622m
,821p
6oim
loom
881
291
3m
im
109,0321!
97
5
3
1
,630m
,383p
,959m
,oi3ml
663m
3i6m
2m
5m
19,520|!
8
5
2
,i45m
,609m
,642m
9i3m
582i
2371
i3im
NAP
1 2000
1 19,203
1 10,310
1 8,002
1 626
I 111
1 114
1 35
1 3
1 2
1 92,777
1 83,559
1 4,340
| 2,217
1 i'670
1 792
1 146
1 8
1 46
1 15,228
1 7,230
1 4,384
1 1,773
1 1,077
I 389
1 257
1 119
1 NA
2001
18,410
9,819
7,667
656
113
114
35
3
2
89,212
79,851
4,377
2,339
1,672
774
147
8
45
15,048
6,872
4,547
1,769
1,080
400
258
122
NA
2002
17
10
6
84
75
4
1
1
15
7
3
2
1
,938
,154
,791
534
321
98
33
5
2
,609
,421
,965
,744
,439
709
323
7
1
,640
,235
,881
,036
,585
545
243
115
NA
2003
17,043
9,642
6,419
528
316
97
34
5
2
80,221
71,038
4,893
1,724
1,437
800
321
7
1
15,170
6,885
3,862
1,972
1,560
538
239
114
NA
2004
16,177
9,191
6,004
524
316
97
39
5
2
76,342
67,096
4,876
1,724
1,437
879
321
7
1
14,807
6,587
3,854
1,931
1,553
533
237
112
NA
2005
15,569
8,739
5,853
519
316
97
39
5
2
72,365
63,154
4,860
1,724
1,437
860
321
7
1
14,444
6,289
3,846
1,890
1,545
528
235
111
NA
2006
14,869
8,287
5,610
515
315
97
38
5
2
68,372
59,213
4,844
1,724
1,437
825
322
7
1
14,082
5,991
3,839
1,849
1,538
523
232
110
NA
15 See .
16 NOX and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken
from EPA (2008).
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
Waste
Solvent Use
Agricultural Burning
20,935p
18,407p
1,307^
793p
390p
w.
op
op
NAP
16,891^ 14,829
14,724pi 12,848
1,117^ 1,031
632
286
^
29
Ipi 1
Ipi 1
NA
14,452
12,461
1,047
624
289
30
1
1
NA
13,403
11,613
850
683
233
23
1
0
NA
13,631
11,956
804
621
226
22
1
0
NA
13,232
11,625
800
564
220
22
1
0
NA
13,114
11,573
797
508
213
22
1
0
NA
12,258
10,784
793
451
207
22
1
0
NA
Source: (EPA 2008, disaggregated based on EPA 2003) except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
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 2006 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 report. For more information
regarding key categories, see section 1.5 and Annex 1 of the inventory report.
Figure ES-16: 2006 Key Categories—Tier 1 Level Assessment
Quality Assurance and Quality Control (QA/QC)
The United States seeks to continually improve the quality, transparency, and credibility of the Inventory of U.S.
Greenhouse Gas Emissions and Sinks. To assist in these efforts, the United States implemented a systematic
approach to QA/QC. While QA/QC has always been an integral part of the U.S. national system for inventory
development, the procedures followed for the current inventory have been formalized in accordance with the
QA/QC plan and the UNFCCC reporting guidelines.
Uncertainty Analysis of Emission Estimates
While the current U.S. emissions inventory provides a solid foundation for the development of a more detailed and
comprehensive national inventory, there are uncertainties associated with the emission estimates. Some of the
17 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
Executive Summary ES-19
-------
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.
ES-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
MFCs, PFCs, & SF6
Nitrous Oxide
Methane
Carbon Dioxide
6,148 6,106 6,192 6,343 6,435 6,494
6,760 6,801 6,839 7,033 6,921 6,981 6,998 7,078 7,130 7,054
8,000 -
7,000 -
6,000 -
. 5,000 -
S
O 4,000 -
u
H 3,000 -
2,000 -
1,000 -
0 -
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure ES-1: U.S. GHG Emissions by Gas
3.6%
2.8%
1.1%
0.7%
-1% -
-2% J
-1.6%
-1.1%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
982
930 906
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
-------
MFCs, PFCs & SF6
N2O
CH4
2.1%
5.2%
7.9%
C02
84.8%
Figure ES-4: 2006 Greenhouse Gas Emissions by Gas
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Natural Gas Systems
Municipal Solid Waste Combustion |
Lime Manufacture |
Ammonia Production and Urea Consumption |
Limestone and Dolomite Use |
Cropland Remaining Cropland |
Soda Ash Manufacture and Consumption |
Aluminum Production |
Petrochemical Production |
Titanium Dioxide Production |
Carbon Dioxide Consumption |
Ferroalloy Production |
Phosphoric Acid Production |
Zinc Production
Petroleum Systems
Lead Production
Silicon Carbide Production and Consumption
5,637.9
< 0.5
< 0.5
< 0.5
CO2 as a Portion
of all Emissions
25
50
75 100
Tg CO2 Eq.
125 150 175
Figure ES-5: 2006 Sources of CO2
-------
2,500 -| Relative Contribution
by Fuel Type
2,000 4
1,500
1,000 -
500
0 J
1
g.
• Natural Gas
Petroleum
• Coal
Figure ES-6: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: Electricity generation also includes emissions of less than 0.5 Tg CO 2 Eq. from geothermal-based electricity
generation.
2,000 -i
1,800 -
1,600 -
. 1,400 -
m 1,200 -
O 1,000 -
™ 800-
H 600 -
400 -
200 -
0 -
II From Electricity
Consumption
• From Direct Fossil
Fuel Combustion
in
Figure ES-7: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
-------
Enteric Fermentation
Landfills
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Forest Land Remaining Forest Land
Wastewater Treatment
Stationary Combustion
Rice Cultivation
Abandoned Coal Mines
Mobile Combustion |
Composting |
Petrochemical Production |
Iron and Steel Production |
Field Burning of Agricultural Residues |
Ferroalloy Production < 0.5
Silicon Carbide Production and Consumption < 0.5
20
CH4 as a Portion
of all Emissions
7.9%
o
40
60 80
Tg CO2 Eq.
100 120
140
Figure ES-8: 2006 Sources of CH4
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment ^^|
Adipic Acid Production B
N2O from Product Uses B
Forest Land Remaining Forest Land |
Composting |
Settlements Remaining Settlements |
Field Burning of Agricultural Residues |
Municipal Solid Waste Combustion < 0.5
265.0
10
N,O as a Portion
of all Emissions
5.2%
©
20 30
Tg CO2 Eq.
40
50
Figure ES-9: 2006 Sources of N2O
-------
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Electrical Transmission
and Distribution
Semiconductor
Manufacture
I
Magnesium Production •
and Processing I
Aluminum Production I
0
MFCs, PFCs, and SF6 as a Portion
of all Emissions
2.1%
25
50 75
TgCO2Eq.
100
125
Figure ES-10: 2006 Sources of MFCs, PFCs, and SF6
7,000 -,
6,000 -
5,000 -
s4'000 -
8 3,000 -
2,000 -
1,000 -
0 -
(1,000) J
Industrial Processes
Agriculture
Waste
LULUCF (sources)
Energy
Land Use, Land-Use Change and Forestry (sinks)
O iH
s s
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and Other
Product Use sectors
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
-------
8% Nuclear
9% Renewable
22%
Natural Gas
22% Coal
39%
Petroleum
Figure ES-12: 2006 U.S. Energy Consumption by Energy Source
2,500 -,
2,000 -
ff 1,500-
8
F 1,000-
500 -
_ Electricity
Generation
Transportation
i
Industry
'Agriculture
Commercial
Residential
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure ES-13: Emissions Allocated to Economic Sectors
Note: Does not include U.S. territories.
-------
CT
LU
0
(_)
2,500 -,
2,000 -
1,500 -
1,000
500
n
. ^ Industrial
- . • • Transportation
Residential (gray)
_
Oi-irMm^i-Ln<£>
O O O O O O O
O O O O O O O
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors
Note: Does not include U.S. territories.
160
150
140
§130
iH
|| ._-
d no
x
-------
CO2 Emissions from Stationary Combustion - Coal
Mobile Combustion: Road & Other
CO2 Emissions from Stationary Combustion - Gas
CO2 Emissions from Stationary Combustion - Oil
Direct N2O Emissions from Agricultural Soil Management
Mobile Combustion: Aviation
CO2 Emissions from Non-Energy Use of Fuels
CH4 Emissions from Enteric Fermentation
CH4 Emissions from Landfills
Emissions from Substitutes for Ozone Depleting Substances
Fugitive Emissions from Natural Gas Systems
Fugitive Emissions from Coal Mining
Indirect N2O Emissions from Applied Nitrogen
CO2 Emissions from Iron and Steel Production
CO2 Emissions from Cement Manufacture
Mobile Combustion: Marine
CH4 Emissions from Manure Management
0 200 400 600
1,000 1,200 1,400 1,600 1,800 2,000 2,200
TgCO2Eq.
Figure ES-16: 2006 Key Categories - Tier 1 Level Assessment
Note: For a complete discussion of the key source analysis see Annex 1.
-------
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 2006. 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/IEA 1997) to
ensure that the emission inventories submitted to the UNFCCC are consistent and comparable between nations. The
IPCC accepted the Revised 1996IPCC 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 Management in National Greenhouse Gas Inventories and
the Good Practice Guidance for Land Use, Land-Use Change, and Forestry, which further expanded upon the
methodologies in the Revised 1996 IPCC Guidelines. The IPCC has also accepted the 2006 Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) at its Twenty-Fifth Session (Mauritius, April 2006). The 2006 IPCC
Guidelines build on the previous bodies of work and includes new sources and gases "... as well as updates to the
previously published methods whenever scientific and technical knowledge have improved since the previous
guidelines were issued." Many of the methodological improvements presented in the 2006 Guidelines have been
adopted in this Inventory.
Overall, this inventory of anthropogenic greenhouse gas emissions provides a common and consistent mechanism
through which Parties to the UNFCCC can estimate emissions and compare the relative contribution of individual
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(l)(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
-------
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 ofradiatively
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).
CO2, CH4, and N2O are continuously emitted to and removed from the atmosphere by natural processes on Earth.
Anthropogenic activities, however, can cause additional quantities of these and other greenhouse gases to be emitted
or sequestered, thereby changing their global average atmospheric concentrations. Natural activities such as
respiration by plants or animals and seasonal cycles of plant growth and decay are examples of processes that only
cycle carbon or nitrogen between the atmosphere and organic biomass. Such processes, except when directly or
5 For more on the science of climate change, see NRC (2001).
6 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in this document for
informational purposes.
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (years) of
Selected Greenhouse Gases
Atmospheric Variable
Pre-industrial atmospheric
concentration
Atmospheric concentration3
Rate of concentration change
Atmospheric lifetime0
C02
278 ppm
379 ppm
1.4ppm/yr
50-200d
CH4
0.715 ppm
1.774 ppm
0.005
ppm/yra
12e
N2O
0.270 ppm
0.3 19 ppm
0.26% yr
114e
SF6
Oppt
5.6 ppt
Linearb
3,200
CF4
40 ppt
74 ppt
Linearb
>50,000
Source: Pre-industrial atmospheric concentrations, current atmospheric concentrations, and rate of concentration changes for all
gases are from IPCC (2007).
a The growth rate for atmospheric CH4 has been decreasing from 1.4 ppb/yr in 1984 to less than 0 ppb/yr in 2001, 2004, and
2005.
b IPCC (2007) identifies the rate of concentration change for SF6 and CF4 as linear.
c Source: IPCC (1996).
d No single lifetime can be defined for CO2 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.
A brief description of each greenhouse gas, its sources, and its role in the atmosphere is given below. The
following section then explains the concept of GWPs, which are assigned to individual gases as a measure of their
relative average global radiative forcing effect.
Water Vapor (H2O). Overall, the most abundant and dominant greenhouse gas in the atmosphere is water vapor.
Water vapor is neither long-lived nor well mixed in the atmosphere, varying spatially from 0 to 2 percent (IPCC
1996). In addition, atmospheric water can exist in several physical states including gaseous, liquid, and solid.
Human activities are not believed to affect directly the average global concentration of water vapor, but, the
radiative forcing produced by the increased concentrations of other greenhouse gases may indirectly affect the
hydrologic cycle. While a warmer atmosphere has an increased water holding capacity, increased concentrations of
water vapor affects the formation of clouds, which can both absorb and reflect solar and terrestrial radiation.
Aircraft contrails, which consist of water vapor and other aircraft emittants, are similar to clouds in their radiative
forcing effects (IPCC 1999).
Carbon Dioxide. In nature, carbon is cycled between various atmospheric, oceanic, land biotic, marine biotic, and
mineral reservoirs. The largest fluxes occur between the atmosphere and terrestrial biota, and between the
atmosphere and surface water of the oceans. In the atmosphere, carbon predominantly exists in its oxidized form as
CO2. Atmospheric CO2 is part of this global carbon cycle, and therefore its fate is a complex function of
geochemical and biological processes. CO2 concentrations in the atmosphere increased from approximately 280
parts per million by volume (ppmv) in pre-industrial times to 379 ppmv in 2005, a 35 percent increase (IPCC 2007
and Hofmann 2004).7'8 The IPCC definitively states that "the present atmospheric CO2 increase is caused by
anthropogenic emissions of CO2" (IPCC 2001). The predominant source of anthropogenic CO2 emissions is the
combustion of fossil fuels. Forest clearing, other biomass burning, and some non-energy production processes (e.g.,
cement production) also emit notable quantities of CO2.
7 The 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. CH4 is primarily produced through anaerobic decomposition of organic matter in biological systems.
Agricultural processes such as wetland rice cultivation, enteric fermentation in animals, and the decomposition of
animal wastes emit CH4, as does the decomposition of municipal solid wastes. CH4 is also emitted during the
production and distribution of natural gas and petroleum, and is released as a by-product of coal mining and
incomplete fossil fuel combustion. Atmospheric concentrations of CH4 have increased by about 143 percent since
1750, from a pre-industrial value of about 722 ppb to 1,774 ppb in 2005, although the rate of increase has been
declining. The IPCC has estimated that slightly more than half of the current CH4 flux to the atmosphere is
anthropogenic, from human activities such as agriculture, fossil fuel use, and waste disposal (IPCC 2007).
CH4 is removed from the atmosphere through a reaction with the hydroxyl radical (OH) and is ultimately converted
to CO2. Minor removal processes also include reaction with chlorine in the marine boundary layer, a soil sink, and
stratospheric reactions. Increasing emissions of CH4 reduce the concentration of OH, a feedback that may increase
the atmospheric lifetime of CH4 (IPCC 2001).
Nitrous Oxide. Anthropogenic sources of N2O emissions include agricultural soils, especially production of
nitrogen-fixing crops and forages, the use of synthetic and manure fertilizers, and manure deposition by livestock;
fossil fuel combustion, especially from mobile combustion; adipic (nylon) and nitric acid production; wastewater
treatment and waste combustion; and biomass burning. The atmospheric concentration of 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. N2O 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
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: 1990-2006
-------
[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 harmful levels of ultraviolet radiation.
Under the Montreal Protocol, the United States phased out the production and importation of halons by 1994 and of
CFCs by 1996. Under the Copenhagen Amendments to the Protocol, a cap was placed on the production and
importation of HCFCs by non-Article 5 * * countries beginning in 1996, and then followed by a complete phase-out
by the year 2030. While ozone depleting gases covered under the Montreal Protocol and its Amendments are not
covered by the UNFCCC; they are reported in this inventory under Annex 6.2 of this report for informational
purposes.
HFCs, PFCs, and SF6 are not ozone depleting substances, and therefore are not covered under the Montreal
Protocol. They are, however, powerful greenhouse gases. HFCs are primarily used as replacements for ozone
depleting substances but also emitted as a by-product of the HCFC-22 manufacturing process. Currently, they have
a small aggregate radiative forcing impact, but it is anticipated that their contribution to overall radiative forcing
will increase (IPCC 2001). PFCs and SF6 are predominantly emitted from various industrial processes including
aluminum smelting, semiconductor manufacturing, electric power transmission and distribution, and magnesium
casting. Currently, the radiative forcing impact of PFCs and SF6 is also small, but they have a significant growth
rate, extremely long atmospheric lifetimes, and are strong absorbers of infrared radiation, and therefore have the
potential to influence climate far into the future (IPCC 2001).
Carbon Monoxide. Carbon monoxide has an indirect radiative forcing effect by elevating concentrations of CH4
and tropospheric ozone through chemical reactions with other atmospheric constituents (e.g., the hydroxyl radical,
OH) that would otherwise assist in destroying CH4 and tropospheric ozone. Carbon monoxide is created when
carbon-containing fuels are burned incompletely. Through natural processes in the atmosphere, it is eventually
oxidized to CO2. Carbon monoxide concentrations are both short-lived in the atmosphere and spatially variable.
Nitrogen Oxides. The primary climate change effects of nitrogen oxides (i.e., NO and NO2) are indirect and result
from their role in promoting the formation of ozone in the troposphere and, to a lesser degree, lower stratosphere,
where it has positive radiative forcing effects.12 Additionally, NOX emissions from aircraft are 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-CH4 volatile organic compounds include substances
such as propane, butane, and ethane. These compounds participate, along with NOX, in the formation of
tropospheric ozone and other photochemical oxidants. NMVOCs are emitted primarily from transportation and
industrial processes, as well as biomass burning and non-industrial consumption of organic solvents.
Concentrations of NMVOCs tend to be both short-lived in the atmosphere and spatially variable.
Aerosols. Aerosols are extremely small particles or liquid droplets found in the atmosphere. They can be produced
by natural events such as dust storms and volcanic activity, or by anthropogenic processes such as fuel combustion
and biomass burning. Aerosols affect radiative forcing differently than greenhouse gases, and their radiative effects
occur through direct and indirect mechanisms: directly by scattering and absorbing solar radiation; and indirectly by
11 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
-------
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
involves an increase in the water content and lifetime of clouds due to the effect of reduced droplet size on
precipitation efficiency (IPCC 2001). Recent research has placed a greater focus on the second indirect radiative
forcing effect of aerosols.
Various categories of aerosols exist, including naturally produced aerosols such as soil dust, sea salt, biogenic
aerosols, sulfates, and volcanic aerosols, and anthropogenically manufactured aerosols such as industrial dust and
carbonaceous13 aerosols (e.g., black carbon, organic carbon) from transportation, coal combustion, cement
manufacturing, waste incineration, and biomass burning.
The net effect of aerosols on radiative forcing is believed to be negative (i.e., net cooling effect on the climate),
although because they remain in the atmosphere for only days to weeks, their concentrations respond rapidly to
changes in emissions.14 Locally, the negative radiative forcing effects of aerosols can offset the positive forcing of
greenhouse gases (IPCC 1996). "However, the aerosol effects do not cancel the global-scale effects of the much
longer-lived greenhouse gases, and significant climate changes can still result" (IPCC 1996).
The IPCC's Third Assessment Report notes that "the indirect radiative effect of aerosols is now understood to also
encompass effects on ice and mixed-phase clouds, but the magnitude of any such indirect effect is not known,
although it is likely to be positive" (IPCC 2001). Additionally, current research suggests that another constituent of
aerosols, black carbon, may have a positive radiative forcing (Jacobson 2001). The primary anthropogenic emission
sources of black carbon include diesel exhaust and open biomass burning.
Global Warming Potentials
A global warming potential is a quantified measure of the globally averaged relative radiative forcing impacts of a
particular greenhouse gas (see Table 1-2). It is defined as the ratio of the time-integrated radiative forcing from the
instantaneous release of 1 kilogram (kg) of a trace substance relative to that of 1 kg of a reference gas (IPCC 2001).
Direct radiative effects occur when the gas itself absorbs radiation. Indirect radiative forcing occurs when chemical
transformations involving the original gas produce a gas or gases that are greenhouse gases, or when a gas
influences other radiatively important processes such as the atmospheric lifetimes of other gases. The reference gas
used is CO2, and therefore GWP weighted emissions are measured in teragrams of CO2 equivalent (Tg CO2 Eq.)15
The relationship between gigagrams (Gg) of a gas and Tg CO2Eq. can be expressed as follows:
( T ^
Tg CO, Eq = (Gg of gas) x (GWP) x ^—
2 V ^ V ' ^1,000 GgJ
where,
Tg CO2Eq. = Teragrams of CO2 Equivalents
13 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot)
(IPCC 2001).
14 Volcanic activity can inject significant quantities of aerosol producing sulfur dioxide and other sulfur compounds into the
stratosphere, which can result in a longer negative forcing effect (i.e., a few years) (IPCC 1996).
15 Carbon comprises 12/44ths of carbon dioxide by weight.
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Gg = Gigagrams (equivalent to a thousand metric tons)
GWP = Global Warming Potential
Tg = 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 2/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 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.
Table 1-2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report
Gas
CO2
CH4b
N2O
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4Fio
C6F14
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
Source: (IPCC 1996)
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 CO2 is not included.
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)
Introduction 1-7
-------
[BEGIN BOX]
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
CO2 radiative forcing and an improved CO2 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
CH4*
N2O
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C4Fio
CsFu
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 from
SAR
TAR
NC
2
(14)
300
(100)
600
NC
500
(20)
600
3,100
200
(800)
2,700
1,600
1,600
(1,700)
AR4
0
4
(12)
3,100
25
700
130
670
(16)
320
3,510
340
890
3,000
1,860
1,900
(1,100)
Source: (IPCC 2007, IPCC 2001)
NC (No Change)
Note: Parentheses indicate negative values.
The GWP of CH4 includes the direct effects and those indirect effects due to the production of tropospheric ozone and
stratospheric water vapor. The indirect effect due to the production of CO2 is not included.
To comply with international reporting standards under the UNFCCC, official emission estimates are reported by
the United States using SAR GWP values. The UNFCCC reporting guidelines for national inventories17 were
updated in 2002 but continue to require the use of GWPs from the SAR so that current estimates of aggregate
greenhouse gas emissions for 1990 through 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 .
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
[END BOX]
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 source category and the unique characteristics of its emissions profile. The individual source leads
determine the most appropriate methodology and collect the best activity data to use in the emission calculations,
based upon their expertise in the source category, as well as coordinating with researchers and contractors familiar
with the sources. A multi-stage process for collecting information from the individual source leads and producing
the Inventory is undertaken annually to compile all information and data.
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.
Introduction 1-9
-------
Once the methodology is in place and the data are collected, the individual source leads calculate emissions and sink
estimates. The source leads then update or create the relevant text and accompanying annexes for the Inventory.
Source leads are also responsible for completing the relevant sectoral background tables of the Common Reporting
Format, conducting quality assurance and quality control (QA/QC) checks, and uncertainty analyses.
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.
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.
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 1996IPCC 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.
[BEGIN BOX]
Box 1-2: IPCC Reference Approach
The UNFCCC reporting guidelines require countries to complete a "top-down" reference approach for estimating
CO2 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.
[END BOX]
Introduction 1-11
-------
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." *8
By definition, key categories include those sources that have the greatest contribution to the absolute level of
national emissions. In addition, when an entire time series of emission estimates is prepared, a thorough
investigation of key categories must also account for the influence of trends of individual source and sink
categories. This analysis culls out source and sink categories that diverge from the overall trend in national
emissions. Finally, a qualitative evaluation of key categories is performed to capture any categories that were not
identified in either of the quantitative analyses.
A Tier 1 approach, as defined in the IPCC's Good Practice Guidance (IPCC 2000), was implemented to identify the
key categories for the United States. This analysis was performed twice; one analysis included sources and sinks
from the Land Use, Land-Use Change, and Forestry (LULUCF) sector, the other analysis did not include the
LULUCF categories.
In addition to conducting Tier 1 level and trend assessments, a qualitative assessment of the source categories, as
described in the IPCC's Good Practice Guidance (IPCC 2000), was conducted to capture any key categories that
were not identified by either quantitative method. One additional key category, international bunker fuels, was
identified using this qualitative assessment. International bunker fuels are fuels consumed for aviation or marine
international transport activities, and emissions from these fuels are reported separately from totals in accordance
with IPCC guidelines. If these emissions were included in the totals, bunker fuels would qualify as a key category
according to the Tier 1 approach. The amount of uncertainty associated with estimation of emissions from
international bunker fuels also supports the qualification of this source category as key.
Table 1-4 presents the key categories for the United States based on the Tier 1 approach (including and excluding
LULUCF categories) using emissions data in this report, and ranked according to their sector and global warming
potential-weighted emissions in 2006. The table also indicates the criteria used in identifying these categories (i.e.,
level, trend, and/or qualitative assessments). Annex 1 of this report provides additional information regarding the
key categories in the United States and the methodologies used to identify them.
Table 1-4: Key Categories for the United States (1990-2006) Based on Tier 1 Approach
2006
Level Trend Level Trend Emissions
Without Without With With (Tg CO2
IPCC Source Categories
Energy
CO2 Emissions from Stationary Combustion - Coal
Mobile Combustion: Road & Other
CO2 Emissions from Stationary Combustion - Gas
CO2 Emissions from Stationary Combustion - Oil
Mobile Combustion: Aviation
CO2 Emissions from Non-Energy Use of Fuels
Mobile Combustion: Marine
CO2 Emissions from Natural Gas Systems
CO2 Emissions from Municipal Solid Waste
Combustion
Gas LULUCF LULUCF LULUCF LULUCF Quala
C02 / / / /
CO2 -f -f -f -f
C02 / / /
CO2 J J J J
CO2 J J J J
C02 / /
CO2 J J J J
CO2 j j j j
C02 / /
Eq.)
2,065.3
1,643.0
1,121.9
594.3
170.6
138.0
42.4
28.5
20.9
18 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
1-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
IPCC Source Categories
Fugitive Emissions from Natural Gas Systems
Fugitive Emissions from Coal Mining
Fugitive Emissions from Petroleum Systems
Mobile Combustion: Road & Other
International Bunker Fuels'3
Industrial Processes
CO2 Emissions from Iron and Steel Production
CO2 Emissions from Cement Manufacture
CO2 Emissions from Ammonia Manufacture and
Urea Application
N2O 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
Direct N2O Emissions from Agricultural Soil
Management
Indirect N2O Emissions from Applied Nitrogen
Waste
CH4 Emissions from Landfills
Land Use, Land Use Change, and Forestry
CO2 Emissions from Forest Land Remaining Forest
Land
CO2 Emissions from Settlements Remaining
Settlements
CO2 Emissions from Cropland Remaining Cropland
CO2 Emissions from Grassland Remaining
Grassland
CO2 Emissions from Landfilled Yard Trimmings
and Food Scraps
CO2 Emissions from Land Converted to Cropland
CH4 Emissions from Forest Land Remaining Forest
Land
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
CH4
CH4
CH4
N2O
Several
CO2
C02
C02
N2O
Several
MFCs
SF6
PFCs
CH4
CH4
N2O
N2O
CH4
C02
C02
CO2
CO2
C02
C02
CH4
Level Trend Level Trend
Without Without With With
LULUCF LULUCF LULUCF LULUCF Quala
/ / / /
/ / / /
/ / / /
/ / / /
j
J J J J
J J J J
J J
J J
J J J J
J J J J
J J
j j
J J J J
J J J
J J J J
J J J J
J J J J
J J
J J
J J
J
•f
j
•f
2006
Emissions
(TgC02
Eq.)
102.4
58.5
28.4
31.1
128.4
49.1
45.7
12.4
5.9
110.4
13.8
13.2
2.5
126.2
41.4
214.7
50.3
125.7
(745.1)
(95.5)
(33.8)
16.2
(10.5)
9.4
24.6
6,807.6
7,017.3
97.0%
5,972.8
6,170.5
96.8%
Qualitative criteria.
Emissions from this source not included in totals.
Note: The Tier 1 approach for identifying key source categories does not directly include assessment of uncertainty in emissions
estimates.
Introduction 1-13
-------
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;
• 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.
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.
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
1.7. Uncertainty Analysis of Emission Estimates
Uncertainty estimates are an essential element of a complete and transparent emissions inventory. Uncertainty
information is not intended to dispute the validity of the inventory estimates, but to help prioritize efforts to improve
the accuracy of future inventories and guide future decisions on methodological choice. While the U.S. Inventory
calculates its emission estimates with the highest possible accuracy, uncertainties are associated to a varying degree
with the development of emission estimates for any inventory. Some of the current estimates, such as those for CO2
emissions from energy-related activities and cement processing, are considered to have minimal uncertainty
associated with them. For some other categories of emissions, however, a lack of data or an incomplete
understanding of how emissions are generated increases the uncertainty surrounding the estimates presented.
Despite these uncertainties, the UNFCCC reporting guidelines follow the recommendation in the 1996IPCC
Guidelines (IPCC/UNEP/OECD/IEA 1997) and require that countries provide single point estimates of uncertainty
for each gas and emission or removal source category. Within the discussion of each emission source, specific
factors affecting the uncertainty associated with the estimates are discussed.
Additional research in the following areas could help reduce uncertainty in the U.S. Inventory:
• Incorporating excluded emission sources. Quantitative estimates for some of the sources and sinks of
greenhouse gas emissions are not available at this time. In particular, emissions from some land-use activities
and industrial processes are not included in the inventory either because data are incomplete or because
methodologies do not exist for estimating emissions from these source categories. See Annex 5 of this report
for a discussion of the sources of greenhouse gas emissions and sinks excluded from this report.
• Improving the accuracy of emission factors. Further research is needed in some cases to improve the accuracy
of emission factors used to calculate emissions from a variety of sources. For example, the accuracy of current
emission factors applied to CH4 and N2O emissions from stationary and mobile combustion is highly uncertain.
• Collecting detailed activity data. Although methodologies exist for estimating emissions for some sources,
problems arise in obtaining activity data at a level of detail in which aggregate emission factors can be applied.
For example, the ability to estimate emissions of SF6 from electrical transmission and distribution is limited due
to a lack of activity data regarding national SF6 consumption or average equipment leak rates.
The overall uncertainty estimate for the U.S. greenhouse gas emissions inventory was developed using the IPCC
Tier 2 uncertainty estimation methodology. An estimate of the overall quantitative uncertainty is shown below, 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.
Table 1-5. Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent)
Gas
C02
CH4
N2O
PFC, HFC & SF6d
2006
Emission
Estimate
(Tg C02 Eq.)
5,983.1
555.3
367.9
147.9
Uncertainty Range Relative to Emission
Estimate"
(Tg C02 Eq.) (%)
Lower
Bound"
5,884.9
508.4
352.2
145.7
Standard
Meanb Deviation
(TgC02Eq.)
Upper Lower Upper
Bound" Bound" Bound"
6,288.6
658.2
449.3
166.3
-2%
-8%
-4%
-1%
5%
19%
22%
12%
6,082.2
576.6
398.4
156.1
105.5
38.9
25.0
5.2
Total 7,054.2 6,999.6 7,439.0 -1% 5% 7,213.3 115.2
Net Emissions 6,170.5 6,059.0 6,615.0 -2% 7% 6,332.3 143.3
Introduction 1-15
-------
(Sources and Sinks)
Notes:
a Range of emission estimates for a 95 percent confidence interval.
b Mean value indicates the arithmetic average of the simulated emission estimates; Standard deviation indicates the extent of
deviation of the simulated values from the mean.
0 The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high
emission estimates for the sub-source categories do not sum to total emissions.
d The overall uncertainty estimate did not take into account the uncertainty in the GWP values for CH4, N2O and high GWP
gases used in the inventory emission calculations for 2006.
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 CRF reporter, serves as a thorough assessment of the anthropogenic
sources and sinks of greenhouse gas emissions for the United States for the time series 1990 through 2006.
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 1996IPCC 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.
Table 1-6: IPCC Sector Descriptions
Chapter/IPCC Sector Activities Included
Energy Emissions of all greenhouse gases resulting from stationary and mobile
energy activities including fuel combustion and fugitive fuel emissions.
Industrial Processes By-product or fugitive emissions of greenhouse gases from industrial
processes not directly related to energy activities such as fossil fuel
combustion.
Solvent and Other Product Emissions, of primarily NMVOCs, resulting from the use of solvents
Use and N2O from product uses.
Agriculture Anthropogenic emissions from agricultural activities except fuel
combustion, which is addressed under Energy.
Land Use, Land-Use Change, Emissions and removals of CO2, CH4, and N2O from forest
and Forestry management, other land-use activities, and land-use change.
Waste Emissions from waste management activities.
Source: (IPCC/UNEP/OECD/IEA 1997)
Within each chapter, emissions are identified by the anthropogenic activity that is the source or sink of the
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
greenhouse gas emissions being estimated (e.g., coal mining). Overall, the following organizational structure is
consistently applied throughout this report:
Chapter/IPCC Sector: Overview of emission trends for each IPCC defined sector
Source category: Description of source pathway and emission trends.
Methodology: Description of analytical methods employed to produce emission estimates and identification of
data references, primarily for activity data and emission factors.
Uncertainty: A discussion and quantification of the uncertainty in emission estimates and a discussion of time-
series consistency.
QA/QC and Verification: A discussion on steps taken to QA/QC and verify the emission estimates, where beyond
the overall U.S. QA/QC plan, and any key findings.
Recalculations: A discussion of any data or methodological changes that 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.
Table 1-7: List of Annexes
ANNEX 1 Key Category Analysis
ANNEX 2 Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of CO2 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3 Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from Stationary
Combustion
3.2. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from Mobile
Combustion and Methodology for and Supplemental Information on Transportation-Related Greenhouse
Gas Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 and CO2 Emissions from Petroleum Systems
3.6. Methodology for Estimating CO2 and N2O Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
3.10. Methodology for Estimating CH4 and N2O Emissions from Manure Management
3.11. Methodology for Estimating N2O Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on Croplands and
Grasslands
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4 IPCC Reference Approach for Estimating CO2 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
Introduction 1-17
-------
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
1-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2. Trends in Greenhouse Gas Emissions
2.1. Recent Trends in U.S. Greenhouse Gas Emissions
In 2006, total U.S. greenhouse gas emissions were 7,054.2 teragrams of carbon dioxide equivalents (Tg CO2 Eq.).l
Overall, total U.S. emissions have risen by 14.7 percent from 1990 to 2006, while the U.S. gross domestic product
has increased by 59 percent over the same period (BEA 2007). Emissions decreased from 2005 to 2006 by 1.1
percent (75.7 Tg CO2 Eq.). The following factors were primary contributors to this decrease: (1) compared to 2005,
2006 had warmer winter conditions, which decreased consumption of heating fuels, as well as cooler summer
conditions, which reduced demand for electricity, (2) restraint on fuel consumption caused by rising fuel prices,
primarily in the transportation sector and (3) increased use of natural gas and renewables in the electric power
sector. 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.
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 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 2006. Emissions from
this source category grew by 19.3 percent (913.8 Tg CO2Eq.) from 1990 to 2006 and were responsible for most of
the increase in national emissions during this period. From 2005 to 2006, these emissions decreased by 1.6 percent
(93.1 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 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).
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
-------
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.
After emissions significantly decreased in 2001 due to the economic slowdown, emissions from fuel combustion
resumed modest growth in 2002, slightly less than the average annual growth rate since 1990. There were a number
of reasons behind this increase. The U.S. economy experienced moderate growth, recovering from weak economic
conditions in 2001. Prices for fuels remained at or below 2001 levels; the cost of natural gas, motor gasoline, and
electricity were all lower—triggering an increase in demand for fuel. In addition, the United States experienced one
of the hottest summers on record, causing a significant increase in electricity use in the residential sector as the use
of air-conditioners increased. Partially offsetting this increased consumption of fossil fuels, however, were
increases in the use of nuclear and renewable fuels. Nuclear facilities operated at the highest capacity on record in
2002. Furthermore, there was a considerable increase in the use of hydroelectric power in 2002 after a very low
output the previous year.
Emissions from fuel combustion continued growing in 2003, at about the average annual growth rate since 1990. A
number of factors played a major role in the magnitude of this increase. The U.S. economy experienced moderate
growth from 2002, causing an increase in the demand for fuels. The price of natural gas escalated dramatically,
causing some electric power producers to switch to coal, which remained at relatively stable prices. Colder winter
conditions brought on more demand for heating fuels, primarily in the residential sector. Though a cooler summer
partially offset demand for electricity as the use of air-conditioners decreased, electricity consumption continued to
increase in 2003. The primary drivers behind this trend were the growing economy and the increase in U.S. housing
stock. Nuclear capacity decreased slightly, for the first time since 1997. Use of renewable fuels rose slightly due to
increases in the use of hydroelectric power and biofuels.
From 2003 to 2004, these emissions increased at a rate slightly higher than the average growth rate since 1990. A
number of factors played a major role in the magnitude of this increase. A primary reason behind this trend was
strong growth in the U.S. economy and industrial production, particularly in energy-intensive industries, causing an
increase in the demand for electricity and fossil fuels. Demand for travel was also higher, causing an increase in
petroleum consumed for transportation. In contrast, the warmer winter conditions led to decreases in demand for
heating fuels, principally natural gas, in both the residential and commercial sectors. Moreover, much of the
increased electricity demanded was generated by natural gas combustion and nuclear power, which moderated the
increase in CO2 emissions from electricity generation. Use of renewable fuels rose very slightly due to increases in
the use biofuels.
Emissions from fuel combustion increased from 2004 to 2005 at a rate slightly lower than the average annual
growth rate since 1990. A number of factors played a role in this slight increase. This small increase is primarily a
result of the restraint on fuel consumption, primarily in the transportation sector, caused by rising fuel prices.
Although electricity prices increased slightly, there was a significant increase in electricity consumption in the
residential and commercial sectors due to warmer summer weather conditions. This led to an increase in emissions
in these sectors with the increased use of air-conditioners. As electricity emissions increased among all end-use
sectors, the fuels used to generate electricity increased as well. Despite a slight decrease in industrial energy-related
emissions, industrial production and manufacturing output actually increased. The price of natural gas escalated
dramatically, causing a decrease in consumption of natural gas in the industrial sector. Use of renewable fuels
decreased slightly due to decreased use of biofuels and decreased electricity output by hydroelectric power plants.
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 by coal
and a greater share generated by natural gas. Coal and natural gas consumption for electricity generation decreased
by 1.3 percent and increased by 6.4 percent, respectively, in 2006, 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
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
Overall, from 1990 to 2006, total emissions of CO2 increased by 914.6 Tg CO2 Eq. (18 percent), while CH4 and
N2O emissions decreased by 50.8 Tg CO2 Eq. (8 percent) and 15.5 Tg CO2 Eq. (4 percent) respectively. During the
same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 57.6 Tg CO2 Eq. (64 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 12 percent
of total emissions in 2006.
Table 2-1 summarizes emissions and sinks from all U.S. anthropogenic sources in weighted units of Tg CO2Eq.,
while unweighted gas emissions and sinks in gigagrams (Gg) are provided in Table 2-2.
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
US Territories
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Natural Gas Systems
Municipal Solid Waste Combustion
Lime Manufacture
Ammonia Manufacture and Urea
Consumption
Limestone and Dolomite Use
Cropland Remaining Cropland
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Phosphoric Acid Production
Zinc Production
Petroleum Systems
Lead Production
Silicon Carbide Production and
Consumption
Land Use, Land-Use Change, and
Forestry (Sink)"
Wood Biomass and Ethanol
Consumption1*
International Bunker Fuelsb
CH4
1990s
5,068.5s
4,724.1s"
l,809.6g
1,485.1s
844.9s
340.1s
216.1s
28.3^
117.2^
86.2^
33. 3'm
33.7s
10.9^
12.0s
16.9^
5.5s
7.1^
4.1^
6.8s"
2.2m
1.2s
1.4^
2.2^
1.5s
0.9^
OAm
0.3&.
°-4B
(737.7)M
219.3M
113.7m
606.1s
i 1995=
1 5,394.2^
i 5,032.4=
1 1,939.3 =
i 1,599.4=
1 876.5^
1 356.5^
1 225.8!
i 35.0=
1 133.2!
1 74.7^
1 36.8!
= 33.8=
1 15-71
z^ i /i ri ™™~~
= IT-.UZZZ
1 17.811
1 7.411
E 7 Q^
1 4.311
5fj ==
__ . 1 ^33
20 ==
_ .0 =
^ ^^
_ .-> ^=
^z I/I •=~
E 2.0=
1 I-5!
1 l.Oll
1 0.3^
1 0.3l
1 0.3!
1 (775. 3)M
1 236.8M
1 100.6M
1 598.91
i 2000
1 5,939.7
i 5 577 1
1 2,282.3
i 1,798.2
i 860.3
1 372.1
1 228.0
1 36.2
1 141.4
1 66.6
1 41.2
1 29.4
1 17.5
1 14.9
1 16.4
1 6.0
1 7.5
1 4.2
1 6.1
1 3.0
1 1.8
1 1.4
1 1.9
1 1.4
1 1-1
1 0.3
1 0.3
1 0.2
1 (673.6)
1 227.3
1 101.1
1 574.3
2001
5,846.
5507
2,244.
1,775.
852.
363.
222.
49.
131.
59.
41.
28.
18.
14.
13.
5.
7.
4.
4.
2.
1.
0.
1.
1.
1.
0.
0.
0.
2
4
3
6
5
6
3
0
9
2
4
8
0
3
3
7
8
1
4
8
7
8
5
3
0
3
3
2
f750.2;
203.
97.
558.
2
6
8
2002
5,908.
5 564
2,253.
1,828.
854.
360.
222.
44.
135.
55.
42.
29.
18.
13.
14.
5.
8.
4.
4.
2.
1.
1.
1.
1.
0.
0.
0.
0.
(826.1
6
8
7
9
8
5
8
0
9
9
9
6
5
7
2
9
5
1
5
9
8
0
o
6
o
6
9
o
J
3
2
y
204.4
89.
563.
;
5
2003
5,952.7
56170
2,283.1
1,807.6
856.0
382.9
236.5
51.0
131.8
54.7
43.1
28.4
19.1
14.5
12.5
4.8
8.3
4.1
4.5
2.8
1.8
1.3
1.3
1.4
0.5
0.3
0.3
0.2
(860.9)
209.5
103.6
559.4
2004
6,038.2
5681 4
2,314.9
1,856.4
857.7
368.3
230.6
53.5
148.9
52.8
45.6
28.1
20.1
15.2
13.2
6.7
7.6
4.2
4.2
2.9
2.1
1.2
1.4
1.4
0.5
0.3
0.3
0.2
(873.7)
224.8
119.0
545.6
2005
6,074.3
5731 0
2,380.2
1,869.8
847.3
358.5
221.9
53.2
139.1
46.6
45.9
29.5
20.7
15.1
12.8
7.4
7.9
4.2
4.2
2.8
1.8
1.3
1.4
1.4
0.5
0.3
0.3
0.2
(878.6)
227.4
122.6
539.7
2006
5,983.1
56379
2,328.2
1,856.0
862.2
326.5
210.1
54.9
138.0
49.1
45.7
28.5
20.9
15.8
12.4
8.6
8.0
4.2
3.9
2.6
1.9
1.6
1.5
1.2
0.5
0.3
0.3
0.2
(883. 7)
234.7
127.1
555.3
Trends in Greenhouse Gas Emissions 2-3
-------
Enteric Fermentation
Landfills
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Forest Land Remaining Forest Land
Wastewater Treatment
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal
Mines
Mobile Combustion
Composting
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural
Residues
Ferroalloy Production
Silicon Carbide Production and
Consumption
International Bunker Fuelsb
N2O
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
Adipic Acid Production
N2O from Product Uses
Forest Land Remaining Forest Land
Composting
Settlements Remaining Settlements
Field Burning of Agricultural
Residues
Municipal Solid Waste Combustion
International Bunker Fuelsb
HFCs
Substitution of Ozone Depleting
Substances0
HCFC-22 Production
Semiconductor Manufacture
PFCs
Semiconductor Manufacture
Aluminum Production
SF6
Electrical Transmission and
Distribution
Magnesium Production and
Processing
Semiconductor Manufacture
Total
Net Emissions (Sources and Sinks)
126.9^
149.6s
124.7s"
84.1s
3LOs
33.9s
4.5s
23.0s
7AM
7. is
6.0^
4.7^
0.3s
0.9s
1.3s
0.7^
+s
+s
383.4s
269.4s"
43.5s
17.0s
12.8s
12.1s
6.3s
15.3s
4.4s
0.5'M
0.4s
1.0^
0.4^
0.5^
1 132
1 144
1 128
1 67
1 35
1 32
1 4
1 24
1 7
1 7
1 8
1 4
1 0
1 1
1 1
1 o
.3 =
.0=
.1 =
.1 =
.2=
•0=
•7=
• 3 =
.2=
.6=
.21
.3 =
.7=
.1 =
•3 =
+=
1 o.m
1 395
1 264
1 53
1 18
1 13
1 12
1 6
1 17
1 4
1 0
1 °
1 1
1 0
1 o
.6=
.8=
.4=
.9=
•4=
• 8=
• 9=
.3 =
.6=
•61
8^=
=
.2=
.41
•5 =
7.0=1 0.9=
36.9Ji
0.3^
36.4S
0.2^
20.8s
2.2s
18.5s
1^ -75=
JZ. /£=
26.7^
5.4^
0.5^
6,148.3s
5,410.6s
1 61
1 28
1 33
1 °
1 15
1 3
1 11
1 28
1 21
1 5
1 o
1 6,494
= 5,718
.8=
.5^
.OH
•31
.6=
.8=
.8=
•0=
• 5M
.6^
.9=
•0=
.7=
1 124.6
1 120.8
1 126.5
1 60.4
1 38.8
1 30.3
1 19.0
1 24.6
1 6.6
1 7.5
1 7.4
1 3.4
1 1.3
1 1.2
1 1-2
1 0.8
1 +
= +
1 0.1
1 385.9
1 262.1
1 52.5
1 18.6
1 14.6
1 13.7
1 7.6
1 6.2
1 4.9
1 2.2
1 1.4
1 I-2
1 0.5
1 0.4
1 0.9
1 100.1
1 71.2
1 28.6
1 0.3
1 13.5
1 4.9
1 8.6
1 19.1
1 15.1
1 3.0
1 LI
1 7,032.6
= 6,359.0
123.6
117.6
125.3
60.3
40.2
30.2
9.4
24.2
6.2
7.6
6.7
3.3
1.3
1.1
1.1
0.8
+
+
0.1
392.9
277.0
49.9
15.1
14.1
14.0
7.8
5.1
4.9
1.3
1.4
1.4
0.5
0.4
0.9
97.9
78.0
19.7
0.2
7.0
3.5
3.5
18.7
15.0
2.9
0.7
6,921.3
6,171.1
123.8
120.1
124.9
56.8
41.3
29.9
16.4
24.1
6.2
6.8
6.2
3.0
1.3
1.1
1.0
0.7
+
+
0.1
376.1
262.0
45.9
16.4
14.0
14.0
7.6
6.1
4.4
2.0
1.4
1.5
0.4
0.4
0.8
106.3
85.0
21.1
0.2
8.7
3.5
5.2
18.0
14.4
2.9
0.7
6,981.2
6,154.4
124.6
125.6
123.3
56.9
40.7
29.2
8.7
23.9
6.4
6.9
6.0
2.7
1.5
1.1
1.0
0.8
+
+
0.1
356.6
247.3
42.3
15.4
14.3
13.6
7.7
6.3
4.4
1.2
1.6
1.5
0.4
0.4
0.9
104.5
92.0
12.3
0.2
7.1
3.3
3.8
18.1
13.8
3.4
0.8
6,998.2
6,137.3
122.4
122.6
114.0
59.8
40.1
28.7
6.9
24.0
6.5
7.6
5.8
2.6
1.6
1.2
1.0
0.9
+
+
0.1
353.5
246.9
39.7
15.2
14.6
13.8
7.8
5.9
4.4
1.1
1.7
1.6
0.5
0.4
1.1
116.6
99.1
17.2
0.2
6.1
3.3
2.8
18.0
13.9
3.2
0.8
7,078.0
6,204.3
124.
123.
102.
57.
41.
28.
12.
23.
6.
6.
5.
2.
1.
1.
1.
0.
5
7
5
1
8
3
3
8
5
8
6
5
6
1
0
9
+
+
0.2
370.
265.
36.
15.
14.
13.
8.
5.
4.
1.
1.
1.
0.
0.
1.
121.
105.
15.
0.
6.
3.
3.
18.
14.
3.
1.
7,129.
6,251.
1
2
3
8
8
9
0
9
4
6
7
5
5
4
;
4
4
8
2
2
2
0
2
0
3
0
9
3
126.2
125.7
102.4
58.5
41.4
28.4
24.6
23.9
6.2
5.9
5.4
2.4
1.6
1.0
0.9
0.8
+
+
0.2
367.9
265.0
33.1
15.6
14.5
14.3
8.1
5.9
4.4
2.8
1.8
1.5
0.5
0.4
1.1
124.5
110.4
13.8
0.3
6.0
3.6
2.5
17.3
13.2
3.2
1.0
7,054.2
6,170.5
+ Does not exceed 0.05 Tg CO2 Eq.
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
a The net CO2 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.
0 Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)
Gas/Source
CO2
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
US Territories
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Natural Gas Systems
Municipal Solid Waste
Combustion
Lime Manufacture
Ammonia Manufacture
and Urea Consumption
Limestone and Dolomite
Use
Cropland Remaining
Cropland
Soda Ash Manufacture
and Consumption
Aluminum Production
Petrochemical
Production
Titanium Dioxide
Production
Carbon Dioxide
Consumption
Ferroalloy Production
Phosphoric Acid
Production
Zinc Production
Petroleum Systems
Lead Production
Silicon Carbide
Production and
Consumption
Land Use, Land-Use
Change, and Forestry
(Sink)"
Wood Biomass and
Ethanol Consumption11
International Bunker
Fuels*
CH,
Enteric Fermentation
Landfills
Natural Gas Systems
Coal Mining
Manure Management
1990
5,068,472
4,724,146
1,809,614
1,485,057
844,937
340,109
216,144
28,285
117,170
86,220
33,278
33,729
10,950
12,004
I 2000
5,939,726
5,577,072
2,282,278
1,798,164
860,325
372,083
228,027
36,195
141,427
66,609
41,190
29,390
17,518
14,872
16,889* 16,402
§
5,533| 5,960
1
7,084| 7,541
§
4,14l| 4,181
6,83 1| 6,086
1
2,22 1| 3,004
1
1,195| 1,752
§
l,416l 1,421
2,152| 1,893
1,529
949
376
285
1,382
1,140
325
311
§
1
375 | 248
§
1
(737,677)% (673,608)
§
219,341% 227,276
§
113,683% 101,125
28,86ll 27,346
6,044l 5,933
7,124| 5,751
5,937l 6,024
4,003 1 2,874
15474| 1,847
2001
5,846,151
5,507,406
2,244,279
1,775,636
852,494
363,629
222,341
49,027
131,887
59,249
41,357
28,793
17,971
14,261
13,305
5,733
7,825
4,147
4,381
2,787
1,697
829
1,459
1,264
986
325
291
199
(750,191)
203,163
97,563
26,608
5,886
5,598
5,968
2,874
1,915
2002
5,908,568
5,564,795
2,253,729
1,828,910
854,822
360,492
222,828
44,014
135,857
55,938
42,898
29,629
18,458
13,652
14,194
5,885
8,549
4,139
4,490
2,857
1,824
989
1,349
1,338
937
320
286
183
(826,758)
204,351
89,101
26,832
5,896
5,720
5,946
2,707
1,964
2003
5,952,650
5,617,047
2,283,069
1,807,591
856,042
382,864
236,452
51,030
131,772
54,744
43,082
28,445
19,058
14,458
12,488
4,753
8,260
4,111
4,503
2,777
1,839
1,311
1,305
1,382
507
316
289
202
(860,912)
209,537
103,583
26,637
5,931
5,981
5,874
2,709
1,938
2004
6,038,211
5,681,363
2,314,907
1,856,373
857,722
368,258
230,617
53,486
148,931
52,771
45,603
28,122
20,097
15,154
13,241
6,702
7,555
4,205
4,231
2,895
2,064
1,198
1,419
1,395
477
302
263
224
(873,660)
224,825
118,975
25,979
5,828
5,838
5,426
2,846
1,908
2005
6,074,306
5,731,045
2,380,222
1,869,848
847,328
358,515
221,921
53,213
139,057
46,627
45,910
29,462
20,673
15,131
12,817
7,397
7,854
4,228
4,207
2,804
1,755
1,321
1,392
1,386
465
287
266
219
(878,605)
227,366
122,580
25,698
5,928
5,890
4,880
2,717
1,988
2006
5,983,108
5,637,931
2,328,153
1,856,047
862,187
326,522
210,140
54,882
137,980
49,119
45,739
28,504
20,922
15,825
12,376
8,615
8,012
4,162
3,923
2,573
1,876
1,579
1,505
1,167
529
293
270
207
(883,665)
234,726
127,097
26,442
6,010
5,985
4,877
2,784
1,972
Trends in Greenhouse Gas Emissions 2-5
-------
Petroleum
Systems 1,612
Forest Land Remaining
Forest Land 213
Wastewater Treatment 1 ,096
Stationary
Combustion 353
Rice Cultivation 339
Abandoned Underground
Coal Mines 2885
Mobile Combustion 224 \
Composting 155
1,442 1,436
904 448
1,173 1,150
316 295
357 364
350 319
i 162 157
i 60 60
1,422
780
1,148
295
325
293
141
61
1,390
416
1,140
306
328
284
131
69
1,368
330
1,141
311
360
276
126
74
1,346
586
1,131
308
326
265
119
75
1,354
1,169
1,136
296
282
257
112
75
Petrochemical |
Production 4 1 5
Iron and Steel Production 63 \
i 58 51
i 58 51
52
48
51
49
55
50
51
45
48
45
Field Burning of |
Agricultural Residues 33 \
Ferroalloy
Production 1 5
1 38 37
i ! +
34
+
38
+
42
+
41
+
39
+
Silicon Carbide |
Production and |
Consumption 1 \
1 1 +
+
+
+
+
+
International Bunker i
Fuels?
N2O
sl
1,237|
i 6 5
i 1,245 1,267
4
1,213
6
1,150
7
1,140
7
1,194
7
1,187
Agricultural Soil |
Management 869
Mobile Combustion 140
Nitric Acid Production 55
Stationary
Combustion 41
Manure Management 39
Wastewater Treatment 20
Adipic Acid Production 49
N2O from
Product Uses 145
i 845 894
169 161
60 49
47 46
44 45
24 25
20 16
i 16 16
845
148
53
45
45
25
20
14
798
137
50
46
44
25
20
14
796
128
49
47
44
25
19
14
855
117
51
48
45
26
19
14
855
107
50
47
46
26
19
14
Forest Land Remaining |
Forest Land 2|
Composting 1 5
i 7 4
i 4 5
6
5
4
5
3
6
5
6
9
6
Settlements Remaining |
Settlements 3\
i 4 5
5
5
5
5
5
Field Burning of |
Agricultural Residues 1 5
Municipal
Solid Waste |
Combustion 25
i ! !
i i i
1
1
1
1
2
1
2
1
2
1
International Bunker <=
Fuels'"
HFCs
35
Ml
i J 3
| M M
3
M
3
M
3
M
4
M
4
M
Substitution of Ozone j
Depletin
HCFC-22
g Substancesc Ml
Production 35
1 M M
i 2 2
M
2
M
1
M
1
M
1
M
1
Semiconductor |
Manufacture +5
PFCs
Ms
i + +
i M M
+
M
+
M
+
M
+
M
+
M
Semiconductor |
Manufacture MJ
Aluminum Production M|
SF6
Electrical
15
Transmission 5
i M M
I M M
i i i
and Distribution 1| 1 1
M
M
1
1
M
M
1
1
M
M
1
1
M
M
1
1
M
M
1
1
Magnesium Production |
and Processing +\
i + +
+
+
+
+
+
Semiconductor |
Manufacture +5
i + +
+
+
+
+
+
+ Does not exceed 0.5 Gg.
M Mixture of multiple gases
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
a The net CO2 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.
0 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. Over the sixteen-year period of 1990 to 2006, total emissions in the Energy, Industrial Processes,
and Agriculture sectors grew by 873.0 Tg CO2 Eq. (17 percent), 21.0 Tg CO2Eq. (7 percent), and 6.6 Tg CO2Eq. (1
percent), respectively. Emissions decreased in the Waste and Solvent and Other Product Use sectors by 18.6 Tg
CO2 Eq. (10 percent) and less than 0.02 Tg CO2 Eq. (less than 1 percent), respectively. Over the same period,
estimates of net C sequestration in the Land Use, Land-Use Change, and Forestry sector increased by 122.2 Tg CO2
Eq. (17 percent).
Figure 2-4: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.)
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and
Forestry (Emissions)
Waste
Total Emissions
Net CO2 Flux from Land Use,
Land-Use Change, and Forestry
(Sinks)*
Net Emissions (Sources and
Sinks)
1990=
5,203.9 =
299.9 =
4.4 =
447.5 =
13.1 =
179.6 =
6,148.3 =
(737.7)=
5,410.6 =
m
H 5,529.6 =
m 315.7=
^
m 453.8 =
^ 13.6 =
^ 176.8 =
m 6,494.0=
m (775.3)=
m 5,718.7=
m 2000
HI 6,067.8
^ 326.5
^ 4.9
^ 447.9
^ 30.0
^ 155.6
m 7,032.6
m (673.6)
^ 6,359.0
2001
5,982.8
297.9
4.9
463.7
20.0
152.1
6,921.3
(750.2)
6,171.1
2002
6,036.3
308.6
4.4
449.0
28.4
154.5
6,981.2
(826.8)
6,154.4
2003
6,078.3
301.2
4.4
434.3
19.7
160.3
6,998.2
(860.9)
6,137.3
2004
6,150.9
315.9
4.4
432.1
17.1
157.7
7,078.0
(873.7)
6,204.3
2005
6,174.4
315.5
4.4
453.6
23.2
158.7
7,129.9
(878.6)
6,251.3
2006
6,076.9
320.9
4.4
454.1
36.9
161.0
7,054.2
(883.7)
6,170.5
* The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only
included in net emissions total.
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
Energy
Energy-related activities, primarily fossil fuel combustion, accounted for the vast majority of U.S. CO2 emissions
for the period of 1990 through 2006. In 2006, approximately 83 percent of the energy consumed in the United
States (on a Btu basis) was produced through the combustion of fossil fuels. The remaining 17 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 also responsible for CH4 and N2O emissions (37
percent and 13 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.
Figure 2-5: 2006 Energy Chapter Greenhouse Gas Sources
Figure 2-6: 2006 U.S. Fossil C Flows (Tg CO2 Eq.)
Trends in Greenhouse Gas Emissions 2-7
-------
Table 2-4: Emissions from Energy (Tg CO2 Eq.)
Gas/Source
CO2
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
US Territories
Non-Energy Use of Fuels
Natural Gas Systems
Municipal Solid Waste
Combustion
Petroleum Systems
Biomass — Wood*
International Bunker Fuels*
Biomass — Ethanol *
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal
Mines
Mobile Combustion
International Bunker Fuels*
N2O
Mobile Combustion
Stationary Combustion
Municipal Solid Waste
Combustion
International Bunker Fuels*
Total
1990^
4,886.4 =
4,724.
1 =
1,809.6 =
1,473.
849.
344.
218.
28.
117.
33.
10.
0.
215.
113.
4.
260.
124.
84.
33.
5 =
9l
4^
5^
•} ^^
j =
2Ji
71
9!
4^
2M
7=1
2Ji
7M
1M
m
9M
7.4H
6.
0=1
4.7^
0.
56.
43.
12.
0.
;.
5,203.
7 =
8^
5^
8^=
=
5^
oM
9M
= 1995m
1 5,215.5i
i 5,032.4p
i l,939.3p
i l,590.2i
i 880.6i
i 359.9i
i 227.5i
i 35.0i
i 133.2i
1 33-8i
1 15. 7|
1 0-3i
1 229. im
1 ioo.6m
1 7.7m
1 246-8l
1 128. lp
1 67. li
1 32.0i
1 7.2|
1 8.2p
1 4.3i
1 o.im
1 67.3i
1 53.4i
1 13-4i
1 °-5l
1 o.9m
1 5,529.6i
1 2000
1 5,765.7
1 5,577.1
1 2,283.1
1 1,801.5
1 858.8
1 385.0
1 237.6
1 51.0
1 141.4
1 29.4
1 17.5
1 0.3
1 218.1
I 101.1
1 9.2
1 234.5
1 126.5
1 60.4
1 30.3
1 6.6
1 7.4
1 3-4
1 0.1
1 67.5
1 52.5
1 14-6
1 0.4
1 0.9
1 6,067.8
2001
5,686.4
5,507.4
2,314.9
1,849.3
861.0
370.8
231.9
53.5
131.9
28.8
18.0
0.3
193.5
97.6
9.7
232.0
125.3
60.3
30.2
6.2
6.7
3.3
0.1
64.4
49.9
14.1
0.4
0.9
5,982.8
2002
5,749.1
5,564.8
2,380.2
1,862.6
850.9
360.9
223.2
53.2
135.9
29.6
18.5
0.3
192.8
89.1
11.5
226.9
124.9
56.8
29.9
6.2
6.2
3.0
0.1
60.4
45.9
14.0
0.4
0.8
6,036.3
2003
5,796.6
5,617.0
2,328.2
1,848.7
866.1
328.7
211.4
54.9
131.8
28.4
19.1
0.3
193.8
103.6
15.7
224.6
123.3
56.9
29.2
6.4
6.0
2.7
0.1
57.1
42.3
14.3
0.4
0.9
6,078.3
2004
5,878.8
5,681.
2,283.
1,801.
858.
385.
237.
51.
148.
28.
20.
0.
205.
4
1
5
8
0
6
0
9
1
1
3
;
119.0
19.
217.
114.
59.
28.
6.
5.
2.
7
4
0
8
7
5
8
6
0.1
54.
39.
14.
0.
1.
6,150.
7
7
6
4
;
9
2005
5,920.5
5,731.0
2,314.9
1,849.3
861.0
370.8
231.9
53.5
139.1
29.5
20.7
0.3
204.8
122.6
22.6
202.3
102.5
57.1
28.3
6.5
5.6
2.5
0.2
51.5
36.3
14.8
0.4
1.1
6,174.4
2006
5,825.6
5,637.9
2,380.2
1,862.6
850.9
360.9
223.2
53.2
138.0
28.5
20.9
0.3
204.4
127.1
30.3
203.3
102.4
58.5
28.4
6.2
5.4
2.4
0.2
48.0
33.1
14.5
0.4
1.1
6,076.9
* These values are presented for informational purposes only and are not included in totals or are already accounted for in other
source categories.
Note: Totals may not sum due to independent rounding.
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 electricity generation sector consists of privately and publicly owned establishments that generate, transmit,
distribute, or sell electricity primarily for use by the public and that meet EIA's definition of an electric utility (EIA
does not include nonutility power producers in this sector). 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
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity
Generation
1990 =
1,488.1 =
1,485.1 =
3.0^
1,527.5 =
844.9^
682.5^
929.5 =
340.1 =
589.4^
750.8^
216.1 =
534.7^
28.3^
4,724.1 =
1,809.6 =
=
I 1,602.5 =
I 1,599.4 =
I
I 1,589.5 =
I 876.5^
I 713.1 =
=
= 356.5 =
I 639.0^
I 810.0^
=
I 584.2^
I
= 5,032.4 =
I 1,939.3 =
= 2000
1 1,801
1 1,798
i 3
1 1,645
= 860
1 784
= 1,129
= 372
1 757
1 964
= 228
1 736
1 36
= 5,577
1 2,282
.6
.2
.4
.1
.3
.7
.7
.1
.6
.6
.0
.6
.2
.1
.3
2001
1,779.2
1,775.6
3.6
1,583.9
852.5
731.4
1,121.8
363.6
758.1
973.5
222.3
751.1
49.0
5,507.4
2,244.3
2002
1,832.3
1,828.9
1
1
5
2
3.4
,572.5
854.8
717.7
,145.6
360.5
785.1
970.3
222.8
747.5
44.0
,564.8
,253.7
2003
1,811.8
1,807.6
4.2
1,592.1
856.0
736.1
1,178.3
382.9
795.4
983.8
236.5
747.3
51.0
5,617.0
2,283.1
2004
1,860.9
1,856.4
4.5
1,596.8
857.7
739.0
1,173.1
368.3
804.9
997.1
230.6
766.5
53.5
5,681.4
2,314.9
2005
1,874.5
1,869.8
4.7
1,579.6
847.3
732.3
1,206.4
358.5
847.9
1,017.3
221.9
795.4
53.2
5,731.0
2,380.2
2006
1,861.0
1,856.0
4.9
1,567.1
862.2
704.9
1,151.9
326.5
825.4
1,003.0
210.1
792.9
54.9
5,637.9
2,328.2
Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated
based on aggregate national electricity consumption by each end-use sector.
Figure 2-7: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Figure 2-8: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
The main driver of emissions in the energy sector is CO2 from fossil fuel combustion. The transportation end-use
sector accounted for 1,861.0 Tg CO2 Eq. in 2006, 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 28
percent of CO2 emissions from fossil fuel combustion. The residential and commercial end-use sectors accounted
for an average 20 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 energy source categories over the
sixteen-year period from 1990 through 2006 included the following:
Total CO2 emissions from fossil fuel combustion increased from 4,724.1 Tg CO2 Eq. to 5,637.9 Tg CO2 Eq
19.3 percent total increase over the sixteen-year period. From 2005 to 2006, these emissions decreased by 93.1
Tg CO2 Eq. (1.6 percent).
CO2 emissions from non-energy use of fossil fuels have increased 20.8 Tg CO2 Eq. (18 percent) from 1990
through 2006. Emissions from non-energy uses of fossil fuels were 138.0 Tg CO2 Eq. in 2006, which
constituted 2.4 percent of overall fossil fuel CO2 emissions and 2.3 percent of total national CO2 emissions,
' Note that electricity generation is the largest emitter of CO2 when electricity is not distributed among end-use sectors.
Trends in Greenhouse Gas Emissions 2-9
-------
approximately the same proportion as in 1990.
• CH4 emissions from natural gas systems were 102.4 Tg CO2 Eq. in 2006; emissions have declined by 22.3 Tg
CO2 Eq. (18 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 58.5 Tg CO2 Eq. This decline of 25.6 Tg CO2 Eq. (30 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 2006, N2O emissions from mobile combustion were 33.1 Tg CO2 Eq. (approximately 9 percent of U. S. N2O
emissions). From 1990 to 2006, N2O emissions from mobile combustion decreased by 24 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 municipal solid waste combustion (20.9 Tg CO2 Eq. in 2006) increased by 10.0 Tg CO2
Eq. (91 percent) from 1990 through 2006, as the volume of plastics and other fossil carbon-containing materials
in municipal solid waste grew.
Industrial Processes
Emissions are produced as a by-product of many non-energy-related industrial process activities. For example,
industrial processes can chemically transform raw materials, which often release waste gases such as CO2, CH4, and
N2O. These processes include iron and steel production, cement manufacture, ammonia manufacture and urea
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 (see Figure 2-9).
Additionally, emissions from industrial processes release HFCs, PFCs and SF6. Table 2-6 presents greenhouse gas
emissions from industrial processes by source category.
Figure 2-9: 2006 Industrial Processes Chapter Greenhouse Gas Sources
Table 2-6: Emissions from Industrial Processes (Tg CO2 Eq.)
Gas/Source
CO2
Iron and Steel Production
Cement Manufacture
Lime Manufacture
Ammonia Manufacture & Urea
Consumption
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Phosphoric Acid Production
Zinc Production
1990^
175.0^
33.3^=
6.8^
2.2^
1.2^
1
1 171.6^
1
1
1 14.0^
1 •
1 17.8^
1
1 •
1
1
2O^^=
.0^=
1
1
1
1
1
S 2000
1 166.5
1 66.6
1 41.2
1 14-9
1 16.4
1 6-°
1 4.2
1 6.1
1 3.0
1 .8
1 -4
1 .9
1 .4
1 .1
200
151.
59.
41.
14.
13.
5.
4.
4.
2.
1.
0.
1.
1.
1.
1
9
2
4
3
3
7
1
4
8
7
8
5
3
0
200
151.
55.
42.
13.
14.
5.
4.
4.
2.
1.
1.
1.
1.
0.
2
0
9
9
7
2
9
1
5
9
8
0
3
3
9
2003
147.8
54.7
43.1
14.5
12.5
4.8
4.1
4.5
2.8
1.8
1.3
1.3
1.4
0.5
2004
151.8
52.8
45.6
15.2
13.2
6.7
4.2
4.2
2.9
2.1
1.2
1.4
1.4
0.5
2005
145.9
46.6
45.9
15.1
12.8
7.4
4.2
4.2
2.8
1.8
1.3
1.4
1.4
0.5
2006
149.5
49.1
45.7
15.8
12.4
8.6
4.2
3.9
2.6
1.9
1.6
1.5
1.2
0.5
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Lead Production
Silicon Carbide Production
and Consumption
CH4
Petrochemical Production
Iron and Steel Production
Ferroalloy Production
Silicon Carbide Production
and Consumption
N2O
Nitric Acid Production
Adipic Acid Production
HFCs
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Semiconductor Manufacture
PFCs
Semiconductor Manufacture
Aluminum Production
SF6
Electrical Transmission and
Distribution
Magnesium Production and
Processing
Semiconductor Manufacture
Total
ii.om
15.3m
36.4p
0.2^
20.8^
2.2^
18.5^
32.7^
0.5^
299.9^
3
1 •
1
1
1 1.1^
1
1
1 •
1
1
1
1 17.3^
1
1 •
1
1 33.0^
1
1
1
3 11 oSEEE
1
1 •
1
1 •
1
1
1 315.7^
1 °-3
! 0.2
1 2.5
! 1.2
1 L2
1 +
1 +
1 24.8
1 18-6
1 6.2
1 ioo-i
1 7L2
1 28-6
1 0.3
1 13.5
1 4.9
1 8-6
1 19-1
1 15-!
1 3.0
1 1.1
3 326.5
0.3
0.2
2.2
1.1
1.1
+
+
20.2
15.1
5.1
97.9
78.0
19.7
0.2
7.0
3.5
3.5
18.7
15.0
2.9
0.7
297.9
0.3
0.2
2.1
1.1
1.0
+
+
22.4
16.4
6.1
106.3
85.0
21.1
0.2
8.7
3.5
5.2
18.0
14.4
2.9
0.7
308.6
0.3
0.2
2.1
1.1
1.0
+
+
21.7
15.4
6.3
104.5
92.0
12.3
0.2
7.1
o o
J.J
3.8
18.1
13.8
3.4
0.8
301.2
0.3
0.2
2.2
1.2
1.0
+
+
21.2
15.2
5.9
116.6
99.1
17.2
0.2
6.1
3.3
2.8
18.0
13.9
3.2
0.8
315.9
0.3
0.2
2.0
1.1
1.0
+
+
21.7
15.8
5.9
121.4
105.4
15.8
0.2
6.2
3.2
3.0
18.2
14.0
3.3
1.0
315.5
0.3
0.2
2.0
1.0
0.9
+
+
21.6
15.6
5.9
124.5
110.4
13.8
0.3
6.0
3.6
2.5
17.3
13.2
3.2
1.0
320.9
+ Does not exceed 0.05 Tg CO2 Eq.
a Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Overall, emissions from industrial processes increased by 7.0 percent from 1990 to 2006 despite decreases in
emissions from several industrial processes, such as iron and steel, 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 sixteen-year period
from 1990 through 2006 included the following:
• HFC emissions from ODS substitutes have been increasing from small amounts in 1990 to 110.4 Tg CO2 Eq. in
2006. 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.
• CO2 and CH4 emissions from iron and steel production increased by 5.2 percent to 50.1 Tg CO2 Eq. in 2006,
but have declined overall by 37.5 Tg CO2 Eq. (42.8 percent) from 1990 through 2006, due to restructuring of
the industry, technological improvements, and increased scrap utilization.
• PFC emissions from aluminum production decreased by 87 percent (16.1 Tg CO2 Eq.) from 1990 to 2006, due
to both industry emission reduction efforts and lower domestic aluminum production.
• N2O emissions from adipic acid production were 5.9 Tg CO2 Eq. in 2006, 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 Tg CO2 Eq. annually since 1998.
Trends in Greenhouse Gas Emissions 2-11
-------
• CO2 emissions from ammonia manufacture and urea consumption (12.4 Tg CO2 Eq. in 2006) have decreased by
4.5 Tg CO2 Eq. (27 percent) since 1990, due to a decrease in domestic ammonia manufacture. This decrease in
ammonia manufacture can be attributed to market fluctuations and high natural gas prices.
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, 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 2006 (see Table 2-7).
Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.)
Gas/Source
N2O
N2O 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
2001
4.9
4.9
4.9
2002
4.4
4.4
4.4
2003
4.4
4.4
4.4
2004
4.4
4.4
4.4
2005
4.4
4.4
4.4
2006
4.4
4.4
4.4
• In 2006, N2O emissions from product uses constituted 1 percent of U.S. N2O emissions. From 1990 to 2006,
emissions from this source category decreased by less than 1 percent, though slight increases occurred in
intermediate years.
Agriculture
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes, including
the following source categories: enteric fermentation in domestic livestock, livestock manure management, rice
cultivation, agricultural soil management, and field burning of agricultural residues.
In 2006, agricultural activities were responsible for emissions of 454.1 Tg CO2 Eq., or 6.4 percent of total U.S.
greenhouse gas emissions. CH4 and N2O were the primary greenhouse gases emitted by agricultural activities. CH4
emissions from enteric fermentation and manure management represented about 23 percent and 7 percent of total
CH4 emissions from anthropogenic activities, respectively, in 2006. Agricultural soil management activities, such
as fertilizer application and other cropping practices, were the largest source of U.S. N2O emissions in 2006,
accounting for 72 percent.
Figure 2-10: 2006 Agriculture Chapter Greenhouse Gas Sources
Table 2-8: Emissions from Agriculture (Tg CO2 Eq.)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural
Residues
Total
1990=
165.7^
126.9=
31.0=
7.1^1
0.7 =
281.8 =
269.4 =
12.1 =
0.4 =
447.5^
i
1 175.8^
1 132.3^
1
|
1 •
1
1
|
i
1 •
1
1 453.8^
1 2000
3 171.7
3 124.6
1 38.8
i 7.5
i 0.8
1 276.3
i 262.1
i 13.7
i 0.5
1 447.9
2001
172.2
123.6
40.2
7.6
0.8
291.5
277.0
14.0
0.5
463.7
2002
172.6
123.8
41.3
6.8
0.7
276.4
262.0
14.0
0.4
449.0
2003
173.0
124.6
40.7
6.9
0.8
261.3
247.3
13.6
0.4
434.3
2004
170.9
122.4
40.1
7.6
0.9
261.2
246.9
13.8
0.5
432.1
2005
174.0
124.5
41.8
6.8
0.9
279.6
265.2
13.9
0.5
453.6
2006
174.4
126.2
41.4
5.9
0.8
279.8
265.0
14.3
0.5
454.1
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Note: Totals may not sum due to independent rounding.
Some significant trends in U.S. emissions from Agriculture include the following:
• Agricultural soils produced approximately 72 percent of N2O emissions in the United States in 2006.
Estimated emissions from this source in 2006 were 265.0 Tg CO2 Eq. Annual N2O emissions from
agricultural soils fluctuated between 1990 and 2006, although overall emissions were 1.6 percent lower in
2006 than in 1990.
• Enteric fermentation was the largest source of CH4 emissions in 2006, at 126.2 Tg CO2 Eq. Although
emissions from enteric fermentation have decreased by less than 1 percent between 1990 and 2006,
emissions increased about 2 percent between 1990 and 1994 and decreased 8 percent 1995 to 2004, mainly
due to decreasing populations of both beef and dairy cattle and improved feed quality for feedlot cattle.
The last two years have shown an increase in emissions. During this timeframe, populations of sheep have
decreased 45 percent since 1990 while horse populations have increased over 80 percent, mostly over the
last 5 years. Goat and swine populations have increased 1 percent and 14 percent, respectively, during this
timeframe.
• Overall, emissions from manure management increased 29 percent between 1990 and 2006. This
encompassed an increase of 34 percent for CH4, from 31.0 Tg CO2 Eq. in 1990 to 41.4 Tg CO2 Eq. in
2006; and an increase of 18 percent for N2O, from 12.1 Tg CO2 Eq. in 1990 to 14.3 Tg CO2 Eq. in 2006.
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 CH4 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 13
percent of total U.S. greenhouse gas emissions in 2006. Forests (including vegetation, soils, and harvested wood)
accounted for approximately 84 percent of total 2006 net CO2 flux, urban trees accounted for 11 percent, mineral
and organic soil carbon stock changes accounted for 5 percent, and landfilled yard trimmings and food scraps
accounted for 1 percent of the total net flux in 2006. 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 through these soils, liming, and urea fertilization,
combined. 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 2006 resulted in a net C flux of -883.7 Tg CO2 Eq. (Table 2-9).
This represents an offset of approximately 14.8 percent of total U.S. CO2 emissions, or 12.5 percent of total
greenhouse gas emissions in 2006. Between 1990 and 2006, total land use, land-use change, and forestry net C flux
resulted in a 20 percent increase in CO2 sequestration.
Table 2-9: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)
Sink Category
Forest Land Remaining
Forest Land
Cropland Remaining
Cropland
Land Converted to
1990=
'I!'!
1995=
(659.9)|
9.4^
i 2000
1 (550-7)
1 (38.4)
1 9.4
2001
(623.4)
(40.0)
9.4
2002
(697.3)
(40.3)
9.4
2003
(730.9)
(40.5)
9.4
2004
(741.4)
(40.9)
9.4
2005
(743.6)
(41.0)
9.4
2006
(745.1)
(41.8)
9.4
Trends in Greenhouse Gas Emissions 2-13
-------
Grassland Remaining ^
Grassland (L9)H 16A 16A 16A 16A l63 l63 16'2
Land Converted to
Grassland (14-3)B (16-3)B (16-3) (16-3) (16-3) (16-3) (16-3) (16-3) (16-3)
Settlements Remaining ^
Settlements (60.6)^ (71.5)^ (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)
Other (Landfilled Yard ^
Trimmings and
Food Scraps) _ (23.9)^j (14-1)^ (n-5) (n-6) (1L8) (10-°) (9-6) (10-°) (10-5)
Total _ (737.7)Ji (775.3)^ (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Land use, land-use change, and forestry source categories also resulted in emissions of CO2, CH4, and N2O that are
not included in the net CO2 flux estimates presented in Table 2-9. 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
2006, and increase of 13 percent relative to 1990. The application of synthetic fertilizers to forest and settlement
soils in 2006 resulted in direct N2O emissions of 1.8 Tg CO2 Eq. Direct N2O emissions from fertilizer application
increased by approximately 74 percent between 1990 and 2006. Emissions of CH4 and N2O from forest fires
fluctuate widely from year to year, but overall increased by 449 percent between 1990 and 2006 (Table 2-10).
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) _
Source Category _ 1990 1995 ^g 2000 2001 2002 2003 2004 2005 2006
CO2 7.1 ^^ 7.0 ^ 7.5 7.8 8.5 8.3 7.6 7.9 8.0
Cropland Remaining Cropland:
Liming of Agricultural Soils &
Urea Fertilization 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0
CH4 4.5 ^( 4.7 ^ 19.0 9.4 16.4 8.7 6.9 12.3 24.6
Forest Land Remaining Forest
Land: Forest Fires 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6
N2O 1.5 1.8 ^J 3.5 2.7 3.5 2.7 2.6 3.1 4.3
Forest Land Remaining Forest
Land: Forest Fires 0.5 U 0.5 ^ 1.9 1.0 1.7 0.9 0.7 1.2 2.5
Forest Land Remaining Forest
Land: Forest Soils 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3
Settlements Remaining
Settlement Soils _ 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5
Total _ 13.1 ^^ 13.6 ^ 30.0 20.0 28.4 19.7 17.1 23.2 36.9
Note: Totals may not sum due to independent rounding.
Other significant trends from 1990 to 2006 in land use, land-use change, and forestry emissions include:
• Net C sequestration by forest land has increased 20 percent. This is primarily due to increased forest
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 16 years, although only at an average rate of 0. 1 percent per year.
• Net sequestration of C by urban trees has increased by 57 percent over this sixteen-year period. 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 56 percent. This is due
in part to a decrease in the amount of yard trimmings and food scraps generated. In addition, the proportion of
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 2006,
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 emissions. Emissions of CH4 and N2O from composting grew from 1990 to 2006, and resulted in emissions of
3.3 Tg CO2 Eq. A summary of greenhouse gas emissions from the Waste chapter is presented in Table 2-11.
Figure 2-11: 2006 Waste Chapter Greenhouse Gas Sources
Overall, in 2006, waste activities generated emissions of 161.0 Tg CO2 Eq., or 2.3 percent of total U.S. greenhouse
gas emissions.
Table 2-11: Emissions from Waste (Tg CO2 Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
Composting
N2O
Wastewater Treatment
Composting
Total
1990 =
172.9^
149.6 =
23.0 =
0.3^
6.6^
6.3^
0.4^
179.6^
=
1 169.1^
1 144.0^
1
1
i
i
1
i 176.8 =
1 2000
3 146.7
3 120.8
3 24.6
1 1.3
S 8.9
S 7.6
S 1.4
1 155.6
2001
143.0
117.6
24.2
1.3
9.2
7.8
1.4
152.1
2002
145.5
120.1
24.1
1.3
9.0
7.6
1.4
154.5
2003
151.0
125.6
23.9
1.5
9.3
7.7
1.6
160.3
2004
148.1
122.6
24.0
1.6
9.6
7.8
1.7
157.7
2005
149.0
123.7
23.8
1.6
9.7
8.0
1.7
158.7
2006
151.1
125.7
23.9
1.6
9.9
8.1
1.8
161.0
Note: Totals may not sum due to independent rounding.
Some significant trends in U.S. emissions from Waste include the following:
• From 1990 to 2006, net CH4 emissions from landfills decreased by 23.9 Tg CO2 Eq. (16 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 2006, CH4 and N2O emissions from wastewater treatment increased by 0.8 Tg CO2 Eq. (4
percent) and 1.8 Tg CO2 Eq. (29 percent), respectively.
• CH4 and N2O emissions from composting each increased by less than 0.1 Tg CO2 Eq. (1 percent) from
2005 to 2006. Emissions from composting have been continually increasing since 1990, from 0.7 Tg CO2
Eq. to 3.3 Tg CO2 Eq. in 2006, a four-fold increase over the time series.
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.
5 Lhe 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.
Trends in Greenhouse Gas Emissions 2-15
-------
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 2006. Transportation activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted for about 19 percent of U.S. greenhouse gas emissions in
2006. 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 19 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 8 percent of U.S. emissions; unlike other economic sectors, agricultural sector emissions were dominated
by N2O emissions from agricultural soil management and CH4 emissions from enteric fermentation, rather than CO2
from fossil fuel combustion. The commercial sector accounted for roughly 6 percent of emissions, while U.S.
territories accounted for about 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.
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 2006.
Figure 2-12: Emissions Allocated to Economic Sectors
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq. and Percent of Total in
2006)
Sector/Source
Electricity Generation
CO2 from Fossil Fuel
Combustion
Stationary Combustion
Electrical
Transmission and
Distribution
Municipal Solid Waste
Combustion
Limestone and
Dolomite Use
Transportation
CO2 from Fossil Fuel
Combustion
Mobile Combustion
Substitution of Ozone
Depleting Substances
1990 =
1,859.1 1
3
1,809.61
8.6!
=
1
26.?|
=
H.4l
=
2.8|
1,544.1 1
1
l,485.ll
47.2|
3
+ 1
19951
1,989.71
1
1,939.31
9-l|
i
1
21.51
i
16.21
i
3.7l
1,685.8|
1
1,599.41
56-5l
1
18.61
2000
2,328.9
2,282.3
10.6
15.1
17.9
3.0
1,917.5
1,798.2
54.7
52.6
2001
2,290.9
2,244.3
10.4
15.0
18.4
2.9
1,895.8
1,775.6
51.9
57.2
2002
2,300.4
2,253.7
10.4
14.4
18.9
2.9
1,948.5
1,828.9
47.5
61.1
2003
2,329
2,283
10
13
19
2
1,925
1,807
43
64
.4
.1
.7
.8
.5
.4
.9
.6
.8
.4
2004
2,363.4
2,314.9
10.8
13.9
20.5
3.4
1,975.4
1,856.4
40.9
67.8
2005
2,430.0
2,380.2
11.0
14.0
21.1
3.7
1,987.2
1,869.8
37.5
69.7
2006
2,377.8
2,328.2
10.8
13.2
21.3
4.3
1,969.5
1,856.0
34.1
69.5
Percent"
33.7%
33.0%
0.2%
0.2%
0.3%
0.1%
27.9%
26.3%
0.5%
1.0%
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Non-Energy Use of
Fuels
Industry
CO2 from Fossil Fuel
Combustion
Non-Energy Use of
Fuels
Stationary Combustion
Mobile Combustion
Coal Mining
Abandoned
Underground Coal
Mines
Natural Gas Systems
Petroleum Systems
Titanium Dioxide
Production
Aluminum Production
Iron and Steel
Production
Ferroalloy Production
Ammonia
Manufacture and
Urea Consumption
Cement Manufacture
Lime Manufacture
Limestone and
Dolomite Use
Soda Ash Manufacture
and Consumption
Carbon Dioxide
Consumption
Silicon Carbide
Production and
Consumption
Lead Production
Zinc Production
Petrochemical
Production
Phosphoric Acid
Production
Adipic Acid
Production
Nitric Acid Production
N2O Product Uses
HCFC-22 Production
Semiconductor
Manufacture
Magnesium
Production and
Processing
Substitution of Ozone
Depleting Substances
Agriculture
CO2 from Fossil Fuel
11.9 =
1,460.31
798.21
99.61
0.6|
84. ll
6.0!
158.41
34.21
=
1.2l
25.41
=
87.5|
2.2l
=
=
16.91
33.31
12.0|
=
2.8|
=
4'1
L41
=
0.4!
0.3|
0.91
1
3.l|
l.sl
15.31
17.01
4.4l
36.41
=
2.9l
=
5.41
506.81
46.761
11
1,478
819
115
5
0
67
8
161
32
1
17
76
2
17
36
14
3
4
1
0
0
1
3
1
17
18
4
33
5
5
J
•°|
.91
7!
'1
.2!
9 =
.31
1
i
.51
.0!
.01
1
1
•8l
•Ol
1
.71
i
•31
4-E
1
'|
.ol
1
8^
E
5l
o E
.61
.ol
i
.ol
1
.61
1.21
524.1 1
57.321
12.1
1,432.9
809.4
118.4
4.9
0.8
60.4
7.4
155.9
30.6
1 O
l.O
14.7
67.8
1.9
16.4
41.2
14.9
3.0
4.2
1.4
0.3
0.3
1.1
4.2
1.4
6.2
18.6
4.9
28.6
6.3
3.0
3.1
528.0
50.88
11.1
1,384.3
801.8
115.5
4.6
0.9
60.3
6.7
154.1
30.5
1.7
7.8
60.3
1.5
13.3
41.4
14.3
2.9
4.1
0.8
0.2
0.3
1.0
3.9
1.3
5.1
15.1
4.9
19.7
4.5
2.9
3.1
533.4
50.69
10.9
1,384.9
801.9
115.8
4.4
0.9
56.8
6.2
154.5
30.2
1.8
9.7
57.0
1.4
14.2
42.9
13.7
2.9
4.1
1.0
0.2
0.3
0.9
4.0
1.3
6.1
16.4
4.4
21.1
4.3
2.9
3.7
529.3
52.89
10.1
1,375.5
811.0
113.2
4.3
0.9
56.9
6.0
151.8
29.5
1.8
8.3
55.8
1.3
12.5
43.1
14.5
2.4
4.1
1.3
0.2
0.3
0.5
3.9
1.4
6.3
15.4
4.4
12.3
4.3
3.4
4.4
498.0
45.02
10.2
1,388.9
806.6
131.4
4.6
1.0
59.8
5.8
142.1
29.0
2.1
7.1
53.8
1.4
13.2
45.6
15.2
3.4
4.2
1.2
0.2
0.3
0.5
4.1
1.4
5.9
15.2
4.4
17.2
4.3
3.2
4.8
499.2
51.12
10.2
1,354.3
801.8
121.8
4.5
1.0
57.1
5.6
132.0
28.6
1.8
7.2
47.6
1.4
12.8
45.9
15.1
3.7
4.2
1.3
0.2
0.3
0.5
3.9
1.4
5.9
15.8
4.4
15.8
4.4
3.3
5.2
521.3
45.52
9.9
1,371.5
818.6
120.8
4.6
1.0
58.5
5.4
130.9
28.7
1.9
6.4
50.1
1.5
12.4
45.7
15.8
4.3
4.2
1.6
0.2
0.3
0.5
3.6
1.2
5.9
15.6
4.4
13.8
4.8
3.2
5.7
533.6
43.60
0.1%
19.4%
11.6%
1.7%
0.1%
0.0%
0.8%
0.1%
1.9%
0.4%
0.0%
0.1%
0.7%
0.0%
0.2%
0.6%
0.2%
0.1%
0.1%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.1%
0.2%
0.1%
0.2%
0.1%
0.0%
0.1%
7.6%
0.6%
Trends in Greenhouse Gas Emissions 2-17
-------
Combustion
Stationary Combustion
Mobile Combustion
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
N2O from Agricultural
Soil Management
Liming of Agricultural
Soils
Urea Fertilization
CH4 and N2O from
Forest Fires
N2O from Forest Soils
Commercial
CO2 from Fossil Fuel
Combustion
Stationary Combustion
Substitution of Ozone
Depleting Substances
Landfills
Human Sewage
Wastewater Treatment
Composting
Residential
CO2 from Fossil Fuel
Combustion
Stationary Combustion
Substitution of Ozone
Depleting Substances
Settlement Soil
Fertilization
U.S. Territories
CO2 from Fossil Fuel
Combustion
Total Emissions
Sinks
CO2 Flux from Forests
Urban Trees
CO2 Flux from
Agricultural Soil
Carbon Stocks
Landfilled Yard
Trimmings and Food
Scraps
Net Emissions
(Sources and Sinks)
1
+1
0.4l
126.9|
43.0|
7.l|
=
l.ll
=
269.41
3
4.?1
2.4|
=
4.9l
o.i|
396.91
=
216.l|
1.2|
3
+ 1
149.61
6.3l
23.0|
0.7|
346.91
=
340. ll
5.51
3
0.3!
1
i-o|
34.1 1
=
34.ll
6,148.31
(737.7)1
(621.7)1
(60.6)1
3
=
(31.5)1
1
3
(23.9)1
3
5,410.61
+1
o.si
132.3J
48.01
7.6i
i.oi
264.81
4.41
2.7J
5.2i
0.2!
404.5
225.8
1.3
0.7
144.0
6.9
24.3i
1.51
370.9 i
356.5i
5.0J
8.1J
1-2J
41.ll
41. lj
6,494.0j
(775.3)1
(659.9)1
(71.5)|
(29.7)1
(14.1)1
5,718.7i
1 + + + + + + +
1 0.4 0.4 0.5 0.4 0.4 0.4 0.4
j 124.6 123.6 123.8 124.6 122.4 124.5 126.2
I 52.5 54.2 55.2 54.3 53.9 55.7 55.7
| 7.5 7.6 6.8 6.9 7.6 6.8 5.9
I 1.3 1.2 1.1 1.2 1.4 1.4 1.3
1 262.1 277.0 262.0 247.3 246.9 265.2 265.0
1 4.3 4.4 5.0 4.6 3.9 4.3 4.4
1 3.2 3.4 3.6 3.7 3.7 3.5 3.6
| 20.9 10.4 18.0 9.6 7.6 13.6 27.0
0.3 0.3 0.3 0.3 0.3 0.3 0.3
390.3 383.0 388.1 410.2 404.6 400.4 394.6
228.0 222.3 222.8 236.5 230.6 221.9 210.1
1.2 1.2 1.2 1.3 1.3 1.2 1.2
5.5 7.4 9.6 12.1 15.0 18.5 22.4
120.8 117.6 120.1 125.6 122.6 123.7 125.7
7.6 7.8 7.6 7.7 7.8 8.0 8.1
24.6 24.2 24.1 23.9 24.0 23.8 23.9
2.6 2.7 2.7 3.1 3.3 3.3 3.3
I 387.7 379.3 376.6 399.6 385.5 376.0 344.8
I 372.1 363.6 360.5 382.9 368.3 358.5 326.5
I 4.3 3.9 4.0 4.2 4.3 4.2 3.9
1 10.1 10.3 10.7 11.0 11.4 11.9 12.9
1 1.2 1.4 1.5 1.5 1.6 1.5 1.5
| 47.3 54.5 53.3 59.7 61.0 60.5 62.4
1 47.3 54.5 53.3 59.7 61.0 60.5 62.4
j 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2
1 (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)
j (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)
; (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)
1 (29.0) (30.6) (30.9) (31.1) (31.5) (31.7) (32.6)
1 (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5)
I 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5
0.0%
0.0%
1.8%
0.8%
0.1%
0.0%
3.8%
0.1%
0.1%
0.4%
0.0%
5.6%
3.0%
0.0%
0.3%
1.8%
0.1%
0.3%
0.0%
4.9%
4.6%
0.1%
0.2%
0.0%
0.9%
0.9%
100.0%
-12.5%
-10.6%
-1.4%
-0.5%
-0.1%
87.5%
Note: Includes all emissions of CO2, CH4, N2O, HFCs, PFCs, and SF6.
Totals may not sum due to independent rounding.
ODS (Ozone Depleting Substances)
+ Does not exceed 0.05 Tg CO2 Eq. or 0.05%.
a Percent of total emissions for year 2006.
Parentheses indicate negative values or sequestration.
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 2006. 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 decreased from 2005
to 2006 by 2 percent, primarily due to reduced 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.
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)
Gas/Fuel Type or Source
C02
CO2 from Fossil Fuel Combustion
Coal
Natural Gas
Petroleum
Geothermal
Municipal Solid Waste Combustion
Limestone and Dolomite Use
CH4
Stationary Combustion*
N2O
Stationary Combustion*
Municipal Solid Waste Combustion
SF6
Electrical Transmission and
Distribution
Total
1990
1,823.
1,809.
1,531.
176.
101.
0.
10.
2.
0.
0.
8.
8.
0.
26.
26.
1,859.
3
6
3
2
8
4
9
8
6
6
5
1
5
7
7
1
I 19951 2000
1,958.6s 2,302.8
1,939.31 2,282.3
1,648.7% 1,909.6
229. Si, 280.9
60.7% 91.5
0.3U 0.4
15.71 17.5
3.?1 3.0
0.6! 0.7
0.6| 0.7
9.ol 10.4
8.6!
0.5:
21.5
21.5!
1 1,989.7|
10.0
0.4
15.1
15.1
2,328.9
2001
2,265.1
2,244.3
1,852.3
289.6
102.0
0.4
18.0
2.9
0.7
0.7
10.1
9.7
0.4
15.0
15.0
2,290.9
2002
2,275.1
2,253.7
1,868.3
306.0
79.1
0.4
18.5
2.9
0.7
0.7
10.1
9.7
0.4
14.4
14.4
2,300.4
2003
2,304.5
2,283.1
1,906.2
278.3
98.1
0.4
19.1
2.4
0.7
0.7
10.4
10.0
0.4
13.8
13.8
2,329.4
2004
2,338.4
2,314.9
1,917.6
296.8
100.1
0.4
20.1
3.4
0.7
0.7
10.5
10.0
0.4
13.9
13.9
2,363.4
2005
2,404.6
2,380.2
1,958.4
319.1
102.3
0.4
20.7
3.7
0.7
0.7
10.7
10.3
0.4
14.0
14.0
2,430.0
2006
2,353.4
2,328.2
1,932.4
339.6
55.7
0.4
20.9
4.3
0.7
0.7
10.5
10.1
0.4
13.2
13.2
2,377.8
Note: Totals may not sum due to independent rounding.
* Includes only stationary combustion emissions related to the generation of electricity.
To distribute electricity emissions among economic end-use sectors, emissions from the source categories assigned
to the electricity generation sector were allocated to the residential, commercial, industry, transportation, and
agriculture economic sectors according to retail sales of electricity (EIA 2006c and Duffield 2006). These three
source categories include CO2 from Fossil Fuel Combustion, CH4 and N2O from Stationary Combustion, and SF6
from Electrical Transmission and Distribution Systems.6
When emissions from electricity are distributed among these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (29 percent), followed closely by emissions from transportation activities, which account
for 28 percent of total emissions. Emissions from the residential and commercial sectors also increase substantially
when emissions from electricity are included, due to their relatively large share of electricity consumption. In all
sectors except agriculture, CO2 accounts for more than 80 percent of greenhouse gas emissions, primarily from the
combustion of fossil fuels.
6 Emissions were not distributed to U.S. territories, since the electricity generation sector only includes emissions related to the
generation of electricity in the 50 states and the District of Columbia.
Trends in Greenhouse Gas Emissions 2-19
-------
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
2006.
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors
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 2006
Sector/Gas
Industry
Direct Emissions
CO2
CH4
N2O
MFCs, PFCs,
andSF6
Electricity-
Related
C02
CH4
N20
SF6
Transportation
Direct Emissions
CO2
CH4
N2O
HFCsb
Electricity-
Related
C02
CH4
N2O
SF6
Commercial
Direct Emissions
C02
CH4
N20
MFCs
Electricity-
Related
CO2
CH4
N20
SF6
Residential
Direct Emissions
C02
CH4
N2O
1990^
2,100.4p
1,460.3^
l,070.1p
286.5p
40.4p
63.3P
640.1P
627.7p
2.9m
9.2m
1,541.2m
l,544.1p
1,496.9m
4.5m
42.67p
+m
3.im
3. lp
+m
+m
+m
946.3m
396.9p
216. im
173.8p
l.Oji
+JH
549.3ml
538.7P
0.2p
2.5m
7.9p
952.4m
346.9m
340.1p
4.4m
2.im
3 1995^
1 2,ui.im
1 1,478.0^
1 l,103.0p
| 273.6p
1 44.8p
1 56.6P
1 663. lP
1 652.8p
1
1
1 7.2p
| 1,688.9m
1 l,685.8p
1 l,610.7p
1 4.im
1 52.46p
1 18-6P
1
1 3. lp
1 +m
5 ^JEEE
1 +ml
1 1,003.8m
1 404.5p
1 225.8p
1 170.0p
1
1 °-7P
| 599.4P
1 590.0P
1
1 2.im
1
1 l,026.5p
1 370.9p
1 356.5p
1
1
3 2000
1 2,174.3
1 1,432.9
1 1,091.3
1 258.3
1 33.7
1 49.6
1 741.4
1 733.1
1 0.2
1 3.3
1 4.8
1 1,921.0
1 1,917.5
1 1,810.2
1 3.2
1 51.53
1 52-57
1 3.49
1 3-4
1 +
1 +
1 +
1 1,141.9
1 390.3
1 228.0
1 147.6
1 9.3
1 5-5
1 751.6
1 743.2
1 0.2
1 3.3
1 4.9
1 1,160.7
1 387.7
1 372.1
1 3.4
1 2.1
2001
2,061.1
1,384.3
1,066.4
255.4
28.9
33.6
676.8
669.2
0.2
3.0
4.4
1,899.4
1,895.8
1,786.7
3.1
48.80
57.20
3.69
3.6
+
+
+
1,149.8
383.0
222.3
143.8
9.5
7.4
766.7
758.1
0.2
3.4
5.0
1,153.2
379.3
363.6
3.1
2.3
2002
2,051.6
1,384.9
1,065.7
251.3
30.6
37.3
666.7
659.4
0.2
2.9
4.2
1,952.0
1,948.5
1,839.8
2.7
44.82
61.13
3.49
3.5
+
+
+
1,151.1
388.1
222.8
146.4
9.4
9.6
763.0
754.6
0.2
3.4
4.8
1,178.0
376.6
360.5
3.1
2.3
2003
2,064.0
1,375.5
1,069.6
247.8
29.8
28.2
688.5
681.1
0.2
3.1
4.1
1,930.2
1,925.9
1,817.7
2.5
41.26
64.41
4.33
4.3
+
+
+
1,172.7
410.2
236.5
151.9
9.7
12.1
762.5
754.4
0.2
3.4
4.5
1,211.2
399.6
382.9
3.3
2.4
2004
2,075.4
1,388.9
1,086.5
240.5
29.5
32.4
686.5
679.2
0.2
3.0
4.0
1,980.0
1,975.4
1,866.6
2.4
38.51
67.84
4.59
4.5
+
+
+
1,187.2
404.6
230.6
149.0
9.9
15.0
782.6
774.3
0.2
3.5
4.6
1,207.2
385.5
368.3
3.3
2.5
2005
2,038.3
1,354.3
1,065.8
226.7
30.0
31.7
683.9
676.8
0.2
3.0
3.9
1,992.0
1,987.2
1,880.0
2.3
35.20
69.74
4.78
4.7
+
+
+
1,212.5
400.4
221.9
149.9
10.1
18.5
812.0
803.5
0.2
3.6
4.7
1,241.7
376.0
358.5
3.3
2.4
2006
2,029.2
1,371.5
1,084.6
227.1
29.9
30.0
657.7
650.9
0.2
2.9
3.6
1,974.5
1,969.5
1,865.9
2.1
31.96
69.46
5.03
5.0
+
+
+
1,204.4
394.6
210.1
152.0
10.2
22.4
809.8
801.5
0.2
3.6
4.5
1,187.8
344.8
326.5
3.1
2.3
Percent"
28.5%
19.2%
15.2%
3.2%
0.4%
0.4%
9.2%
9.1%
0.0%
0.0%
0.1%
27.7%
27.6%
26.2%
0.0%
0.4%
1.0%
0.1%
0.1%
0.0%
0.0%
0.0%
16.9%
5.5%
2.9%
2.1%
0.1%
0.3%
11.4%
11.2%
0.0%
0.1%
0.1%
16.7%
4.8%
4.6%
0.0%
0.0%
2-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
HFCs
Electricity-
Related
C02
CH4
N2O
SF6
Agriculture
Direct Emissions
C02
CH4
N20
Electricity-
Related
C02
CH4
N2O
SF6
U.S. Territories
Total
0.3p
605.5^
593.8p
0.2p
2.8p
8.7p
567.9m
506.8p
53.8p
170.3P
282.6P
61.2P
60.0p
+p
0.3p
0.9p
34.im
6,148.3p
8-j JZZZ
. 1 SEE
1 655.6P
1 645.4p
1
1
1 7.1p
1 592.5P
1 524.1p
1 64.4p
1 180.7P
| 279.0P
1 68.5P
1 67.4p
1 +P
1
1 0.7p
1 41.1p
1 6,494.0p
1 10-!
1 773.0
1 764.4
1 0.2
1 3.4
1 5.0
1 587.4
1 528.0
1 58.4
1 190.8
1 278.8
1 59.4
1 58.7
1 +
1 0.3
1 0.4
1 47.3
1 7,032.6
10.3
773.9
765.2
0.2
3.4
5.1
603.2
533.4
58.5
181.8
293.1
69.8
69.0
+
0.3
0.5
54.5
6,921.3
10.7
801.4
792.6
0.2
3.5
5.0
595.1
529.3
61.4
189.1
278.8
65.8
65.1
+
0.3
0.4
53.3
6,981.2
11.0
811.6
802.9
0.2
3.6
4.8
560.5
498.0
53.3
181.8
262.9
62.5
61.9
+
0.3
0.4
59.7
6,998.2
11.4
821.7
813.0
0.2
3.6
4.8
567.2
499.2
58.7
178.0
262.6
68.1
67.3
+
0.3
0.4
61.0
7,078.0
11.9
865.6
856.6
0.3
3.8
5.0
584.9
521.3
53.4
186.4
281.5
63.6
63.0
+
0.3
0.4
60.5
7,129.9
12.9
843.0
834.4
0.3
3.7
4.7
595.8
533.6
51.6
199.1
282.9
62.3
61.6
+
0.3
0.3
62.4
7,054.2
0.2%
11.8%
11.7%
0.0%
0.1%
0.1%
8.4%
7.5%
0.7%
2.8%
4.0%
0.9%
0.9%
0.0%
0.0%
0.0%
0.9%
100.0%
Note: Emissions from electricity generation are allocated based on aggregate electricity consumption in each end-use sector.
Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg CO2 Eq. or 0.05 percent.
a Percent of total emissions for year 2006.
b Includes primarily HFC-134a.
Industry
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 by-product of the non-energy-related
industrial process activities. The variety of activities producing these non-energy-related emissions, to name a few
includes fugitive CH4 emissions from coal mining, by-product CO2 emissions from cement manufacture, and HFC,
PFC, and SF6 by-product 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 accounted
for 28 percent of U.S. greenhouse gas emissions in 2006. The largest sources of transportation GHGs in 2006 were
passenger cars (34 percent), light duty trucks, which include sport utility vehicles, pickup trucks, and minivans (28
percent), freight trucks (20 percent) and commercial aircraft (7 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 2006, transportation emissions rose by 28 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 39 percent from 1990 to 2006, 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
Trends in Greenhouse Gas Emissions 2-21
-------
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 reflects an increasing market share of light duty trucks, which have grown from about one-
fifth of new vehicle sales in the 1970s to slightly over hah0 of the market by 2004. Increasing fuel prices have since
decreased the momentum of light duty truck sales, and average new vehicle fuel economy improved in 2005 and
2006 as the market share of passenger cars increased. VMT growth among all passenger vehicles has also been
impacted, growing an average annual rate of 0.8 percent from 2004 to 2006, compared to an annual rate of 2.7
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 25 percent from 1990 to
2006. This rise in CO2 emissions, combined with an increase in HFCs from virtually no emissions in 1990 to 69.5
Tg CO2 Eq. in 2006, led to an increase in overall emissions from transportation activities of 28 percent.
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)
Gas/Vehicle Type
Passenger Cars
C02
CH4
N2O
HFCs
Light-Duty Trucks
C02
CH4
N2O
HFCs
Medium- and Heavy-
Duty Trucks
CO2
CH4
N2O
HFCs
Buses
CO2
CH4
N2O
HFCs
Motorcycles
CO2
CH4
N2O
Commercial Aircraft -
Domestic"
CO2
CH4
N2O
Other Aircraft -
Domestic1"
C02
CH4
N2O
1990^
656
628
2
25
336
320
1
14
228
227
0
8
8
0
1
1
138
136
0
1
43
43
0
0
8^^=
^=
3
|
1
1
1
| lO.l^H
1
1
1
1 22.1^
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1 2000
1 694.
1 643.
i 1.
1 25.
1 24.
1 508.
1 466.
1 1.
1 22.
1 18-
1 344.
1 341.
1 1.
1 1.
1 11.
1 10.
1 °-
1 0.
1 1.
1 1.
1 165.
1 164.
1 °-
1 1.
1 32.
1 32.
1 o.
1 o.
6
5
6
2
3
1
0
1
4
6
3
5
+
2
6
2
9
1
+
1
9
8
+
+
9
2
1
6
6
2
1
3
2001
699.1
647.9
1.5
23.8
25.9
513.3
470.3
1.1
21.3
20.6
343.6
340.6
+
1.2
1.7
10.3
10.0
0.1
+
0.2
1.7
1.7
+
+
154.4
152.9
0.1
1.5
34.1
33.7
0.1
0.3
2002
713.7
662.6
1.4
22.5
27.2
525.1
483.2
0.9
18.5
22.5
357.9
354.8
+
1.2
1.8
10.0
9.6
0.1
+
0.2
1.7
1.7
+
+
147.6
146.1
0.1
1.4
32.2
31.9
0.1
0.3
2003
692.4
642.1
1.3
21.0
28.0
560.4
518.8
0.8
16.6
24.2
354.4
351.2
+
1.3
1.9
10.8
10.5
0.1
+
0.2
1.7
1.6
+
+
145.4
143.9
0.1
1.4
31.1
30.8
0.1
0.3
2004
689.5
640.0
1.2
19.5
28.8
583.0
540.8
0.7
15.3
26.1
367.4
364.1
+
1.2
2.1
15.1
14.7
0.1
+
0.2
1.8
1.7
+
+
144.4
142.9
0.1
1.4
34.5
34.1
0.1
0.3
2005
705.8
658.4
1.1
17.8
28.5
544.0
501.9
0.7
13.7
27.7
395.2
391.9
+
1.2
2.1
12.1
11.8
0.1
+
0.2
1.6
1.6
+
+
152.0
150.4
0.1
1.5
31.1
30.8
0.1
0.3
2006
678.4
634.5
1.0
15.6
27.2
556.6
514.9
0.7
12.7
28.3
404.6
401.3
+
1.1
2.2
12.5
12.1
0.1
+
0.3
1.9
1.9
+
+
143.6
142.1
0.1
1.4
28.8
28.5
0.1
0.3
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Ships and Boats -
Domestic0
CO2
CH4
N2O
MFCs
Rail
CO2
CH4
N2O
MFCs
Pipelines'1
CO2
Lubricants
CO2
47
46
0
0
38
38
0
0
36
36
11
11
^ 56
^ 55
^ 0
^ 0
1 o
1 44
§ 42
^ 0
1 0
^ 1
^ 38
^ 38
^ n
1 n
I 65.1
I 61.0
I 0.1
i 0.5
I 3.4
I 50.1
I 45.1
i o.i
I 0.3
i 4.6
i 35.2
i 35.2
i 12.1
i 12.1
47.4
43.2
0.1
0.3
3.7
50.8
45.4
0.1
0.3
5.0
33.6
33.6
11.1
11.1
65.4
60.8
0.1
0.5
4.0
50.7
44.9
0.1
0.3
5.4
36.6
36.6
10.9
10.9
38.3
33.6
0.1
0.3
4.3
52.8
46.6
0.1
0.3
5.8
32.7
32.7
10.1
10.1
47.1
42.1
0.1
0.4
4.6
55.8
49.2
0.1
0.4
6.1
31.2
31.2
10.2
10.2
50.8
45.6
0.1
0.4
4.7
56.6
49.8
0.1
0.4
6.4
32.3
32.3
10.2
10.2
47.7
42.4
0.1
0.4
4.9
57.9
51.0
0.1
0.4
6.5
32.4
32.4
9.9
9.9
Other Transportation
(Unspecified)6 + + + 0.1 0.1 0.2 0.2
Total Transportation 1,547.2^^ 1,688.9^^ 1,921.0 1,899.4 1,952.0 1,930.2 1,980.0 1,992.0 1,974.5
International Bunker
Fuel/ 702.2 98.6 90.0 104.6 120.2 123.8 128.4
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding. Emissions estimates for passenger cars, light-duty trucks and heavy-duty
trucks are calculated using fuel consumption data from FHWA's Highway Statistics, which used an updated methodology to
develop the 2006 estimates. In the most recent Highway Statistics, FHWA also updated 2005 fuel consumption estimates, but
did not revise other prior years. This causes some discontinuity in the emissions estimates between 2004 and 2005.
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.
a 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.
0 Fluctuations in emission estimates are associated with fluctuations in reported fuel consumption, and may reflect data collection
problems.
d CO2 estimates reflect natural gas used to power pipelines, but not electricity. While the operation of pipelines produces CH4
and N2O, these emissions are not directly attributed to pipelines in the US Inventory.
e Combination of gases; balancing item for transportation emissions not specifically identified in table but which are included in
transportation economic sector emissions identified in Table 2-14.
f Emissions from International Bunker Fuels include emissions from both civilian and military activities; these emissions are not
included in the transportation totals.
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 increases 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,
Trends in Greenhouse Gas Emissions 2-23
-------
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 2006, enteric fermentation was the largest
source of CH4 emissions in the U.S., and agricultural soil management was the largest source of N2O emissions in
the U.S. This sector also includes small amounts of CO2 emissions from fossil fuel combustion by motorized farm
equipment like 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 33 percent of total U.S. emissions. Electricity
generation also accounted for the largest share of CO2 emissions from fossil fuel combustion, approximately 41
percent in 2006. Electricity was consumed primarily in the residential, commercial, and industrial end-use sectors
for lighting, heating, electric motors, appliances, electronics, and air conditioning.
[BEGIN BOX]
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.
• In the Electricity Generation economic sector, CO2 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 N2O are also based on the EIA electric utility sector. Additional sources include CO2 and
N2O from Municipal Solid Waste Combustion, 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 CO2 from Limestone and Dolomite Use (from
pollution control equipment installed in electricity generation plants).
• In the Transportation economic sector, the CO2 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 the CH4 and N2O from Mobile Combustion, based on the EIA transportation sector.
Substitutes of Ozone Depleting Substitutes are apportioned based on their specific end-uses within the source
category, with emissions from transportation refrigeration/air-conditioning systems to this economic sector.
Finally, CO2 emissions from Non-Energy Uses of Fossil Fuels identified as lubricants for transportation
vehicles are included in the Transportation economic sector.
• For the Industry economic sector, the CO2 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 N2O are also based on the EIA
industrial sector, minus emissions apportioned to the Agriculture economic sector described below. Substitutes
of Ozone Depleting Substitutes are apportioned based on their specific end-uses within the source category,
with most emissions falling within the Industry economic sector (minus emissions from the other economic
sectors). 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
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
emissions (i.e., emissions from the actual process to make the material, not from fuels to power the plant) from
such activities as cement production, iron and steel production, and ammonia manufacture. 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 CO2 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 CO2 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.
• As agriculture equipment is included in EIA's industrial fuel consuming sector surveys, additional data is used
to extract 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 CO2 emissions from fossil fuel combustion, and CH4 and N2O
emissions from stationary and mobile combustion (all data is removed from the Industrial economic sector, to
avoid double-counting). The other emission sources included in this economic sector are intuitive for the
agriculture sectors, such as N2O emissions from Agricultural Soils, CH4 from Enteric Fermentation (i.e.,
exhalation from the digestive tracts of domesticated animals), CH4 and N2O from Manure Management, CH4
from Rice Cultivation, CO2 emissions from liming of agricultural soils and urea application, and CH4 and N2O
from Forest Fires. N2O emissions from the application of fertilizers to tree plantations (termed "forest land" by
the IPCC) are also included in the Agriculture economic sector.
• The Residential economic sector includes the CO2 emissions from the combustion of fossil fuels reported for
the EIA residential sector. Stationary combustion emissions of CH4 and N2O are also based on the EIA
residential fuel consuming sector. Substitutes of Ozone Depleting Substitutes are apportioned based on their
specific end-uses within the source category, with emissions from residential air-conditioning systems to this
economic sector. N2O emissions from the application of fertilizers to developed land (termed "settlements" by
the IPCC) are also included in the Residential economic sector.
• The Commercial economic sector includes the CO2 emissions from the combustion of fossil fuels reported in
the EIA commercial fuel consuming sector data. Stationary combustion emissions of CH4 and N2O are also
based on the EIA commercial sector. Substitutes of Ozone Depleting Substitutes are apportioned based on their
specific end-uses within the source category, with emissions from commercial refrigeration/air-conditioning
systems to this economic sector. Public works sources including direct CH4 from Landfills and CH4 and N2O
from Wastewater Treatment and Composting are included in this economic sector.
[END BOX]
[BEGIN BOX]
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 2006; (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
Trends in Greenhouse Gas Emissions 2-25
-------
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 Table 2-16).
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100)
Variable
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Population"1
Greenhouse Gas Emissions6
1990 =
100 i
100 i
100 1
100 i
100 1
100 1
m i
1
1
1
^107 1
1
1
1
= 2000
= 138
= 127
= 117
= 116
= 113
= 114
2001
139
125
115
112
114
113
2002
141
128
116
115
115
114
2003
145
129
116
115
116
114
2004
150
131
119
118
117
115
2005
155
134
119
118
118
116
2006
159
135
117
117
119
115
Growth
Rate3
3.0%
1.9%
1.0%
1.0%
1.1%
0.9%
a Average annual growth rate
b Gross Domestic Product in chained 2000 dollars (BEA 2007)
0 Energy-content-weighted values (EIA 2007b)
d U.S. Census Bureau (2007)
e GWP-weighted values
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product
Source: BEA (2007), U.S. Census Bureau (2007), and emission estimates in this report.
[END BOX]
2.3. Indirect Greenhouse Gas Emissions (CO, NOx, NMVOCs, and SO2)
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 CH4 emissions—to form CO2. Therefore, increased atmospheric concentrations of CO limit
the number of hydroxyl molecules (OH) available to destroy CH4.
7 See .
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
Table 2-17: Emissions of NOX, CO, NMVOCs, and SO2 (Gg)
Gas/Activity
NOX
Mobile Fossil Fuel
Combustion
Stationary Fossil Fuel
Combustion
Industrial Processes
Oil and Gas Activities
Municipal Solid Waste
Combustion
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel
Combustion
Stationary Fossil Fuel
Combustion
Industrial Processes
Municipal Solid Waste
Combustion
Agricultural Burning
Oil and Gas Activities
Waste
Solvent Use
NMVOCs
Mobile Fossil Fuel
Combustion
Solvent Use
Industrial Processes
Stationary Fossil Fuel
Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
Waste
Agricultural Burning
S02
Stationary Fossil Fuel
Combustion
Industrial Processes
1990=
21
10
9
130
119
5
4
20
10
5
2
20
18
1
#45M
,920^
591^
139^
28^
1^
>461^
,000^
,125 =
978^
691^
302^
1=:
912^
554^
673^
NA^
,407^
8 NOX and CO emission estimates from field
from EPA (2008).
1
| 21,272=
1 •
1 10,622^
1 •
|
1
1
1 •
z; oo^^^
i 55^=
1
1 3^
1 \m
1 109,032^
1 •
1 97,630=
1 m
| 5,383^
1
1 •
E3 1 073;==
1
1
1 im
1 5^
1 19,520^
1 •
1 5,609p
1
1 •
1
1
1 •
|
1
1
1 16,891^
1 •
1 14,724^
1 1,117^
= 2000
I I9
I 10
8_
—
I 92
I 83
I 4
I 2
I 1
I 15
I 7
1 4
I 1
H l
I 14
I 12
1 1
,203
,310
,002
626
111
114
35
3
2
,777
,559
,340
,217
,670
792
146
8
46
,228
,230
,384
,773
,077
389
257
119
NA
,829
,848
,031
2001
18,410
9,819
7,667
656
113
114
35
3
2
89,212
79,851
4,377
2,339
1,672
774
147
8
45
15,048
6,872
4,547
1,769
1,080
400
258
122
NA
14,452
12,461
1,047
2002
17,938
10,154
6,791
534
321
98
33
5
2
84,609
75,421
4,965
1,744
1,439
709
323
7
1
15,640
7,235
3,881
2,036
1,585
545
243
115
NA
13,403
11,613
850
2003
17,043
9,642
6,419
528
316
97
34
5
2
80,221
71,038
4,893
1,724
1,437
800
321
7
1
15,170
6,885
3,862
1,972
1,560
538
239
114
NA
13,631
11,956
804
2004
16,177
9,191
6,004
524
316
97
39
5
2
76,342
67,096
4,876
1,724
1,437
879
321
7
1
14,807
6,587
3,854
1,931
1,553
533
237
112
NA
13,232
11,625
800
2005
15,569
8,739
5,853
519
316
97
39
5
2
72,365
63,154
4,860
1,724
1,437
860
321
7
1
14,444
6,289
3,846
1,890
1,545
528
235
111
NA
13,114
11,573
797
2006
14,869
8,287
5,610
515
315
97
38
5
2
68,372
59,213
4,844
1,724
1,437
825
322
7
1
14,082
5,991
3,839
1,849
1,538
523
232
110
NA
12,258
10,784
793
burning of agricultural residues were estimated separately, and therefore not taken
Trends in Greenhouse Gas Emissions 2-27
-------
Mobile Fossil Fuel
Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
Waste
Solvent Use
Agricultural Burning
793^3
NA^
^^=
NA^^
632
286
29
1
1
NA
624
289
30
1
1
NA
683
233
23
1
0
NA
621
226
22
1
0
NA
564
220
22
1
0
NA
508
213
22
1
0
NA
451
207
22
1
0
NA
Source: (EPA 2005) except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
[BEGIN BOX]
Box 2-3: Sources and Effects of Sulfur Dioxide
Sulfur dioxide (SO2) 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 SO2 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 SO2 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 SO2
emissions in the Clean Air Act.
Electricity generation is the largest anthropogenic source of SO2 emissions in the United States, accounting for 71
percent in 2006. 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.
[END BOX]
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
• MFCs, PFCs, & SF
6
Nitrous Oxide
r Methane
• Carbon Dioxide
6,148 6,106
6i192 6,343 6,435 6,494 *
6731 6,760 6,801 6,839 7.033 6,921 6,981 6,998 7,078 7,130 7,054
8,000 -
7,000 -
6,000 -
. 5,000 -
S
O 4,000 -
i5?
H 3,000 -
2,000 -
1,000 -
0 -
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas
3.6%
2.8%
1.1%
0.7%
-1% -
-2% J
-1.6%
-1.1%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
n,n 982
930 906
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
-------
Industrial Processes Waste LULUCF (s°urces)
7,000 -,
6,000
5,000 -
d- 4,000 -
UJ
0
u 3,000 -
2,000 -
1,000
Q
(1,000)
Agriculture N. 1> n i
— -^X^""^" zz ; •—
Energy
Land Use, Land-Use Change and Forestry (sinks)
8 S 8 a * X X * % % 8 g 8 3 S S 8
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and Other
Product Use sector
Figure 2-4: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion I
Petroleum Systems I
Municipal Solid Waste Combustion I
Stationary Combustion I
Abandoned Underground Coal Mines |
5,637.9
Energy as a Portion
of all Emissions
25 50 75 100 125 150
Tg CO2 Eq.
Figure 2-5: 2006 Energy Sector Greenhouse Gas Sources
-------
Natural Gas Emissions
1,163
NEU Emissions 121
Fossil Fuel Non-Energy
Non-Energy Consumption Use U.S.
Use imports U.S. Temtones
6/ Territories °
55
Non-Energy Use
Carbon Sequestered
240
Note: Totals may not sum due to independent rounding.
The "Balancing item11 above accounts for the statistical imbalances
and unknowns in the reported data sets combined here.
Figure 2-6 2006 U.S. (Tg C02 Eq.)
-------
2,500 -,
2,000 -
fi" 1,500 -
O
™ 1,000 -
H
500 -
0 -
Relative Contribution
by Fuel Type
O
u
1
g.
l Natural Gas
Petroleum
I Coal
I
i/i .g
Figure 2-7: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: Electricity generation also includes emissions of less than 0.5 Tg CO 2 Eq. from geothermal-based electricity generation.
2,000 -,
1,800 -
1,600
. 1,400
S" 1,200 -
O 1,000 -
p 800 ]
K 600
400
200 -
0 J
• From Electricity
Consumption
• From Direct Fossil
Fuel Combustion
1
i.
Figure 2-8: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
-------
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
Lime Manufacture ^^B
Nitric Acid ^^|
HCFC-22 Production ^B
Electrical Transmission and Distribution ^^|
Ammonia Production and Urea Application ^B
Limestone and Dolomite Use ^|
Aluminum Production |
Adipic Acid f
Semiconductor Manufacture |
Soda Ash Manufacture and Consumption |
Petrochemical Production |
Magnesium Production and Processing |
Titanium Dioxide Production |
Carbon Dioxide Consumption |
Ferroalloy Production |
Phosphoric Acid Production |
Zinc Production
Lead Production < 0.5
Silicon Carbide Production and Consumption < 0.5
Industrial Processes
as a Portion of all Emissions
4.5%
25
50 75
TgCO2Eq.
100
125
Figure 2-9: 2006 Industrial Processes Chapter Greenhouse Gas Sources
Agricultural Soil
Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
265.0
Agriculture as a Portion of all
Emissions
6.4%
50
100
TgC02Eq.
150
200
Figure 2-10: 2006 Agriculture Chapter GHG Sources
-------
Landfills
Waste as a Portion of
all Emissions
2.3%
Composting
I
20 40 60 80 100 120 140
TgCO2Eq.
Figure 2-1 1 : 2006 Waste Chapter Greenhouse Gas Sources
2,500 -,
2,000 -
.
O
o
0) 1 ,000 -
500
Electricity Generation
Transportation
Industry
Agriculture
. Commercial
Residential
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 2-12: Emissions Allocated to Economic Sectors
-------
2,500 -,
2,000
S 1,500 -
ra 1,000
500
0
Industrial
Transportation
Residential (gray)
Commercial (black)
Agriculture
O)O)O)O)O)O)O)O)O)O)OOOOOOO
O)O)O)O)O)O)O)O)O)O)OOOOOOO
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors
170 -,
160 -
150 -
§ 140
7\ 130 -
I 120 -
^ 11°
v
s i°°
90 -
80 -
70 -
Real GDP
Population
Emissions per
capita
Emissions per
$GDP
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product
-------
-------
3. Energy
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting for
86 percent of total emissions on a carbon dioxide (CO2) equivalent basis in 2006. This included 97, 37, and 13
percent of the nation's CO2, methane (CH4), 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 28,193 Tg of CO2 were added to the atmosphere
through the combustion of fossil fuels in 2005, of which the United States accounted for about 20 percent.l Due to
the relative importance of fossil fuel combustion-related CO2 emissions, they are considered separately, and in more
detail than other energy-related emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N2O, as well
as indirect greenhouse gases such as nitrogen oxides (NOX), carbon monoxide (CO), and non-CH4 volatile organic
compounds (NMVOCs). Mobile fossil fuel combustion was the second largest source of N2O emissions in the
United States, and overall energy-related activities were collectively the largest source of these indirect greenhouse
gas emissions.
Figure 3-1: 2006 Energy Chapter Greenhouse Gas Sources
Figure 3-2: 2006 U.S. Fossil Carbon Flows (Tg CO2 Eq.)
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. CO2 emissions from these
activities, however, are not included in national emissions totals because biomass fuels are of biogenic origin. It is
assumed that the C released during the consumption of biomass is recycled as U.S. forests and crops regenerate,
causing no net addition of CO2 to the atmosphere. The net impacts of land-use and forestry activities on the C cycle
are accounted for separately within the Land Use, Land-Use Change, and Forestry chapter. Emissions of other
greenhouse gases from the combustion 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 teragrams of CO2 equivalents (Tg CO2 Eq.),
while unweighted gas emissions in gigagrams (Gg) are provided in Table 3-2. Overall, emissions due to energy-
related activities were 6,076.9 Tg CO2 Eq. in 2006, an increase of 17 percent since 1990.
Table 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.)
1 Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Annual 2005 EIA (2007).
Energy 3-1
-------
Gas/Source
C02
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
Natural Gas Systems
Municipal Solid Waste
Combustion
Petroleum Systems
Wood Biomass and Ethanol
Consumption *
International Bunker Fuels*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground
Coal Mines
Mobile Combustion
International Bunker Fuels*
N2O
Mobile Combustion
Stationary Combustion
Municipal Solid Waste
Combustion
International Bunker Fuels*
Total
1990 =
4,886.4^
4,724.1^
1,809.6 =
1,485.1 =
844.9 =
340.1^
216.1 =
28.3^
117.2=:
33.7^
10.9m
0AM
219.3JJI
113.7ii
260.8 H
124.7^
84.1 =
33.9^
7.4^
6.0^
4.7H
43.5^
12.8 =
i.om
5,203.9 =
=
M 5,215.5'M
1 5,032.4^
1 1,939.3^
1 1,599.4^
= 876.5^
1 356.5^
1 225.8^
1 35.0s;
1 133.2&J
1 33.8^
I 15. 7^
1 0.3JJI
1
m 100.6JJJI
M 246.8s;
M 128.1==
M 67.1&J
M 32.0&J
Hi
8*) ^=
.2^=
m
a
m
M 53.4^
m 13.4&J
1
a
= 5,529.6^
= 2000
M 5,765.7
M 5,577.1
M 2,282.3
1 1,798.2
= 860.3
1 372.1
1 228.0
OH 36.2
1 141.4
Hi 29.4
1 17.5
M 0.3
1 227.3
a 101.1
M 234.5
M 126.5
M 60.4
M 30.3
M 6.7
1 7.4
M 3.4
M 0.1
M 67.5
M 52.5
M 14.6
1 0.4
M 0.9
= 6,067.8
2001
5,686.4
5,507.4
2,244.3
1,775.6
852.5
363.6
222.3
49.0
131.9
28.8
18.0
0.3
203.2
97.6
232.0
125.3
60.3
30.2
6.2
6.7
o o
J.J
0.1
64.4
49.9
14.1
0.4
0.9
5,982.8
2002
5,749.1
5,564.8
2,253.7
1,828.9
854.8
360.5
222.8
44.0
135.9
29.6
18.5
0.3
204.4
89.1
226.9
124.9
56.8
29.9
6.2
6.2
3.0
0.1
60.4
45.9
14.0
0.4
0.8
6,036.3
2003
5,796.6
5,617.0
2,283.1
1,807.6
856.0
382.9
236.5
51.0
131.8
28.4
19.1
0.3
209.5
103.6
224.6
123.3
56.9
29.2
6.4
6.0
2.7
0.1
57.1
42.3
14.4
0.4
0.9
6,078.3
2004
5,878.8
5,681.4
2,314.9
1,856.4
857.7
368.3
230.6
53.5
148.9
28.1
20.1
0.3
224.8
119.0
217.4
114.0
59.8
28.7
6.6
5.8
2.6
0.1
54.7
39.7
14.6
0.4
1.1
6,150.9
2005
5,920.5
5,731.0
2,380.2
1,869.8
847.3
358.5
221.9
53.2
139.1
29.5
20.7
0.3
22 7. 4
122.6
202.4
102.5
57.1
28.3
6.5
5.6
2.5
0.2
51.5
36.3
14.8
0.4
1.1
6,174.4
2006
5,825.6
5,637.9
2,328.2
1,856.0
862.2
326.5
210.1
54.9
138.0
28.5
20.9
0.3
234.7
127.1
203.3
102.4
58.5
28.4
6.2
5.4
2.4
0.2
48.0
33.1
14.5
0.4
1.1
6,076.9
* These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to independent rounding.
Table 3-2: CO2, CH4, and N2O Emissions from Energy (Gg)
Gas/Source
C02
Fossil Fuel
Combustion
Non-Energy Use
of Fuels
Natural Gas
Systems
Municipal Solid
Waste
Combustion
Petroleum
Systems
Wood Biomass
and Ethanol
Consumption *
1990^
4,886,370&i
4,724,
117,170|
33'729B
10,950|
376^
2 19, 34 M
= 1995 =
H 5,215,5091;
15.032,4161
M 133,2341
1 33,8061
1 15,7121
1 34ll
1 2 3 6,77 5M
m 2000
1^5,765,732
(5,577,072
B 141,427
B 29,390
B 17,518
H 325
M 227,276
2001
5,686,382
5,507,406
131,887
28,793
17,971
325
203,163
2002
5,749,059
5,564,795
135,857
29,629
18,458
320
204,351
2003
5,796,639
5,617,047
131,772
28,445
19,058
316
209,537
2004
5,878,815
5,681,363
148,931
28,122
20,097
302
224,825
2005
5,920,526
5,731,045
139,057
29,462
20,673
287
227,366
2006
5,825,631
5,637,931
137,980
28,504
20,922
293
234, 726
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
International
Bunker Fuels*
CH4
Natural Gas
Systems
Coal Mining
Petroleum
Systems
Stationary
Combustion
Abandoned
Underground
Coal Mines
Mobile
Combustion
International
Bunker Fuels*
N2O
Mobile
Combustion
Stationary
Combustion
Municipal Solid
Waste
Combustion
International
Bunker Fuels*
113,683^=
12,417^
5,937^
4,003^
8JJi
183^
3M
= 100,627=
1 11,754^
1
1 3,193^
1 1,524^
1
1
1
1 6Jji
1
1
1
1
1 3^
1 ^07,725
| 11,168
1 6,024
1 2'874
1 1,442
1 316
1 35°
1 162
1 6
1 218
1 169
1 47
1 1
1 3
97,563
11,048
5,968
2,874
1,436
295
319
157
5
208
161
46
1
3
89,101
10,804
5,946
2,707
1,422
295
293
141
4
195
148
45
1
3
103,583
10,693
5,874
2,709
1,390
306
284
131
6
184
137
46
1
3
118,975
10,353
5,426
2,846
1,368
311
276
126
7
176
128
47
1
3
122,580
9,636
4,880
2,717
1,346
308
265
119
7
166
117
48
1
4
127,097
9,679
4,877
2,784
1,354
296
257
112
7
155
107
47
1
4
* 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.
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source
Category 1A)
CO2 emissions from fossil fuel combustion in 2006 decreased by 1.6 percent from the previous year. This decrease
is primarily a result of the restraint on fuel consumption caused by rising fuel prices, primarily in the transportation
sector, an increase in the cost of electricity, and decreases in the cost of natural gas. Additionally, warmer winter
conditions in 2006 decreased the demand for heating fuels. In 2006, CO2 emissions from fossil fuel combustion
were 5,637.9 Tg CO2 Eq., or 19 percent above emissions in 1990 (see Table 3-3).2
Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.)
Fuel/Sector
Coal
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas
1990^
1,698.
2.
11.
152.
9=
9^
8^
3^
m 1995 =
1 1,805
m i
i 11
m 143
.4 =
.7 =
•1 =
•0 =
NE^
1,531. ~~
0.
1,011.
3 =
611
511
m 1,648
1 0
1 1,172
.7 =
.9 =
.0 =
g 2000
g 2,053.2
1 i.o
1 8.2
g 133.5
1 NE
g 1,909.6
g 0.9
g 1,220.5
2001
1,996.3
1.0
8.4
133.5
NE
1,852.3
1.0
1,175.3
2002
2,002.8
1.1
8.4
123.4
NE
1,868.3
1.7
1,227.6
2003
2,043.1
1.2
7.9
124.0
NE
1,906.2
3.8
1,200.3
2004
2,058.4
1.2
9.7
126.2
NE
1,917.6
3.6
1,180.1
2005
2,094.1
0.9
9.2
122.0
NE
1,958.4
3.7
1,173.9
2006
2,065.3
0.6
6.2
122.0
NE
1,932.4
4.1
1,155.1
'• An additional discussion of fossil fuel emission trends is presented in the Trends in U.S. Greenhouse Gas Emissions Chapter.
Energy 3-3
-------
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Geothermal*
Total
239.8^
143.1 =
416.3^
36.1 =
176.2^
NO^
2,013.3H
97.4^
61.2=
276.3^
1,449.0=
101.8=
27.6^
0.40^
4,724.1^
1 264
1 165
1 474
1 38
1 229
i N
1 2,054
1 90
1 49
1 259
1 1,561
1 60
1 34
.4 =
.4 =
.4 =
.4 =
.5 =
"O^
•7=
•5 =
.0^
.0 =
.7 =
.0 =
1 0.34^
1 5,032
.4 =
=5 270.6
H 172.7
1 460.0
g 35.7
g 280.9
m 0.7
g 2,303.0
g 100.5
H 47.2
g 266.8
g 1,762.5
g 91.5
g 34.6
1 0.36
g 5,577.1
260.3
165.1
425.0
34.1
289.6
1.2
2,335.5
102.2
48.8
294.0
1,741.6
102.0
46.8
0.35
5,507.4
265.0
171.0
447.2
37.2
306.0
1.2
2,334.0
94.4
43.4
284.3
1,791.7
79.1
41.1
0.37
5,564.8
277.5
176.7
433.0
33.4
278.3
1.4
2,373.3
104.2
51.8
299.1
1,774.2
98.1
45.8
0.37
5,617.0
264
170
415
32
296
1
2,442
102
50
316
1,824
100
48
.5
.0
.5
.0
.8
.3
.5
.5
.9
.0
.4
.1
.6
0.38
5,681
.4
262.7
163.2
394.5
33.2
319.1
1.3
2,462.7
95.0
49.6
330.9
1,836.7
102.3
48.2
0.38
5,731.0
237.5
154.1
389.3
33.2
339.6
1.4
2,417.1
88.5
49.8
350.9
1,822.8
55.7
49.4
0.38
5,637.9
NE (Not estimated)
NO (Not occurring)
* Although not technically a fossil fuel, geothermal energy-related CO2 emissions are included for reporting purposes.
Note: Totals may not sum due to independent rounding.
Trends in CO2 emissions from fossil fuel combustion are influenced by many long-term and short-term factors. On
a year-to-year basis, the overall demand for fossil fuels in the United States and other countries generally fluctuates
in response to changes in general economic conditions, energy prices, weather, and the availability of non-fossil
alternatives. For example, in a year with increased consumption of goods and services, low fuel prices, severe
summer and winter weather conditions, nuclear plant closures, and lower precipitation feeding hydroelectric dams,
there would likely be proportionally greater fossil fuel consumption than a year with poor economic performance,
high fuel prices, mild temperatures, and increased output from nuclear and hydroelectric plants.
Longer-term changes in energy consumption patterns, however, tend to be more a function of aggregate societal
trends that affect the scale of consumption (e.g., population, number of cars, and size of houses), the efficiency with
which energy is used in equipment (e.g., cars, power plants, steel mills, and light bulbs), and social planning and
consumer behavior (e.g., walking, bicycling, or telecommuting to work instead of driving).
CO2 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 of the C per unit of energy as coal, and natural gas has only about 55 percent.3 Producing a
unit of heat or electricity using natural gas instead of coal can reduce the CO2 emissions associated with energy
consumption, and using nuclear or renewable energy sources (e.g., wind) can essentially eliminate emissions (see
Box 3-2). Table 3-4 shows annual changes in emissions during the last five years for coal, petroleum, and natural
gas in selected sectors.
Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg CO2
Eq. and Percent)
Sector
Electricity Generation
Electricity Generation
Electricity Generation
Transportation a
Residential
Fuel Type
Coal
Natural Gas
Petroleum
Petroleum
Natural Gas
2002 to 2003
38
-27
19
-17.
12
.0
.6
.0
.5
.5
2.0%
-9.0%
24.0%
-1.0%
4.7%
2003 to 2004
11
18
2.
50
-12
.4
.5
.0
.2
.9
0.6%
6.6%
2.0%
2.8%
-4.7%
2004 to 2005
40.8
22.3
2.2
12.3
-1.9
2.1%
7.5%
2.2%
0.7%
-0.7%
2005 to 2006
-26.0
20.5
-46.6
-13.9
-25.2
-1.3%
6.4%
-45.5%
-0.8%
-9.6%
1 Based on national aggregate carbon content of all coal, natural gas, and petroleum fuels combusted in the United States.
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Commercial
Industrial
Industrial
All Sectors b
Natural Gas
Coal
Natural Gas
All Fuels b
5.7
0.6
-14.2
52.3
3.3%
0.5%
-3.2%
0.9%
-6
2
-17
64
.7
o
.J
.5
.3
-3.8%
1.8%
-4.0%
1.1%
-6.8
-4.3
-21.0
49.7
-4.0%
-3.4%
-5.1%
0.9%
-9.
0.
-5.
-93.
1
1
2
1
-5.6%
0.1%
-1.3%
-1.6%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
In the United States, 82 percent of the energy consumed in 2006 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 (9 percent), primarily
hydroelectric power and biofuels (EIA 2007a). Specifically, petroleum supplied the largest share of domestic
energy demands, accounting for an average of 43 percent of total fossil fuel based energy consumption in 2006.
Coal and natural gas followed in order of importance, each accounting for 28 percent of total consumption.
Petroleum was consumed primarily in the transportation end-use sector, the vast majority of coal was used in
electricity generation, and natural gas was broadly consumed in all end-use sectors except transportation (see Figure
3-5) (EIA 2007a).
Figure 3-3: 2006 U.S. Energy Consumption by Energy Source
Figure 3-4: U.S. Energy Consumption (QuadrillionBtu)
Figure 3-5: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
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 the C in fossil fuels used to produce energy is eventually converted to atmospheric CO2.
[BEGIN BOX]
Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends
In 2006, weather conditions became warmer in the winter and slightly cooler in the summer, compared to 2005.
4 See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-CO2 gas
emissions from fossil fuel combustion.
Energy 3-5
-------
The winter was significantly warmer than usual, with heating degree days in the United States 12 percent below
normal (see Figure 3-6). Warmer winter conditions led to a decrease in demand for heating fuels. Summer
temperatures were substantially warmer than usual, with cooling degree days 10 percent above normal (see Figure
3-7) (EIA 2007I),5 however the demand for electricity only increased slightly due to the cooler summer conditions
compared to 2005.
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2006)
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2006)
Although no new U.S. nuclear power plants have been constructed in recent years, the utilization (i.e., capacity
factors6) of existing plants in 2006 remained high at just under 90 percent. Electricity output by hydroelectric
power plants increased in 2006 by approximately 7 percent. Electricity generated by nuclear plants in 2006
provided almost 3 times as much of the energy consumed in the United States as hydroelectric plants (EIA 2007a).
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 (1974-2006)
[END BOX]
For the purpose of international reporting, the Intergovernmental Panel on Climate Change (IPCC)
(IPCC/UNEP/OECD/IEA 1997) recommends that particular adjustments be made to national fuel consumption
statistics. Certain fossil fuels can be manufactured into plastics, asphalt, lubricants, or other products. A portion of
the C consumed for these non-energy products can be stored (i.e., sequestered) indefinitely. To account for the fact
that the C in these fuels ends up in products instead of being combusted (i.e., oxidized and released into the
atmosphere), consumption of fuels for non-energy purposes is estimated and subtracted from total fuel consumption
estimates. Emissions from non-energy uses of fuels are estimated in the Carbon Emitted and Stored in Products
from Non-Energy Uses of Fossil Fuels section in this chapter.
According to the UNFCCC reporting guidelines, CO2 emissions from the consumption of fossil fuels for aviation
and marine international transport activities (i.e., international bunker fuels) should be reported separately, and not
5 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily
temperature below 65° F, while cooling degree days are deviations of the mean daily temperature above 65° F. Heating degree
days have a considerably greater affect on energy demand and related emissions than do cooling degree days. Excludes Alaska
and Hawaii. Normals are based on data from 1971 through 2000. The variation in these normals during this time period was
+10 percent and +14 percent for heating and cooling degree days, respectively (99 percent confidence interval).
6 The capacity factor is defined as the ratio of the electrical energy produced by a generating unit for a given period of time to
the electrical energy that could have been produced at continuous full-power operation during the same period (EIA 2007a).
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
included in national emission totals. Estimates of international bunker fuel emissions for the United States are
provided in Table 3-5, and explained in detail later in the chapter.
Table 3-5: CO2 Emissions from International Bunker Fuels (Tg CO2 Eq.)*
Vehicle Mode
Aviation
Marine
Total
1990^
45
68
113
3
1
|
3
1 2000
3 59.9
1 41.3
1 101.1
2001
58.7
38.9
97.6
2002
61.1
28.0
89.1
2003
58.
44.
103.
8
8
6
2004
64.9
54.1
119.0
2005
67.5
55.1
122.6
2006
71.1
56.0
127.1
* See International Bunker Fuels section for additional detail.
Note: Totals may not sum due to independent rounding.
End-Use Sector Consumption
An alternative method of presenting CO2 emissions is to allocate emissions associated with electricity generation to
the sectors in which it is used. Four end-use sectors were defined: industrial, transportation, residential, and
commercial. For the discussion below, electricity generation emissions have been distributed to each end-use sector
based upon the sector's share of national electricity consumption. This method of distributing emissions assumes
that each sector consumes electricity generated from an equally carbon-intensive mix of fuels and other energy
sources. After the end-use sectors are discussed, emissions from electricity generation are addressed separately.
Emissions from U.S. territories are also calculated separately due to a lack of end-use-specific consumption data.
Table 3-6 and Figure 3-9 summarize CO2 emissions from direct fossil fuel combustion and pro-rated electricity
generation emissions from electricity consumption by end-use sector.
Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity
Generation
1990^
1,488.1^
1,485.1^
3.0^
1,527.5^
844.9^
682.5^
929.5^
340.1^
589.4^
750.8^
216.1^
534.7^
28.3^
4,724.1^
1,809.6^
=
I 1,602.5^
I 1,599.4^
I
I 1,589.5^
= 876.5^
I 713.1^
I
I 356.5^
1 639.0^
I 810.0^
I 225.8^
I 584.2^
I
= 5,032.4^
1 1,939.3^
= 2000
I 1
I 1
I 1
I 1
= 5
1 2
,801
,798
3
,645
860
784
,129
372
757
964
228
736
36
,577
,282
.6
.2
.4
.1
.3
.7
.7
.1
.6
.6
.0
.6
.2
.1
.3
2001
1,779.2
1,775.6
3.6
1,583.9
852.5
731.4
1,121.8
363.6
758.1
973.5
222.3
751.1
49.0
5,507.4
2,244.3
2002
1,832.3
1,828.9
3.4
1,572.5
854.8
717.7
1,145.6
360.5
785.1
970.3
222.8
747.5
44.0
5,564.8
2,253.7
2003
1,811.8
1,807.6
4.2
1,592.1
856.0
736.1
1,178.3
382.9
795.4
983.8
236.5
747.3
51.0
5,617.0
2,283.1
2004
1,860.9
1,856.4
4.5
1,596.8
857.7
739.0
1,173.1
368.3
804.9
997.1
230.6
766.5
53.5
5,681.4
2,314.9
2005
1,874.5
1,869.8
4.7
1,579.6
847.3
732.3
1,206.4
358.5
847.9
1,017.3
221.9
795.4
53.2
5,731.0
2,380.2
2006
1,861.0
1,856.0
4.9
1,567.1
862.2
704.9
1,151.9
326.5
825.4
1,003.0
210.1
792.9
54.9
5,637.9
2,328.2
Note: Totals may not sum due to independent rounding. Emissions from fossil fuel combustion by electricity generation are
allocated based on aggregate national electricity consumption by each end-use sector.
Figure 3-9: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
Energy 3-7
-------
Transportation End-Use Sector
The transportation end-use sector accounted for 1,861.0 Tg CO2 in 2006, representing 33 percent of total CO2
emissions from fossil fuel combustion; the largest share of any end-use economic sector7. Fuel purchased in the
U.S. for international aircraft and marine travel accounted for an additional 127.1 Tg CO2 in 2006; 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 62 percent of CO2 emissions, medium- and heavy-duty trucks 22 percent, domestic commercial aircraft
7.6 percent, and other sources just over 8 percent. (See Table 3-7 for a detailed breakdown of CO2 emissions by
mode and fuel type.)
Domestic transportation CO2 emissions increased by almost 25 percent (372.9 Tg) between 1990 and 2006, an
annualized increase of 1.5 percent. From 2005 to 2006 transportation CO2 emissions decreased by 0.7 percent.
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 CH4 and N2O; these emissions are included
beginning in Table 3-21 the "Mobile Combustion" Section. Annex 3.2 presents total emissions from all
transportation and mobile sources, including CO2, N2O, CH4, and HFCs.
Carbon dioxide emissions from passenger cars and light-duty trucks totaled 1,151.3 Tg in 2006, an increase of 21
percent (200.1 Tg) from 1990. The increase in light-duty CO2 emissions is due primarily to the growth in vehicle
travel, which substantially outweighed improvements in vehicle fuel economy. Light-duty vehicle miles traveled
(VMT) increased 39 percent from 1990 to 2006; average vehicle fuel economy increased from 18.9 miles per gallon
(mpg) in 1990 to 20.4 mpg in 2006, primarily reflecting the retirement of older vehicles. Among new vehicles sold
annually, average fuel economy gradually declined from 1990 to 2006 (Figure 3-10), reflecting substantial growth
in sales of light-duty trucks relative to passenger cars (Figure 3-11). Average new vehicle fuel economy improved
in 2005 and 2006 as the market share of passenger cars increased in response to rising fuel prices.
Figure 3-10: Sales-Weighted Fuel Economy of New Passenger Cars and Light-Duty Trucks, 1990-2006
Figure 3-11: Sales of New Passenger Cars and Light-Duty Trucks, 1990-2006
Medium- and heavy-duty truck8 CO2 emissions increased by 76 percent (173.4 Tg) from 1990 to 2006,
representing the largest percentage increase of any major transportation mode. Fuel economy for the medium- and
heavy-duty truck fleet did not significantly improve over this period, and most likely declined from levels recorded
in the late 1990s. Meanwhile, medium- and heavy-duty truck VMT increased by 52 percent. CO2 from the
domestic operation of commercial aircraft increased by 4 percent (5.4 Tg) from 1990 to 2006, well below the
growth in travel activity (passenger miles traveled grew by 69 percent from 1990 to 2005, the most recent year of
available data). 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 aviation9, CO2 emissions decreased by
approximately 5.2 percent (9.4 Tg CO2) between 1990 and 2006. This decline reflects a 56 percent decrease in
7 Note that electricity generation is the largest emitter of CO2 when electricity is not distributed among end-use sectors.
8 Includes "medium- and heavy-duty trucks" fueled by gasoline, diesel and LPG.
9 Includes consumption of jet fuel and aviation gasoline. Does not include aircraft bunkers, which are not accounted for in
national emission totals.
3-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
emissions from domestic military operations, which more than offset a small increase in domestic commercial and
general aviation emissions. For further information on all greenhouse gas emissions from transportation sources,
please refer to Table A-108 in Annex 3.2.
Table 3-7: CO2 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO2 Eq.)E
Fuel/Vehicle Type
Gasoline
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty
Trucks'3
Buses
Motorcycles
Recreational Boats
Distillate Fuel Oil (Diesel)
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty
Trucksb
Buses
Rail
Recreational Boats
Ships and Other Boats
Ships (Bunkers)
Jet Fuel
Commercial Aircraft -
Domestic
Military Aircraft
General Aviation Aircraft
Aircraft (Bunkers)
Aviation Gasoline
General Aviation Aircraft
Residual Fuel Oil
Ships and Other Boats0
Ships (Bunkers) c
Natural Gas
Passenger Cars
Light-Duty Trucks
Buses
Pipeline
LPG
Light-Duty Trucks
Medium- and Heavy-Duty
Trucksb
Buses
Electricity
Rail
Total (Including Bunkers) d
Total (Excluding Bunkers) d
19901=
982.8i
621.0^
308.9p
38.7i
0.3i
1.7i
12.1i
272.7m
7.8i
11.3m
188.3|
7.9p
35.1i
1.9i
8.8i
11.6i
222.6m
136.7m
33.9i
6.3|
45.7m
3.1i
3.1i
so.ii
23.7i
56.4i
36.1|
+m
+m
+m
36. im
i.4i
0.5i
o.si
+m
3.oi
3.0i
l,601.8p
1,488.11
* 1995^
1 l,038.9p
1 597.0^
i 389.9p
1 35. 8p
i 0.4p
i
i u.im
i 325.1P
i 7.7m
1 14.7m
1 234.9P
i
i 39.2m
i
8/-JZZ:
.O^
i
1 222.1m
i 143. lp
1 23.5m
i 5.3m
i 50.2m
i 2.7m
i 2.7m
i 71.7m
i 30.5m
i 4i.2m
i 38.4P
1 0-ip
1 +m
i o.ip
i 38.2p
i i.ip
i o.sp
i o.sp
i
i
1 l,703.1p
1 1,602.5^
1 2000
i 1,135.7
1 639.9
1 446.0
1 36.0
1 0.4
1 1.8
1 11.6
1 401.0
1 3.6
1 19.8
1 305.1
1 10.1
1 41.7
1 2.7
1 H.7
1 6.3
1 253.8
1 164.2
1 20.5
1 9.2
1 59.9
1 2.5
1 2.5
1 69.9
1 34.9
1 35.0
1 35-7
1 +
1 +
1 0.4
1 35.2
1 0.7
1 0.3
1 0.4
1 +
1 3.4
1 3.4
1 1,902.7
1 1,801.6
2001
1,145.4
644.2
449.4
35.0
0.4
1.7
14.6
401.6
3.6
20.6
305.1
9.2
41.8
2.8
13.2
5.3
242.8
152.9
22.5
8.8
58.7
2.4
2.4
46.1
12.6
33.6
34.1
+
+
0.5
33.6
0.8
0.3
0.5
+
3.6
3.6
1,876.8
1,779.2
2002
1,172.3
658.9
461.3
35.5
0.3
1.7
14.6
415.1
3.7
21.6
318.8
8.7
41.5
2.9
12.8
5.1
236.8
146.1
20.4
9.1
61.1
2.3
2.3
53.3
30.5
22.8
37.2
+
+
0.6
36.6
0.8
0.3
0.5
+
3.4
3.4
1,921.4
1,832.3
2003
1,176.5
638.0
491.5
30.6
0.3
1.6
14.5
421.8
4.2
26.9
320.0
9.4
42.4
3.0
8.3
7.6
231.5
143.9
19.9
8.8
58.8
2.1
2.1
45.0
7.8
37.2
33.4
+
+
0.7
32.7
1.0
0.4
0.6
+
4.2
4.2
1,915.4
1,811.8
2004
1,194.8
635.8
511.6
30.9
0.4
1.7
14.4
447.2
4.3
28.8
332.5
13.4
44.7
3.0
10.0
10.5
239.8
142.9
20.4
11.5
64.9
2.2
2.2
58.3
14.7
43.6
32.0
+
+
0.8
31.2
1.1
0.4
0.7
+
4.5
4.5
1,979.8
1,860.9
2005
1181.2
654.2
476.0
34.7
0.4
1.6
14.3
462.2
4.2
25.5
356.5
10.6
45.1
3.1
7.9
9.3
246.3
150.4
16.9
11.4
67.5
2.4
2.4
66.0
20.2
45.8
33.2
+
+
0.8
32.3
1.1
0.4
0.6
+
4.7
4.7
1,997.1
1,874.5
2006
1,170.0
630.4
488.0
35.2
0.4
1.9
14.1
472.1
4.1
26.4
365.4
10.9
46.0
3.205
7.4
8.7
239.5
142.1
14.8
11.4
71.1
2.3
2.3
64.9
17.7
47.2
33.2
+
+
0.8
32.4
1.1
0.4
0.6
+
4.9
4.9
1,988.1
1,861.0
Note: Totals may not sum due to independent rounding. Emissions estimates for passenger cars, light-duty trucks and heavy-
duty trucks are calculated using fuel consumption data from FHWA's Highway Statistics, which used an updated methodology to
develop the 2005 and 2006 estimates This causes some discontinuity in the emissions estimates for gasoline and diesel on-road
vehicles between 2004 and 2005.
a This table does not include emissions from non-transportation mobile sources, such as agricultural equipment and
Energy 3-9
-------
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.
0 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.
d Official estimates exclude emissions from the combustion of both aviation and marine international bunker fuels; however,
estimates including international bunker fuel-related emissions are presented for informational purposes.
+ Less than 0.05 Tg CO2 Eq.
Industrial End-Use Sector
The industrial end-use sector accounted for 28 percent of CO2 emissions from fossil fuel combustion. On average,
55 percent of these emissions resulted from the direct consumption of fossil fuels for steam and process heat
production. The remaining 45 percent was associated with their consumption of electricity for uses such as motors,
electric furnaces, ovens, and lighting.
The industrial end-use 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 2007a and EIA 2005).
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.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 2005 to 2006, total industrial production and manufacturing output increased by 3.9 and 4.9 percent,
respectively (FRB 2006). Over this period, output increased for Petroleum Refineries, Chemicals, Primary Metals,
Food, and Nonmetallic Mineral Products, but decreased slightly for Paper (see Figure 3-12).
Figure 3-12: Industrial Production Indices (Index 2002=100)
Despite the growth in industrial output (62 percent) and the overall U.S. economy (59 percent) from 1990 to 2006,
CO2 emissions from the industrial end-use sector increased by only 3.0 percent over that time. A number of factors
are believed to have caused this disparity between rapid growth in industrial output and decrease in industrial
emissions, including: (1) more rapid growth in output from less energy-intensive industries relative to traditional
manufacturing industries, and (2) improvements in energy efficiency. In 2006, CO2 emissions from fossil fuel
combustion and electricity use within the industrial end-use sectors were 1,571.0 Tg CO2 Eq., or 0.8 percent below
2005 emissions.
Residential and Commercial End-Use Sectors
The residential and commercial end-use sectors accounted for an average 20 and 18 percent, respectively, of CO2
emissions from fossil fuel combustion. Both end-use sectors were heavily reliant on electricity for meeting energy
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.
3-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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. The
remaining emissions 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 2006, CO2 emissions from fossil fuel combustion and electricity use within the residential and
commercial end-use sectors were 1,151.9 Tg CO2 Eq. and 1,003.0 Tg CO2 Eq., respectively.
Emissions from the residential and commercial sectors have generally been increasing since 1990, and are often
correlated with short-term fluctuations in energy consumption caused by weather conditions, rather than prevailing
economic conditions (see Table 3-6). In the long-term, both end-use sectors are also affected by population growth,
regional migration trends, and changes in housing and building attributes (e.g., size and insulation).
Emissions from natural gas consumption represent over 72 and 73 percent of the direct (not including electricity)
fossil fuel emissions from the residential and commercial sectors, respectively. In 2006, natural gas emissions
decreased by 10 percent and 6 percent, respectively, in each of these sectors. The decrease in emissions in both
sectors is a result of warmer conditions in the United States.
Electricity sales to the residential and commercial end-use sectors in 2006 decreased less than 1 percent in the
residential sector and increased by 2 percent in the commercial sector. The trend in the commercial sector can
largely be attributed to the growing economy (2.9 percent), which led to increased demand for electricity. Increased
consumption due to the growing economy was somewhat offset by decreased air conditioning-related electricity
consumption in the residential sector with the cooler summer compared to 2005, and increases in electricity prices.
Electricity-related emissions in both the residential and commercial sectors decreased due to decreased
consumption; total emissions from the residential sector decreased by 8.9 percent in 2006, with emissions from the
commercial sector 5.3 percent lower than in 2005.
Electricity Generation
The process of generating electricity is the single largest source of CO2 emissions in the United States, representing
39 percent of total CO2 emissions from all CO2 emissions sources across the United States. Electricity generation
also accounted for the largest share of CO2 emissions from fossil fuel combustion, approximately 41 percent in
2006. 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 3-13).
Figure 3-13: Electricity Generation Retail Sales by End-Use Sector
The electric power industry includes all power producers, consisting of both regulated utilities and nonutilities (e.g.
independent power producers, qualifying cogenerators, and other small power producers). For the underlying
energy data used in this chapter, the Energy Information Administration (EIA) categorizes electric power generation
into three functional categories: the electric power sector, the commercial sector, and the industrial sector. The
electric power sector consists of electric utilities and independent power producers whose primary business is the
production of electricity,1 J while the other sectors consist of those producers that indicate their primary business is
other than the production of electricity.
11 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).
Energy 3-11
-------
In 2006, the amount of electricity generated (in kWh) increased by 0.1 percent. This growth is due to the growing
economy, expanding industrial production, and warmer summer conditions. However, CO2 emissions decreased by
2.2 percent, as a smaller share of electricity was generated by coal and a greater share generated by natural gas.
Coal and natural gas consumption for electricity generation decreased by 1.3 percent and increased by 6.4 percent,
respectively, in 2006, and nuclear power increased by less than 1 percent. As a result of the decrease in coal
consumption, C intensity from direct fossil fuel combustion decreased slightly overall in 2006 (see Table 3-8). 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 2006. The amount of electricity generated from renewables increased by 8.1
percent in 2006.
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 2007b). The United States does not include territories in
its national energy statistics, so fuel consumption data for territories were collected separately from Grillot
(2007).12
For consistency of reporting, the IPCC has recommended that countries report energy data using the
International Energy Agency (IEA) reporting convention and/or IEA data. Data in the IEA format are
presented "top down"—that is, energy consumption for fuel types and categories are estimated from energy
production data (accounting for imports, exports, stock changes, and losses). The resulting quantities are
referred to as "apparent consumption." The data collected in the United States by EIA, and used in this
inventory, are, instead, "bottom up" in nature. In other words, they are collected through surveys at the point of
delivery or use and aggregated to determine national totals.13
It is also important to note that U.S. fossil fuel energy statistics are generally presented using gross calorific
values (GCV) (i.e., higher heating values). Fuel consumption activity data presented here have not been
adjusted to correspond to international standard, which are to report energy statistics in terms of net calorific
values (NCV) (i.e., lower heating values).14
2. Subtract uses accounted for in the Industrial Processes chapter. Portions of the fuel consumption data for six
fuel categories—coking coal, industrial other coal, petroleum coke, natural gas, residual fuel oil, and other
oil—were reallocated to the industrial processes chapter, as they were consumed during non-energy related
industrial activity. To make these adjustments, additional data were collected from AISI (1995 through 2007),
Gambogi (2007), Coffeyville Resources Nitrogen Fertilizers, LLC (2007), Corathers (2007), U.S. Census
Bureau (2007), EIA (2007h), EIA (2001), Smith, G. (2007), USGS (1998 through 2002), USGS (1995), USGS
12 Fuel consumption by U.S. territories (i.e., American Samoa, Guam, Puerto Rico, U.S. Virgin Islands, Wake Island, and other
U.S. Pacific Islands) is included in this report and contributed emissions of 55 Tg CO2 Eq. in 2006.
13 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.
14 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.
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
(1991a through 2006a), USGS (199Ib through 2006b), USGS (1991 through 2005), andUSGS (1995 through
2006).15
3. Adjust for biofuels, conversion of fossil fuels, and exports ofCO2. Fossil fuel consumption estimates are
adjusted downward to exclude (1) fuels with biogenic origins, (2) fuels created from other fossil fuels, and (3)
exports of CO2. Fuels with biogenic origins are assumed to result in no net CO2 emissions, and must be
subtracted from fuel consumption estimates. These fuels include ethanol added to motor gasoline and biomass
gas used as natural gas. Synthetic natural gas is created from industrial coal, and is currently included in EIA
statistics for both coal and natural gas. Therefore, synthetic natural gas is subtracted from energy consumption
statistics.16 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 (2007b) and data for synthetic natural gas were collected from EIA (2007e),
and data for CO2 exports were collected from the Dakota Gasification Company (2006), Fitzpatrick (2002),
Erickson (2003), EIA (2006), and EIA (2007e).
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 FHWA Vehicle Miles Traveled (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 higher to match the value obtained from the bottom-up analysis based on
VMT. As the total distillate consumption estimate from EIA is considered to be accurate at the national level,
the distillate consumption totals for the residential, commercial, and industrial sectors were adjusted downward
proportionately. 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 (2007), Benson (2002 through 2004), DOE (1993 through 2005), EIA (2007a), EIA (1991
through 2005), EPA (2004), and FHWA (1996 through 2006).
5. Adjust for fuels consumed for non-energy uses. U.S. aggregate energy statistics include consumption of fossil
fuels for non-energy purposes. Depending on the end-use, this can result in storage of some or all of the C
contained in the fuel for a period of time. As the emission pathways of C used for non-energy purposes are
vastly different than fuel combustion, these emissions are estimated separately in the Carbon Emitted and
Stored in Products from Non-Energy Uses of Fossil Fuels section in this chapter. Therefore, the amount of
fuels used for non-energy purposes was subtracted from total fuel consumption. Data on non-fuel consumption
was provided by EIA (2007b).
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).17 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 2007) supplied data on military jet fuel and marine fuel use.
Commercial jet fuel use was obtained from BEA (1991 through 2007) and DOT (1991 through 2007); residual
and distillate fuel use for civilian marine bunkers was obtained from DOC (1991 through 2007) for 1990
through 2002, and DHS (2008) for 2003 through 2008. Consumption of these fuels was subtracted from the
15 See sections on Iron and Steel Production, Ammonia Manufacture, Petrochemical Production, Titanium Dioxide Production,
Ferroalloy Production, Aluminum Production, and Silicon Carbide Production in the Industrial Processes chapter.
16 These adjustments are explained in greater detail in Annex 2.1.
17 See International Bunker Fuels section in this chapter for a more detailed discussion.
Energy 3-13
-------
corresponding fuels in the transportation end-use sector. Estimates of international bunker fuel emissions are
discussed further in the section entitled International Bunker Fuels.
7. Determine the total C content of fuels consumed. Total C was estimated by multiplying the amount of fuel
consumed by the amount of C in each fuel. This total C estimate defines the maximum amount of C that could
potentially be released to the atmosphere if all of the C in each fuel was converted to CO2. The C content
coefficients used by the United States were obtained from EIA's Emissions of Greenhouse Gases in the United
States 2006 (EIA 2007c) and EIA's Monthly Energy Review and published supplemental tables on petroleum
product detail EIA (EIA 2007b). 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 2006); for each vehicle category, the percent gasoline,
diesel, and other (e.g., CNG, LPG) fuel consumption are estimated using data from DOE (1993 through
2005).
• For non-road vehicles, activity data were obtained from AAR (2007), APTA (2007 and 2006), BEA (1991
through 2007), Benson (2002 through 2004), DOE (1993 through 2005), DESC (2007), DOC (1991 through
2007), DOT (1991 through 2007), EIA (2007a), EIA (2007d), EIA (2007g), EIA (2002), EIA (1991 through
2005), EPA (2004), FAA (2005), 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.18 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 (2007a) and USAF (1998).
19
[BEGIN BOX]
Box 3-2: Carbon Intensity of U.S. Energy Consumption
18 FAA's System for assessing Aviation's Global Emissions (SAGE) model develops aircraft fuel burn and emissions for all
commercial flights globally in a given year. The SAGE model dynamically models aircraft performance, fuel bum, and
emissions, and is based on actual flight-by-flight aircraft movements. See
-------
Fossil fuels are the dominant source of energy in the United States, and CO2 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
CO2 in the energy conversion process, such as renewable (i.e., hydropower, biofuels, geothermal, solar, and wind)
and nuclear sources.20
Energy-related CO2 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 CO2 Eq./QBtu for natural gas to upwards of 95 Tg CO2 Eq./QBtu for coal and petroleum coke.21
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 CO2
Eq./Btu). Energy generated from nuclear and many renewable sources do not result in direct emissions of CO2.
Biofuels such as wood and ethanol are also considered to be C neutral; although these fuels do emit CO2, in the long
run the CO2 emitted from biomass consumption does not increase atmospheric CO2 concentrations if the biogenic C
emitted is offset by the growth of new biomass.22 The overall C intensity of the U. S. economy is thus dependent
upon the quantity and combination of fuels and other energy sources employed to meet demand.
Table 3-8 provides a time series of the C intensity for each sector of the U.S. economy. The time series incorporates
only the energy consumed from the direct combustion of fossil fuels in each sector. For example, the C intensity for
the residential sector does not include the energy from or emissions related to the consumption of electricity for
lighting or wood for heat. Looking only at this direct consumption of fossil fuels, the residential sector exhibited
the lowest C intensity, which is related to the large percentage of its energy derived from natural gas for heating.
The C intensity of the commercial sector has predominantly declined since 1990 as commercial businesses shift
away from petroleum to natural gas. The industrial sector was more dependent on petroleum and coal than either
the residential or commercial sectors, and thus had higher C intensities over this period. The C intensity of the
transportation sector was closely related to the C content of petroleum products (e.g., motor gasoline and jet fuel,
both around 70 Tg CO2 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 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu)
Sector
Residential a
Commercial a
Industrial a
Transportation a
Electricity Generation b
U.S. Territories'
All Sectors c
1990^
57.3^
59.2^
63.7^
71.0^
86.71^
74.1 =
3
3
1
3
3
| 86.0^
3
1
1 2000
3 56.7
3 57.1
1 62.6
1 71.0
1 85.6
1 73.2
3 72.7
2001
56.9
57.4
63.5
71.0
85.2
73.6
72.7
2002
56.6
57.0
62.8
71.0
85.0
73.7
72.5
2003
56.8
57.3
63.2
71.0
85.7
74.0
72.7
2004
56.9
57.6
63.6
71.0
85.4
74.6
72.9
2005
56.6
57.6
64.0
71.1
85.0
74.6
73.1
2006
56.7
57.5
64.2
71.1
84.6
74.6
73.0
a Does not include electricity or renewable energy consumption.
b Does not include electricity produced using nuclear or renewable energy.
0 Does not include nuclear or renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
20 Small quantities of CO2, however, are released from some geologic formations tapped for geothermal energy. These
emissions are included with fossil fuel combustion emissions from the electricity generation. Carbon dioxide emissions may also
be generated from upstream activities (e.g., manufacture of the equipment) associated with fossil fuel and renewable energy
activities, but are not accounted for here.
21 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
22 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.
Energy 3-15
-------
In contrast to Table 3-8, Table 3-9 presents C intensity values that incorporate energy consumed from all sources
(i.e., fossil fuels, renewables, and nuclear). In addition, the emissions related to the generation of electricity have
been attributed to both electricity generation and the end-use sectors in which that electricity was eventually
consumed.23 This table, therefore, provides a more complete picture of the actual C intensity of each end-use sector
per unit of energy consumed. The transportation end-use sector in Table 3-9 emerges as the most C intensive when
all sources of energy are included, due to its almost complete reliance on petroleum products and relatively minor
amount of biomass-based fuels used, such as ethanol. The "other end-use sectors" (i.e., residential, commercial, and
industrial) use significant quantities of biofuels such as wood, thereby lowering the overall C intensity. The C
intensity of the electricity generation sector differs greatly from the scenario in Table 3-8, where only the energy
consumed from the direct combustion of fossil fuels was included. This difference is due almost entirely to the
inclusion of electricity generation from nuclear and hydropower sources, which do not emit CO2.
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg CO2 Eq./QBtu)
Sector
Transportation a
Other End-Use Sectors a' b
Electricity Generation °
All Sectors d
1990^
70.8^
57.5^
59.0^
61.1^
1
=
1
= 57.9^
=
1 2000
= 70.6
1 57.7
= 59.9
1 61.4
2001
70.5
58.4
60.2
61.8
2002
70.5
57.6
59.2
61.3
2003
70.3
58.0
59.8
61.5
2004
70.2
58.0
59.6
61.5
2005
70.1
58.2
59.9
61.6
2006
70.0
57.5
58.8
61.1
a Includes electricity (from fossil fuel, nuclear, and renewable sources) and direct renewable energy consumption.
b Other End-Use Sectors includes the residential, commercial, and industrial sectors.
0 Includes electricity generation from nuclear and renewable sources.
d Includes nuclear and renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
By comparing the values in Table 3-8 and Table 3-9, a few observations can be made. The use of renewable and
nuclear energy sources has resulted in a significantly lower C intensity of the U.S. economy. Over the sixteen-year
period of 1990 through 2006, 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 CO2 emissions per dollar of gross domestic product (GDP) have both
declined since 1990 (BEA 2007).
Figure 3-14: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and Per Dollar GDP
C intensity estimates were developed using nuclear and renewable energy data from EIA (2007a) and fossil fuel
consumption data as discussed above and presented in Annex 2.1.
[END BOX]
23 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.
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 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 2006. 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 inventory variables from the inventory estimation model for International Bunker Fuels, to realistically
characterize the interaction (or endogenous correlation) between the variables of these two models. About 150
input variables were modeled for CO2 from energy-related Fossil Fuel Combustion (including about 10 for non-
energy fuel consumption and about 20 for International Bunker Fuels).
Energy 3-17
-------
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.24 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.25
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).26 For purposes of this uncertainty analysis, each input variable was simulated 10,000 times through Monte
Carlo Sampling.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-10. Fossil fuel combustion
CO2 emissions in 2006 were estimated to be between 5,542.9 and 5,944.7 Tg CO2 Eq. at a 95 percent confidence
level. This indicates a range of 2 percent below to 5 percent above the 2006 emission estimate of 5,637.9 Tg CO2
Eq.
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-related Fossil Fuel
Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent)
Fuel/Sector
2006
Emission
Estimate
(TgC02
Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
Lower Bound Upper Bound Lower Bound Upper Bound
Coalb
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas b
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum b
Residential
2,065.3
0.6
6.2
122.0
NE
1,932.4
4.1
1,155.1
237.5
154.1
389.3
33.2
339.6
1.4
2,417.1
88.5
1,996.8
0.5
5.9
117.3
NE
1,856.4
3.6
1,164.8
230.8
149.7
399.5
32.3
329.6
1.2
2,282.9
83.8
2,262.1
0.7
7.1
142.4
NE
2,119.9
4.9
1,231.2
254.2
164.9
440.0
35.5
356.9
1.6
2,554.7
92.8
-3%
-6%
-5%
-4%
NA
-4%
-12%
+1%
-3%
-3%
+3%
-3%
-3%
-12%
-6%
-5%
+10%
+15%
+15%
+17%
NA
+10%
+19%
+7%
+7%
+7%
+13%
+7%
+5%
+17%
+6%
+5%
24 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.
25 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.
26 Although, in general, random uncertainties are the main focus of statistical uncertainty analysis, when the uncertainty
estimates are elicited from experts, their estimates include both random and systematic uncertainties. Hence, both these types of
uncertainties are represented in this uncertainty analysis.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Commercial
Industrial
Transportation
Electric Utilities
U.S. Territories
Total (excluding
Geothermal) b
Geothermal
Total (including
Geothermal) b'c
49.8
350.9
1,822.8
55.7
49.4
5,637.6
0.4
5,637.9
47.5
305.2
1,700.5
53.3
45.6
5,542.5
NE
5,542.9
51.8
407.1
1,940.0
59.7
54.9
5,944.3
NE
5,944.7
-5%
-13%
-7%
-4%
-8%
-2%
NE
-2%
+4%
+16%
+6%
+7%
+11%
+5%
NE
+5%
NA (Not Applicable)
NE (Not Estimated)
a Range of emission estimates predicted by Monte Carlo 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.
0 Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for CO2 emissions from
geothermal production.
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
The Energy Information Administration (ElA 2007b) updated energy consumption data for all years. These
revisions primarily impacted the emission estimates for 2005. Overall, these changes resulted in an average annual
increase of 0.8 Tg COa Eq. (less than 0.1 percent) in COa emissions from fossil fuel combustion for the period 1990
through 2005.
Planned Improvements
To reduce uncertainty of CO2 from fossil fuel combustion estimates, efforts will be taken to work with EIA and
other agencies to improve the quality of the U.S. territories data. This improvement is not all-inclusive, and is part
of an ongoing analysis and efforts to continually improve the CO2 from fossil fuel combustion estimates. In
addition, further expert ilicitation may be conducted to better quantify the total uncertainty associated with
emissions from this source.
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).
CO2 emissions arise from non-energy uses via several pathways. Emissions may occur during the manufacture of a
Energy 3-19
-------
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 62 percent of the total C consumed for non-energy purposes was stored in products, and not released to
the atmosphere; the remaining 38 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 3-11, fossil fuel emissions in 2006 from the non-energy uses of fossil fuels were 138.0 Tg CO2
Eq., which constituted approximately 2 percent of overall fossil fuel emissions, approximately the same proportion
as in 1990. In 2006, the consumption of fuels for non-energy uses (after the adjustments described above) was
5,417.8 TBtu, an increase of 21 percent since 1990 (see Table 3-12). About 65.4 Tg of the C (239.6 Tg CO2 Eq.) in
these fuels was stored, while the remaining 37.6 Tg C (138.0 Tg CO2 Eq.) was emitted. The proportion of C
emitted as CO2 has remained about constant since 1990, at about 36 to 40 percent of total non-energy consumption
(see Table 3-11).
Table 3-11: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.)
Year
Potential Emissions
C Stored
Emissions as a % of Potential
Emissions
1990^
312.6^
195.5^
37%^
117.2^
3
| 346.8^
|
3
3 133.2^
= 2000
1 385.5
= 244.1
1 37%
= 141.4
2001
364.8
232.9
36%
131.9
2002
368.4
232.6
37%
135.9
2003
356.3
224.5
37%
131.8
2004
394.9
246.0
38%
148.9
2005
382.2
243.1
36%
139.1
2006
377.6
239.6
37%
138.0
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 3-12
and Table 3-13 have been adjusted to subtract non-energy uses that are included in the source categories of the
Industrial Processes chapter.27 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
27 These source categories include Iron and Steel Production, Lead Production, Zinc Production, Ammonia Manufacture, Carbon
Black Manufacture (included in Petrochemical Production), Litanium Dioxide Production, Ferroalloy Production, Silicon
Carbide Production, and Aluminum Production.
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
lifecycle approach was used in the development of these factors in order to account for losses in the production
process and during use. Because losses associated with municipal solid waste management are handled separately
in this sector under the Municipal Solid Waste Combustion source category, the storage factors do not account for
losses at the disposal end of the life cycle. For industrial coking coal and distillate fuel oil, storage factors were
taken from IPCC/UNEP/OECD/IEA (1997), which in turn draws from Marland and Rotty (1984). For the
remaining fuel types (petroleum coke, miscellaneous products, and other petroleum), IPCC does not provide
guidance on storage factors, and assumptions were made based on the potential fate of C in the respective NEU
products.
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Year
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical
Plants, Other Uses
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401°F)
Other Oil (>401°F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc.
Prod.)
Total
1990^
4,221.2^
O.Op
8~ ?=
.2^=
276.0P
1,110.2m
1,119.0^
186.3^
77.3P
325.7p
677.2p
2i.3m
Sl.Op
100.9p
7.0p
33.3^=
137.8P
176.0P
176.0P
86.7p
0.7p
86.0P
4,483.9p
m
1 4,771.8^
i
1 1L3P
1 330.4^
1 1,178.2^
m 1,484.7^
m 177.8^
I 285.3p
i 350.6^
1 612.7^
1 40.1^
1 44.1^
i
i
i 40.6^
i
i 167.9^
i 167.9^
i
i
i
m 5,030.6^
1 2000
1 5,261.1
1 62.8
1 12-4
1 421.1
1 1,275.7
1 1,604.6
1 189.9
1 228.7
1 592.8
1 554.3
1 12.6
1 47.8
1 94.4
1 11.7
1 33.1
1 119.2
1 179.4
1 179.4
1 165.5
1 16.4
1 149.1
3 5,605.9
2001
5,044.4
25.6
11.3
407.8
1,256.9
1,539.0
174.0
199.8
489.4
525.9
35.8
128.1
77.9
11.7
36.3
124.9
164.3
164.3
80.3
+
80.3
5,289.0
2002
5,032.4
46.5
12.0
364.6
1,239.9
1,565.4
171.9
166.1
564.2
456.2
57.8
110.2
99.5
11.7
32.2
134.2
162.4
162.4
138.6
1.5
137.2
5,333.4
2003
4,865.3
72.1
11.9
352.0
1,219.5
1,437.8
159.0
158.3
573.4
501.0
59.0
76.9
75.7
11.7
31.0
126.0
150.1
150.1
127.9
9.3
118.6
5,143.4
2004
5,308.4
214.7
11.9
360.2
1,303.8
1,436.7
161.0
156.5
687.9
547.8
63.5
161.3
47.2
11.7
30.8
113.4
152.1
152.1
110.8
5.1
105.7
5,571.3
2005
5,210.0
109.7
11.9
390.3
1,323.2
1,442.0
160.2
146.0
678.6
518.7
67.7
145.0
60.9
11.7
31.4
112.8
151.3
151.3
107.6
5.2
102.4
5,468.9
2006
5,160.5
85.9
12.4
403.2
1,225.6
1,491.8
130.6
105.1
592.9
573.4
122.3
178.7
68.7
11.7
25.2
133.2
147.0
147.0
110.3
5.4
104.9
5,417.8
+ Does not exceed 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.
Table 3-13: 2006 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Adjusted
Non-Energy
Sector/Fuel Type
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical Plants
Asphalt & Road Oil
LPG
Lubricants
Use3
(TBtu)
5,160.5
85.9
12.4
403.2
1,225.6
1,491.8
130.6
Carbon
Content
Coefficient
(Tg C/QBtu)
-
31.00
25.63
14.47
20.62
16.78
20.24
Potential
Carbon
(TgC)
97.8
2.7
0.3
5.8
25.3
25.0
2.6
Storage
Factor
-
0.10
0.62
0.62
1.00
0.62
0.09
Carbon
Stored
(TgC)
64.9
0.3
0.2
3.6
25.3
15.4
0.2
Carbon
Emissions
(TgC)
32.9
2.4
0.1
2.2
0.0
9.6
2.4
Carbon
Emissions
(Tg C02 Eq.)
120.8
8.8
0.4
8.2
0.0
35.3
8.8
Energy 3-21
-------
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
105.1
592.9
573.4
122.3
178.7
68.7
11.7
25.2
133.2
147.0
147.0
110.3
5.4
104.9
5,417.8
18.24
18.14
19.95
17.51
27.85
19.86
19.95
19.81
20.33
20.24
-
20.24
20.00
1.9
10.8
11.4
2.1
5.0
1.4
0.2
0.5
2.7
3.0
3.0
2.2
0.1
2.1
103.0
0.62
0.62
0.62
0.62
0.50
0.62
0.50
0.58
0.00
0.09
-
0.09
0.10
1.2
6.6
7.0
1.3
2.5
0.8
0.1
0.3
0.0
0.3
0.3
0.2
0.0
0.2
65.4
0.7
4.1
4.4
0.8
2.5
0.5
0.1
0.2
2.7
2.7
2.7
2.0
0.1
1.89
37.6
2.7
15.2
16.1
3.0
9.1
1.9
0.4
0.8
9.9
9.9
9.9
7.3
0.4
6.9
138.0
+ Does not exceed 0.05 TBtu
- Not applicable.
aTo avoid double counting, exports have been deducted.
Note: Totals may not sum due to independent rounding.
Lastly, emissions were estimated by subtracting the C stored from the potential emissions (see Table 3-11). More
detail on the methodology for calculating storage and emissions from each of these sources is provided in Annex
2.3.
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 Air Quality and Emissions Trends Report (EPA 2006a), Toxics Release Inventory, 1998
(2000a), Biennial Reporting System (EPA 2004a, 2006b, 2007), and pesticide sales and use estimates (EPA 1998,
1999, 2002, 2004b); the El A 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, 2007); 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 (CMA 1999); and the American Chemistry Council (ACC 2005 through
2007) 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)
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
asphalt, (3) lubricants, and (4) waxes. For the remaining fuel types (the "other" category), the storage factors were
taken directly from the IPCC Guidelines for National Greenhouse Gas Inventories, where available, and otherwise
assumptions were made based on the potential fate of carbon in the respective NEU products. To characterize
uncertainty, five separate analyses were conducted, corresponding to each of the five categories. In all cases,
statistical analyses or expert judgments of uncertainty were not available directly from the information sources for
all the activity variables; thus, uncertainty estimates were determined using assumptions based on source category
knowledge.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-14 (emissions) and Table 3-15
(storage factors). Carbon emitted from non-energy uses of fossil fuels in 2006 was estimated to be between 110.2
and 150.3 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 20 percent below to 9 percent
above the 2006 emission estimate of 138.0 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.
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Non-Energy Uses of Fossil Fuels
(Tg CO2 Eq. and Percent)
Source
2006
Emission
Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Upper Bound Lower Bound Upper Bound
Bound
Feedstocks
Asphalt
Lubricants
Waxes
Other
Total
C02
C02
CO2
C02
C02
C02
83.0
0.0
19.1
0.8
35.2
138.0
66.4
0.1
15.7
0.6
16.5
110.2
99.5
0.7
22.1
1.2
38.3
150.3
-20%
NA
-17%
-23%
-53%
-20%
+20%
NA
+16%
+59%
+9%
+9%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
NA (Not Applicable)
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent)
Source
Gas
2006
Storage
Factor
Uncertainty Range Relative to Emission Estimate3
(%) (%) (%, Relative)
Feedstocks
Asphalt
Lubricants
Waxes
Other
C02
C02
C02
C02
C02
62%
100%
9%
58%
24%
Lower Bound
59%
99%
4%
44%
20%
Upper Bound
64%
100%
18%
69%
64%
Lower Bound
-4%
-1%
-58%
-24%
-17%
Upper Bound
+3%
+0%
+89%
+19%
+162%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval, as a percentage of the
inventory value (also expressed in percent terms).
In Table 3-15, feedstocks and asphalt contribute least to overall storage factor uncertainty on a percentage basis.
Although the feedstocks category—the largest use category in terms of total carbon flows—appears to have tight
confidence limits, this is to some extent an artifact of the way the uncertainty analysis was structured. As discussed
in Annex 2.3, the storage factor for feedstocks is based on an analysis of six fates that result in long-term storage
(e.g., plastics production), and eleven that result in emissions (e.g., volatile organic compound emissions). Rather
than modeling the total uncertainty around all of these fate processes, the current analysis addresses only the storage
fates, and assumes that all C that is not stored is emitted. As the production statistics that drive the storage values
are relatively well-characterized, this approach yields a result that is probably biased toward understating
Energy 3-23
-------
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 2006 as well as their trends 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).
Finally, although U.S.-specific storage factors have been developed for feedstocks, asphalt, lubricants, and waxes,
default values from IPCC are still used for two of the non-energy fuel types (industrial coking coal and distillate
oil), and broad assumptions are being used for the remaining fuels (petroleum coke, miscellaneous products, and
other petroleum). Over the long term, there are plans to improve these storage factors by conducting analyses of C
fate similar to those described in Annex 2.3.
3.3. Stationary Combustion (excluding CO2) (IPCC Source Category 1A)
Stationary combustion encompasses all fuel combustion activities from fixed sources (versus mobile combustion).
Other than CO2, which was addressed in the previous section, gases from stationary combustion include the
greenhouse gases CH4 and N2O and the indirect greenhouse gases NOX, CO, and NMVOCs.28 Emissions of these
gases from stationary combustion sources depend upon fuel characteristics, size and vintage, along with combustion
technology, pollution control equipment, and ambient environmental conditions. Emissions also vary with
operation and maintenance practices.
28 Sulfur dioxide (SO2) emissions from stationary combustion are addressed in Annex 6.3.
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
N2O 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. CH4 emissions from stationary
combustion are primarily a function of the CH4 content of the fuel and combustion efficiency.
Emissions of CH4 decreased 16 percent overall since 1990 to 6.2 Tg CO2 Eq. (296 Gg) in 2006. This decrease in
CH4 emissions was primarily due to lower wood consumption in the residential sector. Conversely, N2O emissions
rose 13 percent since 1990 to 14.5 Tg CO2 Eq. (47 Gg) in 2006. The largest source of N2O emissions was coal
combustion by electricity generators, which alone accounted for 66 percent of total N2O emissions from stationary
combustion in 2006. Overall, however, stationary combustion is a small source of CH4 and N2O in the United
States.
Table 3-16: CH4 Emissions
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural gas
Wood
Industrial
Coal
Fuel Oil
Natural gas
Wood
Commercial/Institutiona
1
Coal
Fuel Oil
Natural gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
+ Does not exceed 0.05 Tg CO2
from Stationary
Combustion (Tg CO2
0.6^=
0.3^^
0.1^^
0.9^^
0.9 ^^
0.4^^
0.2^^
0.3^^
0.5^^
3.5^=
+^=
7.4^=
Eq.
0.4^
0.1 =
1.6 =
0.3^
0.2^
1.0 =
0.9^
0.4^
4.0^
0.1 =
3.1 =
! 2000
! 0.7
! 0.4
! 0.1
! 0.1
! 0.1
! 1.6
! 0.3
! 0.2
! 0.2
! i.o
! 0.9
! +
! 0.1
! 0.3
! 0.4
! 3.4
! 0.1
! 0.3
! 0.5
! 2.5
! 0.1
! +
! +
! +
! +
! 6.6
Eq.)
2001
0.7
0.4
0.1
0.1
0.1
1.5
0.3
0.2
0.2
0.9
0.9
+
0.1
0.3
0.4
3.1
0.1
0.3
0.5
2.2
0.1
+
0.1
+
+
6.2
2002
0.7
0.4
0.1
0.1
0.1
1.4
0.3
0.2
0.2
0.8
0.9
+
0.1
0.3
0.4
3.1
0.1
0.3
0.5
2.3
0.1
+
0.1
+
+
6.2
2003
0.7
0.4
0.1
0.1
0.1
1.4
0.3
0.2
0.2
0.8
0.9
+
0.2
0.3
0.4
3.3
0.1
0.3
0.5
2.4
0.1
+
0.1
+
+
6.4
2004
0.7
0.4
0.1
0.1
0.1
1.5
0.3
0.2
0.2
0.9
0.9
+
0.1
0.3
0.4
3.3
0.1
0.3
0.5
2.5
0.1
+
0.1
+
+
6.5
2005
0.7
0.4
0.1
0.1
0.1
1.5
0.3
0.2
0.1
0.9
0.9
+
0.1
0.3
0.4
3.3
0.1
0.3
0.5
2.5
0.1
+
0.1
+
+
6.5
2006
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
3.1
+
0.3
0.4
2.3
0.1
+
0.1
+
+
6.2
Note: Totals may not sum due to independent rounding.
Table 3-17: N2O Emissions
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
from Stationary
1990^^
SAjjjjjjJi
7.6^^
»m
Combustion (Tg CO2
1995^
8.1^1
0.1^=
0.7^
0.4^
0.3^
I 2000
1 10.0
1 9.4
1 0.2
1 0.2
\ 0.2
\ 3-3
\ 0.7
1 0.5
1 0.3
Eq.)
2001
9.7
9.1
0.2
0.2
0.1
3.1
0.7
0.5
0.2
2002
9.7
9.2
0.2
0.2
0.2
3.0
0.6
0.5
0.2
2003
10.0
9.4
0.2
0.2
0.2
3.0
0.6
0.5
0.2
2004
10.0
9.5
0.2
0.2
0.2
3.1
0.6
0.5
0.2
2005
10.3
9.7
0.2
0.2
0.2
3.1
0.6
0.6
0.2
2006
10.1
9.5
0.1
0.2
0.2
3.2
0.6
0.6
0.2
Energy 3-25
-------
Wood
Commercial/Institutiona
1
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
+ Does not exceed 0.05 Tg CO2
12.8^^
Eq.
1.9^^3
+'j==i
0.1^^
0.6^^
13.4S
1.9
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.2
0.5
0.1
+
0.1
+
+
14.6
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.4
0.1
+
0.1
+
+
14.1
1.6
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.4
0.1
+
0.1
+
+
14.0
1.6
0.4
+
0.1
0.1
0.1
0.9
+
0.3
0.2
0.5
0.1
+
0.1
+
+
14.3
1.7
0.4
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
+
+
14.6
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
+
+
14.8
1.7
0.3
+
0.1
0.1
0.1
0.8
+
0.2
0.1
0.5
0.1
+
0.1
+
+
14.5
Note: Totals may not sum due to independent rounding.
Table 3-18: CH4 Emissions
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial/Institutiona
1
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
+ Does not exceed 0.5 Gg
from Stationary
1990^^
9^^=J
+ ==i
353^^
Combustion
1995SEEEEE
7^^=
5^=
+^^=
341^=
(Gg)
2000
33
20
3
5
4
76
14
7
8
47
43
1
7
15
20
162
3
15
24
120
2
+
2
+
+
316
2001
32
20
4
5
4
71
14
8
8
41
41
1
7
15
19
147
3
15
23
105
3
+
3
+
+
295
2002
32
20
3
5
4
69
13
8
8
40
42
1
6
15
20
149
4
14
24
108
3
+
3
+
+
295
2003
34
20
4
5
5
68
13
8
8
39
44
1
7
16
20
158
4
15
25
114
3
+
3
+
+
306
2004
34
20
4
5
5
71
13
9
7
42
43
1
7
15
20
159
4
15
24
117
3
+
3
+
+
311
2005
35
21
4
6
5
71
13
9
7
41
42
1
7
15
20
157
3
14
24
117
3
+
3
+
+
308
2006
34
21
2
6
5
72
13
10
7
42
40
1
7
14
18
147
2
13
21
111
3
+
3
+
+
296
Note: Totals may not sum due to independent rounding.
Table 3-19: N2O Emissions
from Stationary
Combustion (Gg)
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial/Institutiona
1
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990^
26^
24iJii
10^1
5^=
1^=
^1
+^=
2^=
I
I
\
\
\
\
\
\
\
\
\
\
\
\
\
\
:\
\
\
\
\
\
\
\
\
\
\
I 2000
I 32
\ 30
\ 1
\ 1
\ 1
\ 11
\ 2
\ 1
\ 1
| 6
| 1
\ +
1 +
1 +
1 +
I 3
I +
1 1
I +
I 2
\ +
I +
1 +
1 +
1 +
1 41
2001
31
29
1
1
+
10
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
46
2002
31
30
1
1
1
10
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
45
2003
32
30
1
+
1
10
2
2
1
5
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
46
2004
32
31
1
1
1
10
2
2
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
47
2005
33
31
1
1
1
10
2
2
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
48
2006
32
31
+
1
1
10
2
2
1
6
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
47
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
Methodology
CH4 and N2O emissions were estimated by multiplying fossil fuel and wood consumption data by emission factors
(by sector and fuel type). National coal, natural gas, fuel oil, and wood consumption data were grouped by sector:
industrial, commercial, residential, electricity generation, and U.S. territories. For the CH4 and N2O estimates, fuel
consumption data for coal, natural gas, fuel oil for the United States were obtained from EIA's Monthly Energy
Review and unpublished supplemental tables on petroleum product detail (EIA 2007a). Wood consumption data for
the United States was obtained from EIA's Annual Energy Review (EIA 2007b). Because the United States does
not include territories in its national energy statistics, fuel consumption data for territories were provided separately
by Grillot (2007).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 (2004). Estimates for wood biomass consumption for fuel combustion do not include wood wastes,
liquors, municipal solid waste, tires, etc. that are reported as biomass by EIA.
29 U.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
Energy 3-27
-------
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/EIA (2001) report.31 For these variables, the uncertainty
ranges were assigned to the input variables based on the data reported in SAIC/EIA (2001).32 However, the CH4
emission factors differ from those used by EIA. Since these factors were obtained from IPCC/UNEP/OECD/IEA
(1997), uncertainty ranges were assigned based on IPCC default uncertainty estimates (IPCC 2000).
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-20. Stationary combustion
CH4 emissions in 2006 (including biomass) were estimated to be between 4.3 and 13.4 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 31 percent below to 116 percent above the 2006 emission estimate of 6.2
Tg CO2 Eq.33 Stationary combustion N2O emissions in 2006 (including biomass) were estimated to be between
11.0 and 42.2 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 24 percent below to 190
percent above the 2006 emissions estimate of 14.5 Tg CO2 Eq.
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg CO2 Eq. and Percent)
2006 Emission
Estimate Uncertainty Range Relative to Emission Estimate"
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.
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Source Gas (TgCO2Eq.) (Tg CO2 Eg.) (%)
Stationary Combustion
Stationary Combustion
CH4
N2O
6.2
14.5
Lower
Bound
4.3
11.0
Upper
Bound
13.4
42.2
Lower
Bound
-31%
-24%
Upper
Bound
+116%
+190%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
The uncertainties associated with the emission estimates of CH4 and N2O are greater than those associated with
estimates of CO2 from fossil fuel combustion, which mainly rely on the carbon content of the fuel combusted.
Uncertainties in both CH4 and N2O estimates are due to the fact that emissions are estimated based on emission
factors representing only a limited subset of combustion conditions. For the indirect greenhouse gases, uncertainties
are partly due to assumptions concerning combustion technology types, age of equipment, emission factors used,
and activity data projections.
QA/QC and Verification
A source-specific QA/QC plan for stationary combustion was developed and implemented. This effort included a
Tier 1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved
checks specifically focusing on the activity data and emission factor sources and methodology used for estimating
CH4, N2O, and the indirect greenhouse gases from stationary combustion in the United States. Emission totals for
the different sectors and fuels were compared and trends were investigated.
Recalculations Discussion
Historical CH4 and N2O emissions from stationary sources (excluding CO2) were revised due to several changes.
One of the most significant changes was implementing stationary combustion emission factors updated in IPCC
(2006). As a result, N2O emission factors for coal consumption in all sectors, and CH4 emission factors for
industrial petroleum and natural gas were revised. Slight changes to emission estimates for sectors are also due to
revised data from El A (2007a). 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 (2007b) were revised for the
residential, industrial, and electric power sectors. The combination of the methodological and historical data
changes resulted in an average annual decrease of 0.6 Tg CO2 Eq. (8.3 percent) in CH4 emissions from stationary
combustion and an average annual increase of 0.6 Tg CO2 Eq. (4.9 percent) in N2O emissions from stationary
combustion for the period 1990 through 2005.
Planned Improvements
Several items are being evaluated to improve the CH4 and N2O emission estimates from stationary combustion and
to reduce uncertainty. Efforts will be taken to work with EIA and other agencies to improve the quality of the U.S.
territories data. Because these data are not broken out by stationary and mobile uses, further research will be aimed
at trying to allocate consumption appropriately. In addition, the uncertainty of biomass emissions will be further
investigated since it was expected that the exclusion of biomass from the uncertainty estimates would reduce the
uncertainty; and in actuality the exclusion of biomass increases the uncertainty. These improvements are not all-
inclusive, but are part of an ongoing analysis and efforts to continually improve these stationary estimates.
3.4. Mobile Combustion (excluding CO2) (IPCC Source Category 1A)
Mobile combustion produces greenhouse gases other than CO2, including CH4, N2O, and indirect greenhouse gases
including NOX, CO, and NMVOCs. Mobile combustion includes 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
that have utility associated with their movement but do not have a primary purpose of transporting people or goods
(e.g., snowmobiles, riding lawnmowers, etc.). Annex 3.2 includes a summary of all emissions from both
transportation and mobile sources.
Energy 3-29
-------
As with stationary combustion, N2O and NOX emissions are closely related to fuel characteristics, air-fuel mixes,
combustion temperatures, and the use of pollution control equipment. N2O, in particular, can be formed by the
catalytic processes used to control NOX, CO, and hydrocarbon emissions. Carbon monoxide emissions from mobile
combustion are significantly affected by combustion efficiency and the presence of post-combustion emission
controls. CO emissions are highest when air-fuel mixtures have less oxygen than required for complete combustion.
These emissions occur especially in idle, low speed, and cold start conditions. CH4 and NMVOC emissions from
motor vehicles are a function of the CH4 content of the motor fuel, the amount of hydrocarbons passing
uncombusted through the engine, and any post-combustion control of hydrocarbon emissions (such as catalytic
converters).
Table 3-21 and Table 3-22 provide CH4 and N2O emission estimates in Tg CO2Eq.; Table 3-23 and Table 3-24
present these estimates in Gg of each gas.34
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 (9 percent). From 1990 to 2006, mobile source CH4 emissions declined by 50
percent, to 2.4 Tg CO2 Eq. (112 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 24
percent, to 33.1 Tg CO2 Eq (107 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 40 percent
decrease in mobile source N2O emissions from 1998 to 2006 (see Figure 3-15). Overall, CH4 and N2O emissions
were predominantly from gasoline-fueled passenger cars and light-duty trucks.
Figure 3-15: Mobile Source CH4 and N2O Emissions
Table 3-21: CH4 Emissions from Mobile Combustion (Tg CO2 Eq.)
Fuel Type/Vehicle Type"
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
1990^
4.2^
2.6^
1.4^
i
1
i
i
1 2000
3 2.8
1 1-6
1 1.1
2001
2.7
1.5
1.1
2002
2.4
1.4
0.9
2003
2.2
1.3
0.8
2004
2.0
1.2
0.7
2005
1.9
1.1
0.7
2006
1.7
1.0
0.7
Medium- and Heavy-
Duty Trucks and Buses 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Motorcycles + + + + + + +
Diesel On-Road + + + + + + +
Passenger Cars + + + + + + +
Light-Duty Trucks + + + + + + +
Medium- and Heavy-
Duty Trucks and Buses + + + + + + +
Alternative Fuel On-
Road + + + + 0.1 0.1 0.1
Non-Road 0.5 0.5 0.5 0.5 0.5 0.6 0.6
oiups tiiici JjOtits ~ SEEEEEE EEEEEE;
Domestic 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Rail 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Agricultural Equipment 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Construction/Mining 0.1 ^^ 0.1 0.1 0.1 0.1 0.1 0.1 0.1
34 See Annex 3.2 for a complete time series of emission estimates for 1990 through 2006.
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Aircraft - Domestic 0.2 0.1 0.1 0.1 0.1 0.1 0.1
Otherb + + 0.1 0.1 0.1 0.1 0.1
Total 3.4 3.3 3.0 2.7 2.6 2.5 2.4
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
a See Annex 3.2 for definitions of on-road vehicle types.
b "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
Table 3-22: N2O Emissions from Mobile Combustion (Tg CO2 Eq.)
Fuel Type/Vehicle Type
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-
Duty Trucks and Buses
Motorcycles
Diesel On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-
Duty Trucks and Buses
Alternative Fuel On-
Road
Non-Road
Ships and Boats -
Domestic
Rail
Agricultural Equipment
Construction/Mining
Equipment
Aircraft - Domestic
Other*
Total
1990^
40.1^
25.4^
14.1^
0.3^
0.2^
1-7^
0.2^
43.5^
3
1
1
1 22.1^
1
|
1
1
1
1
1
1
1
|
1
1
1
1
1
3 2000
1 48.4
1 25.2
1 22.4
1 0.9
1 +
1 °-3
1 +
1 +
1 0-3
1 0.1
1 3.7
1 0.5
1 0.3
1 °-3
1 0.4
1 1.9
1 0.3
1 52.5
2001
45.9
23.8
21.2
0.9
+
0.3
+
+
0.3
0.1
3.6
0.3
0.3
0.3
0.4
1.8
0.3
49.9
2002
41.8
22.5
18.5
0.9
+
0.3
+
+
0.3
0.1
3.6
0.5
0.3
0.3
0.5
1.7
0.3
45.9
2003
38.4
21.0
16.5
0.9
+
0.3
+
+
0.3
0.2
3.4
0.3
0.3
0.3
0.5
1.7
0.3
42.3
2004
35.6
19.5
15.3
0.8
+
0.3
+
+
0.3
0.2
3.6
0.4
0.3
0.4
0.5
1.7
0.4
39.7
2005
32.1
17.7
13.6
0.8
+
0.3
+
+
0.3
0.2
3.7
0.4
0.4
0.4
0.5
1.7
0.4
36.3
2006
29.0
15.6
12.6
0.7
+
0.3
+
+
0.3
0.2
3.6
0.4
0.4
0.4
0.5
1.6
0.4
33.1
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
*"Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
Table 3-23: CH4 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-
Duty Trucks and Buses
Motorcycles
Diesel On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-
Duty Trucks and Buses
Alternative Fuel On-
1990^
201^
125^
i
i
i
I
I
I
I
i
i
1
i
1 2000
1 134
1 77
1 50
1 5
1 1
1 !
1 +
1 +
1 1
1 1
2001
129
72
52
5
1
1
+
+
1
2
2002
112
66
41
4
1
1
+
+
1
2
2003
103
61
38
4
1
1
+
+
1
2
2004
96
56
35
4
1
1
+
+
1
3
2005
88
52
32
3
1
1
+
+
1
3
2006
82
47
31
3
1
1
+
+
1
3
Energy 3-31
-------
Non-Roiid 22 EEEEEE 24 EEEEEE 26 25 26 24 26 27 27
Agricultural Equipment 4 5 5666677
(^-Oristructiori/iviining EEEEEEE EEEEEEE
Equipment 2
Aircraft - Domestic
Other*
Total
: 3^^=
I 7^^=
i 2^^^
\
\ 3
i 7
1 2
i 162
3
7
2
157
3
7
2
141
3
6
3
131
3
7
3
126
4
7
3
119
4
7
3
112
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
* "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport
equipment, commercial equipment, and industrial equipment.
Table 3-24: N2O Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy -
Duty Trucks and Buses
Motorcycles
Diesel On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy -
Duty Trucks and Buses
Alternative Fuel On-Road
Non-Road
Ships and Boats -
Domestic
Rail
Agricultural Equipment
Construction/Mining
Equipment
Aircraft - Domestic
Other*
Total
1990 1
129 =
82 1
45 i
2 1
+ i
i |
+ I
+ i
i 1
+ i
10 1
i 1
i i
i |
i 1
6 i
i i
140 1
1
i
1
1
1
1
H1 1
i
1
1
i
1
• i 1
i
^i |
1
i
i
i
^2000
^156
^^^z -3
^^= J
2001
148
77
69
o
J
+
1
+
+
1
+
11
1
1
1
1
6
1
161
2002
135
72
60
3
+
1
+
+
1
+
12
2
1
1
1
6
1
148
2003
124
68
53
3
+
1
+
+
1
1
11
1
1
1
2
5
1
137
2004
115
63
49
o
J
+
1
+
+
1
1
12
1
1
1
2
6
1
128
2005
104
57
44
2
+
1
+
+
1
1
12
1
1
1
2
6
1
117
2006
93
50
41
2
+
1
+
+
1
1
12
1
1
1
2
5
1
107
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
* "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
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.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
EPA (2008, 2005, 2003) provides emission estimates of NOX, CO, and NMVOCs for eight categories of on-road
vehicles,35 aircraft, and seven categories of non-road vehicles36 These emission estimates primarily reflect EPA
data, which, in final iteration, will be published on the National Emission Inventory (NEI) Air Pollutant Emission
Trends web site. The methodology used to develop these estimates can be found on EPA's Air Pollutant Emission
Trends website, at .
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)37 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 emissions characteristics of segment 2 were used to define
running emissions, and subtracted from the total FTP emissions to determine start emissions. These were then
recombined based upon the ratio of start to running emissions for each vehicle class from MOBILE6.2, an EPA
emission factor model that predicts gram per mile emissions of CC>2, CO, HC, NOx, and PM from vehicles under
various conditions, to approximate average driving characteristics.38
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 2006 were obtained from the Federal Highway Administration's (FHWA)
Highway Performance Monitoring System database as reported in Highway Statistics (FHWA 1996 through 2007).
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 2007)
and information on total motor vehicle fuel consumption by fuel type from FHWA (1996 through 2007). 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
35 These categories included: gasoline passenger cars, diesel passenger cars, light-duty gasoline trucks less than 6,000 pounds in
weight, light-duty gasoline trucks between 6,000 and 8,500 pounds in weight, light-duty diesel trucks, heavy-duty gasoline
trucks and buses, heavy-duty diesel trucks and buses, and motorcycles.
36 These categories included: locomotives, marine vessels, farm equipment, construction equipment, other non-road liquid fuel
(e.g. recreational vehicles and lawn and garden equipment), and other non-road gaseous fuel (e.g., other non-road equipment
running on compressed natural gas).
37 Alternative fuel and advanced technology vehicles are those that can operate using a motor fuel other than gasoline or diesel.
This includes electric or other bifuel or dual fuel vehicles that may be partially powered by gasoline or diesel.
38 Additional information regarding the model can be found online at http://www.epa.gov/OMS/m6.htm.
Energy 3-33
-------
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).
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.
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).39 Activity
data were obtained from AAR (2007), APTA (2007 and 2006), BEA (1991 through 2005), Benson (2002 through
2004), DHS (2008), DOC (1991 through 2007), DOE (1993 through 2007), DESC (2007), DOT (1991 through
2007), EIA (2007a, 2007b, 2007d, 2002), EIA (1991 through 2007), EPA (2006b), Esser (2003 through 2004),
FAA (2007 and 2006), Gaffney (2007), Lou (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 2006 estimates of CH4and 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 CH4 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 CH4 and N2O emissions from on-
road vehicles are summarized in Table 3-25. As noted above, an uncertainty analysis was not performed for CH4
and N2O emissions from non-road vehicles. Mobile combustion CH4 emissions (from on-road vehicles) in 2006
were estimated to be between 1.7 and 1.9 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 6
percent below to 6 percent above the corresponding 2006 emission estimate of 1.8 Tg CO2 Eq. Also at a 95 percent
confidence level, mobile combustion N2O emissions from on-road vehicles in 2006 were estimated to be between
23.8 and 35.2 Tg CO2 Eq., indicating a range of 19 percent below to 19 percent above the corresponding 2006
emission estimate of 29.5 Tg CO2 Eq.
Table 3-25. Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Mobile Sources (Tg CO2
Eq. and Percent)
39 The consumption of international bunker fuels is not included in these activity data, but is estimated separately under the
International Bunker Fuels source category.
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Source
2006 Emission
Estimate" Uncertainty Range Relative to Emission Estimate3,1"
Gas (TgC02Eq.) (Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
On-Road Sources
On-Road Sources
CH4
N2O
1.8 1.7 1.9 -6% 6%
29.5 23.8 35.2 -19% 19%
a2006 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 Simulation for a 95 percent confidence interval.
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.
Carbon dioxide emissions from gasoline-powered on-road sources are now calculated directly using "bottom-up"
fuel sales data; this methodology is similar to the bottom-up calculation of CO2 from transportation diesel sources
implemented beginning with the 1990-2004 inventory report. On-road gasoline fuel sales estimates come from
FHWA's Highway Statistics (FHWA 1996 through 2007). The ethanol component of these fuel sales is subtracted
to yield a fossil-only estimate, which is used to calculate CO2 for gasoline-powered passenger cars, light-duty
trucks, medium- and heavy-duty trucks, and buses. To preserve EIA's estimate of total gasoline consumption
across all sectors, adjustments were made to estimated gasoline consumption by recreational boats, the commercial
sector and the industrial sector. EIA estimates of transportation sector fuel consumption continue to serve as the
foundation of inventory estimates for other fuel types (jet fuel, aviation gasoline, residual fuel, natural gas, LPG and
natural gas). CO2 from these fuels continues to be apportioned to individual modes using bottom-up data from BTS,
FAA, and DOE's Transportation Energy Data Book.
Vehicle age distributions for 1999 to the present were revised based on new data obtained from EPA's MOVES
model (EPA 2007c). Diesel fractions for light trucks and medium- and heavy-duty trucks and buses were updated
based on data obtained from the Transportation Energy Data Book (DOE 1993 through 2007) for 1998 through
2003, which increased emissions from diesel vehicles and reduced emissions from gasoline vehicles. Updates were
made to alternative fuel vehicle (AFV) vehicle miles traveled (VMT) numbers based on new activity data (ICF
2006a) and biodiesel was also added as a vehicle category under alternative fuel vehicles. VMT and fuel
consumption estimates for on-road vehicles were also revised for 2005 based on updated data from FHWA's
Highway Statistics (FHWA 1996 through 2007).
Energy 3-35
-------
Several changes were also made in the calculation of emissions from non-road vehicles. Similar to the previous
inventory, commercial aircraft energy consumption estimates for 2000-2005 come from the Federal Aviation
Administration's (FAA) System for Assessing Aviation's Global Emissions (SAGE) database (FAA 2006).
Aviation estimates were developed without the availability of 2006 data from the Federal Aviation Administration's
(FAA) System for Assessing Aviation's Global Emissions (SAGE) database. Estimates for 1990-1999 were
calculated using fuel consumption estimates from the Bureau of Transportation Statistics (DOT 1991 through 2007)
adjusted based on the 2000-2005 data. For 2006, an estimate - similar to the method used for 1990-1999 - was
derived using a combination of data from BTS and SAGE data. Class II and III railroad diesel use estimates are
now obtained from the American Short Line and Regional Railroad Association, with new data for 2002, 2004, and
2006 (Whorton 2006 through 2007).
+As a result of these changes, average estimates of CH4 and N2O emissions from mobile combustion were slightly
lower relative to the previous inventory—showing a decrease of no more than 0.7 Tg CO2 Eq. (2.0 percent) each
year—for the period 1990 through 2000. Larger decreases in estimates occurred for years 2002 to 2005 when
comparing the current inventory estimates with the previous inventory's estimates. The greatest decrease, 1.5 Tg
CO2 Eq. (4 percent), occurs with the 2005 N2O estimate. Estimates for the year 2001 are the exception, as these
estimates increased from the previous Inventory's estimates by 0.07 Tg CO2 Eq. for CH4 and 0.15 Tg CO2 Eq. for
N2O.
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 new emission factors for non-road sources. 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.
2. Examine the feasibility of estimating aircraft N2O and CH4emissions 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.
3. 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.
4. Develop improved estimates of domestic aviation fuel consumption. The inventory calculation of domestic jet
fuel consumption is derived by first estimating international aviation bunker fuel consumption and subtracting
this value from EIA' s estimate of total jet fuel consumption. Aviation bunker fuel estimates involve a number
of uncertainties, including the lack of specific data on the amount of total jet fuel consumption to allocate to
international bunkers. As mentioned above, FAA's SAGE database contains detailed data of domestic
operations of aircraft and associated fuel consumption, and could potentially be used for a direct calculation of
commercial aviation fuel consumption similar to the bottom-up approaches currently used for transportation
diesel sources and on-road gasoline.
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
5. Improve the process of apportioning VMT by vehicle type to each fuel type. The current inventory process for
estimating VMT by vehicle/fuel type category involves apportioning VMT on the basis of fuel consumption.
While this is a reasonable simplification, this approach implicitly assumes the same average fuel economy for
gasoline and diesel vehicles. A more accurate apportionment of VMT by fuel type for light-duty trucks and
medium/heavy-duty trucks could potentially be developed using data on vehicle travel from the Vehicle
Inventory and Use Survey (U.S. Census Bureau 2000) and other publications, or using VMT breakdowns by
vehicle/fuel type combinations from the MOBILE6 or MOVES models.
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.
3.5. Coal Mining (IPCC Source Category 1B1a)
Three types of coal mining related activities release CH4to the atmosphere: underground mining, surface mining,
and post-mining (i.e., coal-handling) activities. Underground coal mines contribute the largest share of CH4
emissions. All 120 gassy underground coal mines in the United States employ ventilation systems to ensure that
CH4 levels remain within safe concentrations. These systems can exhaust significant amounts of CH4 to the
atmosphere in low concentrations. Additionally, 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 2006, 13 coal mines collected CH4from
degasification systems and sold this gas to a pipeline, thus reducing emissions to the atmosphere. In addition, one
coal mine used CH4from its degasification system to heat mine ventilation air on site. Two of the coal mines that
sold gas to pipelines also used CH4to generate electricity or fuel a thermal coal dryer. Surface coal mines also
release CH4 as the overburden is removed and the coal is exposed, but the level of emissions is much lower than
from underground mines. Finally, some of the CH4 retained in the coal after mining is released during processing,
storage, and transport of the coal.
Total CH4 emissions in 2006 were estimated to be 58.5 Tg CO2 Eq. (2,784 Gg), a decline of 30 percent since 1990
(see Table 3-26 and Table 3-27). Of this amount, underground mines accounted for 61 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 CH4 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 steadily increased.
Table 3-26: CH4 Emissions from Coal Mining (Tg CO2 Eq.)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
Total
1990 =
62.3^
67.9 =
(5.6)^
12.0 =
7.7 =
2.0 =
84.1 =
1 1995=
1 46.7=
3 59.1 =
1 (12.4)=
i 11.5 =
I 6.9 =
I 1.9 =
I 67.1 =
i 2000
1 39.4
= 55.0
1 (15.6)
= 12.3
= 6.7
= 2.0
= 60.4
2001
38.2
55.5
(17.2)
13.2
6.8
2.1
60.3
2002
35.5
54.7
(19.2)
12.8
6.4
2.1
56.8
2003
36.0
53.0
(17.0)
12.4
6.4
2.0
56.9
2004
38
53
(15.
12
6
2
59
.1
.2
1)
.9
.6
.1
.8
2005
35
52
(17.
13
6
2
57
.2
.3
1)
.3
.4
.2
.1
2006
35.9
54.6
(18.7)
14.0
6.3
2.3
58.5
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-27: CH4 Emissions from Coal Mining (Gg)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
1990=
2,968^
3,234^
(266)^
574=
I
I 2,226=
i 2,816=
!
j 548^
i 2000
1 1,875
= 2,619
1 (744)
1 586
2001
1,820
2,641
(821)
627
2002
1,692
2,605
(913)
610
2003
1,715
2,522
(807)
592
2004
1,813
2,534
(721)
616
2005
1,675
2,491
(815)
633
2006
1,709
2,599
(891)
668
Energy 3-37
-------
Post-Mining (Underground) 318 325 305 306 317 306 298
Post-Mining (Surface) 95 102 99 96 100 103 109
Total 4,003|i 2,874 2,874 2,707 2,709 2,846 2,717 2,784
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Methodology
The methodology for estimating CH4 emissions from coal mining consists of two parts. The first part involves
estimating CH4 emissions from underground mines. Because of the availability of ventilation system measurements,
underground mine emissions can be estimated on a mine-by-mine basis and then summed to determine total
emissions. The second step involves estimating emissions from surface mines and post-mining activities by
multiplying basin-specific coal production by basin-specific emission factors.
Underground mines. Total CH4 emitted from underground mines was estimated as the sum of CH4 liberated from
ventilation systems and CH4 liberated by means of degasification systems, minus CH4 recovered and used. The
Mine Safety and Heath Administration (MSHA) samples CH4 emissions from ventilation systems for all mines with
detectable40 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 CH4 liberated
from their degasification systems. For mines that sell recovered CH4to a pipeline, pipeline sales data published by
state petroleum and natural gas agencies were used to estimate degasification emissions. For those mines for which
no other data are available, default recovery efficiency values were developed, depending on the type of
degasification system employed.
Finally, the amount of CH4 recovered by degasification systems and then used (i.e., not vented) was estimated. In
2006, thirteen active coal mines sold recovered CH4 into the local gas pipeline networks, while one coal mine used
recovered CH4 on site. Emissions avoided for these projects were estimated using gas sales data reported by various
state agencies. For most mines with recovery systems, companies and state agencies provided individual well
production information, which was used to assign gas sales to a particular year. For the few remaining mines, coal
mine operators supplied information regarding the number of years in advance of mining that gas recovery occurs.
In the case of Jim Walter Resources (JWR), the emissions avoided data was taken from the 1605b reports that the
mining company has been filing with the Department of Energy (DOE) since 1991 as part of their Voluntary
Reporting Program.
Surface Mines and Post-Mining Emissions. Surface mining and post-mining CH4 emissions were estimated by
multiplying basin-specific coal production, obtained from the Energy Information Administration's Annual Coal
Report (see Table 3-28) (EIA 2006), by basin-specific emission factors. Surface mining emission factors were
developed by assuming that surface mines emit two times as much CH4 as the average in situ CH4 content of the
coal. Revised data on in situ CH4 content and emissions factors are taken from EPA (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 3-28: Coal Production (Thousand Metric Tons)
40 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.
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Year Underground Surface Total
1995 359^477 577^638 937J15"
2000
2001
2002
2003
2004
2005
2006
338,173
345,305
324,219
320,047
333,449
334,404
325,703
635,592
676,142
667,619
651,251
674,551
691,460
728,459
973,765
1,021,446
991,838
971,297
1,008,000
1,025,864
1,054,162
Uncertainty
A quantitative uncertainty analysis was conducted for the coal mining source category using the IPCC-
recommended Tier 2 uncertainty estimation methodology. Because emission estimates from underground
ventilation systems were based on actual measurement data, uncertainty is relatively low. A degree of imprecision
was introduced because the measurements used were not continuous but rather an average of quarterly
instantaneous readings. Additionally, the measurement equipment used can be expected to have resulted in an
average of 10 percent overestimation of annual CH4 emissions (Mutmansky and Wang 2000). Estimates of CH4
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 3-29. Coal mining CH4 emissions in 2006 were
estimated to be between 53.3 and 76.3 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 9
percent below to 30 percent above the 2006 emission estimate of 58.5 Tg CO2 Eq.
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg CO2 Eq. and
Percent)
2006 Emission
Estimate Uncertainty Range Relative to Emission Estimate"
Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower Upper Lower Upper Bound
Bound Bound Bound
Coal Mining CH4 58.5
53.3 76.3 -9% +30%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Recalculations Discussion
In 2006, recalculations of emissions avoided at three JWR coal mines in Alabama were performed as the mining
company provided copies of their 1605b reports that they had been filing with DO. These reports cover the years
1991 through 2005. The 2006 report has not yet been filed, however JWR provided the 2006 data. In previous
inventories, emissions avoided calculations for any pre-drainage wells at JWR coal mines were based on publicly-
available data records from the Alabama State Oil & Gas Board. Emission reductions were calculated for pre-
drainage wells located inside the mine plan boundaries and were declared "shut-in" by the O&G Board. The total
production for a well was claimed in the year that the well was shut-in and mined through.
Energy 3-39
-------
Secondly, the gas content values assigned to each coal basin in the surface mine emissions component of the
inventory were changed to reflect recent work carried out by U.S. EPA (EPA 2005). This change for the 2006
inventory also impacted the reported emissions attributed to surface mining operations (active and post mining) for
all past reported years (1990 - 2005), resulting in increased emission estimates for surface and post-surface mining
operations for all reported years.
Finally, the conversion factor used previously to convert from mmcf of methane to Gg of CH4 was 52,150 (1990 -
2005). The conversion factor used in the natural gas emissions inventory is 51,921. In order to ensure consistency of
emissions estimates across the inventory, the conversion factor for the active mines inventory was changed to
51,921. This change impacted all previous year's inventories for the values calculated and reported for Gg of
methane emitted, and for Tg of CO2 Eq. emitted. The difference between these factors is 0.44 percent.
3.6. Abandoned Underground Coal Mines (IPCC Source Category 1B1a)
Underground coal mines contribute the largest share of CH4 emissions, with active underground mines the leading
source of underground emissions. However, mines also continue to release CH4 after closure. As mines mature and
coal seams are mined through, mines are closed and abandoned. Many are sealed and some flood through intrusion
of groundwater or surface water into the void. Shafts or portals are generally filled with gravel and capped with a
concrete seal, while vent pipes and boreholes are plugged in a manner similar to oil and gas wells. Some abandoned
mines are vented to the atmosphere to prevent the buildup of CH4 that may find its way to surface structures through
overburden fractures. As work stops within the mines, the CH4 liberation decreases but it does not stop completely.
Following an initial decline, abandoned mines can liberate CH4 at a near-steady rate over an extended period of
time, or, if flooded, produce gas for only a few years. The gas can migrate to the surface through the conduits
described above, particularly if they have not been sealed adequately. In addition, diffuse emissions can occur
when CH4 migrates to the surface through cracks and fissures in the strata overlying the coal mine. The following
factors influence abandoned mine emissions:
• Time since abandonment;
• Gas content and adsorption characteristics of coal;
• CH4 flow capacity of the mine;
• Mine flooding;
• Presence of vent holes; and
• Mine seals.
Gross abandoned mine CH4 emissions ranged from 6.0 to 9.1 Tg CO2Eq. from 1990 through 2006, 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 CO2Eq.) 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 2006, with only one closure in 2006. By 2006, gross abandoned mine emissions
declined to 6.8 Tg CO2Eq. (see Table 3-30 and Table 3-31). Gross emissions are reduced by methane recovered and
used at 20 mines, resulting in net emissions in 2006 of 5.4 Tg CO2Eq.
Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg CO2 Eq.)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990^=
6.0^
0.0^
6.0^
i
E ft Q5EEEEEE
i
i
i 2000
i 8.9
i 1.5
i 7.4
2001
8.2
1.5
6.7
2002
7.7
1.6
6.2
2003
7.5
1.5
6.0
2004
7.3
1.5
5.8
2005
7.0
1.4
5.6
2006
6.8
1.4
5.4
Note: Totals may not sum due to independent rounding.
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 3-31: CH4 Emissions from Abandoned Coal
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990^=
Mines (Gg)
1995=
424^
32=
392^
= 2000
I 422
= 72
I 350
2001
389
70
319
2002
368
75
293
2003
356
72
284
2004
347
71
276
2005
333
68
265
2006
322
65
257
Note: Totals may not sum due to independent rounding.
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 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 CH4 leaves the system, the reservoir
pressure, Pr, declines as described by the isotherm. The emission rate declines because the mine pressure (Pw) is
essentially constant at atmospheric pressure, for a vented mine, and the PI term is essentially constant at the
pressures of interest (atmospheric to 30 psia). A rate-time equation can be generated that can be used to predict
future emissions. This decline through time is hyperbolic in nature and can be empirically expressed as:
q=q1(l+bD1tf
where,
q = Gas rate at time t in mmcf/d
q; = Initial gas rate at time zero (to) in million cubic feet per day mmcfd)
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
Energy 3-41
-------
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 mcf/d
q; = Initial gas flow rate at time zero (to) 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 CH4 emissions. This
same relationship is assumed for abandoned mines. It was determined that 441 abandoned mines closing after 1972
produced emissions greater than 100 mcfd when active. Further, the status of 264 of the 44 1 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).
Table 3-32: Number of gassy abandoned mines occurring in U.S. basins grouped by class according to post-
abandonment state
Basin
Central Appl.
Illinois
Northern Appl.
Warrior Basin
Western Basins
Total
Sealed
23
28
41
0
25
117
Vented
25
o
J
22
0
o
3
53
Flooded Total Known Unknown Total Mines
48
14
16
14
2
94
96
45
79
14
30
264
111
25
32
0
9
177
207
70
111
14
39
441
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.
Information that is readily available such as coal production by state and county are helpful, but do 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
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
States, representing 78 percent of the emissions. State-specific, initial emission rates were used based on average
coal mine CH4 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. 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. CH4
degasification amounts were added to the quantity of CH4 ventilated for the total CH4 liberation rate for fifteen
mines that closed between 1992 and 2006. 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 2006, emission totals were downwardly adjusted to reflect abandoned mine CH4 emissions
avoided from those mines. The inventory totals were not adjusted for abandoned mine reductions in 1990 through
1992, because no data was reported for abandoned coal mining CH4 recovery projects during that time.
Uncertainty
A quantitative uncertainty analysis was conducted to estimate the uncertainty surrounding the estimates of
emissions from abandoned underground coal mines. The uncertainty analysis described below provides for the
specification of probability density functions for key variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide the range within which, with 95 percent certainty,
emissions from this source category are likely to fall.
As discussed above, the parameters for which values must be estimated for each mine in order to predict its decline
curve are: 1) the coal's adsorption isotherm; 2) CH4 flow capacity as expressed by permeability; and 3) pressure at
abandonment. Because these parameters are not available for each mine, a methodological approach to estimating
emissions was used that generates a probability distribution of potential outcomes based on the most likely value
and the probable range of values for each parameter. The range of values is not meant to capture the extreme
values, but values that represent the highest and lowest quartile of the cumulative probability density function of
each parameter. Once the low, mid, and high values are selected, they are applied to a probability density function.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-33. Abandoned coal mines
CH4 emissions in 2006 were estimated to be between 4.5 and 6.4 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 17 percent below to 19 percent above the 2006 emission estimate of 5.4 Tg CO2 Eq. One of the
reasons for the relatively narrow range is that mine-specific data is used in the methodology. The largest degree of
uncertainty is associated with the unknown status mines (which account for 40 percent of the mines), with a ±50
percent uncertainty.
Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal
Mines (Tg CO2 Eq. and Percent)
2006 Emission Uncertainty Range Relative to Emission
Estimate Estimate"
Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Abandoned Underground Coal CH4 5.4 4.5 6.4 -17% +19%
Mines
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Energy 3-43
-------
3.7. Natural Gas Systems (IPCC Source Category 1B2b)
The U.S. natural gas system encompasses hundreds of thousands of wells, hundreds of processing facilities, and
over a million miles of transmission and distribution pipelines. Overall, natural gas systems emitted 102.4 Tg CO2
Eq. (4,877 Gg) of CH4 in 2006, an 18 percent decrease over 1990 emissions (see Table 3-34 and Table 3-35), and
28.5 Tg CO2 Eq. (28,504Gg) of non-combustion CO2 in 2006, a 15 percent decrease over 1990 emissions (see Table
3-36 and Table 3-37). Improvements in management practices and technology, along with the replacement of older
equipment, have helped to stabilize emissions.
CH4 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 27 percent of CH4 emissions and about 25 percent of non-combustion CO2 emissions
from natural gas systems in 2006.
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 CH4 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 power plants or chemical plants. Compressor station facilities, which contain large reciprocating and
turbine compressors, are used to move the gas throughout the United States transmission system. Fugitive CH4
emissions from these compressor stations and from metering and regulating stations account for the majority of the
emissions from this stage. Pneumatic devices and engine uncombusted exhaust are also sources of CH4 emissions
from transmission facilities.
Natural gas is also injected and stored in underground formations, or liquefied and stored in above ground tanks,
during periods of low demand (e.g., summer), and withdrawn, processed, and distributed during periods of high
demand (e.g., winter). Compressors and dehydrators are the primary contributors to emissions from these storage
facilities. CH4 emissions from the transmission and storage sector account for approximately 37 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 1,250,000 miles of distribution mains in 2006, an increase from just over 947,000 miles in
1990 (OPS 2007b). Distribution system emissions, which account for approximately 24 percent of CH4 emissions
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
from natural gas systems and less than 1 percent of non-combustion CO2 emissions, result mainly from fugitive
emissions from gate stations and pipelines.41 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 2006 were 20
percent lower than 1990 levels.
Table 3-34. CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.)*
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
32.7^
14.9=
46.3^
30.8^
124.7^
i
i
i
i
i
1
i 2000
i 38.8
i 14.6
i 43.8
= 29.3
1 126.5
2001
41.5
14.7
40.7
28.5
125.3
2002
42.5
14.2
42.4
25.8
124.9
2003
40.1
13.6
42.8
26.9
123.3
2004
32.9
13.4
40.9
26.8
114.0
2005
25.0
11.8
38.5
27.2
102.5
2006
27.6
11.9
38.2
24.7
102.4
*Inchiding CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-35. CH4 Emissions from Natural Gas Systems (Gg)*
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990 =
1,555 =
707^
1,468 =
5,937^
i
I
1
1
1
1 6,098^
3 2000
1 1,849
1 693
1 2,087
1 1,395
1 6,024
2001
1,976
699
1,936
1,356
5,968
2002
2,024
675
2,019
1,228
5,946
2003
1,909
646
2,039
1,279
5,874
2004
1,566
639
1,947
1,275
5,426
2005
1,190
560
1,834
1,296
4,880
2006
1,317
568
1,817
1,176
4,877
*Inchiding CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-36. Non-combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990^
5.9^
27.8^
0.1 =
I
1
1
1
I
1 2000
1 6.0
1 23.3
1 0.1
1 +
1 29.4
2001
6.3
22.4
0.1
+
28.8
2002
6.5
23.1
0.1
+
29.6
2003
6.3
22.0
0.1
+
28.4
2004
6.2
21.8
0.1
+
28.1
2005
7.6
21.7
0.1
+
29.5
2006
7.2
21.2
0.1
+
28.5
Note: Totals may not sum due to independent rounding.
Table 3-37. Non-combustion CO2 Emissions from Natural Gas Systems (Gg)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990^
5
27
33
58^
m 1995^
m 9
= 24
= 33
60^
42^
m 2000
1 5,956
1 23,333
m 60
1 41
m 29,390
2001
6,307
22,387
59
40
28,793
2002
6,463
23,066
61
40
29,629
2003
6,342
22,002
61
40
28,445
2004
6,242
21,780
61
40
28,122
2005
7,627
21,736
60
39
29,462
2006
7,203
21,204
59
37
28,504
Note: Totals may not sum due to independent rounding.
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 and EPA (EPA/GRI1996). The EPA/GRI study
developed over 80 CH4 emission and activity factors to characterize emissions from the various components within
the operating stages of the U.S. natural gas system. The same activity factors were used to estimate both CH4 and
41 The percentages of total emissions from each stage may not sum to 100 percent due to independent rounding.
Energy 3-45
-------
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. For other years, a set of industry activity factor
drivers was developed that can be used to update activity factors. These drivers include statistics on gas production,
number of wells, system throughput, miles of various kinds of pipe, and other statistics that characterize the changes
in the U.S. natural gas system infrastructure and operations.
See Annex 3.4 for more detailed information on the methodology and data used to calculate CH4 and non-
combustion CO2 emissions from natural gas systems.
Activity factor data were taken from the following sources: American Gas Association (AGA 1991 through 1998);
Minerals and Management Service (MMS 2007a-e); Monthly Energy Review (ElA 20071); Natural Gas Liquids
Reserves Report (EIA 2005); Natural Gas Monthly (EIA 2007b,c,e); the Natural Gas STAR Program annual
emissions savings (EPA 2007); Oil and Gas Journal (OGJ 1997 through 2007); Office of Pipeline Safety (OPS
2007a-b) and other Energy Information Administration publications (EIA 2001, 2004, 2007a,d); World Oil
Magazine (2007a-b). Data for estimating emissions from hydrocarbon production tanks is incorporated (EPA
1999). Coalbed CH4 well activity factors were taken from the Wyoming Oil and Gas Conservation Commission
(Wyoming 2007) and the Alabama State Oil and Gas Board (Alabama 2007). Other state well data was taken from:
American Association of Petroleum Geologists (AAPG 2004); Brookhaven College (Brookhaven 2004); Kansas
Geological Survey (Kansas 2007); Montana Board of Oil and Gas Conservation (Montana 2007); Oklahoma
Geological Survey (Oklahoma 2007); Morgan Stanley (Morgan Stanley 2005); Rocky Mountain Production Report
(Lippman (2003); New Mexico Oil Conservation Division (New Mexico 2007a,b); Texas Railroad Commission
(Texas 2007a-d); Utah Division of Oil, Gas and Mining (Utah 2007). Emission factors were taken from EPA/GRI
(1996). GTFs Unconventional Natural Gas and Gas Composition Databases (GTI 2001) were used to adapt the
CH4 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 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 is
summarized in Table 3-38. Natural gas systems CH4 emissions in 2006 were estimated to be between 79.1 and
148.4 Tg CO2 Eq. at a 95 percent confidence level. Natural gas systems non-combustion CO2 emissions in 2006
were estimated to be between 22.0 and 41.3 Tg CO2 Eq. at 95 percent confidence level.
Table 3-38: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-combustion CO2 Emissions from Natural
Gas Systems (Tg CO2 Eq. and Percent)
2006
Emission
Estimate Uncertainty Range Relative to Emission Estimate"
Source Gas (Tg CO2 Eq.) (TgCO2Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper Bound
Natural Gas Systems CH4 102.4 79.1 148.4 -23% +45%
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Natural Gas Systems'3 CO2 28.5 22.0 41.3 -23% +45%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
b An uncertainty analysis for the non-combustion CO2 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-combustion CO2 emissions.
Recalculations Discussion
Offshore oil and gas platform counts are driven by the percentage of total platforms that are located on oil and gas
fields, respectively, as identified by MMS. This percentage can be calculated fromMMS (2007a,b,e) for years 2003
onward. For year 1992, the estimate was provided by MMS by direct communication. The oil platform count for
years 1990, 1991, and 1993 through 2002 are driven by a linear projection based on known platform counts in 1992
and 2003. A miscalculation in year 2003 for oil platform count was re-estimated, which caused the entire time
series prior to year 2003 (except 1992) to change. This change resulted in a reallocation of platform counts to the
natural gas and petroleum models. The total number of offshore platforms, both oil and gas, used as drivers
remained the same. The effects of this recalculation are most significant in 1990, with an absolute difference of 31
Gg; less significant changes occurred in all subsequent years.
The second recalculation is a result of changing several base year (1992) activity factor and emissions factor data to
the exact values from the EPA/GRI 1996 report. These changes were small and the effects were an increase of less
than 1 percent in 1992 CH4 emissions.
A third recalculation is the result of updating previous years' activity and Natural Gas STAR reduction values with
revised data. This is especially evident in 2005, where the revised reductions data reports an additional 443 Gg of
reductions totaled from all four sectors; decreasing total 2005 emission estimates by nearly 9.5 percent.
QA/QC and Verification Discussion
A tier 2 QA/QC analysis was undertaken to examine why emissions from small reciprocating compressors are lower
in the production sector than in other sectors of the natural gas industry. The emission factor for these compressors
is based on EPA/GRI 1996. Background information from EPA/GRI 1996, along with information from the
Natural Gas STAR program was analyzed and it was determined that the emission factor for small compressors in
the eastern United States (U.S. East) was significantly lower than the emission factor developed for the western area
of the country (U.S. West). Details of the emission factor development revealed that the U.S. East emission factor
in EPA/GRI 1996 does not include fugitives from compressor seals and pressure relief valves. Experience from the
Natural Gas STAR Program demonstrates that seal leakage from rod packing is the largest source of fugitive
emissions from reciprocating compressors. To account for compressor seal leakage, the U.S. West emission factor
was used for the entire United States for 1990 through 2006. These updated emission factors are an interim
improvement and further research is underway to compare these updated emissions factors with recent vendor data.
Planned Improvements
Currently, activity factors for most sources in the natural gas inventory are dependent on EPA/GRI 1996 estimates
of activity data in base year 1992. The activity factors for all years other than the base year are estimated from the
base year activity data and are driven by an appropriate activity driver. However, in some instances activity data are
directly available from published sources and there is no need to derive the current year activity data through the use
of drivers. Research is underway to determine the feasibility of using published activity data, where available, and
whether this would impact any of the emission factors currently used.
Separately, work has been initiated to update select emission factors from the earlier study. Where relevant, these
emission factors will be incorporated into the inventory when they become available.
As noted above, additional research will be undertaken to evaluate, and as necessary refine, the emission factor for
small reciprocating compressors in the U.S. West region.
Energy 3-47
-------
3.8. Petroleum Systems (IPCC Source Category 1B2a)
CH4 emissions from petroleum systems are primarily associated with crude oil production, transportation, and
refining operations. During each of these activities, CH4 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 calculations previously discussed, and hence have not been taken into account in this inventory.
Total CH4 and CO2 emissions from petroleum systems in 2006 were 28.4 Tg CO2 Eq. (1,354 Gg CH4) and 0.3 Tg
CO2 (293 Gg) respectively. Since 1990, CH4 emissions have declined by 16 percent, due to industry efforts to
reduce emissions and a decline in domestic oil production (see Table 3-39, Table 3-40, Table 3-41, and Table 3-42).
CO2 emissions have also declined by 22 percent since 1990 due to similar reasons.
Production Field Operations. Production field operations account for over 97 percent of total CH4 emissions from
petroleum systems. Vented CH4 from field operations account for over 91 percent of the emissions from the
production sector, unburned CH4 combustion emissions account for 5.2 percent, fugitive emissions are 3.4 percent,
and process upset emissions, slightly over one-tenth of a percent. The most dominant sources of emissions, in the
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 CH4 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 methane 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, 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 while the remaining 1.5 percent of the 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 hah0 of one percent of total
CH4 emissions from the oil industry. Venting from tanks and marine vessel loading operations accounts for 64
percent of CH4 emissions from crude oil transportation. Fugitive emissions, almost entirely from floating roof
tanks, account for 19 percent. The remaining 17 percent is 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 over two percent of total CH4
emissions from the oil industry because most of the CH4 in crude oil is removed or escapes before the crude oil is
delivered to the refineries. There is an insignificant amount of CH4 in all refined products. Within refineries,
vented emissions account for about 87 percent of the emissions, while fugitive and combustion emissions account
for approximately six and seven percent, respectively. Refinery system blowdowns for maintenance and the process
of asphalt blowing—with air, to harden the asphalt—are the primary venting contributors. Most of the fugitive CH4
emissions from refineries are from leaks in the fuel gas system. Refinery combustion emissions include small
amounts of unburned CH4 in process heater stack emissions and unburned CH4 in engine exhausts and flares.
Table 3-39: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.)
Activity
Production Field Operations
1990^
33.2^
m 2000
m 29.6
2001
29.5
2002
29.2
2003
28.5
2004
28.0
2005
27.6
2006
27.7
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Pneumatic device venting
Tank venting
Combustion & process upsets
Misc. venting & fugitives
Wellhead fugitives
Grade Oil Transportation
Refining
Total
10.31
3.8i
1.9i
16.8i
0.5i
o.ii
0.51
33.9i
^H
1.7^^3
^^.
9.0
3.2
1.6
15.3
0.5
0.1
0.6
30.3
8.9
3.2
1.6
15.3
0.5
0.1
0.6
30.2
8.9
3.2
1.6
15.1
0.5
0.1
0.6
29.9
8.7
3.1
1.5
14.7
0.5
0.1
0.6
29.2
8.6
3.0
1.5
14.5
0.4
0.1
0.6
28.7
8.3
2.8
1.5
14.5
0.4
0.1
0.6
28.3
8.4
2.9
1.5
14.5
0.4
0.1
0.6
28.4
Note: Totals may not sum due to independent rounding.
Table 3-40: CH4 Emissions from Petroleum
Activity
Production Field Operations
Pneumatic device venting
Tank venting
Combustion & process upsets
Misc. venting & fugitives
Wellhead fugitives
Grade Oil Transportation
Refining
Total
19901
1,5811
489^
1791
881
7991
261
71
25!
1,6121
Systems (Gg)
1995g==s
^i
=
^i
= l,524p^
2000
1,409
428
154
76
728
22
5
28
1,442
2001
1,404
425
154
75
727
22
5
27
1,436
2002
1,390
424
151
75
717
23
5
27
1,422
2003
1,357
412
150
73
701
22
5
27
1,390
2004
1,335
408
142
72
692
21
5
28
1,368
2005
1,314
397
135
71
691
20
5
28
1,346
2006
1,321
399
138
72
693
20
5
28
1,354
Note: Totals may not sum due to independent rounding.
Table 3-41: CO2 Emissions from Petroleum
Activity
Production Field Operations
Pneumatic device venting
Tank venting
Misc. venting & fugitives
Wellhead fugitives
Total
+ Does not exceed 0.05 Tg CO2 Eq.
19901
0.4^
+^
0.31
+1
+^
0.4^
Table 3-42: CO2 Emissions from Petroleum
Activity
Production Field Operations
Pneumatic device venting
Tank venting
Misc. venting & fugitives
Wellhead fugitives
Total
1990!=
3761
271
3281
18g
m
3761
Systems (Tg CO2
^
0.3 ===
^^
^S
Systems (Gg)
^
\===
^
Eq.)
2000
0.3
+
0.3
+
+
0.3
2000
325
24
283
17
1
325
2001
0.3
+
0.3
+
+
0.3
2001
325
24
283
17
1
325
2002
0.3
+
0.3
+
+
0.3
2002
320
24
278
16
1
320
2003
0.3
+
0.3
+
+
0.3
2003
316
23
276
16
1
316
2004
0.3
+
0.3
+
+
0.3
2004
302
23
262
16
1
302
2005
0.3
+
0.2
+
+
0.3
2005
287
22
248
16
1
287
2006
0.3
+
0.3
+
+
0.3
2006
293
22
253
16
1
293
Note: Totals may not sum due to independent rounding.
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.
Energy 3-49
-------
The methodology for estimating CH4 emissions from the 64 oil industry activities employs emission factors initially
developed by EPA (1999) and activity factors that are based on two EPA studies (1996, 1999) and EPA (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 2006. 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 2007a-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
methane 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 years 1990 through 2006 were collected from a wide variety of statistical resources. For some
years, complete activity factor data were not available. In such cases, one of three approaches was employed.
Where appropriate, the activity factor was calculated from related statistics using ratios developed for EPA (1996).
For example, EPA (1996) found that the number of heater treaters (a source of CH4 emissions) is related to both
number of producing wells and annual production. To estimate the activity factor for heater treaters, reported
statistics for 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 2006 based on EPA (1999). Lastly, the previous year's data
were used when data for the current year were unavailable. The CH4 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 2006, 1990 through 2007, 1995 through 2007a-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, 2007a-c), analysis of MMS data (EPA 2005, MMS 2004), the Oil & Gas Journal (OGJ 2007a,b), the
Interstate Oil and Gas Compact Commission (IOGCC 2007), and the United States Army Corps of Engineers
(1995-2005).
Uncertainty
This section describes the analysis conducted to quantify uncertainty associated with the estimates of emissions
from petroleum systems. Performed using @RISK software and the IPCC-recommended Tier 2 methodology
(Monte Carlo Simulation technique), the method employed provides for the specification of probability density
functions for key variables within a computational structure that mirrors the calculation of the inventory estimate.
The results provide the range within which, with 95 percent certainty, emissions from this source category are likely
to fall.
The detailed, bottom-up inventory analysis used to evaluate U.S. petroleum systems reduces the uncertainty related
to the CH4 emission estimates in comparison with a top-down approach. However, some uncertainty still remains.
Emission factors and activity factors are based on a combination of measurements, equipment design data,
engineering calculations and studies, surveys of selected facilities and statistical reporting. Statistical uncertainties
arise from natural variation in measurements, equipment types, operational variability and survey and statistical
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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
93.0 percent of the total 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 3-43 Petroleum systems CH4
emissions in 2006 were estimated to be between 20.5 and 69.3 Tg CO2 Eq., while CO2 emissions were estimated to
be 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 2006 emission estimates of 28.4 and 0.3 Tg CO2 Eq. for CH4 and CO2, respectively.
Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg CO2 Eq. and
Percent)
2006 Emission
Estimate Uncertainty Range Relative to Emission Estimate"
Source Gas (TgCO2Eq.) (TgCO2Eq.) (%)
Petroleum Systems CH4 28.4
Petroleum Systems CO2 0.3
Lower
Bound
20.5
0.2
Upper
Bound
69.3
0.7
Lower
Bound
-28%
-28%
Upper
Bound
+144%
+144%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of vented, fugitive, and process upset CO2 emissions from the production sector were incorporated into
the petroleum systems inventory for 1990-2006. CO2 emissions were estimated using the methane emission
sources' activity factors and drivers for the corresponding CO2 emission sources. The emission factors for CO2
were estimated by multiplying the methane emission factors by a conversion factor, which is the ratio of CO2
content divided by methane content in produced associated gas. The only exceptions to this methodology are the
emission factors for crude oil storage tanks, which were estimated from API TankCalc simulation runs. CO2
emissions from the production sector account for 293 Gg of CO2 in the year 2006. CO2 emissions from the
transportation and refining sectors are assumed to be negligible. Combustion emissions are already accounted for in
the Fossils Fuels Combustion inventory.
In addition, two types of activity factor and seven types of activity driver revisions were made in the 2006
Petroleum Systems emissions inventory. All revisions but one were due to updating previous years' data with
revised data from existing data sources. The one exception to the general revisions was the recalculation of an
activity driver for oil platforms. Offshore oil and gas platform counts are driven by the percentage of total platforms
that are located on oil and gas fields, respectively, as identified by MMS. This percentage can be calculated from
MMS (2007a-c) for years 2003 onward. For year 1992, the estimate was provided by MMS by direct
communication. The oil platform counts for years 1990, 1991, and 1993 through 2002 are driven by a linear
projection based on known platform counts in 1992 and 2003. A miscalculation in year 2003 was re-estimated,
causing the entire time series prior to year 2003 (except 1992) to change. This change resulted in a reallocation of
platform counts to the natural gas and petroleum models. The total number of offshore platforms, both oil and gas,
used as drivers remained the same.
Overall changes resulted in a decrease in total emissions of approximately 0.22 Tg CO2 Eq. (0.8 percent) for year
2005. For 1990 and 1991, total emissions decreased by 2 percent or less; while between 1993 and 2004 the total
emission estimates increased by up to 13 percent from the previous year's inventory estimates. This increase is
largely due to the recalculation of the oil platform activity driver.
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 in (EPA 2005)
Energy 3-51
-------
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.
[BEGIN BOX]
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 CO2 is produced from both naturally-occurring CO2
reservoirs and from industrial sources such as natural gas processing plants and ammonia plants. In the current
Inventory, emissions from naturally-produced CO2 are estimated based on the application.
In the current Inventory report, the CO2 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 CO2 used in EOR
operations is assumed to be fully sequestered. Additionally, all anthropogenic CO2 emitted from natural gas
processing and ammonia plants is assumed to be emitted to the atmosphere, regardless of whether the CO2 is
captured or not. These emissions are currently included in the Natural Gas Systems and the Ammonia Manufacture
sections of the Inventory report, respectively.
IPCC (2006) includes, for the first time, methodological guidance to estimate emissions from the capture, transport,
injection, and geological storage of CO2. 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 CO2 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 CO2 emissions estimates for geologic storage.
In October 2007, the U. S. EPA announced plans to develop regulations for geologic sequestration of CO2 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 CO2 capture, transport, injection and
geologic storage are not yet included in national totals. Preliminary estimates indicate that the amount of CO2
captured from industrial and natural sites, as well as fugitive emissions from pipelines is 39.0 Tg CO2 (39,041 Gg
CO2) (see Table 3-44). Site-specific monitoring and reporting data for CO2 injection sites (i.e., EOR operations)
were not readily available, therefore, these estimates assume all CO2 is emitted.
Table 3-44: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.)
Year
Acid Gas Removal Plants
Naturally Occurring CO2
Ammonia Production Plants
Pipelines Transporting CO2
Total
1990^=
4.8^
^ol
0.0^
20.0^
1995^
3.7^
99 "7
26.9^
2000
2.3
23.1
0.7
0.0
26.1
2001
2.9
23.4
0.7
0.0
27.0
2002
2.9
23.0
0.7
0.0
26.6
2003
3.0
24.4
0.7
0.0
28.1
2004
3.7
27.0
0.7
0.0
31.4
2005
6.0
28.2
0.7
0.0
34.9
2006
7.0
31.4
0.7
0.0
39.0
Table 3-45: Potential Emissions from CO2 Capture and Transport (Gg)
Year
Acid Gas Removal Plants
Naturally Occurring CO2
Ammonia Production Plants
Pipelines Transporting CO2
1990^
4,832^
15,129^
0^
8^=:
&
3 100^^=:
| 3,672^
1 22,547p
| 676JJIJ:
\ 2000 2001 2002 2003 2004 2005 2006
\ 2,264 2,894 2,943 2,993 3,719 5,992 6,997
\ 23,149 23,442 22,967 24,395 27,002 28,192 31,359
\ 676 676 676 676 676 676 676
\ 8888778
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Total 19,969s 26,904= 26,098 27,020 26,595 28,073 31,405 34,868 39,041
[END BOX]
3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5)
Combustion is used to manage about 7 to 17 percent of the municipal solid wastes (MSW) generated in the United
States, depending on the source of the estimate and the scope of materials included in the definition of solid waste
(EPA 2000b, Goldstein and Matdes 2001, Kaufman et al. 2004a, Simmons et al. 2006). Almost all combustion of
municipal solid wastes in the United States occurs at waste-to-energy facilities where useful energy is recovered,
and thus emissions from waste combustion are accounted for in the Energy chapter. Combustion of municipal solid
wastes results in conversion of the organic inputs to 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 combustion are calculated by estimating the quantity of waste combusted and the fraction of the waste that is
C derived from fossil sources.
Most of the organic materials in municipal solid wastes are of biogenic origin (e.g., paper, yard trimmings), and
have their net C flows accounted for under the Land Use, Land-Use Change, and Forestry chapter. However, some
components—plastics, synthetic rubber, synthetic fibers, and carbon black—are of fossil origin. Plastics in the U.S.
waste stream are primarily in the form of containers, packaging, and durable goods. Rubber is found in durable
goods, such as carpets, and in non-durable goods, such as clothing and footwear. Fibers in municipal solid wastes
are predominantly from clothing and home furnishings. Tires (which contain rubber and carbon black) are also
considered a "non-hazardous" waste and are included in the municipal solid waste combustion estimate, though
waste disposal practices for tires differ from the rest of municipal solid waste (viz., most combustion occurs outside
of MSW combustion facilities).
Over 31 million metric tons of municipal solid wastes were combusted in the United States in 2006 (EPA 2007).
CO2 emissions from combustion of municipal solid wastes rose 91 percent since 1990, to an estimated 20.9 Tg CO2
Eq. (20,922 Gg) in 2006, as the volume of synthetic fibers and other fossil C-containing materials in MSW
increased (see Table 3-46 and Table 3-47). Waste combustion is also a source of N2O emissions (De Soete 1993).
N2O emissions from municipal solid waste combustion were estimated to be 0.4 Tg CO2 Eq. (1 Gg N2O) in 2006,
and have not changed significantly since 1990.
Table 3-46: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Tg CO2 Eq.)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N2O
Total
1990^
10.9^
8.0^
0.2^
0.2^
1.3 =
1.2 =
0.5 =
11.4^
1
|
| 10.3s
1
1
1
1
1
1 16.2s
3 2000
3 17.5
3 11.8
3 0.9
3 1.2
1 1.6
1 2.0
1 0.4
3 17.9
2001
18.0
12.1
0.9
1.2
1.7
2.1
0.4
18.4
2002
18.5
12.3
1.0
1.2
1.8
2.2
0.4
18.9
2003
19.1
12.7
1.0
1.3
1.8
2.3
0.4
19.5
2004
20.1
13.4
1.1
1.4
1.9
2.3
0.4
20.5
2005
20.7
13.7
1.2
1.6
1.9
2.4
0.4
21.1
2006
20.9
13.7
1.2
1.6
1.9
2.5
0.4
21.3
Table 3-47: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Gg)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
1990 H
10,950 m
7,976 M
191 m
249 m
M 1995 H
= 15,712 m
= 10,347 a
m
= 1,099 m
= 2000
^17,518
= 11,791
= 893
^1,167
2001
17,971
12,094
895
1,170
2002
18,458
12,316
952
1,245
2003
19,058
12,657
1,010
1,320
2004
20,097
13,356
1,108
1,449
2005
20,673
13,662
1,207
1,579
2006
20,922
13,746
1,207
1,579
Energy 3-53
-------
Synthetic Rubber in MSW 1,334 ^U,640 !,721 !,760 1,815 M71 M73 !,902
Synthetic Fibers 1,200 ^^1,830 2,090 2,185 2,257 2,312 2,352 2,489
Methodology
Emissions of CO2 from MSW combustion include CO2 generated by the combustion of plastics, synthetic fibers,
and synthetic rubber, as well as the combustion of synthetic rubber and carbon black in tires. These emissions were
estimated by multiplying the amount of each material combusted by the C content of the material and the fraction
oxidized (98 percent). Plastics combusted in municipal solid wastes were categorized into seven plastic resin types,
each 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 combustion sources is provided
in Annex 3.6.
For each of the methods used to calculate CO2 emissions from municipal solid waste combustion, data on the
quantity of product combusted and the C content of the product are needed. For plastics, synthetic rubber, and
synthetic fibers, the amount of material in municipal solid wastes and its portion combusted were taken from the
Characterization of Municipal Solid Waste in the United States (EPA 2000b, 2002, 2003, 2005a, 2006b, 2007) 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, 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 municipal solid waste combustion
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).
Combustion of municipal solid waste also results in emissions of N2O. These emissions were calculated as a
function of the total estimated mass of municipal solid waste combusted and an emission factor. 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 combusted in each year; for 1990 through 2004, these data were derived from the
information published in BioCycle (Simmons et al. 2006). Data on total waste combusted was not available for
2005 and 2006, so the values for 2005 and 2006 were assumed to equal the most recent value available (2004).
Table 3-48 provides data on municipal solid waste generation and percentage combustion 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).
Table 3-48: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted
Year
1990
1995
2000
Waste Generation
266,365,714
296,390,405
371,071,109
Combusted (%)
11.5
10.0
7.0
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2001 353,086,962a 7.4a
2002 335,102,816 7.7
2003 343,482,645b 7.6b
2004 351,862,474 7.4
2005 351,862,474C 7.4C
2006 351,86,2474° 7.4°
a Interpolated between 2000 and 2002 values.
b Interpolated between 2002 and 2004 values.
0 Assumed equal to 2004 value.
Uncertainty
A Tier 2 Monte Carlo analysis was performed to determine the level of uncertainty surrounding the estimates of
CO2 emissions and N2O emissions from municipal solid waste combustion. IPCC Tier 2 analysis allows the
specification of probability density functions for key variables within a computational structure that mirrors the
calculation of the inventory estimate. Uncertainty estimates and distributions for waste generation variables (i.e.,
plastics, synthetic rubber, and textiles generation) were obtained through a conversation with one of the authors of
the Municipal Solid Waste in the United States reports. Statistical analyses or expert judgments of uncertainty were
not available directly from the information sources for the other variables; thus, uncertainty estimates for these
variables were determined using assumptions based on source category knowledge and the known uncertainty
estimates for the waste generation variables.
The uncertainties in the waste combustion emission estimates arise from both the assumptions applied to the data
and from the quality of the data. Key factors include MS W combustion rate; fraction oxidized; missing data on
MSW composition; average C content of MSW components; assumptions on the syntheti^iogenic 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 3-49. Municipal solid waste
combustion CO2 emissions in 2006 were estimated to be between 16.8 and 23.7 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 20 percent below to 13 percent above the 2006 emission estimate of 20.9
Tg CO2 Eq. Also at a 95 percent confidence level, municipal solid waste combustion N2O emissions in 2006 were
estimated to be between 0.1 and 1.1 TgCO2Eq. This indicates a range of 66 percent below to 184 percent above
the 2006 emission estimate of 0.4 Tg CO2 Eq.
Table 3-49: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from Municipal Solid Waste Combustion
(Tg CO2 Eq. and Percent)
Source
Municipal Solid Waste Combustion
Municipal Solid Waste Combustion
Gas
CO2
N2O
2006
Emission
Estimate
(Tg C02
Eq.)
20.9
0.4
Uncertainty Range Relative to
Estimate"
(TgC02Eq.)
Lower Upper
Bound Bound
16.8 23.7
0.1 1.1
(
Lower
Bound
-20%
-66%
Emission
At)
Upper
Bound
13%
184%
aRange of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
QA/QC and Verification
A source-specific QA/QC plan was implemented for MSW Combustion. This effort included a Tier 1 analysis, as
well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved checks specifically
Energy 3-55
-------
focusing on the activity data and specifically focused on the emission factor and activity data sources and
methodology used for estimating emissions from MSW combustion. Trends across the time series were analyzed to
determine whether any corrective actions were needed.
Planned Improvements
Additional data sources for calculating an N2O emission factor for U.S. MSW combustion will be investigated for
future drafts. In addition, the use of new techniques using radiocarbon dating to directly measure biogenic C
content of MSW combustion flue gas will also be investigated. Additional data sources for calculating an N2O
emission factor for U.S. MSW combustion will be investigated for future drafts. In addition, the use of new
techniques using radiocarbon dating to directly measure biogenic C content of MSW combustion flue gas will also
be investigated. Furthermore, efforts have been initiated to reconcile differences in the separate data sources used
for the CO2 and N2O emission calculations
3.10. Energy Sources of Indirect Greenhouse Gas Emissions
In addition to the main greenhouse gases addressed above, many energy-related activities generate emissions of
indirect greenhouse gases. Total emissions of nitrogen oxides (NOX), carbon monoxide (CO), and non-CH4 volatile
organic compounds (NMVOCs) from energy-related activities from 1990 to 2006 are reported in Table 3-50.
Table 3-50: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg)
Gas/Source
NOX
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
International Bunker Fuels*
CO
Mobile Combustion
Stationary Combustion
Municipal Solid Waste
Combustion
Oil and Gas Activities
International Bunker Fuels*
NMVOCs
Mobile Combustion
Stationary Combustion
Oil and Gas Activities
Municipal Solid Waste
Combustion
International Bunker Fuels*
1990=
21
10
9
;
125
119
5
12
10
139^
,000^
912^
= 1995=
I 20
I 10
1 9
1 1
I 104
I 97
1 5
I 1
I 10
I 8
,631 =
,821 =
100^
,540m
,383^
316^
,073^
113=
745 =
•> ' ^^ =
973^
582^
237^
= 2000
M 18,537
= 10,310
= 8,002
M Hi
1 114
M 1,334
M 89,715
Hi 83,559
1 4'340
1 146
M 1,670
= 124
I 8,953
= 7,230
m 1,077
M 389
1 257
M 44
2001
17,714
9,819
7,667
113
114
1,266
86,046
79,851
4,377
147
1,672
120
8,610
6,872
1,080
400
258
42
2002
17,364
10,154
6,791
321
98
988
82,148
75,421
4,965
323
1,439
118
9,608
7,235
1,585
545
243
35
2003
16,474
9,642
6,419
316
97
900
77,689
71,038
4,893
321
1,437
112
9,223
6,885
1,560
538
239
32
2004
15,607
9,191
6,004
316
97
1,190
73,731
67,096
4,876
321
1,437
128
8,910
6,587
1,553
533
237
41
2005
15,005
8,739
5,853
316
97
1,190
69,773
63,154
4,860
321
1,437
133
8,597
6,289
1,545
528
235
41
2006
14,309
8,287
5,610
315
97
1,731
65,815
59,213
4,844
322
1,437
150
8,284
5,991
1,538
523
232
56
* These values are presented for informational purposes only and are not included in totals.
Note: Totals may not sum due to independent rounding.
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.
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
Program emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the accuracy of the emission factors used and accurate estimates of
activity data. A quantitative uncertainty analysis was not performed.
3.11. International Bunker Fuels (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.42 These decisions are reflected in the Revised 1996
IPCC Guidelines, as well as the 2006 IPCC GLs, in which countries are requested to report emissions from ships or
aircraft that depart from their ports with fuel purchased within national boundaries and are engaged in international
transport separately from national totals (IPCC/UNEP/OECD/IEA 1997).43
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.44 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.45
Emissions of CO2 from aircraft are essentially a function of fuel use. CH4 and N2O emissions also depend upon
engine characteristics, flight conditions, and flight phase (i.e., take-off, climb, cruise, decent, and landing). CH4 is
the product of incomplete combustion and occur 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
42 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).
43 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil
Aviation Organization.
44 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).
45 Naphtha-type jet fuel was used in the past by the military in turbojet and turboprop aircraft engines.
Energy 3-57
-------
that are engaged in international transport. Ocean-going ships are generally classified as cargo and passenger
carrying, military (i.e., Navy), fishing, and miscellaneous support ships (e.g., tugboats). For the purpose of
estimating greenhouse gas emissions, international bunker fuels are solely related to cargo and passenger carrying
vessels, which is the largest of the four categories, and military vessels. Two main types of fuels are used on sea-
going vessels: distillate diesel fuel and residual fuel oil. CO2 is the primary greenhouse gas emitted from marine
shipping.
Overall, aggregate greenhouse gas emissions in 2006 from the combustion of international bunker fuels from both
aviation and marine activities were 128.4 Tg CO2 Eq., or 12 percent above emissions in 1990 (see Table 3-51 and
Table 3-52). Although emissions from international flights departing from the United States have increased
significantly (56 percent), emissions from international shipping voyages departing the United States have
decreased by 18 percent since 1990. The majority of these emissions were in the form of CO2; however, small
amounts of CH4 and N2O were also emitted.
Table 3-51: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.)
Gas/Mode
1990
2000
2001
2002 2003
2004
2005
2006
C02
Aviation
Marine
CH4
Aviation
Marine
N2O
Aviation
Marine
97.6
58.7
38.9
0.1
0.1
0.9
0.6
0.3
89.1
61.1
28.0
0.1
0.1
0.8
0.6
0.2
103.6
58.8
44.8
0.1
0.1
0.8
0.6
0.3
119.0
64.9
54.1
0.1
0.1
1.1
0.6
0.4
122.6
67.5
55.1
0.1
0.1
1.1
0.7
0.4
127.1
71.1
56.0
0.2
0.1
1.1
0.7
0.4
Total
102.2
98.6
90.0 104.6 120.2 123.8 128.4
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-52: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N2O
Aviation
Marine
1990^
113,683^
45,731^
67,952^
i
1 100,627^
m
m
1
1
1
1
1
1
i 2000
1 101,125
= 59,853
1 41,272
1 6
i 2
i 4
i 3
i 2
i i
2001
97,563
58,696
38,866
5
2
4
3
2
1
2002
89,101
61,120
27,981
4
2
3
3
2
1
2003
103,583
58,806
44,777
6
2
4
3
2
1
2004
118,975
64,891
54,084
7
2
5
3
2
1
2005
122,580
67,517
55,063
7
2
5
4
2
1
2006
127,097
71,141
55,956
7
2
5
4
2
1
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Methodology
Emissions of CO2 were estimated by applying C content and fraction oxidized factors to fuel consumption activity
data. This approach is analogous to that described under CO2 from Fossil Fuel Combustion. C content and fraction
oxidized factors for jet fuel, distillate fuel oil, and residual fuel oil were taken directly from EIA and are presented
in Annex 2.1, Annex 2.2, and Annex 3.7 of this Inventory. Density conversions were taken from Chevron (2000),
ASTM (1989), and USAF (1998). Heat content for distillate fuel oil and residual fuel oil were taken from EIA
(2007) and USAF (1998), and heat content for jet fuel was taken from EIA (2007). A complete description of the
methodology and a listing of the various factors employed can be found in Annex 2.1. See Annex 3.7 for a specific
discussion on the methodology used for estimating emissions from international bunker fuel use by the U.S.
military.
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Emission estimates for CH4 and N2O were calculated by multiplying emission factors by measures of fuel
consumption by fuel type and mode. Emission factors used in the calculations of CH4 and N2O emissions were
obtained from the Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). For aircraft emissions, the
following values, in units of grams of pollutant per kilogram of fuel consumed (g/kg), were employed: 0.09 for CH4
and 0.1 for N2O For marine vessels consuming either distillate diesel or residual fuel oil the following values
(g/MJ), were employed: 0.32 for CH4 and 0.08 for N2O. Activity data for aviation included solely jet fuel
consumption statistics, while the marine mode included both distillate diesel and residual fuel oil.
Activity data on aircraft fuel consumption were collected from three government agencies. Jet fuel consumed by
U.S. flag air carriers for international flight segments was supplied by the Bureau of Transportation Statistics (DOT
1991 through 2006). It was assumed that 50 percent of the fuel used by U.S. flagged carriers for international
flights—both departing and arriving in the United States—was purchased domestically for flights departing from
the United States. In other words, only one-half of the total annual fuel consumption estimate was used in the
calculations. Data on jet fuel expenditures by foreign flagged carriers departing U.S. airports was taken from
unpublished data collected by the Bureau of Economic Analysis (BEA) under the U. S. Department of Commerce
(BEA 1991 through 2006). Approximate average fuel prices paid by air carriers for aircraft on international flights
was taken from DOT (1991 through 2006) and used to convert the BEA expenditure data to gallons of fuel
consumed. Data on U.S. Department of Defense (DoD) aviation bunker fuels and total jet fuel consumed by the
U.S. military was supplied by the Office of the Under Secretary of Defense (Installations and Environment), DoD.
Estimates of the percentage of each Service's total operations that were international operations were developed by
DoD. Military aviation bunkers included international operations, operations conducted from 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 2007). 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 3-53. 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 2007) for 1990 through 2002, and the
Department of Homeland Security's Bunker Report for 2003 through 2006 (DHS 2008). Activity data on distillate
diesel consumption by military vessels departing from U.S. ports were provided by DESC (2007). 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 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
U.S. and Foreign Carriers
Foreign Carriers
U.S. Military
Total
1990^
1,954^
2,051^
862^
4,867^
1
1
1 2,544^
1
i
1 2000
1 2,737
1 3,162
1 480
i 6,380
2001
2,619
3,113
524
6,255
2002
2,495
3,537
482
6,515
2003
2,418
3,377
473
6,268
2004
2,466
3,953
498
6,917
2005
2,760
3,975
462
7,198
2006
2,914
4,272
400
7,586
Note: Totals may not sum due to independent rounding.
Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons)
Fuel Type
Residual Fuel Oil
Distillate Diesel Fuel & Other
U.S. Military Naval Fuels
Total
1990^
4,781^
617^
522^
5,920^
n
i
i
i
n
1 2000
1 2,967
1 290
1 329
1 3,586
2001
2,846
204
318
3,368
2002
1,937
158
348
2,443
2003
3,152
290
459
3,901
2004
3,695
505
530
4,730
2005
3,881
444
471
4,796
2006
4,004
446
414
4,864
Note: Totals may not sum due to independent rounding.
Energy 3-59
-------
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.46 For example, smaller aircraft on shorter routes often carry sufficient fuel to
complete several flight segments without refueling in order to minimize time spent at the airport gate or take
advantage of lower fuel prices at particular airports. This practice, called tankering, when done on international
flights, complicates the use of fuel sales data for estimating bunker fuel emissions. Tankering is less common with
the type of large, long-range aircraft that make many international flights from the United States, however. Similar
practices occur in the marine shipping industry where fuel costs represent a significant portion of overall operating
costs and fuel prices vary from port to port, leading to some tankering from ports with low fuel costs.
Particularly for aviation, the DOT (1991 through 2007) international flight segment fuel data used for U.S. flagged
carriers does not include smaller air carriers and unfortunately defines flights departing to Canada and some flights
to Mexico as domestic instead of international. As for the BEA (1991 through 2007) data on foreign flagged
carriers, there is some uncertainty as to the average fuel price, and to the completeness of the data. It was also not
possible to determine what portion of fuel purchased by foreign carriers at U.S. airports was actually used on
domestic flight segments; this error, however, is believed to be small.47
Uncertainties exist with regard to the total fuel used by military aircraft and ships, and in the activity data on
military operations and training that were used to estimate percentages of total fuel use reported as bunker fuel
emissions. Total aircraft and ship fuel use estimates were developed from DoD records, which document fuel sold
to the Navy and Air Force from the Defense Logistics Agency. These data may slightly over or under estimate
actual total fuel use in aircraft and ships because each Service may have procured fuel from, and/or may have sold
to, traded with, and/or given fuel to other ships, aircraft, governments, or other entities. There are uncertainties in
aircraft operations and training activity data. Estimates for the quantity of fuel actually used in Navy and Air Force
flying activities reported as bunker fuel emissions had to be estimated based on a combination of available data and
expert judgment. Estimates of marine bunker fuel emissions were based on Navy vessel steaming hour data, which
reports fuel used while underway and fuel used while not underway. This approach does not capture some voyages
that would be classified as domestic for a commercial vessel. Conversely, emissions from fuel used while not
underway preceding an international voyage are reported as domestic rather than international as would be done for
a commercial vessel. There is uncertainty associated with ground fuel estimates for 1997 through 2001. Small fuel
quantities may have been used in vehicles or equipment other than that which was assumed for each fuel type.
There are also uncertainties in fuel end-uses by fuel-type, emissions factors, fuel densities, diesel fuel sulfur content,
aircraft and vessel engine characteristics and fuel efficiencies, and the methodology used to back-calculate the data
set to 1990 using the original set from 1995. The data were adjusted for trends in fuel use based on a closely
correlating, but not matching, data set. All assumptions used to develop the estimate were based on process
knowledge, Department and military Service data, and expert judgments. The magnitude of the potential errors
related to the various uncertainties has not been calculated, but is believed to be small. The uncertainties associated
with future military bunker fuel emission estimates could be reduced through additional data collection.
Although aggregate fuel consumption data have been used to estimate emissions from aviation, the recommended
method for estimating emissions of gases other than CC>2 in the Revised 1996 IPCC Guidelines is to use data by
specific aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC also recommends that cruise altitude emissions be
estimated separately using fuel consumption data, while landing and take-off (LTO) cycle data be used to estimate
46 See uncertainty discussions under Carbon Dioxide Emissions from Fossil Fuel Combustion.
47 Although foreign flagged air carriers are prevented from providing domestic flight services in the United States, passengers
may be collected from multiple airports before an aircraft actually departs on its international flight segment. Emissions from
these earlier domestic flight segments should be classified as domestic, not international, according to the IPCC.
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
near-ground level emissions of gases other than CO2.48
There is also concern as to the reliability of the existing DOC (1991 through 2007) data on marine vessel fuel
consumption reported at U.S. customs stations due to the significant degree of inter-annual variation.
QA/QC and Verification
A source-specific QA/QC plan for international bunker fuels was developed and implemented. This effort included
a Tier 1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved
checks specifically focusing on the activity data and emission factor sources and methodology used for estimating
CO2, CH4, and N2O from international bunker fuels in the United States. Emission totals for the different sectors
and fuels were compared and trends were investigated. No corrective actions were necessary.
Recalculations Discussion
Historical activity data for aviation was revised for both U.S. and foreign carriers. In addition, distillate and
residual fuel oil consumption by cargo or passenger carrying marine vessels from 2003 through 2006 was revised
using DHS (2008). These historical data changes resulted in changes to the emission estimates for 1990 through
2005, which averaged to an annual decrease in emissions from international bunker fuels of 4.3 Tg CO2 Eq. (4.7
percent) in CO2 emissions, an annual decrease of less than 0.1 Tg CO2 Eq. (8 percent) in CH4 emissions, and annual
decrease of less than 0.1 Tg CO2 Eq. (4 percent) in N2O emissions.
3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A)
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 2006, total CO2 emissions from the burning of woody biomass in the industrial, residential, commercial, and
electricity generation sectors were approximately 204.4 Tg CO2 Eq. (204,435 Gg) (see Table 3-55 and Table 3-56).
As the largest consumer of woody biomass, the industrial sector was responsible for 67 percent of the CO2
emissions from this source. The residential sector was the second largest emitter, constituting 20 percent of the
total, while the commercial and electricity generation sectors accounted for the remainder.
Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.)
End-Use Sector
Industrial
Residential
Commercial
1990 g
135.3 1
59.8 1
6.8 1
1
s
s
1
=2000
^153.6
^43.3
2001
135.4
38.2
6.9
2002
131.1
39.2
7.1
2003
128.0
41.2
7.4
2004
138.5
42.3
7.3
2005
136.3
42.3
7.2
2006
137.9
40.2
6.7
48 U.S. aviation emission estimates for CO, NOX, 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-defined domestic CO, NOX, and NMVOC emissions by including landing and
take-off (LTO) cycles by aircraft on international flights, but underestimate because they do not include emissions from aircraft
on domestic flight segments at cruising altitudes. The estimates in Mobile Combustion are also likely to include emissions from
ocean-going vessels departing from U.S. ports on international voyages.
Energy 3-61
-------
Electricity Generation 13.3 13.0 15.5 17.3 17.0 19.1 19.6
Total 215.2 193.5 192.8 193.8 205.1 204.8 204.4
Note: Totals may not sum due to independent rounding.
Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector
Industrial
Residential
Commercial
Electricity
Generation
Total
1990 =
135,348^
59,808 =
6,779 =
13,252^
215,186^
m 1995^
m 155,075^
m 53,621^
m 7,463^
H 12,932^
m 229,091^
m 2000
M. 153,559
m 43,309
m 7,370
M. 13,851
m 218,088
2001
135,415
38,153
6,887
13,034
193,489
2002
131,079
39,184
7,080
15,487
192,830
2003
127,970
41,247
7,366
17,250
193,833
2004
138,522
42,278
7,252
17,034
205,086
2005
136,269
42,278
7,191
19,704
204,812
2006
137,929
40,215
6,685
19,606
204,435
Note: Totals may not sum due to independent rounding.
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 emissions), and have been employed in
urban areas with poor air quality. However, because ethanol is a hydrocarbon fuel, its combustion emits CO2.
In 2006, the United States consumed an estimated 459 trillion Btu of ethanol, and as a result, produced
approximately 30.3 Tg CO2 Eq. (30,291 Gg) (see Table 3-57 and) 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.
Table 3-57: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq.)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990^^=
4
0
4
I
I
\
1 2000
i 9.1
i 0.1
1 +
i 9.2
2001
9.
0.
9.
5
2
+
7
2002
11.3
0.2
+
11.5
2003
15.4
0.3
0.1
15.7
2004
19.3
0.4
0.1
19.7
2005
22.0
0.5
0.1
22.6
2006
29.6
0.6
0.1
30.3
+ Does not exceed 0.05 Tg CO2 Eq.
Table 3-58: CO2 Emissions from Ethanol Consumption (Gg)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990^
4,066^
55^
33^
4,155^
i
1 7,570^
1
1
i.
3 2000
1 9,078
= 85
= 25
1 9,188
2001
9,479
172
22
9,673
2002
11,280
209
31
11,520
2003
15,353
296
55
15,704
2004
19,267
418
55
19,740
2005
22,014
478
62
22,554
2006
29,566
641
84
30,291
Methodology
Woody biomass emissions were estimated by applying two EIA gross heat contents (Lindstrom 2006) to U.S.
consumption data (EIA 2007) (see Table 3-59), provided in energy units for the industrial, residential, commercial,
and electric generation sectors. One heat content (16.953114 MMBtu/MT wood and wood waste) was applied to
the industrial sector's consumption, while the other heat content (15.432359 MMBtu/MT wood and wood waste)
was applied to the consumption data for the other sectors. An EIA emission factor of 0.434 MT C/MT wood
(Lindstrom 2006) was then applied to the resulting quantities of woody biomass to obtain CO2 emission estimates.
It was assumed that the woody biomass contains black liquor and other wood wastes, has a moisture content of 12
percent, and is converted into CO2 with 100 percent efficiency. The emissions from ethanol consumption were
calculated by applying an EIA emission factor of 17.99 Tg C/QBtu (Lindstrom 2006) to U.S. ethanol consumption
3-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
estimates that were provided in energy units (EIA 2007) (see Table 3-60).
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990^
1,442^
580^
129^
2,216^
1
i
i
i
1
1
3 2000
1 1,636
1 420
1 71
3 134
1 2,262
2001
1,443
370
67
126
2,006
2002
1,396
380
69
150
1,995
2003
1,363
400
71
167
2,002
2004
1,476
410
70
165
2,121
2005
1,452
410
70
185
2,116
2006
1,469
390
65
190
2,114
Table 3-60: Ethanol Consumption (Trillion Btu)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990^
61.7^
0.8^
0.5^
63.0^
i
| 114.8^
1
1
i
1 2000
3 137.7
1 1.3
3 0.4
1 139.3
2001
143.7
2.6
0.3
146.7
2002
171.0
3.2
0.5
174.7
2003
232.8
4.5
0.8
238.1
2004
292.1
6.3
0.8
299.3
2005
333.8
7.2
0.9
342.0
2006
448.3
9.7
1.3
459.3
Uncertainty
It is assumed that the combustion efficiency for woody biomass is 100 percent, which is believed to be an
overestimate of the efficiency of wood combustion processes in the United States. Decreasing the combustion
efficiency would increase emission estimates. Additionally, the heat content applied to the consumption of woody
biomass in the residential, commercial, and electric power sectors is unlikely to be a completely accurate
representation of the heat content for all the different types of woody biomass consumed within these sectors.
Emission estimates from ethanol production are more certain than estimates from woody biomass consumption due
to better activity data collection methods and uniform combustion techniques.
Recalculations Discussion
Residential wood consumption values were revised in 1997, 1999, and 2000 based on updated information from
EIA's Annual Energy Review (EIA 2007). EIA (2007) also reported minor changes in wood consumption for all
sectors in 2005. This adjustment of historical data for wood biomass consumption resulted in an average annual
increase in emissions from wood biomass consumption of 1.1 Tg CO2 Eq. (0.6 percent) from 1990 through 2005.
Industrial and commercial sector ethanol consumption is now estimated in EIA (2007), which slightly decreased
estimates for ethanol consumed in the transportation sector in all years. As a result of these adjustments, average
annual emissions from ethanol consumption in the transportation sector decreased by 0.2 Tg CO2 Eq. (1.8 percent).
Energy 3-63
-------
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems |
Municipal Solid Waste Combustion |
Stationary Combustion |
Abandoned Underground Coal Mines |
Energy as a Portion
of all Emissions
5,637.9
25
50 75 100
Tg CO2 Eq.
125 150
Figure 3-1: 2006 Energy Sector Greenhouse Gas Sources
-------
Natural Gas Emissions
1,163
NEU Emissions 121
Fossil Fuel Non-Energy
Non-Energy Consumption Use U.S.
Use imports U.S. Temtones
6/ Territories °
55
Non-Energy Use
Carbon Sequestered
240
Note: Totals may not sum due to independent rounding.
The "Balancing item11 above accounts for the statistical imbalances
and unknowns in the reported data sets combined here.
Figure 3-2 2006 U.S. (Tg C02 Eq.)
-------
8% Nuclear
9% Renewable
22%
Natural Gas
22% Coal
39%
Petroleum
Figure 3-3: 2006 U.S. Energy Consumption by Energy Source
-------
120 -i
100
^
S 80
§
E.
E 60-
20 -
Total Energy
Fossil Fuels
Renewable & Nuclear
0 J
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu)
Note: Expressed as gross calorific values
8
2,500 -,
2,000 -
1,500 -
1,000 -
500 -
0 -
Relative Contribution
by Fuel Type
.. Natural Gas
Petroleum
I Coal
Figure 3-5: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: The electricity generation sector also includes emissions of less than 0.5 Tg CO 2 Eq.
from geothermal-based electricity generation
-------
Normal
(4,524 Heating Degree Days)
Figure 3-6. Annual Deviations from Normal Heating Degree Days for the United States (1950-2006)
Note: Climatological normal data are highlighted.
Statistical confidence interval for "normal" climatology period of 1961 through 1990.
Normal
(1,242 Cooling Degree Days)
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2006)
Note: Climatological normal data are highlighted.
Statistical confidence interval for "normal" climatology period of 1961 through 1990.
100
O
-------
2,000 -,
1,800 -
1,600 -
"J 1,200 -
O 1,000 -
^ 800-
I- 600 -
400 -
200 -
0 J
II From Electricity
Consumption
• From Direct Fossil
Fuel Combustion
. •;=
"! S
=i -i=
Figure 3-9: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion
O
O
O
^
$
ro
l/l
"oi
T3
O
s:
12,000 -,
10,000
8,000 -
6,000
4,000 -
2,000 -
Q
1
Passenger Cars
< ^N ^"~ ^^^^
__----- Light-Duty Trucks
------- -' '" "
3i-i
-------
120
110
100
90
80
70
60
Total
" TfTdusEriar
Index
Total excluding Computers,
Communications Equip., and
Semiconductors
110 -,
100
90
80 J
120 -,
110
100
90 -
80
70 -
Paper
_ Stqne, C|ayA_Glass
Products
Chemicals
80 J
Primary
Metals
_.-jooiOi-irMm^i-Ln<£>
QiQiCTiCTiCTiCTiCTiCTiCTiOOOOOOO
QiQiCTiCTiCTiCTiCTiCTiCTiCTiOOOOOOO
Figure 3-12: Industrial Production Indexes (Index 2002=100)
-------
I
Industrial
1,600 -,
1,400 -
1,200 -
1,000 -
2 800 -
600
400 -
•^-^DCOOtN-xJ-^DCOOtN-xJ-^DCOOtN-xJ-^D
I—.1—I—CO CO CO CO CO CTi CTi CTi CTi CTi o O O O
CT1CT1CT1CT1CT1CT1CT1CT1CT1CT1CT1CT1CT1OOOO
Figure 3-13: Electric Generation Retail Sales by End-Use Sector
Note: The transportation end-use sector consumes minor quanties of electricity.
Commercial
-------
105 -|
100
& 95 -
O
o 90 '
£ 85 -
X
-------
4. Industrial Processes
Greenhouse gas emissions are produced as the by-products of various non-energy-related industrial activities. That
is, these emissions are produced from an industrial process itself and are not directly a result of energy consumed
during the process. For example, raw materials can be chemically transformed from one state to another. This
transformation can result in the release of greenhouse gases such as carbon dioxide (CO2), methane (CH4), or
nitrous oxide (N2O). The processes addressed in this chapter include iron and steel production, cement
manufacture, lime manufacture, ammonia manufacture and urea consumption, limestone and dolomite use (e.g., flux
stone, flue gas desulfurization, and glass manufacturing), soda ash manufacture 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).
Figure 4-1: 2006 Industrial Processes Chapter Greenhouse Gas Sources
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 2006, industrial processes generated emissions of 320.9 teragrams of CO2 equivalent (Tg CO2 Eq.), or 5 percent
of total U.S. greenhouse gas emissions. CO2 emissions from all industrial processes were 149.5 Tg CO2 Eq.
(149,465 Gg) in 2006, or 2 percent of total U.S. CO2 emissions. CH4 emissions from industrial processes resulted
in emissions of approximately 2.0 Tg CO2 Eq. (94 Gg) in 2006, which was less than 1 percent of U.S. CH4
emissions. N2O emissions from adipic acid and nitric acid production were 21.6 Tg CO2 Eq. (70 Gg) in 2006, or 4
percent of total U.S. N2O emissions. In 2006, combined emissions of HFCs, PFCs and SF6 totaled 147.9 Tg CO2
Eq. Overall, emissions from industrial processes increased by 7.0 percent from 1990 to 2006 despite decreases in
emissions from several industrial processes, such as iron and steel, 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.
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.
Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.)
Gas/Source
C02
Iron and Steel Production
Cement Manufacture
1990=
175.0 =
86.2=
33.3^
1 1995^
1 171.6^
1 74.7^
1
m 2000 2001 2002 2003 2004 2005 2006
m 166.5 151.9 151.0 147.8 151.8 145.9 149.5
m 66.6 59.2 55.9 54.7 52.8 46.6 49.1
js 41.2 41.4 42.9 43.1 45.6 45.9 45.7
Industrial Processes 4-1
-------
Lime Manufacture
Ammonia Manufacture & Urea
Consumption
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
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
Ferroalloy Production
Silicon Carbide Production and
Consumption
N2O
Nitric Acid Production
Adipic Acid Production
HFCs
Substitution of Ozone Depleting
Substances
HCFC-22 Production
Semiconductor Manufacturing HFCs
PFCs
Semiconductor Manufacturing PFCs
Aluminum Production
SF6
Electrical Transmission and
Distribution
Magnesium Production and Processing
Semiconductor Manufacturing SF6
Total
+ Does not exceed 0.05 Tg CO2 Eq.
12
16
5
4
6
2
1
1
2
1
0
0
0
2
0
1
32
17
15
36
0
36
0
20
2
18
32
26
5
0
299
.5^^=
.1^^=
.2^=
.2^=
.2^=;
.5^=:
.9^^=
.3^^=
,4^^=
.9^=
. 3 =EEE:
+==
.0^^=
.3^=
.3^=
.4^=
.2^^
.5^^=
.7^=;
.7^=;
.4^=;
.5^=
14.0^^
17.8^^
7.4^^=;
5.7^^
2.0^^=
1.5^^=
0.3^^=;
1.1^^
t .jzEEEEE:
+^^=
18.9^^
11.8^^
14.9
16.4
6.0
4.2
6.1
3.0
.8
.4
.9
.4
.1
0.3
0.2
2.5
1.2
1.2
+
+
24.8
18.6
6.2
100.1
71.2
28.6
0.3
13.5
4.9
8.6
19.1
15.1
3.0
1.1
14.3
13.3
5.7
4.1
4.4
2.8
1.7
0.8
1.5
1.3
1.0
0.3
0.2
2.2
1.1
1.1
+
+
20.2
15.1
5.1
97.9
78.0
19.7
0.2
7.0
3.5
3.5
18.7
15.0
2.9
0.7
326.5 297.9
13
14
5
4
4
2
1
1
1
1
0
0
0
2.
1
1
22.
16
6
106.
85
21
0
8.
3
5
18.
14
2
0
308.
7
2
9
1
5
9
8
0
3
3
9
3
2
1
1
0
+
+
4
4
1
3
0
1
2
7
5
2
0
4
9
7
6
14.5
12.5
4.8
4.1
4.5
2.8
1.8
1.3
1.3
1.4
0.5
0.3
0.2
2.1
1.1
1.0
+
+
21.7
15.4
6.3
104.4
92.0
12.3
0.2
7.1
3.3
3.8
18.1
13.8
3.4
0.8
301.2
15.2
13.2
6.7
4.2
4.2
2.9
2.1
1.2
1.4
1.4
0.5
0.3
0.2
2.2
1.2
1.0
+
+
21.2
15.2
5.9
116.6
99.1
17.2
0.2
6.1
3.3
2.8
18.0
13.9
3.2
0.8
315.9
15
12
7
4
4
2
1
1
1
1
0
0
0
2
1
1
21
15
5
121
105
15
0
6
3
3
18
14
3
1
315
.1 15.8
.8 12.4
.4 8.6
.2 4.2
.2 3.9
.8 2.6
.8 1.9
.3 1.6
.4 1.5
.4 1.2
.5 0.5
.3 0.3
.2 0.2
.0 2.0
.1 1.0
.0 0.9
+ +
+ +
.7 21.6
.8 15.6
.9 5.9
.4 124.5
.4 110.4
.8 13.8
.2 0.3
.2 6.1
.2 3.6
.0 2.5
.2 17.3
.0 13.2
.3 3.2
.0 1.0
.5 320.9
Note: Totals may not sum due to independent rounding.
a Small amounts of PFC emissions also result from this source.
Table 4-2: Emissions from Industrial Processes
Gas/Source 1990^ 1995
CO2 175,018^ 171,600
Iron and Steel 86,220^ 74,729
Production M
Cement Manufacture 33,278^ 36,847
Lime Manufacture 12,004^ 14,019
Ammonia 16,889^ 17,796
Manufacture & Urea ^
Consumption ^
(Gg)
2000
166,452
66,609
41,190
14,872
16,402
2001
151,944
59,249
41,357
14,261
13,305
2002
150,960
55,938
42,898
13,652
14,194
2003
147
54
43
14
12
,752
,744
,082
,458
,488
2004
151,841
52,771
45,603
15,154
13,241
2005
145,
46,
45,
15,
12,
926
627
910
131
817
2006
149,465
49,119
45,739
15,825
12,376
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Limestone and
Dolomite Use
Soda Ash Manufacture
and Consumption
Aluminum Production
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
Ferroalloy Production
Silicon Carbide
Production and
Consumption
N2O
Nitric Acid Production
Adipic Acid
Production
HFCs
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Semiconductor
Manufacturing HFCs
PFCs
Semiconductor
Manufacturing PFCs
Aluminum Production
SF6
Electrical
Transmission and
Distribution
Magnesium
Production and
Processing
Semiconductor
Manufacturing SF6
+ Does not exceed 0.5 Gg
M (Mixture of gases)
5,533^ 7,359^
M M=
4,141^ 4,304^
M
6,831^= 5,659^=;
2,221^ 2,750^
M
1,195^ 1,526^
M ^
1,416M 1,422^
M
2,152^ 2,036^
1,529^ 1,513^
:=
949M 1,013^
285^
375^
M
M
106^ 116^
41^
M M=
63^
:=
M
M
1Q4M 117^
55^ 61^
49^
M
MM
:=
Mii
^
+^
M^ M^
'M
MM
iM
:=
:=
'M
'M
M ME
+^
5,960
4,181
6,086
3,004
1,752
1,421
1,893
1,382
1,140
311
248
117
58
58
1
1
80
60
20
M
M
2
+
M
M
M
1
1
+
+
5,733
4,147
4,381
2,787
1,697
829
1,459
1,264
986
291
199
103
51
51
+
+
65
49
16
M
M
2
+
M
M
M
1
1
+
+
5,885
4,139
4,490
2,857
1,824
989
1,349
1,338
937
286
183
101
52
48
+
+
72
53
20
M
M
2
+
M
M
M
1
1
+
+
4,753
4,111
4,503
2,777
1,839
1,311
1,305
1,382
507
289
202
101
51
49
+
+
70
50
20
M
M
1
+
M
M
M
1
1
+
+
6,702
4,205
4,231
2,895
2,064
1,198
1,419
1,395
477
263
224
106
55
50
+
+
68
49
19
M
M
1
+
M
M
M
1
1
+
+
7,397
4,228
4,207
2,804
1,755
1,321
1,392
1,386
465
266
219
97
51
45
+
+
70
51
19
M
M
1
+
M
M
M
1
1
+
+
8,615
4,162
3,923
2,573
1,876
1,579
1,505
1,167
529
270
207
94
48
45
+
+
70
50
19
M
M
1
+
M
M
M
1
1
+
+
Note: Totals may not sum due to independent rounding.
a Small amounts of PFC emissions also result from this source.
Industrial Processes 4-3
-------
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 planned 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 data is obtained through a survey of manufacturers conducted by various organizations (specified within
each source); the uncertainty of the activity data is a function of the reliability of plant-level production data and is
influenced by the completeness of the survey response. The emission factors used were either derived using
calculations that assume precise and efficient chemical reactions, or were based upon empirical data in published
references. As a result, uncertainties in the emission coefficients can be attributed to, among other things,
inefficiencies in the chemical reactions associated with each production process or to the use of empirically-derived
emission factors that are biased; therefore, they may not represent U.S. national averages. Additional assumptions
are described within each source.
The uncertainty analysis performed to quantify uncertainties associated with the 2006 inventory estimates from
industrial processes continues a multi-year process for developing credible quantitative uncertainty estimates for
these source categories using the IPCC Tier 2 approach. As the process continues, the type and the characteristics
of the actual probability density functions underlying the input variables are identified and better characterized
(resulting in development of more reliable inputs for the model, including accurate characterization of correlation
between variables), based primarily on expert judgment. Accordingly, the quantitative uncertainty estimates
reported in this section should be considered illustrative and as iterations of ongoing efforts to produce accurate
uncertainty estimates. The correlation among data used for estimating emissions for different sources can influence
the uncertainty analysis of each individual source. While the uncertainty analysis recognizes very significant
connections among sources, a more comprehensive approach that accounts for all linkages will be identified as the
uncertainty analysis moves forward.
4.1. Cement Manufacture (IPCC Source Category 2A1)
Cement manufacture is an energy- and raw-material-intensive process that results in the generation of CO2 from
both the energy consumed in making the cement and the chemical process itself.l Cement is manufactured in 37
states and Puerto Rico. CO2 emitted from the chemical process of cement production is the second largest source of
industrial CO2 emissions in the United States.
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.
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
During the cement production process, 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 by-product
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 2006, U.S. clinker production—including Puerto Rico—totaled 88,453 thousand metric tons (van Oss 2007).
The resulting emissions of CO2 from 2006 cement production were estimated to be 45.7 Tg CO2 Eq. (45,739 Gg)
(see Table 4-3).
Table 4-3: CO2 Emissions from Cement Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg C02 Eq.
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
45.7
Gg
33,278
36,847
41,190
41,357
42,898
43,082
45,603
45,910
45,739
After falling in 1991 by two percent from 1990 levels, cement production emissions grew every year through 2005,
and then decreased slightly from 2005 to 2006. Overall, from 1990 to 2006, emissions increased by 37 percent.
Cement continues to be a critical component of the construction industry; therefore, the availability of public
construction funding, as well as overall economic growth, have had considerable influence on cement production.
Methodology
CO2 emissions from cement manufacture are created by the chemical reaction of carbon-containing minerals (i.e.,
calcining limestone) 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
CO2 emissions were estimated by applying an emission factor, in tons of CO2 released per ton of clinker produced,
to the total amount of clinker produced. The emission factor used in this analysis is the product of the average lime
fraction for clinker of 65 percent (van Oss 2008) 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:
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. CO2 emissions that result from the production of lime used to create
masonry cement are included in the Lime Manufacture source category (van Oss 2008).
Industrial Processes 4-5
-------
,
Clinker
= 0.65 CaO
44.01g/moleCO
56.08 g/moleCaO
= 0.51 tons CO /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 are not accounted for by the clinker emission factor. The IPCC recommends that these additional CKD CO2
emissions should be estimated as two percent of the CO2 emissions calculated from clinker production. Total
cement production emissions were calculated by adding the emissions from clinker production to the emissions
assigned to CKD (IPCC 2006).3
The 1990 through 2006 activity data for clinker production (see Table 4-4) were obtained through a personal
communication with Hendrik van Oss (van Oss 2007) of the USGS and through the USGS Mineral Yearbook:
Cement (USGS 1993 through 2006). The data were compiled by USGS through questionnaires sent to domestic
clinker and cement manufacturing plants.
Table 4-4: Clinker Production (Gg)
2000
2001
2002
2003
2004
2005
2006
79,656
79,979
82,959
83,315
88,190
88,783
88,453
Uncertainty
The uncertainties contained in these estimates are primarily due to uncertainties in the lime content of clinker and in
the percentage of CKD recycled inside the 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 2008). CKD loss can
range from 1.5 to 8 percent depending upon plant specifications. Additionally, some amount of CO2 is reabsorbed
when the cement is used for construction. As cement reacts with water, alkaline substances such as calcium
hydroxide are formed. During this curing process, these compounds may react with CO2 in the atmosphere to create
calcium carbonate. This reaction only occurs in roughly the outer 0.2 inches of surface area. Because the amount
of CO2 reabsorbed is thought to be minimal, it was not estimated.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-5. Cement Manufacture CO2
emissions were estimated to be between 39.8 and 52.0 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 13 percent below and 14 percent above the emission estimate of 45.7 Tg CO2 Eq.
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Cement Manufacture (Tg CO2 Eq.
3 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 2008).
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
and Percent)
Source
Cement Manufacture
2006 Emission
Gas Estimate
(Tg C02 Eq.)
CO2 45.7
Uncertainty Range Relative to Emission Estimate a
(Tg C02 Eq.) (%)
Lower Upper Lower
Bound Bound Bound
39.8 52.0 -13%
Upper
Bound
+14%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4.2. Lime Manufacture (IPCC Source Category 2A2)
Lime is an important manufactured product with many industrial, chemical, and environmental applications. Its
major uses are in steel making, flue gas desulfurization (FGD) systems at coal-fired electric power plants,
construction, and water purification. 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. CO2 is generated
during the calcination stage, when limestone—mostly calcium carbonate (CaCO3)—is roasted at high temperatures
in a kiln to produce CaO and CO2. The CO2 is given off as a gas and is normally emitted to the atmosphere. In
certain applications, lime reabsorbs CO2 during use.
Lime production in the United States—including Puerto Rico—was reported to be 20,929 thousand metric tons in
2006 (USGS 2007). This resulted in estimated CO2 emissions of 15.8 Tg CO2 Eq. (or 15,825 Gg) (see Table 4-6).
Table 4-6: CO2 Emissions from Lime Manufacture (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg C02 Eq.
12.0
14.0
14.9
14.3
13.7
14.5
15.2
15.1
15.8
Gg
12,004
14,019
14,872
14,261
13,652
14,458
15,154
15,131
15,825
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, 21 percent; construction uses, 13 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 2006, the amount of lime used for construction decreased slightly from
2005 levels, most likely as a result of increased prices for lime and the downturn in new home construction (USGS
2007).
Lime production in 2006 slightly increased over 2005, the fourth annual increase in production after four years of
decline. Overall, from 1990 to 2006, lime production has increased by 32 percent. Annual consumption for
industrial and chemical, and environmental lime consumption increased by 8 percent and 7 percent, respectively
(USGS 2007). The increase in environmental production for environmental uses is attributed in part to growth in
demand for flue gas desulfurization technologies, particularly at incineration plants, and wastewater treatment
Industrial Processes 4-7
-------
(USGS 2007).
Methodology
During the calcination stage of lime manufacture, 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 by-product during the production of lime (IPCC 2006).
Lime production data (high-calcium- and dolomitic-quicklime, high-calcium- and dolomitic -hydrated, and dead-
burned dolomite) for 1990 through 2006 (see Table 4-7) were obtained from USGS (1992 through 2007). Natural
hydraulic lime, which is produced from CaO and hydraulic calcium silicates, is not produced in the United States
(USGS 2006). 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 4-8 (USGS 1992 through 2007, IPCC 2000). The CaO and CaO'MgO contents of lime were obtained from
the IPCC (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.
Table 4-7: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and Dead-Burned-
Dolomite Lime Production (Gg) _
High-Calcium Dolomitic High-Calcium Dolomitic Dead-Burned
Year Quicklime _ Quicklime _ Hydrated _ Hydrated _ Dolomite
1995 13,165 2,635 2,027 363 308
2000
2001
2002
2003
2004
2005
2006
14,300
13,600
13,400
13,900
14,200
14,100
15,000
3,000
2,580
2,420
2,460
3,020
2,990
2,950
1,550
2,030
1,500
2,140
2,140
2,220
2,370
421
447
431
464
421
474
409
200
200
200
200
200
200
200
Table 4-8: Adjusted Lime Production" (Gg)
Year High-Calcium Dolomitic
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
1990
1995
2000
2001
2002
2003
2004
2005
2006
12,514
14,700
15,473
15,137
14,536
15,520
15,820
15,781
16,794
2,809
3,207
3,506
3,105
2,934
2,998
3,526
3,535
3,448
a Minus water content of hydrated lime
Uncertainty
The uncertainties contained in these estimates can be attributed to slight differences in the chemical composition of
these products. Although the methodology accounts for various formulations of lime, it does not account for the
trace impurities found in lime, such as iron oxide, alumina, and silica. Due to differences in the limestone used as a
raw material, a rigid specification of lime material is impossible. As a result, few plants manufacture lime with
exactly the same properties.
In addition, a portion of the CO2 emitted during lime manufacture will actually be reabsorbed when the lime is
consumed. As noted above, lime has many different chemical, industrial, environmental, and construction
applications. In many processes, CO2 reacts with the lime to create calcium carbonate (e.g., water softening). CO2
reabsorption rates vary, however, depending on the application. For example, 100 percent of the lime used to
produce precipitated calcium carbonate reacts with CO2; whereas most of the lime used in steel making reacts with
impurities such as silica, sulfur, and aluminum compounds. A detailed accounting of lime use in the United States
and further research into the associated processes are required to quantify the amount of CO2 that is reabsorbed.4
In some cases, lime is generated from calcium carbonate by-products at pulp mills and water treatment plants.5 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.6
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.
4 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).
5 Some carbide producers may also regenerate lime from their calcium hydroxide by-products, which does not result in
emissions of CO2. In making calcium carbide, quicklime is mixed with coke and heated in electric furnaces. The regeneration of
lime in this process is done using a waste calcium hydroxide (hydrated lime) [CaC2 + 2H2O -> C2H2 + Ca(OH) 2], not calcium
carbonate [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.
6 Based on comments submitted by and personal communication with Dr. Sergio F. Galeano, Georgia-Pacific Corporation.
Industrial Processes 4-9
-------
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-9. Lime CO2 emissions were
estimated to be between 14.6 and 17.1 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 15.8 Tg CO2 Eq.
Table 4-9: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Manufacture (Tg CO2 Eq. and
Percent)
Source
Gas
2006
Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lime Manufacture
C02
15.8
14.6 17.1 -8% +8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 emissions from lime manufacture were revised for all years in the timeseries to remove estimates
of CO2 recovery associated with lime use during sugar refining and precipitate calcium carbonate (PCC) production.
Currently, research does not indicate that CO2 used in these processes stems from CO2 captured during lime
production. Additional research is needed to determine if lime production plants in the US capture CO2 as well as
to determine the fates of precipitates formed during the sugar refining process. This change resulted in an average
annual emission increase of 9.5 percent.
4.3. Limestone and Dolomite Use (IPCC Source Category 2A3)
Limestone (CaCO3) and dolomite (CaCO3MgCO3)7 are basic raw materials used by a wide variety of industries,
including construction, agriculture, chemical, metallurgy, glass manufacture, 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 by-product. 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 2006, approximately 13,192 thousand metric tons of limestone and 5,886 thousand metric tons of dolomite were
consumed during production for these applications. Overall, usage of limestone and dolomite resulted in aggregate
CO2 emissions of 8.6 Tg CO2 Eq. (8,615 Gg) (see Table 4-10 and Table 4-11). Emissions in 2006 increased 17
percent from the previous year and have increased 56 percent overall from 1990 through 2006.
Table 4-10: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.)
Activity
Flux Stone
Glass Making
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990^
3.0^
0.2^
1.4^
0.1^
0.8^
3
1
3
1
3
3
1
1 2000
i 2.8
i 0.4
i 1.8
i 0.1
i 0.9
1 6.0
2001
2.5
0.1
2.6
0.1
0.5
5.7
2002
2.4
0.1
2.8
0.0
0.7
5.9
2003
2.1
0.3
1.9
0.0
0.4
4.8
2004
4.1
0.4
1.9
0.0
0.4
6.7
2005
3.3
0.4
3.0
0.0
0.7
7.4
2006
5.1
0.7
2.1
0.0
0.7
8.6
7 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: 1990-2006
-------
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 4-11: CO2 Emissions from Limestone & Dolomite Use (Gg)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990^
2,999^
2,554^
446^
217^
189^
28^
1,433^
64^
819^
5,533i!
i
3 4,004^
1 3,077^
i
i
i
i
i 1,663 =
= 41^
i 1,119=
i
= 2000
I 2,830
I 1,810
I 1,020
I 368
I 368
I 0
I 1,774
= 73
I 916
I 5,960
2001
2,514
1,640
874
113
113
0
2,551
53
501
5,733
2002
2,405
1,330
1,075
61
61
0
2,766
0
652
5,885
2003
2,081
913
1,168
339
339
0
1,950
0
383
4,753
2004
4,112
2,023
2,088
350
350
0
1,871
0
369
6,702
2005
3,265
1,398
1,867
427
406
21
2,985
0
721
7,397
2006
5,072
2,291
2,781
747
717
31
2,061
0
735
8,615
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.
Methodology
CO2 emissions were calculated by multiplying the quantity of limestone or dolomite consumed by the average C
content, approximately 12.0 percent for limestone and 13.2 percent for dolomite (based on stoichiometry), 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.
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 2006 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 4-12) were obtained from the USGS Minerals Yearbook: Crushed Stone Annual Report (USGS
1993, 1995a, 1996a through 2007a). The production capacity data for 1990 through 2006 of dolomitic magnesium
metal (see Table 4-13) also came from the USGS (1995b, 1996b through 2007b). 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 2006 Minerals Yearbook: Magnesium; therefore, it is assumed that this process continues to be non-
existent in the United States (USGS 2007b). During 1990 and 1992, the USGS did not conduct a detailed survey of
limestone and dolomite consumption by end-use. Consumption for 1990 was estimated by applying the 1991
percentages of total limestone and dolomite use constituted by the individual limestone and dolomite uses to 1990
total use. Similarly, the 1992 consumption figures were approximated by applying an average of the 1991 and 1993
percentages of total limestone and dolomite use constituted by the individual limestone and dolomite uses to the
1992 total.
Additionally, each year the USGS withholds data on certain limestone and dolomite end-uses due to 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.
Industrial Processes 4-11
-------
Finally, there is a large quantity of crushed stone reported to the USGS under the category "unspecified uses." A
portion of this consumption is believed to be limestone or dolomite used for emissive end uses. The quantity listed
for "unspecified uses" was, therefore, allocated to each reported end-use according to each end uses fraction of total
consumption in that year.8
Table 4-12: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Other Miscellaneous Uses
Total
1990 =
6,738^
5,804^
933 =
489 =
430^
59 =
3,258^
1,835 =
12,319 =
1
1
1 6,995 =
1 1,941 =
1 U89 =
3
3
1 3,779^
1 2,543^
1 16,445^
1 2000
3 6
3 4
=S 2
1 4
1 2
3 13
,249
,114
,135
836
836
0
,031
,081
,197
2001
5,558
3,727
1,831
258
258
0
5,798
1,138
12,751
2002
5
o
3
2
6
1
13
,275
,023
,252
139
139
0
,286
,483
,183
2003
4,521
2,075
2,446
771
771
0
4,432
870
10,594
2004
8,971
4,599
4,373
796
796
0
4,253
840
14,859
2005
7,086
3,176
3,910
966
923
43
6,785
1,638
16,475
2006
11,030
5,208
5,822
1,693
1,629
64
4,683
1,671
19,078
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 4-13: Dolomitic Magnesium Metal Production Capacity (Metric Tons)
Year Production Capacity
1990
1995
2000
2001
2002
2003
2004
2005
2006
35,000
22,222
40,000
29,167
0
0
0
0
0
Note: Production capacity for 2002, 2003, 2004, 2005, and 2006 amounts to zero because the last U.S. production plant
employing the dolomitic process shut down mid-2001 (USGS 2002b through 2007b).
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 significant inherent uncertainty associated with estimating withheld data points for specific
8 This approach was recommended by USGS.
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 4-14. Limestone and Dolomite
Use CO2 emissions were estimated to be between 8.0 and 9.2 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 8.6 Tg CO2 Eq.
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Limestone and Dolomite Use (Tg
CO2 Eq. and Percent)
Source Gas
2006 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Limestone and Dolomite Use CO2
8.6
8.0 9.2 -7% +7%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Emission estimates for 2003 were revised to reflect updated limestone production data. This change resulted in a
less than one percent increase in 2003 emissions.
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 to be included in future inventories (e.g., glass production, other process use of
carbonates) may be removed and the emission estimates included there.
4.4. Soda Ash Manufacture and Consumption (IPCC Source Category 2A4)
Soda ash (sodium carbonate, Na2CO3) is a white crystalline solid that is readily soluble in water and strongly
alkaline. Commercial soda ash is used as a raw material in a variety of industrial processes and in many familiar
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.9 During
9 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 by-product, 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
Industrial Processes 4-13
-------
the production process used in Wyoming, trona ore is treated to produce soda ash. CO2 is generated as a by-product
of this reaction, and is eventually emitted into the atmosphere. In addition, CO2 may also be released when soda ash
is consumed.
In 2006, CO2 emissions from the manufacture of soda ash from trona were approximately 1.6 Tg CO2 Eq. (1,626
Gg). Soda ash consumption in the United States generated 2.5 Tg CO2 Eq. (2,536 Gg) in 2006. Total emissions
from soda ash manufacture and consumption in 2006 were 4.2 Tg CO2 Eq. (4,162 Gg) (see Table 4-15 and Table
4-16). Emissions have fluctuated since 1990. These fluctuations were strongly related to the behavior of the export
market and the U.S. economy. Emissions in 2006 decreased by approximately 1.6 percent from the previous year,
and have increased overall by approximately 0.5 percent since 1990.
Table 4-15: CO2 Emissions from Soda Ash Manufacture and Consumption (Tg CO2Eq.)
Year Manufacture
1990 1.4
1995 1.6
2000
2001
2002
2003
2004
2005
2006
.5
.5
.5
.5
.6
.7
.6
Consumption
2.7
2.7
2.7
2.6
2.7
2.6
2.6
2.6
2.5
Total
4.1
4.3
4.2
4.1
4.1
4.1
4.2
4.2
4.2
Note: Totals may not sum due to independent rounding.
Table 4-16: CO2 Emissions from Soda Ash Manufacture and Consumption (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Manufacture
1,431
1,607
1,529
1,500
1,470
1,509
1,607
1,655
1,626
Consumption
2,710
2,698
2,652
2,648
2,668
2,602
2,598
2,573
2,536
Total
4,141
4,304
4,181
4,147
4,139
4,111
4,205
4,228
4,162
Note: Totals may not sum due to independent rounding.
The United States represents about one-fourth of total world soda ash output. The approximate distribution of soda
ash by end-use in 2006 was glass making, 50 percent; chemical production, 29 percent; soap and detergent
manufacturing, 9 percent; distributors, 4 percent; flue gas desulfurization, 2 percent; water treatment, 2 percent;
pulp and paper production, 1 percent; and miscellaneous, 3 percent (USGS 2007).
Although the United States continues to be a major supplier of world soda ash, China, which surpassed the United
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.
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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. CO2 and water are generated as by-products of the calcination process. CO2
emissions from the calcination of trona can be estimated based on the following chemical reaction:
2(Na (CO )(HCO )«2H O) -» 3Na CO + 5H O + CO
V 3V 3/v 3/ 2 / 23 2 2
[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 16.7 million metric tons of
trona mined in 2006 for soda ash production (USGS 2007) resulted in CO2 emissions of approximately 1.6 Tg CO2
Eq. (1,626 Gg).
Once manufactured, most soda ash is consumed in glass and chemical production, with minor amounts in soap and
detergents, pulp and paper, flue gas desulfurization and water treatment. As soda ash is consumed for these
purposes, additional CO2 is usually emitted. In these applications, it is assumed that one mole of C is released for
every mole of soda ash used. Thus, approximately 0.113 metric tons of C (or 0.415 metric tons of CO2) are released
for every metric ton of soda ash consumed.
The activity data for trona production and soda ash consumption (see Table 4-17) were taken from USGS (1994
through 2007). Soda ash manufacture and consumption data were collected by the USGS from voluntary surveys of
the U.S. soda ash industry.
Table 4-17: Soda Ash Manufacture and Consumption (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Manufacture*
14,700
16,500
15,700
15,400
15,100
15,500
16,500
17,000
16,700
Consumption
6,530
6,500
6,390
6,380
6,430
6,270
6,260
6,200
6,110
* Soda ash manufactured from trona ore only.
Uncertainty
Emission estimates from soda ash manufacture have relatively low associated uncertainty levels in that reliable and
accurate data sources are available for the emission factor and activity data. The primary source of uncertainty,
however, results from the fact that emissions from soda ash consumption are dependent upon the type of processing
employed by each end-use. Specific information characterizing the emissions from each end-use is limited.
Therefore, there is uncertainty surrounding the emission factors from the consumption of soda ash.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-18. Soda Ash Manufacture
and Consumption CO2 emissions were estimated to be between 3.9 and 4.5 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of approximately 7 percent below and 7 percent above the emission estimate of 4.2 Tg
Industrial Processes 4-15
-------
CO2 Eq.
Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Soda Ash Manufacture and
Consumption (Tg CO2 Eq. and Percent)
Source
2006
Emission
Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Soda Ash Manufacture and
Consumption CO2 42 3.9 4.5 -7% +7%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Planned Improvements
Future inventories are anticipated to estimate emissions from glass production and other use of carbonates. These
inventories will extract soda ash consumed for glass production and other use of carbonates from the current soda
ash consumption emission estimates and include them under those sources.
4.5. Ammonia Manufacture (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 nitrogen production plant located in Kansas is
producing ammonia from petroleum coke feedstock. In some plants the CO2 produced is captured and used to
produce urea. The brine electrolysis process for production of ammonia does not lead to process-based CO2
emissions.
There are five principal process steps in synthetic ammonia production from natural gas feedstock. The primary
reforming step converts CH4 to CO2, carbon monoxide (CO), and H2 in the presence of a catalyst. Only 30 to 40
percent of the CH4 feedstock to the primary reformer is converted to CO and CO2. The secondary reforming step
converts the remaining CH4 feedstock to CO and CO2. The CO in the process gas from the secondary reforming
step (representing approximately 15 percent of the process gas) is converted to CO2 in the presence of a catalyst,
water, and air in the shift conversion step. CO2 is removed from the process gas by the shift conversion process,
and the hydrogen gas is combined with the nitrogen (N2) gas in the process gas during the ammonia synthesis step
to produce ammonia. The CO2 is included in a waste gas stream with other process impurities and is absorbed by a
scrubber solution. In regenerating the scrubber solution, CO2 is released.
The conversion process for conventional steam reforming of CH4, including primary and secondary reforming and
the shift conversion processes, is approximately as follows:
(catalyst)
0.88 CH4 + 1.26 Air + 1.24 H2O > 0.88 CO2 + N2 + 3 H2
N2 + 3 H2 -» 2 NH3
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:
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2 NH3 + 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. CO2 emissions associated with other uses of urea
are accounted for in this chapter. Net emissions of CO2 from ammonia manufacture in 2006 were 11.8 Tg CO2 Eq.
(11,832 Gg), and are summarized in Table 4-19 and Table 4-20. Emissions of CO2 from urea consumed for non-
fertilizer purposes in 2006 totaled 0.5 Tg CO2 Eq. (543 Gg), and are summarized in Table 4-19 and Table 4-20.
The decrease in ammonia manufacture in recent years is due to several factors, including market fluctuations and
high natural gas prices. Ammonia manufacture relies on natural gas as both a feedstock and a fuel, and as such,
domestic manufacturers are competing with imports from countries with lower gas prices. If natural gas prices
remain high, it is likely that domestically manufactured ammonia will continue to decrease with increasing ammonia
imports (EEA 2004).
Table 4-19: CO2Emissions from Ammonia Manufacture and Urea Consumption (Tg CO2 Eq.)
Source
Ammonia Manufacture
Urea Consumption3
Total
1990^
16.5^
0.4^
16.9^
i
i
i
i
1 2000
= 15.9
= 0.5
1 16.4
2001
12.8
0.5
13.3
2002
13.7
0.5
14.2
2003
11.9
0.6
12.5
2004
12.7
0.5
13.2
2005
12.3
0.5
12.8
2006
11.8
0.5
12.4
Note: Totals may not sum due to independent rounding.
a Urea 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.
Table 4-20: CO2 Emissions from Ammonia Manufacture and Urea Consumption (Gg)
Source
Ammonia
Manufacture
Urea Consumption3
Total
1990^
16,528^
361^
16,889^
i
i ^
i
i
i 17,796^
1 2000 2001 2002 2003 2004 2005 2006
1 15,922 12,795 13,660 11,937 12,695 12,293 11,832
1 480 510 534 551 546 524 543
1 16,402 13,305 14,194 12,488 13,241 12,817 12,376
Note: Lotals may not sum due to independent rounding.
a Urea 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.
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 manufacture 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. 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.
Approximately 87 percent (TIG 2002) of urea consumed in the U.S. is consumed as a nitrogenous fertilizer on
Industrial Processes 4-17
-------
agricultural lands. The total amount of urea consumed is estimated based on this percent and 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 4-21. CO2 emissions associated with the remaining urea are estimated
using a factor of 0.73 tons of CO2 per ton of urea consumed. Total urea production is estimated based on the amount
of urea applied plus the sum of net urea imports and exports.
All ammonia production and subsequent urea production are assumed to be from the same process—conventional
catalytic reforming of natural gas feedstock, with the exception of ammonia production from petroleum coke
feedstock at one plant located in Kansas. The CO2 emission factor for production of ammonia from petroleum coke
is based on plant specific data, wherein all C contained in the petroleum coke feedstock that is not used for urea
production is assumed to be emitted to the atmosphere as CO2 (Bark 2004). Ammonia and urea are assumed to be
manufactured in the same manufacturing complex, as both the raw materials needed for urea production are
produced by the ammonia production process. The CO2 emission factor (3.57 metric tons CO2/metric ton NH3) is
applied to the percent of total annual domestic ammonia production from petroleum coke feedstock.
The emission factor of 1.2 metric 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
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 U.S. for use of natural gas as a feedstock. The EFMA
reference also indicates that more than 99 percent of the CH4 feedstock to the catalytic reforming process is
ultimately converted to CO2. The emission factor of 3.57 metric 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 4-21) was obtained from Coffeyville Resources (Coffeyville
2005, 2006, 2007) 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 through 2007). With the exception of 2006 urea export data, import and export data for urea
were obtained from the U.S. Census Bureau Current Industrial Reports Fertilizer Materials and Related Products
annual and quarterly reports for 1997 through 2006 (U.S. Census Bureau 1998 through 2007), The Fertilizer
Institute (TFI2002) 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 4-21). Because the U.S. Census Bureau did
not report urea export data for 2006, 2005 data were proxied.
Table 4-21: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg)
Year Ammonia Production Urea Applied as Urea Imports Urea Exports
Fertilizer
1990
1995
2000
2001
2002
2003
2004
2005
2006
15,425
15,788
14,342
11,092
12,577
10,279
10,939
10,143
9,962
3,296
3,623
4,382
4,655
4,871
5,025
4,982
4,779
4,958
1,860
2,936
3,904
4,800
3,840
4,973
4,935
5,026
5,029
774
881
663
792
970
723
704
579
579
Uncertainty
The uncertainties presented in this section are primarily due to how accurately the emission factor used represents
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
an average across all ammonia plants using natural gas feedstock, and the assumption that 87 percent of urea
consumed is as fertilizer. 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.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-22. Ammonia Manufacture
and Urea Consumption CO2 emissions were estimated to be between 11.1 and 13.8 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 10 percent below and 12 percent above the emission
estimate of 12.4 Tg CO2 Eq.
Table 4-22: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ammonia Manufacture and Urea
Consumption (Tg CO2 Eq. and Percent)
2006 Emission
Estimate Uncertainty Range Relative to Emission Estimate"
Source Gas (TgCO2Eq.) (TgCO2Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Ammonia Manufacture
and Urea Consumption CO2 12.4 11.1 13.8 -10% 12%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 emissions from ammonia manufacture and urea consumption were revised for all years to allocate
CO2 emissions associated with urea applied as fertilizer to the Land Use, Land-Use Change, and Forestry chapter.
Revised estimates reflect a new methodology that estimates urea production and consumption based on urea
consumed as fertilizer. Previous estimates of urea production are believed to have overestimated actual urea
production. On average, this change resulted in a 19 percent decrease in emissions for each year in the timeseries
1990-2005; however, because CO2 captured during ammonia manufacture to produce urea is estimated based on the
amount of urea produced, emissions from ammonia manufacturing have increased.
Planned Improvements
Plans for improvements to the ammonia-manufacture and urea-application source category include updating
emission factors to include both fuel and feedstock CO2 emissions 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.
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 by-product and is released from reactor vents into the atmosphere.
Currently, the nitric acid industry controls for emissions of NO and NO2 (i.e., NOX). As such, the industry uses a
combination of non-selective catalytic reduction (NSCR) and selective catalytic reduction (SCR) technologies. In
the process of destroying NOX, NSCR systems are also very effective at destroying N2O. However, NSCR units are
Industrial Processes 4-19
-------
generally not preferred in modern plants because of high energy costs and associated high gas temperatures.
NSCRs were widely installed in nitric plants built between 1971 and 1977. Approximately 20 percent of nitric acid
plants use NSCR (Choe et al. 1993). The remaining 80 percent use SCR or extended absorption, neither of which is
known to reduce N2O emissions.
N2O emissions from this source were estimated to be 15.6 Tg CO2 Eq. (50 Gg) in 2006 (see Table 4-23). Emissions
from nitric acid production have decreased by 7.8 percent since 1990, with the trend in the time series closely
tracking the changes in production.
Table 4-23: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
TgC02Eq.
17.0
18.9
18.6
15.1
16.4
15.4
15.2
15.8
15.6
Gg
55
61
60
49
53
50
49
51
50
Methodology
N2O emissions were calculated by multiplying nitric acid production by the amount of N2O emitted per unit of nitric
acid produced. The emission factor was determined as a weighted average of 2 kg N2O / metric ton HNO3 for plants
using non-selective catalytic reduction (NSCR) systems and 9 kg N2O/metric ton HNO3 for 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. An estimated 20 percent of HNO3 plants in
the United States are equipped with NSCR (Choe et al. 1993). Hence, the emission factor is equal to (9 x 0.80) + (2
x 0.20) = 7.6 kg N2O per metric ton HNO3.
Nitric acid production data for 1990 through 2004 was obtained from the U.S. Census Bureau, Current Industrial
Reports (2006) and for 2005 through 2006, from the U.S. Census Bureau, Current Industrial Reports (2007) (see
Table 4-24).
Table 4-24: Nitric Acid Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Gg
7,195
8,019
7~900
6,417
6,941
6,522
6,467
6,711
6,637
Uncertainty
The overall uncertainty associated with the 2006 N2O emissions estimate from nitric acid production was calculated
4-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 4-25. N2O emissions from nitric
acid production were estimated to be between 9.4 and 22.1 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 40 percent below to 41 percent above the 2006 emissions estimate of 15.6 Tg
C02Eq.
Table 4-25: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From Nitric Acid Production (Tg CO2
Eq. and Percent)
Source
Gas
2006 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission
Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Nitric Acid Production N2O 15.6 9A 22.1 -40% +41%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The nitric acid production values for 2003 and 2005 have been updated relative to the previous Inventory based on
revised production data published by the U.S. Census Bureau (2006, 2007). The updated production data for 2003
resulted in a decrease of 0.6 Tg CO2 Eq. (3.3 percent) in N2O emissions relative to the previous Inventory. The
updated production data for 2005 resulted in an increase of 1.0 Tg CO2 Eq. (6.1 percent) in N2O emissions relative
to the previous Inventory. Minor changes in production data due to directly citing U.S. Census Bureau reports in
this Inventory resulted in negligible changes in N2O emissions relative to the previous Inventory (less than one-
tenth of one percent) for all other years in the timeseries, respectively. Additionally, the N2O emission factor for
plants not equipped with NSCR systems has been updated based on IPCC Guidelines (2006), which resulted in
a slight decrease in emissions in each year of the time series relative to the previous Inventory. Overall, these
changes resulted in an average annual decrease in N2O emissions of 0.9 Tg CO2 Eq. (4.8 percent) for the period
1990 through 2005 relative to the previous inventory.
Planned Improvements
Planned improvements are focused on assessing the plant-by-plant implementation of NOX abatement technologies
to more accurately match plant production capacities to appropriate emission factors, instead of using a national
profiling of abatement implementation.
4.7. 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. 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).
Industrial Processes 4-21
-------
Adipic acid is produced through a two-stage process during which N2O is generated in the second stage. The first
stage of manufacturing usually involves the oxidation of cyclohexane to form a cyclohexanone/cyclohexanol
mixture. The second stage involves oxidizing this mixture with nitric acid to produce adipic acid. N2O is generated
as a by-product 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.10 Only one small plant, representing approximately two percent of production, does not control
for N2O(Reimer 1999).
N2O emissions from adipic acid production were estimated to be 5.9 Tg CO2 Eq. (19 Gg) in 2006 (see Table 4-26).
National adipic acid production has increased by approximately 36 percent over the period of 1990 through 2006, to
approximately one million metric tons. At the same time, emissions have been reduced by 61 percent due to the
widespread installation of pollution control measures in the late 1990s.
Table 4-26: N2O Emissions from Adipic Acid Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg CO2 Eq.
15.3
17.3
6.2
5.1
6.1
6.3
5.9
5.9
5.9
Gg
49
56
20
16
20
20
19
19
19
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 2006 were unavailable and, thus, were calculated by applying 4.4, 4.2, 0.0, and 0.0
percent national production growth rates, respectively. 2003 national production 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. Subsequently, the growth rates
for 2004, 2005, and 2006 were based on the change between the estimated 2003 production data and the reported
2004 production data, the change between 2004 reported production data and the estimated 2005 production data,
and between the estimated 2005 production data and the reported 2006 production data, respectively (see discussion
below on sources of production data). For the other two plants, N2O emissions were calculated by multiplying
adipic acid production by an emission factor (i.e., N2O emitted per unit of adipic acid produced) and adjusting for
the percentage of N2O released as a result of plant-specific emission controls. On the basis of experiments, the
overall reaction stoichiometry for N2O production in the preparation of adipic acid was estimated at approximately
0.3 metric tons of N2O per metric ton of product (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 "During 1997, the N2O emission controls installed by the third plant operated for approximately a quarter of the year.
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
(1 - [N2O destruction factor x abatement system utility factor])
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 as described above.
National adipic acid production data (see Table 4-27) 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 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 2006, 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).
Table 4-27: Adipic Acid Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Gg
735
830
925
835
921
961
1,002
1,002
1,002
Uncertainty
The overall uncertainty associated with the 2006 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.
Industrial Processes 4-23
-------
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-28. N2O emissions from
adipic acid production were estimated to be between 5.0 and 6.9 Tg CO2 Eq. at the 95 percent confidence level.
This indicates a range of approximately 15 percent below to 16 percent above the 2006 emission estimate of 5.9 Tg
CO2 Eq.
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from Adipic Acid Production (Tg CO2
Eq. and Percent)
2006 Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (Tg C02 Eq.) (%}
Lower Upper Lower Upper
Bound Bound Bound Bound
Adipic Acid Production N2O 5.9 5.0 6.9 -15% +16%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The adipic acid production value for 2005 was recalculated. In the 1990-2005 Inventory, 2005 production was
calculated by applying the annual production growth rate from 2003 to 2004 of 4 percent to 2004 production. In
this Inventory, 2005 production was recalculated because 2006 production data is now available (CW 2007). 2005
production was estimated through linear interpolation between 2004 and 2006 reported production data. The
updated production value for 2005 resulted in a decrease of 0.3 Tg CO2 Eq. (4.1 percent) in N2O emissions relative
to the previous inventory. Additionally, changes based on IPCC Guidelines (2006) to the N2O destruction factor
and abatement system utilization factor for one plant resulted in an increase of between 0.1 and 0.2 Tg CO2 Eq. (0.8
to 3.2 percent) in N2O emissions in each year of the historical time series, respectively.
Planned Improvements
Improvement efforts will be focused on obtaining direct measurement data from facilities. If they become available,
cross verification with top-down approaches will provide a useful Tier 2 level QC check. Also, additional
information on the actual performance of the latest catalytic and thermal abatement equipment at plants with
continuous emission monitoring may support the re-evaluation of current default abatement values.
4.8. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption
CO2 and CH4 are emitted from the production of silicon carbide (SiC), a material used as an industrial abrasive. To
make SiC, quartz (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.
CO2 is also emitted from the consumption of SiC for metallurgical and other non-abrasive applications. The USGS
reports that a portion (approximately 50 percent) of SiC is used in metallurgical and other non-abrasive applications,
primarily in iron and steel production (USGS 2005a).
CO2 from SiC production and consumption in 2006 were 0.2 Tg CO2 Eq. (207 Gg). Approximately 44 percent of
these emissions resulted from SiC production while the remainder result from SiC consumption. CH4 emissions
from SiC production in 2006 were 0.01 Tg CO2 Eq. CH4 (0.4 Gg) (see Table 4-29 and Table 4-30).
Table 4-29: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.)
Year
C02
CH4
Total
1990^^
0.4^^
1995^
iiM
2000
0.2
+
0.3
2001
0.2
+
0.2
2002
0.2
+
0.2
2003
0.2
+
0.2
2004
0.2
+
0.2
2005
0.2
+
0.2
2006
0.2
+
0.2
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 4-30: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)
Year 2000 2001 2002 2003 2004 2005 2006
CO2 248 199 183 202 224 219 207
C^.H-4 itEEEEE ± _ _ _ _ _ _
+ Does not exceed 0.5 Gg.
Methodology
Emissions of CO2 and CH4 from the production of SiC were calculated by multiplying annual SiC production by the
emission factors (2.62 metric tons CO2/metric ton SiC for CO2 and 11.6 kg CH4/metric ton SiC for CH4) provided
by the 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 2005 were obtained from the Minerals Yearbook: Manufactured Abrasives
(USGS 1991a through 2005a, 2006). Production data for 2006 were obtained from a personal communication with
the USGS Minerals Commodity Specialist (Corathers 2007). Silicon carbide consumption by major end use was
obtained from the Minerals Yearbook: Silicon (USGS 1991b through 2005b) (see Table 4-31) for years 1990
through 2004 and from the USGS Minerals Commodity Specialist for 2005 and 2006 (Corathers 2006, 2007). Net
imports for the entire time series were obtained from the U.S. Census Bureau (2005 through 2007).
Table 4-31: Production and Consumption of Silicon Carbide (Metric Tons)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Production
105,000
75,400
45,000
40,000
30,000
35,000
35,000
35,000
35,000
Consumption
172,464
227,397
225,280
162,142
180,956
191,289
229,692
220,150
199,938
Uncertainty
There is uncertainty associated with the emission factors used because they are based on stoichiometry as opposed
to monitoring of actual SiC production plants. An alternative would be to calculate emissions based on the quantity
of petroleum coke used during the production process rather than on the amount of silicon carbide produced.
However, these data were not available. For CH4, there is also uncertainty associated with the hydrogen-containing
volatile compounds in the petroleum coke (IPCC 2006). There is also some uncertainty associated with production,
net imports, and consumption data as well as the percent of total consumption that is attributed to metallurgical and
other non-abrasive uses.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-32. 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 were
estimated to be between 9 percent below and 10 percent above the emission estimate of 0.01 Tg CO2 Eq. at the 95
Industrial Processes 4-25
-------
percent confidence level.
Table 4-32: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from Silicon Carbide Production
and Consumption (Tg CO2 Eq. and Percent)
2006 Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Silicon Carbide Production
and Consumption
Silicon Carbide Production
and Consumption
CO2 0.2
CH4 +
Lower
Bound
0.2
+
Upper
Bound
0.2
+
Lower
Bound
-10%
-9%
Upper
Bound
+10%
+10%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 Tg CO2 Eq. or 0.5 Gg.
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 CH4 and CO2 emissions.
Petrochemicals are chemicals isolated or derived from petroleum or natural gas. CH4 emissions are presented here
from the production of C black, ethylene, ethylene dichloride, and methanol, while CO2 emissions are presented
here for only C black production. The CO2 emissions from petrochemical processes other than C black are
currently included in the Carbon Stored in Products from Non-Energy Uses of Fossil Fuels Section of the Energy
chapter. The CO2 from C black production is included here to allow for the direct reporting of CO2 emissions from
the process and direct accounting of the feedstocks used in the process.
C black is an intensely black powder generated by the incomplete combustion of an aromatic petroleum or coal-
based feedstock. Most C black produced in the United States is added to rubber to impart strength and abrasion
resistance, and the tire industry is by far the largest consumer. Ethylene is consumed in the production processes of
the plastics industry including polymers such as high, low, and linear low density polyethylene (HDPE, 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 2006 were 2.6 Tg CO2 Eq. (2,573 Gg) and 1.0 Tg CO2
Eq. (48 Gg), respectively (see Table 4-33 and Table 4-34), totaling 3.6 Tg CO2 Eq. Emissions of CO2 from C black
production decreased from 2.8 Tg CO2 Eq. (2,805 Gg) in 2005 to 2.6 Tg CO2 Eq. (2,573 Gg) in 2006 . There has
been an overall increase in CO2 emissions from C black production of 16 percent since 1990. CH4 emissions from
petrochemical production decreased by less than 1 percent from the previous year and increased 16 percent since
1990.
Table 4-33: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.)
Year
C02
CH4
1990^=;
1995^
2000
3.0
1.2
2001
2.8
1.1
2002
2.9
1.1
2003
2.8
1.1
2004
2.9
1.2
2005
2.8
1.1
2006
2.6
1.0
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Total 4.2 3.9 4.0 3.9 4.1 4.0 3.6
Table 4-34: CO2 and CH4 Emissions from Petrochemical Production (Gg)
Year
C02
CH4
1990^^^
1995^
2000
3,004
58
2001
2,787
51
2002
2,857
52
2003
2,777
51
2004
2,895
55
2005
2,804
51
2006
2,573
48
Methodology
Emissions of CH4 were calculated by multiplying annual estimates of chemical production by the appropriate
emission factor, as follows: 11 kg CH^/metric ton C black, 1 kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton
ethylene dichloride,11 and 2 kg CH^metric ton methanol. Although the production of other chemicals may also
result in CH4 emissions, there were not sufficient data available to estimate their emissions.
Emission factors were taken from the Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Annual
production data for 1990 (see Table 4-35) were obtained from the Chemical Manufacturer's Association Statistical
Handbook (CMA 1999). Production data for 1991 through 2006 were obtained from the American Chemistry
Council's Guide to the Business of Chemistry (ACC 2002, 2003, 2005 through 2007) and the International Carbon
Black Association (Johnson 2003, 2005 through 2007).
Table 4-35: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
Carbon Black
Ethylene
Ethylene Dichloride
Methanol
1990^
1,307^
16,542^
6,282^
3,785^
^
1 1,619^
1 21,215^
1 7,829^
1 4,992^
3 2000
1 !'769
i 24,971
i 9,866
1 4,876
2001
1,641
22,521
9,294
3,402
2002
1,682
23,623
9,288
3,289
2003
1,635
22,957
9,952
3,166
2004
1,705
25,660
12,111
2,937
2005
1,651
23,954
11,261
2,336
2006
1,515
25,000
9,737
1,123
Almost all C black in the United States is produced from petroleum-based or coal-based feedstocks using the
"furnace black" process (European IPPC Bureau 2004). The furnace black process is a partial combustion process
in which a portion of the C black feedstock is combusted to provide energy to the process. C black is also produced
in the United States by the thermal cracking of acetylene-containing feedstocks ("acetylene black process") and by
the thermal cracking of other hydrocarbons ("thermal black process"). One U. S. C black plant produces C black
using the thermal black process, and one U.S. C black plant produces C black using the acetylene black process
(The Innovation Group 2004).
The furnace black process produces C black from "C black feedstock" (also referred to as "C black oil"), which is a
heavy aromatic oil that may be derived as a byproduct of either the petroleum refining process or the metallurgical
(coal) coke production process. For the production of both petroleum-derived and coal-derived C black, the
"primary feedstock" (i.e., C black feedstock) is injected into a furnace that is heated by a "secondary feedstock"
(generally natural gas). Both the natural gas secondary feedstock and a portion of the C black feedstock are
oxidized to provide heat to the production process and pyrolyze the remaining C black feedstock to C black. The
"tail gas" from the furnace black process contains CO2, carbon monoxide, sulfur compounds, CH4, and non-CH4
volatile organic compounds. A portion of the tail gas is generally burned for energy recovery to heat 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
11 The emission factor obtained from IPCC/UNEP/OECD/IEA (1997), page 2.23 is assumed to have a misprint; the chemical
identified should be ethylene dichloride (C2H4C12) rather than dichloroethylene (C2H2C12).
Industrial Processes 4-27
-------
during the process. The C content of national C black production is subtracted from the total amount of C contained
in primary and secondary C black feedstock to find the amount of C lost during the production process. It is
assumed that the C lost in this process is emitted to the atmosphere as either CH4 or CO2. The C content of the CH4
emissions, estimated as described above, is subtracted from the total C lost in the process to calculate the amount of
C emitted as CO2. The total amount of primary and secondary C black feedstock consumed in the process (see
Table 4-36) is estimated using a primary feedstock consumption factor and a secondary feedstock consumption
factor estimated from U.S. Census Bureau (1999 and 2004) data. The average C black feedstock consumption
factor for U.S. C black production is 1.43 metric tons of C black feedstock consumed per metric ton of C black
produced. The average natural gas consumption factor for U.S. C black production is 341 normal cubic meters of
natural gas consumed per metric ton of C black produced. The amount of C contained in the primary and secondary
feedstocks is calculated by applying the respective C contents of the feedstocks to the respective levels of feedstock
consumption (EIA 2003, 2004).
Table 4-36: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons)
Activity
Primary Feedstock
Secondary Feedstock
1990^
1,864^
302^
1
1
§
1 2000
1 2,521
1 408
2001
2,339
379
2002
2,398
388
2003
2,331
377
2004
2,430
393
2005
2,353
381
2006
2,159
350
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
etal. 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 4-37. Petrochemical production
CO2 emissions were estimated to be between 1.7 and 3.6 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 35 percent below to 39 percent above the emission estimate of 2.6 Tg CO2 Eq.
Petrochemical production CH4 emissions were estimated to be between 0.9 and 1.1 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 9 percent below to 9 percent above the emission estimate
of 1.0TgCO2Eq.
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and CO2
Emissions from Carbon Black Production (Tg CO2 Eq. and Percent)
2006 Emission
Source Gas Estimate
(Tg C02 Eq.)
Petrochemical Production CO2 2.6
Petrochemical Production CH4 1.0
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower
Bound
1.7
0.9
Upper
Bound
3.6
1.1
Lower
Bound
-35%
-9%
Upper
Bound
+39%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 from carbon black have been revised for 2005 to reflect new production data. The revision
resulted in a decrease in emissions of less than one percent.
Planned Improvements
Future improvements to the petrochemicals source category include research into the use of acrylonitrile in the
United States, revisions to the C black CH4 and CO2 emission factors, and research into process and feedstock data
to obtain Tier 2 emission estimates from the production of methanol, ethylene, propylene, ethylene dichloride, and
ethylene oxide.
4.10. 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:
2 FeTiO3 + 7 C12 + 3 C HX 2 TiCl4 + 2 FeCl3 + 3 CO2
2 TiCl4 + 2 O2 -» 2 TiO2 + 4 C12
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 petroleum coke is manufactured specifically for this purpose.
Emissions of CO2 in 2006 were 1.9 Tg CO2 Eq. (1,876 Gg), an increase of 7 percent from the previous year and an
increase of 57 percent since 1990 (Table 4-38).
Table 4-3 8: CO2 Emissions from Titanium Dioxide (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
Tg CO2 Eq.
1.2
1.5
1.8
1.7
1.8
Gg
1,195
1,526
1,752
1,697
1,824
Industrial Processes 4-29
-------
2003
2004
2005
2006
1.8
2.1
1.8
1.9
1,839
2,064
1,755
1,876
Methodology
Emissions of CO2 from TiO2 production were calculated by multiplying annual TiO2 production by chloride-
process-specific emission factors.
Data were obtained for the total amount of TiO2 produced each year. For years previous to 2004, it was assumed
that TiO2 was produced using the chloride process and the sulfate process in the same ratio as the ratio of the total
U.S. production capacity for each process. As of 2004, the last remaining sulfate-process plant in the United States
had closed. As a result, all U.S. current TiO2 production results from the chloride process (USGS 2005). An
emission factor of 0.4 metric tons C/metric ton TiO2 was applied to the estimated chloride-process production. It
was assumed that all TiO2 produced using the chloride process was produced using petroleum coke, although some
TiO2 may have been produced with graphite or other C inputs. The amount of petroleum coke consumed annually
in TiO2 production was calculated based on the assumption that petroleum coke used in the process is 90 percent C
and 10 percent inert materials.
The emission factor for the TiO2 chloride process was taken from the 2006IPCC 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 4-39) were obtained from a personal
communication with Joe Gambogi, USGS Commodity Specialist, of the USGS (Gambogi 2007) and through the
Minerals Yearbook: Titanium Annual Report (USGS 1991 through 2005). Percentage chloride-process data were
not available for 1990 through 1993, and data from the 1994 USGS Minerals Yearbook were used for these years.
Because a sulfate-process plant closed in September 2001, the chloride-process percentage for 2001 was estimated
based on a discussion with Joseph Gambogi (2002). By 2002, only one sulfate plant remained online in the United
States and this plant closed in 2004 (USGS 2005). The composition data for petroleum coke were obtained from
Onder and Bagdoyan (1993).
Table 4-39: Titanium Dioxide Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Gg
979
1,250
,400
,330
,410
,420
,540
,310
,400
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.
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Also, annual TiO2 is not reported by USGS by the type of production process used (chloride or sulfate). Only the
percentage of total production capacity by process is reported. The percent of total TiO2 production capacity that
was attributed to the chloride process was multiplied by total TiO2 production to estimate the amount of TiO2
produced using the chloride process (since, as of 2004, the last remaining sulfate-process plant in the United States
closed). This assumes that the chloride-process plants and sulfate-process plants operate at the same level of
utilization. Finally, the emission factor was applied uniformly to all chloride-process production, and no data were
available to account for differences in production efficiency among chloride-process plants. In calculating the
amount of petroleum coke consumed in chloride-process TiO2 production, literature data were used for petroleum
coke composition. Certain grades of petroleum coke are manufactured specifically for use in the TiO2 chloride
process; however, this composition information was not available.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-40. Titanium dioxide
consumption CO2 emissions were estimated to be between 1.7 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 4-40: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Titanium Dioxide Production (Tg
CO2 Eq. and Percent)
2006
Emission
Source Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(TgC02Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Titanium Dioxide Production CO2 1.9
1.7 2.1 -12% +13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 emissions from titanium dioxide production were updated to reflect a revised chloride-process
emission factor provided by the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). The
change in emission factor resulted in a decrease in emissions of 8.6 percent for each year in the timeseries.
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)
CO2 is used for a variety of commercial applications, including food processing, chemical production, carbonated
beverage production, and refrigeration, and is also used in petroleum production for enhanced oil recovery (EOR).
CO2 used for EOR is injected into the underground reservoirs to increase the reservoir pressure to enable additional
petroleum to be produced.
For the most part, CO2 used in non-EOR applications will eventually be released to the atmosphere, and for the
purposes of this analysis CO2 used in commercial applications other than EOR is assumed to be emitted to the
atmosphere. CO2 used in EOR applications is discussed in the Energy Chapter under "Carbon Capture and Storage,
including Enhanced Oil Recovery" and is not discussed in this section.
CO2 is produced from naturally occurring CO2 reservoirs, as a by-product from the energy and industrial production
processes (e.g., ammonia production, fossil fuel combustion, ethanol production), and as a by-product from the
production of crude oil and natural gas, which contain naturally occurring CO2 as a component. Only CO2
Industrial Processes 4-31
-------
produced from naturally occurring CO2 reservoirs and used in industrial applications other than EOR is included in
this analysis. Neither by-product CO2 generated from energy nor industrial production processes nor CO2 separated
from crude oil and natural gas are included in this analysis for a number of reasons. CO2 captured from biogenic
sources (e.g., ethanol production plants) is not included in the inventory. CO2 captured from crude oil and gas
production is used in EOR applications and is therefore reported in the Energy Chapter. Any CO2 captured from
industrial or energy production processes (e.g., ammonia plants, fossil fuel combustion) and used in non-EOR
applications is assumed to be emitted to the atmosphere. The CO2 emissions from such capture and use are
therefore accounted for under Ammonia Production, Fossil Fuel Combustion, or other appropriate source category.
CO2 is produced as a by-product of crude oil and natural gas production. This CO2 is separated from the crude oil
and natural gas using gas processing equipment, and may be emitted directly to the atmosphere, or captured and
reinjected into underground formations, used for EOR, or sold for other commercial uses. A further discussion of
CO2 used in EOR is described in the Energy Chapter under "Box 3-3 Carbon Dioxide Transport, Injection, and
Geological Storage." The only 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 U.S. Facilities
are producing CO2 from these natural reservoirs, but they are only producing CO2 for EOR applications, not for
other commercial applications (Allis et al. 2000). CO2 production from these facilities is discussed in the Energy
Chapter.
In 2006, the amount of CO2 produced by the Mississippi and New Mexico facilities for commercial applications and
subsequently emitted to the atmosphere were 1.6 Tg CO2Eq. (1,579 Gg) (see Table 4-41). This amount represents
an increase of 17.9 percent from the previous year and an increase of 9.9 percent from emissions in 1990. This
increase was due to an in 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.
Table 4-41: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg)
Year Tg CO2 Eq.
1990 1.4
1995 1.4
2000 1.4
2001 0.8
2002
2003
2004
2005
2006
.0
o
.5
.2
.3
.6
Gg
1,416
1,422
1,421
829
989
1,311
1,198
1,321
1,579
Methodology
CO2 emission estimates for 1990 through 2006 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.
CO2 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 (ARI2006, 2007) for
1990 to 2000 and from the Annual Reports for Denbury Resources (Denbury Resources 2002 through 2007) for
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2001 to 2006 (see Table 4-42). Denbury Resources reported the average CO2 production in units of MMCF CO2
per day for 2001 through 2006 and reported the percentage of the total average annual production that was used for
EOR. CO2 production data for the Bravo Dome, New Mexico facility were obtained from the Advanced Resources
International, Inc. (ARI 2006, 2007).
Table 4-42: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for Jackson Dome and
Bravo Dome
Year Jackson Dome CO2 Jackson Dome % Used Bravo Dome CO2 Bravo Dome % Used
Production (Gg) for Non-EOR Production (Gg) for Non-EOR
1990
1995
2000
2001
2002
2003
2004
2005
2006
1,353
L.353
1,353
1,624
2,010
3,286
4,214
4,678
7,615
100%
100%
100%
47%
46%
38%
27%
27%
20%
6,301
6,862
6,834
6,627
6,420
6,213
6,006
5,799
5,613
1%
1%
1%
1%
1%
1%
1%
1%
1%
Uncertainty
Uncertainty is associated with the number of facilities that are currently producing CO2from naturally occurring
CO2 reservoirs for commercial uses other than EOR, and for which the CO2 emissions are not accounted for
elsewhere. Research indicates that there are only two such facilities, which are in New Mexico and Mississippi;
however, additional facilities may exist that have not been identified. In addition, it is possible that CO2 recovery
exists in particular production and end-use sectors that are not accounted for elsewhere. Such recovery may or may
not affect the overall estimate of CO2 emissions from that sector depending upon the end use to which the recovered
CO2 is applied. Further research is required to determine whether CO2 is being recovered from other facilities for
application to end uses that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-43. CO2 consumption CO2
emissions were estimated to be between 1.3 and 2.0 Tg CO2 Eq. at the 95 percent confidence level. This indicates a
range of approximately 21 percent below to 26 percent above the emission estimate of 1.6 Tg CO2 Eq.
Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and
Percent)
2006 Emission TT , . , „ ^ , +• + ^ • • ^ +• ^ a
„ „ „ ,. Uncertainty Range Relative to Emission Estimate
Source Gas Estimate
(Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
CO2 Consumption
CO2 1.6 1.3 2.0 -21% 26%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Data for total Bravo Dome CO2 production were updated for the entire time series based on new production data
from the facility. These changes resulted in an average annual emission increase of less than one percent for 1990
through 2005.
Industrial Processes 4-33
-------
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+c,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)
(EFMA2000). The primary chemical reactions for the production of phosphoric acid from phosphate rock are:
Ca3(PO4)2 + 4H3PO4 -> 3Ca(H2PO4)2
3Ca(H2PO4)2 + 3H2SO4 + 6H2O -> 3CaSO4 6H2O + 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:
CaCO3 + H2SO4 + H2O -> CaSO4 2H2O + CO2
Total marketable phosphate rock production in 2006 was 30.1 million metric tons. Approximately 87 percent of
domestic phosphate rock production was mined in Florida and North Carolina, while approximately 13 percent of
production was mined in Idaho and Utah. In addition, 2.4 million metric tons of crude phosphate rock was imported
for consumption in 2006. Marketable phosphate rock production, including domestic production and imports for
consumption, decreased by approximately 16 percent between 2005 and 2006. However, over the 1990 to 2006
period, production has decreased by 26 percent. Total CO2 emissions from phosphoric acid production were 1.2 Tg
CO2 Eq. (1,167 Gg) in 2006 (see Table 4-44).
Table 4-44: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. and Gg)
Year 1
1990
1995
2000
2001
2002
2003
2004
2005
2006
fg CO2 Eq.
1.5
1.5
1.4
1.3
1.3
1.4
1.4
1.4
1.2
Gg
1,529
1,513
,382
,264
,338
,382
,395
,383
,167
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Methodology
CO2 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 Mineral Yearbook: Phosphate Rock disaggregated phosphate rock mined annually in
Florida and North Carolina from phosphate rock mined annually in Idaho and Utah, and reported the annual
amounts of phosphate rock exported and imported for consumption (see Table 4-45). For the years 1990, 1991,
1992, 2005, and 2006 only nationally aggregated mining data was reported by USGS. For these years, the
breakdown of phosphate rock mined in Florida and North Carolina, and the amount mined in Idaho and Utah, are
approximated using 1993 to 2004 data. Data for domestic production of phosphate rock, exports of phosphate rock,
and imports of phosphate rock for consumption for 1990 through 2006 were obtained from USGS Minerals
Yearbook: Phosphate Rock (USGS 1994 through 2007. From 2004-2006, the USGS reported no exports of
phosphate rock from U.S. producers (USGS 2005 through 2007).
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
4-46).
Carbonate content data for phosphate rock mined in Florida are used to calculate the CO2 emissions from
consumption of phosphate rock mined in Florida and North Carolina (87 percent of domestic production) and
carbonate content data for phosphate rock mined in Morocco are used to calculate CO2 emissions from consumption
of imported phosphate rock. The CO2 emissions calculation is based on the assumption that all of the domestic
production of phosphate rock is used in uncalcined form. At last reporting, the USGS noted that one phosphate
rock producer in Idaho produces calcined phosphate rock; however, no production data were available for this
single producer (USGS 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.
Table 4-45: Phosphate Rock Domestic Production, Exports, and Imports (Gg)
Location/Year
U.S. Production3
FL&NC
ID&UT
Exports— FL & NC
Imports — Morocco
Total U.S. Consumption
]
49
42
7
6
44
1990=
,800=
,494!
,3061
,240^
451=
^U_I_ _l:zz
\ 1995|i
\ 43,720P
\ 38,100=1
\ 5,620^
; 2,76011
i 1,800=1
\ 42,760=1
2000
37,370
31,900
5,470
299
1,930
39,001
39
28
4
2
35
J001
830
,100
,730
9
,500
,321
2002
34,720
29,800
4,920
62
2,700
37,358
2003
36,410
31,300
5,110
64
2,400
38,746
2004
36,530
31,600
4,930
-
2,500
39,030
2005
36,000
31,140
4,860
-
2,630
38,630
2006
30,100
26,037
4,064
-
2,420
32,520
a USGS does not disaggregate production data regionally (FL & NC and ID & UT) for 1990 and 2006. Data for those years are
estimated based on the remaining time series distribution.
- Assumed equal to zero.
Table 4-46: Chemical Composition of Phosphate Rock (percent by weight)
Central North (
Composition Florida North Florida (calc
Total Carbon (as C) 1.60 1.76 0.76 0.60 1.56
Industrial Processes 4-35
Composition
Central
Florida
North Florida
North Carolina
(calcined)
Idaho
(calcined)
Morocco
-------
Inorganic Carbon (as C)
Organic Carbon (as C)
Inorganic Carbon (as CO2)
1.00
0.60
3.67
0.93
0.83
3.43
0.41
0.35
1.50
0.27
1.00
1.46
0.10
5.00
Source: FIPR 2003
- Assumed equal to zero.
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 2006. For previous years in the time
series, USGS provided the data disaggregated regionally; however, for 2006 only total U.S. phosphate rock
production were reported. Regional production for 2006 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 2006 regional production data represents actual production in those regions. Total
U.S. phosphate rock production data are not considered to be a significant source of uncertainty because all the
domestic phosphate rock producers report their annual production to the USGS. Data for imports for consumption
and exports of phosphate rock used in the emission calculation are based on international trade data collected by the
U.S. Census Bureau. These U.S. government economic data are not considered to be a significant source of
uncertainty.
An additional source of uncertainty in the calculation of 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
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 4-47. 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 19 percent above the emission estimate of 1.2 Tg CO2
Eq.
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Phosphoric Acid Production (Tg
CO2 Eq. and Percent)
Source
Gas
2006 Emission
Estimate
Uncertainty Range Relative to Emission Estimate3
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
(Tg C02 Eg.) (Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Phosphoric Acid Production CO2 L2 LO L4 -18% +19%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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)
In addition to being an energy intensive process, the production of iron and steel also generates process-related
emissions of CO2 and CH4. Iron is produced by first reducing iron oxide (iron ore) with metallurgical coke in a
blast furnace to produce pig iron (impure or crude iron containing about 3 to 5 percent C by weight). Metallurgical
coke is manufactured using coking coal as a raw material. Iron may be introduced into the blast furnace in the form
of raw iron ore, pellets, briquettes, or sinter. Pig iron is used as a raw material in the production of steel, which
contains about 4 percent C by weight. Pig iron is also used as a raw material in the production of iron products in
foundries. The pig iron production process produces CO2 emissions and fugitive CH4 emissions.
The production of metallurgical coke from coking coal and the consumption of the metallurgical coke used as a
reducing agent in the blast furnace are considered in the inventory to be non-energy (industrial) processes, not
energy (combustion) processes. Metallurgical coke is produced by heating coking coal in a coke oven in a low-
oxygen environment. The process drives off the volatile components of the coking coal and produces coal
(metallurgical) coke. Coke oven gas and coal tar are C containing by-products of the coke manufacturing process.
Coke oven gas is generally burned as a fuel within the steel mill. Coal tar is used as a raw material to produce
anodes used for primary aluminum production and other electrolytic processes, and also used in the production of
other coal tar products. The coke production process produces CO2 emissions and fugitive CH4 emissions.
Sintering is a thermal process by which fine iron-bearing particles, such as air emission control system dust, are
baked, which causes the material to agglomerate into roughly one-inch pellets that are then recharged into the blast
furnace for pig iron production. Iron ore particles may also be formed into larger pellets or briquettes by
mechanical means, and then agglomerated by heating prior to being charged into the blast furnace. The sintering
process produces CO2 emissions and fugitive CH4 emissions.
The metallurgical coke is a reducing agent in the blast furnace. CO2 is produced as the metallurgical coke used in
the blast furnace process is oxidized and the iron ore is reduced. Steel is produced from pig iron in a variety of
specialized steel-making furnaces. The majority of CO2 emissions from the iron and steel process come from the
use of coke in the production of pig iron, with smaller amounts evolving from the removal of C from pig iron used
to produce steel. Some C is also stored in the finished iron and steel products.
Emissions of CO2 and CH4 from iron and steel production in 2006 were 49.1 Tg CO2 Eq. (49,119 Gg) and 0.9 Tg
CO2 Eq. (45 Gg), respectively (see Table 4-48 and Table 4-49), totaling 50.1 Tg CO2 Eq. Emissions increased in
2006 after declining steadily from 1990 to 2005 due to restructuring of the industry, technological improvements,
and increased scrap utilization. Interannual fluctuations in CO2 emissions per unit of steel produced result, in part,
because iron and steel emission estimates include emissions associated with producing metallurgical coke.
Metallurgical coke emissions are included here because metallurgical coke is primarily used to produce iron and
steel; however, some amounts are also used to produce other metals (e.g., lead, zinc). In 2006, domestic production
of pig iron increased by 1.8 percent and coal coke production decreased by 1.9 percent. Overall, domestic pig iron
and coke production have declined since the 1990s. Pig iron production in 2006 was 21 percent lower than in 2000
and 23 percent below 1990 levels. Coke production in 2006 was 21 percent lower than in 2000 and 41 percent
below 1990 levels. Overall, emissions from iron and steel productions have declined by 43 percent (37.4 Tg CO2
Eq.) from 1990 to 2006.
Industrial Processes 4-37
-------
Table 4-48: CO2 and CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.)
Year
C02
CH4
Total
1990^=
87.5^^
1995^^
76.0^=
2000
66.6
1.2
67.8
2001
59.2
1.1
60.3
2002
55.9
1.0
57.0
2003
54.7
1.0
55.8
2004
52.8
1.0
53.8
2005
46.6
1.0
47.6
2006
49.1
0.9
50.1
Table 4-49: CO2 and CH4 Emissions from Iron and Steel Production (Gg)
Year
C02
CH4
1990^
86,220^
!
| 74,729^
!
! 2000
! 66,609
! 58
2001
59,249
51
2002
55,938
48
2003
54,744
49
2004
52,771
50
2005
46,627
45
2006
49,119
45
Methodology
Coking coal is used to manufacture metallurgical (coal) coke that is used primarily as a reducing agent in the
production of iron and steel, but is also used in the production of other metals including lead and zinc (see Lead
Production and Zinc Production in this chapter). Emissions associated with producing metallurgical coke from
coking coal are estimated, and then attributed to the iron and steel sector. To estimate emission from coke produced
from coking coal the amount of C contained in coke (calculated by multiplying the amount of C contained in coke
by the amount of coke produced) is deducted from the amount of C contained in the coking coal (calculated by
multiplying the C content of coking coal by the amount of coking coal consumed). The amount of coking coal
needed for these production processes is deducted from coking coal amounts provided in the Energy chapter to
avoid double counting.. Emissions associated with the consumption of coke to produce pig iron are also estimated.
The C content of the coking coal and coke consumed in these processes were estimated by multiplying the energy
consumption by material specific C-content coefficients. The C content coefficients used are presented in Annex
2.1.
Emissions from the reuse of scrap steel were also estimated by assuming that all the associated C content of the
scrap steel, which has an associated C content of approximately 0.5 percent, are released during the scrap re-use
process.
Lastly, emissions from C anodes, used during the production of steel in electric arc furnaces (EAFs), were also
estimated. Emissions of CO2 were calculated by multiplying the annual production of steel in EAFs by an emission
factor (4.4 kg CO2/ton stee!EAF)- It was assumed that the C anodes used in the production of steel in EAFs are
composed of 80 percent petroleum coke and 20 percent coal tar pitch (DOE 1997). Since coal tar pitch is a by-
product of the coke production process and its C-related emissions have already been accounted for earlier in the
iron and steel emissions calculation as part of the process, the emissions were reduced by the amount of C in the
coal tar pitch used in the anodes to avoid double counting.
Emissions associated with the production of coke from coking coal, pig iron production, the re-use of scrap steel,
and the consumption of C anodes during the production of steel were summed.
Additionally, the coal tar pitch component of C anodes consumed during the production of aluminum is accounted
for in the aluminum production section of this chapter. The emissions were reduced by the amount of coal tar pitch
used in aluminum production to avoid double counting. The amount of coal tar pitch consumed for processes other
than the aluminum production and as EAF anodes and net imports of coal tar were also estimated. A storage factor
was applied to estimate emissions associated with other coal tar pitch consumption and net imports.
C storage was accounted for by assuming that all domestically manufactured steel had a C content of 0.1 percent.
Furthermore, any pig iron that was not consumed during steel production, but fabricated into finished iron products,
was assumed to have a C content of 4 percent.
The potential CO2 emissions associated with C contained in pig iron used for purposes other than iron and steel
production, stored in the steel product, stored as coal tar, and attributed to C anode consumption during aluminum
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
production were summed and subtracted from the total emissions estimated above.
The production processes for coal coke, sinter, and pig iron result in fugitive emissions of CH4, which are emitted
via leaks in the production equipment rather than through the emission stacks or vents of the production plants. The
fugitive emissions were calculated by applying emission factors taken from the 1995 IPCC Guidelines
(IPCC/UNEP/OECD/IEA 1995) (see Table 4-50) to annual domestic production data for coal coke, sinter, and pig
iron.
Table 4-50: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg)
Material Produced g CH^kg produced
Coal Coke 0.5
Pig Iron 0.9
Sinter 0.5
Source: IPCC/UNEP/OECD/IEA 1997.
Data relating to the amount of coal consumed at coke plants, and for the production of coke for domestic
consumption in blast furnaces, were taken from the Energy Information Administration (EIA), Quarterly Coal
Report October through December (EIA 1998 through 2004a) and January through March (EIA 2006a, 2007). Data
on total coke consumed for pig iron production were taken from the American Iron and Steel Institute (AISI),
Annual Statistical Report (AISI 2001 through 2007). Scrap steel consumption data for 1990 through 2005 were
obtained fmmAnnual Statistical Report (AISI 1995, 2001 through 2006) (see Table 4-51). Because scrap steel
consumption data were unavailable for 2006, 2005 data were used. Crude steel production, as well as pig iron use
for purposes other than steel production, was also obtained from Annual Statistical Report (AISI 1996, 2001
through 2007). C content percentages for pig iron and the CO2 emission factor for C anode emissions from steel
production were obtained from IPCC Good Practice Guidance (IPCC 2000). C content percentages for crude steel
were taken from USGS (2005a). Data on the non-energy use of coking coal were obtained from EIA's Emissions of
U.S. Greenhouse Gases in the United States (EIA 2004b, 2006b). Information on coal tar net imports was
determined using data from the U.S. Bureau of the Census's U.S. International Trade Commission's Trade Dataweb
(U.S. Bureau of the Census 2007). Coal tar consumption for aluminum production data was estimated based on
information gathered by EPA's Voluntary Aluminum Industrial Partnership (VAIP) program and data from USAA
Primary Aluminum Statistics (USAA 2004, 2005, 2006) (see Aluminum Production in this chapter). Annual
consumption of iron ore used in sinter production for 1990 through 2005 was obtained from the USGS Iron Ore
Yearbook (USGS 1994 through 2005b). Iron ore consumption for 2006 was obtained from the USGS Minerals
Commodity Specialist (Jorgenson 2007). The CO2 emission factor for C anode emissions from aluminum
production was taken from the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Estimates for the
composition of C anodes used during EAF steel and aluminum production were obtained from Energy and
Environmental Profile of the U.S. Aluminum Industry (DOE 1997).
Table 4-51: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons)
Gas/Activity Data 2000 2001 2002 2003 2004 2005 2006
Coal Consumption at Coke
Plants 26,254 23,655 21,461 21,998 21,473 21,259 20,827
Coke Consumption for Pig
Iron 25,043^ 19,307 17,236 15,959 15,482 15,068 13,848 14,729
Basic Oxygen Furnace Steel
Production 56,216^ 56,721^ 53,965 47,359 45,463 45,874 47,714 42,705 42,119
Electric Arc Furnace Steel
Production 33,510^ 38,472^ 47,860 42,774 46,125 47,804 51,969 52,194 56,071
Coke Production 18,877 17,191 15,221 15,579 15,340 15,167 14,882
Iron Ore Consumption for
Sinter 10,784 9,234 9,018 8,984 8,047 8,313 7,085
Industrial Processes 4-39
-------
Domestic Pig Iron
Production for Steel 49,062^ 50,233^ 47,888 42,134 40,226 40,644 42,292 37,222 37,903
Uncertainty
The time series data sources for production of coal coke, sinter, pig iron, steel, and aluminum upon which the
calculations are based are assumed to be consistent for the entire time series. The estimates of CO2 emissions from
the production and utilization of coke are based on consumption data, average C contents, and the fraction of C
oxidized. Uncertainty is associated with the total U.S. coke consumption and coke consumed for pig iron
production. These data are provided by different data sources (EIA and AISI) and comparisons between the two
datasets for net imports, production, and consumption identified discrepancies; however, the data chosen are
considered the best available. These data and factors produce a relatively accurate estimate of CO2 emissions.
However, there are uncertainties associated with each of these factors. For example, C oxidation factors may vary
depending on inefficiencies in the combustion process, where varying degrees of ash or soot can remain unoxidized.
Simplifying assumptions were made concerning the composition of C anodes and the C contents of all pig iron and
crude steel. It was also assumed that all coal tar used during anode production originates as a by-product of the
domestic coking process. There is also uncertainty associated with the total amount of coal tar products produced
and with the storage factor for coal tar. Uncertainty surrounding the CO2 emission factor for C anode consumption
in aluminum production was also estimated.
For the purposes of the CH4 calculation it is assumed that none of the CH4 is captured in stacks or vents and that all
of the CH4 escapes as fugitive emissions. Additionally, the CO2 emissions calculation is not corrected by
subtracting the C content of the CH4, which means there may be a slight double counting of C as both CO2 and CH4.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-52. Iron and Steel CO2
emissions were estimated to be between 40.3 and 56.5 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 18 percent below and 15 percent above the emission estimate of 49.1 Tg CO2 Eq.
Iron and Steel CH4 emissions were estimated to be between 0.9 Tg CO2 Eq. and 1.0 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 0.9 Tg CO2 Eq.
Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from Iron and Steel Production
(Tg. CO2 Eq. and Percent)
Source
Iron and Steel Production
Iron and Steel Production
Gas
C02
CH4
2006
Emission
Estimate
(Tg C02 Eq.)
49.1
0.9
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower
Bound Bound Bound
40.3 56.5 -18%
0.9 1.0 -8%
Upper
Bound
+15%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 from iron and steel production have been revised for the entire time series to reflect a revised
carbon content for crude steel. This revision resulted in an average annual increase in emissions of 2 percent
throughout the timeseries.
Planned Improvements
Plans for improvements to the Iron and Steel source category are to include methodologies outlined in the 2006
IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). These methodologies involve the
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
inclusion of energy- and flux-related emissions in the iron and steel emission estimates as well as emissions
associated with metallurgical coke production, sinter production, pellet production, and direct reduced iron ore
production in addition to iron and steel production.
4.14. Ferroalloy Production (IPCC Source Category 2C2)
CO2 and CH4 are emitted from the production of several ferroalloys. Ferroalloys are composites of iron and other
elements such as silicon, manganese, and chromium. When incorporated in alloy steels, ferroalloys are used to alter
the material properties of the steel. Estimates from two types of ferrosilicon (25 to 55 percent and 56 to 95 percent
silicon), silicon metal (about 98 percent silicon), and miscellaneous alloys (36 to 65 percent silicon) have been
calculated. Emissions from the production of ferrochromium and ferromanganese are not included here because of
the small number of manufacturers of these materials in the United States. Subsequently, government information
disclosure rules prevent the publication of production data for these production facilities.
Similar to emissions from the production of iron and steel, CO2 is emitted when metallurgical coke is oxidized
during a high-temperature reaction with iron and the selected alloying element. Due to the strong reducing
environment, CO is initially produced, and eventually oxidized to CO2. A representative reaction equation for the
production of 50 percent ferrosilicon is given below:
Fe2O3 +2SiO2 + 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 CH4 and other volatiles. The amount of CH4 that is released is dependent on furnace efficiency,
operation technique, and control technology.
Emissions of CO2 from ferroalloy production in 2006 were 1.5 Tg CO2 Eq. (1,505 Gg) (see Table 4-53 and Table
4-54), which is an eight percent increase from the previous year and a 30 percent reduction since 1990. Emissions
of CH4 from ferroalloy production in 2006 were 0.01 Tg CO2 Eq. (0.4 Gg), which is an 11 percent increase from the
previous year and a 37 percent decrease since 1990.
Table 4-53: CO2 and CH^Emissions frorriJFerroalloy Production (Tg CO2 Eq.)
Year
C02
CH4
Total
1990^=
I
I
I
I
1 2000
1 L9
i +
i 1.9
2001
1.5
+
1.5
2002
1.3
+
1.4
2003
1.3
+
1.3
2004
1.4
+
1.4
2005
1.4
+
1.4
2006
1.5
+
1.5
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-54: CO2 and CH4 Emissions from Ferroalloy Production (Gg)
Year
C02
CH4
1990^=
0.7^=
1
|
1
1 2000
i 1,893
= 0.5
2001
1,459
0.4
2002
1,349
0.4
2003
1,305
0.4
2004
1,419
0.4
2005
1,392
0.4
2006
1,505
0.4
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 CH^metric ton of alloy produced). Additionally, for ferrosilicon alloys containing 56 to 95 percent
silicon, an emission factor for 75 percent silicon ferrosilicon was applied for both CO2 and CH4 (4 metric tons
Industrial Processes 4-41
-------
CO2/metric ton alloy produced and 1 kg CHVmetric 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
biomass, or graphite C inputs. The amount of petroleum coke consumed in ferroalloy production was calculated
assuming that the petroleum coke used is 90 percent C and 10 percent inert material.
Ferroalloy production data for 1990 through 2006 (see Table 4-55) were obtained from the USGS through personal
communications with the USGS Silicon Commodity Specialist (Corathers 2007) and through the Minerals
Yearbook: Silicon Annual Report (USGS 1991 through 2006). Because USGS does not provide estimates of silicon
metal production for 2006, 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 4-55). The
composition data for petroleum coke was obtained from Onder and Bagdoyan (1993).
Table 4-55: Production of Ferroalloys (Metric Tons)
Ferrosilicon Ferrosilicon Misc. Alloys
Year 25%-55% 56%-95% Silicon Metal 32-65%
_J990 321,385 109,566 145,744 ZMfA^^.
1995 184,000 128,000 163,000 99,500
2000
2001
2002
2003
2004
2005
2006
229,000
167,000
156,000
115,000
120,000
123,000
164,000
100,000
89,000
98,600
80,500
92,300
86,100
88,700
184,000
137,000
113,000
139,000
150,000
148,000
148,000
NA
NA
NA
NA
NA
NA
NA
NA (Not Available)
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.12 Even though emissions from
ferroalloys produced with coking coal or graphite inputs would be counted in national trends, they may be generated
with varying amounts of CO2 per unit of ferroalloy produced. The most accurate method for these estimates would
be to base calculations on the amount of reducing agent used in the process, rather than the amount of ferroalloys
produced. These data, however, were not available.
Emissions of CH4 from ferroalloy production will vary depending on furnace specifics, such as type, operation
technique, and control technology. Higher heating temperatures and techniques such as sprinkle charging will
reduce CH4 emissions; however, specific furnace information was not available or included in the CH4 emission
estimates.
Also, annual ferroalloy production is now reported by the USGS in three broad categories: ferroalloys containing 25
to 55 percent silicon (including miscellaneous alloys), ferroalloys containing 56 to 95 percent silicon, and silicon
metal. It was assumed that the IPCC emission factors apply to all of the ferroalloy production processes, including
12 Emissions and sinks of biogenic carbon are accounted for in the Land Use, Land-Use Change, and Forestry chapter.
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 4-56. Ferroalloy production CO2
emissions were estimated to be between 1.3 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 1.5 Tg CO2 Eq. Ferroalloy
production CH4 emissions were estimated to be between a range of approximately 12 percent below and 12 percent
above the emission estimate of 0.01 Tg CO2 Eq.
Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ferroalloy Production (Tg CO2 Eq.
and Percent)
Source
Ferroalloy Production
Ferroalloy Production
Gas
C02
CH4
2006 Emission
Estimate
(Tg C02 Eq.)
1.5
Uncertainty
(TgCO
Lower
Bound
1.3
Range Relative
2Eq.)
Upper
Bound
1.7
to Emission
Lower
Bound
-12%
-12%
Estimate"
Upper
Bound
+12%
+12%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 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 eight percent of the world total (USGS 2006). The
United States was also a major importer of primary aluminum. The production of primary aluminum—in addition
to consuming large quantities of electricity—results in process-related emissions of CO2 and two perfluorocarbons
(PFCs): perfluoromethane (CF4) and perfluoroethane (C2F6).
CO2 is emitted during the aluminum smelting process when alumina (aluminum oxide, A12O3) is reduced to
aluminum using the Hall-Heroult reduction process. The reduction of the alumina occurs through electrolysis in a
molten bath of natural or synthetic cryolite (Na3AlF6). The reduction cells contain a C lining that serves as the
cathode. C is also contained in the anode, which can be a C mass of paste, coke briquettes, or prebaked C blocks
from petroleum coke. During reduction, most of this C is oxidized and released to the atmosphere as CO2.
Process emissions of CO2 from aluminum production were estimated to be 3.9 Tg CO2 Eq. (3,923 Gg) in 2006 (see
Table 4-57). The C anodes consumed during aluminum production consist of petroleum coke and, to a minor
extent, coal tar pitch. The petroleum coke portion of the total CO2 process emissions from aluminum production is
considered to be a non-energy use of petroleum coke, and is accounted for here and not under the CO2 from Fossil
Fuel Combustion source category of the Energy sector. Similarly, the coal tar pitch portion of these CO2 process
emissions is accounted for here rather than in the Iron and Steel source category of the Industrial Processes sector.
Table 4-57: CO2 Emissions from Aluminum Production (Tg CO2 Eq. and Gg)
Year TgCO2Eq. Gg
Industrial Processes 4-43
-------
1990
1995
2000
2001
2002
2003
2004
2005
2006
6.8
5/7
6.1
4.4
4.5
4.5
4.2
4.2
3.9
6,831
5,659
6,086
4,381
4,490
4,503
4,231
4,207
3,923
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 level of production depends on the
frequency and duration of these anode effects. As the frequency and duration of the anode effects increase,
emissions increase.
Since 1990, emissions of CF4 and C2F6 have both declined by 87 percent to 2.1 Tg CO2 Eq. of CF4 (0.4 Gg) and 0.4
Tg CO2 Eq. of C2F6 (0.04 Gg) in 2006, as shown in Table 4-77 and Table 4-78. This decline is due both to
reductions in domestic aluminum production and to actions taken by aluminum smelting companies to reduce the
frequency and duration of anode effects. Since 1990, aluminum production has declined by 44 percent, while the
average CF4 and C2F6 emission rates (per metric ton of aluminum produced) have each been reduced by 76 percent.
Table 4-58: PFC Emissions from Aluminum Production (Tg CO2 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
CF4
15.9
10.2
7.8
3.0
4.6
3.3
2.4
2.5
2.1
C2F6
2.7
1.7
0.8
0.4
0.7
0.5
0.4
0.4
0.4
Total
18.5
11.8
8.6
3.5
5.2
3.8
2.8
3.0
2.5
Note: Totals may not sum due to independent rounding.
Table 4-59: PFC Emissions from Aluminum Production (Gg)
Year CF4 C2F6
1990 2.4 0.3
2000 1.2 0.1
2001 0.5 +
2002 0.7 0.1
2003 0.5 0.1
2004 0.4 +
2005 0.4 +
2006 0.3 +
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
+ Does not exceed 0.05 Gg
In 2006, U.S. primary aluminum production totaled approximately 2.3 million metric tons, a slight decrease from
2005 production levels. Due to high electric power costs in various regions of the country, aluminum production
has been curtailed at several U.S. smelters, which resulted in 2006 production levels that were approximately 40
percent lower than the levels in 1999, the year with the highest production since 1995.
Methodology
CO2 emissions released during aluminum production were estimated using the combined application of process-
specific emissions estimates modeling with individual partner reported data. These estimates are achieved through
information gathered by EPA's Voluntary Aluminum Industrial Partnership (VAIP) program.
Most of the CO2 emissions released during aluminum production occur during the electrolysis reaction of the C
anode, as described by the following reaction.
2A12O3 + 3C -» 4A1 + 3CO2
For prebake smelter technologies, CO2 is also emitted during the anode baking process. These emissions can
account for approximately 10 percent of total process CO2 emissions from prebake smelters. The CO2 emission
factor employed was estimated from the production of primary aluminum metal and the C consumed by the process.
Emissions vary depending on the specific technology used by each plant (e.g., prebake or Sederberg). CO2 process
emissions were estimated using the methodology recommended by IPCC (2006).
The prebake process specific formula recommended by IPCC (2006) accounts for various parameters, including net
C consumption, and the sulfur, ash, and impurity content of the baked anode. For anode baking emissions, process
formulas account for packing coke consumption, the sulfur and ash content of the packing coke, as well as the pitch
content and weight of baked anodes produced. The Sederberg process formula accounts for the weight of paste
consumed per metric ton of aluminum produced, and pitch properties, including sulfur, hydrogen, and ash content.
Through the VAIP, process data have been reported for 1990, 2000, 2003, 2004, 2005, and 2006. 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 12 out of 13 operating smelters in
2006. 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 13 in 2006, 1 out of 15 smelters in 2005, and 5 out
of 23 between 1990 and 2003), CO2 emission estimates were estimated using Tier 1 Sederberg and/or Prebake
emission factors (metric ton of CO2 per metric ton of aluminum produced) from IPCC (2006).
Aluminum production data for 12 out of 13 operating smelters were reported under the VAIP in 2006. Between
1990 and 2005, production data were provided by 21 of the 23 U.S. smelters that operated during at least part of
that period. For the non-reporting smelters, production was estimated based on the difference between reporting
smelters and national aluminum production levels (USAA 2006), with allocation to specific smelters based on
reported production capacities (USGS 2002).
PFC emissions from aluminum production were estimated using a per-unit production emission factor that is
expressed as a function of operating parameters (anode effect frequency and duration), as follows:
PFC (CF4 or C2F6) kg/metric ton Al = S x Anode Effect Minutes/Cell-Day
where,
Industrial Processes 4-45
-------
S = Slope coefficient (kg PFC/metric ton Al/(Anode Effect minutes/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 2006,
smelter-specific slope coefficients were available and were used for smelters representing between 30 and 55
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 technology-specific slope coefficients were applied (IPCC 2001, 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 2006, 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 2006, 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 and then by 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 2006 were obtained via communication with USGS (USGS, 2007).
For 1990 through 2001 (see Table 4-79) data were obtained from USGS, Mineral Industry Surveys: Aluminum
Annual Report (USGS 1995, 1998, 2000, 2001, 2002). For 2002 through 2005, national aluminum production data
were obtained from the United States Aluminum Association's Primary Aluminum Statistics (USAA 2004, 2005,
2006).
Table 4-60: Production of Primary Aluminum (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Gg
4,048
3,375
3,668
2,637
2,705
2,704
2,517
2,478
2,284
Uncertainty
The overall uncertainties associated with the 2006 CO2, CF4, and C2F6 emission estimates were calculated using a
Tier 2 approach, 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 2 percent (IPCC
2006). For additional variables, such as net C consumption, and sulfur and ash content in baked anodes, estimates
for uncertainties associated with reported and default data were obtained from IPCC (2006). A Monte Carlo
analysis was applied to estimate the overall uncertainty of the CO2 emission estimate for the U.S. aluminum industry
as a whole, and the results are provided below.
To estimate the uncertainty associated with emissions of CF4 and C2F6, the uncertainties associated with three
variables were estimated for each smelter: (1) the quantity of aluminum produced, (2) the anode effect minutes per
cell day (which may be reported directly or calculated as the product of anode effect frequency and anode effect
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
duration), and (3) the smelter- or technology-specific slope coefficient. A Monte Carlo analysis was then applied to
estimate the overall uncertainty of the emission estimate for each smelter or company and for the U.S. aluminum
industry as a whole.
The results of this quantitative uncertainty analysis are summarized in Table 4-61. Aluminum production-related
CO2 emissions were estimated to be between 3.7 and 4.1 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 5 percent below to 5 percent above the emission estimate of 3.9 Tg CO2 Eq.
Also, production-related CF4 emissions were estimated to be between 1.9 and 2.3 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 9 percent below to 9 percent above the emission estimate
of 2.1 Tg CO2 Eq. Finally, aluminum production-related C2F6 emissions were estimated to be between 0.3 and 0.4
Tg CO2 Eq. at the 95 percent confidence level. This indicates a range of approximately 17 percent below to 17
percent above the emission estimate of 0.4 Tg CO2 Eq.
Table 4-61: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from Aluminum Production (Tg
CO2 Eq. and Percent)
Source
Aluminum Production
Aluminum Production
Aluminum Production
Gas
C02
CF4
C2F6
2006
Emission
Estimate
(Tg C02 Eq.)
3.9
2.1
0.4
Uncertainty Range Relative to
(Tg C02 Eq.)
Lower Upper
Bound Bound
3.7 4.1
1.9 2.3
0.3 0.4
2006 Emission Estimate"
Lower Upper
Bound Bound
-5% +5%
-9% +9%
-17% +17%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
The 2006 emission estimate was developed using IPCC (2001) slope coefficients for 7 of the 8 operating smelters
without site-specific PFC measurements. If these slope coefficients were revised to incorporate recent IPCC (2006)
slope data, overall PFC emission estimates for 2006 would probably be on the order of 10 percent lower than
current estimates. Additionally, since these smelters are owned by one company, data have been reported on a
company-wide basis as totals or weighted averages. Consequently, uncertainties in anode effect minutes per cell
day, slope coefficients, and aluminum production have been applied to the company as a whole, and not on a
smelter-specific basis. This probably overestimates the uncertainty associated with the cumulative emissions from
these smelters, because errors that were in fact independent were treated as if they were correlated. It is therefore
likely that uncertainties calculated above for the total U.S. 2006 emission estimates for CF4 and C2F6 are also
overestimated.
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 (MacNeal et al.
1990, Gariepy and Dube 1992, Ko et al. 1993, Ten Eyck and Lukens 1996, Zurecki 1996).
Recalculations Discussion
The 2005 emission estimates were updated to reflect revised prebake smelter production data. This change has
resulted in a less than one percent increase in PFC and CO2 emissions for 2005.
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
Industrial Processes 4-47
-------
portion of the SF6 reacts with the magnesium to form a thin molecular film of mostly magnesium oxide and
magnesium fluoride. The amount of SF6 reacting in magnesium production and processing is assumed to be
negligible and thus all SF6 used is assumed to be emitted into the atmosphere. Sulfur hexafluoride has been used in
this application around the world for the last twenty years.
The magnesium industry emitted 3.2 Tg CO2 Eq. (0.1 Gg) of SF6 in 2006, representing a decrease of approximately
3 percent from 2005 emissions (see Table 4-62). The recent closure of a production facility in Canada has resulted
in supply pressures in North America for magnesium ingot that may encourage the expansion of primary
magnesium production in the United States (USGS 2007a). The automotive industry is continuing to work towards
converting components to magnesium for fuel efficiency gains. As a result of this shift, magnesium die casting
processing is forecasted to grow by 3 percent for 2007 with another 4 percent gain in 2008 (NADCA 2007).
Table 4-62: SF6 Emissions from Magnesium Production and Processing (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg C02 Eq.
5.4
5.6
3.0
2.9
2.9
3.4
3.2
3.3
3.2
GS
o.:
o.:
0.
0.
0.
0.
0.
0.
0.
y
^
>
>
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 2006 from primary production, secondary production (i.e., recycling), and die casting were generally
reported by Partnership participants. When a Partner did not report emissions, they were estimated based on the
metal processed and emission rate reported by that Partner in previous years. (The extrapolation was based on the
trend shown by Partners reporting in the current and previous years.) Emissions for one Partner that is a secondary
producer were estimated based on the average emission factor for other Partners that are secondary producers.
Emission factors for 2002 to 2006 for sand casting activities were also acquired through the Partnership. The 1999
through 2006 emissions from casting operations (other than die) were estimated by multiplying emission factors (kg
SF6 per metric ton of Mg produced or processed) by the amount of metal produced or consumed. The emission
factors for casting activities are provided below in Table 4-63. The emission factors for primary production,
secondary production and sand casting are withheld to protect company-specific production information. However,
the emission factor for primary production has not risen above the average 1995 Partner value of 1.1 kg SF6 per
metric ton.
Die casting emissions for 1999 through 2006, which accounted for 25 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 2006, 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, emissions 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
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
for the other industry sectors (i.e., permanent mold, wrought, and anode casting) were based on discussions with
industry representatives.
Table 4-63: SF6 Emission Factors (kg SF6 per metric ton of magnesium)
Permanent
Year Die Casting Mold Wrought Anodes
1999
2000
2001
2002
2003
2004
2005
2006
2.14a
0.72
0.72
0.71
0.81
0.81
0.76
0.86
2
2
2
2
2
2
2
2
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.
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 2006 were available from the USGS (USGS 2002, 2003, 2005, 2006, 2007b). 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 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 2006 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
4-63.
Uncertainty
To estimate the uncertainty of the estimated 2006 SF6 emissions from magnesium production and processing, EPA
estimated the uncertainties associated with three variables (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.
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). As is the case for other sources of SF6
emissions, total SF6 consumption data for magnesium production and processing in the United States were not
available. Sulfur hexafluoride may also be used as a cover gas for the casting of molten aluminum with high
magnesium content; however, to what extent this technique is used in the United States is unknown.
Industrial Processes 4-49
-------
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-64. SF6 emissions associated
with magnesium production and processing were estimated to be between 2.7 and 3.6 Tg CO2 Eq. at the 95 percent
confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately
14 percent below to 14 percent above the 2006 emissions estimate of 3.2 Tg CO2 Eq.
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
Processing (Tg CO2 Eq. and Percent)
Source
Magnesium
Production
2006 Emission Uncertainty Range Relative to Emission
Gas Estimate Estimate"
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower
Bound
SF6 3.2 2.7
Upper
Bound
3.6
Lower
Bound
-14%
Upper
Bound
+14%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Data from the USGS (USGS 2007b) slightly revised the amount of magnesium processed in 2005 for the wrought,
sand and permanent mold casting sectors. In addition, wrought production numbers for 1990 and 1992 were revised
to match historical USGS publications based on a data review. Revisions were also made to the approach for
extrapolating and interpolating data for non-reporting Partners in order to improve accuracy. Emission estimates for
secondary production activities by a non-reporting Partner were added for the years 2001 through 2006. The
default historical emission factor for secondary production from 1990 to 1998 was also revised to be held constant
at the 1999 Partner reported value. These changes resulted in an average annual increase in SF6 emissions of 0.03
Tg CO2 Eq. (approximately 0.5 percent) for 1990 to 1998 and 0.6 Tg CO2 Eq. (approximately 22 percent) for 2001
to 2005 relative to the previous report.
Planned Improvements
As more work assessing the degree of cover gas degradation and associated byproducts is undertaken and
published, results could potentially be used to refine the emission estimates, which currently assume (per IPCC
Good Practice Guidance, IPCC 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 during this inventory year in a limited fashion; because the amounts are
negligible these emissions are only being monitored and recorded at this time. Additionally, as more companies
join the partnership, in particular those from sectors not currently represented, such as permanent mold and anode
casting, emission factors will be refined to incorporate these additional data.
4.17. 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
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 2006, U.S. primary and secondary zinc production totaled 510,000 metric tons (USGS 2008 ). The resulting
emissions of CO2 from zinc production in 2006 were estimated to be 0.5 Tg CO2 Eq. (529 Gg) (see Table 4-65). All
2006 CO2 emissions result from secondary zinc production.
Table 4-65: CO2 Emissions from Zinc Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
TgC02Eq.
0.9
1.0
1.1
1.0
0.9
0.5
0.5
0.5
0.5
Gg
949
1,013
1,140
986
937
507
477
465
529
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 electro-thermic-process zinc plant in
Monaca, PA (USGS 2004). In 2006, emissions, which are nearly half that of 1990 (44 percent), increased by 14
percent over 2005 levels despite decreases in overall production due to an increase in production from emissive
secondary zinc production processes.
Methodology
Non-energy CO2 emissions from zinc production result from those processes that use metallurgical coke or other C-
based materials as reductants. Sjardin (2003) provides an emission factor of 0.43 metric tons CO2/ton zinc
produced for emissive zinc production processes; however, this emission factor is based on the Imperial Smelting
Furnace production process. Because the Imperial Smelting Furnace production process is not used in the United
States, emission factors specific to those emissive zinc production processes used in the United States, which consist
of the electro-thermic and Waelz Kiln processes, were needed. Due to the limited amount of information available
for these electro-thermic processes, only Waelz Kiln process-specific emission factors were developed. These
emission factors were applied to both the Waelz Kiln process and the electro-thermic zinc production processes. A
Waelz Kiln emission factor based on the amount of zinc produced was developed based on the amount of
metallurgical coke consumed for non-energy 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 0.84 metric tons C 3.67 metric tons CO2 3.66 metric tons CO2
f^f^ — x x —
Waelz Kiln metric tons zinc metric ton coke metric ton C metric ton zinc
The USGS disaggregates total U.S. primary zinc production capacity into zinc produced using the electro-thermic
process and zinc produced using the electrolytic process; however, the USGS does not report the amount of zinc
Industrial Processes 4-51
-------
produced using each process, only the total zinc production capacity of the zinc plants using each process. The total
electro-thermic zinc production capacity is divided by total primary zinc production capacity to estimate the percent
of primary zinc produced using the electro-thermic process. This percent is then multiplied by total primary zinc
production to estimate the amount of zinc produced using the electro-thermic process, and the resulting value is
multiplied by the Waelz Kiln process emission factor to obtain total CO2 emissions for primary zinc production.
According to the USGS, the only remaining plant producing primary zinc using the electro-thermic process closed
in 2003 (USGS 2004). Therefore, CO2 emissions for primary zinc production are reported only for years 1990
through 2002.
In the United States, secondary zinc is produced through either the electro-thermic or Waelz Kiln process. In 1997,
the Horsehead Corporation plant, located in Monaca, PA, produced 47,174 metric tons of secondary zinc using the
electro-thermic process (Queneau et al. 1998). This is the only plant in the United States that uses the electro-
thermic process to produce secondary zinc, which, in 1997, accounted for 13 percent of total secondary zinc
production. This percentage was applied to all years within the time series up until the Monaca plant's closure in
2003 (USGS 2004) to estimate the total amount of secondary zinc produced using the electro-thermic process. This
value is then multiplied by the Waelz Kiln process emission factor to obtain total CO2 emissions for secondary zinc
produced using the electro-thermic process.
U.S. secondary zinc is also produced by processing recycled EAF dust in a Waelz Kiln furnace. Due to the
complexities of recovering zinc from recycled EAF dust, an emission factor based on the amount of EAF dust
consumed rather than the amount of secondary zinc produced is believed to represent actual CO2 emissions from the
process more accurately (Stuart 2005). An emission factor based on the amount of EAF dust consumed was
developed based on the amount of metallurgical coke consumed per ton of EAF dust consumed, 0.4 metric tons
coke/metric ton EAF dust consumed (Viklund-White 2000), and the following equation:
0.4 metric tons coke 0.84 metric tons C 3.67 metric tons CO2 1.23 metric tons CO2
EF = x x =
EAF Dust metric tons EAF dust metric ton coke metric ton C metric ton EAF Dust
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 4-66) were obtained
through the USGS Mineral Yearbook: Zinc (USGS 1994 through 2008)
Table 4-66: Zinc Production (Metric Tons)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Primary
262,704
231,840
227,800
203,000
181,800
186,900
188,200
191,120
113,000
Secondary
341,400
353,000
440,000
375,000
366,000
381,000
358,000
349,000
397,000
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Uncertainty
The uncertainties contained in these estimates are two-fold, relating to activity data and emission factors used.
First, there are uncertainties associated with the percent of total zinc production, both primary and secondary, that is
attributed to the electro-thermic and Waelz Kiln emissive zinc production processes. For primary zinc production,
the amount of zinc produced annually using the electro-thermic process is estimated from the percent of primary-
zinc production capacity that electro-thermic production capacity constitutes for each year of the time series. This
assumes that each zinc plant is operating at the same percentage of total production capacity, which may not be the
case and this calculation could either overestimate or underestimate the percentage of the total primary zinc
production that is produced using the electro-thermic process. The amount of secondary zinc produced using the
electro-thermic process is estimated from the percent of total secondary zinc production that this process accounted
for during a single year, 2003. The amount of secondary zinc produced using the Waelz Kiln process is estimated
from the percent of total secondary zinc production this process accounted for during a single year, 1997. This
calculation could either overestimate or underestimate the percentage of the total secondary zinc production that is
produced using the electro-thermic or Waelz Kiln processes. Therefore, there is uncertainty associated with the fact
that percents of total production data estimated from production capacity, rather than actual production data, are
used for emission estimates.
Second, there are uncertainties associated with the emission factors used to estimate CO2 emissions from the
primary and secondary production processes. Because the only published emission factors are based on the
Imperial Smelting Furnace, which is not used in the United States, country-specific emission factors were developed
for the Waelz Kiln zinc production process. Data limitations prevented the development of emission factors for the
electro-thermic process. Therefore, emission factors for the Waelz Kiln process were applied to both electro-
thermic and Waelz Kiln production processes. Furthermore, the Waelz Kiln emission factors are based on materials
balances for metallurgical coke and EAF dust consumed during zinc production provided by Viklund-White (2000).
Therefore, the accuracy of these emission factors depend upon the accuracy of these materials balances.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-67. Zinc production CO2
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.
Table 4-67: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Zinc Production (Tg CO2 Eq. and
Percent)
Source
Zinc Production
Gas
C02
2006 Emission
Estimate
(TgC02Eq.)
0.5
Uncertainty Range Relative to
(TgC02Eq.)
Lower Upper
Bound Bound
0.4 0.7
Emission Estimate"
(%)
Lower Upper
Bound Bound
-21% +25%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 18 separate smelters located in 11 states (USGS 2006). Secondary lead
production has increased in the United States over the past decade while primary lead production has decreased. In
2006, secondary lead production accounted for approximately 88 percent of total lead production (Smith 2007,
USGS 1995).
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
Industrial Processes 4-53
-------
increased by 7 percent from 2005 to 2006 and has decreased by 62 percent since 1990 (Smith 2007, USGS 1995)
Approximately 92 percent of U. S. secondary lead is produced by recycling lead acid batteries in either blast
furnaces or reverberatory furnaces (USGS 2006). The remaining 8 percent of secondary lead is produced from lead
scrap. Similar to primary lead production, CO2 emissions result when a reducing agent, usually metallurgical coke,
is added to the smelter to aid in the reduction process (Sjardin 2003). U.S. secondary lead production increased by
half a percent from 2005 to 2006, and has increased by 25 percent since 1990.
At last reporting, the United States was the third largest mine producer of lead in the world, behind China and
Australia, accounting for 13 percent of world production in 2005 (USGS 2006). In 2006, U.S. primary and
secondary lead production totaled 1,313,000 metric tons (Smith 2007). The resulting emissions of CO2 from 2006
production were estimated to be 0.3 Tg CO2Eq. (270 Gg) (see Table 4-68). The majority of 2006 lead production is
from secondary processes, which account for 86 percent of total 2006 CO2 emissions.
Table 4-68: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg CO2 Eq.
0.3
0.3
6.3
0.3
0.3
0.3
0.3
0.3
0.3
Gg
285
298
311
291
286
289
263
266
270
After a gradual increase in total emissions from 1990 to 2000, total emissions have decreased by five percent since
1990, largely due to a decrease in primary production (62 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 and even increased slightly in 2006 (USGS 2006, Smith 2007).
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 2006 activity data for primary and secondary lead production (see Table 4-69) were obtained
through the USGS Mineral Yearbook: Lead (USGS 1994 through 2008).
Table 4-69: Lead Production (Metric Tons)
Year
1990
1995
2000
2001
2002
Primary
404,000
374,000
341,000
290,000
262,000
Secondary
922,000
1,020,000
1,130,000
1,090,000
1,100,000
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2003
2004
2005
2006
245,000
148,000
143,000
153,000
1,140,000
1,127,000
1,154,000
1,160,000
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 4-70. 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 16 percent above the emission estimate of 0.3 Tg CO2 Eq.
Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lead Production (Tg CO2 Eq. and
Percent)
Source
Lead Production
2006 Emission
Gas Estimate
(Tg C02 Eq.)
CO2 0.3
Uncertainty Range Relative
(Tg C02 Eq.)
Lower Upper
Bound Bound
0.2 0.3
to Emission Estimate"
Lower Upper
Bound Bound
-16% +16%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CO2 emissions from lead production were revised for the 2001, 2002, 2004, 2005, and 2006 to reflect
updated secondary production activity (USGS 2008). This change resulted in a less than 2 percent decrease in
emissions for 2001 and 2002, and a less than 2 percent increase in emissions for 2004 and 2005.
4.19. HCFC-22 Production (IPCC Source Category 2E1)
Trifluoromethane (HFC-23 or CHF3) is generated as a by-product during the manufacture of chlorodifluoromethane
(HCFC-22), which is primarily employed in refrigeration and air conditioning systems and as a chemical feedstock
for manufacturing synthetic polymers. Between 1990 and 2000, U.S. production of HCFC-22 increased
significantly as HCFC-22 replaced chlorofluorocarbons (CFCs) in many applications. Since 2000, U.S. production
has fluctuated 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. Clean Air Act.13 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, SbCl5. The reaction of the catalyst and HF produces SbCLFy, (where x + y = 5), which reacts with
chlorinated hydrocarbons to replace chlorine atoms with fluorine. The HF and chloroform are introduced by
13 As construed, interpreted, and applied in the terms and conditions of the Montreal Protocol on Substances that Deplete the
Ozone Layer. [42 U.S.C. §7671m(b), CAA §614]
Industrial Processes 4-55
-------
submerged piping into a continuous-flow reactor that contains the catalyst in a hydrocarbon mixture of chloroform
and partially fluorinated intermediates. The vapors leaving the reactor contain HCFC-21 (CHC12F), HCFC-22
(CHC1F2), HFC-23 (CHF3), HC1, chloroform, and HF. The under-fluorinated intermediates (HCFC-21) and
chloroform are then condensed and returned to the reactor, along with residual catalyst, to undergo further
fluorination. The final vapors leaving the condenser are primarily HCFC-22, HFC-23, HC1 and residual HF. The
HC1 is recovered as a useful byproduct, and the HF is removed. Once separated from HCFC-22, the HFC-23 is
generally vented to the atmosphere as an unwanted by-product, but it is sometimes captured for use in a limited
number of applications.
Emissions of HFC-23 in 2006 were estimated to be 13.8 Tg CO2 Eq. (1.2 Gg) (Table 4-67). This quantity
represents a 13 percent decline from 2005 emissions and a 62 percent decline from 1990 emissions. Both declines
are primarily due to decreases in the HFC-23 emission rate. These decreases are 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 2006, two of which used thermal oxidation to significantly lower their HFC-
23 emissions.
Table 4-71: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
TgC02Eq.
36.4
33.0
28.6
19.7
21.1
12.3
17.2
15.8
13.8
Gg
3
3
2
2
2
1
1
1
1
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. 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).
The five plants that have operated since 1994 measure(d) 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.
Production data and emission estimates were prepared in cooperation with the U.S. manufacturers of HCFC-22
(ARAP 1997, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007; RTI 1997; RTI 2008). Annual estimates of
U.S. HCFC-22 production are presented in Table 4-68.
Table 4-72: HCFC-22 Production (Gg)
Year Gg
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
1990
1995
2000
2001
2002
2003
2004
2005
2006
139
155
186
152
149
138
155
156
154
Uncertainty
The uncertainty analysis presented in this section was based on a Monte Carlo simulation as described in the 2006
IPCC Guidelines for each plant 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 results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-73. HCFC-22 production HFC
emissions were estimated to be between 12.9 and 15.2 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 13.8 Tg CO2Eq.
Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and
Percent)
Source
HCFC-22 Production
Gas
HFC-23
2006 Emission
Estimate
(Tg C02 Eq.)
13.8
Uncertainty Range Relative
(Tg C02 Eq.)
Lower Upper
Bound Bound
12.9 15.2
to Emission Estimate"
(%)
Lower Upper
Bound Bound
-7% +10%
a Range of emission reflect a 95 percent confidence interval.
Recalculations
EPA recently completed a comprehensive review of plant-level estimates of HFC-23 emissions and HCFC-22
production (RTI, 2008). This review resulted in generally small adjustments to estimates of HCFC-22 production
and HFC-23 emissions. As noted above, the HFC-23 emissions for three plants that operated in the early 1990s
were re-calculated to conform with the 2006 IPCC Guidelines using the Tier 1 emission factor of 0.04 kg HFC-
23/kg HCFC-22. This revision increased the estimated U.S. emissions by 4 to 6 percent for 1990 to 1993. The
largest adjustment was for the year 1995, for which the HFC-23 emissions estimate increased by 22 percent. This
increase reflected a correction made by one plant to its emissions estimate. This calculation was documented in the
plant's files and made the plant's 1995 emission rate more consistent with its emission rates for previous and
following years. There were also minor revisions (ranging from -4 percent to +10 percent) to the emissions
estimated for 2000, 2002, 2004 and 2005. These changes reflected revisions that plants made to their estimates after
they were submitted to the Alliance for Responsible Atmospheric Policy, which aggregates the emissions of the
plants and sends the total to EPA. Again, the revised estimates were documented in the plants' files.
4.20. Substitution of Ozone Depleting Substances (IPCC Source Category 2F)
Hydrofluorocarbons (HFCs) and perfluorocarbons (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
Industrial Processes 4-57
-------
Act Amendments of 1990.14 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 4-74 and Table 4-75.
Table 4-74: Emissions of HFCs and PFCs from OPS Substitutes (Tg CO2 Eq.)
Gas
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-236fa
CF4
Others*
Total
1990^
0.3 =
1
i
1
1
i
i
1
1
1
i
1 2000
I +
\ +
1 5.2
I 57.2
I 4.1
I 0.5
\ +
I 4.0
I 71.2
2001
+
0.1
6.0
62.0
5.4
0.6
+
3.9
78.0
2002
+
0.1
6.8
66.3
6.8
0.6
+
4.3
85.0
2003
+
0.2
7.8
70.0
8.3
0.7
+
4.9
92.0
2004
+
0.3
9.0
73.8
10.1
0.7
+
5.2
99.1
2005
+
0.4
10.3
76.3
12.2
0.8
+
5.4
105.4
2006
+
0.6
12.3
76.6
14.4
0.8
+
5.7
110.4
+ Does not exceed 0.05 Tg CO2 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 perfluoropoly ethers (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 4-75: Emissions of HFCs and PFCs from OPS Substitution (Mg)
Gas
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-236fa
CF4
Others*
1990^
+^
+^
+^
M^
I 1995p
= +m
1 +jii
I
I 19,536p
I
I
= +m
I
1 2000
1 1
1 44
1 1,873
1 44,001
1 1,089
= 85
1 1
1 M
2001
1
92
2,150
47,712
1,415
94
1
M
2002
1
166
2,442
51,016
1,781
103
1
M
2003
1
268
2,798
53,843
2,194
111
2
M
2004
1
400
3,220
56,787
2,654
118
2
M
2005
1
562
3,675
58,700
3,200
125
2
M
2006
1
913
4,395
58,923
3,782
131
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 perfluoropoly ethers (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.*5 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
14 [42 U.S.C § 7671, CAA § 601]
15 R-4Q4A contains HFC-125, HFC-143a, and HFC-134a.
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
1990 to 110.4 Tg CO2 Eq. in 2006. This increase was in large part the result of efforts to phase out CFCs and other
ODSs in the United States. In the short term, this trend is expected to continue, and will likely accelerate over the
next decade as HCFCs, which are interim substitutes in many applications, are themselves phased-out under the
provisions of the Copenhagen Amendments to the Montreal Protocol. Improvements in the technologies associated
with the use of these gases and the introduction of alternative gases and technologies, however, may help to offset
this anticipated increase in emissions.
Table 4-76 presents HFCs and PFCs emissions by end-use sector for 1990 through 2006. The end-use sectors that
contributed the most toward emissions of HFCs and PFCs as ODS substitutes in 2006 include refrigeration and air-
conditioning (94.6 Tg CO2 Eq., or approximately 86 percent), aerosols (11.6 Tg CO2 Eq., or approximately 10
percent), and foams (2.4 Tg CO2 Eq., or approximately 2 percent). Within the refrigeration and air-conditioning
end-use sector, motor vehicle air-conditioning was the highest emitting end-use (55.8 Tg CO2 Eq.), followed by
retail food and refrigerated transport. Each of the end-use sectors is described in more detail below.
Table 4-76: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) by Sector
Gas
Refrigeration/Air Conditioning
Aerosols
Foams
Solvents
Fire Protection
Total
1990^
1 1995^
1
8""" 1 z=
_^ .1^=
1
1
1
1
3 2000
1 58.6
1 10.1
3 +
3 2.1
3 +
1 71.2
2001
65.3
10.3
+
1.8
+
78.0
2002
71.6
10.6
1.0
1.6
+
85.0
2003
77.7
10.8
1.8
1.3
+
92.0
2004
84.4
11.1
2.0
1.3
+
99.1
2005
90.1
11.3
2.2
1.3
0.5
105.4
2006
94.6
11.6
2.4
1.3
0.6
110.4
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 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
Industrial Processes 4-59
-------
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 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 HFCs, such as HFC-23, HFC-236fa, and HFC-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
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
level of uncertainty associated with the aggregate emissions resulting from the top 16 end-uses, comprising over 95
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, one new end-use was included in the uncertainty estimate- fire extinguishing
streaming agents. Any end-uses included in previous years' uncertainty analysis were included in the current
uncertainty analysis, whether or not those end-uses were included in the top 95 percent of emissions from ODS
Substitutes.
In order to calculate uncertainty, functional forms were developed to simplify some of the complex "vintaging"
aspects of some end-use sectors, especially with respect to refrigeration and air-conditioning, and to a lesser degree,
fire extinguishing. These sectors calculate emissions based on the entire lifetime of equipment, not just equipment
put into commission in the current year, thereby necessitating simplifying equations. The functional forms used
variables that included growth rates, emission factors, transition from ODSs, change in charge size as a result of the
transition, disposal quantities, disposal emission rates, and either stock for the current year or original ODS
consumption. Uncertainty was estimated around each variable within the functional forms based on expert
judgment, and a Monte Carlo analysis was performed. The most significant sources of uncertainty for this source
category include the emission factors for mobile air-conditioning and retail food refrigeration, as well as the stock
(MT) of retail food refrigerant.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-77. Substitution of ozone
depleting substances HFC and PFC emissions were estimated to be between 110.1 and 129.6 Tg CO2 Eq. at the 95
percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of
approximately 0.3 percent below to 17 percent above the emission estimate of 110.4 Tg CO2 Eq.
Table 4-77: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg CO2
Eq. and Percent)
Source
Substitution of Ozone
Depleting Substances
Gases
HFCs and
PFCs
2006 Emission
Estimate
(Tg C02 Eq.)
110.4
Uncertainty Range Relative
(Tg C02 Eq.)
Lower Upper
Bound Bound
110.1 129.6
to Emission Estimate"
Lower Upper
Bound Bound
-0.3% +17%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
An extensive review of the chemical substitution trends, market sizes, growth rates, and charge sizes, together with
input from industry representatives, resulted in updated assumptions for the Vintaging Model. These changes
resulted in an average annual net decrease of 8.5 Tg CO2 Eq. (14 percent) in HFC and PFC emissions from the
substitution of ozone depleting substances for the period 1990 through 2005. The refrigeration and air conditioning
sector was the source of the greatest change, with an average annual net decrease of 10.2 Tg CO2 Eq. (15 percent) in
emissions. This decrease can be attributed to changes in the assumptions regarding the quantity of emissions at end
of life (disposal) across the entire sector, based on revised assumptions considering input from industry
representatives, as well significant modification to assumptions for chiller end uses, based on industry input.
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.
Industrial Processes 4-61
-------
A single 300 mm silicon wafer that yields between 400 to 500 semiconductor products (devices or chips) may
require as many as 100 distinct fluorinated-gas-using process steps, principally to deposit and pattern dielectric
films. Plasma etching (or patterning) of dielectric films, such as silicon dioxide and silicon nitride, is performed to
provide pathways for conducting material to connect individual circuit components in each device. The patterning
process uses plasma-generated fluorine atoms, which chemically react with exposed dielectric film, to selectively
remove the desired portions of the film. The material removed as well as undissociated fluorinated gases flow into
waste streams and, unless emission abatement systems are employed, into the atmosphere. PECVD chambers, used
for depositing dielectric films, are cleaned periodically using fluorinated and other gases. During the cleaning cycle
the gas is converted to fluorine atoms in plasma, which etches away residual material from chamber walls,
electrodes, and chamber hardware. Undissociated fluorinated gases and other products pass from the chamber to
waste streams and, unless abatement systems are employed, into the atmosphere. In addition to emissions of
unreacted gases, some fluorinated compounds can also be transformed in the plasma processes into different
fluorinated compounds which are then exhausted, unless abated, into the atmosphere. For example, when C2F6 is
used in cleaning or etching, CF4 is generated and emitted as a process by-product. Besides dielectric film etching
and PECVD chamber cleaning, much smaller quantities of fluorinated gases are used to etch poly silicon films and
refractory metal films like tungsten.
For 2006, total weighted emissions of all fluorinated greenhouse gases by the U.S. semiconductor industry were
estimated to be 4.8 Tg CO2 Eq. Combined emissions of all fluorinated greenhouse gases are presented in Table
4-78 and Table 4-79 below for years 1990, 1995 and the period 2000 to 2006. The rapid growth of this industry
and the increasing complexity (growing number of layers) of semiconductor products led to an increase in emissions
of 149 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 34 percent between 1999 and 2006. Together, industrial
growth and use of abatement technologies resulted in a net increase in emissions of 64 percent between 1990 and
2006.
Table 4-78: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.)
Year
CF4
C2F6
C3F8
C4F8
HFC-23
SF6
NF3*
Total
1990
0.7
1.5
0.0
0.0
0.2
0.5
0.0
2.9
1995^
1.3
2.5
0.0
0-0
0.3
0.9
0.0
5.0 ^
I 2000
\ 1.8
'• 3.0
\ 0.1
; 0.0
; 0.3
\ 1.1
\ 0.1
\ 6.3
2001
1.3
2.1
0.1
0.0
0.2
0.7
0.1
4.5
2002
1.1
2.2
0.1
0.0
0.2
0.7
0.3
4.3
2003
1.0
2.1
0.1
0.1
0.2
0.8
0.2
4.3
2004
1.1
2.1
0.0
0.1
0.2
0.8
0.2
4.3
2005
1.1
2.0
0.0
0.1
0.2
1.0
0.2
4.4
2006
1.2
2.2
0.0
0.1
0.3
1.0
0.3
4.8
Note: Totals may not sum due to independent rounding.
* NF3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.
Table 4-79: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)
Year
CF4
C2F6
C3F8
C4F8
HFC-23
SF6
NF3
1990 H
115 ^
160 ^
0 ^
0 ^
15 ^
22 ^
3 ^
1 1995 H
i. 193 'HI
1 272 M
1 o m
i o a
1 25 m
z; oo 5=z
z; JO 5=z
i 6 a
m 2000
an. 281
m 322
m is
a o
m 23
m 45
m 11
2001
202
230
14
0
15
31
12
2002
174
241
10
6
15
28
32
2003
161
227
14
9
16
35
30
2004
172
225
6
9
17
35
30
2005
169
217
5
13
18
41
26
2006
183
242
5
13
22
40
40
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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).16 The availability and applicability of Partner
data differs across the 1990 through 2006 time series. Consequently, emissions from semiconductor manufacturing
were estimated using three distinct methods, one each for the periods 1990 through 1994, 1995 through 1999, and
2000 and beyond.
1990 through 1994
For 1990 through 1994, Partnership data was unavailable and emissions were modeled using the PEVM (Burton
and Beizaie 2001).17 1990 to 1994 emissions are assumed to be primarily uncontrolled, since reduction strategies
such as chemical substitution and abatement were not widespread during this period.
PEVM is based on the assumption that PFC emissions from semiconductor manufacturing vary with (1) the number
of layers on 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 feature size),18 and (2) product type (discrete, memory or logic).19 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 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, 2007).
The emission factor in PEVM is the average of the four historical emission factors derived by dividing the total
annual emissions reported by the Partners for each year between 1996 and 1999 by the total TMLA estimated for
the Partners in each of those years. Since Partners are not believed to have applied significant emission reduction
measures before 2000, the resulting average emission factor does not reflect such measures.
16 A Partner refers to a participant of 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.
17 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.
18 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).
19 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 4-63
-------
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 accurate 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 layer-weighted capacity of the plants operated by the Partners and the total
layer-weighted capacity of all of the semiconductor plants in the United States; this ratio represents the share of
layer-weighted capacity attributable to the Partnership. The layer-weighted capacity of a plant (or group of plants)
consists of the silicon capacity of that plant multiplied by the estimated number of layers used to fabricate products
at that plant. This method assumes that Partners and non-Partners have similar capacity utilizations and per-layer
emission factors. Plant capacity, linewidth technology, and products manufactured information is contained in the
World Fab Watch (WFW) database, which is updated quarterly (see for example, Semiconductor Equipment and
Materials Industry 2007).
2000 through 2006
The U.S. 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),
however, 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 World emissions figure
by the non-Partner share of total layer-weighted silicon capacity for each year (as described above).20 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 industry (see Semiconductor Equipment and Materials Industry 2007).21'22'23
20 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 LMLA across fabs manufacturing similar classes of products. However, the
impact of replacing missing values on the non-Partner LMLA capacity share was inconsequential.
21 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. Lo 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 was 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. Lhe monthly ramp rate was applied from the first-quarter of silicon volume (FQSV), to determine the
average design capacity over the 2006 period.
22 In 2006, the industry trend in co-owemship 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. layer-weighted manufacturing capacity.
23 Lwo 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.
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Gas-Specific Emissions
Two different approaches were also used to estimate the distribution of emissions of specific PFCs. Before 1999,
when there was no consequential adoption of PFC-reducing measures, a fixed distribution was assumed to apply to
the entire U.S. industry. This distribution was based upon the average PFC purchases by semiconductor
manufacturers during this period and the application of IPCC default emission factors for each gas (Burton and
Beizaie 2001). For the 2000 through 2006 period, the 1990 through 1999 distribution was assumed to apply to the
non-Partners. Partners, however, began to report gas-specific emissions during this period. Thus, gas specific
emissions for 2000 through 2006 were estimated by adding the emissions reported by the Partners to those
estimated for the non-Partners.24
Data Sources
Partners estimate their emissions using a range of methods. For 2006, we assume that most Partners used a method
as least as accurate as the IPCC's Tier 2c Methodology, recommended in the IPCC (2000), since that has been their
approach for the past several years. Although some of the default emission factors have been updated in the IPCC
(2006) guidelines, as of the 2006 reporting year Partners continue to use the IPCC (2000) default emission factors.25
The Partners with relatively high emissions use leading-edge manufacturing technology, the newest process
equipment. When purchased, this equipment is supplied with PFC emission factors, measured using industry
standard guidelines (International Sematech, 2006). The larger emitting Partners likely use these process-specific
emission factors instead of the less accurate default emission factors provided in IPCC guidelines; however, the
documentation regarding Partner emissions is incomplete (Burton and Kshetry, 2007).
Data used to develop emission estimates were prepared in cooperation with the Partnership. Estimates of operating
plant capacities and characteristics for Partners and non-Partners were derived from the Semiconductor Equipment
and Materials Industry (SEMI) World Fab Watch (formerly International Fobs on Disk) database (1996 through
2007). Estimates of silicon consumed by linewidth from 1990 through 2006 were derived from information from
VLSI Research (2007), and the number of layers per linewidth was obtained from International Technology
Roadmap for Semiconductors: 2006 Update (Burton and Beizaie 2001, ITRS 2007).
Uncertainty
A quantitative uncertainty analysis26 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 2006 is
approximately ±10 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
24 In recent years, the Partnership started reporting gas-specific emissions using GWP values from the Third Assessment Report
(TAR), while in previous years the values were taken from the Second Assessment Report (SAR). The emissions reported here
are restated using GWPs from the SAR.
25 Currently, the majority of Partners use the IPCC (2000) Tier 2c guidelines, which most closely resemble the IPCC (2006) Tier
2a guidelines.
26 All uncertainties listed in this section are 95 percent confidence intervals.
Industrial Processes 4-65
-------
was estimated based 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.27 A relative error of approximately 11 percent was estimated for the PEVM emission factor, based on
the standard deviation of the 1996 to 1999 emission factors.28
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 4-80. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing were estimated to be between 4.8 and 5.5 Tg CO2 Eq.
at a 95 percent confidence level. This range represents 10 percent below to 8 percent above the 2006 emission
estimate of 5.1 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.
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg CO2 Eq. and Percent)
2006
Emission Uncertainty Range
Source Estimate" Relative to Emission Estimate1"
Gas (TgCO2Eq.) (TgCO2Eq.) (%)
Semiconductor
Manufacture
HFC, PFC,
andSF6 5.1
Lower
Bound0
4.8
Upper
Bound0
5.5
Lower
Bound
-10%
Upper
Bound
+8%
a Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match
that shown in Table 4-78.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
0 Absolute lower and upper bounds were calculated using the corresponding lower and upper bounds in percentages.
Planned Improvements
The method to estimate non-Partner related emissions (i.e., PEVM) is not expected to change (with the exception of
possible future updates to emission factors and added technology nodes). Future improvements to the national
emission estimates will primarily be associated with determining the portion of national emissions to attribute to
Partner report totals (about 80 percent in recent years) and improvements in Partner emission reporting (e.g.,
adoption of the IPCC (2006) guidelines). 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.)
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
27 Error propagation resulted in Partnership gas-specific uncertainties ranging from 17 to 33 percent.
28 The average of 1996 to 1999 emission factor is used to derive the PEVM emission factor.
4-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
equipment that transmits and distributes electricity (RAND 2004). The gas has been employed by the electric
power industry in the United States since the 1950s because of its dielectric strength and arc-quenching
characteristics. It is used in gas-insulated substations, circuit breakers, and other switchgear. Sulfur hexafluoride
has replaced flammable insulating oils in many applications and allows for more compact substations in dense urban
areas.
Fugitive emissions of SF6 can escape from gas-insulated substations and switch gear through seals, especially from
older equipment. The gas can also be released during equipment manufacturing, installation, servicing, and
disposal. Emissions of SF6 from equipment manufacturing and from electrical transmission and distribution
systems were estimated to be 13.2 Tg CO2 Eq. (0.6 Gg) in 2006. This quantity represents a 51 percent decrease
from the estimate for 1990 (see Table 4-81 and Table 4-82). This decrease is believed to be a response to increases
in the price of SF6 during the 1990s and to a growing awareness of the environmental impact of SF6 emissions,
through programs such as the EPA's SF6 Emission Reduction Partnership for Electric Power Systems.
Table 4-81: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Tg CO2 Eq.)
Electric Power Electrical Equipment
Year Systems Manufacturers Total
1990
1995
2000
2001
2002
2003
2004
2005
2006
26.4
20.9
14.4
14.5
13.6
13.2
13.3
13.2
12.4
0.3
0.5
0/7
0.6
0.8
0.7
0.7
0.8
0.8
26.7
21.5
15.1
15.0
14.4
13.8
13.9
14.0
13.2
Table 4-82: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg)
2000
2001
2002
2003
2004
2005
2006
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 2006 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to 2006 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
Industrial Processes 4-67
-------
2007 Utility Data Institute (UDI) Directories of Electric Power Producers and Distributors (UDI2001, 2004, 2007).
(Transmission miles are defined as the miles of lines carrying voltages above 34.5 kV.) Over the period from 1999
to 2006, 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 46 percent of total U.S. transmission miles.
For each year, the emissions reported by partner utilities were added to the emissions estimated for utilities that have
never participated in the Partnership (i.e., non-partners).
Emissions from partner utilities were estimated using a combination of reported data and, where reported data were
unavailable, interpolated or extrapolated data. If a partner utility did not provide data for a historical year,
emissions were interpolated between years for which data were available or extrapolated based on partner-specific
transmission mile growth rates. In 2006, non-reporting partners account for approximately 6 percent of the total
emissions attributable 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 2001 UDI Directory of Electric Power Producers and Distributors (UDI 2001). Two
equations were developed, one for small and one for large utilities (i.e., with less or more than 10,000 transmission
miles, respectively). The distinction between utility sizes was made because the regression analysis showed that the
relationship between emissions and transmission miles differed for small and large transmission networks. The
same equations were used to estimate non-partner emissions in 1999 and every year thereafter because non-partners
were assumed not to 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) = 0.88 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 were assumed to increase at an annual rate of 1.2 percent between 2000 and 2003 and 2.8 percent between
2003 and 2006.
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 2006, 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 global emissions from this source during the 1990 to 1998
period. To estimate global emissions, the RAND survey of global SF6 sales were used, together with the following
equation 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
4-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
substances, it is applicable to emissions from any long-lived pressurized equipment that is periodically serviced
during its lifetime.)
Emissions (kilograms SF6) = SF6 purchased to refill existing equipment (kilograms) + nameplate capacity29 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.
Sulfur hexafluoride purchased to refill existing equipment in a given year was assumed to be approximately equal to
the SF6 purchased by utilities in that year. Gas purchases by utilities and equipment manufacturers from 1961
through 2003 are available from the RAND (2004) survey. To estimate the quantity of SF6 released or recovered
from retiring equipment, the nameplate capacity of retiring equipment in a given year was assumed to equal 81.2
percent of the amount of gas purchased by electrical equipment manufacturers 40 years previous (e.g., in 2000, the
nameplate capacity of retiring equipment was assumed to equal 81.2 percent of the gas purchased in 1960). The
remaining 18.8 percent was assumed to have been emitted at the time of manufacture. The 18.8 percent emission
factor is an average 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 1998.
U.S. emissions between 1990 and 1998 are assumed to follow the same trajectory as global emissions during this
period. To estimate U.S. emissions, global emissions for each year from 1990 through 1998 were divided by the
estimated global emissions from 1999. The result was a time series of factors that express each year's global
emissions as a multiple of 1999 global emissions. Historical U.S. emissions were estimated by multiplying the
factor for each respective year by the estimated U.S. emissions of SF6 from electric power systems in 1999
(estimated to be 15.0 Tg CO2 Eq.).
Two factors may affect the relationship between the RAND sales trends and actual global emission trends. One is
utilities' inventories of SF6 in storage containers. When SF6 prices rise, utilities are likely to deplete internal
inventories before purchasing new SF6 at the higher price, in which case SF6 sales will fall more quickly than
emissions. On the other hand, when SF6 prices fall, utilities are likely to purchase more SF6 to rebuild inventories,
in which case sales will rise more quickly than emissions. This effect was accounted for by applying 3-year
smoothing to utility SF6 sales data. The other factor that may affect the relationship between the RAND sales trends
and actual global emissions is the level of imports from and exports to Russia and China. SF6 production in these
countries is not included in the RAND survey, but may have been significant during the 1990 through 1999 period.
This factor was not accounted for; however, atmospheric studies confirmed that the downward trend in the
estimated global emissions between 1995 and 1998 was real (see the Uncertainty discussion below).
1990 through 2006 Emissions from Manufacture of Electrical Equipment
The 1990 to 2006 emissions estimates for original equipment manufacturers (OEMs) were derived by assuming that
manufacturing emissions equal 10 percent of the quantity of SF6 charged into new equipment. The quantity of SF6
charged into new equipment was estimated based on statistics compiled by the National Electrical Manufacturers
Association (NEMA). These statistics were provided for 1990 to 2000; the quantities of SF6 charged into new
equipment for 2001 to 2006 were estimated using partner reported data and the total industry SF6 nameplate
capacity estimate (128.4 Tg CO2 Eq. in 2006). 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 2006 was
calculated. This ratio was then multiplied by the total industry nameplate capacity estimate to derive the amount of
SF6 charged into new equipment for the entire industry. The 10 percent emission rate is the average of the "ideal"
29 Nameplate capacity is defined as the amount of SF6 within fully charged electrical equipment.
Industrial Processes 4-69
-------
and "realistic" manufacturing emission rates (4 percent and 17 percent, respectively) identified in a paper prepared
under the auspices of the International Council on Large Electric Systems (CIGRE) in February 2002 (O'Connell et
al. 2002).
Uncertainty
To estimate the uncertainty associated with emissions of SF6 from electric transmission and distribution,
uncertainties associated with three quantities were estimated: (1) emissions from partners, (2) emissions from non-
partners, and (3) emissions from manufacturers of electrical equipment. A Monte Carlo analysis was then applied to
estimate the overall uncertainty of the emissions estimate.
Total emissions from the SF6 Emission Reduction Partnership include emissions from both reporting and non-
reporting partners. For reporting partners, individual partner-reported SF6 data was assumed to have an uncertainty
of 10 percent. Based on a Monte Carlo analysis, the cumulative uncertainty of all partner reported data was
estimated to be 4.1 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 2006
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 2006) will remain at levels defined by partners who reported in 1999. However, the last
source of uncertainty was not modeled.
Uncertainties were also estimated regarding the quantity of SF6 charged into equipment by equipment
manufacturers, which is projected from 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 4-83. Electrical Transmission
and Distribution SF6 emissions were estimated to be between 11.1 and 15.4 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 13.2
Tg C02 Eq.
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg CO2 Eq. and Percent)
Source
2006
Emission
Estimate
Gas (Tg CO2 Eq.)
Uncertainty Range Relative to 2006 Emission Estimate"
(TgC02Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Electrical Transmission
and Distribution SFg 13.2 11.1 15.4 -16% +17%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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. However, U.S. emission patterns may
differ from global emission patterns.
4-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Recalculations Discussion
Relative to the previous Inventory report, SF6 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 the assumptions used in
interpolating and extrapolating non-reported partner data; (3) new information on transmission mile growth
available in the UDI 2007 database; 4) removal of double counting between parent companies and their subsidiaries
in UDI databases; and 5) revision in the methodology for estimating 2001 to 2006 OEM emissions. For the period
1999 through 2006, estimates have been revised to incorporate additional data from new partners. Additionally,
partner estimates are now based on partner-specific transmission mile growth rates, obtained via the UDI 2001,
2004, and 2007 databases. Partner data and the industry SF6nameplate capacity estimates are now used to estimate
OEM emissions from 2001 onwards, since NEMA data for these years does not exist. Based on the revisions listed
above, SF6 emissions from electric transmission and distribution decreased from 1990 to 2000 and in 2003 and
increased in 2002, 2004 and 2005, compared to the 1990 to 2005 inventory. The magnitude of the differences
between the 1990 to 2005 inventory estimates and this year's estimates varied by year and ranged from 0 to 6
percent.
[BEGIN BOX]
Box 4-1: Potential Emission Estimates of HFCs, PFCs, and SF6
Emissions of HFCs, 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:
• By-product emissions. Some emissions do not result from the consumption or use of a chemical, but are the
unintended by-products 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 4-84 presents potential emission estimates for HFCs and PFCs from the substitution of ozone depleting
substances, HFCs, PFCs, and SF6 from semiconductor manufacture, and SF6 from magnesium production and
processing and electrical transmission and distribution.30 Potential emissions associated with the substitution for
ozone depleting substances were calculated using the EPA's Vintaging Model. Estimates of HFCs, 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
30
See Annex 5 for a discussion of sources of SF6 emissions excluded from the actual emissions estimates in this report.
Industrial Processes 4-71
-------
emissions estimates for electrical transmission and distribution were developed using U.S. utility purchases of SF6
for electrical equipment. From 1999 through 2006, estimates were obtained from reports submitted by participants
in EPA's SF6 Emission Reduction Program 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 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF6 from Selected Sources (Tg CO2 Eq.)
Source
Substitution of Ozone Depleting Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Magnesium Production and Processing
Electrical Transmission and Distribution
Potential
182.1
7.6
3.2
22.6
Actual
110.4
2.5
13.8
4.8
3.2
13.2
- Not applicable.
[END BOX]
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 2006 are reported in Table 4-85.
Table 4-85: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source
NOX
Other Industrial Processes
Chemical & Allied Product Manufacturing
Metals Processing
Storage and Transport
Miscellaneous*
CO
Metals Processing
Other Industrial Processes
Chemical & Allied Product Manufacturing
Storage and Transport
Miscellaneous*
NMVOCs
Storage and Transport
Other Industrial Processes
Chemical & Allied Product Manufacturing
Metals Processing
Miscellaneous*
1990^
591 =
343^
152^
88^
4,125^
2,395^
487=
1,073 =
69^
101 =
2,422^
1,352=:
364^
575^
111 =
20^
m
1
i
1
1
H
W-
1 3,959^
OH 2,159^
1
1 1,110=
m 23=
i
H 2,642^
1 1,499=,
1
1
1
1
i 2000
i 626
i 434
i 95
i 81
i 14
i 2
i 2,217
i 1,175
== 538
1 327
i 154
i 23
i 1,773
i 1,067
i 412
1 23°
g 61
i 3
2001
656
457
97
86
15
1
2,339
1,252
558
338
162
30
1,769
1,082
381
238
65
4
2002
534
390
63
63
17
2
1,744
895
444
258
107
39
2,036
1,346
401
226
42
20
2003
528
385
61
63
17
1
1,724
895
444
257
107
22
1,972
1,304
394
223
42
10
2004
524
381
61
63
17
1
1,724
895
444
257
107
22
1,931
1,274
386
220
42
9
2005
519
377
61
63
17
1
1,724
895
443
257
107
22
1,890
1,245
379
217
42
8
2006
515
373
61
62
17
1
1,724
895
443
257
107
22
1,849
1,215
372
214
41
7
* Miscellaneous includes the following categories: catastrophic/accidental release, other combustion, health services, cooling
towers, and fugitive dust. It does not include agricultural fires or slash/prescribed burning, which are accounted for under the
Field Burning of Agricultural Residues source.
Note: Totals may not sum due to independent rounding.
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
4-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
combined, using basic activity data (e.g., the amount of raw material processed) as an indicator of emissions.
National activity data were collected for individual categories from various agencies. Depending on the category,
these basic activity data may include data on production, fuel deliveries, raw material processed, etc.
Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
Program emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the accuracy of the emission factors used and accurate estimates of
activity data. A quantitative uncertainty analysis was not performed.
Industrial Processes 4-73
-------
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
Lime Manufacture ^^^|
Nitric Acid ^^^|
MCFC-22 Production ^H
Electrical Transmission and Distribution ^^|
Ammonia Production and Urea Application ^B
Limestone and Dolomite Use ^|
Aluminum Production |
Adipic Acid |
Semiconductor Manufacture |
Soda Ash Manufacture and Consumption |
Petrochemical Production |
Magnesium Production and Processing |
Titanium Dioxide Production |
Carbon Dioxide Consumption |
Ferroalloy Production |
Phosphoric Acid Production |
Zinc Production
Lead Production < 0.5
Silicon Carbide Production and Consumption < 0.5
Industrial Processes
as a Portion of all
Emissions
4.5%
25
50 75
TgCO2Eq.
100
125
Figure 4-1: 2006 Industrial Processes Chapter Greenhouse Gas Sources
-------
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 2006 (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: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg)
Gas/Source 1995! i2000 2001 2002 2003 2004 2005 2006
N2O from Product Uses = ! i
TgC02
Gg
Eq.
4.4^
14=
4.6! !
15! !
4.9
16
4.9
16
4.4
14
4.4
14
4.4
14
4.4
14
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 (CGA 2003). N2O is primarily used in carrier gases with oxygen to
administer more potent inhalation anesthetics for general anesthesia and as an anesthetic in various dental and
veterinary applications. As such, it is used to treat short-term pain, for sedation in minor elective surgeries, and as
an induction anesthetic. The second main use of N2O is as a propellant in pressure and aerosol products, the largest
application being pressure-packaged whipped cream. Small quantities of N2O also are used in the following
applications:
• Oxidizing agent and etchant used in semiconductor manufacturing;
• 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 2006 was approximately 15 Gg. N2O emissions were 4.4 Tg CO2 Eq. (14 Gg) in 2006 (see
Table 5-3). Production of N2O stabilized during the 1990s because medical markets had found other substitutes for
anesthetics, and more medical procedures were being performed on an outpatient basis using local anesthetics that
do not require N2O. The use of N2O as a propellant for whipped cream has also stabilized due to the increased
popularity of cream products packaged in reusable plastic tubs (Heydorn 1997).
Table 5-2: N2O Emissions from N2O Product Usage (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg CO2 Eq.
4.4
4.6
4.9
4.9
4.4
4.4
4.4
4.4
4.4
Gg
14
15
16
16
14
14
14
14
14
Solvent and Other Product Use 5-1
-------
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 = Zi [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 2006, 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 emissions 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 emissions 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 (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, and 2006 were held at the 2003 value.
The 1996 share of the total quantity of N2O used by each subcategory was obtained from SRI Consulting's Nitrous
Oxide, North America report (Heydorn 1997). The 1990 through 1995 share of total quantity of N2O used by each
subcategory was kept the same as the 1996 number provided by SRI Consulting. The 1997 through 2001 share of
total quantity of N2O usage by sector was obtained from communication with a N2O industry expert (Tupman
2002). The 2002 and 2003 share of total quantity of N2O usage by sector was obtained from CGA (2002, 2003).
Due to unavailable data, the share of total quantity of N2O usage data for 2004, 2005, and 2006 was assumed to
equal the 2003 value. The emissions rate for the food processing propellant industry was obtained from SRI
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Consulting'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 2006
IPCC Guidelines.
Table 5-3: N2O Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Gg
16
17
17
17
15
15
15
15
15
Uncertainty
The overall uncertainty associated with the 2006 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 2006 emissions estimate of 4.4 Tg CO2 Eq.
Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From N2O Product Usage (Tg CO2 Eq. and
Percent)
2006 Emission Uncertainty Range Relative to Emission
Source Gas Estimate Estimate"
(TgC02Eq.) (TgC02Eq.)
Lower Upper Lower Upper
Bound Bound Bound Bound
N2O Product Usage
N2O 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.
Recalculations Discussion
The N2O emission factor for medical applications has been updated relative to the previous Inventory based on the
revised IPCC Guidelines for National Greenhouse Gas Inventories (2006). The updated emission factor resulted in
an average increase in N2O emissions from N2O product usage relative to the previous inventory for each year in the
1990 through 2005 timeseries of 0.1 Tg CO2 Eq. (2 percent), respectively.
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.
Solvent and Other Product Use 5-3
-------
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).! Non-CH4 volatile organic compounds (NMVOCs), commonly referred to as "hydrocarbons,"
are the primary gases emitted from most processes employing organic or petroleum based solvents. As some of
industrial applications also employ thermal incineration as a control technology, combustion by-products, such as
carbon monoxide (CO) and nitrogen oxides (NOX), are also reported with this source category. In the United States,
emissions from solvents are primarily the result of solvent evaporation, whereby the lighter hydrocarbon molecules
in the solvents escape into the atmosphere. The evaporation process varies depending on different solvent uses and
solvent types. The major categories of solvent uses include: degreasing, graphic arts, surface coating, other
industrial uses of solvents (i.e., electronics, etc.), dry cleaning, and non-industrial uses (i.e., uses of paint thinner,
etc.).
Total emissions of NOX, NMVOCs, and CO from 1990 to 2006 are reported in Table 5-5.
Table 5-5: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg)
Activity
NOX
Surface Coating
Graphic Arts
Degreasing
Dry Cleaning
Other Industrial Processes3
Non-Industrial Processes'3
Other
CO
Surface Coating
Other Industrial Processes3
Dry Cleaning
Degreasing
Graphic Arts
Non-Industrial Processes'3
Other
NMVOCs
Surface Coating
Non-Industrial Processes'3
Degreasing
Dry Cleaning
Graphic Arts
Other Industrial Processes3
Other
1990 =
i m
i m
+ =
+ =
+ ^
+ ^
+ ^
NA ji
5 ^
+ =
4 M
+ =
+ =
+ =
+ =
NA M
5,216 M
2,289 =
1,724 =
675 m
195 M
249 m
85 M
+ =
= 1995 !
1 3 i
1 2 i
1 1 !
1 + i
1 +
1 +
1 + i
1 +
1 5 i
1 1 !
1 3 i
1 1 !
1 + i
1 + i
1 + i
1 NA !
1 5,609 i
= 2,432 i
= 1,858 i
1 716 i
1 209 i
1 307 i
1 87 !
1 + i
i 2000
3
i 3
i +
i +
i +
i +
; +
; +
i 46
i 46
i +
i +
i +
i +
i +
i +
i 4,384
i 1,767
i 1,676
i 316
i 265
i 222
i 98
i 40
2001
3
3
+
+
+
+
+
+
45
45
+
+
+
+
+
+
4,547
1,863
1,707
331
212
229
103
42
2002
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,881
1,590
1,457
283
232
195
88
36
2003
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,862
1,582
1,450
281
231
194
88
36
2004
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,854
1,579
1,447
281
230
194
88
36
2005
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,846
1,576
1,444
280
230
193
88
36
2006
5
5
+
+
+
+
+
+
1
1
+
+
+
+
+
+
3,839
1,573
1,441
280
229
193
87
36
a Includes rubber and plastics manufacturing, and other miscellaneous applications.
b Includes cutback asphalt, pesticide application adhesives, consumer solvents, and other miscellaneous applications.
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg.
1 Solvent usage in the United States also results in the emission of small amounts of hydrofluorocarbons (HFCs) and
hydrofluoroethers (HFEs), which are included under Substitution of Ozone Depleting Substances in the Industrial Processes
chapter.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 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 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
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes. This
chapter provides an assessment of non-carbon-dioxide emissions from the following source categories: enteric
fermentation in domestic livestock, livestock manure management, rice cultivation, agricultural soil management,
and field burning of agricultural residues (see Figure 6-1). Carbon dioxide (CO2) emissions and removals from
agriculture-related land-use activities, such as conversion of grassland to cultivated land, are presented in the Land
Use, Land-Use Change, and Forestry chapter. CO2 emissions from on-farm energy use are accounted for in the
Energy chapter.
Figure 6-1: 2006 Agriculture Chapter Greenhouse Gas Emission Sources
In 2006, the agricultural sector was responsible for emissions of 454.1 teragrams of CO2 equivalent (Tg CO2 Eq.),
or 6 percent of total U.S. greenhouse gas emissions. Methane (CH4) and nitrous oxide (N2O) were the primary
greenhouse gases emitted by agricultural activities. CH4 emissions from enteric fermentation and manure
management represent about 23 percent and 7 percent of total CH4 emissions from anthropogenic activities,
respectively. Of all domestic animal types, beef and dairy cattle were by far the largest emitters of CH4. Rice
cultivation and field burning of agricultural residues were minor sources of CH4. Agricultural soil management
activities such as fertilizer application and other cropping practices were the largest source of U.S. N2O emissions,
accounting for 72 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 2006, CH4
emissions from agricultural activities increased by 5 percent, while N2O emissions fluctuated from year to year, but
overall decreased by less than 1 percent.
Table 6-1: Emissions from Agriculture (Tg CO2 Eq.)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
N2O
Agricultural Soil
Management
Manure Management
Field Burning of Agricultural
Residues
Total
1990
165.7
126.9
31.0
7.1 I
0.7 |
281.8 !
269.4 |
12.1 |
0.4 I
447.5
1995!
175.8!
132.31
35.2!
7.6!
0.7!
278.0!
264.8!
12.8!
0.4!
453.8!
1 2000
! 171.7
I 124.6
1 38.8
7.5
0.8
276.3
262.1
13.7
0.5
! 447.9
2001
172.2
123.6
40.2
7.6
0.8
291.5
277.0
14.0
0.5
463.7
2002
172.6
123.8
41.3
6.8
0.7
276.4
262.0
14.0
0.4
449.0
2003
173.0
124.6
40.7
6.9
0.8
261.3
247.3
13.6
0.4
434.3
2004
170.9
122.4
40.1
7.6
0.9
261.2
246.9
13.8
0.5
432.1
2005
174.0
124.5
41.8
6.8
0.9
279.6
265.2
13.9
0.5
453.6
2006
174.4
126.2
41.4
5.9
0.8
279.8
265.0
14.3
0.5
454.1
Note: Totals may not sum due to independent rounding.
Table 6-2: Emissions from Agriculture (Gg)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
1990
7,890
6,044
1,474
339 !
1995i
8,373i
6,302!
1,676!
363!
1 2000
1 8,174
! 5,933
1 1,847
357
2001
8,201
5,886
1,915
364
2002
8,219
5,896
1,964
325
2003
8,236
5,931
1,938
328
2004
8,138
5,828
1,908
360
2005
8,284
5,928
1,988
326
2006
8,304
6,010
1,972
282
Agriculture 6-1
-------
Field Burning of Agricultural j j
Residues 33 ! 321 38 37 34 38 42 41 39
N2O 909 j 897J 891 940 892 843 842 902 902
Agricultural Soil | j
Management 869 j 854J 845 894 845 798 796 855 855
Manure Management 39 j 41| 44 45 45 44 44 45 46
Field Burning of Agricultural I |
Residues 1_ | ij 1_ 1_ 1_ 1_ 2 2 2
Note: Totals may not sum due to independent rounding.
6.1. Enteric Fermentation (IPCC Source Category 4A)
CH4 is produced as part of normal digestive processes in animals. During digestion, microbes resident in an
animal's digestive system ferment food consumed by the animal. This microbial fermentation process, referred to
as enteric fermentation, produces CH4 as a by-product, which can be exhaled or eructated by the animal. The
amount of CH4 produced and 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 CH4 because of their
unique digestive system. Ruminants possess a rumen, or large "fore-stomach," in which microbial fermentation
breaks down the feed they consume into products that can be absorbed and metabolized. The microbial
fermentation that occurs in the rumen enables them to digest coarse plant material that non-ruminant animals
cannot. Ruminant animals, consequently, have the highest CH4 emissions among all animal types.
Non-ruminant 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 CH4is 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 lead 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).
CH4 emission estimates from enteric fermentation are provided in Table 6-3 and Table 6-4. Total livestock CH4
emissions in 2006 were 126.2 Tg CC>2 Eq. (6,010 Gg). Beef cattle remain the largest contributor of CH4 emissions
from enteric fermentation, accounting for 71 percent in 2006. Emissions from dairy cattle in 2006 accounted for 24
percent, and the remaining emissions were from horses, sheep, swine, and goats.
From 1990 to 2006, emissions from enteric fermentation have decreased by less than 1 percent. Generally,
emissions have been decreasing since 1995 to 2004, mainly due to decreasing populations of both beef and dairy
cattle and improved feed quality for feedlot cattle. The last two years have shown an increase in emissions. During
this timeframe, populations of sheep have decreased 45 percent since 1990 while horse populations have increased
over 80 percent, mostly over the last 5 years. Goat and swine populations have increased 1 percent and 14 percent,
respectively, during this timeframe.
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg CO2 Eq.)
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
1990
89.9
31.2
1.9
1.9
1.7
0.3
126.9
1995
1 96.9!
1 29.9!
1 1.91
! i.5i
! 1.91
0.2
132.3
2000
90.4
28.9
2.0
1.2
1.9
0.3
124.6
2001
89.4
28.8
2.1
1.2
1.9
0.3
123.6
2002
89.3
29.0
2.3
1.1
1.9
0.3
123.8
2003
89.5
29.2
2.6
1.1
1.9
0.3
124.6
2004
87.2
28.9
3.0
1.0
1.9
0.3
122.4
2005
88.2
29.6
3.5
1.0
1.9
0.3
124.5
2006
89.2
30.3
3.5
1.0
1.9
0.3
126.2
Note: Totals may not sum due to independent rounding.
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg)
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
1990
4,281
1,488
91
91
81
13
6,044
1995
1 4,616|
1 1,4221
1 92!
! 72i
! 88!
12
6,302
2000
4,304
1,377
94
56
88
12
5,933
2001
4,257
1,374
99
55
88
12
5,886
2002
4,251
1,381
108
53
90
13
5,896
2003
4,260
1,393
126
51
90
13
5,931
2004
4,155
1,377
144
49
91
13
5,828
2005
4,198
1,411
166
49
92
13
5,928
2006
4,249
1,441
166
50
93
13
6,010
Note: Totals may not sum due to independent rounding.
Methodology
Livestock emission estimates fall into two categories: cattle and other domesticated animals. Cattle, due to their
large population, large size, and particular digestive characteristics, account for the majority of CH4 emissions from
livestock in the United States. A more detailed methodology (i.e., IPCC Tier 2) was therefore applied to estimate
emissions for all cattle except for bulls. Emission estimates for other domesticated animals (horses, sheep, swine,
goats, and bulls) were handled using a less detailed approach (i.e., IPCC Tier 1).
While the large diversity of animal management practices cannot be precisely characterized and evaluated,
significant scientific literature exists that describes the quantity of CH4 produced by individual ruminant animals,
particularly cattle. The Cattle Enteric Fermentation Model (CEFM), developed by EPA to estimate cattle enteric
CH4 emissions, incorporates this information and other analyses of livestock population, feeding practices and
production characteristics were used to estimate emissions from cattle populations.
National cattle population statistics were disaggregated into the following cattle sub-populations:
• Dairy Cattle
o Calves
o Heifer Replacements
o Cows
• Beef Cattle
o Calves
o Heifer Replacements
o Heifer and Steer Stackers
o Animals in Feedlots (Heifers and Steers)
o Cows
o 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 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
Agriculture 6-3
-------
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 2007).
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 CH4 conversion rates (Ym) (expressed as the fraction of gross energy converted to CH4) 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). For feedlot animals, DE and Ym values recommended by Johnson (1999) were used.
Values from EPA (1993) were used for dairy replacement heifers. For grazing beef cattle, DE values were based on
diet information in NRC (2000) and Ym values were based on Johnson (2002). Weight data were estimated from
Feedstuffs (1998), Western Dairyman (1998), and expert opinion. See Annex 3.9 for more details on the method
used to characterize cattle diets in the United States.
To estimate CH4 emissions from all cattle types except bulls and calves younger than 7 months, 1 the population was
divided into state, age, sub-type (e.g., dairy cows and replacements, beef cows and replacements, heifer and steer
stackers, and heifer and steer in feedlots), and production (e.g., pregnant, lactating) groupings to more fully capture
differences in CH4 emissions from these animal types. 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 CH4 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 were multiplied by the emission factor for each cattle type. More details are
provided in Annex 3.9.
Emission estimates for other animal types were based on average emission factors representative of entire
populations of each animal type. CH4 emissions from these animals accounted for a minor portion of total CH4
emissions from livestock in the United States from 1990 through 2006. 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 2007). Horse population data were obtained from the
FAOSTAT database (FAO 2007), because USDA does not estimate U.S. horse populations annually. Goat
population data were obtained for 1992, 1997, and 2002 (USDA 2007); these data were interpolated and
extrapolated to derive estimates for the other years. CH4 emissions 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 CH4emissions from
enteric fermentation.
1 Emissions from bulls are estimated using a Tier 1 approach because it is assumed there is minimal variation in population and
diets; calves younger than 7 months are assumed to emit little or no CH/t.
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Uncertainty
Quantitative uncertainty of this source category was performed through the IPCC-recommended Tier 2 uncertainty
estimation methodology, Monte Carlo Stochastic Simulation technique as described in ICF (2003). These
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 2006 activity data and emission factor input variables used in the current submission. Consequently,
these uncertainty estimates were directly applied to the 2006 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) because we wanted to capture the fact that these variables
can not 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 112.3 to 148.9 Tg CO2 Eq., calculated as 11
percent below and 18 percent above the actual 2006 emission estimate of 126.2 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.
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg CO2 Eq. and
Percent)
Source
Enteric Fermentation
2006
Emission
Gas Estimate
(TgC02Eq.)
CH4 126.2
Uncertainty Range Relative to
(Tg C02 Eq.)
Lower Upper
Bound Bound
112.3 148.9
Emission Estimate3' b
(%)
Lower Upper
Bound Bound
-11% +18%
a Range of emissions 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 2006 estimates.
QA/QC and Verification
In order to ensure the quality of the emission estimates from enteric fermentation, the IPCC Tier 1 and Tier 2
Quality Assurance/Quality Control (QA/QC) procedures were implemented consistent with the U.S. QA/QC plan.
Tier 2 QA procedures included independent peer review of emission estimates. Particular emphasis was placed this
year on reviewing and implementing the revised IPCC Guidelines (IPCC 2006). Additionally, as described below,
this year the CEFM was modified to allow generation of the estimates by state, which required further QA/QC to
ensure consistency of estimates generated by the updated model.
Recalculations Discussion
There were several modifications that had an effect on emission estimates, including:
Agriculture 6-5
-------
The Cfi (a coefficient used for calculating the net energy required for maintenance) used for lactating cattle
was adjusted from 0.322 (previously used for all cattle) to 0.386, based on the revised IPCC equations
(IPCC 2006). This change had the effect of increasing the energy requirement for maintenance of lactating
cows and thus increasing emissions for dairy cows by approximately 7 percent and beef cows by
approximately 16 percent.
During the QA/QC process it was noted that the C factor (a coefficient used in calculating the net energy
required for growth) of 0.8 was only being used for some feedlot heifers, and all other cows and heifers
were being calculated using a C factor of 1.0. This has been updated so that all cows and heifers use a C
factor of 0.8 and all steer use a C factor of 1.0, as stated in the revised IPCC Guidelines (IPCC 2006). This
change resulted in an increase in emissions of between three and ten percent in animal subcategories that
experience weight gain (e.g., feedlot, replacement, and stacker animals), depending on the subcategory.
The equation used to calculate the net energy of growth (NEg), which is part of the gross energy equation,
was also updated to match the simplified equation provided in the revised IPCC Guidelines (IPCC 2006).
The equation now reads:
NEg =22.02 xf^^T'xWG1-097
Previously the equation used was:
NEn =4.18x0.0635
0.891 x (Weight xQ.96)>
N-i075
478
(WGxO.92)1'097
Where,
NEg = The net energy required for growth, MJ/day
Weight = Average live body weight of the animals in the population, kg
C = A coefficient that is 0.8 for females, 1.0 for steer, and 1.2 for bulls
MW = The mature weight of an adult female in moderate condition, kg
WG = The average weight gain for animals in the population, kg/day
This change resulted in a decrease of less than one half of one percent in animal subcategories that
experience growth (i.e., weight gain, including, feedlot, replacement, and stacker animals).
• In the current inventory, the CEFM, which was used to calculate emissions from cattle enteric
fermentation, was updated to output results by individual state rather than by regional groupings, during
this process two changes occurred. First, the averaging approach used to calculate the step-up DE and Ym
for feedlot animals is based on an average of the feedlot and stacker diet characteristics. Given that we
changed the model to run 50 states rather than 7 regions, the final values for the step-up diet characteristics
changed slightly. Second, the milk production numbers are now input at the state, rather than regional
level, which allows for data input at a more detailed level. Both of these changes had a very small effect
on emissions compared to the additional modifications, discussed above.
• Population estimates were revised by FAO for 2001 through 2005 for horses.
• The USDA published revised population estimates that affected historical emissions estimated for swine in
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
2005. 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 99 Gg (7.6 percent) per year and beef
cattle increased an average of 435 Gg (11.1 percent) per year over the entire time series. Historical emission
estimates for swine in 2005 increased by less than one half of one percent as a result of the USDA revisions
described above. Historical emission estimates for horses increased by an average of 35 percent from 2001 through
2005.
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 methane 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 discussed above several revisions will be investigated, including:
• the possible inclusion of bulls into the CEFM at a Tier 1 or 2 level;
• updating input variables that are from older data sources, such as beef births by month and beef cow
lactation rates;
• the possible breakout of other animal types from national estimates to state-level estimates; and
• including bison in the estimates for other domesticated animals.
It is anticipated that 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 anthropogenic methane (CH4) and nitrous oxide (N2O)
emissions. Methane is produced by the anaerobic decomposition of manure. Direct N2O emissions are produced as
part of the nitrogen cycle through the nitrification and denitrification of the organic nitrogen in livestock manure
and urine.2 Indirect N2O emissions are produced as result of the volatilization of nitrogen as NH3 and NOX and
runoff and leaching of nitrogen during treatment, storage and transportation.
When livestock or poultry manure are stored or treated in systems that promote anaerobic conditions (e.g., as a
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.
Agriculture 6-7
-------
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, 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 ammonia (NH3) or organic
nitrogen is converted to nitrates and nitrites (nitrification), and then handled anaerobically where the nitrates and
nitrites are reduced to nitrogen gas (N2), with intermediate production of N2O and nitric oxide (NO) (denitrification)
(Groffman et al. 2000). These emissions are most likely to occur in dry manure handling systems that have aerobic
conditions, but that also contain pockets of anaerobic conditions due to saturation. A very small portion of the total
nitrogen excreted is expected to convert to N2O in the waste management system (WMS). Indirect N2O emissions
are produced when nitrogen 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 is exposed to weather. Runoff losses are also specific to the type of animal housed on the operation.
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 2006 were 41.4 Tg CO2 Eq. (1,972 Gg), 34 percent higher than in 1990. Emissions
increased on average by 0.6 Tg CO2 Eq. (2.0 percent) annually over this period. The majority of this increase was
from swine and dairy cow manure, where emissions increased 34 and 49 percent, respectively. Although the
majority of manure in the United States is handled as a solid, producing little CH4, the general trend in manure
management, particularly for dairy and swine (which are both shifting towards larger facilities), is one of increasing
use of liquid systems. Also, new regulations limiting the application of manure nutrients have shifted manure
management practices at smaller dairies from daily spread to manure managed and stored on 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 2006); 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 2005 to 2006, there was a 1 percent decrease in
total CH4 emissions, due to minor shifts in the animal populations and the resultant effects on manure management
system allocations and increased use of anaerobic digesters.
In 2006, total N2O emissions were estimated to be 14.3 Tg CO2 Eq. (46 Gg); in 1990, emissions were 12.1 Tg CO2
Eq. (39 Gg). These values include both direct and indirect N2O emissions from manure management. N2O
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 an
18 percent increase from 1990 to 2006 and a 2.5 percent increase from 2005 through 2006.
Table 6-6 and Table 6-7 provide estimates of CH4 and N2O emissions from manure management by animal
category.
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2 Eq.)
Gas/Animal Type
CH41
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N202
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Total
1990
31.0
12.0
2.5
13.1
0.1
+
2.8
0.5
12.1
3.5
5.5
1.2
0.1
+
1.5
0.2
43.0
1995
35.2
13.4
2.6
16.0
0.1
+
2.7
0.4
12.8
3.5
5.9
1.4
0.1
+
1.6
0.2
48.0
2000
38.8
15.8
2.4
17.4
0.1
+
2.6
0.5
13.7
3.6
6.7
1.4
0.1
+
1.7
0.2
52.5
2001
40.2
16.6
2.4
17.8
0.1
0.0
2.7
0.5
14.0
3.6
6.9
1.4
0.1
0.0
1.7
0.2
54.2
2002
41.3
17.3
2.4
18.3
0.1
+
2.7
0.5
14.0
3.7
6.7
1.5
0.1
+
1.7
0.3
55.2
2003
40.7
17.7
2.3
17.2
0.1
+
2.7
0.6
13.6
3.7
6.3
1.5
0.1
+
1.7
0.3
54.3
2004
40.1
17.2
2.3
17.1
0.1
+
2.6
0.7
13.8
3.7
6.5
1.5
0.1
+
1.7
0.3
53.9
2005
41.8
17.9
2.3
17.9
0.1
+
2.6
0.8
13.9
3.7
6.5
1.5
0.1
+
1.7
0.4
55.7
2006
41.4
17.9
2.5
17.5
0.1
+
2.7
0.8
14.3
3.8
6.7
1.5
0.1
+
1.8
0.4
55.7
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
'includes CH4 emission reductions due to anaerobic digestion.
Includes both direct and indirect N2O emissions.
Table 6-7: CH4 and N2O Emissions from Manure Management (Gg)
Gas/Animal Type
CH/
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N202
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
1990
1,474
572
120
623
7
1
131
22
39
11
18
4
+
+
5
1
1995
1,676
638
121
762
5
1
128
21
41
11
19
5
+
+
5
1
2000
1,847
751
114
830
4
1
125
22
44
12
22
5
+
+
5
1
2001
1,915
792
117
849
4
1
129
23
45
12
22
5
+
+
5
1
2002
1,964
822
113
873
4
1
127
25
45
12
22
5
+
+
6
1
2003
1,938
844
112
821
4
1
127
29
44
12
20
5
+
+
6
1
2004
1,908
818
111
815
4
1
126
34
44
12
21
5
+
+
6
1
2005
1,988
854
112
853
4
1
126
39
45
12
21
5
+
+
6
1
2006
1,972
852
117
832
4
1
126
39
46
12
22
5
+
+
6
1
Note: Totals may not sum due to independent rounding.
'includes CH4 emission reductions due to anaerobic digestion.
Includes both direct and indirect N2O emissions.
+ Less than 0.5 Gg.
Methodology
The methodologies presented in IPCC (2006) form the basis of the CH4 and N2O emission estimates for each animal
type. The calculation of emissions requires the following information:
• Animal population data (by animal type and state);
• Amount of N produced (excretion rate by animal type times animal population);
• Amount of volatile solids produced (excretion rate by animal type times animal population);
• CH4 producing potential of the volatile solids (by animal type);
Agriculture 6-9
-------
• Extent to which the CH4 producing potential is realized for each type of manure management system (by
state and manure management system, including the impacts of any biogas collection efforts);
• Portion of manure managed in each manure management system (by state and animal type); and
• Portion of manure deposited on pasture, range, or paddock or used in daily spread systems.
This section presents a summary of the methodologies used to estimate CH4 and N2O emissions from manure
management for this inventory. See Annex 3. 10 for more detailed information on the methodology and data used to
calculate CH4 and N2O emissions from manure management.
Both CH4 and N2O emissions were estimated by first determining activity data, including animal population, waste
characteristics, and manure management system usage. For swine and dairy cattle, manure management system
usage was determined for different farm size categories using data from USD A (USD A 1996b, 1998b, 2000b) and
EPA (ERG 2000a, EPA 2002a, 2002b). For beef cattle and poultry, manure management system usage data were
not tied to farm size but were based on other data sources (ERG 2000a, USDA 2000c, UEP 1999). For other animal
types, manure management system usage was based on previous estimates (EPA 1992).
MCFs and N2O emission factors were determined for all manure management systems. MCFs for dry systems were
set equal to default IPCC factors based on each state's climate for each year (IPCC 2006). MCFs for liquid/slurry,
anaerobic lagoon, and deep pit systems were calculated based on the forecast performance of biological systems
relative to temperature changes as predicted in the van't Hoff-Arrhenius equation. The MCF calculations model the
average monthly ambient temperature, a minimum system temperature, the carryover of volatile solids (VS) in the
system from month to month due to long storage times exhibited by anaerobic lagoon systems, and a factor to
account for management and design practices that result in the loss of VS from lagoon systems. Direct N2O
emission factors for all systems were set equal to default IPCC factors (IPCC 2006). For indirect N2O, the default
indirect N2O emission factors suggested by IPCC were used: 0.010 kg N2O-N/kg N for volatilization and 0.0075 kg
-N/kg N for runoff/leaching. The amount of nitrogen that is lost due to volatilization of NH3 and NOX (FracGas) is
based on WMS-specific volatilization values as estimated from U.S. EPA's National Emission Inventory -Ammonia
Emissions from Animal Agriculture Operations (EPA 2005). The amount of nitrogen that is lost due to runoff and
leaching (FraCmnoff/ieachmg) is based on regional cattle runoff data from EPA's Office of Water (EPA 2002b).
CH4 emissions were estimated using the VS production for livestock. For all cattle groups except bulls and calves,
regional animal-specific VS production rates that are related to the diet of the animal for each year of the inventory
were used (Pederson et al., 2007). For other animal groups, VS production was calculated using a national average
VS production rate from the Agricultural Waste Management Field Handbook (USDA 1 996a), which was then
multiplied by the average weight of the animal and the state-specific animal population. The resulting VS for each
animal group were then multiplied by the maximum CH4 producing capacity of the waste (B0) and the state- and
WMS-specific MCFs.
The maximum CH4 producing capacity of the VS, or B0, was determined based on data collected in a literature
review (ERG 2000b). B0 data were collected for each animal type for which emissions were estimated.
Anaerobic digester reductions for 1990-2005 were estimated based on data from the EPA AgSTAR program,
including information presented in the AgSTAR Digest (EPA 2000, 2003b, 2006). Anaerobic digestion reductions
for 2006 were calculated based on data from an AgSTAR digester inventory (ERG 2008).
Nitrogen excretion rates from the USDA Agricultural Waste Management Field Handbook (USDA 1 996a) were
used for all livestock except sheep, goats, and horses. Data from the American Society of Agricultural Engineers
(ASAE 1999) were used for these animal types.
Direct N2O emissions were estimated by determining total Kjeldahl nitrogen (TKN)3 production for all livestock
3Total Kjeldahl nitrogen is a measure of organically bound nitrogen and ammonia nitrogen.
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
wastes using a national average N excretion rate for each animal group from USD A (1996a), which was then
multiplied by the average weight of the animal and the state-specific animal population. State- and WMS-specific
direct N2O emission factors were then applied to total nitrogen production to estimate direct N2O emissions.
Indirect N2O emissions were calculated by first estimating the amount of nitrogen loss from volatilization and
runoff/leaching by multiplying the N excreted by FracGas and FracRunoff/Leaching- The N losses were then multiplied by
the indirect N2O emission factors to estimate indirect N2O emissions.
Uncertainty
An analysis was conducted for the manure management emission estimates presented in EPA's Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2001 (EPA 2003a, ERG 2003) to determine the uncertainty associated
with estimating CH4 and N2O emissions from livestock manure management. 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.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 6-8 Manure management CH4
emissions in 2006 were estimated to be between 34.0 and 49.7 Tg CO2 Eq. at a 95 percent confidence level, which
indicates a range of 18 percent below to 20 percent above the actual 2006 emission estimate of 41.4 Tg CO2 Eq. At
the 95 percent confidence level, N2O emissions were estimated to be between 12.0 and 17.7 Tg CO2 Eq. (or
approximately 16 percent below and 24 percent above the actual 2006 emission estimate of 14.3 Tg CO2 Eq.).
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O (Direct and Indirect) Emissions from Manure
Management (Tg CO2 Eq. and Percent)
Source
Manure Management
Manure Management
2006 Emission
Gas Estimate
(Tg C02 Eq.)
CH4 41.4
N2O 14.3
Uncertainty Range Relative to Emission
Estimate3
(TgC02Eq.) (%)
Lower
Bound
34.0
12.0
Upper
Bound
49.7
17.7
Lower
Bound
-18%
-16%
Upper
Bound
+20%
+24%
aRange 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 N2O emissions4 from managed systems and
CH4 emissions from livestock manure. All errors identified were corrected. Order of magnitude checks were also
conducted, and corrections made where needed. Manure 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 nitrogen excreted and the sum
of county estimates for the full time series.
4N2O emissions in the previous inventory reflect only direct emissions whereas the current N2O emissions include both direct
and indirect emissions from livestock manure management.
Agriculture 6-11
-------
Recalculations Discussion
There was a major change in the N2O and CH4 emissions calculations for the 2006 inventory. These emissions are
now calculated from the "bottom-up" such that CH4 and N2O are calculated for each animal group, manure
management system, and state. These values are then summed to calculate the total greenhouse gas emissions from
manure management in the United States. This methodology differs from previous inventories which calculated
state weighted average N2O emission factors and methane conversion factors (MCFs). Although this new
methodology does not alter the overall estimates of greenhouse gases associated with this section, it now allows
emissions to be viewed by animal type and manure management system at the state and national level.
In the previous N2O inventory, dairy heifers and beef on feed each had a separate WMS distribution for managed
systems and unmanaged systems. The managed WMS distribution was used to calculate a state average EF for
managed systems. In the new inventory methodology, dairy heifers and beef on feed have one WMS distribution
that represents managed and unmanaged systems. For all animals, emissions are calculated for each WMS using the
EF for that system, and not using a state average EF. This change in calculation methodology results in a slightly
different (less than one percent change) emission estimate for these animal groups.
The inventory now includes indirect N2O emissions in the manure management sector associated with N losses from
volatilization of nitrogen as ammonia (NH3), nitrogen oxides (NOX), and leaching and runoff, as recommended by
IPCC (2006). These indirect N2O emissions are added to the direct N2O emissions to present a more complete
picture of N2O emissions from manure management.
The days per year used in N2O calculations was changed from 365 to 365.25 to include leap years and to be
consistent with the CH4 inventory calculations.
Methane emission reductions from anaerobic digestion for 2006 were calculated from an AgSTAR digester
inventory by summing the estimated emission reductions by animal type (ERG 2008). Anaerobic digestion
reductions in previous years were based on data obtained from AgSTAR Digests (EPA 2000, 2003b, 2006).
Errors were identified in the calculation of the sheep WMS distribution; population values for other states were
incorrectly distributed in the calculations. Correcting this error resulted in very small changes in N2O emissions
estimates from sheep.
Changes were made to the current calculations involving animal population data. Animal population data were
updated to reflect the final estimates reports from USDA NASS (USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c,
2000a, 2004a-e, 2006a-c, 2007a-d). The population data may differ from previous inventories because some values
changed due to USDA NASS review. For horses, state-level populations were estimated using the national FAO
population data (FAO 2007) and the state distributions from the 1992, 1997, and 2002 Census of Agriculture
(USDA 2005). The FAO horse population estimates for recent years increased dramatically between the 2005 and
2006 inventories, resulting in a much larger estimated horse population, and therefore greater greenhouse gas
emissions from this sector.
With these recalculations, CH4 emission estimates from manure management systems are slightly higher than
reported in the previous inventory for dairy cattle and swine, as well as horses for years 2001 through 2005. On
average, annual CH4 emission estimates are more than those of the previous inventory by about one percent.
N2O emission estimates from manure management systems have increased by approximately 30 percent for all years
of the current inventory compared to the previous inventory due to the change in calculation methodology, which
incorporates direct and indirect N2O emissions. The most significant changes in N2O emissions compared to the
previous inventory occurred in the poultry and swine sectors, whose emissions were approximately 70 percent
higher due to the inclusion of indirect N2O emissions.
Changes were made to the Cattle Enteric Fermentation Model that produces the VS estimates for all cattle groups
except bulls and calves. Refer to the Recalculations section in the Enteric Fermentation to see specific changes
made to the model.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Planned Improvements
The manure management inventory 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 inventory and CEFM are using
the same data sources and variables where appropriate.
The American Society of Agricultural Engineers proposed new standards for manure production characteristics in
2004 and finalized them in 2005. These data were investigated and evaluated for incorporation into future
estimates.
A method to better estimate anaerobic digester CH4 emission reductions will be investigated. This method would
include separating systems with anaerobic digesters from the total animal population before estimating CH4
emissions, and then estimating emissions from the digesters using the amount of biogas/CH4 collected and a 99
percent destruction efficiency.
The uncertainty analysis will be updated for in the future to more accurately assess uncertainty of emission
calculations. This update is necessary due to the extensive changes in emission calculation methodology in the
1990 through 2006 inventory, including estimation of emissions at the WMS level and the use of new calculations
and variables for indirect N2O emissions.
The current methodology for calculating runoff for indirect N2O emissions will be reevaluated. Currently runoff is
estimated at all manure management systems based on outdoor cattle operations. A new methodology may be
incorporated which takes into account more recent model runs from EPA's Office of Water.
In order to improve the efficiency of MCF calculations, MCFs will be calculated in a database instead of
spreadsheets in the next inventory. Calculating MCFs in a database will also increase the overall efficiency of CH4
emission estimates by linking directly to the database that calculates CH4 estimates.
6.3. Rice Cultivation (IPCC Source Category 4C)
Most of the world's rice, and all rice in the United States, is grown on flooded fields. When fields are flooded,
aerobic decomposition of organic material gradually depletes most of the oxygen present in the soil, causing
anaerobic soil conditions. Once the environment becomes anaerobic, CH4 is produced through anaerobic
decomposition of soil organic matter by methanogenic bacteria. As much as 60 to 90 percent of the CH4 produced
is oxidized by aerobic methanotrophic bacteria in the soil (some oxygen remains at the interfaces of soil and water,
and soil and root system) (Holzapfel-Pschorn et al. 1985, Sass et al. 1990). Some of the CH4is also leached away as
dissolved CH4 in floodwater that percolates from the field. The remaining un-oxidized CH4 is transported from the
submerged soil to the atmosphere primarily by diffusive transport through the rice plants. Minor amounts of CH4
also escape from the soil via diffusion and bubbling through floodwaters.
The water management system under which rice is grown is one of the most important factors affecting CH4
emissions. Upland rice fields are not flooded, and therefore are not believed to produce CH4. In deepwater rice
fields (i.e., fields with flooding depths greater than one meter), the lower stems and roots of the rice plants are dead,
so the primary CH4 transport pathway to the atmosphere is blocked. The quantities of CH4 released from deepwater
fields, therefore, are believed to be significantly less than 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 CH4to oxidize but also inhibits further CH4 production in soils.
All rice in the United States is grown under continuously flooded conditions; none is grown under deepwater
conditions. Mid-season drainage does not occur except by accident (e.g., due to levee breach).
Other factors that influence CH4 emissions from flooded rice fields include fertilization practices (especially the use
of organic fertilizers), soil temperature, soil type, rice variety, and cultivation practices (e.g., tillage, seeding, and
weeding practices). The factors that determine the amount of organic material available to decompose (i.e., organic
Agriculture 6-13
-------
fertilizer use, soil type, rice variety,5 and cultivation practices) are the most important variables influencing the
amount of CH4 emitted over the growing season; the total amount of CH4 released depends primarily on the amount
of organic substrate available. Soil temperature is known to be an important factor regulating the activity of
methanogenic bacteria, and therefore the rate of CH4 production. However, although temperature controls the
amount of time it takes to convert a given amount of organic material to CH4, that time is short relative to a growing
season, so the dependence of total emissions over an entire growing season on soil temperature is weak. The
application of synthetic fertilizers has also been found to influence CH4 emissions; in particular, both nitrate and
sulfate fertilizers (e.g., ammonium nitrate and ammonium sulfate) appear to inhibit CH4 formation.
Rice is cultivated in eight states: Arkansas, California, Florida, Louisiana, Mississippi, Missouri, Oklahoma, and
Texas.6 Soil types, rice varieties, and cultivation practices for rice vary from state to state, and even from farm to
farm. However, most rice farmers apply organic fertilizers in the form of residue from the previous rice crop, which
is left standing, disked, or rolled into the fields. Most farmers also apply synthetic fertilizer to their fields, usually
urea. Nitrate and sulfate fertilizers are not commonly used in rice cultivation in the United States. In addition, the
climatic conditions of Arkansas, southwest Louisiana, Texas, and Florida allow for a second, or ratoon, rice crop.
CH4 emissions from ratoon crops have been found to be considerably higher than those from the primary crop. This
second rice crop is produced from regrowth of the stubble after the first crop has been harvested. Because the first
crop's stubble is left 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 CH4in the United States (Table 6-9 and Table 6-10). In 2006, CH4 emissions
from rice cultivation were 5.9 Tg CO2 Eq. (282 Gg). Although annual emissions fluctuated unevenly between the
years 1990 and 2006, ranging from an annual decrease of 14 percent to an annual increase of 17 percent, there was
an overall decrease of 17 percent over the sixteen-year period, due to an overall decrease in primary crop area7
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.
Table 6-9: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990 |
5.1 i
2.1 |
0.7
+
1.0
0.4
0.1
+
0.6
2.1
+
+
1.1
0.9
7.1 I
1995 |
5.6 i
2.4 |
0.8
+
1.0
0.5
0.2
+
0.6
2.1
+
0.1 i
1.1 i
0.8 |
7.6 I
2000
5.5
2.5
1.0
+
0.9
0.4
0.3
+
0.4
2.0
+
0.1
1.3
0.7
7.5
2001
5.9
2.9
0.8
+
1.0
0.5
0.4
+
0.4
1.7
+
+
1.1
0.6
7.6
2002
5.7
2.7
0.9
+
1.0
0.5
0.3
+
0.4
1.1
+
+
0.5
0.5
6.8
2003
5.4
2.6
0.9
+
0.8
0.4
0.3
+
0.3
1.5
+
+
1.0
0.5
6.9
2004
6.0
2.8
1.1
+
1.0
0.4
0.3
+
0.4
1.6
+
+
1.1
0.5
7.6
2005
6.0
2.9
0.9
+
0.9
0.5
0.4
+
0.4
0.8
+
+
0.5
0.4
6.8
2006
5.1
2.5
0.9
+
0.6
0.3
0.4
+
0.3
0.9
+
+
0.5
0.4
5.9
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.
6 A 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.
The 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: 1990-2006
-------
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-10: CH4 Emissions from Rice Cultivation (Gg)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990i
241i
102
34
1
46i
21
7
+|
30
98
+|
2
52
45i
3391
\ 1995
! 265
114
40
2
I 48
! 24
10
| +
27
98
+
4
54
I 40
1 363
1 2000
| 260
120
47
2
41
I 19
14
j +
18
97
+
2
1 61
! 34
! 357
2001
283
138
40
1
46
22
18
+
18
81
+
2
52
27
364
2002
274
128
45
1
45
22
15
+
18
52
+
2
25
24
325
2003
255
124
43
+
38
20
15
+
15
73
+
2
50
22
328
2004
283
132
50
1
45
20
17
+
19
77
+
2
50
24
360
2005
287
139
45
1
45
22
18
+
17
39
1
+
22
17
326
2006
241
119
44
1
29
16
18
+
13
41
+
1
22
18
282
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
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).
The harvested rice areas for the primary and ratoon crops in each state are presented in Table 6-11. Primary crop
areas for 1990 through 2006 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 2007). Harvested rice areas in Florida, which are not reported by USDA, were obtained from: Tom
Schueneman (1999b, 1999c, 2000, 2001a) and Arthur Kirstein (2003, 2006), Florida agricultural extension agents;
Dr. Chris Deren (2002) of the Everglades Research and Education Centre at the University of Florida; Gaston
Cantens (2004, 2005), Vice President of Corporate Relations of the Florida Crystals Company; and Rene Gonzalez
(2007a), Plant Manager of Sem-Chi Rice Company. Harvested rice areas for Oklahoma, which also are not reported
by USDA, were obtained from Danny Lee of the Oklahoma Farm Services Agency (2003 through 2007). Acreages
for the ratoon crops were derived from conversations with the agricultural extension agents in each state. In
Arkansas, ratooning occurred only in 1998, 1999, 2005, and 2006, when the ratooned area was less than 1 percent
of the primary area (Slaton 1999 through 2001a; Wilson 2002 through 2007). In Florida, the ratooned area was 50
percent of the primary area from 1990 to 1998 (Schueneman 1999a), about 65 percent of the primary area in 1999
(Schueneman 2000), around 41 percent of the primary area in 2000 (Schueneman 200 la), about 60 percent of the
primary area in 2001 (Deren 2002), about 54 percent of the primary area in 2002 (Kirstein 2003), about 100 percent
of the primary area in 2003 (Kirstein 2004), about 77 percent of the primary area in 2004 (Cantens 2005), 0 percent
of the primary area in 2005 (there was no ratooning this year due to Hurricane Wilma), and about 28 percent of the
primary area in 2006 (Gonzalez 2007a). In Louisiana, the percentage of the primary area that was ratooned was
constant at 30 percent over the 1990 to 1999 period, increased to approximately 40 percent in 2000, returned to 30
percent in 2001, dropped to 15 percent in 2002, rose to 35 percent in 2003, returned to 30 percent in 2004, dropped
Agriculture 6-15
-------
to 13 percent in 2005 and increased to 20 percent in 2006 (Linscombe 1999, 2001a, 2002 through 2007; Bollich
2000). In Texas, the percentage of the primary area that was ratooned was constant at 40 percent over the 1990 to
1999 period, increased to 50 percent in 2000 due to an early primary crop, and then decreased to 40 percent in 2001,
37 percent in 2002, 38 percent in 2003, 35 percent in 2004, 27 percent in 2005 and increased to 39 percent in 2006
(Klosterboer 1999, 2000, 2001a, 2002, 2003; Stansel 2004, 2005; Texas Agricultural Experiment Station 2006,
2007). California, Mississippi, Missouri, and Oklahoma have not ratooned rice over the period 1990 through 2006
(Guethle 1999, 2000, 2001a, 2002 through 2007; Lee 2003 through 2007; Mutters 2002 through 2005; Street 1999
through 2003; Walker 2005, 2007).
Table 6-11: Rice Areas Harvested (Hectares)
State/Crop
Arkansas
Primary
Ratoon*
California
Florida
Primary
Ratoon
Louisiana
Primary
Ratoon
Mississippi
Missouri
Oklahoma
Texas
Primary
Ratoon
Total
Primary
Total
Ratoon
Total
1990
485,633
0
159,854
4,978
2,489
220,558
66,168
101,174
32,376
617
142,857
57,143
1,148,047
125,799
1,273,847
19951
542,291 1
01
188,1831
9,7131
4'856I
230,6761
69,2031
116,5521
45,3261
3641
128,693 1
51,4771
1,261,7961
125,5361
1,387,3331
1 2000
1 570,619
1 o
1 221,773
1 7,801
1 3'193
1 194,253
1 77,701
1 88,223
i 68,393
1 283
1 86,605
1 43,302
1 1,237,951
1 124,197
1 1,362,148
2001
656,010
0
190,611
4,562
2,752
220,963
66,289
102,388
83,772
265
87,414
34,966
1,345,984
104,006
1,449,991
2002
608,256
0
213,679
5,077
2,734
216,512
32,477
102,388
73,654
274
83,367
30,846
1,303,206
66,056
1,369,262
2003
588,830
0
205,180
2,369
2,369
182,113
63,739
94,699
69,203
53
72,845
27,681
1,215,291
93,790
1,309,081
2004
629,300
0
238,770
3,755
2,899
215,702
64,711
94,699
78,915
158
88,223
30,878
1,349,523
98,488
1,448,011
2005
661,675
662
212,869
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
* Arkansas ratooning occurred only in 1998, 1999, 2005, and 2006.
Note: Totals may not sum due to independent rounding.
To determine what CH4 emission factors should be used for the primary and ratoon crops, CH4 flux information
from rice field measurements in the United States was collected. Experiments which involved atypical or
nonrepresentative management practices (e.g., the application of nitrate or sulfate fertilizers, or other substances
believed to suppress CH4 formation), as well as experiments in which measurements were not made over an entire
flooding season or floodwaters were drained mid-season, were excluded from the analysis. The remaining
experimental results8 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 et al. 1992; Sass et al. 1991a,
1991b) were averaged to derive an emission factor for the primary crop, and the experimental results from ratoon
crops with added synthetic fertilizer (Lindau and Bollich 1993, Lindau et al. 1995) were averaged to derive an
emission factor for the ratoon crop. The resultant emission factor for the primary crop is 210 kg CHVhectare-
8 In some of these remaining experiments, measurements from individual plots were excluded from the analysis because of the
aforementioned reasons. In addition, one measurement from the ratooned fields (i.e., the flux of 2.041 g/m /day in Lindau and
Bollich 1993) was excluded, because this emission rate is unusually high compared to other flux measurements in the United
States, as well as IPCC (2006) default emission factors.
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
season, and the resultant emission factor for the ratoon crop is 780 kg CH^hectare-season.
Uncertainty
The largest uncertainty in the calculation of CH4 emissions from rice cultivation is associated with the emission
factors. Seasonal emissions, derived from field measurements in the United States, vary by more than one order of
magnitude. This inherent variability is due to differences in cultivation practices, in particular, fertilizer type,
amount, and mode of application; differences in cultivar type; and differences in soil and climatic conditions. A
portion of this variability is accounted for by separating primary from ratooned areas. However, even within a
cropping season or a given management regime, measured emissions may vary significantly. Of the experiments
used to derive the emission factors applied here, primary emissions ranged from 22 to 479 kg CHVhectare-season
and ratoon emissions ranged from 481 to 1,490 kg CH4/hectare-season. The uncertainty distributions around the
primary and ratoon emission factors were derived using the distributions of the relevant primary or ratoon emission
factors available in the literature and described above. Variability about the rice emission factor means was not
normally distributed for either primary or ratooned crops, but rather skewed, with a tail trailing to the right of the
mean. A lognormal statistical distribution was, therefore, applied in the Tier 2 Monte Carlo analysis.
Other sources of uncertainty include the primary rice-cropped area for each state, percent of rice-cropped area that
is ratooned, and the extent to which flooding outside of the normal rice season is practiced. Expert judgment was
used to estimate the uncertainty associated with primary rice-cropped area for each state at 1 to 5 percent, and a
normal distribution was assumed. Uncertainties were applied to ratooned area by state, based on the level of
reporting performed by the state. No uncertainties were calculated for the practice of flooding outside of the normal
rice season because CH4 flux measurements have not been undertaken over a sufficient geographic range or under a
broad enough range of representative conditions to account for this source in the emission estimates or its associated
uncertainty.
To quantify the uncertainties for emissions from rice cultivation, a Monte Carlo (Tier 2) uncertainty analysis was
performed using the information provided above. The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 6-12. Rice cultivation CH4 emissions in 2006 were estimated to be between 2.1 and 12.8 Tg
CO2 Eq. at a 95 percent confidence level, which indicates a range of 65 percent below to 117 percent above the
actual 2006 emission estimate of 5.9 Tg CO2 Eq.
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg CO2 Eq. and
Percent)
Source
Gas
2006 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Rice Cultivation
CH4
5.9
2.1 12.8 -65% 117%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
QA/QC and Verification
A source-specific QA/QC plan for rice cultivation was developed and implemented. This effort included a Tier 1
analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures focused on comparing trends across years,
states, and cropping seasons to attempt to identify any outliers or inconsistencies. No problems were found.
Recalculations Discussion
When compiling the previous inventory, no data on area harvested and percent of area ratooned in Florida were
available for 2005, and consequently 2004 data was held constant. This year, Gonzalez (2007a) was able to provide
data for 2005 as well as 2006, resulting in an decrease of about 0.6 percent in the estimate for 2005.
Agriculture 6-17
-------
6.4. Agricultural Soil Management (IPCC Source Category 4D)
Nitrous oxide is produced naturally in soils through the microbial processes of nitrification and denitrification.9 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).10 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.11 Indirect emissions of N2O occur through two pathways: (1) volatilization and subsequent
atmospheric deposition of applied N,12 and (2) surface runoff and leaching of applied N into groundwater and
surface water. Direct emissions from agricultural lands (i.e., croplands and grasslands) are included in this section,
while direct emissions from forest lands and settlements are presented in the Land Use, Land-Use Change, and
Forestry chapter. However, indirect N2O emissions from all sources (cropland, grassland, forest lands, settlements,
and managed manure) are reported in this chapter.
Figure 6-2: Agricultural Sources and Pathways of N that Result in N2O Emissions
Agricultural soils produce the majority of N2O emissions in the United States. Estimated emissions from this source
in 2006 were 265.0 Tg CO2 Eq. (855 Gg N2O) (see Table 6-13 and Table 6-14). Annual N2O emissions from
agricultural soils fluctuated between 1990 and 2006, although overall emissions were 1.6 percent lower in 2006 than
in 1990. Year-to-year fluctuations are largely a reflection of annual variation in weather patterns, synthetic fertilizer
use, and crop production. On average, cropland accounted for approximately 64 percent of total direct emissions,
while grassland accounted for approximately 36 percent. Estimated direct and indirect N2O emissions by sub-
source category are provided in Table 6-15 and Table 6-16.
Table 6-13: N2O Emissions from Agricultural Soils (Tg CO2 Eq.)
Activity
Direct
Cropland
Grassland
1990
218.3
130.9
87.4
1 1995!
! 210.3!
! 133. lj
| 77.2i
1 2000
1 216.0
I 142.0
j 74.0
2001
222.3
147.6
74.8
2002
217.7
137.1
80.6
2003
202.2
130.2
72.0
2004
208.6
136.1
72.5
2005
217.9
140.0
77.9
2006
214.7
138.9
75.8
9 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 nitrogen gas
(N2)- Nitrous oxide is a gaseous intermediate product in the reaction sequence of denitrification, which leaks from microbial
cells into the soil and then into the atmosphere. Nitrous oxide is also produced during nitrification, although by a less well-
understood mechanism (Nevison 2000).
10 Drainage and cultivation of organic soils in former wetlands enhances mineralization of N-rich organic matter, thereby
enhancing N2O emissions from these soils.
1! Asymbiotic N fixation is the fixation of atmospheric N2 by bacteria living in soils that do not have a direct relationship with
plants.
12 These processes entail volatilization of applied N as ammonia (NH3) and oxides of N (NOX), transformation of these gases
within the atmosphere (or upon deposition), and deposition of the N primarily in the form of particulate ammonium (NH/t), nitric
acid (HNO3), and NOX.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Indirect (All Land-Use
Types)
Cropland
Grassland
Forest Land
Settlements
Total
51.1
30.1
20.6
+
0.3
269.4
54.
30,
23,
0,
! o.
1 264.
,5
.5
.6
.1
.4i
,8!
46.0
28.4
17.1
0.1
0.4
1 262.1
54.7
28.9
25.2
0.1
0.5
277.0
44.3
24,
18,
0.
0,
262.
.8
.9
1
.5
0
45.0
27.8
16.7
0.1
0.5
247.3
38.3
21.6
16.1
0.1
0.5
246.9
47.3
28.4
18.3
0.1
0.5
265.2
50.3
30.2
19.5
0.1
0.5
265.0
+ Less than 0.05 Tg CO2 Eq.
Table 6-14: N2O Emissions from Agricultural Soils (Gg N2O)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use
Types)
Cropland
Grassland
Forest Land
Settlements
Total
1990
704
422
282
165
97
67
+
1
869
1 1995!
1 678!
! 429J
I 249!
1 176!
1 98!
! 76!
1 +1
1 1!
1 854!
! 2000
1 697
I 458
I 239
149
92
55
+
1
1 845
2001
717
476
241
176
93
81
+
2
894
2002
702
442
260
143
80
61
+
2
845
2003
652
420
232
145
90
54
+
2
798
2004
673
439
234
124
70
52
+
2
796
2005
703
452
251
153
92
59
+
2
855
2006
693
448
244
162
97
63
+
2
855
+ Less than 0.5 Gg N2O
Table 6-15: Direct N2O Emissions from Agricultural Soils by Land-Use and N Input (Tg CO2 Eq.
Activity
1990
1995!
2000 2001 2002 2003 2004 2005 2006
Cropland
Mineral Soils
Synthetic Fertilizer
Organic Amendments3
Residue Nb
Otherc
Organic Soils
Grassland
Synthetic Fertilizer
PRP Manure
Managed Manured
Sewage Sludge
Residue Nb
Otherc
Total
130.9
128.1
51.3
9.4
9.0
58.4
2.8
87.4
3.0
19.8
0.6
0.3
12.5
51.3
218.3
133.1
130.3
55.3
10.1
9.6
55.2
2.9 1
77.2
2.6
18.4
0.5
0.3
11.4
44.0
1 210.3!
| 142.0
139.1
55.8
10.2
10.2
62.8
2.9
74.0
2.5
19.6
0.5
0.4
10.4
40.7
! 216.0
147.6
144.7
57.2
11.1
9.7
66.8
2.9
74.8
2.6
18.5
0.5
0.4
10.9
41.8
222.3
137.1
134.3
54.2
10.7
8.9
60.4
2.9
80.6
2.7
23.3
0.5
0.4
10.8
42.8
217.7
130.2
127.4
50.4
10.0
10.4
56.5
2.9
72.0
2.5
19.2
0.5
0.4
10.3
39.2
202.2
136.1
133.2
55.3
10.7
9.2
58.1
2.9
72.5
2.5
20.9
0.5
0.5
10.5
37.6
208.6
140.0
137.1
53.6
10.4
9.6
63.6
2.9
77.9
2.5
18.9
0.5
0.5
11.2
44.2
217.9
138.9
136.1
53.6
10.7
10.1
61.7
2.9
75.8
2.6
19.6
0.5
0.5
10.4
42.2
214.7
a Organic amendment inputs include managed manure amendments and other commercial organic fertilizer (i.e., dried blood,
dried manure, tankage, compost, and other).
b Residue N inputs include unharvested fixed N from legumes as well as crop residue N.
0 Other N inputs include mineralization from decomposition of soil organic matter as well as asymbiotic fixation of N from the
atmosphere.
d Accounts for managed manure that is applied to grassland soils.
Table 6-16: Indirect N2O Emissions from all Land Use Types (Tg CO2 Eq.)
Activity
Cropland
Volatilization and Atm.
Deposition
Surface Leaching & Run-Off
Grassland
1990!
30. li
5.8|
24.3!
20.6
1995
30.5
6.1
24.4
23.6
1 2000
! 28.4
! 6.7
I 21.7
17.1
2001
28.9
6.1
22.8
25.2
2002
24.8
6.0
18.8
18.9
2003
27.8
6.4
21.4
16.7
2004
21.6
6.1
15.5
16.1
2005
28.4
6.6
21.8
18.3
2006
30.2
6.5
23.7
19.5
Agriculture 6-19
-------
Volatilization and Atm.
Deposition
Surface Leaching & Run-Off
Forest Land
Volatilization and Atm.
Deposition
Surface Leaching & Run-Off
Settlements
Volatilization and Atm.
Deposition
Surface Leaching & Run-Off
Total
10.7
9.9
+
+
+
0.3
0.1
0.2
51.ll
10.2
13.4
0.1
+
+
0.4
0.1
0.3
54.5
9.3
7.8
0.1
+
0.1
0.4
0.1
0.3
1 46.0
9.4
15.8
0.1
+
0.1
0.5
0.2
0.3
54.7
9.3
9.6
0.1
+
0.1
0.5
0.2
0.3
44.3
9.4
7.2
0.1
+
0.1
0.5
0.2
0.3
45.0
9.2
6.9
0.1
+
0.1
0.5
0.2
0.3
38.3
10.1
8.2
0.1
+
0.1
0.5
0.2
0.3
47.3
9.4
10.1
0.1
+
0.1
0.5
0.2
0.3
50.3
+ Less than 0.05 Tg CO2 Eq.
Figure 6-3 through Figure 6-6 show regional patterns in N2O emissions for direct sources and regional patterns of N
losses leading to indirect N2O emissions, respectively, for major crops and grasslands across the United States.
Direct N2O emissions tend to be high in the Corn Belt (Illinois, Iowa, Indiana, Ohio, southern Minnesota, and
eastern Nebraska). A large portion of the land in many of these states is covered with highly fertilized corn and
with N-fixing soybean cropping. Emissions are also high in North Dakota, Kansas, and Texas, primarily from
irrigated cropping and dryland wheat cropping. 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 in many states 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 for 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, coarse-textured soils facilitate nitrification and moderate direct
emissions in grasslands in some southeastern states, but indirect emissions are relatively high in Florida and Georgia
grasslands due to high rates of N volatilization and NO3 leaching in coarse-textured soils.
Figure 6-3: Major Crops, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-
2006 (Tg CO2 Eq./state/year)
Figure 6-4: Grasslands, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-2006
(Tg CO2 Eq./state/year)
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT
Model, 1990-2006 (Gg N/state/year)
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT
Model, 1990-2006 (Gg N/state/year)
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Methodology
The Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) divide the Agricultural Soil Management
source category into three components: (1) direct emissions from agricultural soils due to N additions to cropland
and grassland mineral soils, planting of legumes on cropland and grassland soils, and drainage and cultivation of
organic cropland soils; (2) direct emissions from soils due to the deposition of manure by livestock on PRP
grasslands; and (3) indirect emissions from soils and water due to N additions and manure deposition to soils that
leads to volatilization, leaching, or runoff of N and subsequent conversion to N2O. Moreover, the 2006 IPCC
Guidelines (IPCC 2006) recommend reporting total emissions from managed lands, and, therefore, this chapter
includes estimates for direct emissions due to asymbiotic fixation of N from the atmosphere13 and decomposition of
soil organic matter and litter.
The methodology used to estimate emissions from agricultural soil management in the United States is based on a
combination of IPCC Tier 1 and 3 approaches. A Tier 3, process-based model (DAYCENT) was used to estimate
direct emissions from major crops on mineral (i.e., non-organic) soils; as well as most of the direct emissions from
grasslands. The Tier 3 approach is more refined for estimating N2O emissions in the United States, accounting for
more of the environmental and management influences on soil N2O emissions than the IPCC Tier 1 method (see
Box 6-1 for further elaboration). The Tier 1 IPCC methodology was used to estimate (1) direct emissions from non-
major crops on mineral soils, (2) the portion of the grassland direct emissions that were not estimated with the Tier
3 DAYCENT model, and (3) direct emissions from drainage and cultivation of organic cropland soils. The Tier 1
approach was based on the 2006 IPCC Guidelines (IPCC 2006). Indirect emissions were also estimated with a
combination of DAYCENT and the IPCC Tier 1 method.
Several recommendations from IPCC (2006) have been adopted that are considered improvements over previous
IPCC methods, including: (1) estimating the contribution of N from crop residues to indirect soil N2O emissions, (2)
adopting a revised emission factor for direct N2O emissions, (3) removing double counting of emissions from N-
fixing crops associated with the symbiotic and crop residue N input categories, (4) using revised crop residue
statistics to compute N inputs to soils based on harvest yield data, and (5) accounting for indirect as well as direct
emissions from N made available via mineralization of soil organic matter and litter, in addition to asymbiotic
fixation (i.e., computing total emissions from managed land). IPCC (2006) recommends reporting all emissions
from managed lands, largely because management affects all processes leading to soil N2O emissions. Agronomic
practices, particularly tillage, have a pervasive impact on soil processes. 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. 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.
[BEGIN BOX]
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions
13 N inputs from asymbiotic N fixation are not directly addressed in 2006 IPCC Guidelines, but are a component of the total
emissions from managed lands and are included in the Tier 3 approach developed for this Inventory.
Agriculture 6-21
-------
The Tier 1 approach (IPCC 2006) is based on multiplying activity data on different N sources (e.g., synthetic
fertilizer, manure, N fixation, etc.) by the appropriate default IPCC emission factors to estimate N2O emissions on a
source-by-source basis. 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, it is necessary to know the amount of N inputs and also the conditions under which the
anthropogenic activity is increasing mineral N in a soil profile. The Tier 1 approach requires a minimal amount of
activity data, readily available in most countries (e.g., total N applied to crops); calculations are simple; and the
methodology is highly transparent. The Tier 3 approach is thought to produce more accurate estimates; it accounts
for land-use and management impacts and their interaction with environmental factors (i.e., weather patterns and
soil characteristics), which may enhance or dampen anthropogenic influences. However, the Tier 3 approach
requires more refined activity data (e.g., crop-specific N amendment rates, daily weather, soil types, etc.) and
considerable computational resources and programming expertise. The Tier 3 methodology is less transparent, and
thus it is critical to evaluate the output of Tier 3 methods with 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 N2O
emissions only during that year and cannot be stored in soils and contribute to N2O emission in subsequent years.
This is a simplifying assumption that is likely to create bias in estimated N2O emissions for a specific year. In
contrast, the process-based model used in the Tier 3 approach includes such legacy effects when N is mineralized
from soil organic matter and emitted as N2O during subsequent years.
[END BOX]
Direct N2O Emissions from Cropland Soils
Major Crop Types on Mineral Cropland Soils
The DAYCENT ecosystem model (Del Grosso et al. 2001, Parton et al. 1998) was used to estimate direct N2O
emissions from mineral cropland soils that are managed for production of major crops—specifically corn, soybeans,
wheat, alfalfa hay, other hay, sorghum, and cotton—representing approximately 90 percent of total croplands in the
United States. DAYCENT simulated crop growth, soil organic matter decomposition, greenhouse gas fluxes, and
key biogeochemical processes affecting N2O emissions, and the simulations were driven by model input data
generated from daily weather records (Thornton et al. 1997, 2000; Thornton and Running 1999), land management
surveys (see citations below), and soil physical properties determined from national soil surveys (Soil Survey Staff
2005).
DAYCENT simulations were conducted for each major crop at the county scale in the United States. 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. However, land management data (e.g., timing of planting, harvesting,
intensity of cultivation) were only available at the agricultural region level as defined by the Agricultural Sector
Model (McCarl et al. 1993). There are 63 agricultural regions in the contiguous United States, and most states
correspond to one region, except for those states with greater heterogeneity in agricultural practices, where there are
further subdivisions. While several cropping systems were simulated for each county in an agricultural region with
county-level weather and soils data, the model parameters that determined the influence of management activities on
soil N2O emissions (e.g., when crops were planted/harvested) did not differ among the counties in an agricultural
region. Consequently, the results will best represent emissions at the regional (i.e., state) and national levels due to
the scale of management data.
Nitrous oxide emission estimates from DAYCENT are influenced by N additions, crop type, irrigation, and other
factors in aggregate, and, therefore, it is not possible to partition N2O emissions by anthropogenic activity directly
from model outputs (e.g., N2O emissions from synthetic fertilizer applications cannot be distinguished from those
resulting from manure applications). Nitrous oxide emissions from managed agricultural lands are the result of
interactions 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
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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). 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 D AYCENT model. The percentages were then multiplied by the total 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 by source of N, which is
valuable for reporting purposes and is similar to the IPCC (2006) Tier 1 method (which assumes the rate of direct
N2O emissions does not vary by source).
D AYCENT was used to estimate direct N2O emissions due to mineral N available from: (1) the application of
synthetic fertilizers, (2) the application of livestock manure, (3) the retention of crop residues (i.e., leaving residues
in the field after harvest instead of burning or collecting residues), and (4) mineralization of soil organic matter and
litter, in addition to asymbiotic fixation. This last source is generated internally by the DAYCENT model. For the
first three practices, annual increases in soil mineral N due to anthropogenic activity were obtained or derived from
the following sources:
• Crop-specific N-fertilization rates: Data sources for fertilization rates include Alexander and Smith (1990),
Anonymous (1924), Battaglin and Goolsby (1994), Engle and Makela (1947), ERS (1994, 2003), Fraps and
Asbury (1931), Ibach and Adams (1967), Ibach et al. (1964), NFA (1946), NRIAI (2003), Ross and Mehring
(1938), Skinner (1931), Smalley et al. (1939), Taylor (1994), USDA (1966, 1957, 1954, 1946). Information on
fertilizer use and rates by crop type for different regions of the United States were obtained primarily from the
USDA Economic Research Service Cropping Practices Survey (ERS 1997) with additional data from other
sources, including the National Agricultural Statistics Service (NASS 1992, 1999, 2004).
• Managed manure production and application to croplands and grasslands: Manure N amendments applied to
croplands and grasslands (not including PRP manure) were determined using USDA Manure N Management
Databases for 1997 (Kellogg et al. 2000; Edmonds et al. 2003). 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 by first determining the population of animals that were on feedlots or otherwise housed in order to
collect and manage the manure. Annual animal population data for all livestock types, except horses and goats,
were obtained for all years from the U.S. Department of Agriculture-National Agricultural Statistics Service.
Population data used for cattle, swine, and sheep were downloaded from the USDA NASS Population
Estimates Database (USDA 2007a). Poultry population data were obtained from USDA NASS reports (USDA
1995a, 1995b, 1998a, 1999, 2004a, 2004b, 2006a, 2006b, 2007b, 2007c). Horse population data were obtained
from the FAOSTAT database (FAO 2007). Goat population data for 1992, 1997, and 2002 were obtained from
the Census of Agriculture (USDA 2005); these data were interpolated and extrapolated to derive estimates for
the other years. Information regarding the poultry turnover (i.e., slaughter) rate was obtained from state Natural
Resource Conservation Service personnel (Lange 2000). Additional population data for different farm size
categories for dairy and swine were obtained from the 1992, 1997, and 2002 Census of Agriculture (USDA
2005). Once the animal populations for each livestock type and management system were estimated, these
populations were multiplied by a typical animal mass constant (USDA 1996, ASAE 1999; NRC 2000, ERG
2003, EPA 1992, Safley 2000) to derive total animal mass for each animal type in each management system.
Total Kjeldahl N14 excreted per year for each livestock type and management system was then calculated using
daily rates of N excretion per unit of animal mass (USDA 1996, ASAE 1999). The annual amounts of Kjeldahl
N were then summed over all livestock types and management systems to derive estimates of the annual
managed manure N produced. Nitrogen available for application was estimated for managed systems based on
the total amount of N produced in manure minus N losses and including the addition of N from bedding
14 Total Kjeldahl N is a measure of organically bound N and ammonia N in both solid and liquid wastes.
Agriculture 6-23
-------
materials. Nitrogen losses include direct nitrous oxide emissions, volatilization of ammonia and NOX, and
runoff and leaching; more information on these losses is available in Annex 3.10, Manure Management.
Animal-specific bedding factors were set equal to IPCC default factors (IPCC 2006). The estimated amount of
manure available for application was adjusted for the small percent of poultry manure used for cattle feed
between 1990 and 2002 (Carpenter 1992, Carpenter and Starkey 2007). The remaining manure N that was not
applied to major crops and grassland was assumed to be applied to non-major crop types. Frequency and rates
of manure application to cropland during the inventory period were estimated from data compiled by the USDA
Natural Resources Conservation Service for 1997 (Edmonds et al. 2003), with adjustments based on managed
manure N excretion in other years of the inventory.
• Retention of crop residue, N mineralization from soil organic matter, and asymbiotic N fixation from the
atmosphere: The IPCC approach considers this information as separate activity data. However, they are not
treated as separate activity data in DAYCENT simulations because residue production, N fixation,
mineralization of N from soil organic matter, and asymbiotic fixation are internally generated by the model. In
other words, DAYCENT accounts for the influence of N fixation, mineralization of N from soil organic matter,
and retention of crop residue on N2O emissions, but these are not model inputs. The total input of N from these
sources is determined during the model simulations.
• Historical and modern crop rotation and management information (e.g., timing and type of cultivation, timing
of planting/harvest, etc.): These activity data were derived from Kurd (1930, 1929), Latta (1938), Iowa State
College Staff Members (1946), Bogue (1963), Hurt (1994), USDA (20041), USDA (2000b) as extracted by Eve
(2001) and revised by Ogle (2002), CTIC (1998), Piper et al. (1924), Hardies and Hume (1927), Holmes (1902,
1929), Spillman (1902, 1905, 1907, 1908), Chilcott (1910), Smith (1911), Kezer (ca. 1917), Hargreaves (1993),
ERS (2002), Warren (1911), Langston et al. (1922), Russell et al. (1922), Elliott and Tapp (1928), Elliott
(1933), Ellsworth (1929), Garey (1929), Hodges et al. (1930), Bonnen and Elliott (1931), Brenner et al. (2002,
2001), and Smith et al. (2002).
DAYCENT simulations produced per-area estimates of N2O emissions (g N2O-N m"2) for major crops, which were
multiplied by the cropland area data to obtain county-scale emission estimates. Cropland area data were from
NASS (USDA 2006g). The emission estimates by reported crop areas in the county were scaled to the regions, and
the national estimate was calculated by summing results across all regions. DAYCENT is sensitive to actual
interannual variability in weather patterns and other controlling variables, so emissions associated with individual
activities vary through time even if the management practices remain the same (e.g., if N fertilization remains the
same for two years). In contrast, Tier 1 methods do not capture this variability and rather have a linear, monotonic
response that depends solely on management practices. DAYCENT's ability to capture these interactions between
management and environmental conditions produces more accurate estimates of N2O emissions than the Tier 1
method.
Non-Major Crop Types on Mineral Cropland Soils
The Tier 1 methodology (IPCC 2006) 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 which were not included in the DAYCENT 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
other commercial organic fertilizers;15 and (3) the retention of above- and below-ground crop residues. Non-
manure organic amendments were not included in the DAYCENT simulations because county-level data were not
available and this source of fertilizer is a very small portion of total organic amendments. Consequently, non-
manure organic amendments, as well as manure amendments not included in the DAYCENT simulations, were
15 Other commercial organic fertilizers include manure applied to non-major crops, dried blood, dried manure, tankage, compost,
other, but excludes sewage sludge that is used as commercial fertilizer.
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
included in the Tier 1 analysis. The following sources were used to derive activity data.
• A process-of-elimination approach was used to estimate 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 on non-major crops.
• A process-of-elimination approach was used to estimate manure N additions for non-major crops, because 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 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, 1992a, 1993, 1994; AAPFCO
1995 through 2000a, 2000b, 2002 through 2007).
• Crop residue N was derived by combining amounts of above- and below-ground biomass, which were
determined based on crop production yield statistics (USDA 1994a, 1998b, 2003, 2005i, 2006b, 2007), dry
matter fractions (IPCC 2006), linear equations to estimate above-ground biomass given dry matter crop yields
(IPCC 2006), ratios of below-to-above-ground biomass (IPCC 2006), and N contents of the residues (IPCC
2006).
The total increase in soil mineral N from applied fertilizers and crop residues was multiplied by the IPCC (2006)
default emission factor (IPCC 2006) to derive an estimate of direct N2O emissions from non-major crop types.
Drainage and Cultivation of Organic Cropland Soils
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 Natural
Resources Inventory (NRI) (USDA 2000b, as extracted by Eve 2001 and amended by Ogle 2002), using
temperature and precipitation data from Daly et al. (1994, 1998) to subdivide areas into temperate and tropical
climates. Data were available for 1982, 1992 and 1997, which were linearly interpolated and extrapolated to
estimate areas for the other years in the inventory time series. 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 N2O Emissions from Grassland Soils
As with N2O from croplands, the Tier 3 process-based DAYCENT model and Tier 1 method described in the IPCC
(2006) guidelines were combined to estimate emissions from grasslands. Grasslands include pastures and
rangelands used for grass forage production, where the primary use is livestock grazing. Rangelands are typically
extensive areas of native grasslands that are not intensively managed, while pastures are often seeded grasslands,
possibly following tree removal, which may or may not be improved with practices such as irrigation and
interseeding legumes.
DAYCENT was used to simulate county-scale N2O emissions from grasslands resulting from manure deposited by
livestock directly onto the pasture (i.e., PRP manure, which is simulated internally within the model), N fixation
from legume seeding, managed manure amendments (i.e., manure other than PRP manure), and synthetic fertilizer
application. The simulations used the same weather, 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 Annex 3.11. Other N inputs were simulated
Agriculture 6-25
-------
within the DAYCENT framework, including N input from mineralization due to decomposition of soil organic
matter and plant litter, as well as asymbiotic fixation of N from the atmosphere and atmospheric N deposition.
DAYCENT simulations produced per-area estimates of N2O emissions (g N2O-N m"2) for pasture and rangelands,
which were multiplied by the reported pasture and rangeland areas in the county. Grassland area data were obtained
from the NRI (USDA 2000b). The 1997 NRI area data for pastures and rangeland were aggregated to the county
level to estimate the grassland areas for 1995 to 2006, and the 1992 NRI pasture and rangeland data were
aggregated to the county level to estimate areas from 1990 to 1994. The county estimates were scaled to the 63
agricultural regions, and the national estimate was calculated by summing results across all regions.
Manure N deposition from grazing animals is modeled internally within DAYCENT. Comparisons with estimates
of total manure deposited on PRP (see Annex 3.11) showed that DAYCENT accounted for approximately 73
percent of total PRP manure. The remainder of the PRP manure N excretions were assumed to be excreted on
federal grasslands (i.e., DAYCENT simulations were only conducted for privately-owned grasslands), and the N2O
emissions were estimated using the Tier 1 method with IPCC default emission factors (IPCC 2006).
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 NEBRA (2007). Sewage sludge data on soil
amendments in agricultural lands were only available at the national scale, and it was not possible to associate
application with specific soil conditions and weather at the county scale. Consequently, emissions from sewage
sludge were also estimated using the Tier 1 method with IPCC default emission factors (IPCC 2006).
Total Direct N2O Emissions from Cropland and Grassland Soils
Emission estimates from DAYCENT and the IPCC method were summed to provide total national emissions for
grasslands in the United States. Annual direct emissions from major and non-major crops on mineral cropland soils,
from drainage and cultivation of organic cropland soils, and from grassland soils were summed to obtain total direct
N2O emissions from agricultural soil management (see Table 6-13 and Table 6-14).
Indirect N2O 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 or organic amendments (e.g., manure, sewage sludge)
and deposition of PRP manure N made available from mineralization of soil organic matter and asymbiotic fixation
also contributes to volatilized N emissions. Through atmospheric deposition, volatilized N can be returned to soils,
and a portion is emitted to the atmosphere as N2O. The second pathway occurs via leaching and runoff of soil N
(primarily in the form of nitrate [NO3~]) that was made available through anthropogenic activity on managed lands,
mineralization of soil organic matter, asymbiotic fixation, and atmospheric deposition. The nitrate is subject to
denitrification in water bodies, which leads to additional N2O emissions. Regardless of the eventual location of the
indirect 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 N2O Emissions from Atmospheric Deposition of Volatilized N from Managed Soils
Similarly to the direct emissions calculation, several approaches were combined to estimate the amount of applied N
that was transported from croplands, grasslands, forest lands, and settlements, through volatilization. DAYCENT
was used to simulate the amount of N transported from land areas whose direct emissions were simulated with
DAYCENT (i.e., major croplands and most grasslands), while the Tier 1 method was used for areas that were not
simulated with DAYCENT (i.e., non-major croplands, sewage sludge application on grasslands, PRP manure N
excretion on federal grasslands) (IPCC 2006). The IPCC (2006) default emission factor was used to estimate
indirect N2O emissions associated with the amount of volatilized N (Table 6-16).
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Indirect N2O from Leaching/Runoff
As in the calculations of indirect emissions from volatilized N, several approaches were combined to estimate the
amount of applied N that was transported from croplands, grasslands, forest lands, and settlements through leaching
and surface runoff into water bodies. DAYCENT was used to simulate the amount of N transported from major
cropland types and most grasslands. N transport from all other areas (i.e., non-major croplands, sewage sludge
amendments on grasslands, PRP manure N excreted on federal grasslands, in addition to N inputs on settlements
and forest lands) was estimated using the IPCC (2006) default factors for the amount of N subject to leaching and
runoff from mineral fertilizer, manure, above- and below-ground crop residues, soil organic matter decomposition
and asymbiotic fixation. The IPCC (2006) default emission factor was used to estimate indirect N2O emissions
associated with N losses through leaching and runoff (Table 6-16).
Uncertainty
Uncertainty was estimated differently for each of the following four 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 not calculated by DAYCENT, and
(4) indirect emissions not calculated by DAYCENT.
Uncertainties from the Tier 1 and Tier 3 estimates were combined using simple error propagation (IPCC 2006), and
the results are summarized in Table 6-17. Agricultural direct soil N2O emissions in 2006 were estimated to be
between 191.7 and 238.9 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 11 percent below
and 11 percent above the 2006 emission estimate of 214.7 Tg CO2 Eq. The indirect soil N2O emissions in 2006
were estimated to range from 28.0 to 113.2 Tg CO2 Eq. at a 95 percent confidence level, indicating an uncertainty
of 44 percent below and 125 percent above the 2006 emission estimate of 50.3 Tg CO2 Eq.
Table 6-17: Quantitative Uncertainty Estimates of N2O Emissions from Agricultural Soil Management in 2006 (Tg
CO2 Eq. and Percent)
2006 Emission Uncertainty Range Relative to Emission
Source Gas Estimate Estimate
(TgC02Eq.) (TgC02Eq.) (%)
Direct Soil N2O Emissions N2O
Indirect Soil N2O Emissions N2O
Lower
Bound
214.7 191.7
50.3 28.0
Upper
Bound
238.9
113.2
Lower
Bound
-11%
-44%
Upper
Bound
11%
125%
Note: Due to lack of data, uncertainties in areas for major crops, managed manure N production and PRP manure N production
are currently treated as certain.
QA/QC and Verification
For quality control, DAYCENT results for N2O emissions and NO3 leaching were compared with field data
representing various cropped/grazed systems, soils types, and climate patterns (Del Grosso et al. 2005). N2O
measurement data were available for seven sites in the United States and one in Canada, representing 25 different
combinations of fertilizer treatments and cultivation practices. DAYCENT estimates of N2O emissions were closer
to measured values at all sites except for Colorado irrigated corn (Figure 6-7). In general, IPCC Tier 1 methodology
tends to over-estimate when observed values are low and under-estimate 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 0.73 and 0.96 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 also an improvement over the IPCC Tier 1 method (see
additional information in Annex 3.11).
Figure 6-7: Comparison of measured emissions at field sites with modeled emissions using the DAYCENT
Agriculture 6-27
-------
simulation model
Spreadsheets containing input data and PDFs required for DAYCENT simulations of major croplands and
grasslands and unit conversion factors were checked, as well as the program scripts that were used to run the Monte
Carlo Analysis. An error was identified in direct N2O estimates from major crops. The units were not converted
correctly with the transfer of data between the DAYCENT model and the structural uncertainty estimator, leading to
an over-estimation of direct N2O emissions from major crops. The error has been resolved and corrected.
Spreadsheets containing input data and emission factors required for the Tier 1 approach used for non-major crops
and grasslands not simulated by DAYCENT were checked and no errors were found.
Recalculations Discussion
Revisions in the calculations for the Agricultural Soil N2O Inventory included (1) using state-level N data for on-
farm use to estimate synthetic N fertilizer application on non-major crops, (2) including uncertainty in DAYCENT
outputs of N volatilization and N leaching/runoff in the calculation of uncertainty for indirect emissions, (3) using a
default uncertainty of ±50 percent for Tier 1 uncertainties that were addressed in previous inventory, including crop
yields and organic fertilizers, (4) assuming that manure N available for land application not accounted for by the
DAYCENT simulations was applied to non-major crop types, (5) revising DAYCENT parameterization for
sorghum, and (6) correcting an error in the empirically-based uncertainty estimator.
In the past Inventory, N fertilizer application to minor crops was based on total N available for application after
subtracting the amount applied to major crops, settlements, and forest lands. In the latest Inventory, a USGS study
(Ruddy et al. 2006) provides data from sales records about the on-farm use of fertilizers, which were used to
estimate the amount of N applied to non-major crops after subtracting the amount estimated for major crops from
the DAYCENT simulations. Previously it was assumed that 90 percent of the synthetic N fertilizer used in the
United States was applied to agricultural soils whereas the on-farm-use data raise the amount to 97 percent. In
addition, after accounting for the amount applied to major crops and grasslands in the DAYCENT simulations, the
latest Inventory assumes that all manure N available for agricultural land application is applied to non-major crops.
Due to these changes, direct N2O emissions from non-major crops are approximately 83 percent higher, on average,
compared to the previous Inventory. However, direct soil N2O emissions from major crops reported in the 1990-
2005 Inventory were over-estimated by approximately a factor of 2 as a result of a unit conversion error in the
empirically-based uncertainty estimator. Because major crops are the greatest source, total emission estimates are
approximately 27.5 percent lower, on average, than reported in the 1990-2005 Inventory. The revised
parameterization for sorghum had a minor influence on the emission estimates.
Planned Improvements
Three major improvements are planned for the Agricultural Soil Management sector. The first improvement is to
incorporate more land-use survey data from the NRI (USDA 2000b) into the DAYCENT simulation analysis,
beyond the area estimates for rangeland and pasture that are currently used to estimate emissions from grasslands.
NRI has a record of land-use activities since 1982 for all U.S. agricultural land, which is estimated at about 386
Mha. NASS is used as the basis for land-use records in the current Inventory, and there are three major
disadvantages to this cropping survey. 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 does provide 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 N2O methods more consistent with the
methods used to estimate C stock changes for agricultural soils. However, the structure of model input files that
contain land management data will need to be extensively revised to facilitate use of NRI data.
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
The second planned improvement is to further refine the uncertainty analysis. New studies are being completed and
published evaluating agricultural management impacts on soil N2O emissions, and these studies can be incorporated
into the empirical analysis, leading to a more robust assessment of structural uncertainty in DAYCENT. Moreover,
structural uncertainty is currently only evaluated for emission estimates in croplands, but structural uncertainty is
likely to be significant for grasslands as well, and it is anticipated that the analysis of structural uncertainty could be
expanded in the near future to include grasslands. In addition, the Monte Carlo analysis will be expanded to address
uncertainties in activity data related to crop- and grassland areas, as well as irrigation and tillage histories.
Currently, the land-area statistics are treated as certain because the NASS data do not include a measure of
uncertainty. Incorporating land-use survey data from the NRI will facilitate the assessment of uncertainties in
agricultural activity data.
The third planned improvement is to further evaluate the application of manure to major and minor crops, as well as
N recovery and losses from manure management systems and field application. Manure amendments are a key
source of N leading to N2O emissions so any further improvements in this estimation will reduce uncertainties in the
emission estimates. We will also evaluate potential for change in application rates over time due to regulation of
confined animal feeding operations; this will improve the emission estimates and reduce uncertainty. Additional
improvements are minor but will lead to more accurate estimates, including updating DAYMET weather for more
recent years.
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F)
Farming activities produce large quantities of agricultural crop residues, and farmers use or dispose of these
residues in a variety of ways. For example, agricultural residues can be left on or plowed into the field; composted
and then applied to soils; landfilled; or burned in the field. Alternatively, they can be collected and used as fuel,
animal bedding material, supplemental animal feed, or construction material. Field burning of crop residues is not
considered a net source of CO2, because the carbon released to the atmosphere as CO2 during burning is assumed to
be reabsorbed during the next growing season. Crop residue burning is, however, a net source of CH4, N2O, CO,
and NOX, which are released during combustion.
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. Less than 5 percent of the residue for each of these crops is burned each year, except for rice. ^ Annual
emissions from this source over the period 1990 to 2006 have remained relatively constant, averaging
approximately 0.8 Tg CO2 Eq. (36 Gg) of CH4 and 0.4 Tg CO2 Eq. (1 Gg) of N2O (see Table 6-18 and Table 6-19).
Table 6-18: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.)
Gas/Crop Type
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
1990
0.7
0.1
0.1
+
0.3
+
0.1
+
0.4
+
+
1995 !
0.7 !
0.1 |
0.1
+
0.3
+
0.2
+
0.4
+
+ 1
2000
0.8
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
2001
0.8
0.1
0.1
+
0.3
+
0.2
+
0.5
+
+
2002
0.7
0.1
0.1
+
0.3
+
0.2
+
0.4
+
+
2003
0.8
0.1
0.1
+
0.4
+
0.2
+
0.4
+
+
2004
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
2005
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
2006
0.8
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
16 The fraction of rice straw burned each year is significantly higher than that for other crops (see "Methodology" discussion
below).
Agriculture 6-29
-------
Sugarcane
Corn
Barley
Soybeans
Peanuts
Total
+
0.1
+
0.2
+
1.1
+ I
0.1 I
+ |
0.2 |
+ |
i.o !
+
0.1
+
0.3
+
1.3
+
0.1
+
0.3
+
1.2
+
0.1
+
0.3
+
1.1
+
0.1
+
0.2
+
1.2
+
0.1
+
0.3
+
1.4
+
0.1
+
0.3
+
1.4
+
0.1
+
0.3
+
1.3
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-19: CH4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg)
Gas/Crop Type 1990 1995J 2000 2001 2002 2003 2004 2005 2006
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N2O
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
CO
NOx
33
7
4
1
13
1
7
+
1
+
+
+
+
+
1
+
691
28
32 1
5
4
1
13
li
8
+|
1
+|
+|
+|
+|
+|
1
+|
663
29 !
38
5
4
1
17
1
10
+
1
+
+
+
+
+
1
+
792
35
37
5
4
1
16
+
11
+
1
+
+
+
+
+
1
+
774
35
34
4
3
1
15
+
10
+
1
+
+
+
+
+
1
+
709
33
38
6
5
1
17
+
9
+
1
+
+
+
+
+
1
+
800
34
42
5
4
1
20
+
11
+
2
+
+
+
+
+
1
+
879
39
41
5
5
1
19
+
11
+
2
+
+
+
+
+
1
+
860
39
39
4
4
1
18
+
12
+
2
+
+
+
+
+
1
+
825
38
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
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 carbon (C) and nitrogen (N) released during burning, the following equation was used:17
CH4 and N2O Emissions from Field Burning of Agricultural Residues= (Fraction of Residues Burned In Situ) x
(Mass of Fuel Available for Combustion) x (Burning Efficiency) x (Emission Factor) x l(T3
Where:
Burning Efficiency = The proportion of prefire fuel biomass consumed
To calculate the mass of fuel available for combustion, the following equation was used:
Mass of Fuel Available for Combustion = (Annual Crop Production)
x (Residue/Crop Product Ratio) x (Dry Matter Content of the Residue)
17 As is explained later in this section, the fraction of rice residues burned varies among states, so these equations were applied at
the state level for rice. These equations were applied at the national level for all other crop types.
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
To calculate the emission factor, the following equation was used:
Emission Factor = (Combustion Efficiency) x (C or N Content of the Residue)
x (Emissions Ratio) x (Conversion Factor) x 1,000
Where:
Combustion Efficiency = The proportion of CH4 or N2O released with respect to the total amount of C
or N available in the burned material, respectively
Emissions Ratio = g CH4-C/g C released or g N2O-N/g N released
Conversion Factor = Molecular weight ratio of Or\4: C or N2O :N
The types of crop residues burned in the United States were determined from various state-level greenhouse gas
emission inventories (ILENR 1993, Oregon Department of Energy 1995, Wisconsin Department of Natural
Resources 1993) and publications on agricultural burning in the United States (Jenkins et al. 1992, Turn et al. 1997,
EPA 1992).
[BEGIN BOX]
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) this year's 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 USD A data on area harvested for
each crop multiplied by the estimated fraction of residue burned for that crop (see Table 6-22).
The IPCC (2006) default run resulted in 20 percent higher emissions of CH4 and 36 percent higher emissions of
N2O than the current estimates in this inventory. It was determined that 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.
[END BOX]
Crop production data for all crops except rice in Florida and Oklahoma were taken from the USDA's Field Crops,
Final Estimates 1987-1992, 1992-1997, 1997-2002 (USDA 1994, 1998, 2003), and Crop Production Summary
(USDA 2005, 2006, 2007). 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), and crop yields for Arkansas (USDA 1994, 1998, 2003, 2005, 2006) were applied to Oklahoma
acreages^ (Lee 2003 through 2006). The production data for the crop types whose residues are burned are
18 Rice production yield data are not available for Oklahoma, so the Arkansas values are used as a proxy.
Agriculture 6-31
-------
presented in Table 6-20.
The percentage of crop residue burned was assumed to be 3 percent for all crops in all years, except rice, based on
state inventory data (ILENR 1993, Oregon Department of Energy 1995, Noller 1996, Wisconsin Department of
Natural Resources 1993, and Cibrowski 1996). Estimates of the percentage of rice residue burned were derived
from state-level estimates of the percentage of rice area burned each year, which were multiplied by state-level
annual rice production statistics. The annual percentages of rice area burned in each state were obtained from
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;
Klosterboer 1999a, 1999b, 2000 through 2003; Lancero 2006, 2007; Lee 2005 through 2007; Lindberg 2002
through 2005; Linscombe 1999a, 1999b, 2001 through 2007; 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, 2007; Walker 2004 through 2007; Wilson 2003 through 2007)
(see Table 6-21). The estimates provided for Florida remained constant over the entire 1990 through 2006 period,
while the estimates for all other states varied over the time series, except for Missouri, which remained constant
through 2005 and dropped in 2006. 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
2006 because of a legislated reduction in rice straw burning (Lindberg 2002), although there was a slight increase
from 2004 to 2005 (see Table 6-21).
All residue/crop product mass ratios except sugarcane were obtained from Strehler and Stutzle (1987). The datum
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
Stutzle (1987). Peanut dry matter content was obtained through personal communications with Jen Ketzis (1999),
who accessed Cornell University's Department of Animal Science's computer model, Cornell Net Carbohydrate and
Protein System. The residue carbon contents and nitrogen contents for all crops except soybeans and peanuts are
from Turn et al. (1997). The residue C content for soybeans and peanuts is the IPCC default
(IPCC/UNEP/OECD/IEA 1997). The N content of soybeans is from Barnard and Kristoferson (1985). The N
content of peanuts is from Ketzis (1999). These data are listed in Table 6-22. The burning efficiency was assumed
to be 93 percent, and the combustion efficiency was assumed to be 88 percent, for all crop types (EPA 1994).
Emission ratios for all gases (see Table 6-23) were taken from the Revised 1996 IPCC Guidelines
(IPCC/UNEP/OECD/IEA 1997).
Table 6-20: Agricultural Crop Production (Gg of Product)
Crop
Wheat
Rice
Sugarcane
Corn*
Barley
Soybeans
Peanuts
1990i
74,292!
7,114!
25,525j
201,534!
9,192i
52,416!
1,635!
I 1995i
! 59,404!
1 7,947!
| 27,922!
! 187,970!
! 7,824i
1 59,174!
! 1,570!
1 2000
I 60,641
1 8,705
! 32,762
| 251,854
! 6,919
I 75,055
! 1,481
2001
53,001
9,794
31,377
241,377
5,407
78,671
1,940
2002
43,705
9,601
32,253
227,767
4,940
75,010
1,506
2003
63,814
9,084
30,715
256,278
6,059
66,778
1,880
2004
58,738
10,565
26,320
299,914
6,091
85,013
1,945
2005
57,280
10,150
24,137
282,311
4,613
83,368
2,209
2006
49,316
8,813
26,752
267,598
3,920
86,770
1,576
*Com for grain (i.e., excludes corn for silage).
Table 6-21: Percent of Rice Area Burned by State
State
Arkansas
California
Florida3
Louisiana
Mississippi
Missouri
1990S !
13%! !
75%! |
o%| 1
6%| I
io%! I
18%! I
1995! !
13%! !
59%! |
0%l I
6%| |
io%! |
18%! |
2000
13%
27%
0%
5%
40%
18%
2001
13%
23%
0%
4%
40%
18%
2002
16%
13%
0%
3%
8%
18%
2003
22%
14%
0%
3%
65%
18%
2004
17%
11%
0%
3%
23%
18%
2005
22%
16%
0%
3%
23%
18%
2006
27%
10%
0%
5%
25%
3%
Oklahoma 90%! I 90%! I 90% 90% 90% 100% 88% 94% 0%
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Texas 1%| i 1%| i 0% 0% 0% 0% 0% 0% 0%
aAlthough rice is cultivated in Florida, crop residue burning is illegal.
Table 6-22: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues
Crop Residue/Crop Fraction of Dry Matter C N Burning Combustion
Ratio Residue Burned Fraction Fraction Fraction Efficiency Efficiency
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
1.3
1.4
0.8
1.0
1.2
2.1
1.0
0.03
Variable
0.03
0.03
0.03
0.03
0.03
0.93
0.91
0.62
0.91
0.93
0.87
0.86
0.4428
0.3806
0.4235
0.4478
0.4485
0.4500
0.4500
0.0062
0.0072
0.0040
0.0058
0.0077
0.0230
0.0106
0.93
0.93
0.93
0.93
0.93
0.93
0.93
0.88
0.88
0.88
0.88
0.88
0.88
0.88
Table
Gas
CH4a
coa
N20b
N0xb
6-23 : Greenhouse <
Emission Ratio
0.005
0.060
0.007
0.121
a Mass of C compound released (units of C) relative to mass of total C released from burning (units of C).
b Mass of N compound released (units of N) relative to mass of total N released from burning (units of N).
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 6-24. CH4 emissions from field
burning of agricultural residues in 2006 were estimated to be between 0.3 and 1.5 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 65 percent below and 79 percent above the 2006 emission estimate of
0.8 Tg CO2 Eq. Also at the 95 percent confidence level, N2O emissions were estimated to be between 0.2 and 0.9
Tg CO2 Eq. (or approximately 64 percent below and 73 percent above the 2006 emission estimate of 0.5 Tg CO2
Eq.).
Table 6-24: Tier 2 Uncertainty Estimates for CH4 and N2O Emissions from Field Burning of Agricultural Residues
(Tg CO2 Eq. and Percent)
2006 Emission Uncertainty Range Relative to Emission
Source Gas Estimate Estimate"
(TgC02Eq.) (TgC02Eq.)
Field Burning of Agricultural Residues
Field Burning of Agricultural Residues
CH4
N2O
0.8
0.5
Lower
Bound
0.3
0.2
Upper
Bound
1.5
0.9
Lower
Bound
-65%
-64%
Upper
Bound
79%
73%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6-33
-------
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 2005 and 2006 were updated using data from USDA (2007). This change resulted in
an increase in the CH4 emission estimate for 2005 of 0.2 percent, and a decrease in the N2O emission estimate for
2005 of 0.1 percent. In addition, a more robust uncertainty analysis was run this year, taking into account shared
variables between the Field Burning of Agricultural Residues and Rice Cultivation sources and correcting errors
that were identified in the uncertainty analysis undertaken for the previous inventory. These changes resulted in a
greater uncertainty range surrounding the 2006 estimates than those presented in the previous inventory for the 2005
emission estimates.
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.
6-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Agricultural Soil
Management
Enteric Fermentation
Manure Management ^^1
Rice Cultivation 1
Field Burning of
Agricultural Residues
0
^^^ Agriculture as a Portion of
^^1 all Emissions
^^ 6.4%
0
50 100 150 200 250 3(
TgCO2Eq.
Figure 6-1: 2006 Agriculture Chapter GHG Sources
-------
Figure 8-2
Agricultural Sources and Pathways of N that Result in N20 Emissions
Synthetic N Fertilizers
Organic
Amendments
Includes both commercial and
non-commercial fertilizers (i.e.,
animal manure, compost,
sewage sludge, tenSrage, etc)
Urine and Dyng from
Grazing Animals
Crop Residues
Includes above- and belowground
residues for all oops (non-N and N
fixing) and from perennial forage
crops and pastures following renewal
Mineralization of
Soil Organic Matter
N-Rxing Craps
N Emissions
Biomass Burning
Although N emissions from
biomass burning are not currently
accounted for in the Inventory,
they are a potential source of N to
soils through volatilization and
deposition.
Storage and Management
of Livestock Manure
includes nen-NjQ N emissions from storage and
management of manure used as fertilizer.
This graphic illustrates tie sources and pathways of nitrogen that result in direct and indirect N^G emissions from soiis in the United States. Sources of nitrogen applied to, or deposited
on, soils are represented with arrows on the left-hand side of the graphic. Emission pathways are also shown with arrows. On the iower right-hand side is a cut-away view of a
representative section of a manaaed soil; histosoi cultivation is represented here.
X-1
-------
Figure 8-3
Major Crops, Average Annual Direct N20 Emissions Estimated Using the DAYCENT Model,
1990-2006 (Tg C02 Eq./state/year)
Tg C02 Eq./state/year
< 0.25
Q 0.25-0.5
n °-5-i
D1-2
5-10
10-13.8
X-2 of U.S. ias and 1990-2006
-------
Figure 8-4
Grasslands, Average Annual Direct N20 Emissions Estimated Estimated Using the DAYCENT Model,
1990-2006 (To C02 Eq./state/year)
Tg C02 Eq./state/year
D <0.25
n 0.25-0.5
n °-5-i
m-2
5-10
10-11.9
X-3
-------
Figure 8-5
Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions Using the DAYCENT Model,
1990-2006 (Gg N/state/year)
Gg N/state/year
n
-------
Figure 6-6
Grasslands, Average Annual N Losses Leading to Indirect N20 Emissions Using the DAYCENT Model,
1990-2006 (Gg N/state/year)
Gg N/state/year
D10-20
D 50-100
• 200-400
• 400-872.3
X-5
-------
Figure 8-7
Comparison of measured emissions at field sites with
modeled emissions using the DAYCENT simulation model
60 -\
50 -
40 '
30 -
10 '
1 Measured
DAYCENT
: IPCC
0 -1
™~ m
I
CO NE
dryland dryland
wheat wheat
Ml corn/
soy/
allalta
TNcorn CO CO Ontario
irrigated irrigated corn
corn corn/
barley
X-6 Inwentorf of U.S. ias and 1990-2006
-------
-------
7. Land Use, Land-Use Change, and Forestry
This chapter provides an assessment of the net greenhouse gas flux1 resulting from the uses and changes in land
types and forests in the United States. The Intergovernmental Panel on Climate Change (IPCC) Good Practice
Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003) recommends reporting fluxes according to
changes within and conversions between certain land-use types, termed forest land, cropland, grassland, and
settlements (as well as wetlands). The greenhouse gas flux from Forest Land Remaining Forest Land is reported
using estimates of changes in forest carbon (C) stocks, non-carbon dioxide (CO2) emissions from forest fires, and
the application of synthetic fertilizers to forest soils. The greenhouse gas flux reported in this chapter from
agricultural lands (i.e., cropland and grassland) includes changes in organic C stocks in mineral and organic soils
due to land use and management, and emissions of CO2 due to the application of crushed limestone and dolomite to
managed land (i.e., soil liming) 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.
Agricultural mineral and organic soil C flux calculations are based primarily on national surveys, so these results are
largely constant over multi-year intervals, with large discontinuities between intervals. For the landfilled yard
trimmings and food scraps source, periodic solid waste survey data were interpolated so that annual storage
estimates could be derived. In addition, because the most recent national forest, and land-use surveys were
completed prior to 2005, the estimates of CO2 flux from forests, agricultural soils, and landfilled yard trimmings and
food scraps are based in part on extrapolation. CO2 flux from urban trees is based on neither annual data nor
periodic survey data, but instead on data collected over the period 1990 through 1999. This flux has been applied to
the entire time series, and periodic U.S. census data on changes in urban area have been used to develop annual
estimates of CO2 flux.
Land use, land-use change, and forestry activities in 2006 resulted in a net C sequestration of 883.7 Tg CO2 Eq.
(241.0 Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 14.8 percent of total U.S. CO2
emissions. Total land use, land-use change, and forestry net C sequestration2 increased by approximately 20
percent between 1990 and 2006. This increase was primarily due to an increase in the rate of net C accumulation in
forest C stocks. Net C accumulation in Settlements Remaining Settlements, Land Converted to Grassland, and
Cropland Remaining Cropland increased, while net C accumulation in landfilled yard trimmings and food scraps
slowed over this period. The Grassland Remaining Grassland land-use category resulted in a net C sink from 1990
through 1994 and then remained a fairly constant emission source. Emissions from Land Converted to Cropland
declined between 1990 and 2006.
Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)
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
-------
Sink Category 1995^ 2000 2001 2002 2003 2004 2005 2006
Forest Land Remaining p^
Forest Land1 (621.7)il (659.9)^ (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)
Cropland Remaining p^
Cropland (30.1)il (39.4)^ (38.4) (40.0) (40.3) (40.5) (40.9) (41.0) (41.8)
Land Converted to Cropland 9-4 9-4 9-4 9-4 9-4 9-4 9-4
Grassland Remaining pE;
Grassland 16.4 16.4 16.4 16.4 16.3 16.3 16.2
Land Converted to p^
Grassland (14-3)H (16-3)B| (16-3) (16-3) (16-3) (16-3) (16-3) (16-3) (16-3)
Settlements Remaining p^
Settlements2 (60.6) il (71.5)^ (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)
Other (Landfilled Yard p^
Trimmings and Food p^
_Scrarjs) (1/U)^j (1L5) (1L6) (1L8) (10-°) (9-6) (10-°) (10-5)
Total (737. (775.3) =j (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
1 Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land.
2 Estimates include C stock changes on both Settlements Remaining Settlements and Land Converted to Settlements.
Table 7-2: Net CO2 Flux from Carbon Stock Changeshi Land Use, Land-Use Change, and Forestry (Tg C)
Sink Category 2000 2001 2002 2003 2004 2005 2006
Forest Land Remaining p^
Forest Land1 (169.6)H (180.0)^ (150.2) (170.0) (190.2) (199.3) (202.2) (202.8) (203.2)
Cropland Remaining
Cropland
Land Converted to Cropland
Grassland Remaining
Grassland
Land Converted to
Grassland
Settlements Remaining
Settlements2
Other (Landfilled Yard
Trimmings and Food
Scraps)
Total
(6.5)^
(201.2)^
1 (10.7) =
1
1 4-5B
1 (4-5)B
| (19.5)^
1 (3.9)1
1 (211.4) =
1 (10.5)
1 2.6
1 4-5
1 (4-5)
1 (22.5)
1 (3.1)
1 (183.7)
(10.9)
2.6
4.5
(4.5)
(23.1)
(3.2)
(204.6)
(H.O)
2.6
4.5
(4.5)
(23.7)
(3.2)
(225.5)
(H.O)
2.6
4.5
(4.5)
(24.3)
(2.7)
(234.8)
(H.l)
2.6
4.5
(4.5)
(24.9)
(2.6)
(238.3)
(H.2)
2.6
4.4
(4.5)
(25.4)
(2.7)
(239.6)
(11.4)
2.6
4.4
(4.5)
(26.0)
(2.9)
(241.0)
Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to
independent rounding.
1 Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land.
2 Estimates include C stock changes on both Settlements Remaining Settlements and Land Converted to Settlements.
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 2006 resulted in CO2 emissions of 8.0 Tg CO2 Eq. (8,012 Gg). The
application of synthetic fertilizers to forest and settlement soils in 2006 resulted in direct N2O emissions of 1.8 Tg
CO2 Eq. (6 Gg). Direct N2O emissions from fertilizer application increased by approximately 174 percent between
1990 and 2006. Forest fires in 2006 resulted in methane (CH4) emissions of 24.6 Tg CO2 Eq. (1,169 Gg), and in
N2O emissions of 2.5 Tg CO2 Eq. (8 Gg).
Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)
Source Category 2000 2001 2002 2003 2004 2005 2006
CO2 7.5 7.8 8.5 8.3 7.6 7.9 8.0
Cropland Remaining Cropland:
Liming of Agricultural Soils & 7.5 7.8 8.5 8.3 7.6 7.9 8.0
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Urea Fertilization
CH4
Forest Land Remaining Forest Land:
Forest Fires
N2O
Forest Land Remaining Forest Land:
Forest Fires
Forest Land Remaining Forest Land:
Forest Soils1
Settlements Remaining Settlements:
Settlement Soils2
Total
13.1^
1
1
1
1
|
1
| 13.6=
1 19.0
1 19.0
1 3.5
1 1.9
1 0.3
1 1.2
= 30.0
9.4
9.4
2.7
1.0
0.3
1.4
20.0
16.4
16.4
3.5
1.7
0.3
1.5
28.4
8.7
8.7
2.7
0.9
0.3
1.5
19.7
6.9
6.9
2.6
0.7
0.3
1.6
17.1
12.3
12.3
3.1
1.2
0.3
1.5
23.2
24.6
24.6
4.3
2.5
0.3
1.5
36.9
Note: These estimates include direct emissions only. Indirect N2O emissions are reported in the Agriculture chapter. Totals may
not sum due to independent rounding.
1 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.
2 Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to
Settlements, but not from land-use conversion.
Table 7-4: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Gg)
Source Category
C02
Cropland Remaining Cropland:
Liming of Agricultural Soils &
Urea Fertilization
CH4
Forest Land Remaining Forest Land:
Forest Fires
N20
Forest Land Remaining Forest Land:
Forest Fires
Forest Land Remaining Forest Land:
Forest Soils1
Settlements Remaining Settlements:
Settlement Soils2
199(^^= 1995^^=
7,084^ 7,049^
^ ^
7,084^ 7,049^
JEEEEE EEEEE
224^
5EEEE EEEEE
JEEEEE EEEEE
3^^E; 4^^^
2000
7,541
7,541
904
904
11
6
1
4
2001
7,825
7,825
448
448
9
3
1
5
2002
8,549
8,549
780
780
11
5
1
5
2003
8,260
8,260
416
416
9
3
1
5
2004
7,555
7,555
330
330
8
2
1
5
2005
7,854
7,854
586
586
10
4
1
5
2006
8,012
8,012
1,169
1,169
14
8
1
5
Note: These estimates include direct emissions only. Indirect N2O emissions are reported in the Agriculture chapter. Totals may
not sum due to independent rounding.
1 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.
2 Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to
Settlements, but not from land-use conversion.
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.
Land Use, Land-Use Change, and Forestry 7-3
-------
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 following six IPCC land-use categories:3 Forest Land, Cropland, Grassland,
Wetlands, Settlements and Other Land (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
(FIA) Database.5 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 NRI or FIA. In 1990, the United States had a total of 243
million hectares of Forest Land, 169 million hectares of Cropland, 301 million hectares of Grassland, 32 million
hectares of Wetlands, 32 million hectares of Settlements, and 28 million hectares in the Other Land7 category
(Table 7-5). By 2006, the total area in Forest Land had increased by 3.9 percent to 252 million hectares, Cropland
had declined by 4.0 percent to 162 million hectares, Grassland declined by 2.8 percent to 293 million hectares,
Wetlands decreased by 4.8 percent to 31 million hectares, Settlements increased by 32.2 percent to 42 million
hectares, and Other Land decreased by 11.1 percent to 25 million hectares.
Table 7-5. Land use areas during the inventory reporting period (millions of hectares)
Land Use
Forest Land
Cropland
Grassland
Wetlands
Settlements
Other Land
1990=
243s
30ll
1
1
I 2%B
|
1
1
l 2000
! 249
j 163
! 296
j 31
j 40
! 25
2001
250
163
295
31
41
25
2002
250
162
295
31
41
25
2003
251
162
294
31
42
25
2004
251
162
294
31
42
25
2005
252
162
293
31
42
25
2006
252
162
293
31
42
25
Note: Unmanaged land is not currently estimated because the only land designated as unmanaged occurs in Alaska, which has
not been included in the current US land representation assessment. See planned improvements for discussion on plans to
include Alaska in future inventory reports.
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.
Figure 7-1. Percent of Total Land Area in Each Land-Use Category by State
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
3 Land-use category definitions are provided in the Methodology section.
4 NRI data is available at .
5 FIA data is available at
-------
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.). Approach 3 extends Approach 2 by allowing each
land-use conversion to be tracked on a spatially explicit basis. The three approaches are not presented as
hierarchical tiers and are not mutually exclusive.
According to IPCC (2003), 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. The NRI and the FIA data surveys meet the standards for Approach 3, but the data from NLCD
that are currently utilized only meet the standards for Approach I.8 Consequently, Approach 1 is being used to
provide a full representation of land use in the current inventory. The United States is pursuing an effort to analyze
available data with the intent of moving beyond Approach 1 in future inventories.
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 (2003, 2006) provide 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
8 A new NLCD product is being developed that will meet the standards of Approach 3 data, with explicit information on land
cover change, opposed to information based solely on land cover for individual years.
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.
Land Use, Land-Use Change, and Forestry 7-5
-------
definition of forest,11 while definitions of Cropland, Grassland, and Settlements are based on the NRI.12 The
definitions for 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 (36.58m) 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 Other Land. 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 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
Other Land.
• 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 Other Land.
• Wetlands: A land-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.
11 See .
12 See .
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.
16 A 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 guidelines (2006) do not include provisions to separate desert and tundra as land categories.
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
IPCC (2006) provides guidance under "Wetlands" for managed peatlands and flooded lands, such as reservoirs
developed for hydroelectricity, irrigation, and navigation. 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 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; water control structures and
spillways; parks within urban and built-up areas; and highways, railroads, and other transportation facilities if
they are surrounded by urban or built-up areas. 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.
• 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. It also specifically includes roads through forests (excluding
unimproved roads/trails) and all types of roads through Grassland and Cropland areas that are discernible using
aerial photography or remote sensing imagery (i.e., interstate highways, state highways, other paved roads,
gravel roads, dirt roads, and railroads).
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. The
NRI is conducted by the USD A Natural Resources Conservation Service and is designed to assess soil, water, and
related environmental resources on nonfederal 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. The NRI survey was conducted every 5 years between 1982 and
1997, but shifted to annualized data collection in 1998.
The FIA program, conducted by the USFS, is used to obtain forest area and management data 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.
Land Use, Land-Use Change, and Forestry 7-7
-------
Because NRI only includes land use information for non-federal land, and the FIA only records for forest land,18
major gaps exist when the datasets are combined, such as federal grassland operated by the Bureau of Land
Management (BLM), USD A, and National Park Service, as well as most of Alaska19. Consequently, the NLCD is
used as a supplementary database to account for federal land areas 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. It is based primarily on Landsat Thematic Mapper imagery. The NLCD contains
21 categories of land cover information, which have been aggregated into the six IPCC land-use categories, and the
data are available at a spatial resolution of 30 meters. 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.
Along with the incorporation of NLCD data, another major step has been taken 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, which covers only non-federal land, 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 forest land on
federal lands. Moreover, dependence exists between the Forest Land area and the amount of land designated as
other land uses in the NRI and NLCD, such as grassland, cropland and wetland, and thus there are inconsistencies in
the Forest Land definitions among the three databases. 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 for non-federal and federal land, respectively. Adjustments were allotted to
grassland and wetlands, based on the proportion of land within each of these land-use categories at the state-level.
A higher proportion of grassland led to a larger adjustment in grassland area and vice versa. 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.
There are minor differences between the U.S. Census Survey20 land area estimates and the land use surveys derived
for 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 NPJ and FIA surveys. Regardless, the total
difference between the U.S. Census Survey and the data sources used in the inventory is relatively minor, estimated
at about 6 million hectares for the total land base of over 800 million hectares currently included in the Inventory, or
a 0.7 percent difference.
Approach for Combining Data Sources
The managed land base in the United States has been classified into the six IPCC land-use categories using
definitions21 developed to meet national circumstances, while adhering to IPCC (2006). In practice, the land was
18 FIA does collect some data on nonforest land use, but these are held in regional databases versus the national database. The
status of these data is being investigated.
19 The 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.
20 See .
21 Definitions are provided in the previous section.
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
initially classified into a variety of land-use categories using the NRI, FIA and NLCD, and then aggregated into the
six broad land uses identified in IPCC (2006). Details on the approach used to combine data sources for each land
use are described below along with 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 and at this time the NLCD cannot be
used to classify land use in this region. FIA surveys are currently being conducted on U.S. territories and will
become available in the future. FIA data will also be collected in Hawaii in the future.
• Cropland: Cropland is classified using the NRI, which covers all non-federal lands, within 49 states, 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 Alaska and U.S. territories are
excluded from both NRI data collection and the NLCD22. Though crops are grown on some federal lands,
these Cropland areas are considered minimal and are excluded from the inventory.
• Grassland: Grassland on non-federal lands is classified using the NRI within 49 states, 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. Alaska and U.S. territories are excluded from both NRI data
collection and the current release of the NLCD product23. Grassland on federal BLM lands, National Parks and
within USFS lands are covered by the NLCD. Department of Defense grasslands are also included in area
estimates using the NLCD.
• Wetlands: NRI captures wetlands on non-federal lands within 49 states, while federal wetlands are covered by
the NLCD. 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. 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. If within an urban area, a forested area is classified as nonforest by FIA,
regardless of size. Settlements on federal lands are covered by NLCD. Settlements in Alaska and U.S.
territories are currently excluded from NRI and NLCD.
• Other Land: Any land not falling into the other five land categories and, therefore, categorized as Other Land is
classified using the NRI and NLCD. Other land in Alaska and U.S. territories are excluded from the NLCD.
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
22 With the exception of non-federal cropland in Puerto Rico, which are included in the NRI survey.
23 With the exception of non-federal grasslands in Puerto Rico, which are included in the NRI survey.
Land Use, Land-Use Change, and Forestry 7-9
-------
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 GHG 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).
Planned Improvements
Area data by land-use category are not estimated for major portions of Alaska and 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 be evaluated for representing land use in
U.S. Territories.
Another planned improvement is to utilize Approach 3-type area data for the U.S. land base. A new NLCD product,
with spatially-explicit information on land-use change is currently being developed and will qualify as Approach 3.
By using this new data product in combination with the existing NRI and FIA databases, land-use statistics will be
further subdivided by land-use change categories as recommended in IPCC (2006). This will include land
remaining in a land-use category and land converted to another land-use category (e.g., Forest Land Remaining
Forest Land, Cropland Converted to Forest Land, Grassland Converted to Forest Land). The additional
subdivisions will provide more explicit land-use change statistics than currently reported, and also provide better
accounting of emissions and stock changes associated with land use activities.
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, current estimates using the NRI and NLCD databases will be compared
and reconciled to the extent possible with the Army Corps of Engineers National Inventory of Dams (ACE 2005)
which provides data on the total surface area of reservoirs created by dams.
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
• Belowground biomass, which includes all living biomass of coarse living roots greater than 2 mm diameter.
• Dead wood, which includes all non-living woody biomass either standing, lying on the ground (but not
including litter), or in the soil.
• Litter, which includes the litter, fumic, and humic layers, and all non-living biomass with a diameter less than
7.5 cm at transect intersection, lying on the ground.
• Soil organic 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).
C is continuously cycled among these storage pools and between forest ecosystems and the atmosphere as a result of
biological processes in forests (e.g., photosynthesis, respiration, growth, mortality, decomposition, and disturbances
such as fires or pest outbreaks) and anthropogenic activities (e.g., harvesting, thinning, clearing, and replanting). As
trees photosynthesize and grow, C is removed from the atmosphere and stored in living tree biomass. As trees die
and otherwise deposit litter and debris on the forest floor, C is released to the atmosphere or transferred to the soil
by organisms that facilitate decomposition.
The net change in forest C is not equivalent to the net flux between forests and the atmosphere because timber
harvests do not cause an immediate flux of C to the atmosphere. Instead, harvesting transfers C to a "product pool."
Once in a product pool, the C is emitted over time as CO2 when the wood product combusts or decays. The rate of
emission varies considerably among different product pools. For example, if timber is harvested to produce energy,
combustion releases C immediately. Conversely, if timber is harvested and used as lumber in a house, it may be
many decades or even centuries before the lumber decays and C is released to the atmosphere. If wood products are
disposed of 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 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
7-1. 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.
Land Use, Land-Use Change, and Forestry 7-11
-------
Figure 7-2: Forest Sector Carbon Pools and Flows
Approximately 33 percent (303 million hectares) of the U.S. land area is forested (Smith et al. 2004b). The current
forest inventory includes 249 million hectares in the conterminous 48 states (USDA Forest Service 2006b) that are
considered managed and are included in this inventory. The additional forest lands are located in Alaska and
Hawaii. This inventory includes approximately 3.7 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 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-seven percent of U.S. forests (204 million hectares) are classified as timberland, meaning they meet minimum
levels of productivity and are available for timber harvest. Nine percent of Alaska forests and 79 percent of forests
in the conterminous United States are classified as timberlands. Of the remaining nontimberland forests, 31 million
hectares are reserved forest lands (withdrawn by law from management for production of wood products) and 68
million hectares are lower productivity forest lands (Smith et al. 2004b). 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 7 million hectares. Current trends in forest area represent average
annual change of only about 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 Net volume of growing stock on U.S. timberlands
increased by 36 percent from 1953 to 1997. 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 2006. 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
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.
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
being released rapidly to the atmosphere (Skog and Nicholson 1998, Skog in preparation). 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 745.1 Tg
CO2Eq. (203.2 Tg C) in 2006 (Table 7-6, Table 7-7, and Figure 7-2). In addition to the net accumulation of C in
harvested wood pools, sequestration is a reflection of net forest growth and increasing forest area over this period.
Overall, average C in forest ecosystem biomass (aboveground and belowground) increased from 71 to 75 Mg C/ha
between 1990 and 2007 (see Table A-4 for average C densities by specific regions and forest types). Continuous,
regular annual surveys are not available over the period for each state; therefore, estimates for non-survey years
were derived by interpolation between known data points. Survey years vary from state to state, and national
estimates are a composite of individual state surveys. Therefore, changes in sequestration over the interval 1990 to
2006 are the result of the sequences of new inventories for each state. Net annual sequestration increased by 20
percent for 2006 relative to 1990. C in forest ecosystem biomass had the greatest effect on total change. As
discussed above, this was due to increased C density and total forest land. Management practices that increase C
stocks on forest land, as well as afforestation and reforestation efforts influence the trends of increased C densities
in forests and increased forest land in the United States.
Table 7-6. Net Annual Changes in C Stocks (Tg CO2/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 =
(489.1)1
(287.6) =
(54.2) =
(40.1) =
(63.3)1
(43.9)1
(132.6)1
(64.8)1
(67.9)1
(621.7) =
1 1995&
1 (540.5)1
I (318.4)s
I (62.4)s
I (57.5)i
1 (34.9)1
1 (67.5)1
1 (119.4)1
1 (55.2)1
1 (64.1)1
I (659.9)1
i 2000
i (436.8)
i (335.4)
i (67.2)
i (44.9)
1 (17.3)
i 28.0
1 (H3.9)
1 (47.0)
1 (66.9)
i (550.7)
2001
(529.0)
(367.7)
(73.7)
(50.0)
(36.3)
(1.3)
(94.5)
(31.9)
(62.6)
(623.4)
2002
(598.0)
(384.4)
(76.9)
(53.0)
(47.7)
(36.0)
(99.2)
(35.1)
(64.2)
(697.3)
2003
(635.1)
(406.5)
(80.9)
(56.9)
(56.2)
(34.5)
(95.9)
(35.4)
(60.4)
(730.9)
2004
(635.1)
(406.5)
(80.9)
(56.9)
(56.2)
(34.5)
(106.3)
(45.5)
(60.8)
(741.4)
2005
(635.1)
(406.5)
(80.9)
(56.9)
(56.2)
(34.5)
(108.5)
(47.3)
(61.2)
(743.6)
2006
(635.1)
(406.5)
(80.9)
(56.9)
(56.2)
(34.5)
(110.0)
(45.3)
(64.7)
(745.1)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, 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. Forest area
estimates are based on interpolation and extrapolation of inventory data as described in the text and in Annex 3.12. Harvested
wood estimates are based on results from annual surveys and models. Totals may not sum due to independent rounding.
Table 7-7. Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic C
Harvested Wood
Products in Use
SWDS
Total Net Flux
1990=
(133.4)=
(78.4)=
(14.8)=
(10.9)=
(17.3)=
(12.0) =
(36.2)=
(17.7) =
(18.5) =
(169.6) =
i
1 (147.4)=!
i
1
1
1
1 (18.4)=!
1
1
1 (17.5)fi
i (180.0)^
E 2000
1 (H9.1)
1 (91.5)
1 (18.3)
1 (12.2)
1 (4.7)
1 7.6
1 (31.1)
1 (12.8)
1 (18.2)
1 (150.2)
2001
(144.3)
(100.3)
(20.1)
(13.6)
(9.9)
(0.4)
(25.8)
(8.7)
(17.1)
(170.0)
2002
(163.1)
(104.8)
(21.0)
(14.5)
(13.0)
(9.8)
(27.1)
(9.6)
(17.5)
(190.2)
2003
(173.2)
(110.9)
(22.1)
(15.5)
(15.3)
(9.4)
(26.1)
(9.7)
(16.5)
(199.3)
2004
(173.2)
(110.9)
(22.1)
(15.5)
(15.3)
(9.4)
(29.0)
(12.4)
(16.6)
(202.2)
2005
(173.2)
(110.9)
(22.1)
(15.5)
(15.3)
(9.4)
(29.6)
(12.9)
(16.7)
(202.8)
2006
(173.2)
(110.9)
(22.1)
(15.5)
(15.3)
(9.4)
(30.0)
(12.3)
(17.7)
(203.2)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, 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.
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-
Land Use, Land-Use Change, and Forestry 7-13
-------
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
1990s
245,7991
40,106s
14=547s
2,896g
2,453s
4,557s
15,652s
1,862s
1,2311
6311
41,968s
i 1995s
i 249,036^
i 40,810s
i 14,955s
i 2,974s
i 2,515s
i 4,641s
i 15,725s
i 2,033S
i 1,311s
i 722S
i 42,843s
I 2000
| 252,251
1 41,535
1 15,405
1 3,063
1 2,592
1 4,680
| 15,795
1 2,193
| 1,382
3 810
1 43,728
2001
252,798
41,654
15,496
3,081
2,605
4,684
15,788
2,224
1,395
829
43,878
2002
253,443
41,798
15,596
3,102
2,618
4,694
15,788
2,250
1,404
846
44,048
2003
254,155
41,962
15,701
3,123
2,633
4,707
15,798
2,277
1,413
863
44,238
2004
254,889
42,135
15,812
3,145
2,648
4,723
15,807
2,303
1,423
880
44,438
2005
255,624
42,308
15,923
3,167
2,664
4,738
15,817
2,332
1,436
896
44,640
2006
256,358
42,481
16,034
3,189
2,679
4,753
15,826
2,362
1,448
913
44,843
2007
257,093
42,654
16,145
3,211
2,695
4,769
15,835
2,392
1,461
931
43,376
Forest Area estimates include portions of Alaska, which represents an addition relative to previous versions of this table. Forest
C stocks do not include forest stocks in U.S. territories, Hawaii, 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)
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 7-3: Estimates of Net Annual Changes in C Stocks for Major C Pools
Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States, 2007
[BEGIN BOX]
Box 7-1: CO? Emissions from Forest Fires
As stated previously, the forest inventory approach implicitly accounts for emissions due to disturbances such as
forest fires, because only C remaining in the forest is estimated. Net C stock change is estimated by subtracting
consecutive C stock estimates. A disturbance removes C from the forest. The inventory data on which net C stock
estimates are based already reflect this C loss. Therefore, estimates of net annual changes in C stocks for U.S.
forestland already account for CO2 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 CO2 emissions from fire disturbance, these estimates are being highlighted here, using the full extent
of available data. Non-CO2 greenhouse gas emissions from forest fires are also quantified in a separate section
below.
The IPCC (2003) methodology was employed to estimate CO2 emissions from forest fires. CO2 emissions for the
lower 48 states and Alaska in 2006 were estimated to be 267.9 Tg CO2/yr. This amount is masked in the estimate of
net annual forest carbon stock change for 2006, however, because this net estimate accounts for the amount
sequestered minus any emissions.
Table 7-9: Estimates of CO2 (Tg/yr) emissions for the lower 48 states and Alaska1
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
CO2 emitted in
the Lower 48
States (Tg/yr)
36.8
51.1
196.9
99.7
149.0
92.4
43.4
111.4
266.6
CO2 emitted in
Alaska
(Tg/yr)
12.0
0.2
10.3
3.0
29.7
3.0
32.1
22.9
1.3
Total CO2
emitted
(Tg/yr)
48.8
51.3
207.2
102.6
178.7
95.4
75.5
134.3
267.9
1 Note that these emissions have already been accounted for in the estimates of net annual changes in carbon stocks, which
accounts for the amount sequestered minus any emissions.
[END BOX]
Methodology
The methodology described herein is consistent with IPCC (2003) and IPCC/UNEP/OECD/IEA (1997). Estimates
of net annual C stock change, or flux, of forest ecosystems are derived from applying C estimation factors to forest
inventory data and interpolating between successive inventory-based estimates of C stocks. C emissions from
harvested wood are based on factors such as the allocation of wood to various primary and end-use products as well
as half-life (the time at which half of amount placed in use will have been discarded from use) and expected
disposition (e.g., product pool, SWDS, combustion). Different data sources are used to estimate the C stocks and
stock change in forest ecosystems or harvested wood products. See Annex 3.12 for details and additional
information related to the methods described below.
Forest Carbon Stocks and Fluxes
The first step in developing forest ecosystem estimates is to identify useful inventory data and resolve any
inconsistencies among datasets. Forest inventory data were obtained from the USDA Forest Service FIA program
(Prayer and Furnival 1999, USDA Forest Service 2006a). Inventories include forest lands25 of the conterminous
United States and are organized as a number of separate datasets, each representing a complete inventory, or survey,
of an individual state at a specified time. Forest C calculations are organized according to these state surveys, and
the frequency of surveys varies by state. To calculate a C stock change, at least two surveys are needed in each
state. Thus, the most recent surveys for each state are used as well as all additional consistent inventory data back
through 1990. Because C flux is based on change between successive C stocks, consistent representation of forest
land in successive inventories is necessary. In order to achieve accurate representation of forests from 1990 to the
present, state-level data are sometimes subdivided or additional inventory sources are used to produce the consistent
state or sub-state inventories.
The principal FIA datasets employed are freely available for download at USDA Forest Service (2006b) as the
Forest Inventory and Analysis Database (FIADB) Version 2.1. These data are identified as "snapshot" files, also
identified as FISDB 2.1, and include detailed plot information, including individual-tree data. However, to achieve
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.
Land Use, Land-Use Change, and Forestry 7-15
-------
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 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. A detailed list of the specific inventory data used
in this inventory is in Table A-188 of Annex 3.12.
Forest C stocks are estimated from inventory data by a collection of conversion factors and models referred to as
FORCARB2 (Birdsey and Heath 1995, Birdsey and Heath 2001, Heath et al. 2003, Smith et al. 2004a), which have
been formalized in an application referred to as the Carbon Calculation Tool (CCT), (Smith et al. 2007). The
conversion factors and model coefficients are usually categorized by region and forest type, and forest C stock
estimates are dependent on these particular sets of factors. Factors are applied to the data at the scale of FIA
inventory plots. The results are estimates of C density (Mg per hectare) for the various forest pools. C density for
live trees, standing dead trees, understory vegetation, down dead wood, forest floor, and soil organic matter are
estimated. All non-soil pools except forest floor can be separated into aboveground and belowground components.
The live tree and understory C pools are pooled as biomass in this inventory. Similarly, standing dead trees and
down dead wood are pooled as dead wood in this inventory. Definitions of ecosystem pools and the C conversion
process follow, with additional information in Annex 3.12.
Live Biomass, Dead Wood, and Litter Carbon
Live tree C pools include aboveground and belowground (coarse root) biomass of live trees with diameter at
diameter breast height (d.b.h.) of at least 2.54 cm at 1.37 m above the forest floor. Separate estimates are made for
full-tree and aboveground-only biomass in order to estimate the belowground component. If inventory plots include
data on individual trees, tree C is based on Jenkins et al. (2003) and is a function of species and diameter. Some
inventory data do not provide measurements of individual trees; tree C in these plots is estimated from plot-level
volume of merchantable wood, or growing-stock volume, of live trees, which is calculated from updates of Smith et
al. (2003). Some inventory data, particularly some of the older datasets, may not include sufficient information to
calculate tree C because of incomplete or missing tree or volume data; C estimates for these plots are based on
averages from similar, but more complete, inventory data.
Understory vegetation is a minor component of biomass, which is defined as all biomass of undergrowth plants in a
forest, including woody shrubs and trees less than 2.54 cm d.b.h. In this inventory, it is assumed that 10 percent of
total understory C mass is belowground. Estimates of C density are based on information in Birdsey (1996).
The two components of dead wood—standing dead trees and down dead wood—are estimated separately. The
standing dead tree C pools include aboveground and belowground (coarse root) mass and include trees of at least
2.54 cm d.b.h. Down dead wood is defined as pieces of dead wood greater than 7.5 cm diameter, at transect
intersection, that are not attached to live or standing dead trees. Down dead wood includes stumps and roots of
harvested trees. Ratios of down dead wood to live tree are used to estimate this quantity. Litter C is the pool of
organic C (also known as duff, humus, and fine woody debris) above the mineral soil and includes woody fragments
with diameters of up to 7.5 cm. Estimates are based on equations of Smith and Heath (2002).
Forest Soil C
Soil organic C (SOC) includes all organic material in soil to a depth of 1 meter but excludes the coarse roots of the
biomass or dead wood pools. Estimates of SOC are based on the national STATSGO spatial database (USD A
1991), and the general approach described by Amichev and Galbraith (2004). Links to FIA inventory data were
developed with the assistance of the USD A Forest Service FIA Geospatial Service Center by overlaying FIA forest
inventory plots on the soil C map. Thus, SOC is defined by region and forest type group.
C stocks and fluxes for Forest Land Remaining Forest Land are reported in pools following IPCC (2006). Total
forest C stock and flux estimates start with the plot-level calculations described above. The separate C densities are
summed and multiplied by the appropriate expansion factors to obtain a C stock estimate for the plot. In turn, these
are summed to state or sub-state total C stocks. Annualized estimates of C stocks are based on interpolating or
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
extrapolating as necessary to assign a C stock to each year. For example, the C stock of Alabama for 2007 is an
extrapolation of the two most recent inventory datasets for that particular state, which are from 1999 and 2003.
Flux, or net annual stock change, is simply the difference between two successive years with the appropriate sign
convention so that net increases in ecosystem C are identified as negative flux. This methodological detail accounts
for the constant estimates of flux from the second most recent inventory to the present (see 2003 through 2006 on
Table 7-6 as an example).
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 (in preparation) using the WOODCARB II 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 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 & forthcoming). Estimates for
disposal of products reflect the change over time in the fraction of products discarded to SWDS (as opposed to
burning or recycling) and the fraction of SWDS that are in sanitary landfills versus dumps.
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:
1 A) 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 product 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 2 A 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.
Land Use, Land-Use Change, and Forestry 7-17
-------
Uncertainty
The 2006 flux estimate for forest C stocks is estimated to be between -579.0 and -913.2 Tg CO2 Eq. at a 95 percent
confidence level. This includes a range of -471.2 to -802.2 Tg CO2 Eq. in forest ecosystems and -85.5 to -136.8 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, as discussed
above. More information on the uncertainty estimates for Net CO2 Flux from Forest Land Remaining Forest Land:
Changes in Forest C Stocks is contained within the Uncertainty Annex.
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)
Source
Forest Ecosystem
Harvested Wood Products
Gas
C02
C02
2006 Flux
Estimate
(Tg C02 Eq.)
(635.1)
(110.0)
Uncertainty Range Relative to Flux Estimate"
(Tg C02 Eq.) (%)
Lower
Bound
(802.2)
(136.8)
Upper
Bound
(471.2)
(85.5)
Lower Upper
Bound Bound
-26% +26%
-24% +22%
Total Forest CO2 (745.1) (913.2) (579.0) -23% +22%
Note: Parentheses indicate negative values or net sequestration.
aRange of flux estimates predicted by Monte Carlo stochastic simulation for a 95 percent confidence interval.
QA/QC and Verification
As discussed above, the FIA program has conducted consistent forest surveys based on extensive statistically-based
sampling of most of the forest land in the conterminous United States, dating back to 1952. The main purpose of
the FIA program has been to estimate areas, volume of growing stock, and timber products output and utilization
factors. The FIA program includes numerous quality assurance and quality control (QA/QC) procedures, including
calibration among field crews, duplicate surveys of some plots, and systematic checking of recorded data. Because
of the statistically-based sampling, the large number of survey plots, and the quality of the data, the survey
databases developed by the FIA program form a strong foundation for C stock estimates. Field sampling protocols,
summary data, and detailed inventory databases are archived and are publicly available on the Internet (USDA
Forest Service 2006b).
Many key calculations for estimating current forest C stocks based on FIA data are based on coefficients from the
FORCARB2 model (see additional discussion in the Methodology section above and in Annex 3.12). The model
has been used for many years to produce national assessments of forest C stocks and stock changes. General quality
control procedures were used in performing calculations to estimate C stocks based on survey data. For example,
the derived C datasets, which include inventory variables such as areas and volumes, were compared with standard
inventory summaries such as Resources Planning Act (RPA) Forest Resource Tables or selected population
estimates generated from the FIA Database (FIADB), which are available at an FIA Internet site (USDA Forest
Service 2006b). Agreement between the C datasets and the original inventories is important to verify accuracy of
the data used. Finally, C stock estimates were compared with previous inventory report estimates to ensure that any
differences could be explained by either new data or revised calculation methods (see the "Recalculations"
discussion below).
Estimates of the HWP variables and the HWP Contribution under the production accounting approach use data from
U.S. Census and USDA Forest Service surveys of production and trade. Factors to convert wood and paper from
original units to C units are based on estimates by industry and Forest Service published sources. The
WOODCARB II model uses estimation methods suggested by 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
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
discarded to SWDS needs to match EPA estimates of discards each year over the period 1990 to 2000. These
criteria help reduce uncertainty in estimates of annual change in C in products in use in the United States and to a
lesser degree reduces uncertainty in estimates of annual change in C in products made from wood harvested in the
United States.
Recalculations Discussion
The overall process for developing annualized estimates of forest ecosystem C stocks based on the individual state
surveys and the C conversion factors are identical to that presented in the previous inventory (Smith et al. 2007).
However, revised estimates of forest ecosystem C stock increased by 3 percent for 1990 and 2005. Similarly,
estimated net stock change increased by 4 percent for 1990 and by 6 percent for 2005. The addition of newly
available forest inventory data as well as some refinements in previously existing data were the principal factors
contributing to these changes. Inventory data changed for 31 of the 48 states included in the previous inventory.
However, not all of the changes are apparent in the list of inventory data used for C estimates (Table A-186)
because some changes involved reclassification and recalculation of existing data. In addition, a portion of Alaska
forest is included in this inventory for the first time. Carbon stock and change estimates for the early 1990s are still
sensitive to updates made over the last year, which are primarily associated with the most recent data per state,
because 13 of the 49 states are still entirely or partly based on two C stock estimates (Table A-186). Thus, even an
update for a 2006 C stock, for example, is propagated throughout the interval when stock change is linearly
interpolated between the two stocks.
The basic model and data used to estimate HWP contribution under the production approach are unchanged since
the previous inventory (Skog in preparation). However, minor modifications to some model coefficients resulted in
slight increases in estimated C sequestration so that net annual additions to C in HWP increased by 0.5 and 5
percent for 1990 and 2005, respectively, with an average increase of 3 percent across the sixteen years.
Modifications to parameters included: (1) shorter half-life for decay in dumps and (2) separation of decay in dumps
from decay in landfills.
Planned Improvements
The ongoing annual surveys by the FIA Program will improve precision of forest C estimates as new state surveys
become available (Gillespie 1999). The annual surveys will eventually include all states. To date, five states are
not yet reporting any data from the annualized sampling design of FIA: Hawaii, Mississippi, 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. However, long-term residual effects on soil and forest
floor C stocks are likely after land-use change. Estimates of such effects are being developed based on methods
described by Woodbury et al. (2007), and preliminary results demonstrate effects on soil organic C and forest floor.
Additional development is required to link model results with: 1) the C change methods used for this inventory
(Smith et al. 2007), and 2) a consistent representation of the land base and land-use change for the United States
(See 7.1 Representation of the U.S. LandBase in the National Greenhouse Gas Inventory for more details).
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.
Land Use, Land-Use Change, and Forestry 7-19
-------
Non-C02 Emissions From Forest Fires
Emissions of non-CO2 gases from forest fires were estimated using the default IPCC (2003) methodology.
Emissions from this source in 2006 were estimated to be 24.6 Tg CO2 Eq. of CH4 and 2.5 Tg CO2 Eq. of N2O, as
shown in Table 7-10 and Table 7-11. The estimates of non-CO2 emissions from forest fires account for both the
lower 48 states and Alaska.
Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. forests1
Gas
CH4
N2O
Total
1990 =
4.5^
0.5^
4.9^
\
I
I
I
3 2000
1 19.0
1 1.9
3 20.9
2001
9.4
1.0
10.4
2002
16.4
1.7
18.0
2003
8.7
0.9
9.6
2004
6.9
0.7
7.6
2005
12.3
1.2
13.6
2006
24.6
2.5
27.0
Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (Gg Gas) for U.S. forests1
Gas
CH4
N2O
1990^
213^
1 =
I
I
I
3 2000
3 904
1 6
2001
448
3
2002
780
5
2003
416
3
2004
330
2
2005
586
4
2006
1,169
8
Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
Methodology
The IPCC (2003) Tier 2 default methodology was used to calculate non-CO2 emissions from forest fires. Estimates
for CH4 emissions were calculated by multiplying the total estimated C emitted (see Table 7-12) from forest burned
by gas-specific emissions ratios and conversion factors. N2O emissions were calculated in the same manner, but
were also multiplied by anN-C ratio of 0.01 as recommended by IPCC (2003). The equations used were:
CH4 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, presented in Table 7-12 below, are the same estimates used to generate
estimates of CO2 emissions from forest fires, presented earlier in Box 7-1. See Table A-197 and explanation in
Annex 3.12 for more details on the methodology used to estimate C emitted from forest fires.
Table 7-13: Estimated Carbon Released from Forest Fires for U.S. Forests
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
C Emitted (Tg/yr)
13.3
14.0
56.5
28.0
48.7
26.0
20.6
36.6
73.1
Uncertainty
Non-CO2 gases emitted from forest fires depend on several variables, including forest area and average C density
for forest land in both Alaska and the lower 48 states, emission ratios, and combustion factor values (proportion of
biomass consumed by fire). To quantify the uncertainties for emissions from forest fires, a Monte Carlo (Tier 2)
uncertainty analysis was performed using information about the uncertainty surrounding each of these variables.
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 7-14.
Table 7-14: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg CO2 Eq. and Percent)
2006 Emission Uncertainty Range Relative to
Source Gas Estimate Emission Estimate
(TgC02Eq.) (TgC02Eq.) (%)
Non-CO2 Emissions from Forest Fires CH4
N2O
Lower
Bound
24.6 7.7
2.5 0.8
Upper
Bound
42.1
4.4
Lower
Bound
-69%
-69%
Upper
Bound
71%
75%
QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted consistent with the U.S. QA/QC plan. The QA/QC plan for
forest fires followed the QA/QC plan implemented for forest C. A source-specific QA/QC plan for forest fires will
be developed and implemented for the next inventory. Quality control measures 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
Average carbon density for Alaska was updated from 70 Mg/ha to 331 Mg/ha based on new data from the FIA
National Program. In addition, the static ratio used in the previous inventory to estimate the proportion of
forestland burned from data on total area burned was replaced with a ratio that varied across the inventory time
series. See Annex 3.12 for details and additional information related to the methods described.
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 5.5 from 1990 to 2006. 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.
Table 7-15. N2O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
TgCO2Eq. (
0.1 (
0.2 (
0.3
0.3
0.3
0.3
0.3
0.3
0.3
3?
).2
).5
.0
.1
.1
.1
.1
.1
.1
Note: These estimates include direct N2O emissions from N fertilizer additions only. Indirect N2O emissions from fertilizer
Land Use, Land-Use Change, and Forestry 7-21
-------
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 are 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 (North
Carolina Sate Forest Nutrition Cooperative 2002). Not accounting for fertilizer applied to non-pine plantations is
justified because fertilization is routine for pine forests but rare for hardwoods (Binkley et al. 1995). For each year,
the area of pine receiving N fertilizer was multiplied by the midpoint of the reported range of N fertilization rates
(150 Ibs. N per acre). Data for areas of forests receiving fertilizer outside the southeastern United States were not
available, so N additions to non-southeastern forests are not included here. It should be expected, however, that
emissions from the small areas of fertilized forests in other regions would not be substantial because the majority of
trees planted and harvested for timber are in the southeastern United States (USDA Forest Service 2001). Area data
for pine plantations receiving fertilizer in the Southeast were not available for 2002, 2003, 2004, 2005, and 2006, so
data from 2001 were used for these years. The N applied to forests was multiplied by the IPCC (2006) default
emission factor of 1 percent to estimate direct N2O emissions. The volatilization and leaching/runoff fractions,
calculated according to the IPCC default factors of 10 percent and 30 percent, respectively, were included with all
sources of indirect emissions in the Agricultural Soil Management source category of the Agriculture chapter.
Uncertainty
The amount of N2O emitted from forests depends not only on N inputs, but also on a large number of variables,
including organic C availability, O2 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 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 2006 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 1.1 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 59 percent below and 211 percent above the 2006 emission estimate of
0.3 Tg CO2 Eq.
Table 7-16: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in Forest Land Remaining Forest Land
(Tg CO2 Eq. and Percent)
2006 Emission Uncertainty Range Relative to
Source Gas Estimate Emission Estimate
26 Uncertainty is unknown for the fertilization rates so a conservative value of ±50% was used in the analysis.
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
(Tg C02 Eg.) (Tg C02 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Forest Land Remaining Forest Land: N2O
Fluxes from Soils N2O 0.3 0.1 1.1 -59% +211%
Note: This estimate includes direct N2O emissions from N fertilizer additions to both Forest Land Remaining Forest Land and
Land Converted to Forest Land.
Recalculations Discussion
No recalculations were performed for the time series.
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 or sink for
atmospheric CO2 in most soils. Changes in inorganic C stocks are typically minor. Soil organic C is the dominant
organic C pool in cropland ecosystems, because biomass and dead organic matter have considerably less C and
those pools are relatively ephemeral. IPCC/UNEP/OECD/IEA (1997) and IPCC (2006) recommends reporting
changes in soil organic C stocks due to agricultural land-use and management activities on mineral soils and organic
soils.27
Typical well-drained mineral soils contain from 1 to 6 percent organic C by weight, although some mineral soils
that are saturated with water for substantial periods during the year may contain significantly more C (NRCS 1999).
When mineral soils undergo conversion from their native state to agricultural uses, as much as half the SOC can be
lost to the atmosphere. The rate and ultimate magnitude of C loss will depend on pre-conversion conditions,
conversion method and subsequent management practices, climate, and soil type. In the tropics, 40 to 60 percent of
the C loss generally occurs within the first 10 years following conversion; C stocks continue to decline in
subsequent decades but at a much slower rate. In temperate regions, C loss can continue for several decades,
reducing stocks by 20 to 40 percent of native C levels. Eventually, the soil can reach a new equilibrium 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
27 CO2 emissions associated with liming are also estimated but included in a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-23
-------
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 a year of the inventory 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. For this area, CO2 emissions and removals-^ due
to changes in mineral soil C stocks are estimated using a Tier 3 approach for the majority of annual crops. A Tier 2
IPCC method is used for the remaining crops (vegetables, tobacco, perennial/horticultural crops, and rice) not
included in the Tier 3 method. In addition, a Tier 2 method is used for very gravelly, cobbly or shaley soils (i.e.,
classified as soils that have greater than 35 percent of soil volume comprised of gravel, cobbles or shale) and for
additional changes in mineral soil C stocks that were not addressed with the Tier 2 or 3 approaches (i.e., change in
C stocks after 1997 due to Conservation Reserve Program enrollment). Emissions from organic soils are estimated
using a Tier 2 IPCC method.
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 2006 (see Table 7-17 and Table 7-18). In 2006, mineral
soils were estimated to remove about 69.5 Tg CO2 Eq. (19.0 Tg C). This rate of C storage in mineral soils
represented about a 20 percent increase in the rate since the initial reporting year of 1990. Emissions from organic
soils were about 27.7 Tg CO2 Eq. (7.5 Tg C) in 2006. In total, U.S. agricultural soils in Cropland Remaining
Cropland removed approximately 41.8 Tg CO2 Eq. (11.4 Tg C) in 2006.
Table 7-17: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990 =
(57.5) =
27.4^
(30.1) =
i
1
E
1
i 2000
! (66.1)
! 27.7
! (38.4)
2001
(67.7)
27.7
(40.0)
2002
(68.0)
27.7
(40.3)
2003
(68.1)
21.1
(40.5)
2004
(68.5)
27.7
(40.9)
2005
(68.7)
27.7
(41.0)
2006
(69.5)
27.7
(41.8)
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 CO2 Flux from Soil C Stock Changes in
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990 =
(15.7) =
7.5^
(8.2) =
i
1
i
1 (10.7) =
i 2000
! (18.0)
! 7.5
! (10.5)
Cropland Remaining Cropland (Tg C)
2001
(18.5)
7.5
(10.9)
2002
(18.5)
7.5
(11.0)
2003
(18.6)
7.5
(11.0)
2004
(18.7)
7.5
(H.l)
2005
(18.7)
7.5
(11.2)
2006
(19.0)
7.5
(H.4)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
28 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
29 Note that removals occur through crop and forage uptake of CO2 into biomass C that is later incorporated into soils pools.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
The net increase in soil C stocks (39 percent for 2006, relative to 1990) was largely due to an increase in annual
cropland enrolled in the Conservation Reserve Program, intensification of crop production by limiting the use of
bare-summer fallow in semi-arid regions, increased hay production, and adoption of conservation tillage (i.e.,
reduced- and no-till practices). At present (2006), cropland enrolled in the Conservation Reserve Program accounts
for 32 percent of the increase of C stocks for Cropland Remaining Cropland on mineral soils (Table 7-18).
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 sequestration in mineral soils occurred in the Midwest, where
there were 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. 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.
Figure 7-5: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland
Figure 7-6: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland
The estimates presented here are restricted to C stock changes in agricultural soils. Agricultural soils are also
important sources of other greenhouse gases, particularly N2O from application of fertilizers, manure, and crop
residues and from cultivation of legumes, as well as CH4 from flooded rice cultivation. These emissions are
accounted for in the Agriculture chapter, along with non-CO2 greenhouse gas emissions from field burning of crop
residues and CH4 and N2O emissions from livestock digestion and manure management.
Methodology
The following section includes a description of the methodology used to estimate changes in soil C stocks due to:
(1) agricultural land-use and management activities on mineral soils; 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 ca. 400,000 points in
agricultural land of 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 collected for each NRI point on a 5-
year cycle beginning in 1982, and were subdivided into four inventory time periods, 1980 through 1984, 1985
through 1989, 1990 through 1994, and 1995 through 2000.
30
NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-25
-------
NRI points were classified as Cropland Remaining Cropland for an inventory time period (e.g., 1990 through 1994
and 1995 through 2000) if the land use had been cropland for 20 years.3 * Cropland includes all land used to
produce food or fiber, as well as forage that is harvested and used as feed (e.g., hay and silage).
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 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 1997, 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 input, along with information about soil physical
properties. Input data on land use and management can be specified at monthly resolution and include land-use
type, crop/forage type and management activities (e.g., planting, harvesting, fertilization, manure amendments,
tillage, irrigation, residue removal, grazing, and fire). The model computes net primary productivity and C
additions to soil, soil temperature, and water dynamics, in addition to turnover, stabilization, and mineralization of
soil organic matter C and nutrient (N, K, S) elements. This method is more accurate than the Tier 1 and 2
approaches provided by the IPCC, because the simulation model treats changes as continuous over time rather than
the simplified discrete changes represented in the default method (see Box 7-2 for additional information). National
estimates were obtained by simulating historical land-use and management patterns as recorded in the USDA
National Resources Inventory (NRI) survey. Land-use and management activities were grouped into inventory time
periods (i.e., time "blocks") for 1980 through 1984, 1985 through 1989, 1990 through 1994, and 1995 through
2000, using NRI data from 1982, 1987, 1992, and 1997, respectively.
[BEGIN BOX]
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,
31 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
which are based on a classification of land areas into a number of discrete states based on a highly aggregated
classification of climate, soil, and management (i.e., only six climate regions, seven soil types and eleven
management systems occur in U.S. agricultural land under the IPCC categorization scheme). 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 CO2 emissions and uptake) are treated as continuous variables, which
change on a monthly time step. C emissions and removals are an outcome of plant production and decomposition
processes, which are simulated in the model structure. Thus, changes in soil C stocks are influenced by not only
changes in land use and management but also inter-annual climate variability and secondary feedbacks between
management activities, climate and soils as they affect primary production and decomposition. This latter
characteristic constitutes one of the greatest differences between the methods, and forms the basis for a more
complete accounting of soil C stock changes in the Tier 3 approach compared with Tier 2 methodology.
Because the Tier 3 model simulates a continuous time period rather than as an equilibrium step change used in the
IPCC methodology (Tier 1 and 2), the Tier 3 model addresses the delayed response of the soil to management and
land-use changes, which can occur due to variable weather patterns and other environmental constraints that interact
with land use and management and affect the time frame over which stock changes occur. Moreover, the Tier 3
method also accounts for the overall effect of increasing yields and, hence, C input to soils that have taken place
across management systems and crop types within the United States. Productivity has increased by 1 to 2 percent
annually over the past 4 to 5 decades for most major crops in the United States (Reilly and Fuglie 1998), which is
believed to have led to increases in cropland soil C stocks (e.g., Allmaras et al. 2000). This is a major difference
from the IPCC-based Tier 1 and 2 approaches, in which soil C stocks change only with discrete changes in
management and/or land use, rather than a longer term trend such as gradual increases in crop productivity.
[END BOX]
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 of the inventory. Specifically, county-scale ratios of manure available 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 amount of 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. Managed systems include feedlots or other housing (which requires manure to be collected
and managed); unmanaged systems include daily spread, pasture, range, and paddock systems. Annual animal
population data for all livestock types, except horses and goats, were obtained for all years from the U.S.
Department of Agriculture-National Agricultural Statistics Service. Population data used for cattle, swine, and
sheep were downloaded from the USDA NASS Population Estimates Database (USDA 2007a). Poultry population
data were obtained from USDA NASS reports (USDA 1995a, 1995b, 1998a, 1999, 2004a, 2004b, 2006a, 2006b,
2007b, 2007c). Horse population data were obtained from the FAOSTAT database (FAO 2007). Goat population
data for 1992, 1997, and 2002 were obtained from the Census of Agriculture (USDA 2005); these data were
Land Use, Land-Use Change, and Forestry 7-27
-------
interpolated and extrapolated to derive estimates for the other years. Information regarding poultry turnover (i.e.,
slaughter) rate was obtained from state Natural Resource Conservation Service personnel (Lange 2000). Additional
population data for different farm size categories for dairy and swine were obtained from the 1992, 1997, and 2002
Census of Agriculture (USDA 2005).
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, and runoff and leaching. 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, aggregated to county-scale from the Parameter-elevation Regressions on Independent Slopes
Model (PRISM) database (Daly et al. 1994), were used as an input in the model simulations. Soil attributes, which
were obtained from an NRI database, were assigned based on field visits and soil series descriptions. Where more
than one inventory point was located in the same county (i.e., same weather) and had the same land-
use/management histories and soil type, data inputs to the model were identical and, therefore, these points were
clustered for simulation purposes. For the 370,738 NRI points representing non-federal cropland and grassland,
there were a total of 170,279 clustered points that represent the unique combinations of climate, soils, land use, and
management in the modeled data set. Each NRI cluster point was run 100 times as part of the uncertainty
assessment, yielding a total of over 14 million simulation runs for the analysis. C stock estimates from Century
were adjusted using a structural uncertainty estimator accounting for uncertainty in model algorithms and parameter
values (Ogle et al. 2007). Mean changes in C stocks and 95 percent confidence intervals were estimated for 1990 to
1994 and 1995 to 2000 (see Uncertainty section for more details). C stock changes from 2001 to 2006 were
assumed to be similar to the 1995 to 2000 block, 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).33 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).34 U.S. factors associated with
32 Pasture/Range/Paddock manure additions to soils are addressed in the Grassland Remaining Grassland and Land Converted
to Grassland categories.
33 The polygons displayed in Figure 7-5 through Figure 7-6 are the Major Land Resource Areas.
34 Stock change factors have been derived from published literature to reflect changes in tillage, cropping rotations and
intensification, land-use change between cultivated and uncultivated conditions, and drainage of organic soils.
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
organic matter amendments were not estimated because of an insufficient number of studies to analyze those
impacts. Instead, factors from IPCC (2003) were used to estimate the effect of those activities. Euliss and Gleason
(2002) provided the data for computing the change in SOC storage resulting from restoration of wetland enrolled in
the Conservation Reserve Program.
Similar to the Tier 3 Century method, activity data were primarily based on the historical land-use/management
patterns recorded in the NRI. Each NRI point was classified by land use, soil type, climate region (using PPJSM
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 2006 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 2006 were adjusted to account for additional C stock
changes associated with gains or losses in soil C after 1997 due to changes in Conservation Reserve Program
enrollment. The change in enrollment acreage relative to 1997 was based on data from USDA-FSA (2007) for 1998
through 2006, 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 2006.
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 mineral soil C stocks and organic soil C stocks disaggregated to the level of the inventory methodology
employed (i.e., Tier 2 and Tier 3). A combined uncertainty estimate for changes in soil C stocks occurring within
Cropland Remaining Cropland is also included. Uncertainty estimates from each component were combined using
the error propagation equation in accordance with IPCC (2006). The combined uncertainty was calculated by
taking the square root of the sum of the squares of the standard deviations of the uncertain quantities. More details
on how the individual uncertainties were developed appear later in this section. The combined uncertainty for soil
C stocks in Cropland Remaining Cropland ranged from 38 percent below and 35 percent above the 2006 stock
change estimate of -41.8 Tg CO2 Eq.
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining
Land Use, Land-Use Change, and Forestry 7-29
-------
Cropland (Tg CO2 Eq. and Percent)
Source
2006 Flux
Estimate1
(Tg C02 Eq.)
Uncertainty Range Relative to Flux
Estimate1
(Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Mineral Soil C Stocks: Cropland Remaining
Cropland, Tier 3 Inventory Methodology
Mineral Soil C Stocks: Cropland Remaining
Cropland, Tier 2 Inventory Methodology
Mineral Soil C Stocks: Cropland Remaining
Cropland (Change in CRP enrollment relative to
1997)
Organic Soil C Stocks: Cropland Remaining
Cropland, Tier 2 Inventory Methodology
(64.0)
(3.0)
(2.5)
27.7
(74.1)
(6.9)
(3.7)
15.8
(53.5)
0.8
(1.2)
36.9
-16%
-127%
-50%
-43%
+16%
+128%
+50%
+33%
Combined Uncertainty for Flux associated with
Agricultural Soil Carbon Stock Change in
Cropland Remaining Cropland
(41.8)
(57.9) (27.3)
-38%
+35%
Flux estimates based on soil C stock changes.
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. The manure amendment records were not recorded correctly in a subset of
the Century model output; corrective actions were taken to resolve this error. As discussed in the uncertainty
sections, results were compared to field measurements, and a statistical relationship was developed to assess
uncertainties in the model's predictive capability. The comparisons included over 40 long-term experiments,
representing about 800 combinations of management treatments across all of the sites (Ogle et al. 2007). Inventory
reporting forms and text were reviewed and revised as needed to correct transcription errors.
Recalculations Discussion
Two changes were implemented in the current inventory that led to a change in the time series. First, there was a
modification in the land use classification. The classification is based on the land use in a specific year of the
inventory and the previous 20 years. However, in the 1990 through 2005 inventory, each point was only classified
once based on the entire NRI time series of the land-use history. This approach led to incorrect classifications for
the early 1990s. For example, a NRI point may have been cropland in 1982, 1987 and 1992, but converted to
grassland in 1997. In the previous inventory, the NRI point would be classified as Land Converted to Grassland for
the entire inventory from 1990 through 2005. This is incorrect for the early 1990s because the point was Cropland
Remaining Cropland during those years. Second, the time series for manure N between 1990 and 2006, which was
used to adjust manure applications relative to 1997, was based on manure N available for application rather than
manure N production. Overall, the recalculations resulted in an average annual decrease of 1.9 Tg CO2 Eq. for the
period 1990 through 2005, compared to the previous inventory.
Planned Improvements
Several improvements are planned for the agricultural soil C inventory. The first improvement is to incorporate
new land-use and management activity data from the NRI. In the current inventory, NRI data only provide land-use
and management statistics through 1997, but it is anticipated that new statistics will be released in the coming year
for 2000 through 2003. The new data will greatly improve the accuracy of land-use and management influences on
soil C in the latter part of the time series.
The second improvement is to incorporate additional crops into the Tier 3 approach. Currently, crops such as
vegetables, rice, perennial and horticultural crops have not been fully implemented in the Century model
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
application. However, efforts are currently underway to further develop the model application for simulating soil C
dynamics in land managed for production of these crops. This improvement is expected to reduce uncertainties in
the inventory results.
The third improvement is to incorporate remote sensing in the analysis for estimation of crop and forage production.
Specifically, the Enhanced Vegetation Index (EVI) product that is derived from MODIS satellite imagery is being
used to refine the production estimation for the Tier 3 assessment framework. EVI reflects changes in plant
"greenness" over the growing season and can be used to compute production based on the light use efficiency of the
crop or forage (Potter et al. 1993). In the current framework, production is simulated based on the weather data, soil
characteristics, and the genetic potential of the crop. While this method produces reasonable results, remote sensing
can be used to refine the productivity estimates and reduce biases in crop production and subsequent C input to soil
systems. It is anticipated that precision in the Tier 3 assessment framework will be increased by 25 percent or more
with the new method.
The fourth improvement is to develop an automated quality control system to evaluate the results from Century
model simulations. Currently, there are over 14 million simulations, and it is not possible to manually review each
simulation. Results are aggregated and evaluated at larger scales such as MLRAs and States. QA/QC at these
larger scales may not uncover errors at the scale of individual NRI points, which is the scale at which the Century
model is used to simulate soil C dynamics. An automated system would greatly improve QA/QC, performing
checks on the results from each simulation and identifying errors for further refinements.
The final improvement is to further develop the uncertainty analysis for the Tier 3 method by addressing the
uncertainty inherent in the Century model results for other agricultural land (i.e., Grassland Remaining Grassland,
Land Converted to Grassland, and Land Converted to Cropland). In addition, uncertainties need to be addressed in
the simulation of soil C stocks for the pre-NRI time period (i.e., before 1979). In the current analysis, inventory
development focused on uncertainties in the last two decades because the management activity during the most
recent time periods will likely have the largest impact on current trends in soil C storage. However, legacy effects
of past management can also have a significant effect on current C stock trends, as well as trajectories of those C
stocks in the near future. Therefore, a planned improvement is to revise the inventory to address uncertainties in
management activity prior to 1979, providing a more rigorous accounting of uncertainties associated with the Tier 3
method.
C02 Emissions from Agricultural Liming
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 3.9 Tg CO2 Eq. to 5.0 Tg CO2 Eq. In 2006, liming of agricultural soils in the United
States resulted in emissions of 4.4 Tg CO2 Eq. (1.2 Tg C), representing about a 6 percent decrease in emissions
since 1990 (see Table 7-17 and Table 7-18).
Table 7-20: Emissions from Limingjof AgriculturaiSoils (Tg CO2 Eq.)
Source 1995^j 200° 2001 2002 2003 2004 2005 2006
Liming of Soils1 4.3 4.4 5.0 4.6 3.9 4.3 4.4
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
historical data only.
1 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to
Grassland.
Table 7-21: Emissions from Liming of Agricultural Soils (Tg C)
Source 2000 2001 2002 2003 2004 2005 2006
Liming of Soils1 1.3^ 1.2 1.2 1.4 1.2 1.1 1.2 1.2
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
Land Use, Land-Use Change, and Forestry 7-31
-------
historical data only.
1 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to
Grassland.
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 CC>2 emission factors from West and McBride (2005). These emission factors (0.059
metric ton C/metric ton limestone, 0.064 metric ton C/metric ton dolomite) are lower than the IPCC default emission
factors, because they account for the portion of agricultural lime that may leach through the soil and travel by rivers
to the ocean (West and McBride 2005). The annual application rates of limestone and dolomite were derived from
estimates and industry statistics provided in the Minerals Yearbook and Mineral Industry Surveys (Tepordei 1993,
1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006; Willett 2007; USGS 2007). To
develop these data, the U.S. Geological Survey (USGS; U.S. Bureau of Mines prior to 1997) obtained production
and use information by surveying crushed stone manufacturers. Because some manufacturers were reluctant to
provide information, the estimates of total crushed limestone and dolomite production and use were divided into
three components: (1) production by end-use, as reported by manufacturers (i.e., "specified" production); (2)
production reported by manufacturers without end-uses specified (i.e., "unspecified" production); and (3) estimated
additional production by manufacturers who did not respond to the survey (i.e., "estimated" production).
The "unspecified" and "estimated" amounts of crushed limestone and dolomite applied to agricultural soils were
calculated by multiplying the percentage of total "specified" limestone and dolomite production applied to
agricultural soils by the total amounts of "unspecified" and "estimated" limestone and dolomite production. In other
words, the proportion of total "unspecified" and "estimated" crushed limestone and dolomite that was applied to
agricultural soils (as opposed to other uses of the stone) was assumed to be proportionate to the amount of
"specified" crushed limestone and dolomite that was applied to agricultural soils. In addition, data were not
available for 1990, 1992, and 2006 on the fractions of total crushed stone production that were limestone and
dolomite, and on the fractions of limestone and dolomite production that were applied to soils. To estimate the
1990 and 1992 data, a set of average fractions were calculated using the 1991 and 1993 data. These average
fractions were applied to the quantity of "total crushed stone produced or used" reported for 1990 and 1992 in the
1994 Minerals Yearbook (Tepordei 1996). To estimate 2006 data, the previous year's fractions were 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).
The primary source for limestone and dolomite activity data is the Minerals Yearbook, published by the Bureau of
Mines through 1994 and by the USGS from 1995 to the present. In 1994, the "Crushed Stone" chapter in the
Minerals Yearbook began rounding (to the nearest thousand) quantities for total crushed stone produced or used. It
then reported revised (rounded) quantities for each of the years from 1990 to 1993. In order to minimize the
inconsistencies in the activity data, these revised production numbers have been used in all of the subsequent
calculations. Since limestone and dolomite activity data are also available at the state level, the national-level
estimates reported here were broken out by state for the first time this year, but are not reported here.
Table 7-22: Applied Minerals (Million Metric Tons)
Mineral
Limestone
Dolomite
1990^
19
2
i
1 17.30^
1
3 2000
1 15.86
1 3.81
2001
16.10
3.95
2002
20.45
2.35
2003
18.71
2.25
2004
15
2
.50
.33
2005
18.09
1.85
2006
18.20
1.87
Note: These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland
Remaining Grassland, and Land Converted to Grassland.
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
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 2006 were estimated to be between 0.2 and 8.5 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of 95 percent below to 95 percent above the 2006 emission estimate of 4.4
Tg C02 Eq.
Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of Agricultural Soils (Tg
CO2 Eq. and Percent)
„ 2006 Emissions Uncertainty Range Relative to Emissions
Source Estimate Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Liming of Agricultural Soils1
C02 4.4
Lower Upper Lower
Bound Bound Bound
0.2 8.5 -95%
Upper
Bound
95%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
1 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to
Grassland.
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 2005 has been revised. Consequently, the reported emissions resulting from
liming in 2005 have also changed. In the previous inventory, to estimate 2005 data, the previous year's fractions
were applied to a 2005 estimate of total crushed stone presented in the USGS Mineral Industry Surveys: Crushed
Stone and Sand and Gravel in the First Quarter of 2006 (USGS 2006). 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 2005. These values have replaced those used in the previous inventory to calculate the quantity of
minerals applied to soil and the emissions from liming.
C02 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 US totaled 3.6 Tg CO2 Eq. (1.0 Tg C) in 2006 (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 3.7 Tg CO2 Eq.
Table 7-24: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.)
Source 1990^ 2000 2001 2002 2003 2004 2005 2006
Urea Fertilization1 2.4^^ 2.7^^ 3.2 3.4 3.6 3.7 3.7 3.5 3.6
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
Land Use, Land-Use Change, and Forestry 7-33
-------
historical data only.
1 Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, and Land
Converted to Grassland.
Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C)
Source 1995 ^g 2000 2001 2002 2003 2004 2005 2006
Urea Fertilization1 0.9 0.9 1.0 1.0 1.0 1.0 1.0
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
historical data only.
1 Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, and Land
Converted to Grassland.
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, 1996, 1997,
1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006) 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 use data for the 2007 fertilizer year were not available in time for publication, so July through December
2006 fertilizer use was estimated by calculating the percent change (increase or decrease) in fertilizer use from
January through June 2005 to July through December 2005. This percent change was then multiplied by the
January through June 2006 data to estimate July through December 2006 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.
Table 7-26: Applied Urea (Million Metric Tons)
2000 2001 2002 2003 2004 2005 2006
Urea Fertilizer1 4.38 4.66 4.87 5.02 4.98 4.78 4.96
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
historical data only.
'These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland Remaining
Grassland, and Land Converted to Grassland.
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 may be included in
consumption totals; it was determined through personal communication with Fertilizer Regulatory Program
Coordinator David L. Terry (2007), however, that amount is most likely very small. 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 2006 were estimated to be between 2.1 and 3.8 Tg CO2 Eq. at the 95
percent confidence level. This indicates a range of 43 percent below to 3 percent above the 2006 emission estimate
of3.6TgCO2Eq.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 7-27: Quantitative Uncertainty Estimates for CO2 Emissions from Urea Fertilization (Tg CO2 Eq. and
Percent)
„ 2006 Emissions
Gas _ ,.
Estimate
(Tg CO2 Eq.)
Source * 4'
Uncertainty Range Relative to Emissions
Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Urea Fertilization CO2 3.6
2.1 3.8 -43% 3%
aRange 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, and Land Converted to Grassland.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and input, documentation, and calculation. Minor errors were
found in these steps and corrective actions were taken, including a data point that was incorrectly transcribed.
Inventory reporting forms and text were reviewed and revised as needed to correct transcription errors.
Recalculations Discussion
Emissions from Urea production and application were previously included in the Industrial Processes Chapter. That
chapter has been modified to only include emissions from Urea production.
Planned Improvements
Several improvements are planned for the urea fertilization inventory. The first 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. The second improvement is to investigate and quantify, if possible, the amount of urea that is currently
included in urea consumption totals, but is used for non-agricultural practices such as deicing.
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 in the past 20
years35 according to the USDA NRI land use survey (USDA-NRCS 2000). Consequently, the area considered in
Land Converted to Cropland changes through time with land-use change. Lands are retained in this category for 20
years as recommended by the IPCC guidelines (IPCC 2006) unless there is another land-use change. Background
on agricultural C stock changes is provided in Cropland Remaining Cropland and will only be summarized here for
Land Converted to Cropland. Soils are the largest pool of C in agricultural land, and also have the greatest potential
for storage or release of C, because biomass and dead organic matter C pools are relatively small and ephemeral
compared with soils. The IPCC/UNEP/OECD/IEA (1997) and the IPCC (2003, 2006) recommend 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.36
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 9.4 Tg CO2 Eq. (2.6 Tg C) in 2006. Emissions from mineral soils were
35 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
36 CO2 emissions associated with liming are also estimated but included in a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-35
-------
estimated at 6.7 Tg CO2 Eq. (1.8 Tg C) in 2006, while drainage and cultivation of organic soils led to annual losses
of 2.6 Tg CO2 Eq. (0.7 Tg C) in 2006.
Table 7-28: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990^^=;
14.7^^
1995^^=
\ 2000
6.7
2.6
9.4
2001
6.7
2.6
9.4
2002
6.7
2.6
9.4
2003
6.7
2.6
9.4
2004
6.7
2.6
9.4
2005
6.7
2.6
9.4
2006
6.7
2.6
9.4
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
historical data only. Totals may not sum due to independent rounding.
Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990^=;
4.0^^
1995^^=
\ 2000
1.8
0.7
2.6
2001
1.8
0.7
2.6
2002
1.8
0.7
2.6
2003
1.8
0.7
2.6
2004
1.8
0.7
2.6
2005
1.8
0.7
2.6
2006
1.8
0.7
2.6
Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
historical data only. Totals may not sum due to independent rounding.
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 sequestration in the
Intermountain West and Central United States. These areas were gaining C following conversion, because
croplands were irrigated or receiving higher fertilizer inputs relative to the previous land use. Emissions from
organic soils were largest in California, Florida and the upper Midwest, which coincided with largest concentrations
of cultivated organic soils in the United States.
Figure 7-7: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Land Converted to Cropland
Figure 7-8: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-2006
Land Converted to Cropland
Methodology
The following section includes a brief description of the methodology used to estimate changes in soil C stocks due
to agricultural land-use and management activities on mineral and organic soils for Land Converted to Cropland.
Soil C stock changes were estimated for Land Converted to Cropland according to land-use histories recorded in the
USDA NRI survey (USDA-NRCS 2000).37 Land use and some management information (e.g., crop type, soil
attributes, and irrigation) were collected for each NRI point on a 5-year cycle beginning in 1982, and were
subdivided into four inventory time periods, 1980 through 1984, 1985 through 1989, 1990 through 1994 and 1995
through 2000. NRI points were classified as Land Converted to Cropland for an inventory time period (e.g., 1990
through 1994 and 1995 through 2000) if the land use was cropland in the respective inventory time period but had
37 More recent NRI land use survey data are available and will be incorporated by the public review.
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
been another use during the previous 20 years.38 Cropland includes all land used to produce food or fiber, as well
as forage that is harvested and used as feed (e.g., hay and silage). Further elaboration on the methodologies and
data used to estimate stock changes for mineral and organic soils are provided in the Cropland Remaining Cropland
section and Annex 3.13.
Mineral Soil Carbon Stock Changes
A Tier 3 model-based approach was used to estimate C stock changes for soils on Land Converted to Cropland used
to produce a majority of all crops. 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 vegetable, tobacco, perennial/horticultural crops, and
rice; land on very gravelly, cobbly or shaley soils (greater than 35 percent by volume); and land converted from
forest or federal ownership.39
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 USDA National Resources Inventory (USDA-NRCS 2000). The methods used for Land Converted
to Cropland are the same as those described in the Tier 3 portion of Cropland Remaining Cropland Section for
mineral soils (see Cropland Remaining Cropland Tier 3 methods section for additional information).
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 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 2006.
Uncertainty
Uncertainty analysis for mineral soil C stock changes using the Tier 3 and Tier 2 approaches were based on the
same method described for Cropland Remaining Cropland, except that the uncertainty inherent in the structure of
the Century model was not addressed. 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). A combined
38 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
39 Federal land is not a land use, but rather an ownership designation that is treated as forest or nominal grassland for purposes of
these calculations. The specific use for federal lands is not identified in the NRI survey (USDA-NRCS 2000).
Land Use, Land-Use Change, and Forestry 7-37
-------
uncertainty estimate for changes in agricultural soil C stocks occurring within Land Converted to Cropland is also
included. Uncertainty estimates from each component were combined using the error propagation equation in
accordance with IPCC (2006), 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 25 percent below and 22 percent above the inventory estimate of 9.4 Tg CO2 Eq.
Table 7-30: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Land Converted to
Cropland (Tg CO2 Eq. and Percent)
2006 Flux Uncertainty Range Relative to Flux
Estimate1 Estimate1
Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
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
2.6
4.1
2.6
2.0
2.3
1.2
3.1
5.8
3.7
-21%
-44%
-53%
21%
41%
41%
Combined Uncertainty for Flux associated
with Soil Carbon Stock Change in Land
Converted to Cropland
9.4
7.0
11.4
-25%
22%
Flux estimates based on soil C stock change.
QA/QC and Verification
See QA/QC and Verification Section under Cropland Remaining Cropland.
Recalculations Discussion
Two changes were implemented in the current inventory that led to a change in the time series. First, there was a
modification in the land use classification. The classification is based on the land use in a specific year of the
inventory and the previous 20 years. However, in the 1990 through 2005 inventory, each point was only classified
once based on the entire NRI time series of the land-use history. This approach led to incorrect classifications for
the early 1990s. For example, a NRI point may have been grassland in 1982, 1987 and 1992, but converted to
cropland in 1997. In the previous inventory, the NRI point would be classified as Land Converted to Cropland for
the entire inventory from 1990 through 2005. This is incorrect for the early 1990s because the point was Grassland
Remaining Grassland during those years. Second, the time series for manure N between 1990 through 2006, which
was used to adjust manure applications relative to 1997, was based on manure N available for application rather
than manure N production. Overall, these recalculations resulted in an average annual increase in emissions of 3.3
Tg CO2 Eq. for soil C stock changes in Land Converted to Cropland over the time series from 1990 through 2005,
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 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^ 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
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
20 years40 according to the USDA NRI land use survey (USDA-NRCS 2000). Consequently, the area considered in
Grassland Remaining Grassland changes through time with land-use change. Background on agricultural C stock
changes is provided in the Cropland Remaining Cropland section and will only be summarized here for Grassland
Remaining Grassland. Soils are the largest pool of C in agricultural land, and also have the greatest potential for
storage or release of C, because biomass and dead organic matter C pools are relatively small and ephemeral
compared to soils. The IPCC/UNEP/OECD/IEA (1997) and IPCC (2003, 2006) recommend 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 during the early
1990s, but this trend was reversed over the decade, with small losses of C prevailing during the latter part of the
time series. Organic soils lost about the same amount of C in each year of the inventory. Due to the pattern for
mineral soils, the overall trend shifted from small increases in soil C during 1990 to decreases in soil C during the
latteryears of the inventory, estimated at 16.2 Tg CC>2 Eq. (4.4 Tg C) in 2006. Overall, flux rates changed by 18.1
Tg CO2 Eq. (4.9 Tg C) from 1990 to 2006.
Table 7-31: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990^^^^
1 OO^SEEEEE
16.6^=
\ 2000
12.8
3.7
16.4
2001
12.7
3.7
16.4
2002
12.7
3.7
16.4
2003
12.7
3.7
16.4
2004
12.6
3.7
16.3
2005
12.6
3.7
16.3
2006
12.5
3.7
16.2
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 CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990^^
1995^=
4.5^
\ 2000
3.5
1.0
4.5
2001
3.5
1.0
4.5
2002
3.5
1.0
4.5
2003
3.5
1.0
4.5
2004
3.4
1.0
4.5
2005
3.4
1.0
4.4
2006
3.4
1.0
4.4
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
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 is losing soil organic C in the United States largely due to droughts that
are causing small losses of C on a per hectare basis, but are occurring over a large land base. In areas with net gains
in soil organic C, sequestration was driven by irrigation and seeding legumes. Similar to Cropland Remaining
Cropland, emission rates from drained organic soils were highest along the southeastern coastal region, in the
northeast central United States surrounding the Great Lakes, and along the central and northern portions of the west
coast.
Figure 7-9: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-2006
Grassland Remaining Grassland
40 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
41 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 7-10: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-
2006 Grassland Remaining Grassland
Methodology
The following section includes a brief description of the methodology used to estimate changes in soil C stocks due
to agricultural land-use and management activities on mineral and organic soils for Grassland Remaining
Grassland.
Soil C stock changes were estimated for Grassland Remaining Grassland according to land-use histories recorded
in the USDA NRI survey (USDA-NRCS 2000).42 Land use and some management information (e.g., irrigation,
legume pastures) were collected for each NRI point on a 5-year cycle beginning in 1982, 1980 through 1984, 1985
through 1989, 1990 through 1994 and 1995 through 2000. NRI points were classified as Grassland Remaining
Grassland for an inventory time period (e.g., 1990 through 1994 and 1995 through 2000) if the land use was
grassland in the inventory time period and had been grassland for the previous 20 years.43 Grassland includes
pasture and rangeland used for grass forage production, where the primary use is livestock grazing. Rangelands are
typically extensive areas of native grassland that are not intensively managed, while pastures are often seeded
grassland, possibly following tree removal, that may or may not be improved with practices such as irrigation and
interseeding legumes. Further elaboration on the methodologies and data used to estimate stock changes from
mineral and organic soils are provided in the Cropland Remaining Cropland section and Annex 3.13.
Mineral Soil Carbon Stock Changes
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 Resources Conservation Service (Edmonds, et al. 2003), and then adjusted using county-level
estimates of manure available for application in other years of the inventory. Specifically, county-scale ratios of
manure available 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
urea 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. Managed systems include feedlots or other housing (which requires manure to be collected
and managed); unmanaged systems include daily spread, pasture, range, and paddock systems. Annual animal
42More recent NRI land use survey data are available and will be incorporated by the public review.
43 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
population data for all livestock types, except horses and goats, were obtained for all years from the U.S.
Department of Agriculture-National Agricultural Statistics Service. Population data used for cattle, swine, and
sheep were downloaded from the USDA NASS Population Estimates Database (USDA 2007a). Poultry population
data were obtained from USDA NASS reports (USDA 1995a, 1995b, 1998a, 1999, 2004a, 2004b, 2006a, 2006b,
2007b, 2007c). Horse population data were obtained from the FAOSTAT database (FAO 2007). Goat population
data for 1992, 1997, and 2002 were obtained from the Census of Agriculture (USDA 2005); these data were
interpolated and extrapolated to derive estimates for the other years. Information regarding poultry turnover (i.e.,
slaughter) rate was obtained from state Natural Resource Conservation Service personnel (Lange 2000). Additional
population data for different farm size categories for dairy and swine were obtained from the 1992, 1997, and 2002
Census of Agriculture (USDA 2005).
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). Manure
amendments were an input to the Century Model based on manure N available for application from all other
managed or unmanaged systems. 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. Nitrogen losses include direct nitrous oxide emissions, volatilization of ammonia and NOx, and
runoff and leaching. 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. See the Tier 3 methods in Cropland
Remaining Cropland section for additional discussion on the Tier 3 methodology for mineral soils.
Tier 2 Approach
The Tier 2 approach is based on the same methods described in the Tier 2 portion of Cropland Remaining Cropland
Section for mineral soils (see Cropland Remaining Cropland Tier 2 methods section for additional information).
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between 1990 and 2006 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 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 2006.
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). A combined
Land Use, Land-Use Change, and Forestry 7-41
-------
uncertainty estimate for changes in agricultural soil C stocks occurring within Grassland Remaining Grassland is
also included. Uncertainty estimates from each component were combined using the error propagation equation in
accordance with IPCC Guidelines (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 18 percent below and 15 percent above the inventory estimate of 16.2 Tg CO2 Eq.
Table 7-33: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Grassland Remaining
Grassland (Tg CO2 Eq. and Percent)
2006 Flux Uncertainty Range Relative to Flux
Estimate1 Estimate1
Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Mineral Soil C Stocks Grassland Remaining
Grassland, Tier 3 Inventory Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland (Change in Soil C due to Sewage
Sludge Amendments)
Organic Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
13.9
(0.2)
(1.2)
3.7
12.5
(0.3)
(1.7)
1.2
15.3
0.0
(0.6)
5.5
-10%
-89%
-50%
-66%
10%
127%
50%
49%
Combined Uncertainty for Flux Associated
with Agricultural Soil Carbon Stock Change
in Grassland Remaining Grassland
16.2
13.4
18.6
-18%
15%
Flux estimates based on soil C stock changes.
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 2006 to
account for additional C stock changes associated with amending grassland soils with sewage sludge.
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. The manure amendment records were not recorded correctly in a subset of
the Century model output; corrective actions were taken to resolve this error.
Recalculations Discussion
Two changes were implemented in the current inventory that led to a change in the time series. First, there was a
modification in the land use classification. The classification is based on the land use in a specific year of the
inventory and the previous 20 years. However, in the previous inventory, each point was only classified once based
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
on the entire NRI time series of the land-use history. This approach led to incorrect classifications for the early
1990s. For example, a NRI point may have been grassland in 1982, 1987 and 1992, but converted to cropland in
1997. In the previous inventory, the NRI point would be classified as Land Converted to Cropland for the entire
inventory from 1990 through 2005. This is incorrect for the early 1990s because the point was Grassland
Remaining Grassland during those years. Second, the time series for manure N between 1990 through 2006, which
was used to adjust manure applications relative to 1997, was based on manure N available for application rather
than manure N production. Overall, the recalculations resulted in an average annual decrease in emissions of 0.5 Tg
CO2 Eq. for the time series over the period from 1990 through 2005, 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 during
the previous 20 years44 according to the USDA NRI land use survey (USDA-NRCS 2000). Consequently, the area
of Land Converted to Grassland changes through time with land-use change. Lands are retained in this category for
20 years as recommended by IPCC (2006) unless there is another land use change. Background on agricultural C
stock changes is provided in Cropland Remaining Cropland and will only be summarized here for Land Converted
to Grassland. Soils are the largest pool of C in agricultural land, and also have the greatest potential for storage or
release of C, because biomass and dead organic matter C pools are relatively small and ephemeral compared with
soils. IPCC/UNEP/OECD/IEA (1997) and IPCC (2003, 2006) recommend 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.45
Land-use and management of mineral soils in Land Converted to Grassland led to an increase in soil C stocks from
1990 through 2006, which was largely caused by annual cropland converted into pasture (see Table 7-34 and Table
7-35). Stock change rates over the time series varied from -14.7 to -17.2 Tg CO2 Eq./yr (4 to 5 Tg C). 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 Tg C).
Table 7-34: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.)
Soil Type
Mineral Soils1
Organic Soils
Total Net Flux
1990!
(14.7)1
0.5!
(14.3)!
!
!
!
!
i 2000
I (17.2)
\ 0.9
1 (16.3)
2001
(17.2)
0.9
(16.3)
2002
(17.2)
0.9
(16.3)
2003
(17.2)
0.9
(16.3)
2004
(17.2)
0.9
(16.3)
2005
(17.2)
0.9
(16.3)
2006
(17.2)
0.9
(16.3)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
1 Stock changes due to application of sewage sludge are reported in Grassland Remaining Grassland.
Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C)
Soil Type 2000 2001 2002 2003 2004 2005 2006
Mineral Soils1 (4.7) (4.7) (4.7) (4.7) (4.7) (4.7) (4.7)
44 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
45 CO2 emissions associated with liming are also estimated but included in a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-43
-------
Organic Soils 0.2 0.2 0.2 0.2 0.2 0.2 0.2
Total Net Flux (4.5) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5)
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.
1 Stock changes due to application of sewage sludge in Land Converted to Grassland are reported in Grassland Remaining
Grassland.
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 southeast and northwest, and the amount of sequestration increased through the 1990s. The patterns
were driven by conversion of annual cropland into continuous pasture. Emissions from organic soils were largest in
California, Florida and the upper Midwest, which coincides with largest concentrations of organic soils in the
United States that are used for agricultural production.
Figure 7-11: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 1993-
2006 Land Converted to Grassland
Figure 7-12: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 1993-
2006 Land Converted to Grassland
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.
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).46 Land use and some management information (e.g., legume
pastures, crop type, soil attributes, and irrigation) was collected for each NRI point on a 5-year cycle beginning in
1982, and was subdivided into four inventory time periods, 1980 through 1984, 1985 through 1989, 1990 through
1994 and 1995 through 2000. NRI points were classified as Land Converted to Grassland for an inventory time
period (e.g., 1990 through 1994 and 1995 through 2000) if the land use was grassland at the end of the respective
inventory time period but had been another use in the previous 20 years.47 Grassland includes pasture and
rangeland used for grass forage production, where the primary use is livestock grazing. Rangeland typically
includes extensive areas of native grassland that are not intensively managed, while pastures are often seeded
grassland, possibly following tree removal, that may or may not be improved with practices such as irrigation and
interseeding legumes. Further elaboration on the methodologies and data used to estimate stock changes from
mineral and organic soils are provided in the Cropland Remaining Cropland section and Annex 3.13.
Mineral Soil Carbon Stock Changes
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
46 More recent NRI land use survey data are available and will be incorporated by the public review.
47 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification was based on less than 20 years of recorded land-use history for the time series from 1982 to 2001.
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.48 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 USDA
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 Cropland Tier 2 Approach 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 2006.
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). A combined
uncertainty estimate for changes in agricultural soil C stocks occurring within Land Converted to Grassland is also
included. Uncertainty estimates from each component were combined using the error propagation equation in
accordance with IPCC (2006), (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
13 percent below and 14 percent above the 2006 estimate of 16.3 Tg CO2 Eq.
Table 7-36: Quantitative Uncertainty Estimates1 for C Stock Changes occurring within Land Converted to
Grassland (Tg CO2 Eq. and Percent)
2006 Flux
Estimate1 Uncertainty Range Relative to Flux
Source (Tg CO2 Eq.) Estimate1
48 Federal land is not a land use, but rather an ownership designation that is treated as forest or nominal grassland for purposes of
these calculations. The specific use for federal lands is not identified in the NRI survey (USDA-NRCS 2000).
Land Use, Land-Use Change, and Forestry 7-45
-------
(Tg C02 Eg.)
Lower Upper Lower Upper
Bound Bound Bound Bound
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
(12.2)
(5.0)
0.9
(12.5)
(7.0)
0.2
(11.9)
(2.8)
1.8
-2%
-39%
-76%
2%
43%
104%
Combined Uncertainty for Flux associated with
Agricultural Soil Carbon Stocks in Land
Converted to Grassland
(16.3)
(18.4) (14.0) -13%
14%
Flux estimates based on soil C stock changes.
QA/QC and Verification
See the QA/QC and Verification section under Grassland Remaining Grassland.
Recalculations Discussion
Two changes were implemented in the current inventory that led to a change in the time series. First, there was a
modification in the land use classification. The classification is based on the land use in a specific year of the
inventory and the previous 20 years. However, in the 1990 through 2005 inventory, each point was only classified
once based on the entire NRI time series of the land-use history. This approach led to incorrect classifications for
the early 1990s. For example, a NRI point may have been cropland in 1982, 1987 and 1992, but converted to
grassland in 1997. In the previous inventory, the NRI point would be classified as Land Converted to Grassland for
the entire inventory from 1990 through 2005. This is incorrect for the early 1990s because the point was Cropland
Remaining Cropland during those years. Second, the time series for manure N between 1990 through 2006, which
was used to adjust manure applications relative to 1997, was based on manure N available for application rather
than manure N production. Overall, the recalculations resulted in an average annual decrease in emissions of 0.1 Tg
CO2 Eq. for the time series from 1990 through 2005, 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.
7.8. 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 78.1 Tg CO2 Eq. (21 Tg C) over the period from 1990 through
2006. Total sequestration increased by 57 percent between 1990 and 2006 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 U.S. Census data on urban
area (Table 7-37). Net C flux from urban trees in 2006 was estimated to be -95.5 Tg CO2 Eq. (-26 Tg C).
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Net C flux from urban trees is proportionately greater on an area basis than that of forests. This trend is primarily
the result of different net growth rates in urban areas versus forests—urban trees often grow faster than forest trees
because of the relatively open structure of the urban forest (Nowak and Crane 2002). Also, areas in each case are
accounted for differently. Because urban areas contain less tree coverage than forest areas, the C storage per
hectare of land is in fact smaller for urban areas. However, urban tree reporting occurs on a per unit tree cover basis
(tree canopy area), rather than total land area. Urban trees, therefore, appear to have a greater C density than
forested areas (Nowak and Crane 2002).
Table 7-37: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Tg CO2 Eq.
(60.6)
(71.5)
(82.4)
(84.6)
(86.8)
(88.9)
(91.1)
(93.3)
(95.5)
TgC
(16.5)
(19.5)
(22.5)
(23.1)
(23.7)
(24.3)
(24.9)
(25.4)
(26.0)
Note: Parentheses indicate net sequestration.
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.49 The
UFORE model is a computer model that uses standardized field data from random plots 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 15 U.S. cities: 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; and Woodbridge, NJ. The gross C sequestration estimates were
derived from field data that were collected in these 15 cities during the period from 1989 through 2006, including
tree measurements of stem diameter, tree height, crown height, and crown width, and information on location,
species, and canopy condition. The field data were converted to annual gross C sequestration rates for each species
(or genus), diameter class, and land-use condition (forested, park-like, and open growth) by applying allometric
equations, a root-to-shoot ratio, moisture contents, a C content of 50 percent (dry weight basis), an adjustment factor
to account for smaller aboveground biomass volumes (given a particular diameter) in urban conditions compared to
forests, an adjustment factor to account for tree condition (fair to excellent, poor, critical, dying, or dead), and
annual diameter and height growth rates. The annual gross C sequestration rates for each species (or genus),
49 Oakland and Chicago estimates were based on prototypes to the UFORE model.
Land Use, Land-Use Change, and Forestry 7-47
-------
diameter class, and land-use condition 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 were taken from the scientific
literature (see Nowak 1994, Nowak et al. 2002), and the adjustments to account for smaller volumes in urban
conditions were based on information in Nowak (1994). A root-to-shoot ratio of 0.26 was taken from Cairns et al.
(1997), and species- or genus-specific moisture contents were taken from various literature sources (see Nowak
1994). 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).
Annual gross C emission estimates were derived by applying estimates of annual mortality and condition, and
assumptions about whether dead trees were removed from the site, to C stock estimates. These values were derived
as intermediate steps in the sequestration calculations, and different decomposition rates were applied to dead trees
left standing compared with those removed from the site. The annual gross C emission rates for each species (or
genus), diameter class, and condition class were then scaled up to city estimates using tree population information.
Estimates of annual mortality rates by diameter class and condition class were derived from a study of street-tree
mortality (Nowak 1986). Assumptions about whether dead trees would be removed from the site were based on
expert judgment of the authors. Decomposition rates were based on literature estimates (Nowak and Crane 2002).
National annual net C sequestration by urban trees was calculated based on estimates of gross and net sequestration
from 13 of the 15 cities (Table 7-38), and urban area and urban tree cover data for the United States. Annual net C
sequestration estimates were derived for 13 cities by subtracting the annual gross emission estimates from the
annual gross sequestration estimates.^ The urban areas are based on 1990 and 2000 U.S. Census data. The 1990
U.S. Census defined urban land as "urbanized areas," which included land with a population density greater than
1,000 people per square mile, and adjacent "urban places," which had predefined political boundaries and a
population total greater than 2,500. In 2000, the U.S. Census replaced the "urban places" category with a new
category of urban land called an "urban cluster," which included areas with more than 500 people per square mile.
Urban land area has increased by approximately 36 percent from 1990 to 2000; Nowak et al. (2005) estimate that
the changes in the definition of urban land have resulted in approximately 20 percent of the total reported increase
in urban land area from 1990 to 2000. Under both 1990 and 2000 definitions, urban encompasses most cities,
towns, and villages (i.e., it includes both urban and suburban areas). The gross and net C sequestration values for
each city were divided by each city's area of tree cover to determine the average annual sequestration rates per unit
of tree area for each city. The median value for gross sequestration (0.31 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).
Table 7-38: 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/m2cover-yr) for 15 U.S. Cities
City Carbon Gross Annual Net Annual Tree Gross Annual Net Annual
50 Two cities did not have net estimates.
7-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Stocks Sequestration Sequestration Cover Sequestration per Sequestration per
Area of Tree Cover Area of Tree Cover
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
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
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
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
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%
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
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
NA = not analyzed.
Sources: Nowak and Crane (2002) and Nowak (2007a,c).
Uncertainty
Uncertainty associated with changes in C stocks in urban trees includes the uncertainty associated with urban area,
percent urban tree coverage, and estimates of gross and net C sequestration for the 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 the 15 U.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 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 (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 7-39. The net C flux
from changes in C stocks in urban trees was estimated to be between -112.1 and -76.5 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 17 percent below and 20 percent above the 2006 flux estimate of -95.5
Tg CO2 Eq.
Table 7-39: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg
CO2 Eq. and Percent)
2006 Flux
Estimate Uncertainty Range Relative to Flux Estimate
Source Gas (Tg CO2 Eq.) (TgCO2Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Changes in C Stocks in
Urban Trees CO2 (95.5) (112.1) (76.5) -17% 20%
Note: Parentheses indicate negative values or net sequestration.
Land Use, Land-Use Change, and Forestry 7-49
-------
QA/QC and Verification
The net C flux resulting from urban trees was calculated using estimates of gross and net C sequestration estimates
for urban trees and urban tree coverage area found in literature. The validity of these data for their use in this
section of the inventory was evaluated through correspondence established with an author of the papers. Through
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).
Recalculations Discussion
New data was added for six U.S. cities: Freehold, NJ; Minneapolis, MN; Moorestown, NJ; San Francisco, CA;
Washington, DC; and Woodbridge, NJ. Data for Sacramento, CA was removed from the urban trees estimates
because it was analyzed using a different methodology. These changes brought the total number of included cities
to 15, providing a better median estimate of net and gross sequestration than the previous inventory estimate based
on data from 10 U.S. cities.
There was also a slight change in the methodology for adjusting urban tree growth rates to account for tree
condition. Some of the older studies used average growth rates based on the typical growth conditions of different
land-use categories. In contrast, some of the newer studies adjust growth factors based on the condition of the tree,
which is determined using tree competition factors (depending on whether it is open grown or suppressed) for each
individual tree. The cities that use each of these methodologies are identified above in the Methodology section.
The difference that resulted from this change in methodological approach is very small and likely washes out on
average (Nowak 2007b).
These changes resulted in changes in the estimates of net annual C sequestration by urban trees for the time period
1990 through 2005. On average, estimates of net annual C sequestration by urban trees increased by 5.3 percent
over the period from 1990 to 2005 relative to the previous report.
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 term, 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 less than those
occurring on cropped soils, and, therefore, account for a smaller proportion of total U.S. soil N2O emissions per unit
area. In addition to synthetic N fertilizers, a portion of surface applied sewage sludge is applied to settlement areas.
In 2006, N2O emissions from this source were 1.5 Tg CO2 Eq. (4.7 Gg). There was an overall increase of 48
percent over the period from 1990 through 2006 due to a general increase in the application of synthetic N
7-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 7-40.
Table 7-40: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg)
Year Tg CO2 Eq. G
1990
1995
2000
2001
2002
2003
2004
2005
2006
L.O
L.2
.2
.4
.5
.5
.6
.5
.5
3.2
3.9
4.0
4.6
4.7
4.9
5.0
4.8
4.7
Note: These estimates include direct N2O emissions from N fertilizer additions only. Indirect N2O 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.
Methodology
For soils within Settlements Remaining Settlements, the IPCC Tier 1 approach was used to estimate soil N2O
emissions from synthetic N fertilizer and sewage sludge additions. Estimates of direct N2O emissions from soils in
settlements were based on the amount of N in synthetic commercial fertilizers applied to settlement soils and the
amount of N in sewage sludge applied to non-agricultural land and in surface disposal of sewage sludge.
Nitrogen applications to settlement soils are 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
2001 were used for 2002 through 2006. 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 direct N2O
emissions (IPCC 2006). The volatilized and leached/runoff proportions, calculated with the IPCC default
volatilization factors (10 or 20 percent, respectively, for synthetic or organic N fertilizers) and leaching/runoff factor
for wet areas (30 percent), were included with the total N contributions to indirect emissions, as reported in the N2O
Emissions from Agricultural Soil Management source category of the Agriculture chapter.
Uncertainty
The amount of N2O emitted from settlements depends not only on N inputs, but also on a large number of variables,
including organic C availability, O2 partial pressure, soil moisture content, pH, temperature, and irrigation/watering
practices. The effect of the combined interaction of these variables on N2O flux is complex and highly uncertain.
The IPCC default methodology 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.
Land Use, Land-Use Change, and Forestry 7-51
-------
Uncertainty in fertilizer N application was assigned a default level51 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 2006 emissions estimates. The results of the quantitative uncertainty analysis are
summarized in Table 7-41. N2O emissions from soils in Settlements Remaining Settlements in 2006 were estimated
to be between 0.8 and 3.9 Tg CO2Eq. at a 95 percent confidence level. This indicates a range of 49 percent below
to 163 percent above the 2006 emission estimate of 1.5 Tg CO2 Eq.
Table 7-41: Quantitative Uncertainty Estimates of N2O Emissions from Soils in Settlements Remaining Settlements
(Tg CO2 Eq. and Percent)
2006 Uncertainty Range Relative to 2006 Emission
Emissions Estimate
Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Settlements Remaining Settlements'.
N2O Fluxes from Soils N2O L5 0.8 3.9 -49% 163%
Note: This estimate includes direct N2O emissions from N fertilizer additions to both Settlements Remaining Settlements and
from Land Converted to Settlements.
Recalculations Discussion
A new data source was used for N fertilization in the current inventory. Instead of assuming settlement soils receive
10 percent of total synthetic N fertilizer applied in the United States, fertilization data were based on county-scale
non-farm application amounts from a database compiled by the USGS (Ruddy et al. 2006). According to the USGS
data, approximately 1.7 percent of synthetic fertilizer N sold was for non-farm use in 1990 and this gradually
increased to 3.1 percent in 2001. After subtracting forest application from non-farm fertilizer use, this change
resulted in a 75 percent decrease in the emission estimates for 2005 and an average decrease of about 78 percent
over the period from 1990 to 2005.
Planned Improvements
The key planned improvement is to estimate emissions using the process-based DAYCENT model instead of the
IPCC default methodology. DAYCENT has been used to estimate N2O emissions from agricultural soils, reducing
bias and improving precision in estimates for the cropland and grassland soils. Applying the DAYCENT model is
also anticipated to reduce uncertainties in the estimated emissions from settlement soils. In addition, this planned
improvement would incorporate state-level settlement area data from the National Resource Inventory. Another
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.
7.9. 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
51 No uncertainty is provided with the USGS application data (Ruddy et al. 2006) so a conservative ±50% was used in the
analysis.
7-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
7.10. 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. C 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. C 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 and food scraps collected annually and the fraction that is landfilled have
declined over the last decade. In 1990, over 51 million metric tons (wet weight) of yard trimmings and food scraps
were generated (i.e., put at the curb for collection to be taken to disposal sites or to composting facilities) (EPA
2007; Schneider 2007, 2008). Since then, programs banning or discouraging disposal have led to an increase in
backyard composting and the use of mulching mowers, and a consequent 7 percent decrease in the amount of yard
trimmings 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 31 percent in 2006. The net effect of the reduction in generation and the
increase in composting is a 60 percent decrease in the quantity of yard trimmings disposed in landfills since 1990.
Food scraps generation has grown by 50 percent since 1990, but the proportion of food scraps discarded in landfills
has decreased slightly from 81 percent in 1990 to 80 percent in 2006. 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 C storage from 23.9 Tg CO2 Eq. in 1990 to 10.5 Tg CO2 Eq. in 2006 (Table
7-42 and Table 7-43).
Table 7-42: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
1990^
|i|
(23.9) =
1 QQC5==
i""J^=
(12.6)^
(0.8)^
(6.0)=|
(5.8)^
(1.6) p=
(14.1)=!
i 2000
1 (8-2)
I (0.4)
j (4.0)
1 (3.7)
i (3.3)
1 (11.5)
2001
(8.5)
(0.5)
(4.1)
(3.8)
(3.1)
(11.6)
2002
(8.7)
(0.6)
(4.2)
(3.9)
(3.1)
(11.8)
2003
(7.1)
(0.4)
(3.5)
(3.2)
(2.9)
(10.0)
2004
(6.2)
(0.3)
(3.1)
(2.8)
(3.4)
(9.6)
2005
(6.5)
(0.4)
(3.2)
(2.9)
(3.5)
(10.0)
2006
(6.8)
(0.5)
(3.3)
(3.0)
(3.7)
(10.5)
Note: Totals may not sum due to independent rounding.
Table 7-43: Net Changes inYard Trimnimgand Food Scrap Stocks in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
1 oon^=
!?!
1995^
a
2000
(2.2)
(0.1)
(1.1)
(1.0)
(0.9)
2001
(2.3)
(0.1)
(1.1)
(1.0)
(0.8)
2002
(2.4)
(0.2)
(1.1)
(1.1)
(0.8)
2003
(1.9)
(0.1)
(0.9)
(0.9)
(0.8)
2004
(1.7)
(0.1)
(0.8)
(0.8)
(0.9)
2005
(1.8)
(0.1)
(0.9)
(0.8)
(0.9)
2006
(1.9)
(0.1)
(0.9)
(0.8)
(1.0)
Land Use, Land-Use Change, and Forestry 7-53
-------
Total Net Flux (6.5)^ (3.9)^ (3.1) (3.2) (3.2) (2.7) (2.6) (2.7) (2.9)
Note: Totals may not sum due to independent rounding.
Methodology
As empirical evidence shows, the removal of C from the natural cycling of C between the atmosphere and biogenic
materials, which occurs when wastes of biogenic origin are deposited in landfills, sequesters C (Barlaz 1998, 2005,
2008). When wastes of sustainable, biogenic origin (such as yard trimming and food scraps) are landfilled and do
not completely decompose, the C that remains is effectively removed from the global C cycle. Estimates of net C
flux resulting from landfilled yard trimmings and food scraps were developed by estimating the change in landfilled
C stocks between inventory years, based on methodologies presented for the Land Use, Land-Use Change and
Forestry sector in IPCC (2003). C stock estimates were calculated by determining the mass of landfilled C resulting
from yard trimmings or food scraps discarded in a given year; adding the accumulated landfilled C from previous
years; and subtracting the portion of C landfilled in previous years that decomposed.
To determine the total landfilled C stocks for a given year, the following were estimated: 1) the composition of the
yard trimmings; 2) the mass of yard trimmings and food scraps discarded in landfills; 3) the C storage factor of the
landfilled yard trimmings and food scraps adjusted by mass balance; and 4) the rate of decomposition of the
degradable C. The composition of yard trimmings was assumed to be 30 percent grass clippings, 40 percent leaves,
and 30 percent branches on a wet weight basis (Oshins and Block 2000). The yard trimmings were subdivided,
because each component has its own unique adjusted C storage factor and rate of decomposition. The mass of yard
trimmings and food scraps disposed of in landfills was 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: 2006
Facts and Figures (EPA 2007), which provides data for 1960, 1970, 1980, 1990, 2000, 2002, and 2004 through
2006. 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 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 90 percent and 10 percent respectively in 1980, to 67 percent and 33 percent in
1960).
The amount of C disposed of in landfills each year, starting in 1960, was estimated by converting the discarded
landfilled yard trimmings and food scraps from a wet weight to a dry weight basis, and then multiplying by the
initial (i.e., pre-decomposition) C content (as a fraction of dry weight). The dry weight of landfilled material was
calculated using dry weight to wet weight ratios (Tchobanoglous et al. 1993, cited by Barlaz 1998) and the initial C
contents were determined by Barlaz (1998, 2005, 2008) (Table 7-44).
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 7-44).
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 CH4 and CO2 (the CH4 emissions resulting from decomposition of yard trimmings and
food scraps are accounted for in the Waste chapter). The degradable portion of the C is assumed to decay according
to first order kinetics. 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 CH4 in the Waste chapter.
7-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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:
LFCi,t = I Wi,n x (1 - MQ) x ICQ x {[CSi x ICQ] + [(1 - (CS, x ICQ)) x e'k(t-n) ]}
n
where,
t = Year for which C stocks are being estimated (year),
i = Waste type for which C stocks are being estimated (grass, leaves, branches, food scraps),
LFC i?t = Stock of C in landfills in year /, for waste /' (metric tons),
Wj,n = Mass of waste /' disposed in landfills in year n (metric tons, wet weight),
n = Year in which the waste was disposed (year, where 1960 U
-------
in experiments. However, if the only decomposition is anaerobic, then CH4-C = CO2-C.
be defined by:
2 x CH4-C + CS = ICC
Thus, the system should
The C outputs (= 2 x CH4-C + CS ) were less than 100 percent of the initial C mass for food scraps, leaves, grass,
and branches (75, 94, 86, and 90 percent, respectively). For these materials, it was assumed that the unaccounted
for C had exited the experiment as CH4 and CO2, and no adjustment was made to the measured value of CS. The
resulting C stocks are shown in Table 7-45.
Table 7-44: 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 (% H2O)
CS, proportion of initial C stored (%)
Initial C Content (%)
Half -life (years)
Grass
70
53
45
5
Yard Trimmings
Leaves Branches
30 10
85 77
46 49
20 23
Food Scraps
70
16
51
4
Table 7-45: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Carbon Stocks
1990^
156.9 =
15.8 =
70.2 =
70.9 =
17.9^
174.8 =
;
;
;
;
;
1
1
\ 2000
\ 192.9
\ 18.3
\ 87.2
\ 87.4
\ 24.1
\ 217.1
2001
195.2
18.5
88.3
88.4
25.0
220.2
2002
197.6
18.6
89.5
89.5
25.8
223.4
2003
199.5
18.8
90.4
90.4
26.6
226.2
2004
201.2
18.8
91.3
91.1
27.5
228.8
2005
203.0
19.0
92.1
91.9
28.5
231.5
2006
204.9
19.1
93.0
92.8
29.5
234.4
Note: Totals may not sum due to independent rounding.
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). 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 7-46. Total yard
trimmings and food scraps CO2 flux in 2006 was estimated to be between -19.1 and -6.0 Tg CO2 Eq. at a 95 percent
confidence level (or 19 of 20 Monte Carlo stochastic simulations). This indicates a range of -82 percent below to 43
percent above the 2006 flux estimate of -10.5 Tg CO2 Eq. More information on the uncertainty estimates for Yard
Trimmings and Food Scraps in Landfills is contained within the Uncertainty Annex.
Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and Food Scraps in
Landfills (Tg CO2 Eq. and Percent)
52 The molar ratio of CH4 to CO2 is 1:1 for carbohydrates (e.g., cellulose, hemicellulose). For proteins as C3 2H5ON0&, me
molar ratio is 1.65 CH4 per 1.55 CO2 (Barlaz et al. 1989). Given the predominance of carbohydrates, for all practical purposes,
the overall ratio is 1:1.
7-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Source
2006 Flux
Estimate
Gas (Tg CO2 Eq.)
Uncertainty Range Relative to Flux Estimate"
(TgC02Eq.) (%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Yard Trimmings and
Food Scraps CO2 (10.5) (19.1) (6.0) -82% +43%
aRange of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate negative values or net C sequestration.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and input, documentation, and calculation.
Recalculations Discussion
The half lives of branches and food scraps were updated to be consistent with recommended values for food scraps
and woody materials provided in IPCC (2006) for analyzing landfill CH4.
The current inventory uses detailed unpublished backup data (Schneider 2007, 2008) for some years not previously
shown in the MSW Facts and Figures reports (EPA 1999, 2003, 2005, 2005a, 2006, 2007). This data included
updated generation, materials recovery, composting, combustion, and discard data for 1960, 1970, 1980, and 1990
through 2006. This newly available data allowed several previous interpolations to be replaced with the complete
time series of data used to create the MSW Facts and Figures reports (EPA 1999, 2003, 2005, 2005a, 2006, 2007).
Additionally, updated experimental results from Barlaz (2008) were incorporated. These data changed several
estimates for leaves: the initial C content (from 42 percent to 46 percent), the proportion of initial C stored (from 72
percent to 85 percent), and the C output from CH4, used as a check on the mass balance, The proportion of initial C
stored for grass also changed (from 68 percent to 53 percent). These changes are the result of a re-interpretation of
the experimental results, which combined a sample of the material being tested (e.g., leaves) with a sample of
"seed" material—decomposed refuse—containing microorganisms capable of anaerobic decomposition. Because
the seed material also contained some organic C, the mass balance had to be adjusted to net out the influence of the
C from the seed. The re-interpretation of the results accounts for differences in the rates of decomposition of the
seed along compared to the seed plus the material being tested.
These changes resulted in an average 7 percent increase in stocks across the time series and a 13 percent change in
the stocks for 2005 compared to the previous inventory.
Planned Improvements
Future work may 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 CH4 emissions described in the Waste chapter.
Land Use, Land-Use Change, and Forestry 7-57
-------
7-1
Percent of Total Land Area in Each Land-Use Category by State
Croplands
Grasslands
Wetlands
Forest Lands
Other Lands
D11%-30% D31%-50%
X-1
-------
Figure 7-2
Forest Sector Carbon Pools and Flows
Combustion from
forest fires (carbon
dioxide, methane)
Harvest
Processing/ Residue
/--^Consumption
/_ J*
soil Qrianie
Material
Decompostion Methane
Flaring
and
Utilization
Legend
Carbon Pool
Carbon transfer or flux
Combustion
Source: Heath et al. 2003
X-2 of U.S. ias and 1990-2006
-------
50
-50
o
-e
G -100
-150
#
tt -200
£
-250
, Soil
Harvested Wood
Forest, Nonsoil
Total Net Change
Figure 7-3: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools
-------
7-4
Average C Density In the Forest Tree Pool in the Conterminous U.S., 2007
.f "' "-'- '3-ft":'- >",L"" *•.
'•;&£*'. •'• \&
''-..-. i..-v|- * " ^"-!"r
• '...v/"^v*;%!-; -:.-" ;- "f •
.'. -^jSSi»;' |fX''f
Live Tree
Mg C02 Eq./ha
1-200
HI 201-400
• over 400
Note: This graphic shows county-average carbon densities for live trees on forestland, including both above- and belowground biomass. These data
are based on the most recent forest inventory survey in each state. (See Table A-3 for the most recent inventory year for each state or substate.)
X-3
-------
Figure 7-5
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland
Tg C02 Eq./year
D > 0
n-0.1 too
n-0.5 to-0.1
n-it°-°-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.
X-4 of U.S. ias and 1990-2006
-------
7-6
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States, 1993-2006
Cropland Remaining Cropland
Note: Values greater than zero represent emissions.
Tg CO, Eq./year
>2
No organic soils
X-5
-------
Figure 7-7
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States, 1993-2006
Land Converted to Cropland
Tg C02 Eq./year
D > 0
n-0.1 too
n-0.5 to-0.1
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
X-6 Inwentorf of U.S. ias and 1990-2006
-------
7-8
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States, 1993-2006
Land Converted to Cropland
Note: Values greater than zero represent emissions.
Tg CO, Eq./year
Q0.5to1
.1 to 0.5
to 0.1
No organic soils
X-7
-------
Figure 7-9
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States, 1993-2006
Grassland Remaining Grassland
Tg C02 Eq./year
D > 0
n-0.1 too
n-0.5 to-0.1
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
X-8 Inwentorf of U.S. ias and 1990-2006
-------
Figure 7-10
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States, 1993-2006
Grassland Remaining Grassland
Note: Values greater than zero represent emissions.
Tg CO, Eq./year
.stoi
.1 to 0.5
to 0.1
Q| No organic soils
X-9
-------
Figure 7-11
Total Net Annual C02 Flux For Mineral Soils Under Agricultural Management within States, 1993-2006
Land Converted to Grassland
v
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.
X-10 of U.S. ias and Sinks: 1990-2006
-------
Figure 7-12
Total Net Annual C02 Flux For Organic Soils Under Agricultural Management within States, 1993-2006
Land Converted to Grassland
<-?.*
Note: Values greater than zero represent emissions.
Tg CO, Eq./year
Q0.5to1
.1 to 0.5
to 0.1
No organic soils
X-11
-------
-------
8. Waste
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 2006,l the second
largest contribution of any CH4 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 less than 3 percent of total U.S. N2O emissions. Nitrogen
oxide (NOX), carbon monoxide (CO), and non-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.
Figure 8-1: 2006 Waste Chapter Greenhouse Gas Sources
Overall, in 2006, waste activities generated emissions of 161.0 Tg CO2 Eq., or just over 2 percent of total U.S.
greenhouse gas emissions.
Table 8-1: Emissions from Waste (Tg CO2 Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
Composting
N2O
Domestic Wastewater
Treatment
Composting
Total
1990 =
172 9^^
149.6H1
23.0^
«|
=
0.4 =
179.6^
1 QQ^SEEE
l_yy
-------
8.1. Landfills (IPCC Source Category 6A1)
In 2006, landfill CH4 emissions were approximately 125.7 Tg CO2 Eq. (5,985 Gg of CH4), representing the second
largest source of CH4 emissions in the United States, behind enteric fermentation. Emissions from municipal solid
waste (MSW) landfills, which received about 64 percent of the total solid waste generated in the United States,
accounted for about 88 percent of total landfill emissions, while industrial landfills accounted for the remainder.
Approximately 1,800 operational landfills exist in the United States, with the largest landfills receiving most of the
waste and generating the majority of the CH4 (BioCycle 2006, adjusted to include missing data from five states).
After being placed in a landfill, waste (such as paper, food scraps, and yard trimmings) is initially decomposed by
aerobic bacteria. After the oxygen has been depleted, the remaining waste is available for consumption by
anaerobic bacteria, which break down organic matter into substances such as cellulose, amino acids, and sugars.
These substances are further broken down through fermentation into gases and short-chain organic compounds that
form the substrates for the growth of methanogenic bacteria. These CH4-producing anaerobic bacteria convert the
fermentation products into stabilized organic materials and biogas consisting of approximately 50 percent carbon
dioxide (CO2) and 50 percent CH4, by volume.2 Significant CH4 production typically begins one or two years after
waste disposal in a landfill and continues for 10 to 60 years or longer.
From 1990 to 2006, net CH4 emissions from landfills decreased by approximately 16 percent (see Table 8-3 and
Table 8-4), with small increases occurring in some interim years. This downward trend in overall emissions is the
result of increases in the amount of landfill gas collected and combusted,3 which has more than offset the additional
CH4 generation resulting from an increase in the amount of municipal solid waste landfilled.
Methane emissions from landfills are a function of several factors, including: (1) the total amount of 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 CH4 that is recovered and either flared or used for
energy purposes; and (4) the amount of CH4 oxidized in landfills instead of being released into the atmosphere. The
estimated annual quantity of waste placed in MSW landfills increased from about 209 Tg in 1990 to 307 Tg in
2006, an increase of 47 percent (see Annex 3.14). During this period, the estimated CH4 recovered and combusted
from MSW landfills increased as well. In 1990, for example, approximately 888 Gg of CH4 were recovered and
combusted (i.e., used for energy or flared) from landfills, while in 2006, 5,958 Gg CH4 was combusted. In 2006, an
estimated 26 new landfill gas-to-energy (LFGTE) projects and 41 new flares began operation, resulting in a
4.4 percent increase in the quantity of CH4 recovered and combusted from 2005 levels.
Over the next several years, the total amount of municipal solid waste generated is expected to increase as the U.S.
population continues to grow. The percentage of waste landfilled, however, may decline due to increased recycling
and composting practices. In addition, the quantity of CH4 that is recovered and either flared or used for energy
purposes is expected to 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 CH4 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).
Table 8-3: CH4 Emissions from Landfills (Tg_CO2 Eq.)
Activity 2000 2001 2002 2003 2004 2005 2006
MSW Landfills 206.9 211.4 225.8 225.8 233.7 241.2 248.6
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 non-CH4 volatile
organic compounds (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: 1990-2006
-------
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
12.3 =
(13.6)=
(5.D =
(16.6) =
149.6^
1
1
1 (22.0)^
1 (16.0)^
1 144.0^
1 15.2
1 (51.3)
1 (36.7)
i (13.4)
1 120.8
15.5
(56.1)
(40.3)
(13.1)
117.6
15.8
(57.2)
(44.9)
(14.0)
120.1
15.8
(57.2)
(44.9)
(14.0)
125.6
16.0
(60.6)
(52.7)
(13.6)
122.6
16.1
(62.2)
(57.7)
(13.7)
123.7
16.2
(65.3)
(59.8)
(14.0)
125.7
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at both municipal and industrial landfills.
Table 8-4: CH4 Emissions from Landfills (Gg)
Activity
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
1990=
8,219^
585^
(646)^
(242)^
(792) =
7,124^
=
I 9,132^
I
1 (1,113)=
1 (1,047)^
m (762)^
1 6,859^
3 2000
i 9,854
3 725
m (2,441)
I (1,747)
= (639)
I 5,751
2001
10,068
739
(2,670)
(1,917)
(622)
5,598
2002
10,367
746
(2,721)
(2,037)
(636)
5,720
2003
10,754
754
(2,723)
(2,140)
(665)
5,981
2004
11,127
760
(2,888)
(2,512)
(649)
5,838
2005
11,486
760
(2,961)
(2,748)
(654)
5,890
2006
11,838
770
(3,110)
(2,848)
(665)
5,985
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at municipal and industrial landfills.
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 CH4 recovered and combusted, minus the CH4 oxidized before
being released into the atmosphere:
CH4jg0l1(j Waste = [CH4>MSW + CH4)ln(j — R] — Ox
where,
CH4>Soild Waste = CH4 emissions from solid waste
CH4 MSW = CH4 generation from municipal solid waste landfills,
CH4 md = CH4 generation from industrial landfills,
R = CH4 recovered and combusted, and
Ox = CH4 oxidized from MSW and industrial landfills before release to the atmosphere.
The methodology for estimating CH4 emissions from municipal solid waste landfills is based on the first order
decay model described by the Intergovernmental Panel on Climate Change (IPCC 2006). Values for the CH4
generation potential (L0) and rate constant (k) were obtained from an analysis of CH4 recovery rates for a database
of 52 landfills and from published studies of other landfills (RTI 2004; EPA 1998; SWANA 1998; Peer, Thorneloe,
and Epperson 1993). The rate constant was found to increase with average annual rainfall; consequently, values of
k were developed for 3 ranges of rainfall. The annual quantity of waste placed in landfills was apportioned to the 3
ranges of rainfall based on the percent of the U.S. population in each of the 3 ranges, and historical census data were
used to account for the shift in population to more arid areas over time. For further information, see Annex 3.14.
National landfill waste generation and disposal data for 1989 through 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 EP A'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,
Waste 8-3
-------
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 (MCF of 1) and those disposed in dumps (MCF of 0.6). Please see the Recalculations
Discussion section and 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 2007), and a database
maintained by the Energy Information Administration (EIA) for the voluntary reporting of greenhouse gases (EIA
2007). 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 2006 was estimated. This quantity likely
underestimates flaring because these databases do not have information on all flares in operation. Additionally, the
EIA and LMOP databases provided data on landfill gas flow and energy generation for landfills with LFGTE
projects. If a landfill in the EIA database was also in the LMOP and/or the flare vendor database, the emissions
avoided were based on the EIA data because landfill owners or operators reported the amount recovered based on
measurements of gas flow and concentration, and the reporting accounted for changes over time. If both flare data
and LMOP recovery data were available for any of the remaining landfills (i.e., not in the EIA database), then the
emissions recovery was based on the LMOP data, which provides reported landfill-specific data on gas flow for
direct use projects and project capacity (i.e., megawatts) for electricity projects. The flare data, on the other hand,
only provided a range of landfill gas flow for a given flare size. Given that each LFGTE project is likely to also
have a flare, double counting reductions from flares and LFGTE projects in the LMOP database was avoided by
subtracting emissions reductions associated with LFGTE projects for which a flare had not been identified from the
emissions reductions associated with flares.
A destruction efficiency of 99 percent was applied to CH4 recovered to estimate CH4 emissions avoided. The value
for efficiency was selected based on the range of efficiencies (98 to 100 percent) recommended for flares in EPA's
AP-42 Compilation of Air Pollutant Emission Factors, Chapter 2.4 (EPA 1998) efficiencies used to establish new
source performance standards (NSPS) for landfills, and in recommendations for closed flares used in LMOP.
Emissions from industrial landfills were estimated from activity data for industrial production, waste disposal
factors, and the first order decay model. 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 CH4 oxidized by the landfill cover at
both municipal and industrial landfills was assumed to be ten percent of the CH4 generated that is not recovered
(IPCC 2006, Mancinelli and McKay 1985, Czepiel et al. 1996). To calculate net CH4 emissions, both CH4
recovered and CH4 oxidized were subtracted from CH4 generated at municipal and industrial landfills.
Uncertainty
Several types of uncertainty are associated with the estimates of CH4 emissions from landfills. The primary
uncertainty concerns the characterization of landfills. Information is not available on two fundamental factors
affecting CH4 production: the amount and composition of waste placed in every landfill for each year of its
operation. The approach used here assumes that the CH4 generation potential and the rate of decay that produces
CH4, as determined from several studies of CH4 recovery at landfills, are representative of U.S. landfills.
Additionally, the approach used to estimate the contribution of industrial wastes to total CH4 generation introduces
uncertainty. Aside from uncertainty in estimating CH4 generation potential, uncertainty exists in the estimates of
oxidation by cover soils. There is also uncertainty in the estimates of methane that is recovered by flaring and
energy projects. The IPCC default value of 10 percent for uncertainty in recovery estimates was used in the
uncertainty analysis when metering was in place (for about 64 percent of the methane estimated to be recovered).
For flaring without metered recovery data (approximately 34 percent of the methane estimated to be recovered), a
much higher uncertainty of approximately 50 percent was used (e.g., when recovery was estimated as 50 percent of
the flare's design capacity).
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 CH4 emissions in
2006 were estimated to be between 74.7 and 168.5 TgCO2Eq., which indicates a range of 41 percent below to 34
percent above the 2006 emission estimate of 125.7 Tg CO2 Eq.
Table 8-5. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg CO2 Eq. and Percent)
2006 Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Landfills CH4 125.7 74.7 168.5 -41% +34%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 methane 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 1990 to 2006 inventory report, the proportion of waste disposed of in managed landfills versus
open dumps prior to 1980 was re-evaluated. Based on the historical data presented by Minz et al. (2003), a timeline
was developed for the transition from the use of open dumps for solid waste disposed to the use of managed
landfills. Based on this timeline, 6 percent of the waste that was land disposed in 1940 was disposed of in managed
landfills and 94 percent was managed in open dumps. Between 1940 and 1980, the fraction of waste land disposed
transitioned towards managed landfills until 100 percent of the waste was disposed of in managed landfills in 1980.
Although this timeline was based primarily on information about MSW disposal, a similar trend in disposal
practices was expected for industrial landfills; therefore, this same time line was applied to the industrial landfills.
For wastes disposed of in dumps, a methane correction factor (MCF) of 0.6 was used based on the recommended
IPCC default value for uncharacterized land disposal (IPCC 2006); this MCF is equivalent to assuming 50 percent
of the open dumps are deep and 50 percent are shallow. The recommended IPCC default value for the MCF for
managed landfills of 1 was used for the managed landfills (IPCC 2006). This recalculation reduced the MSW
landfill CH4 generation rate for the 1990 to 2005 time series by 5.6 percent, and it reduced the industrial landfill
CH4 generation rate for the 1990 to 2005 time series by 1.8 percent.
Another significant recalculation, which affected estimates of CH4 recovery, was associated with updating the EIA,
LMOP, and flare vendor databases. The estimates of gas recovery by LFGTE projects for 1990 to 2005 increased
because more landfills with operational gas recovery projects were identified and included in the LFGTE database.
However, many of these LFGTE projects did not have a corresponding flare in the flare vendor database. The gas
recovery and combustion estimates from the flare database were adjusted by deducting the recovery and combustion
estimates associated with these LFGTE projects with unmatched flares from the flare combustion totals. This
results in a decrease in the estimates for flaring. For the 1990 to 2005 time series, the recalculation resulted in an
average increase of 1.4 percent in the amount of CH4 recovered and destroyed by gas-to-energy projects and a net
decrease of 0.5 percent in the estimated CH4 emissions.
Waste 8-5
-------
Overall, these recalculations resulted in an average decrease of 7.8 percent in emissions across the time series
relative to the previous inventory.
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.
[Begin Text Box]
Box 8-1: Biogenic Emissions and Sinks of Carbon
CO2 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 CO2 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).
[End Box]
8.2. Wastewater Treatment (IPCC Source Category 6B)
Wastewater treatment processes can produce anthropogenic CH4 and N2O emissions. Wastewater from domestic
(municipal sewage) and industrial sources is treated to remove soluble organic matter, suspended solids, pathogenic
organisms, and chemical contaminants. Treatment may either occur on site, most commonly through septic systems
or package plants,4 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 biomass (sludge) is removed from the effluent prior to
discharge to the receiving stream. Microorganisms can biodegrade soluble organic material in wastewater under
aerobic or anaerobic conditions, where the latter condition produces CH4. During collection and treatment,
wastewater may be accidentally or deliberately managed under anaerobic conditions. In addition, the sludge may be
further biodegraded under aerobic or anaerobic conditions. The generation of N2O may also result from the
treatment of domestic wastewater during both nitrification and denitrification of the nitrogen present, usually in the
^Package plants are treatment plants assembled in a factory, skid mounted, and transported to the treatment site.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
form of urea, ammonia, and proteins. These compounds are converted to nitrate (NO3) through the aerobic process
of nitrification. Denitrification occurs under anoxic conditions (without free oxygen), and involves the biological
conversion of nitrate into dinitrogen gas (N2). N2O can be an intermediate product of both processes, but is more
often associated with denitrification.
The principal factor in determining the CH4 generation potential of wastewater is the amount of degradable organic
material in the wastewater. Common parameters used to measure the organic component of the wastewater are the
Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Under the same conditions,
wastewater with higher COD (or BOD) concentrations will generally yield more CH4than wastewater with lower
COD (or BOD) concentrations. BOD represents the amount of oxygen that would be required to completely
consume the organic matter contained in the wastewater through aerobic decomposition processes, while COD
measures the total material available for chemical oxidation (both biodegradable and non-biodegradable). Because
BOD is an aerobic parameter, it is preferable to use COD to estimate CH4 production. The principal factor in
determining the N2O generation potential of wastewater is the amount of N in the wastewater.
In 2006, CH4 emissions from domestic wastewater treatment were 16.0 Tg CO2 Eq. (762 Gg). Emissions gradually
increased from 1990 through 1997, but have decreased since 1998 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 2006, CH4 emissions from industrial wastewater treatment were estimated to be 7.9 Tg CO2 Eq. (374
Gg). Industrial emission sources have increased across the time series through 1999 and then fluctuated up and
down in keeping with production changes associated with the treatment of wastewater from the pulp and paper
manufacturing, meat and poultry processing, fruit and vegetable processing, and starch-based ethanol production
industries.5 Table 8-6 and Table 8-7 provide CH4 and N2O emission estimates from domestic and industrial
wastewater treatment. With respect to N2O, the United States identifies two distinct sources for 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 2006 emissions of N2O
from centralized wastewater treatment processes and from effluent were estimated to be 0.3 Tg CO2 Eq. (1 Gg) and
7.8 Tg CO2 Eq. (25 Gg), respectively. Total N2O emissions from domestic wastewater were estimated to be 8.1 Tg
CO2 Eq. (26 Gg). N2O emissions from wastewater treatment processes gradually increased across the time series as
a result of increasing U.S. population and protein consumption.
Table 8-6. CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.)
Activity
CH4
Domestic
Industrial*
N2O
Domestic
Total
1990^
23.0^
16.4^
6.6^
6.3^
6.3^
29.3^
i
1
i
i
1
I
I
i 2000
1 24.6
i 16.8
i 7.8
1 7.6
1 7.6
3 32.2
2001
24.2
16.6
7.5
7.8
7.8
32.0
2002
24.1
16.5
7.6
7.6
7.6
31.7
2003
23.9
16.4
7.6
7.7
7.7
31.6
2004
24.0
16.3
7.7
7.8
7.8
31.8
2005
23.8
16.2
7.6
8.0
8.0
31.8
2006
23.9
16.0
7.9
8.1
8.1
32.0
* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, and
starch-based ethanol production industries.
Note: Totals may not sum due to independent rounding.
Table 8-7. CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
CH4
Domestic
Industrial*
1990^
1,096^
782^
314^
=
1 1,158 =
=
1
i 2000
1 1,173
i 802
1 371
2001
1,150
792
358
2002
1,148
786
362
2003
1,140
780
360
2004
1,141
775
366
2005
1,131
770
361
2006
1,136
762
374
5 Other industrial sectors include organic chemicals, starch production, alcohol refining, creameries, and textiles; however,
emissions from these sectors are considered to be insignificant.
Waste 8-7
-------
N^O 20^^^ 22^^^ 24 25 25 25 25 26 26
Domestic 24 25 25 25 25 26 26
* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, and
starch-based ethanol production industries.
Note: Totals may not sum due to independent rounding.
Methodology
Domestic Wastewater CH4 Emission Estimates
Domestic wastewater CH4 emissions originate from both septic systems and from centralized treatment systems,
such as publicly owned treatment works (POTWs). Within these centralized systems, CH4 emissions can arise from
aerobic systems that are not well managed, anaerobic systems (anaerobic lagoons and facultative lagoons), and from
anaerobic digesters when the captured biogas is not completely combusted. CH4 emissions from septic systems
were estimated by multiplying the total BOD5 produced in the United States by the percent of wastewater treated in
septic systems (21 percent), the maximum CH4 producing capacity for domestic wastewater (0.60 kg CH4/kg BOD),
and the CH4 correction factor (MCF) for septic systems (0.5). CH4 emissions from POTWs were estimated by
multiplying the total 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 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 CH^m3 CH4), and the destruction efficiency associated with burning the biogas in
an energy/thermal device (0.99)6 The methodological equations are:
Emissions from Septic Systems = A
= (% onsite) x (total BOD5 produced) x (B0) x (MCF-septic) x 1/10A6
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 (l-% BOD removed in prim, treat.)] x (% operations not well
managed) x (B0) x (MCF-aerobic_not_well_man) x 1/10A6
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 1/10A6
Emissions from Anaerobic Digesters = D
= [(POTW_flow_AD) x (digester gas)/(per capita flow)] x conversion to m3 x (FRAC_CH4) x (365.25) x (density
ofCH4) x (1-DE) x 1/10A9
Total CH4 Emissions (Gg) = A + B + C + D
Where:
% onsite = Flow to septic systems / total flow
% collected = Flow to POTWs / total flow
6 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).
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
% aerobic =
% anaerobic =
% aerobic 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 =
B0 =
MCF-septic =
1/10A6 =
MCF-aerobic_not_well_man. =
MCF-anaerobic =
DE =
POTW_flow_AD =
digester gas =
per capita flow =
conversion to m3=
FRAC_CH4 =
density of CH4 =
1/10A9 =
Flow to aerobic systems / total flow to POTWs
Flow to anaerobic systems / total flow to POTWs
Percent of aerobic systems that do not employ primary treatment
Percent of aerobic systems that employ primary treatment
32.5 %
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/kgBOD)
CH4 correction factor for septic systems (0.5)
Conversion factor, kg to Gg
CH4 correction factor for aerobic systems that are not well managed
(0.3)
CH4 correction factor for anaerobic systems (0.8)
CH4 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)
Wastewater flow to POTW per person per day (100 gal/person/day)
Conversion factor, ft3 to m3 (0.0283)
Proportion CH4 inbiogas (0.65)
662 (g CH4/m3 CH4)
Conversion factor, g to Gg
U.S. population data were taken from the U.S. Census Bureau International Database (U.S. Census 2007a) and
include the populations of the United States, American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and
the Virgin Islands. Table 8-8 presents U.S. population and total BOD5 produced for 1990 through 2006. 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 2007b), with data for intervening years obtained by linear interpolation. The
wastewater flow to aerobic systems and anaerobic systems, and the wastewater flow to POTWs that have anaerobic
digesters were obtained from the 1992, 1996, 2000, and 2004 Clean Watershed Needs Survey (EPA 1992, 1996,
2000, and 2004a).7 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 CH4 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 new
source performance standards (NSPS) for landfills, and in recommendations for closed flares used by LMOP. The
cubic feet of digester gas produced per person per day (1.0 ft3/person/day) and the proportion of CH4 in biogas
(0.65) come from Metcalf and Eddy (1991). The wastewater flow to a POTW (100 gal/person/day) was taken from
the Great Lakes-Upper Mississippi River Board of State and Provincial Public Health and Environmental Managers,
"Recommended Standards for Wastewater Facilities (Ten-State Standards)" (2004).
7 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.
Waste 8-9
-------
Table 8-8. U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Population
254
271
287
289
292
295
297
300
303
BOD5
8,350
8,895
9,419
9,509
9,597
9,685
9,774
9,864
9,954
Source: U.S. Census Bureau (2006a); Metcalf & Eddy 1991 and 2003.
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 four industries that meet these criteria are pulp and paper manufacturing; meat and poultry processing;
vegetables, fruits, and juices processing; and starch-based ethanol production. Table 8-9 contains production data
for these industries.
Table 8-9. U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg)
Meat Poultry Vegetables,
Year Pulp and Paper (Live Weight Killed) (Live Weight Killed) Fruits and Juices Ethanol
1990
1995
2000
2001
2002
2003
2004
2005
2006
128.9
140.9
142.8
134.3
132.7
131.9
136.4
131.4
137.4
27.3
30.8
32.1
31.6
32.7
32.3
31.2
31.4
32.5
14.6
18.9
22.2
22.8
23.5
23.7
24.4
25.1
25.5
38.7
46.9
50.9
45.0
47.7
44.8
47.8
43.3
42.6
2.7
4.2
4.9
5.3
6.4
8.4
10.2
11.7
14.5
CH4 emissions from these categories were estimated by multiplying the annual product output by the average
outflow, the organics loading (in COD) in the outflow, the percentage of organic loading assumed to degrade
anaerobically, and the emission factor. Ratios of BOD :COD in various industrial wastewaters were obtained from
EPA (1997a) and used to estimate COD loadings. The B0 value used for all industries is the IPCC default value of
0.25 kg CH4/kg COD (IPCC 2006). The methodological equation is:
CH4 (industrial wastewater) = P x W x COD x TA x B0 x MCF
Where:
CH4 (industrial wastewater)
P
W
COD
TA
= Total CH4 emissions from industrial wastewater (kg/year)
= Industry output (metric tons/year)
= Wastewater generated (m3/metric ton of product)
= Organics loading in wastewater (kg /m3)
= Percent of wastewater treated anaerobically on site
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
B0 = Maximum CH4 producing potential of industrial wastewater (default value of
0.25 kg CH4/kg COD)
MCF = CH4 correction factor, indicating the extent to which the organic content
(measured as COD) degrades anaerobically
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 1993b). 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
1993b). 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). Therefore, the pulp and paper CH4 emission
calculation is:
Methane = Production x Flow x BOD x 42% x COD:BOD Ratio x %TA x Bo x MCF
Where:
Production = metric tons of pulp, paper, and paperboard production
Flow = cubic meters of wastewater generated per ton production
BOD = BOD concentration in influent (4000 mg/L)
42% = Percent of BOD entering secondary treatment
COD:BOD = COD to BOD ratio (for pulp and paper, COD:BOD = 2)
%TA = estimated percent of wastewater treated anaerobically on site (25%)
Bo = maximum methane producing capacity (0.25 mg CH4/mg COD)
MCF = methane conversion factor for anaerobic deep lagoons (0.80)
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
2006 (Pulp and Paper 2005, 2006 and monthly reports from 2003 through 2006; Paper 360° 2007). The overall
wastewater outflow was estimated to be 85 nrVmetric ton, and the average BOD concentrations in raw wastewater
was estimated to be 0.4 gram BOD/liter (EPA 1997b, EPA 1993b, World Bank 1999).
The meat and poultry processing industry makes extensive use of anaerobic lagoons in sequence with screening, fat
traps and dissolved air flotation when treating wastewater on site. About 33 percent of meat processing operations
(EPA 2002) and 25 percent of poultry processing operations (U.S. Poultry 2006) perform on-site treatment in
anaerobic lagoons. The IPCC default B0 of 0.25 kg CH^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 USD A Agricultural Statistics
Database and the Agricultural Statistics Annual Reports (USD A 2007a). Data collected by EPA's Office of Water
provided estimates for wastewater flows into anaerobic lagoons: 5.3 and 12.5 mVmetric 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.
Waste 8-11
-------
Treatment of wastewater from fruits, vegetables, and juices processing includes screening, coagulation/settling and
biological treatment (lagooning). The flows are frequently seasonal, and robust treatment systems are preferred for
on-site treatment. Effluent is suitable for discharge to the sewer. This industry is likely to use lagoons intended for
aerobic operation, but the large seasonal loadings may develop limited anaerobic zones. In addition, some
anaerobic lagoons may also be used (Nemerow and Dasgupta 1991). Consequently, 5 percent of these wastewater
organics are assumed to degrade anaerobically. The IPCC default B0 of 0.25 kg CH4/kg COD and default MCF of
0.8 for anaerobic treatment were used to estimate the CH4 produced from these on-site treatment systems. The
USD A National Agricultural Statistics Service (USDA 2007a) provided production data for potatoes, other
vegetables, citrus fruit, non-citrus fruit, and grapes processed for wine. Outflow and BOD data, presented in Table
8-10, were obtained from EPA (1974) for potato, citrus fruit, and apple processing, and from EPA (1975) for all
other sectors.
Table 8-10. Wastewater Flow (nrVton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices
Production
Wastewater Outflow
Commodity (m3/ton)
Vegetables
Potatoes
Other Vegetables
Fruit
Apples
Citrus
Non-citrus
Grapes (for wine)
10.27
8.86
3.66
10.11
12.42
2.783
BOD
(g/L)
1.765
0.813
1.371
0.317
1.204
1.831
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 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).
Available information was compiled from the industry on wastewater generation rates, which ranged from 1.25
gallon per gallon ethanol produced (for dry milling) to 10 gallons per gallon ethanol produced (for wet milling)
(Ruocco 2006a,b; Merrick 1998; Donovan 1996; and NRBP 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
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
(ERG 2006). CH4 emissions were then estimated as follows:
Methane = [Production x Flow x COD x 3.785 x % TA x Bo x MCF x % Not Recovered] + [Production x Flow x
3.785 x COD x %TA x Bo x MCF x (% Recovered) x (1-DE)] x 1/10A9
Where:
Production = gallons ethanol produced (wet milling or dry milling)
Flow = gallons wastewater generated per gallon ethanol produced (1.25 dry milling,
10 wet milling)
COD = COD concentration in influent (3 g/1)
3.785 = conversion, gallons to liters
% TA = percent of wastewater treated anaerobically (for dry milling operations, this
value is estimated separately for facilities using biomethanators with 100%
recovery and facilities using other anaerobic systems)
Bo = maximum methane producing capacity (0.25 g CH4/g COD)
MCF = methane conversion factor (0.8 for anaerobic systems)
% Recovered = percent of wastewater treated in system with emission recovery
% Not Recovered = 1 - percent of wastewater treated in system with emission recovery
DE = destruction efficiency of recovery system (99%)
1/10A9 = conversion factor, g to Gg
A time series of CH4 emissions for 1990 through 2006 was developed based on production data from the Renewable
Fuels Association (RFA 2006).
Domestic Wastewater N2O Emission Estimates
N2O emissions from domestic wastewater (wastewater treatment) were estimated using the IPCC (2006)
methodology, including calculations that take into account N removal with sewage sludge, non-consumption and
industrial wastewater N, and emissions from advanced centralized wastewater treatment plants:
• In the United States, a certain amount of N is removed with sewage sludge, which is applied to land,
incinerated or landfilled (NSLUDGE)- The N disposal into aquatic environments is reduced to account for the
sewage sludge application.8
• The IPCC methodology uses annual, per capita protein consumption (kg protein/[person-year]). This number is
likely to underestimate the amount of protein entering the sewer or septic system. Food (waste) that is not
consumed is often washed down the drain, as a result of the use of garbage disposals. Also, bath and laundry
water can be expected to contribute to N loadings. As a result, a factor of 1.4 for non-consumption N is
introduced for each year in the Inventory.9 Furthermore, a significant quantity of industrial wastewater (N) is
co-discharged with domestic wastewater. To account for this, a factor of 1.25 is used.10
8 The methodology for estimating the quantity of sewage sludge N not entering aquatic environments is described in Annex 3.11
9 Metcalf & Eddy (1991) provide a typical influent nitrogen concentration of 40 mg/L Total Kjeldahl Nitrogen (TKN) for
average wastewater from residences, which includes bathwater, laundry, and the use of garbage disposals. The factor for non-
consumptive protein was estimated based on wastewater treated in 1990, the percent of population serviced by centralized
treatment systems, and the per capita TKN loading, resulting in a factor of 1.4.
10 The type, composition, and quantity of this co-discharged wastewater vary greatly between municipalities. Metcalf & Eddy
(1991) provide a range of influent nitrogen concentrations of 20 to 85 mg/L TKN (average 55) for combined residential and
industrial wastewater, while residential wastewater loading was roughly estimated at 40 mg TKN/liter (see previous footnote).
Until better data become available, the amount of N in wastewater is increased by 10 mg/L to account for industrial co-discharge
Waste 8-13
-------
• Small amounts of gaseous nitrogen oxides are formed as by-products in the conversion of nitrate to N gas in
anoxic biological treatment systems. Approximately 7 grams N2O is generated per capita per year if wastewater
treatment includes intentional nitrification and denitrification (Scheehle and Doom 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
N20MT/DENII= [(USPOPND) x EF2 x F^.COM] x 1/10*9
N20WOOTMT/DEMT = {[(USPOP x WWTP) - USPOPNDx FIND_COM] x EFJ x 1/10*9
NZOHFFLUHNT = {[(USpop x Protein x F^ x FNON.CON x F^.^) - NSLUDGE] x EF3 x 44/28} x l/lOA6
where,
N2OToiAL = Annual emissions of N2O (kg)
N2OPLANT = N2O emissions from centralized wastewater treatment plants (kg)
N2OMT/DEMT = N2O emissions from centralized wastewater treatment plants with
nitrification/denitrification (kg)
N2OWour MT/DENIT = N2O emissions from centralized wastewater treatment plants without
nitrification/denitrification (kg)
N2OEFFLUENT = N2O emissions from wastewater effluent discharged to aquatic environments (kg)
USpop = U.S. population
USPOPND = U.S. population that is served by biological denitrification (from CWNS)
WWTP = Fraction of population using WWTP (as opposed to septic systems)
EFi = Emission factor (3.2 g N2O/person-year)
EF2 = Emission factor (7 g N2O/person-year)
Protein = Annual per capita protein consumption (kg/person/year)
FNPR = Fraction of N in protein, default = 0.16 (kg N/kg protein)
FNON-CON = Factor for non-consumed protein added to wastewater (1.4)
FIND-COM = Factor for industrial and commercial co-discharged protein into the sewer system (1.25)
NSLUDGE = N removed with sludge, kg N/yr
EF3 = Emission factor (0.005 kg N2O -N/kg sewage-N produced)
44/28 = Molecular weight ratio of N2O to N2
U.S. population data were taken from the U.S. Census Bureau International Database (U.S. Census 2007a) and
include the populations of the United States, American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and
the Virgin Islands. The fraction of the U.S. population using wastewater treatment plants is based on data from the
1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, and 2005 American Housing Survey (U.S. Census 2007b). Data
for intervening years were obtained by linear interpolation. The emission factor (EF^ to estimate emissions from
wastewater treatment was taken from IPCC (2006). Data on annual per capita protein intake were provided by U.S.
(factor of 1.25).
8-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Department of Agriculture Economic Research Service (ERS 2006b). Protein consumption data for 2005 and 2006
were extrapolated from data for 1990 through 2004. Table 8-11 presents the data for U.S. population and average
protein intake. An emission factor to estimate emissions from effluent (EF3) has not been specifically estimated for
the United States, thus the 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) for 1988, 1996, and 1998 and from Beecher et al. (2007) for 2004. Intervening years were interpolated,
and estimates for 2005 and 2006 were forecasted from the rest of the time series. An estimate for the nitrogen
removed as sludge (NSLIIDGE) 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 2006, 263 Tg
N was removed with sludge.
Table 8-11. U.S. Population (Millions) and Average Protein Intake [kg/(person-year)J
Year
1990
1995
2000
2001
2002
2003
2004
2005
2006
Population
254
271
287
289
292
295
297
300
303
Protein
38.7
39.8
41.3
42.0
40.9
40.9
41.3
41.7
41.9
Source: U.S. Census Bureau 2006a, USDA ERS 2006b.
Uncertainty
The overall uncertainty associated with both the 2006 CH4 and N2O emissions estimates from wastewater treatment
and discharge was calculated using the IPCC Good Practice Guidance Tier 2 methodology (2000). Uncertainty
associated with the parameters used to estimate CH4 emissions include that of numerous input variables used to
model emissions from domestic wastewater, and wastewater from pulp and paper manufacture, meat and poultry
processing, fruits and vegetable processing, and ethanol production. 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.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 8-12. CH4 emissions from
wastewater treatment were estimated to be between 15.0 and 35.2 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 37 percent below to
48 percent above the 2006 emissions estimate of 23.9 Tg CO2 Eq. N2O emissions from wastewater treatment were
estimated to be between 1.8 and 16.2 Tg CO2Eq., which indicates a range of approximately 78 percent below to
100 percent above the actual 2006 emissions estimate of 8.1 Tg CO2 Eq.
Table 8-12. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg CO2 Eq.
and Percent)
2006
Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(TgC02Eq.) (TgC02Eq.)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
CH
Wastewater Treatment 4 23.9 15.0 35.2 -37% +48%
Waste 8-15
-------
Domestic CH4 16.0 7.9 26.6 -51% +66%
Industrial CH4 7.9 4.5 12.8 -43% +62%
Domestic Wastewater N2
Treatment O 8.1 1.8 16.2 -78% +100%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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 2006 estimates for CH4 emissions from domestic wastewater include one major methodological refinement and
one major data change. First, for centralized wastewater treatment systems, CH4 emissions were estimated based on
the total BOD5 available for biological treatment rather than the total BOD5 entering wastewater treatment plants.
Metcalf and Eddy (1991) estimate that 25-40 percent of BOD5 at aerobic and anaerobic plants is removed through
primary sedimentation, meaning that not all of the BOD5 entering treatment plants has the potential to generate
methane during biological treatment. This change resulted in a decrease of methane emissions from centrally treated
anaerobic systems of 20 percent, and an overall reduction in methane emissions of 4.5 to 5.5 percent. The major
data adjustment for the current inventory estimates involved the adjustment of the 1995 AHS data (US Census
Bureau 2007b) that indicates the percent of wastewater treated onsite versus the percent collected. The previous
Inventory indicated a total percent of wastewater treated onsite and collected of 97.6 percent for 1995, while all
other years had a total of approximately 99.5 percent. Reevaluation of the 1995 AHS data resulted in an updated
total percent of 99.5 percent.
For industrial wastewater, the 2006 estimates include a change in calculation methodology for pulp and paper, and
the inclusion of wastewater emissions from U.S. starch-based ethanol production. First, the types of primary
treatment in place at pulp and paper operations were evaluated and it was concluded that due to the majority of
operations using mechanical clarifiers, negligible emissions of CH4 occur during primary treatment. The estimate of
BOD treated anaerobically during secondary treatment was also updated based on the number of operations
expected to have non-aerated stabilization basins. These systems were reclassified as anaerobic deep lagoons, and
CH4 emissions were revised. These changes resulted in a decrease in emissions from pulp and paper wastewater
treatment of 18.5 percent across the time series.
Next, emissions associated with ethanol production were estimated, as described earlier. The addition of this
industrial sector increased industrial wastewater emission estimates by 0.4 to 0.9 percent across the time series.
Flow and BOD data for fruits and vegetable processing wastewater were updated to reflect commodity-specific
data, which had minimal impact on the emissions. Overall, the CH4 emission estimates for wastewater treatment are
on average 6 percent lower than the previous inventory.
8-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
For N2O emissions from domestic wastewater, one major data source adjustment was made along with two minor
changes to account for co-discharged industrial and commercial wastewater and to update the values used for the
nitrogen composition of sludge. The 2006 estimates utilize protein consumption data from the U.S. Department of
Agriculture Economic Research Service (USDA 2006b). The previous inventory report used UN FAO protein
consumption data. The protein data changed on average approximately one percent for each year in the timeseries.
The 2006 estimates also apply a factor for co-discharged industrial and commercial wastewater to the emission
factors for direct N2O emissions from centralized wastewater treatment plants. This resulted in a N2O emission
factor from centralized treatment plants that have intentional nitrification/denitrification unit operations of 8.75 g
N2O/person-year (7 g N2O/person-year x 1.25) and a N2O emission factor from centralized wastewater treatment
plants that do not have intentional nitrification/denitrification unit operations of 4 g N2O/person-year (3.2 g
N2O/person-year x 1.25). In addition, the nitrogen composition of sludge was updated to 3.9 percent, representing
an average nitrogen composition, rather than the previous value of 3.3 percent which represented a median value.
The sludge generation estimates across the time series changed slightly based on the inclusion of a new reference
for sludge generation in 2004.
Overall, emissions from wastewater treatment and discharge (CH4 and N2O) decreased by an average of
approximately 5 percent from the previous inventory.
Planned Improvements Discussion
The methodology to estimate CH4 emissions from domestic wastewater treatment currently utilizes estimates for the
percentage of centrally treated wastewater that is treated by aerobic systems and anaerobic systems. These data
come from the 1992, 1996, 2000, and 2004 CWNS. The designation of systems as aerobic or anaerobic could be
further refined to differentiate aerobic systems with the potential to generate small amounts of CH4 (aerobic
lagoons) versus other types of aerobic systems, and to differentiate between anaerobic systems to allow for the use
of different MCFs for different types of anaerobic treatment systems. Currently it is assumed that all aerobic
systems are well managed and produce no CH4] and that all anaerobic systems have an MCF of 0.8. Efforts to
obtain better data reflecting emissions from various types of municipal treatment systems are currently being
pursued.
Available data on wastewater treatment emissions at petroleum refineries 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 products of composting, depending on its quality, can
be recycled as fertilizer and soil amendment, or be disposed in a landfill.
Composting is an aerobic process and a large fraction of the degradable organic carbon in the waste material is
converted into carbon dioxide (CO2). Methane (CH4) 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 per cent of the initial carbon content in the
Waste 8-17
-------
material (IPCC 2006). Composting can also produce emissions of nitrous oxide (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).
From 1990 to 2006, the amount of material composted in the United States has increased from 3,810 Ggto 18,852
Gg, an increase of almost 400 percent. Emissions of CH4 and N2O from composting have increased by the same
percentage (see Table 8-13 and Table 8-14). In 2006, CH4 emissions from composting were 1.6 Tg CO2 Eq. (75
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 started 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).
Table 8-13: CH4 and N2O Emissions from Composting (Tg CO2 Eq.)
Activity
CH4
N20
Total
1990
0.3
0.4
0.7
1995
0.7
0.8
1.5
2000
1.3
1.4
2.6
2001
1.3
1.4
2.7
2002
1.3
1.4
2.7
2003
1.5
1.6
3.1
2004
1.6
1.7
3.3
2005
1.6
1.7
3.3
2006
1.6
1.8
3.3
Table 8-14: CH4 and N2O Emissions from Composting (Gg)
Activity
CH4
N2O
1990
15
1
1995
35
3
2000
60
4
2001
60
5
2002
61
5
2003
69
5
2004
74
6
2005
75
6
2006
75
6
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 8-13 and Table 8-14 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 CH4
recovery is expected to occur at composting operations):
Et = MxEFt
where,
E! = CH4 or N2O emissions from composting, Gg CH4 or N2O,
M = mass of organic waste composted in Gg,
EF; = emission factor for composting, 4 g CH^/kg of waste treated (wet basis) and 0.3 g
N2O/kg of waste treated (wet basis), and
i = designates either CH4 or N2O.
Estimates of the quantity of waste composted (M) are presented in Table 8-15. Estimates of the quantity composted
for 1990, 1995, 2001, and 2002 were taken from EPA's Municipal Solid Waste Generation, Recycling, and
Disposal in the United States: Facts and Figures for 2003 (EPA 2005); estimates of the quantity composted for
2003 through 2005 were taken from EPA's Municipal Solid Waste In The United States: 2005 Facts and Figures
(EPA 2006). The quantity composted estimate for 2006 was taken from the "2006 MSW Characterization Data
Tables" associated with EPA's Municipal Solid Waste In The United States: 2006 Facts and Figures (EPA 2007).
8-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Table 8-15: U.S. Waste Composted (Gg)
Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006
Waste Composted 3,810 8,682 14,923 15,014 15,187 17,309 18,570 18,643 18,852
Source: EPA 2005, EPA 2006, and EPA 2007.
Uncertainty
The estimated uncertainty from the 2006 IPCC Guidelines is ±50 percent for the Tier 1 methodology. Emissions
from composting in 2006 were estimated to be between 1.7 and 5.0 Tg CO2 Eq., which indicates a range of 50
percent below to 50 percent above the actual 2006 emission estimate of 3.3 Tg CO2 Eq. (see Table 8-16).
Table 8-16 : Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg CO2 Eq. and Percent)
Source
2005
Emission
Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Composting CH4, N2O 3.3 L7 5.0 -50% +50%
Recalculations Discussion
No recalculations were performed because this is the first year that composting has been included in the inventory.
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 2006 are provided in Table 8-17.
Table 8-17: Emissions of NOX, CO, and NMVOC from Waste (Gg)
Gas/Source
NOX
Landfills
Wastewater Treatment
Miscellaneous3
CO
Landfills
Wastewater Treatment
Miscellaneous3
NMVOCs
Wastewater Treatment
Miscellaneous3
Landfills
1990^
I
I
I
I
1
!
1
l
I
I 731^
!
!
!
1 2000
1 2
1 2
1 +
1 +
1 8
1 7
1 1
1 +
1 H9
1 23
1 51
1 46
2001
2
2
+
+
8
7
1
+
122
23
53
46
2002
2
2
+
+
7
6
+
+
115
22
50
44
2003
2
2
+
+
7
6
+
+
114
22
49
43
2004
2
2
+
+
7
6
+
+
112
21
48
43
2005
2
2
+
+
7
6
+
+
111
21
48
42
2006
2
2
+
+
7
6
+
+
110
21
47
42
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.
+ Does not exceed 0.5 Gg.
Waste 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 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: 1990-2006
-------
Landfills
Composting
I
Waste as a Portion of
all Emissions
2.3%
20
40
60 80
TgCO2Eq.
100
120
140
Figure 8-1: 2006 Waste Chapter Greenhouse Gas Sources
-------
-------
9. Other
The United States does not report any greenhouse gas emissions under the Intergovernmental Panel on Climate
Change (IPCC) "Other" sector.
Other 9-1
-------
-------
10. Recalculations and Improvements
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S.
Greenhouse Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the
use of better methods or data, and the overall usefulness of the report. In this effort, the United States follows the
Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (IPCC 2000), which states, "It is
good practice to recalculate historic emissions when methods are changed or refined, when new source categories
are included in the national inventory, or when errors in the estimates are identified and corrected."
The results of all methodology changes and historical data updates are presented in this section; detailed
descriptions of each recalculation are contained within each source's description contained in this report, if
applicable. Table 10-1 summarizes the quantitative effect of these changes on U.S. greenhouse gas emissions and
Table 10-2 summarizes the quantitative effect on U.S. sinks, both relative to the previously published U.S.
Inventory (i.e., the 1990 through 2005 report). These tables present the magnitude of these changes in units of
teragrams of carbon dioxide equivalent (Tg CO2 Eq). In addition to the changes summarized by the tables below,
the following sources and gases were added to the current inventory:
• CO2 emissions from Cropland remaining Cropland, which include CO2 emissions from agricultural liming and
urea fertilization;
• CO2 emissions from Petroleum Systems, which account for vented, fugitive and process upset emissions
sources from 29 activities for crude oil production field operations; and
• CH4 and N2O emissions from Composting.
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 2005) 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 2005, underwent some of the most important methodological and historical data
changes. A brief summary of the recalculation and/or improvement undertaken is provided for each emission
source.
• Agricultural Soil Management. Changes occurred as a result of incorporating state-level N fertilizer application
data for on-farm use as opposed to regional data, revising assumptions of manure N availability for land
application, and revising DAYCENT parameterization for sorghum. Overall, changes resulted in an average
annual decrease in N2O emissions from Agricultural Soil Management of 102.1 Tg CO2 Eq. (27.5 percent) for
the period 1990 through 2005.
• Net CO 2 Flux from Land Use, Land-Use Change, and Forestry. Forest Land Remaining Forest Land is the
principal section contributing to the change in net CO2 flux from Land Use, Land-Use Change, and Forestry
sector. The addition of newly available forest inventory data as well as some refinements in previously existing
data were the principal factors contributing to the changes. Changes for the period 1990 through 2005, as
compared to the estimates presented in the previous inventory, are based on the cumulative effects of (1)
incorporating and updating state and sub-state inventory data, and (2) including a portion of Alaska forest for
the first time. Minor refinements to the harvested wood product contribution included (1) shorter half-life for
decay in dumps and (2) separation of decay in dumps from decay in landfills. Overall, these changes, in
combination with adjustments in the other sources/sinks within the sector, resulted in an average annual
increase in net flux of CO2 to the atmosphere from the Land Use, Land-Use Change, and Forestry sector of 20.1
Tg CO2 Eq. (2.5 percent) for the period 1990 through 2005.
• Landfills. For municipal solid waste landfills, changes to historical data resulted from revising the proportion
of waste disposed of in managed landfills versus open dumps prior to 1980 and from using the recommended
Recalculations and Improvements 10-1
-------
IPCC (2006) default value for uncharacterized land disposal. Additionally, Energy Information Administration,
Landfill Methane Outreach Program, and flare vendor databases were updated, affecting estimates of CH4
recovery. Overall, changes resulted in an average annual decrease in CH4 emissions from landfills of 11.4 Tg
CO2 Eq. (7.8 percent) for the period 1990 through 2005.
• Enteric Fermentation. Changes in the estimates of CH4 emissions resulting from Enteric Fermentation occurred
as a result of (1) modifying the Cfi coefficient based on the revised IPCC equations (IPCC 2006), (2) updating
the C factor in accordance with the revised IPCC Guidelines (IPCC 2006), (3) revising the equation for net
energy of growth (NEg), (4) modifying the Cattle Enteric Fermentation Model to output at the state level and
include more detailed data inputs, (5) incorporating revised FAO horse population estimates for 2001 through
2005, and (6) including revised USDA estimates of swine population for 2005. Overall, changes resulted in an
average annual increase in CH4 emissions from Enteric Fermentation of 11.4 Tg CO2 Eq. (9.9 percent) from
1990 through 2005.
• Substitution of Ozone Depleting Substances. An extensive review of chemical substitution trends, market sizes,
growth rates, and charge sizes, together with input from industry representatives, resulted in updated
assumptions for the Vintaging Model, which is used to calculate emissions from this category. These changes
resulted in an average annual decrease in hydrofluorocarbon (HFC) emissions from the Substitution of Ozone
Depleting Substances of 7.4 Tg CO2 Eq. (14.1 percent) for the period 1990 through 2005.
• Settlements Remaining Settlements The data source used for N fertilization was updated for N2O Emissions
from Settlement Soils. This fertilization data is based on county-scale non-farm application amounts from a
USGS database. Overall, changes resulted in an average annual decrease in N2O emissions from Settlements
Remaining Settlements of 4.4 Tg CO2 Eq. (78.1 percent) for the period 1990 through 2005.
• International Bunker Fuels. Historical activity data for aviation was revised for both U.S. and foreign carriers.
In addition, distillate and residual fuel oil consumption by cargo or passenger carrying marine vessels from
2003 through 2006 was revised. Overall, changes resulted in an average annual increase in CO2 emissions
from International Bunker Fuels of 4.2 Tg CO2 Eq. (4.5 percent) for the period 1990 through 2005.
• Manure Management. Several changes were made in this section. First, a major change in the N2O emission
calculations is that emissions are now calculated from the "bottom-up" such that emissions are calculated for
each animal group, manure management system, and state. These values are then summed to calculate the total
greenhouse gas emissions from manure management in the United States. Second, dairy heifers and beef on
feed now have one WMS distribution that represents managed and unmanaged systems, and emissions are
calculated for each WMS using the EF for that system, and not using a state average EF. Third, the inventory
now includes indirect N2O emissions in the manure management sector associated with N losses from
volatilization of nitrogen as ammonia (NH3), nitrogen oxides (NOx), and leaching and runoff. Fourth, the days
per year used in N2O calculations was changed from 365 to 365.25 to include leap years and to be consistent
with the CH4 inventory calculations. Fifth, changes were also made to the current calculations involving animal
population data. Overall, the changes resulted in an average annual increase in N2O emissions from Manure
Management of 4.0 Tg CO2 Eq. (43.1 percent) for the period 1990 through 2005.
• Coal Mining. Three changes were made across the coal mining sector. First, recalculations of emissions
avoided at three JWR coal mines in Alabama were performed as the mining company reported and filed data
for 1991 through 2005; data was also provided for 2006. Secondly, the gas content values assigned to each coal
basin in the surface mine emissions component of the inventory were changed to reflect recent work carried out
by U. S. EPA. Third, the conversion factor used to convert from mmcf of methane was updated to be consistent
across the inventory. Overall, the changes resulted in an average annual increase in CH4 emissions from Coal
Mining of 3.7 Tg CO2 Eq. (6.2 percent) for the period 1990 through 2005.
• Ammonia Manufacture and Urea Consumption. CO2 emissions estimates were revised for all years to
incorporate a new methodology that estimates urea production and consumption based on urea consumed as
fertilizer. The new methodology allocated CO2 emissions associated with urea applied as fertilizer to the Land
Use, Land-Use Change, and Forestry chapter. Overall, the changes resulted in an average annual decrease in
CO2 emissions from Ammonia Manufacture and Urea Consumption of 3.0 Tg CO2 Eq. (15.8 percent) for the
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
period 1990 through 2005.
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Carbon Dioxide Consumption
Municipal Solid Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloy Production
Ammonia Manufacture and Urea
Consumption
Phosphoric Acid Production
Petrochemical Production
Silicon Carbide Production and
Consumption
Lead Production
Zinc Production
Cropland Remaining Cropland3
Petroleum Systems
Land-Use, Land-Use Change, and
Forestry (Sink)
International Bunker Fuels
Wood Biomass and Ethanol
Consumption
CH4
Stationary Combustion
Mobile Combustion
Coal Mining
Abandoned Underground Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production and
Consumption
Iron and Steel Production
Ferroalloy Production
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
Forest Land Remaining Forest Land
Landfills
Wastewater Treatment
Composting3
1990^
NC^
NC=
1.3=
NCflli
NCflli
NC^
NC^
7.1=
NC^
NC^l
11.2=
0.1=
(1L4)1^
(1.8)=
0.3=
1 1995 =
1
1
1
1
1
i 1.2=
1
!
E +==i
1
1 (0.1)1111
1 NCl^
1
1
1 (2.7)1^
1
1 NCiiii
1
1
1
1
1
!
i
1 +011
I
1 (0.7)=
1
1
1
1
1
1
!
1 NC^
1
1 11.7=111
1
1
i
1 0.7111
1 (13.0)f^
E //-. o \EEEE
E (U.OJEEEE
1
1 2000
1 (0-2)
1 (7.8)
1 0-4
1 +
1 NC
1 1.5
1 NC
1 NC
1 +
1 (0.4)
1 (0.2)
1 NC
1 1-5
I NC
1 (3.2)
1 NC
1 NC
1 NC
1 NC
1 NC
1 7.5
1 0-3
1 83.1
1 M:
1 r^.o;
1 10.6
1 (0.7)
1 (o.i)
1 4.5
1 +
1 (o.i)
1 2.4
1 NC
1 NC
1 +
1 NC
1 11-1
1 0.1
1 NC
1 +
1 5.0
1 (H.l)
1 (1.8)
1 1.3
2001
3.1
(4.3)
0.5
+
NC
1.4
NC
NC
+
(0.4)
(0.2)
NC
1.3
NC
(3.4)
NC
NC
NC
+
NC
7.8
0.3
17.3
NC
NC
11.1
(0.6)
0.1
4.8
+
(0.1)
2.8
NC
NC
+
NC
11.1
0.1
NC
+
3.4
(10.1)
(1.7)
1.3
2002
15.8
7.6
0.5
+
NC
1.3
NC
NC
+
(0.1)
(0.2)
NC
1.3
NC
(3.6)
NC
NC
NC
+
NC
8.5
0.3
(14.9)
NC
NC
13.8
(0.6)
(0.1)
4.8
+
(0.1)
3.1
NC
NC
+
NC
11.2
0.1
NC
+
6.0
(10.3)
(1.7)
1.3
2003
0.1
(7.5)
0.4
+
NC
1.4
+
NC
+
(0.4)
(0.2)
NC
1.4
NC
(3.7)
NC
NC
NC
NC
NC
8.3
0.3
(49.0)
19.9
(0.1)
10.1
(0.6)
(0.1)
4.8
+
(0.4)
3.4
NC
NC
+
NC
11.6
0.2
NC
+
0.7
(9.3)
(1.7)
1.5
2004
(26.1)
(31.7)
(1.3)
(0.1)
NC
1.4
NC
NC
4
4
(0.2)
NC
1.5
NC
(3.7)
NC
NC
NC
+
NC
7.6
0.3
(48.9)
21.8
NC
5.3
(0.6)
(0.1)
5.2
+
(5.1)
3.3
NC
NC
NC
NC
11.9
0.3
NC
4
4
(9.5)
(1.7)
1.6
2005
(15.2)
(20.2)
(3.3)
1.3
NC
1.5
NC
NC
+
(0.2)
(0.2)
+
1.4
NC
(3.5)
+
(0.1)
NC
+
NC
7.9
0.3
(50.2)
25.4
20.9
0.4
(0.5)
(0.1)
4.7
+
(8.7)
(0.2)
NC
NC
NC
NC
12.4
0.5
+
+
0.7
(8.3)
(1.6)
1.6
Recalculations and Improvements 10-3
-------
International Bunker Fuels
N2O
Stationary Combustion
Mobile Combustion
Adipic Acid Production
Nitric Acid Production
Manure Management
Agricultural Soil Management
Field Burning of Agricultural
Residues
Wastewater Treatment
N2O from Product Uses
Municipal Solid Waste Combustion
Settlements Remaining Settlements
Forest Land Remaining Forest Land
Composting3
International Bunker Fuels
HFCs, PFCs, and SF6
Substitution of Ozone Depleting
Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Electrical Transmission and
Distribution
Magnesium Production and
Processing
NC NC NC +
(113.9) (109.6) (103.1) (103.2)
0.6
(0.7)
0.2
(1.0)
4.1
0.6
0.2
0.2
(0.8)
4.2
0.6
(1.2)
0.2
(0.9)
4.3
0.6
(1.4)
0.2
(1.4)
4.3
(114.7) (112.0) (104.0) (102.9)
(91.7)
0.6
(1.5)
0.2
(0.8)
4.4
(91.9)
(98.5)
1.0
(1.7)
(0.1)
0.1
4.4
(99.9)
+
0.1
NC
(4.4)
0.5
1.4
0.2
0.1
NC
(4.0)
0.3
1.4
+
0.1
NC
(4.1)
0.6
1.4
(0.1)
0.1
NC
(4.3)
0.1
1.6
(0.1)
0.1
NC
(4.4)
+
1.7
+
0.1
NC
(4.3)
0.1
1.7
NC NC
NC
0.1
0.2 0.2
(11.1) (10.2) (9.9) (13.0) (13.2) (17.2)
(9.7)
NC
(1.2)
+
(10.6)
NC
(0.1)
+
(11.8) (13.5) (15.3) (18.0)
NC
1.3
+
NC
+
+
+ NC
1.6 (0.7)
0.1
0.5
0.6 0.6 0.6 0.6
Net Change in Total Emissions
Percent Change
(93.7);
-2.1%
(77.0)^ (114.6) (105.7) (83.4) (106.0) (125.7) (130.5)
-0.4%^ -0.5% -1.4% -1.6% -2.5% -2.7% -2.8%
+ Absolute value does not exceed 0.05 Tg CO2 Eq. or 0.05 percent.
NC (No Change)
aNew source category relative to previous inventory.
b Excludes net CO2 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and
Wood Biomass and Ethanol Consumption.
Note: Lotals may not sum due to independent rounding.
Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from Land Use, Land-Use Change, and Forestry (Tg
CO2Eq.)
Component: Net CO2 Flux From
Land Use, Land-Use Change, and
Forestry
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements
Other
Net Change in Total Flux
Percent Change
1990 =
(1.9)=
6.1=
0.3=
(1.1)=
(24.9)^
-3.5%=
1 1995 =
1
1
1
1
1
1
§^ /r\ OY==
^U.oj^=
1
1
1 2000
1 87.9
1 (1.9)
1 2.1
1 0.2
1 NC
1 (4.3)
1 (1.0)
1 83.1
1 11.0%
2001
22.3
(2.0)
2.1
0.2
NC
(4.4)
(1.0)
17.3
2.3%
2002
(9.2)
(2.6)
2.1
0.2
NC
(4.5)
(1.0)
(14.9)
-1.8%
2003
(43.9)
(2.2)
2.1
0.2
NC
(4.6)
(0.6)
(49.0)
-6.0%
2004
(44.1)
(1.5)
2.1
0.2
NC
(4.7)
(0.9)
(48.9)
-5.9%
2005
(44.9)
(1.6)
2.1
0.2
NC
(4.8)
(1.2)
(50.2)
-6.1%
NC (No Change)
Note: Numbers in parentheses indicate a decrease in estimated net flux of CO2 to the atmosphere, or an increase in net
sequestration.
Note: Totals may not sum due to independent rounding.
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
11. References
Executive Summary
BEA (2007) 2006 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, 2007. Available online at .
EIA (2007a) "Supplemental Tables on Petroleum Product detail." Monthly Energy Review, September 2007.
Unpublished. Energy Information Administration (EIA), U.S. Department of Energy. Washington, DC, DOE/EIA-
0035(2007/09).
EIA (2007b) International Energy Annual 2005. Energy Information Administration (EIA), U.S. Department of
Energy. Washington, DC. Updated June-October 2007. Available online at
.
EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency
(EPA), Washington, DC. Available online at < http://www.epa.gov/air/airtrends/index.html>. December 19, 2006.
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, P.J. 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-XWDoc. 10 (1.IV.2000).
IPCC (1996) Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change,
J.T. Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, and K. Maskell. (eds.). Cambridge
University Press. Cambridge, 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.
References 11-1
-------
(FCCC/CP/2002/8). March 28, 2003.
U.S. Census Bureau (2007) U.S. Census Bureau International Database (IDE). Available online at
. August 15, 2007.
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) ^4/r 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, DJ. 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-XWDoc. 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, L.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.
11-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Trends in Greenhouse Gas Emissions
BEA (2007) 2006 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, 2007. Available online at .
Duffield, J. (2006) Personal communication. Jim Duffield, Office of Energy Policy and New Uses, USD A and
Lauren Flinn, ICF International. April and December.
EIA (2007b) Short-Term Energy Outlook. Energy Information Administration, U.S. Department of Energy,
Washington, DC.
EIA. (2007c) Annual Energy Review. "Appendix A. Table A3 : Approximate Heat Content of Petroleum
Consumption." Energy Information Administration, U.S. Department of Energy. Washington, D.C. Available
online at
EIA (1991 through 2006) Fuel Oil and Kerosene Sales. "Table 22: Adjusted Sales for Farm Use: Distillate Fuel Oil
and Kerosene; Sales for Electric Power and Oil Company Uses: Distillate Fuel Oil and Residual Fuel Oil, 2005."
Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at
EPA (200$) 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, P.J. van der Linden, X. Dai, C.A. Johnson, andK. Maskell (eds.).
Cambridge University Press. Cambridge, United Kingdom.
U.S. Census Bureau (2007) U.S. Census Bureau International Database (IDE). Available online at
. August 15, 2007.
Energy
EIA (2007) International Energy Annual 2007. Energy Information Administration, U.S. Department of Energy.
Washington, DC. Updated June-October 2007. Available online at .
APTA (2006) Commuter Rail National Totals. American Public Transportation Association, Washington, DC.
Available online at .
BEA (2007) 2006 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and
References 11-3
-------
"real" GDP, 1929-2006. Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC.
July 29, 2007. Available online at .
BEA (1991 through 2007) 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.
Coffeyville Resources Nitrogen Fertilizers, LLC (2007) Business Data. Available online at
September 15, 2007.
Corathers, L. (2007) Personal communication. Lisa Corathers, Commodity Specialist, U.S. Geological Survey and
Michael Obeiter, ICF International. September 2007.
Dakota Gasification Company (2006) CO2 Pipeline Route and Designation Information. Bismarck, ND. 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 (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense
Energy Support Center, Defense Logistics Agency, U.S. Department of Defense. Washington, DC.
DOC (1991 through 2007) 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 2005) Transportation Energy Data Book. Office of Transportation Technologies, Center for
Transportation Analysis, Energy Division, Oak Ridge National Laboratory. Oak Ridge, TN. ORNL-6959.
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 (2007a) Annual Energy Review 2006. Energy Information Administration, U.S. Department of Energy.
Washington, DC. DOE/EIA-0384(2006). June 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 (2007c) Emissions of Greenhouse Gases in the United States 2006, Draft Report. Office of Integrated Analysis
and Forecasting, Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE-EIA-
0573(2006).
EIA (2007d) "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 (2007e) Natural Gas Annual 2006. Energy Information Administration, U.S. Department of Energy.
Washington, DC. DOE/EIA-0131(06). November 2007.
EIA (20071) Short-Term Energy Outlook. Energy Information Administration, U.S. Department of Energy.
Washington, DC. December 2006.
11-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
EIA (2007g) 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 (2007h) Quarterly Coal Report. Energy Information Administration, U.S. Department of Energy. Washington,
DC. DOE/EIA-0121.
EIA (2006) Historical Natural Gas Annual, 1930 - 2006. Energy Information Administration, U.S. Department of
Energy. Washington, DC.
EIA (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 (2004; 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 (2005) "Table 32: General Aviation Aircraft Fuel Consumption," FAA Aerospace Forecasts Fiscal Years 2005
- 2016. Federal Aviation Administration. Available online at
.
Fitzpatrick, E. (2002) The Weyburn Project: A Model for International Collaboration. Available online at
.
FHWA (1996 through 2006) Highway Statistics. Federal Highway Administration, U.S. Department of
Transportation. Washington, DC. Report FHWA-PL-96-023-annual.
FRB (2006) Industrial Production and Capacity Utilization. Federal Reserve Statistical Release, G.17, Federal
Reserve Board. Available online at November 7, 2006.
Gaffney, J. (2007) Personal communication, Commuter Rail Diesel Consumption, American Public Transportation
Association.
Gambogi, J. (2007) Personal communication. Joseph Gambogi, Commodity Specialist, U.S. Geological Survey and
Michael Obeiter, ICF International. October 2007.
Grillot, M. (2007) Personal communication. Mike Grillot, Energy Information Administration and Lauren Pederson,
ICF International. U.S. Territories Fossil Fuel Consumption, 1990-2006. Unpublished. U.S. Energy Information
Administration. Washington, DC.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories. The National Greenhouse Gas
References 11-5
-------
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 1996IPCC 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) Telephone 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. Census Bureau (2007) Current Industrial Reports Fertilizer Materials and Related Products: 2006 Summary.
Available online at < http://www.census.gOv/industry/l/mq325b065.pdf>.
USGS (1998 through 2002) Mineral Yearbook: Aluminum Annual Report. U.S. Geological Survey, Reston, VA.
USGS (1995 through 2006) 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 2006a) Silicon: Annual Report. U.S. Geological Survey, U.S. Department of the Interior.
Washington, DC.
USGS (1991b through 2006b) 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.
Carbon Emitted from Non-Energy Uses of Fossil Fuels
ACC (2005 through 2007) Guide to the Business of Chemistry. American Chemistry Council.
Adler, B. (2001) Personal communication. Bob Adler, U.S. Energy Information Administration (EIA) to Robert
Lanza, ICF International. September 14, 2001.
APC (2003 through 2006) APC Year-End Statistics. American Plastics Council website. Available online at
.
APC (2001) as reported in ACS (2001) "Production: slow gains in output of chemicals and products lagged behind
U.S. economy as a whole." Chemical & Engineering News, 79(26). June 25, 2001. Available online at
.
APC (2000) as reported in "Facts & Figures for the Chemical Industry." Chemical and Engineering News, 78(26).
June 26, 2000. American Plastics Council, Arlington, VA. Available online at
.
11-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Bank of Canada (2006) Financial Markets Department Year Average of Exchange Rates. Available online at
.
CMA(1999) U.S. Chemical Industry Statistical Handbook. Chemical Manufacturer's Association, Washington,
DC.
Connolly, U. (2000) Personal communication. Una Connelly, National Asphalt Pavement Association to Suzanne
Bratis, ICF International. August 2000.
EIA (2007) 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 (2005) EM Manufacturing Consumption of Energy (MECS) 2002. U.S. Department of Energy, Energy
Information Administration. Washington, DC.
EIA (2001) Manufacturing Energy Consumption Survey (MECS) 1998. U.S. Department of Energy, Energy
Information Administration. Washington, DC. Available online at
.
EIA (1997) Manufacturing Energy Consumption Survey (MECS) 1994. U.S. Department of Energy, Energy
Information Administration. Washington, DC. December 1997. DOE/EIA-0512(94).
EIA (1994) Manufacturing Energy Consumption Survey (MECS) 1991. U.S. Department of Energy, Energy
Information Administration. Washington, DC. December 1994. DOE/EIA-0512(91).
EIIP (1999) Methods for Estimating Greenhouse Gas Emissions from Combustion of Fossil Fuels. Emissions
Inventory Improvement Program: State and Territorial Air Pollution Program Administrators/Association of Local
Air Pollution Control Officials and U.S. Environmental Protection Agency, EIIP Document Series Volume VIII,
Chapter 1, STAPPA/ALAPCO/EPA, Washington, DC. August 2000. Available online at
. August 28, 2000.
EIIP (1998) "Area Sources." In Asphalt Paving. Emissions Inventory Improvement Program: State and Territorial
Air Pollution Program Administrators/Association of Local Air Pollution Control Officials and U.S. Environmental
Protection Agency, EIIP Document Series Volume III, Chapter 17, STAPPA/ALAPCO/EPA, Washington, DC.
August 2000. Available online at . July 27, 2000.
Eldredge-Roebuck, B. (2000) Personal communication Brandt Eldredge-Roebuck, American Plastics Council to Joe
Casola, ICF International. July 11, 2000.
EPA (2007) Biennial Reporting System (BRS) Database. Envirofacts Warehouse, U.S. Environmental Protection
Agency. Washington, DC. Available online at .
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. Envirofacts Warehouse, U.S. Environmental Protection
Agency. Washington, DC. Available online at .
EPA (2004a) Biennial Reporting System (BRS). Envirofacts Warehouse, U.S. Environmental Protection Agency.
Washington, DC. Available online at .
EPA (2004b) Pesticides Industry Sales and Usage: 2000 and 2001 Market Estimates. Office of Prevention,
Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at
.
References 11-7
-------
EPA (2004c) "Ch. 11: Mineral Products Industry, Hot Mix Asphalt Plants." AP 42, Fifth Edition Compilation of
Air Pollutant Emission Factors, Volume 1: Stationary Point and Area Sources. Available online at
February 25, 2008.
EPA (2002) Pesticides Industry Sales and Usage, 1998 and 1999 Market Estimates. Office of Prevention,
Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at
. July 2003.
EPA (2001) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1999. Office of Atmospheric Programs,
U.S. Environmental Protection Agency. Washington, DC. EPA 236-R-01-001.
EPA (2000a) Toxics Release Inventory, 1998. Office of Information Analysis and Access, Office of Environmental
Information, U.S. Environmental Protection Agency. Washington, DC. Available online at
.
EPA (2000b) Hot Mix Asphalt Plants Emission Assessment Report (Draft Report), AP-42. Office of Air Quality
Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. June 2000. Available
online at July 25, 2000.
EPA (1999) Pesticides Industry Sales and Usage: 1996 and 1997Market Estimates. , Office of Prevention,
Pesticides and Toxic Substances, U.S. Environmental Protection Agency, Washington, DC. Available online at
.
EPA (1998) Pesticides Industry Sales and Usage, 1994 and 1995 Market Estimates. Office of Prevention,
Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at
July 2003.
EPA (1995) Asphalt Paving Operations, AP-42. Office of Air Quality Planning and Standards, U.S. Environmental
Protection Agency, Research Triangle Park, NC.
FEB (2007) Fiber Economics Bureau, as cited in C&EN (2007) "Gains in Chemical Output Continue," Chemical &
Engineering News, American Chemical Society. Available online at July 2, 2007.
FEB (2003, 2005, 2006) Fiber Economics Bureau, as cited in C&EN (2006) Production: Growth in the Norm.
Chemical & Engineering News, American Chemical Society. Available online at .
FEB (2001) as reported in "Production: slow gains in output of chemicals and products lagged behind U.S.
economy as a whole." Chemical and Engineering News, Vol. 79(26). Fiber Economics Bureau, Washington, DC.
June 25, 2001. Available online at .
The Financial Planning Association (2006) Canada/US Cross-Border Tools: US/Canada Exchange Rates.
Available online at . August 16, 2006.
Gosselin, Smith, and Hodge (1984) Clinical Toxicology of Commercial Products. Fifth Edition, Williams &
Wilkins, Baltimore, MD
IISRP (2003) IISRP Forecasts Moderate Growth in North America to 2007. International Institute of Synthetic
Rubber Producers, Inc. Available online at .
IISRP (2000) as reported in ACS (2001) "Facts & Figures for the Chemical Industry." Chemical and Engineering
News, Vol. 78(26).June 26, 2000. International Institute of Synthetic Rubber Producers, Houston, Texas. Available
online at . February
18, 2000
11-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
INEGI (2006) Production bmta total de las unidades economicas manufacturer as por Subsector, Rama, Subrama y
Clase de actividad. Available online at
. August 15,
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.
Marland, G. and R. M. Rotty (1984) "Carbon dioxide emissions from fossil fuels: a procedure for estimation and
results for 1950-1982." Tellus, 36B(4), 232-261.
Miller, T. (1999) Material Safety Data Sheet, Carbon Black. Continental Carbon Company. September 1, 1999.
Available online at . October 10, 2003.
NPRA (2001) Selected Petrochemical Statistics—U.S. Trade, Production and Consumption. National Petrochemical
& Refiners Association. Washington, DC.
PAN (2002) Pesticides Database. Pesticide Action Network North America. Available online at
. 2003.
RMA (2006) Scrap Tire Markets in the United States 2005 Edition. Rubber Manufacturers Association.
Washington, DC. November 2006.
RMA (2002) U.S. Scrap Tire Markets 2001. Rubber Manufacturers Association. Washington, DC. December 2002.
Schneider, S. (2007) E-mail communication Shelly Schneider, Franklin Associates to Sarah Shapiro, ICF
International., A Division of ERG. January 10, 2007.
SPI (2000) "The Society of the Plastics Industry." Available online at
. June 28, 2000.
Statistics Canada (2006) "Canadian Trade by Industry - NAICS Codes: NAICS 3252 - Resin, Synthetic Rubber, and
Artificial and Synthetic Fibres and Filaments Manufacturing (NAICS 3252)." Available online at
.
STMC (2003) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
Association. Washington, DC. Available online at
and
. July 7, 2003.
Tooly, L. (2001) E-mail communication. Email from Lee Tooly, EPA's Office of Air Quality Planning and
Standards to Robert Lanza, ICF International. August 20, 2001.
U.S. Census Bureau (2004) Soap and Other Detergent Manufacturing: 2002. December 2004, EC02-311-325611
(RV). Available online at .
References 11-9
-------
U.S. Census Bureau (2003) U.SInternational Trade Commission (USITC) Trade Dataweb. Available online at
.
U.S. Census Bureau (1999) 1997Economic Census, Manufacturing—Industry Series, Petroleum Lubricating Oil
and Grease Manufacturing and Petroleum Refining. EC97M-3241D andEC97M-3241A (2 reports).
U.S. International Trade Commission (2007) Available online at . November 7, 2007.
U.S. International Trade Commission (2006) Available online at . September 27, 2006.
Wood, A. (2003) "Compendium of Pesticide Common Names." Available online at
.
Stationary Combustion (excluding CO2)
EIA (2007a) 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 (2007b) Annual Energy Review 2006. Energy Information Administration, U.S. Department of Energy.
Washington, DC. DOE/EIA-0384(2006). June 2007.
EPA (2004; 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. (2007) Personal communication. U.S. Territories Fossil Fuel Consumption, 1990-2006. 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-XWDoc. 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 CO2)
AAR (2007) Railroad Facts, 2007 Ed. Policy and Economics Department, Association of American Railroads,
Washington, DC.
ANL (2006) Argonne National Laboratory (2006) GREET model Version 1.7. June 2006.
APTA (2007) Public Transportation Fact Book. American Public Transportation Association, Washington, DC.
11-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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). Personal communication with Elissa Kay, Residual and Distillate Fuel Oil Consumption (International
Bunker Fuels). Department of Homeland Security, Bunker Report. January 11, 2008.
DESC (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense
Energy Support Center, Defense Logistics Agency, U.S. Department of Defense.
DOC (1991 through 2007) Unpublished Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign
Countries. Form-563, Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce.
DOE (1993 through 2007) 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, U.S. Department of
Transportation, Bureau of Transportation Statistics, Washington, DC. DAI-10.
EIA (2007a) 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 (2007b) International Energy Annual. World Petroleum Supply and Disposition, Table 3.1. Available online at
.
EIA (2007c) Annual Energy Review 2006. Energy Information Administration, U.S. Department of Energy,
Washington, DC. July 2006. DOE/EIA-0384(2005).
EIA (2007d) Natural Gas Annual 2006. 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 2007) Fuel Oil and Kerosene Sales. Energy Information Administration, U.S. Department of
Energy, Washington, DC. DOE/EIA-0535-annual.
EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. Available online at .
EPA (2007a) Annual Certification Test Results Report. Office of Transportation and Air Quality, U.S.
References 11-11
-------
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 (2006a) NONROAD Model. Office of Transportation and Air Quality, U.S. Environmental Protection Agency.
Available online at .
EPA (2005) National Emissions Inventory Air Pollutant Emissions Trends Data. Available online at
.
EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between the Office of Air
Pollution and the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA).
December 22, 2003.
EPA (2000) Mobile6 Vehicle Emission Modeling Software. Office of Mobile Sources, U.S. Environmental
Protection Agency, Ann Arbor, Michigan.
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 (2007). FAA Aerospace Forecasts Fiscal Years 2007-2020. Table 30 "General Aviation Aircraft Fuel
Consumption," Federal Aviation Administration. Available online at <
http://www.faa.gov/data_statistics/aviation/aerospace_forecasts/2007-
2020/media/FORECAST%20BOOK%20SM.pdf/>.
FAA (2006) Email correspondence containing aviation emissions estimates from the System for Assessing
11-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Aviation's Global Emissions (SAGE). August 2006.
FHWA (1996 through 2007) Highway Statistics. Federal Highway Administration, U.S. Department of
Transportation, Washington, DC. Report FHWA-PL-96-023-annual. Available online at
.
Gaffney, J. (2007) Personal communication, Commuter Rail Diesel Consumption, American Public Transportation
Association.
ICF (2006a) Revisions to Alternative Fuel Vehicle (AFV) Emission Factors for the U.S. Greenhouse Gas Inventory.
Memorandum from ICF International to John Davies, Office of Transportation and Air Quality, U.S. Environmental
Protection Agency. November 2006.
ICF (2006b) Revised Gasoline Vehicle EFsfor LEV and Tier 2 Emission Levels. Memorandum from ICF
International to John Davies, Office of Transportation and Air Quality, U.S. Environmental Protection Agency.
November 2006.
ICF (2004) Update of Methane and Nitrous Oxide Emission Factors for On-Highway Vehicles. Final Report to U.S.
Environmental Protection Agency. February 2004.
IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC 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.
Lou, J. (2007) Personal Communication with Joel Lou, Residual and Distillate Fuel Oil Consumption for Vessel
(Both International and Domestic) for American Samoa, U.S. Pacific Islands, and Wake Island.
Unnasch, S., L. Browning, andE. 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 2007) Personal communication, Class II and III Rail energy consumption, American
Short Line and Regional Railroad Association.
Coal Mining
AAPG (1984) Coalbed Methane Resources of the United States. AAPG Studies in Geology Series #17.
DOE (1983) Methane Recovery from Coalbeds: A Potential Energy Source. U.S. Department of Energy.
DOE/METC/83-76.
EIA (2006) Annual Coal Report 1991-2005 (Formerly called Coal Industry Annual). Table 3. U.S. Department of
Energy, Energy Information Administration, Washington, DC.
EPA (1996) Evaluation and Analysis of Gas Content and Coal Properties of Major Coal Bearing Regions of the
United States. U.S. Environmental Protection Agency. EPA/600/R-96-065.
GRI (1988) A Geologic Assessment of Natural Gas from Coal Seams. Topical Reports, Gas Research Institute 1986-
References 11-13
-------
Mutmansky, Jan M. and Yanebi Wang (2000) "Analysis of Potential Errors in Determination of Coal Mine Annual
Methane Emissions." Mineral Resources Engineering, 9(4). December 2000.
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.
API (2005) "Table 12—Section III—Producing Oil Wells in the United States by State." In Basic Petroleum Data
Book. American Petroleum Institute, Volume XXV, Number 1. February 2005.
Alabama (2007) "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 (2007a) Number of Producing Gas and Gas Condensate Wells, 1989-2005, Natural Gas Navigator. Energy
Information Administration, U.S. Department of Energy. Washington, DC. Available online at
.
EIA (2007b) "Table 1—Supply and Disposition of Dry Natural Gas in the United States 1999-2006." Natural Gas
Monthly, Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at
.
EIA (2007c) "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 (2007d) "Table 5.2." Monthly Energy Review. Energy Information Administration, U.S. Department of
Energy. Washington, DC. Available online at .
EIA (2007e) "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 (20071) 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
11-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Information Administration, Department of Energy. Washington, DC.
EIA (2004) USLNG 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 (2007) Natural Gas STAR Reductions 1990-2006. 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. Harrison, M., T. Shires, J. Wessels, and R.
Cowgill, (eds.). Radian International LLC for National Risk Management Research Laboratory, Air Pollution
Prevention and Control Division, Research Triangle Park, NC. EPA-600/R-96-080a.
GTI (2001) Gas Resource Database: Unconventional Natural Gas and Gas Composition Databases. Second
Edition. GRI-01/0136.
IPCC (2007) 2007 IP CC Guidelines for National Greenhouse Gas Inventories. The National Greenhouse Gas
Inventories Programme, Intergovernmental Panel on Climate Change. H.S. Eggleston, L. Buendia, K. Miwa, T
Ngara, and K. Tanabe, (eds.). Hayama, Kanagawa, Japan.
Kansas (2007) "Oil and Gas Production Data, All Wells." Kansas Geological Survey. University of Kansas.
Available online at .
Lippman (2003) Rocky Mountain Region Second Quarter 2003 Production Report. Lippman Consulting, Inc.
MMS (2007a) Gulf of Mexico Region Offshore Information. Minerals Management Service, U.S. Department of
Interior. Available online at .
MMS (2007b) Gulf of Mexico Region Products/Free Data. Minerals Management Service, U.S. Department of
Interior. Available online at .
MMS (2007c) Gulfwide Emission Inventory Study for the Regional Haze and Ozone Modeling Effort. OCS Study
MMS 2004-072.
MMS (2007d) OCS Platform Activity. Minerals Management Service, U.S. Department of Interior. Available
online at .
MMS (2007e) Pacific OCS Region. Minerals Management Service, U.S. Department of Interior. Available online
at .
Montana (2007) Montana Online Oil and Gas Information System. Montana Board of Oil and Gas Conservation,
Billing Office. Available online at .
Morgan Stanley (2005) "Barnett Shale Update: None-Core Confidence Rises." Available online at
-------
Shale.pdfX
New Mexico (2007a) "Annual Gas Well Counts by State District" Available online at
.
New Mexico (2007b) "Districts." Available online at .
OGJ (1997-2007) "Worldwide Gas Processing." Oil & Gas Journal, PennWell Corporation, Tulsa, OK.
Oklahoma (2007) Oklahoma Petroleum Information Center—Coalbed-Methane Completions database. Oklahoma
Geological Survey. Available online at .
OPS (2007a) Natural Gas Transmission Pipeline Annual Mileage. Office of Pipeline Safety, U.S. Department of
Transportation. Washington, DC. Available online at .
OPS (2007b) Distribution Annuals Data. Office of Pipeline Safety, U.S. Department of Transportation.
Washington, DC. Available online at .
Texas (2007a) Gas Well Counts by County. Texas Railroad Commission. Available online at
.
Texas (2007b) Oil Well Counts by County. Texas Railroad Commission. Available online at
.
Texas (2007c) The Barnett Shale Regional Report. Brad Foster,. Devon Energy, Texas Railroad Commission.
Available online at .
Texas (2007d) Oil and Gas District Boundaries. Texas Railroad Commission. Available online at
.
Utah (2007) Oil and Gas Data Download. Utah Division of Oil, Gas and Mining, Department of Natural Resources.
Available online at .
World Oil Magazine (2007a) "Outlook 2007: Producing Gas Wells." 228(2). February 2007. Available online at <
http://www.worldoil.com/magazine/MAGAZINE_DETAIL.asp?ART_ID=3115&MONTH_YEAR=Feb-2007 >.
World Oil Magazine (2007b) "Outlook 2007: Producing Oil Wells." 228(2). February 2007. Available online at <
http://www.worldoil.com/magazine/MAGAZINE_DETAIL.asp?ART_ID=3114&MONTH_YEAR=Feb-2007 >.
Wyoming (2007) "Wyoming Oil and Gas Conservation Commission." Available online at
.
Petroleum Systems
EIA (1990 through 2006) Petroleum Supply Annual 1990-2005 Volume 1. Energy Information Administration, U.S.
Department of Energy. Washington, DC.
EIA (1990 through 2007) Refinery Capacity Report. Energy Information Administration, U.S. Department of
Energy. Washington, DC. Available online at
.
EIA (1995 through 2QQla) Annual Energy Review. Energy Information Administration, U.S. Department of Energy.
Washington, DC. Available online at .
11-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
EIA(1995 through 2001b~) Monthly Energy Review. Energy Information Administration, U.S. Department of
Energy. Washington, DC. Available online at .
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 (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 (1996) Methane Emissions from the U.S. Petroleum Industry (Draft). Prepared by Radian. U.S. Environmental
Protection Agency. June 1996.
EPA (1995) Compilation of Air Pollutant Emission Factors AP-42, Fifth Edition, Volume I: Stationary Point and
Area Sources. U.S. Environmental Protection Agency. Available online at
.
EPA/GRI (1996a) Methane Emissions from the Natural Gas Industry, V7: Blow and Purge Activities. Prepared by
Radian. U.S. Environmental Protection Agency. April 1996.
EPA/GRI (1996b) Methane Emissions from the Natural Gas Industry, VI1: Compressor Driver Exhaust. Prepared
by Radian. U.S. Environmental Protection Agency. April 1996.
EPA/GRI (1996c) Methane Emissions from the Natural Gas Industry, V12: Pneumatic Devices. Prepared by
Radian. U.S. Environmental Protection Agency. April 1996.
EPA/GRI (1996d) Methane Emissions from the Natural Gas Industry, VI3: Chemical Injection Pumps. Prepared
by Radian. U.S. Environmental Protection Agency. April 1996.
IOGCC (2007) Marginal Wells: fuel for economic growth 2006 Report. Interstate Oil & Gas Compact Commission.
Available online at < http://www.iogcc.state.ok.us/news_pubs.aspx>.
MMS (2001) Field and Reserve Information. 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.
MMS (2007a) OCS Platform Activity. Minerals Management Service, U.S. Department of Interior. Available
online at .
MMS (2007b) Platform Information and Data. Minerals Management Service, U.S. Department of Interior.
Available online at .
MMS (2007c) Pacific OCS Region. Minerals Management Service, U.S. Department of Interior. Available online at
.
OGJ (2007a) Oil and Gas Journal 1990-2007. Pipeline Economics Issue, September 2007.
OGJ (2007b) Oil and Gas Journal 1990-2007. Worldwide Refining Issue, January 1, 2007.
United States Army Corps of Engineers (1995-2005) Waterborne Commerce of the United States, Part 5: National
Summaries. U.S. Army Corps of Engineers. Washington, DC.
References 11-17
-------
Municipal Solid Waste Combustion
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) 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 (2005a) Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures
for 2003. Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington.
DC. Available online at .
EPA (2003) Characterization of Municipal Solid Waste in the United States: 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 (and Data
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."
BioCycles, 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.
11-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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-XWDoc. 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.
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 to Sarah Shapiro, ICF
International., A Division of ERG. 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) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006.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.
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.
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 2007) Unpublished BE-36 survey data. Bureau of Economic Analysis (BEA), U.S. Department
of Commerce. Washington, DC.
Chevron (2000) Aviation Fuels Technical Review (FTR-3). Chevron Products Company, Chapter 2. Available
online at.
DESC (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense
References 11-19
-------
Energy Support Center, Defense Logistics Agency, U.S. Department of Defense. Washington, DC.
DOC (1991 through 2007) 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 2007) Fuel Cost and Consumption. Airline Information, Bureau of Transportation Statistics,
U.S. Department of Transportation. Washington, DC.
EIA (2007) 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).
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 (2007) Annual Energy Review 2006. Energy Information Administration, U.S. Department of Energy.
Washington, DC. DOE/EIA-0384(2006). June 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.
Lindstrom, P. (2006) Personal communication. Perry Lindstrom, Energy Information Administration and Jean Kim,
ICF International.
Industrial Processes
Cement Manufacture
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 (1999 through 2006) Minerals Yearbook: Cement Annual Report. U.S. Geological Survey, Reston, VA.
USGS (1998) Mineral Industrial Survey: Cement 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Mineral Industrial Survey: Cement 1996. U.S. Geological Survey, Reston, VA.
USGS (1993 through 1996) Minerals Yearbook: Cement Annual Report. U.S. Geological Survey, Reston, VA.
van Oss (2007) Personal communication. Hendrik van Oss, Commodity Specialist of the U.S. Geological Survey
and Tristan Kessler, ICF International. October 2, 2007.
van Oss (2008) Personal communication. Hendrik van Oss, Commodity Specialist of the U.S. Geological Survey
11-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
and Chris Steuer, ICF International. February 7, 2008.
Lime Manufacture
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-XWDoc. 10 (1.IV.2000).
Males, E. (2003) Memorandum from Eric Males, National Lime Association to Mr. William N. Irving & Mr. Leif
Hockstad, Environmental Protection Agency. March 6, 2003.
USGS (1992 through 2007) Minerals Yearbook: Lime Annual Report. U.S. Geological Survey, Reston, VA.
Limestone and Dolomite Use
USGS (1995 through 2007a) Minerals Yearbook: Crushed Stone Annual Report. U.S. Geological Survey, Reston,
VA.
USGS (1995 through 2007b) Minerals Yearbook: Magnesium Annual Report. U.S. Geological Survey, Reston,
VA.
USGS (1993) Minerals Yearbook: Crushed Stone Annual Report 1991. U.S. Geological Survey, Reston, VA.
Soda Ash Manufacture 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 (1994 through 2007) Minerals Yearbook: Soda Ash Annual Report. U.S. Geological Survey, Reston, VA.
Ammonia Manufacture and Urea Consumption
Bark (2004) CoffeyvilleNitrogen Plant Available online at
December 15, 2004.
Coffeyville Resources Nitrogen Fertilizers, LLC (2005 through 2007) Business Data. 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.
EIA (2001) Manufacturing Energy Consumption Survey (MECS) 1998. U.S. Department of Energy, Energy
Information Administration. Washington, DC. Available online at
.
EIA (1994) Manufacturing Energy Consumption Survey (MECS) 1991. U.S. Department of Energy, Energy
Information Administration. Washington, DC. December 1994. DOE/EIA-0512(91).
References 11-21
-------
IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC 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.
TFI (2002) U.S. Nitrogen Imports/Exports Table. The Fertilizer Institute. Available online at
. August 2002.
TIG (2002) Chemical Profiles - Urea. The Innovation Group. Available online at . September 2007.
U.S. Census Bureau (2007) Current Industrial Reports Fertilizer Materials and Related Products: 2006 Summary.
Available online at < http://www.census.gOv/industry/l/mq325b065.pdf>.
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. ITC (2002) United States International Trade Commission Interactive Tariff and Trade DataWeb, Version
2.5.0. Available online at . August 2002.
Nitric Acid Production
US Census Bureau (2007) Current Industrial Reports. Fertilizers and Related Chemicals: First Quarter 2007.
"Table 1: Summary of Production of Principal Fertilizers and Related Chemicals." June, 2007. MQ325B(07)-1.
Available online at < http://www.census.gOv/industry/l/mq325b071.pdf>.
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.
US Census Bureau (2006) Current Industrial Reports., "Table 995: Inorganic Chemicals and Fertilizers." August,
2006. Series MAQ325A Available online at .
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.
Choe, J.S., P. J. Cook, and P.P. Petrocelli (1993) "Developing N2O Abatement Technology for the Nitric Acid
11-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Industry." Prepared for presentation at the 1993 ANPSG Conference. Air Products and Chemicals, Inc.,
Allentown, PA.
Adipic Acid Production
ACC (2003) "Adipic Acid Production." Table 3.12—Production of the Top 100 Chemicals. American Chemistry
Council Guide to the Business of Chemistry. August 2003.
C&EN (1995) "Production of Top 50 Chemicals Increased Substantially in 1994." Chemical & Engineering News,
73(15): 17. April 10, 1995.
C&EN (1994) "Top 50 Chemicals Production Rose Modestly Last Year." Chemical & Engineering News,
72(15):13. April 11, 1994.
C&EN (1993) "Top 50 Chemicals Production Recovered Last Year." Chemical & Engineering News, 71(15): 11.
April 12, 1993.
C&EN (1992) "Production of Top 50 Chemicals Stagnates in 1991." Chemical & Engineering News, 70(15): 17.
April 13, 1992.
Childs, D. (2003) Personal communication. 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) "Product Focus: Adipic Acid." Chemical Week. August 1-8, 2007.
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. (1999) Personal communication. Ron Reimer, DuPont, USA and Heike Mainhardt, ICF International.
May 19, 1999.
Thiemens, M.H., and W.C. Trogler (1991) "Nylon production; an unknown source of atmospheric nitrous oxide."
Science 251:932-934.
Silicon Carbide Production
Corathers, L. (2007) Personal communication between Lisa Corathers, Commodity Specialist, U.S. Geological
Survey and Michael Obeiter of ICF International. September 2007.
Corathers, L. (2006) Personal communication between Lisa Corathers, Commodity Specialist, U.S. Geological
References 11-23
-------
Survey and Erin Fraser of ICF International. October 2006.
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.
U.S. Census Bureau (2005 through 2007) U.SInternational Trade Commission (USITC) Trade DataWeb.
Available online at .
USGS (2006) Minerals Yearbook: Manufactured Abrasives Annual Report 2005. U.S. Geological Survey, Reston,
VA.
USGS (1991a 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 2007) Guide to the Business of Chemistry. American Chemistry Council,
Arlington, VA.
CMA(1999) U.S. Chemical Industry Statistical Handbook. Chemical Manufacturer's Association. Washington,
DC.
EIA (2004) Annual Energy Review 2003. Energy Information Administration, U.S. Department of Energy.
Washington, DC. DOE/EIA-0384(2003). September 2004.
EIA (2003) Emissions of Greenhouse Gases in the United States 2002. Office of Integrated Analysis and
Forecasting, Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE-EIA-
0573(2002). February 2003.
European IPPC Bureau (2004) Draft Reference Document on Best Available Techniques in the Large Volumen
Inorganic Chemicals—Solid and Others Industry, Table 4.21. European Commission, 224. August 2004.
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. (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.
11-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Srivastava, Manoj, ID. 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 .
U.S. Census Bureau (2008) U.SInternational Trade Commission (USITC) Trade DataWeb. Available online at
. January 2008.
U.S. Census Bureau (2006) U.S International Trade Commission (USITC) Trade DataWeb. Available online at
. Fall 2006.
U.S. Census Bureau (2004) 2002 Economic Census: Manufacturing—Industry Series: Carbon Black
Manufacturing. Department of Commerce. Washington, DC. EC02-311-325182. September 2004.
U.S. Census Bureau (1999) 1997Economic 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.
Gambogi, J. (2007) Personal communication. Joseph Gambogi, Commodity Specialist, U.S. Geological Survey and
Michael Obeiter, ICF International. October 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.
Onder, H, and E.A. Bagdoyan (1993) Everything You 've Always Wanted to Know about Petroleum Coke. Allis
Mineral Systems.
USGS (1991 through 2005) 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.
Denbury Resources Inc. (2002 through 2007) Annual Report, 2004, 6.
Phosphoric Acid Production
EFMA (2000) "Production of Phosphoric Acid." Best Available Techniques for Pollution Prevention and Control
References 11-25
-------
in the European Fertilizer Industry. Booklet 4 of 8. European Fertilizer Manufacturers Association. Available
online at .
FIPR (2003) "Analyses of Some Phosphate Rocks." Facsimile 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 2006) Minerals Yearbook. Phosphate Rock Annual Report. U.S.
Geological Survey, Reston, VA.
Iron and Steel Production
AISI (1995 through 2007) Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
DOE (1997) Energy and Environmental Profile of the U.S. Aluminum Industry. Office of Industrial Technologies,
U.S. Department of Energy. July 1997.
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 (2006b) Emissions of Greenhouse Gases in the United States 2005. Energy Information Administration, U.S.
Department of Energy. Washington, DC. DOE/EIA-0573 (2005).
EIA (1998 through 2004a) Quarterly Coal Report: October-December, Energy Information Administration, U.S.
Department of Energy. Washington, DC. DOE/EIA-0121.
EIA (2004b) Emissions of Greenhouse Gases in the United States 2003. Energy Information Administration, U.S.
Department of Energy, Washington, DC. DOE/EIA-0573.
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-XWDoc. 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.
IPCC/UNEP/OECD/IEA (1995) "Volume 3: Greenhouse Gas Inventory Reference Manual. Table 2-T.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.
Jorgenson J. (2007) Personal communication. John Jorgenson, Commodity Specialist, U.S. Geological Survey and
Tristan Kessler, ICF International. October.
11-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
USAA (2004 through 2006) Primary Aluminum Statistics. U.S. Aluminum Association, Washington, DC. January
2006.
U.S. Census Bureau (2007) U.S International Trade Commission (USITC) Trade Dataweb. Available online at
. Accessed Fall 2007.
USGS (2005a) Mineral Commodity Profiles—Iron and Steel. Open-File Report 2005-1254. U.S. Geological
Survey, Reston, VA.
USGS (1994 through 2004, 2005b) Minerals Yearbook: Iron Ore Report. U.S. Geological Survey, Reston, VA.
Ferroalloy Production
Corathers, L. (2007) Personal communication between Lisa Corathers, Commodity Specialist, U.S. Geological
Survey and Tristan Kessler of ICF International. November 6, 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.
Onder, H., and E.A. Bagdoyan (1993) Everything You 've Always Wanted to Know about Petroleum Coke. Allis
Mineral Systems.
USGS (1991 through 2006) Minerals Yearbook: Silicon Annual Report. U.S. Geological Survey, Reston, VA
Aluminum Production
Kantamaneni R. and D. Pape (2001) "2000 Aluminum Inventory—Uncertainty Analysis," EPA Contract No. 68-
W6-0029, Task Order 408. Memorandum to EPA from ICF International. October, 18, 2001.
Gariepy, B. and G. Dube (1992) "Treating Aluminum with Chlorine." U.S. Patent 5,145,514. Issued September 8,
1992.
IAI (2003) Aluminum Sector Greenhouse Gas Protocol: Greenhouse Gas Emissions Monitoring and Reporting by
the Aluminum Industry, International Aluminum Institute, May 2003. Available at .
IPCC (2006) 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-XWDoc. 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.
References 11-27
-------
USAA (2004 through 2006) Primary Aluminum Statistics. U.S. Aluminum Association, Washington, DC.
USGS (2007) Email Communication with Lee Bray on September 19, 2007. U.S. Geological Survey, Reston, VA.
USGS (2006) Mineral Commodity Summaries. U.S. Geological Survey, Reston, VA.
USGS (1995, 1998, 2000 through 2002) Minerals Yearbook: Aluminum Annual Report. U.S. Geological Survey,
Reston, VA.
Victor, D.G. and GJ. MacDonald (1998) "A Model for Estimating Future Emissions of Sulfur Hexafluoride and
Perfluorcarbons." Interim Report for the International Institute for Applied Systems Analysis (IIASA). July, 1998.
Available online at . 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," #13,1996 Annual Conference Proceedings, International Magnesium
Association. Ube City, Japan.
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.
NADCA (2007) Twarog, Daniel L. State of the IndustryReport. Die Casting Industry Links, North American Die
Casting Association, February.
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.
USGS (2007a) Mineral Industry Surveys: Magnesium in the Second Quarter. U.S. Geological Survey, Reston, VA.
Available online at .
USGS (2002, 2003, 2005 through 2007b) Minerals Yearbook: Magnesium Annual Report. U.S. Geological Survey,
Reston, VA. Available online at .
Zinc Production
QueneauP.B., S.E. James, J.P. 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) CC>2 Emission Factors for Non-Energy Use in the Non-Ferrous Metal, Ferroalloys and Inorganics
Industry. Copernicus Institute. Utrecht, the Netherlands.
11-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Stuart (2005) Personal communication. Eric Stuart, Steel Manufacturers Association and Christopher Steuer, ICF
International. October 31, 2005.
USGS (1994 through 2008) Minerals Yearbook: Zinc Annual Report. U.S. Geological Survey, Reston, VA.
Viklund-White C. (2000) "The Use of LCA for the Environmental Evaluation of the Recycling of Galvanized
Steel." ISIJ International. Volume 40 No. 3: 292-299.
Lead Production
Dutrizac, J.E., V. Ramachandran, and J.A. Gonzalez (2000) Lead-Zinc 2000. The Minerals, Metals, and Materials
Society.
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 2006) Minerals Yearbook: Lead Annual Report. U.S. Geological Survey, Reston, VA.
HCFC-22 Production
ARAP (2007) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S. Environmental Protection Agency. October 2, 2007.
ARAP (2006) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental Protection Agency. July 11, 2006.
ARAP (2005) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S. Environmental Protection Agency. August 9, 2005.
ARAP (2004) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S. Environmental Protection Agency. June 3, 2004.
ARAP (2003) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental Protection Agency. August 18, 2003.
ARAP (2002) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S. Environmental Protection Agency. August 7, 2002.
ARAP (2001) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Deborah Ottinger of the U.S. Environmental Protection Agency. August 6, 2001.
ARAP (2000) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
Atmospheric Policy to Sally Rand of the U.S. Environmental Protection Agency. August 13, 2000.
References 11-29
-------
ARAP (1999) Facsimile from Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy to
Deborah Ottinger Schaefer of the U.S. Environmental Protection Agency. September 23, 1999.
ARAP (1997) Letter from Dave Stirpe, Director, Alliance for Responsible Atmospheric Policy to Elizabeth Dutrow
of the U.S. Environmental Protection Agency. December 23, 1997.
Rand, S., M. Branscome, and D. Ottinger (1999) "Opportunities for the Reduction of HFC-23 Emissions from the
Production of HCFC-22." In: Proceedings from the Joint IPCC/TEAP Expert Meeting On Options for the
Limitation of Emissions ofHFCs andPFCs. Petten, the Netherlands, 26-28 May 1999.
RTI (1997) "Verification of Emission Estimates of HFC-23 from the Production of HCFC-22: Emissions from
1990 through 1996." Report prepared by Research Triangle Institute for the Cadmus Group. November 25, 1997;
revised February 16, 1998.
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.
Subsitution of Ozone Depleting Substances
IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC 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.
Semiconductor Manufacture
Burton, C.S., and R, Beizaie (2001) "EPA's PFC Emissions Model (PEVM) v. 2.14: Description and
Documentation" prepared for Office of Global Programs, U. S. Environmental Protection Agency, Washington, DC.
20001 November 2001.
Burton, C.S., and 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 Sematech (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) International Technology Roadmap for Semiconductors: 2006 Update. January 2007. This and earlier
editions and updates are available at Information about the number of interconnect layers for
years 1990 - 2010 is contained in Burton and Beizaie, 2001. PEVM is updated using new editions and updates of
the ITRS, which are published annually.
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 (UV.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 (2007) World Fab Watch, January 2006 Edition.
11-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
VLSI Research, Inc. (2007) Document 327028, V6.12.1—Worldwide Silicon Demand by Wafer Size, by
Linewidth and by Device Type. January 2007. Available online at .
Electrical Transmission and Distribution
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.
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) RAND Environmental Science and Policy Center, "Trends in SF6 Sales and End-Use Applications:
1961-2003," Katie D. Smythe. International Conference on SF6 and the Environment: Emission Reduction
Strategies. Scottsdale, AZ. December 1-3, 2004.
UDI (2007) 2007 UDI Directory of Electric Power Producers and Distributors, 115th Edition, Plaits.
UDI (2004) 2004 UDI Directory of Electric Power Producers and Distributors, 112th Edition, Plaits.
UDI (2001) 2007 UDI Directory of Electric Power Producers and Distributors, 109th Edition, Plaits.
Industrial Sources of Indirect Greenhouse Gases
EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006.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.
Solvent and Other Product Use
Nitrous Oxide from Product Uses
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.
CGA (2003) "CGA Nitrous Oxide Abuse Hotline: CGA/NWSA Nitrous Oxide Fact Sheet." Compressed Gas
Association. November 3, 2003.
CGA (2002) "CGA/NWSA Nitrous Oxide Fact Sheet." Compressed Gas Association. March 25, 2002.
Heydorn, B. (1997) "Nitrous Oxide—North America." Chemical Economics Handbook, SRI Consulting. May 1997.
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.
References 11-31
-------
Solvent Use
EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006.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, 386:271-284.
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.
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 (2007) FAOSTAT Statistical Database. Food and Agriculture Organization of the United Nations. Available
online at .
Feedstuffs (1998) "Nutrient requirements for pregnant replacement heifers." Feedstuffs, Reference Issue, p. 50.
ICF (2006) Cattle Enteric Fermentation Model: Model Documentation. Prepared by ICF International for the
Environmental Protection Agency. June 2006.
ICF (2003) Uncertainty Analysis of 2001 Inventory Estimates of Methane Emissions from Livestock Enteric
Fermentation in the U.S. Memorandum from ICF International to the Environmental Protection Agency. May
2003.
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-XWDoc. 10 (1.IV.2000).
11-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC 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.
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. FeedSci.
Technol. 112:131-154.
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.
Lange, J. (2000) Personal Communication. Lee-Ann Tracy, ERG and JohnLange, Agricultural Statistician, U. S.
Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 8, 2000.
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."./. 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) 1996 Beef NRC: Appendix Table 22. National Research Council.
USDA (2007) Quick Stats: Agricultural Statistics Database. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. Available online at . July 20,
2007.
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. March 1996.
Available online at .
USD A: APHIS: VS (2002) Reference of 2002 Dairy Management Practices. National Animal Health Monitoring
System. Fort Collins, CO. Available online at .
USD A: 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 .
USD A: 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 .
References 11-33
-------
Western Dairyman (1998) "How Big Should Heifers Be at Calving?" The Western Dairyman, p. 12. September
1998.
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.
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 (2QQ6) 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
ftp://ftp.epa.gov/EmisInventory/2002finalnei/documentation/nonpoint/nh3 inventory _draft_042205.pdf> August
2007.
EPA (2003&) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001. EPA 430-R-03-004. U.S.
Environmental Protection Agency. Washington, DC. April 15, 2003.
EPA (2003b) AgSTAR Digest. Office of Air and Radiation, U.S. Environmental Protection Agency. Washington,
DC. Winter 2003. July 2006.
EPA (2002a) Development Document for the Final Revisions to the National Pollutant Discharge Elimination
System (NPDES) Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations (CAFOS).
U.S. Environmental Protection Agency. EPA-821-R-03-001. December 2002.
EPA (2002b) Cost Methodology for the Final Revisions to the National Pollutant Discharge Elimination System
Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations. U.S. Environmental
Protection Agency. EPA-821-R-03-004. December 2002.
EPA (2000) AgSTAR Digest. Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC.
EPA (1992) Global Methane Emissions from Livestock and Poultry Manure, Office of Air and Radiation, U.S.
Environmental Protection Agency. February 1992.
ERG (2003) "Methodology for Estimating Uncertainty for Manure Management Greenhouse Gas Inventory."
Contract No. GS-10F-0036, Task Order 005. Memorandum to EPA from ERG, Lexington, MA. September 26,
2003.
ERG (2001) Summary of development ofMDP 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 B0 Literature
11-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Review). ERG, Lexington, MA. June 2000.
FAO (2007) Yearly U.S. total horse population data from the Food and Agriculture Organization of the United
Nations database. Available online at . June 2007.
Garrett, W.N. and D.E. Johnson (1983) "Nutritional energetics of ruminants." Journal of Animal Science,
57(suppl.2):478-497.
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
Biogeochemcial Cycles, 14(4):1061-1070.
Hashimoto, A.G. (1984) "Methane from Swine Manure: Effect of Temperature and Influent Substrate Composition
on Kinetic Parameter (k)."^4gr/cuItural 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 JohnLange, 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.
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 (2007) National Climate Data Center (NCDC). Available online at
(for all states except Alaska and Hawaii) and (for Alaska and
Hawaii). June 2007.
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 ICF 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.
References 11-35
-------
Safley, L.M., Jr. and P.W. 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) Voluntary Survey Results—Estimated Percentage Participation/Activity, Caged Layer Environmental
Management Practices, Industry data submissions for EPA profile development, United Egg Producers and National
Chicken Council. Received from John Thorne, Capitolink. June 2000.
USDA (2007a) Published Estimates Database. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at . May 2006.
USDA (2007b) Chicken and Eggs 2006 Summary. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. February 2007. Available online at
.
USDA (2007c) Poultry - Production and Value 2006 Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2007. 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
.
USDA (2005) 1992, 1997, 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 (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,
11-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
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
Bollich, P. (2000) Personal Communication. Pat Bollich, Professor with Louisiana State University Agriculture
Center and PaytonDeeks, ICF 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, ICF 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 ICF International. July 30, 2004.
Cicerone R.J., C.C. Delwiche, S.C. Tyler, and P.R. Zimmerman (1992) "Methane Emissions from California Rice
Paddies with Varied Treatments." Global Biogeochemical Cycles, 6:233-248.
Deren, C. (2002) 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. (2007a) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Sarah
Menassian, ICF International. August 29, 2007.
References 11-37
-------
Gonzalez, R. (2007b) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Victoria
Thompson, ICF International. August 2007.
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 CarenMintz, ICF International. June 19, 2003.
Guethle, D. (2002) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and CarenMintz, ICF International. August 19, 2002.
Guethle, D. (200la) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and CarenMintz, ICF International. July 31, 2001.
Guethle, D. (200Ib) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and CarenMintz, ICF International. . September 4, 2001.
Guethle, D. (2000) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and PaytonDeeks, ICF International. May 17, 2000.
Guethle, D. (1999) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative
Extension Service and Payton Deeks, ICF International. August 6, 1999.
Holzapfel-Pschorn, A., R. Conrad, and W. Seiler (1985) "Production, Oxidation, and Emissions of Methane in Rice
Paddies." FEMSMicrobiology 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-XWDoc. 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. Arthur Kirstein, 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,
11-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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. (200 la) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M
University and Caren Mintz, ICF International. August 6, 2001.
Klosterboer, A. (200 Ib) 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 PaytonDeeks, 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. (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 P.K. Bollich (1993) "Methane Emissions from Louisiana First and Ratoon Crop Rice." Soil
Science, 156:42-48.
Lindau, C.W., P.K Bollich, and R.D. DeLaune (1995) "Effect of Rice Variety on Methane Emission from Louisiana
Rice." Agriculture, Ecosystems and Environment, 54:109-114.
References 11-39
-------
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 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) 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 June 3, 1999.
May hew, W. (1997) Personal Communication. Walter May hew, 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 .
11-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Saichuk, J. (1997) Personal Communication. John Saichuk, Louisiana State University and Holly Simpkins, ICF
Incorporated. November 24, 1997.
Sass, R.L., F.M Fisher, P.A. Harcombe, and F.T. Turner (1991a) "Mitigation of Methane Emissions from Rice
Fields: Possible Adverse Effects of Incorporated Rice Straw." Global Biogeochemical Cycles, 5:275-287.
Sass, R.L., F.M. Fisher, F.T. Turner, and M.F. Jund (1991b) "Methane Emissions from Rice Fields as Influenced by
Solar Radiation, Temperature, and Straw Incorporation." Global Biogeochemical Cycles, 5:335-350.
Sass, R.L., F.M. Fisher, P.A. Harcombe, and F.T. Turner (1990) "Methane Production and Emissions in a Texas
Rice Field." Global Biogeochemical Cycles, 4:47-68.
Schueneman, T. (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 Deeks, 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 Deeks, 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.
Schueneman, T. (1997) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach
County, FL and Barbara Braatz, ICF Incorporated. November 7, 1997.
Slaton, N. (200 la) 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 Deeks, 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.
References 11-41
-------
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. (200la) 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 PaytonDeeks, 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 (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
.
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
.
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.
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. (2005) Email correspondence. Tim Walker, Assistant Research Professor, Mississippi State University
Delta Branch Exp. Station and Lauren Flinn, ICF International.. July 2005.
11-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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. 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 2007) 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.
Anderson, S. (2000) Personal Communication. Lee-Ann Tracy, ERG and Steve Anderson, Agricultural Statistician,
U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 31, 2000.
Anonymous (1924) Fertilizer Used on Cotton, 1923-1924. "Miscellaneous Agricultural Statistics," Table 753.
1924 Yearbook of the Department of Agriculture, 1171.
ASAE (1999) ASAE Standards 1999, 46th Edition. American Society of Agricultural Engineers. St. Joseph, MI.
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.
Bastian, R. (2006) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection
Agency, Washington, DC and Lauren Flinn, ICF International.. July 17, 2006.
Bastian, R. (2005) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection
Agency, Washington, DC and Lauren Flinn, ICF International. September 2005.
Bastian, R. (2003) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection
Agency, Washington, DC and Caren Mintz, ICF International. August 13, 2003.
Bastian, R. (2002) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection
Agency, Washington, DC and Caren Mintz, ICF International.. August 23, 2002.
Battaglin, W.A., and D. A. Goolsby (1994) Spatial Data in Geographic Information System Format on Agricultural
Chemical Use, Land Use, and Cropping Practices in the United States. U.S. Geological Survey Water-Resources
References 11-43
-------
Investigations Report 94-4176.
Bogue A.G. (1963) From Prairie to Corn Belt: Farming on the Illinois and low a prairies 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, I, 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 USDA
Natural Resources Conservation Service. Fort Collins, CO.
Brenner, J., K. Paustian., G. Bluhm, J. Cipra, M. Easter, E.T. Elliott, T. Koutza, K. Killian, J. Schuler, S. Williams
(2001) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation Practice
Application in Iowa. Final report to the Iowa Conservation Partnership. Colorado State University Natural
Resource Ecology Laboratory and U.S. Department of Agriculture Natural Resources Conservation Service. Fort
Collins, CO.
Brumme, R., Borken, W., and Finke, S. (1999) "Hierarchical control on nitrous oxide emission in forest
ecosystems." Global Biochem. Cycles, 13:1137-1148.
Butterbach-Bahl, K., R. Gasche, L. Breuer, and H. Papen. (1997) "Fluxes of NO and N2O from temperate forest
soils: impact of forest type, N deposition and of liming on the NO and N2O emissions." Nutr. Cycl. Agroecosyst.,
48:79-90.
Carpenter, G.H. (1992) "Current Litter Practices and Future Needs." In 1992 National Poultry Waste Management
Symposium Proceedings. J.P. Blake, J.O. Donald, and P.H. Patterson (eds.); Auburn University Printing Service.
Auburn, AL, 268-273.
Carpenter, G. and J. Starkey (2007) Personal Communication. Glenn Carpenter, USDA; John Starkey, U.S. Poultry
& Egg Association and Victoria Thompson, ICF International, April to June, 2007.
ChilcottE.C. (1910)^4 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.
Clough, T., J.E. Bertram, R.R. Sherlock, R.L. Leonard, and B.L. Nowicki (2006) "Comparison of measured and
EF5-r-derived N2O fluxes from a spring-fed river." Glob. Change Biol., 12:477-488.
Cochran, W.G. (1977) Sampling Techniques, Third Edition. Wiley Publishing, New York.
Corre, M.D., D.J. Pennock, C. van Kessel, and O.K. Elliott (1999) "Estimation of annual nitrous oxide emissions
from a transitional grassland-forest region in Saskatchewan, Canada. Biogeochem., 44:29-49.
CTIC (1998) 1998 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 P. A. Pasteris (1998) "Development of high-
quality spatial datasets for the United States." Proc., 1st International Conference on Geospatial Information in
Agriculture and Forestry, Lake Buena Vista, FL, I-512-I-519. June 1-3, 1998.
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.
11-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
DAYMET (No date) Daily Surface Weather and Climatological Summaries. Numerical Terradynamic Simulation
Group (NTSG), University of Montana. Available online at .
Deal, P. (2000) Personal communication. Lee-Ann Tracy, ERG and Peter B. Deal, Rangeland Management
Specialist, Florida Natural Resource Conservation Service. June 21, 2000.
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., 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, and D.S. Schimel (2001)
"Simulated Interaction of Carbon Dynamics and Nitrogen Trace Gas Fluxes Using the DAYCENT Model." In
Schaffer, M., L. Ma, S. Hansen, (eds.); Modeling Carbon and Nitrogen Dynamics for Soil Management. CRC
Press. Boca Raton, Florida. 303-332.
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.
Denier van der Gon, H., and A. Bleeker (2005) "Indirect N2O emission due to atmospheric N deposition for the
Netherlands." Atmos. Environ., 39:5827-5838.
Dong, L.F., D.B. Nedwell, I. Colbeck, and J. Finch (2004) "Nitrous oxide emission from some English and Welsh
rivers and estuaries." Water Air Soil Pollution: Focus, 4:127-134.
Edmonds, L., N. Gollehon, R.L. Kellogg, B. Kintzer, L. Knight, C. Lander, J. Lemunyon, D. Meyer, D.C. Moffitt,
and J. Schaeffer (2003) "Costs Associated with Development and Implementation of Comprehensive Nutrient
Management Plans." Part 1. Nutrient Management, Land Treatment, Manure and Wastewater Handling and
Storage, andRecordkeeping. Natural Resource Conservation Service, U.S. Department of Agriculture.
Elliott, F.F. (1933) Types of Farming in the United States. U.S. Department of Commerce. Government Printing
Office. Washington, DC.
Elliott, F.F. and J.W. Tapp (1928) Types of Farming in North Dakota. U.S. Department of Agriculture Technical
Bulletin Number 102.
Ellsworth, J.O. (1929) Types of Farming in Oklahoma. Agricultural Experiment Station Bulletin Number 181.
Oklahoma Agricultural and Mechanical College.
Engle, R.H. and B.R. Makela (1947) "Where is All the Fertilizer Going?" The Fertilizer Review. The National
Fertilizer Association, Vol. XXII, 6:7-10.
EPA (2003) Clean Watersheds Needs Survey 2000—Report to Congress, U.S. Environmental Protection Agency.
Washington, DC. Available online at .
EPA (2002) Cost Methodology for the Final Revisions to the National Pollutant Discharge Elimination System
Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations. EPA-821-R-03-004.
December 2002.
EPA (1999) Biosolids Generation, Use and Disposal in the United States. Office of Solid Waste, U.S.
Environmental Protection Agency. Available online at .
References 11-45
-------
EPA (1997) 1996 Clean Watersheds Needs Survey Report to Congress—Assessment of Needs for Publicly Owned
Wastewater Treatment Facilities, Correction of Combined Sewer Overflows, and management of Storm Water and
Nonpoint Source Pollution in the United States, U.S. Environmental Protection Agency. Washington, DC.
Available online at .
EPA (1993) Federal Register. Part II. Standards for the Use and Disposal of Sewage Sludge; Final Rules. U.S.
Environmental Protection Agency, 40 CFR Parts 257, 403, and 503.
EPA (1992) Global Methane Emissions from Livestock and Poultry Manure. Office of Air and Radiation , U.S.
Environmental Protection Agency. February 1992.
ERG (2003) Methodology for Estimating Uncertainty for Manure Management Greenhouse Gas Inventory.
Contract No. GS-10F-0036, Task Order 005. Memorandum to EPA from ERG. September 26, 2003.
ERS (2003) Ag Chemical and Production Technology. Economic Research Service, U.S. Department of
Agriculture.
ERS (2002) Economic Research Service, U.S. Department of Agriculture. Available online at
.
ERS (1997) Cropping Practices Survey Data—1995. Economic Research Service, U.S. Department of Agriculture.
Available online at .
ERS (1994) Fertilizer Use and Price Statistics. Stock #86012. Economic Research Service, U.S. Department of
Agriculture.
ERS (19%$) Agricultural Resources—Inputs Situation and Outlook Report. AR-9. Economic Research Service, U.S.
Department of Agriculture.
Eve, M. (2001) E-mail correspondence. Statistics on U.S. organic soil areas cultivated in 1982, 1992, and 1997,
which were extracted from the 1997 National Resources Inventory. Marlen Eve of the Natural Resources Ecology
Laboratory to Barbara Braatz and Caren Mintz, ICF International. September 21, 2001.
FAO (2006) "Yearly U.S. total horse population." Food and Agriculture Organization of the United Nations
database. Available online at .
Fraps, G.S. and S.E. Asbury (1931) Commercial Fertilizers in 1930-1931 and Their Uses. Agricultural Experiment
Station Bulletin Number 434. Agricultural and Mechanical College of Texas.
Hardies, E.W. and A.N. Hume (1927) Wheat in South Dakota. Agronomy Department Bulletin Number 222.
Agricultural Experiment Station, South Dakota State College of Agriculture and Mechanical Arts. Brookings, SD.
Garey, L.F. (1929) Types of Farming in Minnesota. Agricultural Experiment Station Bulletin Number 257.
University of Minnesota. St. Paul, MN.
Grant, W.R. andR.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.
Hiscock, K.M., A.S. Bateman, T. Fukada, and P.P. Dennis (2002) "The concentration and distribution of
groundwater N2O in the Chalk aquifer of eastern England." In J. Van Ham, A.P.M. Baede, R. Guicherit, and
J.G.F.M Williams-Jacobse (eds.); Proc. 3rd Internal. Symp. Non-CO2 Greenhouse Gases. Maastricht, The
Netherlands, 185-190.
11-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Hiscock, K.M., A.S. Bateman, I. H. Muhlherr, T. Fukada, and P.P. Dennis (2003) "Indirect emissions of nitrous
oxide from regional aquifers in the United Kingdom." Environ. Sci. Technol., 37:3507-3512.
Hodges, J.A., F.F. Elliott, and W.E. Grimes (1930) Types of Farming in Kansas. Agricultural Experiment Station
Bulletin Number 251. Kansas State Agricultural College. Manhattan, KS.
Holmes C.L. (1929) Types of Farming in Iowa. Agricultural Experiment Station Bulletin Number 259. Iowa State
College of Agriculture and Mechanic Arts. Ames, IA.
Holmes G.K. (1902) "Practices in Crop Rotation." Yearbook of the Department of Agriculture, 519-532.
Kurd E.B. (1929) The Corn Enterprise in Iowa. Agricultural Experiment Station Bulletin Number 268. Iowa State
College of Agriculture and Mechanic Arts. Ames, IA.
Kurd E.B. (1930) Cropping Systems in Iowa Past and Present. Agricultural Experiment Station Bulletin Number
268. Iowa State College of Agriculture and Mechanic Arts. Ames, IA.
Hurt, R.D. (1994) American Agriculture: A Brief History. Iowa State University Press. Ames, IA.
Ibach, D.B. and J.R. Adams (1967) Fertilizer Use in the United States by Crops and Areas, 1964 Estimates.
Statistical Bulletin Number 408, U.S. Department of Agriculture.
Ibach, D.B., J.R. Adams, and E.I. Fox (1964) Commercial Fertilizer used on Crops and Pasture in the United
States, 1959 Estimates. U.S. Department of Agriculture Statistical Bulletin Number 348.
Iowa State College Staff Members (1946)^4 Century of Farming in Iowa 1846-1946. The Iowa State College Press.
Ames, IA.
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 (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 (UV.2000). May 2000.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories.
Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
Co-Operation and Development, International Energy Agency. Paris, France.
Johnson, D. (2000) Personal Communication. Lee-Ann Tracy, ERG and Dan Johnson, State Water Management
Engineer, California Natural Resource Conservation Service. June 23, 2000.
Kellogg R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon (2000) Manure Nutrients Relative to Capacity of
Cropland and Pastureland to Assimilate Nutrients: Spatial and Temporal Trends for the United States. U.S.
Department of Agriculture Publication Number npsOO-0579.
Kezer A. (ca 1917) Dry Farming in Colorado. Colorado State Board of Immigration, Denver, CO.
Klemedtsson, L.; Kasimir Klemedtsson, A.; Escala, M., and A. Kulmala (1999) "Inventory of N2O emission from
References 11-47
-------
farmed European peatlands." InApproaches to Greenhouse Gas Inventories ofBiogenic Sources in Agriculture,
Proc. Workshop at Lokeberg, Sweden. A. Freibauer and M. Kaltschmitt (eds.). 79-91. 9-10 July 1998.
Kuchler, AW. (1964) "The Potential Natural Vegetation of the Conterminous United States." Amer. Geographical
Soc. NY, Special Publication No. 36.
Lange, J. (2000) Personal Communication. Lee-Ann Tracy, ERG and JohnLange, Agricultural Statistician, U.S.
Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 8, 2000.
Langston C.W., L.M. Davis, C.A. Juve, O.C. Stine, A.E. Wight, AJ. 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.
Me Farland, M.J. (2001) Biosolids Engineering, New York: McGraw-Hill, p. 2.12.
Metcalf and Eddy, Inc. (1991) Wastewater Engineering: Treatment, Disposal, and Reuse, Third Edition. McGraw-
Hill Publishing Company, New York, 772.
Miller, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Paul Miller, Iowa Natural Resource
Conservation Service. June 12, 2000.
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.
Mosier, A.R. (2004) E-mail correspondence regarding the uncertainty in estimates of N application rates for specific
crops (+/-20). Arvin Mosier, Agricultural Research Service, USDA and Stephen Del Grosso, Natural Resource
Ecology Laboratory, Colorado State University,. 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 AgChl(99). National Agricultural
Statistics Service, U.S. Department of Agriculture. Available online at
.
NASS (1992) Agricultural Chemical Usage: 1991 Field Crops Summary. Report AgChl(92). National Agricultural
Statistics Service, U.S. Department of Agriculture. Available online at
.
NEBRA (2007) A National Biosolids Regulation, Quality, End Use & Disposal Survey. North East Biosolids and
Residuals Association, July 21, 2007
NFA (1946) Charting the Fertilizer Course: Results ofNFA 's Third Practice Survey. National Fertilizer
Association. The Fertilizer Review. Vol. XXI, 2:7-13.
NRAES (1992) On-Farm Composting Handbook (NRAES-54). Natural Resource, Agriculture, and Engineering
Service. Available online at .
11-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
NRIAI (2003) Regional Budget and Cost Information. Natural Resources Inventory and Analysis Institute, Natural
Resources Conservation Service. USD A. Available online at:
Ogle, S. (2002) E-mail correspondence containing revised statistics on U.S. histosol areas cultivated in 1982, 1992,
and 1997, which were extracted from the 1997 National Resources Inventory by Marlen Eve. Stephen Ogle, Natural
Resources Ecology Laboratory and Barbara Braatz , ICF International. January 9, 2002.
Ogle, S.M., FJ. Breidt, M. Easter, S. Williams, andK. Paustian. (2007) "Empirically-Based Uncertainty Associated
with Modeling Carbon Sequestration in Soils." Ecological Modeling 205:453-463.
Parton, W.J., M.D. Hartman, D.S. Ojima, and D.S. Schimel (1998) "DAYCENT: Its Land Surface Submodel:
Description and Testing". Glob. Planet. Chang. 19: 35-48.
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, B.C. Parker, E.W. Sheets, and A.T. Semple (1924) "Hay." Yearbook of the Department of
Agriculture, 285-376.
Poe, G., N. Bills, B. Bellows, P. Crosscombe, R. Koelsch, M. Kreher, and P. Wright (1999) Documenting the Status
of Dairy Manure Management in New York: Current Practices and Willingness to Participate in Voluntary
Programs. Staff Paper, Dept. of Agricultural, Resource, and Managerial Economics, Cornell University, Ithaca,
NY, September 1999.
Reay, D.S., K.A. Smith, and A.C. Edwards (2004) "Nitrous oxide in agricultural drainage waters following field
fertilisation." Water Air Soil Pollution: Focus, 4:437-451.
Reay, D., K.A. Smith, A.C. Edwards, K.M. Hiscock, L.F. Dong, and D. Nedwell (2005) "Indirect nitrous oxide
emissions: revised emission factors." Environ. Sciences, 2:153-158.
Rochette, P., D.A. Angers, G. Belanger, M.H. Chantigny, D. Prevost, G. Levesque, (2004) "Emissions of N2O from
alfalfa and soybean crops in eastern Canada." Soil Sci. Soc. Am. J. 68:493-506.
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 Soils and Men. Agricultural Yearbook 1938. U.S.
Department of Agriculture.
Russell E.Z., S.S. Buckley, C.E. Baker, C.E. Gibbons, R.H. Wilcox, H.W. Hawthorne, S.W. Mendum, O.C. Stine,
O.K. Holmes, A.V. Swarthout, W.B. Bell, G.S. Jamieson, C.W. Warburton, and C.F. Langworthy (1922) Hog
Production and Marketing. Yearbook of the U.S. Department of Agriculture.
Safley, L.M. (2000) Personal Communication. Deb Bartram, ERG and L.M. Safley, President, Agri-Waste
Technology. June 2000.
Safley, L.M., M.E. Casada, J.W. Woodbury, and J.F. Roos (1992) Global Methane Emissions from Livestock and
Poultry Manure. EPA/400/1-91/048, Office of Air and Radiation, U.S. Environmental Protection Agency.
February 1992.
Sawamoto, T., Y. Nakajima, M. Kasuya, H. Tsuruta, and K. Yagi (2005) "Evaluation of emission factors for
References 11-49
-------
indirect N2O emission due to nitrogen leaching in agro-ecosystems." Geophys. Res. Lett. 32(3),
doi: 10.1029/2004GL021625.
Saxton, K.E., WJ. 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, JJ. (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 WJ. (1908) Types of Farming in the United States. Yearbook of the Department of Agriculture, 351-366.
Spillman WJ. (1907) Cropping Systems for Stock Farms. Yearbook of the Department of Agriculture, 385-398.
Spillman WJ. (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.
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.
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, P.E. 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.
11-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
TVA (1991) Commercial Fertilizers 1991. Tennessee Valley Authority, Muscle Shoals, AL.
TVA (1992a) Commercial Fertilizers 1992. Tennessee Valley Authority, Muscle Shoals, AL.
TVA (1992b) Fertilizer Summary Data 1992. Tennessee Valley Authority, Muscle Shoals, AL.
TVA (1993) Commercial Fertilizers 1993. Tennessee Valley Authority, Muscle Shoals, AL.
TVA (1994) Commercial Fertilizers 1994. Tennessee Valley Authority, Muscle Shoals, AL.
USDA (2007) Crop Production 2006 Summary, National Agricultural Statistics Service, Agricultural Statistics
Board, U.S. Department of Agriculture, Washington, DC. Available online at .
USDA-NASS (2007) USDA National Agricultural Statistics Service, Quick Stats for U.S. and all states county data
for crops. U.S. Department of Agriculture, National Agricultural Statistics Service. Washington, D.C.,
http ://www. nass .usda. gov/QuickStats/Create_County_All.j sp
USDA (2006a) Agriculture Statistics 2006. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC.
USDA (2006b) Crop Production 2005 Summary. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at .
USDA (2005a) Cattle. National Agricultural Statistics Service, U.S. Department of Agriculture. Washington, DC.
January 28, 2005. Available online at .
USDA (2005b) Cattle on Feed. National Agricultural Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 21, 2005. Available online at .
USDA (2005c) Hogs and Pigs. National Agricultural Statistics Service, U.S. Department of Agriculture.
Washington, DC. March 24, 2005. Available online at .
USDA (2005d) Chicken and Eggs Annual Summary. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. February 2005. Available online at .
USDA (2005e) Poultry Production and Value Annual Summary. National Agricultural Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 28, 2005. Available online at
.
USDA (2005f) Sheep and Goats. National Agricultural Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 28, 2005. Available online at .
USDA (2005g) 1992, 1997, and 2002 Census of Agriculture. National Agricultural Statistics Service, U.S.
Department of Agriculture. Washington, DC. Available online at .
USDA (2005h) Agriculture Statistics 2005. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at or
.
USDA (2005i) Crop Production 2004 Summary. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at .
USDA (2004a) Cattle—Final Estimates 1999-2003. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. April 2004. Available online at
References 11-51
-------
.
USDA (2004b) Hogs and Pigs—Final Estimates 1998-2002. National Agricultural Statistics Service, U.S.
Department of Agriculture. Washington, DC. March 2004. Available online at
.
USDA (2004c) Chicken and Eggs—Final Estimates 1998-2003. National Agricultural Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2004d) Poultry Production and Value—Final Estimates 1998-2002. National Agricultural Statistics
Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2004e) Sheep and Goats—Final Estimates 1999-2003. National Agricultural Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2003) Crop Production 2002 Summary. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at . Accessed May 2003.
USDA (2000a) Cattle on Feed. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. April 14, 2000. Data also available online at .
USDA (2000b) 1997 National Resources Inventory. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at .
USDA (2000c) Agricultural Statistics 2000. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at .
USDA (1999a) Cattle—Final Estimates 1994-98. National Agricultural Statistics Service, U.S. Department of
Agriculture. Washington, DC. January 1999. Data also available online at .
USDA (1999b) Poultry Production and Value—Final Estimates 1994-97. National Agricultural Statistics Service,
U.S. Department of Agriculture. Washington, DC. March.
USDA (1999c) Sheep and Goats—Final Estimates 1994-1998. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. January 1999.
USDA (1998a) Chicken and Eggs—Final Estimates 1994-97. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. December 1998.
USDA (1998b) Field Crops Final Estimates 1992-97. Statistical Bulletin Number 947a. National Agricultural
Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at
. Accessed July 2001.
USDA (1998c) Hogs and Pigs—Final Estimates 1993-97. National Agriculture Statistics Service, U.S. Department
of Agriculture. Washington, DC. December 1998. Data also available online at
.
USDA (1996) Agricultural Waste Management Field Handbook, National Engineering Handbook (NEH), Part 651.
Natural Resources Conservation Service, U.S. Department of Agriculture. July 1996.
USDA (1995a) Cattle—Final Estimates 1989-93. National Agriculture Statistics Service, U.S. Department of
11-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Agriculture. Washington, DC. January 1995. Data also available online at .
USDA (1995b) Poultry Production and Value—Final Estimates 1989-1993. National Agriculture Statistics
Service, U.S. Department of Agriculture. Washington, DC.
USDA (1994a) Field Crops: Final Estimates, 1987-1992. Statistical Bulletin Number 896, National Agriculture
Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at
.
USDA (1994b) Hogs and Pigs—Final Estimates 1988-92. National Agriculture Statistics Service, U.S. Department
of Agriculture. Washington, DC. December 1994. Data also available online at
.
USDA (1994c) Sheep and Goats—Final Estimates 1989-1993, National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. January 1994.
USDA. (1966) Consumption of Commercial Fertilizers and Primary Plant Nutrients in the United States, 1850-
1964 and By States, 1945-1964. Statistical Bulletin Number 375, Statistical Reporting Service, U.S. Department of
Agriculture.
USDA. (1957) Fertilizer Used on Crops and Pastures in the United States—1954 Estimates. Statistical Bulletin
Number 216, Agricultural Research Service, U.S. Department of Agriculture.
USDA. (1954) Fertilizer Use and Crop Yields in the United States. Agricultural Handbook Number 68, the
Fertilizer Work Group, U.S. Department of Agriculture.
USDA. (1946) Fertilizers and Lime in the United States. Miscellaneous Publication Number 586, U.S. Department
of Agriculture.
VEMAP (1995) Members (J.M. Melillo, J. Borchers, J. Chaney, 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 CC>2 Doubling." Global Biogeochemical Cycles, 9:407-437.
Vogelmann, J.E., S.M. Howard, L. Yang, C. R. Larson, B. K. Wylie, and J. N. VanDriel (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.
Williams-Jacobse, J.G.F.M. (ed.) (2002) Proceedings 3rd International Symposium Non-CO2 Greenhouse Gase.,
Maastricht, the Netherlands, 185-190.
Wright, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Peter Wright, Cornell University, College of
Agriculture and Life Sciences. June 23, 2000.
Field Burning of Agricultural Residues
References 11-53
-------
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. Earthscan 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 PaytonDeeks, 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.
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. (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. (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 and Sinks: 1990. Office of Research and Planning,
Illinois Department of Energy and Natural Resources. Springfield, IL.
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.
11-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 1996IPCC 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 of 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 Flinn, 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 PaytonDeeks, 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.
Klosterboer, A. (1999b) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M
University and PaytonDeeks, ICF International.. August 12, 1999.
Lancero, J. (2007) Email correspondence. Jeff Lancero, California Air Resources Board and Victoria Thompson,
ICF International. July 24, 2007.
Lancero, J. (2006) mail 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.
References 11-55
-------
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. (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 Deeks, 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 Deeks, ICF International. August 17, 2000.
Noller, J. (1996) Personal Communication. JohnNoller, Missouri Department of Natural Resources and Heike
Mainhardt, ICF Incorporated. July 30, 1996.
11-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 .
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 Deeks, 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. Sttitzle (1987) "Biomass Residues." In Hall, D.O. and Overend, R.P. (eds.) Biomass. John
Wiley and Sons, Ltd. Chichester, UK.
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
.
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
.
Turn, S.Q., B.M. Jenkins, J.C. Chow, L.C. Pritchett, D. Campbell, T. Cahill, and S.A. Whalen (1997) "Elemental
characterization of paniculate matter emitted frombiomass 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.
References 11-57
-------
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. (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 Flinn, 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 CarenMintz, ICF International. June 11, 2003.
Wisconsin Department of Natural Resources (1993) Wisconsin Greenhouse Gas Emissions: Estimates for 1990.
Bureau of Air Management, Wisconsin Department of Natural Resources, Madison, WI.
Land Use, Land-Use Change, and Forestry
IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. The Intergovernmental
11-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Panel on Climate Change, National Greenhouse Gas Inventories Programme, J. Penman, et al., eds. August 13,
2004. Available online at .
Forest Land Remaining Forest Land: Changes in Forest Carbon Stock
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. Washington, DC: American Forest &
Paper Association.
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.
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 ofU. S. Greenhouse Gas Emissions and Sinks: 1990-2004. EPA, Office of Atmospheric
Programs. Washington, DC.
References 11-59
-------
Prayer, W.E., and G.M. Furnival (1999) "Forest Survey Sampling Designs: A History." Journal of Forestry 97(12):
4-10.
Gillespie, A.J.R. (1999) "Rationale for a National Annual Forest Inventory Program." Journal of Forestry 97(12):
16-20.
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 (+/-
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 (+7-1.2%). October 27, 2006.
Heath, L.S., J.E., Smith, and R.A. Birdsey (2003) Carbon Trends in U. S. Forestlands: A Context for the Role of
Soils in Forest Carbon Sequestration. In J. M. Kimble, L. S. Heath, R. A. Birdsey, and R. Lai, editors. The Potential
ofU. S. Forest Soils to Sequester Carbon and Mitigate the Greenhouse Effect. Lewis Publishers (CRC Press). Boca
Raton, FL, 35-45.
Heath, L. S., and J.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. Madison, WI: USD A, Forest Service, Forest Products Laboratory. Available online at
.
Howard, James L. (forthcoming) U.S. timber production, trade, consumption, and price statistics 1965 to 2005.
Res. Pap. FPL-RP-XXX. Madison, WI: USD A, Forest Service, Forest Products Laboratory.
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.
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.
11-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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.
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
Conf., 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, P.E. Schroeder, and R.A. Birdsey (2000) "Toward Error Analysis of Large-Scale Forest
Carbon Budgets." Global Ecology andBiogeography 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 J.E. Smith (2004) "A method countries can use to estimate changes in carbon stored in
harvested wood products and the uncertainty of such estimates." Environmental Management 33(Suppl. 1):S65-
S73.
Skog, K.E. (In preparation) Sequestration of carbon in harvested wood products for the United States. USDA Forest
Service, Forest Products Laboratory. Draft manuscript, July 2007.
Smith, J.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 (2004 a) "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, J.E., L.S. Heath, and M.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.
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.
References 11-61
-------
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.
USDA Forest Service. (2006a) Forest Inventory and Analysis National Program, FIA library. Available online at
. Accessed September 20, 2006.
USDA Forest Service. (2006b) Forest Inventory and Analysis Data Center. Available online at
. Accessed September 20, 2006.
USDA Forest Service. (2006c) FIA Data Mart: Download. Available online at
. Click on documentation link to download Users Guide
to the Forest Inventory Snapshot Database Version 2.1. Accessed September 20, 2006.
USDA Forest 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.
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, J.E. (2006) "Land Use Change Effects on Forest Carbon Cycling
Throughout the Southern United States." Journal of Environmental Quality, 35:1348-1363.
Woodbury, P.B., L.S. Heath, and J.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: N2O Fluxes from Soils
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. In: Nitrogen Fertilization
in the Environment, P.E. Bacon (ed.), Marcel Decker, Inc., New York.
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.
North Carolina State Forest Nutrition Cooperative (2002) 31st Annual Report. Available online at
. Accessed October 2004.
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 .
11-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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., and T.H. Dao (2000) "Soil organic carbon sequestration
potential of adopting conservation tillage in U.S. croplands." J Soil Water Conserv 55:365-373.
Armentano, T.V. 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. I,
281-311.
Brady, N.C. and R.R. Weil (1999) The Nature and Properties of Soils. Prentice Hall. Upper Saddle River, NJ, 881.
CTIC (1998) "1998 Crop Residue Management Executive Summary." Conservation Technology Information
Center. West Lafayette, IN.
Daly, C., R.P. Neilson, and D.L. Phillips (1994) "A Statistical-Topographic Model for Mapping Climatological
Precipitation Over Mountainous Terrain." Journal of Applied Meteorology 33:140-158.
Edmonds, L., R. L. Kellogg, B. Kintzer, L. Knight, C. Lander, J. Lemunyon, D. Meyer, D.C. Moffitt, and J.
Schaefer (2003) "Costs associated with development and implementation of Comprehensive Nutrient Management
Plans." Parti—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 (2006) Yearly U.S. Total Horse Population Data from the Food and Agriculture Organization of the United
Nations database. Available online at . Accessed July 2006.
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 Pastur eland to Assimilate Nutrients: Spatial and Temporal Trends for the United States. U.S.
References 11-63
-------
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.
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 AgCHl(99). National Agricultural
Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at
.
NASS (1992) Agricultural Chemical Usage: 1991 Field Crops Summary. Report AgChl(92). National Agricultural
Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at
.
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," USDA Agriculture
Handbook 296, United States Department of Agriculture, Natural Resources Conservation Service, National Soil
Survey Cente., Lincoln, NE, pp. 156.
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
Ogle, S.M., M.D. Eve, F.J. Breidt, and K. Paustian (2003) "Uncertainty in estimating land use and management
impacts on soil organic carbon storage for U.S. agroecosystems between 1982 and 1997." Global Change Biology
9:1521-1542.
Ogle, S.M., 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., F.J. Breidt, M. Easter, S. Williams and K. Paustian. (2007) "Empirically-Based Uncertainty Associated
with Modeling Carbon Sequestration Rates in Soils." Ecological Modeling 205:453-463.
Parton, W.J., D.S. Schimel, C.V. Cole, D.S. Ojima (1987) "Analysis of factors controlling soil organic matter levels
in Great Plains grasslands." Soil Science Society of America Journal 51:1173-1179.
Parton, W.J., J.W.B. Stewart, C.V. Cole. (1988) "Dynamics of C, N, P, and S in grassland soils: a model."
Biogeochemistry 5:109-131.
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.
11-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Potter, C. S., J.T. Randerson, C.B. Fields, P.A. 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-FSA (2007) Conservation Reserve Program Summary and Enrollment Statistics FY 2006. U.S. Department
of Agriculture, Farm Service Agency. Washington, D.C., Available online at
http://www.fsa.usda.gov/Internet/FSA_File/06rpt.pdf.
USDA (2006a) Cattle. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC.
January 2006. Available online at .
USDA (2006b) Cattle on Feed. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. April 2006. Available online at .
USDA (2006c) Chicken and Eggs 2005 Summary. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. February 2006. Available online at .
USDA (2006d) Poultry - Production and Value 2005 Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2006. Available online at .
USDA (2006e) Published Estimates Database. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. Available online at . Accessed May 2006.
USDA (2005a) Cattle. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC.
January 28, 2005. Available online at .
USDA (2005b) Cattle on Feed. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 21, 2005. Available online at .
USDA (2005c) Hogs and Pigs. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. March 24, 2005. Available online at .
USDA (2005d) Chicken and Eggs Annual Summary. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. February 2005. Available online at .
USDA (2005e) Poultry Production and Value Annual Summary. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 28, 2005. Available online at
.
USDA (20051) Sheep and Goats. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. January 28, 2005. Available online at .
USDA (2005g) Census of Agriculture. National Agriculture Statistics Service, U.S. Department of Agriculture.
Washington, DC. Data for 1992, 1997, and 2002 available from in June 2005.
USDA (2004a) Cattle—Final Estimates 1999-2003. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. April 2004. Available online at
References 11-65
-------
.
USDA (2004b) Hogs and Pigs—Final Estimates 1998-2002. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. March 2004. Available online at
.
USDA (2004c) Chicken and Eggs—Final Estimates 1998-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2004d) Poultry Production and Value—Final Estimates 1998-2002. National Agriculture Statistics Service,
U.S. Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2004e) Sheep and Goats—Final Estimates 1999-2003. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. April 2004. Available online at
.
USDA (2000) Chicken and Eggs—Final Estimates 1988-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. Available online at . May 3, 2000.
USDA (1999a) Cattle—Final Estimates 1994-98. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. January 1999. Available online at .
USDA (1999b) Poultry Production and Value—Final Estimates 1994-97. National Agriculture Statistics Service,
U.S. Department of Agriculture. Washington, DC. March 1999.
USDA (1999c) Sheep and Goats—Final Estimates 1994-1998. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. January 1999.
USDA (1998a) Chicken and Eggs—Final Estimates 1994-97. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. December 1998.
USDA (1998b) Hogs and Pigs—Final Estimates 1993-97. National Agriculture Statistics Service, U.S. Department
of Agriculture. Washington, DC. December 1998. Available online at .
USDA (1995a) Cattle—Final Estimates 1989-93. National Agriculture Statistics Service, U.S. Department of
Agriculture. Washington, DC. January 1995. Available online at .
USDA (1995b) Poultry Production and Value—Final Estimates 1989-1993. National Agriculture Statistics
Service, U.S. Department of Agriculture. Washington, DC.
USDA (1994a) Hogs and Pigs—Final Estimates 1988-92. National Agriculture Statistics Service, U.S. Department
of Agriculture. Washington, DC. December 1994. Available online at .
USDA (1994b) Sheep and Goats—Final Estimates 1989-1993. National Agriculture Statistics Service, U.S.
Department of Agriculture. Washington, DC. January 1994.
USDA-NRCS (2000) Digital Data And Summary Report: 1997 National Resources Inventory. Revised December
2000. Resources Inventory Division, Natural Resources Conservation Service, United States Department of
Agriculture. Beltsville, MD.
11-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Liming and Urea
AAPFCO (1995 through 2000, 2002 through 2007) 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.
Tepordei, V.V. (1997 through 2006) "Crushed 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," InMinerals Yearbook 1994. U.S. Department of the Interior/Bureau of
Terry, D. (2007) Email correspondence. David Terry, Fertilizer Regulatory program, University of Kentucky and
David Berv, ICF International. September 7, 2007.
Mines, Washington, DC. Available online at
. Accessed August 2000.
Tepordei, V.V. (1995) "Crushed Stone," InMinerals Yearbook 1993. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1107-1147.
Tepordei, V V. (1994) "Crushed Stone," InMinerals Yearbook 1992. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1279-1303.
Tepordei, V.V. (1993) "Crushed Stone," InMinerals Yearbook 1991. U.S. Department of the Interior/Bureau of
Mines, Washington, DC. pp. 1469-1511.
TVA (1991 through 1994) Commercial Fertilizers. Tennessee Valley Authority, Muscle Shoals, AL.
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
.
USGS (2006) Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of 2006. 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.
Willett, J.C. (2007) "Crushed Stone," InMinerals Yearbook 2005. U.S. Department of the Interior/U.S. Geological
References 11-67
-------
Survey, Washington, DC. Available online at
. Accessed August 2007.
Settlements Remaining Settlements: Changes in Carbon Stocks in Urban Trees
Cairns, M.A., S. Brown, E.H. Helmer, and G.A. Baumgardner (1997) "Root Biomass Allocation in the World's
Upland Forests." Oceologia 111: 1-11.
deVries, R.E. (1987) A Preliminary Investigation of the Growth and Longevity of Trees in Central Park. New
Brunswick, NJ: Rutgers University, M.S. thesis.
Dwyer, J.F., D.J. Nowak, M.H. Noble, and S.M Sisinni (2000) Connecting People with Ecosystems in the 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) 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.
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.
Nowak, D.J., (1986) "Silvics of an Urban Tree Species: Norway Maple (Acer platanoides 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):37-42.
Nowak, D.J., J.T. Walton, L.G. Kaya, and J.F. Dwyer (2005) "The Increasing Influence of Urban Environments on
U.S. Forest Management." Journal of Forestry.
11-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
Smith, W.B. and S.R. Shifley (1984) Diameter Growth, Survival, and Volume Estimates for Trees in Indiana and
Illinois. Res. Pap. NC-257. North Central Forest Experiment Station, U.S. Department of Agriculture Forest
Service. St. Paul, MN.
Settlements Remaining Settlements: N2O Fluxes from Soils
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.
Ruddy B.C., D.L. Lorenz, and D.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, 2007) 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. EPA. 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 .
References 11-69
-------
Oshins, C., and D. Block (2000) "Feedstock Composition at Composting Sites." Biocycle 41(9):31-34.
Schneider, S. (2007, 2008) Email correspondence. Shelly Schneider, Franklin Associates, A Division of ERG and
Sarah Shapiro, ICF International.
Tchobanoglous, G., H. Theisen, and S.A. Vigil (1993) Integrated Solid Waste Management, 1st edition. McGraw-
Hill, NY. Cited by Barlaz (1998).
Waste
Landfills
40 CFR Part 60, Subpart Cc (2005) Emission Guidelines and Compliance Times for Municipal Solid Waste
Landfills, 60.30c~60.36c, Code of Federal Regulations, Title 40. Available online at
.
40 CFR Part 60, Subpart WWW (2005) Standards of Performance for Municipal Solid Waste Landfills, 60.750-
60.759, Code of Federal Regulations, Title 40. Available online at
.
Bingemer, H. and J. Crutzen (1987) "The Production of Methane from Solid Wastes," Journal of Geophysical
Research, 92:2181-2187.
BioCycle (2006) "15th Annual BioCycle Nationwide Survey: The State of Garbage in America" By P. Simmons,
N. Goldstein, S. Kaufman, N. Goldstein, N. Themelis, and J. Thompson. BioCycle. April 2006.
Czepiel, P., B. Mosher, P. Crill, and R. Harriss (1996) "Quantifying the Effect of Oxidation on Landfill Methane
Emissions." Journal of Geophysical Research, 101(D11):16721-16730.
EIA (2007) Voluntary Greenhouse Gas Reports for EIA Form 1605B (Reporting Year 2005). Available online at
.
EPA (2007) Landfill Gas-to-Energy Project Database. Landfill Methane and Outreach Program. July 2007.
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 (2007). Production Data Supplied by ERG for 1990-2006 for Pulp and Paper, Fruits and Vegetables, and
Meat. July.
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.
11-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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, and D. Epperson (1993) "A Comparison of Methods for Estimating Global Methane
Emissions from Landfills." Chemosphere, 26(l-4):387-400.
RTI (2004) Documentation for Changes to the Methodology for the Inventory of Methane Emissions from
Landfills. September 2004.
Solid Waste Association of North America (SWAN A) (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.
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 (2006) U.S. Department of Energy - Energy Information Administration (EIA). Annual Energy Outlook 2006
with Projections to 2030. DOE/EIA-0383(2006). (February). Available online at
. Date Accessed: October 2006.
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.
EPA-440/1-75-046. Washington DC, October 1975.
References 11-71
-------
EPA (1992) Clean Watersheds Needs Survey 1992 - Report to Congress. Office of Wastewater Management, U.S.
Environmental Protection Agency. Washington, DC.
EPA (1993a) Anthropogenic Methane Emissions in the U.S.: Estimates for 1990, Report to Congress. Office of Air
and Radiation, U.S. Environmental Protection Agency. Washington, DC. April 1993.
EPA (1993b) Development Document for the Proposed Effluent Limitations Guidelines and Standards for the Pulp,
Paper andPaperboardPoint Source Category. EPA-821-R-93-019. Office of Water, U.S. Environmental
Protection Agency. Washington, DC. October 1993.
EPA (1996) 1996 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 B &
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.
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.,
11-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
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 (20061) 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) 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.
LBNL (2003) Lawrence Berkeley National Laboratory (LBNL). Energy Efficiency Improvement and Cost Saving
Opportunities for the Corn Wet Milling Industry: An ENERGY STAR® Guide for Energy and Plant Managers.
LBNL-52307. July. Available online at . Accessed October 2006.
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 andReuse, 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, D.C. (May 3). Available online at . Accessed October 2006.
Paper 360° (2007) "U.S. production rises slightly in December." March 2007. Available online at <
References 11-73
-------
http://www.thefreelibrary.eom/U.S.+production+rises+slightly+in+December.(The+Pulse)-a0161909243>.
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.
Rausch (2006) "The Future of Coproducts from Corn Processing." Applied Biochemistry and Biotechnology. 128:
47-86. Available online at . Accessed October, 2006.
Renewable Fuels Association (2006) Historic U.S. Fuel Ethanol Production. Available online at
. Accessed June 2007.
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.
U.S. Census Bureau (2007a) International Database. Available online at
and . Accessed July 2007.
U.S. Census Bureau (2007b) "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 July 2007.
USDA (2007a) National Agricultural Statistics Service. Washington, DC. Available online at
and <
http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/>. Accessed July 2007.
USDA (2007b) Economic Research Service. U.S. Food Supply: Nutrients and Other Food Components, Per Capita
Per Day. Washington DC. Available online at
. Accessed July 2007.
USDA (2005) United States Department of Agriculture (USDA). Office of Energy Policy and New Uses. USDA's
2002 Ethanol Cost-of-Production Survey. Agricultural Economic Report Number 841. July.
USPoultry (2006) Email correspondence. John Starkey, USPOULTRY to D. Bartram, ERG. 30 August 2006.
White and Johnson (2003) White, P.J. 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-
11-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2006
-------
X.
Waste Sources of Indirect Greenhouse Gas Emissions
EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency,
Washington, DC. December 19, 2006. 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 (EPA). December 22,
2003.
EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42. Office of Air Quality Planning and Standards,
U.S. Environmental Protection Agency, Research Triangle Park, NC. October 1997.
References 11-75
------- |