EPA430-R-13-001
APRIL 12,2013
U.S. Environmental Protection Agency
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
U.S.A.
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. To request free copies of this report, call
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All data tables of this document are available for the full time series 1990 through 2011, 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) 343-897, weitz.melissa@epa.gov.
For more information regarding climate change and greenhouse gas emissions, see the EPA web site at
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Released for printing: April 15, 2013
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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 emissions from fuel combustion was led by Leif Hockstad. Venu Ghanta directed the work on mobile
combustion and transportation. Work on industrial process emissions was led by Mausami Desai. Work on fugitive
methane emissions from the energy sector was directed by Melissa Weitz and Gate Hight. Calculations for the
waste sector were led by Rachel Schmeltz. Tom Wirth directed work on the Agriculture, and together with Jennifer
Jenkins and Pete Epanchin, directed work on the Land Use, Land-Use Change, and Forestry chapters. Work on
emissions of HFCs, PFCs, and SF6 was directed by Deborah Ottinger and Dave Godwin.
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 and the full Inventory team at ICF International including
Randy Freed, Diana Pape, Robert Lanza, Toby Mandel, Lauren Pederson, Mollie Averyt, Victoria Thompson, Mark
Flugge, Tristan Kessler, Katrin Moffroid, Seth Greenburg, Larry O'Rourke, Deborah Harris, Emily Rowan, Joseph
Indvik, Aaron Sobel, Leslie Chinery, Dean Gouveia, Neha Mukhi, Eric Stricklin, Alexander Lataille, Pier LaFarge,
Nick Devonshire, Andrew Pettit, Rachel Steele, Marybeth Riley-Gilbert, Sarah Biggar, Greg Carlock, Ben Eskin,
David Towle, Bikash Acharya, Derina Man, Bobby Renz, Delia Jones, Christine Wrublesky, Rebecca Ferenchiak,
Jessica Renny, Maribelle Rodriguez, Dustin Meyer, Nikita Pavlenko, Thuy Phung, and Cassandra Snow for
synthesizing this report and preparing many of the individual analyses. Eastern Research Group, RTI International,
Raven Ridge Resources, and Ruby Canyon Engineering Inc. also provided significant analytical support.
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The United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas
Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention on
Climate Change (UNFCCC). 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. 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.
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Table of Contents
ACKNOWLEDGMENTS I
PREFACE Ill
TABLE OF CONTENTS V
LIST OF TABLES, FIGURES, AND BOXES VIM
EXECUTIVE SUMMARY 1
ES.l. Background Information 2
ES.2. Recent Trends in U.S. Greenhouse Gas Emissions and Sinks 4
ES.3. Overview of Sector Emissions and Trends 16
ES.4. Other Information 20
1. INTRODUCTION 1-1
1.1 Background Information 1-2
1.2 Institutional Arrangements 1-10
1.3 Inventory Process 1-10
1.4 Methodology and Data Sources 1-12
1.5 Key Categories 1-13
1.6 Quality Assurance and Quality Control (QA/QC) 1-17
1.7 Uncertainty Analysis of Emission Estimates 1-18
1.8 Completeness 1-20
1.9 Organization of Report 1-20
2. TRENDS IN GREENHOUSE GAS EMISSIONS 2-1
2.1 Recent Trends in U.S. Greenhouse Gas Emissions and Sinks 2-1
2.2 Emissions by Economic Sector 2-19
2.3 Indirect Greenhouse Gas Emissions (CO, NOX, NMVOCs, and SO2) 2-30
3. ENERGY 3-1
3.1 Fossil Fuel Combustion (IPCC Source Category 1A) 3-5
3.2 Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-37
3.3 Incineration of Waste (IPCC Source Category lAla) 3-44
3.4 Coal Mining (IPCC Source Category IB la) 3-48
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3.5 Abandoned Underground Coal Mines (IPCC Source Category IBla) 3-51
3.6 Petroleum Systems (IPCC Source Category lB2a) 3-54
3.7 Natural Gas Systems (IPCC Source Category lB2b) 3-60
3.8 Energy Sources of Indirect Greenhouse Gas Emissions 3-72
3.9 International Bunker Fuels (IPCC Source Category 1: Memo Items) 3-73
3.10 WoodBiomass andEthanol Consumption (IPCC Source Category 1A) 3-78
4. INDUSTRIAL PROCESSES 4-1
4.1 Cement Production (IPCC Source Category 2Al) 4-6
4.2 Lime Production (IPCC Source Category 2A2) 4-9
4.3 Other Process Uses of Carbonates (IPCC Source Category 2A3) 4-14
4.4 Soda Ash Production and Consumption (IPCC Source Category 2A4) 4-17
4.5 Glass Production (IPCC Source Category 2A7) 4-20
4.6 Ammonia Production (IPCC Source Category 2B1) 4-23
4.7 Urea Consumption for Non-Agricultural Purposes 4-27
4.8 Nitric Acid Production (IPCC Source Category 2B2) 4-29
4.9 Adipic Acid Production (IPCC Source Category 2B3) 4-32
4.10 Silicon Carbide Production (IPCC Source Category 2B4) and Consumption 4-34
4.11 Petrochemical Production (IPCC Source Category 2B5) 4-37
4.12 Titanium Dioxide Production (IPCC Source Category 2B5) 4-40
4.13 Carbon Dioxide Consumption (IPCC Source Category 2B5) 4-43
4.14 Phosphoric Acid Production (IPCC Source Category 2B5) 4-46
4.15 Iron and Steel Production (IPCC Source Category 2C1) and Metallurgical Coke Production 4-49
4.16 Ferroalloy Production (IPCC Source Category 2C2) 4-58
4.17 Aluminum Production (IPCC Source Category 2C3) 4-61
4.18 Magnesium Production and Processing (IPCC Source Category 2C4) 4-66
4.19 Zinc Production (IPCC Source Category 2C5) 4-70
4.20 Lead Production (IPCC Source Category 2C5) 4-73
4.21 HCFC-22 Production (IPCC Source Category 2E1) 4-75
4.22 Substitution of Ozone Depleting Substances (IPCC Source Category 2F) 4-78
4.23 Semiconductor Manufacture (IPCC Source Category 2F6) 4-82
4.24 Electrical Transmission and Distribution (IPCC Source Category 2F7) 4-89
4.25 Industrial Sources of Indirect Greenhouse Gases 4-95
5. SOLVENT AND OTHER PRODUCT USE 5-1
5.1 Nitrous Oxide from Product Uses (IPCC Source Category 3D) 5-1
5.2 Indirect Greenhouse Gas Emissions from Solvent Use 5-4
6. AGRICULTURE 6-1
6.1 Enteric Fermentation (IPCC Source Category 4A) 6-2
vi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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6.2 Manure Management (IPCC Source Category 4B) 6-8
6.3 Rice Cultivation (IPCC Source Category 4C) 6-14
6.4 Agricultural Soil Management (IPCC Source Category 4D) 6-19
6.5 Field Burning of Agricultural Residues (IPCC Source Category 4F) 6-36
7. LAND USE, LAND-USE CHANGE, AND FORESTRY 7-1
7.1 Representation of the U.S. Land Base 7-4
7.2 Forest Land Remaining Forest Land 7-14
7.3 Land Converted to Forest Land (IPCC Source Category 5A2) 7-30
7.4 Cropland Remaining Cropland (IPCC Source Category 5B1) 7-31
7.5 Land Converted to Cropland (IPCC Source Category 5B2) 7-44
7.6 Grassland Remaining Grassland (IPCC Source Category 5C1) 7-49
7.7 Land Converted to Grassland (IPCC Source Category 5C2) 7-54
7.8 Wetlands Remaining Wetlands 7-58
7.9 Settlements Remaining Settlements 7-63
7.10 Land Converted to Settlements (Source Category 5E2) 7-69
7.11 Other (IPCC Source Category 5G) 7-70
8. WASTE 8-1
8.1 Landfills (IPCC Source Category 6A1) 8-4
8.2 Wastewater Treatment (IPCC Source Category 6B) 8-15
8.3 Waste Incineration (IPCC Source Category 6C) 8-28
8.4 Composting (IPCC Source Category 6D) 8-28
8.5 Waste Sources of Indirect Greenhouse Gases 8-30
9. OTHER 9-1
10. RECALCULATIONS AND IMPROVEMENTS 10-1
11. REFERENCES 11-1
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Table ES-1: Global Wanning Potentials (100-Year Time Horizon) Used in this Report 3
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg or million metric tons CO2 Eq.) 5
Table ES-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg or million metric
tonsCO2Eq.) 10
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg or million
metric tons CO2Eq.) 17
Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg or million metric tons CO2 Eq.).... 19
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg or million metric tons CO2 Eq.) 19
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg or million metric tons CO2 Eq.) 21
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed
(Tg or million metric tons CO2Eq.) 22
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100) 23
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (Years) of
Selected Greenhouse Gases 1-4
Table 1 -2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report 1-8
Table 1-3: Comparison of 100-Year GWPs 1-9
Table 1-4: Key Categories for the United States (1990-2011) 1-14
Table 1 -5: Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent) 1-19
Table 1-6: IPCC Sector Descriptions 1-20
Table 1-7: List of Annexes 1-22
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) 2-4
Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-6
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.)... 2-8
Table 2-4: Emissions from Energy (TgCO2Eq.) 2-9
Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 2-10
Table 2-6: Emissions from Industrial Processes (TgCO2Eq.) 2-13
Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.) 2-15
Table 2-8: Emissions from Agriculture (Tg CO2 Eq.) 2-15
Table 2-9: Net CO2 Flux fromLand Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-17
Table 2-10: Emissions fromLand Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 2-17
Table 2-11: Emissions from Waste (Tg CO2 Eq.) 2-18
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq. and Percent of Total in
2011) 2-20
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (TgCO2Eq.) 2-22
viii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related Emissions
Distributed (TgCO2Eq.) and Percent of Total in 2011 2-23
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-25
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100) 2-29
Table 2-17: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) 2-30
Table 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.) 3-2
Table 3-2: CO2, CH4, andN2O Emissions fromEnergy (Gg) 3-3
Table 3-3: CO2, CH4, and N2O Emissions from Fossil Fuel Combustion (TgCO2Eq.) 3-5
Table 3-4: CO2, CH4, and N2O Emissions from Fossil Fuel Combustion (Gg) 3-5
Table 3-5: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.) 3-5
Table 3-6: Annual Change in CO2 Emissions and Total 2011 Emissions from Fossil Fuel Combustion for Selected
Fuels and Sectors (TgCO2Eq. and Percent) 3-6
Table 3-7: CO2, CH4, andN2O Emissions from Fossil Fuel Combustion by Sector (Tg CO2 Eq.) 3-10
Table 3-8: CO2, CH4, and N2O Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.) 3-11
Table 3-9: CO2 Emissions from Stationary Fossil Fuel Combustion (Tg CO2 Eq.) 3-12
Table 3-10: CH4 Emissions from Stationary Combustion (Tg CO2 Eq.) 3-13
Table 3-11: N2O Emissions from Stationary Combustion (Tg CO2 Eq.) 3-13
Table 3-12: CO2 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO2 Eq.)a 3-19
Table 3-13: CH4 Emissions fromMobile Combustion (Tg CO2 Eq.) 3-21
Table 3-14: N2O Emissions fromMobile Combustion (Tg CO2 Eq.) 3-22
Table 3-15: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu) 3-27
Table 3-16: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-related Fossil Fuel
Combustion by Fuel Type and Sector (TgCO2Eq. and Percent) 3-29
Table 3-17: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Energy-Related Stationary
Combustion, Including Biomass (TgCO2Eq. and Percent) 3-33
Table 3-18: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Mobile Sources (Tg CO2
Eq. and Percent) 3-36
Table 3-19: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.) 3-38
Table 3-20: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-39
Table 3-21: 2011 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-40
Table 3-22: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Non-Energy Uses of Fossil Fuels
(Tg CO2 Eq. and Percent) 3-41
Table 3-23: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent) 3-42
Table 3-24: CO2 and N2O Emissions from the Incineration of Waste (TgCO2Eq.) 3-44
Table 3-25: CO2 and N2O Emissions from the Incineration of Waste (Gg) 3-45
Table 3 -26: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-46
Table 3-27: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from the Incineration of Waste (Tg CO2 Eq.
and Percent) 3-47
Table 3-28: CH4 Emissions from Coal Mining (Tg CO2 Eq.) 3-48
ix
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Table 3-29: CH4 Emissions from Coal Mining (Gg) 3-48
Table 3-30: Coal Production (Thousand Metric Tons) 3-49
Table 3-31: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg CO2 Eq. and
Percent) 3-50
Table 3-32: CH4 Emissions from Abandoned Coal Mines (Tg CO2 Eq.) 3-51
Table 3-33: CH4 Emissions from Abandoned Coal Mines (Gg) 3-52
Table 3-34: Number of Gassy Abandoned Mines Present in U.S. Basins, Grouped by Class According to Post-
Abandonment State 3-53
Table 3-35: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal
Mines (Tg CO2 Eq. and Percent) 3-54
Table 3-36: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-56
Table 3-37: CH4 Emissions from Petroleum Systems (Gg) 3-56
Table 3-38: CO2 Emissions from Petroleum Systems (Tg CO2 Eq.) 3-56
Table 3-39: CO2 Emissions from Petroleum Systems (Gg) 3-56
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg CO2 Eq. and
Percent) 3-58
Table 3-41: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.) 3-60
Table 3-42: Potential Emissions from CO2 Capture and Transport (Gg) 3-60
Table 3-43: CH4 Emissions from Natural Gas Systems (TgCO2Eq.)a 3-61
Table 3-44: CH4Emissions from Natural Gas Systems (Gg)a 3-61
Table 3-45: Calculated Potential CH4 and Captured/Combusted CH4 from Natural Gas Systems (Tg CO2 Eq.)... 3-62
Table 3-46: Non-combustion CO2 Emissions from Natural Gas Systems (TgCO2Eq.) 3-62
Table 3-47: Non-combustion CO2 Emissions from Natural Gas Systems (Gg) 3-62
Table 3-48: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-energy CO2 Emissions from Natural Gas
Systems (Tg CO2 Eq. and Percent) 3-65
Table 3-49: NOX, CO, and NMVOC Emissions from Energy-Related Activities (Gg) 3-72
Table 3 -50: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.) 3-74
Table 3-51: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg) 3-74
Table 3-52: Aviation CO2 and N2O Emissions for International Transport (Tg CO2 Eq.) 3-75
Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-76
Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons) 3-76
Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.) 3-78
Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Gg) 3-79
Table 3-57: CO2 Emissions fromEthanol Consumption (Tg CO2 Eq.) 3-79
Table 3-58: CO2 Emissions fromEthanol Consumption (Gg) 3-79
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu) 3-80
Table 3-60: Ethanol Consumption by Sector (Trillion Btu) 3-80
Table 4-1: Emissions from Industrial Processes (TgCO2Eq.) 4-2
Table 4-2: Emissions from Industrial Processes (Gg) 4-3
x Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-3: CO2 Emissions from Cement Production (Tg CO2 Eq. and Gg) 4-7
Table 4-4: Clinker Production (Gg) 4-8
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Cement Production (Tg CO2 Eq. and
Percent) 4-9
Table 4-6: CO2 Emissions from Lime Production (Tg CO2 Eq. and Gg) 4-10
Table 4-7: Potential, Recovered, and Net CO2 Emissions from Lime Production (Gg) 4-10
Table 4-8: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and Dead-Burned-
Dolomite Lime Production (Gg) 4-11
Table 4-9: Adjusted Lime Production3 (Gg) 4-12
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Production (Tg CO2 Eq. and
Percent) 4-13
Table 4-11: CO2 Emissions from Other Process Uses of Carbonates (Tg CO2 Eq.) 4-14
Table 4-12: CO2 Emissions from Other Process Uses of Carbonates (Gg) 4-14
Table 4-13: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-15
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Other Process Uses of Carbonates
(Tg CO2 Eq. and Percent) 4-16
Table 4-15: CO2 Emissions from Soda Ash Production and Consumption Not Associated with Glass Manufacturing
(TgC02Eq.) 4-18
Table 4-16: CO2 Emissions from Soda Ash Production and Consumption Not Associated with Glass Manufacturing
(Gg) 4-18
Table 4-17: Soda Ash Production and Consumption Not Associated with Glass Manufacturing (Gg) 4-19
Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Soda Ash Production and
Consumption (Tg CO2 Eq. and Percent) 4-20
Table 4-19: CO2 Emissions from Glass Production (Tg CO2 Eq. and Gg) 4-21
Table 4-20: Limestone, Dolomite, and Soda Ash Consumption Used in Glass Production (Thousand Metric Tons) 4-
22
Table 4-21: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Glass Production (Tg CO2 Eq. and
Percent) 4-23
Table 4-22: CO2 Emissions from Ammonia Production (Tg CO2 Eq.) 4-24
Table 4-23: CO2 Emissions from Ammonia Production (Gg) 4-24
Table 4-24: Ammonia Production and Urea Production (Gg) 4-25
Table 4-25: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ammonia Production (Tg CO2 Eq.
and Percent) 4-26
Table 4-26: CO2 Emissions from Urea Consumption for Non-Agricultural Purposes (Tg CO2 Eq.) 4-27
Table 4-27: CO2 Emissions from Urea Consumption for Non-Agricultural Purposes (Gg) 4-27
Table 4-28: Urea Production, Urea Applied as Fertilizer, Urea Imports, and Urea Exports (Gg) 4-28
Table 4-29: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Urea Consumption for Non-
Agricultural Purposes (Tg CO2 Eq. and Percent) 4-28
Table 4-30: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg) 4-29
Table 4-31: Nitric Acid Production (Gg) 4-30
XI
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Table 4-32: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from Nitric Acid Production (Tg CO2 Eq.
and Percent) 4-31
Table 4-33: N2O Emissions from Adipic Acid Production (Tg CO2 Eq. and Gg) 4-32
Table 4-34: Adipic Acid Production (Gg) 4-33
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from Adipic Acid Production (Tg CO2
Eq. and Percent) 4-34
Table 4-36: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.) 4-35
Table 4-37: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg) 4-35
Table 4-38: Production and Consumption of Silicon Carbide (Metric Tons) 4-36
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from Silicon Carbide Production
and Consumption (Tg CO2 Eq. and Percent) 4-36
Table 4-40: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.) 4-37
Table 4-41: CO2and CH4 Emissions from Petrochemical Production (Gg) 4-37
Table 4-42: Production of Selected Petrochemicals (Thousand Metric Tons) 4-38
Table 4-43: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons) 4-39
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and CO2
Emissions from Carbon Black Production (Tg CO2 Eq. and Percent) 4-39
Table 4-45: CO2 Emissions from Titanium Dioxide (Tg CO2 Eq. and Gg) 4-41
Table 4-46: Titanium Dioxide Production (Gg) 4-42
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Titanium Dioxide Production (Tg
CO2 Eq. and Percent) 4-42
Table 4-48: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg) 4-44
Table 4-49: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications 4-45
Table 4-50: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and
Percent) 4-45
Table 4-51: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. andGg) 4-46
Table 4-52: Phosphate Rock Domestic Consumption, Exports, and Imports (Gg) 4-47
Table 4-53: Chemical Composition of Phosphate Rock (percent by weight) 4-48
Table 4-54: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Phosphoric Acid Production (Tg
CO2 Eq. and Percent) 4-49
Table 4-55: CO2 and CH4 Emissions from Metallurgical Coke Production (Tg CO2 Eq.) 4-51
Table 4-56: CO2 and CH4 Emissions from Metallurgical Coke Production (Gg) 4-51
Table 4-57: CO2 Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-52
Table 4-58: CO2 Emissions from Iron and Steel Production (Gg) 4-52
Table 4-59: CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.) 4-52
Table 4-60: CH4 Emissions from Iron and Steel Production (Gg) 4-52
Table 4-61: Material Carbon Contents for Metallurgical Coke Production 4-53
Table 4-62: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from Metallurgical
Coke Production (Thousand Metric Tons) 4-53
xii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-63: Production and Consumption Data for the Calculation of CO2 Emissions from Metallurgical Coke
Production (million ft3) 4-54
Table 4-64: CO2 Emission Factors for Sinter Production and Direct Reduced Iron Production 4-54
Table 4-65: Material Carbon Contents for Iron and Steel Production 4-54
Table 4-66: CH4 Emission Factors for Sinter and Pig Iron Production 4-55
Table 4-67: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons) 4-56
Table 4-68: Production and Consumption Data for the Calculation of CO2 Emissions from Iron and Steel
Production (million ft3 unless otherwise specified) 4-56
Table 4-69: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from Iron and Steel Production
and Metallurgical Coke Production (Tg. CO2Eq. and Percent) 4-57
Table 4-70: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.) 4-59
Table 4-71: CO2 and CH4 Emissions from Ferroalloy Production (Gg) 4-59
Table 4-72: Production of Ferroalloys (Metric Tons) 4-59
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ferroalloy Production (Tg CO2 Eq.
and Percent) 4-60
Table 4-74: CO2 Emissions from Aluminum Production (Tg CO2 Eq. and Gg) 4-61
Table 4-75: PFC Emissions from Aluminum Production (Tg CO2Eq.) 4-62
Table 4-76: PFC Emissions from Aluminum Production (Gg) 4-62
Table 4-77: Production of Primary Aluminum (Gg) 4-65
Table 4-78: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from Aluminum Production (Tg
CO2 Eq. and Percent) 4-65
Table 4-79: SF6 Emissions from Magnesium Production and Processing (Tg CO2 Eq. and Gg) 4-66
Table 4-80: SF6 Emission Factors (kg SF6 per metric ton of magnesium) 4-67
Table 4-81: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
Processing (Tg CO2 Eq. and Percent) 4-69
Table 4-82: Zinc Production (Metric Tons) 4-70
Table 4-83: CO2 Emissions fromZinc Production (Tg CO2 Eq. and Gg) 4-71
Table 4-84: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Zinc Production (Tg CO2 Eq. and
Percent) 4-73
Table 4-85: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg) 4-74
Table 4-86: Lead Production (Metric Tons) 4-74
Table 4-87: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lead Production (Tg CO2 Eq. and
Percent) 4-75
Table 4-88: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg) 4-76
Table 4-89: HCFC-22 Production (Gg) 4-77
Table 4-90: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and
Percent) 4-77
Table 4-91: Emissions of HFCs and PFCs from ODS Substitutes (TgCO2Eq.) 4-78
Table 4-92: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-78
xill
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Table 4-93: Emissions of HFCs and PFCs from ODS Substitutes (TgCO2Eq.) by Sector 4-79
Table 4-94: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg CO2
Eq. and Percent) 4-81
Table 4-95: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.) 4-83
Table 4-96: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-83
Table 4-97: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg CO2 Eq. and Percent) 4-87
Table 4-98: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Tg CO2 Eq.).. 4-
89
Table 4-99: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg) 4-89
Table 4-100: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg CO2 Eq. and percent) 4-93
Table 4-101: 2011 Potential and Actual Emissions of HFCs, PFCs, and SF6 from Selected Sources (Tg CO2 Eq.). 4-
95
Table 4-102: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-95
Table 5-1: N2O Emissions from Solvent and Other Product Use (TgCO2Eq. and Gg) 5-1
Table 5-2: N2O Production (Gg) 5-1
Table 5-3: N2O Emissions from N2O Product Usage (Tg CO2 Eq. and Gg) 5-2
Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from N2O Product Usage (Tg CO2 Eq. and
Percent) 5-4
Table 5-5: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg) 5-5
Table 6-1: Emissions from Agriculture (TgCO2Eq.) 6-2
Table 6-2: Emissions from Agriculture (Gg) 6-2
Table 6-3: CH4 Emissions from Enteric Fermentation (TgCO2Eq.) 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) 6-6
Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2Eq.) 6-9
Table 6-7: CH4 and N2O Emissions fromManure 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) 6-13
Table 6-9: Implied Emission Factors for CH4 fromManure Management (kg/head/year) 6-13
Table 6-10: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.) 6-15
Table 6-11: CH4 Emissions from Rice Cultivation (Gg) 6-16
Table 6-12: Rice Area Harvested (Hectares) 6-17
Table 6-13: Ratooned Area as Percent of Primary Growth Area 6-17
Table 6-14: Non-USDA Data Sources for Rice Harvest Information 6-17
Table 6-15: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg CO2 Eq. and
Percent) 6-19
Table 6-16: N2O Emissions from Agricultural Soils (Tg CO2 Eq.) 6-22
xiv Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 6-17: N2O Emissions from Agricultural Soils (Gg) 6-22
Table 6-18: Direct N2O Emissions from Agricultural Soils by Land Use Type and N Input Type (Tg CO2 Eq.)... 6-23
Table 6-19: Indirect N2O Emissions from all Land-Use Types (TgCO2Eq.) 6-23
Table 6-20: Quantitative Uncertainty Estimates of N2O Emissions from Agricultural Soil Management in 2011 (Tg
CO2 Eq. and Percent) 6-34
Table 6-21: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.) 6-36
Table 6-22: CH4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg) 6-37
Table 6-23: Agricultural Crop Production (Gg of Product) 6-39
Table 6-24: U.S. Average Percent Crop Area Burned by Crop (Percent) 6-39
Table 6-25: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-39
Table 6-26: Greenhouse Gas Emission Ratios and Conversion Factors 6-39
Table 6-27: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Field Burning of
Agricultural Residues (TgCO2Eq. and Percent) 6-40
Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 7-
2
Table 7-2: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg C) 7-2
Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (TgCO2Eq.) 7-2
Table 7-4: Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-3
Table 7-5: Managed and Unmanaged Land Area by Land Use Categories (thousands of hectares) 7-5
Table 7-6: Land Use and Land-Use Change forthe U.S. Managed Land Base (thousands of hectares) 7-5
Table 7-7: Net Annual Changes in C Stocks (Tg CO^yr) in Forest and Harvested Wood Pools 7-17
Table 7-8: Net Annual Changes in C Stocks (TgC/yr) in Forest and Harvested Wood Pools 7-18
Table 7-9: Forest area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools 7-18
Table 7-10: Estimates of CO2 (Tg/yr) Emissions for the Lower 48 States and Alaska3 7-21
Table 7-11: 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) 7-24
Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (TgCO2Eq.) for U.S. Forests3 7-26
Table 7-13: Estimated Non-CO2 Emissions from Forest Fires (GgGas) for U.S. Forests3 7-26
Table 7-14: Estimated Carbon Released from Forest Fires for U.S. Forests 7-27
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg CO2 Eq. and Percent) 7-27
Table 7-16: Direct N2O Fluxes from Soils in Forest Land Remaining Forest Land (TgCOiEq. andGgN2O).... 7-28
Table 7-17: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in Forest Land Remaining Forest Land
(Tg CO2 Eq. and Percent) 7-30
Table 7-18: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.) 7-32
Table 7-19: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C) 7-32
Table 7-20: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Cropland
Remaining Cropland (Tg CO2 Eq. and Percent) 7-38
Table 7-21: Emissions from Liming of Agricultural Soils (TgCO2Eq.) 7-39
xv
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Table 7-22: Emissions from Liming of Agricultural Soils (Tg C) 7-39
Table 7-23: Applied Minerals (Million Metric Tons) 7-40
Table 7-24: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of Agricultural Soils (Tg
CO2 Eq. and Percent) 7-41
Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.) 7-41
Table 7-26: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C) 7-42
Table 7-27: Applied Urea (Million Metric Tons) 7-42
Table 7-28: Quantitative Uncertainty Estimates for CO2 Emissions from Urea Fertilization (Tg CO2 Eq. and Percent)
7-43
Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.) 7-44
Table 7-30: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-44
Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Land Converted to
Cropland (Tg CO2 Eq. and Percent) 7-47
Table 7-32: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.) 7-49
Table 7-33: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-49
Table 7-34: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes Occurring Within Grassland Remaining
Grassland (Tg CO2Eq. and Percent) 7-53
Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.) 7-54
Table 7-36: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-55
Table 7-37: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring within Land Converted to
Grassland (Tg CO2 Eq. and Percent) 7-57
Table 7-38: Emissions from PeatlandsRemaining Peatlands (Tg CO2 Eq.) 7-59
Table 7-39: Emissions from Peatlands Remaining Peatlands (Gg) 7-60
Table 7-40: Peat Production of Lower 48 States (in thousands of Metric Tons) 7-61
Table 7-41: Peat Production of Alaska (in thousands of Cubic Meters) 7-61
Table 7-42: Tier-2 Quantitative Uncertainty Estimates for CO2 Emissions from Peatlands Remaining Peatlandsl-62
Table 7-43: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C) 7-63
Table 7-44: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover (Percent), and
Annual C Sequestration per Area of Tree Cover (kg C/m2-yr) for 28 U.S. Cities 7-66
Table 7-45: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees
(Tg CO2 Eq. and Percent) 7-67
Table 7-46: Direct N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg N2O) 7-68
Table 7-47: Quantitative Uncertainty Estimates of N2O Emissions from Soils in Settlements Remaining Settlements
(Tg CO2 Eq. and Percent) 7-69
Table 7-48: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.) 7-70
Table 7-49: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (TgC) 7-70
Table 7-50: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%), Initial C Content (%),
and Decay Rate (year"1) for Landfilled Yard Trimmings and Food Scraps in Landfills 7-73
Table 7-51: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-73
xvi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 7-52: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and Food Scraps in
Landfills (Tg CO2 Eq. and Percent) 7-74
Table 8-1: Emissions from Waste (Tg CO2 Eq.) 8-2
Table 8-2: Emissions from Waste (Gg) 8-2
Table 8-3: CH4 Emissions from Landfills (Tg CO2Eq.) 8-6
Table 8-4 :CH4 Emissions from Landfills (Gg) 8-6
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg CO2 Eq. and Percent)8-9
Table 8-6: Materials Discarded in the Municipal Waste Stream by Waste Type, percent (EPA 2011) 8-14
Table 8-7: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.) 8-16
Table 8-8: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg) 8-16
Table 8-9: U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg) 8-18
Table 8-10: Domestic Wastewater CH4 Emissions from Septic and Centralized Systems (2011) 8-19
Table 8-11: Industrial Wastewater CH4 Emissions by Sector (2011) 8-19
Table 8-12: U.S. Pulp and Paper, Meat, Poultry, Vegetables, Fruits and Juices, Ethanol, and Petroleum Refining
Production (Tg) 8-19
Table 8-13: Variables Used to Calculate Percent Wastewater Treated Anaerobically by Industry (%) 8-20
Table 8-14: Wastewater Flow (m3/ton) and BOD Production (g/L) for U.S. Vegetables, Fruits, and Juices Production
8-21
Table 8-15: U.S. Population (Millions), Population Served by Biological Denitrification (Millions), Fraction of
Population Served by Wastewater Treatment (%), Available Protein (kg/person-year), Protein Consumed
(kg/person-year), and Nitrogen Removed with Sludge (Gg-N/year) 8-25
Table 8-16: Fate of Sludge Removed by Domestic Wastewater Treatment 8-25
Table 8-17: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg CO2 Eq.
and Percent) 8-25
Table 8-18: CH4 and N2O Emissions from Composting (Tg CO2 Eq.) 8-29
Table 8-19: CH4 and N2O Emissions from Composting (Gg) 8-29
Table 8-20: U.S. Waste Composted (Gg) 8-29
Table 8-21 : Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg CO2 Eq. and Percent) 8-
30
Table 8-22: Emissions of NOX, CO, and NMVOC from Waste (Gg) 8-31
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.) 10-4
Table 10-2: Revisions to Annual Net CO2 Fluxes from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.) 10-6
Figure ES-1: U.S. Greenhouse Gas Emissions by Gas 4
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 5
Figure ES-3: Cumulative Change in Annual U.S. Greenhouse Gas Emissions Relative to 1990 5
Figure ES-4: 2011 Greenhouse Gas Emissions by Gas (Percentages based on Tg CO2 Eq.) 8
Figure ES-5: 2011 Sources of CO2 Emissions 9
xvil
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Figure ES-6: 2011 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 10
Figure ES-7: 2011 End-Use Sector Emissions of CO2, CH4, and N2O from Fossil Fuel Combustion 10
Figure ES-8: 2011 Sources of CH4 Emissions 13
Figure ES-9: 2011 Sources of N2O Emissions 14
Figure ES-10: 2011 Sources of HFCs, PFCs, and SF6 Emissions 15
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector 17
Figure ES-12: 2011 U.S. Energy Consumption by Energy Source 18
Figure ES-13: Emissions Allocated to Economic Sectors 21
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors 22
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 23
Figure ES-16: 2011 Key Categories 25
Figure 1-1: U.S. QA/QC Plan Summary 1-18
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas 2-1
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 2-2
Figure 2-3: Cumulative Change in Annual U.S. Greenhouse Gas Emissions Relative to 1990 2-2
Figure 2-4: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector 2-8
Figure 2-5: 2011Energy Chapter Greenhouse Gas Sources 2-9
Figure 2-6: 2011 U.S. Fossil Carbon Flows (TgCO2Eq.) 2-9
Figure 2-7: 2011 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-11
Figure 2-8: 2011 End-Use Sector Emissions from Fossil Fuel Combustion 2-11
Figure 2-9: 2011 Industrial Processes Chapter Greenhouse Gas Sources 2-13
Figure 2-10: 2011 Agriculture Chapter Greenhouse Gas Sources 2-15
Figure 2-11: 2011 Waste Chapter Greenhouse Gas Sources 2-18
Figure 2-12: Emissions Allocated to Economic Sectors 2-20
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors 2-23
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-29
Figure 3-1: 2011 Energy Chapter Greenhouse Gas Sources 3-1
Figure 3-2: 2011 U.S. Fossil CarbonFlows (Tg CO2 Eq.) 3-2
Figure 3-3: 2011 U.S. Energy Consumption by Energy Source 3-7
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu) 3-8
Figure 3-5: 2011 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-8
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2011) 3-9
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2011) 3-9
Figure 3-8: Nuclear, Hydroelectric, and Wind Power Plant Capacity Factors in the United States (1990-2011).. 3-10
Figure 3-9: Electricity Generation Retail Sales by End-Use Sector 3-14
Figure 3-10: Industrial Production Indices (Index 2007= 100) 3-16
Figure 3-11: Sales-Weighted Fuel Economy of New Passenger Cars and Light-Duty Trucks, 1990-2010 3-19
xviii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 3-12: Sales of New Passenger Cars and Light-Duty Trucks, 1990-2010 3-19
Figure 3-13: Mobile Source CH4 and N2O Emissions 3-21
Figure 3-14: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and Per Dollar GDP 3-27
Figure 4-1: 2011 Industrial Processes Chapter Greenhouse Gas Sources 4-2
Figure 6-1: 2011 Agriculture Chapter Greenhouse Gas Emission Sources 6-1
Figure 6-2: Sources and Pathways of N that Result in N2O Emissions from Agricultural Soil Management 6-21
Figure 6-3: Major Crops, Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-2011 (Tg
CO2Eq./year) 6-24
Figure 6-4: Grasslands, Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 1990-2011 (Tg CO2
Eq./year) 6-25
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions Estimated Using the
DAYCENT Model, 1990-2011 (GgN/year) 6-26
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions Estimated Using the
DAYCENT Model, 1990-2011 (GgN/year) 6-27
Figure 6-7: Comparison of Measured Emissions at Field Sites and Modeled Emissions Using the DAYCENT
Simulation Model and IPCC Tier 1 Approach 6-35
Figure 7-1. Percent of Total Land Area in the General Land-Use Categories for 2011 7-7
Figure 7-2: Forest Sector Carbon Pools and Flows 7-16
Figure 7-3: Estimates of Net Annual Changes inC Stocks for Major C Pools 7-19
Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States, 2010 7-20
Figure 7-5: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 2011,
Cropland Remaining Cropland 7-33
Figure 7-6: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 2011,
Cropland Remaining Cropland 7-34
Figure 7-7: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 2011, Land
Converted to Cropland 7-45
Figure 7-8: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 2011, Land
Converted to Cropland 7-46
Figure 7-9: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 2011,
Grassland Remaining Grassland 7-50
Figure 7-10: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 2011,
Grassland Remaining Grassland 7-51
Figure 7-11: Total Net Annual CO2 Flux for Mineral Soils under Agricultural Management within States, 2011,
Land Converted to Grassland 7-55
Figure 7-12: Total Net Annual CO2 Flux for Organic Soils under Agricultural Management within States, 2011,
Land Converted to Grassland 7-56
Figure 8-1: 2011 Waste Chapter Greenhouse Gas Sources 8-1
Figure 8-2: Management of Municipal Solid Waste in the United States, 2010 (BioCycle 2010) 8-12
Figure 8-3: MSW Management Trends from 1990 to 2010 (EPA 2011) 8-13
Figure 8-4: Percent of Recovered Degradable Materials from 1990 to 2010, percent (EPA 2011) 8-14
xix
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Baw.es
BoxES-1: Methodological Approach for Estimating and Reporting U.S. Emissions and Sinks 2
BoxES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data 23
BoxES- 3: Recalculations of Inventory Estimates 26
Box 1-1: Methodological approach for estimating and reporting U.S. emissions and sinks 1-2
Box 1-2: The IPCC Fourth Assessment Report and Global Warming Potentials 1-8
Box 1-3 :IPCC Reference Approach 1-13
Box 2-1: Methodology for Aggregating Emissions by Economic Sector 2-27
Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data 2-28
Box2-3: Sources and Effects of Sulfur Dioxide 2-31
Box 3-1: Methodological approach for estimating and reporting U.S. emissions and sinks 3-4
Box 3-2: Energy Data from the Greenhouse Gas Reporting Program 3-4
Box 3 -3: Weather and Non-Fossil Energy Effects on CCh from Fossil Fuel Combustion Trends 3-8
Box 3-4: Uses of Greenhouse Gas Reporting Program Data in Reporting Emissions from Industrial Sector Fossil
Fuel Combustion 3-25
Box 3-5: Carbon Intensity of U.S. Energy Consumption 3-26
Box 3-6: Carbon Dioxide Transport, Injection, and Geological Storage 3-59
Box 4-1: Methodological Approach for Estimating and Reporting U.S. Emissions and Sinks 4-6
Box 4-2: Potential Emission Estimates of HFCs, PFCs, and SF6 4-94
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions 6-28
Box 6-2: Comparison of Tier 2 U.S. Inventory Approach and IPCC (2006) Default Approach 6-38
Box 7-1: Methodological Approach for Estimating and Reporting U.S. Emissions and Sinks 7-3
Box 7-2: CO2 Emissions from Forest Fires 7-20
Box 7-3: Tier 3 Approach for Soil C Stocks Compared to Tier 1 or 2 Approaches 7-35
Box 8-1: Methodological Approach for Estimating and Reporting U.S. Emissions and Sinks 8-1
Box 8-2: Waste Data from the Greenhouse Gas Reporting Program 8-3
Box 8-3: Nationwide Municipal Solid Waste Data Sources 8-11
Box 8-4: Overview of the Waste Sector 8-12
Box 8-5: Description of a Modern, Managed Landfill 8-14
Box 8-6: Biogenic Wastes in Landfills 8-15
xx Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 2011. To ensure that the U.S. emissions inventory is comparable to those of other UNFCCC Parties, the
estimates presented here were calculated using methodologies consistent with those recommended in the Revised
1996 Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), the IPCC Good Practice Guidance and Uncertainty Management in National
Greenhouse Gas Inventories (IPCC 2000), and the IPCC Good Practice Guidance for Land Use, Land-Use Change,
and Forestry (IPCC 2003). Additionally, the U.S. emission inventory has continued to incorporate new
methodologies and data from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). The
use of the most recently published calculation methodologies by the IPCC, as contained in the 2006 IPCC
Guidelines, is considered to improve the rigor and accuracy of this inventory and is fully in line with the prior IPCC
guidance. The structure of this report is consistent with the UNFCCC guidelines for inventory reporting.4 For most
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 Xa) 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 < http://unfccc.int/resource/docs/2006/sbsta/eng/09.pdf>.
Executive Summary ES-1
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source categories, the IPCC methodologies were expanded, resulting in a more comprehensive and detailed estimate
of emissions.
lifByifiiiit^iiiP^^
In following the UNFCCC requirement under Article 4.1 to develop and submit national greenhouse gas emissions
inventories, the emissions and sinks presented in this report are organized by source and sink categories and
calculated using internationally-accepted methods provided by the IPCC.5 Additionally, the calculated emissions
and sinks in a given year for the United States are presented in a common manner in line with the UNFCCC
reporting guidelines for the reporting of inventories under this international agreement.6 The use of consistent
methods to calculate emissions and sinks by all nations providing their inventories to the UNFCCC ensures that
these reports are comparable. In this regard, U.S. emissions and sinks reported in this inventory report are
comparable to emissions and sinks reported by other countries. Emissions and sinks provided in this inventory do
not preclude alternative examinations, but rather this inventory report presents emissions and sinks in a common
format consistent with how countries are to report inventories under the UNFCCC. The report itself follows this
standardized format, and provides an explanation of the IPCC methods used to calculate emissions and sinks, and
the manner in which those calculations are conducted.
On October 30, 2009, the U.S. Environmental Protection Agency (EPA) published a rule for the mandatory
reporting of greenhouse gases (GHG) from large GHG emissions sources in the United States. Implementation of 40
CFR Part 98 is referred to as the Greenhouse Gas Reporting Program (GHGRP). 40 CFR part 98 applies to direct
greenhouse gas emitters, fossil fuel suppliers, industrial gas suppliers, and facilities that inject CO2 underground for
sequestration or other reasons7. Reporting is at the facility level, except for certain suppliers of fossil fuels and
industrial greenhouse gases. The GHGRP dataset and the data presented in this inventory report are complementary
and, as indicated in the respective methodological and planned improvements sections in this report's chapters, EPA
is using the data, as applicable, to improve the national estimates presented in this inventory.
Greenhouse gases trap heat and make the planet warmer. The most important greenhouse gases directly emitted by
humans include CO2, CH4, N2O, and several other fluorine-containing halogenated substances. 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 2010, concentrations of these
greenhouse gases have increased globally by 39, 158, and 18 percent, respectively (IPCC 2007 and NOAA/ESLR
2009). This annual report estimates the total national greenhouse gas emissions and removals associated with
human activities across the United States.
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
See < http://www.ipcc-nggip.iges.or.jp/public/index.html>.
6 See.
7 See and .
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
albedo).8 The IPCC developed the Global Warming Potential (GWP) concept to compare the ability of each
greenhouse gas to trap heat in the atmosphere relative to another gas.
The GWP of a greenhouse gas is defined as the ratio of the time-integrated radiative forcing from the instantaneous
release of 1 kilogram (kg) of a trace substance relative to that of 1 kg of a reference gas (IPCC 2001). Direct
radiative effects occur when the gas itself is a greenhouse gas. The reference gas used is CO2, and therefore GWP-
weighted emissions are measured in teragrams (or million metric tons) of CO2 equivalent (Tg CCh Eq.).9'10 All
gases in this Executive Summary are presented in units of Tg COa Eq.
The UNFCCC reporting guidelines for national inventories were updated in 2006,11 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 2011 are consistent with estimates developed prior to
the publication of the IPCC Third Assessment Report (TAR) (IPCC 2001) and the IPCC Fourth Assessment Report
(AR4) (IPCC 2007). 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 CCh 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
CO2
CH4*
N2O
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2Fe
C4Fio
C6Fi4
SFe
GWP
1
21
310
11,700
650
2,800
1,300
3,800
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
Source: IPCC (1996)
* The CH4 GWP includes the direct
effects and those indirect effects due
to the production of tiopospheric
ozone and stratospheric water vapor.
The indirect effect due to the
production of CO2 is not included.
8 Albedo is a measure of the Earth's reflectivity, and is defined as the fraction of the total solar radiation incident on a body that
is reflected by it.
Carbon comprises 12/44ths of carbon dioxide by weight.
10 One teragram is equal to 1012 grams or one million metric tons.
11 See .
Executive Summary ES-3
-------
Global warming potentials are not provided for CO, NOX, NMVOCs, SCh, 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).
In 2011, total U.S. greenhouse gas emissions were 6,702.3 Tg, or million metric tons, CCh Eq. Total U.S. emissions
have increased by 8.4 percent from 1990 to 2011, and emissions decreased from 2010 to 2011 by 1.6 percent (108.0
Tg CO2 Eq.). The decrease from 2010 to 2011 was due to a decrease in the carbon intensity of fuels consumed to
generate electricity due to a decrease in coal consumption, with increased natural gas consumption and a significant
increase in hydropower used. Additionally, relatively mild winter conditions, especially in the South Atlantic
Region of the United States where electricity is an important heating fuel, resulted in an overall decrease in
electricity demand in most sectors. Since 1990, U.S. emissions have increased at an average annual rate of 0.4
percent. 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 2011.
Figure ES-1: U.S. Greenhouse Gas Emissions by Gas
•MFCs, PFCs, & SF
"Hsthane
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
-6,6%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Figure ES-3: Cumulative Change in Annual U.S. Greenhouse Gas Emissions Relative to 1990
1,200 -i
1400 H
1,000 -|
900 -
i 800 ]
in 700 -I
-------
Soda Ash Production and
Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Wetlands Remaining
Wetlands
Lead Production
Petroleum Systems
Silicon Carbide Production
and Consumption
Land Use, Land-Use Change,
and Forestry (Sink)"
WoodBiomass andEthanol
Consumption11
International Bunker Fuels'
CH4
Natural Gas Systems
Enteric Fermentation
Landfills
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest
Land
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal
Mines
Petrochemical Production
Mobile Combustion
Composting
Iron & Steel & Metallurgical
Coke Production
Field Burning of Agricultural
Residues
Ferroalloy Production
Silicon Carbide Production
and Consumption
Incineration of Waste
International Bunker Fuels'
N2O
Agricultural Soil Management
Stationary Combustion
Mobile Combustion
Manure Management
Nitric Acid Production
Forest Land Remaining Forest
Land
Adipic Acid Production
Wastewater Treatment
N2O from Product Uses
Composting
2.8
1.2 .
1.4
2.2 '
1.5
0.6
1.5
1.0
0.5
0.4
0.4
(794.5)
218.6
103.5
639.9
161.2
132.7
147.8
84.1
31.5
35.2
15.9
2.5
7.1
7.5
6.0
2.3
4.6
0.3
1.0
0.2
+
+
+
0.1
344.3
227.9
12.3
44.0
14.4
18.2
2.1
15.8
3.5
4.4
0.4
3.0
1.8
1.3 /
1.4
1-9
1.0 /
1.3
1.1
0.6 /
0.3
0.2 /
(997.8)''
228.7 .
113.1 /
593.6
159.0
137.0
112.5/
56.9
47.6
29.2 /
16.5
8.0
6.8 /
6.6
5.5
3.1 /
2.4''
1.6
0.7 /'
0.2
+
+ '
+
0.1
356.1
237.5'
20.6
36.9 /
17.1 /
16.9
6.9 /
7.4/'
4.7
4.4
1.7 /'
2.9
1.9
1.9
1.6
1.5
1.0
1.2
1.0
0.6
0.3
0.2
(929.2)
238.3
115.3
618.6
168.4
141.8
111.6
57.9
52.4
29.8
16.6
14.4
6.2
6.4
5.3
3.3
2.1
1.7
0.7
0.2
+
+
+
0.1
376.1
252.3
21.2
29.0
18.0
19.7
12.1
10.7
4.8
4.4
1.8
3.0
1.8
1.8
1.6
1.5
1.2
1.2
1.0
0.5
0.3
0.2
(902.6)
251.7
114.3
618.8
163.4
141.4
113.6
67.1
51.5
30.0
16.6
8.7
7.2
6.6
5.3
2.9
1.9
1.7
0.6
0.2
+
+
+
0.1
349.7
245.4
21.1
25.5
17.8
16.9
7.4
2.6
4.9
4.4
1.9
2.6
1.6
1.8
1.5
1.0
0.9
1.0
1.1
0.5
0.3
0.1
(882.6)
245.1
106.4
603.8
150.7
140.6
113.3
70.3
50.5
30.5
16.5
5.7
7.3
6.3
5.1
2.9
1.8
1.6
0.4
0.2
+
+
+
0.1
338.7
242.8
20.7
111
17.7
14.0
5.0
2.8
5.0
4.4
1.8
2.7
1.8
2.2
1.7
1.5
1.2
1.1
1.0
0.5
0.3
0.2
(888.8)
264.5
117.0
592.7
143.6
139.3
106.8
72.4
51.8
30.8
16.4
4.7
8.6
6.3
5.0
3.1
1.8
1.5
0.5
0.2
+
+
+
0.1
343.9
244.5
22.6
20.7
17.8
16.8
4.2
4.4
5.1
4.4
1.7
2.7
1.9
1.8
1.7
1.3
1.3
1.2
0.9
0.5
0.3
0.2
(905.0)
264.5
111.3
587.2
144.7
137.4
103.0
63.2
52.0
31.5
16.2
14.2
6.6
6.3
4.8
3.1
1.7
1.5
0.6
0.2
+
+
+
0.1
356.9
247.2
22.0
18.5
18.0
15.5
11.9
10.6
5.2
4.4
1.7
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Settlements Remaining „ ;
Settlements 1.0 1.5 1.6 1.5 1.4 1.5 1.5
Incineration of Waste 0.5 - 0.4 .. 0.4 0.4 0.4 0.4 0.4
Field Burning of Agricultural
Residues 0.1 0.1 0.1 0.1 0.1 0.1 0.1
Wetlands Remaining
Wetlands + + / + + + + +
International Bunker Fuehc 0.9 1.0 1.0 1.0 0.9 1.0 1.0
HFCs 36.9 115.0 120.0 117.5 112.0 121.3 129.0
Substitution of Ozone
Depleting Substances'1 0.3 99.0 / 102.7 103.6 106.3 114.6 121.7
HCFC-22 Production 36.4 15.8 17.0 13.6 5.4 6.4 6.9
Semiconductor Manufacture 0.2 0.2 0.3 0.3 0.2 0.4 0.3
PFCs 20.6 6.2 7.7 6.6 4.4 5.9 7.0
Semiconductor Manufacture 2.2 3.2/' 3.8 3.9 2.9 4.4 4.1
Aluminum Production 18.4 3.0 3.8 2.7 1.6 1.6 2.9
SF6 32.6 15.0 12.3 11.4 9.8 10.1 9.4
Electrical Transmission and
Distribution 26.7 11.1 / 8.8 8.6 8.1 7.8 7.0
Magnesium Production and
Processing 5.4 2.9 2.6 1.9 1.1 1.3 1.4
Semiconductor Manufacture 0.5 1.0 / 0.8 0.9 0/7 1_0 0_9_
Total 6,183.3 7,195.3 7,263.2 7,048.8 6,586.6 6,810.3 6,702.3
Net Emissions (Sources and
Sinks) 5,388.7 6,197.4 6,334.0 6,146.2 5,704.0 5,921.5 5,797.3
+ Does not exceed 0.05 Tg CO2 Eq.
a Parentheses indicate negative values or sequestration. The net CCh flux total includes both emissions and
sequestration, and constitutes a net sink in the United States. Sinks are only included in net emissions total.
b Emissions from Wood Biomass and Ethanol Consumption are not included specifically in summing energy sector
totals. Net carbon fluxes from changes in biogenic carbon reservoirs are accounted for in the estimates for Land
Use, Land-Use Change, and Forestry.
0 Emissions from International Bunker Fuels are not included in totals.
d Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Figure ES-4 illustrates the relative contribution of the direct greenhouse gases to total U.S. emissions in 2011. The
primary greenhouse gas emitted by human activities in the United States was CC>2, representing approximately 83.7
percent of total greenhouse gas emissions. The largest source of €62, and of overall greenhouse gas emissions, was
fossil fuel combustion. CH4 emissions, which have decreased by 8.2 percent since 1990, resulted primarily from
natural gas systems, enteric fermentation associated with domestic livestock, and decomposition of wastes in
landfills. Agricultural soil management, mobile source fuel combustion and stationary fuel combustion were the
major sources of N2O emissions. Ozone depleting substance substitute emissions and emissions of HFC-23 during
the production of HCFC-22 were the primary contributors to aggregate HFC emissions. PFC emissions resulted
from semiconductor manufacturing and as a by-product of primary aluminum production, while electrical
transmission and distribution systems accounted for most SF6 emissions.
Executive Summary ES-7
-------
Figure ES-4: 2011 Greenhouse Gas Emissions by Gas (Percentages based on Tg COz Eq.)
HFCs, PFCs,
&SF6
2.2%
Overall, from 1990 to 2011, total emissions of CO2 increased by 504.0 Tg CO2 Eq. (9.9 percent), while total
emissions of CH4 decreased by 52.7 Tg €62Eq. (8.2 percent), and N2O increased by 12.6 Tg CO2 Eq. (3.6 percent).
During the same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 55.1 Tg CO2 Eq. (61.1
percent). From 1990 to 2011, HFCs increased by 92.0 Tg CO2 Eq. (249.3 percent), PFCs decreased by 13.6 Tg CO2
Eq. (66.1 percent), and SF6 decreased by 23.3 Tg CO2 Eq. (71.3 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 these gases 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 13.5 percent of total emissions in 2011. The following sections describe each gas's contribution to total U.S.
greenhouse gas emissions in more detail.
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 39 percent (IPCC 2007 and NOAA/ESLR 2009), principally due to the combustion of fossil fuels. Within the
United States, fossil fuel combustion accounted for 94.0 percent of CO2 emissions in 2011. Globally, approximately
31,780 Tg of CO2 were added to the atmosphere through the combustion of fossil fuels in 2010, of which the United
States accounted for about 18 percent.12 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). In addition to fossil-fuel combustion, several other sources emit significant quantities of CO2. These
sources include, but are not limited to non-energy use of fuels, iron and steel production and cement production
(Figure ES-5).
Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Statistics 2010 < http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm> EIA (2013).
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-5: 2011 Sources of COz Emissions
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Prod, & Metallurgical Coke Prod,
Natural Gas Systems
Cement Production
Lime Production
Incineration of Waste
Other Process Uses of Carbonates
Ammonia Production
Cropland Remaining Cropland
Urea Consumption for Non-Agricultural Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Wetlands Remaining Wetlands
Lead Production
Petroleum Systems
Silicon Carbide Production and Consumption
5,277
C02 as a Portion
of all Emissions
<0,5
<0.5
25 50 75 100
Tg C02 Eq.
125
150
Note: Electricity generation also includes emissions of less than 0.05 Tg CChEq. from geothermal-based generation.
As the largest source of U.S. greenhouse gas emissions, CCh from fossil fuel combustion has accounted for
approximately 78 percent of GWP-weighted emissions since 1990, and is approximately 79 percent of total GWP-
weighted emissions in 2011. Emissions of CCh from fossil fuel combustion increased at an average annual rate of
0.5 percent from 1990 to 2011. The fundamental factors influencing this trend include (1) a generally growing
domestic economy over the last 22 years, and (2) an overall growth in emissions from electricity generation and
transportation activities. Between 1990 and 2011, COa emissions from fossil fuel combustion increased from
4,748.5 Tg CO2 Eq. to 5,277.2 Tg CCh Eq.—an 11.1 percent total increase over the twenty-two-year period. From
2010 to 2011, these emissions decreased by 130.9 Tg CO2 Eq. (2.4 percent).
Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S.
emission trends. Changes in CCh 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. In the short term, the overall consumption of fossil fuels in the United States fluctuates
primarily 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. In the long 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 behavioral choices (e.g., walking, bicycling, or telecommuting to work instead of driving).
Executive Summary ES-9
-------
Figure ES-6: 2011 COz Emissions from Fossil Fuel Combustion by Sector and Fuel Type
2,500 -|
2,000 -
iff 1,500 -
ra 1,000 -
500 -
0 -
Relative Contribution
by Fuel Type
2,159
50
222
; Petroleum
I Coal
2 Natural Gas
329
1,745
773
I
1Z
E
Figure ES-7: 2011 End-Use Sector Emissions of COz, Cm, and NzO from Fossil Fuel
Combustion
2,000 -i
1,500 -
8 1,000 -
500 -
0 J
From Direct Fossil Fuel Combustion
I From Electricity Consumption
1,769
50
I
a
1,401
1,137
,2
i
The five major fuel consuming sectors contributing to CC>2 emissions from fossil fuel combustion are electricity
generation, transportation, industrial, residential, and commercial. CCh emissions are produced by the electricity
generation sector as they consume fossil fuel to provide electricity to one of the other four sectors, or "end-use"
sectors. For the discussion below, electricity generation emissions have been distributed to each end-use sector on
the basis of each sector's share of aggregate electricity consumption. This method of distributing emissions assumes
that each end-use sector consumes electricity that is generated from the national average mix of fuels according to
their carbon intensity. Emissions from electricity generation are also addressed separately after the end-use sectors
have been discussed.
Note that emissions from U.S. territories are calculated separately due to a lack of specific consumption data for the
individual end-use sectors. Figure ES-6, Figure ES-7, and Table ES-3 summarize CCh emissions from fossil fuel
combustion by end-use sector.
Table ES-3: COz Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector
(Tg or million metric tons COz Eq.)
End-Use Sector
1990
2005
2007
2008
2009
2010
2011
ES-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories3
Total
Electricity Generation
1,497.0
1,494.0
3.0
1,535.3
848.6
686.7
931.4
338.3
593.0
757.0 .
219.0
538.0
27.9
4,748.5
1,820.8
1,896.5
1,891.7
4.7
1,560.4
823.4
737.0
1,214.7
357.9
856.7
1,027.2
223.5
803.7
50.0
* 5,748.7
2,402.1
, 1,909.7
/ 1,904.7
5.1
1,559.9
844.4
715.4
1,205.2
341.6
863.5
1,047.7
218.9
828.8
45.2
/" 5,767.7
2,412.8
1,820.7
1,816.0
4.7
1,499.3
802.0
697.3
1,189.9
347.0
842.9
1,039.8
223.8
816.0
41.0
5,590.6
2,360.9
1,753.7
1,749.2
4.5
1,324.6
722.6
602.0
1,123.5
337.0
786.5
976.8
223.4
753.5
43.8
5,222.4
2,146.4
1,768.4
1,763.9
4.5
1,421.3
780.2
641.1
1,175.0
334.6
840.4
993.9
220.6
773.3
49.6
5,408.1
2,259.2
1,749.3
1,745.0
4.3
1,392.1
773.2
618.9
1,125.6
328.8
796.9
960.5
222.1
738.4
49.7
5,277.2
2,158.5
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.
a 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.
Transportation End-Use Sector. Transportation activities (excluding international bunker fuels) accounted for 33
percent of CC>2 emissions from fossil fuel combustion in 2011.13 Virtually all of the energy consumed in this end-
use sector came from petroleum products. Nearly 65 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. From 1990 to 2011, transportation
emissions rose by 17 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 34 percent from 1990 to 2011, as a result of a confluence of factors including population
growth, economic growth, urban sprawl, and low fuel prices over much of this period. It is noted that the more
recent trend for transportation has shown a general decline in emissions, due to recent slow growth in economic
activity, higher fuel prices, and an associated decrease in the demand for passenger transportation.
Industrial End-Use Sector. Industrial €62 emissions, resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed by industry, accounted for 26 percent of CCh from
fossil fuel combustion in 2011. Approximately 56 percent 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. In contrast to the other
end-use sectors, emissions from industry have steadily declined since 1990. This decline is 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.
Residential and Commercial End-Use Sectors. The residential and commercial end-use sectors accounted for 21
and 18 percent, respectively, of CC>2 emissions from fossil fuel combustion in 2011. Both sectors relied heavily on
electricity for meeting energy demands, with 71 and 77 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. Emissions from the residential and
commercial end-use sectors have increased by 21 percent and 27 percent since 1990, respectively, due to increasing
electricity consumption for lighting, heating, air conditioning, and operating appliances.
Electricity Generation. The United States relies on electricity to meet a significant portion of its energy demands.
Electricity generators consumed 36 percent of U.S. energy from fossil fuels and emitted 41 percent of the CCh from
fossil fuel combustion in 2011. The type of fuel combusted by electricity generators has a significant effect on their
If emissions from international bunker fuels are included, the transportation end-use sector accounted for 34.5 percent of U.S.
emissions from fossil fuel combustion in 2011.
Executive Summary ES-11
-------
emissions. For example, some electricity is generated with low COa emitting energy technologies, particularly non-
fossil options such as nuclear, hydroelectric, or geothermal energy. Electricity generators relied on coal for
approximately 42 percent their total energy requirements in 2011, and accounted for 95 percent of all coal consumed
for energy in the United States in 2011. Recently a decrease in the carbon intensity of fuels consumed to generate
electricity has occurred due to a decrease in coal consumption, and increased natural gas consumption and other
generation sources. Across the time series, changes in electricity demand and the carbon intensity of fuels used for
electricity generation have a significant impact on CCh emissions.
Other significant CCh trends included the following:
• CO2 emissions from non-energy use of fossil fuels have increased by 13.1 Tg CCh Eq. (11.2 percent) from
1990 through 2011. Emissions from non-energy uses of fossil fuels were 130.6 TgCChEq. in 2011, which
constituted 2.3 percent of total national COa emissions, approximately the same proportion as in 1990.
• CO2 emissions from iron and steel production and metallurgical coke production increased by 8.5 Tg CCh
Eq. (15.3 percent) from 2010 to 2011, continuing a two-year trend of increasing emissions primarily due to
increased steel production associated with improved economic conditions. Despite this, from 1990 through
2011, emissions declined by 35.6 percent (35.5 Tg CCh Eq.). This overall decline is due to the
restructuring of the industry, technological improvements, and increased scrap utilization.
• In 2011, CO2 emissions from cement production increased by 0.7 Tg CCh Eq. (2.3 percent) from 2010.
After decreasing in 1991 by 2.2 percent from 1990 levels, cement production emissions grew every year
through 2006. Since 2006, emissions have fluctuated through 2011 due to the economic recession and
associated decrease in demand for construction materials. Overall, from 1990 to 2011, emissions from
cement production have decreased by 4.9 percent, a decrease of 1.6 Tg CO2 Eq.
• Net CO2 uptake from Land Use, Land-Use Change, and Forestry increased by 110.5 Tg CO2 Eq. (13.9
percent) from 1990 through 2011. 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, and
harvested wood pools. 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 (CH4) is more than 20 times as effective as CO2 at trapping heat in the atmosphere (IPCC 1996). Over the
last two hundred and fifty years, the concentration of CH4 in the atmosphere increased by 158 percent (IPCC 2007).
Anthropogenic sources of CH4 include natural gas and petroleum systems, agricultural activities, landfills, coal
mining, wastewater treatment, stationary and mobile combustion, and certain industrial processes (see Figure ES-8).
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-8: 2011 Sources of CH4 Emissions
Natural Gas Systems
Enteric Fermentation
Landfills
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Petrochemical Production
Mobile Combustion |
Composting |
Iron and Steel Prod, & Metallurgical Coke Prod. |
Field Burning of Agricultural Residues
Ferroalloy Production
Silicon Carbide Production and Consumption
Incineration of Waste
as a Portion
of all Emissions
25 50 75 100
Tg CO, Eq.
125
150
Some significant trends in U.S. emissions of CH4 include the following:
• Natural gas systems were the largest anthropogenic source category of CH4 emissions in the United States
in 2011 with 144.7 Tg CCh Eq. of CH4 emitted into the atmosphere. Those emissions have decreased by
16.5 Tg CO2 Eq. (10.2 percent) since 1990. The decrease in CH4 emissions is due largely to a decrease in
emissions from transmission and storage due to increased voluntary reductions and a decrease in
distribution emissions due to a decrease in cast iron and unprotected steel pipelines. Emissions from field
production accounted for approximately 37 percent of CH4 emissions from natural gas systems in 2011.
CH4 emissions from field production decreased by 12 percent from 1990 through 2011; however, the trend
was not stable over the time series-emissions from this source increased by 43 percent from 1990 through
2006, and then declined by 38 percent from 2006 to 2011. Reasons for this trend include such factors as
increased voluntary reductions, as well as the effects of the recent global economic slowdown.
• Enteric fermentation is the second largest anthropogenic source of CH4 emissions in the United States. In
2011, enteric fermentation CH4 emissions were 137.4 Tg CCh Eq. (23.4 percent of total CH4 emissions),
which represents an increase of 4.6 Tg CC>2 Eq. (3.5 percent) since 1990. This increase in emissions from
1990 to 2011 in enteric generally follows the increasing trends in cattle populations. From 1990 to 1995
emissions increased and then decreased from 1996 to 2001, mainly due to fluctuations in beef cattle
populations and increased digestibility of feed for feedlot cattle. Emissions generally increased from 2002
to 2007, though with a slight decrease in 2004, as both dairy and beef populations underwent increases and
the literature for dairy cow diets indicated a trend toward a decrease in feed digestibility for those years.
Emissions decreased again from 2008 to 2011 as beef cattle populations again decreased.
• Landfills are the third largest anthropogenic source of CH4 emissions in the United States, accounting for
17.5 percent of total CH4 emissions (103.0 Tg CO2 Eq.) in 2011. From 1990 to 2011, CH4 emissions from
landfills decreased by 44.7 Tg CCh Eq. (30.3 percent), with small increases occurring in some interim
years. This downward trend in overall emissions can be attributed to a 21 percent reduction in the amount
of decomposable materials (i.e., paper and paperboard, food scraps, and yard trimmings) discarded in MSW
landfills over the time series (EPA 2010) and an increase in the amount of landfill gas collected and
Executive Summary ES-13
-------
combusted,14 which has more than offset the additional CH4 emissions resulting from an increase in the
amount of municipal solid waste landfilled.
In 2011, CH4 emissions from coal mining were 63.2 Tg CO2 Eq., a 9.2 Tg CO2 Eq. (12.6 percent) decrease
under 2010 emission levels. The overall decline of 20.8 Tg CO2 Eq. (24.8 percent) from 1990 results from
the mining of less gassy coal from underground mines and the increased use of CH4 collected from
degasification systems.
Methane emissions from manure management increased by 65.3 percent since 1990, from 31.5 Tg CO2 Eq.
in 1990 to 52.0 Tg CO2 Eq. in 2011. 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.
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 (IPCC 1996). Since 1750, the global atmospheric concentration of N2O has risen by approximately 19
percent (IPCC 2007). The main anthropogenic activities producing N2O in the United States are agricultural soil
management, stationary fuel combustion, fuel combustion in motor vehicles, manure management and nitric acid
production (see Figure ES-9).
Figure ES-9: 2011 Sources of NzO Emissions
Agricultural Soil Management |||||||||||||||||||||( 9jj| 247
Stationary Combustion
Mobile Combustion
Manure Management
Nitric Acid Production
Forest Land Remaining Forest Land
Wastewater Treatment ••••• of all Emissions
5.3%
NZO from Product Uses
Composting |^|
Settlements Remaining Settlements |H
Incineration of Waste | < Q.5
Field Burning of Agricultural Residues | < 0,5
Wetlands Remaining Wetlands < 0.5
10 15 20 25
TgC02Eq,
Some significant trends in U.S. emissions of N2O include the following:
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-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Agricultural soils accounted for approximately 69.3 percent of N2O emissions and 3.7 percent of total
emissions in the United States in 2011. Estimated emissions from this source in 2011 were 247.2 Tg CO2
Eq. Annual N2O emissions from agricultural soils fluctuated between 1990 and 2011, although overall
emissions were 8.5 percent higher in 2011 than in 1990. Annual N2O emissions from agricultural soils
fluctuated between 1990 and 2011, largely as a reflection of annual variation in weather patterns, synthetic
fertilizer use, and crop production.
N2O emissions from stationary combustion increased 9.7 Tg CO2 Eq. (79.3 percent) from 1990 through
2011. N2O emissions from this source increased primarily as a result of an increase in the number of coal
fluidized bed boilers in the electric power sector.
In 2011, N2O emissions from mobile combustion were 18.5 Tg CO2 Eq. (5.2 percent of U.S. N2O
emissions). From 1990 to 2011, N2O emissions from mobile combustion decreased by 58.0 percent.
However, from 1990 to 1998 emissions increased by 25.6 percent, due to control technologies that reduced
NOX emissions while increasing N2O emissions. Since 1998, newer control technologies have led to an
overall decline of 36.8 Tg CO2 Eq. (66.6 percent) in N2O from this source.
N2O emissions from adipic acid production were 10.6 Tg CO2 Eq. in 2011, and have decreased
significantly in recent years due to the widespread installation of pollution control measures. Emissions
from adipic acid production have decreased by 32.9 percent since 1990 and by 39.6 percent since a peak in
1995.
and §F6
HFCs and PFCs are families of synthetic chemicals that are used as alternatives to Ozone Depleting Substances,
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 (IPCC 1996).
Other emissive sources of these gases include electrical transmission and distribution systems, HCFC-22 production,
semiconductor manufacturing, aluminum production, and magnesium production and processing (see Figure ES-10).
Figure ES-10: 2011 Sources of HFCs, PFCs, and SFe Emissions
Substitution of Ozone Depleting Substances ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^f ^^^1 122
Electrical Transmission and Distribution
Hcrc-22 Production ^^^^^^^^ HFCs, PFCs, and SF6 as a Portion
of all Emissions
Semiconductor Manufacture ^^^^^^^^^H 2.2%
Aluminum Production
Magnesium Production and Processing
10 20
Tg C02 Eq,
Some significant trends in U.S. HFC, PFC, and SF6 emissions include the following:
Executive Summary ES-15
-------
• Emissions resulting from the substitution of ozone depleting substances (ODS) (e.g., CFCs) have been
consistently increasing, from small amounts in 1990 to 121.7 Tg CCh Eq. in 2011. Emissions from ODS
substitutes are both the largest and the fastest growing source of HFC, PFC, and SF6 emissions. These
emissions have been increasing as phase-out of ODS required under the Montreal Protocol came 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 81.0 percent (29.5 Tg CO2 Eq.) from 1990
through 2011, due to a steady decline in the emission rate of HFC-23 (i.e., the amount of HFC-23 emitted
per kilogram of HCFC-22 manufactured) and the use of thermal oxidation at some plants to reduce HFC-23
emissions.
• SF6 emissions from electric power transmission and distribution systems decreased by 73.6 percent (19.6
Tg COa Eq.) from 1990 to 2011, primarily because of higher purchase prices for SF6 and efforts by industry
to reduce emissions.
• PFC emissions from aluminum production decreased by 84.0 percent (15.5 Tg CO2 Eq.) from 1990 to
2011, due to both industry emission reduction efforts and declines in domestic aluminum production.
In accordance with the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), and the 2003 UNFCCC Guidelines on Reporting and Review (UNFCCC 2003),
Figure ES-11 and Table ES-4 aggregate emissions and sinks by these chapters. Emissions of all gases can be
summed from each source category from IPCC guidance. Over the twenty-two-year period of 1990 to 2011, total
emissions in the Energy, Industrial Processes, and Agriculture sectors grew by 478.4 Tg CO2 Eq. (9.1 percent), 10.3
Tg COa Eq. (3.3 percent), and 47.6 Tg CO2 Eq. (11.5 percent), respectively. Emissions from the Waste and Solvent
and Other Product Use sectors decreased by 40.2 TgCO2Eq. (23.9 percent) and less than 0.1 TgCO2Eq. (0.4
percent), respectively. Over the same period, estimates of net C sequestration in the Land Use, Land-Use Change,
and Forestry (LULUCF) sector (magnitude of emissions plus CO2 flux from all LULUCF source categories)
increased by 87.6 Tg CO2 Eq. (11.2 percent).
ES-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
o
u
7,500 -i
7,000 -
6,SOO -
6,000 -
5,500
5,000 -
4,500 -
4,000 -
3,500 -
3,000 -
2,500 -
2,000 -
1,500 -
1,000 -
500 -
0 -
(500) -
(1,000) -
(1,500) J
Industrial Processes
Agriculture
Waste
LULUCF (sources)
Energy
CPC^
2 emissions for the period of 1990 through 2011. In 2011,
approximately 87 percent of the energy consumed in the United States (on a Btu basis) was produced through the
combustion of fossil fuels. The remaining 13 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 and N2O
emissions (43 percent and 11 percent of total U.S. emissions of each gas, respectively). Overall, emission sources in
the Energy chapter account for a combined 85.7 percent of total U.S. greenhouse gas emissions in 2011.
Executive Summary ES-17
-------
Figure ES-12: 2011 U.S. Energy Consumption by Energy Source
Renewable
Nuclear Electric Ener§Y
Power 5'6%
7,3%
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 and metallurgical coke production, cement production, ammonia
production and urea consumption, lime production, other process uses of carbonates (e.g., flux stone, flue gas
desulfurization, and glass manufacturing), soda ash production and consumption, titanium dioxide production,
phosphoric acid production, ferroalloy production, glass 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 4.9 percent of U.S. greenhouse gas
emissions in 2011.
and 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 about 0.1 percent of total U.S. anthropogenic
greenhouse gas emissions on a carbon equivalent basis in 2011.
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 23.4 percent and 8.9 percent of total CH4 emissions from
anthropogenic activities, respectively, in 2011. Agricultural soil management activities such as fertilizer application
and other cropping practices were the largest source of U.S. N2O emissions in 2011, accounting for 69.3 percent. In
2011, emission sources accounted for in the Agricultural chapters were responsible for 6.9 percent of total U.S.
greenhouse gas emissions.
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
and
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 resulted in a net uptake (sequestration) of C in the United States. Forests (including vegetation,
soils, and harvested wood) accounted for 92 percent of total 2011 net CO2 flux, urban trees accounted for 8 percent,
mineral and organic soil carbon stock changes accounted for 1 percent, and landfilled yard trimmings and food
scraps accounted for 1 percent of the total net flux in 2011. 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 5 times as much C as is emitted from these soils through liming and urea fertilization.
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 2011 resulted in a net C sequestration of 905.0 Tg CO2 Eq.
(Table ES-5). This represents an offset of 16.1 percent of total U.S. CO2 emissions, or 13.5 percent of total
greenhouse gas emissions in 2011. Between 1990 and 2011, total land use, land-use change, and forestry net C flux
resulted in a 13.9 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, and harvested wood
pools. 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 COz Flux from Land Use, Land-Use Change, and Forestry (Tg or million metric
tons COz 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 Lrimmings
and Food Scraps)
1990
(696.8)
(34.1)
21.0
(5.3)
(7.7)
(47.5)
(24.2)
2005
•i (905.0)
(20.3)
13.5
(LO)
(10.2)
(63.2)
• (11.6)
2007
! (859.3)
(6.6)
14.5
7.1
(9.0)
(65.0)
(10.9)
2008
(833.3)
(5.2)
14.5
7.2
(9.0)
(66.0)
(10.9)
2009
(811.3)
(4.6)
14.5
7.3
(8.9)
(66.9)
(12.7)
2010
(817.6)
(3.0)
14.5
7.3
(8.8)
(67.9)
(13.3)
2011
(833.5)
(2.9)
14.5
7.4
(8.8)
(68.8)
(13.0)
Total (794.5) ; (997.8) ; (929.2) (902.6) (882.6) (888.8) (905.0)
Note: Lotals 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. Liming of agricultural soils
and urea fertilization in 2011 resulted in CO2 emissions of 8.1 Tg CO2 Eq. (8,117 Gg). Lands undergoing peat
extraction (i.e., Peatlands Remaining Peatlands) resulted in CO2 emissions of 0.9 TgCO2Eq. (918 Gg), andN2O
emissions of less than 0.05 Tg CO2 Eq. The application of synthetic fertilizers to forest soils in 2011 resulted in
direct N2O emissions of 0.4 Tg CO2 Eq. (1 Gg). Direct N2O emissions from fertilizer application to forest soils have
increased by 455 percent since 1990, but still account for a relatively small portion of overall emissions.
Additionally, direct N2O emissions from fertilizer application to settlement soils in 2011 accounted for 1.5 Tg CO2
Eq. (5 Gg). This represents an increase of 51 percent since 1990. Forest fires in 2011 resulted in CH4 emissions of
14.2 Tg CO2 Eq. (675 Gg), and in N2O emissions of 11.6 Tg CO2 Eq. (37 Gg).
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg or million metric
tons COz Eq.)
Source Category 1990 2005 2007 2008 2009 2010 2011
C02 8.1 8.9 9.2 9.6 8.3 9.4 9.0
Executive Summary ES-19
-------
Cropland Remaining Cropland: Liming of Agricultural
Soils 4.7 4.3 4.5 5.0 3.7 4.7 4.5
Cropland Remaining Cropland: Urea Fertilization 2.4 3.5 3.8 3.6 3.6 3.7 5.3
Wetlands Remaining Wetlands: Peatlands Remaining
Peatlands 1.0 1.1 1.0 1.0 1.1 1.0 0.9
CH4 2.5 8.0 14.4 8.7 5.7 4.7 14.2
Forest Land Remaining Forest Land: Forest Fires 2.5 8.0 14.4 8.7 5.7 4.7 14.2
N2O 3.1 8.4 13.7 8.9 6.4 5.6 13.4
Forest Land Remaining Forest Land: Forest Fires 2.0 6.6 11.7 7.1 4.7 3.8 11.6
Forest Land Remaining Forest Land: Forest Soils 0.1 0.4 0.4 0.4 0.4 0.4 0.4
Settlements Remaining Settlements: Settlement Soils 1.0 1.5 1.6 1.5 1.4 1.5 1.5
Wetlands Remaining Wetlands: Peatlands Remaining
Peatlands + + + + + + +
Total 13.7 25.4 ! 37.3 27.2 20.4 19.7 36.6
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
The Waste chapter contains emissions from waste management activities (except incineration of waste, which is
addressed in the Energy chapter). Landfills were the largest source of anthropogenic greenhouse gas emissions in
the Waste chapter, accounting for 80.7 percent of this chapter's emissions, and 17.5 percent of total U.S. CH4
emissions.15 Additionally, wastewater treatment accounts for 16.7 percent of Waste emissions, 2.8 percent of U.S.
CH4 emissions, and 1.5 percent of U.S. N2O emissions. Emissions of CH4 and N2O from composting are also
accounted for in this chapter, generating emissions of 1.5 Tg CCh Eq. and 1.7 Tg CCh Eq., respectively. Overall,
emission sources accounted for in the Waste chapter generated 1.9 percent of total U.S. greenhouse gas emissions in
2011.
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 2011.
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.
ES-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-13: Emissions Allocated to Economic Sectors
2,500 -,
2,000 -
ff 1,500 -
8
P1 1,000 -
500 -
Electric
Power Industry
Agriculture
* Commercial (Black)
Residential (Grey)
ch0>mc^aichcnc^m0^OQQQ
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg or million
metric tons COz Eq.)
Implied Sectors
Electric Power Industry
Transportation
Industry
Agriculture
Commercial
Residential
U.S. Territories
Total Emissions
1990
1,866.1
1,553.2
1,538.8
458.0
388.1
345.4
33.7
6,183.3
2005
2,445.7
2,012.3 4
1,416.2
517.4
374.1 "
371.3 «
58.2 „
7,195.3
2007
2,455.6
1 2,013.1
1,456.1
555.6
, 372.0
358.2
52.6
7,263.2
2008
2,402.0
1,916.0
1,398.8
535.3
380.9
366.0
49.8
7,048.8
2009
2,187.6
1,840.6
1,244.2
525.4
382.9
358.1
47.9
6,586.6
2010
2,303.0
1,852.2
1,331.8
528.7
376.9
359.6
58.0
6,810.3
2011
2,200.9
1,829.4
1,332.0
546.6
378.0
357.3
58.0
6,702.3
Land Use, Land-Use Change, and Forestry
(Sinks) (794.5) (997.8)
(929.2) (902.6) (882.6) (888.8) (905.0)
Net Emissions (Sources and Sinks) 5,388.7 6,197.4 6,334.0 6,146.2 5,704.0 5,921.5 5,797.3
Note: Totals may not sum due to independent rounding. Emissions include CCh, CFLi, N2O, HFCs, PFCs, and SF
-------
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.16 These source categories include CCh from
fossil fuel combustion and the use of limestone and dolomite for flue gas desulfurization, €62 and N2O from
incineration of waste, CH4 and N2O from stationary sources, and SF6 from electrical transmission and distribution
systems.
When emissions from electricity are distributed among these sectors, industrial activities account for the largest
share of U.S. greenhouse gas emissions (28 percent) in 2011. Transportation is the second largest contributor to
total U.S. emissions (27 percent). The residential and commercial sectors contributed the next largest shares of total
U.S. greenhouse gas emissions in 2011. Emissions from these sectors increase substantially when emissions from
electricity are included, due to their relatively large share of electricity consumption (e.g., lighting, appliances, etc.).
In all sectors except agriculture, CC>2 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 2011.
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related
Emissions Distributed (Tg or million metric tons COz Eq.)
Implied Sectors
Industry
Transportation
Residential
Commercial
Agriculture
U.S. Territories
Total Emissions
Land Use, Land-Use Change,
and Forestry (Sinks)
Net Emissions (Sources and
1990
2,181.3
1,556.3
939.5 ,
953.1
519.3'. /'•
33.7,"''
6,183.3
(794.5)'
5,388.7
2005
2,102.4
2,017.2 *
1,192.4 ;
1,243.6 ,,
581.5
58.2 \
7,195.3
(997.8) ,/"
6,197.4 :
2007
2,113.6
2,018.2
1,215.6
1,237.1
626.2
52.6
7,263.2
(929.2)
6,334.0
2008
2,036.3
1,920.8
1,211.1
1,223.6
607.1
49.8
7,048.8
(902.6)
6,146.2
2009
1,789.8
1,845.2
1,150.8
1,159.6
593.3
47.9
6,586.6
(882.6)
5,704.0
2010
1,916.9
1,856.9
1,165.2
1,216.3
597.1
58.0
6,810.3
(888.8)
5,921.5
2011
1,897.2
1,833.7
1,131.0
1,169.8
612.6
58.0
6,702.3
(905.0)
5,797.3
See Table 2-14 for more detailed data.
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors
2,500 -I
2,000 -
o- 1,500 -
O
u
1,000
500
Industry
Transportation
, Residential (Black)
Commercial (Gray)
Agriculture
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-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 2011; (4) emissions per unit of total gross domestic product as a measure of national economic activity;
and (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 0.4 percent
since 1990. This rate is slightly faster than that for total energy and for fossil fuel consumption, and much slower
than that for electricity consumption, overall gross domestic product and national population (see Figure ES-15).
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100)
Variable
GDPb
Electricity Consumption0
Fossil Fuel Consumption0
Energy Consumption0
Population"1
Greenhouse Gas Emissions6
1990
100
100
100 ,
100
100'.
100 ,
2005
157 ,
134 *
119 ,
119 «
118 /
116 / t
2007
. 165
! 137
, 119
; 120
121
, 117
2008
164
136
116
117
122
114
2009
159
131
109
111
123
107
2010
163
137
112
115
124
110
2011 Growth Rate3
166
136
101
102
125
108
2.5%
1.5%
0.1%
0.1%
1.1%
0.4%
a Average annual growth rate
b Gross Domestic Product in chained 2005 dollars (BEA 2012)
0 Energy content-weighted values (EIA 2013)
d U.S. Census Bureau (2012)
e GWP-weighted values
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic
Product
Source: BEA (2012), U.S. Census Bureau (2012), and emission estimates in this report.
170 -
160 -
150 -
140 -
130 -
120 -
110 -
100 -
90 -
80 -
70 -
60 -
, - Real GDP
Population
Emissions
per capita
Emissions
per$GDP
S
§ S
Executive Summary ES-23
-------
%^ti fe%sjS|iMi'i 11s3
The IPCC 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 2011 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.
See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
ES-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure ES-16: 2011 Key Categories
CO2 Etntesions from Stationary Combustion - Coal - Elec. Gen.
C02 Emissions from Mobile Combustion: Road
CO2 Emissions from Stationary Combustion - Gas - Industrie
CO2 Emissions from Stationary Combustion - Gas - Elec. Gen,
CO2 Emissions from Stationary Combustion - Oil ~ Industrial
CO2 Emissions from Stationary Combustion • Gas - Residential
Direct N20 Emissions from Agricultural Soil Managemait
CO2 Emissions from Stationary Combustion - Gas - Commercial
CO2 Emissions from Nobile Combustion: Aviation
Fugitive Emissions from Natural Gas Systems
CH4 Emissions from Enteric Fermentation
CO2 Emissions from Non-Energy Use of Fuels
Emissions from Substitutes for Ozone Depletiig Substances
CH4 Emissions from Landfills
CO2 Emissions from Stationary Combustion ~ Coal - Industrial
CO2 Emissions from Mobile Combustion: Other
CO2 Emissions from Stationary Combustion - Oil - Residential
D2 Emissions from troll and Steel Prod, & Metallurgical Coke Prod.
Fugitive Emissions from Coal Mtiing
CH4 Emissions from Manure Management
Indirect N2O Emissions from Applied Nitrogen
C02 Emissions from Mobile Combustion: Marine
CO2 Emissions from Stationary Combustion - Oil - Commercial
CO2 Emissions from Stationary Combustion - Oil - U.S. Territories
C02 Emissions from Natural Gas Systems
Fugitive Emissions from Petroleum Systems
Non-CO2 Emissions from Stationary Combustion - Elec. Gen.
Key Categories as a Portion of All
Emissions
200 400 600 800 1,000 1,200 1,400 1,600 1,800
TgCO,Eq.
Note: For a complete discussion of the key category analysis, see Annex 1 . Black bars indicate a Tier 1 level assessment key
category. Gray bars indicate a Tier 1 level assessment key category.
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.
of
While the current U.S. emissions inventory provides a solid foundation for the development of a more detailed and
comprehensive national inventory, there are uncertainties associated with the emission estimates. Some of the
current estimates, such as those for COa 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
Executive Summary ES-25
-------
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.
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 2006 IPCC
Guidelines (IPCC 2006), which states, "Both methodological changes and refinements over time are an essential
part of improving inventory quality. It is good practice to change or refine methods" when: available data have
changed; the previously used method is not consistent with the IPCC guidelines for that category; a category has
become key; the previously used method is insufficient to reflect mitigation activities in a transparent manner; the
capacity for inventory preparation has increased; new inventory methods become available; and for correction of
errors." 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 2011) has been
recalculated to reflect the change, per the 2006 IPCC Guidelines (IPCC 2006). Changes in historical data are
generally the result of changes in statistical data supplied by other agencies. References for the data are provided for
additional information.
ES-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
This report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions and
sinks for the years 1990 through 2011. 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. 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."18'19
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.. ."20 The United States views this report as an opportunity
to fulfill these commitments under the UNFCCC.
In 1988, preceding the creation of the UNFCCC, the World Meteorological Organization (WMO) and the United
Nations Environment Programme (UNEP) jointly established the Intergovernmental Panel on Climate Change
(IPCC). The role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the scientific,
technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced
climate change, its potential impacts and options for adaptation and mitigation (IPCC 2003). Under Working Group
1 of the IPCC, nearly 140 scientists and national experts from more than thirty countries collaborated in the creation
of the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) to
ensure that the emission inventories submitted to the UNFCCC are consistent and comparable between nations. The
IPCC accepted the Revised 1996 IPCC Guidelines at its Twelfth Session (Mexico City, September 11-13, 1996).
This report presents information in accordance with these guidelines. 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
18 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).
19 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate
Change. See . (UNEP/WMO 2000)
20 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
-------
Guidelines build on the previous bodies of work and includes new sources and gases "... as well as updates to the
previously published methods whenever scientific and technical knowledge have improved since the previous
guidelines were issued." Many of the methodological improvements presented in the 2006 Guidelines have been
adopted in this Inventory.
Overall, this inventory of anthropogenic greenhouse gas emissions provides a common and consistent mechanism
through which Parties to the UNFCCC can estimate emissions and compare the relative contribution of individual
sources, gases, and nations to climate change. The inventory provides a national estimate of sources and sinks for
the United States, including all states and U.S. territories.21 The structure of this report is consistent with the current
UNFCCC Guidelines on Annual Inventories (UNFCCC 2006).
In following the UNFCCC requirement under Article 4.1 to develop and submit national greenhouse gas emissions
inventories, the emissions and sinks presented in this report are organized by source and sink categories and
calculated using internationally-accepted methods provided by the IPCC.22 Additionally, the calculated emissions
and sinks in a given year for the U.S. are presented in a common manner in line with the UNFCCC reporting
guidelines for the reporting of inventories under this international agreement.23 The use of consistent methods to
calculate emissions and sinks by all nations providing their inventories to the UNFCCC ensures that these reports
are comparable. In this regard, U.S. emissions and sinks reported in this inventory report are comparable to
emissions and sinks reported by other countries. Emissions and sinks provided in this inventory do not preclude
alternative examinations, but rather this inventory report presents emissions and sinks in a common format
consistent with how countries are to report inventories under the UNFCCC. The report itself follows this
standardized format, and provides an explanation of the IPCC methods used to calculate emissions and sinks, and
the manner in which those calculations are conducted.
On October 30, 2009, the U.S. Environmental Protection Agency (EPA) published a rule for the mandatory
reporting of greenhouse gases (GHG) from large GHG emissions sources in the United States. Implementation of 40
CFR Part 98 is referred to as the Greenhouse Gas Reporting Program (GHGRP). 40 CFR Part 98 applies to direct
greenhouse gas emitters, fossil fuel suppliers, industrial gas suppliers, and facilities that inject CO2 underground for
sequestration or other reasons24. Reporting is at the facility level, except for certain suppliers of fossil fuels and
industrial greenhouse gases. The GHGRP dataset and the data presented in this inventory report are complementary
and, as indicated in the respective planned improvements sections in this report's chapters, EPA is analyzing the
data for use, as applicable, to improve the national estimates presented in this inventory.
l.i
For over the past 200 years, the burning of fossil fuels such as coal and oil, deforestation, and other sources have
caused the concentrations of heat-trapping "greenhouse gases" to increase significantly in our atmosphere. These
21 U.S. Territories include American Samoa, Guam, Puerto Rico, U.S. Virgin Islands, Wake Island, and other U.S. Pacific
Islands.
See .
23 See
24 See and .
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
gases absorb some of the energy being radiated from the surface of the earth and trap it in the atmosphere,
essentially acting like a blanket that makes the earth's surface warmer than it would be otherwise.
Greenhouse gases are necessary to life as we know it, because without them the planet's surface would be about 60
°F cooler than present. But, as the concentrations of these gases continue to increase in the atmosphere, the Earth's
temperature is climbing above past levels. According to NOAA and NASA data, the Earth's average surface
temperature has increased by about 1.2 to 1.4 °F since 1900. The ten warmest years on record (since 1850) have all
occurred in the past 13 years (EPA 2009). Most of the warming in recent decades is very likely the result of human
activities. Other aspects of the climate are also changing such as rainfall patterns, snow and ice cover, and sea level.
If greenhouse gases continue to increase, climate models predict that the average temperature at the Earth's surface
could increase from 2.0 to 11.5 °F above 1990 levels by the end of this century (IPCC 2007). Scientists are certain
that human activities are changing the composition of the atmosphere, and that increasing the concentration of
greenhouse gases will change the planet's climate. But they are not sure by how much it will change, at what rate it
will change, or what the exact effects will be.25
<*dSOJ
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 (CCh), 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.26 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, CC>2, methane (CH4), nitrous oxide (N2O), and ozone
(Os). 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.27 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) ozone (Os). 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
2^ For more information see
26 For more on the science of climate change, see NRC (2001).
Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in this document for
informational purposes.
Introduction 1-3
-------
affect the absorptive characteristics of the atmosphere. Comparatively, however, the level of scientific
understanding of aerosols is still very low (IPCC 2001).
CO2, CH4, and N2O are continuously emitted to and removed from the atmosphere by natural processes on Earth.
Anthropogenic activities, however, can cause additional quantities of these and other greenhouse gases to be emitted
or sequestered, thereby changing their global average atmospheric concentrations. Natural activities such as
respiration by plants or animals and seasonal cycles of plant growth and decay are examples of processes that only
cycle carbon or nitrogen between the atmosphere and organic biomass. Such processes, except when directly or
indirectly perturbed out of equilibrium by anthropogenic activities, generally do not alter average atmospheric
greenhouse gas concentrations over decadal timeframes. Climatic changes resulting from anthropogenic activities,
however, could have positive or negative feedback effects on these natural systems. Atmospheric concentrations of
these gases, along with their rates of growth and atmospheric lifetimes, are presented in Table 1 -1.
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and
Atmospheric Lifetime (Years) of Selected Greenhouse Gases
Atmospheric Variable CCh CH4 NzO SFeCF4
Pre-industrial atmospheric
concentration
Atmospheric concentration
Rate of concentration change
Atmospheric lifetime (years)
280 ppm
390 ppm
1 .4 ppm/yr
50-200d
0.700 ppm
1.750-1. 871 ppnf
0.005 ppm/yrb
12e
0.270 ppm
0.322-0.323 ppma
0.26%/yr
114e
Oppt
6.8-7.4ppt
Linear0
3,200
40ppt
74ppt
Linear0
>50,000
Source: Pre-industrial atmospheric concentrations and rate of concentration changes for all gases are from IPCC (2007). The
current atmospheric concentration for CCh is from NOAA/ESRL (2009).
a The range is the annual arithmetic averages from a mid-latitude Northern-Hemisphere site and a mid-latitude Southern-
Hemisphere site for October 2006 through September 2007 (CDIAC 2009).
b 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.
0 IPCC (2007) identifies the rate of concentration change for SFe and CF4 as linear.
d No single lifetime can be defined for CCh 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 (CO2). 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 CCh is part of this global carbon cycle, and therefore its fate is a complex function of
geochemical and biological processes. COa concentrations in the atmosphere increased from approximately 280
parts per million by volume (ppmv) in pre-industrial times to 389ppmvin2011, a 38.9 percent increase (IPCC 2007
and NOAA/ESRL 2012).28-29 The IPCC definitively states that "the present atmospheric CO2 increase is caused by
28 The pre-industrial period is considered as the time preceding the year 1750 (IPCC 2001).
29 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).
1-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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. In its Fourth Assessment Report, the IPCC stated "most of
the observed increase in global average temperatures since the mid-20th century is very likely due to the observed
increased in anthropogenic greenhouse gas concentrations," of which CO2is the most important (IPCC 2007).
Methane (CH4). 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 158
percent since 1750, from a pre-industrial value of about 700 ppb to 1,750-1,871 ppb in2010,30 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 (N2O). Anthropogenic sources of N2O emissions include agricultural soils, especially production of
nitrogen-fixing crops and forages, the use of synthetic and manure fertilizers, and manure deposition by livestock;
fossil fuel combustion, especially from mobile combustion; adipic (nylon) and nitric acid production; wastewater
treatment and waste incineration; and biomass burning. The atmospheric concentration of N2O has increased by 19
percent since 1750, from a pre-industrial value of about 270 ppb to 322-323 ppb in 2010,31 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 (Oi). Ozone is present in both the upper stratosphere,32 where it shields the Earth from harmful levels of
ultraviolet radiation, and at lower concentrations in the troposphere,33 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. As of IPCC's fourth assessment,
"whether or not recently observed changes in ozone trends are already indicative of recovery of the global ozone
layer is not yet clear" (IPCC 2007).
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).
3" The range is the annual arithmetic averages from a mid-latitude Northern-Hemisphere site and a mid-latitude Southern-
Hemisphere site for October 2006 through September 2007 (CDIAC 2010).
3! The range is the annual arithmetic averages from a mid-latitude Northern-Hemisphere site and a mid-latitude Southern-
Hemisphere site for October 2006 through September 2007 (CDIAC 2010).
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.
33 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.
Introduction 1-5
-------
Halocarbons, Perfluorocarbons, and Sulfur Hexafluoride. Halocarbons are, for the most part, man-made chemicals
that have both direct and indirect radiative forcing effects. Halocarbons that contain chlorine (CFCs, HCFCs,
methyl chloroform, and carbon tetrachloride) and bromine (halons, methyl bromide, and hydrobromofluorocarbons
HFCs) result in stratospheric ozone depletion and are therefore controlled under the Montreal Protocol on
Substances that Deplete the Ozone Layer. Although CFCs and HCFCs include potent global warming gases, their
net radiative forcing effect on the atmosphere is reduced because they cause stratospheric ozone depletion, which
itself is an important greenhouse gas in addition to shielding the Earth from 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 534 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 (NOX). 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 they have positive radiative forcing effects.35 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
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
34 Article 5 of the Montreal Protocol covers several groups of countries, especially developing countries, with low consumption
rates of ozone depleting substances. Developing countries with per capita consumption of less than 0.3 kg of certain ozone
depleting substances (weighted by their ozone depleting potential) receive financial assistance and a grace period often
additional years in the phase-out of ozone depleting substances.
NOX emissions injected higher in the stratosphere, primarily from fuel combustion emissions from high altitude supersonic
aircraft, can lead to stratospheric ozone depletion.
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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
carbonaceous36 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.37 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, has a positive radiative forcing, and that its presence "in the atmosphere above highly
reflective surfaces such as snow and ice, or clouds, may cause a significant positive radiative forcing" (IPCC 2007).
The primary anthropogenic emission sources of black carbon include diesel exhaust and open biomass burning.
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 CC>2 equivalent (Tg COa Eq.).38
The relationship between gigagrams (Gg) of a gas and Tg CCh Eq. can be expressed as follows:
TgC02Eq = (Ggofggs)x(GWP)
'Gg,
where,
Tg CO2 Eq. = Teragrams of CO2 Equivalent
Gg = Gigagrams (equivalent to a thousand metric tons)
GWP = Global Warming Potential
Tg = Teragrams
36 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot)
(IPCC 2001).
37 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).
38 Carbon comprises 12/44ths of carbon dioxide by weight.
Introduction 1-7
-------
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.^
Greenhouse gases with relatively long atmospheric lifetimes (e.g., €62, 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., 862 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
C02
CH4b
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2Fe
C4Fio
C6Fi4
SFe
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.
ifjppfPiPSiffaffpf^
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
39 Framework Convention on Climate Change; ; 1 November 2002; Report of the
Conference of the Parties at its eighth session; held at New Delhi from 23 October to 1 November 2002; Addendum; Part One:
Action taken by the Conference of the Parties at its eighth session; Decision -/CP.8; Communications from Parties included in
Annex I to the Convention: Guidelines for the Preparation of National Communications by Parties Included in Annex I to the
Convention, Part 1: UNFCCC reporting guidelines on annual inventories; p. 7. (UNFCCC 2003)
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 CC>2 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*
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2Fe
C4FiO
C6F14
SF6
SAR
1
21
310
11,700
650
2,800
1,300
3,800
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
TAR
1
23
296
12,000
550
3,400
1,300
4,300
120
3,500
9,400
1,500
5,700
11,900
8,600
9,000
22,200
AR4
1
25
298
14,800
675
3,500
1,430
4,470
124
3,220
9,810
1,640
7,390
12,200
8,860
9,300
22,800
Change 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 inventories40 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 2011 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.
40 See .
Introduction 1-9
-------
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.
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.
H « «•
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
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
series, and conduct a special source-specific peer review process involving relevant experts from industry,
government, and universities.
Once the methodology is in place and the data are collected, the individual source leads calculate emissions and sink
estimates. The source leads then update or create the relevant text and accompanying annexes for the Inventory.
Source leads are also responsible for completing the relevant sectoral background tables of the Common Reporting
Format, conducting quality assurance and quality control (QA/QC) checks, and uncertainty analyses.
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.
The MR 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.
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 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.
Introduction 1-11
-------
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.
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.
Emissions of greenhouse gases from various source and sink categories have been estimated using methodologies
that are consistent with the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997). In addition, the United States references the additional guidance provided in the
IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (IPCC 2000),
the IPCC Good Practice Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003), and the 2006 IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006). To the extent possible, the present report relies
on published activity and emission factor data. Depending on the emission source category, activity data can
include fuel consumption or deliveries, vehicle-miles traveled, raw material processed, etc. Emission factors are
factors that relate quantities of emissions to an activity.
The IPCC methodologies provided in the Revised 1996 IPCC Guidelines represent baseline methodologies for a
variety of source categories, and many of these methodologies continue to be improved and refined as new research
and data become available. In this regard, the U.S. has implemented many methodological improvements published
in the IPCC 2006 Guidelines. The use of the most recently published calculation methodologies by the IPCC, as
contained in the 2006 IPCC Guidelines, is fully in line with the IPCC good practice guidance for methodological
choice to improve rigor and accuracy. In addition, the improvements in using the latest methodological guidance
from the IPCC has been recognized by the UNFCCC's Subsidiary Body for Scientific and Technological Advice in
the conclusions of its 30th Session41, Numerous U.S. inventory experts were involved in the development of the
2006 IPCC Guidelines, and their expertise has provided this latest guidance from the IPCC with the most
appropriate calculation methods that are then used in this inventory. This report uses the IPCC methodologies when
applicable, and supplements them with other available country-specific 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.
41 These Subsidiary Body for Scientific and Technological Advice (SBSTA) conclusions state, "The SBSTA acknowledged that
the 2006 IPCC Guidelines contain the most recent scientific methodologies available to estimate emissions by sources and
removals by sinks of greenhouse gases (GHGs) not controlled by the Montreal Protocol, and recognized that Parties have gained
experience with the 2006 IPCC Guidelines. The SBSTA also acknowledged that the information contained in the 2006 IPCC
Guidelines enables Parties to further improve the quality of their GHG inventories." See
1-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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.
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."42
By definition, key categories include those sources that have the greatest contribution to the absolute level of
national emissions. In addition, when an entire time series of emission estimates is prepared, a thorough
investigation of key categories must also account for the influence of trends and uncertainties of individual source
and sink categories. This analysis culls out source and sink categories that diverge from the overall trend in national
emissions. Finally, a qualitative evaluation of key categories is performed to capture any categories that were not
identified in any of the quantitative analyses.
A Tier 1 approach, as defined in the IPCC's Good Practice Guidance (IPCC 2000), was implemented to identify the
key categories for the United States. This analysis was performed twice; one analysis included sources and sinks
from the Land Use, Land-Use Change, and Forestry (LULUCF) sector, the other analysis did not include the
LULUCF categories. Following the Tier 1 approach, a Tier 2 approach, as defined in the IPCC's Good Practice
Guidance (IPCC 2000), was then implemented to identify any additional key categories not already identified in the
Tier 1 assessment. This analysis, which includes each source category's uncertainty assessments (or proxies) in its
calculations, was also performed twice to include or exclude LULUCF categories.
In addition to conducting Tier 1 and 2 level and trend assessments, a qualitative assessment of the source categories,
as described in the IPCC's Good Practice Guidance (IPCC 2000), was conducted to capture any key categories that
were not identified by either quantitative method. One additional key category, international bunker fuels, was
identified using this qualitative assessment. International bunker fuels are fuels consumed for aviation or marine
international transport activities, and emissions from these fuels are reported separately from totals in accordance
with IPCC guidelines. If these emissions were included in the totals, bunker fuels would qualify as a key category
according to the Tier 1 approach. The amount of uncertainty associated with estimation of emissions from
international bunker fuels also supports the qualification of this source category as key, because it would qualify
bunker fuels as a key category according to the Tier 2 approach. Table 1-4 presents the key categories for the United
States (including and excluding LULUCF categories) using emissions and uncertainty data in this report, and ranked
according to their sector and global warming potential-weighted emissions in 2011. The table also indicates the
criteria used in identifying these categories (i.e., level, trend, Tier 1, Tier 2, and/or qualitative assessments). Annex
1 of this report provides additional information regarding the key categories in the United States and the
methodologies used to identify them.
See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
Introduction 1-13
-------
Table 1-4: Key Categories for the United States (1990-2011)
IPCC Source Categories
Gas
Tierl
Level Trend Level Trend
Without Without With With
LULUCF LULUCF LULUCE LULUCF
Tier 2
Level Trend Level Trend
Without Without With With
LULUCF LULUCF LULUCF LULUCF
Quala
2011
Emissions
(Tg C02
Eq.)
Energy
,CQ§ Emissions from
~ V .--£••
' '*>'
CO2 Emissions from
Mobile Combustion: Road
CO2 Emissions from
Stationary Combustion -
Gas - Electricity Generation
^''StafjonaiyiOoipbvistien - pfl
? Industrial•»••
CO2 Emissions from
Stationary Combustion -
Gas - Residential
,CO»-EHl|ssiaas from
CO2 Emissions from
Mobile Combustion:
Aviation
CO2 Emissions from
Stationary Combustion -
Coal - Industrial
,CQf Emissions from
CO2 Emissions from
Stationary Combustion - Oil
- Residential
.fpaEmis-l
Tk IF -
Manae '
CO2 Emissions from
Stationary Combustion - Oil
- Commercial
C02
CO2
C02
CO2
C02
C02
CO2
1,466.
408.8
254.6
148.4
90.1
73.6
46.7
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
CO2 Emissions from
Natural Gas Systems
CO2 Emissions from
Stationary Combustion -
Coal - Commercial
, • Fjigitif e Emissions from
Natuftl Gas Systems ',
Fugitive Emissions from
Coal Mining
Fugitive Emissions from,
/peljatejjni Systems'f
Non-CO2 Emissions from
Stationary Combustion -
Residential
.Non-CQa-Emissions from / '
• Siatieliarf /Csftibustion — -
Electjicitji Genpf tiea,J-' /
N2O Emissions from
Mobile Combustion: Road
Non-CO2 Emissions from
Stationary Combustion -
Industrial
c*
C02
eps ,.-
C02
/CHI
CH4
f~T^~f-
\^fL^
CH4
TfsO
N20
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* *
*
* *
* * 9 9
• • •
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•
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•
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14.4
2.7
Industrial Processes
CO2 Emissions from
Cement Production
N2O Emissions from Adipic
Acid Production
/EmpsioHs fipmj Spbstitates
fot
SFe Emissions from
Electrical Transmission and
Distribution
/HFCJ-2.,3. Einigsiejis pf>m
PFC Emissions from
Aluminum Production
C02
,-COg .
N20
HiGWP
HiGWP
31.6
10.6
7.0
2.9
Introduction 1-15
-------
m
Mi
froditctioa pad -
*
Agriculture
,CB4 Emissions ffQin
CFLi Emissions from
Manure Management
,084 EinjsSioHs/fioin-Riee
JJuftjvajtan/ '
Direct NiO Emissions from
Agricultural Soil
Management
/ Indirect NaQ. Emissions
Ijjtn Af pEe4:MtiegB|t
SB*
CH4
/CH4 -
N2O
-'H»9
/"
/
9 •
/*
/*
* *
• •
* * *
laJ
52.0
,4.
195.2
«|!
Waste
CB4 Emtssioms -fjoin
.'EajKjgils /x 'x '
ea .
X " /
X
if)^if^
i-M^Hw
Land Use, Land Use Change, and Forestry
CO2 Emissions from
Grassland Remaining
Grassland
•'.-Cf&pjfldf * •'" /
CO2 Emissions from
Landfilled Yard Trimmings
and Food Scraps
,COjEm|ssiQmsfromj.Hrb^H, ;
CO2 Emissions from
Changes in Forest Carbon
Stocks
,p5f ,Emif f|ens-fi»m F.a reft
N2O Emissions from Forest
Fires
.(Jft
C02
C02
C02
,,€H4 -
N20
9
•/
•
9 9
9 9
9 9
9 9
9 9
9 9
Subtotal Without LULUCF
Total Emissions Without LULUGF
Percent of Total Without LULUCF
Subtotal With LULUCF
Total Emissions With LULUCF
/?• wcent of Tottl With, LUWCF
•^
1A
(13.0)
(833.5)
/l4
11.6
6,513.9
/6J
-------
i.i
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.
Key attributes of the QA/QC plan are summarized in Figure 1-1. These attributes 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 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
Introduction 1-17
-------
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.
Figure 1-1: U.S. QA/QC Plan Summary
Figure 1-1: U S. QAW3C Plan Summary
re
c
O)
•Obtain data in electronic
format (if possible)
•Review spreadsheet
construction
•Avoid hardwring
•Use data validation
•Protect cells
•Develop automatic
checkers for;
•OutJiefs, negative \>slues? or
missing data
•Variable types rriatchvalues
•Time series amsisssrey
•Maintain trackingtab for
status of gathering efforts
•roht'iit rnpnrt ton inn
efetronn rnrmuMSiM -itiur
•Fio idKCtfll teteietine'foi
fjrirn-u d4«i@lfcmeit*
«< llltdl 11 I Oplt Lit Jl d?t3
siil'lCPs
*LI t dri'JIoi -itinti nf dh
> prhng'titeirnl
preaH he^t
•Oiinmient ^ urn|it!0ir
•Clearly label parameter-;,
units, 3rd conversion factors
•Review spreadsheet
integrity
•Equations
•Units
*!nput and output
•Develop automated
checkers tor;
• Input rangss
•CaioilaQons
^w^a^i3i|§risf:8^'f;:;.^ ^vf.^^^.^^-^^^'^,;
Data Gathering
Data Doeymcntation Calculating Emissions
•Common starting versions
for each Inventory year
•Utilise unalterable
summary tab tor each
source spreadsheet for
finMngto a master summary
spreadsheet
•Follow strict version
control procedures
•Docun
Cross-Cutting
Coordination
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, 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. The UNFCCC reporting guidelines follow
the recommendation in the 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) and require that countries
provide single point estimates 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
1-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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. Estimates of quantitative uncertainty for the overall greenhouse gas
emissions inventory are 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 and in Annex 7. Consistent with the IPCC Good Practice Guidance (IPCC 2000), 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 COz Eq. and Percent)
2011 Emission Uncertainty Range Relative to Emission Standard
Estimate3 Estimate1" Mean0 Deviation0
Gas (TgCChEq.) (Tg CCh Eq.) (%) (Tg CCh Eq.)
C02
CH4e
N20e
PFC, HFC & SF«e
Total
Net Emissions (Sources and Sinks)
5,612.9
587.2
356.9
145.3
6,702.3
5,797.3
Lower
Bound"1
5,470
508
326
141
6,575
5,633
Upper
Bound"
5,847
668
502
158
7,017
6,143
Lower
Bound
-3%
-13%
-9%
-3%
-2%
-3%
Upper
Bound
4%
14%
41%
9%
5%
6%
5,658
581
405
149
6,794
5,884
97
39
45
4
114
132
Notes:
a Emission estimates reported in this table correspond to emissions from only those source categories for which quantitative
uncertainty was performed this year. Thus the totals reported in this table exclude approximately 4.6 Tg CCh Eq. of emissions
for which quantitative uncertainty was not assessed. Hence, these emission estimates do not match the final total U.S.
greenhouse gas emission estimates presented in this Inventory.
b The lower and upper bounds for emission estimates correspond to a 95 percent confidence interval, with the lower bound
corresponding to 2.5th percentile and the upper bound corresponding to 97.5th percentile.
c 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.
d The lower and upper bound emission estimates for the sub-source categories do not sum to total emissions because the low and
high estimates for total emissions were calculated separately through simulations.
e The overall uncertainty estimates did not take into account the uncertainty in the GWP values for CH/i, N2O and high GWP
gases used in the inventory emission calculations for 2011.
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 uncertainty associated with the emission estimates and for a
Introduction 1-19
-------
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.
This report, along with its accompanying CRF tables, 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 2011. Although this
report is intended to be comprehensive, certain sources have been identified which were 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 implemented, new emission sources are quantified and included in the
Inventory. For a complete list of sources not included, see Annex 5 of this report.
In accordance with the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), and the 2006 UNFCCC Guidelines on Reporting and Review (UNFCCC 2006),
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
Use from the use of solvents and N2O from product
uses.
Agriculture Anthropogenic emissions from agricultural
activities except fuel combustion, which is
addressed under Energy.
Land Use, Land-Use Emissions and removals of CCh, CLLi, and N2O
Change, and Forestry from forest 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
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
SOUK6 Category. Description of source pathway and emission trends.
1-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 COa 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.
Introduction 1-21
-------
Table 1-7: List of Annexes
ANNEX 1 Key Category Analysis
ANNEX 2 Methodology and Data for Estimating CCh Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of CCh 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 CLU, N2O, and Indirect Greenhouse Gases from Stationary
Combustion
3.2. Methodology for Estimating Emissions of CLU, 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 Emissions from Commercial Aircraft Jet Fuel Consumption
3.4. Methodology for Estimating CEU Emissions from Coal Mining
3.5. Methodology for Estimating CEU Emissions from Natural Gas Systems
3.6. Methodology for Estimating CtLt and CCh Emissions from Petroleum Systems
3.7. Methodology for Estimating CCh and N2O Emissions from Incineration of Waste
3.8. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.9. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances
3.10. Methodology for Estimating CEU Emissions from Enteric Fermentation
3.11. Methodology for Estimating CtLt and N2O Emissions from Manure Management
3.12. Methodology for Estimating N2O Emissions and Soil Organic C Stock Changes from Agricultural Soil
Management (Cropland and Grassland)
3.13. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.14. Methodology for Estimating CLU 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 Not Included
ANNEX 6 Additional Information
6.1. Global Warming Potential Values
6.2. Ozone Depleting Substance Emissions
6.3. Sulfur Dioxide Emissions
6.4. Complete List of Source Categories
6.5. Constants, Units, and Conversions
6.6. Abbreviations
6.7. Chemical Formulas
ANNEX 7 Uncertainty
7.1. Overview
7.2. Methodology and Results
7.3. Planned Improvements
7.4. Additional Information on Uncertainty Analyses by Source
1-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
In 2011, total U.S. greenhouse gas emissions were 6,702.3 Tg or million metric tons €62 Eq. Total U.S. emissions
have increased by 8.4 percent from 1990 to 2011, and emissions decreased from 2010 to 2011 by 1.6 percent (108.0
TgCChEq.). The decrease from 2010 to 2011 was due to a decrease in the carbon intensity of fuels consumed to
generate electricity due to a decrease in coal consumption, with increased natural gas consumption and a significant
increase in hydropower used. Additionally, relatively mild winter conditions, especially in the South Atlantic
Region of the United States where electricity is an important heating fuel, resulted in an overall decrease in
electricity demand in most sectors. Since 1990, U.S. emissions have increased at an average annual rate of 0.4
percent.
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas
• MFCs, PFCs, & SF6
Nitrous Oxide
8,000 -|
7,000 -
6,000 -
iff 5,000 -
6'
u 4,000 -
P
3,000 -
2,000 -
1,000 -
0 -
1 Nfethane "Carbon DioMde
,c , R774 6823
Trends 2-1
-------
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
3,4%
-6,6%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Figure 2-3: Cumulative Change in Annual U.S. Greenhouse Gas Emissions Relative to 1990
981 1'012 969
1,080
627
519
As the largest contributor to U.S. greenhouse gas emissions, carbon dioxide (CCh) from fossil fuel combustion has
accounted for approximately 78 percent of global warming potential (GWP) weighted emissions since 1990, from
77 percent of total GWP-weighted emissions in 1990 to 79 percent in 2011. Emissions from this source category
grew by 11.1 percent (528.7 Tg CCh Eq.) from 1990 to 2011 and were responsible for most of the increase in
national emissions during this period. From 2010 to 2011, these emissions decreased by 2.4 percent (130.9 Tg CCh
Eq.). Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S.
emission trends.
Changes in CCh 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 fluctuates primarily 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 behavioral choices (e.g., walking, bicycling, or telecommuting to work
instead of driving).
Energy-related CCh 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 €62 emissions
because of the lower C content of natural gas.
A brief discussion of the year to year variability in fuel combustion emissions is provided below, beginning with
2007.
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Emissions from fossil fuel combustion decreased from 2007 to 2008. Several factors contributed to this decrease in
emissions. An increase in energy prices coupled with the economic downturn led to a decrease in energy demand
and a resulting decrease in emissions from 2007 to 2008. In 2008, the price of coal, natural gas, and petroleum used
to generate electricity, as well as the price of fuels used for transportation, increased significantly. As a result of this
price increase, coal, natural gas, and petroleum consumption used for electricity generation decreased by 1.4
percent, 2.5 percent, and 28.8 percent, respectively. The increase in the cost of fuels to generate electricity translated
into an increase in the price of electricity, leading to a decrease in electricity consumption across all sectors except
the commercial sector. The increase in transportation fuel prices led to a decrease in vehicle miles traveled (VMT)
and a 4.7 percent decrease in transportation fossil fuel combustion emissions from 2007 to 2008. Cooler weather
conditions in the summer led to a decrease in cooling degree days by 8.7 percent and a decrease in electricity
demand compared to 2007, whereas cooler winter conditions led to a 5.6 percent increase in heating degree days
compared to 2007 and a resulting increase in demand for heating fuels. The increased emissions from winter heating
energy demand was offset by a decrease in emissions from summer cooling related electricity demand. Lastly,
renewable energy consumption for electricity generation increased by 9.5 percent from 2007 to 2008, driven by a
significant increase in solar and wind energy consumption (of 17.3 percent and 60.2 percent, respectively).43 This
increase in renewable energy generation contributed to a decrease in the carbon intensity of electricity generation.
From 2008 to 2009, CC>2 from fossil fuel combustion emissions experienced a decrease of 6.6 percent, the greatest
decrease of any year over the course of the twenty-year period. Various factors contributed to this decrease in
emissions. The continued economic downturn resulted in a 3.1 percent decrease in GDP, and a decrease in energy
consumption across all sectors. The economic downturn also impacted total industrial production and manufacturing
output, which decreased by 11.4 and 13.8 percent, respectively. In 2009, the price of coal used to generate electricity
increased, while the price of natural gas used to generate electricity decreased significantly. As a result, natural gas
was used for a greater share of electricity generation in 2009 than 2008, and coal was used for a smaller share. The
fuel switching from coal to natural gas and additional electricity generation from other energy sources in 2009,
which included a 6.3 percent increase in hydropower generation from the previous year, resulted in a decrease in
carbon intensity, and in turn, a decrease in emissions from electricity generation. From 2008 to 2009, industrial
sector emissions decreased significantly as a result of a decrease in output from energy-intensive industries of 24.6
percent in nonmetallic mineral and 26.0 percent in primary metal industries. The residential and commercial sectors
only experienced minor decreases in emissions as summer and winter weather conditions were less energy-intensive
from 2008 to 2009, and the price of electricity only increased slightly. Heating degree days decreased slightly and
cooling degree days decreased by 3.8 percent from 2008 to 2009.
From 2009 to 2010, CO2 emissions from fossil fuel combustion increased by 3.6 percent, which represents one of
the largest annual increases in CCh emissions from fossil fuel combustion for the twenty one-year period.44 This
increase is primarily due to an increase in economic output 2009 to 2010, where total industrial production and
manufacturing output increased by 5.4 and 6.3 percent, respectively (FRB 2011). Carbon dioxide emissions from
fossil fuel combustion in the industrial sector increased by 8.0 percent, including increased emissions from the
combustion of fuel oil, natural gas and coal. Overall, coal consumption increased by 5.4 percent, the largest increase
in coal consumption for the twenty one-year period between 1990 and 2011. In 2010, weather conditions remained
fairly constant in the winter and were much hotter in the summer compared to 2009, as heating degree days
decreased slightly by 0.7 percent and cooling degree days increased by 18.6 percent to their highest levels in the
twenty one-year period. As a result of the more energy-intensive summer weather conditions, electricity sales to the
residential and commercial end-use sectors in 2010 increased approximately 6.0 percent and 1.8 percent,
respectively.
From 2010 to 2011, CC>2 emissions from fossil fuel combustion decreased by 2.4 percent. This decrease is a result of
multiple factors including: (1) a decrease in the carbon intensity of fuels consumed to generate electricity due to a
decrease in coal consumption, with increased natural gas consumption and a significant increase in hydropower
used; (2) a decrease in transportation-related energy consumption due to higher fuel costs, improvements in fuel
efficiency, and a reduction in miles traveled; and (3) relatively mild winter conditions resulting in an overall
decrease in energy demand in most sectors. In addition, changing fuel prices played a role in the decreasing
43 Renewable energy, as defined in EIA's energy statistics, includes the following energy sources: hydroelectric power,
geothermal energy, biofuels, solar energy, and wind energy.
44 This increase also represents the largest absolute and percentage increase since 1988 (EIA 2011 a).
Trends 2-3
-------
emissions. Significant increases in the price of motor gasoline in the transportation sector led to a decrease in energy
consumption by 1.1 percent. In addition, an increase in the price of coal and a concurrent decrease in natural gas
prices led to a 5.7 percent decrease and a 2.5 percent increase in fuel consumption of these fuels by electric
generators. This change in fuel prices also reduced the carbon intensity of fuels used to produce electricity in 2011,
further contributing to the decrease in fossil fuel combustion emissions.
Overall, from 1990 to 2011, total emissions of CO2 increased by 504.0 Tg CO2 Eq. (9.9 percent), while total
emissions of CH4 decreased by 52.7 Tg CO2Eq. (8.2 percent), and total emissions of N2O increased 12.6 Tg CO2
Eq. (3.6 percent). During the same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 55.1 Tg
CO2 Eq. (61.1 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. These
were estimated to offset 13.5 percent of total emissions in 2011.
Table 2-1 summarizes emissions and sinks from all U. S. anthropogenic sources in weighted units of Tg CO2 Eq.,
while unweighted gas emissions and sinks in gigagrams (Gg) are provided in Table 2-2.
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg COz Eq.)
Gas/Source
CO2
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
5
4
1
1
1990
,108.8
,748.5 '-•
,820.8, '
,494.0 '-:,
848.6
338.3
219.0
27.9
117.4
2005
6,109.3
5,748.7
• 2,402.1 /
1,891.7,
823.4
357.9
223.5 ..
50.0 /
142.7
2007
6,128.6
5,767.7
2,412.8
1,904.7
844.4
341.6
218.9
45.2
134.9
2008
5,944.8
5,590.6
2,360.9
1,816.0
802.0
347.0
223.8
41.0
139.5
5
5
2
1
2009
,517.9
,222.4
,146.4
,749.2
722.6
337.0
223.4
43.8
124.0
2010
5
5
2
1
,736.
,408,
,259,
,763,
780,
334,
220,
49,
132,
4
.1
.2
.9
.2
.6
.6
.6
.8
2011
5,612.9
5,277.2
2,158.5
1,745.0
773.2
328.8
222.1
49.7
130.6
Iron and Steel Production & Metallurgical Coke
Production
Natural Gas Systems
Cement Production
Lime Production
Incineration of Waste
Other Process Uses of Carbonates
Ammonia Production
Cropland Remaining Cropland
Urea Consumption for Non-Agricultural Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Wetlands Remaining Wetlands
Lead Production
Petroleum Systems
Silicon Carbide Production and Consumption
Land Use, Land-Use Change, and Forestry (Sink)"
WoodBiomass andEthanol Consumption11
International Bunker Fuels"
CH4
Natural Gas Systems
Enteric Fermentation
99.8 .
37.7' •'
33.3V
11.5
8.0
4.9
13.0
7.1
3.8
3.4 "
6.8
2.8 •
1.2
1.4
2.2
1.5'
0.6
1.5
1.0
0.5V
0.4 ;
0.4 '-•
(794.5)
218.6
103.5,
639.9
161.2
132.7
66.7 /
29.9
45.2
14.3
12.5
6.3
9.2
7.9
3.7 /
4.3
4.1
3.0
1.8 /
1.3
1.4
1.9
1.0 ,
1.3
1.1
0.6
0.3 /
0.2
(997.8)
228.7
113.1 /
593.6
159.0
137.0 ,
71.3
30.9
44.5
14.6
12.7
7.4
9.1
8.2
4.9
4.1
4.3
2.9
1.9
1.9
1.6
1.5
1.0
1.2
1.0
0.6
0.3
0.2
(929.2)
/ 238.3
115.3
618.6
168.4
141.8
66.8
32.6
40.5
14.3
11.9
5.9
7.9
8.6
4.1
3.6
4.5
3.0
1.8
1.8
1.6
1.5
1.2
1.1
1.0
0.5
0.3
0.2
(902.6)
251.7
114.3
618.8
163.4
141.4
43.0
32.2
29.0
11.2
11.7
7.6
7.9
7.2
3.4
2.8
3.0
2.6
1.6
1.8
1.5
1.0
0.9
1.0
1.1
0.5
0.3
0.1
(882.6)
245.1
106.4
603.8
150.7
140.6
55.7
32.3
30.9
13.1
12.0
9.6
8.7
8.4
4.4
3.5
2.7
2.7
1.8
2.2
1.7
1.5
1.2
1.1
1.0
0.5
0.3
0.2
(888.8)
264.5
117.0
592.7
143.6
139.3
64.3
32.3
31.6
13.8
12.0
9.2
8.8
8.1
4.3
3.5
3.3
2.7
1.9
1.8
1.7
1.3
1.3
1.2
0.9
0.5
0.3
0.2
(905.0)
264.5
111.3
587.2
144.7
137.4
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Landfills
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Petrochemical Production
Mobile Combustion
Composting
Iron and Steel Production & Metallurgical Coke
Production
Field Burning of Agricultural Residues
Ferroalloy Production
Silicon Carbide Production and Consumption
Incineration of Waste
International Bunker Fuels0
N20
Agricultural Soil Management
Stationary Combustion
Mobile Combustion
Manure Management
Nitric Acid Production
Forest Land Remaining Forest Land
Adipic Acid Production
Wastewater Treatment
N2O from Product Uses
Composting
Settlements Remaining Settlements
Incineration of Waste
Field Burning of Agricultural Residues
Wetlands Remaining Wetlands
International Bunker Fuels0
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
Net Emissions (Sources and Sinks)
147.8
84.1'
31.5
35.2 ;
15.9
2.5'.
7.1 :
7.5 '
6.0
2.3,
4.6
0.3 ""
1.0
0.2 ,
+ , '
+ '
+ ,
0.1
344.3
227.9
12.3
44.0
14.4
18.2-'
2.1-
15.8
3.5 -
4.4 "•
0.4
1.0
0.5
0.1
+
0.9
36.9
0.3
36.4
0.2'
20.6
2.2
18.4
32.6
26.7 •"
5.4-
0.5 '.'
6,183.3
5,388.7
112.5
56.9
47.6
29.2 /'
16.5
8.0
6.8 /
6.6
5.5
3.1
2.4 /
1.6
0.7
0.2 /
+•'
'. +
+
0.1 /
356.1
237.5
20.6 .
36.9 /
17.1
: 16.9
6.9 .
7.4 /
4.7
4.4
1.7 .•
1.5.-'
0.4
0.1
+ .
1.0 /
115.0
99.0
15.8 /
0.2
6.2
3.2
3.0 /
15.0
11.1
2.9
1.0 /
7,195.3
6,197.4
: 111.6
57.9
52.4
29.8
16.6
14.4
6.2
6.4
5.3
3.3
2.1
1.7
0.7
0.2
+
+
+
0.1
376.1
252.3
21.2
29.0
18.0
19.7
12.1
10.7
4.8
4.4
1.8
1.6
0.4
0.1
+
1.0
120.0
. 102.7
17.0
0.3
7.7
3.8
3.8
12.3
8.8
2.6
0.8
' 7,263.2
6,334.0
113.6
67.1
51.5
30.0
16.6
8.7
7.2
6.6
5.3
2.9
1.9
1.7
0.6
0.2
+
+
+
0.1
349.7
245.4
21.1
25.5
17.8
16.9
7.4
2.6
4.9
4.4
1.9
1.5
0.4
0.1
+
1.0
117.5
103.6
13.6
0.3
6.6
3.9
2.7
11.4
8.6
1.9
0.9
7,048.8
6,146.2
113.3
70.3
50.5
30.5
16.5
5.7
7.3
6.3
5.1
2.9
1.8
1.6
0.4
0.2
+
+
+
0.1
338.7
242.8
20.7
22.7
17.7
14.0
5.0
2.8
5.0
4.4
1.8
1.4
0.4
0.1
+
0.9
112.0
106.3
5.4
0.2
4.4
2.9
1.6
9.8
8.1
1.1
0.7
6,586.6
5,704.0
106.8
72.4
51.8
30.8
16.4
4.7
8.6
6.3
5.0
3.1
1.8
1.5
0.5
0.2
+
+
+
0.1
343.9
244.5
22.6
20.7
17.8
16.8
4.2
4.4
5.1
4.4
1.7
1.5
0.4
0.1
+
1.0
121.3
114.6
6.4
0.4
5.9
4.4
1.6
10.1
7.8
1.3
1.0
6,810.3
5,921.5
103.0
63.2
52.0
31.5
16.2
14.2
6.6
6.3
4.8
3.1
1.7
1.5
0.6
0.2
+
+
+
0.1
356.9
247.2
22.0
18.5
18.0
15.5
11.9
10.6
5.2
4.4
1.7
1.5
0.4
0.1
+
1.0
129.0
121.7
6.9
0.3
7.0
4.1
2.9
9.4
7.0
1.4
0.9
6,702.3
5,797.3
+ Does not exceed 0.05 Tg CO2 Eq.
a The net CCh 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 Wood Biomass and Ethanol Consumption are not included specifically in summing energy sector totals. Net
carbon fluxes from changes in biogenic carbon reservoirs are accounted for in the estimates for Land Use, Land-Use Change, and
Forestry.
c Emissions from International Bunker Fuels are not included in totals.
d Small amounts of PFC emissions also result from this source.
Note: Totals may not sum due to independent rounding.
Trends 2-5
-------
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
U.S. Territories
Non-Energy Use of Fuels
Iron and Steel Production &
Metallurgical Coke Production
Natural Gas Systems
Cement Production
Lime Production
Incineration of Waste
Other Process Uses of Carbonates
Ammonia Production
Cropland Remaining Cropland
Urea Consumption for Non-
Agricultural Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and
Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Wetlands Remaining Wetlands
Lead Production
Petroleum Systems
Silicon Carbide Production and
Land Use, Land-Use Change, and
Forestry
WoodBiomass andEthanol
Consumption11
International Bunker Fuels0
CH4
Natural Gas Systems
Enteric Fermentation
Landfills
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal
Mines
Petrochemical Production
Mobile Combustion
Composting
1990
5,108,811
4,748,532 ' '
1,820,817
1,493,968.
848,556 :
338,347 -
218,963
27,882 .
117,414
99,781
37,665 '
33,278,
11,488
7,972
4,907-
13,047
7,084
3,784
3,429 ,.
6,831
2,822
1,195
1,416-
2,152
1,535
632
1,529 ',.
1,033
516
394
375
(794,529) ,
218,637
103,463
30,473
7,678
6,321
7,037 '
4,003 '••
1,499
1,677
758 -
118'.
339
355 '
288
108
218
15.'"
2005
6,109,336
• 5,748,674,
, ,, 2,402,142
1,891,744
823,408 ,
357,902*'
223,510
49,968
142,701 .
66,666
29,923
45,197,
14,322
12,452
6,339
9,196
7,854
3,653 .
4,330
4,142
2,960 ,
1,755
1,321
1,392
1,928
1,030
1,342
1,079 ,
553'
306
219
(997,828)
228,651
113,139
28,269
7,572
. ' 6,522 ,
5,357''
2,710
2,265
1,390,
785
383
326
315
264
150 ,
113
75
2007
6,128,551
5,767,654
2,412,827
1,904,652
844,420
341,649
218,874
45,232
134,887
71,277
30,851
44,538
14,579
12,711
7,365
9,074
8,222
4,944
4,070
4,251
2,937
1,930
1,867
1,552
1,536
1,025
1,203
1,012
562
311
196
(929,202)
238,308
115,345
29,459
8,018
6,751
5,314
2,756
2,493
1,421
791
684
295
305
254
155
100
79
2008
5,944,813
5,590,638
2,360,920
1,815,999
802,040
346,962
223,759
40,959
139,484
66,822
32,622
40,531
14,345
11,876
5,885
7,883
8,638
4,065
3,572
4,477
2,960
1,809
1,780
1,599
1,523
1,159
1,132
992
547
300
175
(902,605)
251, 734
114,342
29,466
7,782
6,731
5,409
3,196
2,452
1,431
791
413
343
313
253
137
92
80
2009
5,517,926
5,222,419
2,146,415
1,749,166
722,627
337,034
223,358
43,818
123,977
43,029
32,187
29,018
11,164
11,688
7,583
7,855
7,236
3,415
2,833
3,009
2,569
1,648
1,784
1,469
1,045
943
977
1,089
525
320
145
(882,625)
245,057
106,410
28,751
7,178
6,693
5,397
3,348
2,403
1,455
786
271
349
298
244
138
88
75
2010
5,736,400
5,408,119
2,259,190
1,763,870
780,240
334,589
220,616
49,615
132,839
55,746
32,313
30,924
13,145
12,038
9,560
8,678
8,351
4,365
3,455
2,722
2,697
1,769
2,203
1,663
1,481
1,182
1,087
1,010
542
332
181
(888,771)
264,459
116,992
28,224
6,838
6,632
5,083
3,447
2,466
1,467
779
222
410
301
237
146
85
73
2011
5,612,855
5,277,246
2,158,510
1,745,001
773,192
328,759
222,098
49,685
130,554
64,259
32,344
31,632
13,795
12,038
9,153
8,795
8,117
4,329
3,505
3,292
2,712
1,903
1,811
1,663
1,299
1,286
1,151
918
538
347
170
(905,041)
264,527
111,316
27,964
6,893
6,542
4,907
3,011
2,478
1,499
770
675
316
300
231
148
82
74
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Iron and Steel Production & I
Metallurgical Coke Production 46' 34 33 31 17 25 28
Field Burning of Agricultural
Residues 10 , 8, 11 11 11 11 10
Ferroalloy Production 1 " + + + + + +
Silicon Carbide Production and
Consumption 1 + . + + + + +
Incineration of Waste + + + + + + +
International Bunker Fuelsc 7 5 56565
N2O 1,111 1,149 1,213 1,128 1,093 1,109 1,151
Agricultural Soil Management 735 766 814 792 783 789 797
Stationary Combustion 40 66 68 68 67 73 71
Mobile Combustion 142 119 / 94 82 73 67 60
Manure Management 46 55 .•' 58 57 57 57 58
Nitric Acid Production 59' 55 64 54 45 54 50
Forest Land Remaining Forest
Land 7 22 / 39 24 16 13 38
Adipic Acid Production 51 ', 24, 34 8 9 14 34
Wastewater Treatment 11 , 15 16 16 16 16 17
N2O from Product Uses 14 14 14 14 14 14 14
Composting 1 6,66 6 5 6
Settlements Remaining Settlements 3 " , 5 5 5 5 5 5
Incineration of Waste 2 1 1 1 1 1 1
Field Burning of Agricultural
Residues + + /' + + + + +
Wetlands Remaining Wetlands + + + + + + +
International Bunker Fuelsc 3 , 3 33 3 3 3
HFCs M M M M M M M
Substitution of Ozone Depleting
Substances'1 M M M M M M M
HCFC-22 Production 3 , 1 1 1 + 1 1
Semiconductor Manufacture + + / + + + + +
PFCs M M M M M M M
Semiconductor Manufacture M M M M M M M
Aluminum Production M M M M M M M
SF6 1,, 1 / + + + + +
Electrical Transmission and
Distribution 1 + + + + + +
Magnesium Production and
Processing +. + .•' + + + + +
Semiconductor Manufacture + + + + + + +_
+ Does not exceed 0.5 Gg.
M Mixture of multiple gases
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 Wood Biomass and Ethanol Consumption are not included specifically in summing energy sector totals. Net carbon
fluxes from changes in biogenic carbon reservoirs are accounted for in the estimates for Land Use, Land-Use Change, and Forestry
0 Emissions from International Bunker Fuels are not included in totals.
d 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 into a set of six sectors defined by the
Intergovernmental Panel on Climate Change (IPCC). Over the twenty -two-year period of 1990 to 2011, total
emissions in the Energy, Industrial Processes, and Agriculture sectors grew by 478.4 Tg COa Eq. (9.1 percent), 10.3
Tg CO2 Eq. (3.3 percent), and 47.6 Tg CO2 Eq. (11.5 percent), respectively. Emissions from the Waste and Solvent
and Other Produce Use sectors decreased by 40.2 Tg COa Eq. (23.9 percent) and less than 0.1 Tg CO2 Eq. (0.4
percent), respectively. Over the same period, estimates of net C sequestration in the Land Use, Land-Use Change,
and Forestry sector increased by 87.6 Tg CO2 Eq. (11.2 percent).
Trends 2-7
-------
Figure 2-4: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
Waste
LULUCF (sources)
iff
8
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
5,267.3 :
316.1
4.4
413.9
13.7 -'
167.8
6,183.3
(794.5)
5,388.7
* The net CCh flux total includes both emissions and
2005
6,251.6 /
330.8 /
4.4'
446.2
25.4 .••'
136.9
7,195.3
(997.8)
6,197.4
2007
' 6,266.9
347.2
4.4
470.9
37.3
136.5
, 7,263.2
(929.2)
; 6,334.0
sequestration, and constitutes a
2008
6,096.2
318.7
4.4
463.6
27.2
138.6
7,048.8
(902.6)
6,146.2
2009
5,699.2
265.3
4.4
459.2
20.4
138.1
6,586.6
(882.6)
5,704.0
sink in the United
2010
5,889.1
303.4
4.4
462.3
19.7
131.4
6,810.3
(888.8)
5,921.5
2011
5,745.7
326.5
4.4
461.5
36.6
127.7
6,702.3
(905.0)
5,797.3
States. Sinks are only
included in net emissions total. Please refer to Table 2-9 for a breakout by source.
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
Energy-related activities, primarily fossil fuel combustion, accounted for the vast majority of U.S. CCh emissions for
the period of 1990 through 2011. In 2011, approximately 87 percent of the energy consumed in the United States
(on a Btu basis) was produced through the combustion of fossil fuels. The remaining 13 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 CC>2 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 (43
percent and 11 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.
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 2-5: 2011Energy Chapter Greenhouse Gas Sources
Fossil Fuel Combustion
Natural Gas Systems
Non-Energy Use of Fuels
Coal Mining
Petroleum Systems
Stationary Combustion
Mobile Combustion |
Incineration of Waste |
Abandoned Underground Coal Mines |
5,277
Energy as a Portion
of all Emissions
0
50
100
Tg C02 Eq.
ISO
200
Figure 2-6: 2011 U.S. Fossil Carbon Flows (Tg COz Eq.)
Table 2-4: Emissions from Energy (Tg COz Eq.)
Gas/Source
CO2
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
Natural Gas Systems
Incineration of Waste
1990
4,912.0
4,748.5
1,820.8
1,494.0
848.6
338.3
219.0 4
27.9 ^
117.4'
37.7 '-
8.0
2005
5,934.1
•* 5,748T/
2,402.1
. 1,891.7
823.4
357.9
1 223.5 •
k 50.0
* 142.7
29.9
12.5
2007
5,946.4
5,767.7
2,412.8
1,904.7
844.4
341.6
218.9
45.2
134.9
30.9
12.7
2008
5,774.9
5,590.6
2,360.9
1,816.0
802.0
347.0
223.8
41.0
139.5
32.6
11.9
2009
5,390.6
5,222.4
2,146.4
1,749.2
722.6
337.0
223.4
43.8
124.0
32.2
11.7
2010
5,585.6
5,408.1
2,259.2
1,763.9
780.2
334.6
220.6
49.6
132.8
32.3
12.0
2011
5,452.5
5,277.2
2,158.5
1,745.0
773.2
328.8
222.1
49.7
130.6
32.3
12.0
Trends 2-9
-------
Petroleum Systems
Biomass - Wood"
International Bunker Fuelsb
Biomass - Ethanol"
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal
Mobile Combustion
Incineration of Waste
International Bunker Fuelsb
N20
Stationary Combustion
Mobile Combustion
Incineration of Waste
International Bunker Fuelsb
Total
0.4
214.4
103.5
4.2
298.6
161.2 .,
84.1-
35.2
7.5
6.0
4.6,
+ .',
o.i ' .
56.8
44.0,,"'
12.3' •
0.5'
0.9
5,267.3
0.3
205.7
113.1
22.9
259.7
159.0
56.9
29.2
6.6
5.5
2.4
+
0.1
57.9
36.9
! 20.6
0.4
1.0
6,251.6
0.3
199.4
115.3
38.9
269.9
168.4
57.9
29.8
6.4
5.3
2.1
+
0.1
50.6
29.0
21.2
0.4
1.0
6,266.9
0.3
197.0
114.3
54.7
274.4
163.4
67.1
30.0
6.6
5.3
1.9
+
0.1
46.9
25.5
21.1
0.4
1.0
6,096.2
0.3
182.8
106.4
62.3
264.8
150.7
70.3
30.5
6.3
5.1
1.8
+
0.1
43.8
22.7
20.7
0.4
0.9
5,699.2
0.3
191.8
117.0
72.6
259.9
143.6
72.4
30.8
6.3
5.0
1.8
+
0.1
43.6
20.7
22.6
0.4
1.0
5,889.1
0.3
191.8
111.3
72.8
252.3
144.7
63.2
31.5
6.3
4.8
1.7
+
0.1
40.8
18.5
22.0
0.4
1.0
5,745.7
+ Does not exceed 0.05 Tg CO2 Eq.
a Emissions from Wood Biomass and Ethanol Consumption are not included specifically in summing energy sector totals. Net
carbon fluxes from changes in biogenic carbon reservoirs are accounted for in the estimates for Land Use, Land-Use Change,
and Forestry
b Emissions from International Bunker Fuels are not included in totals.
Note: Totals may not sum due to independent rounding.
Carbon dioxide 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 CC>2 emissions from fossil fuel combustion are calculated from
these EIA "end-use sectors" based on total consumption and appropriate fuel properties (any additional analysis and
refinement of the EIA data is further explained in the Energy chapter of this report). EIA's fuel consumption data for
the electric power sector comprises electricity-only and combined-heat-and-power (CHP) plants within the NAICS
22 category whose primary business is to sell electricity, or electricity and heat, to the public (nonutility power
producers can be included in this sector as long as they meet they electric power sector definition). EIA statistics for
the industrial sector include fossil fuel consumption that occurs in the fields of manufacturing, agriculture, mining,
and construction. EIA's fuel consumption data for the transportation sector consists of all vehicles whose primary
purpose is transporting people and/or goods from one physical location to another. EIA's fuel consumption data for
the industrial sector consists of all facilities and equipment used for producing, processing, or assembling goods
(EIA includes generators that produce electricity and/or useful thermal output primarily to support on-site industrial
activities in this sector). EIA's fuel consumption data for the residential sector consists of living quarters for private
households. EIA's fuel consumption data for the commercial sector consists of service-providing facilities and
equipment from private and public organizations and businesses (EIA includes generators that produce electricity
and/or useful thermal output primarily to support the activities at commercial establishments in this sector). Table
2-5, Figure 2-7, and Figure 2-8 summarize COa emissions from fossil fuel combustion by end-use sector.
Table 2-5: COz Emissions from Fossil Fuel Combustion by End-Use Sector (Tg COz Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
1990
1,497.0
1,494.0-;" '
3.0
1,535.3
848.6 ,
686.7
931.4
338.3 ' '
593.0 ''•-
757.0
2005
1,896.5
• 1,891.7
4.7
1,560.4
823.4
737.0
1,214.7
357.9
856.7
1,027.2
: 2007
! 1,909.7
1,904.7
5.1
1,559.9
844.4
715.4
1,205.2
341.6
863.5
1,047.7
2008
1,820.7
1,816.0
4.7
1,499.3
802.0
697.3
1,189.9
347.0
842.9
1,039.8
2009
1,753.7
1,749.2
4.5
1,324.6
722.6
602.0
1,123.5
337.0
786.5
976.8
2010
1,768.4
1,763.9
4.5
1,421.3
780.2
641.1
1,175.0
334.6
840.4
993.9
2011
1,749.3
1,745.0
4.3
1,392.1
773.2
618.9
1,125.6
328.8
796.9
960.5
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Combustion
Electricity
U.S. Territories3
Total
Electricity Generation
219.0 -
538.0 ,
27.9 «•
4,748.5
1,820.8
223.5 *w
803.7 ,, .
50.0
5,748.7
2,402.1
218.9
828.8
45.2
; 5,767.7
2,412.8
223.8
816.0
41.0
5,590.6
2,360.9
223.4
753.5
43.8
5,222.4
2,146.4
220.6
773.3
49.6
5,408.1
2,259.2
222.1
738.4
49.7
5,277.2
2,158.5
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.
a 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.
Figure 2-7: 2011 COz Emissions from Fossil Fuel Combustion by Sector and Fuel Type
o
2,500
2,000
1,500
I'OOO
500
0
Relative Contribution
by Fuel Type
2,159
50
222
Pebolann
•Coal
• NataialGas
329
1,745
773
is
3
.S
•s
1
01
3
Figure 2-8: 2011 End-Use Sector Emissions from Fossil Fuel Combustion
2,000 -
1,500 -
iff
8 1,000 -
500 -
0 -
From Direct Fossil Fuel Combustion
•From Electricity Consumption
968
50
.1
v
ui
1,769
,3
8
1,401
1,137
c
Hi
13
*?B
&
3
T3
.a
a
The main driver of emissions in the Energy sector is CO2 from fossil fuel combustion. Electricity generation is the
largest emitter of €62, and electricity generators consumed 36 percent of U.S. energy from fossil fuels and emitted
41 percent of the COa from fossil fuel combustion in 2011. Electricity generation emissions can also be allocated to
the end-use sectors that are consuming that electricity, as presented in Table 2-5. The transportation end-use sector
accounted for 1,749.3 Tg CCh Eq. in 2011 or approximately 33 percent of total COa emissions from fossil fuel
combustion. The industrial end-use sector accounted for 26 percent of €62 emissions from fossil fuel combustion.
The residential and commercial end-use sectors accounted for 21 and 18 percent, respectively, of COa emissions
from fossil fuel combustion. Both of these end-use sectors were heavily reliant on electricity for meeting energy
needs, with electricity consumption for lighting, heating, air conditioning, and operating appliances contributing 71
Trends 2-11
-------
and 77 percent of emissions from the residential and commercial end-use sectors, respectively. Significant trends in
emissions from energy source categories over the twenty two-year period from 1990 through 2011 included the
following:
• Total CO2 emissions from fossil fuel combustion increased from 4,748.5 Tg CO2 Eq. in 1990 to 5,277.2 Tg
CO2 Eq. in 2011 —an 11.1 percent total increase over the twenty two -year period. From 2010 to 2011,
these emissions decreased by 130.9 Tg CO2 Eq. (2.4 percent).
• CH4 emissions from natural gas systems were 144.7 Tg CO2 Eq. in 2011; emissions have decreased by 16.5
Tg CO2 Eq. (10.2 percent) since 1990.
• CO2 emissions from non-energy use of fossil fuels increased by 13.1 Tg CO2 Eq. (11.2 percent) from 1990
through 2011. Emissions from non-energy uses of fossil fuels were 130.6 Tg CO2 Eq. in 2011, which
constituted 2.3 percent of total national CO2 emissions.
• N2O emissions from stationary combustion increased by 9.7 Tg CO2 Eq. (79.3 percent) from 1990 through
2011. N2O emissions from this source increased primarily as a result of an increase in the number of coal
fluidized bed boilers in the electric power sector.
• CO2 emissions from incineration of waste (12.0 TgCO2Eq. in 2011) increased by 4.1 TgCO2Eq. (51.0
percent) from 1990 through 2011, as the volume of plastics and other fossil carbon-containing materials in
municipal solid waste grew.
The decrease in CO2 emissions from fossil fuel combustion in 2011 was a result of multiple factors including: (1) a
decrease in the carbon intensity of fuels consumed to generate electricity due to a decrease in coal consumption,
with increased natural gas consumption and a significant increase in hydropower used; (2) a decrease in
transportation-related energy consumption due to higher fuel costs, improvements in fuel efficiency, and a reduction
in miles traveled; and (3) relatively mild winter conditions, especially in the South Atlantic Region of the United
States where electricity is an important heating fuel, resulting in an overall decrease in electricity demand.
Greenhouse gas emissions are produced as the by-products of many non-energy-related industrial activities. For
example, industrial processes can chemically transform raw materials, which often release waste gases such as CO2,
CH4, and N2O. These processes include iron and steel production and metallurgical coke production, cement
production, ammonia production, urea consumption, lime production, other process uses of carbonates (e.g., flux
stone, flue gas desulfurization, and glass manufacturing), soda ash production and consumption, 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). Industrial processes also release HFCs, PFCs and SF6. 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. Table 2-6 presents greenhouse gas emissions from industrial processes by source
category.
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 2-9: 2011 Industrial Processes Chapter Greenhouse Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Prod, & Metallurgical Coke Prod.
Cement Production
Nitric Add Production
Lime Production
Adipic Acid Production
Other Process Uses of Carbonates
Electrical Transmission and Distribution
HCFC-22 Production
Petrochemical Production
Aluminum Production
Semiconductor Manufacture
Urea Consumption for Non-Agricultural Purposes
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Magnesium Production and Processing
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production |
Silicon Carbide Production and Consumption
122
Industrial Processes as a Fortran
of all Emissions
4,9%
O
<0.5
0 10 20 30 40 50
Tg CO, Eq.
Table 2-6: Emissions from Industrial Processes (Tg COz Eq.)
Gas/Source
CO2
Iron and Steel Production &, Metallurgical Coke
Production
Iron and Steel Production
Metallurgical Coke Production
Cement Production
Lime Production
Other Process Uses of Carbonates
Ammonia Production
Urea Consumption for Non- Agricultural
Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production
Silicon Carbide Production and Consumption
CH4
Petrochemical Production
1990
188.7
99.8
97.3 ;'
2.5 :
33.3
11.5
4.9
13.0 /
3.8
3.4
6.8' .
2.8 /
1.2/
1.4
2.2
1.5. ..•
0.6 !
1.5
0.5
0.4
3.3
2.3
2005
166.3
66.7,
64.6
2.0
45.2
14.3
6.3 /
9.2
3.7'
4.3
4.1
3.0'
1.8
1.3
1.4
1.9
l.O/
1.3''
0.6
0.2
3.9
3.1
2007
/» 172.9
. 71.3
69.2
2.1
44.5
14.6
7.4
9.1
4.9
4.1
4.3
2.9
1.9
1.9
1.6
1.5
1.0
1.2
0.6
0.2
4.0
3.3
60
2008
160.3
66.8
64.5
2.3
40.5
14.3
5.9
7.9
4.1
3.6
4.5
3.0
1.8
1.8
1.6
1.5
1.2
1.1
0.5
0.2
3.6
2.9
70
2009
119.0
43.0
42.1
1.0
29.0
11.2
7.6
7.9
3.4
2.8
3.0
2.6
1.6
1.8
1.5
1.0
0.9
1.0
0.5
0.1
3.3
2.9
2010
141.4
55.7
55.7
2.1
30.9
13.1
9.6
8.7
4.4
3.5
2.7
2.7
1.8
2.2
1.7
1.5
1.2
1.1
0.5
0.2
3.6
3.1
2011
151.3
64.3
62.8
1.4
31.6
13.8
9.2
8.8
4.3
3.5
3.3
2.7
1.9
1.8
1.7
1.3
1.3
1.2
0.5
0.2
3.7
3.1
Trends 2-13
-------
Iron and Steel Production & Metallurgical Coke
Iron and Steel Production
Metallurgical Coke Production
Ferroalloy Production
Silicon Carbide Production and Consumption
N20
Nitric Acid Production
Adipic Acid Production
HFCs
Substitution of Ozone Depleting Substances3
HCFC-22 Production
Semiconductor Manufacture
PFCs
Semiconductor Manufacture
Aluminum Production
SF6
Electrical Transmission and Distribution
Semiconductor Manufacture
Magnesium Production and Processing
Total
1.0
1.0 ,4
+
+ -.
+ ~
34.0
18.2 -*.
15.8 '
36.9
0.3
36.4 *
0.2
20.6
18.4
2.2
32.6
26.7
0.5 -*1
5.4
316.1
0.7
i 0.7
+
+ /
+
24.4
16. 9 /
7.4
115.0
99.0 /
i 15.8
0.2
6.2
3.0,
3.2
15.0
; 11.1 /
* 1.0
2.9
330.8
: 0.7
0.7
+
+
+
30.4
19.7
10.7
120.0
102.7
17.0
0.3
7.7
3.8
3.8
12.3
8.8
0.8
2.6
347.2
0.6
0.6
+
+
+
19.4
16.9
2.6
117.5
103.6
13.6
0.3
6.6
2.7
3.9
11.4
8.6
0.9
1.9
318.7
0.4
0.4
+
+
+
16.8
14.0
2.8
112.0
106.3
5.4
0.2
4.4
1.6
2.9
9.8
8.1
0.7
1.1
265.3
0.5
0.5
+
+
+
21.1
16.8
4.4
121.3
114.6
6.4
0.4
5.9
1.6
4.4
10.1
7.8
1.0
1.3
303.4
0.6
0.6
+
+
+
26.1
15.5
10.6
129.0
121.7
6.9
0.3
7.0
2.9
4.1
9.4
7.0
0.9
1.4
326.5
+ Does not exceed 0.05 Tg CO2 Eq.
a Small amounts of PFC emissions also result from
this source.
Overall, emissions from the Industrial Processes sector increased by 3.3 percent from 1990 to 2011. Significant
trends in emissions from industrial processes source categories over the twenty-two-year period from 1990 through
2011 included the following:
• Combined CC>2 and CH4 emissions from iron and steel production and metallurgical coke production
increased by 15.2 percent to 64.8 Tg CO2 Eq. from 2010 to 2011, but have declined overall by 35.9 Tg
CO2 Eq. (35.6 percent) from 1990 through 2011, due to restructuring of the industry, technological
improvements, and increased scrap steel utilization.
• CO2 emissions from ammonia production (8.8 Tg CCh Eq. in 2011) decreased by 4.3 Tg CC>2 Eq. (32.6
percent) since 1990. This is due to a decrease in domestic ammonia production primarily attributed to
market fluctuations. Urea consumption for non-agricultural purposes (4.3 Tg CCh Eq. in 2011) increased by
0.5 Tg CO2 Eq. (14.4 percent) since 1990.
• N2O emissions from adipic acid production were 10.6 Tg CC>2 Eq. in 2011, and have decreased
significantly in recent years due to the widespread installation of pollution control measures. Emissions
from adipic acid production have decreased by 32.9 percent since 1990 and by 39.6 percent since a peak in
1995.
• HFC emissions from ODS substitutes have been increasing from small amounts in 1990 to 121.7 Tg CCh
Eq. in 2011. This increase results from efforts to phase out CFCs and other OD S' 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.
• PFC emissions from aluminum production decreased by about 84.0 percent (15.5 Tg COa Eq.) from 1990
to 2011, due to both industry emission reduction efforts and lower domestic aluminum production.
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. greenhouse gas emissions in 2011 (see Table 2-7).
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 2-7: NzO Emissions from Solvent and Other Product Use (Tg COz Eq.)
Gas/Source
N20
N2O from Product Uses
Total
1990
4.4
4.4
4.4
2005
4.4
4.4
4.4 4
2007
4.4
4.4
4.4
2008
4.4
4.4
4.4
2009
4.4
4.4
4.4
2010
4.4
4.4
4.4
2011
4.4
4.4
4.4
In 2011, N2O emissions from product uses constituted 1.2 percent of U.S. N2O emissions. From 1990 to 2011,
emissions from this source category decreased by 0.4 percent, though slight increases occurred in intermediate
years.
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 2011, agricultural activities were responsible for emissions of 461.5 Tg €62 Eq., or 6.9 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 23.4 percent and 8.9 percent of total
CH4 emissions from anthropogenic activities, respectively, in 2011. Agricultural soil management activities, such as
fertilizer application and other cropping practices, were the largest source of U.S. N2O emissions in 2011,
accounting for 69.3 percent.
Figure 2-10: 2011 Agriculture Chapter Greenhouse Gas Sources
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation •
Field Burning of Agricultural Residues < 0.5
247
Agriculture as a Portion of all Emissions
0 50
Tg C02 Eq.
Table 2-8: Emissions from Agriculture (Tg COz Eq.)
100
ISO
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural
Residues
N2O
1990 ,
171.5 ,4
132.7 /
31.5
7.1 ,
0.2
242.3
2005 !
191.5
137.0
47.6
6.8
0.2 •
254.7
2007
200.5
141.8
52.4
6.2
0.2
270.4
2008
200.3
141.4
51.5
7.2
0.2
263.3
2009
198.6
140.6
50.5
7.3
0.2
260.6
2010
199.9
139.3
51.8
8.6
0.2
262.4
2011
196.3
137.4
52.0
6.6
0.2
265.2
Trends 2-15
-------
Agricultural Soil Management
Manure Management
Field Burning of Agricultural
Residues
Total
227.9 I
14.4
0.1 /
413.9 ;
237.5 „
17.1
0.1
446.2 «
252.3
18.0
0.1
470.9
245.4
17.8
0.1
463.6
242.8
17.7
0.1
459.2
244.5
17.8
0.1
462.3
247.2
18.0
0.1
461.5
Note: Totals may not sum due to independent rounding.
Some significant trends in U.S. emissions from Agriculture source categories include the following:
• Agricultural soils produced approximately 69.3 percent of N2O emissions in the United States in 2011.
Estimated emissions from this source in 2011 were 247.2 Tg CO2 Eq. Annual N2O emissions from
agricultural soils fluctuated between 1990 and 2011, although overall emissions were 8.5 percent higher in
2011 than in 1990. Nitrous oxide emissions from this source have not shown any significant long-term
trend, as their estimation is highly sensitive to the amount of N applied to soils, which has not changed
significantly over the time-period, and to weather patterns and crop type.
• Enteric fermentation was the second largest source of CH4 emissions in the United States in 2011, at 137.4
Tg COa Eq. Generally, from 1990 to 1995 emissions increased and then decreased from 1996 to 2001.
These trends were mainly due to fluctuations in beef cattle populations and increased digestibility of feed
for feedlot cattle. Emissions generally increased from 2002 to 2007, though with a slight decrease in 2004.,
as both dairy and beef populations underwent increases and the literature for dairy cow diets indicated a
trend toward a decrease in feed digestibility for those years. Emissions decreased again from 2008 to 2011
as beef cattle populations again decreased. Regarding trends in other animals, during the timeframe of this
analysis, populations of sheep have decreased 52 percent while horse populations have almost doubled,
with each annual increase ranging from about 2 to 6 percent. Goat and swine populations have increased 25
percent and 22 percent, respectively, during this timeframe, though with some slight annual decreases. The
populations of American bison and mules, burros, and donkeys have more than tripled and quadrupled,
respectively.
• Overall, emissions from manure management increased 52.8 percent between 1990 and 2011. This
encompassed an increase of 65.3 percent for CH4, from 31.5 TgCO2Eq. in 1990 to 52.0 TgCO2Eq. in
2011; and an increase of 25.3 percent for N2O, from 14.4 Tg CO2 Eq. in 1990 to 18.0 Tg CO2 Eq. in 2011.
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.
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 13.5
percent of total U.S. greenhouse gas emissions in 2011. Forests (including vegetation, soils, and harvested wood)
accounted for approximately 92 percent of total 2011 net CO2 flux, urban trees accounted for 8 percent, mineral and
organic soil carbon stock changes accounted for 1 percent, and landfilled yard trimmings and food scraps accounted
for 1 percent of the total net flux in 2011. 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 5 times as much C as is emitted from these soils through liming and urea fertilization. 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
and food scraps carbon in landfills.
Land use, land-use change, and forestry activities in 2011 resulted in a net C sequestration of 905.0 Tg CO2 Eq.
(246.8 Tg C) (Table 2-9). This represents an offset of approximately 16.1 percent of total U.S. CO2 emissions, or
13.5 percent of total greenhouse gas emissions in 2011. Between 1990 and 2011, total land use, land-use change,
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
and forestry net C flux resulted in a 13.9 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, and
harvested wood pools.
Table 2-9: Net COz Flux from Land Use, Land-Use Change, and Forestry (Tg COz 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 ;
(696.8) /!
(34.1)/
21.0
(5.3) .
(7.7) /
(47.5)
(24.2) .-
(794.5)
2005 „
(905.0) 1
(20.3)
13.5
(1.0)
(10.2)
(63.2)
(11.6)
(997.8)
2007
(859.3)
(6.6)
14.5
7.1
(9.0)
(65.0)
(10.9)
(929.2)
2008
(833.3)
(5.2)
14.5
7.2
(9.0)
(66.0)
(10.9)
(902.6)
2009
(811.3)
(4.6)
14.5
7.3
(8.9)
(66.9)
(12.7)
(882.6)
2010
(817.6)
(3.0)
14.5
7.3
(8.8)
(67.9)
(13.3)
(888.8)
2011
(833.5)
(2.9)
14.5
7.4
(8.8)
(68.8)
(13.0)
(905.0)
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 8.1 Tg CO2 Eq. in
2011, an increase of about 14.6 percent relative to 1990. Lands undergoing peat extraction resulted in €62
emissions of 0.9 TgCO2Eq. (918 Gg), andN2O emissions of less than 0.05 TgCO2Eq. N2O emissions from the
application of synthetic fertilizers to forest soils have increased from 0.1 Tg CO2 Eq. in 1990 to 0.4 Tg CO2 Eq. in
2011. Settlement soils in 2011 resulted in direct N2O emissions of 1.5 TgCO2Eq., a 51 percent increase relative to
1990. Emissions fromforest fires in2011 resulted in CH4 emissions of 14.2 Tg CO2 Eq., and inN2O emissions of
11.6 Tg CO2 Eq. (Table 2-10).
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg COz Eq.)
Source Category
CO2
Cropland Remaining Cropland: Liming of Agricultural
Soils
Cropland Remaining Cropland: Urea Fertilization
Wetlands Remaining Wetlands: Peatlands Remaining
Peatlands
CH4
Forest Land Remaining Forest Land: Forest Fires
N2O
Forest Land Remaining Forest Land: Forest Fires
Forest Land Remaining Forest Land: Forest Soils
Settlements Remaining Settlements: Settlement Soils
Wetlands Remaining Wetlands: Peatlands Remaining
Peatlands
Total
1990
8.1
4.7
2.4
1.0
2.5
2.5
3.1
2.0
0.1
1.0
13.7
: 2005
8.9
4.3
3.5
1.1
8.0
8.0
8.4
6.6
0.4
1.5
25.4
, 2007
' 9.2
.-'" 4.5
3.8
.-•'• i.o
14.4
14.4
13.7
11.7
0.4
1.6
• 37.3
2008
9.6
5.0
3.6
1.0
8.7
8.7
8.9
7.1
0.4
1.5
27.2
2009
8.3
3.7
3.6
1.1
5.7
5.7
6.4
4.7
0.4
1.4
20.4
2010
9.4
4.7
3.7
1.0
4.7
4.7
5.6
3.8
0.4
1.5
19.7
2011
9.0
4.5
3.7
0.9
14.2
14.2
13.4
11.6
0.4
1.5
36.6
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Other significant trends from 1990 to 2011 in emissions from land use, land-use change, and forestry source
categories include:
• Net C sequestration by forest land (i.e., carbon stock accumulation in the five carbon pools) has increased
by approximately 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
Trends 1-M
-------
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 20 years, although only at an average rate of 0.2 percent per year.
Net sequestration of C by urban trees has increased by 44.9 percent over the period from 1990 to 2011.
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 46.2 percent since
1990. This is due in part to a decrease in the amount of yard trimmings and food scraps generated. In
addition, the proportion of yard trimmings and food scraps landfilled has decreased, as there has been a
significant rise in the number of municipal composting facilities in the United States.
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 2-11). In 2011,
landfills were the third largest source of U.S. anthropogenic CH4 emissions, accounting for 17.5 percent of total U.S.
CH4 emissions.45 Additionally, wastewater treatment accounts for 16.7 percent of Waste emissions, 2.8 percent of
U.S. CH4 emissions, and 1.5 percent of NaO emissions. Emissions of CEU and N2O from composting grew from
1990 to 2011, and resulted in emissions of 3.3 Tg CO2 Eq. in 2011. A summary of greenhouse gas emissions from
the Waste chapter is presented in Table 2-11.
Figure 2-11: 2011 Waste Chapter Greenhouse Gas Sources
Landfills
Wastewater Treatment
Waste as a Portion of all Emissions
1.9%
Composting
I
40
60
Tg C02 Eq,
80
100
120
Overall, in 2011, waste activities generated emissions of 127.7 Tg CCh Eq., or 1.9 percent of total U.S. greenhouse
gas emissions.
Table 2-11: Emissions from Waste (Tg COz Eq.)
Gas/Source
CH4
Landfills
1990
164.0
147.8
2005
130.5
112.5
2007
129.8
111.6
2008
131.9
113.6
2009
131.4
113.3
2010
124.7
106.8
2011
120.8
103.0
Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as
described in the Land Use, Land-Use Change, and Forestry chapter.
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Wastewater Treatment
Composting
N2O
Wastewater Treatment
Composting
Total
15.9 ,
0.3
3.8
3.5
0.4 ~
164.0
16.5 ;
1.6
6.4
4.7 /
1.7
130.5
: 16.6
1.7
6.7
4.8
1.8
136.5
16.6
1.7
6.8
4.9
1.9
138.6
16.5
1.6
6.7
5.0
1.8
138.1
16.4
1.5
6.8
5.1
1.7
131.4
16.2
1.5
6.9
5.2
1.7
127.7
Note: Totals may not sum due to independent rounding.
Some significant trends in U.S. emissions from waste source categories include the following:
• From 1990 to 2011, net CH4 emissions from landfills decreased by 44.7 Tg €62 Eq. (30.3 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 as well as reduction in the amount of
decomposable materials (i.e., paper and paperboard, food scraps, and yard trimmings) discarded in MSW
landfills over the time series,46 which has more than offset the additional CH4 emissions resulting from an
increase in the amount of municipal solid waste landfilled.
• Combined CH4 and N2O emissions from composting have generally increased since 1990, from 0.7 Tg €62
Eq. to 3.3 Tg €62 Eq. in 2011, which represents slightly less than a five-fold increase over the time series.
• From 1990 to 2011, CH4 and N2O emissions from wastewater treatment increased by 0.2 Tg €62 Eq. (1.6
percent) and 1.7 Tg €62 Eq. (49.7 percent), respectively.
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 (33 percent) of
U.S. greenhouse gas emissions in 2011. Transportation activities, in aggregate, accounted for the second largest
portion (27 percent). Emissions from industry accounted for about 20 percent of U.S. greenhouse gas emissions in
2011. 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 20 percent of U.S. greenhouse gas emissions were contributed by the residential, agriculture, and
commercial sectors, plus emissions from U.S. territories. The residential sector accounted for 5 percent, and
primarily consisted of CCh 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 CCh
from fossil fuel combustion. The commercial sector accounted for roughly 6 percent of emissions, while U.S.
territories accounted for less than 1 percent. Carbon dioxide was also emitted and sequestered (in the form of C) 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 2011.
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.
Trends 2-19
-------
Figure 2-12: Emissions Allocated to Economic Sectors
Ef
2,500 -
2,000 -
i'500 -
1,000 -
500 -
Electric
Power Industry
Transportation
Industry
Agriculture
• Commercial (Black)
Residential (Grey)
rsl nJ
-------
Urea Consumption for Non- Agricultural
Purposes
Stationary Combustion
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Magnesium Production and Processing
Mobile Combustion
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production
Silicon Carbide Production and
Consumption
Agriculture
N2O from Agricultural Soil Management
Enteric Fermentation
Manure Management
CO2 from Fossil Fuel Combustion
CELi and N2O from Forest Fires
Rice Cultivation
Liming of Agricultural Soils
Urea Fertilization
CO2 and N2O from Managed Peatlands
Mobile Combustion
Stationary Combustion
N2O from Forest Soils
Field Burning of Agricultural Residues
Commercial
CO2 from Fossil Fuel Combustion
Landfills
Substitution of Ozone Depleting
Substances
Wastewater Treatment
Human Sewage
Composting
Stationary Combustion
Residential
CO2 from Fossil Fuel Combustion
Substitution of Ozone Depleting
Substances
Stationary Combustion
Settlement Soil Fertilization
U.S. Territories
CO2 from Fossil Fuel Combustion
Non-Energy Use of Fuels
Stationary 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
Note: Includes all emissions of CO2, CLU,
sum due to independent rounding.
3.8
4.9
2.8
1.2
1.4
2.2
5.4
0.9
1.5
0.6
1.5
0.5
0.4
458.0
227.9
132.7
45.8
31.0
4.5
7.1
4.7
2.4
1.0
0.3
0.1
0.3
+
388.1
219.0
147.8
+
15.9,
3.5
0.7
1.3
345.4
338.3
0.3
5.7,
1.0
33.7
27.9
5.7
0.1
6,183.3
(794.5)
(696.8)
(47.5)-
(24.2)
(26.0)
5,388.7
N20, HFCs,
„
3.7
4.6
3.0
1.8
1.3
1.4
2.9
1.3
1.9
1.0
1.3
0.6
0.2
517.4
237.5
137.0
64.6
46.8
14.6
6.8
4.3
3.5
1.1
0.5
0.4
0.2
+
374.1
223.5
112.5
12.3
16.5
4.7
3.3
1.3
371.3
357.9
7.3
4.6
1.5
58.2
50.0
8.1
0.2
7,195.3
, (997.8)
(905.0)
. (63.2)
/ (H.6)
(18.0)
6,197.4
PFCs, and SFe.
4.9
4.5
2.9
1.9
1.9
1.6
2.6
1.3
1.5
1.0
1.2
0.6
0.2
555.6
252.3
141.8
70.3
48.4
26.1
6.2
4.5
3.8
1.0
0.5
0.4
0.3
+
372.0
218.9
111.6
15.4
16.6
4.8
3.5
1.3
358.2
341.6
10.7
4.4
1.6
52.6
45.2
7.2
0.2
' 7,263.2
I (929.2)
(859.3)
. (65.0)
(10.9)
6.0
6,334.0
4.1
4.2
3.0
1.8
1.8
1.6
1.9
1.3
1.5
1.2
1.1
0.5
0.2
535.3
245.4
141.4
69.3
45.4
15.7
7.2
5.0
3.6
1.0
0.5
0.4
0.3
+
380.9
223.8
113.6
17.2
16.6
4.9
3.5
1.3
366.0
347.0
12.9
4.7
1.5
49.8
41.0
8.7
0.2
7,048.8
(902.6)
(833.3)
(66.0)
(10.9)
7.6
6,146.2
3.4
3.7
2.6
1.6
1.8
1.5
1.1
1.3
1.0
0.9
1.0
0.5
0.2
525.4
242.8
140.6
68.2
46.7
10.4
7.3
3.7
3.6
1.1
0.5
0.4
0.3
+
382.9
223.4
113.3
20.1
16.5
5.0
3.3
1.3
358.1
337.0
15.1
4.5
1.4
47.9
43.8
3.9
0.2
6,586.6
(882.6)
(811.3)
(66.9)
(12.7)
8.3
5,704.0
4.4
4.1
2.7
1.8
2.2
1.7
1.3
1.4
1.5
1.2
1.1
0.5
0.2
528.7
244.5
139.3
69.5
47.6
8.5
8.6
4.7
3.7
1.0
0.5
0.4
0.3
+
376.9
220.6
106.8
23.6
16.4
5.1
3.2
1.3
359.6
334.6
19.1
4.4
1.5
58.0
49.6
8.2
0.2
6,810.3
(888.8)
(817.6)
(67.9)
(13.3)
10.0
5,921.5
4.3
4.0
2.7
1.9
1.8
1.7
1.4
1.4
1.3
1.3
1.2
0.5
0.2
546.6
247.2
137.4
70.0
49.4
25.7
6.6
4.5
3.7
0.9
0.5
0.4
0.3
+
378.0
222.1
103.0
27.0
16.2
5.2
3.3
1.3
357.3
328.8
22.6
4.4
1.5
58.0
49.7
8.2
0.2
6,702.3
(905.0)
(833.5)
(68.8)
(13.0)
10.3
5,797.3
Parentheses indicate negative values or sequestration.
0.1%
0.1%
+
+
+
+
+
+
+
+
+
+
+
8.2%
3.7%
2.0%
1.0%
0.7%
0.4%
0.1%
0.1%
0.1%
+
+
+
+
+
5.6%
3.3%
1.5%
0.4%
0.2%
0.1%
+
+
5.3%
4.9%
0.3%
0.1%
+
0.9%
0.7%
0.1%
+
100.0%
-13.5%
-12.4%
-1.0%
-0.2%
0.2%
86.5%
Totals may not
Trends 2-21
-------
ODS (Ozone Depleting Substances)
+ Does not exceed 0.05 Tg CO2 Eq. or 0.05 percent.
a Percent of total emissions for year 2011.
blncludes the effects of net additions to stocks of carbon stored in harvested wood products.
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 33 percent of total U.S. greenhouse gas
emissions in 2011. Emissions increased by 18 percent since 1990, as electricity demand grew and fossil fuels
remained the dominant energy source for generation. Electricity generation-related emissions decreased from 2010
to 2011 by 4.4 percent, primarily due to decreased CC>2 emissions from fossil fuel combustion. Electricity sales to
the residential and commercial end-use sectors in 2011 decreased approximately 1.5 percent and 0.8 percent,
respectively. The trend in the residential and commercial sectors can largely be attributed to milder, less energy-
intensive winter conditions compared to 2010. Electricity sales to the industrial sector in 2011 increased
approximately 0.5 percent. Overall, in 2011, the amount of electricity generated (in kWh) decreased by 0.8 percent
from the previous year. As a result, CCh emissions from the electric power sector decreased by 4.4 percent as the
consumption of coal and petroleum for electricity generation decreased by 5.7 percent and 19.9 percent,
respectively, in 2011 and the consumption of natural gas for electricity generation, increased by 2.5 percent. Table
2-13 provides a detailed summary of emissions from electricity generation-related activities.
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg COz Eq.)
Gas/Fuel Type or Source
CO2
Fossil Fuel Combustion
Coal
Natural Gas
Petroleum
Geothermal
Incineration of Waste
Other Process Uses of
Carbonates
CH4
Stationary Combustion*
Incineration of Waste
N2O
Stationary Combustion*
Incineration of Waste
SF6
Electrical Transmission and
Distribution
Total
1990
1,831.2
1,820.8
1,547.6
175.3
97.5
0.4
8.0
2.5
0.3
0.3
+ -
7.8
7.4-
0.5 ,
26.7
26.7
1,866.1
2005
2,417.8
2,402.1
1,983.8
318.8
99.2
0.4
12.5
3.2
0.5
0.5
+
16.4
16.0
0.4
11.1
11.1
. 2,445.7
, 2007
< 2,429.2
2,412.8
1,987.3
, 371.3
53.9
0.4
12.7
3.7
0.5
0.5
+
17.1
16.7
0.4
8.8
8.8
2,455.6
2008
2,375.7
2,360.9
1,959.4
361.9
39.2
0.4
11.9
2.9
0.5
0.5
+
17.2
16.8
0.4
8.6
8.6
2,402.0
2009
2,161.9
2,146.4
1,740.9
372.2
33.0
0.4
11.7
3.8
0.4
0.4
+
17.2
16.8
0.4
8.1
8.1
2,187.6
2010
2,276.0
2,259.2
1,827.6
399.0
32.2
0.4
12.0
4.8
0.5
0.5
+
18.8
18.5
0.4
7.8
7.8
2,303.0
2011
2,175.1
2,158.5
1,722.7
408.8
26.6
0.4
12.0
4.6
0.4
0.4
+
18.3
17.9
0.4
7.0
7.0
2,200.9
Note: Totals may not sum due to independent rounding.
* Includes only stationary combustion emissions related to the generation of electricity.
+ Does not exceed 0.05 Tg CO2 Eq.
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 each economic sector's share of retail sales of electricity consumption
(EIA 2011 and Duffield 2006). These source categories include CCh from Fossil Fuel Combustion, CH4 and N2O
from Stationary Combustion, Incineration of Waste, Other Process Uses of Carbonates, and SF6 from Electrical
Transmission and Distribution Systems. Note that only 50 percent of the Other Process Uses of Carbonates
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
emissions were associated with electricity generation and distributed as described; the remainder of Other Process
Uses of Carbonates emissions were attributed to the industrial processes economic end-use sector.47
When emissions from electricity are distributed among these sectors, industry activities account for the largest share
of total U.S. greenhouse gas emissions (28.3 percent), followed closely by emissions from transportation (27.4
percent). Emissions from the residential and commercial sectors also increase substantially when emissions from
electricity are included. In all sectors except agriculture, CCh accounts for more than 80 percent of greenhouse gas
emissions, primarily from the combustion of fossil fuels.
Table 2-14 presents a detailed breakdown of emissions from each of these economic sectors, with emissions from
electricity generation distributed to them. Figure 2-13 shows the trend in these emissions by sector from 1990 to
2011.
Figure 2-13: Emissions with Electricity Distributed to Economic Sectors
2,500 -,
2,000 -
1,500
1,000 -
500 -
Industry
Transportation
Residential (Black)
Commercial (Gray)
>" Agriculture
CPioicnaiaioicnCTicncioooooooaoooo
-rHT-jT-iT-)-rH-r-4THT-jTH-iHfNjr^fN|r^f\lfMfMfNJO4fNlrslrvi
Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-
Related Emissions Distributed (Tg COz Eq.) and Percent of Total in 2011
Sector/Gas
Industry
Direct Emissions
C02
CH4
N20
HFCs, PFCs, and
Electricity-Related
CO2
CH4
N2O
SFe
Transportation
Direct Emissions
CO2
CH4
N2O
HFCsb
1990
2,181.3
1,538.8
1,146.5
291.5
42.4 ' "
58.4
642.4 •
630.4
0.1
2.7
9.2 ,
1,556.3
1,553.2
1,505.8
4.4
43.03 ••
+ '
2005
2,102.4
1,416.2,
1,096.3
256.2
33.0
30.6 /
686.2
"• 678.4
0.1
4.6 /
3.1
2,017.2
; 2,012.3
1,901.9
2.1
35.43
72.9
2007
2,113.6
1,456.1
1,115.4
267.0
39.0
34.6
657.5
650.4
0.1
4.6
2.4
2,018.2
/ 2,013.1
1,914.9
1.8
27.54
68.8
2008
2,036.3
1,398.8
1,068.9
271.0
27.8
31.1
637.6
630.6
0.1
4.6
2.3
1,920.8
1,916.0
1,825.5
1.6
23.96
64.9
2009
1,789.8
1,244.2
935.3
261.4
24.9
22.6
545.7
539.3
0.1
4.3
2.0
1,845.2
1,840.6
1,757.7
1.5
21.17
60.2
2010
1,916.9
1,331.8
1,017.2
256.9
29.5
28.3
585.0
578.2
0.1
4.8
2.0
1,856.9
1,852.3
1,773.4
1.5
19.08
58.4
2011
1,897.2
1,332.0
1,016.7
249.5
34.4
31.5
565.1
558.5
0.1
4.7
1.8
1,833.7
1,829.4
1,754.0
1.4
16.88
57.1
Percent3
28.3%
19.9%
15.2%
3.7%
0.5%
0.5%
8.4%
8.3%
+
0.1%
+
27.4%
27.3%
26.2%
+
0.3%
0.9%
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 2-23
-------
Electricity-Related
C02
CH4
N20
SFe
Commercial
Direct Emissions
C02
CH4
N20
HFCs
Electricity -Related
CO2
CH4
N2O
SFe
Residential
Direct Emissions
CO2
CH4
N2O
HFCs
Electricity -Related
C02
CH4
N20
SFe
Agriculture
Direct Emissions
CO2
CH4
N2O
Electricity -Related
CO2
CH4
N2O
SFe
U.S. Territories
Total
3.1 .
3.1
+
+ '
+
939.5
388.1
219.0
164.9
4.2 '
+ ,
551.4 ••
541.1
0.1
2.3
7.9
953.1
345.4
338.3
4.6, ,
2.1
0.3 ,
607.8
596.4
0.1
2.6 :
8.7
519.4
458.0 .
39.2 '
174.1
244.7
61.4.
60.2
+
0.3
0.9
33.7
6,183.3
4.8
4.8
+
+ /
+ '
1,192.4
374.1 ,
223.5 ••'
131.5
6.8
12.3 ,
818.3
808.9
0.2
5.5 /
3.7''
1,243.6
371.3
357.9 /
3.6
2.4
7.3
872.3 /'
862.3
0.2
5.8
4.0 /''
581.6
517.4
55.7 ,
199.7,
262.0
64.1
63.4 ,
+ ..•'
0.4
0.3
58.2
7,195.3
: 5.2
5.1
+
+
+
1,215.6
372.0
218.9
130.8
7.0
15.4
843.5
834.5
0.2
5.9
3.0
1,237.1
, 358.2
341.6
3.5
2.5
10.7
878.8
869.4
0.2
6.1
3.2
626.2
555.6
57.7
215.1
282.8
70.6
69.9
+
0.5
0.3
52.6
„ 7,263.2
4.8
4.7
+
+
+
1,211.1
380.9
223.8
132.8
7.1
17.2
830.2
821.2
0.2
5.9
3.0
1,223.6
366.0
347.0
3.7
2.4
12.9
857.6
848.2
0.2
6.1
3.1
607.1
535.3
55.1
209.1
271.1
71.8
71.0
+
0.5
0.3
49.8
7,048.8
4.6
4.5
+
+
+
1,150.8
382.9
223.4
132.4
7.1
20.1
767.9
758.9
0.2
6.0
2.8
1,159.6
358.1
337.0
3.6
2.3
15.1
801.6
792.2
0.2
6.3
3.0
593.3
525.4
55.0
204.4
266.0
67.9
67.1
+
0.5
0.3
47.9
6,586.6
4.6
4.5
+
+
+
1,165.2
376.9
220.6
125.6
7.1
23.6
788.3
779.0
0.2
6.4
2.7
1,216.3
359.6
334.6
3.5
2.4
19.1
856.7
846.7
0.2
7.0
2.9
597.1
528.7
57.0
204.7
266.9
68.5
67.7
+
0.6
0.2
58.0
6,810.3
4.3
4.3
+
+
+
1,131.0
378.0
222.1
121.7
7.2
27.0
752.9
744.1
0.2
6.3
2.4
1,169.8
357.3
328.8
3.5
2.4
22.6
812.5
803.0
0.2
6.8
2.6
612.6
546.6
58.5
210.6
277.6
65.9
65.2
+
0.5
0.2
58.0
6,702.3
0.1%
0.1%
+
+
+
16.9%
5.6%
3.3%
1.8%
0.1%
0.4%
11.2%
11.1%
+
0.1%
+
17.5%
5.3%
4.9%
0.1%
+
0.3%
12.1%
12.0%
+
0.1%
+
9.1%
8.2%
0.9%
3.1%
4.1%
1.0%
1.0%
+
+
+
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 2011.
b Includes primarily HFC-134a.
The industrial end-use sector includes CCh 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 includes
methane emissions from petroleum and natural gas systems, fugitive CH4 emissions from coal mining, by-product
CO2 emissions from cement manufacture, and HFC, PFC, and SF6 by-product emissions from semiconductor
manufacture, to name a few. Since 1990, industrial sector emissions have declined. The decline has occurred both
in direct emissions and indirect emissions associated with electricity use. However, the decline in direct emissions
has been sharper. 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
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 effect on industrial emissions.
When electricity-related emissions are distributed to economic end-use sectors, transportation activities accounted
for 27 percent of U.S. greenhouse gas emissions in 2011. The largest sources of transportation greenhouse gases in
2011 were passenger cars (41.2 percent), light duty trucks, which include sport utility vehicles, pickup trucks, and
minivans (17.4 percent), freight trucks (21.0 percent), rail (6.5 percent), and commercial aircraft (6.1 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.
Although average fuel economy over this period increased slightly due primarily to the retirement of older vehicles,
average fuel economy among new vehicles sold annually gradually declined from 1990 to 2004. The decline in new
vehicle fuel economy between 1990 and 2004 reflected the increasing market share of light duty trucks, which grew
from about one -fifth of new vehicle sales in the 1970s to slightly over half of the market by 2004. Increasing fuel
prices have since decreased overall light duty truck sales, and average new vehicle fuel economy has improved since
2005 as the market share of passenger cars increased. Over the 1990s through early this decade, growth in vehicle
travel substantially outweighed improvements in vehicle fuel economy; however, the rate of Vehicle Miles Traveled
(VMT) growth slowed considerably starting in 2005 (and declined rapidly in 2008) while average vehicle fuel
economy increased. In 2011, fuel VMT fell by 0.7 percent.48 Additionally, consumption of diesel fuel has
continued to decrease recently, due in part to a decrease in commercial activity and freight trucking as a result of the
economic recession. Table 2-15 provides a detailed summary of greenhouse gas emissions from transportation-
related activities with electricity-related emissions included in the totals.
In terms of the overall trend, from 1990 to 2011, transportation emissions rose by 19 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 34 percent from
1990 to 2011, as a result of a confluence of factors including population growth, economic growth, urban sprawl,
and low fuel prices over much of this period.
Then, from 2008 to 2009, CCh emissions from the transportation end-use sector declined 4 percent. The decrease in
emissions can largely be attributed to decreased economic activity in 2009 and an associated decline in the demand
for transportation. Modes such as medium- and heavy-duty trucks were significantly impacted by the decline in
freight transport. From 2009 to 2011, CC>2 emissions from the transportation end-use sector stabilized even as
economic activity rebounded slightly.
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 17 percent from 1990 to
2011. This rise inCO2 emissions, combined with an increase inHFCs from close to zero emissions in 1990 to 57.1
Tg COa Eq. in 2011, led to an increase in overall emissions from transportation activities of 18 percent.
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)
Gas/Vehicle
Passenger Cars
C02
1990
657.4
629.3
2005
709.5
662.3
2007
847.4
804.4
2008
807.0
769.3
2009
798.7
766.0
2010
794.1
763.8
2011
787.4
759.0
48 VMT and fuel use by vehicle class (VM-1 table) were not available from FHWA for 2011, but trends in overall diesel and
gasoline consumption were released in FHWA's Table MF-21 and MF-27. Fuel use in vehicle classes that are predominantly
gasoline was estimated to fall by the rate of decrease in gasoline consumption between 2010 and 2011. Fuel use in vehicle
classes that were predominantly diesel was estimated to grow by the same rate of diesel fuel consumption increase in 2011. The
2010-2011 change in VMT from FHWA's Traffic Volume Trends was then distributed to vehicle classes based on these fuel
consumption estimates, assuming no relative change in MPG between vehicle classes.
Trends 2-25
-------
CH4
N2O
HFCs
Light-Duty Trucks
C02
CH4
N2O
HFCs
Medium- and Heavy-Duty
Trucks
C02
CH4
N2O
HFCs
Buses
C02
CH4
N2O
HFCs
Motorcycles
C02
CH4
N2O
Commercial Aircraft3
C02
CH4
N2O
Other Aircraftb
C02
CH4
N2O
Ships and Boats0
C02
CH4
N2O
HFCs
Rail
C02
CH4
N2O
HFCs
Other Emissions from
Electricity Generation"1
Pipelines6
C02
Lubricants
CO2
Total Transportation
International Bunker Fuel/
2.6-
25.4
+
336.6
321.1'-'
1.4
14.1
+
231.1
230.1
0.2'
0.8
+
8.4
8.4'
+
+ •
+
1.8
1.7-
+ '.
+
110.9
109.9
+ ,
1.1,
78.3
77.5'
0.1
0.7,
45.1
44.5
+
0.6
+ r
39.0
38.5
0.1
0.3
+ '
0.1
36.0
36.0 ,
11.8
11.8
1,556.3
104.5
1.1
17.8
28.4
551.3
505.9
0.7
13.7
31.0
408.4
396.0
0.1
1.1
11.1
12.1
:.,, 11.8
+
+
0.2
1.7
1.6
+
+
134.0
132.7
+
1.3
59.7
59.1
+
0.6
45.2
44.5
+
0.6
+
53.0
50.3
0.1
0.4
2.2
0.1
32.2
32.2
10.2
10.2
2,017.2
114.3
1.1
17.3
24.6
366.4
330.1
0.3
5.9
30.1
444.7
431.6
0.1
1.4
11.5
18.0
17.6
+
+
0.3
4.3
4.3
+
+
141.0
139.7
+
1.3
42.4
42.0
+
0.4
55.2
54.4
+
0.8
+
54.4
51.6
0.1
0.4
2.2
0.1
34.2
34.2
10.2
10.2
2,018.2
116.5
1.0
14.7
22.1
347.0
312.8
0.3
5.2
28.6
427.0
413.9
0.1
1.4
11.6
17.4
17.0
+
+
0.4
4.5
4.4
+
+
128.5
127.3
+
1.2
48.2
47.8
+
0.4
45.4
44.7
+
0.6
+
50.7
47.9
0.1
0.4
2.3
+
35.6
35.6
9.5
9.5
1,920.8
115.5
0.9
12.4
19.3
349.5
317.4
0.3
5.2
26.6
389.2
376.3
0.2
1.1
11.6
16.5
16.1
+
+
0.4
4.3
4.2
+
+
120.7
119.5
+
1.1
36.8
36.4
+
0.3
40.8
40.2
+
0.6
+
43.4
40.7
0.1
0.3
2.3
+
36.7
36.7
8.5
8.5
1,845.2
107.5
0.9
10.9
18.6
348.0
317.6
0.3
4.7
25.4
402.9
390.0
0.1
1.1
11.6
16.3
15.9
+
+
0.4
3.8
3.8
+
+
114.4
113.3
+
1.1
40.5
40.1
+
0.4
44.1
43.4
+
0.6
+
46.3
43.5
0.1
0.3
2.3
+
37.1
37.1
9.5
9.5
1,856.9
118.2
0.8
9.4
18.3
331.4
302.6
0.3
4.0
24.5
401.1
388.3
0.1
1.0
11.7
17.4
16.9
+
+
0.4
3.7
3.6
+
+
115.7
114.6
+
1.1
34.2
33.8
+
0.3
48.2
47.4
+
0.7
+
48.0
45.3
0.1
0.4
2.3
+
37.7
37.7
9.0
9.0
1,833.7
112.4
Note: Totals may not sum due to independent rounding. Passenger cars and light-duty trucks include vehicles
typically used for personal travel and less than 8500 Ibs; medium- and heavy-duty trucks include vehicles larger than
8500 Ibs. HFC emissions primarily reflect HFC-134a.
+ Does not exceed 0.05 Tg CO2 Eq.
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.
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
d Other emissions from electricity generation are a result of waste incineration (as the majority of municipal solid
waste is combusted in "trash-to-steam" electricity generation plants), electrical transmission and distribution, and a
portion of Other Process Uses of Carbonates (from pollution control equipment installed in electricity generation
plants).
e CO2 estimates reflect natural gas used to power pipelines, but not electricity. While the operation of pipelines
produces CFLi and N2O, these emissions are not directly attributed to pipelines in the US Inventory.
f Emissions from International Bunker Fuels include emissions from both civilian and military activities; these
emissions are not included in the transportation totals.
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 and wastewater treatment emissions increasing slightly.
The residential sector is heavily reliant on electricity for meeting energy needs, with electricity consumption for
lighting, heating, air conditioning, and operating appliances. The remaining emissions were largely due to the direct
consumption of natural gas and petroleum products, primarily for heating and cooking needs. Emissions from the
residential sectors have generally been increasing since 1990, and are often correlated with short-term fluctuations in
energy consumption caused by weather conditions, rather than prevailing economic conditions. In the long-term,
this sector is also affected by population growth, regional migration trends, and changes in housing and building
attributes (e.g., size and insulation).
The agriculture sector includes a variety of processes, including enteric fermentation in domestic livestock, livestock
manure management, and agricultural soil management. In 2011, agricultural soil management was the largest
source of N2O emissions, and enteric fermentation was the second largest source of CH4 emissions in the United
States. This sector also includes small amounts of COa emissions from fossil fuel combustion by motorized farm
equipment like tractors. The agriculture sector is less reliant on electricity than the other sectors.
In presenting the Economic Sectors in the annual Inventory of U.S. Greenhouse Gas Emissions and Sinks, the
Inventory expands upon the standard IPCC sectors common for UNFCCC reporting. 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 COa, CH4, and N2O
from waste incineration, as the majority of municipal solid waste is combusted in "trash-to-steam" electricity
generation plants. The Electricity Generation economic sector also includes SF6 from Electrical Transmission and
Distribution, and a portion of CCh from Other Process Uses of Carbonates (from pollution control equipment
installed in electricity generation plants).
In the Transportation economic sector, the CCh 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
Trends 2-27
-------
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 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 Metallurgical Coke Production, and Ammonia Production.
Additionally, fugitive emissions from energy production sources, such as Natural Gas Systems, Coal Mining, and
Petroleum Systems are included in the Industry economic sector. A portion of CO2 from Other Process Uses of
Carbonates (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.
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
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 2011; (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 0.4 percent
since 1990. This rate is slightly faster than that for total energy consumption and slightly slower than growth in
national population since 1990 and much slower than that for electricity consumption and overall gross domestic
product, respectively. Total U.S. greenhouse gas emissions are growing at a rate similar to that of fossil fuel
consumption since 1990 (see Table 2-16).
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100)
Chapter/IPCC Sector
Greenhouse Gas Emissions e
Energy Consumption °
Fossil Fuel Consumption c
Electricity Consumption c
GDPb
Population d
1990
100
100-,v
100
100 '•:
100. .
100
2005 ,
116
119
119
134 /
157
118
2007
117
120
119
137
165
121
2008
114
117
116
136
164
122
2009
107
111
109
131
159
123
2010
110
115
112
137
163
124
2011 Growth3
108
102
101
136
166
125
0.4%
0.1%
0.1%
1.5%
2.5%
1.1%
a Average annual growth rate
b Gross Domestic Product in chained 2005 dollars (BEA 2012)
0 Energy-content-weighted values (EIA 2012)
d U.S. Census Bureau (2012)
e GWP-weighted values
Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic
Product
a
1
170 -]
160 -
ISO -
140 -
130
120 -
110 -
100 -
90
80 -
70
60 J
Real GDP
Population
Emissions
per capita
Emissions
per $GDP
Source: BEA (2011), U.S. Census Bureau (2011), and emission estimates in this report.
Trends 2-29
-------
The reporting requirements of the UNFCCC49 request that information be provided on indirect greenhouse gases,
which include CO, NOX, NMVOCs, and SCh. 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 SCh, 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, SOa 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.
Since 1970, the United States has published estimates of emissions of CO, NOX, NMVOCs, and SO2 (EPA 2010,
EPA 2009),50 which are regulated under the Clean Air Act51. 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 SOz (Gg)
Gas/Activity
NOx
Mobile Fossil Fuel Combustion
Stationary Fossil Fuel Combustion
Industrial Processes
Forest Land Reminaing Forest Land
Oil and Gas Activities
Waste Combustion
Agricultural Burning
Solvent Use
Waste
CO
Mobile Fossil Fuel Combustion
Forest Land Reminaing Forest Land
1990
21,781
10,862-
10,023
591 '
76
139
82
6
1
+
132,671
119,360
2,695
2005
21,305
9,012
5,858
569.-'
102
321 .
129 /
6
3
2 /'
112,21
62,692
3,650
, 2007
1 14,817
7,965
•" 5,432
537
436
318
114
8
4
2
79,180
55,253
15,568
2008
13,809
7,441
5,148
520
263
318
106
7
4
2
69,387
51,533
9,394
2009
11,641
6,206
4,159
568
173
393
128
7
3
2
57,611
43,355
6,180
2010
11,610
6,206
4,159
568
142
393
128
8
3
2
56,494
43,355
5,062
2011
11,897
6,206
4,159
568
431
393
128
7
3
2
66,773
43,355
15,364
49 See .
50 NOX and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken
from EPA (2009) and EPA (2010).
Due to redevelopment of the information technology systems for the National Emission Inventory (NEI), publication of the
most recent emissions for these pollutants was not available for this report. For an overview of the activities and the schedule for
developing the 2011 National Emissions Inventory, with the goal of producing Version 1 in the summer o f 2013, see <
http://www.epa.gov/ttn/chief/eis/201 lnei/201 lplan.pdf>
2-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Stationary Fossil Fuel Combustion
Industrial Processes
Waste Combustion
Oil and Gas Activities
Agricultural Burning
Waste
Solvent Use
NMVOCs
Mobile Fossil Fuel Combustion
Solvent Use
Industrial Processes
Oil and Gas Activities
Stationary Fossil Fuel Combustion
Waste Combustion
Waste
Agricultural Burning
S02
Stationary Fossil Fuel Combustion
Industrial Processes
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Waste
Solvent Use
Agricultural Burning
5,000
4,125'
978
302
205
1'.
5
20,930
10,932
5,216-
2,422
554
912
222'
673'
NA .'
20,935
18,407
1,307
793
390,
38 ,
+
* 4,649
1,555
- 1,403
318 /
166
7
2 /
13,761
6,330
., 3,851
, ' 1,997 /
510
716
241 -
114-
:, NA'
13,466
11,541
'• ' 831-
889
181
24 /
1 /
* 4,744
1,640
.. 1,421
320
225
7
2
13,423
5,742
3,839
1,869
509
1,120
234
111
NA
11,799
10,172
807
611
184
24
1
4,792
1,682
1,430
322
224
7
2
13,254
5,447
3,834
1,804
509
1,321
230
109
NA
10,368
8,891
795
472
187
23
1
4,543
1,549
1,403
345
226
7
2
9,313
4,151
2,583
1,322
599
424
159
76
NA
8,599
7,167
798
455
154
24
1
4,543
1,549
1,403
345
227
7
2
9,313
4,151
2,583
1,322
599
424
159
76
NA
8,599
7,167
798
455
154
24
1
4,543
1,549
1,403
345
205
7
2
9,313
4,151
2,583
1,322
599
424
159
76
NA
8,599
7,167
798
455
154
24
1
NA
NA
NA NA
NA
NA NA
Source: (EPA 2010, EPA 2009) except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg.
Sulfur dioxide (SCh) 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 862 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 862 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 SCh emissions in the Clean Air Act.
Electricity generation is the largest anthropogenic source of SCh emissions in the United States, accounting for 60
percent in 2011. 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.
Trends 2-31
-------
-------
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting for
85.7 percent of total greenhouse gas emissions on a carbon dioxide (CCh) equivalent basis in 2011.52 This included
97, 43, and 11 percent of the nation's CCh, methane (CH4), and nitrous oxide (N2O) emissions, respectively.
Energy-related CCh emissions alone constituted 81 percent of national emissions from all sources on a CCh
equivalent basis, while the non-CCh emissions from energy-related activities represented a much smaller portion of
total national emissions (4.4 percent collectively).
Emissions from fossil fuel combustion comprise the vast majority of energy-related emissions, with €62 being the
primary gas emitted (see Figure 3-1). Globally, approximately 31,780 Tg of CCh were added to the atmosphere
through the combustion of fossil fuels in 2010, of which the United States accounted for about 18 percent.53 Due to
their relative importance, fossil fuel combustion-related CCh emissions are considered separately, and in more detail
than other energy-related emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N2O. Stationary
combustion of fossil fuels was the second largest source of N2O emissions in the United States and mobile fossil fuel
combustion was the third largest source.
Figure 3-1: 2011 Energy Chapter Greenhouse Gas Sources
Fossil Fuel Combustion
Natural Gas Systems
Non-Energy Use of Fuels
Coal Mining
Petroleum Systems
Stationary Combustion
Mobile Combustion I
Incineration of Waste I
Abandoned Underground Coal Mines |
5,277
Energy as a Portion
of all Emissions
50
100
TgCO2Eq.
ISO
200
52 Estimates are presented in units of teragrams of carbon dioxide equivalent (Tg CCh Eq.), which weight each gas by its global
warming potential, or GWP, value. See section on global warming potentials in the Executive Summary.
Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Statistics 2011 < http://tonto.eia.doe.gov/cfapps/ipdbproject/IEDIndex3.cfm> EIA (2011).
Energy 3-1
-------
Figure 3-2: 2011 U.S. Fossil Carbon Flows (Tg COz 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. Table 3-1 summarizes emissions from the Energy sector in units of
teragrams (or million metric tons) of CO2 equivalents (Tg CCh Eq.), while unweighted gas emissions in gigagrams
(Gg) are provided in Table 3-2. Overall, emissions due to energy-related activities were 5,745.7 Tg CC>2 Eq. in
2011, an increase of 9. Ipercent since 1990.
Table 3-1: COz, Cm, and NzO Emissions from Energy (Tg COz Eq.)
Gas/Source
CCh
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
Natural Gas Systems
Incineration of Waste
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
Incineration of Waste
1990
4,912.0
4,748.5
1,820.8
1,494.0
848.6
338.3
219.0 :
27.9 '•
Ill A
37.7
8.0
0.4
214.4
103.5
4.2
298.6
161.2
84.1
35.2
7.5
6.0
4.6 .
+ •
2005
5,934.1
5,748.7
2,402.1 .
1,891.7
823.4 .
357.9
223.5 ' ••
50.0
142.7
29.9 :
12.5 /
0.3 ./
205. 7 '
113.1 ':
22.9 : :
259.7
159.0
56.9
29.2
6.6
5.5
2.4 .
+ . •'
2007
5,946.4
5,767.7
2,412.8
1,904.7
844.4
341.6
218.9
45.2
134.9
30.9
12.7
0.3
199.4
115.3
38.9
269.9
168.4
57.9
29.8
6.4
5.3
2.1
+
2008
5,774.9
5,590.6
2,360.9
1,816.0
802.0
347.0
223.8
41.0
139.5
32.6
11.9
0.3
197.0
114.3
54.7
274.4
163.4
67.1
30.0
6.6
5.3
1.9
+
2009
5,390.6
5,222.4
2,146.4
1,749.2
722.6
337.0
223.4
43.8
124.0
32.2
11.7
0.3
182.8
106.4
62.3
264.8
150.7
70.3
30.5
6.3
5.1
1.8
+
2010
5,585.6
5,408.1
2,259.2
1,763.9
780.2
334.6
220.6
49.6
132.8
32.3
12.0
0.3
191.8
117.0
72.6
259.9
143.6
72.4
30.8
6.3
5.0
1.8
+
2011
5,452.5
5,277.2
2,158.5
1,745.0
773.2
328.8
222.1
49.7
130.6
32.3
12.0
0.3
191.8
111.3
72.8
252.3
144.7
63.2
31.5
6.3
4.8
1.7
+
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
International Bunker Fuels"
N2O
Mobile Combustion
Stationary Combustion
Incineration of Waste
International Bunker Fuels"
Total
0.1
56.8
44.0
12.3
0.5
0.9 /
5,267.3
0-1
57.9
36.9
20.6
0.4
1.0 /
6,251.6
0-1
50.6
29.0
21.2
0.4
1.0
, 6,266.9
0.1
46.9
25.5
21.1
0.4
1.0
6,096.2
0.1
43.8
22.7
20.7
0.4
0.9
5,699.2
0.1
43.6
20.7
22.6
0.4
1.0
5,889.1
0.1
40.8
18.5
22.0
0.4
1.0
5,745.7
+ Does not exceed 0.05 Tg CCh Eq.
a These values are presented for informational purposes only, in line with IPCC methodological guidance and UNFCCC reporting
obligations, and are not included in the specific energy sector contribution to the totals, and are already accounted for elsewhere.
Note: Totals may not sum due to independent rounding.
Table 3-2: COz, CH4, and N2O Emissions from Energy (Gg)
Gas/Source
1990
2005
2007
2008
2009
2010
2011
C02 4,911,977 5,934,056 5,946,414 5,774,919 5,390,591 5,585,642 5,452,528
Fossil Fuel Combustion 4,748,532 5,748,674 / 5,767,654 5,590,638 5,222,419 5,408,119 5,277,246
Non-Energy Use of
Fuels 117,414 142,701 134,887 139,484 123,977 132,839 130,554
Natural Gas Systems 37,665 29,923 / 30,851 32,622 32,187 32,313 32,344
Incineration of Waste 7,972 12,452 12,711 11,876 11,688 12,038 12,038
Petroleum Systems 394 , 306 311 300 320 332 347
Biomass-Wood" 214,410 205,708 199,383 196,995 182,785 191,811 191,764
International Bunker
Fuels" 103,463 ' 113,139 115,345 114,342 106,410 116,992 111,316
Biomass-Ethanol" 4,227 22,943 38,924 54,739 62,272 72,648 72,763
CH4 14,220 12,365 12,853 13,067 12,610 12,375 12,016
Natural Gas Systems 7,678 7,572 / 8,018 7,782 7,178 6,838 6,893
Coal Mining 4,003 . 2,710 / 2,756 3,196 3,348 3,447 3,011
Petroleum Systems 1,677 1,390 1,421 1,431 1,455 1,467 1,499
Stationary Combustion 355 , 315 305 313 298 301 300
Abandoned
Underground Coal
Mines 288 264 254 253 244 237 231
Mobile Combustion 218 113 100 92 88 85 82
Incineration of Waste + + + + + + +
International Bunker
Fuels" 7 '. 5 5 6 5 6 5
N2O 183 187 163 151 141 141 132
Mobile Combustion 142 119 94 82 73 67 60
Stationary Combustion 40 66 / 68 68 67 73 71
Incineration of Waste 2 1 1 1 1 1 1
International Bunker
Fuels" 3 3 3_ 3 3 3 3_
+ Does not exceed 0.05 Tg CO2 Eq.
a These values are presented for informational purposes only, in line with IPCC methodological guidance and UNFCCC reporting
obligations, and are not included in the specific energy sector contribution to the totals, and are already accounted for elsewhere.
Note: Totals may not sum due to independent rounding.
It is noted that in this chapter the methodological guidance was primarily taken from the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories. The use of the most recently published calculation methodologies by the
IPCC, as contained in the 2006 IPCC Guidelines, is fully in line with the IPCC good practice guidance for
methodological choice to improve rigor and accuracy. In addition, the improvements in using the latest
methodological guidance from the IPCC has been recognized by the UNFCCC's Subsidiary Body for Scientific and
Technological Advice in the conclusions of its 30th Session, Numerous U.S. inventory experts were involved in the
Energy 3-3
-------
development of the 2006 IPCC Guidelines, and their expertise has provided this latest guidance from the IPCC with
the most appropriate calculation methods that are then used in this chapter.54
In following the UNFCCC requirement under Article 4.1 to develop and submit national greenhouse gas emission
inventories, the emissions and sinks presented in this report and this chapter, are organized by source and sink
categories and calculated using internationally-accepted methods provided by the Intergovernmental Panel on
Climate Change (IPCC). Additionally, the calculated emissions and sinks in a given year for the United States are
presented in a common manner in line with the UNFCCC reporting guidelines for the reporting of inventories under
this international agreement. The use of consistent methods to calculate emissions and sinks by all nations
providing their inventories to the UNFCCC ensures that these reports are comparable. In this regard, U.S. emissions
and sinks reported in this inventory report are comparable to emissions and sinks reported by other countries.
Emissions and sinks provided in this inventory do not preclude alternative examinations, but rather this inventory
presents emissions and sinks in a common format consistent with how countries are to report inventories under the
UNFCCC. The report itself, and this chapter, follows this standardized format, and provides an explanation of the
IPCC methods used to calculate emissions and sinks, and the manner in which those calculations are conducted.
On October 30, 2009, the U.S. Environmental Protection Agency (EPA) published a rule for the mandatory
reporting of greenhouse gases (GHG) from large GHG emissions sources in the United States. Implementation of 40
CFR Part 98 is referred to as the Greenhouse Gas Reporting Program (GHGRP). 40 CFR Part 98 applies to direct
greenhouse gas emitters, fossil fuel suppliers, industrial gas suppliers, and facilities that inject CO2 underground for
sequestration or other reasons. Reporting is at the facility level, except for certain suppliers of fossil fuels and
industrial greenhouse gases. 40 CFR part 98 requires reporting by 41 industrial categories. Data reporting by
affected facilities included the reporting of emissions from fuel combustion at that affected facility. In general, the
threshold for reporting is 25,000 metric tons or more of CO2 Eq. per year.
The GHGRP dataset and the data presented in this inventory report are complementary and, as indicated in the
respective planned improvements sections for source categories in this chapter, EPA is analyzing how to use
facility-level GHGRP data to improve the national estimates presented in this Inventory (see, also, Box 3-1). Most
methodologies used in the GHGRP are consistent with IPCC, though for the GHGRP, facilities collect detailed
information specific to their operations according to detailed measurement standards, which may differ with the
more aggregated data collected for the inventory to estimate total, national U.S. emissions. It should be noted that
the definitions and provisions for reporting fuel types in the GHGRP may differ from those used in the inventory in
meeting the UNFCCC reporting guidelines. In line with the UNFCCC reporting guidelines, the inventory report is a
comprehensive accounting of all emissions from fuel types identified in the IPCC guidelines and provides a separate
reporting of emissions from biomass. Further information on the reporting categorizations in GHGRP and specific
data caveats associated with monitoring methods in the GHGRP has been provided on the GHGRP website.
EPA presents the data collected by the GHGRP through a data publication tool that allows data to be viewed in
several formats including maps, tables, charts and graphs for individual facilities or groups of facilities.
54 These Subsidiary Body for Scientific and Technological Advice (SBSTA) conclusions state, "The SBSTA acknowledged that
the 2006 IPCC Guidelines contain the most recent scientific methodologies available to estimate emissions by sources and
removals by sinks of greenhouse gases (GHGs) not controlled by the Montreal Protocol, and recognized that Parties have gained
experience with the 2006 IPCC Guidelines. The SBSTA also acknowledged that the information contained in the 2006 IPCC
Guidelines enables Parties to further improve the quality of their GHG inventories." See
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Emissions from the combustion of fossil fuels for energy include the gases CC>2, CH4, and N2O. Given that CCh is
the primary gas emitted from fossil fuel combustion and represents the largest share of U.S. total emissions, COa
emissions from fossil fuel combustion are discussed at the beginning of this section. Following that is a discussion
of emissions of all three gases from fossil fuel combustion presented by sectoral breakdowns. Methodologies for
estimating CO2 from fossil fuel combustion also differ from the estimation of CH4 and N2O emissions from
stationary combustion and mobile combustion. Thus, three separate descriptions of methodologies, uncertainties,
recalculations, and planned improvements are provided at the end of this section. Total COa, CH4, and N2O
emissions from fossil fuel combustion are presented in Table 3-3 and Table 3-4.
Table 3-3: COz, Cm, and NzO Emissions from Fossil Fuel Combustion (Tg COz Eq.)
Gas
CO2
CH4
N2O
Total
1990
4,748.5
12.0 -
56.3
4,816.9
2005
5,748.7
9.0
57.5
5,815.2
2007
5,767.7
8.5
50.2
; 5,826.4
2008
5,590.6
8.5
46.6
5,645.7
2009
5,222.4
8.1
43.4
5,273.9
2010
5,408.1
8.1
43.3
5,459.5
2011
5,277.2
8.0
40.5
5,325.8
Table 3-4: COz, Cm, and NzO Emissions from Fossil Fuel Combustion (Gg)
Gas
CO2
CH4
N20
1990
4,748,532
574
182
2005
5,748,674
429
186
2007
' 5,767,654
404
162
2008
5,590,638
405
150
2009
5,222,419
385
140
2010
5,408,119
386
140
2011
5,277,246
382
131
Note: Totals may not sum due to independent rounding
CO2 is the primary gas emitted from fossil fuel combustion and represents the largest share of U.S. total greenhouse
gas emissions. CC>2 emissions from fossil fuel combustion are presented in Table 3-5. In 2011, CCh emissions from
fossil fuel combustion decreased by 2.4 percent relative to the previous year. The decrease in CCh emissions from
fossil fuel combustion was a result of multiple factors including: (1) a decrease in the carbon intensity of fuels
consumed to generate electricity due to a decrease in coal consumption, with increased natural gas consumption and
a significant increase in hydropower used; (2) a decrease in transportation-related energy consumption due to higher
fuel costs, improvements in fuel efficiency, and a reduction in miles traveled; and (3) relatively mild winter
conditions, especially in the South Atlantic Region of the United States where electricity is an important heating
fuel, resulting in an overall decrease in electricity demand. In 2011, CCh emissions from fossil fuel combustion
were 5,277.2 Tg CO2 Eq., or 11.1 percent above emissions in 1990 (see Table 3-5).55
Table 3-5: COz Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg COz Eq.)
Fuel/Sector
Coal
Residential
Commercial
Industrial
Transportation
Electricity Generation
1990
1,718.4
3.0
12.0
155.3
NE
1,547.6
2005
2,112.3
0.8
9.3
115.3
NE
1,983.8
; 2007
2,105.1
0.7
6.7
107.0
NE
1,987.3
2008
2,072.6
0.7
6.5
102.6
NE
1,959.4
2009
1,834.3
0.7
6.0
83.3
NE
1,740.9
2010
1,933.5
0.6
5.7
96.2
NE
1,827.6
2011
1,821.9
0.5
5.1
90.1
NE
1,722.7
55 An additional discussion of fossil fuel emission trends is presented in the Trends in U.S. Greenhouse Gas Emissions Chapter.
Energy 3-5
-------
U.S. Territories
Natural Gas
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Geothermal*
Total
0.6
1,000.3
238.0
142.1
408.9
36.0
175.3
NO
2,029.4
97.4
64.9
284.4
1,457.9
97.5
27.2
0.4
4,748.5
: 3.o
1,166.7
. 262.2
162.9
388.5
33.1
318.8
1.3
2,469.3
94.9
51.3
319.6
1,858.7
99.2
45.7
0.4
5,748.7
!: 3.4
1,226.3
, 256.3
163.5
398.6
35.2
371.3
1.4
2,435.8
84.6
48.7
338.7
1,869.5
53.9
40.4
0.4
' 5,767.7
3.4
1,237.9
265.5
171.1
401.0
36.7
361.9
1.6
2,279.8
80.7
46.1
298.4
1,779.3
39.2
36.0
0.4
5,590.6
3.4
1,216.6
258.8
168.9
377.3
37.9
372.2
1.5
2,171.1
77.6
48.5
261.9
1,711.3
33.0
39.0
0.4
5,222.4
3.4
1,276.0
258.6
167.7
411.1
38.1
399.0
1.5
2,198.2
75.4
47.2
273.0
1,725.8
32.2
44.7
0.4
5,408.1
3.5
1,290.3
254.6
170.4
416.3
38.8
408.8
1.5
2,164.6
73.6
46.7
266.8
1,706.2
26.6
44.7
0.4
5,277.2
NE (Not estimated)
* Although not technically a fossil fuel, geothermal energy-related CCh emissions are included for
reporting purposes.
Note: Totals may not sum due to independent rounding.
Trends in COa 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, size of houses, and number of houses),
the efficiency with which energy is used in equipment (e.g., cars, power plants, steel mills, and light bulbs), and
social planning and consumer behavior (e.g., walking, bicycling, or telecommuting to work instead of driving).
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.56 Table 3-6
shows annual changes in emissions during the last five years for coal, petroleum, and natural gas in selected sectors.
Table 3-6: Annual Change in COz Emissions and Total 2011 Emissions from Fossil Fuel
Combustion for Selected Fuels and Sectors (Tg COz Eq. and Percent)
Sector Fuel Type
Electricity Generation Coal
Electricity Generation Natural Gas
Electricity Generation Petroleum
Transportation3 Petroleum
Residential Natural Gas
Commercial Natural Gas
Industrial Coal
Industrial Natural Gas
All Sectors" All Fuels"
2007 to 2008
-27.9 -1.4%
-9.3 -2.5%
-14.7 -27.2%
-90.2 -4.8%
9.3 3.6%
7.6 4.6%
-4.4 -4.1 o/o
2.4 0.6%
-177.0 -3.1%
2008 to 2009
-218.5 -11.2%
10.3 2.8%
-6.3 -15.9%
-68.0 -3.8%
-6.7 -2.5%
-2.2 -1.3%
-19.3 -18.8%
-23.7 -5.9%
-368.2 -6.6%
2009 to 2010
86.7 5.0%
26.8 7.2%
-0.8 -2.3%
14.5 0.8%
-0.3 -0.1%
-1.2 -0.7%
12.8 15.4%
33.8 9.0%
185.7 3.6%
2010 to 2011
-104.9 -5.7%
9.8 2.5%
-5.6 -17.4%
-19.5 -1.1%
-3.9 -1.5%
2.6 1.6%
-6.0 -6.3%
5.2 1.3%
-130.9 -2.4%
Total 2011
1,722.7
408.8
26.6
1,706.2
254.6
170.4
90.1
416.3
5,277.2
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
56 Based on national aggregate carbon content of all coal, natural gas, and petroleum fuels combusted in the United States.
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
In the United States, 87 percent of the energy consumed in 2011 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 (7 percent) and by a variety of renewable energy sources (6 percent), primarily
hydroelectric power and biofuels (EIA 2013).57 Specifically, petroleum supplied the largest share of domestic
energy demands, accounting for 40 percent of total U.S. energy consumption in 2011. Natural gas and coal
followed in order of energy demand importance, each accounting for approximately 23 percent of total U.S. energy
consumption, respectively. Petroleum was consumed primarily in the transportation end-use sector and the vast
majority of coal was used in electricity generation. Natural gas was broadly consumed in all end-use sectors except
transportation (see Figure 3-5) (EIA 2013).
Figure 3-3: 2011 U.S. Energy Consumption by Energy Source
Renewable
Energy
Nuclear Electric 5.5%
Power
7.3%
Renewable energy, as defined in EIA's energy statistics, includes the following energy sources: hydroelectric power,
geothermal energy, biofuels, solar energy, and wind energy
Energy 3-7
-------
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu)
Q.
E
c
o
u
120 n
100
60
m -
Total Energy
Fossil Fuels
Renewable & Nuclear
Figure 3-5: 2011 COz Emissions from Fossil Fuel Combustion by Sector and Fuel Type
2,SOO -i
2,000 -
iff 1,5
500 -
0 -
SO
o
r
222
!? Petroleum
•Coal
• Natural Gas
1,745
2,159
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 CCh and smaller amounts of other gases,
including CH4, CO, and NMVOCs.58 These other C containing non-CCh gases are emitted as a byproduct of
incomplete fuel combustion, but are, for the most part, eventually oxidized to CCh in the atmosphere. Therefore, it
is assumed that all of the C in fossil fuels used to produce energy is eventually converted to atmospheric €62.
In 2011, weather conditions were relatively mild during the winter, especially in the South Atlantic Region of the
United States where electricity is an important heating fuel, resulting in an overall decrease in electricity demand.
The United States in 2011 also experienced a slightly warmer summer compared to 2010, as heating degree days
See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-CCh gas
emissions from fossil fuel combustion.
3-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
decreased (3.2 percent) and cooling degree days increased by 1.4 percent. This slight increase in cooling degree days
led to only a minor increase in electricity demand to cool homes. However the warmer winter conditions resulted in
a significant decrease in the amount of energy required for heating, with heating degree days in the United States 4.5
percent below normal (see Figure 3-6). Summer conditions were slightly warmer in 2011 compared to 2010, and
summer temperatures were much warmer than normal, with cooling degree days 21.5 percent above normal (see
Figure 3-7) (EIA 2012a).59
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States
(1950-2011)
20 -i
10 -
Normal
(4,524 Heating Degree Days)
To E
I E
99% Confidence
-20 -'
R
T-t n in rx a*
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States
(1950-2011)
||
" Q
30 -|
20 -
10
0
-10
-20
99% Confidence
Normal
(1,242 Cooling Degree Days)
en cn en
Although no new U.S. nuclear power plants have been constructed in recent years, the utilization (i.e., capacity
factors60) of existing plants in 2011 remained high at 89 percent. Electricity output by hydroelectric power plants
increased significantly in 2011 by approximately 25 percent. In recent years, the wind power sector has been
showing strong growth, such that, on the margin, it is becoming a relatively important electricity source. Electricity
generated by nuclear plants in 2011 provided approximately twice as much of the energy consumed in the United
States as hydroelectric plants (EIA 2013). Nuclear, hydroelectric, and wind power capacity factors since 1990 are
shown in Figure 3-8.
-^ 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).
60The capacity factor equals generation divided by net summer capacity. Summer capacity is defined as "The maximum output
that generating equipment can supply to system load, as demonstrated by a multi-hour test, at the time of summer peak demand
(period of June 1 through September 30)." Data for both the generation and net summer capacity are from EIA (2012a).
Energy 3-9
-------
Figure 3-8: Nuclear, Hydroelectric, and Wind Power Plant Capacity Factors in the United
States (1990-2011)
oooooooooooo
bw
In addition to the CC>2 emitted from fossil fuel combustion, CH4 and N2O are emitted from stationary and mobile
combustion as well. Table 3-7 provides an overview of the COa, CH4, and N2O emissions from fossil fuel
combustion by sector.
Table 3-7: COz, Cm, and NzO Emissions from Fossil Fuel Combustion by Sector (Tg COz Eq.)
End-Use Sector
Electricity Generation
C02
CH4
N2O
Transportation
CO2
CH4
N2O
Industrial
CO2
CH4
N20
Residential
C02
CH4
N20
Commercial
C02
CH4
N2O
U.S. Territories*
Total
1990
1,828.5
1,820.8
0.3
7.4
1,542.6
1,494.0
4.6
44.0
853.5
848.6
1.6
3.3
344.1
338.3
4.6
1.1 ,
220.2
219.0
0.9 .
0.4
28.0
4,816.9
2005
2,418.6
2,402.1
0.5 .
16.0 /
1,931.0
1,891.7
2.4 .
36.9
828.1
823.4
1.5
3.2 /'
362.5
' 357.9
3.6
1.0 /
224.8
223.5
0.9
0.4 /
50.2
5,815.2
; 2007
2,430.0
2,412.8
0.5
16.7
1,935.8
1,904.7
2.1
29.0
849.0
844.4
1.5
3.1
346.0
341.6
3.5
0.9
220.1
218.9
0.9
0.3
45.4
' 5,826.4
2008
2,378.2
2,360.9
0.5
16.9
1,843.4
1,816.0
1.9
25.5
806.3
802.0
1.4
2.9
351.6
347.0
3.7
0.9
225.0
223.8
0.9
0.3
41.1
5,645.7
2009
2,163.7
2,146.4
0.4
16.8
1,773.7
1,749.2
1.8
111
726.4
722.6
1.2
2.5
341.5
337.0
3.6
0.9
224.6
223.4
0.9
0.3
44.0
5,273.9
2010
2,278.1
2,259.2
0.5
18.5
1,786.3
1,763.9
1.8
20.7
784.3
780.2
1.3
2.7
339.0
334.6
3.5
0.9
221.9
220.6
0.9
0.3
49.8
5,459.5
2011
2,176.9
2,158.5
0.4
18.0
1,765.2
1,745.0
1.7
18.5
777.2
773.2
1.3
2.7
333.2
328.8
3.5
0.9
223.4
222.1
0.9
0.3
49.9
5,325.8
Note: Totals may not sum due to independent rounding. Emissions from
electricity generation are allocated based on aggregate national electricity
end-use sector.
fossil fuel combustion by
consumption by each
3-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
* U.S. Territories are not apportioned by sector, and emissions are total greenhouse gas emissions
from all fuel combustion sources.
Other than CO2, gases emitted from stationary combustion include the greenhouse gases CH4 and N2O and the
indirect greenhouse gases NOX, CO, and NMVOCs.61 Methane and N2O emissions from stationary combustion
sources depend upon fuel characteristics, size and vintage, along with combustion technology, pollution control
equipment, ambient environmental conditions, and operation and maintenance practices. 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. Methane emissions from stationary combustion
are primarily a function of the CH4 content of the fuel and combustion efficiency.
Mobile combustion produces greenhouse gases other than CO2, including CH4, N2O, and indirect greenhouse gases
including NOX, CO, and NMVOCs. As with stationary combustion, N2O and NOX emissions from mobile
combustion are closely related to fuel characteristics, air-fuel mixes, combustion temperatures, and the use of
pollution control equipment. N2O from mobile sources, in particular, can be formed by the catalytic processes used
to control NOX, CO, and hydrocarbon emissions. Carbon monoxide emissions from mobile combustion are
significantly affected by combustion efficiency and the presence of post-combustion emission controls. Carbon
monoxide emissions are highest when air-fuel mixtures have less oxygen than required for complete combustion.
These emissions occur especially in idle, low speed, and cold start conditions. Methane and 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).
An alternative method of presenting combustion emissions is to allocate emissions associated with electricity
generation to the sectors in which it is used. Four end-use sectors were defined: industrial, transportation,
residential, and commercial. In the table below, electricity generation emissions have been distributed to each end-
use sector based upon the sector's share of national electricity consumption, with the exception of CH4 and N2O
from transportation.62 Emissions from U.S. territories are also calculated separately due to a lack of end-use-specific
consumption data. This method assumes that emissions from combustion sources are distributed across the four end-
use sectors based on the ratio of electricity consumption in that sector. The results of this alternative method are
presented in Table 3-8.
Table 3-8: COz, Cm, and NzO Emissions from Fossil Fuel Combustion by End-Use Sector (Tg
COz Eq.)
End-Use Sector
Transportation
C02
CH4
N20
Industrial
CO2
CH4
N2O
Residential
CO2
CH4
N2O
Commercial
C02
CH4
N20
U.S. Territories*
1990
1,545.6
1,497.0
4.6
44.0
1,543.1
1,535.3
1.7
6.1
939.6
931.4
4.7
3.5
760.5
757.0
1.0
2.6
28.0
2005
1,935.8
1,896.5
2.4
36.9
1,570.1
1,560.4
1.7
8.1
1,225.1
1,214.7
3.8
6.7
1,034.0
1,027.2
1.1
5.7
50.2
2007
1,940.9
1,909.7
2.1
29.1
1,569.5
1,559.9
1.6
8.1
1,215.7
1,205.2
3.6
6.9
1,054.9
1,047.7
1.1
6.1
45.4
2008
1,848.1
1,820.7
1.9
25.5
1,508.7
1,499.3
1.5
7.9
1,200.7
1,189.9
3.9
7.0
1,047.1
1,039.8
1.1
6.2
41.1
2009
1,778.2
1,753.7
1.8
22.7
1,333.2
1,324.6
1.4
7.2
1,134.3
1,123.5
3.7
7.1
984.2
976.8
1.1
6.3
44.0
2010
1,790.8
1,768.4
1.8
20.7
1,430.8
1,421.3
1.5
8.0
1,186.4
1,175.0
3.7
7.8
1,001.6
993.9
1.1
6.7
49.8
2011
1,769.5
1,749.3
1.7
18.5
1,401.4
1,392.1
1.5
7.9
1,136.9
1,125.6
3.7
7.5
968.1
960.5
1.1
6.5
49.9
61 Sulfur dioxide (SO2) emissions from stationary combustion are addressed in Annex 6.3.
Separate calculations were performed for transportation-related CH4 and N2O. The methodology used to calculate these
emissions are discussed in the mobile combustion section.
Energy 3-11
-------
Total
4,816.9
5,815.2
5,826.4 5,645.7 5,273.9 5,459.5 5,325.8
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.
* U.S. Territories are not apportioned by sector, and emissions are total greenhouse gas emissions from all
fuel combustion sources.
Stationary Combustion
The direct combustion of fuels by stationary sources in the electricity generation, industrial, commercial, and
residential sectors represent the greatest share of U.S. greenhouse gas emissions. Table 3-9 presents CO2 emissions
from fossil fuel combustion by stationary sources. The CO2 emitted is closely linked to the type of fuel being
combusted in each sector (see Methodology section for CO2 from fossil fuel combustion). Other than CO2, gases
emitted from stationary combustion include the greenhouse gases CH4 and N2O. Table 3-10 and Table 3-11 present
CH4 and N2O emissions from the combustion of fuels in stationary sources.63 Methane and N2O emissions from
stationary combustion sources depend upon fuel characteristics, combustion technology, pollution control
equipment, ambient environmental conditions, and operation and maintenance practices. 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. Methane emissions from stationary combustion
are primarily a function of the CH4 content of the fuel and combustion efficiency. The CH4 and N2O emission
estimation methodology was revised in 2010 to utilize the facility-specific technology and fuel use data reported to
EPA's Acid Rain Program (see Methodology section for CH4 and N2O from stationary combustion). Please refer to
Table 3-7 for the corresponding presentation of all direct emission sources of fuel combustion.
Table 3-9: COz Emissions from Stationary Fossil Fuel Combustion (Tg COz Eq.)
Sector/Fuel Type
Electricity Generation
Coal
Natural Gas
Fuel Oil
Geo thermal
Industrial
Coal
Natural Gas
Fuel Oil
Commercial
Coal
Natural Gas
Fuel Oil
Residential
Coal
Natural Gas
Fuel Oil
U.S. Territories
Coal
Natural Gas
Fuel Oil
Total
1990
1,820.8
1,547.6
175.3
97.5
0.4
848.6
155.3
408.9
284.4
219.0
12.0
142.1
64.9
338.3
3.0
238.0
97.4
27.9
0.6
NO
27.2
3,254.6
! 2005
2,402.1
1,983.8
318.8
99.2
0.4
823.4
115.3
388.5
319.6
223.5
9.3
162.9
51.3
357.9
0.8
262.2
: 94.9
50.0
3.0
1.3
45.7
I 3,856.9
! 2007
2,412.8
1,987.3
371.3
53.9
0.4
844.4
107.0
398.6
338.7
218.9
6.7
163.5
48.7
341.6
0.7
256.3
: 84.6
45.2
3.4
1.4
40.4
I 3,863.0
2008
2,360.9
1,959.4
361.9
39.2
0.4
802.0
102.6
401.0
298.4
223.8
6.5
171.1
46.1
347.0
0.7
265.5
80.7
41.0
3.4
1.6
36.0
3,774.6
2009
2,146.4
1,740.9
372.2
33.0
0.4
722.6
83.3
377.3
261.9
223.4
6.0
168.9
48.5
337.0
0.7
258.8
77.6
43.8
3.4
1.5
39.0
3,473.3
2010
2,259.2
1,827.6
399.0
32.2
0.4
780.2
96.2
411.1
273.0
220.6
5.7
167.7
47.2
334.6
0.6
258.6
75.4
49.6
3.4
1.5
44.7
3,644.2
2011
2,158.5
1,722.7
408.8
26.6
0.4
773.2
90.1
416.3
266.8
222.1
5.1
170.4
46.7
328.8
0.5
254.6
73.6
49.7
3.5
1.5
44.7
3,532.2
"^ Since emission estimates for U.S. territories cannot be disaggregated by gas in Table 3-8 and Table 3-9, the values for CELi
andN2O exclude U.S. territory emissions.
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 3-10: Cm Emissions from Stationary Combustion (Tg COz Eq.)
Sector/Fuel Type
Electricity Generation
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
+ Does not exceed 0.05 Tg
1990
0.3
0.3
+ ,
0.1
+
1.6
0.3
0.2
0.2
0.9
0.9
+
0.2
0.3
0.4
4.6
0.2
0.3
0.4
3.7 '
+
+
+
+
+
7.5
; C02 Eq.
2005
0.5
0.3
+
0.1
+
1.5
0.3
0.2
0.1
0.9
0.9
+
0.2
0.3
0.5
3.6
0.1
0.3
0.5
2.8
0.1
+
0.1
+
+
6.6
2007
0.5
0.3
+
0.1
+
1.5
0.2
0.2
0.1
0.9
0.9
+
0.1
0.3
0.5
3.5
+
0.3
0.5
2.7
0.1
+
0.1
+
+
6.4
2008
0.5
0.3
+
0.1
+
1.4
0.2
0.2
0.2
0.9
0.9
+
0.1
0.3
0.5
3.7
+
0.2
0.5
2.9
0.1
+
0.1
+
+
6.6
2009
0.4
0.3
+
0.1
+
1.2
0.2
0.1
0.1
0.8
0.9
+
0.1
0.3
0.5
3.6
+
0.2
0.5
2.8
0.1
+
0.1
+
+
6.3
2010
0.5
0.3
+
0.2
+
1.3
0.2
0.1
0.2
0.9
0.9
+
0.1
0.3
0.5
3.5
+
0.2
0.5
2.8
0.1
+
0.1
+
+
6.3
2011
0.4
0.3
+
0.2
+
1.3
0.2
0.1
0.2
0.9
0.9
+
0.1
0.3
0.5
3.5
+
0.2
0.5
2.8
0.1
+
0.1
+
+
6.3
Note: Totals may not sum due to independent rounding.
Table 3-11: NzO Emissions from
Sector/Fuel Type
Electricity Generation
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
1990
7.4
6.3 -,"
0.1
1.0
+ .
3.3
0.8
0.5 '
0.2
1.8
0.4
0.1 •
0.2
0.1
0.1
1.1
+ '
0.3
0.1
0.7 •'
0.1
+
0.1
+
Stationary
2005
16.0
11.6
0.1 .
4.3 /'
+
3.2
0.6
0.5 /
0.2
1.9
0.4
+ ••'
0.1
0.1
0.1
1.0
+ ''
0.3
0.1
0.6 /
0.1
+
0.1
+ /
Combustion (Tg
, 2007
16.7
11.4
0.1
5.2
+
3.1
0.5
0.6
0.2
1.8
0.3
+
0.1
0.1
0.1
0.9
+
0.2
0.1
0.5
0.1
+
0.1
+
2008
16.8
11.6
+
5.2
+
2.9
0.5
0.5
0.2
1.7
0.3
+
0.1
0.1
0.1
1.0
+
0.2
0.1
0.6
0.1
+
0.1
+
COzEq
2009
16.8
11.2
+
5.6
+
2.5
0.4
0.4
0.2
1.6
0.3
+
0.1
0.1
0.1
0.9
+
0.2
0.1
0.6
0.1
+
0.1
+
•)
2010
18.5
12.5
+
5.9
+
2.7
0.5
0.4
0.2
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.2
0.1
0.5
0.1
+
0.1
+
2011
17.9
12.1
+
5.8
+
2.7
0.4
0.3
0.2
1.7
0.3
+
0.1
0.1
0.1
0.9
+
0.2
0.1
0.5
0.1
+
0.1
+
Energy 3-13
-------
Wood
Total
12.3
20.6
21.2
21.1
20.7
22.6
22.0
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Electricity Generation
The process of generating electricity is the single largest source of CCh emissions in the United States, representing
38 percent of total CCh emissions from all CCh emissions sources across the United States. Methane and N2O
accounted for a small portion of emissions from electricity generation, representing less than 0.1 percent and 0.8
percent, respectively. Electricity generation also accounted for the largest share of CCh emissions from fossil fuel
combustion, approximately 41 percent in 2011. Methane and N2O from electricity generation represented 6 and 45
percent of emissions from fossil fuel combustion in 2011, respectively. Electricity was consumed primarily in the
residential, commercial, and industrial end-use sectors for lighting, heating, electric motors, appliances, electronics,
and air conditioning (see Figure 3-9).
Figure 3-9: Electricity Generation Retail Sales by End-Use Sector
Residential
Commercial
1
c
.2
&
1,500 -I
1,400 -
1,300 -
1,200 -
1,100 -
1,000 -
900 -
800 J
Industrial
g
The electric power industry includes all power producers, consisting of both regulated utilities and nonutilities (e.g.
independent power producers, qualifying cogenerators, and other small power producers). For the underlying energy
data used in this chapter, the Energy Information Administration (EIA) places electric power generation into three
functional categories: the electric power sector, the commercial sector, and the industrial sector. The electric power
sector consists of electric utilities and independent power producers whose primary business is the production of
electricity,64 while the other sectors consist of those producers that indicate their primary business is something
other than the production of electricity.
The industrial, residential, and commercial end-use sectors, as presented in Table 3-8, were reliant on electricity for
meeting energy needs. The residential and commercial end-use sectors were especially reliant on electricity
consumption for lighting, heating, air conditioning, and operating appliances. Electricity sales to the residential and
commercial end-use sectors in 2011 decreased approximately 1.5 percent and 0.8 percent, respectively. The trend in
the residential and commercial sectors can largely be attributed to milder, less energy-intensive winter conditions
compared to 2010. Electricity sales to the industrial sector in 2011 increased approximately 0.5 percent. Overall, in
2011, the amount of electricity generated (in kWh) decreased by 0.8 percent from the previous year. As a result,
CO2 emissions from the electric power sector decreased by 4.5 percent as the consumption of coal and petroleum for
"4 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).
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
electricity generation decreased by 5.7 percent and 17.4 percent, respectively, in 2011 and the consumption of
natural gas for electricity generation, increased by 2.5 percent.
Industrial Sector
The industrial sector accounted for 25 percent of CC>2 emissions from fossil fuel combustion, 17 percent of CH4
emissions from fossil fuel combustion, and 7 percent of N2O emissions from fossil fuel combustion. CC>2, CH4, and
N2O emissions resulted from the direct consumption of fossil fuels for steam and process heat production.
The industrial sector, per the underlying energy consumption data from EIA, includes activities such as
manufacturing, construction, mining, and agriculture. The largest of these activities in terms of energy consumption
is manufacturing, of which six industries—Petroleum Refineries, Chemicals, Paper, Primary Metals, Food, and
Nonmetallic Mineral Products—represent the vast majority of the energy use (EIA 2012a and EIA 2009b).
In theory, emissions from the industrial sector should be highly correlated with economic growth and industrial
output, but heating of industrial buildings and agricultural energy consumption are also affected by weather
conditions.65 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 effect on industrial emissions.
From 2010 to 2011, total industrial production and manufacturing output increased by 4.1 and 4.8 percent,
respectively (FRB 2012). Over this period, output increased across all production indices for Food, Petroleum
Refineries, Chemicals, Paper, Primary Metals, and Nonmetallic Mineral Products (see Figure 3-10).
65 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.
Energy 3-15
-------
Figure 3-10: Industrial Production Indices (Index 2007=100)
110 -I
100
90 -
80 -
70 -
60 -
50 -
Total Industrial
Index , <..
Total excluding Computers
Communications Equipment and
Semiconductor
oioioicnaioiovoioiCTioooooooooooo
Despite the growth in industrial output (51 percent) and the overall U.S. economy (66 percent) from 1990 to 2011,
CO2 emissions from fossil fuel combustion in the industrial sector decreased by 8.9 percent over the same time
series. A number of factors are believed to have caused this disparity between 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) energy-intensive industries such as steel are employing new
methods, such as electric arc furnaces, that are less carbon intensive than the older methods. In 2011, CO2, CH4, and
N2O emissions from fossil fuel combustion and electricity use within the industrial end-use sector totaled 1,401.4 Tg
CO2 Eq., or approximately 2.1 percent below 2010 emissions.
Residential and Commercial Sectors
The residential and commercial sectors accounted for 6 and 4 percent of CO2 emissions from fossil fuel combustion,
44 and 12 percent of CH4 emissions from fossil fuel combustion, and 2 and 1 percent of N2O emissions from fossil
fuel combustion, respectively. Emissions from these sectors were largely due to the direct consumption of natural
gas and petroleum products, primarily for heating and cooking needs. Coal consumption was a minor component of
energy use in both of these end-use sectors. In 2011, CO2, CH4, and N2O emissions from fossil fuel combustion and
electricity use within the residential and commercial end-use sectors were 1,136.9 Tg CO2 Eq. and 968.1 Tg CO2
Eq., respectively. Total CO2, CH4, and N2O emissions from the residential and commercial sectors decreased by 4.2
and 3.3 percent from 2010 to 2011, 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. In the long-term, both sectors are also affected by population growth, regional migration
trends, and changes in housing and building attributes (e.g., size and insulation).
Combustion emissions from natural gas consumption represent about 77 percent of the direct fossil fuel CO2
emissions from both the residential and commercial sectors, respectively. In 2011, natural gas combustion CO2
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
emissions from the residential and commercial sectors decreased by 1.5 percent and increased by 1.6 percent,
respectively.
U.S. Territories
Emissions from U.S. territories are based on the fuel consumption in American Samoa, Guam, Puerto Rico, U.S.
Virgin Islands, Wake Island, and other U.S. Pacific Islands. As described in the Methodology section for €62 from
fossil fuel combustion, this data is collected separately from the sectoral-level data available for the general
calculations. As sectoral information is not available for U.S. Territories, CCh, CH4, and N2O emissions are not
presented for U.S. Territories in the tables above, though the emissions will include some transportation and mobile
combustion sources.
Transportation Sector and Mobile Combustion
This discussion of transportation emissions follows the alternative method of presenting combustion emissions by
allocating emissions associated with electricity generation to the transportation end-use sector, as presented in Table
3-8. For direct emissions from transportation (i.e., not including emissions associated with the sector's electricity
consumption), please see Table 3-7.
Transportation End-Use Sector
The transportation end-use sector accounted for 1,769.5 Tg CCh Eq. in 2011, which represented 33 percent of CC>2
emissions, 22 percent of CH4 emissions, and 46 percent of N2O emissions from fossil fuel combustion, respectively.
Fuel purchased in the U.S. for international aircraft and marine travel accounted for an additional 111.3 Tg CCh in
2011; these emissions are recorded as international bunkers and are not included in U.S. totals according to
UNFCCC reporting protocols. Among domestic transportation sources, light duty vehicles (including passenger
cars and light-duty trucks) represented 61 percent of CCh emissions, medium- and heavy-duty trucks 22 percent,
commercial aircraft 7 percent, and other sources 11 percent. See Table 3-12 for a detailed breakdown of CCh
emissions by mode and fuel type. Emissions of €62 from the combustion of ethanol for transportation and emissions
associated with the agricultural and industrial processes involved in the production of ethanol are captured in other
sectors.66 Ethanol consumption from the transportation sector has increased from 0.7 billion gallons in 1990 to 12.3
billion gallons in 2011. For further information, see the section on wood biomass and ethanol consumption at the
end of this chapter, and table A-90 in Annex 3.2.
From 1990 to 2011, transportation emissions rose by 18 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 3 4 percent from 1990 to 2011, as a result of a
confluence of factors including population growth, economic growth, urban sprawl, and low fuel prices over much
of this period.
From 2010 to 2011, €62 emissions from the transportation end-use sector decreased by 1.2 percent. The decrease in
emissions can largely be attributed to slow growth in economic activity in 2011, decreasing median household
income, higher fuel prices and an associated decrease in the demand for passenger transportation. Commercial
aircraft emissions continued to fall, having decreased 18 percent since 2007. Decreases in jet fuel emissions
(excluding bunkers) are due in part to improved operational efficiency that results in more direct flight routing,
improvements in aircraft and engine technologies to reduce fuel burn and emissions, and the accelerated retirement
of older, less fuel efficient aircraft.
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 CC>2 from fossil fuel combustion, which increased by 20 percent from 1990 to
2011. This rise inCCh emissions, combined with an increase inHFCs from close to zero emissions in 1990 to 57.1
Net carbon fluxes from changes in biogenic carbon reservoirs are accounted for in the estimates for Land Use, Land-Use
Change and Forestry, in line with IPCC methodological guidance and UNFCCC reporting obligations.
Energy 3-17
-------
Tg COa Eq. in 2011, led to an increase in overall emissions from transportation activities of 18 percent (see table 2-
14).
Transportation Fossil Fuel Combustion CO2 Emissions
Domestic transportation COa emissions increased by 17 percent (252.2 Tg COa Eq.) between 1990 and 2011, an
annualized increase of 0.8 percent. However, between 2010 and 2011, COa emissions from domestic transportation
decreased by 1%, which contrasted with the previous year's trend of increasing emissions. Almost all of the energy
consumed by the transportation sector is petroleum-based, including motor gasoline, diesel fuel, jet fuel, and
residual oil.67 Transportation sources also produce CH4 and N2O; these emissions are included in Table 3-13 and
Table 3-14 in the "Mobile Combustion" Section. Annex 3.2 presents total emissions from all transportation and
mobile sources, including COa, N2O, CH4, and HFCs.
Carbon dioxide emissions from passenger cars and light-duty trucks totaled 1,061.6 Tg COa Eq. in 2011, an increase
of 12 percent (111.2 Tg COa Eq.) from 1990. COa emissions from passenger cars and light-duty trucks peaked at
1,184.3 Tg COa Eq. in 2004, and since then have declined about 10 percent. Over the 1990s through early this
decade, growth in vehicle travel substantially outweighed improvements in vehicle fuel economy; however, the rate
of Vehicle Miles Traveled (VMT) growth slowed considerably starting in 2005 (and declined rapidly in 2008) while
average vehicle fuel economy increased. Among new vehicles sold annually, average fuel economy gradually
declined from 1990 to 2004 (Figure 3-11), reflecting substantial growth in sales of light-duty trucks—in particular,
growth in the market share of sport utility vehicles—relative to passenger cars (Figure 3-12). New vehicle fuel
economy improved beginning in 2005, largely due to higher light-duty truck fuel economy standards, which have
risen each year since 2005. The overall increase in fuel economy is also due to a slightly lower light-duty truck
market share, which peaked in 2004 at 45 percent and declined to 36 percent in 2011.
Passenger car COa emissions increased by 21 percent from 1990 to 2011, light-duty truck COa emissions decreased
by 6 percent and medium- and heavy-duty trucks increased by 69 percent. 68 COa from the domestic operation of
commercial aircraft increased by 4 percent (4.7 Tg COa Eq.) from 1990 to 2011. Across all categories of aviation,
CO2 emissions decreased by 20.8 percent (38.9 Tg CO2 Eq.) between 1990 and 2011. 69 This includes a 64 percent
(22.4 Tg COa Eq.) decrease in emissions from domestic military operations. For further information on all
greenhouse gas emissions from transportation sources, please refer to Annex 3.2.
Biofuel estimates are presented in the Energy chapter for informational purposes only, in line with IPCC methodological
guidance and UNFCCC reporting obligations. Net carbon fluxes from changes in biogenic carbon reservoirs in croplands are
accounted for in the estimates for Land Use, Land-Use Change, and Forestry (see Chapter 7). More information and additional
analyses on biofuels are available at EPA's "Renewable Fuels: Regulations & Standards" See
68 Includes "light-duty trucks" fueled by gasoline, diesel and LPG
Includes consumption of jet fuel and aviation gasoline. Does not include aircraft bunkers, which are not included in national
emission totals, in line with IPCC methodological guidance and UNFCCC reporting obligations.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 3-11: Sales-Weighted Fuel Economy of New Passenger Cars and Light-Duty Trucks,
1990-2010
23.0 -
22,5 -
22,0 -
,. 21.5
1 21,0-1
<2 20.S -
8. 20.0
| 19.5 -
's 19,0
18,5 -
18,0 -
o
CT>
CTv
fM
cn
Ch
en
en
en
en
Oi
on
CO
CTl
cn
o
o
o
fsl
o
o
O
o
fM
o
o
fM
s
O
fM
in
o
O
CM
ID
O
o
(M
o
o
IN
CO
o
o
CM
en
o
o
fM
O
fM
O
fM
Model Year
Figure 3-12: Sales of New Passenger Cars and Light-Duty Trucks, 1990-2010
100% i
j 75% H
I 50% ^
25% -
Passenger Cars
Light-Duty Trucks
o>
o>
en
cn
ov
rM \.:-'
11.7 '••••-,
2005
1,187.8
658.0
478.7
34.9
0.4
1.6
14.1
458.1
4.2 ;
25.8
360.6
10.6
45.6
3.1
8.1
9.4
2007"
1,181.2
800.2
315.5
46.6
0.7
4.3
13.9
476.3
4.1
13.6
384.6
15.9
46.6
3.3
8.2
8.2
2008
1,130.3
765.6
298.9
47.2
0.8
4.4
13.5
451.6
3.7
12.1
366.1
15.2
43.2
3.4
7.9
9.0
2009
1,128.5
762.4
304.1
43.6
0.8
4.2
13.3
409.7
3.6
12.1
332.2
14.1
36.3
3.5
8.0
8.2
2010
1,125.0
760.0
303.7
43.6
0.8
3.8
13.1
426.3
3.8
12.6
345.9
14.1
39.0
3.5
7.5
9.5
2011
1,100.4
754.8
288.2
39.9
0.8
3.6
13.0
435.4
4.1
13.1
347.8
15.1
41.0
3.6
10.7
7.5
Energy 3-19
-------
Jet Fuel6 184.2 189.3 : 179.5 173.0 154.1 151.5 146.5
Commercial Aircraft1 109.9 132.7 139.7 127.3 119.5 113.3 114.6
Military Aircraft 35.0 - 19.4 , 17.8 17.6 15.4 13.6 12.6
General Aviation Aircraft 39.4 37.3 22.0 28.2 19.2 24.6 19.4
International Bunker Fuels0 38.0 : 60.1 61.5 56.1 52.8 61.0 64.9
International Bunker Fuels
From Commercial Aviation 30.0 55.6 57.5 52.4 49.2 57.4 61.7
Aviation Gasoline 3.1 2.4 2.2 2.0 1.8 1.9 1.9
General Aviation Aircraft 3.1 2.4 2.2 2.0 1.8 1.9 1.9
Residual Fuel Oil 22.6 19.3 29.0 19.9 15.4 19.3 20.1
Ships and Other Boatsf 22.6 . , 19.3 ' 29.0 19.9 15.4 19.3 20.1
International Bunker Fuels0 53.7 ,, 43.6 45.6 49.2 45.4 46.5 38.9
Natural Gas 36.0 33.1 35.2 36.7 37.9 38.1 38.8
Passenger Cars + + + + + + +
Light-Duty Trucks + , + + + + + +
Buses + 0.8 1.0 1.1 1.2 1.1 1.1
Pipeline11 36.0 , 32.2 34.2 35.6 36.7 37.1 37.7
LPG 1.4 1.7 1.4 2.5 1.7 1.8 1.9
Light-Duty Trucks 0.6', 1.3 1.0 1.8 1.2 1.3 1.3
Medium- and Heavy-Duty
Trucksb 0.8 0.4 0.4 0.7 0.5 0.6 0.6
Buses + + + + + + +
Electricity 3.0 4.7 5.1 4.7 4.5 4.5 4.3
Rail 3.0 . . 4.7 5.1 4.7 4.5 4.5 4.3
Ethanolz
4.1
22.4
38.1
53.8
61.2
71.2
71.3
Total
1,497.0
1,896.5
1,909.7 1,820.7 1,753.7 1,768.4 1,749.3
Total (Including Bunkers) '
1,600.5
2,009.6 : 2,025.1 1,935.0 1,860.1 1,885.3 1,860.6
a This table does not include emissions from non-transportation mobile sources, such as agricultural equipment and
construction/mining equipment; it also does not include emissions associated with electricity consumption by pipelines or
lubricants used in transportation.
b Includes medium- and heavy-duty trucks over 8,500 Ibs.
c Official estimates exclude emissions from the combustion of both aviation and marine international bunker fuels; however,
estimates including international bunker fuel-related emissions are presented for informational purposes.
d In 2011, FHWA changed how vehicles are classified, moving from a system based on body-type to one that is based on
wheelbase. This change in methodology in FHWA's VM-1 table resulted in large changes in VMT by vehicle class, thus leading
to a shift in emissions among on-road vehicle classes in the 2007 to 2010 time period.
e For BY2011, EPA implemented revisions which adjusted the apportionment of total jet fuel energy consumption, as well as the
methodology and sources for calculation of CO2 from aircrafts. For more information, see Recalculations Discussion in the CO2
from Fossil Fuel Combustion section, as well as Annex 3.3.
f Fluctuations in emission estimates reflect data collection problems.
B: Ethanol estimates are presented for informational purposes only. See section 3.10 of this chapter and the estimates in Land Use,
Land-Use Change, and Forestry (see Chapter 7), in line with IPCC methodological guidance and UNFCCC reporting obligations,
for more information on ethanol.
h Pipelines reflect CO2 emissions from natural gas powered pipelines transporting natural gas.
1 Commercial aircraft, as modeled in FAA's AEDT, consists of passenger aircraft, cargo, and other chartered flights.
Note: Totals may not sum due to independent rounding.
+ Less than 0.05 Tg CO2 Eq.
Mobile Fossil Fuel Combustion CH4 and N2O Emissions
Mobile combustion includes emissions of CH4 and N2O from all transportation sources identified in the U.S.
inventory with the exception of pipelines, which are stationary;70 mobile sources also include non-transportation
sources such as construction/mining equipment, agricultural equipment, vehicles used off-road, and other sources
(e.g., snowmobiles, lawnmowers, etc.). Annex 3.2 includes a summary of all emissions from both transportation
and mobile sources. Table 3-13 and Table 3-14 provide CH4 and N2O emission estimates in Tg €62 Eq.71
70 Fugitive emissions of CFLi from natural gas systems are reported under the Industrial economic sector. More information on
the methodology used to calculate these emissions are included in Annex 3.4
71 See Annex 3.2 for a complete time series of emission estimates for 1990 through 2011.
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Mobile combustion was responsible for a small portion of national CH4 emissions (0.3 percent) but was the third
largest source of U.S. N2O emissions (5 percent). From 1990 to 2011, mobile source CEU emissions declined by 62
percent, to 1.7 Tg CO2 Eq. (82 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 58 percent,
to 18.5 Tg CO2 Eq. (60 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 67 percent decrease in
mobile source N2O emissions from 1998 to 2011 (Figure 3-13). Overall, CH4 and N2O emissions were
predominantly from gasoline-fueled passenger cars and light-duty trucks.
Figure 3-13: Mobile Source Cm and NzO Emissions
60 i
50
iff
40 -
8 30 H
20 -
10 -
H,0
CH4
01 en
s s
ra
01
o>
en
en
if
en
en
en
en
ID
01
en
fs
en
en
eo
en
en
en
en
en
tfi
O
Table 3-13: ChU Emissions from Mobile Combustion (Tg COz Eq.)
Fuel Type/Vehicle Type3
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
1990
4.2
2.6
1.4
2005 ;
1.9
1.1
0.7 /
2007 e
1.6
1.1
0.3
2008
1.4
1.0
0.3
2009
1.3
0.9
0.3
2010
1.2
0.9
0.3
2011
1.2
0.8
0.3
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
Rail
Aircraftf
Agricultural Equipment15
Construction/Mining
Equipment0
Otherd
Total
0.2
0.1
0.1
0.1
0.3
+
0.1
0.1,
0.1
o.i •
0.5
+
0.1
+
0.1
0.1
0.1
0.1
0.5
+
0.1
+
0.1
0.1
0.1
0.1
0.4
+
0.1
+
0.1
0.1
0.1
4.6
2.4
2.1
1.9
0.1
0.1
0.4
+
0.1
+
0.1
0.1
0.1
1.8
0.1
0.1
0.4
+
0.1
+
0.1
0.1
0.1
1.8
0.1
0.1
0.5
+
0.1
+
0.1
0.1
0.1
1.7
a See Annex 3.2 for definitions of on-road vehicle types.
b Includes equipment, such as tractors and combines, as well as fuel consumption from trucks that are used off-road in
agriculture.
c Includes equipment, such as cranes, dumpers, and excavators, as well as fuel consumption from trucks that are used off-road in
construction.
Energy 3-21
-------
d "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment, as well as fuel consumption from trucks that are
used off-road for commercial/industrial purposes.
e In 2011, FHWA changed how vehicles are classified, moving from a system based on body-type to one that is based on
wheelbase. This change in methodology in FHWA's VM-1 table resulted in large changes in VMT by vehicle class, thus leading
to a shift in emissions among on-road vehicle classes in the 2007 to 2010 time period.
f CH4 emissions from jet engine aircrafts have been zeroed out across the time series. For more information, see the
Recalculations Discussion in the CELi and N2O from Fossil Fuel Combustion section.
Note: Totals may not sum due to independent rounding.
+ Less than 0.05 Tg CO2 Eq.
Table 3-14: NzO Emissions from Mobile Combustion (Tg CO2 Eg.)
Fuel Type/Vehicle Type3
Gasoline On-Road
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty
Trucks and Buses
Motorcycles
Diesel On-Road
1990
40.1
25.4
14.L '
0.6
+
0.2
2005 ;
32.2 .«
17.8 /
13.6
0.8 /
+ ••'
0.3
2007 e
24.1
17.3
5.8
0.9
+
0.4
2008
20.7
14.6
5.2
0.9
+
0.4
2009
18.3
12.4
5.1
0.7
+
0.4
2010
16.1
10.8
4.6
0.6
+
0.4
2011
13.9
9.4
4.0
0.5
+
0.4
Passenger Cars
Light-Duty Trucks
Medium- and Heavy-Duty
Trucks and Buses
Alternative Fuel On-Road
Non-Road
Ships and Boats
Rail
Aircraft
Agricultural Equipment15
Construction/Mining
Equipment0
Otherd
Total
0.2 •
0.1
3.7 „,
0.6
0.3
1.8
0.2* ;
0.3
0.4
44.0
0.3
0.2
4.3
0.6
0.4
1.8 /
0.4 /
0.5
0.6 /
36.9 4
0.4
0.2
4.4
0.8
0.4
1.7
0.4
0.5
0.6
29.0
0.4
0.2
4.1
0.6
0.3
1.7
0.4
0.5
0.6
25.5
0.4
0.2
3.9
0.6
0.3
1.5
0.4
0.5
0.6
22.7
0.4
0.2
3.9
0.6
0.3
1.5
0.4
0.6
0.6
20.7
0.4
0.2
4.0
0.7
0.3
1.4
0.4
0.6
0.6
18.5
a See Annex 3.2 for definitions of on-road vehicle types.
b Includes equipment, such as tractors and combines, as well as fuel consumption from trucks that are used off-road in
agriculture.
c Includes equipment, such as cranes, dumpers, and excavators, as well as fuel consumption from trucks that are used off-road in
construction.
d "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment, as well as fuel consumption from trucks that are
used off-road for commercial/industrial purposes.
e In 2011, FLTWA changed how vehicles are classified, moving from a system based on body-type to one that is based on
wheelbase. This change in methodology in FHWA's VM-1 table resulted in large changes in VMT by vehicle class, thus leading
to a shift in emissions among on-road vehicle classes in the 2007 to 2010 time period.
Note: Totals may not sum due to independent rounding.
+ Less than 0.05 Tg CO2 Eq.
CO2
Methodology
The methodology used by the United States for estimating CCh 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 in line with a Tier 2 method in the 2006 IPCC Guidelines for National
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Greenhouse Gas Inventories (IPCC 2006). 72 The use of the most recently published calculation methodologies by
the IPCC, as contained in the 2006 IPCC Guidelines, is considered to improve the rigor and accuracy of this
inventory and is fully in line with IPCC good practice guidance. 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 2013). The EIA does not
include territories in its national energy statistics, so fuel consumption data for territories were collected
separately from Jacobs (2010).73
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 on an annual basis
and used in this inventory are predominantly from mid-stream or conversion energy consumers such as
refiners and electric power generators. These annual surveys are supplemented with end-use energy
consumption surveys, such as the Manufacturing Energy Consumption Survey, that are conducted on a
periodic basis (every 4 years). These consumption data sets help inform the annual surveys to arrive at the
national total and sectoral breakdowns for that total.74
It is also important to note that U.S. fossil fuel energy statistics are generally presented using gross calorific
values (GCV) (i.e., higher heating values). Fuel consumption activity data presented here have not been
adjusted to correspond to international standards, which are to report energy statistics in terms of net
calorific values (NCV) (i.e., lower heating values).75
2. Subtract uses accounted for in the Industrial Processes chapter. Portions of the fuel consumption data for
seven fuel categories—coking coal, distillate fuel, industrial other coal, petroleum coke, natural gas,
residual fuel oil, and other oil—were reallocated to the industrial processes chapter, as they were consumed
during non-energy related industrial activity. To make these adjustments, additional data were collected
from AISI (2004 through 2012a), Coffeyville (2012), U.S. Census Bureau (2011), EIA (2012b), USGS
(1991 through2011), USGS (1994 through2011), USGS (1995, 1998, 2000 through2002), USGS (2007),
USGS (2009), USGS (2010), USGS (2011), USGS (1991 through 20lOa), USGS (1991 through 201 Ob),
USGS (2012a) and USGS (2012b).76
3. Adjust for conversion of fuels and exports ofCC>2. Fossil fuel consumption estimates are adjusted
downward to exclude fuels created from other fossil fuels and exports of CCh.77 Synthetic natural gas is
72 The IPCC Tier 3B methodology is used for estimating emissions from commercial aircraft.
73 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 49.7 Tg CCh Eq. in 2011.
74 See IPCC Reference Approach for estimating CCh emissions from fossil fuel combustion in Annex 4 for a comparison of U.S.
estimates using top-down and bottom-up approaches.
75 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.
7^ See sections on Iron and Steel Production and Metallurgical Coke Production, Ammonia Production and Urea Consumption,
Petrochemical Production, Titanium Dioxide Production, Ferroalloy Production, Aluminum Production, and Silicon Carbide
Production and Consumption in the Industrial Processes chapter.
Energy statistics from EIA (2013) are already adjusted downward to account for ethanol added to motor gasoline, and biogas
in natural gas.
Energy 3-23
-------
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.78 Since October 2000,
the Dakota Gasification Plant has been exporting COa to Canada by pipeline. Since this CC>2 is not emitted
to the atmosphere in the United States, energy used to produce this CC>2 is subtracted from energy
consumption statistics. To make these adjustments, additional data for ethanol were collected from EIA
(2012a), data for synthetic natural gas were collected from EIA (2012b), and data for CCh exports were
collected from the Eastman Gasification Services Company (2011), Dakota Gasification Company (2006),
Fitzpatrick (2002), Erickson (2003), EIA (2008) and DOE (2012).
4. Adjust Sectoral Allocation of Distillate Fuel Oil and Motor Gasoline. EPA had conducted a separate
bottom-up analysis of transportation fuel consumption based on the Federal Highway Administration's
(FHWA) VMT that indicated that the amount of distillate and motor gasoline consumption allocated to the
transportation sector in the EIA statistics should be adjusted. Therefore, for these estimates, the
transportation sector's distillate fuel and motor gasoline consumption was adjusted upward to match the
value obtained from the bottom-up analysis based on VMT. As the total distillate and motor gasoline
consumption estimate from EIA are considered to be accurate at the national level, the distillate
consumption totals for the residential, commercial, and industrial sectors were adjusted downward
proportionately. The data sources used in the bottom-up analysis of transportation fuel consumption include
AAR (2008 through 2012), Benson (2002 through 2004), DOE (1993 through 2012), EIA (2007a), EIA
(1991 through 2013), EPA (2009), and FHWA (1996 through 2013).79
5. Adjust for fuels consumed for non-energy uses. U.S. aggregate energy statistics include consumption of
fossil fuels for non-energy purposes. These are fossil fuels that are manufactured into plastics, asphalt,
lubricants, or other products. Depending on the end-use, this can result in storage of some or all of the C
contained in the fuel for a period of time. As the emission pathways of C used for non-energy purposes are
vastly different than fuel combustion (since the C in these fuels ends up in products instead of being
combusted), these emissions are estimated separately in the Carbon Emitted and Stored in Products from
Non-Energy Uses of Fossil Fuels section in this chapter. Therefore, the amount of fuels used for non-
energy purposes was subtracted from total fuel consumption. Data on non-fuel consumption was provided
by EIA (2013).
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).80 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
2012) supplied data on military jet fuel and marine fuel use. Commercial jet fuel use was obtained from
FAA (2013); residual and distillate fuel use for civilian marine bunkers was obtained from DOC (1991
through 2012) for 1990 through 2001 and 2007 through 2010, and DHS (2008) for 2003 through 2006.
Consumption of these fuels was subtracted from the corresponding fuels in the transportation end-use
sector. Estimates of international bunker fuel emissions for the United States are discussed in detail later in
the International Bunker Fuels section of this chapter.
78 These adjustments are explained in greater detail in Annex 2.1.
79 The source of VMT and fuel consumption is FHWA's VM-1 table. The data collection methodology has undergone
substantial revision for only years 2007 to 2010, while prior years have remain unchanged Several of the vehicle type categories
have changed. For instance, passenger car has been replaced by "Light duty vehicle, short WB" and other 4 axle- 2 tire has been
replaced by "Light duty vehicle, long WB". With this change in methodology, there are substantial differences in activity data
among vehicle classes, even though overall VMT and fuel consumption is unchanged. While this is the best data available on
vehicle activity, the time series reflects changes in the definition of vehicle classes between 2006- 2007 when this change in
methodology was implemented.
80 See International Bunker Fuels section in this chapter for a more detailed discussion.
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 €62. The C
content coefficients used by the United States were obtained from EIA's Emissions of Greenhouse Gases in
the United States 2008 (EIA 2009a), and an EPA analysis of C content coefficients used in the mandatory
reporting rule (EPA 2010a). A discussion of the methodology used to develop the C content coefficients
are presented in Annexes 2.1 and 2.2.
8. Estimate CO2 Emissions. Total €62 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 fromFHWA (1996 through 2013); for each vehicle category, the
percent gasoline, diesel, and other (e.g., CNG, LPG) fuel consumption are estimated using data from
DOE (1993 through 2012).
• For non-road vehicles, activity data were obtained from AAR (2008 through 2012), APTA (2007
through 2012), APTA (2006), BEA (1991 through 2011), Benson (2002 through 2004), DOE (1993
through 2012), DESC (2012), DOC (1991 through 2012), DOT (1991 through 2012), EIA (2009a),
EIA (201 la), EIA (2002), EIA (1991 through 2013), EPA (2012b), and Gaffney (2007).
• For jet fuel used by aircraft, CO2 emissions from commercial aircraft were developed by the U. S.
Federal Aviation Administration (FAA) using a Tier 3B methodology, consistent with the 2006 IPCC
Guidelines for National Greenhouse Gas Inventories (see Annex 3.3). CO2 emissions from other
aircraft were calculated directly based on reported consumption of fuel as reported by EIA. Allocation
to domestic military uses was made using DoD data (see Annex 3.8). General aviation jet fuel
consumption is determined as the remainder of total jet fuel use net all other jet fuel use as determined
by FAA and DoD. For more information, see the Recalculations Discussion in the CH4 and N2O from
Fossil Combustion Section, as well as Annex 3.2.
Heat contents and densities were obtained from EIA (2012a) and USAF (1998).81
As described in the calculation methodology, total fossil fuel consumption for each year is based on aggregated end-
use sector consumption published by the Energy Information Administration (EIA) of the U.S. Department of
Energy (DOE). The availability of facility-level combustion emissions through EPA's Greenhouse Gas Reporting
Program (GHGRP) has provided an opportunity to better characterize the industrial sector's energy consumption
and emissions in the United States, through a disaggregation of EIA's industrial sector fuel consumption data from
select industries.
For the GHGRP's 2010 and 2011 reporting years, facility-level fossil fuel combustion emissions reported through
the GHGRP were categorized and distributed to specific industry types by utilizing facility-reported NAICS codes
(as published by the U.S. Census Bureau), and associated data available from EIA's 2010 Manufacturing Energy
For a more detailed description of the data sources used for the analysis of the transportation end use sector see the Mobile
Combustion (excluding CCh) and International Bunker Fuels sections of the Energy chapter, Annex 3.2, and Annex 3.8.
Energy 3-25
-------
Consumption Survey (MECS). As noted previously in this report, the definitions and provisions for reporting fuel
types in the GHGRP include some differences from the inventory's use of El A national fuel statistics to meet the
UNFCCC reporting guidelines. The IPCC has provided guidance on aligning facility-level reported fuels and fuel
types published in national energy statistics, which guided this exercise.82
This year's effort represents the first attempt to align, reconcile, and coordinate the facility-level reporting of fossil
fuel combustion emissions under the GHGRP with the national-level approach presented in this report. Consistent
with recommendations for reporting the inventory to the UNFCCC, progress was made on certain fuel types for
specific industries and has been included in the Common Reporting Format (CRF) tables that are submitted to the
UNFCCC along with this report.83 However, a full mapping was not completed this year due to fuel category
differences between national statistics published by EIA and facility-level reported GHGRP data. Furthermore,
given that calendar year 2010 was the first year in which emissions data were reported to the GHGRP, this year's
examination only focused on 2010 and 2011. For this year's exercise, the efforts in reconciling fuels focused on
standard, common fuel types (e.g., natural gas, distillate fuel oil, etc.) where the fuels inEIA's national statistics
aligned well with facility-level GHGRP data. For these reasons, the current information presented in the CRF tables
should be viewed as an initial attempt at this exercise. Additional efforts will be made for future inventory reports to
improve the mapping of fuel types, and examine ways to reconcile and coordinate any differences between facility-
level data and national statistics. Additionally, in order to expand this effort through the full time series presented in
this report, further analyses will be conducted linking the GHGRP's facility-level reporting with the information
published by EIA in its MECS data, other available MECS survey years , and any further informative sources of
data. It is believed that this year's analysis has led to improvements in the presentation of data in the inventory, but
further work will be conducted, and future improvements will be realized in subsequent inventory reports.
Fossil fuels are the dominant source of energy in the United States, and COa is the dominant greenhouse gas emitted
as a product from their combustion. Energy-related CCh emissions are impacted by not only lower levels of energy
consumption 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 COa Eq./QBtu for coal and petroleum coke.84 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. The overall C intensity of the U. S. economy is thus dependent upon the quantity and combination of fuels and
other energy sources employed to meet demand.
Table 3-15 provides a time series of the C intensity for each sector of the U.S. economy. The time series
incorporates only the energy consumed from the direct combustion of fossil fuels in each sector. For example, the C
intensity for the residential sector does not include the energy from or emissions related to the consumption of
electricity for lighting. 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.
82 See Section 4 "Use of Facility-Level Data in Good Practice National Greenhouse Gas Inventories" of the IPCC meeting
report, and specifically the section on using facility-level data in conjunction with energy data, at
83 See < http://www.epa.gov/climatechange/ghgemissions/usinventoryreport.html>
84 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 3-15: 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. Territories0
All Sectors c
1990
57.4
59.2
64.3
71.1
87.3
73.0 .
73.0
; 2005
.« 56.6
57.5
64.3
71.4
85.8
73.4 /
73.5
, 2007
4 56.3
57.1
64.1
71.9
84.7
73.5
73.3
2008
56.0
56.7
63.5
71.6
84.9
73.3
73.1
2009
55.9
56.8
63.0
71.5
83.7
73.1
72.4
2010
55.8
56.8
63.0
71.5
83.6
73.1
72.4
2011
55.7
56.6
62.6
71.5
82.9
73.1
72.0
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.
Over the twenty-two-year period of 1990 through 2011, however, the C intensity of U.S. energy consumption has
been fairly constant, as the proportion of fossil fuels used by the individual sectors has not changed significantly.
Per capita energy consumption fluctuated little from 1990 to 2007, but in 2011 was approximately 17.9 percent
below 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 CCh emissions
per dollar of gross domestic product (GDP) have both declined since 1990 (BEA 2012).
Figure 3-14: U.S. Energy Consumption and Energy-Related COz Emissions Per Capita and Per
Dollar GDP
CO^/Energy
Consumption
Energy Consumption/capita**""'
Energy
Consumption/$GDP
0V 0V 0V 0V 0V 0V
0V 0V 0V 0V 0V 0V 0V 0V 0V 0V
C intensity estimates were developed using nuclear and renewable energy data from EIA (2012a), EPA (2010a), and
fossil fuel consumption data as discussed above and presented in Annex 2.1.
Uncertainty and Time Series Consistency
For estimates of CC>2 from fossil fuel combustion, the amount of COa 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
Energy 3-27
-------
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 €62
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 CCh 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 CCh 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. The amount of CCh
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 CCh estimates. Detailed discussions on the uncertainties associated with C emitted from Non-Energy Uses of
Fossil Fuels can be found within that section of this chapter.
Various sources of uncertainty surround the estimation of emissions from international bunker fuels, which are
subtracted from the U.S. totals (see the detailed discussions on these uncertainties provided in the International
Bunker Fuels section of this chapter). Another source of uncertainty is fuel consumption by U.S. territories. The
United States does not collect energy statistics for its territories at the same level of detail as for the fifty states and
the District of Columbia. Therefore, estimating both emissions and bunker fuel consumption by these territories is
difficult.
Uncertainties in the emission estimates presented above also result from the data used to allocate CO2 emissions
from the transportation end-use sector to individual vehicle types and transport modes. In many cases, bottom-up
estimates of fuel consumption by vehicle type do not match aggregate fuel-type estimates from El A. Further
research is planned to improve the allocation into detailed transportation end-use sector emissions.
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 Stochastic Simulation technique, with @RISK software.
For this uncertainty estimation, the inventory estimation model for CCh from fossil fuel combustion was integrated
with the relevant variables from the inventory estimation model for International Bunker Fuels, to realistically
characterize the interaction (or endogenous correlation) between the variables of these two models. About 120 input
variables were modeled for CO2 from energy-related Fossil Fuel Combustion (including about 10 for non-energy
fuel consumption and about 20 for International Bunker Fuels).
In developing the uncertainty estimation model, uniform distributions were assumed for all activity-related input
variables and emission factors, based on the SAIC/EIA (2001) report.85 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.86
85 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.
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,
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 (S AIC/EIA
2001).87 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 3-16. Fossil fuel combustion
CO2 emissions in 2011 were estimated to be between 5,073.1 and 5,716.2 Tg €62 Eq. at a 95 percent confidence
level. This indicates a range of 1 percent below to 6 percent above the 2011 emission estimate of 5,277.2 Tg €62
Eq.
Table 3-16: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Energy-related
Fossil Fuel Combustion by Fuel Type and Sector (Tg COz Eq. and Percent)
Fuel/Sector
Coal"
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas b
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum b
Residential
Commercial
Industrial
Transportation
Electric Utilities
U.S. Territories
Total (excluding Geothermal) b
Geothermal
Total (including Geothermal) b'c
2011 Emission
Estimate
(Tg C02 Eq.)
1,821.9
0.5
5.1
90.1
NE
1,722.7
3.5
1,290.3
254.6
170.4
416.3
38.8
408.8
1.5
2,164.6
73.6
46.7
266.8
1,706.2
26.6
44.7
5,276.8
0.4
5,277.2
Uncertainty
Range Relative
to Emission
Estimate3
(Tg CO2 Eq.) (%)
Lower
Bound
1,717.0
0.5
4.7
84.6
NE
1,617.6
2.9
1,264.9
244.6
163.9
411.2
37.3
392.7
1.3
1,991.2
67.2
43.3
193.2
1,565.5
24.4
39.0
5,072.6
NE
5,073.1
Upper
Bound
2,030.5
0.6
6.0
107.3
NE
1,921.8
4.3
1,386.0
275.0
184.0
463.4
41.9
433.6
1.7
2,392.7
79.8
50.0
336.7
1,907.5
29.8
52.3
5,715.8
NE
5,716.2
Lower
Bound
-3%
-6%
-5%
-4%
NA
-4%
-12%
+0%
-3%
-3%
+0%
-3%
-3%
-13%
-5%
-6%
-5%
-20%
-5%
-5%
-8%
-1%
NE
-1%
Upper
Bound
+9%
+15%
+15%
+17%
NA
+10%
+19%
+6%
+7%
+7%
+10%
+7%
+5%
+17%
+7%
5%
4%
18%
8%
9%
11%
+6%
NE
+6%
NA (Not Applicable)
NE (Not Estimated)
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b The low and high estimates for total emissions were calculated separately through simulations and, hence, the low
and high emission estimates for the sub-source categories do not sum to total emissions.
c Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for CCh
emissions from geothermal production.
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.
87 Although, in general, random uncertainties are the main focus of statistical uncertainty analysis, when the uncertainty
estimates are elicited from experts, their estimates include both random and systematic uncertainties. Hence, both these types of
uncertainties are represented in this uncertainty analysis.
Energy 3-29
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Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
QA/QC and Verification
A source-specific QA/QC plan for CCh 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 COa 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 (EIA 2013) updated energy consumption statistics across the time series
relative to the previous Inventory. These revisions primarily impacted the emission estimates from 2007 to 2010;
however, revisions to industrial and transportation petroleum consumption as well as industrial natural gas and coal
consumption impacted emission estimates across the time series. Overall, these changes resulted in an average
annual increase of 8.8 Tg CCh Eq. (0.2 percent) in CCh emissions from fossil fuel combustion for the period 1990
through 2010.
During the development of the current Inventory, commercial jet fuel consumption data for the 1990 through 2011
time series was provided by FAA. The revised 1990 and 1995 through 2010 estimates were developed with the
Aviation Environmental Design Tool (AEDT) using radar-informed data, and are considered more accurate. The
radar-informed method that was used to estimate emissions for commercial aircraft for all years 1990 and 1995
through 2011, but was not possible for 1991 through 1995 because the radar data set is not available for those years.
FAA developed OAG schedule-informed inventories modeled with AEDT and great circle trajectories for 1990,
2000 and 2010 to generate the best possible jet fuel burn estimates for the 1990 through 1999 time series.
International aviation bunker fuel consumption from 1990 to 2011 for commercial aircraft departing from the United
States was recalculated in the same manner.
Two other changes to the calculation of jet fuel consumption and COa emissions were undertaken. The first is that
international bunker jet fuel consumption is now calculated directly, while general aviation jet fuel consumption is
calculated as the remainder of total EIA jet fuel consumption net all other jet fuel consumption. In past years'
inventories, general aviation consumption was obtained directly from FAA's Aerospace Forecast, while
international aviation bunker fuels were calculated as the remainder of jet fuel energy consumption net all other jet
fuel consumption. Due to concerns about time series consistency in the FAA Aerospace Forecast data when
applying it to general aviation, as well as due to the availability of international jet fuel consumption from FAA's
AEDT model, it was determined that aviation international bunker fuels should be calculated directly. Total
international bunker jet fuel consumption is calculated as the sum of international commercial jet fuel consumption
(FAA 2013) and international military jet fuel consumption (DESC 2012). Sources of energy consumption for other
jet fuel remains the same: total jet fuel consumption is obtained from EIA (2012a), domestic commercial aviation is
obtained from FAA's AEDT model (FAA 2013), and domestic military fuel consumption is provided by DESC
(2012).
Additionally, FAA AEDT's model estimates for CC>2 emissions from domestic commercial aviation are used
directly. As described above, this follows the IPCC Tier 3b methodology. To calculate emissions for domestic jet
fuel use from aircraft other than commercial aviation, AEDT's estimate for domestic commercial CCh is subtracted
from total domestic CCh emissions from jet fuels. This value is then distributed to domestic military aviation and
general aviation based on their proportional energy consumption.
As a result of these changes, estimates of CCh emissions from combustion of jet fuel were slightly lower than the
previous Inventory report, by 10.1 percent (6.5 Tg CCh Eq.).
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Planned Improvements
To reduce uncertainty of €62 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 €62 from fossil fuel combustion estimates. In
addition, further expert elicitation may be conducted to better quantify the total uncertainty associated with
emissions from this source.
The availability of facility-level combustion emissions through EPA's (GHGRP) will continue to be examined to
help better characterize the industrial sector's energy consumption in the United States, and further classify business
establishments according to industrial economic activity type. Most methodologies used in EPA's GHGRP are
consistent with IPCC, though for EPA's GHGRP, facilities collect detailed information specific to their operations
according to detailed measurement standards, which may differ with the more aggregated data collected for the
Inventory to estimate total, national U.S. emissions. In addition, and unlike the reporting requirements for this
chapter under the UNFCCC reporting guidelines, some facility-level fuel combustion emissions reported under the
GHGRP may also include industrial process emissions.88 In line with UNFCCC reporting guidelines, fuel
combustion emissions are included in this chapter, while process emissions are included in the Industrial Processes
chapter of this report. In examining data from EPA's GHGRP that would be useful to improve the emission
estimates for the CO2 from fossil fuel combustion category, particular attention will also be made to ensure time
series consistency, as the facility-level reporting data from EPA's GHGRP are not available for all inventory years
as reported in this inventory. Additional, analyses will be conducted to align reported facility-level fuel types and
IPCC fuel types per the national energy statistics. Additional work will commence to ensure CO2 emissions from
biomass are separated in the facility-level reported data, and maintaining consistency with national energy statistics
provided by EIA. In implementing improvements and integration of data from EPA's GHGRP, the latest guidance
from the IPCC on the use of facility-level data in national inventories will continue to be relied upon.89
Methodology
Methane and N2O emissions from stationary combustion were estimated by multiplying fossil fuel and wood
consumption data by emission factors (by sector and fuel type for industrial, residential, commercial, and U.S.
Territories; and by fuel and technology type for the electric power sector). Beginning with the current Inventory
report, the electric power sector utilizes a Tier 2 methodology, whereas all other sectors utilize a Tier 1
methodology. The activity data and emission factors used are described in the following subsections.
Industrial, Residential, Commercial, and U.S. Territories
National coal, natural gas, fuel oil, and wood consumption data were grouped by sector: industrial, commercial,
residential, and U.S. territories. For the CH4 and N2O estimates, wood consumption data for the United States was
obtained from EIA's Annual Energy Review (EIA 2012a). Fuel consumption data for coal, natural gas, and fuel oil
for the United States were obtained from EIA's Monthly Energy Review and unpublished supplemental tables on
petroleum product detail (EIA 2013). Because the United States does not include territories in its national energy
statistics, fuel consumption data for territories were provided separately by Jacobs (2010).90 Fuel consumption for
the industrial sector was adjusted to subtract out construction and agricultural use, which is reported under mobile
88 See
89 See
90 U.S. territories data also include combustion from mobile activities because data to allocate territories' energy use were
unavailable. For this reason, CELi and N2O emissions from combustion by U.S. territories are only included in the stationary
combustion totals.
Energy 3-31
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sources.91 Construction and agricultural fuel use was obtained from EPA (2010a). 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. Tier 1 default emission factors for these three end-use sectors were provided by the
2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006) which, according to this guidance,
"are based on the IPCC 1996 Guidelines." U.S. territories' emission factors were estimated using the U.S. emission
factors for the primary sector in which each fuel was combusted.
Electric Power Sector
The electric power sector now uses a Tier 2 emission estimation methodology as fuel consumption for the electricity
generation sector by control-technology type was obtained from EPA's Acid Rain Program Dataset (EPA 2012).
This combustion technology- and fuel-use data was available by facility from 1996 to 2011. The Tier 2 emission
factors used were taken from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006),
which in turn are based on emission factors published by U. S. EPA.
Since there was a difference between the EPA (2012) and EIA (2012a) total energy consumption estimates, the
remaining energy consumption from EIA (2012a) was apportioned to each combustion technology type and fuel
combination using a ratio of energy consumption by technology type from 1996 to 2011.
Energy consumption estimates were not available from 1990 to 1995 in the EPA (2012) dataset, and as a result,
consumption was calculated using total electric power consumption from EIA (2012a) and the ratio of combustion
technology and fuel types from EPA (2012). The consumption estimates from 1990 to 1995 were estimated by
applying the 1996 consumption ratio by combustion technology type to the total EIA consumption for each year
from 1990 to 1995. Emissions were estimated by multiplying fossil fuel and wood consumption by technology- and
fuel-specific Tier 2 IPCC emission factors.
Lastly, there were significant differences between wood biomass consumption in the electric power sector between
the EPA (2012) and EIA (2012a) datasets. The higher wood biomass consumption from EIA (2012a) in the electric
power sector was distributed to the residential, commercial, and industrial sectors according to their percent share of
wood biomass energy consumption calculated from EIA (2012a).
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 and Time-Series Consistency
Methane 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 Stochastic 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 COa from fossil fuel combustion to realistically characterize
the interaction (or endogenous correlation) between the variables of these three models. About 55 input variables
were simulated for the uncertainty analysis of this source category (about 20 from the CO2 emissions from fossil
fuel combustion inventory estimation model and about 35 from the stationary source inventory models).
91 Though emissions from construction and farm use occur due to both stationary and mobile sources, detailed data was not
available to determine the magnitude from each. Currently, these emissions are assumed to be predominantly from mobile
sources.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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.92 For these variables, the uncertainty
ranges were assigned to the input variables based on the data reported in SAIC/EIA (2001).93 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 3-17. Stationary combustion
CH4 emissions in 2011 (including biomass) were estimated to be between 2.8 and 17.5 Tg CO2 Eq. at a 95 percent
confidence level. This indicates a range of 35 percent below to 138 percent above the 2011 emission estimate of 6.3
Tg CO2 Eq.94 Stationary combustion N2O emissions in 2011 (including biomass) were estimated to be between 5.9
and 41.4 Tg CO2 Eq. at a 95 percent confidence level. This indicates a range of 56 percent below to 67 percent
above the 2011 emissions estimate of 22.0 Tg CO2 Eq.
Table 3-17: Tier 2 Quantitative Uncertainty Estimates for ChU and NzO Emissions from
Energy-Related Stationary Combustion, Including Biomass (Tg COz Eq. and Percent)
Source Gas 2011 Emission Uncertainty Range Relative to Emission Estimate3
Estimate
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Stationary Combustion
Stationary Combustion
CH4
N20
6.3
22.0
Lower
Bound
2.8
5.9
Upper
Bound
17.5
41.4
Lower
Bound
-35%
-56%
Upper
Bound
+138%
+67%
a Range of emission estimates predicted by Monte Carlo Stochastic 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.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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.
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.
93 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.
The low emission estimates reported in this section have been rounded down to the nearest integer values and the high
emission estimates have been rounded up to the nearest integer values.
Energy 3-33
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Recalculations Discussion
CH4 and N2O emissions from stationary sources (excluding CO2) across the entire time series were revised due
revised data from EIA (2013) relative to the previous Inventory. The historical data changes resulted in an average
annual decrease of less than 0.1 Tg CO2 Eq. (0.1 percent) in CH4 emissions from stationary combustion and an
average annual increase of less than 0.1 Tg CO2 Eq. (less than 0.1 percent) in N2O emissions from stationary
combustion for the period 1990 through 2010.
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.
Future improvements to the CH4 and N2O from Stationary Combustion category involve research into the
availability of CH4 and N2O from stationary combustion data, and analyzing data reported under EPA's GHGRP. In
examining data from EPA's GHGRP that would be useful to improve the emission estimates for CH4 and N2O from
Stationary Combustion category, particular attention will be made to ensure time series consistency, as the facility-
level reporting data from EPA's GHGRP are not available for all Inventory years as reported in this inventory. In
implementing improvements and integration of data from EPA's GHGRP, the latest guidance from the IPCC on the
use of facility-level data in national inventories will be relied upon. 95
Methodology
Estimates of CH4 and N2O emissions from mobile combustion were calculated by multiplying emission factors by
measures of activity for each fuel and vehicle type (e.g., light-duty gasoline trucks). Activity data included vehicle
miles traveled (VMT) for on-road vehicles and fuel consumption for non-road mobile sources. The activity data and
emission factors used are described in the subsections that follow. A complete discussion of the methodology used
to estimate CH4 and N2O emissions from mobile combustion and the emission factors used in the calculations is
provided in Annex 3.2.
On-Road Vehicles
Estimates of CH4 and N2O emissions from gasoline and diesel on-road vehicles are based on VMT and emission
factors by vehicle type, fuel type, model year, and emission control technology. Emission estimates for alternative
fuel vehicles (AFVs) 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 (CARD) and
Environment Canada laboratory test results of different vehicle and control technology types. The EPA, CARD and
Environment Canada tests were designed following the Federal Test Procedure (FTP), which covers three separate
driving segments, since vehicles emit varying amounts of greenhouse gases 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
95 See
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 bi-fuel or dual-fuel vehicles that may be partially powered by gasoline or diesel.
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
emissions. For each test ran, 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 €62, CO, HC, NOX, and
PM from vehicles under various conditions, to approximate average driving characteristics.97
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 2011 were obtained from the Federal Highway Administration's (FHWA)
Highway Performance Monitoring System database as reported in Highway Statistics (FHWA 1996 through
2013).98 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
2012) and information on total motor vehicle fuel consumption by fuel type from FHWA (1996 through 2013).
VMT for AFVs were taken fromBrowning (2003). The age distributions of the U.S. vehicle fleet were obtained
from EPA (2012, 2000), and the average annual age-specific vehicle mileage accumulation of U.S. vehicles were
obtained from EPA (2000).
Control technology and standards data for on-road vehicles were obtained from EPA's Office of Transportation and
Air Quality (EPA 2007a, 2007b, 2000, 1998, and 1997) and Browning (2005). These technologies and standards are
defined in Annex 3.2, and were compiled from EPA (1993, 1994a, 1994b, 1998, 1999a) and
IPCC/UNEP/OECD/IEA (1997).
Non-Road Vehicles
To estimate emissions from non-road vehicles, fuel consumption data were employed as a measure of activity, and
multiplied by fuel-specific emission factors (in grams of N2O and CH4 per kilogram of fuel consumed).99 Activity
data were obtained from AAR (2008 through 2012), APTA (2007 through 2011), APTA (2006), BEA (1991 through
200), Benson (2002 through 2004), DHS (2008), DOC (1991 through 2012), DOE (1993 through 2012), DESC
(2012), DOT (1991 through 2012), EIA (2008a, 2007a, 2012a, 2002), EIA (2007 through 2011), EIA (1991 through
2013), EPA (2012b), Esser (2003 through 2004), FAA (2013), Gaffney (2007), and Whorton (2006 through 2012).
Emission factors for non-road modes were taken from IPCC/UNEP/OECD/IEA (1997) and Browning (2009).
Uncertainty and Time-Series Consistency
A quantitative uncertainty analysis was conducted for the mobile source sector using the IPCC-recommended Tier 2
uncertainty estimation methodology, Monte Carlo Stochastic Simulation technique, using @RISK software. The
uncertainty analysis was performed on 2011 estimates of CH4 and N2O emissions, incorporating probability
distribution functions associated with the major input variables. For the purposes of this analysis, the uncertainty
was modeled for the following four major sets of input variables: (1) vehicle miles traveled (VMT) data, by on-road
Additional information regarding the model can be found online at http://www.epa.gov/OMS/m6.htm.
98 The source of VMT and fuel consumption is FHWA's VM-1 table. The data collection methodology has undergone
substantial revision for only years 2007-2010, while prior years have remain unchanged Several of the vehicle type categories
have changed. For instance, passenger car has been replaced by "Light duty vehicle, short WB" and other 4 axle- 2 tire has been
replaced by "Light duty vehicle, long WB". With this change in methodology, there are substantial differences in activity data
among vehicle classes, even though overall VML and fuel consumption is unchanged. While this is the best data available on
vehicle activity, the time series reflects changes in the definition of vehicle classes between 2006- 2007 when this change in
methodology was implemented.
The consumption of international bunker fuels is not included in these activity data, but is estimated separately under the
International Bunker Fuels source category.
Energy 3-35
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vehicle and fuel type and (2) emission factor data, by on-road vehicle, fuel, and control technology type, (3) fuel
consumption, data, by non-road vehicle and equipment type, and (4) emission factor data, by non-road vehicle and
equipment 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 €62
emissions, the emission pathways of CH4 and N2O are highly complex.
Mobile combustion CH4 emissions from all mobile sources in 2011 were estimated to be between 1.5 and 2.1 Tg
CO2 Eq. at a 95 percent confidence level. This indicates a range of 14 percent below to 20 percent above the
corresponding 2011 emission estimate of 1.7 Tg CCh Eq. Also at a 95 percent confidence level, mobile combustion
N2O emissions from mobile sources in 2011 were estimated to be between 16.1 and 21.5 TgCChEq., indicating a
range of 13 percent below to 16 percent above the corresponding 2011 emission estimate of 18.5 Tg CCh Eq.
Table 3-18: Tier 2 Quantitative Uncertainty Estimates for ChU and NzO Emissions from
Mobile Sources (Tg COz Eq. and Percent)
Source
Gas
2011 Emission Uncertainty Range Relative to Emission Estimate3
Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mobile Sources
Mobile Sources
CH4
N2O
1.7 1.5 2.1 -14% +20%
18.5 16.1 21.5 -13% +16%
a Range of emission estimates predicted by Monte Carlo Stochastic 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.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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. Each year, adjustments are made to the methodologies
used in calculating emissions in the current Inventory relative to previous Inventory reports.
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Emissions of CH4 from jet fuels are no longer considered to be emitted across the time series from aircraft gas
turbine engines burning jet fuel A at higher power settings. 10° Recent research indicates that modern aircraft jet
engines are typically net consumers of methane (Santoni et al, 2011). Methane is emitted at low power and idle
operation, but at higher power modes aircraft engines consumer methane. Over the range of engine operating
modes, aircraft engines are net consumers of methane on average. Based on this data, methane emissions factors for
jet aircraft were reported as zero in this year's Inventory to reflect the latest emissions testing data. DOE's
methodology for estimating Fuel Oil and Kerosene Sales data was revised across the time series. This affected
vessel bunkering distillate fuel consumption estimates for years 2008-2010 in particular.
Finally, a revision was made to the calculation of Heavy Duty trucks LNG VMT for years 2005 through 2010. This
resulted in significantly lower emissions estimate from LNG vehicles, as well as among all Alternative Fueled
Vehicles.
As a result of these changes, estimates of CH4 emissions were slightly lower than the previous Inventory report,
while N2O emissions were slightly higher.CH4 emissions for 2008 decreased the most, 6.7 percent (0.1 Tg CO2 Eq.).
N2O emissions for 2008 increased by 0.9 percent (0.2 Tg CO2 Eq.), the greatest increase relative to the previous
Inventory.
Planned Improvements
While the data used for this report represent the most accurate information available, four areas have been identified
that could potentially be improved in the short-term given available resources.
• Develop updated emissions factors for diesel vehicles, motorcycle, and biodiesel vehicles. Previous
emission factors were based upon extrapolations from other vehicle classes and new test data from
Environment Canada and other sources may allow for better estimation of emission factors for these
vehicles.
• Develop new emission factors for non-road equipment. The current inventory estimates for non-CO2
emissions from non-road sources are based on emission factors from IPCC guidelines published in 1996.
Recent data on non-road sources from Environment Canada and the California Air Resources Board will be
investigated in order to assess the feasibility of developing new N2O and CH4 emissions factors for non-
road equipment.
• Develop improved estimates of domestic waterborne fuel consumption. The inventory estimates for
residual and distillate fuel used by ships and boats is based in part on data on bunker fuel use from the U.S.
Department of Commerce. Domestic fuel consumption is estimated by subtracting fuel sold for
international use from the total sold in the United States. It may be possible to more accurately estimate
domestic fuel use and emissions by using detailed data on marine ship activity. The feasibility of using
domestic marine activity data to improve the estimates is currently being investigated.
• 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.
100 "Recommended Best Practice for Quantifying Speciated Organic Gas Emissions from Aircraft Equipped with Turbofan,
Turbojet and Turboprop Engines," EPA-420-R-09-901, May 27, 2009 (see
Energy 3-37
-------
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 (metallurgical) coke (manufactured from coking coal). The non-energy applications of these fuels are equally
diverse, including feedstocks for the manufacture of plastics, rubber, synthetic fibers and other materials; reducing
agents for the production of various metals and inorganic products; and non-energy products such as lubricants,
waxes, and asphalt (IPCC 2006).
CO2 emissions arise from non-energy uses via several pathways. Emissions may occur during the manufacture of a
product, as is the case in producing plastics or rubber from fuel-derived feedstocks. Additionally, emissions may
occur during the product's lifetime, such as during solvent use. Overall, throughout the time series and across all
uses, about 61 percent of the total C consumed for non-energy purposes was stored in products, and not released to
the atmosphere; the remaining 39 percent was emitted.
There are several areas in which non-energy uses of fossil fuels are closely related to other parts of this Inventory.
For example, some of the NEU products release CCh at the end of their commercial life when they are combusted
after disposal; these emissions are reported separately within the Energy chapter in the Incineration of Waste 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 the inventory calculations adjust for the effect of net exports on the mass of C in non-energy
applications.
As shown in Table 3-19, fossil fuel emissions in 2011 from the non-energy uses of fossil fuels were 130.6 Tg CC>2
Eq., which constituted approximately 2 percent of overall fossil fuel emissions. In 2011, the consumption of fuels
for non-energy uses (after the adjustments described above) was 4,747.6 TBtu, an increase of 7.2 percent since 1990
(see Table 3-20). About 52.6 Tg (192.8 Tg CO2 Eq.) of the C in these fuels was stored, while the remaining 35.6 Tg
C (130.6 Tg CO2 Eq.) was emitted.
Table 3-19: COz Emissions from Non-Energy Use Fossil Fuel Consumption (Tg COz Eq.)
Year
Potential Emissions
C Stored
Emissions as a % of Potential
Emissions
1990
308.7
191.3 "*
38%
117.4
2005 I
381.7 *
239.0 /
37%
142.7 •«
2007
367.0
232.2
37%
134.9
2008
342.6
203.2
41%
139.5
2009
311.5
187.5
40%
124.0
2010
328.4
195.6
40%
132.8
2011
323.3
192.8
40%
130.6
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 (2012) (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 3-20
and Table 3-21 have been adjusted to subtract non-energy uses that are included in the source categories of the
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Industrial Processes chapter.101 Consumption values were also adjusted to subtract net exports of intermediary
chemicals.
For the remaining non-energy uses, the quantity of C stored was estimated by multiplying the potential emissions by
a storage factor.
• For several fuel types—petrochemical feedstocks (including natural gas for non-fertilizer uses, LPG,
pentanes plus, naphthas, other oils, still gas, special naphtha, and industrial other coal), asphalt and road oil,
lubricants, and waxes—U.S. data on C stocks and flows were used to develop C storage factors, calculated
as the ratio of (a) the C stored by the fuel's non-energy products to (b) the total C content of the fuel
consumed. A lifecycle approach was used in the development of these factors in order to account for losses
in the production process and during use. Because losses associated with municipal solid waste
management are handled separately in this sector under the Incineration of Waste source category, the
storage factors do not account for losses at the disposal end of the life cycle.
• For industrial coking coal and distillate fuel oil, storage factors were taken from IPCC/UNEP/OECD/IEA
(1997), which in turn draws from Marland and Rotty (1984).
• For the remaining fuel types (petroleum coke, miscellaneous products, and other petroleum), IPCC does not
provide guidance on storage factors, and assumptions were made based on the potential fate of C in the
respective NEU products.
Table 3-20: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Year
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical Plants
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401 ° F)
Other Oil (>401 ° F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc. Prod.)
Total
1990
4,165.4
+
8.2 /
281.3 '
1,170.2 ,
1,119.5 /
186.3
84.8
326.0
661.6 „
21.3 .•••'
27.2'
100.8 ..
7.0 /
33.3
137.8 ,
176.0
176.0
86.7
0.7 /'
86.0
4,428.1
: 2005
5,177.2
80.5
11.9 /'
261.0 '
, 1,323.2 „
' 1,666.1 /
160.2
:, W5-1 /•
679.9
499.8 ,
67.7 /
105.2
60.9 .
11.7 /
31.4
112.8 ,
151.3
151.3
121.9
4.6 /
117.3
, 5,450.4
: 2007
5,012.3
2.3
11.9
223.0
. 1,197.0
1,703.3
161.2
91.6
542.5
669.1
44.2
117.8
75.4
17.5
21.9
133.5
152.2
152.2
108.4
5.9
102.5
, 5,272.9
2008
4,626.9
29.2
11.9
227.3
1,012.0
1,609.2
149.6
64.9
467.2
599.1
47.3
147.4
83.2
17.5
19.1
142.0
141.3
141.3
132.1
2.7
129.4
4,900.3
2009
4,340.3
6.4
11.9
220.5
873.1
1,702.6
134.5
70.1
451.3
393.0
133.9
117.2
44.3
17.5
12.2
151.8
127.1
127.1
59.6
1.0
58.5
4,526.9
2010
4,539.0
64.8
10.3
223.1
877.8
1,890.4
149.5
75.1
473.2
405.3
152.5
-
25.6
17.5
15.4
158.8
141.2
141.2
123.6
1.0
122.6
4,803.8
2011
4,490.0
60.8
10.3
222.2
859.5
1,969.6
141.8
26.3
468.0
347.8
167.6
-
20.6
17.5
14.6
163.3
133.9
133.9
123.6
1.0
122.6
4,747.6
+ Does not exceed 0.05 Tg
- Not applicable.
101 These source categories include Iron and Steel Production, Lead Production, Zinc Production, Ammonia Manufacture,
Carbon Black Manufacture (included in Petrochemical Production), Titanium Dioxide Production, Ferroalloy Production, Silicon
Carbide Production, and Aluminum Production.
Energy 3-39
-------
Table 3-21: 2011 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Adjusted Carbon
Non-Energy Content Potential Storage Carbon Carbon Carbon
Use3 Coefficient Carbon Factor Stored Emissions Emissions
Sector/Fuel Type (TBtu) (Tg C/QBtu) (Tg C) (Tg C) (Tg C) (Tg CO2 Eq.)
Industry
Industrial Coking
Coal
Industrial Other Coal
Natural Gas to
Chemical Plants
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401°F)
Other Oil (>401°F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous
Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum
(Misc. Prod.)
Total
4,490.0
60.8
10.3
222.2
859.5
1,969.6
141.8
26.3
468.0
347.8
167.6
-
20.6
17.5
14.6
163.3
133.9
133.9
123.6
1.0
122.6
4,747.6
31.00
25.82
14.47
20.55
17.06
20.20
19.10
18.55
20.17
17.51
27.85
19.74
20.17
19.80
20.31
-
20.20
-
20.20
20.00
83.0
1.9
0.3
3.2
17.7
33.6
2.9
0.5
8.7
7.0
2.9
-
0.4
0.4
0.3
3.3
2.7
2.7
2.5
+
2.5
88.2
0.10
0.59
0.59
1.00
0.59
0.09
0.59
0.59
0.59
0.59
0.30
0.59
0.50
0.58
+
-
0.09
-
0.09
0.10
52.1
0.2
0.2
1.9
17.6
20.0
0.3
0.3
5.2
4.2
1.7
-
0.2
0.2
0.2
+
0.2
0.2
0.2
+
0.2
52.6
30.9
1.7
0.1
1.3
0.1
13.6
2.6
0.2
3.5
2.8
1.2
-
0.2
0.2
0.1
3.3
2.5
2.5
2.2
+
2.2
35.6
113.4
6.2
0.4
4.8
0.3
49.9
9.5
0.7
12.9
10.4
4.4
-
0.6
0.6
0.4
12.2
9.0
9.0
8.2
0.1
8.1
130.6
+ Does not exceed 0.05 Tg
- Not applicable.
a To avoid double counting, net 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 3-19). 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 energy recovery, Toxics Release
Inventory (TRI) releases, hazardous waste incineration, and volatile organic compound, solvent, and non-
combustion CO emissions. 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
2001), National Emissions Inventory (NEI) Air Pollutant Emissions Trends Data (EPA 2010), Toxics Release
Inventory, 1998 (2000b), Biennial Reporting System (EPA 2004, 2009), Resource Conservation and Recovery Act
Information System (2013), and pesticide sales and use estimates (EPA 1998, 1999, 2002, 2004, 2011); the EIA
Manufacturer's Energy Consumption Survey (MECS) (EIA 1994, 1997, 2001, 2005, 2010); the National
Petrochemical & Refiners Association (NPRA 2002); the U.S. Bureau of the Census (1999, 2004, 2009); Bank of
Canada (2012); Financial Planning Association (2006); INEGI (2006); the United States International Trade
Commission (2011); Gosselin, Smith, and Hodge (1984); the Rubber Manufacturers' Association (RMA 2009a,b);
the International Institute of Synthetic Rubber Products (IISRP 2000, 2003); the Fiber Economics Bureau (FEE
2012); and the American Chemistry Council (ACC 2003-2011, 2012). Specific data sources are listed in full detail
in Annex 2.3.
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 Stochastic Simulation technique), provides for the specification of probability
density functions for key variables within a computational structure that mirrors the calculation of the inventory
estimate. The results presented below provide the 95 percent confidence interval, the range of values within which
emissions are likely to fall, for this source category.
As noted above, the non-energy use analysis is based on U.S.-specific storage factors for (1) feedstock materials
(natural gas, LPG, pentanes plus, naphthas, other oils, still gas, special naphthas, and other industrial coal), (2)
asphalt, (3) lubricants, and (4) waxes. For the remaining fuel types (the "other" category in Table 3-20 and Table
3-21), 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 3-22 (emissions) and Table 3-23
(storage factors). Carbon emitted from non-energy uses of fossil fuels in 2011 was estimated to be between 106.1
and 162.9 Tg CCh Eq. at a 95 percent confidence level. This indicates a range of 19 percent below to 25 percent
above the 2011 emission estimate of 130.6 Tg COa 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 3-22: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Non-Energy
Uses of Fossil Fuels (Tg COz Eq. and Percent)
Source
Feedstocks
Asphalt
Lubricants
Waxes
Other
Total
Gas
C02
C02
CO2
CO2
C02
CO2
2011 Emission
Estimate
(Tg C02 Eq.)
84.1
0.3
18.6
0.4
27.1
130.6
Uncertainty Range Relative to Emission Estimate3
(Tg C02
Lower Bound
65.1
0.1
15.4
0.3
16.7
106.1
Eq.)
Upper Bound
119.7
0.6
21.7
0.7
28.6
162.9
(°/
Lower Bound
-23%
-59%
-17%
-28%
-38%
-19%
Upper Bound
42%
119%
16%
64%
6%
25%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Energy 3-41
-------
Table 3-23: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy
Uses of Fossil Fuels (Percent)
Source
Feedstocks
Asphalt
Lubricants
Waxes
Other
Gas
CO2
CO2
C02
C02
C02
2011 Storage
Factor
(%)
59%
99.6%
9%
58%
8%
Uncertainty Range Relative to Emission Estimate3
(%) (%, Relative)
Lower Bound
52%
99%
4%
49%
7%
Upper Bound
61%
100%
17%
71%
41%
Lower Bound
-12%
-1%
-57%
-15%
-2%
Upper Bound
3%
0%
89%
22%
439%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval, as a
percentage of the inventory value (also expressed in percent terms).
In Table 3-23, feedstocks and asphalt contribute least to overall storage factor uncertainty on a percentage basis.
Although the feedstocks category—the largest use category in terms of total carbon flows—appears to have tight
confidence limits, this is to some extent an artifact of the way the uncertainty analysis was structured. As discussed
in Annex 2.3, the storage factor for feedstocks is based on an analysis of six fates that result in long-term storage
(e.g., plastics production), and eleven that result in emissions (e.g., volatile organic compound emissions). Rather
than modeling the total uncertainty around all of these fate processes, the current analysis addresses only the storage
fates, and assumes that all C that is not stored is emitted. As the production statistics that drive the storage values
are relatively well-characterized, this approach yields a result that is probably biased toward understating
uncertainty.
As is the case with the other uncertainty analyses discussed throughout this document, the uncertainty results above
address only those factors that can be readily quantified. More details on the uncertainty analysis are provided in
Annex 2.3.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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 2011 as well as their trends across
the time series.
Petrochemical input data reported by EIA will continue to be investigated in an attempt to address an input/output
discrepancy in the NEU model. Since 2001, the C accounted for in the feedstocks C balance outputs (i.e., storage
plus emissions) exceeds C inputs. Prior to 2001, the C balance inputs exceed outputs. A portion of this discrepancy
has been reduced (see Recalculations Discussion, below) and two strategies have been developed to address the
remaining portion (see Planned Improvements, below).
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Relative to the previous Inventory, emissions from non-energy uses of fossil fuels decreased by an average of 1.0 Tg
CO2 Eq. (0.7 percent) across the entire time series. Changes ranged from an increase of about 7 €62 Eq. in 2010 to a
decrease of about 9 COa Eq. in 1999. The main catalyst for these recalculations was changes to historic fossil fuel
consumption input data acquired from the Energy Information Agency (EIA). The EIA annually revises its fossil
fuel consumption estimates, which may affect historic Inventory emissions from non-energy uses of fossil fuels.
Since the methodology for calculating emissions from non-energy uses of fossil fuels remained the same relative to
the previous inventory, changes to consumption input data is the primary cause of the recalculations. Overall, the net
effect of these changes was a slight decrease in emission estimates across the entire time series.
There are several improvements planned for the future:
• More accurate accounting of C in petrochemical feedstocks. EPA has worked with EIA to determine the
cause of an input/output discrepancy in the C mass balance contained within the NEU model. In the future,
two strategies to reduce or eliminate this discrepancy will continue to be pursued. First, accounting of C in
imports and exports will be improved. The import/export adjustment methodology will be examined to
ensure that net exports of intermediaries such as ethylene and propylene are fully accounted for. Second,
reconsider the use of top-down C input calculation in estimating emissions will be reconsidered.
Alternative approaches that rely more substantially on the bottom-up C output calculation will be
considered instead.
• 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).
• Reviewing the trends in fossil fuel consumption for non-energy uses. Annual consumption for several fuel
types is highly variable across the time series, including industrial coking coal and other petroleum
(miscellaneous products). A better understanding of these trends will be pursued to identify any
mischaracterized or misreported fuel consumption for non-energy uses.
• Updating the average C content of solvents was researched, since the entire time series depends on one
year's worth of solvent composition data. Unfortunately, the data on C emissions from solvents that were
readily available do not provide composition data for all categories of solvent emissions and also have
conflicting definitions for volatile organic compounds, the source of emissive C in solvents. Additional
sources of solvents data will be identified in order to update the C content assumptions.
• Although U.S.-specific storage factors have been developed for feedstocks, asphalt, lubricants, and waxes,
default values from IPCC are still used for two of the non-energy fuel types (industrial coking coal and
distillate oil), and broad assumptions are being used for miscellaneous products and other petroleum. Over
the long term, there are plans to improve these storage factors by conducting analyses of C fate similar to
those described in Annex 2.3 or deferring to more updated default storage factors from IPCC where
available.
• Finally improvements to this category will involve analysis of the data reported under EPA's GHGRP. In
examining data from EPA's GHGRP that would be useful to improve the emission estimates for the C
emitted from non-energy uses of fossil fuels category, particular attention will be made to ensure time
series consistency, as the facility-level reporting data from EPA's GHGRP are not available for all
Inventory years as reported in this Inventory. In implementing improvements and integration of data from
EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories
Energy 3-43
-------
will be relied upon.
102
Incineration is used to manage about 7 to 19 percent of the solid wastes generated in the United States, depending on
the source of the estimate and the scope of materials included in the definition of solid waste (EPA 2000, Goldstein
and Matdes 2001, Kaufman et al. 2004, Simmons et al. 2006, van Haaren et al. 2010). In the context of this section,
waste includes all municipal solid waste (MSW) as well as tires. In the United States, almost all incineration of
MSW occurs at waste-to-energy facilities or industrial facilities where useful energy is recovered, and thus
emissions from waste incineration are accounted for in the Energy chapter. Similarly, tires are combusted for energy
recovery in industrial and utility boilers. Incineration of waste results in conversion of the organic inputs to €62.
According to IPCC guidelines, when the CCh emitted is of fossil origin, it is counted as a net anthropogenic
emission of CCh to the atmosphere. Thus, the emissions from waste incineration are calculated by estimating the
quantity of waste combusted and the fraction of the waste that is C derived from fossil sources.
Most of the organic materials in municipal solid wastes are of biogenic origin (e.g., paper, yard trimmings), and
have their net C flows accounted for under the Land Use, Land-Use Change, and Forestry chapter. However, some
components—plastics, synthetic rubber, synthetic fibers, and carbon black—are of fossil origin. Plastics in the U.S.
waste stream are primarily in the form of containers, packaging, and durable goods. Rubber is found in durable
goods, such as carpets, and in non-durable goods, such as clothing and footwear. Fibers in municipal solid wastes
are predominantly from clothing and home furnishings. As noted above, tires (which contain rubber and carbon
black) are also considered a "non-hazardous" waste and are included in the waste incineration estimate, though
waste disposal practices for tires differ from municipal solid waste. Estimates on emissions from hazardous waste
incineration can be found in Annex 2.3 and are accounted for as part of the C mass balance for non-energy uses of
fossil fuels.
Approximately 26.5 million metric tons of MSW was incinerated in the United States in 2011 (EPA 201 la). CO2
emissions from incineration of waste rose 51 percent since 1990, to an estimated 12.0 Tg €62 Eq. (12,038 Gg) in
2011, as the volume of tires and other fossil C-containing materials in waste increased (see Table 3-24 and Table
3-25). Waste incineration is also a source of N2O and CH4 emissions (De Soete 1993; IPCC 2006). N2O emissions
from the incineration of waste were estimated to be 0.4 Tg CO2 Eq. (1 Gg N2O) in 2011, and have not changed
significantly since 1990. CH4 emissions from the incineration of waste were estimated to be less than 0.05 Tg CO2
Eq. (less than 0.5 Gg CH4) in 2011, and have not changed significantly since 1990.
Table 3-24: COz and NzO Emissions from the Incineration of Waste (Tg COz Eq.)
Gas/Waste Product
CO2
Plastics
Synthetic Rubber in
Tires
Carbon Black in Tires
Synthetic Rubber in
MSW
Synthetic Fibers
N2O
CH4
Total
1990
8.0
5.6
0.3
0.4
0.9
0.8
0.5
+
8.5
2005
12.5
6.9
1.6
2.0
0.8
1.2
0.4
+
12.9
2007
12.7
6.7
1.8
2.3
0.8
1.2
0.4
+
13.1
2008
11.9
6.1
1.7
2.1
0.8
1.2
0.4
+
12.3
2009
11.7
6.2
1.6
1.9
0.8
1.2
0.4
+
12.1
2010
12.0
6.6
1.6
1.9
0.8
1.2
0.4
+
12.4
2011
12.0
6.6
1.6
1.9
0.8
1.2
0.4
+
12.4
+ Does not exceed 0.05 Tg CO2 Eq.
102 See
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 3-25: COz and NzO Emissions from the Incineration of Waste (Gg)
Gas/Waste Product
CO2
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N2O
CH4
1990
7,972
5,588
308
385
854
838
2
+
2005
12,452
6,919
1,599
1,958
765 .
1,211
1
+ /
, 2007
.4 12,711
6,660
1,823
/' 2,268
775
1,185
1
+
2008
11,876
6,148
1,693
2,085
758
1,192
1
+
2009
11,688
6,233
1,560
1,903
767
1,226
1
+
2010
12,038
6,573
1,560
1,903
772
1,230
1
+
2011
12,038
6,573
1,560
1,903
772
1,230
1
+
+ Does not exceed 0.5 Gg.
Emissions of CCh from the incineration of waste include CC>2 generated by the incineration of plastics, synthetic
fibers, and synthetic rubber, as well as the incineration of synthetic rubber and carbon black in tires. These emissions
were estimated by multiplying the amount of each material incinerated by the C content of the material and the
fraction oxidized (98 percent). Plastics incinerated in municipal solid wastes were categorized into seven plastic
resin types, each 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 CCh were calculated based on the amount of scrap tires
used for fuel and the synthetic rubber and carbon black content of tires.
More detail on the methodology for calculating emissions from each of these waste incineration sources is provided
in Annex 3.6.
For each of the methods used to calculate COa emissions from the incineration of waste, data on the quantity of
product combusted and the C content of the product are needed. For plastics, synthetic rubber, and synthetic fibers,
the amount of specific materials discarded as municipal solid waste (i.e., the quantity generated minus the quantity
recycled) was taken fromMunicipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and
Figures (EPA 2000 through 2003, 2005 through 201 Ib) and detailed unpublished backup data for some years not
shown in the reports (Schneider 2007). The most recent Facts and Figures report contains data for 2010, so the
amount of discards in 2011 were assumed to equal 2010 data. The proportion of total waste discarded that is
incinerated was derived from data in BioCycle's "State of Garbage in America" (van Haaren et al. 2010). The most
recent data provides the proportion of waste incinerated for 2008, so the corresponding proportion in 2011 is
assumed to be equal to the proportion in 2008. For synthetic rubber and carbon black in scrap tires, information was
obtained from U.S. Scrap Tire Management Summary for 2005 through 2009 data (RMA 2011). For 2010 and 2011,
synthetic rubber mass in tires is assumed to be equal to that in 2009 due to a lack of more recently available data.
Average C contents for the "Other" plastics category and synthetic rubber in municipal solid wastes were calculated
from 1998 and 2002 production statistics: C content for 1990 through 1998 is based on the 1998 value; C content for
1999 through 2001 is the average of 1998 and 2002 values; and C content for 2002 to date is based on the 2002
value. Carbon content for synthetic fibers was calculated from 1999 production statistics. Information about scrap
tire composition was taken from the Rubber Manufacturers' Association internet site (RMA 2012a).
The assumption that 98 percent of organic C is oxidized (which applies to all waste incineration categories for CC>2
emissions) was reported in EPA's life cycle analysis of greenhouse gas emissions and sinks from management of
solid waste (EPA 2006).
Incineration of waste, including MSW, also results in emissions of N2O and CH4. These emissions were calculated
as a function of the total estimated mass of waste incinerated and an emission factor. As noted above, N2O and CH4
emissions are a function of total waste incinerated in each year; for 1990 through 2008, these data were derived from
Energy 3-45
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the information published in BioCycle (van Haaren et al. 2010). Data on total waste incinerated was not available
for 2009, 2010, or 2011, so this value was assumed to equal the most recent value available (2008).
Table 3-26 provides data on municipal solid waste discarded and percentage combusted for the total waste stream.
According to Covanta Energy (Bahor 2009) and confirmed by additional research based on ISWA (ERC 2009), all
municipal solid waste combustors in the United States are continuously fed stoker units. The emission factors of
N2O and CH4 emissions per quantity of municipal solid waste combusted are default emission factors for this
technology type and were taken from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC
2006).
Table 3-26: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted.
Year Incinerated (% of
Waste Discarded Waste Incinerated Discards)
1990 235,733,657 30,632,057 13.0
2005 259,559,787 25,973,520 10.0
2007
2008
2009
2010
2010
268,279,240
268,541,088
268,54 l,088a
268,54 l,088a
268,54 l,088a
24,788,539
23,674,017
23,674,017 a
23,674,017 a
23,674,017 a
9.2
8.8
8.8a
8.8a
8.8a
a Assumed equal to 2008 value.
Source: van Haaren et al. (2010).
A Tier 2 Monte Carlo analysis was performed to determine the level of uncertainty surrounding the estimates of CO2
emissions and N2O emissions from the incineration of waste (given the very low emissions for CH4, no uncertainty
estimate was derived). IPCC Tier 2 analysis allows the specification of probability density functions for key
variables within a computational structure that mirrors the calculation of the inventory estimate. Uncertainty
estimates and distributions for waste generation variables (i.e., plastics, synthetic rubber, and textiles generation)
were obtained through a conversation with one of the authors of the Municipal Solid Waste in the United States
reports. Statistical analyses or expert judgments of uncertainty were not available directly from the information
sources for the other variables; thus, uncertainty estimates for these variables were determined using assumptions
based on source category knowledge and the known uncertainty estimates for the waste generation variables.
The uncertainties in the waste incineration emission estimates arise from both the assumptions applied to the data
and from the quality of the data. Key factors include MSW incineration rate; fraction oxidized; missing data on
waste composition; average C content of waste components; assumptions on the synthetic/biogenic C ratio; and
combustion conditions affecting N2O emissions. The highest levels of uncertainty surround the variables that are
based on assumptions (e.g., percent of clothing and footwear composed of synthetic rubber); the lowest levels of
uncertainty surround variables that were determined by quantitative measurements (e.g., combustion efficiency, C
content of C black).
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-27. Waste incineration CO2
emissions in 2011 were estimated to be between 9.6 and 14.9 Tg CO2 Eq. at a 95 percent confidence level. This
indicates a range of 21 percent below to 24 percent above the 2011 emission estimate of 12.0 Tg CO2 Eq. Also at a
95 percent confidence level, waste incineration N2O emissions in 2011 were estimated to be between 0.2 and 1.5 Tg
CO2 Eq. This indicates a range of 50 percent below to 320 percent above the 2011 emission estimate of 0.4 Tg CO2
Eq.
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 3-27: Tier 2 Quantitative Uncertainty Estimates for COz and NzO from the Incineration
of Waste (Tg COz Eq. and Percent)
2011
Emission
Estimate
Source Gas (Tg CCh Eq.)
Incineration of Waste CO2 12.0
Incineration of Waste N2O 0.4
Uncertainty Range Relative to Emission Estimate3
(Tg COz Eq.) (%)
Lower
Bound
9.6
0.2
Upper
Bound
14.9
1.5
Lower
Bound
-21%
-50%
Upper
Bound
+24%
+320%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
A source-specific QA/QC plan was implemented for incineration of waste. This effort included a Tier 1 analysis, as
well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved checks specifically
focusing on the activity data and specifically focused on the emission factor and activity data sources and
methodology used for estimating emissions from incineration of waste. Trends across the time series were analyzed
to determine whether any corrective actions were needed. Actions were taken to streamline the activity data
throughout the calculations on incineration of waste.
The current Inventory has been revised relative to the previous report. The calculations for synthetic rubber in MSW
previously did not assume that 98 percent of organic C is oxidized, so this change was made to each of the past
calculations years. This resulted in an average of -0.1 percent change in total CCh Eq. emissions since 1990.
The availability of facility-level waste incineration through EPA's GHGRP will be examined to help better
characterize waste incineration operations in the United States. This characterization could include future
improvements as to the operations involved in waste incineration for energy, whether in the power generation sector
or the industrial sector. Additional examinations will be necessary as, unlike the reporting requirements for this
chapter under the UNFCCC reporting guidelines,103 some facility-level waste incineration emissions reported under
the GHGRP may also include industrial process emissions. In line with UNFCCC reporting guidelines, emissions
for waste incineration with energy recovery are included in this chapter, while process emissions are included in the
industrial processes chapter of this report. In examining data from EPA's GHGRP that would be useful to improve
the emission estimates for the waste incineration category, particular attention will also be made to ensure time
series consistency, as the facility-level reporting data from EPA's GHGRP are not available for all inventory years
as reported in this inventory. Additionally, analyses will focus on ensuring CC>2 emissions from the biomass
component of waste are separated in the facility-level reported data, and on maintaining consistency with national
waste generation and fate statistics currently used to estimate total, national U.S. greenhouse gas emissions. In
implementing improvements and integration of data from EPA's GHGRP, the latest guidance from the IPCC on the
use of facility-level data in national inventories will be relied upon.104
103 See
104 See
Energy 3-47
-------
Additional improvements will be to improve the transparency in the current reporting of waste incineration.
Currently, hazardous industrial waste incineration is included within the overall calculations for the carbon emitted
from the non-energy uses of fossil fuels category. Additional examinations will be made in to any waste
incineration activities covered that do not include energy recovery.
Three types of coal mining related activities release CH4 to the atmosphere: underground mining, surface mining,
and post-mining (i.e., coal-handling) activities. Underground coal mines contribute the largest share of CH4
emissions. In 2011, 128 gassy underground coal mines in the United States employed ventilation systems to ensure
that CH4 levels remained within safe concentrations. These systems can exhaust significant amounts of CH4 to the
atmosphere in low concentrations. Additionally, 23 U.S. coal mines supplemented 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 2011, 14 coal mines collected CH4 from
degasification systems and utilized this gas, thus reducing emissions to the atmosphere; all of these mines sold CH4
to the natural gas pipeline, including one that also used CH4 to fuel a thermal coal dryer. In addition, one of the
mines destroyed a portion of its ventilation air methane using a thermal oxidizer. 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. Post-mining, some of the CH4 retained in the coal is released during processing, storage, and
transport of the coal.
Total CH4 emissions in 2011 were estimated to be 63.2 Tg CO2 Eq. (3,011 Gg), a decline of 25 percent since 1990
(see Table 3-28 and Table 3-29). Of this amount, underground mines accounted for 67 percent, surface mines
accounted for 21 percent, and post-mining emissions accounted for 12 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 CH4 emissions have remained fairly level, while surface coal production and its associated emissions
have generally increased.
Table 3-28: Cm Emissions from Coal Mining (Tg COz Eq.)
Activity
UG Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (UG)
Post-Mining (Surface)
Total
1990
62.3
67.9
(5.6)
12.0 .
7.7 .
2.0
84.1
2005
35.0
50.2
(15.2)
13.3
6.4
2.2
56.9
« 2007
« 35.7
50.9
(15.2)
13.8
6.1
2.2
57.9
2008
44.4
60.5
(16.1)
14.3
6.1
2.3
67.1
2009
49.8
66.1
(16.4)
12.9
5.6
2.1
70.3
2010
51.8
71.5
(19.7)
12.9
5.7
2.1
72.4
2011
42.4
59.0
(16.7)
13.0
5.8
2.1
63.2
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-29: Cm Emissions from Coal Mining (Gg)
Activity
UG Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (UG)
Post-Mining (Surface)
Total
1990
2,968
3,234
(265.9)
573.6
368.3
93.2
4,003
•4 2005
: 1,668
2,390 .
„ (721.6)
633.1
305.9 "
102.9
2,710
2007
1,700
il 2,422
(721.8)
- 658.9
289.6
107.1
2,756
2008
2,113
2,881
(768.0)
680.5
292.0
110.6
3,196
2009
2,367
3,149
(781.6)
614.2
266.7
99.8
3,348
2010
2,463
3,403
(940.2)
614.3
270.2
99.8
3,447
2011
2,015
2,811
(795.6)
619.6
275.6
100.7
3,011
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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
detectable CH4 concentrations. These mine-by-mine measurements are used to estimate CH4 emissions from
ventilation systems.105
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 CH4 to a pipeline, pipeline sales data published by
state petroleum and natural gas agencies were used to estimate degasification emissions. For those mines for which
no other data are available, default recovery efficiency values were developed, depending on the type of
degasification system employed.
Finally, the amount of CH4 recovered by degasification systems and then used (i.e., not vented) was estimated. In
2011, 14 active coal mines sold recovered CH4 into the local gas pipeline networks, and one of these mines used
recovered CH4 to fuel a thermal coal dryer. In addition, one of the mines that used gas from its degasification
system also destroyed a portion of its ventilation air methane using a thermal oxidizer. 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. Data was not available for Pennsylvania
degasification wells for 2011, thus underground emissions avoided were estimated for two mines.
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 3-30) (EIA 2012), 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 3-30: Coal Production (Thousand Metric Tons)
Year
1990
2005
2007
2008
2009
2010
2011
Underground
384,244
334,398
319,139
323,932
301,241
305,862
313,529
Surface
546,808
691,448
720,023
737,832
671,475
676,177
684,807
Total
931,052
1,025,846
1,039,162
1,061,764
972,716
998,337
998,337
MSHA records coal mine CH4 readings with concentrations of greater than 50 ppm (parts per million) CH4. Readings below
this threshold are considered non-detectable.
Energy 3-49
-------
and
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 3-31. Coal mining CH4 emissions in 2011 were
estimated to be between 53.5 and 74.5 Tg CCh Eq. at a 95 percent confidence level. This indicates a range of 15.4
percent below to 17.7 percent above the 2011 emission estimate of 63.2 Tg CC>2 Eq.
Table 3-31: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Coal Mining
(Tg COz Eq. and Percent)
Source
Gas
2011 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Coal Mining
CH4
63.2
53.5 74.5 -15.4% +17.7%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
For the current inventory, updated mine maps were received for the Jim Walter Resources (JWR) Blue Creek #4 and
#7 mines, which showed changes in planned locations of areas to be mined and provided a more accurate depiction
of the dates that certain pre-drainage CMM wells were mined through. As a result, the mined-through dates were
adjusted for some wells relative to the previous Inventory based on updated mine plans, and underground emissions
avoided values changed slightly from 2005 to 2010. Also, several pre-mining wells were mis-identified as post-
mining wells, changing how their emissions were calculated.
Underground coal production for the state of Utah was inadvertently entered as underground and surface coal
production in 2010. As a result, surface coal production values were corrected for 2010.
Future improvements to the Coal Mining category will include analysis of the data reported by underground coal
mines to EPA's GHGRP. This data was first collected in 2012 from underground coal mines liberating 36,500,000
actual cubic feet of methane (approximately 700 MT CH4, or 14,700 MTCChe) per year. In examining data from
EPA's GHGRP that would be useful to improve the emission estimates for the underground coal mines sub-category
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
of the Coal Mining category, particular attention will be made to ensure time series consistency, as the facility-level
reporting data from EPA's GHGRP are not available for all inventory years as reported in this inventory. In
implementing improvements and integration of data from EPA's GHGPJ3, the latest guidance from the IPCC on the
use of facility-level data in national inventories will be relied upon.106
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, 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 CCh Eq. from 1990 through 2011, varying, in
general, by less than 1 percent 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 CCh Eq.) due to the large number of mine closures
from 1994 to 1996 (70 gassy mines closed during the three-year period). In spite of this rapid rise, abandoned mine
emissions have been generally on the decline since 1996. There were fewer than fifteen gassy mine closures during
each of the years from 1998 through 2011, with only two closures in 2011. By 2011, gross abandoned mine
emissions decreased slightly to 7.3 Tg CCh Eq. (see Table 3-32 and Table 3-33). Gross emissions are reduced by
CH4 recovered and used at 38 mines, resulting in net emissions in 2011 of 4.8TgCO2Eq.
Table 3-32: ChU Emissions from Abandoned Coal Mines (Tg COz Eq.)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990
6.0
+
6.0
2005
7.0
1.5
5.5
2007
8.9
3.6
5.3
2008
9.0
3.7
5.3
2009
8.1
3.0
5.1
2010
7.6
2.7
5.0
2011
7.3
2.4
4.8
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg CO2 Eq.
106
See
Energy 3-51
-------
Table 3-33: ChU Emissions from Abandoned Coal Mines (Gg)
Activity 1990 2005 2007 2008 2009 2010 2011
Abandoned Underground Mines 288 334 = 425 429 388 364 347
Recovered & Used + . 70 - 172 177 143 126 116
Total 288 264 254 253 244 237 231
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Gg
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 productivity index or PI term, which is
expressed as the flow rate per unit of pressure change, is essentially constant at the pressures of interest (atmospheric
to 30 psia). A rate-time equation can be generated that can be used to predict future emissions. This decline through
time is hyperbolic in nature and can be empirically expressed as:
q = q, (l+bDit)(-1/b)
where,
q = Gas flow rate at time t in million cubic feet per day (mmcfd)
qi = Initial gas flow rate at time zero (t0), mmcfd
b = The hyperbolic exponent, dimensionless
Dj = 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 flooded mines
was established by fitting a decline curve to emissions from field measurements. An exponential equation was
developed from emissions data measured at eight abandoned mines known to be filling with water located in two of
the five basins. Using a least squares, curve-fitting algorithm, emissions data were matched to the exponential
equation shown below. There was not enough data to establish basin-specific equations as was done with the
vented, non-flooding mines (EPA 2003).
q = qle (-Dt)
where,
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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q = Gas flow rate at time t in mmcfd
qi = Initial gas flow rate at time zero (t0), mmcfd
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 flow rate that would
exist if the mine had an open vent. The total volume emitted will be the same, but emissions will occur over a
longer period of time. The methodology, therefore, treats the emissions prediction from a sealed mine similarly to
the emissions prediction from a vented mine, but uses a lower initial rate depending on the degree of sealing. A
computational fluid dynamics simulator was used with the conceptual abandoned mine model to predict the decline
curve for inhibited flow. The percent sealed is defined as 100 x (l - (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 thousand cubic feet per day (mcfd) account for 98 percent of
all CH4 emissions. This same relationship is assumed for abandoned mines. It was determined that 469 abandoned
mines closing after 1972 produced emissions greater than 100 mcfd when active. Further, the status of 273 of the
469 mines (or 58 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 42 percent
of the mines whose status is unknown were placed in one of these 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 3-34: Number of Gassy Abandoned Mines Present in U.S. Basins, Grouped by Class
According to Post-Abandonment State
Basin
Central Appl.
Illinois
Northern Appl.
Warrior Basin
Western Basins
Total
Sealed
26
30
42
0
27
125
Vented
25
3
22
0
3
53
Flooded Total Known Unknown Total Mines
48
14
16
16
2
96
99
47
80
16
32
274
129
27
36
0
10
202
228
74
116
16
42
476
Inputs to the decline equation require the average emission rate and the date of abandonment. Generally this data is
available for mines abandoned after 1971; 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-1971 mines; thus, their emissions may be characterized by the same decline curves.
During the 1970s, 78 percent of CH4 emissions from coal mining came from seventeen counties in seven states. In
addition, mine closure dates were obtained for two states, Colorado and Illinois, for the hundred year period
extending from 1900 through 1999. The data were used to establish a frequency of mine closure histogram (by
decade) and applied to the other five states with gassy mine closures. As a result, basin-specific decline curve
equations were applied to 145 gassy coal mines estimated to have closed between 1920 and 1971 in the United
States, representing 78 percent of the emissions. State-specific, initial emission rates were used based on average
coal mine 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 vented to determine the total CH4 liberation rate for all
mines that closed between 1992 and 2011. Since the sample of gassy mines (with active mine emissions greater
than 100 mcfd) is assumed to account for 78 percent of the pre-1972 and 98 percent of the post-1971 abandoned
Energy 3-53
-------
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 2011, 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.
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
rather 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 3-35. Abandoned coal mine CH4
emissions in 2011 were estimated to be between 4.0 and 6.2 Tg CCh Eq. at a 95 percent confidence level. This
indicates a range of 18 percent below to 27 percent above the 2011 emission estimate of 4.8 Tg CCh 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 42 percent of the mines), with a ±51
percent uncertainty.
Table 3-35: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Abandoned
Underground Coal Mines (Tg COz Eq. and Percent)
2011 Emission Uncertainty Range Relative to Emission Estimate3
Estimate
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Abandoned Underground
Coal Mines CH4 48 40 62 -18% +27%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Methane 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 €62 emissions from petroleum systems are primarily associated with crude oil production and refining
operations but are negligible in transportation operations. Combustion €62 emissions from fuels are already
accounted for in the Fossil Fuels Combustion source category, and hence have not been taken into account in the
Petroleum Systems source category. Total CH4 and CCh emissions from petroleum systems in 2011 were 31.5 Tg
CO2 Eq. (1,499 Gg CH4) and 0.3 Tg CO2 (347 Gg), respectively. Since 1990, CH4 emissions have declined by 10.6
percent, due to industry efforts to reduce emissions and a decline in domestic oil production. However, in recent
years, domestic oil production has begun to increase again, resulting in greater CH4 emissions from the petroleum
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
sector. Since 2008, when production began to increase, CH4 emissions have increased by almost 5 percent (see Table
3-36 and Table 3-37). CCh emissions have declined by 11.9 percent since 1990, but have similarly increased in
recent years due to increased domestic production. Since 2008, €62 emissions have increased by nearly 16 percent
(see Table 3-38 and Table 3-39).
Production Field Operations. Production field operations account for 98.4 percent of total CH4 emissions from
petroleum systems. Vented CH4 from field operations account for approximately 90 percent of the emissions from
the production sector, uncombusted CH4 emissions (i.e. unburned fuel) account for 6.5 percent, fugitive emissions
are 3.4 percent, and process upset emissions are slightly over two -tenths of a percent. The most dominant sources of
emissions, in order of magnitude, are shallow water offshore oil platforms, natural-gas-powered high bleed
pneumatic devices, oil tanks, natural-gas powered low bleed pneumatic devices, gas engines, deep water offshore
platforms, and chemical injection pumps. These seven sources alone emit about 94 percent of the production field
operations emissions. Offshore platform emissions are a combination of fugitive, vented, and uncombusted fuel
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 oil 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 estimated 25 percent of such pumps that use associated gas to drive pneumatic pumps. The remaining 6 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 CH4 emissions in production field
operations, refer to Annex 3.5.
Since 1990, CH4 emissions from production of crude oil have decreased by 10.8 percent. This reduction was a result
of a significant decrease in annual domestic production. From 1990 until 2008, domestic production of crude oil
decreased by 32 percent. However, since 2008, domestic production of oil has begun to increase again, resulting in
greater emissions of CH4. Since 2008, CH4 emissions from crude oil production have increased by 4.8 percent. This
is mainly from production activities such as pneumatic device venting, tank venting, process upsets, and
combustion.
Vented CCh associated with field operations account for 99 percent of the total CCh emissions from production field
operations, while fugitive and process upsets together account for less than 1 percent of the emissions. The most
dominant sources of vented emissions are oil tanks, high bleed pneumatic devices, shallow water offshore oil
platforms, low bleed pneumatic devices, and chemical injection pumps. These five sources together account for 98.5
percent of the non-combustion COa emissions from production field operations, while the remaining 1.5 percent of
the emissions is distributed among 24 additional activities within the three categories: vented, fugitive and process
upsets. Note that CCh from associated gas flaring is accounted in natural gas systems production emissions.
Crude Oil Transportation. Crude oil transportation activities account for less than 0.4 percent of total CH4
emissions from the oil industry. Venting from tanks, truck loading, and marine vessel loading operations accounts
for 75.4 percent of CH4 emissions from crude oil transportation. Fugitive emissions, almost entirely from floating
roof tanks, account for 18.3 percent of CH4 emissions from crude oil transportation. The remaining 6.6 percent is
distributed among three additional sources within the vented emissions category. Emissions from pump engine
drivers and heaters were not estimated due to lack of data.
Since 1990, CH4 emissions have decreased by almost 29 percent. However, because emissions from crude oil
transportation account for such a small percentage of the total emissions from the petroleum industry, this has had
little impact on the overall emissions. CH4 emissions from crude oil transportation have remained the same since
2000.
Crude Oil Refining. Crude oil refining processes and systems account for less than 1.3 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 81 percent of the emissions, while fugitive and combustion emissions account for
approximately 9 and 9.5 percent, respectively. Refinery system biowdowns 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.
Energy 3-55
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CH4 emissions from refining of crude oil have increased almost 6 percent since 1990; however, similar to the
transportation subcategory, this increase has had little effect on the overall emissions of CH4. Since 1990, CH4
emissions have teetered between 17 and 20 Gg.
Asphalt blowing from crude oil refining accounts for 4.3 percent of the total non-combustion COa emissions in
petroleum systems. Since 2000, the year in which COa emissions from refining peaked, emissions of CC>2 have
dropped by approximately 29 percent.
Table 3-36: Cm Emissions from Petroleum Systems (Tg COz Eq.)
Activity
Production Field Operations
Pneumatic device venting
Tank venting
Combustion & process upsets
Misc. venting & fugitives
Wellhead fugitives
Crude Oil Transportation
Refining
Total
Note: Totals may not sum due to
Table 3-37: Cm Emissions
Activity
Production Field Operations
Pneumatic device venting
Tank venting
Combustion & process upsets
Misc. venting & fugitives
Wellhead fugitives
Crude Oil Transportation
Refining
Total
1990
34.7 :
10.3
5.3
1.9
16.8
0.6
0.1
0.4
35.2 •• ,.
independent rounding.
from Petroleum
1990
1,653
489 V
250
88
799
26
7
18
1,677 *:
Note: Totals may not sum due to independent rounding.
Table 3-38: COz Emissions from Petroleum
Activity 1990 2005
Production Field
Operations
Pneumatic device venting
Tank venting
Misc. venting & fugitives
Wellhead fugitives
Crude Refining
Total
0.4 0.3
+ +
0.3 '•'.: • 0.2
+ •'-,' +
+ • +
+ +
0.4 0.3
2005
28.7 <
8.4
3.9
1.5
14.5
0.4
0.1
0.4
29.2
2007
29.3
8.4
4.1
1.5
15.0
0.4
0.1
0.4
29.8
2008
29.5
8.7
3.9
1.6
14.8
0.5
0.1
0.4
30.0
2009
30.1
8.8
4.2
2.0
14.6
0.5
0.1
0.4
30.5
2010
30.3
8.7
4.4
2.0
14.7
0.5
0.1
0.4
30.8
2011
31.0
9.0
4.7
2.1
14.7
0.5
0.1
0.4
31.5
Systems (Gg)
2005
1,366
398 *J
188
71
690 -
19
5
19
1,390
Systems (Tg
2007 2008
0.3 0.3
0.3 0.2
0.3 0.3
2007
1,396
398
193
72
714
20
5
19
1,421
COz Eq.
2009
0.3
0.3
0.3
2008
1,407
416
185
75
706
24
5
19
1,431
,
2010
0.3
0.3
0.3
2009
1,432
419
202
94
694
23
5
18
1,455
2011
0.3
0.3
0.3
2010
1443
416
211
95
700
22
5
19
1,467
2011
1,475
428
221
99
702
24
5
19
1,499
+ Does not exceed 0.05 Tg CCh Eq.
Note: Totals may not sum due to independent rounding.
Table 3-39: COz Emissions from Petroleum Systems (Gg)
Activity 1990 2005 2007 2008 2009 2010 2011
Production Field
Operations 376 285 j 293 284 306 317 332
Pneumatic device venting 27 , 22 22 23 23 23 24
Tank venting 328 , 246 253 243 265 276 291
Misc. venting & fugitives 18 16 * 16 16 16 16 16
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Wellhead fugitives 1 1 11111
Crude Refining 18 20 J 18 16 14 15 15
Total 394 306 311 300 320 332 347
Note: Totals may not sum due to independent rounding.
The methodology for estimating CH4 emissions from petroleum systems is based on comprehensive studies of CH4
emissions from U.S. petroleum systems (EPA 1996, EPA 1999). These studies calculated emission estimates for 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
negligible.
Key references for activity data and emission factors are the Energy Information Administration annual and monthly
reports (EIA 1990 through 2011, 1995 through 201 la-c), "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, BOEMRE and BOEM reports (BOEMRE 2005,
BOEM 2012a-c), analysis of BOEMRE data (EPA 2005, BOEMRE 2004), the Oil & Gas Journal (OGJ 2012a,b),
the Interstate Oil and Gas Compact Commission (IOGCC 2011, and the United States Army Corps of Engineers,
(1995-2010).
The methodology for estimating CH4 emissions from the 64 oil industry activities employs emission factors initially
developed by EPA (1999). Activity data for the years 1990 through 2011 were collected from a wide variety of
statistical resources. Emissions are estimated for each activity by multiplying emission factors (e.g., emission rate
per equipment item or per activity) by the corresponding activity data (e.g., equipment count or frequency of
activity). EPA (1999) provides emission 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, BOEMRE 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 2011. The number of platforms in shallow water and the number of platforms
in deep water are used as activity data and are taken from Bureau of Ocean Energy Management (BOEM) (formerly
Bureau of Ocean Energy Management, Regulation, and Enforcement [BOEMRE]) statistics (BOEM 2012a-c). For
oil storage tanks, the emissions factor was calculated as the total emissions per barrel of crude charge from E&P
Tank data weighted by the distribution of produced crude oil gravities from the HPDI production database (EPA
1999, HPDI 2010).
For some years, complete activity data were not available. In such cases, one of three approaches was employed.
Where appropriate, the activity data 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 data for heater treaters, reported
statistics for wells and production were used, along with the ratios developed for EPA (1996). In other cases, the
activity data was held constant from 1990 through 2011 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 data. See Annex 3.5 for additional detail.
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 and one activity from petroleum
refining. Emissions are estimated for each activity by multiplying emission factors by their corresponding activity
data. 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 E&P Tank simulation
runs, and the emission factor for asphalt blowing, which was derived using the methodology and sample data from
API (2009).
Energy 3-57
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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 Stochastic Simulation technique), the method employed provides for the specification of probability density
functions for key variables within a computational structure that mirrors the calculation of the inventory estimate.
The results provide the range within which, with 95 percent certainty, emissions from this source category are likely
to fall.
The detailed, bottom-up inventory analysis used to evaluate U.S. petroleum systems reduces the uncertainty related
to the CH4 emission estimates in comparison to a top-down approach. However, some uncertainty still remains.
Emission factors and activity factors are based on a combination of measurements, equipment design data,
engineering calculations and studies, surveys of selected facilities and statistical reporting. Statistical uncertainties
arise from natural variation in measurements, equipment types, operational variability and survey and statistical
methodologies. Published activity factors are not available every year for all 64 activities analyzed for petroleum
systems; therefore, some are estimated. Because of the dominance of the seven major sources, which account for 92
percent of the total methane emissions, the uncertainty surrounding these seven sources has been estimated most
rigorously, and serves as the basis for determining the overall uncertainty of petroleum systems emission estimates.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-40. Petroleum systems CH4
emissions in 2011 were estimated to be between 23.9 and 78.4 Tg CCh Eq., while CC>2 emissions were estimated to
be between 0.3 and 0.9 Tg CCh Eq. at a 95 percent confidence level. This indicates a range of 24 percent below to
149 percent above the 2011 emission estimates of 31.5 and 0.3 Tg CC>2 Eq. for CH4 and CCh, respectively.
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Petroleum
Systems (Tg COz Eq. and Percent)
Source
Petroleum Systems
Petroleum Systems
Gas
CH4
C02
2011 Emission
Estimate
(Tg C02 Eq.)b
31.5
0.3
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Upper Lower
Boundb Boundb Boundb
23.9 78.4 -24%
0.3 0.9 -24%
Upper
Boundb
149%
149%
a Range of 2011 relative uncertainty predicted by Monte Carlo Stochastic Simulation, based on 1995 base
year activity factors, for a 95 percent confidence interval.
b All reported values are rounded after calculation. As a result, lower and upper bounds may not be
duplicable from other rounded values as shown in table.
Note: Totals may not sum due to independent rounding
The petroleum inventory is continually being reviewed and assessed to determine whether emission factors and
activity factors accurately reflect current industry practice. A QA/QC analysis was performed for data gathering and
input, documentation, and calculation. The primary focus of the QA/QC checks is determining if the assumptions in
the Inventory are consistent with current industry practices through review of regulations, public webcasts, and the
Natural Gas STAR Program. Finally, QA/QC checks are consistently conducted to minimize human error in the
model calculations.
Most revisions for the current Inventory relative to the previous report were due to updating the previous report's
data with revised data from existing data sources. In addition, when activity data updates are made for a particular
emissions source, the entire time series is revised or corrected, which may result in slight changes in estimated
emissions from past years.
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
EPA's GHGRP published 2011 emissions data from the first year of reporting from the oil and gas sector in early
2013. GHGRP data will be reviewed for incorporation in the Inventory. Sources where GHGRP national totals are
outside of the range expected based on the Inventory are being closely examined. Key reasons for differences are
being determined. For example, it is being assessed whether differences in activity data or emissions factors are
driving the emissions total difference. Coverage of GHGRP data is also being evaluated; EPA's GHGRP has a
threshold for reporting, versus coverage for the Inventory, which represents total national-level emissions. Finally,
in line with the UNFCCC reporting guidelines and IPCC guidance, it must be determined how to calculate emissions
for the entire time series (i.e., 1990-2011) so that emissions calculated in earlier years use a consistent methodology
with emissions calculated using more recent data from EPA's GHGRP. For some sources, it may be appropriate to
use GHGRP data throughout the time series; for other sources, existing Inventory factors may be appropriate for
other years. In particular, whether certain emissions sources currently accounted for in the Energy sector should be
separately accounted for in the petroleum systems source category estimates (e.g., CCh process emissions from
hydrogen production) will be investigated.
In order to improve the offshore platform emission calculations, more current (post-2000) inventories of the Gulf of
Mexico platforms will be reviewed. This may provide more accurate inventories for the number of platforms,
platform activity, deep water assignments, and oil and gas production.
EPA plans to review Gas STAR reduction data to determine whether some of the reductions deducted from the
Natural Gas System emissions estimates should instead be deducted from the Petroleum Systems emissions
estimates.
Carbon dioxide is produced, captured, transported, and used for Enhanced Oil Recovery (EOR) as well as
commercial and non-EOR industrial applications. This CCh is produced from both naturally-occurring CCh
reservoirs and from industrial sources such as natural gas processing plants and ammonia plants. In the Inventory,
emissions from naturally-produced CCh are estimated based on the application.
In the inventory, COa 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 Production sections of the inventory
report, respectively.
IPCC includes 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 (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 the United States, facilities that conduct geologic sequestration of CO2 and all other facilities that inject CO2,
including facilities conducting enhanced oil and gas recovery, are required to report greenhouse gas data annually to
EPA through its GHGRP. Facilities conducting geologic sequestration of CO2 are required to develop and
implement an EPA-approved site-specific monitoring, reporting and verification plan, and to report the amount of
CO2 sequestered using a mass balance approach. Data from this program will be evaluated closely and opportunities
for improving the emission estimates will be considered.
Preliminary estimates indicate that the amount of CO2 captured from industrial and natural sites is 46.2 Tg CO2 Eq.
(46,198 Gg) (see Table 3-41and Table 3-42). 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.
Energy 3-59
-------
Table 3-41: Potential Emissions from COz Capture and Transport (Tg COz Eq.)
Stage
Acid Gas Removal Plants
Naturally Occurring CO2
Ammonia Production Plants
Pipelines Transporting CO2
1990
4.8
20.8
2005
5.8
28.3
0.7
2007
6.4
33.1
0.7
2008
6.6
36.1
0.6
2009
7.0
39.7
0.6
2010
11.6
34.0
0.7
2011
11.6
34.0
0.7
Total 25.6 34.7 40.1 43.3 47.3 46.2 46.2
+ Does not exceed 0.05 Tg CO2 Eq.
Note; Totals may not sum due to independent rounding.
Table 3-42: Potential Emissions from COz Capture and Transport (Gg)
Stage
Acid Gas Removal Plants
Naturally Occurring CO2
Ammonia Production Plants
Pipelines Transporting CO2
Total
1990
4,832
20,811
+
8
25,643
2005
5,798
28,267
676
7
34,742
2007
6,088
33,086
676
7
40,141
2008
6,630
36,102
580
8
43,311
2009
7,035
39,725
580
8
47,340
2010
11,554
33,967
677
8
46,198
2011
11,554
33,967
677
8
46,198
+ Does not exceed 0.5 Gg.
Note: Totals do not include emissions from pipelines transporting CO2. Totals may not sum due to independent rounding.
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 144.7 Tg CC>2
Eq. (6,893 Gg) of CH4in2011, a 10 percent decrease compared to 1990 emissions (see Table 3-43, Table 3-44, and
Table 3-45) and 32.3 TgCC^Eq. (32,344 Gg) of non-combustion CCh in 2011, a 14 percent decrease compared to
1990 emissions (see Table 3-46 and Table 3-47). The decrease in CH4 emissions is due largely to a decrease in
emissions from transmission and storage due to increased voluntary reductions and a decrease in distribution
emissions due to a decrease in cast iron and unprotected steel pipelines.
CH4 and non-combustion CCh 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 COa 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. Emissions from pneumatic devices, gas wells with liquids unloading, and gas well completions and
refracturing (workovers) with and without hydraulic fracturing account for the majority of CH4 emissions. Flaring
emissions account for the majority of the non-combustion CCh emissions. Emissions from field production
accounted for approximately 37 percent of CH4 emissions and about 33 percent of non-combustion COa emissions
from natural gas systems in 2011. CH4 emissions from field production decreased by nearly 12 percent from 1990-
2011; however, the trend was not stable over the time series—emissions from this source increased 43 percent from
1990-2006, and then declined by 38 percent from 2006 to 2011. Reasons for this trend likely include increased
voluntary reductions, as well as the effects of the recent global economic slowdown.
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 €62
emissions come from acid gas removal units, which are designed to remove CC>2 from natural gas. Processing plants
account for about 14 percent of CH4 emissions and approximately 66 percent of non-combustion CCh 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 30
percent of emissions from natural gas systems, while CCh emissions from transmission and storage account for less
than 1 percent of the non-combustion CC>2 emissions from natural gas systems. CH4 emissions from this source
decreased by 11 percent from 1990-2011 due to increased voluntary reductions (e.g., replacement of high bleed
pneumatics with low bleed pneumatics, replacement of wet seals with dry seals).
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 1,231,000 miles of distribution mains in 2011, an increase of approximately 287,000 miles
since 1990 (PHMSA 2011). Distribution system emissions, which account for approximately 19 percent of CH4
emissions from natural gas systems and less than 1 percent of non-combustion CO2 emissions, result mainly from
fugitive emissions from gate stations and pipelines. An increased use of plastic piping, which has lower emissions
than other pipe materials, has reduced emissions from this stage. Distribution system CH4 emissions in 2011 were
16 percent lower than 1990 levels.
Table 3-43 and Table 3-44 show total CH4 emissions for the four major stages of natural gas systems, in Tg CO2 Eq
(Table 3-43) and Gg (Table 3-44). Table 3-45 gives more information on how the numbers in Table 3-43 were
calculated. Table 3-45 shows the calculated CH4 release (i.e. potential emissions before any controls are applied)
from each stage, and the amount of CH4 that is estimated to have been flared, captured, or otherwise controlled, and
therefore not emitted to the atmosphere. Subtracting the value for CH4 that is controlled from the value for
calculated potential release of CH4 results in the total emissions values. More disaggregated information on
potential emissions and emissions is available in the Annex. See Methodology for Estimating CH4 and CO2
Emissions from Natural Gas Systems.
Table 3-43: Cm Emissions from Natural Gas Systems (Tg COz Eq.)a
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
60.8
17.9 •*
49.2
33.4 *
161.2
2005
75.5
i 14.2
39.5
29.8 '
159.0
2007
83.1
40.8
"', 29.3
168.4
2008
76.4
15.9
41.2
29.9
163.4
2009
61.9
17.5
42.4
28.9
150.7
2010
57.2
16.5
41.6
28.3
143.6
2011
53.4
19.6
43.8
27.9
144.7
aThese values represent CH4 emitted to the atmosphere. CH4 that is captured, flared, or otherwise
controlled (and not emitted to the atmosphere) has been calculated and removed from emission totals.
Note: Totals may not sum due to independent rounding.
Table 3-44: Cm Emissions from Natural Gas Systems (Gg)a
Stage 1990 2005 2007 2008 2009 2010 20~11
Field Production
Processing
2,893
851 ••
3,595
«l 677 ,
3,958
A 723
3,640
756
2,948
834
2,724
787
2,545
932
Energy 3-61
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Transmission and Storage 2,343 ., 1,879 1,942 1,964 2,021 1,980 2,087
Distribution 1,591 M 1,421 j| 1,396 1,422 1,376 1,348 1,329
Total
7,678
7,572
8,018 7,782 7,178 6,838 6,893
a These values represent CFLi emitted to the atmosphere. CH4 that is captured, flared, or otherwise controlled (and not
emitted to the atmosphere) has been calculated and removed from emission totals.
Note: Totals may not sum due to independent rounding.
Table 3-45: Calculated Potential ChUand Captured/Combusted Cmfrom Natural Gas
Systems (Tg COz Eq.)
Calculated Potential}
Field Production
Processing
Transmission and Storage
Distribution
Captured/Combusted
Field Production
Processing
Transmission and Storage
Distribution
Net Emissions
Field Production
Processing
Transmission and Storage
Distribution
1990
161.5
60.9
17.9
49.2 , .:
33.4 :
0.2 list
0.2 mi
+ Sli
+ il
+ '(&;•&
161.2 |||
60.8 ggf
17.9 g|
49.2 SI
33.4 !?;i
2005
205.3
105.4
17.3 •*
51.9
30.8 "
46.3
29.9
3.0 J
12.4
0.9
159.0
75.5
14.2 <•«
39.5
29.8 ~
2007
220.0
119.4
1 18.2
52.0
30.3
51.6
36.3
1 3.1
11.2
1.0
168.4
83.1
1 15.2
40.8
29.3
2008
225.4
123.2
19.0
52.5
30.7
62.0
46.8
3.1
11.3
0.8
163.4
76.4
15.9
41.2
29.9
2009
205.5
103.7
19.3
52.5
30.0
54.7
41.8
1.8
10.0
1.1
150.7
61.9
17.5
42.4
28.9
2010
207.4
105.6
19.9
52.7
29.2
63.8
48.4
3.3
11.1
0.9
143.6
57.2
16.5
41.6
28.3
2011
206.5
103.9
21.1
52.7
28.8
61.8
50.5
1.6
8.8
0.9
144.7
53.4
19.6
43.8
27.9
Note: Totals may not sum due to independent rounding.
+ Emissions are less than 0.1 Tg CCh Eq.
% In this context, "potential" means the total emissions calculated before voluntary reductions and regulatory controls are applied.
Table 3-46: Non-combustion COz Emissions from Natural Gas Systems (Tg COz Eq.)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990 til
9.8 S|;
27.8 itg
0.1 SIS
+ Jfg|
37.7 ms
2005
8.1
21.7 '
0.1 _
+ ,-
29.9
2007
9.5
il 21.2
,, O-1
+
30.9
2008
11.1
21.4
0.1
+
32.6
2009
10.9
21.2
0.1
+
32.2
2010
10.9
21.3
0.1
+
32.3
2011
10.8
21.5
0.1
+
32.3
Note: Totals may not sum due to independent rounding.
+ Emissions are less than 0.1 Tg CCh Eq.
Table 3-47: Non-combustion COz Emissions from Natural Gas Systems (Gg)
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
9,795
27,763
62 ,
46
37,665
2005
8,070
21,746 '
64
42 ' -
29,923
2007
9,546
il 21,199
', 64
; 42
30,851
2008
11,130
21,385
65
42
32,622
2009
10,893
21,188
65
41
32,187
2010
10,862
21,346
65
40
32,313
2011
10,774
21,466
65
40
32,344
Note: Totals may not sum due to independent rounding.
3-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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The methodology for natural gas emissions estimates presented in this Inventory involves the calculation of CH4 and
CO2 emissions for over 100 emissions sources, and then the summation of emissions for each natural gas sector
stage.
The calculation of emissions for each source of emissions in natural gas systems generally occurs in three steps:
Step 1. Calculate Potential Methane - Collect activity data on production and equipment in use and
apply emission factors (i.e., scfgas per unit or activity)
Step 2. Compile Reductions Data -Calculate the amount of the methane that is not emitted, using data on
voluntary action and regulations
Step 3. Calculate Net Emissions - Deduct methane that is not emitted from the total methane potential
estimates to develop net CH4 emissions, and calculate CO? emissions
This approach of calculating potential CH4 and then applying reductions data to calculate net emissions was
used to ensure an accurate time series that reflects real emission trends. As noted below, key data on
emissions are from a 1996 report containing data collected in 1992. Since the time of this study, practices
and technologies have changed. While this study still represents best available data for some emission
sources, using these emission factors alone to represent actual emissions without adjusting for emissions
controls would in many cases overestimate emissions. As updated emission factors reflecting changing
practices are not available for most sources, the 1992 emission factors continue to be used for many sources
for all years of the Inventory, but they are considered to be potential emissions factors, representing what
emissions would be if practices and technologies had not changed over time.
For the inventory, the calculated potential emissions are adjusted using data on reductions reported to Gas
STAR, and data on regulations that result in CH4 reductions. As more data become available, alternate
approaches may be considered. For example, new data—such as API/ANGA data on liquids unloading—can
enable EPA to disaggregate or stratify a source into two or more distinct sub-categories based upon different
technology types, each with unique emission factors.
Step 1. Calculate Potential Methane
In the first step, potential CH4 is calculated by multiplying activity data (such as miles of pipeline or number of
wells) by factors that relate that activity data to potential emissions. Potential CH4 is the amount of CH4 that would
be emitted in the absence of any control technology or mitigation activity. It is important to note that potential CH4
factors in most cases do not represent emitted CH4, and must be adjusted for any emissions-reducing technologies,
or practices, as appropriate. For more information, please see the Annex.
Potential Methane Factors
The primary basis for estimates of CH4 and non-combustion-related CCh 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 factors to characterize emissions from the various components within the operating stages of
the U.S. natural gas system. The EPA/GRI study was based on a combination of process engineering studies,
collection of activity data and measurements at representative gas facilities conducted in the early 1990s. Methane
compositions from GTI 2001 are adjusted year to year using gross production for oil and gas supply National
Energy Modeling System (NEMS) regions from the EIA. Therefore, emission factors may vary from year to year
due to slight changes in the CH4 composition for each NEMS oil and gas supply module region. The majority of
emission factors used in the Inventory were derived from the EPA/GRI study. The emission factors used to estimate
CH4 were also used to calculate non-combustion CCh emissions. The Gas Technology Institute's (GTI, formerly
GRI) Unconventional Natural Gas and Gas Composition Databases (GTI 2001) were used to adapt the CH4 emission
factors into non-combustion related CC>2 emission factors. Additional information about CC>2 content in
transmission quality natural gas was obtained from numerous U.S. transmission companies to help further develop
the non-combustion CCh emission factors.
Although the inventory primarily uses EPA/GRI emission factors, significant updates were made to the emissions
estimates for two sources in recent Inventories: liquids unloading; and gas well completions with hydraulic
Energy 3-63
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fracturing and workovers with hydraulic fracturing (refracturing). In the case of liquids unloading, the methodology
was revised to calculate national emissions through the use region-specific emission factors developed from well
data collected in a survey conducted by API/ANGA (API/ANGA 2012). This approach may result in slight
differences in the national results provided by API/ANGA. It is important to note that in this new methodology, the
emission factors used for liquids unloading are not potential factors, but are factors for actual emissions. See the
Recalculations Discussion for more information on the methodology for liquids unloading. For gas well
completions with hydraulic fracturing and workovers with hydraulic fracturing (refracturing), a potential emission
factor developed by EPA was applied to completions and refracturings to calculate potential emissions (EPA
2012a). Previous Inventory versions also included updated emission factors for production condensate tank vents
(both with and without control devices) and transmission and storage centrifugal compressors (both with wet seals
and with dry seals). See the Annex for more detailed information on the methodology and data used to calculate
CH4 and non-combustion CCh emissions from natural gas systems.
Updates to emission factors using the GHGRP data for natural gas systems (40 CFR 98, subpart W) and other data
will be evaluated as they become available.
Activity Data
Activity data were taken from the following sources: Drillinglnfo, Inc (Drillinglnfo 2012), American Gas
Association (AGA 1991-1998); Bureau of Ocean Energy Management, Regulation and Enforcement (previous
Minerals and Management Service) (BOEMRE 2010a-d); Monthly Energy Review (EIA 201 If); Natural Gas
Liquids Reserves Report (EIA 2005); Natural Gas Monthly (EIA 201 lb,c,e); the Natural Gas STAR Program annual
emissions savings (EPA 2012); Oil and Gas Journal (OGJ 1997-2011); Pipeline and Hazardous Materials Safety
Administration (PHMSA 2011); Federal Energy Regulatory Commission (FERC 2011) and other Energy
Information Administration publications (EIA 2001, 2004, 2010a,d). Data for estimating emissions from
hydrocarbon production tanks were incorporated (EPA 1999). Coalbed CH4 well activity factors were taken from
the Wyoming Oil and Gas Conservation Commission (Wyoming 2009) and the Alabama State Oil and Gas Board
(Alabama 2010).
For many sources, recent direct activity data are not available. For these sources, a set of industry activity data
drivers was developed and is used to update activity data. 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. For example, recent data on various types of field separation
equipment in the production stage (i.e., heaters, separators, and dehydrators) are unavailable. Each of these types of
field separation equipment was determined to relate to the number of non-associated gas wells. Using the number of
each type of field separation equipment estimated by GRI/EPA in 1992, and the number of non-associated gas wells
in 1992, a factor was developed that is used to estimate the number of each type of field separation equipment
throughout the time series. More information on activity data and drivers is available in Annex 3.4.
Step 2. Compile Reductions Data—Calculate the amount of the methane that is not emitted, using data on
voluntary action and regulations
The emissions calculated in Step 1 above represent potential emissions from an activity, and do not take into account
any use of technologies and practices that reduce emissions. To take into account use of such technologies, data,
where available, are collected on both regulatory and voluntary reductions. Regulatory actions reducing emissions
include state regulations requiring controls at completions with hydraulic fracturing, and National Emission
Standards for Hazardous Air Pollutants (NESHAP) regulations for dehydrator vents and condensate tanks.
Voluntary reductions included in the Inventory are those reported to GasSTAR for activities such as voluntary
reduced emissions completions, replacing a high bleed pneumatic device with a low bleed device, and replacing wet
seals with dry seals at reciprocating compressors. For more information on these reductions, please see the Annex.
The emission estimates presented in Table 3-43 and Table 3-44 are the CH4 that is emitted to the atmosphere (i.e.,
net emissions), not potential emissions without capture or flaring.
Future Inventories will include impacts of the New Source Performance Standards (NSPS) for oil and gas (EPA
2012b). The NSPS came into effect in 2012. Reductions resulting from that regulation will first impact emissions
estimates in the 1990 through 2012 Inventory, to be released in 2014. The regulation, which targets VOCs, is
expected to achieve a 95 percent reduction in VOCs from hydraulically fractured gas wells completions and
workovers with hydraulic fracturing (refracturing), with CH4 reduction co-benefits. The rule also has VOC
3-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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reduction requirements for compressors, storage vessels, pneumatic controllers, and equipment leaks at processing
plants, which will also impact CH4 emissions.
Step 3. Calculate Net Emissions
In the final step, emission reductions from voluntary and regulatory actions are deducted from the total calculated
potential emissions to estimate the net emissions that are presented in Table 3 -43, and included in the Inventory
totals. Note that for liquids unloading, condensate tanks, and centrifugal compressors, emissions to the atmosphere
are calculated directly using emission factors that vary by technology.
A quantitative uncertainty analysis was conducted to determine the level of uncertainty surrounding estimates of
emissions from natural gas systems using the recommended methodology from IPCC. EPA produced the results
presented below in Table 3-48, which provide with 95 percent certainty the range within which emissions from this
source category are likely to fall for the year 2011. 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 IPCC guidance notes that in using this method, "some uncertainties that are not addressed by
statistical means may exist, including those arising from omissions or double counting, or other conceptual errors, or
from incomplete understanding of the processes that may lead to inaccuracies in estimates developed from models."
As a result, the understanding of the uncertainty of emissions estimates for this category will evolve and will
improve as the underlying methodologies and datasets improve.
The @RISK model was used to quantify the uncertainty associated with the emissions estimates using the top
twelve emission sources for the year 2010. The uncertainty analysis was not updated for the 1990-2011 Inventory;
instead, the uncertainty ranges calculated previously were applied to 2011 emissions estimates. The majority of
sources in the current inventory were calculated using the same emission factors and activity data for which PDFs
were developed in the 1990-2010 uncertainty analysis. As noted above, several emissions sources have been updated
with this year's Inventory, and the 2010 uncertainty ranges will not reflect the uncertainty associated with the
recently updated emission factors and activity data sources. Future inventories will include updates to the
uncertainty analysis.
The results presented below provide with 95 percent certainty the range within which emissions from this source
category are likely to fall for the year 2011, using the recommended IPCC methodology. The heterogeneous nature
of the natural gas industry makes it difficult to sample facilities that are completely representative of the entire
industry. Additionally, highly variable emission rates were measured among many system components, making the
calculated average emission rates uncertain. The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 3-48. Natural gas systems CH4 emissions in 2011 were estimated to be between 117.2 and
188.1 Tg COa Eq. at a 95 percent confidence level. Natural gas systems non-energy COa emissions in 2011 were
estimated to be between 26.2 and 42.0 Tg CC>2 Eq. at 95 percent confidence level.
Table 3-48: Tier 2 Quantitative Uncertainty Estimates for ChU and Non-energy COz Emissions
from Natural Gas Systems (Tg COz Eq. and Percent)
Source
Natural Gas Systems
Natural Gas Systems'5
Gas
CH4
C02
2011 Emission
Estimate
(Tg C02 Eq.)c
144.7
32.3
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Upper Lower
Bound0 Bound0 Bound0
117.2 188.1 -19%
26.2 42.0 -19%
Upper
Bound0
+30%
+30%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
b An uncertainty analysis for the non-energy CCh emissions was not performed. The relative uncertainty estimated
(expressed as a percent) from the CH4 uncertainty analysis was applied to the point estimate of non-energy CCh
emissions.
Energy 3-65
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0 All reported values are rounded after calculation. As a result, lower and upper bounds may not be duplicable from
other rounded values as shown in Table 3-43.
and
The natural gas emission estimates in the Inventory are continually being reviewed and assessed to determine
whether emission factors and activity factors accurately reflect current industry practice. A QA/QC analysis was
performed for data gathering and input, documentation, and calculation. QA/QC checks are consistently conducted
to minimize human error in the model calculations.
In addition, through review of information associated with regulations, public webcasts, and the Natural Gas STAR
Program, QA/QC checks are performed to determine that the assumptions in the Inventory are consistent with
current industry practices. In the development of the current Inventory, EPA held a stakeholder workshop in
September 2012 on the emissions estimates for Natural Gas Systems. Feedback on the methods, and new data
received from stakeholders helped improve the quality of the estimates in the Inventory. Further, information from
comments received through expert and public review of the Inventory was reviewed and incorporated, as
appropriate.
As a result of the QA/QC checks, the Inventory was updated to correct an error in the production sector estimates for
dehydrators, Kimray pumps, and dehydrator vents. Previous Inventories included the use of an inconsistent
dehydrator ratio (dehydrators per non-associated gas well) for the Northeast region; this was updated to use a
consistent national dehydrator ratio across all regions. This change in dehydrator ratios directly affects the number
of dehydrators and dehydrator venting. However, it also indirectly impacts Kimray pumps because the Kimray pump
activity factor is a function of dehydrator output. The impact of this revision was to increase emissions from these
sources. The largest component of this increase is from Kimray pumps, while the dehydrator vents and dehydrators
constitute a smaller portion of the increase.
The QA/QC checks also identified that emissions from condensate tanks (both controlled and uncontrolled
combined) more than doubled between the previous Inventory report and the current Inventory. The primary cause
of this was the increase of 2010 condensate activity data in the Southwest region from 15 MMbbl/yr (in the previous
Inventory) to 51 MMbbl/yr (in the current Inventory); this increase can be further traced to be almost entirely from
Railroad Commission (RRC) District 8 in Texas. Although this activity data increase is significant, it was officially
reported to El A, and is assumed to be reasonably accurate.
In some cases, the emission reductions reported under the Natural Gas STAR program were incorrectly accounted in
the calculation of annual reductions in previous Inventories. In some cases, the length of time that reductions
occurred for Natural Gas STAR technologies and practices was being aggregated incorrectly. The Gas STAR
reporting categories were reviewed, and it was determined which activities result in a one-time reduction that should
reduce emissions in only one year of the Inventory (e.g. a performing a REC at a well completion) versus activities
that result in ongoing reductions that should continue throughout the time series (e.g. replacing a high-bleed
pneumatic device with a low-bleed pneumatic device). Once the reductions were properly classified, the reductions
were recalculated throughout the time series. This error resulted in an overestimate of emission reductions in some
areas, and an underestimate in other cases.
Finally, Several recent ambient measurement studies (e.g. Petron et al. 2012) have implied higher methane
emissions from natural gas systems in certain areas than would be expected based on bottom-up estimates. EPA is
aware of such studies and is interested in feedback on how information from atmospheric measurement studies can
be used to improve U.S. GHG Inventory estimates. Some factors for consideration include whether measurements
taken are representative of all natural gas producing areas in the U.S., and what activities were taking place at the
time of measurement (general operating conditions, or high-emission venting events), and how such measurements
can inform emission factors and activity data used to calculate national emissions.
Additional QA/QC for Updates
Additional QA/QC was performed on sources with major updates in the 1990-2011 Inventory: hydraulically
fractured well completions and workovers with hydraulic fracturing (refracturing), and liquids unloading. In the
development of this Inventory, the review of preliminary GHGRP data for liquids unloading and well completions
3-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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with hydraulic fracturing, and workovers with hydraulic fracturing (refracturing) was prioritized. Initial data from
GHGRP were used in a QC cross-check against updates under consideration for those emissions sources. The
preliminary cross-checks confirm substantial emissions for these sources and support the direction of the changes.
QA/QC of Update to Completions at Wells with Hydraulic Fracturing and Workovers with
Hydraulic Fracturing (Refracturing)
Additional analyses and data on these sources were reviewed, and both expert and public review comments were
evaluated to QA/QC the Inventory estimates. Further, in the course of development of the 2012 NSPS for Oil and
Gas, data submitted by commenters was analyzed, including detailed data provided by URS. As a result of this
analysis, it was determined that the Inventory potential emission factor for hydraulic fracturing completions and
workovers with hydraulic fracturing (refracturing) provides a valid central estimate of potential emissions from this
source. In the subsequent development of the Inventory, the NSPS data and analysis was reviewed, and it was
determined that it was also appropriate to apply the factor in the Inventory. Since the time of the NSPS analysis,
other information has become available on emissions from hydraulic fracturing. For example, information from
O'Sullivan and Paltsev (2012) was reviewed, which generally supports EPA's potential emission factor as a national
average reflecting potential emissions from all unconventional formation types. The paper also provides more detail
on emissions from shale gas, which may be reviewed related to planned improvements.
Also in the course of the development of the NSPS, EPA received comments and industry data on workovers with
hydraulic fracturing (refracturing) that supported a revision of the refracture rate from 10 percent to 1 percent. The
recent ANGA/API survey data show a similar refracture frequency. EPA made this change in the current Inventory,
which resulted in a reduced number of workovers with hydraulic fracturing compared to previous inventories.107
Some commenters on the public review draft of this Inventory suggested that the amount of flaring and RECs may
be underestimated, especially at workover sites. Commenters calculated net emissions from their own data and
commenters used GHGRP data to calculate lower net emissions per well than calculated by the inventory. Some
commenters recommended that EPA separate the population of wells into those that vent and those that do not vent,
and apply a lower 'net' emission factor for wells that do not vent. Many commenters suggested that EPA continue to
review GHGRP data, and seek other data on emissions from this source to evaluate the appropriateness of the
emission factors used and the coverage of the data on reductions from RECs and flaring. Several commenters
suggested that the potential factor overestimates potential emissions; one commenter provided data showing a
slightly higher potential emission factor. One comment suggested that the count of well completions may be
underestimated, and two commenters suggested that the refracture rate may be an overestimate.
Initial GHGRP data show lower overall CH4 emissions from well completions with hydraulic fracturing and
workovers with hydraulic fracturing (refracturing) than calculated in the Inventory. Facilities reporting to GHGRP
reported emissions of 6.2 TgCO2Eq. of CH4 in 2011, while the Inventory estimate for 2011 is 16.7TgCO2Eq. of
CH4. A result of a lower GHGRP result is to be expected, as GHGRP data exclude well completions occurring at
facilities below the GHGRP reporting threshold of 25,000 mt CO2 Eq.; however, many of the well completions
nationwide are likely captured in the GHGRP data set. The GHGRP data indicate that the Inventory activity data on
well completions and use of RECs compare well with the industry-reported activity data, but that the Inventory may
not be accounting for all of the flaring of gas during completion and workovers with hydraulic fracturing
(refracturing).
QA/QC of Update to Liquids Unloading
EPA also reviewed information on liquids unloading provided in the recent API/ANGA report, and assessed key
differences between API/ANGA with EPA's inventory estimates. As noted below in Recalculations Discussion,
EPA concluded that the data set provided by API/ANGA provided broader coverage, more recent data, and more
information on use of plunger lifts and other control technologies than the other data sets available to EPA at the
time of development of the previous Inventories' emission factors and methodology.
107 por Details of these analyses, please see Background Supplemental Technical Support Document for the Final New Source
Performance Standards for oil and gas, available at http://www.epa.gov/airquality/oilandgas/pdfs/20120418tsd.pdf
Energy 3-67
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EPA received several subsequent comments on this update through the public review of the draft Inventory. Several
comments supported the update. One comment suggested that the update is inappropriate because the API/ANGA
survey may not be representative of all wells in the U.S., and noted available data sources that indicate higher
emission factors for earlier years in the time series. EPA reviewed the available data and concluded that they were
accurate data points for those years, but they do not represent more recent practices. Another commenter noted that
the assumption of no plunger lifts in operation in 1990 is an underestimate. EPA will continue to assess new data on
past liquids unloading practices and emissions and consider improvements to the time series. Commenters suggested
and EPA agreed that it should continue to review GHGRP data, and seek other data on emissions from liquids
unloading to evaluate the appropriateness of the update.
Initial GHGRP data show higher CH4 emissions from liquids unloading than calculated in the inventory. Facilities
reporting to GHGRP reported emissions of 6.0 Tg CO2 Eq. of CH4 in 2011, while the inventory estimate for 2011 is
5.4 Tg CO2 Eq. Due to the GHGRP threshold, a lower GHGRP result would be expected, as data reported should
not include all liquids unloading occurring nationally, only liquids unloading occurring at facilities meeting the
GHGRP reporting threshold. GHGRP data confirm the average emissions per well calculated in the Inventory, but
indicate that emissions from liquids unloading are highly variable. A few GHGRP sources report relatively higher
emissions from this activity that might not be captured in the average emission factors used in the Inventory.
GHGRP data also indicate that nationally, more wells vent emissions from liquids unloading than are included in the
GHG Inventory, and that more wells have plunger lifts than are included in the inventory. GHGRP data from the
Rocky Mountain region in particular show a much larger number of wells practicing liquids unloading than are
captured in the inventory.
New data related to these emission sources will continue to be evaluated, and in particular, GHGRP data submitted
in 2012 and 2013 will be reviewed for possible future improvements to the Inventory.
Information and data related to the emission estimates was received through the Inventory preparation process, the
formal public notice and comment process of the proposed oil and gas NSPS for VOCs, and through a stakeholder
workshop on the natural gas sector emissions estimates. All relevant information provided was carefully evaluated,
and updates were made to two key sources in the expert review draft: liquids unloading, and completions with
hydraulic fracturing and workovers with hydraulic fracturing (refracturing). Additional updates were made to well
counts (activity data), which impact multiple sources. Emission estimates will continue to be refined to reflect the
most robust data and information available. In particular, data from EPA's GHGRP will be reviewed and potentially
incorporated; GHGRP data will be published for the first year of emissions data from the oil and gas sector in 2013.
The recalculations in the current Inventory relative to the previous report primarily impacted CH4 emission estimates
in the production sector, which in 2010 decreased from 126.0 Tg COa Eq. in the previous Inventory to 57.2 Tg CC>2
Eq. in the current Inventory. The key reason for this change is the recalculation for liquids unloading, which in 2010
decreased CH4 emissions from 85.6 Tg COa Eq. in the previous Inventory to 5.4 Tg CC>2 Eq. in the current
Inventory.
Liquids Unloading
The largest change in emissions was due to an update to the methodology for liquids unloading (85.6 Tg €62 Eq. for
2010 in the previous Inventory versus 5.4 TgCChEq. for 2010 in the current Inventory). Data on liquids unloading
from a survey conducted by API/ANGA (API/ANGA 2012) were reviewed. The survey included data from over
50,000 wells. The API/ANGA data and emission factors were compared to the data and emission factors used to
develop the previous and current Inventories' estimates of liquids unloading, and to the GRI/EPA 1996 data used to
develop previous Inventory estimates. Inventories prior to the 2011 Inventory relied on a 1996 GRI factor for
liquids unloading. The GRI factor was based on assumptions of venting using average gas production rates. The
2011 Inventory was updated with new emission factors for liquids unloading, developed by using engineering
equations with depth and pressure data from a sample of wells to calculate casing volume, sample data from a Gas
STAR partner to calculate duration of blowdowns, and assumptions from GRI on number of blowdowns per well
per year. The data set provided by API/ANGA provided broader coverage, more recent data, and more information
on use of plunger lifts and other control technologies than the other data sets. The API/ANGA data showed that
both wells with and without hydraulic fracturing practice liquids unloading, while the Inventory previously only
3-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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included wells without hydraulic fracturing in its estimates for liquids unloading. The data also showed far more
widespread use of control technologies than was being captured in previous Inventories, and shorter emissions
duration from liquids unloading. The API/ANGA data were considered to be an improvement over the previously
used data, and the Inventory was updated with the API/ANGA data. Using the API/ANGA data, liquids unloading
emissions factors were developed for wells with plunger lifts, and for wells without plunger lifts for each NEMS
region.108 These values were then applied to well counts for each region, using the percentages of wells venting for
liquids unloading with plunger lifts, and wells venting without plunger lifts in each region, from the API/ANGA
data. The API/ANGA data showed a larger national percentage of wells using plunger lifts than had been
calculated. This discrepancy is due to the use of API/ANGA data at a regional level. Regions with large well
populations but lower plunger lifts usage caused the calculated national percentage of wells with plunger lifts to be
lower in the Inventory. For similar reasons, the average emissions per well in the Inventory differ from
API/ANGA's national average factors. API/ANGA data were collected in 2010 and 2011. To calculate emissions
for the time series, for each region, the percentage of wells requiring liquids unloading determined from the
API/ANGA data were held constant across the 1990 through 2011 time series. It was then estimated that no plunger
lifts and no artificial lifts were in operation in any region in 1990, and then this estimate was increased linearly up to
the percentage indicated by the API/ANGA data for that region in 2010. Please see the above QA/QC and
Verification Discussion for other information reviewed, and quality checks conducted in relation to this
recalculation.
Completions with Hydraulic Fracturing and Workovers with Hydraulic Fracturing
(Refracturing)
Methodological changes made to the completions with hydraulic fracturing and workovers with hydraulic fracturing
(refracturing) CH4 emission estimates resulted in an increase in the emission estimates (3.8 Tg CChe for 2010 in the
previous Inventory versus 16.7 Tg CCh Eq. for 2010 in the current Inventory). In EPA's analysis for the NSPS
signed April 17, 2012 (EPA 2012a), EPA recalculated emissions for wells with hydraulic fracturing, based on
updated activity data for the number of completed wells with hydraulic fracturing, a revised refracturing rate, and a
revised estimate of state regulatory reductions. In this Inventory, emissions were recalculated using the same
approach. First, well completions numbers were updated using DI Desktop data (Drillinglnfo 2012). Previous
Inventories used data from state websites and had incomplete coverage of completions, omitting completions in tight
sands and most shale formations and coal bed methane (CBM), due to a lack of data. For instance, the previous
Inventory only included gas wells with hydraulic fracturing from CBM wells in six states and from shale gas wells
in Texas. The more complete DI Desktop data used in the current Inventory provided national coverage of
formations that predominantly employ hydraulic fracturing (i.e., shale, tight gas, and CBM), which lead to an
increased number of wells with hydraulic fracturing. Second, consistent with the updated NSPS analysis, a
refracture rate of 1 percent (i.e., 1 percent of all wells with hydraulic fracturing are assumed to be refractured in a
year) was applied. For each year of the Inventory the total count of wells with hydraulic fracturing is multiplied by
0.01 to obtain the number of workovers. Previous Inventories used a refracture rate of 10 percent. Third, the
potential emission factor for these activities was rounded from 9,175 Mscf gas per completion/workover to 9,000
Mscf gas per completion/workover, consistent with the updated NSPS analysis. Finally, the method for reducing
emissions due to reductions resulting from state regulations requiring control of emissions from completions and
workovers was updated. The update applies reductions from state regulations starting in 2008, when these
regulations came into effect. Previous Inventories incorrectly deducted these reductions beginning in 1990. As a
result, the update reduces the percentage of emissions reduced due to regulations from 51 percent across the time
series, to 9 percent in 2008 and 14 percent from 2009 through 2011. As in previous Inventories, voluntary reductions
reported to GasSTAR are also deducted from potential emissions totals.109 For more information on the updates to
emissions from completions with hydraulic fracturing and refracturing, please see the NSPS Technical Support
In some cases, emission factors for wells with plunger lifts are higher than for wells without plunger lifts. Reasons for
unexpected result may include plunger lifts being installed at wells with greater liquids loading, and therefore a need for frequent
lifts with gas venting.
Gas STAR reductions for hydraulic fracturing were updated using 2011 reports between the public review draft (which
deducted 2010 reductions as the 2011 data was not yet available) and this final inventory.
Energy 3-69
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Document (EPA 2012a). Please see the above QA/QC and Verification Discussion for other information reviewed,
and quality checks conducted in relation to this recalculation.
Well Counts
Activity data on well counts was updated using DI Desktop data. Previous Inventories relied on EIA data. As noted
above under Completions with Hydraulic Fracturing and Refracturing, the previous Inventory only included gas
wells with hydraulic fracturing from CBM wells in six states and from shale gas wells in Texas. The more complete
DI Desktop data used in the current Inventory provided national coverage of formations that predominantly
employed hydraulic fracturing (i.e., shale, tight gas, and CBM), which lead to an increased number of wells with
hydraulic fracturing. This in turn led to a decrease in the total number of wells estimated to not employ hydraulic
fracturing. The change in data source also resulted in a change in the number of associated gas wells. Please see the
Annex for more information on how well categories (i.e. associated gas wells, non-associated gas wells, non-
associated gas wells with hydraulic fracturing) were determined.
GasSTAR Reductions
In addition to the corrections discussed above in the QA/QC section, two updates were made to the GasSTAR
Reductions. The first update was to add in reductions from the additional reports received in 2012, which contain
data on emissions reductions up to the year 2011. The second was to remove from the total Gas STAR reductions
number any reductions associated with liquids unloading, as those are already taken into account in the updated
liquids unloading methodology. For more information, please see above Recalculations discussion on liquids
unloading.
The impact of the correction noted in the QA/QC discussion, the update with new Gas STAR data, and the removal
of emissions reductions associated with liquids unloading varies across the time series. The recalculation resulted in
a small increase in total Gas STAR reductions for 2010, from 55.8 Tg CCh Eq. in the previous Inventory versus 56.2
Tg CO2 Eq. in the current Inventory.
During the current Inventory cycle, EPA plans to continue to review available information on these and other
sources, including data from the Greenhouse Gas Reporting Program, to potentially update these estimates.
In addition to these methodological updates, some of the calculated emissions for the 1990 through 2011 time series
have changed from the previous Inventory report due to corrections noted above in QA/QC and Verification
Discussion.
The emission estimates will continue to be refined to reflect the most robust data and information available.
Substantial amounts of new information will be made available in the coming year through a number of channels
including EPA's GHGRP, research studies by various organizations, government and academic researchers, and
industry. There are relevant ongoing studies that are collecting new information related to natural gas system
emissions (e.g. GTI data on pipelines, University of Texas at Austin (UT Austin) and Environmental Defense Fund
(EOF) data on natural gas systems). EPA looks forward to reviewing information and data from these studies as they
become available for potential incorporation in the Inventory.
Gas STAR Reductions
Gas STAR data is being reviewed to determine where reductions can be assigned to specific emissions sources in
the Inventory. In general, the Inventory continues to use aggregated Gas STAR reductions by natural gas system
stage (i.e., production, processing, transmission and storage, and distribution). In some cases, emissions reductions
reported to Gas STAR have been matched to potential emissions calculated in the Inventory, to provide a net
emissions number for specific emissions sources. Table A-132 "CH4 Reductions Derived from the Natural Gas
STAR Program (Gg)" in the Annex presents sources for which Gas STAR reductions can be matched to Inventory
emissions sources. Net emissions values for these sources are presented in Table "Net emissions for select sources
(Gg)" of Annex 3.4. Data will continue to be reviewed to determine where net emissions can be presented for
additional sources. Some reported reduction activities cover multiple Inventory sources. It is not possible at this
3-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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time to attribute those reductions to specific Inventory source categories, and they will remain included in the
"Other" category.
Incorporation of GHGRP Data
EPA's GHGRP published 2011 emissions data from the first year of reporting from the oil and gas sector in early
2013. As noted above in QA/QC and Verification Discussion, in the development of the Inventory, review of
preliminary GHGRP data was prioritized for liquids unloading and well completions with hydraulic fracturing and
workovers with hydraulic fracturing (refracturing), and used this data was used to perform QA/QC checks on the
major updates to these sources.
GHGRP data continues to be reviewed for incorporation in the Inventory. Sources where GHGRP national totals
are outside of the range expected based on the Inventory are being closely examined. Key reasons for differences
are being determined. For example, it is being assessed whether differences in activity data or emissions factors are
driving the emissions total difference. Coverage of GHGRP data is also being evaluated; EPA's GHGRP has a
threshold for reporting, versus coverage for the Inventory, which represents total national-level emissions. Finally,
in line with the UNFCCC reporting guidelines and IPCC guidance, it must be determined how to calculate emissions
for the entire time series (i.e., 1990-2011) so that emissions calculated in earlier years use a consistent methodology
with emissions calculated using more recent data from EPA's GHGRP. For some sources, it may be appropriate to
use GHGRP data throughout the time series; for other sources, existing Inventory factors may be appropriate for
other years.
Source-Specific Updates
Hydraulic Fracturing
Analysis of available data to update reductions data for this source is a priority for next year's Inventory.
Commenters on the public review draft suggested that significant flaring of emissions from completions and
workovers with hydraulic fracturing (refracturing) is occurring that is not taken into account in the Inventory. EPA
will continue to seek information on flaring to ensure that the Inventory reflects industry practices. Several methods
are being considered for estimating well completion emissions reductions to account for RECs and flaring not
reported to Gas STAR. Alternative methods could potentially involve different emission factors for completions
without controls, completions with flaring, and completions with RECS. EPA will review 2011 and 2012 GHGRP
data from this source, and assess how the data can be best incorporated into the inventory, and how the recent data
can best inform emissions calculations throughout the 1990-2012 time series.
Additionally, EPA will assess differences between emissions in different unconventional formation types (e.g., coal
seams, tight sands). Data sources to be reviewed for these updates will include GHGRP data and information from
upcoming studies, such as the UT Austin, EOF, and industry study.
Liquids Unloading
EPA is prioritizing examination of GHGRP data to update emission factors, the number of wells that perform
liquids unloading, and use of plunger lifts for the Inventory. GHGRP data are also being reviewed to assess whether
regional factors can be developed, or whether national factors are more appropriate until more years of data are
available from the GHGRP. Commenters during the public review of the Inventory noted that there were other
available data sources that indicate higher emission factors for earlier years in the time series, and suggested
alternative methods for determining emissions throughout the time series including a step-wise approach based on
production data. EPA will investigate additional data sources on liquids unloading practices and emissions
throughout the time series. EPA plans to complete several analyses of GHGRP data suggested by commenters, such
as examining liquids unloading emissions in different formation types (especially CBM), reviewing emissions
differences between reports using different methods to calculate emissions, and reviewing outliers. EPA will also
take into consideration usage of best available monitoring methods.
Centrifugal Compressors
Through expert review comments, measured emissions data developed by El Paso Corporation for centrifugal
compressors with both wet and dry seals were also identified. Although these studies and data sets could not be
Energy 3-71
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fully evaluated prior to release of the public review draft of the 1990-2011 Inventory, this data and additional data
from upcoming studies will be reviewed as they become available, and related GHGRP data will also be analyzed
for potential updates to this source category.
Produced water
An expert review comment noted that the Inventory includes emissions from produced water from CBM formations
only. Whether other sources of produced water emissions are incorrectly omitted from the Inventory and whether
data is available to include these sources will be investigated, if appropriate.
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 2011 are reported in Table 3-49.
Table 3-49: NQX, CO, and NMVOC Emissions from Energy-Related Activities (Gg)
Gas/Source
NOx
Mobile Combustion
Stationary
International Bunker
Fuels*
Oil and Gas
Waste Combustion
CO
Mobile Combustion
Stationary
Waste Combustion
Oil and Gas
International Bunker
Fuels*
NMVOCs
Mobile Combustion
Oil and Gas
Stationary
Waste Combustion
International Bunker
Fuels*
1990
21,106
10,862
10,023
1,956
139
82
125,640
119,360
5,000
978
302
103
12,620
10,932
554
912
222
57
2005
15,319
9,012
5,858
1,704
321
129
69,062
62,692
4,649
1,403 .
318 /
133
7,798
6,330 /
510
716
241 /
54
, 2007
13,829
7,965
•' 5,432
1,733
318
114
61,739
55,253
4,744
1,421
320
135
7,604
5,742
509
1,120
234
55
2008
13,012
7,441
5,148
1,832
318
106
58,078
51,533
4,792
1,430
322
129
7,507
5,447
509
1,321
230
57
2009
10,887
6,206
4,159
1,692
393
128
49,647
43,355
4,543
1,403
345
121
5,333
4,151
599
424
159
53
2010
10,887
6,206
4,159
1,790
393
128
49,647
43,355
4,543
1,403
345
136
5,333
4,151
599
424
159
56
2011
10,887
6,206
4,159
1,542
393
128
49,647
43,355
4,543
1,403
345
137
5,333
4,151
599
424
159
50
* These values are presented for informational purposes only and are not included in totals.
Note: Totals may not sum due to independent rounding.
Due to the lack of data available at the time of publication, emission estimates for 2010 and 2011 rely on 2009 data
as a proxy. Emission estimates for 2009 were obtained from preliminary data (EPA 2010, EPA 2009), and
disaggregated based on EPA (2003), which, in its final iteration, will be published on the National Emission
Inventory (NET) Air Pollutant Emission Trends web site. Due to redevelopment of the information technology
systems for the NEI, publication of the most recent emissions for these pollutants (i.e., indirect greenhouse gases)
3-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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was not available for this report. 1 10 Emissions were calculated either for individual categories or for many
categories combined, using basic activity data (e.g., the amount of raw material processed) as an indicator of
emissions. National activity data were collected for individual categories from various agencies. Depending on the
category, these basic activity data may include data on production, fuel deliveries, raw material processed, etc.
Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
Program emissions inventory, and other EPA databases.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 20 1 1 . Details on the emission trends through time are described in more detail in the Methodology section,
above.
and
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.
9
Emissions resulting from the combustion of fuels used for international transport activities, termed international
bunker fuels under the UNFCCC, are 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.1l1 These decisions are reflected in the IPCC methodological
guidance, including the 2006 IPCC Guidelines, in which countries are requested to report emissions from ships or
aircraft that depart from their ports with fuel purchased within national boundaries and are engaged in international
transport separately from national totals (IPCC 2006).l n
Two transport modes are addressed under the IPCC definition of international bunker fuels: aviation and marine.113
Greenhouse gases emitted from the combustion of international bunker fuels, like other fossil fuels, include COa,
CH4 and N2O for marine transport modes, and CC>2 and N2O for aviation transport modes. 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
110 por gjj overview of the activities and the schedule for developing the 2011 National Emissions Inventory, with the goal of
producing Version 1 in the summer of 2013, See < http://www.epa.gov/ttn/chief/eis/201 lnei/201 lplan.pdf>
1!! 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).
H2 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil
Aviation Organization.
113 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).
Energy 3-73
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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.114
Emissions of CO2 from aircraft are essentially a function of fuel use. N2O emissions also depend upon engine
characteristics, flight conditions, and flight phase (i.e., take-off, climb, cruise, decent, and landing). Recent data
suggest that little or no CH4 is emitted by modern engines (Anderson et al., 2011), and as a result, CH4 emissions
from this category are considered zero. In jet engines, N2O is primarily produced by the oxidation of atmospheric
nitrogen, and the majority of emissions occur during the cruise phase. International marine bunkers comprise
emissions from fuels burned by ocean-going ships of all flags that are engaged in international transport. Ocean-
going ships are generally classified as cargo and passenger carrying, military (i.e., U.S. 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 2011 from the combustion of international bunker fuels from both
aviation and marine activities were 112.4 Tg CO2 Eq., or 8 percent above emissions in 1990 (see Table 3-50 and
Table 3-51). Emissions from international flights and international shipping voyages departing from the United
States have increased by 71 percent and decreased by 29 percent, respectively, since 1990. The majority of these
emissions were in the form of CO2; however, small amounts of CH4 (from marine transport modes) and N2O were
also emitted.
Table 3-50: COz, Cm, and N26 Emissions from International Bunker Fuels (Tg COz Eq.)
Gas/Mode
CO2
Aviation
Commercial
Military
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
Total
1990
103.5
38.0 -."••
30.0
8.1 ••;
65.4 •
0.1
-
0.1 '
0.9
0.4 ,
0.5 .
104.5
2005
113.1
60.1
55. 6
4.5 /
53.0
0.1
-
0.1
1.0
0.6
0.4
114.3
; 2007
115.3
61.5
/ 57.5
4.0
53.9
0.1
•'
0.1
1.0
0.6
0.4
116.5
2008
114.3
56.1
52.4
3.8
58.2
0.1
-
0.1
1.0
0.6
0.5
115.5
2009
106.4
52.8
49.2
3.6
53.6
0.1
-
0.1
0.9
0.5
0.4
107.5
2010
117.0
61.0
57.4
3.6
56.0
0.1
-
0.1
1.0
0.6
0.4
118.2
2011
111.3
64.9
61.7
3.2
46.5
0.1
-
0.1
1.0
0.6
0.4
112.4
- Assumed to be zero
Note: Totals may not sum due to independent rounding.
emissions.
Includes aircraft cruise altitude
Table 3-51: COz, Cm and NzO Emissions from International Bunker Fuels (Gg)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N2O
1990
103,463
38,034
65,429
7 ;
_
7 •'
3
2005
113,139
60,125 /
53,014
5
,
5
3
,; 2007
4 115,345
61,489
53,856
5
_
5
3
2008
114,342
56,146
58,196
6
_
6
3
2009
106,410
52,785
53,625
5
_
5
3
2010
116,992
60,967
56,025
6
_
6
3
2011
111,316
64,857
46,459
5
_
5
3
114 Naphtha-type jet fuel was used in the past by the military in turbojet and turboprop aircraft engines.
3-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Aviation 1212 2 2 2 2
Marine 2 1 11111
- Assumed to be zero
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-52: Aviation COz and NzO Emissions for International Transport (Tg COz Eg.)
Aviation Mode 1990 2005 2007 2008 2009 2010 2011
Commercial Aircraft 30.0 55.6 57.5 52.4 49.2 57.4 61.7
Military Aircraft 8.1 4.5 4.0 3.8 3.6 3.6 3.2
Total 38.0 60.1 61.5 56.1 52.8 61.0 64.9
+ Does not exceed 0.05 Tg CO2 Eq.
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. Carbon content and
fraction oxidized factors for jet fuel, distillate fuel oil, and residual fuel oil were taken directly from El A and are
presented in Annex 2.1, Annex 2.2, and Annex 3.8 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 (2012) and USAF (1998), and heat content for jet fuel was taken from EIA (2013). A complete description of
the methodology and a listing of the various factors employed can be found in Annex 2.1. See Annex 3.8 for a
specific discussion on the methodology used for estimating emissions from international bunker fuel use by the U.S.
military.
Emission estimates for CH4 and N2O were calculated by multiplying emission factors by measures of fuel
consumption by fuel type and mode. Emission factors used in the calculations of CH4 and N2O emissions were
obtained from the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) and the 2006 IPCC Guidelines
(IPCC 2006). For aircraft emissions, the following values, in units of grams of pollutant per kilogram of fuel
consumed (g/kg), were employed: 0.1 for N2O (IPCC 2006). 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 domestic and international aircraft fuel consumption were developed by the U.S. Federal Aviation
Administration (FAA) using radar-informed data from the FAA Enhanced Traffic Management System (ETMS) for
1990, 2000 through 2011 as modeled with the Aviation Environmental Design Tool (AEDT). This bottom-up
approach is built from modeling dynamic aircraft performance for each flight occurring within an individual
calendar year. The analysis incorporates data on the aircraft type, date, flight identifier, departure time, arrival time,
departure airport, arrival airport, ground delay at each airport, and real-world flight trajectories. To generate results
for a given flight within AEDT, the radar-informed aircraft data is correlated with engine and aircraft performance
data to calculate fuel burn and exhaust emissions. Information on exhaust emissions for in-production aircraft
engines comes from the International Civil Aviation Organization (ICAO) Aircraft Engine Emissions Databank
(EDB). This bottom-up approach is in accordance with the Tier 3B method from the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories.
International aviation CO2 estimates for 1990 and 2000 through 201 lare obtained from FAA's AEDT model (FAA
2013). The radar-informed method that was used to estimate CO2 emissions for commercial aircraft for 1990, and
2000 through 2011 is not possible for 1991 through 1999 because the radar data set is not available for years prior to
2000. FAA developed OAG schedule-informed inventories modeled with AEDT and great circle trajectories for
1990, 2000 and 2010. Because fuel consumption and CO2 emission estimates for years 1991-1999 are unavailable,
consumption estimates for these years were calculated using fuel consumption estimates from the Bureau of
Transportation Statistics (DOT 1991 through 2011), adjusted based on2000 through 2005 data.
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
Energy 3-75
-------
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 2011). 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 3.8 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 2011) for 1990 through 2001, 2007, through 2011, and the
Department of Homeland Security's Bunker Report for 2003 through 2006 (DHS 2008). Fuel consumption data for
2002 was interpolated due to inconsistencies in reported fuel consumption data. Activity data on distillate diesel
consumption by military vessels departing from U.S. ports were provided by DESC (2012). 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 3-54.
Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
U.S. and Foreign Carriers
U.S. Military
Total
1990
3,222
862
4,084
2005
5,983
462
6,445
2007
.' 6,184
410
6,594
2008
5,634
386
6,021
2009
5,293
367
5,660
2010
6,173
367
6,540
2011
6,634
326
6,960
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
2005
3,881
444
471
4,796
: 2007
.' 4,059
358
444
I 4,861
2008
4,373
445
437
5,254
2009
4,040
426
374
4,841
2010
4,141
476
448
5,065
2011
3,463
393
341
4,197
Note: Totals may not sum due to independent rounding.
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.115 For example, smaller aircraft on shorter routes often carry sufficient fuel to
complete several flight segments without refueling in order to minimize time spent at the airport gate or take
advantage of lower fuel prices at particular airports. This practice, called tankering, when done on international
flights, complicates the use of fuel sales data for estimating bunker fuel emissions. Tankering is less common with
the type of large, long-range aircraft that make many international flights from the United States, however. Similar
practices occur in the marine shipping industry where fuel costs represent a significant portion of overall operating
costs and fuel prices vary from port to port, leading to some tankering from ports with low fuel costs.
Uncertainties exist with regard to the total fuel used by military aircraft and ships, and in the activity data on military
operations and training that were used to estimate percentages of total fuel use reported as bunker fuel emissions.
115 See uncertainty discussions under Carbon Dioxide Emissions from Fossil Fuel Combustion.
3-76 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 COa in the 2006 IPCC Guidelines is to use data by specific
aircraft type, number of individual flights and, ideally, movement data to better differentiate between domestic and
international aviation and to facilitate estimating the effects of changes in technologies. The IPCC also recommends
that cruise altitude emissions be estimated separately using fuel consumption data, while landing and take-off (LTO)
cycle data be used to estimate near-ground level emissions of gases other than CCh.116
There is also concern regarding the reliability of the existing DOC (2011) data on marine vessel fuel consumption
reported at U.S. customs stations due to the significant degree of inter-annual variation.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2010. Details on the emission trends through time are described in more detail in the Methodology section,
above
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.
116 U.S. aviation emission estimates for CO, NOX, and NMVOCs are reported by EPA's National Emission Inventory (NET) 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 3-77
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Changes to emission estimates are due to revisions made to historical activity data for marine residual and distillate
fuel oil consumption and a methodology change for collecting U.S. and Foreign Carrier Aviation Jet Fuel
Consumption. The 2011 data formats, developed by the FAA using radar-informed data from the ETMS for 1990,
and 2000 through 2011 as modeled with the AEDT, were used to recalculate prior inventories. This bottom-up
approach is in accordance with the Tier 3B method from the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories. The activity data covers the time series 1990, and 2000 through 2011 with domestic defined as the 50
states and separately as the 50 states and U.S. Territories. Emissions of CH4 from jet fuels are no longer considered
to be emitted across the time series from aircraft gas turbine engines burning jet fuel A at higher power settings 117.
Recent research indicates that modern aircraft jet engines are typically net consumers of methane (Santoni et al.
2011). Methane is emitted at low power and idle operation, but at higher power modes aircraft engines consumer
methane. Over the range of engine operating modes, aircraft engines are net consumers of methane on
average. Based on this data, methane emissions factors for jet aircraft were reported as zero in this year's Inventory
to reflect the latest emissions testing data.
These historical data changes resulted in changes to the emission estimates for the entire time-series to the previous
Inventory, which averaged to an annual decrease in emissions from international bunker fuels of 6.5 Tg CC>2 Eq.
(5.4 percent) in CCh emissions, an annual decrease of 0.04 Tg CC>2 Eq. (25.8 percent) in CH4 emissions, and an
annual average decrease of 0.1 Tg CC>2 Eq. (9.7 percent) inN2O emissions.
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 COa in addition to CH4 and N2O already covered in this chapter. In line with
the reporting requirements for inventories submitted under the UNFCCC, CO2 emissions from biomass combustion
have been estimated separately from fossil fuel CO2 emissions and are not directly included in the energy sector
contributions to U.S. totals. In accordance with IPCC methodological guidelines, any such emissions are calculated
by accounting for net carbon (C) fluxes from changes in biogenic C reservoirs in wooded or crop lands. For a more
complete description of this methodological approach, see the Land Use, Land-Use Change, and Forestry chapter
(Chapter 7), which accounts for the contribution of any resulting CO2 emissions to U.S. totals within the Land Use,
Land-Use Change and Forestry sector's approach.
In 2011, total CO2 emissions from the burning of woody biomass in the industrial, residential, commercial, and
electricity generation sectors were approximately 191.8 Tg CO2 Eq. (191,764 Gg) (see Table 3-55 and Table 3-56).
As the largest consumer of woody biomass, the industrial sector was responsible for 70 percent of the CO2 emissions
from this source. The residential sector was the second largest emitter, constituting 25 percent of the total, while the
commercial and electricity generation sectors accounted for the remainder.
Table 3-55: COz Emissions from Wood Consumption by End-Use Sector (Tg COz Eq.)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
143.2
63.3
7.2
0.7
214.4
2005
148.4
48.3
7.9
1.2
205.7
2007
143.2
45.9
7.8
2.4
199.4
2008
136.0
50.2
8.1
2.8
197.0
2009
123.9
48.4
8.2
2.4
182.8
2010
133.7
47.4
8.1
2.6
191.8
2011
133.4
48.1
7.9
2.4
191.8
Note: Totals may not sum due to independent rounding.
"Recommended Best Practice for Quantifying Speciated Organic Gas Emissions from Aircraft Equipped with Turbofan,
Turbojet and Turboprop Engines," EPA-420-R-09-901, May 27, 2009 (See
3-78 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 3-56: COz Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
143,219
63,286
7,173 ,
733
214,410
2005
148,384
48,282
7,861 .
1,182
205,708
; 2007
143,243
45,929
7,817
2,394
199,383
2008
135,961
50,155
8,126
2,754
196,995
2009
123,856
48,415
8,161
2,353
182,785
2010
133,743
47,437
8,079
2,552
191,811
2011
133,399
48,051
7,880
2,434
191,764
Note: Totals may not sum due to independent rounding.
Biomass-derived fuel consumption in the United States transportation sector consisted primarily of ethanol use.
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.
In 2011, the United States consumed an estimated 1,063 trillion Btu of ethanol, and as a result, produced
approximately 72.8 Tg €62 Eq. (72,763 Gg) (see Table 3-57 and Table 3-58) of COa 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: COz Emissions from Ethanol Consumption (Tg COz Eq.)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990
4.1 : '
0.1 ' ''•
+
4.2
2005
22.4
0.5
0.1
22.9
, 2007
38.1
0.7
0.1
38.9
2008
53.8
0.8
0.1
54.7
2009
61.2
0.9
0.2
62.3
2010
71.2
1.2
0.2
72.6
2011
71.3
1.2
0.2
72.8
+ Does not exceed 0.05 Tg CO2 Eq.
Table 3-58: COz Emissions from Ethanol Consumption (Gg)
End-Use Sector
Transportation*
Industrial
Commercial
Total
1990
4,136
56
34 .
4,227
; 2005
22,414
468
60
22,943
2007
' 38,116
674
135
38,924
2008
53,796
797
146
54,739
2009
61,191
888
194
62,272
2010
71,221
1,192
235
72,648
2011
71,333
1,194
235
72,763
a See Annex 3.2, Table A-88 for additional information on transportation consumption of
these fuels.
Woody biomass emissions were estimated by applying two EIA gross heat contents (Lindstrom 2006) to U.S.
consumption data (see Table 3-59), provided in energy units. This year woody biomass consumption data for the
industrial, residential, and commercial sectors were obtained from EIA 2012, while woody biomass consumption
data for the electricity generation sector was estimated from EPA's Clean Air Market Acid Rain Program dataset
(EPA 2012). The bottom-up analysis of woody biomass consumption based on EPA's Acid Rain Program dataset
indicated that the amount of woody biomass consumption allocated in the EIA statistics should be adjusted.
Therefore, for these estimates, the electricity generation sector's woody biomass consumption was adjusted
downward to match the value obtained from the bottom-up analysis based on EPA's Acid Rain Program dataset. As
the total woody biomass consumption estimate from EIA is considered to be accurate at the national level, the
woody biomass consumption totals for the industrial, residential, and commercial sectors were adjusted upward
proportionately.
One heat content (16.95 MMBtu/MT wood and wood waste) was applied to the industrial sector's consumption,
while the other heat content (15.43 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
Energy 3-79
-------
quantities of woody bio mass to obtain CCh emission estimates. It was assumed that the woody bio mass contains
black liquor and other wood wastes, has a moisture content of 12 percent, and is converted into €62 with 100
percent efficiency. The emissions from ethanol consumption were calculated by applying an emission factor of
18.67 Tg C/QBtu (EPA 2010) to U.S. ethanol consumption estimates that were provided in energy units (EIA 2013)
(see Table 3-60).
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
1,525.8 :
613.7' "
69.6
7.1 ,
2,216.2
2005
1,580.8
468.2
76.2
11.5
2,136.7
2007
1,526.0
J 445.4
75.8
23.2
2,070.5
2008
1,448.4
486.4
78.8
26.7
2,040.3
2009
1,319.5
469.5
79.1
22.8
1,891.0
2010
1,424.8
460.0
78.3
24.7
1,987.9
2011
1,421.2
466.0
76.4
23.6
1,987.2
Table 3-60: Ethanol Consumption by Sector (Trillion Btu)
End-Use Sector
Transportation
Industrial
Commercial
Total
1990
60.4
0.8
0.5
61.7
2005
327.4
6.8
0.9
335.1
2007
556.8
9.8
2.0
568.6
2008
785.8
11.6
2.1
799.6
2009
893.9
13.0
2.8
909.7
2010
1,040.4
17.4
3.4
1,061.2
2011
1,042.0
17.4
3.4
1,062.9
It is assumed that the combustion efficiency for woody biomass is 100 percent, which is believed to be an
overestimate of the efficiency of wood combustion processes in the United States. Decreasing the combustion
efficiency would decrease emission estimates. Additionally, the heat content applied to the consumption of woody
biomass in the residential, commercial, and electric power sectors is unlikely to be a completely accurate
representation of the heat content for all the different types of woody biomass consumed within these sectors.
Emission estimates from ethanol production are more certain than estimates from woody biomass consumption due
to better activity data collection methods and uniform combustion techniques.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2010. Details on the emission trends through time are described in more detail in the Methodology section,
above.
pt*. I is* * m
IJI if^f®*^ 1 rf**i i 1 (SS%*S i f*& $fl& f" iH ii^^^l i If* jf* i f%. ff%
Wood and ethanol consumption values were revised relative to the previous Inventory for 2010 based on updated
information from EIA's Annual Energy Review (EIA 2012a). These revisions of historical data for wood biomass
consumption resulted in an average annual decrease in emissions from wood biomass consumption of about 0.1 Tg
CO2 Eq. (0,1 percent) from 1990 through 2010. Slight adjustments were made to ethanol consumption based on
updated information from EIA (2012a), which slightly decreased estimates for ethanol consumed. As a result of
adjustments to historical EIA data, average annual emissions from ethanol consumption decreased by 0.1 Tg €62
Eq. (0.1 percent) relative to the previous Inventory estimates.
The availability of facility-level combustion emissions through EPA's GHGPJ3 will be examined to help better
characterize the industrial sector's energy consumption in the United States, and further classify business
establishments according to industrial economic activity type. Most methodologies used in EPA's GHGRP are
consistent with IPCC, though for EPA's GHGPJ3, facilities collect detailed information specific to their operations
according to detailed measurement standards, which may differ with the more aggregated data collected for the
3-80 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Inventory to estimate total, national U.S. emissions. In addition, and unlike the reporting requirements for this
chapter under the UNFCCC reporting guidelines, some facility-level fuel combustion emissions reported under the
GHGRP may also include industrial process emissions.118 In line with UNFCCC reporting guidelines, fuel
combustion emissions are included in this chapter, while process emissions are included in the Industrial Processes
chapter of this report. In examining data from EPA's GHGRP that would be useful to improve the emission
estimates for the COa from biomass combustion category, particular attention will also be made to ensure time series
consistency, as the facility-level reporting data from EPA's GHGRP are not available for all inventory years as
reported in this inventory. Additionally, analyses will focus on aligning reported facility-level fuel types and IPCC
fuel types per the national energy statistics, ensuring COa emissions from biomass are separated in the facility-level
reported data, and maintaining consistency with national energy statistics provided by EIA. In implementing
improvements and integration of data from EPA's GHGRP, the latest guidance fromthe IPCC on the use of facility-
level data in national inventories will be relied upon.119
118 See
119 See
Energy 3-81
-------
-------
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), and
nitrous oxide (N2O). The processes addressed in this chapter include iron and steel production and metallurgical
coke production, cement production, lime production, other process uses of carbonates (e.g., flux stone, flue gas
desulfurization, and glass manufacturing), ammonia production and urea consumption, petrochemical production,
aluminum production, soda ash production and use, titanium dioxide production, CO2 consumption, ferroalloy
production, glass production, zinc production, phosphoric acid production, lead production, silicon carbide
production and consumption, nitric acid production, and adipic acid production (see Figure 4-1).
In addition to the three greenhouse gases listed above, there are also industrial sources of man-made fluorinated
compounds called hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). The present
contribution of these gases to the radiative forcing effect of all anthropogenic greenhouse gases is small; however,
because of their extremely long lifetimes, many of them will continue to accumulate in the atmosphere as long as
emissions continue. In addition, many of these gases have high global warming potentials; SF6 is the most potent
greenhouse gas the Intergovernmental Panel on Climate Change (IPCC) has evaluated. Usage of HFCs is growing
rapidly since 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, and SF6 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 2011, industrial processes generated emissions of 326.5 teragrams of CO2 equivalent (Tg CO2 Eq.), or 4.9 percent
of total U.S. greenhouse gas emissions. Carbon dioxide emissions from all industrial processes were 151.3 Tg CO2
Eq. (151,292 Gg) in 2011, or 2.7 percent of total U.S. CO2 emissions. Methane emissions from industrial processes
resulted in emissions of approximately 3.7 Tg CO2 Eq. (177 Gg) in 2011, which was less than 1 percent of U.S. CH4
emissions. N2O emissions from adipic acid and nitric acid production were 26.1 TgCO2Eq. (84 Gg) in 2011, or 7.3
percent of total U.S. N2O emissions. In 2011 combined emissions of HFCs, PFCs, and SF6 totaled 145.3 Tg CO2
Eq. Total emissions from Industrial Processes in 2011 were 3.3 percent more than 1990 emissions.
Industrial Processes 4-1
-------
Figure 4-1: 2011 Industrial Processes Chapter Greenhouse Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Prod. & Metallurgical Coke Prod.
Cement Production
Nitric Acid Production
Lime Production
Adipic Acid Production
Other Process Uses of Carbonates
Electrical Transmission and Distribution
HCFC-22 Production
Petrochemical Production
Aluminum Production
Semiconductor Manufacture
Urea Consumption for Non-Agricultural Purposes
Soda Ash Production and Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Magnesium Production and Processing
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production
Silicon Carbide Production and Consumption
122
Industrial Processes
as a Portion of all Emissions
4.9%
<0,5
10
20
30 40
TgCQjEq,
SO
60
70
The slight increase in overall Industrial Processes emissions since 1990 reflects a range of emission trends among
the industrial process emission sources. Emissions resulting from most types of metal production have declined
significantly since 1990, largely due to production shifting to other countries, but also due to transitions to less-
emissive methods of production (in the case of iron and steel) and to improved practices (in the case of PFC
emissions from aluminum production). Emissions from mineral sources have either increased or not changed
significantly since 1990 but largely track economic cycles, while CCh and CH4 emissions from chemical sources
have either decreased or not changed significantly. HFC emissions from the substitution of ozone depleting
substances have increased drastically since 1990, while the emission trends of HFCs, PFCs, and SF6 from other
sources are mixed. Trends are explained further within each emission source category throughout the chapter.
Table 4-1 summarizes emissions for the Industrial Processes chapter in Tg CCh 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 COz Eq.)
Gas/Source
1990
2005
2007
2008
2009
2010
2011
CO2 188.7 166.3 172.9 160.3 119.0 141.4 151.3
Iron and Steel Production &
Metallurgical Coke Production 99.8 66.7 . 71.3 66.8 43.0 55.7 64.3
Iron and Steel Production 97.3 64.6 • 69.2 64.5 42.1 53.7 62.8
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Metallurgical Coke Production
Cement Production
Lime Production
Other Process Uses of Carbonates
Ammonia Production
Urea Consumption for Non-
Agricultural Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and
Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production
Silicon Carbide Production and
Consumption
CH4
Petrochemical Production
Iron and Steel Production &
Metallurgical Coke Production
Iron and Steel Production
Metallurgical Coke Production
Ferroalloy Production
Silicon Carbide Production and
Consumption
N2O
Nitric Acid Production
Adipic Acid Production
HFCs
Substitution of Ozone Depleting
Substances3
HCFC-22 Production
Semiconductor Manufacturing HFCs
PFCs
Semiconductor Manufacturing
PFCs
Aluminum Production
SF6
Electrical Transmission and
Distribution
Magnesium Production and
Processing
Semiconductor Manufacturing SFe
Total
+ Does not exceed 0.05 Tg CO2 Eq.
2.5
33.3 -
-------
Iron and Steel Production
Metallurgical Coke Production
Cement Production
Lime Production
Other Process Uses of Carbonates
Ammonia Production
Urea Consumption for Non-
Agricultural Purposes
Petrochemical Production
Aluminum Production
Soda Ash Production and
Consumption
Titanium Dioxide Production
Carbon Dioxide Consumption
Ferroalloy Production
Glass Production
Zinc Production
Phosphoric Acid Production
Lead Production
Silicon Carbide Production and
Consumption
CH4
Petrochemical Production
Iron and Steel Production &
Metallurgical Coke Production
Iron and Steel Production
Metallurgical Coke Production
Ferroalloy Production
Silicon Carbide Production and
Consumption
N2O
Nitric Acid Production
Adipic Acid Production
HFCs
Substitution of Ozone Depleting
Substances3
HCFC-22 Production
Semiconductor Manufacturing
HFCs
PFCs
Semiconductor Manufacturing PFCs
Aluminum Production
SF6
Electrical Transmission and
Distribution
Magnesium Production and
Processing
Semiconductor Manufacturing SF
-------
methodological choice to improve rigor and accuracy. In addition, the improvements in using the latest
methodological guidance from the IPCC has been recognized by the UNFCCC's Subsidiary Body for Scientific and
Technological Advice in the conclusions of its 30th Session120. Furthermore, the U.S. hosted the July 2004 experts
meeting for the development of the Industrial Processes & Product Use (IPPU) volume of the 2006 IPCC
Guidelines, and numerous U.S. experts participated in developing the methodological guidance that was published
in that volume121. In this regard, not only is it the most recent guidance from the IPCC, but the 2006 IPCC
Guidelines reflects the input of U.S. experts, which makes it that much more applicable to the inventory as explained
in this chapter.
For industrial process sources of CCh and CH4 emissions, a detailed plan was developed and implemented. This plan
was based on the overall 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 process sources. Examples of these procedures include 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. Tier 1 quality assurance and quality control procedures
have been performed for all industrial process sources. Tier 2 procedures were performed for more significant
emission categories, consistent with IPCC good practice.
For most industrial process categories, 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 are defaults from IPCC 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 2011 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.
120 jjjggg Subsidiary Body for Scientific and Technological Advice (SBSTA) conclusions state, "The SBSTA acknowledged
that the 2006 IPCC Guidelines contain the most recent scientific methodologies available to estimate emissions by sources and
removals by sinks of greenhouse gases (GHGs) not controlled by the Montreal Protocol, and recognized that Parties have gained
experience with the 2006 IPCC Guidelines. The SBSTA also acknowledged that the information contained in the 2006 IPCC
Guidelines enables Parties to further improve the quality of their GHG inventories." See
121 See
Industrial Processes 4-5
-------
On October 30, 2009, the U.S. EPA published a rule for the mandatory reporting of greenhouse gases from large
GHG emissions sources in the United States. Implementation of 40 CFR Part 98 is referred to as EPA's Greenhouse
Gas Reporting Program (GHGRP). 40 CFR part 98 applies to direct greenhouse gas emitters, fossil fuel suppliers,
industrial gas suppliers, and facilities that inject CO2 underground for sequestration or other reasons and requires
reporting by 41 industrial categories. Reporting is at the facility level, except for certain suppliers of fossil fuels and
industrial greenhouse gases. In general, the threshold for reporting is 25,000 metric tons or more of CO 2 Eq. per
year. Calendar year 2010 was the first year in which data were reported for many facilities subject to 40 CFR part
98.
EPA's GHGRP dataset and the data presented in this inventory report are complementary and, as indicated in the
respective planned improvements sections for source categories in this chapter, EPA is analyzing how to use
facility-level GHGRP data to improve the national estimates presented in this inventory, giving particular
consideration to ensuring time series consistency. Most methodologies used in EPA's GHGRP are consistent with
IPCC, though for EPA's GHGRP, facilities collect detailed information specific to their operations according to
detailed measurement standards. This may differ with the more aggregated data collected for the inventory to
estimate total, national U.S. emissions. It should be noted that the definitions for source categories in the GHGRP
may differ from those used in this inventory in meeting the UNFCCC reporting guidelines. In line with the
UNFCCC reporting guidelines, the inventory report is a comprehensive accounting of all emissions from source
categories identified in the IPCC guidelines.Further information on the reporting categorizations in EPA's GHGRP
and specific data caveats associated with monitoring methods in EPA's GHGRP has been provided on the EPA's
GHGRP website.
EPA presents the data collected by EPA's GHGRP through a data publication tool that allows data to be viewed in
several formats including maps, tables, charts and graphs for individual facilities or groups of facilities.
Cement production is an energy- and raw material-intensive process that results in the generation of CO2 from both
the energy consumed in making the cement and the chemical process itself. Emissions from fuels consumed for
energy purposes during the production of cement are accounted for in the Energy chapter. COa emitted from the
chemical process of cement production is the second largest source of industrial CO2 emissions in the United States.
Cement is produced in 36 states and Puerto Rico. Texas, California, Missouri, Florida, Pennsylvania, Michigan and
Alabama were the seventh largest (in descending order) cement-producing states in 2011 and accounted for
approximately half of U.S. production (USGS 2012).
During the cement production process, calcium carbonate (CaCOs) 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. Next, the lime is combined with silica-containing materials to produce clinker (an intermediate product),
with the earlier byproduct CO2 being released to the atmosphere. The clinker is then allowed to cool, mixed with a
small amount of gypsum and potentially other materials (e.g., slag), and used to make Portland cement.122
122 Approximately three percent of total clinker production is used to produce masonry cement, which is produced using
plasticizers (e.g., ground limestone, lime) and Portland cement (USGS 2011). Carbon dioxide emissions that result from the
production of lime used to create masonry cement are included in the Lime Manufacture source category.
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
In 2011, U.S. clinker production totaled 61,171 thousand metric tons (USGS 2012).123 The resulting CO2 emissions
were estimated to be 31.6 Tg CO2 Eq. (31,632 Gg) (see Table 4-3).
Table 4-3: COz Emissions from Cement Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 33.3 33,278
2005 45.2 45,197
2007 44.5 44,538
2008 40.5 40,531
2009 29.0 29,018
2010 30.9 30,924
2011 31.6 31,632
Greenhouse gas emissions from cement production grew every year from 1991 through 2006, but have decreased
since. Emissions since 1990 have decreased by eight percent. Emissions decreased significantly between 2008 and
2009, due to the economic recession and associated decrease in demand for construction materials. Emissions
increased slightly from 2009 levels in 2010, and increased slightly again in 2011 due to increasing consumption;
however, emissions were still 22 percent lower in 2010 than peak emissions in 2006. Cement continues to be a
critical component of the construction industry; therefore, the availability of public and private construction funding,
as well as overall economic conditions, have considerable influence on cement production.
CO2 emissions from cement production are created by the chemical reaction of carbon-containing minerals (i.e.,
calcining limestone) in the cement kiln. While in the kiln, limestone is broken down into CO2 and lime, with the
CO2 released to the atmosphere. The quantity of €62 emitted during cement production is directly proportional to
the lime content of the clinker. During calcination, each mole of limestone (CaCOs) heated in the clinker kiln forms
one mole of lime (CaO) and one mole of CCh:
CaCO3 + heat -> CaO + CO2
CO2 emissions were estimated using the Tier 2 methodology from the 2006 IPCC Guidelines. The Tier 2
methodology was used because detailed and complete data (including weights and composition) for carbonate(s)
consumed in clinker production are not available, and thus a rigorous Tier 3 approach is impractical. Tier 2 specifies
the use of aggregated plant or national clinker production data and an emission factor, which is the product of the
average lime fraction for clinker of 65 percent and a constant reflecting the mass of CCh released per unit of lime
(vanOss 2012). This calculation yields an emission factor of 0.51 tons of CCh per ton of clinker produced, which
was determined as follows:
£F =0.6460 CaOx
Clinker
44.01 g/moleCO2
56.08 g/moleCaO
= 0.5070 tons CO /tonclinker
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
123 Based on preliminary data from the Cement Mineral Industry Survey for December 2011, Table 4 (USGS 2012).
Industrial Processes 4-7
-------
emissions should be estimated as two percent of the CCh emissions calculated from clinker production (when data
on CKD generation are not available).124 Total cement production emissions were calculated by adding the
emissions from clinker production to the emissions assigned to CKD (IPCC 2006).
Furthermore, small amounts of impurities (i.e., not calcium carbonate) may exist in the raw limestone used to
produce clinker. The proportion of these impurities is generally minimal, although a small (one to two percent)
amount of magnesium oxide (MgO) may be desirable as a flux. Per the IPCC Tier 2 methodology, a correction for
magnesium oxide is not used, since the amount of magnesium oxide from carbonate is likely very small and the
assumption of a 100 percent carbonate source of CaO already yields an overestimation of emissions (IPCC 2006).
The 1990 through 2011 activity data for clinker production (see Table 4-4) were obtained from USGS (US Bureau
of Mines 1990 through 1993, USGS 1995 through 2012). The data were compiled by USGS (to the nearest ton)
through questionnaires sent to domestic clinker and cement manufacturing plants.
Table 4-4: Clinker Production (Gg)
Year Clinker
1990 64,355
2005 87,405
2007 86,130
2008 78,382
2009 56,116
2010 59,802
2011 61,171a
Note: Clinker
production from 1990-
1994 currently includes
Puerto Rico. Clinker
production from 1995-
2011 excludes Puerto
Rico.
Preliminary data; will
be updated when 2011
Mineral Yearbook for
cement is published.
and
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 materials are CaCCb, 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; 65 percent is used as a
representative value (van Oss 2012). CKD loss can range from 1.5 to 8 percent depending upon plant specifications.
Additionally, some amount of CCh 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 CCh 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 CCh 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. Based on the uncertainties associated with total U.S. clinker production, the CCh emission factor for
clinker production, and the emission factor for additional CO2 emissions from CKD, 2011 CCh emissions from
cement production were estimated to be between 29.4 and 34.0 Tg CCh Eq. at the 95 percent confidence level. This
124 Default IPCC clinker and CKD emission factors were verified through expert consultation with van Oss (2012).
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
confidence level indicates a range of approximately 7.18 percent below and 6.89 percent above the emission
estimate of 31.6 Tg CO2 Eq.
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Cement
Production (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Upper Lower
Lower Bound Bound Bound Upper Bound
Cement Production CCh 31.6 29.4 34.0 -7.18% +6.89%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
€
Activity data for the time series was revised for the current inventory. Specifically, clinker production data for 2006
through 2011 were revised to reflect updated USGS data. In a given inventory year, advance clinker data is typically
used. This data is typically finalized several years later by USGS. The published time series was reviewed to
ensure time series consistency. Published data generally differed from advance data by approximately 1,000 metric
tons, or 1 percent of the total. Details on the emission trends through time are described in more detail in the
Methodology section, above.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Cement Production source category. Particular attention will be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as facility-level reporting data from EPA's GHGRP, with the program's
initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory years (i.e.,
1990 through 2009) as required for this inventory. In implementing improvements and integration of data from
EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will be
relied upon.125
Lime is an important manufactured product with many industrial, chemical, and environmental applications. Its
major uses are in steel making, flue gas desulfurization systems at coal-fired electric power plants, construction, and
water purification. Emissions from fuels consumed for energy purposes during the production of lime are accounted
for in the Energy chapter. Lime is also used as a CO2 scrubber, and there has been experimentation on the use of
lime to capture CO2 from electric power plants. 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]).
125 See
Industrial Processes 4-9
-------
Lime production involves three main processes: stone preparation, calcination, and hydration. Carbon dioxide is
generated during the calcination stage, when limestone—mostly calcium carbonate (CaCOs)—is roasted at high
temperatures in a kiln to produce CaO and COa. The CCh is given off as a gas and is normally emitted to the
atmosphere. Some of the CCh generated during the production process, however, is recovered at some facilities for
use in sugar refining and precipitated calcium carbonate (PCC) production.126
Lime production in the United States—including Puerto Rico—reported to be 19,059 thousand metric tons in 2011
(USGS 2012). This production resulted in estimated net CO2 emissions of 13.8 Tg CO2 Eq. (13,795 Gg) (see Table
4-6 and Table 4-7).
Table 4-6: COz Emissions from Lime Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 11.5 11,488
2005 14.3 14,322
2007
2008
2009
2010
2011
14.6
14.3
11.2
13.1
13.8
14,579
14,345
11,164
13,145
13,795
Table 4-7: Potential, Recovered, and Net COz Emissions from Lime Production (Gg)
Year Potential Recovered" Net Emissions
1990 11,959 471 11,488
2005 15,074 752 14,322
2007
2008
2009
2010
2011
15,248
14,992
11,852
13,788
14,414
669
647
688
644
620
14,579
14,345
11,164
13,145
13,795
1 For sugar refining and PCC production.
Note: Totals may not sum due to independent rounding.
In 2011, lime production increased 5 percent from 2010 levels to 19,059 thousand metric tons, due to an increase in
steel production. Lime production in 2010 rebounded from a 21 percent decline in 2009 to 18,233 thousand metric
tons, which is still eight percent below 2008 levels. Lime production declined in 2009 mostly due to the economic
recession and the associated significant downturn in major markets such as construction and steel. The surprising
rebound in 2010 is primarily due to increased consumption in steelmaking, chemical and industrial uses, and in flue
gas desulfurization. The contemporary lime market is approximately distributed across five end-use categories as
follows: metallurgical uses, 38 percent; environmental uses, 31 percent; chemical and industrial uses, 22 percent;
construction uses, eight percent; and refractory dolomite, one percent. Metallurgical uses made up almost 87
percent of the increase in lime consumption in 2011, and it continues to be the major component of the industry's
recovery since the 2008 through 2009 economic recession.
126 PQQ js obtained from the reaction of CCh with calcium hydroxide. It is used as a filler and/or coating in the paper, food, and
plastic industries.
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
During the calcination stage of lime production, CO2 is given off as a gas and normally exits the system with the
stack gas. To calculate emissions, the amounts of high-calcium and dolomitic lime produced were multiplied by
their respective emission factors using the Tier 2 approach from the 2006 IPCC Guidelines (IPCC 2006). The
emission factor is the product of the stoichiometric ratio between CO2 and CaO, and the average CaO and MgO
content for lime. The CaO and MgO content for lime is assumed to be 95 percent for both high-calcium and
dolomitic 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 (0.9500 CaO/lime) = 0.7455 g CO2/g lime
For dolomitic lime:
[(88.02 g/mole CO2) - (96.39 g/mole CaO)] x (0.9500 CaO/lime) = 0.8675 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 27.2 percent for
dolomitic hydrated lime.
Lime emission estimates were multiplied by a factor of 1.02 to account for lime kiln dust (LKD), which is produced
as a byproduct during the production of lime (IPCC 2006).
Lime emission estimates were further adjusted to account for PCC producers and sugar refineries that recover CO2
emitted by lime production facilities for use as an input into production or refining processes. For CO2 recovery by
sugar refineries, lime consumption estimates (USGS 2011) were multiplied by a CO2 recovery factor to determine
the total amount of CO2 recovered from lime production facilities. According to industry outreach by state agencies,
sugar refineries use captured CO2 for 100 percent of their CO2 input (Lutter 2009). Carbon dioxide recovery by PCC
producers was determined by multiplying estimates for the percentage CO2 of production weight for PCC
production at lime plants by a CO2 recovery factor based on the amount of purchased CO2 by PCC manufacturers
(Prillaman 2008 through 2012). As data were only available starting in 2007, CO2 recovery for the period 1990
through 2006 was extrapolated by determining a ratio of PCC production at lime facilities to lime consumption for
PCC (USGS 1992 through 2008).
Lime production data (high-calcium- and dolomitic-quicklime, high-calcium- and dolomitic-hydrated, and dead-
burned dolomite) for 1990 through 2011 (see Table 4-8) were obtained from USGS (1992 through 2012) and are
compiled by USGS to the nearest ton. Natural hydraulic lime, which is produced from CaO and hydraulic calcium
silicates, is not produced in the United States (USGS 2011). 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,
and is presented in Table 4-9 (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 4-8: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated,
and Dead-Burned-Dolomite Lime Production (Gg)
Year High-Calcium Dolomitic High-Calcium Dolomitic Dead-Burned
Quicklime Quicklime Hydrated Hydrated Dolomite
1990 11,166 2,234 1,781 319 342
2005 14,100 2,990 2,220 474 200
2007 14,700 2,710 2,240 357 230
2008 14,600 2,630 2,070 358 213
2009 11,800 1,830 1,690 261 178
2010 13,300 2,570 1,910 239 214
Industrial Processes 4-11
-------
Year High-Calcium Dolomitic High-Calcium Dolomitic Dead-Burned
Quicklime Quicklime Hydrated Hydrated Dolomite
2011 13,900 2,690 2,010 230 229
Table 4-9: Adjusted Lime Production3 (Gg)
Year High-Calcium Dolomitic
1990 12,466 2,800
2005 15,721 3,522
2007
2008
2009
2010
2011
16,335
16,111
13,034
14,694
15,367
3,190
3,094
2,191
2,951
3,080
1 Minus water content of hydrated lime
The uncertainties contained in these estimates can be attributed to slight differences in the chemical composition of
lime products and recovery rates for sugar refineries and PCC manufacturers located at lime plants. Although the
methodology accounts for various formulations of lime, it does not account for the trace impurities found in lime,
such as iron oxide, alumina, and silica. Due to differences in the limestone used as a raw material, a rigid
specification of lime material is impossible. As a result, few plants produce lime with exactly the same properties.
In addition, a portion of the CC>2 emitted during lime production will actually be reabsorbed when the lime is
consumed. As noted above, lime has many different chemical, industrial, environmental, and construction
applications. In many processes, CCh reacts with the lime to create calcium carbonate (e.g., water softening).
Carbon dioxide reabsorption rates vary, however, depending on the application. For example, 100 percent of the
lime used to produce precipitated calcium carbonate reacts with CCh; whereas most of the lime used in steel making
reacts with impurities such as silica, sulfur, and aluminum compounds. Quantifying the amount of CC>2 that is
reabsorbed would require a detailed accounting of lime use in the United States and additional information about
the associated processes where both the lime and byproduct CCh are "reused" are required to quantify the amount of
CO2 that is reabsorbed. Research conducted thus far has not yielded the necessary information to quantify €62
reabsorbtion rates.127
In some cases, lime is generated from calcium carbonate byproducts at pulp mills and water treatment plants.128
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
^Representatives of the National Lime Association estimate that CCh reabsorption that occurs from the use of lime may offset
as much as a quarter of the CCh emissions from calcination (Males 2003).
128 Some carbide producers may also regenerate lime from their calcium hydroxide byproducts, which does not result in
emissions of CCh. 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 [CaCOs]. Thus, the calcium hydroxide is heated in the kiln to simply expel the water [Ca(OH)2 + heat —»CaO + EhO]
and no CO2 is released.
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
recover the calcium carbonate "mud" after the causticizing operation and calcine it back into lime—thereby
generating CC>2—for reuse in the pulping process. Although this re-generation of lime could be considered a lime
manufacturing process, the COa emitted during this process is mostly biogenic in origin, and therefore is not
included in the industrial processes totals (Miner and Upton 2002). In accordance with IPCC methodological
guidelines, any such emissions are calculated by accounting for net carbon (C) fluxes from changes in biogenic C
reservoirs in wooded or crop lands (see Chapter 7).
In the case of water treatment plants, lime is used in the softening process. Some large water treatment plants may
recover their waste calcium carbonate and calcine it into quicklime for reuse in the softening process. Further
research is necessary to determine the degree to which lime recycling is practiced by water treatment plants in the
United States.
Uncertainties also remain surrounding recovery rates used for sugar refining and PCC production. The recovery rate
for sugar refineries is based on two sugar beet processing and refining facilities located in California that use 100
percent recovered CCh from lime plants (Lutter 2012). This analysis assumes that all sugar refineries located on-site
at lime plants also use 100 percent recovered CCh. The recovery rate for PCC producers located on-site at lime
plants is based on the 2012 value for PCC manufactured at commercial lime plants, given by USGS (Miller 2012).
Another uncertainty is the assumption that calcination emissions for LKD is around 2 percent. The National Lime
association has commented that the estimates of emissions from LKD could be closer to 6 percent. In addition, they
note emissions may also be generated through production of other byproducts/wastes at lime plants (Seeger, 2013).
There is limited data publicly available on LKD generation rates and also quantities, types of other
byproducts/wastes produced at lime facilities. Further research is needed to improve understanding of additional
calcination emissions.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-10. Lime CCh emissions were
estimated to be between 13.4 and 14.2 Tg CCh Eq. at the 95 percent confidence level. This confidence level
indicates a range of approximately 2.6 percent below and 2.6 percent above the emission estimate of 13.8 Tg CCh
Eq.
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Lime
Production (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Lime Production CO2 13.8 13.4 14.2 -2.6% +2.6%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
€
Production data for dead-burned dolomite were updated in the 2011 Lime Minerals Yearbook to three significant
figures, which caused the CC>2 production from lime to change for all years from 2007 through 2010 relative to the
previous inventory. Quicklime and hydrate lime production data were also revised for 2007, 2008, and 2010. These
revisions resulted in a net decrease in emissions for 2007 and 2008 and a net increase for 2009 and 2010.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Lime Production source category. Pending resources, a potential
improvement to the inventory estimates for this source category would include the derivation of an average CCh
recovery rated based on the average of aggregated data reported by facilities under EPA's GHGRP regarding onsite
use of CO2. Particular attention will be made to ensure time series consistency of the emissions estimates presented
in future inventory reports, consistent with IPCC and UNFCCC guidelines. This is required as the facility-level
reporting data from EPA's GHGRP, with the program's initial requirements for reporting of emissions in calendar
year 2010, are not available for all inventory years (i.e., 1990 through 2009) as required for this inventory. In
Industrial Processes 4-13
-------
implementing improvements and integration of data from EPA's GHGRP, the latest guidance from the IPCC on the
use of facility-level data in national inventories will be relied upon.129
Limestone (CaCOs), dolomite (CaCOsMgCOs)130, and other carbonates such as magnesium carbonate and iron
carbonate are basic materials used by a wide variety of industries, including construction,agriculture, chemical,
metallurgy, glass production, and environmental pollution control. This section only addresses limestone and
dolomite use. 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 heated sufficiently enough to calcine the material
and generate CCh as a byproduct. Examples of such applications include limestone used as a flux or purifier in
metallurgical furnaces, as a sorbent in flue gas desulfurization (FGD) systems for utility and industrial plants, and as a
raw material for the production of glass, lime, and cement. Emissions from limestone and dolomite used in other
process sectors such as cement, lime, glass production, and iron & steel, are excluded from this section and reported
under their respective source categories (e.g., glass manufacturing IPCC Source Category 2A7.) Emissions from fuels
consumed for energy purposes during these processes are accounted for in the Energy chapter.
In 2011,19,979 thousand metric tons of limestone and 1,895 thousand metric tons of dolomite were consumed for
these emissive applications, excluding glass manufacturing (USGS 1995 through 2012a). Usage of limestone and
dolomite resulted in aggregate CC>2 emissions of 9.2TgCO2Eq. (9,153Gg) (see Table 4-1 land Table 4-12).
Overall, emissions have increased 87 percent from 1990 through 2011.
Table 4-11: COz Emissions from Other Process Uses of Carbonates (Tg COz Eq.)
Magnesium Other Miscellaneous
Year Flux Stone FGD Production Uses Total
1990 2.6 1.4 0.1 0.8 4.9
2005 2.6 3.0 + 0.7 6.3
2007
2008
2009
2010
2011
2.0
1.0
1.8
1.6
1.5
3.2 +
3.8 +
5.4 +
7.1 +
5.4 +
2.2
1.1
0.4
0.9
2.3
7.4
5.9
7.6
9.6
9.2
Notes: Totals may not sum due to independent rounding. "Other miscellaneous uses" include chemical
stone, mine dusting or acid water treatment, acid neutralization, and sugar refining.
+ Emissions are less than 0.1 Tg CCh Eq.
Table 4-12: COz Emissions from Other Process Uses of Carbonates (Gg)
Year
1990
2005
Flux Stone
2,592
2,649
FGD
1,432
2,973
Magnesium
Production
64
+
Other Miscellaneous Uses
819
718
Total
4,907
6,339
I29 See
Limestone and dolomite are collectively referred to as limestone by the industry, and intermediate varieties are seldom
distinguished.
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
2007
2008
2009
2010
2011
1,958
974
1,784
1,560
1,467
3,177 +
3,799 +
5,403 +
7,064 +
5,420 +
2,230
1,113
396
937
2,266
7,365
5,885
7,583
9,560
9,153
+ Emissions are less than 0.1 Gg CCh Eq.
CO2 emissions were calculated based on the IPCC 2006 Guidelines Tier 2 method by multiplying the quantity of
limestone or dolomite consumed by the emission factor for limestone or dolomite calcination, respectively, Table
2.1 - limestone: 0.43971 tonne CCh/tonne carbonate, and dolomite: 0.47732 tonne CCh/tonne carbonate131 . This
methodology was used for flux stone, flue gas desulfurization systems, chemical stone, mine dusting or acid water
treatment, acid neutralization, and sugar refining. Flux stone used during the production of iron and steel was
deducted from the Other Process Uses of Carbonates estimate and attributed to the Iron and Steel Production
estimate. Similarly limestone and dolomite consumption for glass manufacturing, cement, and lime manufacturing
are excluded from this category and attributed to their respective categories.
Historically, the production of magnesium metal was the only other significant use of limestone and dolomite that
produced CC>2 emissions. At the end of 2001, the sole magnesium production plant operating in the United States
that produced magnesium metal using a dolomitic process that resulted in the release of €62 emissions ceased its
operations (USGS 1995 through20lib).
Consumption data for 1990 through 2011 of limestone and dolomite used for flux stone, flue gas desulfurization
systems, chemical stone, mine dusting or acid water treatment, acid neutralization, and sugar refining (see Table
4-13) were obtained from the USGS Minerals Yearbook: Crushed Stone Annual Report (1995 through 2012a) and
the U.S. Bureau of Mines (1991 and 1993a), which are reported to the nearest ton. The production capacity data for
1990 through 2011 of dolomitic magnesium metal also came from the USGS (1995 through 2012b) and the U.S.
Bureau of Mines (1990 through 1993b). 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.
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.132
Table 4-13: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
Flux Stone
Limestone
Dolomite
FGD
1990
6,737
5,804 .'
933
3,258
2005
.•" 7,022 .
3,165 /
3,857'
6,761
2007
•' 5,305
3,477
1,827
7,225
2008
3
1
1
8
,253
,970
,282
,639
2009
4,623
1,631
2,992
12,288
2010
4,440
1,921
2,520
16,064
2011
4,396
2,531
1,865
12,326
131IPCC 2006, Volume 3: Chapter2
132This approach was recommended by, USGS, the data collection agency.
Industrial Processes 4-15
-------
Other Miscellaneous 1,835 ; 1,632 ; 5,057 2,531 898 2,121 5,152
Uses
Total 11,830 15,415 17,587 14,423 17,809 22,626 21,874
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.
and
The uncertainty levels presented in this section account for uncertainty associated with activity data. Data on
limestone and dolomite consumption are collected by USGS through voluntary national surveys. USGS contacts the
mines (i.e., producers of various types of crushed stone) for annual sales data. The producers report the annual
quantity sold to various end-users/industry types. USGS estimates the historical response rate for the crushed stone
survey to be approximately 70 percent, the rest is estimated by USGS. 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 producer/mines and not the end user. Additionally, there is
significant inherent uncertainty associated with estimating withheld data points for specific end uses of limestone
and dolomite. 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.
Uncertainty in the estimates also arises 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.
The results of the Tier 2 quantitative uncertainty analysis are summarized inTable 4-14. Other Process Uses of
Carbonates CCh emissions were estimated to be between 8.0 and 10.7 Tg CCh Eq. at the 95 percent confidence
level. This indicates a range of approximately 12 percent below and 15 percent above the emission estimate of 9.2
Tg CO2 Eq.
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Other Process
Uses of Carbonates (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Limestone and
Dolomite Use CO2 9.2 8.0 10.7 -12% +15%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations
Limestone and dolomite used in glass manufacturing have been excluded from this source category and are
accounted for in the Glass Production source category (IPCC Source Category 2A7). Previous Inventories did not
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
include a separate Glass Production source, but included emissions from glass manufacturing in the "Limestone and
Dolomite Use" and "Soda Ash Manufacturing" sections. Recalculations were applied to the entire time-series for
limestone and dolomite use (excluding glass manufacturing) emissions, to ensure time-series consistency from 1990
through 2011. Emission estimates for the entire time-series (1990 through 2011) were recalculated by excluding
limestone and dolomite consumption in glass production. Also, the previous calculation methodology employed the
methodology presented in 1996 IPCC guidelines. This methodology relied on the average carbonate C content and
conversion of C to CC>2. The new methodology employed is based on the Tier 2 methodology as presented in the
IPCC 2006 guidelines. For more details on the revised methodology, refer to the Methodology section, above.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Other Process Uses of Carbonates source category. Particular attention will
be made to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent
with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with
the program's initial requirements for reporting of emissions in calendar year 2010, are not available for all
inventory years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and
integration of data from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in
national inventories will be relied upon.133
Soda ash (sodium carbonate, Na2COs) 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. (Emissions from soda ash used in
glass production are reported under IPCC Source Category 2A7. Glass production is its own sub-category and
historical soda ash consumption figures have been adjusted to reflect this change.) After glass manufacturing, soda
ash is used primarily to manufacture many sodium-base inorganic chemicals, including sodium bicarbonate, sodium
chromates, sodium phosphates, and sodium silicates (USGS 2012). 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.134
During the production process used in Wyoming, trona ore is calcined to produce crude soda ash. Carbon dioxide is
generated as a byproduct of this reaction, and is eventually emitted into the atmosphere. In addition, CO2 may also
be released when soda ash is consumed. Emissions from fuels consumed for energy purposes during the production
and consumption of soda ash are accounted for in the Energy sector.
133 See
134 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 CCh 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 CCh is generated as a byproduct, the CCh 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, NaHCOs was produced using soda ash feedstocks mined in
Wyoming and shipped to Colorado. Prior to 2004, because the trona was mined in Wyoming, the production numbers given by
the USGS included the feedstocks mined in Wyoming and shipped to Colorado. In this way, the sodium bicarbonate production
that took place in Colorado was accounted for in the Wyoming numbers.
Industrial Processes 4-17
-------
In 2011, CO2 emissions from the production of soda ash from trona were approximately 1.6 Tg €62 Eq. (1,607 Gg).
Soda ash consumption in the United States generated 1.1 TgCChEq. (1,105 Gg) in 2011. Total emissions from
soda ash production and consumption in 2011 were 2.7 Tg €62 Eq. (2,712 Gg) (see
Table 4-15 and Table 4-16).
Total emissions in 2011 increased by approximately 0.6 percent from emissions in 2010, and have decreased overall
by approximately 3.9 percent since 1990.
Emissions have remained relatively constant over the time series with some fluctuations since 1990. In general,
these fluctuations were related to the behavior of the export market and the U.S. economy. The global soda ash
industry continued to recover from the world economic problems that began in 2009. According to U.S. Geological
Survey (USGS), approximately 17 percent (or 2.45 million metric tons per year) of total industry nameplate capacity
was idled in 2010. Increased demand for soda ash prompted U.S. soda ash producers to raise the sales price of soda
ash in 2011. The U.S. soda ash export association raised the export price citing that global soda ash demand was
increasing (USGS 2012).
Table 4-15: COz Emissions from Soda Ash Production and Consumption Not Associated with
Glass Manufacturing (Tg COz Eq.)
Year Production Consumption Total
1990 1.4 1.4 2.8
2005 1.7 1.3 3.0
2007
2008
2009
2010
2011
1.7
1.7
1.5
1.5
1.6
1.3
1.2
1.1
1.1
1.1
2.9
3.0
2.6
2.7
2.7
Note: Totals may not sum due to independent rounding.
Table 4-16: COz Emissions from Soda Ash Production and Consumption Not Associated with
Glass Manufacturing (Gg)
Year Production Consumption Total
1990 1,431 1,391 2,822
2005 1,655 1,305 2,960
2007
2008
2009
2010
2011
1,675
1,733
1,470
1,548
1,607
1,262
1,227
1,099
1,149
1,105
2,937
2,960
2,569
2,697
2,712
Note: Totals may not sum due to independent rounding.
The United States represents about one-fourth of total world soda ash output. Based on final 2011 reported data,
the estimated distribution of soda ash by end-use in 2011 was chemical production, 55 percent; soap and detergent
manufacturing, 19 percent; distributors, 10 percent; flue gas desulfurization, 7 percent; other uses, 5 percent; pulp
and paper production, 3 percent; and water treatment, 2 percent (USGS 2012).
U.S. natural soda ash is competitive in world markets because the majority of the world output of soda ash is made
synthetically. Although the United States continues to be a major supplier of world soda ash, China, which
surpassed the United States in soda ash production in 2003, is the world's leading producer. Despite this
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
competition, U.S. soda ash exports are expected to increase, causing domestic production to increase slightly (USGS
2012).
During the production process, trona ore is calcined in a rotary kiln and chemically transformed into a crude soda
ash that requires further processing. Carbon dioxide and water are generated as byproducts of the calcination
process. Carbon dioxide emissions from the calcination of trona can be estimated based on the following chemical
reaction:
2(Na3(CO3)(HCO3)'2H2O) -> 3Na2CO3 + 5H2O + CO2
[trona] [soda ash]
Based on this formula, which is consistent with an IPCC Tier 1 approach, approximately 10.27 metric tons of trona
are required to generate one metric ton of CC>2, or an emission factor of 0.097 metric tons CC>2 per metric ton trona
(IPCC 2006). Thus, the 16.5 million metric tons of trona mined in 2011 for soda ash production (USGS 2012)
resulted in CC>2 emissions of approximately 1.6 Tg CC>2 Eq. (1,607 Gg).
Once produced, most soda ash is consumed in chemical and soap production, with minor amounts in pulp and paper,
flue gas desulfurization, and water treatment. As soda ash is consumed for these purposes, additional CCh 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 CCh) are released for every metric ton of soda ash
consumed.
The activity data for trona production and soda ash consumption (see Table 4-17) between 1990 and 2011 were
taken from USGS Minerals Yearbook for Soda Ash (1994 through 2012). Soda ash production and consumption
data were collected by the USGS from voluntary surveys of the U.S. soda ash industry.
Table 4-17: Soda Ash Production and Consumption Not Associated with Glass Manufacturing
(Gg)
Year Production* Consumption*
1990 14,700 3,351
2005 17,000 3,144
2007
2008
2009
2010
2011
17,200
17,800
15,100
15,900
16,500
3,041
2,957
2,647
2,768
2,663
* Soda ash produced from trona ore only.
" Soda ash consumption is sales reported by
producers which exclude imports. Historically,
imported soda ash is less than 1 percent of the
total U.S. consumption (Kostick, 2012).
and
Emission estimates from soda ash production have relatively low associated uncertainty levels in that reliable and
accurate data sources are available for the emission factor and activity data. Soda ash production data was collected
by the USGS from voluntary surveys. A survey request was sent to each of the five soda ash production, all of which
responded, representing 100 percent of the total production data (Kostick 2012). 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 emission factors for each end-use are not available, so a Tier 1 default emission
Industrial Processes 4-19
-------
factor is used for all end uses. 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 Production and
Consumption CCh emissions were estimated to be between 2.6 and 2.9 Tg CCh Eq. at the 95 percent confidence
level. This indicates a range of approximately 5 percent below and 5 percent above the emission estimate of 2.7 Tg
CO2 Eq.
Table 4-18: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Soda Ash
Production and Consumption (Tg COz Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(TgCOiEq.) (Tg C02 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Soda Ash Production
and Consumption CCh 2.7 2.6 2.9 -5% +5%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
In previous Inventories, emissions from soda ash included €62 from glass production. Emissions from glass
production are now included in the Glass Production source category, and historical production figures in Table 4-17
have been adjusted to remove the amount of soda ash associated with non-glass uses. This resulted in an average
emission decrease of 1.3 Tg of CCh across the time-series. All emissions shown in
Table 4-15 and Table 4-16 have been revised accordingly.
Future inventory reports are anticipated to estimate emissions from other uses of soda ash. To add specificity, future
inventories will extract soda ash consumed for other uses of carbonates from the current soda ash consumption
emission estimates and include them under those sources; in 2011 glass production is its own sub-category.
In examining data from EPA's GHGRP that would be useful to improve the emission estimates for Soda Ash and
Consumption category, particular attention will be made to ensure time series consistency of the emissions estimates
presented in future inventory reports, consistent with IPCC and UNFCCC guidelines. This is required as the facility-
level reporting data from EPA's GHGRP, with the program's initial requirements for reporting of emissions in
calendar year 2010, are not available for all inventory years (i.e., 1990 through 2009) as required for this inventory.
In implementing improvements and integration of data from EPA's GHGRP, the latest guidance from the IPCC on
the use of facility-level data in national inventories will be relied upon.135
The glass industry can be divided into four main categories: containers, flat (window) glass, fiber glass, and
specialty glass. The majority of commercial glass produced is container and flat glass (U.S. EPA 2010). Glass
production employs a variety of raw materials in a glass-batch. These include formers, fluxes, stabilizers, and
sometimes colorants. The main former in all types of glass is silica (SiCh). Other major formers in glass include
135 See
4-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
feldspar and boric acid (i.e., borax). Fluxes are added to lower the temperature at which the batch melts. Most
commonly used flux materials are soda ash (sodium carbonate, Na2COs) and potash (potassium carbonate, K2O).
Stabilizers are used to make glass more chemically stable and to keep the finished glass from dissolving and/or
falling apart. Commonly used stabilizing agents in glass production are limestone (CaCCh), dolomite
(CaCOsMgCOs), alumina (A^Os), magnesia (MgO), barium carbonate (BaCOs), strontium carbonate (SrCOs),
lithium carbonate (Li2CO3), and zirconia (OIT 2002). The major raw materials (e.g. fluxes, stabilizers) which emit
process-related CCh emissions are limestone, dolomite, and soda ash. Glass makers also use a certain amount of
recycled scrap glass (cullet), which comes from in-house return of glassware broken in the process or other glass
spillage or retention such as recycling or cullet broker services. The raw materials (primarily limestone, dolomite
and soda ash) release CC>2 emissions during the glass melting process. This is a high-temperature, energy intensive
process. Emissions from fuels consumed for energy purposes during the production of glass are accounted for in the
Energy sector.
In 2011, 614 thousand metric tons of limestone, 0 thousand metric tons of dolomite, and 2,480 thousand metric tons
of soda ash were consumed for glass production (USGS 201 la, 201 Ib). Use of limestone, dolomite, and soda ash in
glass production resulted in aggregate CC>2 emissions of 1.3 Tg CCh Eq. (1,299 Gg) (see Table 4-19). Overall,
emissions have decreased 15 percent from 1990 through 2011.
Emissions from glass production have remained relatively constant over the time series with some fluctuations since
1990. In general, these fluctuations were related to the behavior of the export market and the U.S. economy.
Specifically, the extended downturn in residential and commercial construction and automotive industries between
2008 and 2010 resulted in reduced consumption of glass products, causing a drop in global demand for
limestone/dolomite and soda ash, and a corresponding decrease in emissions. Furthermore, the glass container sector
is one of the leading soda ash consuming sectors in the United States. Some commercial food and beverage package
manufacturers are shifting from glass containers towards lighter and more cost effective polyethylene terephthalate
(PET) based containers, putting downward pressure on domestic consumption of soda ash (USGS 1994 through
20 lib).
Table 4-19: COz Emissions from Glass Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 1.5 1,535
2005 1.9 1,928
2007
2008
2009
2010
2011
1.5
1.5
1.0
1.5
1.3
1,536
1,523
1,045
1,481
1,299
CO2 emissions were calculated based on the IPCC 2006 Guidelines Tier 3 method by multiplying the quantity of
input carbonates (limestone, dolomite, and soda ash) by the carbonate-based emission factor (in metric tons
CCVmetric ton carbonate: limestone: 0.43971; dolomite: 0.47732; and soda ash: 0.41492).
Consumption data for 1990 through 2011 of limestone, dolomite, and soda ash used for glass manufacturing
(seeTable 4-20) were obtained from the USGS Minerals Yearbook: Crushed Stone Annual Report (1995 through
201 la), the USGS Minerals Yearbook: Soda Ash Annual Report (1995 through 20 lib), and the U.S. Bureau of
Mines (1991 and 1993a), which are reported to the nearest ton. 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.
Industrial Processes 4-21
-------
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; or (2) the average percent of total
limestone or dolomite for the withheld end-use in the preceding and succeeding years.
There is a large quantity of limestone and dolomite reported to the USGS under the categories "unspecified -
reported" and "unspecified - estimated." A portion of this consumption is believed to be limestone or dolomite used
for glass manufacturing. The quantities listed under the "unspecified" categories were, therefore, allocated to glass
manufacturing according to the percent limestone or dolomite consumption for glass manufacturing end use for that
year.136
Based on the 2011 reported data, the estimated distribution of soda ash consumption for glass production compared
to total domestic soda ash consumption is 23.2 percent (USGS 2012).
Table 4-20: Limestone, Dolomite, and Soda Ash Consumption Used in Glass Production
(Thousand Metric Tons)
Activity
Limestone
Dolomite
Soda Ash
Total
1990
430
59
3,177
3,666
2005
1 920
541
.••" 3,050 /
A 4,511 ..
2007
1 757
0
" 2,900
1 3,657
2008
879
0
2,740
3,619
2009
139
0
2,370
2,509
2010
999
0
2,510
3,509
2011
614
0
2,480
3,094
Notes: 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.
The uncertainty levels presented in this section arise in part due to variations in the chemical composition of
limestone used in glass production. In addition to calcium carbonate, limestone may contain smaller amounts of
magnesia, silica, and sulfur, among other minerals (potassium carbonate, strontium carbonate and barium carbonate,
and dead burned dolomite). Similarly, the quality of the limestone (and mix of carbonates) 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 of the input carbonates
(limestone, dolomite & soda ash) and not the end user. For 2011, there has been no reported consumption of
dolomite for glass manufacturing. This data has been reported to USGS by dolomite manufacturers and not end-
users (i.e., glass manufacturers). There is a high uncertainty associated with this estimate. Additionally, there is
significant inherent uncertainty associated with estimating withheld data points for specific end uses of limestone
and dolomite. The uncertainty of the estimates for limestone and dolomite 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. Further
research is needed into alternate and more complete sources of data on carbonate-based raw material consumption
by the glass industry.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-21. Glass production CC>2
emissions were estimated to be between 1.2 and 1.4 Tg CCh Eq. at the 95 percent confidence level. This indicates a
range of approximately 4 percent below and 5 percent above the emission estimate of 1.3 Tg CCh Eq.
136This approach was recommended by USGS.
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-21: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Glass
Production (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Glass Production CCh
1.3
1.2 1.4 -4% +5%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Pending resources, future improvements involve evaluating and analyzing data reported under EPA's GHGPJ3 that
would be useful to improve the emission estimates for the Glass Production source category. Particular attention will
be made to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent
with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGPJ3, with
the program's initial requirements for reporting of emissions in calendar year 2010, are not available for all
inventory years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and
integration of data from EPA's GHGPJ3, the latest guidance from the IPCC on the use of facility-level data in
national inventories will be relied upon.137
Emissions of CO2 occur during the production of synthetic ammonia, primarily through the use of natural gas,
petroleum coke, or naphtha as a feedstock. Emissions from fuels consumed for energy purposes during the
production of ammonia are accounted for in the Energy chapter. 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 synthetic ammonia production plant located in Kansas is producing ammonia from petroleum coke
feedstock; other synthetic ammonia production plants in the United States are using natural gas feedstock. In some
plants some of the CO2 produced by the process is captured and used to produce urea rather than being emitted to
the atmosphere. 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 in this step of the process. 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. Carbon dioxide is removed from the process gas
by the shift conversion process, and the hydrogen gas is combined with the nitrogen (N2) gas in the process gas
during the ammonia synthesis step to produce ammonia. The CO2 is included in a waste gas stream with other
process impurities and is absorbed by a scrubber solution. In regenerating the scrubber solution, CO2 is released
from the solution.
The conversion process for conventional steam reforming of CH4, including the primary and secondary reforming
and the shift conversion processes, is approximately as follows:
137 See
Industrial Processes 4-23
-------
(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 during the production of ammonia is emitted directly to the atmosphere. Some of the
ammonia and some of the CO2 produced by the synthetic ammonia process are used as raw materials in the
production of urea [CO(NH2)2], which has a variety of agricultural and industrial applications.
The chemical reaction that produces urea is:
2NH3 + CO2Hx NH2COONH4 -» CO(NH2)2 + H2O
Only the CO2 emitted directly to the atmosphere from the synthetic ammonia production process are accounted for
in determining emissions from ammonia production. The CO2 that is captured during the ammonia production
process and used to produce urea does not contribute to the CO2 emission estimates for ammonia production
presented in this section. Instead, CO2 emissions resulting from the consumption of urea are attributed to the urea
consumption or urea application source category (under the assumption that the C stored in the urea during its
manufacture is released into the environment during its consumption or application). Emissions of CO2 resulting
from agricultural applications of urea are accounted for in the Cropland Remaining Cropland section of the Land-
use, Land-use Change, and Forestry chapter. Emissions of CO2 resulting from non-agricultural applications of urea
(e.g., use as a feedstock in chemical production processes) are accounted for in the Urea Consumption for Non-
Agricultural Purposes section of the Industrial Process chapter.
Total emissions of CO2 from ammonia production in 2011 were 8.8 Tg CO2 Eq. (8,795 Gg), and are summarized in
Table 4-22 and Table 4-23. The observed decrease in ammonia production and associated CO2 emissions between
2007 and 2009 is due to several factors, including market fluctuations and high natural gas prices. Ammonia
production relies on natural gas as both a feedstock and a fuel, and as such, domestic producers are competing with
imports from countries with lower natural gas prices (EEA 2004). The increase in ammonia production (and
associated CO2 emissions) after 2010 is largely attributable to dramatically lower natural gas prices in the United
States after 2009 (EIA 2012).
Table 4-22: COz Emissions from Ammonia Production (Tg COz Eq.)
Source 1990 2005 2007 2008 2009 2010 2011
Ammonia Production 13.0 •. 9.2 9.1 7.9 7.9 8.7 8.8
Total 13.0 9.2 9.1 7.9 7.9 8.7 8.8
Table 4-23: COz Emissions from Ammonia Production (Gg)
Source
Ammonia Production
Total
1990
13,047
13,047
2005
9,196
9,196
2007
9,074
9,074
2008
7,883
7,883
2009
7,855
7,855
2010
8,678
8,678
2011
8,795
8,795
The calculation methodology for non-combustion CO2 emissions from production of synthetic ammonia from
natural gas feedstock is based on the 2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006).
The method uses a CO2 emission factor published by the European Fertilizer Manufacturers Association (EFMA)
that is based on natural gas-based ammonia production technologies that are similar to those employed in the United
States. The CO2 emission factor (1.2 metric tons CO^metric ton NH3, EFMA 2000a) is applied to the percent of
total annual domestic ammonia production from natural gas feedstock.
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Emissions of CCh from ammonia production are then adjusted to account for the use of some of the CCh produced
from ammonia production as a raw material in the production of urea. The €62 emissions reported for ammonia
production are reduced by a factor of 0.733 multiplied by total annual domestic urea production. This corresponds
to a stochiometric CCVurea factor of 44/60, assuming complete conversion of NH3 and CC>2 to urea (IPCC 2006,
EFMA 2000b).
All synthetic 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. Annual ammonia and urea production are shown in Table
4-24. The CCh 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 CCh (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 CCh emission factor for the petroleum coke feedstock process (3.57 metric tons CCh/metric
ton NH3, Bark 2004) is applied to the percent of total annual domestic ammonia production from petroleum coke
feedstock.
The emission factor of 1.2 metric ton CCh/metric ton NH3 for production of ammonia from natural gas feedstock
was taken from the EFMA Best Available Techniques publication, Production of Ammonia (EFMA 2000a). The
EFMA reported an emission factor range of 1.15 to 1.30 metric ton COa/metric ton NH3, with 1.2 metric ton
CCVmetric ton NH3 as a typical value (EFMA 2000a). 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 COa. The emission factor of 3.57 metric ton CCh/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. The
total ammonia production data for 2011 was obtained from American Chemistry Council (2012). For years before
2011, ammonia production data (See Table 4-24) was obtained from Coffeyville Resources (Coffeyville 2005, 2006,
2007a, 2007b, 2009, 2010, 2011, and 2012) and the Census Bureau of the U.S. Department of Commerce (U.S.
Census Bureau 1991 through 1994, 1998 through 2010) as reported in Current Industrial Reports Fertilizer Materials
and Related Products annual and quarterly reports. Urea-ammonia nitrate production was obtained from Coffeyville
Resources (Coffeyville 2005, 2006, 2007a, 2007b, 2009, 2010, 2011, and 2012). Urea production data for 1990
through 2008 were obtained from the Minerals Yearbook: Nitrogen (USGS 1994 through 2009). Urea production
data for 2009 through 2010 were obtained from the U.S. Bureau of the Census (U.S. Bureau of the Census 2010 and
2011). Urea production data for 2011 was estimated using the ammonia production information in 2011 and
assuming that the ratio of urea production to ammonia production is the same as the production ration in 2010.
Table 4-24: Ammonia Production and Urea Production (Gg)
Year Ammonia Production Urea Production
1990 15,425 7,450
2005 10,143 5,270
2007
2008
2009
2010
2011
10,393
9,570
9,372
10,084
10,325
5,590
5,240
5,084
5,122
5,245
and
The uncertainties presented in this section are primarily due to how accurately the emission factor used represents an
average across all ammonia plants using natural gas feedstock. Uncertainties are also associated with natural gas
feedstock consumption data for the U.S. ammonia industry as a whole, the assumption that all ammonia production
Industrial Processes 4-25
-------
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. Uncertainty is also associated with the representativeness of the emission factor
used for the petroleum coke-based ammonia process. It is also assumed that ammonia and urea are produced at
collocated plants from the same natural gas raw material.
Recovery of CCh from ammonia production plants for purposes other than urea production (e.g., commercial sale)
has not been considered in estimating the CC>2 emissions from ammonia production, as data concerning the
disposition of recovered COa are not available. Such recovery may or may not affect the overall estimate of COa
emissions depending upon the end use to which the recovered €62 is applied. Further research is required to
determine whether byproduct COa 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 4-25. Ammonia Production CC>2
emissions were estimated to be between 8.1 and 9.5 Tg CCh Eq. at the 95 percent confidence level. This indicates a
range of approximately 8.0 percent below and 7.1 percent above the emission estimate of 8.8 Tg CCh Eq.
Table 4-25: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Ammonia
Production (Tg COz Eq. and Percent)
2011 Emission
Estimate
Source Gas (Tg CCh Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Ammonia Production CCh 8.8
8.1 9.5 -8.0% +7.1%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Ammonia Production source category. Particular attention will be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of data
from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will
be relied upon.138 Specifically, the planned improvements include assessing data to update the emission factors to
include both fuel and feedstock COa emissions and incorporate CCh 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.
138 See
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
4.7 for
Urea is used as a nitrogenous fertilizer for agricultural applications and also in a variety of industrial applications.
Urea's industrial applications include its use as adhesives, binders, sealants, resins, fillers, analytical reagents,
catalysts, intermediates, solvents, dyestuffs, fragrances, deodorizers, flavoring agents, humectants and dehydrating
agents, formulation components, monomers, paint and coating additives, photosensitive agents, and surface
treatments agents. In addition, urea is used for abating nitrous oxide emissions from coal-fired power plants and
diesel transportation motors.
Urea is produced using ammonia and CCh as raw materials. All urea produced in the United States is assumed to be
produced at ammonia production facilities where both ammonia and CCh are generated. The chemical reaction that
produces urea is:
2NH3 + CO2Hx NH2COONH4 -» CO(NH2)2 + H2O
This section accounts for CCh emissions associated with urea consumed exclusively for non-agricultural purposes.
CO2 emissions associated with urea consumed for fertilizer are accounted for in the Cropland Remaining Cropland
section of the Land Use, Land-Use Change, and Forestry chapter.
Emissions of CCh from urea consumed for non-agricultural purposes in 2011 were estimated to be 4.3 Tg CC>2 Eq.
(4,329 Gg), and are summarized in Table 4-26 and Table 4-27.
Table 4-26: COz Emissions from Urea Consumption for Non-Agricultural Purposes (Tg COz
Eq.)
Source 1990 2005 2007 2008 2009 2010 2011
Urea Consumption 3.8 . 3.7 4.9 4.1 3.4 4.4 4.3
Total 3.8 3.7 4.9 4.1 3.4 4.4 4.3
Table 4-27: COz Emissions from Urea Consumption for Non-Agricultural Purposes (Gg)
Source 1990 2005 2007 2008 2009 2010 2011 '
Urea Consumption 3,784 3,653 4,944 4,065 3,415 4,365 4,329
Total 3,784 3,653 4,944 4,065 3,415 4,365 4,329
Emissions of COa resulting from urea consumption for non-agricultural purposes are estimated by multiplying the
amount of urea consumed in the United States for non-agricultural purposes by a factor representing the amount of
CO2 used as a raw material to produce the urea. This method is based on the assumption that all of the C in urea is
released into the environment as CCh during use.
The amount of urea consumed for non-agricultural purposes in the United States is estimated by deducting the
quantity of urea fertilizer applied to agricultural lands, which is obtained directly from the Land Use, Land-Use
Change, and Forestry chapter (see Table 7-26) and is reported in Table 4-28, from the total domestic supply of urea.
The domestic supply of urea is estimated based on the amount of urea produced plus the sum of net urea imports and
exports. A factor of 0.73 tons of CCh per ton of urea consumed is then applied the resulting supply of urea for non-
agricultural purposes to estimate CO2 emissions from the amount of urea consumed for non-agricultural purposes.
The 0.733 tons of CO2 per ton of urea emission factor is based on the stoichiometry of producing urea from
ammonia and CO2. This corresponds to a stochiometric CCh/urea factor of 44/60, assuming complete conversion of
NH3 and CO2to urea (IPCC 2006, EFMA 2000).
Industrial Processes 4-27
-------
Urea production data for 1990 through 2008 were obtained from the Minerals Yearbook: Nitrogen (USGS 1994
through 2009). Urea production data for 2009 through 2010 were obtained from the U.S. Bureau of the Census
(2011). Urea production data for 2011 was obtained directly from the same source used in the section for Ammonia
Production (Section 4.6) of this report (American Chemistry Council 2012). Urea import data for 2011 were taken
from U.S. Fertilizer Import/Exports from USDA Economic Research Service Data Sets (U.S. Department of
Agriculture 2012). Urea import data for the previous years were obtained from the U.S. Census Bureau Current
Industrial Reports Fertilizer Materials and Related Products annual and quarterly reports for 1997 through 2010
(U.S. Census Bureau 1998 through 2011), The Fertilizer Institute (TFI 2002) for 1993 through 1996, and the United
States International Trade Commission Interactive Tariff and Trade DataWeb (U.S. ITC 2002) for 1990 through
1992 (see Table 4-28). Urea export data for 1990 through 2011 were taken from U.S. Fertilizer Import/Exports from
USDA Economic Research Service Data Sets (U.S. Department of Agriculture 2012).
Table 4-28: Urea Production, Urea Applied as Fertilizer, Urea Imports, and Urea Exports (Gg)
Year
1990
2005
2007
2008
2009
2010
2011
Urea
Production
7,450
5,270
/
5,590
5,240
5,084
5,122
5,245
Urea Applied
as Fertilizer
3,296
4,779
5,214
4,927
4,864
5,650
4,995
Urea Imports
1,860
5,026
6,546
5,459
4,727
6,631
5,860
Urea Exports
854
536
271
230
289
152
207
and
The amount of urea used for non-agricultural purposes is estimated based on estimates of urea production, urea
imports, urea exports, and the amount of urea used as fertilizer. The primary uncertainties associated with this
source category are associated with the accuracy of these estimates as well as the fact that each estimate is obtained
from a different data source. There is also uncertainty associated with the assumption that all of the C in urea is
released into the environment as CCh during use.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-29. CCh emissions associated
with urea consumption for non-agricultural purposes were estimated to be between 4.0 and 4.6 Tg CCh Eq. at the 95
percent confidence level. This indicates a range of approximately 6.7 percent below and 6.3 percent above the
emission estimate of 4.3 Tg CCh Eq.
Table 4-29: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Urea
Consumption for Non-Agricultural Purposes (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Urea Consumption for
Non-Agricultural
Purposes CCh 43 4.0 4.6 -6.7% +6.3%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Future improvements to the urea consumption for non-agricultural purposes source category involve continuing to
research obtaining data on how much urea is consumed for specific applications in the United States and whether C
is released to the environment fully during each application.
4.8
Nitric acid (HNOs) is an inorganic compound used primarily to make synthetic commercial fertilizers. It is also a
major component in the production of adipic acid—a feedstock for nylon—and explosives. Virtually all of the nitric
acid produced in the United States is manufactured by the catalytic oxidation of ammonia (EPA 1997). During this
reaction, N2O is formed as a byproduct and is released from reactor vents into the atmosphere. Emissions from fuels
consumed for energy purposes during the production of nitric acid are accounted for in the Energy chapter.
Currently, the nitric acid industry controls for emissions of NO and NO2 (i.e., NOX). As such, the industry in the US
uses a combination of non-selective catalytic reduction (NSCR) and selective catalytic reduction (SCR)
technologies. In the process of destroying NOX, NSCR systems are also very effective at destroying N2O. However,
NSCR units are generally not preferred in modern plants because of high energy costs and associated high gas
temperatures. NSCRs were widely installed in nitric plants built between 1971 and 1977. Asof2011,
approximately 30 percent of nitric acid plants use NSCR or other catalyst-based N2O abatement technology,
representing 25.6 percent of estimated national nitric acid production (EPA 2010, IFDC 2012, CAR 2013, EPA
2013, EPA 2013a). The remaining 74.4 percent of nitric acid production occurs using SCR or extended absorption,
neither of which is known to reduce N2O emissions.139
N2O emissions from this source were estimated to be 15.5 Tg CO2 Eq. (50 Gg) in 2011 (see Table 4-30). Emissions
from nitric acid production have decreased by 14.7 percent since 1990, with the trend in the time series closely
tracking the changes in production. Emissions have decreased by 28 percent since 1997, the highest year of
production in the time series.
Table 4-30: NzO Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg)
Year Tg CCh Eq. Gg
1990 18.2 59
2005 16.9 55
2007
2008
2009
2010
2011
19.7
16.9
14.0
16.8
15.5
64
54
45
54
50
139 Number of plants and production lines using N2O abatement technology is based on publicly available N2O abatement project
and permit information (EPA 2010, CAR 2013, EPA 2013), supplemented with information available from trade associations
(IFDC 2012) and non-confidential business information data elements from EPA's GHGRP (EPA 2013a). Using boilerplate
production capacity information available for each plant and a national estimate of nitric acid production capacity utilization, we
estimate that approximately 25.6 percent of estimated national nitric acid was produced on lines using NSCR or other catalyst-
based N2O abatement technology as of 2011 (EPA 2010, IFDC 2012, CAR 2013, EPA 2013, EPA 2013a).
Industrial Processes 4-29
-------
For 1990 through 2008, 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 two known
emission factors: 2 kg N2O/metric ton HNCb produced at plants using non-selective catalytic reduction (NSCR)
systems and 9 kg N2O/metric ton HNOs produced at plants not equipped with NSCR (IPCC 2006). In the process of
destroying NOX, NSCR systems destroy 80 to 90 percent of the N2O, which is accounted for in the emission factor
of 2 kg N2O/metric ton HNOs. During this period, approximately 88 percent of nitric acid was produced without
NSCR systems (EPA 2010, EPA 2013), resulting in an emission factor of 8.1 kg N2O/metric ton HNO3.
In 2009, several nitric acid production facilities that did not have NSCR abatement systems installed were closed
(Desai 2012) and one facility installed catalyst-based N2O abatement technology (CAR 2013). As a result, as of
2009 approximately 26 percent of HNOs plants in the United States are equipped with NSCR or catalyst-based N2O
abatement technology representing 19.7 percent of estimated national production (EPA 2010, EPA 2013). Therefore,
the resulting emission factor is 7.6 kg N2O/metric ton HNOs for 2009. In 2010, one NSCR plant was not operated
(IFDC 2012), bringing the percentage controlled with NSCR or catalyst-based N2O abatement technology to 17.2
percent of production. This same plant suspended operations through 2011 (IFDC 2011, EPA 2013) while
additional production lines began controlling their process with NSCR (CAR 2013), bringing the percent of
production controlled with NSCR or catalyst-based N2O abatement technology up to 25.6 percent by 2011. The
resulting emission factor in 2011 is 7.2 kg N2O/metric ton HNOs.
Nitric acid production data for the U.S. for 1990 through 2002 were obtained from the U.S. Census Bureau (2010b);
2003 production data were obtained from the U.S. Census Bureau (2008); 2004 through 2007 production data were
obtained from the U.S. Census Bureau (2009); 2008 and 2009 production data were obtained from the U.S. Census
Bureau (2010a); and 2010 production data were obtained from the U.S. Census Bureau (2011) (see Table 4-31). The
U.S. Census Bureau ceased collecting production data after the second quarter of 2011(2012). The 2011 U.S. Census
Bureau (2012) data that were available showed that the production trends of the first two quarters of 2011 were
within 1 percent of the 2010 production over the same period. Therefore, the 2011 production was assumed to be
the same as 2010.
Table 4-31: Nitric Acid Production (Gg)
Year Gg
1990 7,195
2005 6,711
2007 7,827
2008 6,686
2009 5,924
2010 6,931
2011 6,931
and
Uncertainty associated with the parameters used to estimate N2O emissions includes that of production data, the
share of U.S. nitric acid production attributable to each emission abatement technology over the time series, and the
emission factors applied to each abatement technology type. While some information has been obtained through
outreach with industry associations, limited information is available over the time series for a variety of facility level
variables, including plant specific production levels, abatement technology type and installation date and accurate
destruction and removal efficiency rates. Some information will be available through EPA's GHGRP, but this data
is not available over the time series.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-32. N2O emissions from nitric
acid production were estimated to be between 9.5 and 21.7 Tg CO2 Eq. at the 95 percent confidence level. This
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
indicates a range of approximately 39 percent below to 40 percent above the 2011 emissions estimate of 15.5 Tg
CO2 Eq.
Table 4-32: Tier 2 Quantitative Uncertainty Estimates for NzO Emissions from Nitric Acid
Production (Tg COz Eq. and Percent)
2011 Emission Uncertainty Range Relative to Emission Estimate3
Source Gas Estimate (Tg CCh Eq.) (%)
(Tg COi Eq.) Lower Bound Upper Bound Lower Bound Upper Bound
Nitric Acid Production N2O 15.5 9.5 21.7 -39% +40%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series relative to the previous inventory to ensure
time-series consistency from 1990 through 2011 to reflect improved information available on abatement technology
installation (CAR 2013, EPA 2013). Based on the improved data, the percentage of NSCR-equipped production
was revised for the 1990-2008 years from 17.3 percent to 12.3 percent. Furthermore, emission factors were
developed for the 2009, 2010 and 2011 years to reflect increasing application of abatement technology across the
industry. Details on the emission trends and abatement technology trends through time are described in more detail
in the Methodology section, above.
This inventory incorporates research into the availability of facility level nitric acid production data, abatement
technology type and installation dates, the share of nitric acid production attributable to various abatement
technologies in recent years, as well as efforts to analyze data reported under EPA's GHGRP. These research efforts
are especially important given the cancellation of the U.S. Census Bureau's Current Industrial Reports data series,
from which national Nitric Acid production data have historically been derived. In examining data from EPA's
GHGRP that would be useful to improve the emission estimates for nitric acid production category, particular
attention was made to ensure time series consistency of the emissions estimates presented in future inventory
reports, consistent with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from
EPA's GHGRP, with the program's initial requirements for reporting of emissions in calendar year 2010, are not
available for all inventory years (i.e., 1990 through 2009) as reported in this inventory. Similar research is planned
for upcoming years as more recent GHGRP data become available. In implementing future improvements and
integration of data from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in
national inventories will be relied upon.140
A potential improvement to the inventory estimates for this source category would include the derivation of
country-specific emission factors, based on data reported under EPA's GHGRP. Aggregating facility-level data
elements reported under the GHGRP, specifically emissions and nitric acid production data, EPA will derive a
country-specific emission factor for estimating N2O process emissions in recent years and consider applicability in
past years. If feasible, EPA would propose to include revised estimates in the final GHG inventory published later
this spring using these emission factors derived from the specified GHGRP data elements. 141
140 See
141 As stated, the emission factor be derived from aggregating facility level data on nitric acid production and emissions, also
considering other reported elements such as use of abatement, type of nitric acid production process (e.g. low, medium, high
pressure, etc.). EPA would further describe derivation of the factors from aggregated facility data and publish the factors
themselves in the Nitric Acid Methodology section. In addition, EPA would publish nitric acid production aggregated from
annual facility level reports for 2010 and 2011 in Table 4-31.
Industrial Processes 4-31
-------
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. In 2011, the United States had two companies with a total of
three adipic acid production facilities, all of which were operational (CW 2007; Desai 2010; VA DEQ 2009; EPA
2012). The United States accounts for the largest share of global adipic acid production capacity (30 percent),
followed by the European Union (29 percent) and China (22 percent) (SEI2010). 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. 84 percent of all adipic acid produced in the United States is used in the production of nylon 6,6; nine
percent is used in the production of polyester polyols; four percent is used in the production of plasticizers; and the
remaining four 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). Emissions from fuels consumed for energy purposes during the production of adipic acid are accounted for in
the Energy chapter.
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 byproduct of the nitric acid oxidation stage and is emitted in the waste gas stream (Thiemens and Trogler 1991).
Process emissions from the production of adipic acid vary with the types of technologies and level of emission
controls employed by a facility. In 1990, two of the three major adipic acid-producing plants had N2O abatement
technologies in place and, as of 1998, the three major adipic acid production facilities had control systems in place
(Reimer et al. 1999). One small plant, which last operated in April 2006 and represented approximately two percent
of production, did not control for N2O (VA DEQ 2009; ICIS 2007; VA DEQ 2006).
Very little information on annual trends in the activity data exist for adipic acid. Primary production data is derived
from the American Chemistry Council (ACC) Guide to the Business of Chemistry, which does not provide source
specific trend information. The USGS does not currently publish a Minerals Yearbook for adipic acid, and it is not
included in the general USGS Minerals Commodity Summary.
N2O emissions from adipic acid production were estimated to be 10.6 Tg CO2 Eq. (34 Gg) in 2011 (see Table 4-33).
National adipic acid production has increased by approximately 1 percent over the period of 1990 through 2011, to
roughly 760,000 metric tons. Over the same period, emissions have been reduced by 33 percent due to both the
widespread installation of pollution control measures in the late 1990s and plant idling in the late 2000s. In April
2006, the smallest of the four facilities ceased production of adipic acid (VA DEQ 2009); furthermore, one of the
major adipic acid production facilities was not operational in 2009 or 2010 (Desai 2010). All three remaining
facilities were in operation in 2011, but the abatement utilization rate at the largest production plant was much lower
in 2011 than in 2010, which resulted in a 141 percent increase in emissions from 2010 (EPA 2012).
Table 4-33: NzO Emissions from Adipic Acid Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 15.8 51
2005 7.4 24
2007
2008
2009
2010
2011
10.7
2.6
2.8
4.4
10.6
34
8
9
14
34
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Due to confidential business information, plant names are not provided in this section. The four adipic acid-
producing plants will henceforth be referred to as Plants 1 through 4.
For Plants 1 and 2, 1990 to 2011 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 (Desai 2010, EPA 2012). These
estimates were based on continuous process monitoring equipment installed at the two facilities. In 2009 and 2010,
no adipic acid production occurred at Plant 1 (EPA 2012). For Plant 4, N2O emissions were estimated using the
following equation:
N2O emissions = (production of adipic acid [metric tons {MT} of adipic acid]) x (0.3 MT N2O / MT adipic acid) x
(1 - [N2O destruction factor x abatement system utility factor])
The adipic acid production is multiplied by an emission factor (i.e., N2O emitted per unit of adipic acid produced),
which has been estimated, based on experiments that the reaction stoichiometry for N2O production in the
preparation of adipic acid at approximately 0.3 metric tons of N2O per metric ton of product (IPCC 2006). The
"N2O destruction factor" in the equation 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 (Plants 1 and 2), one plant employs thermal destruction (Plant 3), and the smallest plant
that closed in 2006 used no N2O abatement equipment (Plant 4).
For Plant 3, 2005 through 2011 emissions were obtained directly from the plant engineer and analysis of
Greenhouse Gas Reporting Program data (EPA 2012, Desai 2012). For 1990 through 2004, emissions were
estimated using plant-specific production data and IPCC factors as described above for Plant 4. Production data for
1990 through 2003 was estimated by allocating national adipic acid production data to the plant level using the ratio
of known plant capacity to total national capacity for all U.S. plants. For 2004, actual plant production data were
obtained and used for emission calculations (CW 2005).
Plant capacities for 1990 through 1994 were obtained from Chemical and Engineering News, "Facts and Figures"
and "Production of Top 50 Chemicals" (C&EN 1992 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 2003, the plant capacities for three plants were kept the same as the year 2000
capacities. Plant capacity for 1999 to 2003 for the one remaining plant was kept the same as 1998. For Plant 4,
which last operated in April 2006 (VA DEQ 2009), plant-specific production data were obtained across the time
series from 1990 through 2008 (VA DEQ 2010). Since the plant has not operated since 2006, production through
2010 was assumed to be zero. The plant-specific production data were then used for calculating emissions as
described above.
National adipic acid production data (see Table 4-34) from 1990 through 2011 were obtained from the American
Chemistry Council (ACC 2012), although this data was not used in estimating the emissions from adipic acid plants.
Table 4-34: Adipic Acid Production (Gg)
Year Gg
1990755~
2005 865
2007 850
2008 805
2009 760
2010 710
2011 760
Industrial Processes 4-33
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Uncertainty associated with N2O emission estimates included that of the methods used by companies to monitor and
estimate emissions.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-35. N2O emissions from
adipic acid production for 2011 were estimated to be between 9.6 and 11.6 Tg CO2 Eq. at the 95 percent confidence
level. These values indicate a range of approximately 9 percent below to 9 percent above the 2011 emission
estimate of 10.6 Tg CO2 Eq.
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for NzO Emissions from Adipic Acid
Production (Tg COz Eq. and Percent)
2011Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Adipic Acid Production N2O 10.6 9.6 11.6 -9% +9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Future improvements involve continuing to evaluate, analyze, and use data reported under EPA's GHGRP that
would provide more accurate emission estimates for future years, and could also be useful to improve the emission
factors used for the Adipic Acid Production source category for years prior to 2010. Particular attention would be
made to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent
with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGPJ3, with
the program's initial requirements for reporting of emissions in calendar year 2010, are not available for all
inventory years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and
integration of data from EPA's GHGPJ3, the latest guidance from the IPCC on the use of facility-level data in
national inventories has been, and will continue to be, relied upon.142 Specifically, the planned improvements
include continuing to assess data to update the N2O emission factors (which could be used to improve historical
emission estimates) and update abatement utility and destruction factors based on actual performance of the latest
catalytic and thermal abatement equipment at plants with continuous process and emission monitoring equipment.
Carbon dioxide and CH4 are emitted from the production143 of silicon carbide (SiC), a material used as an industrial
abrasive. Emissions from fuels consumed for energy purposes during the production of silicon carbine are
accounted for in the Energy chapter. To make SiC, quartz (SiO2) is reacted with C in the form of petroleum coke. A
142 See
143 Silicon carbide is produced for both abrasive and metallurgical applications in the United States. Production for metallurgical
applications is not available and therefore both CH4 and CCh estimates are based solely upon production estimates of silicon
carbide for abrasive applications.
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
portion (about 35 percent) of the C contained in the petroleum coke is retained in the SiC. The remaining C is
emitted as CO2, CH4, or CO.
Carbon dioxide is also emitted from the consumption of SiC for metallurgical and other non-abrasive applications.
The USGS reports that a portion (approximately 50 percent) of SiC is used in metallurgical and other non-abrasive
applications, primarily in iron and steel production (USGS 2006a). Markets for manufactured abrasives, including
SiC, are heavily influenced by activity in the U.S. manufacturing sector, especially in the aerospace, automotive,
furniture, housing, and steel manufacturing sectors. As a result of the economic downturn in 2008 and 2009, demand
for SiC decreased in those years. Low cost imports, particularly from China, combined with high relative operating
costs for domestic producers, continue to put downward pressure on the production of SiC in the United States.
However, demand for SiC consumption in the United States has recovered somewhat from its lows in 2009 (USGS
2012a).
Carbon dioxide emissions from SiC production and consumption in 2011 were 0.17 Tg CCh Eq. (170 Gg).
Approximately 54 percent of these emissions resulted from SiC production while the remainder resulted from SiC
consumption. Methane emissions from SiC production in 2011 were 0.01 Tg CO2 Eq. CH4 (0.4 Gg) (see Table
4-36: and Table 4-37).
Table 4-36: COz and ChU Emissions from Silicon Carbide Production and Consumption (Tg
COz Eq.)
Year
C02
CH4
Total
1990
0.4 -
+
0.4
2005
0.2
+
0.2
2007
•! 0.2
+
* 0.2
2008
0.2
+
0.2
2009
0.1
+
0.2
2010
0.2
+
0.2
2011
0.2
+
0.2
+ Does not exceed 0.05 Tg CCh Eq.
Note: Totals may not sum due to independent rounding.
Table 4-37: COz and ChU Emissions from Silicon Carbide Production and Consumption (Gg)
Year 1990 2005 ; 2007 2008 2009 2010 2011
C02 375 219 A 196 175 145 181 170
CH4 1 + .••'' + + + + +_
+ Does not exceed 0.5 Gg.
Emissions of COa and CH4 from the production of SiC were calculated by multiplying annual SiC production by the
emission factors (2.62 metric tons CCh/metric ton SiC for CC>2 and 11.6 kg CH4/metric ton SiC for CH4) provided
by the 2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006).
Emissions of CC>2 from silicon carbide consumption for metallurgical uses were calculated by multiplying the
annual utilization of SiC for metallurgical uses (reported annually in the USGS Minerals Yearbook for Silicon) by
the C content of SiC (31.5 percent), which was determined according to the molecular weight ratio of SiC.
Emissions of CChfrom silicon carbide consumption for other non-abrasive uses were calculated by multiplying the
annual SiC consumption for non-abrasive uses by the C content of SiC (31.5 percent). The annual SiC consumption
for non-abrasive uses was 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 2006a) then minus the SiC
consumption for metallurgical use. Production data for 1990 through 2010 were obtained from the Minerals
Yearbook: Manufactured Abrasives (USGS 1991a through 201 la and 2012b). Production data for 2011 was taken
from the Minerals Commodity Summary: Abrasives (Manufactured) (2012a). Silicon carbide consumption by
major end use was obtained from the Minerals Yearbook: Silicon (USGS 1991b through 201 Ib and2012c) (see
Table 4-38) for years 1990 through 2010. Silicon carbide for metallurgical consumption for 2011 is proxied using
Industrial Processes 4-35
-------
2010 data due to unavailability of data at time of publication. Net imports for the entire time series were obtained
from the U.S. Census Bureau (2005 through 2012).
Table 4-38: Production and Consumption of Silicon Carbide (Metric Tons)
Year
1990
2005
2007
2008
2009
2010
2011
Production
105,000
35,000
35,000
35,000
35,000
35,000
35,000
Consumption
172,465
220,149
179,741
144,928
92,280
154,540
136,222
and
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 uncertainty associated with the use or destruction of
methane generated from the process in addition to uncertainty associated with levels of production, net imports,
consumption levels, and 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 4-39. Silicon carbide production
and consumption CCh emissions were estimated to be between 9 percent below and 10 percent above the emission
estimate of 0.2 Tg CC>2 Eq. at the 95 percent confidence level. Silicon carbide production CH4 emissions were
estimated to be between 9 percent below and 9 percent above the emission estimate of 0.01 Tg CCh Eq. at the 95
percent confidence level.
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for ChU and COz Emissions from
Silicon Carbide Production and Consumption (Tg COz Eq. and Percent)
2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Silicon Carbide Production
and Consumption
Silicon Carbide Production
C02 0.2
CH4 +
Lower Upper Lower
Bound Bound Bound
0.2 0.2 -9%
+ + -9%
Upper
Bound
+10%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 Tg CO2 Eq. or 0.5 Gg.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Silicon Carbide Production source category. Particular attention will be made
to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with
IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of data
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will
be relied upon.144 In addition, improvements will involve 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.
The production of some petrochemicals results in the release of small amounts of CH4 and CCh emissions.
Petrochemicals are chemicals isolated or derived from petroleum or natural gas. Methane emissions from the
production of carbon black, ethylene, ethylene dichloride, and methanol and CC>2 emissions from the production of
carbon black are presented here and reported under IPCC Source Category 2B5. The CC>2 emissions from
petrochemical processes other than carbon black are currently reported under Carbon Emitted from Non-Energy
Uses of Fossil Fuels in the Energy chapter. The CC>2 from carbon black production is included here to allow for the
direct reporting of CCh emissions from the process and direct accounting of the feedstocks used in the process.
Carbon black is an intense black powder generated by the incomplete combustion of an aromatic petroleum or coal-
based feedstock. Most carbon 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. The other major use of carbon black is as a pigment.
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. The primary use of ethylene dichloride is in the production of vinyl chloride
monomer, the precursor to PVC. Ethylene dichloride was used as a fuel additive until 1996 when leaded gasoline
was phased out. Methanol is a chemical feedstock most often converted into formaldehyde, acetic acid and olefins.
It is also an alternative transportation fuel as well as an additive used by municipal wastewater treatment facilities in
the denitrification of wastewater. Emissions of CCh and CH4 from petrochemical production in 2011 were 3.5 Tg
CO2 Eq. (3,505 Gg) and 3.1 Tg CH4 Eq. (148 Gg), respectively (see Table 4-40 and Table 4-41), totaling 6.6 Tg CO2
Eq. There has been an overall increase in CC>2 emissions from carbon black production of 2 percent since 1990.
Methane emissions from petrochemical production have increased by approximately 37 percent since 1990.
Table 4-40: COz and Cm Emissions from Petrochemical Production (Tg COz Eq.)
Year
C02
CH4
Total
1990
3.4
2.3
5.7
2005
4.3
3.1
7.5 ;
2007
4.1
3.3
7.3
2008
3.6
2.9
6.5
2009
2.8
2.9
5.7
2010
3.5
3.1
6.5
2011
3.5
3.1
6.6
Notes: Totals may not sum due to independent rounding.
CO2 emissions are from carbon black production only.
Table 4-41: COz and ChU Emissions from Petrochemical Production (Gg)
Year 1990 2005 , 2007 2008 2009 2010 2011
CO2 3,429 4,330 4,070 3,572 2,833 3,455 3,505
CH4 108 150 155 137 138 146 148
Note: CO2 emissions are from carbon black production only.
144 See
Industrial Processes 4-37
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Emissions of CH4 were calculated by multiplying annual estimates of chemical production by the appropriate
emission factor, as follows: 0.06 kg CHVmetric ton carbon black, 6 kg CHVmetric ton ethylene, 0.0226 kg
CHVmetric ton ethylene dichloride, and 2.3 kg CHVmetric ton methanol. Although the production of other
chemicals may also result in CH4 emissions, insufficient data were available to estimate their emissions.
Emission factors were taken from the 2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006)
Annual production data (see Table 4-42) were obtained from the American Chemistry Council's Guide to the
Business of Chemistry (ACC 2002, 2003, 2005 through 2012) and the International Carbon Black Association
(Johnson 2003 and 2005 through 2012). Methanol production data for 1990 through 2007 were obtained from the
ACC Guide to the Business of Chemistry (ACC 2002, 2003, 2005 through 2011). The ACC discontinued its data
series for Methanol after 2007, so methanol production data for 2008 through 2011 was obtained through the
Methanol Institute (Jordan 2012a and 2012b).
Table 4-42: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
Carbon Black
Ethylene
Ethylene Dichloride
Methanol
1990
1,307
16,542
6,283
3,785
2005
1,651
23,975
11,260
2,336
2007
1,552
25,415
9,565
1,068
2008
1,362
22,555
8,975
810
2009
1,080
22,610
8,120
810
2010
1,317
23,975
8,810
903
2011
1,337
24,410
8,460
760
Almost all carbon 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 carbon black feedstock is combusted to provide energy to the process. Carbon 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. carbon black
plant produces carbon black using the thermal black process, one U.S. carbon black plant produces carbon black
using the acetylene black process, (The Innovation Group 2004), and one carbon black plant uses the lampblack
process (EPA 2000).
The furnace black process produces carbon black from "carbon black feedstock" (also referred to as "carbon 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
carbon black, the "primary feedstock" (i.e., carbon 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 carbon
black feedstock are oxidized to provide heat to the production process and pyrolyze the remaining carbon black
feedstock to carbon black. The "tail gas" from the furnace black process contains CCh, 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 carbon black product dryers. The remaining tail gas may also be burned for energy
recovery, flared, or vented uncontrolled to the atmosphere.
The calculation of the C lost during the production process is the basis for determining the amount of CO2 released
during the process. The C content of national carbon black production is subtracted from the total amount of C
contained in primary and secondary carbon 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 CCh. 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 CCh. The total amount of primary and secondary carbon black feedstock
consumed in the process (see Table 4-43) is estimated using a primary feedstock consumption factor and a
secondary feedstock consumption factor estimated from U. S. Census Bureau (1999, 2004, and 2007) data. The
average carbon black feedstock consumption factor for U.S. carbon black production is 1.69 metric tons of carbon
black feedstock consumed per metric ton of carbon black produced. The average natural gas consumption factor for
U.S. carbon black production is 321 normal cubic meters of natural gas consumed per metric ton of carbon 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 (El A 2003, 2004).
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-43: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock
(Secondary Feedstock) Consumption (Thousand Metric Tons)
Activity 1990 2005 : 2007 2008 2009 2010 2011
Primary Feedstock 2,213 2,794 - 2,627 2,305 1,828 2,229 2,262
Secondary Feedstock 284 359 337 296 235 286 290
For the purposes of emission estimation, 100 percent of the primary carbon black feedstock is assumed to be derived
from petroleum refining byproducts. Carbon black feedstock derived from metallurgical (coal) coke production
(e.g., creosote oil) is also used for carbon black production; however, no data are available concerning the annual
consumption of coal-derived carbon black feedstock. Carbon black feedstock derived from petroleum refining
byproducts is assumed to be 90 percent elemental C (IPCC 2006). It is assumed that 100 percent of the tail gas
produced from the carbon 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
carbon black because of the lack of data concerning the relatively small amount of carbon black produced using the
acetylene black and thermal black processes. The carbon black produced from the furnace black process is assumed
to be 97 percent elemental C (Othmer et al. 1992, IPCC 2006).
The CH4 emission factors used for petrochemical production are based on a limited number of studies. Using plant-
specific factors instead of default or average factors could increase the accuracy of the emission estimates; however,
such data were not available for the current publication. 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 CC>2 emissions from carbon black production calculation
are based on feedstock consumption, import and export data, and carbon black production data. The composition of
carbon black feedstock varies depending upon the specific refinery production process, and therefore the assumption
that carbon black feedstock is 90 percent C gives rise to uncertainty. Also, no data are available concerning the
consumption of coal-derived carbon black feedstock, so CCh 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 carbon black production may be underreported by the U.S. Census Bureau. Finally, the
amount of carbon 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 carbon black is produced using the furnace black process.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-44. Petrochemical production
CO2 emissions were estimated to be between 2.6 and 4.5 Tg CCh Eq. at the 95 percent confidence level. This
indicates a range of approximately 26 percent below to 29 percent above the emission estimate of 3.5 Tg CCh Eq.
Petrochemical production CH4 emissions were estimated to be between 2.2 and 4.0 Tg CCh Eq. at the 95 percent
confidence level. This indicates a range of approximately 29 percent below to 30 percent above the emission
estimate of 3.1 Tg CCh Eq.
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Petrochemical
Production and COz Emissions from Carbon Black Production (Tg CO2 Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg CCh Eq.) (Tg C02 Eq.) (%)
Petrochemical
Production
Petrochemical
Production
C02
CH4
3.5
3.1
Lower
Bound
2.6
2.2
Upper
Bound
4.5
4.0
Lower
Bound
-26%
-29%
Upper
Bound
+29%
+30%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-39
-------
Relative to the previous inventory, emissions data for all years was updated using emission factors published in the
2006 IPCC guidelines (IPCC 2006). Previous reports applied the 1996 IPCC guidelines IPCC/UNEP/OECD/IEA
(1997). A significant decrease in CH4 emissions from carbon black production resulted from this recalculation,
because the emissions factor in the 2006 IPCC guidelines is based on actual data from three European carbon black
facilities. These facilities use thermal treatment to control CH4 emissions, and the assumption of thermal treatment
is recommended for North American facilities as well. The feedstock C content for carbon black was revised from
89 to 90 percent based on the values for carbon black feedstock listed in IPCC (2006) rather than the value used in
the previous inventory, which was an average often petrochemical feedstocks.
The emission factor for ethylene production was revised upward from 1.0 g CH4/kg of product to 6.0 g CH4/kg of
product based on the 2006 IPCC guidelines. This emission factor is based on test data from 15 European facilities
and reflects the most current knowledge of this process. The emission factor for ethylene dichloride was revised in
the 2006 IPCC downward from 0.4 to 0.0226 g CH4/ kg product to reflect the information that CH4 emissions arise
only from combustion of natural gas, not from the production process itself.
The net result of these adjustments to emission factors for Petrochemical Production is that the emission estimate for
2011 is higher than it would have been under the previous methodology, an increase from 4.3 to 6.6 Tg CO2 Eq. The
ethylene process is the primary driver of the increase. A comparison of the results of the two calculation methods is
shown in Table 4-44 for the 2011 data. Between the 1996 and 2006 emission factors Ethylene is increased by 2.57
Tg CO2 Eq and Carbon Black decreased by 0.31 Tg CCh Eq. Overall, the total emission factors increased since
IPCC 1996.
Pending resources, a potential improvement to the inventory estimates for this source category would include the
derivation of country-specific emission factors, based on data reported under EPA's GHGPJ3 which uses a method
similar to IPCC Tier 2 and 3 approaches. Using data elements reported under EPA's GHGPJ3, specifically emissions
and petrochemical production data (i.e., carbon black, ethylene, ethylene oxide, and acrylonitrile) that can be
aggregated from facility level to national level for its use, EPA will derive a country-specific emission factor for
estimating process emissions for each type of petrochemical produced. The new emissions factors derived from
GHGRP data will replace the use of IPCC defaults, as currently described in the methodological section.
Additionally, acrylonitrile and ethylene oxide are chemical processes that are included in the IPCC petrochemical
production source category, but have not been included in the U.S. estimates of emissions from this category due to
a prior lack of data. Data on production of these two chemicals are not available from public sources used to
establish the production and emissions from manufacture of the other petrochemical processes. However,
information from these processes and other petrochemical products are now collected by EPA's GHGPJ3 starting
with calendar year 2010. In order to provide estimates for the entire time series (i.e., 1990 through 2009), EPA will
need to evaluate applicability of more recent GHGPJ3 data to previous years' estimates, and potentially research
additional data that could be utilized to calculate emissions from production of these chemicals.
Titanium dioxide (TiCh) is a metal oxide manufactured from titanium ore, and is principally used as a pigment in
white paint, lacquers, and varnishes. Titanium Dioxide is also used as a pigment in the manufacture of paper, foods,
plastics, and other products. There are two processes for making TiCh: the chloride process and the sulfate process.
The chloride process uses petroleum coke and chlorine as raw materials and emits process-related CCh. Emissions
from fuels consumed for energy purposes during the production of titanium dioxide are accounted for in the Energy
chapter.
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 -» 2 TiCl4 + 2 FeCl3 + 3 CO2
2 TiCL, + 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 FeTiOs (the Ti-containing ore) to form CO2. Since 2004, all TiO2 produced in the United States is through the
chloride process, and a special grade of "calcined" petroleum coke is manufactured specifically for this purpose.
Emissions of CO2 in 2011 were 1.9 Tg CO2 Eq. (1,903 Gg), which represents an increase of 59 percent since 1990
(see Table 4-45).
Table 4-45: COz Emissions from Titanium Dioxide (Tg COz Eq. and Gg)
Year
1990
2005
2007
2008
2009
2010
2011
Tg CO2 Eq.
1.2
1.8
1.9
1.8
1.6
1.8
1.9
Gg
1,195
1,755
1,930
1,809
1,648
1,769
1,903
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
closed; therefore, 100 percent of post-2004 production uses 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 (IPCC 2006). It was
assumed that all TiO2 produced using the chloride process was produced using petroleum coke, although some TiO2
may have been produced with graphite or other C inputs. The amount of petroleum coke consumed annually in
TiO2 production was calculated based on the assumption that the calcined petroleum coke used in the process is 98.4
percent C and 1.6 percent inert materials (Nelson 1969).
The emission factor for the TiO2 chloride process was taken from the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). Titanium dioxide production data and the percentage of total TiO2
production capacity that is chloride process for 1990 through 2010 (see Table 4-46:) were obtained through the
Minerals Yearbook: Titanium Annual Report (USGS 1991 through 2012a). Production data for 2011 was obtained
from the Minerals Commodity Summary: Titanium and Titanium Dioxide (USGS 2012b). Due to lack of available
2011 production capacity data at the time of publication, the 2010 production capacity estimate is used as a proxy
for 2011. Percentage chloride-process data were not available for 1990 through 1993, so 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).
Industrial Processes 4-41
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Table 4-46: Titanium Dioxide Production (Gg)
Year Gg
1990 979
2005 1,310
2007 1,440
2008 1,350
2009 1,230
2010 1,320
2011 1,420
Each year, USGS collects titanium industry data for titanium mineral and pigment production operations. If TiCh
pigment plants do not respond, production from the operations is estimated on the basis of prior year production
levels and industry trends. Variability in response rates varies from 67 to 100 percent of TiCh pigment plants over
the time series.
Although some TiCh 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 CCh per unit of TiCh 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 TiCh produced, sufficient data were not available
to do so.
As of 2004, the last remaining sulfate-process plant in the United States closed. Since annual TiCh production was
not reported by USGS by the type of production process used (chloride or sulfate) prior to 2004 and only the
percentage of total production capacity by process was reported, the percent of total TiCh production capacity that
was attributed to the chloride process was multiplied by total TiCh production to estimate the amount of TiCh
produced using the chloride process. 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 TiCh production, literature data
were used for petroleum coke composition. Certain grades of petroleum coke are manufactured specifically for use
in the TiCh chloride process; however, this composition information was not available.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-47:. Titanium dioxide
consumption CCh emissions were estimated to be between 1.6 and 2.2 Tg CCh Eq. at the 95 percent confidence
level. This indicates a range of approximately 15 percent below and 15 percent above the emission estimate of 1.9
Tg CO2 Eq.
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Titanium
Dioxide Production (Tg COz Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (Tg CCh Eq.) [%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Titanium Dioxide Production CCh 1.9 1.6 2_2 -15% +15%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Production data for 2010 were updated relative to the previous inventory based on recently published data in the
USGS Minerals Yearbook: Titanium 2010 (USGS 2012b). This resulted in a 6 percent decrease in 2010 CO2
emissions from TiCh production relative to the previous report.
Pending resources, a potential improvement to the inventory estimates for this source category would include the
derivation of country-specific emission factors, based on data reported under EPA's GHGRP. Using data elements
reported under the GHGRP, specifically emissions and titanium production data that can be aggregated at the
national level for its use, EPA will derive a country-specific emission factor for estimating process emissions. The
emission factor will be derived from aggregating annual facility-level process line data on annual titanium dioxide
production and facility level emissions,. Information on titanium dioxide production is collected by EPA's GHGRP
starting with calendar year 2010. In order to provide estimates for the entire time series (i.e., 1990 through 2009),
EPA will need to evaluate applicability of more recent GHGRP data to previous years estimates and potentially
research additional data that could be utilized in the calculations for this source category. In implementing
improvements and integration of data from EPA's GHGRP, the latest guidance fromthe IPCC on the use of facility-
level data in national inventories will be relied upon.145
In addition, the planned improvements 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.
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).
Carbon dioxide used for EOR is injected into the underground reservoirs to increase the reservoir pressure to enable
additional petroleum to be produced. For the most part, CCh used in non-EOR applications will eventually be
released to the atmosphere, and for the purposes of this analysis €62 used in commercial applications other than
EOR is assumed to be emitted to the atmosphere. Carbon dioxide used in EOR applications is discussed in the
Energy Chapter under "Carbon Capture and Storage, including Enhanced Oil Recovery" and is not discussed in this
section.
CO2 is produced from naturally occurring CO2 reservoirs, as a byproduct from the energy and industrial production
processes (e.g., ammonia production, fossil fuel combustion, ethanol production), and as a byproduct from the
production of crude oil and natural gas, which contain naturally occurring CO2 as a component. Only CO2 produced
from naturally occurring CO2 reservoirs and used in industrial applications other than EOR is included in this
analysis. Neither byproduct CO2 generated from energy nor industrial production processes nor CO2 separated from
crude oil and natural gas are included in this analysis for a number of reasons. Carbon dioxide captured from
biogenic sources (e.g., ethanol production plants) is not included in the inventory. Carbon dioxide captured from
crude oil and gas production is used in EOR applications and is therefore reported in the Energy Chapter. Any CO 2
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
145 See
Industrial Processes 4-43
-------
are therefore accounted for under Ammonia Production, Fossil Fuel Combustion, or other appropriate source
category.146
CO2 is produced as a byproduct of crude oil and natural gas production. This €62 is separated from the crude oil
and natural gas using gas processing equipment, and may be emitted directly to the atmosphere, or captured and
reinjected into underground formations, used for EOR, or sold for other commercial uses. A further discussion of
CO2 used in EOR is described in the Energy Chapter under the text box titled "Carbon Dioxide Transport, Injection,
and Geological Storage." The only CO2 consumption that is accounted for in this analysis is CO2 produced from
naturally-occurring CO2 reservoirs that is used in commercial applications other than EOR.
There are currently three facilities, one in Mississippi (Jackson Dome) and two in New Mexico (Bravo Dome and
West Bravo Dome), producing CO2 from naturally occurring CO2 reservoirs for use in both EOR and in other
commercial applications (e.g., chemical manufacturing, food production). A fourth facility in Colorado (McCallum
Dome) is producing CO2 from naturally occurring CO2 reservoirs for commercial applications only. There are other
naturally occurring CO2 reservoirs, mostly located in the western United States, that produce CO2 but they are only
producing CO2 for EOR applications, not for other commercial applications (Allis et al. 2000). Carbon dioxide
production from these facilities is discussed in the Energy Chapter.
In 2011, the amount of CO2 produced by the Colorado, Mississippi, and New Mexico facilities for commercial
applications and subsequently emitted to the atmosphere was 1.8 Tg CO2Eq. (1,811 Gg) (see Table 4-48). This is a
decrease of 18 percent from the previous year and an increase of 28 percent since 1990. This increase was largely
due to an in increase in production at the Mississippi facility, despite the low percentage (9 percent) of the facility's
total reported production that was used for commercial applications in 2011.
Table 4-48: COz Emissions from COz Consumption (Tg COz Eq. and Gg)
Year
1990
2005
2007
2008
2009
2010
2011
Tg CO2 Eq.
1.4
1.3
1.9
1.8
1.8
2.2
1.8
Gg
1,416
1,321
1,867
1,780
1,784
2,203
1,811
CO2 emission estimates for 1990 through 2011 were based on production data for the four 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 and the percentage of production that was used for non-EOR applications for the Jackson
Dome, Mississippi facility were obtained from Advanced Resources International (ARI 2006, 2007) for 1990 to
2000 and from the Annual Reports of Denbury Resources (Denbury Resources 2002 through 2012) for 2001 to 2011
(see Table 4-49). Denbury Resources reported the average CO2 production in units of MMCF CO2 per day for 2001
through 2011 and reported the percentage of the total average annual production that was used for EOR. Production
from 1990 to 2000 was set equal to 2001 production. Carbon dioxide production data for the Bravo Dome, New
Mexico facilities were obtained from ARI for 1990 through 2010. Data for the West Bravo Dome facility was only
146 There are currently four known electric power plants operating in the U.S. that capture CCh for use as food-grade CO2 or
other industrial processes; however, insufficient data prevents estimating emissions from these activities as part of CCh
Consumption.
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
available for 2009 and 2010. Since 2011 COa production was not available for Bravo Dome facilities, 2010 data was
used as a proxy for 2011. The percentage of total production that was used for non-EOR applications were obtained
from the New Mexico Bureau of Geology and Mineral Resources (Broadhead 2003 and New Mexico Bureau of
Geology and Mineral Resources 2006). Production data for the McCallum Dome, Colorado facility were obtained
from the Colorado Oil and Gas Conservation Commission (COGCC) for 1999 through 2011 (COGCC 2012).
Production data for 1990 to 1998 and percentage of production used for EOR were assumed to be the same as for
1999.
Table 4-49: COz Production (Gg COz) and the Percent Used for Non-EOR Applications
Year
1990
2005
2007
2008
2009
2010
2011
Jackson Dome, MS
COi Production
(Gg)(% Non-EOR)
1,353(100%)
4,678 (27%)
9,529 (19%)
12,312(14%)
13,201 (13%)
16,487(13%)
19,487(9%)
Bravo Dome, NM
CCh Production
(Gg)(% Non-
EOR)
6,301 (1%)
5,799 (1%)
5,605 (1%)
5,605 (1%)
4,639 (1%)
4,832 (1%)
4,832 (1%)
West Bravo Dome,
NMCO2
Production
(Gg) (% Non-EOR)
-
-
-
-
2,126 (1%)
870 (1%)
870 (1%)
McCallum Dome,
CO
CO2 Production
(Gg)(% Non-EOR)
0.07 (100%)
0.06 (100%)
0.07 (100%)
0.07 (100%)
0.02 (100%)
0.05 (100%)
0.03 (100%)
and
Uncertainty is associated with the number of facilities that are currently producing CO2 from naturally occurring
CO2 reservoirs for commercial uses other than EOR, and for which the CO2 emissions are not accounted for
elsewhere. Research indicates that there are only two such facilities, which are in New Mexico and Mississippi;
however, additional facilities may exist that have not been identified. In addition, it is possible that CO2 recovery
exists in particular production and end-use sectors that are not accounted for elsewhere. Such recovery may or may
not affect the overall estimate of CO2 emissions from that sector depending upon the end use to which the recovered
CO2 is applied. Further research is required to determine whether CO2 is being recovered from other facilities for
application to end uses that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-50. Carbon dioxide
consumption CO2 emissions were estimated to be between 1.4 and 2.4 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of approximately 25 percent below to 30 percent above the emission estimate of 1.8 Tg
CO2 Eq.
Table 4-50: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from COz
Consumption (Tg COz Eq. and Percent)
Source
Gas 2010 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
CCh Consumption CCh
1.4
2.4
-25%
+30%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Carbon Dioxide Consumption source category. Particular attention will be
made to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent
Industrial Processes 4-45
-------
with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGPJ3, with
the program's initial requirements for reporting of emissions in calendar year 2010, are not available for all
inventory years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and
integration of data from EPA's GHGPJ3, the latest guidance from the IPCC on the use of facility-level data in
national inventories will be relied upon.147
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:
Caio-x-y Nax Mgy (PO4)6-x(CO3)xF2+0.4x
The calcium carbonate component of the phosphate rock is integral to the phosphate rock chemistry. Phosphate
rock can also contain organic C that is physically incorporated into the mined rock but is not an integral component
of the phosphate rock chemistry. Phosphoric acid production from natural phosphate rock is a source of CO2
emissions, due to the chemical reaction of the inorganic C (calcium carbonate) component of the phosphate rock.
The phosphoric acid production process involves chemical reaction of the calcium phosphate (Ca3(PO4)2)
component of the phosphate rock with sulfuric acid (H2SO4) and recirculated phosphoric acid (H3PO4) (EFMA
2000). The primary chemical reactions for the production of phosphoric acid from phosphate rock are:
Ca3(PO4)2 + 4H3PO4 -> 3Ca(H2PO4)2
3Ca(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. Emissions from fuels consumed for
energy purposes during the production of phosphoric acid are accounted for in the Energy chapter. The chemical
reaction for the limestone-sulfuric acid reaction is:
CaCO3 + H2SO4 +H2O -> CaSO4 • 2H2O + CO2
Total U.S. phosphate rock production sold or used in 2011 was 28.6 million metric tons (USGS 2012).
Approximately 80 percent of domestic phosphate rock production was mined in Florida and North Carolina, while
approximately 20 percent of production was mined in Idaho and Utah. Total imports of phosphate rock in 2011
were 3.4 million metric tons (USGS 2012). The vast majority, 99 percent, of imported phosphate rock is sourced
from Morocco (USGS 2005). Phosphate rock production, including domestic production and imports for
consumption, increased between 2010 and 2011 by 5 percent. Over the 1990 to 2011 period, domestic production
has decreased by nearly 43 percent. Total CO2 emissions from phosphoric acid production were 1.2 Tg CO2 Eq.
(1,151 Gg)in2011 (see Table 4-51). After experiencing weak market conditions due to the global economic
downturn in 2008 and 2009, demand for and trade in phosphate rock increased in 2010 and 2011 (USGS 2012).
Table 4-51: COz Emissions from Phosphoric Acid Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 1.5 1,529
147 See
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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2005 1.3 1,342
2007
2008
2009
2010
2011
1.2
1.1
1.0
1.1
1.2
1,203
1,132
977
1,087
1,151
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 CCh 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 USGSMineral 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 4-52). For the years 1990, 1991,
1992, and 2005 through 2011, only nationally aggregated mining data was reported by USGS. For the years 1990,
1991, and 1992, the breakdown of phosphate rock mined in Florida and North Carolina, and the amount mined in
Idaho and Utah, are approximated using average share of U.S. production in those states from 1993 to 2004 data.
For the years 2005 through 2011, the same approximation method is used, but the share of U.S. production in those
states data were obtained from the USGS commodity specialist for phosphate rock (USGS 2012). Data for domestic
sales or consumption of phosphate rock, exports of phosphate rock (primarily from Florida and North Carolina), and
imports of phosphate rock for consumption for 1990 through 2011 were obtained from USGS Minerals Yearbook:
Phosphate Rock (USGS 1994 through 2011, 2013). From 2004 through 2011, the USGS reported no exports of
phosphate rock from U.S. producers (USGS 2005 through 2011, USGS 2012).
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 4-53).
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 (80 percent of dome stic production) and
carbonate content data for phosphate rock mined in Morocco are used to calculate CO2 emissions from consumption
of imported phosphate rock. The CCh emissions calculation is based on the assumption that all of the domestic
production of phosphate rock is used in uncalcined form. As of 2006, the USGS noted that one phosphate rock
producer in Idaho produces calcined phosphate rock; however, no production data were available for this single
producer (USGS 2006). The USGS confirmed that no significant quantity of domestic production of phosphate rock
in 2011 is in the calcined form (USGS 2012).
Table 4-52: Phosphate Rock Domestic Consumption, Exports, and Imports (Gg)
Location/Year
U.S. Domestic
Consumption3
FL&NC
ID&UT
Exports— FL & NC
Imports — Morocco
1990
49,800
42,494
7,306
6,240 -.
451 .
2005
35,200
. 28,160
7,040 /
-
2,630
2007
31,100
24,880
6,220
-
2,670
2008
28,900
23,120
5,780
-
2,750
2009
25,500
20,400
5,100
-
2,000
2010
28,100
22,480
5,620
-
2,400
2011
28,600
22,880
5,720
-
3,350
Industrial Processes 4-47
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Total U.S. 1
Consumption 44,011 37,830 33,770 31,650 27,500 30,500 31,950
a USGS does not disaggregate production data regionally (FL & NC and ID & UT) for 1990 and 2005 through 2011. Data
for those years are estimated based on information from the USGS commodity specialist (USGS 2012).
- Assumed equal to zero.
Table 4-53: Chemical Composition of Phosphate Rock (percent by weight)
Composition
Total Carbon (as C)
Inorganic Carbon (as C)
Organic Carbon (as C)
Inorganic Carbon (as CCh)
Central
Florida
1.60
1.00
0.60
3.67
North
Florida
1.76
0.93
0.83
3.43
North Carolina
(calcined)
0.76
0.41
0.35
1.50
Idaho
(calcined)
0.60
0.27
1.00
Morocco
1.56
1.46
0.10
5.00
Source: FIPR 2003
- Assumed equal to zero.
and
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 2011. For previous years in the time series,
USGS provided the data disaggregated regionally; however, beginning in 2006 only total U.S. phosphate rock
production were reported. Regional production for 2011 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 2011 regional production data represents actual production in those regions. Total
U.S. phosphate rock production data are not considered to be a significant source of uncertainty because all the
domestic phosphate rock producers report their annual production to the USGS. Data for exports of phosphate rock
used in the emission calculation are reported by phosphate rock producers and are not considered to be a significant
source of uncertainty. Data for imports for consumption are based on international trade data collected by the U.S.
Census Bureau. These U.S. government economic data are not considered to be a significant source of uncertainty.
An additional source of uncertainty in the calculation of COa 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 CCh 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 COa. However, according to air permit information available to
the public, at least one facility has calcining units permitted for operation (NCDENR, 2013).
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 CCh in the elemental phosphorus production process. The calculation for CCh
emissions is based on the assumption that phosphate rock consumption, for purposes other than phosphoric acid
production, results in COa 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 4-54. Phosphoric acid production
CO2 emissions were estimated to be between 0.9 and 1.4 Tg CCh Eq. at the 95 percent confidence level. This
indicates a range of approximately 18 percent below and 18 percent above the emission estimate of 1.2 Tg CCh Eq.
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-54: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Phosphoric
Acid Production (Tg COz Eq. and Percent)
2011 Emission
Source Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg COz Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Phosphoric Acid Production CCh 1 .2
0.9 1.4 -18% +18%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Emissions were updated relative to the previous inventory based on data for apparent consumption of phosphate
rock (phosphate rock sold or consumed) for the years 2005 through 2010 (USGS 2012). Previous estimates were
made using production of phosphate rock. This resulted in a net decrease in emissions from 2005 through 2010 of
less than 1 percent relative to the previous report.
Pending resources, a potential improvement to the inventory estimates for this source category would include
updating the inorganic carbon content of phosphate rock based on data reported under EPA's GHGRP. This new
inorganic carbon content factor would be applied to regional phosphate rock consumption aggregated from facility
level reports in the methodology, replacing use of USGS national-level data for 2010 and onward. Information from
phosphoric acid producers is now collected by EPA's GHGRP starting with calendar year 2010. In order to provide
estimates for the entire time series (i.e. 1990 through 2009), EPA will need to evaluate applicability of more recent
GHGRP data to previous years estimates and potentially research additional data that could be utilized in the
calculations for this source category.
The production of iron and steel is an energy-intensive activity that generates process-related emissions of CCh and
CH4. Process emissions occur at each step of steel production from the production of raw materials to the
refinement of iron to the making of crude steel. In the United States, steel is produced through both primary and
secondary processes. Historically, primary production—using a basic oxygen furnace (EOF) with pig iron as the
primary feedstock—has been the dominant method. However, secondary production using scrap steel in electric arc
furnaces (EAFs) has increased significantly in recent years due to the increased availability of scrap steel and the
resultant economic advantages of steel recycling. Total production of crude steel in the United States between 2000
and 2008 ranged from a low of 99,320,000 tons to a high of 109,879,000 tons (2001 and 2004, respectively). Due to
the decrease in demand caused by the global economic downturn (particularly from the automotive industry), crude
steel production in the United States sharply decreased to 65,460,000 tons in 2009. In 2010, crude steel production
rebounded to 88,730,000 tons as economic conditions improved and then increased further to 95,240,000 tons in
2011(AISI2012).
Metallurgical coke is an important input in the production of iron and steel. The metallurgical coke production
process produces CCh emissions and fugitive CH4 emissions.
Industrial Processes 4-49
-------
Coke is used to produce iron or pig iron feedstock from raw iron ore. The production of metallurgical coke from
coking coal may occur either on-site at "integrated" iron and steel plants or off-site at "merchant" coke plants.
Metallurgical coke is produced by heating coking coal in a coke oven in a low-oxygen environment; this heating
drives off the volatile components of the coking coal and produces coal (metallurgical) coke. Carbon-containing
byproducts of the metallurgical coke manufacturing process include coke oven gas, coal tar, coke breeze (small-
grade coke oven coke with particle size <5 mm) and light oil. Coke oven gas typically is recovered and used as fuel
for underfiring the coke ovens, as well as a process gas and fuel within the iron and steel mill. Small amounts of
coke oven gas are also sold as synthetic natural gas outside of iron and steel mills (and are accounted for in the
Energy chapter). Coal tar is used as a raw material to produce anodes used for primary aluminum production, EAF
steel production, and other electrolytic processes, and also is used in the production of other coal tar products. Coke
breeze may be used in the sintering process. Light oil is sold to petroleum refiners who use the material as an
additive for gasoline.
Iron is produced by first reducing iron oxide (iron ore) with metallurgical coke in a blast furnace. Iron can be
introduced into the blast furnace in the form of raw iron ore, taconite pellets (9-16 mm iron-containing spheres),
briquettes, or sinter. In addition to metallurgical coke and iron, other inputs to the blast furnace include natural gas,
fuel oil, and coke oven gas. The carbon in the metallurgical coke used in the blast furnace combines with oxides in
the iron ore in a reducing atmosphere to produce blast furnace gas containing carbon monoxide (CO) and CCh. The
CO is then converted and emitted as CO2 when combusted to either pre-heat the blast air used in the blast furnace or
for other purposes at the steel mill. This pig iron or crude iron that is produced from this process contains about 3 to
5 percent carbon by weight. The pig iron production process in a blast furnace produces CO2 emissions and fugitive
CH4 emissions.
Iron can also be produced through the direct reduction process; wherein, iron ore is reduced to metallic iron in the
solid state at process temperatures less than 1000 °C. Direct reduced iron production results in process emissions of
CO2 and CH4 through the consumption of natural gas used during the reduction process.
Sintering is a thermal process by which fine iron-bearing particles, such as from air emission control system dust,
are baked, which causes the material to agglomerate into roughly one-inch pellets that are then recharged into the
blast furnace for pig iron production. Iron ore particles may also be formed into larger pellets or briquettes by
mechanical means, and then agglomerated by heating. The agglomerate is then crushed and screened to produce an
iron-bearing feed that is charged into the blast furnace. The sintering process produces CO2 and fugitive CH4
emissions through the consumption of carbonaceous inputs (e.g., coke breeze, etc.) during the sintering process.
Steel is produced from varying levels of pig iron and scrap steel in specialized EOF and EAF steel-making furnaces.
Carbon inputs to EOF steel-making furnaces include pig iron and scrap steel as well as natural gas, fuel oil, and
fluxes (e.g., limestone, dolomite, etc.). In a EOF, the carbon in iron and scrap steel combines with high-purity
oxygen to reduce the carbon content of the metal to the amount desired for the specified grade of steel. EAFs use
carbon electrodes, charge carbon, and other materials (e.g., natural gas, etc.) to aid in melting metal inputs (primarily
recycled scrap steel), which are refined and alloyed to produce the desired grade of steel. Carbon dioxide emissions
occur in BOFs through the reduction process. In EAFs, CO2 emissions result primarily from the consumption of
carbon electrodes and also from the consumption of supplemental carbon-containing materials used to augment the
melting process.
In addition to the production processes mentioned above, CO2 is also generated at iron and steel mills through the
consumption of process byproducts (e.g., blast furnace gas, coke oven gas, etc.) used for various purposes including
heating, annealing, and electricity generation. Process byproducts sold for use as synthetic natural gas are deducted
and reported in the Energy chapter (emissions associated with natural gas and fuel oil consumption for these
purposes are reported in the Energy chapter).
The majority of CO2 emissions from the iron and steel production process come from the use of metallurgical coke
in the production of pig iron and from the consumption of other process byproducts at the iron and steel mill, with
lesser amounts emitted from the use of flux and from the removal of carbon from pig iron used to produce steel.
Some carbon is also stored in the finished iron and steel products.
According to the 2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006), the production of
metallurgical coke from coking coal is considered to be an energy use of fossil fuel and the use of coke in iron and
steel production is considered to be an industrial process source. Therefore, the Guidelines suggest that emissions
from the production of metallurgical coke should be reported separately in the Energy source, while emissions from
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
coke consumption in iron and steel production should be reported in the industrial process source. However, the
approaches and emission estimates for both metallurgical coke production and iron and steel production are both
presented here because the activity data used to estimate emissions from metallurgical coke production have
significant overlap with activity data used to estimate iron and steel production emissions. In addition, some
byproducts (e.g., coke oven gas, etc.) of the metallurgical coke production process are consumed during iron and
steel production, and some byproducts of the iron and steel production process (e.g., blast furnace gas, etc.) are
consumed during metallurgical coke production. Emissions associated with the consumption of these byproducts
are attributed to the point of consumption. For example, CO2 emissions associated with the combustion of coke
oven gas in the blast furnace during pig iron production are attributed to pig iron production. Emissions associated
with the use of conventional fuels (e.g., natural gas, fuel oil, etc.) for electricity generation, heating and annealing, or
other miscellaneous purposes downstream of the iron and steelmaking furnaces are reported in the Energy chapter.
Metallurgical Coke Production
Emissions of CO2 and CH4 from metallurgical coke production in 2011 were 1.4 Tg CO2 Eq. (1,425 Gg) and less
than 0.00003 Tg CO2 Eq. (less than 0.002 Gg), respectively (see Table 4-55 and Table 4-56), totaling 1.4 Tg CO2
Eq. Emissions decreased in 2011 and have decreased overall since 1990. In 2011, domestic coke production
increased by 3 percent but has decreased overall since 1990. Coke production in 2011 was 26 percent lower than in
2000 and 44 percent below 1990. Overall, emissions from metallurgical coke production have declined by 42
percent (1.0 Tg CO2 Eq.) from 1990 to 2011.
Table 4-55: COz and ChU Emissions from Metallurgical Coke Production (Tg COz Eq.)
Year 1990 2005 1 2007 2008 2009 2010 2011
CO2 2.5 2.0 /t 2.1 2.3 1.0 2.1 1.4
CH4 + *J +/ + + + + +
Total 2.5 2.0 2.1 2.3 1.0 2.1 L±
+ Does not exceed 0.05 Tg CO2 Eq.
Table 4-56: COz and ChU Emissions from Metallurgical Coke Production (Gg)
Year 1990 2005 2007 2008 2009 2010 2011
C02 2,470 ? 2,043 ^ 2,054 2,334 956 2,084 1,425
CH4 + •••** + -^ + + + + +_
+ Does not exceed 0.5 Gg
Iron and Steel Production
Emissions of CO2 and CH4 from iron and steel production in 2011 were 62.8 Tg CO2 Eq. (62,834 Gg) and 0.6 Tg
CO2 Eq. (27.6 Gg), respectively (see Table 4-57 through Table 4-60), totaling approximately 63.4 Tg CO2 Eq.
Emissions increased in 2011 (primarily due to increased steel production associated with improved economic
conditions) but have decreased overall since 1990 due to restructuring of the industry, technological improvements,
and increased scrap steel utilization. Carbon dioxide emission estimates include emissions from the consumption of
carbonaceous materials in the blast furnace, EAF, and EOF, as well as blast furnace gas and coke oven gas
consumption for other activities at the steel mill.
In 2011, domestic production of pig iron increased by 13 percent from 2010 levels. Overall, domestic pig iron
production has declined since the 1990s. Pig iron production in 2011 was 37 percent lower than in 2000 and 39
percent below 1990. Carbon dioxide emissions from steel production have increased by 70 percent (5.6 Tg CO2
Eq.) since 1990, while overall CO2 emissions from iron and steel production have declined by 35 percent (34.5 Tg
CO2Eq.) from 1990 to 2011.
Industrial Processes 4-51
-------
Table 4-57: COz Emissions from Iron and Steel Production (Tg COz Eq.)
Year
Sinter Production
Iron Production
Steel Production
Other Activities3
Total
1990
2.4 J
47.6
8.0
39.3
97.3 ?
2005
1.7
19.4 J
9.4 / ;
34.2'' -;
64.6
2007
1.4
27.0
9.8
31.0
69.2
2008
1.3
25.6
8.4
29.1
64.5
2009
0.8
15.9
7.6
17.8
42.1
2010
1.0
19.1
9.2
24.3
53.7
2011
1.2
19.9
13.5
28.2
62.8
Note: Totals may not sum due to independent rounding.
a Includes emissions from blast furnace gas and coke oven gas combustion for activities at the steel mill other
than consumption in blast furnace, EAFs, or BOFs.
Table 4-58: COz Emissions from Iron and Steel Production (Gg)
Year
Sinter Production
Iron Production
Steel Production
Other Activities a
Total
1990
2,448
47,650 J
7,958
39,256 -
97,311
2005
1,663
1 i9=4i4
. 9,386
. 34,160 /
64,623
2007
; 1,383
27,042
•'• 9,834
30,964
, 69,223
2008
1,299
25,622
8,422
29,146
64,488
2009
763
15,941
7,555
17,815
42,073
2010
1,045
19,109
9,248
24,260
53,662
2011
1,188
19,901
13,515
28,230
62,834
Note: Totals may not sum due to independent rounding.
a Includes emissions from blast furnace gas and coke oven gas combustion for activities at the steel mill other
than consumption in blast furnace, EAFs, or BOFs.
Table 4-59: Cm Emissions from Iron and Steel Production (Tg COz Eq.)
Year
Sinter Production
Iron Production
Total
1990
+
0.9 -*1
1.0
2005
+ t
0.7
0.7
2007
+
0.7
0.7
2008
+
0.6
0.6
2009
+
0.4
0.4
2010
+
0.5
0.5
2011
+
0.6
0.6
+ Does not exceed 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-60: Cm Emissions from Iron and Steel Production (Gg)
Year 1990 2005 2007 2008 2009 2010 2011
Sinter Production 0.9 0.6 0.5 0.4 0.3 0.4 0.4
Iron Production 44.7 -J 33.5 *J 32.7 30.4 17.1 24.2 27.2
Total 45.6 34.1 33.2 30.8 17.4 24.5 27.6
Note: Totals may not sum due to independent rounding.
Emission estimates presented in this chapter are largely based on Tier 2 methodologies provided by the 2006IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006). These Tier 2 methodologies call for a mass
balance accounting of the carbonaceous inputs and outputs during the iron and steel production process and the
metallurgical coke production process. Tier 1 methods are used for certain iron and steel production processes (e.g.
DRI production) for which available data are insufficient for utilizing a Tier 2 method.
Metallurgical Coke Production
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 zinc and lead (see Zinc
Production and Lead Production sections of this chapter). Emissions associated with producing metallurgical coke
from coking coal are estimated and reported separately from emissions that result from the iron and steel production
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
process. To estimate emission from metallurgical coke production, a Tier 2 method provided by the 2006IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006) was utilized. The amount of C contained in
materials produced during the metallurgical coke production process (i.e., coke, coke breeze, coke oven gas, and
coal tar) is deducted from the amount of C contained in materials consumed during the metallurgical coke
production process (i.e., natural gas, blast furnace gas, and coking coal). Light oil, which is produced during the
metallurgical coke production process, is excluded from the deductions due to data limitations. The amount of C
contained in these materials is calculated by multiplying the material-specific C content by the amount of material
consumed or produced (see Table 4-61). The amount of coal tar produced was approximated using a production
factor of 0.03 tons of coal tar per ton of coking coal consumed. The amount of coke breeze produced was
approximated using a production factor of 0.075 tons of coke breeze per ton of coking coal consumed. Data on the
consumption of carbonaceous materials (other than coking coal) as well as coke oven gas production were available
for integrated steel mills only (i.e., steel mills with co-located coke plants). Therefore, carbonaceous material (other
than coking coal) consumption and coke oven gas production were excluded from emission estimates for merchant
coke plants. Carbon contained in coke oven gas used for coke-oven underfiring was not included in the deductions
to avoid double-counting.
Table 4-61: Material Carbon Contents for Metallurgical Coke Production
Material kg C/kg
Coal Tar 0.62
Coke 0.83
Coke Breeze 0.83
Coking Coal 0.73
Material kg C/GJ
Coke Oven Gas 12.1
Blast Furnace Gas 70.8
Source: IPCC 2006, Table 4.3. Coke Oven Gas and
Blast Furnace Gas, Table 1.3.
The production processes for metallurgical coke production results in fugitive emissions of CH4, which are emitted
via leaks in the production equipment, rather than through the emission stacks or vents of the production plants. The
fugitive emissions were calculated by applying Tier 1 emission factors (0.1 g CH4 per metric ton) taken from the
2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006) for metallurgical coke production.
Data relating to the mass of coking coal consumed at metallurgical coke plants and the mass of metallurgical coke
produced at coke plants were taken from the Energy Information Administration (EIA), Quarterly Coal Report
October through December (EIA 1998 through 2012d) (see Table 4-62). Data on the volume of natural gas
consumption, blast furnace gas consumption, and coke oven gas production for metallurgical coke production at
integrated steel mills were obtained from the American Iron and Steel Institute (AISI), Annual Statistical Report
(AISI2004 through 2012a) and through personal communications with AISI (2008b) (see Table 4-63). The factor
for the quantity of coal tar produced per ton of coking coal consumed was provided by AISI (2008b). The factor for
the quantity of coke breeze produced per ton of coking coal consumed was obtained through Table 2-1 of the report
Energy and Environmental Profile of the U.S. Iron and Steel Industry (DOE 2000). Data on natural gas
consumption and coke oven gas production at merchant coke plants were not available and were excluded from the
emission estimate. Carbon contents for coking coal, metallurgical coke, coal tar, coke oven gas, and blast furnace
gas were provided by the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). The
carbon content for coke breeze was assumed to equal the carbon content of coke.
Table 4-62: Production and Consumption Data for the Calculation of COz and Cm Emissions
from Metallurgical Coke Production (Thousand Metric Tons)
Source/Activity Data
Metallurgical Coke Production
Coking Coal Consumption at Coke Plants
Coke Production at Coke Plants
Coal Breeze Production
Coal Tar Production
1990
35,269
25,054
2,645 /
1,058
2005
21,259
•'• 15,167
1,594 -
638
2007 2008 2009 2010 2011
J 20,607 20,022 13,904 19,135 19,445
, 14,698 14,194 10,109 13,628 13,989
-„ 1,546 1,502 1,043 1,435 1,458
618 601 417 574 583
Industrial Processes 4-53
-------
Table 4-63: Production and Consumption Data for the Calculation of COz Emissions from
Metallurgical Coke Production (million ft3)
Source/Activity Data 1990 1 2005 2007 2008 2009 2010 2011
Metallurgical Coke Production
Coke Oven Gas Production3
Natural Gas Consumption
Blast Furnace Gas Consumption
250
24
,767 /
599
,602
.*
114,213
2,996
4,460 -
m 1Q9
3
5
,912
,309
,144
103,191
3,134
4,829
66,155
2,121
2,435
95,405
3,108
3,181
109,044
3,175
3,853
1 Includes coke oven gas used for purposes other than coke oven underfiring only.
Iron and Steel Production
Emissions of CCh from sinter production and direct reduced iron production were estimated by multiplying total
national sinter production and the total national direct reduced iron production by Tier 1 €62 emission factors (see
Table 4-64). Because estimates of sinter production and direct reduced iron production were not available,
production was assumed to equal consumption.
Table 4-64: COz Emission Factors for Sinter Production and Direct Reduced Iron Production
Material Produced Metric Ton
COi/Metric Ton
Sinter 0.2
Direct Reduced Iron 0.7
Source: IPCC 2006, Table 4.1.
To estimate emissions from pig iron production in the blast furnace, the amount of carbon contained in the produced
pig iron and blast furnace gas were deducted from the amount of carbon contained in inputs (i.e., metallurgical coke,
sinter, natural ore, pellets, natural gas, fuel oil, coke oven gas, and direct coal injection). The carbon contained in
the pig iron, blast furnace gas, and blast furnace inputs was estimated by multiplying the material-specific carbon
content by each material type (see Table 4-65). Carbon in blast furnace gas used to pre-heat the blast furnace air is
combusted to form COa during this process.
Emissions from steel production in EAFs were estimated by deducting the carbon contained in the steel produced
from the carbon contained in the EAF anode, charge carbon, and scrap steel added to the EAF. Small amounts of
carbon from direct reduced iron, pig iron, and flux additions to the EAFs were also included in the EAF calculation.
For BOFs, estimates of carbon contained in EOF steel were deducted from carbon contained in inputs such as
natural gas, coke oven gas, fluxes, and pig iron. In each case, the carbon was calculated by multiplying material-
specific carbon contents by each material type (see Table 4-65). For EAFs, the amount of EAF anode consumed
was approximated by multiplying total EAF steel production by the amount of EAF anode consumed per metric ton
of steel produced (0.002 metric tons EAF anode per metric ton steel produced (AISI 2008b)). The amount of flux
(e.g., limestone and dolomite) used during steel manufacture was deducted from the Limestone and Dolomite Use
source category to avoid double-counting.
CO2 emissions from the consumption of blast furnace gas and coke oven gas for other activities occurring at the
steel mill were estimated by multiplying the amount of these materials consumed for these purposes by the material-
specific carbon content (see Table 4-65).
CO2 emissions associated with the sinter production, direct reduced iron production, pig iron production, steel
production, and other steel mill activities were summed to calculate the total €62 emissions from iron and steel
production (see Table 4-57 and Table 4-58).
Table 4-65: Material Carbon Contents for Iron and Steel Production
Material kg C/kg
Coke 0.83
Direct Reduced Iron 0.02
Dolomite 0.13
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
EAF Carbon Electrodes 0.82
EAF Charge Carbon 0.83
Limestone 0.12
Pig Iron 0.04
Steel 0.01
Material kg C/GJ
Coke Oven Gas 12.1
Blast Furnace Gas 70.8
Source: IPCC 2006, Table 4.3. Coke Oven Gas and
Blast Furnace Gas, Table 1.3.
The production processes for 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 Tier 1 emission factors taken from the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) for sinter production and the 1995 IPCC Guidelines
(IPCC/UNEP/OECD/IEA 1995) (see Table 4-66) for pig iron production. The production of direct reduced iron also
results in emissions of CH4 through the consumption of fossil fuels (e.g., natural gas); however, these emissions
estimates are excluded due to data limitations.
Table 4-66: Cm Emission Factors for Sinter and Pig Iron Production
Material Produced Factor Unit
Pig Iron 0.9 g CH4/kg
Sinter 0.07 kg CHVmetric ton
Source: Sinter (IPCC 2006, Table 4.2), Pig Iron (IPCC/UNEP/OECD/IEA
1995, Table 2.2)
Sinter consumption data were obtained from AISFs Annual Statistical Report (AISI2004 through 2012a) and
through personal communications with AISI (2008b) (see Table 4-67). In general, direct reduced iron (DRI)
consumption data were obtained from the USGS Minerals Yearbook - Iron and Steel Scrap (USGS 1991 through
2011). However, data for DRI consumed in EAFs were not available for the years 1990 and 1991. EAF DRI
consumption in 1990 and 1991 was calculated by multiplying the total DRI consumption for all furnaces by the EAF
share of total DRI consumption in 1992. Also, data for DRI consumed in BOFs were not available for the years
1990 through 1993. EOF DRI consumption in 1990 through 1993 was calculated by multiplying the total DRI
consumption for all furnaces (excluding EAFs and cupola) by the EOF share of total DRI consumption (excluding
EAFs and cupola) in 1994.
The Tier 1 CO2 emission factors for sinter production and direct reduced iron production were obtained through the
2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). Data for pig iron production, coke,
natural gas, fuel oil, sinter, and pellets consumed in the blast furnace; pig iron production; and blast furnace gas
produced at the iron and steel mill and used in the metallurgical coke ovens and other steel mill activities were
obtained from AISFs Annual Statistical Report (AISI 2004 through 2012a) and through personal communications
with AISI (2008b) (see Table 4-68).
Data for EAF steel production, flux, EAF charge carbon, and natural gas consumption were obtained from AISFs
Annual Statistical Report (AISI 2004 through 2012a) and through personal communications with AISI (2012b and
2008b). The factor for the quantity of EAF anode consumed per ton of EAF steel produced was provided by AISI
(AISI 2008b). Data for EOF steel production, flux, natural gas, natural ore, pellet sinter consumption as well as
EOF steel production were obtained from AISFs Annual Statistical Report (AISI 2004 through 2012a) and through
personal communications with AISI (2008b). Data for EAF and EOF scrap steel, pig iron, and DRI consumption
were obtained from the USGS Minerals Yearbook - Iron and Steel Scrap (USGS 1991 through 201 l).Data on coke
oven gas and blast furnace gas consumed at the iron and steel mill (other than in the EAF, EOF, or blast furnace)
were obtained from AISFs Annual Statistical Report (AISI 2004 through 2012a) and through personal
communications with AISI (2008b).
Data on blast furnace gas and coke oven gas sold for use as synthetic natural gas were obtained from EIA's Natural
Gas Annual 2011 (EIA 2012b). Carbon contents for direct reduced iron, EAF carbon electrodes, EAF charge
carbon, limestone, dolomite, pig iron, and steel were provided by the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006). The carbon contents for natural gas, fuel oil, and direct injection coal
Industrial Processes 4-55
-------
were obtained from EIA 2012c and EPA 2010. Heat contents for the same fuels were obtained from EIA (1992,
2012a). Heat contents for coke oven gas and blast furnace gas were provided in Table 2-2 of the report Energy and
Environmental Profile of the U.S. Iron and Steel Industry (DOE 2000).
Table 4-67: Production and Consumption Data for the Calculation of COz and Cm Emissions
from Iron and Steel Production (Thousand Metric Tons)
Source/Activity Data
Sinter Production
Sinter Production
Direct Reduced Iron
Production
Direct Reduced Iron
Production
Pig Iron Production
Coke Consumption
Pig Iron Production
Direct Injection Coal
Consumption
EAF Steel Production
EAF Anode and Charge
Carbon Consumption
Scrap Steel Consumption
Flux Consumption
EAF Steel Production
EOF Steel Production
Pig Iron Consumption
Scrap Steel Consumption
Flux Consumption
EOF Steel Production
1990
12,239
498
24,946
49,669
1,485
67
42,691
319
33,511
47,307
14,713
576
43,973
2005
8,315
962
13,832-:
37,222'
2,573 -
1,127
46,600 ,
695
52,194 ,
34,400
11,400
582
42,705
2007
,J 6,914
,«
* 1,310
, 15,039
j| 36,337
2,734
_
1,214
_ 48,400
567
57,004
~ 33,400
9,140
408
41,099
2008
6,497
1,210
14,251
33,730
2,578
1,109
50,500
680
52,791
30,600
8,890
431
39,105
2009
3,814
824
8,572
19,019
1,674
845
43,200
476
36,725
25,900
7,110
318
22,659
2010
5,225
1,100
10,883
26,844
2,279
1,189
47,500
640
49,339
31,200
9,860
431
31,158
2011
5,941
1,270
11,962
30,228
2,604
1,257
164,000
726
52,108
31,300
8,800
454
34,291
Table 4-68: Production and Consumption Data for the Calculation of COz Emissions from
Iron and Steel Production (million ft3 unless otherwise specified)
Source/Activity Data
Pig Iron Production
Natural Gas Consumption
Fuel Oil Consumption
(thousand gallons)
Coke Oven Gas Consumption
Blast Furnace Gas Production
EAF Steel Production
Natural Gas Consumption
EOF Steel Production
Coke Oven Gas Consumption
Other Activities
Coke Oven Gas Consumption
Blast Furnace Gas
Consumption
1990
56,273
163,397
22,033
1,439,380
15,905
3,851
224,883
1,414,778
2005
59,844 ,.
16,170
16,557
1,299,980 /
19,985
524 /
97,132
1,295,520,
2007
56,112
84,498
16,239
1,173,588
28,077
525
93,148
1,168,444
2008
53,349
55,552
15,336
1,104,674
10,826
528
87,327
1,099,845
2009
35,933
23,179
9,951
672,486
7,848
373
55,831
670,051
2010 2011
47,814 59,132
27,505 21,378
14,233 17,772
911,180 1,063,326
10,403 6,263
546 554
80,626 90,718
907,999 1,059,473
The estimates of CCh and CH4 emissions from metallurgical coke production are based on material production and
consumption data and average carbon contents. Uncertainty is associated with the total U.S. coking coal
consumption, total U.S. coke production and materials consumed during this process. Data for coking coal
consumption and metallurgical coke production are from different data sources (EIA) than data for other
carbonaceous materials consumed at coke plants (AISI), which does not include data for merchant coke plants.
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
There is uncertainty associated with the fact that coal tar and coke breeze production were estimated based on coke
production because coal tar and coke breeze production data were not available. Since merchant coke plant data is
not included in the estimate of other carbonaceous materials consumed at coke plants, the mass balance equation for
CO2 from metallurgical coke production cannot be reasonably completed. Therefore, for the purpose of this
analysis, uncertainty parameters are applied to primary data inputs to the calculation (i.e, coking coal consumption
and metallurgical coke production) only.
The estimates of COa emissions from iron and steel production are based on material production and consumption
data and average carbon contents. There is uncertainty associated with the assumption that direct reduced iron and
sinter consumption are equal to production. There is uncertainty associated with the assumption that all coal used
for purposes other than coking coal is for direct injection coal; some of this coal may be used for electricity
generation. There is also uncertainty associated with the carbon contents for pellets, sinter, and natural ore, which
are assumed to equal the carbon contents of direct reduced iron. For EAF steel production, there is uncertainty
associated with the amount of EAF anode and charge carbon consumed due to inconsistent data throughout the time
series. Also for EAF steel production, there is uncertainty associated with the assumption that 100 percent of the
natural gas attributed to "steelmaking furnaces" by AISI is process-related and nothing is combusted for energy
purposes. Uncertainty is also associated with the use of process gases such as blast furnace gas and coke oven gas.
Data are not available to differentiate between the use of these gases for processes at the steel mill versus for energy
generation (i.e., electricity and steam generation); therefore, all consumption is attributed to iron and steel
production. These data and carbon contents produce a relatively accurate estimate of CCh emissions. However,
there are uncertainties associated with each.
For the purposes of the CH4 calculation from iron and steel production it is assumed that all of the CH4 escapes as
fugitive emissions and that none of the CH4 is captured in stacks or vents. Additionally, the CC>2 emissions
calculation is not corrected by subtracting the carbon content of the CH4, which means there may be a slight double
counting of carbon as both €62 and CH4.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-69 for metallurgical coke
production and iron and steel production. Total €62 emissions from metallurgical coke production and iron and
steel production were estimated to be between 53.9 and 75.1 Tg €62 Eq. at the 95 percent confidence level. This
indicates a range of approximately 16 percent below and 17 percent above the emission estimate of 64.2 Tg €62 Eq.
Total CH4 emissions from metallurgical coke production and iron and steel production were estimated to be between
0.5 and 0.7 Tg €62 Eq. at the 95 percent confidence level. This indicates a range of approximately 21 percent
below and 22 percent above the emission estimate of 0.6 Tg €62 Eq.
Table 4-69: Tier 2 Quantitative Uncertainty Estimates for COz and ChU Emissions from Iron
and Steel Production and Metallurgical Coke Production (Tg. COz Eq. and Percent)
Uncertainty Range Relative to Emission
Source Gas 2011 Emission Estimate Estimate3
(Tg CCh Eq.) (Tg CCh Eq.) (%)
Metallurgical Coke & Iron
and Steel Production
Metallurgical Coke & Iron
and Steel Production
C02
CH4
64.2
0.6
Lower
Bound
53.9
0.5
Upper
Bound
75.1
0.7
Lower
Bound
-16%
-21%
Upper
Bound
+17%
+22%
Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
In previous Inventories, the furnace-specific (i.e., EAF and EOF) consumption statistics for scrap steel, pig iron, and
DRI were obtained from AISI's Annual Statistical Report (AISI 2004 through 2012a) and through personal
communication. However, the consumption statistics from AISI's Annual Statistical Report were typically not
disaggregated by furnace type. As a result, total consumption statistics were split based upon furnace-type fractions
derived from the limited years when furnace-specific consumption statistics were available.
Industrial Processes 4-57
-------
More complete furnace-specific consumption statistics were recently identified from the USGS Minerals Yearbook -
Iron and Steel Scrap (USGS 1991 through 2011). Scrap steel and pig iron consumption statistics were complete for
the entire time series from 1990 to 2011, while DRI consumption statistics were complete except for the first few
years of the time series (i.e., 1990 and 1991 forEAFs and 1990 through 1993 forBOFs).
Revised emissions were calculated for the entire time series using these new data sets for the furnace-specific (i.e.,
EAF and EOF) consumption statistics for scrap steel, pig iron, and DRI. In general, the changes in emissions were
minimal. The emissions from iron production decreased slightly, while the emissions from steel production
increased slightly. The net emissions also increased slightly.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Iron and Steel Production source category. Particular attention would be
made to ensure time series consistency of the emissions estimates presented in future inventory reports, consistent
with IPCC and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with
the program's initial requirements for reporting of emissions in calendar year 2010, are not available for all
inventory years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and
integration of data from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in
national inventories will be relied upon.148
Additional improvements include accounting for emission estimates for the production of metallurgical coke to the
Energy chapter as well as identifying the amount of carbonaceous materials, other than coking coal, consumed at
merchant coke plants. Other potential improvements include identifying the amount of coal used for direct injection
and the amount of coke breeze, coal tar, and light oil produced during coke production. Efforts will also be made to
identify inputs for preparing Tier 2 estimates for sinter and direct reduced iron production, as well as identifying
information to better characterize emissions from the use of process gases and fuels within the Energy and Industrial
Processes chapters.
Carbon dioxide 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 (96 to 99 percent silicon), and miscellaneous alloys (32 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. In addition, government
information disclosure rules prevent the publication of production data for these production facilities. Emissions
from fuels consumed for energy purposes during the production of ferroalloys are accounted for in the Energy
chapter.
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
148 See
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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While most of the C contained in the process materials is released to the atmosphere as €62, 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.
Ferroalloy production data for the year 2011 were not available at the time of publication. For the purposes of this
inventory, 2010 annual ferroalloy production data were used as proxy for year 2011. Emissions of CCh from
ferroalloy production in 2011 were 1.7 Tg CO2 Eq. (1,663 Gg) (see Table 4-70 and Table 4-71), which is a 23
percent reduction since 1990. Emissions of CH4 from ferroalloy production in 2011 were 0.01 Tg COa Eq. (0.466
Gg), which is a 31 percent decrease since 1990.
Table 4-70: COz and ChU Emissions from Ferroalloy Production (Tg COz Eq.)
Year
CO2
CH4
Total
1990
2.2
+ "
2.2
2005
1.4
1.4
2007
1.6
| +
1.6
2008
1.6
+
1.6
2009
1.5
+
1.5
2010
1.7
+
1.7
2011
1.7
+
1.7
+ Does not exceed 0.05 Tg CCh Eq.
Note: Totals may not sum due to independent rounding.
Table 4-71: COz and ChU Emissions from Ferroalloy Production (Gg)
Year 1990 2005 2007 2008 2009 2010 2011
C02 2,152 1,392 1,552 1,599 1,469 1,663 1,663
CH4 1 '"•• + -*1 + + + + +_
+ Does not exceed 0.5 Gg.
Emissions of CCh and CH4 from ferroalloy production were calculated using a Tier 1 method from the 2006IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006), specifically by multiplying annual ferroalloy
production by material-specific default emission factors provided by IPCC (2006). 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 CCh (i.e., 2.5 metric tons CCh/metric ton of alloy produced) and an emission factor for 65 percent silicon
was applied for CH4 (i.e., 1 kg CH4/metric ton of alloy produced). Additionally, for ferrosilicon alloys containing 56
to 95 percent silicon, an emission factor for 75 percent silicon ferrosilicon was applied for both CO2 and CH4 (i.e., 4
metric tons CCh/metric ton alloy produced and 1 kg CH4/metric ton of alloy produced, respectively). The emission
factors for silicon metal equaled 5 metric tons CCVmetric 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 in an
electric arc furnace process (IPCC 2006), although some ferroalloys may have been produced with coking coal,
wood, other biomass, or graphite carbon 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 (Onder and
Bagdoyan 1993).
Ferroalloy production data for 1990 through 2011 (see Table 4-72) were obtained from the USGS through personal
communications with the USGS Silicon Commodity Specialist (Corathers 2011, Corathers 2012) and through the
Minerals Yearbook: Silicon Annual Report (USGS 1995 through 2011). Because USGS does not provide estimates
of silicon metal production for 2006 through 2011, 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; however, beginning in 1999, the USGS reported these as a single category. The
composition data for petroleum coke was obtained from Onder and Bagdoyan (1993).
Table 4-72: Production of Ferroalloys (Metric Tons)
Year Ferrosilicon Ferrosilicon Silicon Metal Misc. Alloys
25%-55% 56%-95% 32-65%
1990 321,385 109,566 145,744 72,442
Industrial Processes 4-59
-------
2005 123,000 86,100 148,000 NA
2007
2008
2009
2010
2011
180,000
193,000
123,932
153,000
153,000
90,600
94,000
104,855
135,000
135,000
148,000
148,000
148,000
148,000
148,000
NA
NA
NA
NA
NA
NA (Not Available)
and
Annual ferroalloy production is currently 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 (through 2005 only). Silicon metal production values for 2006 through 2011 are assumed to be equal to 2005
value reported by USGS (USGS did not report silicon metal production for 2006 through 2011). It was assumed
that the IPCC emission factors apply to all of the ferroalloy production processes, including miscellaneous alloys.
Finally, production data for silvery pig iron (alloys containing less than 25 percent silicon) are not reported by the
USGS to avoid disclosing proprietary company data. Emissions from this production category, therefore, were not
estimated.
Also, some ferroalloys may be produced using wood or other biomass as a primary or secondary carbon source
(carbonaceous reductants), 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
carbon is of biogenic origin.149 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 CCh 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, and are also often considered confidential business information.
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.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-73. Ferroalloy production CCh
emissions were estimated to be between 1.5 and 1.9 Tg CCh Eq. at the 95 percent confidence level. This indicates a
range of approximately 12 percent below and 12 percent above the emission estimate of 1.7 Tg CCh Eq. Ferroalloy
production CH4 emissions were estimated to be between a range of approximately 12 percent below and 23 percent
above the emission estimate of 0.01 Tg CC>2 Eq.
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Ferroalloy
Production (Tg COz Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (Tg CCh Eq.) (%)
Ferroalloy Production
Ferroalloy Production
C02 1.7
CH4 +
Lower Upper Lower
Bound Bound Bound
1.5 1.9 -12%
+ + -12%
Upper
Bound
+12%
+23%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
149 Emissions and sinks of biogenic carbon are accounted for in the Land Use, Land-Use Change, and Forestry chapter.
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Details on the emission trends through time are described in more detail in the Methodology section, above.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Ferroalloy Production source category. Particular attention would be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of data
from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will
be relied upon.150
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 4 percent of the world total (USGS 2012a). 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 CC>2 and two perfluorocarbons
(PFCs): perfluoromethane (CF4) and perfluoroethane (CJe).
CO2 is emitted during the aluminum smelting process when alumina (aluminum oxide, A^Os) 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 (NasAlFe). The reduction cells contain a carbon lining that serves as the
cathode. Carbon is also contained in the anode, which can be a carbon mass of paste, coke briquettes, or prebaked
carbon blocks from petroleum coke. During reduction, most of this carbon is oxidized and released to the
atmosphere as CCh.
Process emissions of CCh from aluminum production were estimated to be 3.3 Tg CCh Eq. (3,292 Gg) in 201 1 (see
Table 4-74). The carbon anodes consumed during aluminum production consist of petroleum coke and, to a minor
extent, coal tar pitch. The petroleum coke portion of the total COa 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 CC>2 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.
Table 4-74: COz Emissions from Aluminum Production (Tg CO 2 Eq. and Gg)
Year Tg CCh Eq. Gg
1990 6.8 6,831
2005 4.1 4,142
2007
2008
2009
2010
2011
4.3
4.5
3.0
2.7
3.3
4,251
4,477
3,009
2,722
3,292
150 See
Industrial Processes 4-61
-------
In addition to CCh 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 C2p6. In general, the magnitude of emissions for a given smelter and level of production
depends on the frequency and duration of these anode effects. As the frequency and duration of the anode effects
increase, emissions increase.
Since 1990, emissions of CF4 and C2p6 have declined by 85 percent and 77 percent, respectively, to 2.3 Tg COa Eq.
of CF4 (0.36 Gg) and 0.6 Tg CO2 Eq. of C2F6 (0.066 Gg) in 2011, as shown in Table 4-75 and Table 4-76. 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
51 percent, while the combined CF4 and C2p6 emission rate (per metric ton of aluminum produced) has been reduced
by 67 percent. Emissions rose by approximately 87 percent between 2010 and 2011 due to an increase in U.S.
aluminum production and to process changes at one smelter.
Table 4-75: PFC Emissions from Aluminum Production (Tg COz Eq.)
Year CF4 C2F6 Total
1990 15.8 2.7 18.4
2005 2.5 0.4 3.0
2007
2008
2009
2010
2011
3.2
2.2
1.3
1.2
2.3
0.6
0.5
0.3
0.4
0.6
3.8
2.7
1.6
1.6
2.9
Note: Totals may not sum due to independent rounding.
Table 4-76: PFC Emissions from Aluminum Production (Gg)
Year CF4 C2F6
1990 2.4 0.3
2005 0.4 +
2007 0.5 0.1
2008 0.3 0.1
2009 0.2 +
2010 0.2 +
2011 0.4 0.1
+ Does not exceed 0.05 Gg.
In 2011, U.S. primary aluminum production totaled approximately 2.0 million metric tons a 15 percent increase
from 2010 production levels (USAA 2012). In 2011, five companies managed production at ten operational primary
aluminum smelters. Five smelters were closed the entire year in 2011. Five potlines that were closed in late 2008
and 2009 at four other smelters were also restarted in early 2011 (USGS 2012b). During 2011, monthly U.S.
primary aluminum production was greater in each quarter of 2010 when compared to the corresponding quarter in
2010 (USAA 2012).
For 2012, total production was approximately 2.1 million metric tons compared to 2.0 million metric tons in 2011, a
4 percent increase (USAA 2013). Based on the increase in production, process COa and PFC emissions are likely to
be greater in 2012 compared to 2011 given no significant changes in process controls at operational facilities.
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Process CC>2 and perfluorocarbon (PFC)—i.e., perfluoromethane (CF4) and perfluoroethane (C2p6)—emission
estimates from primary aluminum production for 2010 and 2011 are reported in the EPA's GHGRP database.
Facilities began reporting primary aluminum production process emissions (for 2010) in 2011, for the first time,
GHGRP data (for 2010 and 2011) is available to be incorporated into the inventory. EPA's GHGRP mandates that
all facilities that contain an aluminum production process must report: CF4 and C2p6 emissions from anode effects in
all prebake and Sederberg electrolysis cells, carbon dioxide (CCh) emissions from anode consumption during
electrolysis in all prebake and Sederberg cells, and all COa emissions from onsite anode baking. Data elements (e.g.,
primary aluminum production, anode effect frequency and duration, and slope coefficients) that constitute
confidential business information (CBI) are not reported under EPA's GHGRP at the present time. In prior years,
most facilities reported both the process emissions and the CBI data elements to the Voluntary Aluminum Industry
Partnership (VAIP) program. To estimate the process emissions, EPA's GHGRP uses the process-specific equations
(and certain technology-specific defaults) detailed in subpart F. These equations are based on the Tier 2/Tier 3 IPCC
(2006) methods for primary aluminum production, and Tier 1 methods when estimating missing data elements. It
should be noted that the same methods (i.e., IPCC 2006) are used for estimating the emissions prior to the
availability of the reported GHGRP data in the inventory.
Process COz Emissions from Anode Consumption and Anode Baking
Prior to the introduction of EPA's GHGRP in 2010, CO2 emissions were still estimated with IPCC (2006) methods,
but had to combine individual facility reported data with process-specific emissions modeling. These estimates
were based on information previously gathered from EPA's VAIP program, U.S. Geological Survey (USGS)
Mineral Commodity reviews, and The Aluminum Association (USAA) statistics, among other sources. Since pre-
and post-GHGRP estimates use the same methodology, emission estimates are comparable across the time series.
Most of the CO2 emissions released during aluminum production occur during the electrolysis reaction of the carbon
anode, as described by the following reaction:
2A12O3 + 3C -> 4A1 + 3CC-2
For prebake smelter technologies, CCh is also emitted during the anode baking process. These emissions can
account for approximately 10 percent of total process CO2 emissions from prebake smelters.
Depending on the availability of smelter-specific data, the CCh emitted from electrolysis at each smelter was
estimated from: (1) the smelter's annual anode consumption, (2) the smelter's annual aluminum production and rate
of anode consumption (per ton of aluminum produced) for previous and/or following years, or, (3) the smelter's
annual aluminum production and IPCC default CC>2 emission factors. The first approach tracks the consumption and
carbon content of the anode, assuming that all carbon in the anode is converted to CCh. Sulfur, ash, and other
impurities in the anode are subtracted from the anode consumption to arrive at a C consumption figure. This
approach corresponds to either the IPCC Tier 2 or Tier 3 method, depending on whether smelter-specific data on
anode impurities are used. The second approach interpolates smelter-specific anode consumption rates to estimate
emissions during years for which anode consumption data are not available. This approach avoids substantial errors
and discontinuities that could be introduced by reverting to Tier 1 methods for those years. The last approach
corresponds to the IPCC Tier 1 method (2006), and is used in the absence of present or historic anode consumption
data.
The equations used to estimate CCh emissions in the Tier 2 and 3 methods vary depending on smelter type (IPCC
2006). For Prebake cells, the process formula accounts for various parameters, including net anode consumption,
and the sulfur, ash, and impurity content of the baked anode. For anode baking emissions, the formula accounts for
packing coke consumption, the sulfur and ash content of the packing coke, as well as the pitch content and weight of
baked anodes produced. For Sederberg cells, the process formula accounts for the weight of paste consumed per
metric ton of aluminum produced, and pitch properties, including sulfur, hydrogen, and ash content.
Through the VAIP, anode consumption (and some anode impurity) data have been reported for 1990, 2000, 2003,
2004, 2005, 2006, 2007, 2008, and 2009. 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 CCh process data were provided by 18 of the 23
Industrial Processes 4-63
-------
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, 13 out of 14 operating smelters in 2006, 5 out of 14 operating smelters in, 2007 and 2008, and 3
out of 13 operating smelters in 2009. For years where CCh emissions data or CCh process data were not reported by
these companies, estimates were developed through linear interpolation, and/or assuming representative (e.g.,
previously reported or industry default) values.
In the absence of any previous historical smelter specific process data (i.e., 1 out of 13 smelters in 2009, 1 out of 14
smelters in 2006, 2007, and 2008, 1 out of 15 smelters in 2005, and 5 out of 23 smelters between 1990 and 2003),
CO2 emission estimates were estimated using Tier 1 Sederberg and/or Prebake emission factors (metric ton of CCh
per metric ton of aluminum produced) from IPCC (2006).
Process RFC Emissions from Anode Effects
Smelter-specific PFC emissions from aluminum production for 2010 and 2011 were reported to EPA under the
GHGRP. To estimate their PFC emissions and report them under EPA's GHGRP, smelters use an approach
identical to the Tier 3 approach in the 2006 IPCC Guidelines. Specifically, they use a smelter-specific slope
coefficient as well as smelter-specific operating data to estimate an emission factor using the following equation:
PFC (CF4 or C2F6) kg/metric ton Al = S x (Anode Effect Minutes/Cell-Day)
where,
S = Slope coefficient ((kg PFC/metric ton Al)/( Anode Effect Minutes/Cell-Day))
(Anode Effect Minutes/Cell-Day) = (Anode Effect Frequency/Cell-Day) x Anode Effect Duration (minutes)
They then multiply this emission factor by aluminum production to estimate PFC emissions. All U.S. aluminum
smelters are required to report their emissions under EPA's GHGRP.
Prior to 2010, PFC emissions were estimated using the same equation, but the slope-factor used for some smelters
was technology-specific rather than smelter-specific, making the method a Tier 2 rather than a Tier 3 approach for
those smelters. Emissions and background data were reported to EPA under the VAIP. For 1990 through 2009,
smelter-specific slope coefficients were available and were used for smelters representing between 30 and 94
percent of U.S. primary aluminum production. The percentage changed from year to year as some smelters closed
or changed hands and as the production at remaining smelters fluctuated. For smelters that did not report smelter-
specific slope coefficients, IPCC technology-specific slope coefficients were applied (IPCC 2000, 2006). The slope
coefficients were combined with smelter-specific anode effect data collected by aluminum companies and reported
under the VAIP, to estimate emission factors over time. For 1990 through 2009, 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, representative values (e.g., previously reported or 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 2009, smelter-specific production data were available for smelters representing between 30
and 100 percent of U.S. primary aluminum production. (For the years after 2000, this percentage was near the high
end of the range.) Production at non-reporting smelters was estimated by calculating the difference between the
production reported under VAIP and the total U.S. production supplied by USGS or USAA, and then allocating this
difference to non-reporting smelters in proportion to their production capacity. Emissions were then aggregated
across smelters to estimate national emissions.
Between 1990 and 2009, production data were provided under the VAIP 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 (from USGS and USAA), with allocation to
specific smelters based on reported production capacities (from USGS).
National primary aluminum production data for 2011 were obtained via The Aluminum Association (USAA 2012).
For 1990 through 2001, and 2006 (see Table 4-77) data were obtained from USGS, Mineral Industry Surveys:
Aluminum Annual Report (USGS 1995, 1998, 2000, 2001, 2002, 2007). For 2002 through 2005, and 2007 through
2010 national aluminum production data were obtained from the USAA's Primary Aluminum Statistics (USAA
2004, 2005, 2006, 2008, 2009, 2010, 2011).
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-77: Production of Primary Aluminum (Gg)
Year Gg
1990 4,048
2005 2,478
2007 2,560
2008 2,659
2009 1,727
2010 1,727
2011 1,986
and
Uncertainty was assigned to the CCh, CF4, and C2F6 emission values reported by each individual facility to the
GHGRP. As previously mentioned, the methods for estimating emissions for the GHGRP and this report are the
same, and follow the IPCC (2006) methodology. As a result, it was possible to assign uncertainty bounds (and
distributions) based on an analysis of the uncertainty associated with the facility-specific emissions estimated for
previous inventory years. Uncertainty surrounding the reported CCh, CF4, and C2p6 emission values were
determined to have a normal distribution with uncertainty ranges of ±6, ±16, and ±20 percent, respectively. A
Monte Carlo analysis was applied to estimate the overall uncertainty of the CCh, CF4, and C2F6 emission estimates
for the U.S. aluminum industry as a whole, and the results are provided below.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-78. Aluminum production-
related CO2 emissions were estimated to be between 3.2 and 3.4 Tg CCh Eq. at the 95 percent confidence level.
This indicates a range of approximately 2 percent below to 2 percent above the emission estimate of 3.3 Tg CCh Eq.
Also, production-related CF4 emissions were estimated to be between 2.2 and 2.5 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of approximately 7 percent below to 7 percent above the emission estimate
of 2.3 Tg CO2 Eq. Finally, aluminum production-related C2p6 emissions were estimated to be between 0.5 and 0.7
Tg CO2 Eq. at the 95 percent confidence level. This indicates a range of approximately 11 percent below to 11
percent above the emission estimate of 0.6 Tg CCh Eq.
Table 4-78: Tier 2 Quantitative Uncertainty Estimates for COz and PFC Emissions from
Aluminum Production (Tg COz Eq. and Percent)
Source Gas
Aluminum Production CCh
Aluminum Production CF4
Aluminum Production C2Fe
2011 Emission
Estimate
(Tg C02 Eq.)
3.3
2.3
0.6
Uncertainty Range Relative
(Tg C02 Eq.)
Lower
Bound
3.2
2.2
0.5
Upper
Bound
3.4
2.5
0.7
to 2011 Emission Estimate3
Lower
Bound
-2%
-7%
-11%
Upper
Bound
+2%
+7%
+11%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Previously estimated production-related CCh and PFC emissions for 2010 were replaced with those individual
facility values reported for 2010 to EPA's GHGRP. These data were used to recalculate emissions for that year,
decreasing estimated total CCh emissions by 10 percent and increasing estimated total PFC emissions by 1 percent.
Industrial Processes 4-65
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Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Aluminum Production source category. Particular attention will be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of
data from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories
will be relied upon.15l
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. Sulfur hexafluoride has been used in this application
around the world for more than twenty-five years. A dilute gaseous mixture of SF6 with dry air and/or CCh is blown
over molten magnesium metal to induce and stabilize the formation of a protective crust. A small portion of the SF6
reacts with the magnesium to form a thin molecular film of mostly magnesium oxide and magnesium fluoride. The
amount of SF6 reacting in magnesium production and processing is considered to be negligible and thus all SF6 used
is assumed to be emitted into the atmosphere. Although alternative cover gases, such as AM-cover™ (containing
HFC-134a), Novec™ 612 and dilute SCh systems can be used, many facilities in the United States are still using
traditional SF6 cover gas systems.
The magnesium industry emitted 1.4 Tg CC>2 Eq. (0.06 Gg) of SF6 in 2011, representing an increase of
approximately 8 percent from 2010 emissions (See Table 4-79). The increase can be attributed to: increased demand
for magnesium for use in iron and steel desulfurization as U.S. steel production recovered from the economic
downturn (USGS 201 Ib), and increased production and processing due to improving economic conditions and
increased demand from the automotive industry (USGS 201 Ib). The increase was mitigated in part by continuing
industry efforts to utilize SF6 alternatives, such as Novec™612 and sulfur dioxide, as part of the EPA's SF6
Emission Reduction Partnership for the Magnesium Industry.
Table 4-79: SFe Emissions from Magnesium Production and Processing (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 5.4 0.2
2005 2.9 0.1
2007
2008
2009
2010
2011
2.6
1.9
1.1
1.3
1.4
0.1
0.1
0.04
0.05
0.06
151 See
4-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Emission estimates for the magnesium industry incorporate information provided by some industry participants in
EPA's SF6 Emission Reduction Partnership for the Magnesium Industry. The Partnership started in 1999 and, in
2010, participating companies represented 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 2010 from primary production, secondary production (i.e., recycling), and die casting were generally
reported by Partnership participants. Partners reported their SF6 consumption, which was assumed to be equivalent
to emissions. Although 2010 was the last reporting year under the Partnership, some industry partners provided
information for the year 2011 in the reports for year 2010. For the remaining partners that did not report 2011
emissions, these were estimated based on the metal processed and emission rate reported by that partner in previous
year(s). Each partner's metal production in 2011 was extrapolated from that partner's metal production in 2010 and
the trend observed in previous years. Each partner's emission rate in 2011 was assumed to equal that partner's
emission rate in 2010. When it was determined a Partner is no longer in production, its metal production and
emissions rates were set to zero if no activity information was available.
Emission factors for 2002 to 2006 for sand casting activities were also acquired through the Partnership. For 2007
through 2010 the sand casting partner did not report and the reported emission factor from 2005 was utilized as
being representative of the industry. The same emission factor was also used for 2011 as partners were not required
to report after the year 2010. The 1999 through 2010 emissions from casting operations (other than die) were
estimated by multiplying emission factors (kg SF6 per metric ton of metal produced or processed) by the amount of
metal produced or consumed. For 2011, in the absence of reported data, company -specific emission factors were
assumed to be the same as that in 2010. To estimate emissions for 2011, company-specific emission factors were
multiplied by the corresponding estimated metal production (based on previous years' trend).The emission factors
for casting activities are provided below in Table 4-80. 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 2011 accounted for 15 to 52 percent of all SFe emissions from the U.S.
magnesium industry during this period. These estimates are based on information supplied by industry partners for
1999 through 2010. For 2011, in cases where reported data on company-specific emissions was not available,
company-specific emission factors for 2011 were assumed to be the same as that in 2010. To estimate emissions for
2011, company-specific emission factors were multiplied by the corresponding estimated metal production (based
on previous year's trend). From 2000 to 2010, partners accounted for all U.S. die casting that was tracked by USGS.
For 2011, emissions were estimated for the same companies using the methodology mentioned above. In 1999,
partners did not account for all die casting tracked by USGS, and, therefore, it was necessary to estimate the
emissions of die casters who were not partners. Die casters who were not partners were assumed to be similar to
partners who cast small parts. Due to process requirements, these casters consume larger quantities of SF6 per
metric ton of processed magnesium than casters that process large parts. Consequently, emission estimates from this
group of die casters were developed using an average emission factor of 5.2 kg SF6 per metric ton of magnesium.
This emission factor was developed using magnesium production and SF6 usage data for the year 1999. The
emission factors for the other industry sectors (i.e., permanent mold, wrought, and anode casting) were based on
discussions with industry representatives.
Table 4-80: SFe Emission Factors (kg SFe per metric ton of magnesium)
Year
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Die Casting
2.14a
0.72
0.72
0.71
0.81
0.81
0.79
0.86
0.67
1.15
Permanent Mold
2
2
2
2
2
2
2
2
2
2
Wrought
1
1
1
1
1
1
1
1
1
1
Anodes
1
1
1
1
1
1
1
1
1
1
Industrial Processes 4-67
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2009 1.77 2 11
2010 2.51 2 1 1
2011 2.52 2 1 1
a Weighted average that includes an estimated emission factor of 5.2 kg SFe
per metric ton of magnesium for die casters that do not participate in the
Partnership.
SF6 emission estimates were developed using data provided by the Magnesium Partnership participants in the
previous years (1999 through 2010) and the data published by USGS. U.S. magnesium consumption (casting) data
from 1990 through 2011 were available from the USGS (USGS 2002, 2003, 2005, 2006, 2007, 2008, 2010, 2011,
2012). 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) that
was used for years 1990 through 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 tonfor 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 2010 were provided by the Magnesium Partnership
participants, and for 1990 through 2001 emission factors for this process were assumed to be the same as the 2002
emission factor. For 2011, sand casting emission factor was assumed to be constant at the 2010 value. 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 4-80.
To estimate the uncertainty surrounding the estimated 2011 SF6 emissions from magnesium production and
processing, the uncertainties associated with three variables were estimated (1) emissions reported by magnesium
producers and processors for 2011 that participated in the Magnesium Partnership till 2010, (2) emissions estimated
for magnesium producers and processors that participated in the Partnership till 2010 but did not report 2011
emissions, and (3) emissions estimated for magnesium producers and processors that did not participate in the
Partnership. An uncertainty of 5 percent was assigned to the data reported by each participant in the Partnership. If
partners did not report emissions data during the current reporting year, SF6 emissions data were estimated using
available emission factor and production information reported in prior years; the extrapolation was based on the
company-specific trend for reporting in the current reporting year and the year prior. The uncertainty associated
with the SF6 usage estimate generated from the extrapolated emission factor and production information was
estimated to be 30 percent for each year of extrapolation. The lone sand casting partner has not reported since 2007
and its activity and emission factor were held constant at 2005 levels due to a reporting anomaly in 2006 because of
malfunctions at the facility. The uncertainty associated with the SF6 usage for the sand casting partner was 67
percent. For those industry processes that are not represented in Partnership, such as permanent mold and wrought
casting, SF6 emissions were estimated using production and consumption statistics reported by USGS and estimated
process-specific emission factors (see Table 4-80). The uncertainties associated with the emission factors and
USGS-reported statistics were assumed to be 75 percent and 25 percent, respectively. Emissions associated with
sand casting activities utilized a partner-reported emission factor with an uncertainty of 75 percent. In general,
where precise quantitative information was not available on the uncertainty of a parameter, a conservative (upper-
bound) value was used.
Additional uncertainties exist in these estimates that are not addressed in this methodology, 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).
4-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Sulfur hexafluoride may also be used as a cover gas for the casting of molten aluminum with high magnesium
content; however, the extent to which this technique is used in the United States is unknown.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-81. SF6 emissions associated
with magnesium production and processing were estimated to be between 1.2 and 1.6 Tg CCh Eq. at the 95 percent
confidence level. This indicates a range of approximately 13 percent below to 13 percent above the 2011 emission
estimate of 1.4 Tg CCh Eq. The uncertainty estimates for 2011 are higher relative to the 2010 reporting year which
is due to the fact that emission estimates for 2011 are based more on projected data that actual reported data as
compared to last year with only three emission sources using reported estimates and remaining sources using
projected (highly uncertain) estimates.
Table 4-81: Tier 2 Quantitative Uncertainty Estimates for SFe Emissions from Magnesium
Production and Processing (Tg COz Eq. and Percent)
Source
2011 Emission
Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg COz Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Magnesium
Production
SFe 1.4
1.2 1.6 -13% +13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence
interval.
€
The USGS 2010 Mineral Yearbook for Magnesium showed a revision in its estimate of sand casting production of
magnesium for 2009 in the United States, revising its previous estimate of 44 metric tons in 2009 to 107 metric tons.
In the next inventory report, emissions data reported under EPA's GHGRP will be incorporated in the national
inventory estimates. The emission estimation method required by subpart T of EPA's GHGRP is the same method
which Partners use to estimate emissions when reporting in previous Inventories. Therefore, it is not expected that
there will be any time series consistency issues. Future inventory estimates will use a new data source in future
years, but will rely on a similar to the methodology used for the years 1999 through 2010, where Partner facility-
level reported data were used. For future years, this facility-level data will instead come through EPA's GHGRP for
facilities that meet the reporting threshold.
Cover gas research conducted over the last decade has found that SF6 used for magnesium melt protection can have
degradation rates on the order of 20 percent in die casting applications (Bartos et al. 2007). Current emission
estimates assume (per the 2006 IPCC Guidelines) that all SF6 utilized is emitted to the atmosphere. Additional
research may lead to a revision of IPCC Guidelines to reflect this phenomenon and until such time, developments in
this sector will be monitored for possible application to the inventory methodology. 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 degrade during their exposure to the molten metal. Magnesium producers and
processors have already begun using these cover gases for 2006 through 2011 in a limited fashion; because the
amounts being used by companies on the whole are low enough that they have a minor effect on the overall
emissions from the industry, these emissions are only being monitored and recorded at this time.
Industrial Processes 4-69
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Zinc production in the United States consists of both primary and secondary processes. The majority of zinc
produced in the United States is used for galvanizing. Galvanizing is a process where zinc coating is applied to steel
in order to prevent corrosion. Zinc is used extensively for galvanizing operations in the automotive and construction
industry. Zinc is also used in the production of zinc alloys and brass and bronze alloys (e.g., brass mills, copper
foundries, copper ingot manufacturing, etc.). Zinc compounds and dust are also used, to a lesser extent, by the
agriculture, chemicals, paint, and rubber industries. Emissions from fuels consumed for energy purposes during the
production of Zinc are accounted for in the Energy chapter.
Primary production in the United States is conducted through the electrolytic process, while secondary techniques
include the electrothermic and Waelz kiln processes, as well as a range of other 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, only the electrothermic and Waelz kiln secondary
processes result in non-energy CO2 emissions (Viklund-White 2000).
In the electrothermic process, roasted zinc concentrate and secondary zinc products enter a sinter feed where they
are burned to remove impurities before entering an electric retort furnace. Metallurgical coke added to the electric
retort furnace reduces the zinc oxides and produces vaporized zinc, which is then captured in a vacuum condenser.
In the Waelz kiln process, electric arc furnace (EAF) dust, which is captured during the recycling of galvanized
steel, enters a kiln along with a reducing agent (typically 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 metric ton of zinc is produced for every
metric ton of EAF dust treated (Viklund-White 2000).
In 2011, U.S. primary and secondary refined zinc production were estimated to total 251,000 metric tons (USGS
2012), which was larger than 2010 levels, likely due to the general improvement in the U.S. economy in 2011 (see
Table 4-82). Zinc mine production increased in 2011 compared to 2010 levels, primarily owing to the increased
production at the zinc mining complexes in Tennessee. Primary zinc production (primary slab zinc) slightly
decreased in 2011 due to planned maintenance in the third quarter at a zinc refinery in Tennessee. On the other hand,
secondary zinc production in 2011 increased relative to 2010 owing to an increase in production in the first half of
2011 at a smelter in Pennsylvania (USGS 2012); this smelter in Pennsylvania was previously affected by an outage
in the fourth quarter of 2010 (Horsehead 2012).
Emissions of CO2 from zinc production in 2011 were estimated to be 1.3 Tg CO2 Eq. (1,286 Gg) (see Table 4-83).
All 2011 CO2 emissions resulted from secondary zinc production processes. Emissions from zinc production in the
U.S. have increased overall since 1990 due to a gradual shift from non-emissive primary production to emissive
secondary production. In 2011, emissions were estimated to be 103 percent higher than they were in 1990.
Table 4-82: Zinc Production (Metric Tons)
Year Primary Secondary
1990 262,704 95,708
2005 191,120 156,000
2007
2008
2009
2010
2011
121,000
125,000
94,000
120,000
117,000
157,000
161,000
109,000
129,000
134,000
4-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 4-83: COz Emissions from Zinc Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 0.6 632
2005 1.0 1,030
2007
2008
2009
2010
2011
1.0
1.2
0.9
1.2
1.3
1,025
1,159
943
1,182
1,286
Non-energy COa emissions from zinc production result from the electrothermic and Waelz kiln secondary
production processes, which both use metallurgical coke or other carbon-based materials as reductants. The
methods used to estimate emissions from these processes are based on Tier 1 methods from the 2006IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006). The Tier 1 emission factors provided by IPCC
for Waelz kiln-based secondary production were derived from coke consumption factors and other data presented in
Vikland-White (2000). These coke consumption factors as well as other inputs used to develop the Waelz kiln
emission factors are shown below. IPCC does not provide an emission factor for electrothermic processes due to
limited information; therefore, the Waelz kiln-specific emission factors were also applied to zinc produced from
electrothermic processes.
For Waelz kiln-based production, IPCC recommends the use of emission factors based on EAF dust consumption, if
possible, rather than the amount of zinc produced since the amount of reduction materials used is more directly
dependent on the amount of EAF dust consumed. Since only a portion of emissive zinc production facilities
consume EAF dust, the emission factor based on zinc production is applied to the non-EAF dust consuming
facilities while the emission factor based on EAF dust consumption is applied to EAF dust consuming facilities.
The 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 (i.e., 1.19 metric tons coke/metric
ton zinc produced) (Viklund-White 2000), and the following equation:
1.19 metric tons coke 0.85 metric tons C 3.67 metric tons CO^ 3.70 metric tons CO^
Waelz Kiln metric tons zinc metric tons coke metric tons C metric tons zinc
The Waelz kiln 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 (i.e., 0.4 metric tons coke/metric ton EAF dust
consumed) (Viklund-White 2000), and the following equation:
0.4 metric tons coke 0.85 metric tons C ^-^ metric tons CO 1.24 metric tons CO
EF = x x 2 - 2
EAF Dust metric tons EAF dust metric tons coke metric tons C metric tons EAF Dust
The only companies in the United States that use emissive technology to produce secondary zinc products are
Horsehead, PIZO, and Steel Dust Recycling. For Horsehead, EAF dust is recycled in Waelz kilns at their
Beaumont, TX; Calumet, IL; Palmerton, PA; Rockwood, TN; and Barnwell, SC facilities. These Waelz kiln
facilities produce intermediate zinc products (crude zinc oxide or calcine), most of which is transported to their
Monaca, PA facility where the products are smelted into refined zinc using electrothermic technology. Some of
Horsehead's intermediate zinc products that are not smelted at Monaca are instead exported to other countries
Industrial Processes 4-71
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around the world (Horsehead 2010a). PIZO and Steel Dust Recycling recycle EAF dust into intermediate zinc
products using Waelz kilns, and then sell the intermediate products to companies who smelt it into refined products.
The total amount of EAF dust consumed by Horsehead at their Waelz kilns was available from Horsehead financial
reports for years 2006 through 2011 (Horsehead 2007, 2008, 2010a, 2011, and 2012). Consumption levels for 1990
through 2005 were extrapolated using the percentage change in annual refined zinc production at secondary smelters
in the United States as provided by USGSMinerals Yearbook: Zinc (USGS 1995 through 2011). The EAF dust
consumption values for each year were then multiplied by the 1.24 metric tons CO2/metric ton EAF dust consumed
emission factor to develop CCh emission estimates for Horsehead's Waelz kiln facilities.
The amount of EAF dust consumed and total production capacity were obtained from Steel Dust Recycling's facility
for 2011 (Rowland 2012). SDR's facility in Alabama underwent expansion in 2011 to include a second unit (to be
operational in early- to mid-2012). SDR's facility has been operational since 2008. The amount of EAF dust
consumed by PIZO's facility in 2009, 2010, and 2011 (the only years this facility has been in operation) and Steel
Dust Recycling's facility for 2008, 2009, and 2010 was not publicly available. Therefore, these consumption values,
excluding PIZO's 2011 value, were estimated by calculating the 2008 through 2010 annual capacity utilization of
Horsehead's Waelz kilns and multiplying this utilization ratio by the capacities of the PIZO and Steel Dust
Recycling facilities, which were available from the companies (Horsehead 2007, 2008, 2010a, 2010b, and 2011;
PIZO 2012; Steel Dust Recycling LLC 2012). EAF dust consumption for PIZO's facility for 2011 was calculated by
applying the average annual capacity utilization rates for Horsehead and SDR (Grupo PROMAX) to PIZO's annual
capacity. (Horsehead 2012, Rowland 2012, PIZO 2012). The 1.24 metric tons CO2/metric ton EAF dust consumed
emission factor was then applied to PIZO's and Steel Dust Recycling's estimated EAF dust consumption to develop
CO2 emission estimates for those Waelz kiln facilities.
Refined zinc production levels for Horsehead's Monaca, PA facility (utilizing electrothermic technology) were
available from the company for years 2005 through 2011 (Horsehead 2008, 2011 and 2012). Production levels for
1990 through 2004 were extrapolated using the percentage changes in annual refined zinc production at secondary
smelters in the United States as provided by USGS Minerals Yearbook: Zinc (USGS 1995 through 2011). The 3.70
metric tons CO2/metric ton zinc emission factor was then applied to the Monaca facility's production levels to
estimate COa emissions for the facility. The Waelz kiln production emission factor was applied in this case rather
than the EAF dust consumption emission factor since Horsehead's Monaca facility did not consume EAF dust.
The uncertainties contained in these estimates are two-fold, relating to activity data and emission factors used.
First, there is uncertainty associated with the amount of EAF dust consumed in the United States to produce
secondary zinc using emission-intensive Waelz kilns. The estimate for the total amount of EAF dust consumed in
Waelz kilns is based on (1) an EAF dust consumption value reported annually by Horsehead Corporation as part of
its financial reporting to the Securities and Exchange Commission (SEC), and (2) an EAF dust consumption value
obtained from the Waelz kiln facility operated in Alabama by Steel Dust Recycling LLC. Since actual EAF dust
consumption information is not available for PIZO's facility (2009-2010) and SDR's facility (2008-2010), the
amount is estimated by multiplying the EAF dust recycling capacity of the facility (available from the company's
Web site) by the capacity utilization factor for Horsehead Corporation (which is available from Horsehead's
financial reports). Also, the EAF dust consumption for PIZO's facility in 2011 was estimated by multiplying the
average capacity utilization factor developed from Horsehead Corp. and SDR's annual capacity utilization rates by
PIZO's EAF dust recycling capacity. Therefore, there is uncertainty associated with the assumption used to estimate
PIZO and SDR's annual EAF dust consumption values (except SDR's EAF dust consumption in 2011 which was
obtained from SDR's recycling facility in Alabama).
Second, there are uncertainties associated with the emission factors used to estimate CO2 emissions from secondary
zinc production processes. The Waelz kiln emission factors are based on materials balances for metallurgical coke
and EAF dust consumed as provided by Viklund-White (2000). Therefore, the accuracy of these emission factors
depend upon the accuracy of these materials balances. Data limitations prevented the development of emission
factors for the electrothermic process. Therefore, emission factors for the Waelz kiln process were applied to both
electrothermic and Waelz kiln production processes. The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 4-84. Zinc production CO2 emissions were estimated to be between 1.1 and 1.5 Tg CO2 Eq. at
4-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
the 95 percent confidence level. This indicates a range of approximately 17 percent below and 15 percent above the
emission estimate of 1.3 Tg CCh Eq.
Table 4-84: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Zinc
Production (Tg COz Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg CCh Eq.) (Tg CCh Eq.) [%)
Lower Bound Upper Bound Lower Bound Upper Bound
Zinc Production CO2 l_3 l_l 1.5 -17% +15%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Zinc Production source category. Particular attention would be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of data
from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will
be relied upon.152
Lead production in the United States consists of both primary and secondary processes - both of which emit
(Sjardin 2003). Primary lead production, in the form of direct smelting, occurs at a just a single smelter in Missouri.
This primary lead smelter is expected to be closed by the end of 2013, and a new smelter is proposed to be
constructed at the same location as the existing smelter. Secondary production primarily involves the recycling of
lead acid batteries at approximately 20 separate smelters in the United States. A total of 14 of these secondary
smelters have annual capacities of 15,000 tons or more and were collectively responsible for more than 99 percent of
secondary lead production in 2011(USGS 2012). Secondary lead production has increased in the United States over
the past decade while primary lead production has decreased. In 2011, secondary lead production accounted for
nearly 91 percent of total lead production.
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
increased by approximately 3 percent from 2010 to 2011, but has decreased by 71 percent since 1990 (USGS 1995
through 2012a, Guberman2012).
Similar to primary lead production, COa emissions from secondary production result when a reducing agent, usually
metallurgical coke, is added to the smelter to aid in the reduction process. Carbon dioxide emissions from secondary
production also occur through the treatment of secondary raw materials (Sjardin 2003). In 2011, U.S. secondary
lead production decreased from 2010 levels by approximately 1 percent, but has increased by 23 percent since 1990
(USGS 1995 through 2012a, Guberman2012).
In 2011, U.S. primary and secondary lead production totaled 1,248,000 metric tons (Guberman 2012). The resulting
emissions of CO2 from 2011 production were estimated to be 0.5 Tg CO2 Eq. (538 Gg) (see Table 4-85). The
majority of 2011 lead production is from secondary processes, which accounted for 95 percent of total 2011 CCh
152 See
Industrial Processes 4-73
-------
emissions. At last reporting, the United States was the third largest mine producer of lead in the world, behind
China and Australia, accounting for approximately 8 percent of world production in 2011 (USGS 2012). Emissions
from fuels consumed for energy purposes during the production of lead are accounted for in the Energy chapter.
Table 4-85: COz Emissions from Lead Production (Tg COz Eq. and Gg)
Year Tg CCh Eq. Gg
1990 0.5 516
2005 0.6 553
2007
2008
2009
2010
2011
0.6
0.5
0.5
0.5
0.5
562
547
525
542
538
After a steady increase in total emissions from 1995 to 2000, total emissions have gradually decreased since 2000
but were still 4 percent greater in 2011 than in 1990. Although primary production has decreased significantly (71
percent since 1990), secondary production has increased by about 23 percent over the same time period. Since
secondary production is more emissions-intensive, the increase in secondary production since 1990 has resulted in a
net increase in emissions despite the sharp decrease in primary production (USGS 1995 through 2012a; Guberman
2012).
Non-energy CCh emissions from lead production result from primary and secondary production processes that use
metallurgical coke or other carbon-based materials as reductants. The methods used to estimate emissions for lead
production are based on Sjardin's work (Sjardin 2003) for lead production emissions and Tier 1 methods from the
2006IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). For primary lead production using
direct smelting, Sjardin (2003) and the IPCC (2006) provide an emission factor of 0.25 metric tons CCh/metric ton
lead. For secondary lead production, Sjardin (2003) and IPCC (2006) provide an emission factor of 0.25 metric tons
CCVmetric ton lead for direct smelting, as well as an emission factor of 0.2 metric tons CO2/metric ton lead
produced for the treatment of secondary raw materials (i.e., pretreatment of lead acid batteries). Since the secondary
production of lead involves both the use of the direct smelting process and the treatment of secondary raw materials,
Sjardin recommends an additive emission factor to be used in conjunction with the secondary lead production
quantity. The direct smelting factor (0.25) and the sum of the direct smelting and pretreatment emission factors
(0.45) are multiplied by total U.S. primary and secondary lead production, respectively, to estimate CO2 emissions.
The 1990 through 2011 activity data for primary and secondary lead production (see Table 4-86) were obtained from
the USGS through personal communications with the USGS Lead Commodity Specialist (Guberman 2012) and
through the USGS Mineral Yearbook: Lead (USGS 1995 through 2012a).
Table 4-86: Lead Production (Metric Tons)
Year Primary Secondary
1990 404,000 922,000
2005 143,000 1,150,000
2007
2008
2009
2010
2011
123,000
135,000
103,000
115,000
118,000
1,180,000
1,140,000
1,110,000
1,140,000
1,130,000
4-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 averaged the values provided
by three other studies (Dutrizac et al. 2000, Morris et al. 1983, Ullman 1997). For secondary production, Sjardin
(2003) added a COa 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 4-87. Lead production CC>2
emissions were estimated to be between 0.5 and 0.6 Tg CCh Eq. at the 95 percent confidence level. This indicates a
range of approximately 15 percent below and 15 percent above the emission estimate of 0.5 Tg CC>2 Eq.
Table 4-87: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Lead
Production (Tg COz Eq. and Percent)
Source Gas 2011 Emission Estimate Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Lead Production CCh 0.5 0.5 0.6 -15% +15%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Future improvements involve evaluating and analyzing data reported under EPA's GHGRP that would be useful to
improve the emission estimates for the Lead Production source category. Particular attention would be made to
ensure time series consistency of the emissions estimates presented in future inventory reports, consistent with IPCC
and UNFCCC guidelines. This is required as the facility-level reporting data from EPA's GHGRP, with the
program's initial requirements for reporting of emissions in calendar year 2010, are not available for all inventory
years (i.e., 1990 through 2009) as required for this inventory. In implementing improvements and integration of data
from EPA's GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will
be relied upon.153
Trifluoromethane (HFC-23 or CHF3) is generated as a byproduct during the manufacture of chlorodifluoromethane
(HCFC-22), which is primarily employed in refrigeration and air conditioning systems and as a chemical feedstock
for manufacturing synthetic polymers. Between 1990 and 2000, U.S. production of HCFC-22 increased
significantly as HCFC-22 replaced chlorofluorocarbons (CFCs) in many applications. Between 2000 and 2007, U.S.
production fluctuated but generally remained above 1990 levels. In 2008 and 2009, U.S. production declined
markedly before increasing slightly in 2010 and 2011. 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.154 Feedstock
production, however, is permitted to continue indefinitely.
153 See
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 4-75
-------
HCFC-22 is produced by the reaction of chloroform (CHCls) and hydrogen fluoride (HF) in the presence of a
catalyst, SbCls. The reaction of the catalyst and HF produces SbClxFy, (where x + y = 5), which reacts with
chlorinated hydrocarbons to replace chlorine atoms with fluorine. The HF and chloroform are introduced by
submerged piping into a continuous-flow reactor that contains the catalyst in a hydrocarbon mixture of chloroform
and partially fluorinated intermediates. The vapors leaving the reactor contain HCFC-21 (CHC^F), HCFC-22
(CHC1F2), HFC-23 (CHF3), HC1, chloroform, and HF. The under-fluorinated intermediates (HCFC-21) and
chloroform are then condensed and returned to the reactor, along with residual catalyst, to undergo further
fluorination. The final vapors leaving the condenser are primarily HCFC-22, HFC-23, HC1 and residual HF. The
HC1 is recovered as a useful byproduct, and the HF is removed. Once separated from HCFC-22, the HFC-23 may
be released to the atmosphere, recaptured for use in a limited number of applications, or destroyed.
Three facilities produced HCFC-22 in the U. S. in 2011. Emissions of HFC-23 in 2011 were estimated to be 6.9 Tg
CO2 Eq. (0.6 Gg) (see Table 4-88). This quantity represents a 9 percent increase from 2010 emissions but an 81
percent decline from 1990 emissions. The increase from 2010 emissions was caused by a 9 percent increase in
HCFC-22 production. The decline from 1990 emissions is due to a 21 percent decrease in HCFC-22 production and
a 76 percent decrease in the HFC-23 emission rate since 1990. The decrease in the emission rate is primarily
attributable to five 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, and
(e) another plant began destroying HFC-23.
Table 4-88: HFC-23 Emissions from HCFC-22 Production (Tg COz Eq. and Gg)
Year TgCChEq. Gg
1990 36.4 3
2005 15.8 1
2007
2008
2009
2010
2011
17.0
13.6
5.4
6.4
6.9
1
1
0.5
0.5
0.6
To estimate HFC-23 emissions for five of the eight HCFC-22 plants that have operated in the United States since
1990, methods comparable to the Tier 3 methods in the 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006) were used. Emissions for 2010 and 2011 were obtained through reports submitted by U. S.
HCFC-22 production facilities to EPA's GHGRP. EPA's GHGRP mandates that all HCFC-22 production facilities
report their annual emissions of HFC-23 from HCFC-22 production processes and HFC-23 destruction processes.
Previously, data were obtained by EPA through collaboration with an industry association that received voluntarily
reported HCFC-22 production and HFC-23 emissions annually from all U.S. HCFC-22 producers from 1990
through 2009. These emissions were aggregated and reported to EPA on an annual basis.
For the other three plants, the last of which closed in 1993, methods comparable to the Tier 1 method in the 2006
IPCC Guidelines were used. Emissions from these three plants have been calculated 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 measured concentrations of HFC-23 to estimate their emissions of
HFC-23. Plants using thermal oxidation to abate their HFC-23 emissions monitor the performance of their oxidizers
to verify that the HFC-23 is almost completely destroyed. Plants that release (or historically have released) some of
their byproduct HFC-23 periodically measure HFC-23 concentrations in the output stream using gas
chromatography. This information is combined with information on quantities of products (e.g., HCFC-22) to
estimate HFC-23 emissions.
4-76 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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To estimate 1990 through 2009 emissions, reports from an industry association were used that aggregated HCFC-22
production and HFC-23 emissions from all U.S. HCFC-22 producers and reported them to EPA (ARAP 1997, 1999,
2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010). To estimate 2010 and 2011 emissions,
facility-level data (including both HCFC-22 production and HFC-23 emissions) reported through the EPA's
GHGRP were analyzed (ICF 2012). In 1997 and 2008, comprehensive reviews of plant-level estimates of HFC-23
emissions and HCFC-22 production were performed (RTI1997; RTI2008). The 1997 and 2008 reviews enabled
U.S. totals to be reviewed, updated, and where necessary, corrected, and also for plant-level uncertainty analyses
(Monte-Carlo simulations) to be performed for 1990, 1995, 2000, 2005, and 2006. Estimates of annual U.S. HCFC-
22 production are presented in Table 4-89.
Table 4-89: HCFC-22 Production (Gg)
Year Gg
1990 139
2005 156
2007 162
2008 126
2009 91
2010 101
2011 110
and
The uncertainty analysis presented in this section was based on a plant-level Monte Carlo Stochastic Simulation for
2006. The Monte Carlo analysis used estimates of the uncertainties in the individual variables in each plant's
estimating procedure. This analysis was based on the generation of 10,000 random samples of model inputs from
the probability density functions for each input. A normal probability density function was assumed for all
measurements and biases except the equipment leak estimates for one plant; a log-normal probability density
function was used for this plant's equipment leak estimates. The simulation for 2006 yielded a 95-percent
confidence interval for U.S. emissions of 6.8 percent below to 9.6 percent above the reported total.
The relative errors yielded by the Monte Carlo Stochastic Simulation for 2006 were applied to the U.S. emission
estimate for 2011. The resulting estimates of absolute uncertainty are likely to be reasonably accurate because (1)
the methods used by the three plants to estimate their emissions are not believed to have changed significantly since
2006, and (2) although the distribution of emissions among the plants may have changed between 2006 and 2011
(because both HCFC-22 production and the HFC-23 emission rate declined significantly), the two plants that
contribute significantly to emissions were estimated to have similar relative uncertainties in their 2006 (as well as
2005) emission estimates. Thus, changes in the relative contributions of these two plants to total emissions are not
likely to have a large impact on the uncertainty of the national emission estimate.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-90. HFC-23 emissions from
HCFC-22 production were estimated to be between 6.4 and 7.6 Tg CCh Eq. at the 95 percent confidence level. This
indicates a range of approximately 7 percent below and 10 percent above the emission estimate of 6.9 Tg CC>2 Eq.
Table 4-90: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22
Production (Tg COz Eq. and Percent)
Source
Gas
2011 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
HCFC-22 Production
HFC-23
6.9
6.4 7.6 -7% +10%
a Range of emissions reflects a 95 percent confidence interval.
Industrial Processes 4-77
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Details on the emission trends through time are described in more detail in the Methodology section, above.
2010 emissions were revised downward by 1.7 Tg CO2 Eq., or 21 percent, reflecting a correction made by one plant
to its estimated emissions for that year following the discovery of a malfunction in a flowmeter totalizer.
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
Act Amendments of 1990.155 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
4-9 land Table 4-92.
Table 4-91: Emissions of HFCs and PFCs from ODS Substitutes (Tg COz Eq.)
Gas 1990
HFC-23 + ,
HFC-32 + .'
HFC-125 +
HFC-134a +
HFC-143a + ,
HFC-236fa +
CF4 +
Others* 0.3
Total 0.3
2005
+ ; -
0.3 ' " •
8.5
74.9 ,
8.7 ;v
0.8 -
+
5.6
99.0
2007
+
1.0
12.0
72.2
10.3
0.9
+
6.3
102.7
2008
+
1.3
14.3
69.3
11.1
0.9
+
6.7
103.6
2009
+
1.7
17.3
66.7
12.6
0.9
+
7.0
106.3
2010
+
2.5
22.2
66.8
14.7
0.9
+
7.4
114.6
2011
+
3.2
26.6
66.4
16.8
0.9
+
7.8
121.7
+ Does not exceed 0.05 Tg CO2 Eq.
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-43-10mee, C4Fio, and PFC/PFPEs, the latter being a proxy for a
diverse collection of PFCs and perfluoropolyethers (PFPEs) employed for solvent applications. For estimating purposes, the
GWP value used for PFC/PFPEs was based upon CeFi4.
Note: Totals may not sum due to independent rounding.
Table 4-92: Emissions of HFCs and PFCs from ODS Substitution (Mg)
Gas 1990
HFC-23 +
HFC-32 + <:•'
HFC-125 +
HFC-134a + .,
HFC-143a + .
HFC-236fa +
CF4 +
Others* M '
2005
1
505
3,053
57,637
2,290
125
2
M
2007
1
1,489
4,297
55,517
2,718
136
2
M
2008
2
2,025
5,119
53,273
2,911
141
2
M
2009
2
2,613
6,178
51,326
3,325
144
2
M
2010
2
3,856
7,930
51,402
3,861
146
3
M
2011
2
4,935
9,511
51,007
4,412
147
3
M
M (Mixture of Gases)
+ Does not exceed 0.5 Mg
155 [42 U.S.C § 7671, CAA Title VI]
4-78 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-43-10mee, C4Fio, and PFC/PFPEs, the latter being a proxy for a
diverse collection of PFCs and perfluoropolyethers (PFPEs) employed for solvent applications.
In 1990 and 1991, the only significant emissions of HFCs and PFCs as substitutes to ODSs were relatively small
amounts of HFC-152a—used as an aerosol propellant and also a component of the refrigerant blend R-500 used in
chillers—and HFC-134a in refrigeration end-uses. Beginning in 1992, HFC-134a was used in growing amounts as a
refrigerant in motor vehicle air-conditioners and in refrigerant blends such as R-404 A.156 In 1993, the use of HFCs
in foam production began, and in 1994 ODS substitutes for halons entered widespread use in the United States as
halon production was phased-out. In 1995, these compounds also found applications as solvents.
The use and subsequent emissions of HFCs and PFCs as ODS substitutes has been increasing from small amounts in
1990 to 121.7 TgCChEq. in2011. 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 continue 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 4-93 presents emissions of HFCs and PFCs as ODS substitutes by end-use sector for 1990 through 2011. The
end-use sectors that contributed the most toward emissions of HFCs and PFCs as ODS substitutes in 2011 include
refrigeration and air-conditioning (103.9 Tg CO2 Eq., or approximately 85 percent), aerosols (9.7 Tg CO2 Eq., or
approximately 8 percent), and foams (5.9 Tg CO2 Eq., or approximately 5 percent). Within the refrigeration and air-
conditioning end-use sector, motor vehicle air-conditioning was the highest emitting end-use (42.7 Tg CO2 Eq.),
followed by refrigerated retail food and refrigerated transport. Each of the end-use sectors is described in more
detail below.
Table 4-93: Emissions of HFCs and PFCs from ODS Substitutes (Tg COz Eq.) by Sector
Sector
Refrigeration/Air Conditioning
Aerosols
Foams
Solvents
Fire Protection
Total
1990
+
0.3
+'
+ ••.
+
0.3
2005
87.9 : -
7.3
1.9
1.3
0.5 ;v
99.0
2007
90.3
8.2
2.3
1.3
0.7
102.7
2008
90.4
8.6
2.5
1.3
0.7
103.6
2009
91.3
9.1
3.9
1.3
0.8
106.3
2010
97.6
9.3
5.4
1.3
0.9
114.6
2011
103.9
9.7
5.9
1.4
0.9
121.7
+ Does not exceed 0.05 Tg CO2 Eq.
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 and 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,157 R-404 A, and R-507A.158 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.
156 R.4Q4A contains HFC-125, HFC-143a, andHFC-134a.
157 R-410A contains HFC-32 and HFC-125.
158 R-507A, also called R-507, contains HFC-125 and HFC-143a.
Industrial Processes 4-79
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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 replaced
the use of CFCs with HFC-propellant alternatives. The earliest ozone-friendly MDIs were produced with HFC-
134a, but the industry has started to use HFC-227ea as well. Conversely, since the use of CFC propellants was
banned in 1978, most non-medical 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,
polyolefm, 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 CCh, methylene
chloride, and hydrocarbons. The majority of rigid PU foams have transitioned to HFCs—primarily HFC-134a and
HFC-245fa. Today, these HFCs are used to produce polyurethane appliance, 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, HFC-134a and CCh are 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 (CCU) 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-43-10mee, 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-236fa 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 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 occur.
4-80 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 it tracks the use and emissions of various compounds for the annual "vintages" of new equipment that enter
service in each end-use. The 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 60 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.
and
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 60 end-uses. The uncertainty analysis, however, quantifies the level
of uncertainty associated with the aggregate emissions resulting from the top 21 end-uses, comprising over 95
percent of the total emissions, and 5 other end-uses. These 26 end-uses comprise 97 percent of the total emissions.
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. 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 percent of non-MDI aerosol propellant that is HFC-152a, as well as the manufacturing loss rate
for XPS: Boardstock foam.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-94. Substitution of ozone
depleting substances HFC and PFC emissions were estimated to be between 117.2 and 134.2 Tg CO2 Eq. at the 95
percent confidence level. This indicates a range of approximately 1.5 percent below to 12.8 percent above the
emission estimate of 118.9 Tg CO2 Eq.
Table 4-94: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS
Substitutes (Tg COz Eq. and Percent)
Source
Gases
2011 Emission
Estimate
(Tg C02 Eq.)a
Uncertainty Range Relative to Emission Estimate1"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Substitution of Ozone
Depleting Substances
HFCs and
PFCs
118.9
117.2 134.2 -1.5% +12.8%
Industrial Processes 4-81
-------
a 2011 emission estimates and the uncertainty range presented in this table correspond to selected end-uses within the aerosols,
foams, solvents, fire extinguishing agents, and refrigerants sectors, but not for other remaining categories. Therefore, because the
uncertainty associated with emissions from "other" ODS substitutes was not estimated, they were excluded in the estimates
reported in this table.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
A review of the window unit end-use led to a minor revision in the assumed transition scenario. Overall, this change
to the Vintaging Model had negligible effects on estimates of greenhouse gas emissions across the time series.
Future improvements to the Vintaging Model are planned for the refrigeration and air-conditioning and foam
sectors. New vintages will be added for the motor vehicle air-conditioning, small retail food, domestic refrigeration,
and polyurethane rigid domestic refrigerator and freezer insulation foam end-uses. These vintages will include
transitions to low-GWP alternatives that have been newly introduced into the U.S. market. In addition, a vending
machine end-use may be added to the refrigeration and air-conditioning sector, in order to capture a portion of the
retail food market that may not be adequately encompassed by the small retail food end-use. These updates to the
Vintaging Model are not anticipated to have a significant impact in the near term on the estimates of greenhouse gas
emissions for the refrigeration and air-conditioning and foams sectors, but are anticipated to have an increasingly
larger impact in future years as the low-GWP alternatives penetrate the U.S. market.
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 (CJe), nitrogen
trifluoride (NF3), and sulfur hexafluoride (SF6), although other compounds such as perfluoropropane (CsFg) and
perfluorocyclobutane (c-C4F8) are also used. The exact combination of compounds is specific to the process
employed.
A single 300 mm silicon wafer that yields between 400 to 500 semiconductor products (devices or chips) may
require as many as, or more than 100 distinct fluorinated-gas-using process steps, principally to deposit and pattern
dielectric films. Plasma etching (or patterning) of dielectric films, such as silicon dioxide and silicon nitride, is
performed to provide pathways for conducting material to connect individual circuit components in each device.
The patterning process uses plasma-generated fluorine atoms, which chemically react with exposed dielectric film to
selectively remove the desired portions of the film. The material removed as well as undissociated fluorinated gases
flow into waste streams and, unless emission abatement systems are employed, into the atmosphere. PECVD
chambers, used for depositing dielectric films, are cleaned periodically using fluorinated and other gases. During
the cleaning cycle the gas is converted to fluorine atoms in plasma, which etches away residual material from
chamber walls, electrodes, and chamber hardware. Undissociated fluorinated gases and other products pass from the
chamber to waste streams and, unless abatement systems are employed, into the atmosphere. In addition to
emissions of unreacted gases, some fluorinated compounds can also be transformed in the plasma processes into
different fluorinated compounds which are then exhausted, unless abated, into the atmosphere. For example, when
C2F6 is used in cleaning or etching, CF4 is generated and emitted as a process by-product. Besides dielectric film
etching and PECVD chamber cleaning, much smaller quantities of fluorinated gases are used to etch polysilicon
films and refractory metal films like tungsten.
For 2011, total weighted emissions of all fluorinated greenhouse gases by the U. S. semiconductor industry were
estimated to be 5.3 Tg CCh Eq. Combined emissions of all fluorinated greenhouse gases are presented in Table 4-95
4-82 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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and Table 4-96 below for years 1990, 2005 and the period 2007 to 2011. The rapid growth of this industry and the
increasing complexity (growing number of layers) of semiconductor products led to an increase in emissions of 148
percent between 1990 and 1999, when emissions peaked at 7.2 Tg CCh Eq.159 The emissions growth rate began to
slow after 1999, and emissions declined by 26 percent between 1999 and 2011. Together, industrial growth and
adoption of emissions reduction technologies, including but not limited to abatement technologies, resulted in a net
increase in emissions of 84 percent between 1990 and 2011.
There was a sizable dip seen in emissions between 2008 and 2009, or a 25 percent decrease, due to the slowed
economic growth, and hence production, during this time. This trend is a newly identified historic trend in this
year's inventory and can be attributed to information on historic trends in demand for silicon from a newly
purchased VLSI database, which is used as part of estimating emissions from semiconductor manufacturing (see the
Recalculations Discussion section). While the industry recovered and emissions rose between 2009 and 2010 by
more than 50 percent a small reduction in emission can be seen between 2010 and 2011. This reduction may be
attributable to a reduction in non-Partner activity (TMLA). (As discussed further in the Methodology section, non-
Partners are conservatively assumed to have an emission rate equal to the Partners' emission rate in the late 1990s;
this is higher than the current Partner emission rate).
Table 4-95: RFC, HFC, and SFe Emissions from Semiconductor Manufacture (Tg COz Eq.)
Year
CF4
C2F6
C3F8
C4F8
HFC-23
SFe
NF3*
Total
1990
0.7
1.5 '-•
0.0 ,
0.0
0.2 ,-.;•
0.5
0.0
2.9
2005
1.1
2.0
0.0
0.1
0.2 ,
i.o ;,
0.4
4.4
2007
1.3
2.4
: o.o
•~ 0.1
. : 0.3
0.8
0.5
4.9
2008
1.4
2.4
0.1
0.1
0.3
0.9
0.6
5.1
2009
1.1
1.7
0.0
0.0
0.2
0.7
0.5
3.8
2010
1.7
2.6
0.0
0.0
0.4
1.0
0.5
5.7
2011
1.6
2.3
0.0
0.0
0.3
0.9
0.7
5.3
Note: Totals may not sum due to independent rounding.
* NFs emissions are presented for informational purposes, using the AR4 GWP of 17,200,
and are not included in totals.
Table 4-96: RFC, HFC, and SFe Emissions from Semiconductor Manufacture (Mg)
Year
CF4
C2Fe
C3F8
C4F8
HFC-23
SFe
NF3
1990
115
160
0 , •
0 '-•
15 •• '
22
3
2005
168
216 J
5
13 _
18
40
26 "
2007
205
1 259
6
7
24
35
30
2008
213
257
13
7
25
36
33
2009
166
187
5
4
20
29
33
2010
259
284
5
4
31
42
32
2011
252
255
6
4
29
39
38
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 that estimates industry emissions in the
absence of emission control strategies (Burton and Beizaie 2001).160 The availability and applicability of Partner
159 Complexity is a term denoting the circuit required to connect the active circuit elements (transistors) on a chip. Increasing
miniaturization, for the same chip size, leads to increasing transistor density, which, in turn, requires more complex
interconnections between those transistors. This increasing complexity is manifested by increasing the levels (i.e., layers) of
wiring, with each wiring layer requiring fluorinated gas usage for its manufacture.
160 ^ Partner refers to a participant in the U.S. EPA PFC Reduction/Climate Partnership for the Semiconductor Industry.
Through a Memorandum of Understanding (MoU) with the EPA, Partners voluntarily reported their PFC emissions to the EPA
Industrial Processes 4-83
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data differs across the 1990 through 2011 time series. Consequently, emissions from semiconductor manufacturing
were estimated using five distinct methods, one each for the periods 1990 through 1994, 1995 through 1999, 2000
through 2006, 2007 through 2010, and 2011.
1990 through 1994
From 1990 through 1994, Partnership data was unavailable and emissions were modeled using the PEVM (Burton
and Beizaie 2001).161 The 1990 to 1994 emissions are assumed to be uncontrolled, since reduction strategies such as
chemical substitution and abatement were yet to be developed.
PEVM is based on the recognition that PFC emissions from semiconductor manufacturing vary with: (1) the number
of layers that comprise different kinds of semiconductor devices, including both silicon wafer and metal
interconnect layers, and (2) silicon consumption (i.e., the area of semiconductors produced) for each kind of device.
The product of these two quantities, Total Manufactured Layer Area (TMLA), constitutes the activity data for
semiconductor manufacturing. PEVM also incorporates an emission factor that expresses emissions per unit of
layer-area. Emissions are estimated by multiplying TMLA by this emission factor.
PEVM incorporates information on the two attributes of semiconductor devices that affect the number of layers: (1)
linewidth technology (the smallest manufactured feature size), 162 and (2) product type (discrete, memory or
logic).163 For each linewidth technology, a weighted average number of layers is estimated using VLSI product-
specific worldwide silicon demand data in conjunction with complexity factors (i.e., the number of layers per
Integrated Circuit (1C)) specific to product type (Burton and Beizaie 2001, ITRS 2007). PEVM derives historical
consumption of silicon (i.e., square inches) by linewidth technology from published data on annual wafer starts and
average wafer size (VLSI Research, Inc. 2010).
The emission factor in PEVM is the average of four historical emission factors, each derived by dividing the total
annual emissions reported by the Partners for each of the four years between 1996 and 1999 by the total TMLA
estimated for the Partners in each of those years. Over this period, the emission factors varied relatively little (i.e.,
the relative standard deviation for the average was 5 percent). Since Partners are believed not to have applied
significant emission reduction measures before 2000, the resulting average emission factor reflects uncontrolled
emissions. The emission factor is used to estimate world uncontrolled emissions using publicly available data on
world silicon consumption.
1995 through 1999
For 1995 through 1999, total U.S. emissions were extrapolated from the total annual emissions reported by the
Partners (1995 through 1999). Partner-reported emissions are considered more representative (e.g., in terms of
capacity utilization in a given year) than PEVM estimated emissions, and are used to generate total U.S. emissions
when applicable. The emissions reported by the Partners were divided by the ratio of the total capacity of the plants
operated by the Partners and the total capacity of all of the semiconductor plants in the United States; this ratio
by way of a third party, which aggregated the emissions through 2010. For 2011, while no MOU existed, it was assumed that the
same companies that were Partners in 2010 were "Partners" in 2011 for purposes of estimating inventory emissions.
161 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.
162 By decreasing features of Integrated Circuit components, more components can be manufactured per device, which increases
its functionality. However, as those individual components shrink it requires more layers to interconnect them to achieve the
functionality. For example, a microprocessor manufactured with the smallest feature sizes (65 nm) might contain as many as 1
billion transistors and 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).
163 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.
4-84 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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represents the share of capacity attributable to the Partnership. This method assumes that Partners and non-Partners
have identical capacity utilizations and distributions of manufacturing technologies. Plant capacity data is contained
in the World Fab Forecast (WFF) database and its predecessors, which is updated quarterly (Semiconductor
Equipment and Materials Industry 2011).
2000 through 2006
The emission estimate for the years 2000 through 2006—the period during which Partners began the consequential
application of PFC-reduction measures—was estimated using a combination of Partner reported emissions and
PEVM modeled emissions. The emissions reported by Partners for each year were accepted as the quantity emitted
from the share of the industry represented by those Partners. Remaining emissions, those from non-Partners, were
estimated using PEVM and the method described above. Non-Partners are assumed not to have implemented any
PFC-reduction measures, and hence PEVM model provides emission estimates without such measures. The portion
of the U.S. total attributed to non-Partners is obtained by multiplying PEVM's total U.S. emissions figure by the
non-Partner share of U. S. total silicon capacity for each year as described above.164 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 ITRS 2008 and Semiconductor Equipment and Materials Industry 2011). 165,166,167
2007 through 2010
For the years 2007 through 2010, emissions were also estimated using a combination of Partner reported emissions
and PEVM modeled emissions to provide estimates for non-Partners; however, two improvements were made to the
estimation method employed for the previous years in the time series. First, the 2007 through 2010 emission
estimates account for the fact that Partners and non-Partners employ different distributions of manufacturing
technologies, with the Partners using manufacturing technologies with greater transistor densities and therefore
greater numbers of layers.168 Second, the scope of the 2007 through 2010 estimates is expanded relative to the
estimates for the years 2000 through 2006 to by including emissions from Research and Development (R&D) fabs.
164 This approach assumes that the distribution of linewidth technologies is the same between Partners and non-Partners. As
discussed in the description of the method used to estimate 2007 emissions, this is not always the case.
16^ Special attention was given to the manufacturing capacity of plants that use wafers with 300 mm diameters because the actual
capacity of these plants is ramped up to design capacity, typically over a 2-3 year period. To prevent overstating estimates of
partner-capacity shares from plants using 300 mm wafers, design capacities contained in WFW were replaced with estimates of
actual installed capacities for 2004 published by Citigroup Smith Barney (2005). Without this correction, the partner share of
capacity would be overstated, by approximately 5 percent. For perspective, approximately 95 percent of all new capacity
additions in 2004 used 300 mm wafers, and by year-end those plants, on average, could operate at approximately 70 percent of
the design capacity. For 2005, actual installed capacities were estimated using an entry in the World Fab Watch database (April
2006 Edition) called "wafers/month, 8-inch equivalent," which denoted the actual installed capacity instead of the fully-ramped
capacity. For 2006, actual installed capacities of new fabs were estimated using an average monthly ramp rate of 1100 wafer
starts per month (wspm) derived from various sources such as semiconductor fabtech, industry analysts, and articles in the trade
press. The monthly ramp rate was applied from the first-quarter of silicon volume (FQS V) to determine the average design
capacity over the 2006 period.
166 In 2006, the industry trend in co-ownership of manufacturing facilities continued. Several manufacturers, who are Partners,
now operate fabs with other manufacturers, who in some cases are also Partners and in other cases are not Partners. Special
attention was given to this occurrence when estimating the Partner and non-Partner shares of U.S. manufacturing capacity.
167 xwo 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.
168 EPA considered applying this change to years before 2007, but found that it would be difficult due to the large amount of
data (i.e., technology-specific global and non-Partner TMLA) that would have to be examined and manipulated for each year.
This effort did not appear to be justified given the relatively small impact of the improvement on the total estimate for 2007 and
the fact that the impact of the improvement would likely be lower for earlier years because the estimated share of emissions
accounted for by non-Partners is growing as Partners continue to implement emission-reduction efforts.
Industrial Processes 4-85
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This additional enhancement was feasible through the use of more detailed data published in the World Fab
Forecast. PEVM databases are updated annually as described above. The published world average capacity
utilization for 2007 through 2010 was used for production fabs while for R&D fabs a 20 percent figure was assumed
(SIA 2009).
In addition, publicly available actual utilization data was used to account for differences in fab utilization for
manufacturers of discrete and 1C products for the emissions in 2010 for non-partners. PEVM estimates were
adjusted using technology weighted capacity shares that reflect relative influence of different utilization.
2011
EPA's Partnership with the semiconductor industry, which included Partners' commitment to voluntarily report
emissions data to EPA, ended in 2010. Future Inventories will rely on data reported through EPA's GHGRP for the
semiconductor industry; however, this data was not available for the current inventory. Therefore, to ensure
consistency within the time series, a modification of the 2007 to 2010 method was used. To estimate 2011 Partner
emissions, it was assumed that the emission rate for Partners (Partnership emissions by gas to Partnership total
manufactured layer area) was constant from 2010 to 2011. With this one exception, the method outlined for 2007 to
2010, which used PEVM to estimate non-Partner emissions and added those to estimated "Partner" emissions to
determine total emissions for this sector, was used to estimate emissions in 2011.
Gas-Specific Emissions
Two different approaches were also used to estimate the distribution of emissions of specific fluorinated gases.
Before 1999, when there was no consequential adoption of fluorinated-gas-reducing measures, a fixed distribution
of fluorinated-gas use was assumed to apply to the entire U.S. industry. This distribution was based upon the
average fluorinated-gas purchases made 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 2011 period, the 1990
through 1999 distribution was assumed to apply to the non-Partners. Partners, however, began reporting gas-
specific emissions during this period. Thus, gas-specific emissions for 2000 through 2011 were estimated by adding
the emissions reported by the Partners (or estimated based on Partner reported emissions) to those estimated for the
non-Partners.
Data Sources
Partners estimated their emissions using a range of methods. It is assumed that most Partners used a method at least
as accurate as the IPCC's Tier 2a Methodology, recommended in the IPCC Guidelines for National Greenhouse
Inventories (2006). Data used to develop emission estimates are attributed in part to estimates based on data
provided by the members of the Partnership, and in part from data obtained from PEVM estimates. Estimates of
operating plant capacities and characteristics for Partners and non-Partners were derived from the Semiconductor
Equipment and Materials Industry (SEMI) World Fab Forecast (formerly World Fab Watch) database (1996 through
2012) (e.g., Semiconductor Materials and Equipment Industry, 2012). Actual world capacity utilizations for 2010
were obtained from Semiconductor International Capacity Statistics (SICAS) (SIA, 2010). Estimates of silicon
consumed by linewidth from 1990 through 2011 were derived from information from VLSI Research, Inc. (2010),
and the number of layers per linewidth was obtained from International Technology Roadmap for Semiconductors:
2011 Update (Burton and Beizaie 2001, ITRS 2007, ITRS 2008, ITRS 2011).
A quantitative uncertainty analysis of this source category was performed using the IPCC-recommended Tier 2
uncertainty estimation methodology, the Monte Carlo Stochastic Simulation technique. The equation used to
estimate uncertainty is:
U.S. emissions = ^Partnership gas-specific submittals + [(non-Partner share of World TMLA) x (PEVM Emission
Factor x World TMLA)]
The Monte Carlo analysis results presented below relied on estimates of uncertainty attributed to the four quantities
on the right side of the equation. Estimates of uncertainty for the four quantities were in turn developed using the
4-86 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 2011 is
about ±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 was
estimated based on a separate Monte Carlo simulation to account for the random occurrence of missing data in the
World Fab Forecast database. A relative uncertainty of approximately ±10 percent was estimated for the PEVM
emission factor, based on the standard deviation of the 1996 to 1999 emission factors.169 All estimates of
uncertainties are given at 95-percent confidence intervals.
In developing estimates of uncertainty, consideration was also given to the nature and magnitude of the potential
bias that World activity data (i.e., World TMLA) might have in its estimates of the number of layers associated with
devices manufactured at each technology node. The result of a brief analysis indicated that U.S. TMLA overstates
the average number of layers across all product categories and all manufacturing technologies by 0.12 layers or 2.9
percent.170 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.
In 2009 and 2010 the relative uncertainty of total (i.e., aggregated) reported Partnership PFC emissions, by gas, was
based on an analysis of the uncertainty of 2008 Partner-specific reported emissions by gas, as the Partner-specific
reported data was not available for 2009 and 2010. For the estimated aggregate Partnership PFC emissions data, a
relative uncertainty of ±50 percent was estimated for each gas-specific PFC emissions value reported by an
individual Partner for 2008, and error propagation techniques were used to apply these values to estimate uncertainty
for total Partnership gas-specific estimates for 2008-2010.171 Likewise, individual Partner reported emissions were
not available for 2011. Consequently, the uncertainty associated with total 2011 Partnership gas-specific emissions
in 2011 was assumed to be the same as the uncertainty associated with the 2008, 2009, and 2010 Partnership gas-
specific emissions.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-97. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing were estimated to be between 4.9 and 5.8 Tg CCh Eq.
at a 95 percent confidence level. This range represents 8 percent below to 9 percent above the 2011 emission
estimate of 5.3 Tg CCh 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 4-97: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SFe Emissions from
Semiconductor Manufacture (Tg COz Eq. and Percent)
Source
Semiconductor
Manufacture
2011 Emission
Gas Estimate3
(Tg C02 Eq.)
HFC,
PFC, and , ,
SFe
Uncertainty Range Relative to Emission Estimate1"
(Tg C02 Eq.) (%)
Lower
Bound0
4.9
Upper
Bound0
5.8
Lower
Bound
-8%
Upper
Bound
9%
a Because the uncertainty analysis covered all emissions (including NFs), the emission estimate presented here
does not match that shown in Table 4-95.
b Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence
interval.
c Absolute lower and upper bounds were calculated using the corresponding lower and upper bounds in percentages.
169 The average of 1996 to 1999 emission factor is used to derive the PEVM emission factor.
170This is based on an analysis of 2004 data.
171 Error propagation resulted in Partnership gas-specific uncertainties ranging from 17 to 27 percent. Uncertainty is based on
Partner reported data from 2008, as EPA has not conducted an audit of Partner data at Latham and Watkins since that data was
reported.
Industrial Processes 4-87
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Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Activity data for the time series was revised for the current inventory. Specifically, silicon demand data for the
years 2007-2010 were revised within PEVM, and hence the inventory, to reflect updated published data purchased
from VLSI within the Worldwide Silicon Demand report. The revised inventory now relies on the 2012 version of
this report, which revised historic numbers in the late 2000's since the last purchase of the report for inventory
purposes. The 2012 Silicon Demand report captures the slowdown and drop in silicon demand, particularly in 2009,
due to worldwide economic slowdowns, whereas data previously used did not reflect this. Differences seen between
the datasets used, in terms of millions of squares inches of silicon demanded, were 5.8 percent, 4.8 percent, 22.1
percent, and 9.1 percent for the years 2007, 2008, 2009 and 2010, respectively.
Future years' emissions data from the EPA's GHGRP will be available for use. The data required to be reported for
semiconductor manufacturers under subpart I-Electronics Manufacturing includes PFC, HFC, SF6, and NF3
emissions, as well as emissions of N2O and heat transfer fluid emissions. Therefore a point of consideration for
future national emissions estimates is the inclusion of N2O and emissions from heat transfer fluid (HTF) loss to the
atmosphere.
N2O is used for the chemical vapor deposition process mainly. Deposition is a fundamental step in the fabrication of
a variety of electronic devices. During deposition, layers of dielectric, barrier, or electrically conductive films are
deposited or grown on a wafer or other substrate. Chemical vapor deposition (CVD) enables the deposition of
dielectric or metal films. During the CVD process, gases that contain atoms of the material to be deposited react on
the wafer surface to form a thin film of solid material. Films deposited by CVD may be silicon oxide, single-layer
crystal epitaxial silicon, amorphous silicon, silicon nitride, dielectric anti-reflective coatings, low-k dielectric,
aluminum, titanium, titanium nitride, polysilicon, tungsten, refractory metals or silicides. N2O may be the oxidizer
of choice during deposition of silicon oxide films. N2O may also be used in other manufacturing processes.
Fluorinated Heat transfer fluids, of which some are liquid perfluorinated compounds, are used for temperature
control, device testing, cleaning substrate surfaces and other parts, and soldering in certain types of semiconductor
manufacturing production processes. Evaporation of these fluids is a source of fluorinated emissions (EPA 2006).
When considering the integration of emissions data from a new source, EPA's GHGRP, time series consistency is a
major consideration, consistent with IPCC and UNFCCC guidelines. This is required as facility-level reporting data
from EPA's GHGRP, with the program's initial requirements for reporting of emissions in calendar year 2010, are
not available for all inventory years (i.e., 1990 through 2009) as required for this inventory. In addition, EPA's
GHGRP requires reporters to use an emission estimation method similar, but not the same, as Partners used in the
past. Additionally, EPA's GHGRP provides new emission factors as compared to the IPCC Guidelines which many
Partners relied on. Consideration will also need to be given to the fact that PEVM estimated emissions are likely to
not be consistent with GHGRP emissions data because the PEVM emission factor relies on historic Partner data.
Companies/facilities reporting under subpart I of EPA's GHGRP will represent a larger portion of the sector than
historically reported under the voluntary Partnership.
Along with more emissions information for the semiconductor manufacturing sector, EPA's GHGRP requires the
reporting of emissions from other types of electronics manufacturing, including micro-electro-mechanical systems,
flat panel displays, and photovoltaic cells. Including these sources categories in future national inventories may be a
consideration.
4-88 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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The largest use of SF6, both in the United States and internationally, is as an electrical insulator and interrupter in
equipment that transmits and distributes electricity (RAND 2004). The gas has been employed by the electric power
industry in the United States since the 1950s because of its dielectric strength and arc-quenching characteristics. It
is used in gas-insulated substations, circuit breakers, and other switchgear. Sulfur hexafluoride has replaced
flammable insulating oils in many applications and allows for more compact substations in dense urban areas.
Fugitive emissions of SF6 can escape from gas-insulated substations and switchgear through seals, especially from
older equipment. The gas can also be released during equipment manufacturing, installation, servicing, and
disposal. Emissions of SF6 from equipment manufacturing and from electrical transmission and distribution systems
were estimated to be 7.0 Tg CCh Eq. (0.3 Gg) in 2011. This quantity represents a 74 percent decrease from the
estimate for 1990 (see Table 4-98 and Table 4-99). This decrease is believed to have two causes: a sharp increase in
the price of SF6 during the 1990s and a growing awareness of the environmental impact of SF6 emissions through
programs such as EPA's SF6 Emission Reduction Partnership for Electric Power Systems.
Table 4-98: SFe Emissions from Electric Power Systems and Electrical Equipment
Manufacturers (Tg COz Eq.)
Year
1990
2005
2007
2008
2009
2010
2011
Electric Power
Systems
26.3
10.3
8.2
7.5
7.5
7.0
6.3
Electrical Equipment
Manufacturers
0.3
0.8
0.6
1.1
0.6
0.8
0.8
Total
26.7
11.1
8.8
8.6
8.1
7.8
7.0
Note: Totals may not sum due to independent rounding.
Table 4-99: SFe Emissions from Electric Power Systems and Electrical Equipment
Manufacturers (Gg)
Year Emissions
1990 O
2005 0.5
2007 0.4
2008 0.4
2009 0.3
2010 0.3
2011 0.3
The estimates of emissions from Electrical 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.
For the first time, the inventory methodology incorporates emission estimates from electric power systems reported
through EPA's GHGRP. In 2012, several U.S. electrical power systems began reporting emission estimates to EPA
Industrial Processes 4-89
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through its GHGRP. EPA's GHGRP mandates that users of SF6 in electric power systems are required to report
emissions if the facility has a total SF6 nameplate capacity that exceeds 17,820 pounds (a nameplate-based
approximate of the 25,000 metric tons of CCh equivalent threshold). Many utilities participating in EPA's SF6
Emission Reduction Partnership for Electric Power Systems (Partners) began reporting their emissions through
EPA's GHGRP given the reporting threshold as opposed to through the Partnership as was done historically;
additionally, several utilities that are not Partners reported estimates through EPA's GHGRP. Like Partners, electric
power systems that report their SF6 emissions under EPA's GHGRP are required to use the IPCC Tier 3 utility-level
mass-balance approach (IPCC 2006).
1999 through 2011 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to 2011 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; (2) reporting from utilities required to report under the EPA's GHGRP, which began in 2012 for emissions
occurring in 2011 (GHGRP-Only Reporters); and (3) the relationship between utilities' reported emissions and their
transmission miles as reported in the 2001, 2004, 2007, and 2010 Utility Data Institute (UDI) Directories of Electric
Power Producers and Distributors (UDI 2001, 2004, 2007, 2010), which was applied to the electric power systems
that do not report to EPA (Non-Reporters). (Transmission miles are defined as the miles of lines carrying voltages
above 34.5 kV).
Over the period from 1999 to 2011, Partner utilities, which for inventory purposes are defined as utilities that either
currently are or previously have been part of the Partnership, represented between 43 percent and 48 percent of total
U.S. transmission miles. Partner utilities estimated their emissions using a Tier 3 utility-level mass balance
approach (IPCC 2006). If a Partner utility did not provide data for a particular year, emissions were interpolated
between years for which data were available or extrapolated based on Partner-specific transmission mile growth
rates. In 2011, approximately 0.2 percent of the total emissions attributed to Partner utilities were reported through
Partnership reports. Approximately 72 percent of the total emissions attributed to Partner utilities were reported and
verified through the GHGRP, as described below. Partners without verified 2011 data accounted for approximately
28 percent of the total emissions attributed to Partner utilities.172
EPA's GHGRP requires users of SF6 in electric power systems to report emissions if the facility has a total SF6
nameplate capacity that exceeds 17,820 pounds. (This quantity is the nameplate capacity that would result in annual
SF6 emissions equal to 25,000 metric tons of CO2 equivalent at the historical emission rate reported under the
Partnership.) Like Partners, electric power systems that report their SF6 emissions under EPA's GHGRP are
required to use the Tier 3 utility-level mass-balance approach. Many Partners began reporting their emissions
through EPA's GHGRP in 2012 because their nameplate capacity exceeded the reporting threshold. Partners who
did not report through EPA's GHGRP continued to report through the Partnership.
In addition, many non-Partners began reporting to EPA for the first time through its GHGRP in 2012. Non-Partner
emissions reported and verified under EPA's GHGRP were compiled to form a new category of reported data
(GHGRP-Only Reporters). GHGRP-Only Reporters accounted for 16 percent of U.S. transmission miles and 15
percent of estimated U.S. emissions from electric power system in 20II.173
l7^ It should be noted that data reported through the GHGRP must go through a verification process; only data verified as of
January 1,2013 could be used in the emission estimates for 2011. For Partners whose GHGRP data was not yet verified,
emissions were extrapolated based upon historical Partner-specific transmission mile growth rates, and those Partners are
included in the 'non-reporting Partners' category.
For electric power systems, verification involved a series of electronic range, completeness, and algorithm checks for each report
submitted. In addition, EPA manually reviewed the reported data and compared each facility's reported transmission miles with
the corresponding quantity in the UDI 2010 database (UDI 2010). EPA then followed up with reporters where the discrepancy
between the reported miles and the miles published by UDI was greater than 10 percent, with a goal to improve data quality.
Only GHGRP data verified as of January 1,2013 was included in the emission estimates for 2011.
It should also be noted that GHGRP-reported emissions from five facilities that did not have any associated transmission
miles were included in the emissions estimates for 2011. Emissions from these facilities comprise approximately 0.6 percent of
4-90 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Emissions from Non-Reporters (i.e., utilities other than Partners and GHGRP-Only Reporters) in every year since
1999 were estimated using the results of a regression analysis that correlated emissions from reporting utilities with
their transmission miles. In the United States, SF6 is contained primarily in transmission equipment rated above
34.5 kV. Two equations were developed, one for "non-large" and one for "large" utilities (i.e., with fewer or more
than 10,000 transmission miles, respectively). The distinction between utility sizes was made because the regression
analysis showed that the relationship between emissions and transmission miles differed for non-large and large
transmission networks.
To estimate emissions from non-reporting, non-large utilities, a regression equation based on verified data from both
Partners and GHGRP-Only Reporters was used. As noted above, non-Partner emissions were reported to the EPA
for the first time through its GHGRP in 2012. This data was of particular interest because it provided insight into
the emission rate of non-Partners, which previously was assumed to be equal to the historical (1999) emission rate of
Partners.174 The availability of non-Partner emissions estimates allowed the regression analysis to be modified for
smaller utilities. (The regression equation for larger non-reporting utilities could not be revised, because verified
emissions estimates were not available for any non-Partner utilities with greater than 10,000 transmission miles). To
develop the equation, first, the emission rates and emissions per transmission mile reported by Partners and
GHGRP-Only Reporters with fewer than 10,000 transmission miles in 2011 was reviewed to determine whether
there was a statistically significant difference between these two groups. It was determined that there is no
statistically significant difference among the two sets; therefore, Partner and GHGRP-Only reported data for 2011
were combined to develop a regression equation to estimate the emissions of non-reporting utilities. The equation
was developed based on the emissions reported by a subset of 35 Partner utilities and 39 non-Partner utilities
(representing approximately 40 percent of total U.S. transmission miles for utilities with fewer than 10,000
transmission miles). 2011 transmission mileage data was reported through EPA's GHGRP, with the exception of
transmission mileage data for Partners that did not report through EPA's GHGRP, which was obtained from the
2010 UDI Directory of Electric Power Producers and Distributors (UDI2010).
Historical emissions from non-reporting, non-large utilities were estimated by linearly interpolating between the
1999 regression coefficient and the revised 2011 regression coefficient.
The equation for large utilities was developed based on the 1999 SF6 emissions reported by a subset of 42 Partner
utilities (representing approximately 23 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). This equation was
used to estimate non-Reporter emissions from large utilities from 1999 to 2011.
The regression equations are:
Non-reporting large utilities (more than 10,000 transmission miles, in kilograms):
Emissions (kg) = 0.58 x Transmission Miles
Non-reporting small utilities (less than 10,000 transmission miles, in kilograms):
Emissions (kg) = Annual regression coefficient x Transmission Miles
where the annual regression coefficient ranged linearly from 0.89 in 1999 to 0.34 in 2011
Data on transmission miles for each Non-Reporter for the years 2000, 2003, 2006, and 2009 were obtained from the
2001, 2004, 2007, and 2010 UDI Directories of Electric Power Producers and Distributors, respectively (UDI 2001,
2004, 2007, 2010). The U.S. transmission system grew by over 25,000 miles between 2000 and 2003 and by only
2,400 miles between 2003 and 2006. These periodic increases are assumed to have occurred gradually. Therefore,
transmission mileage was assumed to increase at an annual rate of 1.3 percent between 2000 and 2003 and 0.1
percent between 2003 and 2006. This growth rate grew to 2.8 percent from 2006 to 2009 as transmission miles
increased by 56,000 miles (approximately). The annual growth rate for 2010 and 2011 was extrapolated based on the
growth rate from 2006 to 2009 of 2.8 percent.
total reported and verified emissions. EPA is continuing to investigate whether or not these emissions are already implicitly
accounted for in the relationship between transmission miles and emissions (discussed further below).
Partners in EPA's SFe Emission Reduction Partnership reduced their emissions by approximately 63 percent from 1999 to
2010 and 68 percent from 1999 to 2011.
Industrial Processes 4-91
-------
As a final step, total electric power system 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), the GHGRP-Only reported emissions, and the non-reporting utilities'
emissions (determined using the 1999 and 2011 regression equations).
1990 through 1998 Emissions from Electric Power Systems
Because most utilities participating in the Partnership reported emissions only for 1999 through 2011, 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 1999 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).175 (Although equation 7.3 of the IPCC Guidelines appears in the discussion of substitutes for ozone-
depleting substances, it is applicable to emissions from any long-lived pressurized equipment that is periodically
serviced during its lifetime.)
Emissions (kilograms SF6) = SF6 purchased to refill existing equipment (kilograms) + nameplate capacity of retiring
equipment (kilograms)176
Note that the above equation holds whether the gas from retiring equipment is released or recaptured; if the gas is
recaptured, it is used to refill existing equipment, thereby lowering the amount of SF6 purchased by utilities for this
purpose.
Gas purchases by utilities and equipment manufacturers from 1961 through 2003 are available from the RAND
(2004) survey. To estimate the quantity of SF6 released or recovered from retiring equipment, the nameplate
capacity of retiring equipment in a given year was assumed to equal 81.2 percent of the amount of gas purchased by
electrical equipment manufacturers 40 years previous (e.g., in 2000, the nameplate capacity of retiring equipment
was assumed to equal 81.2 percent of the gas purchased in 1960). The remaining 18.8 percent was assumed to have
been emitted at the time of manufacture. The 18.8 percent emission factor is an average of IPCC default SF6
emission rates for Europe and Japan for 1995 (IPCC 2006). The 40-year lifetime for electrical equipment is also
based on IPCC (2006). The results of the two components of the above equation were then summed to yield
estimates of global SFe emissions from 1990 through 1999.
U.S. emissions between 1990 and 1999 are assumed to follow the same trajectory as global emissions during this
period. To estimate U.S. emissions, global emissions for each year from 1990 through 1998 were divided by the
estimated global emissions from 1999. The result was a time series of factors that express each year's global
emissions as a multiple of 1999 global emissions. Historical U.S. emissions were estimated by multiplying the
factor for each respective year by the estimated U.S. emissions of SF6 from electric power systems in 1999
(estimated to be 15.0 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 and is not accounted for in any another manner by RAND. However,
atmospheric studies confirm that the downward trend in estimated global emissions between 1995 and 1998 was real
(see the Uncertainty discussion below).
175 Ideally, sales to utilities in the U.S. between 1990 and 1999 would be used as a model. However, this information was not
available. There were only two U.S. manufacturers of SFe during this time period, so it would not have been possible to conceal
sensitive sales information by aggregation.
176 Nameplate capacity is defined as the amount of SFe within fully charged electrical equipment.
4-92 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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1990 through 2011 Emissions from Manufacture of Electrical Equipment
The 1990 to 2011 emission estimates for original equipment manufacturers (OEMs) were derived by assuming that
manufacturing emissions equal 10 percent of the quantity of SF6 provided with new equipment. The quantity of SF6
provided with new equipment was estimated based on statistics compiled by the National Electrical Manufacturers
Association (NEMA). These statistics were provided for 1990 to 2000; the quantities of SF6 provided with new
equipment for 2001 to 2011 were estimated using Partner reported data and the total industry SF6 nameplate
capacity estimate (143.1 TgCOaEq. in 2011). 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 2010 was
calculated. Due to the decrease in available Partner data for 2011 - as most Partners reported through the GHGRP
and reporting on these parameters was not required in 2011 - the 2011 ratio was estimated as an average of the 1999
to 2010 ratios. These ratios were then multiplied by the total industry nameplate capacity estimate for each year to
derive the amount of SF6 provided with new equipment for the entire industry. The 10 percent emission rate is the
average of the "ideal" and "realistic" manufacturing emission rates (4 percent and 17 percent, respectively)
identified in a paper prepared under the auspices of the International Council on Large Electric Systems (CIGRE) in
February 2002 (O'Connell et al. 2002).
To estimate the uncertainty associated with emissions of SF6 from Electrical Transmission and Distribution,
uncertainties associated with four quantities were estimated: (1) emissions from Partners, (2) emissions from
GHGRP-Only Reporters, (3) emissions from Non-Reporters, and (4) 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 SFe Emission Reduction Partnership include emissions from both reporting (through the
Partnership or GHGRP) 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 2.5 percent. The uncertainty associated with extrapolated or
interpolated emissions from non-reporting Partners was assumed to be 20 percent.
For GHGRP-Only Reporters, reported SF6 data was assumed to have an uncertainty of 20 percent.177 Based on a
Monte Carlo analysis, the cumulative uncertainty of all GHGRP-Only reported data was estimated to be 5.2 percent.
There are two sources of uncertainty associated with the regression equations used to estimate emissions in 2011
from Non-Reporters: (1) uncertainty in the coefficients (as defined by the regression standard error estimate), and
(2) the uncertainty in total transmission miles for Non-Reporters. Uncertainties were also estimated regarding (1)
the quantity of SF6 supplied with equipment by equipment manufacturers, which is projected from Partner provided
nameplate capacity data and industry SF6 nameplate capacity estimates, and (2) the manufacturers' SF6 emissions
rate.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-100. Electrical Transmission
and Distribution SF6 emissions were estimated to be between 5.8 and 8.5 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of approximately 17 percent below and 21 percent above the emission estimate of 7.0
Tg CO2 Eq.
Table 4-100: Tier 2 Quantitative Uncertainty Estimates for SFe Emissions from Electrical
Transmission and Distribution (Tg COz Eq. and percent)
2011 Emission
Source Gas Estimate Uncertainty Range Relative to 2011 Emission Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Upper
Lower Bound Upper Bound Lower Bound Bound
Uncertainty is assumed to be higher for the GHGRP-Only category, because 2011 is the first year that those utilities have
reported to EPA,.
Industrial Processes 4-93
-------
Electrical Transmission
and Distribution SFe 7.0 5.8 8.5 -17% +21%
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 (RAND 2004), and emissions
based on atmospheric measurements declined by 17 percent over the same period (Levin et al. 2010).
Several pieces of evidence indicate that U.S. SF6 emissions were reduced as global emissions were reduced. First,
the decreases in sales and emissions coincided with a sharp increase in the price of SF6 that occurred in the mid-
1990s and that affected the United States as well as the rest of the world. A representative from DILO, a major
manufacturer of SF6 recycling equipment, stated that most U.S. utilities began recycling rather than venting SF6
within two years of the price rise. Finally, the emissions reported by the one U.S. utility for 1990 through 1999
under the Partnership showed a downward trend beginning in the mid-1990s.
sf^f®^ I /"*! i 1 """a1!"1i*%irtssf W\i jf* ^i i ** IF* i f%. w^
The historical emissions estimated for this source category have undergone significant revisions. First, in the
current inventory, SF6 emission estimates for the period 1990 through 2010 were updated relative to the previous
report based on revisions to interpolated and extrapolated non-reported Partner data. Second, an error was detected
and fixed regarding the treatment of UDI2010 data in the inventory. Due to a change in the transmission mile
growth rate, this impacted SF6 emission estimates for the period 2006 through 2010. Third, the previously-described
interpolation between 1999 and 2011 regression coefficients to estimate emissions from non-reporting utilities with
fewer than 10,000 transmission miles impacted historical estimates for the period 2000 through 2010. Previously, a
conservative coefficient had been used to estimate non-Partner emissions that proved too high once GHGRP -
reported data was analyzed for the 2011 reporting year. As a result of the above changes, SF6 emissions from
electrical transmission and distribution decreased by 37 percent for 2010 relative to the previous report.
With future reporting under EPA's GHGRP, affected electric power systems will be required to report additional
data elements, including the decrease in SF6 inventory, purchases of SF6, disbursements of SF6, and net increase in
total nameplate capacity of equipment operated. This will allow inclusion of GHGRP data on nameplate capacity
and purchases in the inventory in future years. However, particular attention will be made to ensure time series
consistency of the emissions estimates presented in future inventory reports, consistent with IPCC and UNFCCC
guidelines. This is required as facility-level reporting data from EPA's GHGRP are not available for all inventory
years (i.e., 1990 through 2010) as required for this inventory.
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 1996 IPCC 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:
4-94 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
• 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 4-101 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.178 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
emissions estimates for electrical transmission and distribution were developed using U.S. utility purchases of SF6
for electrical equipment. From 1999 through 2007, estimates were obtained from reports submitted by participants in
EPA's SF6 Emission Reduction Partnership for Electric Power Systems. U.S. utility purchases of SF6 for electrical
equipment from 1990 through 1998 were backcasted based on world sales of SF6 to utilities. Purchases of SF6 by
utilities were added to SF6 purchases by electrical equipment manufacturers to obtain total SF6 purchases by the
electrical equipment sector.
Table 4-101: 2011 Potential and Actual Emissions of HFCs, PFCs, and SFe from Selected
Sources (Tg CO2 Eg.)
Source
Substitution of Ozone Depleting Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Magnesium Production and Processing
Electrical Transmission and Distribution
Potential
236.3
-
+
+
17.1
Actual
121.7
2.9
6.9
+
+
11.7
- Not applicable.
+ Does not exceed 0.05 Tg CO2 Eq.
:§ of
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 2011 are reported in Table 4-102.
Table 4-102: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source 1990 I 2005 ' 2007 2008 2009 2010 2011
NOx 591 1 569 537 520 568 568 568
Other Industrial Processes 343 * 437 * 398 379 436 436 436
Metals Processing 88 , 60 , 62 62 60 60 60
178 See Annex 5 for a discussion of sources of SFe emissions excluded from the actual emissions estimates in this report.
Industrial Processes 4-95
-------
Chemical and Allied Product
Manufacturing
Storage and Transport
Miscellaneous*
CO
Metals Processing
Other Industrial Processes
Chemical and Allied Product
Manufacturing
Storage and Transport
Miscellaneous*
NMVOCs
Storage and Transport
Other Industrial Processes
Chemical & Allied Product
Manufacturing
Metals Processing
Miscellaneous*
152
3
5 /
4,125
2,395
487 /
1,073
69
101
2,422
1,352
364 /
575
111
20 /
55
15
2 /
1,555
752
484 /
189
97
32 .••'
1,997
. 1,308
415 /
213
44
17 /
59
16
2
1,640
824
464
223
103
27
1,869
1,224
383
210
43
10
61
16
2
1,682
859
454
240
104
25
1,804
1,182
367
207
42
7
55
15
2
1,549
752
484
187
97
29
1,322
662
395
206
44
15
55
15
2
1,549
752
484
187
97
29
1,322
662
395
206
44
15
55
15
2
1,549
752
484
187
97
29
1,322
662
395
206
44
15
* 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.
Due to the lack of data available at the time of publication, emission estimates for 2010 and 2011 rely on 2009 data
as a proxy. Emission estimates for 2009 were obtained from preliminary data (EPA 2010, EPA 2009), and
disaggregated based on EPA (2003), which, in its final iteration, will be published on the National Emission
Inventory (NEI) Air Pollutant Emission Trends web site. Due to redevelopment of the information technology
systems for the NEI, publication of the most recent emissions for these pollutants (i.e., indirect greenhouse gases)
was not available for this report.179 Emissions were calculated either for individual categories or for many
categories combined, using basic activity data (e.g., the amount of raw material processed) as an indicator of
emissions. National activity data were collected for individual categories from various agencies. Depending on the
category, these basic activity data may include data on production, fuel deliveries, raw material processed, etc.
Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
Program emissions inventory, and other EPA databases.
Uncertainties in these estimates are partly due to the accuracy of the emission factors and activity data used. A
quantitative uncertainty analysis was not performed.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
For an overview of the activities and the schedule for developing the 2011 National Emissions Inventory, with the goal of
producing Version 1 in the summer of 2013, see < http://www.epa.gov/ttn/chief/eis/201 lnei/201 lplan.pdf>
4-96 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 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 CO2 equivalent
basis in 2011 (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: NzO Emissions from Solvent and Other Product Use (Tg COz Eq. and Gg)
Gas/Source 1990 2005 . 2007 2008 2009 2010 2011
N2O from Product Uses
TgCChEq. 4.4 4.4 4.4 4.4 4.4 4.4 4.4
Gg 14 14 .•• 14 14 14 14 14
N2O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. Two companies operate a total of five
N2O production facilities in the United States (Airgas 2007; FTC 2001). N2O is primarily used in carrier gases with
oxygen to administer more potent inhalation anesthetics for general anesthesia, and as an anesthetic in various dental
and veterinary applications. As such, it is used to treat short-term pain, for sedation in minor elective surgeries, and
as an induction anesthetic. The second main use of N2O is as a propellant in pressure and aerosol products, the
largest application being pressure-packaged whipped cream. Small quantities of N2O also are used in the following
applications:
• Oxidizing agent and etchant used in semiconductor manufacturing;
• Oxidizing agent used, with acetylene, in atomic absorption spectrometry;
• Production of sodium azide, which is used to inflate airbags;
• Fuel oxidant in auto racing; and
• Oxidizing agent in blowtorches used by jewelers and others (Heydorn 1997).
Production of N2O in 2011 was approximately 15 Gg (Table 5-2).
Table 5-2: NzO Production (Gg)
Year Gg
1990 16
Solvent and Other Product Use 5-1
-------
2005 15
2007 15
2008 15
2009 15
2010 15
2011 15
N2O emissions were 4.4 Tg CO2 Eq. (14 Gg) in 2011 (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 5-3: NzO Emissions from NzO Product Usage (Tg COz Eq. and Gg)
Year
1990
2005
2007
2008
2009
2010
2011
Tg CO2 Eq.
4.4
4.4
4.4
4.4
4.4
4.4
4.4
Gg
14
14
14
14
14
14
14
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] * [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 2011, 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 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.
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Only the medical/dental and food propellant subcategories were estimated to release emissions into the atmosphere,
and therefore these subcategories were the only usage subcategories with emission rates. For the medical/dental
subcategory, due to the poor solubility of N2O in blood and other tissues, none of the N2O is assumed to be
metabolized during anesthesia and quickly leaves the body in exhaled breath. Therefore, an emission factor of 100
percent was used for this subcategory (IPCC 2006). For N2O used as a propellant in pressurized and aerosol food
products, none of the N2O is reacted during the process and all of the N2O is emitted to the atmosphere, resulting in
an emission factor of 100 percent for this subcategory (IPCC 2006). For the remaining subcategories, all of the N2O
is consumed/reacted during the process, and therefore the emission rate was considered to be zero percent (Tupman
2002).
This chapter's methodological guidance was taken from the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories. This latest guidance from the IPCC best represents the understanding of emissions profiles from
activities from solvents. The use of the most recently published calculation methodologies by the IPCC, as contained
in the 2006 IPCC Guidelines for waste source categories is fully in line with the IPCC good practice guidance for
methodological choice to improve rigor and accuracy. In addition, the improvements in using the latest
methodological guidance from the IPCC has been recognized by the UNFCCC's Subsidiary Body for Scientific and
Technological Advice in the conclusions of its 30th Session.180
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 (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 estimates for years 2004 through 2011 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 years 2004 through 2011 was assumed to equal
the 2003 value. The emissions rate for the food processing propellant industry was obtained from SRI Consulting's
Nitrous Oxide, North America report (Heydorn 1997), and confirmed by a N2O 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.
The overall uncertainty associated with the 2011 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 include production data, total market share of each
end use, and the emission factors applied to each end use, respectively.
180 These Subsidiary Body for Scientific and Technological Advice (SBSTA) conclusions state, "The SBSTA acknowledged
that the 2006 IPCC Guidelines contain the most recent scientific methodologies available to estimate emissions by sources and
removals by sinks of greenhouse gases (GHGs) not controlled by the Montreal Protocol, and recognized that Parties have gained
experience with the 2006 IPCC Guidelines. The SBSTA also acknowledged that the information contained in the 2006 IPCC
Guidelines enables Parties to further improve the quality of their GHG inventories." See
Solvent and Other Product Use 5-3
-------
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 4.1 and 4.7 Tg CO2 Eq. at the 95 percent confidence level. This
indicates a range of approximately 8 percent below to 8 percent above the emissions estimate of 4.4 Tg CO2 Eq.
Table 5-4: Tier 2 Quantitative Uncertainty Estimates for NzO Emissions from NzO Product
Usage (Tg COz Eq. and Percent)
Source
N2O Product
Usage
Gas 2011 Emission
Estimate
(Tg C02 Eq.)
N2O 4.4
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Upper Lower
Bound Bound Bound
4.1 4.7 -8%
Upper
Bound
+8%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence
interval.
Furthermore, methodological recalculations were applied to the entire time-series to ensure time-series consistency
from 1990 through 2011. Details on the emission trends through time-series are described in more detail in the
Methodology section, above.
Planned improvements include a continued evaluation of alternative production statistics for cross verification, a
reassessment of N2O product use subcategories to accurately represent trends, investigation of production and use
cycles, and the potential need to incorporate a time lag between production and ultimate product use and resulting
release of N2O. Additionally, planned improvements include considering imports and exports of N2O for product
uses.
Future inventories will examine data from EPA's GHGPJ3 to improve the emission estimates for the N2O product
use subcategory. Particular attention will be made to ensure time series consistency, as the facility-level reporting
data from EPA's GHGRP are not available for all inventory years as reported in this Inventory.
The use of solvents and other chemical products can result in emissions of various ozone precursors (i.e., indirect
greenhouse gases).181 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 2011 are reported in Table 5-5.
181 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: 1990-2011
-------
Table 5-5: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg)
Activity
NOx
Surface Coating
Graphic Arts
Degreasing
Dry Cleaning
Other Industrial
Processes*
Non-Industrial
Processes'5
Other
CO
Surface Coating
Other Industrial
Processes*
Dry Cleaning
Degreasing
Graphic Arts
Non-Industrial
Processes'5
Other
NMVOCs
Surface Coating
Non-Industrial
Processes'5
Degreasing
Dry Cleaning
Graphic Arts
Other Industrial
Processes*
Other
1990
1
1 '
+
+
+
+
+
NA
5
+
4
+
+
+
+
NA
5,216
2,289
1,724 -
675
195
249
85
+
2005
3
3
+
+
+
+
+ /
+
2
2 /
+
+ /
+
+
+
+
3,851
1,578
1,446
280 /
230
194
88 /
36
: 2007
4
4
+
+
+
+
+
+
2
2
+
+
+
+
+
+
3,839
1,573
1,441
280
229
193
87
36
2008
4
4
+
+
+
+
+
+
2
2
+
+
+
+
+
+
3,834
1,571
1,439
279
229
193
87
36
2009
3
3
+
+
+
+
+
+
2
2
+
+
+
+
+
+
2,583
1,058
970
188
154
130
59
24
2010
3
3
+
+
+
+
+
+
2
2
+
+
+
+
+
+
2,583
1,058
970
188
154
130
59
24
2011
3
3
+
+
+
+
+
+
2
2
+
+
+
+
+
+
2,583
1,058
970
188
154
130
59
24
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.
NA: Not available
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.
Due to the lack of data available at the time of publication, emission estimates for 2010 and 2011 rely on 2009 data
as a proxy. Emission estimates for 2009 were obtained from preliminary data (EPA 2010, EPA 2009), and
disaggregated based on EPA (2003), which, in its final iteration, will be published on the National Emission
Inventory (NEI) Air Pollutant Emission Trends web site. Due to redevelopment of the information technology
systems for the NEI, publication of the most recent emissions for these pollutants (i.e., indirect greenhouse gases)
Solvent and Other Product Use 5-5
-------
was not available for this report.182 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.
and
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.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
182 por an overview of the activities and the schedule for developing the 2011 National Emissions Inventory, with the goal of
producing Version 1 in the summer of 2013, see < http://www.epa.gov/ttn/chief/eis/201 lnei/201 lplan.pdf>
5-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 liming of agricultural soils and conversion of grassland to cultivated
land, are presented in the Land Use, Land-Use Change, and Forestry chapter. Carbon dioxide emissions from on-
farm energy use are accounted for in the Energy chapter.
Figure 6-1: 2011 Agriculture Chapter Greenhouse Gas Emission Sources
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation •
Field Burning of Agricultural Residues < 0,5
Agriculture as a Portion of all
Emissions
6,9%
0
25 50 75 100 125 150 175
Tg C02 Eq,
200 225 250 275
In 2011, the Agriculture sector was responsible for emissions of 461.5 teragrams of CO2 equivalents (Tg CO2 Eq.),
or 6.9 percent of total U.S. greenhouse gas emissions. Methane (CH4) and nitrous oxide (N2O) were the primary
greenhouse gases emitted by agricultural activities. Methane emissions from enteric fermentation and manure
management represent about 23 percent and 9 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 69 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 2011, CH4
emissions from agricultural activities increased by 14.4 percent, while N2O emissions fluctuated from year to year,
but overall increased by 9.5 percent.
Agriculture 6-1
-------
Table 6-1: Emissions from Agriculture (Tg COz 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
171.
5
132. '
7 '
31.5
7.1
0.2 ••
242.
3
227. •
9
14.4 . ,
0.1 '.•
413.
9
2005
191.5 ,
* 137.0 /_
' 47.6 „
6.8 ••'„
0.2 ':
254.7 J
237.5 _
17.1
0.1 ,_
446.2 »
2007
i 200.5
: 141.8
* 52.4
6.2
0.2
i
k 270.4
„ 252.3
18.0
0.1
si 470.9
2008
200.3
141.4
51.5
7.2
0.2
263.3
245.4
17.8
0.1
463.6
2009
198.6
140.6
50.5
7.3
0.2
260.6
242.8
17.7
0.1
459.2
2010
199.9
139.3
51.8
8.6
0.2
262.4
244.5
17.8
0.1
462.3
2011
196.
3
137.
4
52.0
6.6
0.2
265.
2
247.
2
18.0
0.1
461.
5
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
Field Burning of Agricultural Residues
N20
Agricultural Soil Management
Manure Management
Field Burning of Agricultural Residues
1990
8,169
6,321
1,499
339 '
10 ..
782
735
46
+
2005
9,121
6,522 ,«
2,265
326 •*
8 -
821 *
766 .«
55
+ J
2007
9,550
i 6,751
2,493
295
11
872
814
58
111 -+-
2008
9,537
6,731
2,452
343
11
849
792
57
+
2009
9,456
6,693
2,403
349
11
841
783
57
+
2010
9,519
6,632
2,466
410
11
846
789
57
+
2011
9,345
6,542
2,478
316
10
856
797
58
+
+ Lessthan0.5Gg.
Note: Totals may not sum due to independent rounding.
Methane is produced as part of normal digestive processes in animals. During digestion, microbes resident in an
animal's digestive system ferment food consumed by the animal. This microbial fermentation process, referred to as
enteric fermentation, produces CH4 as a byproduct, 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.
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Non-ruminant animals (e.g., swine, horses, and mules) also produce CH4 emissions through enteric fermentation,
although this microbial fermentation occurs in the large intestine. These non-ruminants emit significantly less CH4
on a per-animal basis than ruminants because the capacity of the large intestine to produce CH4 is lower.
In addition to the type of digestive system, an animal's feed quality and feed intake also affect CH4 emissions. In
general, lower feed quality and/or higher feed intake leads to higher CH4 emissions. Feed intake is positively
correlated to animal size, growth rate, and production (e.g., milk production, wool growth, pregnancy, or work).
Therefore, feed intake varies among animal types as well as among different management practices for individual
animal types (e.g., animals in feedlots or grazing on pasture).
Methane emission estimates from enteric fermentation are provided in Table 6-3 and Table 6-4.
Total livestock CH4 emissions in 2011 were 137.4 TgCChEq. (6,542 Gg). Beef cattle remain the largest
contributor of CH4 emissions from enteric fermentation, accounting for 72 percent in 2011. Emissions from dairy
cattle in 2011 accounted for 24 percent, and the remaining emissions were from horses, sheep, swine, goats,
American bison, mules, burros, and donkeys.
From 1990 to 2011, emissions from enteric fermentation have increased by 3.5 percent, and generally follow trends
in cattle populations, although while emissions from beef cattle increased 3 percent from 1990 to 2011, production
of beef increased 16 percent, and while dairy emissions increased 5 percent over the entire time series, milk
production increased 33 percent. This indicates that while emission factors per head are increasing, emission factors
per unit of product are going down. Generally, from 1990 to 1995 emissions increased and then decreased from
1996 to 2001. These trends were mainly due to fluctuations in beef cattle populations and increased digestibility of
feed for feedlot cattle. Emissions generally increased from 2002 to 2007, though with a slight decrease in 2004, as
both dairy and beef populations underwent increases and the literature for dairy cow diets indicated a trend toward a
decrease in feed digestibility for those years. Emissions decreased again from 2008 to 2011 as beef cattle
populations again decreased. Regarding trends in other animals, during the timeframe of this analysis, populations
of sheep have decreased 52 percent while horse populations have more than doubled, with each annual increase
ranging from about 2 to 6 percent. Goat and swine populations have increased 25 percent and 22 percent,
respectively, during this timeframe, though with some slight annual decreases. The populations of American bison
and mules, burros, and donkeys have nearly tripled and quadrupled, respectively.
Table 6-3: ChU Emissions from Enteric Fermentation (Tg COz Eq.)
Livestock Type
Beef Cattle
Dairy Cattle
Swine
Horses
Sheep
Goats
American Bison
Mules, Burros,
and Donkeys
Total
1990
96.2
31.8
1.7
0.8
1.9
0.3
0.1
+
132.7
2005
101.4
,
-------
American Bison 4 „ 17 „ 16 17 17 16 13
Mules, Burros, and
Donkeys 1 2 3 3 3 3 3_
Total 6,321 6,522 6,751 6,731 6,693 6,632 6,542
Note: Totals may not sum due to independent rounding.
Livestock emission estimate methodologies fall into two categories: cattle and other domesticated animals. Cattle,
due to their large population, large size, and particular digestive characteristics, account for the majority of CH4
emissions from livestock in the United States. A more detailed methodology (i.e., IPCC Tier 2) was therefore
applied to estimate emissions for all cattle. Emission estimates for other domesticated animals (horses, sheep,
swine, goats, American bison, and mules, burros, and donkeys) were handled using a less detailed approach (i.e.,
IPCC Tier 1).
While the large diversity of animal management practices cannot be precisely characterized and evaluated,
significant scientific literature exists that provides the necessary data to estimate cattle emissions using the IPCC
Tier 2 approach. The Cattle Enteric Fermentation Model (CEFM), developed by EPA and used to estimate cattle
CH4 emissions from enteric fermentation, incorporates this information and other analyses of livestock population,
feeding practices, and production characteristics.
National cattle population statistics were disaggregated into the following cattle sub-populations:
• Dairy Cattle
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 Steer)
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
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 (NASS) QuickStats database (USDA 2012).
Diet characteristics were estimated by region for U.S. dairy, foraging beef, and feedlot beef 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 ranges 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. 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 and scientific literature,
expert opinion, and modeling of animal physiology.
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
The diet characteristics for dairy cattle were based on Donovan (1999) and an extensive review of nearly 20 years of
literature from 1990 through 2009. Estimates of DE were national averages based on the feed components of the
diets observed in the literature for the following year groupings: 1990-1993, 1994-1998, 1999-2003, 2004-2006,
2007, and 2008 onwards.183 Base year Ym values by region were estimated using Donovan (1999). A ruminant
digestion model (COWPOLL, as selected in Kebreab et al. 2008) was used to evaluate Ym for each diet evaluated
from the literature, and a function was developed to adjust regional values over time based on the national trend.
Dairy replacement heifer diet assumptions were based on the observed relationship in the literature between dairy
cow and dairy heifer diet characteristics.
For feedlot animals, the DE and Ym values used for 1990 were recommended by Johnson (1999). Values for DE
and Ym for 1991 through 1999 were linearly extrapolated based on the 1990 and 2000 data. DE and Ym values for
2000 onwards were based on survey data in Galyean and Gleghorn (2001) and Vasconcelos and Galyean (2007).
For grazing beef cattle, Ym values were based on Johnson (2002), DE values for 1990 through 2006 were based on
specific diet components estimated from Donovan (1999), and DE values from 2007 onwards were developed from
an analysis by Archibeque (2011), based on diet information in Preston (2010) and USDA:APHIS:VS (2010).
Weight and weight gains for cattle were estimated from Holstein (2010), Doren et al. (1989), Enns (2008), Lippke et
al. (2000), Pinchack et al. (2004), Platter et al. (2003), Skogerboe et al. (2000), and expert opinion. See Annex 3.9
for more details on the method used to characterize cattle diets and weights in the United States.
To estimate CH4 emissions from all cattle types except calves 6 months and younger,184 the population was divided
into state, age, sub-type (i.e., dairy cows and replacements, beef cows and replacements, heifer and steer stackers,
heifers and steers in feedlots, and bulls), and production (i.e., pregnant, lactating) groupings to more fully capture
differences in CH4 emissions from these animal types. The transition matrix was used to simulate the age and
weight structure of each sub-type on a monthly basis, to more accurately reflect the fluctuations that occur
throughout the year. Cattle diet characteristics were then used in conjunction with Tier 2 equations from IPCC
(2006) to produce CH4 emission factors for the following cattle types: dairy cows, beef cows, dairy replacements,
beef replacements, steer stackers, heifer stackers, steer feedlot animals, heifer feedlot animals, and bulls. To
estimate emissions from cattle, monthly population data from the transition matrix were multiplied by the calculated
emission factor for each cattle type. More details are provided in Annex 3.9.
Emission estimates for other animal types were based on average emission factors representative of entire
populations of each animal type. Methane emissions from these animals accounted for a minor portion of total CH4
emissions from livestock in the United States from 1990 through 2011. 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 sheep, swine, and horses were obtained for all
years from USDA NASS (USDA 2012). Horse data were not available before the 1997 census and beyond the 2007
census, so the available data were extrapolated back for 1990 through 1996 and forward for 2008 through 2011.
Data between census years were interpolated between the available data points. Goat and mule, burro, and donkey
population data were available for 1987, 1992, 1997, 2002, and 2007 (USDA 1992, 1997, 2012); the remaining
years between 1990 and 2011 were interpolated and extrapolated from the available estimates. American bison
population estimates were available from USDA for 2002 and 2007 (USDA 2012) and from the National Bison
Association (1999) for 1997 through 1999. Additional years were based on observed trends from the National Bison
Association (1999), interpolation between known data points, and ratios of population to slaughter statistics (USDA
2012), as described in more detail in Annex 3.9. Methane emissions from sheep, goats, swine, horses, American
bison, and mules, burros, and donkeys 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. For American bison the emission factor for buffalo was used and adjusted
based on the ratio of live weights to the 0.75 power. The methodology is the same as that recommended by IPCC
(2006).
183 Due to inconsistencies in the 2003 literature values, the 2002 values were used for 2003, as well.
Because calves consume mainly milk and the IPCC recommends the use of a methane conversion factor of zero for all
juveniles consuming only milk, this results in no methane emissions from this subcategory of cattle.
Agriculture 6-5
-------
See Annex 3.9 for more detailed information on the methodology and data used to calculate CH4 emissions from
enteric fermentation.
A quantitative uncertainty analysis for this source category was performed using 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. There have been no
significant changes to the methodology, although the source of some input variables have been updated, at this time
there are not better estimates available for the uncertainty ranges around the 2011 activity data and emission factor
input variables used in the current submission. Consequently, these uncertainty estimates were directly applied to
the 2011 emission estimates.
A total of 185 primary input variables (177 for cattle and 8 for non-cattle) were identified as key input variables for
the uncertainty analysis. A normal distribution was assumed for almost all activity- and emission factor-related
input variables. Triangular distributions were assigned to three input variables (specifically, cow-birth ratios for the
three most recent years included in the 2001 model run) to ensure only positive values would be simulated. 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 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 are summarized in Table 6-5.
Based on this analysis, enteric fermentation CH4 emissions in 2011 were estimated to be between 122.3 and 162.1
Tg CO2 Eq. at a 95 percent confidence level, which indicates a range of 11 percent below to 18 percent above the
2011 emission estimate of 137.4 TgCOaEq. 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 emission estimates.
Among non-cattle, horses represent the largest percent of uncertainty in the previous uncertainty analysis because
the FAO population estimates used for horses at that time had a higher degree of uncertainty than for the USD A
population estimates used for swine, goats, and sheep. The horse populations are now from the same USDA source
as the other animal types, and therefore the uncertainty range around horses is likely overestimated. American
bison, mules, burros, and donkeys were excluded from the initial uncertainty estimate because they were not
included in the estimate of emissions at that time, although because of their small populations they would not
significantly increase the uncertainty estimate ranges of the overall emissions from enteric fermentation.
Table 6-5: Quantitative Uncertainty Estimates for ChU Emissions from Enteric Fermentation
(Tg COz Eq. and Percent)
Source Gas 2011 Emission
Estimate
(Tg C02 Eq.)
Enteric Fermentation CFLi 137.4
Uncertainty Range Relative to Emission Estimate3' b> c
(Tg C02 Eq.) (%)
Lower
Bound
122.3
Upper
Bound
162.1
Lower
Bound
-11%
Upper
Bound
+18%
1 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 the 2011 estimates.
c The overall uncertainty calculated in 2003, and applied to the 2011 emission estimate, did not include uncertainty
estimates for American bison, mules, burros, and donkeys, and was based on the Tier 1 methodology for bulls.
Consequently, there was more uncertainty with bull emissions than with other cattle types.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section.
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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. Recent updates to the foraging
portion of the diet values for cattle made this the area of emphasis for QA/QC this year, with specific attention to the
data sources and comparisons of the current estimates with previous estimates.
In addition, over the past few years, particular importance has been placed on harmonizing the data exchange
between the enteric fermentation and manure management source categories. The current inventory submission now
utilizes the transition matrix from the CEFM for estimating cattle populations and weights for both source
categories, and the CEFM is used to output volatile solids and nitrogen (N) excretion estimates using the diet
assumptions in the model in conjunction with the energy balance equations from the IPCC (2006). This approach
facilitates the QA/QC process for both of these source categories.
There were no modifications to the methodology that had an effect on emission estimates, therefore the only
recalculations were due to changes in activity data, including the following:
• In the previous Inventory, the 2003 dairy DE had an anomalous shift in data that did not mimic actual feeding
conditions. In order to create a more realistic time series, the 2003 data point was dropped and the previous data
point was extended for an extra year. This change increased dairy cattle emissions by 110 Gg (8.1 percent) in
2003.
• The USDA published minor revisions in several categories that affected historical emissions estimated for cattle
in 2010, including dairy cow milk production for several states, and beef replacement heifer populations. .
These changes had an insignificant impact on the overall results.
• There were additional population changes for sheep in 2009 and 2010 and swine for 2010. Historical emission
estimates for sheep increased less than 1 percent per year compared to the previous emission estimates for the
years mentioned above. Swine population changes resulted in an increase in emissions of 0.1 percent.
• In this Inventory horse populations have been estimated from USDA census data available via Quickstats
(USDA 2012), while in the previous Inventory, population estimates were from FAO (2011). New data were
chosen to reduce high levels of uncertainty that exist with the FAO data. Populations and emission estimates
have declined by about 50 percent from previous estimates from 1990 through 2010 as a result of this change.
Continued research and regular updates are necessary to maintain an emissions inventory that reflects the current
base of knowledge. Ongoing revisions for enteric fermentation could include some of the following options:
• Updating input variables that are from older data sources, such as beef births by month and beef cow lactation
rates;
• Investigation of the availability of annual data for the DE and crude protein values of specific diet and feed
components for foraging and feedlot animals;
• Reevaluation of the appropriate age to begin inclusion of enteric fermentation emissions from calves;
• Given the many challenges in characterizing dairy diets, further investigation will be conducted on additional
sources or methodologies for estimating DE for dairy;
• The possible breakout of other animal types (i.e., sheep, swine, goats, horses) from national estimates to state-
level estimates or updating to Tier 2 methodology; and
• The investigation of methodologies for including enteric fermentation emission estimates from poultry.
Agriculture 6-7
-------
In addition, recent changes that have been implemented to the CEFM warrant an assessment of the current
uncertainty analysis; therefore, a revision of the quantitative uncertainty surrounding emission estimates from this
source category will be initiated.
6.2
The management of livestock manure can produce anthropogenic CH4 and N2O emissions. Methane is produced by
the anaerobic decomposition of manure. Direct N2O emissions are produced as part of the N cycle through the
nitrification and denitrification of the organic N in livestock dung and urine.185 Indirect N2O emissions are produced
as result of the volatilization of N as NH3 and NOX and runoff and leaching of N during treatment, storage and
transportation.
When livestock or poultry manure are stored or treated in systems that promote anaerobic conditions (e.g., as a
liquid/slurry in lagoons, ponds, tanks, or pits), the decomposition of materials in the manure tends to produce CH4.
When manure is handled as a solid (e.g., in stacks or drylots) or deposited on pasture, range, or paddock lands, it
tends to decompose aerobically and produce little or no CH4. Ambient temperature, moisture, and manure storage
or residency time affect the amount of CH4 produced because they influence the growth of the bacteria responsible
for CH4 formation. For non-liquid-based manure systems, moist conditions (which are a function of rainfall and
humidity) can promote CH4 production. Manure composition, which varies by animal diet, growth rate, and type,
including the animal's digestive system, also affects the amount of CH4produced. 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 N is
converted to nitrates and nitrites (nitrification), and then handled anaerobically where the nitrates and nitrites are
reduced to dinitrogen gas (N2), with intermediate production of N2O and nitric oxide (NO) (denitrification)
(Groffman et al. 2000). These emissions are most likely to occur in dry manure handling systems that have aerobic
conditions, but that also contain pockets of anaerobic conditions due to saturation. A very small portion of the total
N excreted is expected to convert to N2O in the waste management system (WMS). Indirect N2O emissions are
produced when 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 due
to differences in manure characteristics. Little information is known about leaching from manure management
systems as most research focuses on leaching from land application systems. Since leaching losses are expected to
be minimal, leaching losses are coupled with runoff losses and the runoff/leaching estimate does not include any
leaching losses.
Estimates of CH4 emissions in 2011 were 52.0 Tg CO2 Eq. (2,478 Gg), 65 percent higher than in 1990. Emissions
increased on average by 1.0 Tg CO2 Eq. (3.0 percent) annually over this period. The majority of this increase was
from swine and dairy cow manure, where emissions increased 51 and 111 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
*-°* Direct and indirect N2O emissions from dung 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 dung 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.
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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,
2002, and 2007 farm-size distribution data reported in the Census of Agriculture (USDA 2009a). Methane
emissions from sheep have decreased significantly since 1990 (a 56 percent decrease from 1990 to 2011); however,
this is mainly due to population changes. Overall, sheep contribute less than one percent of CH4 emissions from
animal manure management. From 2010 to 2011, there was a 0.5 percent increase in total CH4 emissions, mainly
due to minor shifts in the animal populations and the resultant effects on manure management system allocations.
In 2011, total N2O emissions were estimated to be 18.0 Tg CO2 Eq. (58 Gg); in 1990, emissions were 14.4 Tg CO2
Eq. (46 Gg). These values include both direct and indirect N2O emissions from manure management. Nitrous oxide
emissions have remained fairly steady since 1990. Small changes in N2O emissions from individual animal groups
exhibit the same trends as the animal group populations, with the overall net effect that N2O emissions showed a 25
percent increase from 1990 to 2011 and a 1.3 percent increase from 2010 through 2011.
Table 6-6 and Table 6-7 provide estimates of CH4 and N2O emissions from manure management by animal
category.
Table 6-6: Cm and NzO Emissions from Manure Management (Tg COz Eq.)
Gas/Animal Type
CH4a
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Bison
Mules and Asses
N2Ob
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Bison
Mules and Asses
Total
1990
31.5
12.6
2.7 /
13.1
0.1
+
2.8.
0.2
+
+ /
14.4
5.3
6.1 /
1.2 /
0.1
+
1.5 /
O.I/
NA
+
45.8
2005
47.6
22.4
2.8
19.2
0.1 .
2.7.;
0.3:*
+
+
17.1
5.7,
7.4
1.8
0.4
+
1.7
0.1
NA
+
, 64.6
2007
52.4
,J 25.7
2.9
-; 20.6
0.1
- * +
2.8
0.2
Jl +
+
18.0
5.9
7.9
2.0
0.4
+
1.7
0.1
NA
+
X 70.3
2008
51.5
26.0
2.8
19.7
0.1
+
2.7
0.2
+
+
17.8
5.8
7.8
2.0
0.4
+
1.7
0.1
NA
+
69.3
2009
50.5
25.9
2.7
18.8
0.1
+
2.7
0.2
+
+
17.7
5.8
7.8
2.0
0.3
+
1.6
0.2
NA
+
68.2
2010
51.8
26.0
2.8
19.9
0.1
+
2.7
0.2
+
+
17.8
5.9
7.8
1.9
0.3
+
1.6
0.2
NA
+
69.5
2011
52.0
26.5
2.8
19.8
0.1
+
2.7
0.2
+
+
18.0
5.9
8.0
2.0
0.3
+
1.6
0.2
NA
+
70.0
+ Less than 0.05 Tg CO2 Eq.
aAccounts for CH4 reductions due to capture and destruction of CH4 at facilities using
anaerobic digesters.
Includes both direct and indirect N2O emissions.
Note: Totals may not sum due to independent rounding. Bison are maintained entirely on
unmanaged WMS; there are no bison N2O emissions from managed systems.
Table 6-7: ChU and NzO Emissions from Manure Management (Gg)
Gas/Animal Type
1990
2005
2007 2008 2009 2010 2011
CH4a
1,499
2,265
2,493 2,452 2,403 2,466 2,478
Agriculture 6-9
-------
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Bison
Mules and Asses
N20b
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Bison
Mules and Asses
599
128'
624
7
1
131'
9
+
+
46
17
20
4
+
+
5
+
NA'
+
1,069
135 .,*
914
3 •»
1
129 '
12 ;
+ ;
+ ,J
55
18, _
24 "
6 -
1 _
+ ,
5 ,
+
NA""
+
1,224
1 136
982
3
1
134
11
+
1 +
58
19
26
6
1
+
5
+
NA
+
1,238
132
938
3
1
129
10
+
+
57
19
25
6
1
+
5
+
NA
+
1,233
131
896
3
1
128
11
+
+
57
19
25
6
1
+
5
+
NA
+
1,239
134
948
3
1
129
11
+
+
57
19
25
6
1
+
5
+
NA
+
1,262
132
941
3
1
127
11
+
+
58
19
26
6
1
+
5
+
NA
+
+ Less than 0.5 Gg.
aAccounts for CH4 reductions due to capture and destruction of CH4 at facilities using
anaerobic digesters.
Includes both direct and indirect N2O emissions.
Note: Totals may not sum due to independent rounding Bison are maintained entirely on
unmanaged WMS; there are no bison N2O emissions from managed systems.
NA: Not available
The methodologies presented in IPCC (2006) form the basis of the CH4 and N2O emission estimates for each animal
type. This section presents a summary of the methodologies used to estimate CH4 and N2O emissions from manure
management. See Annex 3.10 for more detailed information on the methodology and data used to calculate CH4 and
N2O emissions from manure management.
Methane Calculation Methods
The following inputs were used in the calculation of CH4 emissions:
• Animal population data (by animal type and state);
• Typical animal mass (TAM) data (by animal type);
• Portion of manure managed in each WMS, by state and animal type;
• Volatile solids (VS) production rate (by animal type and state or United States);
• Methane producing potential (B0) of the volatile solids (by animal type); and
• Methane conversion factors (MCF), the extent to which the CH4 producing potential is realized for each
type of WMS (by state and manure management system, including the impacts of any biogas collection
efforts).
Methane emissions were estimated by first determining activity data, including animal population, TAM, WMS
usage, and waste characteristics. The activity data sources are described below:
• Annual animal population data for 1990 through 2011 for all livestock types, except goats, horses, mules
and asses, and bison were obtained from USDA National Agriculture Statistics Service (NASS). For cattle,
the USDA populations were utilized in conjunction with birth rates, detailed feedlot placement information,
and slaughter weight data to create the transition matrix in the CEFM 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 Section 6.1 and in more detail in Annex 3.9. Goat population data
for 1992, 1997, 2002, and 2007, horse and mule and ass population data for 1997, 2002 and 2007, and
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
bison population for 2002 and 2007 were obtained from the Census of Agriculture (USDA 2009a). Bison
population data for 1990-1999 were obtained from the National Bison Association (1999).
• The TAM is an annual average weight which was obtained for animal types other than cattle from
information in USD A' sAgricultur al Waste Management Field Handbook (USDA 1996), the American
Society of Agricultural Engineers, Standard D384.1 (ASAE 1999) and others (Meagher 1986, EPA 1992,
Safley 2000, IPCC 2006, ERG 2010a). For a description of the TAM used for cattle, please see section 6.1,
Enteric Fermentation.
• WMS usage was estimated for swine and dairy cattle for different farm size categories using data from
USDA (USDA, APHIS 1996, Bush 1998, Ott 2000, USDA 2009a) 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: APHIS 2000, UEP 1999). For other animal types,
manure management system usage was based on previous estimates (EPA 1992). Bison WMS usage was
assumed to be the same as not on feed (NOF) cattle, while mules and asses were assumed to be the same as
horses.
• VS production rates for all cattle except for bulls and calves were calculated by head for each state and
animal type in the CEFM. VS production rates by animal mass for all other animals were determined using
data fromUSDA's Agricultural Waste Management Field Handbook (USDA 1996, 2008 and ERG 2010b
and 2010c) and data that was not available in the most recent Handbook were obtained from the American
Society of Agricultural Engineers, Standard D384.1 (ASAE 1998) or the 2006 IPCC Guidelines. Bison VS
production was assumed to be the same as NOF bulls.
• The maximum CH4 producing capacity of the VS (B0) was determined for each animal type based on
literature values (Morris 1976, Bryant et al, 1976, Hashimoto 1981, Hashimoto 1984, EPA 1992, Hill 1982,
and Hill 1984).
• MCFs for dry systems were set equal to default IPCC factors based on state climate for each year (IPCC
2006). MCFs for liquid/slurry, anaerobic lagoon, and deep pit systems were calculated based on the
forecast performance of biological systems relative to temperature changes as predicted in the van't Hoff-
Arrhenius equation which is consistent with IPCC (2006) Tier 2 methodology.
• Anaerobic digestion system data were obtained from the EPA AgSTAR Program, including information
presented in the AgSTAR Digest (EPA 2000, 2003, 2006) and the AgSTAR project database (EPA 2012).
Anaerobic digester emissions were calculated based on estimated methane production and collection and
destruction efficiency assumptions (ERG 2008).
To estimate CH4 emissions for cattle and bison, the estimated amount of VS (kg per animal-year) managed in each
WMS for each animal type, state, and year were taken from the CEFM. For animals other than cattle, the annual
amount of VS (kg per year) from manure excreted in each WMS was calculated for each animal type, state, and
year. This calculation multiplied the animal population (head) by the VS excretion rate (kg VS per 1,000 kg animal
mass per day), the TAM (kg animal mass per head) divided by 1,000, the WMS distribution (percent), and the
number of days per year (365.25).
The estimated amount of VS managed in each WMS was used to estimate the CH4 emissions (kg CH4 per year)
from each WMS. The amount of VS (kg per year) were multiplied by the maximum CH4 producing capacity of the
VS (B0) (m3 CH4 per kg VS), the MCF for that WMS (percent), and the density of CH4 (kg CH4per m3 CH4). The
CH4 emissions for each WMS, state, and animal type were summed to determine the total U.S. CH4 emissions.
Nitrous Oxide Calculation Methods
The following inputs were used in the calculation of direct and indirect N2O emissions:
• Animal population data (by animal type and state);
• TAM data (by animal type);
• Portion of manure managed in each WMS (by state and animal type);
• Total Kjeldahl N excretion rate (Nex);
• Direct N2O emission factor (EFWMs);
• Indirect N2O emission factor for volitalization (EFvoiitaiization);
Agriculture 6-11
-------
Indirect N2O emission factor for runoff and leaching
Fraction of N loss from volitalization of NH3 and NOX (Fracgas); and
Fraction of N loss from runoff and leaching
N2O emissions were estimated by first determining activity data, including animal population, TAM, WMS usage,
and waste characteristics. The activity data sources (except for population, TAM, and WMS, which were described
above) are described below:
• Nex rates for all cattle except for bulls and calves were calculated by head for each state and animal type in
the CEFM. Nex rates by animal mass for all other animals were determined using data from USDA's
Agricultural Waste Management Field Handbook (USDA 1996, 2008 and ERG 2010b and 2010c) and data
from the American Society of Agricultural Engineers, Standard D384. 1 (ASAE 1998) and IPCC (2006).
Bison Nex rates were assumed to be the same as NOF bulls.
• All N2O emission factors (direct and indirect) were taken from IPCC (2006). These data are appropriate
because they were developed using U.S. data.
• Country -specific estimates for the fraction of N loss from volatilization (Fracgas) and runoff and leaching
(Fracnmoff/ieach) were developed. Fracgas values were based on WMS-specific volatilization values as
estimated from EPA's National Emission Inventory -Ammonia Emissions from Animal Agriculture
Operations (EPA 2005). FraCnmoff/ieachmg values were based on regional cattle runoff data from EPA's
Office of Water (EPA 2002b; see Annex 3.1).
To estimate N2O emissions for cattle and bison, the estimated amount of N excreted (kg per animal -year) managed
in each WMS for each animal type, state, and year were taken from the CEFM. For animals other than cattle, the
amount of N excreted (kg per year) in manure in each WMS for each animal type, state, and year was calculated.
The population (head) for each state and animal was multiplied by TAM (kg animal mass per head) divided by
1,000, the nitrogen excretion rate (Nex, in kg N per 1000 kg animal mass per day), WMS distribution (percent), and
the number of days per year.
Direct N2O emissions were calculated by multiplying the amount of N excreted (kg per year) in each WMS by the
N2O direct emission factor for that WMS (EFmis, in kg N2O-N per kg N) and the conversion factor of N2O-N to
N2O. These emissions were summed over state, animal, and WMS to determine the total direct N2O emissions (kg of
N2O per year).
Next, indirect N2O emissions from volatilization (kg N2O per year) were calculated by multiplying the amount of N
excreted (kg per year) in each WMS by the fraction of N lost through volatilization (Fractas) divided by 100, and the
emission factor for volatilization (EFvoiatiiization, in kg N2O per kg N), and the conversion factor of N2O-N to N2O.
Indirect N2O emissions from runoff and leaching (kg N2O per year) were then calculated by multiplying the amount
of N excreted (kg per year) in each WMS by the fraction of N lost through runoff and leaching (FraCnmoff/ieach)
divided by 100, and the emission factor for runoff and leaching (EFrunoff/ieach, in kg N2O per kg N), and the
conversion factor of N2O-N to N2O. The indirect N2O emissions from volatilization and runoff and leaching were
summed to determine the total indirect N2O emissions.
The direct and indirect N2O emissions were summed to determine total N2O emissions (kg N2O per year).
and
An analysis (ERG 2003) was conducted for the manure management emission estimates presented in the 1990
through 2001 Inventory report 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. These uncertainty estimates were directly applied to the 201 1 emission estimates.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 6-8. Manure management CH4
emissions in 201 1 were estimated to be between 42.7 and 62.4 Tg CO2 Eq. at a 95 percent confidence level, which
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
indicates a range of 18 percent below to 20 percent above the actual 2011 emission estimate of 52.0 Tg COa Eq. At
the 95 percent confidence level, N2O emissions were estimated to be between 15.1 and 22.3 Tg COa Eq. (or
approximately 16 percent below and 24 percent above the actual 2011 emission estimate of 18.0 TgCChEq.).
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for ChU and NzO (Direct and Indirect)
Emissions from Manure Management (Tg COz Eq. and Percent)
2011 Emission
Source Gas Estimate
(Tg C02 Eq.)
Manure Management CH4 52.0
Manure Management N2O 18.0
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower
Bound
42.7
15.1
Upper
Bound
62.4
22.3
Lower
Bound
-18%
-16%
Upper
Bound
+20%
+24%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
and
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 emissions from managed systems and CH4
emissions from livestock manure. All errors identified were corrected. Order of magnitude checks were also
conducted, and corrections made where needed. Manure N data were checked by comparing state-level data with
bottom up estimates derived at the county level and summed to the state level. Similarly, a comparison was made
by animal and WMS type for the full time series, between national level estimates for N excreted and the sum of
county estimates for the full time series.
Any updated data, including population, are validated by experts to ensure the changes are representative of the best
available U.S. specific data. The U.S. specific values for TAM, Nex, VS, B0, and MCF were also compared to the
IPCC default values and validated by experts. Although significant differences exist in some instances, these
differences are due to the use of U.S. specific data and the differences in U.S. agriculture as compared to other
countries. The U.S. manure management emission estimates use the most reliable country-specific data, which are
more representative of U.S. animals and systems than the IPPC default values.
For additional verification, the implied CH4 emission factors for manure management (kg of CH4 per head per year)
were considered. Table 6-9 presents the implied emission factors of kg of CH4 per head per year used for the
manure management emission estimates as well as the IPCC default emission factors. The U.S. implied emission
factors fall within the range of the IPCC default values, except in the case of sheep, goats, and some years for horses
and dairy cattle. The U.S. implied emission factors are greater than the IPCC default value for those animals due to
the use of U.S.-specific data for typical animal mass and VS excretion. There is an increase in implied emission
factors for dairy and swine across the time series. This increase reflects the dairy and swine industry trend towards
larger farm sizes; large farms are more likely to manage manure as a liquid and therefore produce more CH4
emissions.
Table 6-9: Implied Emission Factors for ChU from Manure Management (kg/head/year)
Animal Type
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Mules and Asses
Bison
IPCC
48-112
1-2
10-45
0.19-0.37
0.13-0.26
0.02-1.4
1.56-3.13
0.76-1.14
NA
Implied
1990 ,
42.3
1.5
11.6
0.6
0.4
0.1
4.2
0.1
1.8
CH4 Emission
1995 «
51.0 -i
1.5
13.0
0.6 -
0.3
0.1
4.1 •
0.1
1.9
Factors
2000
68.2
1.5
14.2 /
0.6 -
0.3
0.1 /
3.9
0.1 ,
1.9/
(kg/head/year)
: 2005 :
81.2
1.6
15.0 /
0.6 -
0.3
0.1 / .
3.1
0.1 ..
2.0
2010
91.0
1.6
14.6
0.5
0.3
0.1
2.6
0.1
2.1
2011
92.2
1.6
14.3
0.5
0.3
0.1
2.6
0.1
2.1
Agriculture 6-13
-------
In addition, IPCC emission factors for N2O were compared to the U.S. inventory implied N2O emission factors.
Default N2O emission factors from the 2006 IPCC were used to estimate N2O emission from each WMS in
conjunction with U.S.-specific Nex values. The implied emission factors differed from the U.S. inventory values due
to the use of U.S.-specific Nex values and differences in populations present in each WMS throughout the time
series.
The CEFM produces population, VS and Nex data for cattle that are used in the manure management inventory. As
a result, all changes to the CEFM described in Section 6.1 Enteric Fermentation contributed to changes in the
population, VS and Nex data used for calculating CH4 and N2O cattle emissions from manure management. This
year the CEFM produced VS and Nex for bulls and as a result of this change in data source, there were changes in
VS and Nex for bulls in all years which impacted CH4 and N2O emissions for these animals. In addition, an error in
the crude protein calculation in the 1990-2010 CEFM impacted Nex estimates for NOF cattle. Combined, these
changes contributed to a 20 percent decrease in the Nex of beef cattle from the 1990-2010 to the 1990-2011
inventory. State animal populations were updated to reflect updated USDA NASS datasets. Population changes
occurred for broilers, layers, pullets and swine in 2010 and sheep in 2009 and 2010. In addition, the data source used
for horse population data was changed from the United Nations Food and Agriculture Organization (FAO) to USDA
Census data. FAO data were previously used because USDA horse data are only updated every 5 years. However,
there were large population differences between the FAO dataset and the USDA data and the USDA data are
country specific and more representative and accurate for U.S. animal population data.
Temperature data were updated to incorporate the most recent available data. The temperature data are used to
estimate MCFs for liquid systems; this update caused minor changes in CH4 emission estimates from dairy, swine,
beef, and poultry from 2008 to 2010.
Updated anaerobic digester data was obtained from the AgSTAR database. The WMS distributions for the current
Inventory for dairy cattle, swine, and poultry were updated to reflect the updated anaerobic digestion data.
Tier 2 emission estimates for mules and asses and North American bison were incorporated into the current
Inventory. Although these animal groups are considered very minor sources of emissions and did not contribute
significantly to the overall U.S. emissions from manure management, they were be included for completeness and
consistency across source categories.
The uncertainty analysis will be updated in the future to more accurately assess uncertainty of emission calculations.
This update is necessary due to the extensive changes in emission calculation methodology, including estimation of
emissions at the WMS level and the use of new calculations and variables for indirect N2O emissions.
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 methanogenie bacteria. As much as 60 to 90 percent of the CH4 produced is
oxidized by aerobic methanotrophic bacteria in the soil (some oxygen remains at the interfaces of soil and water, and
soil and root system) (Holzapfel-Pschorn et al. 1985, Sass et al. 1990). Some of the CH4 is also leached away as
dissolved CH4 in floodwater that percolates from the field. The remaining un-oxidized CH4 is transported from the
submerged soil to the atmosphere primarily by diffusive transport through the rice plants. Minor amounts of CH4
also escape from the soil via diffusion and bubbling through floodwaters.
The water management system under which rice is grown is one of the most important factors affecting CH4
emissions. Upland rice fields are not flooded, and therefore are not believed to produce CH4. In deepwater rice
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 CH4 to oxidize but also inhibits further CH4 production in soils.
All rice in the United States is grown under continuously flooded conditions; none is grown under deepwater
conditions. Mid-season drainage does not occur except by accident (e.g., due to levee breach).
Other factors that influence CH4 emissions from flooded rice fields include fertilization practices (especially the use
of organic fertilizers), soil temperature, soil type, rice variety, and cultivation practices (e.g., tillage, seeding, and
weeding practices). The factors that determine the amount of organic material available to decompose (i.e., organic
fertilizer use, soil type, rice variety,186 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.187 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 southwest Louisiana, Texas, and Florida often allow for a second, or ratoon, rice crop. Ratoon
crops are much less common or non-existent in Arkansas, California, Mississippi, Missouri, Oklahoma, and northern
areas of Louisiana. Methane emissions from ratoon crops have been found to be considerably higher than those
from the primary crop. This second rice crop is produced from regrowth of the stubble after the first crop has been
harvested. Because the first crop's stubble is left behind in ratooned fields, and there is no time delay between
cropping seasons (which would allow the stubble to decay aerobically), the amount of organic material that is
available for anaerobic decomposition is considerably higher than with the first (i.e., primary) crop.
Rice cultivation is a small source of CH4 in the United States (Table 6-10 and Table 6-11). In 2011, CH4 emissions
from rice cultivation were 6.6 Tg CO2 Eq. (316 Gg). Annual emissions fluctuated unevenly between the years 1990
and 2011, ranging from an annual decrease of 23 percent to an annual increase of 17 percent. There was an overall
decrease of 17 percent between 1990 and 2006, due to an overall decrease in primary crop area.188 However,
emission levels increased again by 12 percent between 2006 and 2011 due to an increase in rice crop area in all
states except Oklahoma, which reported no rice production in 2009, 2010, and 2011. All states except California
and Florida reported a decrease in rice crop area from 2010 to 2011. 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 6-10: Cm Emissions from Rice Cultivation (Tg COz Eq.)
State
Primary
Arkansas
1990
5.1
2.1 •' ~
2005
; i
6.0
2.9 •' ~
2007
4.9
2.4
2008
5.3
2.5
2009
5.6
2.6
2010
6.5
3.2
2011
4.7
2.1
186 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.
187 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 emission estimates.
188 The 23 percent decrease occurred between 2010 and 2011; the 17 percent increase happened between 2009 and 2010.
Agriculture 6-15
-------
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
0.7
+
1.0
0.4 /
0.1
+
0.6
2.1
+
+
1.1
0.9 /
7.1 .
0.9
+
0.9
0.5 /
0.4
+
0.4
0.8
+
+
0.5
0.4 .
6.8
1.0
+
0.7
0.3
0.3
+
0.3
1.3
+
+
0.9
0.3
6.2
0.9
+
0.8
0.4
0.4
+
0.3
1.9
+
+
1.2
0.6
7.2
1.0
+
0.8
0.4
0.4
+
0.3
1.8
+
+
1.1
0.7
7.3
1.0
+
1.0
0.5
0.4
+
0.3
2.1
+
+
1.4
0.7
8.6
1.0
+
0.7
0.3
0.2
+
0.3
1.9
+
+
1.0
0.9
6.6
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-11: CH4
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
Emissions
1990
241
102
34
1
46
21
7
+
30
98
+
2
52
45
339
from Rice
2005
287
139
45
1
45
22 ••
18
+
17
39
1
+
22
17
326
Cultivation
2007
235
113
45
1
32
16
15
+
12
60
+
1
42
16
295
(Gg)
2008
254
119
44
1
39
19
17
+
15
89
+
1
59
29
343
2009
265
125
47
1
39
21
17
+
14
84
+
2
51
31
349
2010
308
152
47
1
45
26
21
+
16
101
+
2
68
32
410
2011
224
98
49
2
36
13
11
+
15
92
+
2
46
44
316
+ Lessthan0.5Gg
Note: Totals may not sum due to independent rounding.
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. To that end, the recommended methodology and Tier 2 U.S.-specific emission factors derived from rice
field measurements were used. Average U.S. seasonal emission factors were applied since state-specific and daily
emission factors were not available. Seasonal emissions have been found to be much higher for ratooned crops than
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 6-12, and the area of
ratoon crop area as a percent of primary crop area is shown in Table 6-13. Primary crop areas for 1990 through
2010 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 2012). Source
data for non-USDA sources of primary and ratoon harvest areas are shown in Table 6-14. California, Mississippi,
Missouri, and Oklahoma have not ratooned rice over the period 1990 through 2011 (Beighley 2012; Buehring 2009
through 2011; Guethle 1999 through 2010; Lee 2003 through 2007; Mutters 2002 through 2005; Street 1999 through
2003; Walker 2005, 2007 through 2008).
Table 6-12: Rice Area Harvested (Hectares)
State/Crop
Arkansas
Primary
Ratoona
California
Florida
Primary
Ratoon
Louisiana
Primary
Ratoon
Mississippi
Missouri
Oklahoma
Lexas
Primary
Ratoon
Total Primary
Total Ratoon
Total
1990 I
485,633
-
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
2005
661,675
662
212,869
4,565
-
212,465
27,620
106,435 /
86,605
271
81,344
21,963 *
1,366,228
50,245
1,416,473
2007
>* 536,220
: 5
• 215,702
• ,
6,242
1,873
' **
152,975
; 53,541
76,487
72,036
/
* 58,681
V 21,125
1,118,343
76,544
1,194,887
2008
564,549
6
209,227
5,463
1,639
187,778
75,111
92,675
80,534
77
69,607
36,892
1,209,911
113,648
1,323,559
2009
594,901
6
225,010
5,664
2,266
187,778
65,722
98,341
80,939
-
68,798
39,903
1,261,431
107,897
1,369,328
2010
722,380
7
223,796
5,330
2,275
216,512
86,605
122,622
101,578
-
76,083
41,085
1,468,300
129,971
1,598,271
2011
467,017
5
234,723
8,212
2,311
169,162
59,207
63,942
51,801
-
72,845
56,091
1,067,702
117,613
1,185,315
a Arkansas ratooning occurred only in 1998,1999, and 2005 through 2011.
- No reported value
Note: Lotals may not sum due to independent rounding.
Table 6-13: Ratooned Area as Percent of Primary Growth Area
State
ill
Arkansas
Florida
Louisiana
Lexas
| 1997 1998
0% +
50%
1999 2000
+
65% 41%
30% 40%
40% 50%
2001 2002
60% 54%
30% 15%
40% 37%
2003 2004
0%
100% 77%
35% 30%
38% 35%
2005
0.1%
0%
13%
27%
2006
+
28%
20%
39%
2007
+
30%
35%
36%
2008
+
30%
40%
53%
2009
+
40%
35%
58%
2010
+
43%
40%
54%
2011
+
28%
35%
77%
+ Indicates ratooning less than 0.1 percent.
Table 6-14: Non-USDA Data Sources for Rice Harvest Information
State/Crop 1990
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Arkansas
Ratoon
Wilson (2002 - 2007,2009 - 2012)
Florida
Agriculture 6-17
-------
Primary
Ratoon
Scheuneman Deren Kirstein (2003, 2006)
(1999-2001) (2002)
Scheuneman (1999) Deren Kirstein Cantens
(2002) (2003- (2005)
2004)
Gonzales (2006 -2012)
Gonzales(2006-2012)
Louisiana
Ratoon
Bollich (2000) Linscombe (1999,
2001-2012)
Oklahoma
Primary
Lee
(2003-2007)
Anderson
(2008-2012)
Texas
Ratoon
Klosterboer (1 999 - 2003) Stansel
(2004-2005)
Texas Ag Experiment Station
(2006-2012)
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 that involved atypical or
nonrepresentative management practices (e.g., the application of nitrate or sulfate fertilizers, or other substances
believed to suppress CH4 formation), as well as experiments in which measurements were not made over an entire
flooding season or floodwaters were drained mid-season, were excluded from the analysis. The remaining
experimental results189 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, 199 Ib) 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-
season, and the resultant emission factor for the ratoon crop is 780 kg CH4/hectare-season.
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, particularly 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 uncertainty estimates 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
189 In some of these remaining experiments, measurements from individual plots were excluded from the analysis because of the
aforementioned reasons. In addition, one measurement from the ratooned fields (i. e., the flux of 1,490 kg Cm/hectare-season in
Lindau and Bollich 1993) was excluded, because this emission rate is unusually high compared to other flux measurements in the
United States, as well as IPCC (2006) default emission factors.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 6-15. Rice cultivation CEU emissions in 2012 were estimated to be between 2.5 and 16.3 Tg
CO2 Eq. at a 95 percent confidence level, which indicates a range of 63 percent below to 146 percent above the
actual 2011 emission estimate of 6.6 Tg CC>2 Eq.
Table 6-15: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Rice
Cultivation (Tg COz Eq. and Percent)
Source Gas 2011 Emission Uncertainty Range Relative to Emission Estimate3
Estimate
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Rice Cultivation CH4 6.6
Lower
Bound
2.5
Upper
Bound
16.3
Lower
Bound
-63%
Upper
Bound
+146%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence
interval.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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.
A possible future improvement is to create region-specific emission factors for rice cultivation. The current
methodology uses a nationwide average emission factor, derived from several studies done in a number of states.
The prospective improvement would take the same studies and average them by region, presumably resulting in
more spatially specific emission factors. This prospective improvement would likely not take place for another 2 to
3 years, because the analyses needed for it are currently taking place.
Nitrous oxide is produced naturally in soils through the microbial processes of nitrification and denitrification. 19° A
number of agricultural activities increase mineral N availability in soils, thereby increasing the amount available for
190 Nitrification and denitrification are driven by the activity of microorganisms in soils. Nitrification is the aerobic microbial
oxidation of ammonium (NH4+) to nitrate (NOs"), and denitrification is the anaerobic microbial reduction of nitrate to N2. Nitrous
oxide is a gaseous intermediate product in the reaction sequence of denitrification, which leaks from microbial cells into the soil
Agriculture 6-19
-------
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).191 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, and these processes are influenced by agricultural management through impacts on moisture and
temperature regimes in soils.192 These additional sources of mineral N are included at the recommendation of IPCC
(2006) for complete accounting of management impacts on greenhouse gas emissions, as discussed in the
Methodology section. Indirect emissions of N2O occur through two pathways: (1) volatilization and subsequent
atmospheric deposition of applied/mineralized N, and (2) surface runoff and leaching of applied/mineralized N into
groundwater and surface water.193 Direct emissions from agricultural lands (i.e., cropland and grassland as defined
in Chapter 7, Land Representation Section) are included in this section, while direct emissions from forest lands and
settlements are presented in the Land Use, Land-Use Change, and Forestry chapter. However, indirect N2O
emissions from all land-uses (cropland, grassland, forest lands, and settlements) are reported in this section.
and then into the atmosphere. Nitrous oxide is also produced during nitrification, although by a less well-understood mechanism
(Nevison 2000).
191 Drainage and cultivation of organic soils in former wetlands enhances mineralization of N-rich organic matter, thereby
increasing N2O emissions from these soils.
192 Asymbiotic N fixation is the fixation of atmospheric N2 by bacteria living in soils that do not have a direct relationship with
plants.
These processes entail volatilization of applied or mineralized N as NHs and NOX, transformation of these gases within the
atmosphere (or upon deposition), and deposition of the N primarily in the form of particulate NH4+, nitric acid (HNOs), and NOX.
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 6-2: Sources and Pathways of N that Result in NzO Emissions from Agricultural Soil
Management
• Sources and Pathways of N that Result in N20 Emissions from Agriculiural Soil Management
Asymbiotic Fixation
This graphic illustrates the sources and pathways of nitrogen that result
in direct and indirect N 0 emissions from soils using the methodologies
described in this Inventory. Emission pathways are shown with arrows.
On the lower right-hand side is a cut-away view of a representative
section of a managed soil; histosol cultivation is represented here.
N
. fs N Inputs to
w—-y' Managed Soils
Emissions
7— "^ N
-—-v and Deposition
j\ |ndirect NjQ
l/ Emissions
Histosol
Cultivation
Agriculture 6-21
-------
Agricultural soils produce the majority of N2O emissions in the United States. Estimated emissions from this source
in 2011 were 247.2Tg CO2 Eq. (797 Gg N2O) (see Table 6-16 and Table 6-17). Annual N2O emissions from
agricultural soils fluctuated between 1990 and 2011, although overall emissions were 8.5 percent higher in 2011
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. These percentages are about the same for
indirect emissions since forest lands and settlements account for such a small percentage of total indirect emissions.
Estimated direct and indirect N2O emissions by sub-source category are shown in Table 6-18 and Table 6-19.
Table 6-16: NzO Emissions from Agricultural Soils (Tg COz Eq.)
Activity
Direct
Cropland
Grassland
Indirect (All Land-
Use Types)
Cropland
Grassland
Forest Land
Settlements
Total
+ Less than 0.05 Tg CO2
1990
181.
8
103.
9 '•;
77.9 . ''
46.0
33. '
4
12.
3
+
0.4
227. - .•
9
Eq.
Table 6-17: NzO Emissions from
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use
Types)
Cropland
Grassland
Forest Land
Settlements
Total
1990
587
335
251
149
108
40
0
1
735
2005
195.
8
124.
7 .••'
71.1
41.7
28. /
4 /
. 12.
6
0.1
0.6 /
237.
5 /
Agricultural
2005 ;
632
402
229
135
92
41
+ - *
2
766 i
2007
198.5
128.5
69.9
53.8
41.5
11.6
0.1
0.6
252.3
Soils
2007
640
415
226
174
134
37
+
2
814
2008
193.
0
124.
6
68.4
52.4
40.
2
11.
4
0.1
0.6
245.
4
(Gg)
2008
623
402
221
169
130
37
+
2
792
2009
191.3
122.4
68.9
51.5
39.5
11.4
0.1
0.6
242.8
2009
617
395
222
166
127
37
+
2
783
2010
192.3
125.0
67.3
52.2
40.2
11.3
0.1
0.6
244.5
2011
195.
2
125.
4
69.8
51.9
40.
3
10.
9
0.1
0.6
247.
2
2010 2011
620
403
217
168
130
36
+
2
789
630
405
225
168
130
35
+
2
797
Lessthan0.5GsN2O
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 6-18: Direct NzO Emissions from Agricultural Soils by Land Use Type and N Input Type
(Tg C02 Eq.)
Activity
Cropland
Mineral Soils
Synthetic Fertilizer
Organic
Amendment15
Residue Na
Mineralization and
Asymbiotic
Fixation
Organic Soils
Grassland
Synthetic Fertilizer
PRP Manure
Managed Manure
Sewage Sludge
Residue Nc
Mineralization and
Asymbiotic Fixation
Total
1990
103.9
101.0
40.0
11.6
3.7 ,'
45.8
2.9
77.9
3.0 -
27.7
0.1
0.3 .
2.7
44.2
181.8
2005
124.7
121.8
49.1
13.5
4.3
55.0
2.9
71.1
2.9
25.7
0.1
0.5
2.7
39.2
195.8
! 2007
I 128.5
125.6
53.0
14.0
4.2
- 54.5
2.9
69.9
2.7
23.4
0.2
0.5
2.7
40.5
198.5
2008
124.6
121.7
49.5
13.8
4.1
54.4
2.9
68.4
2.4
22.6
0.1
0.5
2.8
40.0
193.1
2009
122.4
119.5
47.5
13.7
4.1
54.3
2.9
68.9
2.5
22.4
0.1
0.5
2.8
40.5
191.3
2010
125.0
122.1
49.9
13.7
4.1
54.4
2.9
67.3
2.2
22.0
0.1
0.5
2.7
39.8
192.3
2011
125.4
122.5
50.3
13.7
4.1
54.4
2.9
69.8
2.1
21.8
0.1
0.6
2.9
42.3
195.2
a Cropland residue N inputs include N in unharvested legumes as well as crop residue N.
b Organic amendment inputs include managed manure amendments, daily spread manure amendments,
and commercial organic fertilizers (i.e., dried blood, dried manure, tankage, compost, and other).
c Grassland residue N inputs include N in ungrazed legumes as well as ungrazed grass residue N
d Accounts for managed manure and daily spread manure amendments that are applied to grassland soils.
Table 6-19: Indirect NzO Emissions from all Land-Use Types (Tg COz Eq.)
Activity
Cropland
Volatilization & Atm.
Deposition
Surface Leaching & Run-Off
Grassland
Volatilization & Atm.
Deposition
Surface Leaching & Run-Off
Forest Land
Volatilization & Atm.
Deposition
Surface Leaching & Run-Off
Settlements
Volatilization & Atm.
Deposition
Surface Leaching & Run-Off
Total
1990
33.4
13.1
20.2
12.3
7.3
5.0
+
+
+
0.4
0.1
0.2
46.0
2005
28.4
14.3 ,.
14.1
12.6
7.8 .;
4.8
0.1 ,
+
0.1
0.6
0.2
0.4
41.7
2007
41.5
>* 14.4
•~, 27.1
: n.6
:*« 7.8
- 3.8
/ 0.1
+
0.1
0.6
0.2
0.4
53.8
2008
40.2
14.0
26.2
11.4
7.7
3.7
0.1
+
0.1
0.6
0.2
0.4
52.4
2009
39.5
13.8
25.6
11.4
7.7
3.7
0.1
+
0.1
0.6
0.2
0.4
51.5
2010
40.2
13.9
26.3
11.3
7.6
3.6
0.1
+
0.1
0.6
0.2
0.4
52.2
2011
40.3
14.0
26.4
10.9
7.6
3.3
0.1
+
0.1
0.6
0.2
0.4
51.9
+ Less than 0.05 Tg CO2 Eq.
Agriculture 6-23
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Figure 6-3 and Figure 6-6 show regional patterns in direct N2O emissions, and also show N losses from
volatilization, leaching, and runoff that lead to indirect N2O emissions. Annual emissions and N losses in 2011 are
shown for the Tier 3 Approach only.
Direct N2O emissions from croplands tend to be high in the Corn Belt (Illinois, Iowa, Indiana, Ohio, southern
Minnesota, and eastern Nebraska), where a large portion of the land is used for growing highly fertilized corn and
N-fixing soybean crops (Figure 6-3). Direct emissions are also high in Kansas, Missouri and Texas, primarily from
irrigated cropping in western Texas, dryland wheat in Kansas, and hay cropping in eastern Texas and Missouri.
Direct emissions are low in many parts of the eastern United States because a small portion of land is cultivated, and
also low in many western states where rainfall and access to irrigation water are limited.
Direct emissions (Tg CO2 Eq./state/year) from grasslands are highest in the central and western United States
(Figure 6-3) where a high proportion of the land is used for cattle grazing. Most areas in the Great Lake states, the
Northeast, and Southeast have moderate to low emissions even though emissions from these areas tend to be high on
a per unit area basis, because the total amount of grassland is much lower than in the central and western United
States.
Indirect emissions from croplands and grasslands (Figure 6-5 and Figure 6-6) show patterns similar to direct
emissions, because the factors that control direct emissions (N inputs, weather, soil type) also influence indirect
emissions. However, there are some exceptions, because the processes that contribute to indirect emissions (NOs"
leaching, N volatilization) do not respond in exactly the same manner as the processes that control direct emissions
(nitrification and denitrification). For example, coarser-textured soils facilitate relatively high indirect emissions in
Florida grasslands due to high rates of N volatilization and NOs" leaching, even though they have only moderate
rates of direct N2O emissions.
Figure 6-3: Major Crops, Annual Direct NzO Emissions Estimated Using the DAYCENT Model,
1990-2011 (Tg CO2 Eq./year)
Major Crop, Average Annual Direct N20 Emissions Estimated Using the DAYCENT Mattel,
1910-2011 (Is C02 Eq,/year)
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 6-4: Grasslands, Annual Direct NzO Emissions Estimated Using the DAYCENT Model,
1990-2011 (Tg CO2 Eq./year)
grasslands, Average Annual Direct N2Q Emissions Estimated Using the DAYCENT Model,
1880-2011 (Tfl 002 Ef^ear)
Tg C02 Eq./year
D<0.25
DO 25-0 5
DO 5-0 75
S 075-1
ni-2
• 2-4
• >4
Agriculture 6-25
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Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect NzO Emissions
Estimated Using the DAYCENT Model, 1990-2011 (Gg N/year)
Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions
Estimated Using the DAYCENT Model, 1990-2011 (Gg N/year)
Qg N/year
n400
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect NzO Emissions
Estimated Using the DAYCENT Model, 1990-2011 (Gg N/year)
Grasslands, Average Annual N Lasses Leading to Indirect N2Q Emissions
Estimated Using the DAYCENT Model, 1990-2011 (Gg N/year)
The 2006IPCC Guidelines (IPCC 2006) divide the Agricultural Soil Management source category into five
components: (1) direct emissions due to N additions to cropland and grassland mineral soils, including synthetic
fertilizers, sewage sludge applications, crop residues, organic amendments, and biological N fixation associated with
planting of legumes on cropland and grassland soils; (2) direct emissions from soil organic matter mineralization
due to land use and management change, (3) direct emissions from drainage and cultivation of organic cropland
soils; (4) direct emissions from soils due to the deposition of manure by livestock on PRP grasslands; and (5)
indirect emissions from soils and water due to N additions and manure deposition to soils that lead to volatilization,
leaching, or runoff of N and subsequent conversion to N2O.
The United States has adopted recommendations from IPCC (2006) on methods for agricultural soil management.
These recommendations include (1) estimating the contribution of N from crop residues to indirect soil N2O
emissions; (2) adopting a revised emission factor for direct N2O emissions to the extent that Tier 1 methods are used
in the Inventory (described later in this section); (3) removing double counting of emissions from N-fixing crops
associated with the biological N fixation and crop residue N input categories; (4) using revised crop residue statistics
to compute N inputs to soils based on harvest yield data to the extent that Tier 1 methods are used in the Inventory;
(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); (6)
reporting all emissions from managed lands because management affects all processes leading to soil N2O
emissions; and (7) estimating emissions associated with land use and management change which can significantly
change the N mineralization rates from soil organic matter.194 One recommendation from IPCC (2006) that has not
been completely adopted is the accounting of emissions from pasture renewal, which involves occasional plowing to
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 source.
Agriculture 6-27
-------
improve forage production. Pastures are replanted occasionally in rotation with annual crops, and this practice is
represented in the Inventory. However, renewal of pasture that is not rotated with annual crops occasionally is not
common in the United States, and is not estimated.
Direct N2O Emissions
The methodology used to estimate direct 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 a variety of crops that are grown on mineral soils on mineral (i.e., non-organic) soils,
including alfalfa hay, barley, corn, cotton, dry beans, grass hay, grass-clover hay, oats, onions, peanuts, potatoes,
rice, sorghum, soybeans, sugar beets, sunflowers, tomatoes, and wheat; as well as most of the direct emissions from
non-federal grasslands (Del Grosso et al. 2010). The Tier 3 approach has been specifically designed and tested to
estimate N2O emissions in the United States, accounting for more of the environmental and management influences
on soil N2O emissions than the IPCC Tier 1 method (see Box 6-1 for further elaboration). Moreover, the Tier 3
approach allows for the inventory to address direct N2O emissions and soil C stock changes from mineral cropland
soils in a single analysis. Carbon and N dynamics are linked in plant-soil systems through biogeochemical processes
of microbial decomposition and plant production (McGill and Cole 1981). Coupling the two source categories (i.e.,
agricultural soil C and N2O) in a single inventory analysis ensures that there is a consistent treatment of the
processes and interactions are taken into account between C and N cycling in soils.
The Tier 3 approach was based on the cropping and land use histories recorded in the USDA National Resources
Inventory (NRI) survey (USDA-NRCS 2009). The NRI is a statistically-based sample of all non-federal land, and
includes 380,956 points in agricultural land for the conterminous United States and Hawaii that are included in the
Tier 3 method.195 Each point is associated with an "expansion factor" that allows scaling of N2O emissions from
NRI points to the entire country (i.e., each expansion factor represents the amount of area with the same land-
use/management history as the sample point). Land-use and some management information (e.g., crop type, soil
attributes, and irrigation) were originally collected for each NRI point on a 5-year cycle beginning in 1982. For
cropland, data were collected for 4 out of 5 years in the cycle (i.e., 1979-1982, 1984-1987, 1989-1992, and 1994-
1997). However, the NRI program began collecting annual data in 1998, and data are currently available through
2007.
The IPCC (2006) Tier 1 approach is based on multiplying activity data on different N inputs (e.g., synthetic
fertilizer, manure, N fixation, etc.) by the appropriate default IPCC emission factors to estimate N2O emissions on
an input-by-input basis. The Tier 1 approach requires a minimal amount of activity data, readily available in most
countries (e.g., total N applied to crops); calculations are simple; and the methodology is highly transparent. In
contrast, the Tier 3 approach developed for this Inventory employs a process-based model (i.e., DAYCENT) that
represents the interaction of N inputs and the environmental conditions at specific locations. Consequently, the Tier
3 approach produces more accurate estimates; it accounts more comprehensively for land-use and management
impacts and their interaction with environmental factors (i.e., weather patterns and soil characteristics), which will
enhance or dampen anthropogenic influences. However, the Tier 3 approach requires more detailed activity data
(e.g., crop-specific N amendment rates), additional data inputs (e.g., daily weather, soil types, etc.), and considerable
computational resources and programming expertise. The Tier 3 methodology is less transparent, and thus it is
critical to evaluate the output of Tier 3 methods against measured data in order to demonstrate the adequacy of the
method for estimating emissions (IPCC 2006). Another important difference between the Tier 1 and Tier 3
approaches relates to assumptions regarding N cycling. Tier 1 assumes that N added to a system is subject to N2O
emissions only during that year and cannot be stored in soils and contribute to N2O emissions 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 added to soils is
re-mineralized from soil organic matter and emitted as N2O during subsequent years.
195 NRI points were classified as agricultural if under grassland or cropland management between 1990 and 2007. There are
another 148,731 NRI survey points that are cropland ) and are not included in the Tier 3 analysis. The soil N2O emissions
associated with these points are estimated with the IPCC Tier 1 method.
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
The Tier 1IPCC (2006) methodology was used to estimate (1) direct emissions from crops on mineral soils that are
not simulated by DayCent (e.g., tobacco, sugarcane, orchards, vineyards, and other crops); (2) federal grassland
direct emissions, which were not estimated with the Tier 3 DAYCENT model; and (3) direct emissions from
drainage and cultivation of organic cropland soils.
Tier 3 Approach for Mineral Cropland Soils
The DAYCENT biogeochemical model (Parton et al. 1998; Del Grosso et al. 2001, 2011) was used to estimate
direct N2O emissions from mineral cropland soils that are managed for production of a wide variety of crops based
on the cropping histories in the National Resources Inventory (USDA-NRCS 2009), including alfalfa hay, barley,
corn, cotton, dry beans, grass hay, grass-clover hay, oats, onions, peanuts, potatoes, rice, sorghum, soybeans, sugar
beets, sunflowers, tomatoes, and wheat . Crops simulated by DAYCENT are grown on approximately 93 percent of
total croplands in the United States. Crop production is simulated with NASA-CASA production algorithm (Potter
et al.1993, Potter et al. 2007) using the MODIS Enhanced Vegetation Index (EVI) products, MOD13Q1 and
MYD13Q1, with a pixel resolution of 250m. A prediction algorithm was developed to estimate EVI (Gurung et al.
2009) for gap-filling during years over the inventory time series when EVI data were not available (e.g., Data from
the MODIS sensor were only available after 2000 following the launch of the Aqua and Terra Satellites; see Annex
3.11 for more information). DAYCENT also simulated soil organic matter decomposition, greenhouse gas fluxes,
and key biogeochemical processes affecting N2O emissions.
DAYCENT was used to estimate direct N2O emissions due to mineral N available from the following sources: (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. Note that commercial organic fertilizers are addressed
with the Tier 1 method because county-level application data would be needed to simulate applications in
DAYCENT, and currently data are only available at the national scale. The third and fourth sources are generated
internally by the DAYCENT model.
Synthetic fertilizer data were based on fertilizer use and rates by crop type for different regions of the United States
that were obtained primarily from the USDA Economic Research Service Cropping Practices Survey (USDA-ERS
1997, 2011) with additional data from other sources, including the National Agricultural Statistics Service (NASS
1992, 1999, 2004). Frequency and rates of livestock 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. The adjustments were based on
county-scale ratios of manure available for application to soils in other years relative to 1997 (see Annex 3.11 for
further details). Greater availability of managed manure N relative to 1997 was assumed to increase the area
amended with manure, while reduced availability of manure N relative to 1997 was assumed to reduce the amended
area. 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 during storage and transport, and including the addition of N from
bedding materials. Nitrogen losses include direct nitrous oxide emissions, volatilization of ammonia and NOX,
runoff and leaching, and poultry manure used as a feed supplement. For unmanaged systems, it is assumed that no
N losses or additions occur prior to the application of manure to the soil. More information on livestock manure
production is available in the Manure Management Section 6.2 and Annex 3.10.
The IPCC approach considers crop residue N and N mineralized from soil organic matter as activity data. However,
they are not treated as activity data in DAYCENT simulations because residue production, symbiotic N fixation
(e.g., legumes), mineralization of N from soil organic matter, and asymbiotic N fixation are internally generated by
the model as part of the simulation. In other words, DAYCENT accounts for the influence of symbiotic N fixation,
mineralization of N from soil organic matter, retention of crop residue on N2O emissions, and asymbiotic N fixation,
but these are not model inputs. The DAYCENT simulations also accounted for the approximately 3 percent of grain
crop residues that were assumed to be burned based on state inventory data (ILENR 1993, Oregon Department of
Energy 1995, Noller 1996, Wisconsin Department of Natural Resources 1993, and Cibrowski 1996), and therefore
did not contribute to soil N2O emissions.
Additional sources of data were used to supplement the mineral N (USDA ERS 1997, 2011), livestock manure
(Edmonds et al. 2003), and land-use information (USDA-NRCS 2009). The Conservation Technology Information
Agriculture 6-29
-------
Center (CTIC 2004) provided annual data on tillage activity with adjustments for long-term adoption of no-till
agriculture (Towery 2001). Tillage data has an influence on soil organic matter decomposition and subsequent soil
N2O emissions. The time series of tillage data began in 1989 and ended in 2004, so further changes in tillage
practices since 2004 are not currently captured in the inventory. Daily weather data were used as an input in the
model simulations, based on gridded weather data at a 32 km scale from the North America Regional Reanalysis
Product (NARR) (Mesinger et al. 2006). Soil attributes were obtained from the Soil Survey Geographic Database
(SSURGO) (Soil Survey Staff 2011).
EachNRI point was run 100 times as part of the uncertainty assessment, yielding a total of over 18 million
simulations for the analysis. Soil N2O emission estimates from DAYCENT were adjusted using a structural
uncertainty estimator accounting for uncertainty in model algorithms and parameter values (Del Grosso et al. 2010).
Soil N2O emissions and 95 percent confidence intervals were estimated for each year between 1990 and 2007, but
emissions from 2008 to 2011 were assumed to be similar to 2007 because no additional activity data are currently
available from the NRI for the latter years.
Nitrous oxide emissions from managed agricultural lands are the result of interactions among anthropogenic
activities (e.g., N fertilization, manure application, tillage) and other driving variables, such as weather and soil
characteristics. These factors influence key processes associated with N dynamics in the soil profile, including
immobilization of N by soil microbial organisms, decomposition of organic matter, plant uptake, leaching, runoff,
and volatilization, as well as the processes leading to N2O production (nitrification and denitrification). It is not
possible to partition N2O emissions into each anthropogenic activity directly from model outputs due to the
complexity of the interactions (e.g., N2O emissions from synthetic fertilizer applications cannot be distinguished
from those resulting from manure applications). To approximate emissions by activity, the amount of mineral N
added to the soil for each of these sources was determined and then divided by the total amount of mineral N that
was made available in the soil according to the DAYCENT model. The percentages were then multiplied by the
total of direct N2O emissions in order to approximate the portion attributed to key practices. This approach is only
an approximation because it assumes that all N made available in soil has an equal probability of being released as
N2O, regardless of its source, which is unlikely to be the case (Delgado et al., 2009). However, this approach allows
for further disaggregation of emissions by source of N, which is valuable for reporting purposes and is analogous to
the reporting associated with the IPCC (2006) Tier 1 method, in that it associates portions of the total soil N2O
emissions with individual sources of N.
Tier 1 Approach for Mineral Cropland Soils
The IPCC (2006) Tier 1 methodology was used to estimate direct N2O emissions for mineral cropland soils that are
managed for production of crop types not simulated by DAYCENT, such as tobacco, sugarcane, sugar beets, and
millet,. DAYCENT simulations did not include 100 percent of the land area for some crops (e.g., barley, oats,
peanuts, rice, dry beans) so emissions from these lands were also estimated using IPCC Tier 1 methodology. For the
Tier 1 Approach, estimates of direct N2O emissions from N applications were based on mineral soil N that was
made available from the following practices: (1) the application of synthetic commercial fertilizers; (2) application
of managed manure and non-manure commercial organic fertilizers; and (3) the retention of above- and below-
ground crop residues in agricultural fields (i.e., crop biomass that is not harvested). Non-manure organic
amendments were not included in the DAYCENT simulations because county-level data were not available.1%
Consequently, non-manure organic amendments, as well as additional manure that was not added to crops in the
DAYCENT simulations, were included in the Tier 1 analysis. The influence of land-use change on soil N2O
emissions in the Tier 1 apporach has not been addressed in this analysis, but is a planned improvement. The
following sources were used to derive activity data:
• A process-of-elimination approach was used to estimate synthetic N fertilizer additions for crops not
simulated by DAYCENT, 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
196 Commercial organic fertilizers include dried blood, tankage, compost, and other; dried manure and sewage sludge that are
used as commercial fertilizer have been excluded to avoid double counting. The dried manure N is counted with the non-
commercial manure applications, and sewage sludge is assumed to be applied only to grasslands.
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
fertilizer applied to crops and grasslands simulated by DAYCENT (see Tier 3 Approach for Cropland
Mineral Soils Section and Grasslands Section for information on data sources), the remainder of the total
fertilizer used on farms was assumed to be applied to crops that were not simulated by DAYCENT.
• Similarly, a process-of-elimination approach was used to estimate manure N additions for crops that were
not simulated by DAYCENT, because little information exists on application rates for these crops. The
amount of manure N applied in the Tier 3 approach to crops and grasslands was subtracted from total
manure N available for land application (see Tier 3 Approach for Cropland Mineral Soils Section and
Grasslands Section for information on data sources), and this difference was assumed to be applied to crops
that are not simulated by DAYCENT.
• Non-manure, non-sewage-sludge commercial organic fertilizer additions were based on organic fertilizer
consumption statistics, which were converted to units of N using average organic fertilizer N content (TVA
1991 through 1994; AAPFCO 1995 through 2010). Manure and sewage sludge components were
subtracted from total commercial organic fertilizers to avoid double counting.
• Crop residue N was derived by combining amounts of above- and below-ground biomass, which were
determined based on crop production yield statistics (USDA 1994, 1998, 2003, 2005, 2006, 2008, 2009,
2010a), dry matter fractions (IPCC 2006), linear equations to estimate above-ground biomass given dry
matter crop yields from harvest (IPCC 2006), ratios of below-to-above-ground biomass (IPCC 2006), and
N contents of the residues (IPCC 2006). For crops that were only partly simulated by DAYCENT, N inputs
from residue were reduced based on the portion of land not simulated compared to total crop area.
Approximately 3 percent of the crop residues were burned and therefore did not contribute to soil N2O
emissions, based on state inventory data (ILENR 1993, Oregon Department of Energy 1995, Noller 1996,
Wisconsin Department of Natural Resources 1993, and Cibrowski 1996).
The total increase in soil mineral N from applied fertilizers and crop residues was multiplied by the IPCC (2006)
default emission factor to derive an estimate of direct N2O emissions using the Tier 1 Approach.
Drainage and Cultivation of Organic Cropland Soils
The IPCC (2006) Tier 1 methods were used to estimate direct N2O emissions due to drainage and cultivation of
organic soils at a state scale. State-scale estimates of the total area of drained and cultivated organic soils were
obtained from the National Resources Inventory (NRI) (USDA-NRCS 2009) using soils data from the Soil Survey
Geographic Database (SSURGO) (Soil Survey Staff 2011). Temperature data from Daly et al. (1994, 1998) were
used to subdivide areas into temperate and sub-tropical climates using the climate classification from IPCC (2006).
Data were available for 1982, 1992, 1997, 2002 and 2007. 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 IPCC
(2006) were combined to estimate emissions from non-federal and federal grasslands, respectively. 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 N2O emissions from NRI survey locations (USDA-NRCS 2009) on non-federal
grasslands resulting from manure deposited by livestock directly onto pastures and rangelands (i.e., PRP manure), N
fixation from legume seeding, managed manure amendments (i.e., manure other than PRP manure), and synthetic
fertilizer application. Other N inputs were simulated within the DAYCENT framework, including N input from
mineralization due to decomposition of soil organic matter and N inputs from senesced grass litter, as well as
asymbiotic fixation of N from the atmosphere. The simulations used the same weather, soil, and synthetic N
fertilizer data as discussed under the section, Tier 3 Approach for Mineral Cropland Soils. Managed manure N
amendments to grasslands were estimated from Edmonds et al. (2003) and adjusted for annual variation using data
on the availability of managed manure N for application to soils, according to methods described in the Manure
Agriculture 6-31
-------
Management section (Section 6.2) and Annex 3.10. Biological N fixation is simulated within DAYCENT, and
therefore was not an input to the model.
Manure N deposition from grazing animals (i.e., PRP manure) is another key input of N to grasslands. The amounts
of PRP manure N applied on non-federal grasslands for each NRI point were generated internally by the D AYCENT
model based on simulated plant biomass and assumed grazing intensity. DAYCENT simulations of non-federal
grasslands accounted for approximately 56 percent of total PRP manure. The remainder of the PRP manure N
excretions in each state was assumed to be excreted on federal grasslands, and the N2O emissions were estimated
using the IPCC (2006) Tier 1 method with IPCC default emission factors. 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 to agricultural lands were only
available at the national scale, and it was not possible to associate application with specific soil conditions and
weather at the county scale. Therefore, DAYCENT could not be used to simulate the influence of sewage sludge
amendments on N2O emissions from grassland soils, and consequently, emissions from sewage sludge were
estimated using the IPCC (2006) Tier 1 method.
Grassland area data were consistent with the Land Representation reported in Section 7.1. Data were obtained from
the U.S. Department of Agriculture National Resources Inventory^91 and the U.S. Geological Survey (USGS)
National Land Cover Dataset, which were reconciled with the Forest Inventory and Analysis Data.198 The area data
for pastures and rangeland were aggregated to the county level to estimate non-federal and federal grassland
areas.199
Tier 1 estimates of N2O emissions for the PRP manure N deposited on federal grasslands and applied sewage sludge
N were produced by multiplying the N input by the appropriate emission factor. Tier 1 estimates for emissions from
manure N were calculated at the state level and aggregated to the entire country but emission from sewage sludge N
were calculated exclusively at the national scale.
EachNRI point was simulated 100 times as part of the uncertainty assessment, yielding a total of over 18 million
simulation runs for the analysis. Soil N2O emission estimates from DAYCENT were adjusted using a structural
uncertainty estimator accounting for uncertainty in model algorithms and parameter values (Del Grosso et al. 2010).
Soil N2O emissions and 95 percent confidence intervals were estimated for each year between 1990 and 2007, but
emissions from 2008 to 2011 were assumed to be similar to 2007 because no additional activity data are currently
available from the NRI for the latter years.
Total Direct N2O Emissions from Cropland and Grassland Soils
Annual direct emissions from the Tier 1 and 3 approaches for cropland mineral soils, from drainage and cultivation
of organic cropland soils, and from grassland soils were summed to obtain the total direct N2O emissions from
agricultural soil management (see Table 6-16 and Table 6-17).
Indirect N2O Emissions
This section describes the methods used for estimating indirect soil N2O emissions from all land-use types (i.e.,
croplands, grasslands, forest lands, and settlements). Indirect N2O emissions occur when mineral N made available
through anthropogenic activity is transported from the soil either in gaseous or aqueous forms and later converted
into N2O. There are two pathways leading to indirect emissions. The first pathway results from volatilization of N
as NOX and NH3 following application of synthetic fertilizer, organic amendments (e.g., manure, sewage sludge),
and deposition of PRP manure. N made available from mineralization of soil organic matter and residue, including
N incorporated into crops and forage from symbiotic N fixation, and input of N from asymbiotic fixation also
contributes to volatilized N emissions. Volatilized N can be returned to soils through atmospheric deposition, and a
portion of the deposited N is emitted to the atmosphere as N2O. The second pathway occurs via leaching and runoff
USDA-NRCS 2009, Nusser and Goebel 1997,
198 Forest Inventory and Analysis Data,
199 NLCD, Vogelman et al. 2001,
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
of soil N (primarily in the form of NOs") that was made available through anthropogenic activity on managed lands,
mineralization of soil organic matter and residue, including N incorporated into crops and forage from symbiotic N
fixation, and inputs of N into the soil from asymbiotic fixation. The NOs" is subject to denitrification in water
bodies, which leads to N2O emissions. Regardless of the eventual location of the indirect N2O emissions, the
emissions are assigned to the original source of the N for reporting purposes, which here includes croplands,
grasslands, forest lands, and settlements.
Indirect N2O Emissions from Atmospheric Deposition of Volatilized N from Managed Soils
As in the direct emissions calculation, the Tier 3 DAYCENT model and IPCC (2006) Tier 1 methods were
combined to estimate the amount of N that was volatilized and eventually emitted as N2O. DAYCENT was used to
estimate N volatilization for land areas whose direct emissions were simulated with DAYCENT (i.e., most
commodity and some specialty croplands and most grasslands). The N inputs included are the same as described for
direct N2O emissions in the Tier 3 Approach for Cropland Mineral Soils Section and Grasslands Section. Nitrogen
volatilization for all other areas was estimated using the Tier 1 method and default IPCC fractions for N subject to
volatilization (i.e., N inputs on croplands not simulated by DAYCENT, PRP manure N excretion on federal
grasslands, sewage sludge application on grasslands). The Tier 1 method and default fractions were also used to
estimate N subject to volatilization from N inputs on settlements and forest lands (see the Land Use, Land-Use
Change, and Forestry chapter). For the volatilization data generated from both the DAYCENT and Tier 1
approaches, the IPCC (2006) default emission factor was used to estimate indirect N2O emissions occurring due to
re-deposition of the volatilized N (Table 6-19).
Indirect N2O Emissions from Leaching/Runoff
As with the calculations of indirect emissions from volatilized N, the Tier 3 DAYCENT model and IPCC (2006)
Tier 1 method were combined to estimate the amount of N that was subject to leaching and surface runoff into water
bodies, and eventually emitted as N2O. DAYCENT was used to simulate the amount of N transported from lands in
the Tier 3 Approach. N transport from all other areas was estimated using the Tier 1 method and the IPCC (2006)
default factor for the proportion of N subject to leaching and runoff. This N transport estimate includes N
applications on croplands that were not simulated by DAYCENT, sewage sludge amendments on grasslands, PPJ3
manure N excreted on federal grasslands, and N inputs on settlements and forest lands. For both the DAYCENT
Tier 3 and IPCC (2006) Tier 1 methods, nitrate leaching was assumed to be an insignificant source of indirect N2O
in cropland and grassland systems in arid regions as discussed in IPCC (2006). In the United States, the threshold
for significant nitrate leaching is based on the potential evapotranspiration (PET) and rainfall amount, similar to
IPCC (2006), and is assumed to be negligible in regions where the amount of precipitation plus irrigation does not
exceed 80 percent of PET. For leaching and runoff data estimated by the Tier 3 and Tier 1 approaches, the IPCC
(2006) default emission factor was used to estimate indirect N2O emissions that occur in groundwater and
waterways (Table 6-19).
Uncertainty was estimated for each of the following five components of N2O emissions from agricultural soil
management: (1) direct emissions calculated by DAYCENT; (2) the components of indirect emissions (N
volatilized and leached or runoff) calculated by DAYCENT; (3) direct emissions calculated with the IPCC (2006)
Tier 1 method; (4) the components of indirect emissions (N volatilized and leached or runoff) calculated with the
IPCC (2006) Tier 1 method; and (5) indirect emissions calculated with the IPCC (2006) Tier 1 method. Uncertainty
in direct emissions, which account for the majority of N2O emissions from agricultural management, as well as the
components of indirect emissions calculated by DAYCENT were estimated with a Monte Carlo Analysis,
addressing uncertainties in model inputs and structure (i.e., algorithms and parameterization) (Del Grosso et al.
2010). Uncertainties in direct emissions calculated with the IPCC (2006) Tier 1 method, the proportion of
volatilization and leaching or runoff estimated with the IPCC (2006) Tier 1 method, and indirect N2O emissions
were estimated with a simple error propagation approach (IPCC 2006). Uncertainties from the Tier 1 and Tier 3
(i.e., DAYCENT) estimates were combined using simple error propagation (IPCC 2006). Additional details on the
uncertainty methods are provided in Annex 3.11. The combined uncertainty for direct soil N2O emissions ranged
from 18 percent below to 40 percent above the 2011 emissions estimate of 195.2 Tg CO2 Eq., and the combined
Agriculture 6-33
-------
uncertainty for indirect soil N2O emissions ranged from 50 percent below to 151 percent above the 2011 estimate of
51.9TgCO2Eq.
Table 6-20: Quantitative Uncertainty Estimates of NzO Emissions from Agricultural Soil
Management in 2011 (Tg COz Eq. and Percent)
2011 Emission
Estimate
Source Gas (Tg CCh Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Direct Soil N2O Emissions N2O 195.2
Indirect Soil N2O Emissions N2O 51.9
160.0 273.4 -18% 40%
26.1 130.4 -50% 151%
Note: Due to lack of data, uncertainties in managed manure N production, PRP manure N production, other organic fertilizer
amendments, indirect losses of N in the DAYCENT simulations, and sewage sludge amendments to soils are currently treated as
certain; these sources of uncertainty will be included in future Inventories.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
DAYCENT results for N2O emissions and NOs" leaching were compared with field data representing various
cropland and grassland systems, soil types, and climate patterns (Del Grosso et al. 2005, Del Grosso et al. 2008), and
further evaluated by comparing to emission estimates produced using the IPCC (2006) Tier 1 method for the same
sites. Nitrous oxide measurement data were available for 12 sites in the United States and one in Australia,
representing over 30 different combinations of fertilizer treatments and cultivation practices. DAYCENT estimates
of N2O emissions were closer to measured values at most sites compared to the IPCC Tier 1 estimate (Figure 6-7).
In general, IPCC Tier 1 methodology tends to over-estimate emissions when observed values are low and under-
estimate emissions when observed values are high, while DAYCENT estimates are less biased. DAYCENT
accounts for key site-level factors (weather, soil characteristics, and management) that are not addressed in the IPCC
Tier 1 Method, and thus the model is better able to represent the variability in N2O emissions. Nitrate leaching data
were available for three sites in the United States representing nine different combinations of fertilizer amendments.
DAYCENT does have a tendency to under-estimate small emission rates; estimates are increased to correct for this
bias based on a statistical model derived from the comparison of model estimates to measurements (See Annex 3.11
for more information). Regardless, the comparison demonstrates that DAYCENT provides relatively high predictive
capability for N2O emissions and NOs" leaching, and is an improvement over the IPCC Tier 1 method.
6-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 6-7: Comparison of Measured Emissions at Field Sites and Modeled Emissions Using
the DAYCENT Simulation Model and IPCC Tier 1 Approach.
5'
«
x:
2
e»
O
a measured
oDWCENT
•IPCC
40 1
35 -
30 -
25 -
20
15 -
5 -
ffiP$$MfJS*
>** * ^ ° fV^.A^ ^
DAYCENT simulations had errors in the PRP manure N application that were corrected. Errors were also identified
in the level of N uptake by plants that resulted in limited N availability for microbial transformations including
nitrification and denitrification. The availability of N to the plants was modified, and the evaluation shows the
improved fit of the model to measured N2O emissions (Figure 6-7). Crop harvest indices also had errors that were
corrected. One of the key quality control issues was an under-estimation of C stocks in the DAYCENT model due
to higher than expected decomposition rates. The model was re-parameterized to correct this error and accurately
represent soil C dynamics, which has an influence on soil N2O emissions through the decomposition and N
mineralization processes in soils.
Spreadsheets containing input data and probability distribution functions required for DAYCENT simulations of
croplands and grasslands and unit conversion factors were checked, as were the program scripts that were used to
run the Monte Carlo uncertainty analysis. Several errors were identified following re-organization of the calculation
spreadsheets, and corrective actions have been taken. In particular, some of the links between spreadsheets were
missing or needed to be modified. Spreadsheets containing input data, emission factors, and calculations required
for the Tier 1 approach were checked and no errors were found.
€
Methodological recalculations in this year's Inventory were associated with the following improvements: (1)
incorporation of MODIS Enhanced Vegetation Index to reduce uncertainties in the estimation of crop production
and subsequent carbon input to the soil; (2) using the National Resources Inventory (NRI) as the basis for crop
histories and land use change (USDA-NRCS 2009); (3) addition of specific tillage practices with statistics from
Conservation Technology and Information Center (CTIC 2004); (4) extension of the N fertilizer activity data with
new USDA statistics on fertilizer use through 2009 (USDA-ERS 2011); and (5) expansion of the number of crops
simulated by DAYCENT (i.e., dry beans, onions, peanuts, potatoes, rice, sugar beets, sunflowers, and tomatoes).
These changes resulted in an increase in emissions of approximately 16 per cent on average relative to the previous
Inventory. The differences are partly due to the broader scope of the current Inventory that includes the influence of
land use change and tillage on mineral N availability in soils, which is a key driver of nitrification and
denitrification. Synthetic fertilizer rates are also higher for crops based on the updated USDA statistics. In addition,
the dataset was expanded for evaluating the error in model structure, improving the ability to assess uncertainty in
the emission estimates.
Agriculture 6-35
-------
An automated quality assurance/quality control system is currently under development for the Tier 3 method that is
used to estimate the majority of emissions associated with this source category. Currently, quality control is
conducted by manual graphing and queries to determine if values are outside of an expected range. The new system
will automatically create graphs, maps and conduct range checks to improve efficiency in this important step for the
inventory analysis. This development will ensure a more thorough review of the inventory results.
Another improvement is to reconcile the amount of crop residues burned with the Field Burning of Agricultural
Residues source category (Section 6.5). The methodology for Field Burning of Agricultural Residues was
significantly updated recently, but the new estimates of crop residues burned were not incorporated into the
DAYCENT runs for the Agricultural Soil Management source. In the next Inventory report, the estimates will be
reconciled; meanwhile, the estimates presented in this section use the same methodology as used in previous
Inventory reports for determining crop residues burned.
Farming activities produce large quantities of agricultural crop residues, and farmers use or dispose of these residues
in a variety of ways. For example, agricultural residues can be left on or plowed into the field; composted and then
applied to soils; landfilled; or burned in the field. Alternatively, they can be collected and used as fuel, animal
bedding material, supplemental animal feed, or construction material. Field burning of crop residues is not
considered a net source of CO2, because the C released to the atmosphere as CO2 during burning is assumed to be
reabsorbed during the next growing season. Crop residue burning is, however, a net source of CH4, N2O, CO, and
NOX, which are released during combustion.
Field burning is not a common method of agricultural residue disposal in the United States. The primary crop types
whose residues are typically burned in the United States are corn, cotton, lentils, rice, soybeans, sugarcane, and
wheat (McCarty 2009). In 2011, CH4 and N2O emissions from field burning were 0.2 Tg CO2 Eq. (10 Gg) and 0.1
Tg. CO2 Eq. (0.3 Gg), respectively. Annual emissions from this source over the period 1990 to 2011 have remained
relatively constant, averaging approximately 0.2 Tg CO2 Eq. (10 Gg) of CH4 and 0.1 Tg CO2 Eq. (0.3 Gg) of N2O
(see Table 6-21 and Table 6-22).
Table 6-21: Cm and NzO Emissions from Field Burning of Agricultural Residues (Tg COz Eq.)
Gas/Crop Type 1990 2005 ;
CH4 0.2 0.2
Corn + ' '' •< + .•'
Cotton + ,, +
Lentils + , +
Rice + ;•, + /
Soybeans + - , ' + /
Sugarcane + +
Wheat 0.1 0.1
N2O 0.1 0.1
Corn + +
Cotton + , +
Lentils + +
Rice + " +
Soybeans + • '.• +
Sugarcane + +
Wheat + +
Total 0.3 0.2 «i
2007
0.2
+
+
+
0.1
+
+
0.1
0.1
+
+
+
+
+
+
+
0.3
2008
0.2
+
+
+
0.1
+
+
0.1
0.1
+
+
+
+
+
+
+
0.3
2009
0.2
+
+
+
0.1
+
+
0.1
0.1
+
+
+
+
+
+
+
0.3
2010
0.2
+
+
+
0.1
+
+
0.1
0.1
+
+
+
+
+
+
+
0.3
2011
0.2
+
+
+
+
+
+
0.1
0.1
+
+
+
+
+
+
+
0.3
+ Less than 0.05 Tg CO2 Eq.
Note: Totals may not sum due to independent rounding.
6-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 6-22: ChU, NzO, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg)
Gas/Crop Type
CH4
Corn
Cotton
Lentils
Rice
Soybeans
Sugarcane
Wheat
N20
Corn
Cotton
Lentils
Rice
Soybeans
Sugarcane
Wheat
CO
NOx
1990
10
1
+
+
2 -
1
1
5
+
+
+ - ' .
+
+
+
+ • ': •
205
6
2005
8
1
+
+
2
1
1
3
+
+
+
+
+
+
+
166
6
2007
11
1
+
+
3
1
1
4
+
+
+
+
+
+
+
225
8
2008
11
1
+
+
3
1
1
4
+
+
+
+
+
+
+
224
7
2009
11
1
+
+
3
1
2
4
+
+
+
+
+
+
+
226
7
2010
11
1
+
+
3
1
1
4
+
+
+
+
+
+
+
227
8
2011
10
1
+
+
2
1
2
4
+
+
+
+
+
+
+
205
7
+ Lessthan0.5TgCO2Eq.
Note: Totals may not sum due to independent rounding.
The Tier 2 methodology used for estimating greenhouse gas emissions from field burning of agricultural residues in
the United States is consistent with IPCC (2006) (for more details, see Box 6-2). In order to estimate the amounts
of C and N released during burning, the following equation was used:
C or N released = E over all crop types and states (Area Burned -^ Crop Area Harvested x Crop Production x
Residue/Crop Ratio x Dry Matter Fraction x Burning Efficiency x Combustion Efficiency x Fraction of C or N)
where,
Area Burned = Total area of crop burned, by state
Crop Area Harvested = Total area of crop harvested, by state
Crop Production = Annual production of crop in Gg, by state
Residue/Crop Ratio = Amount of residue produced per unit of crop production, by state
Dry Matter Fraction = Amount of dry matter per unit of bio mass for a crop
Fraction of C or N = Amount of C or N per unit of dry matter for a crop
Burning Efficiency = The proportion of prefire fuel biomass consumed200
Combustion Efficiency = The proportion of C or N released with respect to the total amount of C or N
available in the burned material, respectively200
Crop production and area harvested were available by state and year from USDA (2011) for all crops (except rice in
Florida and Oklahoma, as detailed below). The amount C or N released was used in the following equation to
determine the CH4, CO, N2O and NOX emissions from the field burning of agricultural residues:
CH4 and CO, or N2O and NOX Emissions from Field Burning of Agricultural Residues = (C or N Released)
(Emissions Ratio for C or N) x (Conversion Factor)
where,
Emissions Ratio = g CH4-C or CO-C/g C released, or g N2O-N or NOx-N/g N released
Conversion Factor = conversion, by molecular weight ratio, of CH4-C to C (16/12), or CO-C to C (28/12),
or N2O-N to N (44/28), or NOX-N to N (30/14)
200 In IPCC/UNEP/OECD/IEA (1997), the equation for C or N released contains the variable 'fraction oxidized in burning.'
This variable is equivalent to (burning efficiency x combustion efficiency).
Agriculture 6-37
-------
IWPipilililiif*^^
Emissions from Burning of Agricultural Residues were calculated 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 varies slightly in form from the one presented in the IPCC (2006) guidelines, but both equations rely on the
same underlying variables. The IPCC (2006) equation was developed to be broadly applicable to all types of
biomass burning, and, thus, is not specific to agricultural residues. IPCC (2006) default factors are provided only
for four crops (wheat, corn, rice, and sugarcane), while this Inventory analyzes emissions from seven crops. A
comparison of the methods and factors used in (1) the current Inventory and (2) the default IPCC (2006) approach
was undertaken in the 1990 through 2009 Inventory report to determine the magnitude of the difference in overall
estimates resulting from the two approaches. The IPCC (2006) approach was not used because crop-specific
emission factors for N2O were not available for all crops. In order to maintain consistency of methodology, the
IPCC/UNEP/OECD/IEA (1997) approach presented in the Methodology section was used.
The IPCC (2006) default approach resulted in 12 percent higher emissions of CH4 and 25 percent higher emissions
of N2O than the estimates in the 1990 through 2009 Inventory. It is reasonable to maintain the current methodology,
since the IPCC (2006) defaults are only available for four crops and are worldwide average estimates, while current
estimates are based on U.S.-specific, crop-specific, published data.
Crop production data for all crops except rice in Florida and Oklahoma were taken from USDA's QuickStats service
(USDA 2012). Rice production and area data for Florida and Oklahoma, which are not collected by USD A, were
estimated separately. Average primary and ratoon crop yields for Florida (Schueneman and Deren 2002) were
applied to Florida acreages (Schueneman 1999, 2001; Deren 2002; Kirstein 2003, 2004; Cantens 2004, 2005;
Gonzalez 2007 through 2012), and crop yields for Arkansas (USDA 2012) were applied to Oklahoma acreages201
(Lee 2003 through 2006; Anderson 2008 through 2012). The production data for the crop types whose residues are
burned are presented in Table 6-23. Crop weight by bushel was obtained from Murphy (1993).
The fraction of crop area burned was calculated using data on area burned by crop type and state202 from McCarty
(2010) for corn, cotton, lentils, rice, soybeans, sugarcane, and wheat.203 McCarty (2010) used remote sensing data
from Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate area burned by crop. National-level
area burned data were divided by national-level crop area harvested data to estimate the percent of crop area burned
by crop. The average fraction of area burned by crop across all states is shown in Table 6-24. All crop area
harvested data were from USDA (2012), except for rice acreage in Florida and Oklahoma, which is not measured by
USDA (Schueneman 1999, 2001; Deren 2002; Kirstein 2003, 2004; Cantens 2004, 2005; Gonzalez 2007 through
2012; Lee 2003 through 2006; Anderson 2008 through 2012). Data on crop area burned were only available from
McCarty (2010) for the years 2003 through 2007. For other years in the time series, the percent area burned was
assumed to be equal to the average percent area burned from the 5 years for which data were available. This
average was taken at the crop and national level. Table 6-24 shows these percent area estimates aggregated for the
United States as a whole, at the crop level. State-level estimates based on state-level crop area harvested and burned
data were also prepared, but are not presented here.
All residue/crop product mass ratios except sugarcane and cotton were obtained from Strehler and Stutzle (1987).
The datum for sugarcane is from Kinoshita (1988) and that of cotton from Huang et al. (2007). The residue/crop
ratio for lentils was assumed to be equal to the average of the values for peas and beans. Residue dry matter
fractions for all crops except soybeans, lentils, and cotton were obtained from Turn et al. (1997). Soybean and lentil
dry matter fractions were obtained from Strehler and Stutzle (1987); the value for lentil residue was assumed to
equal the value for bean straw. The cotton dry matter fraction was taken from Huang et al. (2007). The residue C
201 Rice production yield data are not available for Oklahoma, so the Arkansas values are used as a proxy.
Alaska and Hawaii were excluded.
203 McCarty (2009) also examined emissions from burning of Kentucky bluegrass and a general "other crops/fallow" category,
but USDA crop area and production data were insufficient to estimate emissions from these crops using the methodology
employed in the Inventory. McCarty (2009) estimates that approximately 18 percent of crop residue emissions result from
burning of the Kentucky bluegrass and "other" categories.
6-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
contents and N contents for all crops except soybeans and cotton are from Turn et al. (1997). The residue C content
for soybeans is the IPCC default (IPCC/UNEP/OECD/IEA 1997). The N content of soybeans is from Barnard and
Kristoferson (1985). The C and N contents of lentils were assumed to equal those of soybeans. The C and N
contents of cotton are from Lachnicht et al. (2004). These data are listed in Table 6-25. The burning efficiency was
assumed to be 93 percent, and the combustion efficiency was assumed to be 88 percent, for all crop types, except
sugarcane (EPA 1994). For sugarcane, the burning efficiency was assumed to be 81 percent (Kinoshita 1988) and
the combustion efficiency was assumed to be 68 percent (Turn et al. 1997). Emission ratios and conversion factors
for all gases (see Table 6-26) were taken from the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997).
Table 6-23: Agricultural Crop Production (Gg of Product)
Crop
Corna
Cotton
Lentils
Rice
Soybeans
Sugarcane
Wheat
1990
201,534
3,376
40
7,114
52,416
25,525
74,292
2005
282,263
5,201 *
238 /
10,132 „
83,507 /
24,137 ,„
57,243 ••„
2007
. 331,177
1 4,182
166
9,033
72,859
27,188
55,821
2008
307,142
2,790
109
9,272
80,749
25,041
68,016
2009
332,549
2,654
266
9,972
91,417
27,608
60,366
2010
316,165
3,942
393
11,027
90,605
24,821
60,062
2011
313,918
3,391
215
8,392
83,172
26,656
54,413
a Com for grain (i.e., excludes com for silage).
Table 6-24: U.S. Average Percent Crop Area Burned by Crop (Percent)
State
Corn
Cotton
Lentils
Rice
Soybeans
Sugarcane
Wheat
1990
+
1
1
10
+
32
2
2005
+
1 •<*
+
6 "-
+
18 '
2 ;
2007
+
1
1
13
+
21
2
2008
+
1
1
10
+
32
2
2009
+
1
1
10
+
32
2
2010
+
1
1
10
+
32
2
2011
+
1
1
10
+
32
2
+ Less than 0.5 percent
Table 6-25: Key Assumptions for Estimating Emissions from Field Burning of Agricultural
Residues
Crop
Com
Cotton
Lentils
Rice
Soybeans
Sugarcane
Wheat
Residue/Crop
Ratio
1.0
1.6
2.0
1.4
2.1
0.2
1.3
Dry Matter
Fraction
0.91
0.90
0.85
0.91
0.87
0.62
0.93
C Fraction
0.448
0.445
0.450
0.381
0.450
0.424
0.443
N Fraction
0.006
0.012
0.023
0.007
0.023
0.004
0.006
Burning
Efficiency
(Fraction)
0.93
0.93
0.93
0.93
0.93
0.81
0.93
Combustion
Efficiency
(Fraction)
0.88
0.88
0.88
0.88
0.88
0.68
0.88
Table 6-26: Greenhouse Gas Emission Ratios and Conversion Factors
Gas
CH4:C
CO:C
N2O:N
NOX:N
Emission Ratio
0.005a
0.060a
0.007b
0.121b
Conversion Factor
16/12
28/12
44/28
30/14
a Mass of C compound released (units of C) relative to
mass of total C released from burning (units of C).
b Mass of N compound released (units of N) relative to
mass of total N released from burning (units of N).
Agriculture 6-39
-------
Due to data and time limitations, uncertainty resulting from the fact that emissions from burning of Kentucky
bluegrass and "other" residues are not included in the emissions estimates was not incorporated into the uncertainty
analysis. The results of the Tier 2 Monte Carlo uncertainty analysis are summarized in Table 6-27. Methane
emissions from field burning of agricultural residues in 2011 were estimated to be between 0.12 and 0.29 Tg CC>2
Eq. at a 95 percent confidence level. This indicates a range of 40 percent below and 42 percent above the 2011
emission estimate of 0.20 Tg COa Eq. Also at the 95 percent confidence level, N2O emissions were estimated to be
between 0.06 and 0.11 Tg CO2 Eq., or approximately 30 percent below and 31 percent above the 2011 emission
estimate of 0.09 Tg CO2 Eq.
Table 6-27: Tier 2 Quantitative Uncertainty Estimates for Cm and NzO Emissions from Field
Burning of Agricultural Residues (Tg COz Eq. and Percent)
Source Gas 2011 Emission
Estimate
(Tg C02 Eq.)
Field Burning of Agricultural Residues CtLt 0.20
Field Burning of Agricultural Residues N2O 0.09
Uncertainty Range Relative to Emission
Estimate3
(Tg COz Eq.) (%)
Lower
Bound
0.12
0.06
Upper
Bound
0.29
0.11
Lower
Bound
-40%
-30%
Upper
Bound
42%
31%
"Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
and
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. For some crops and years in Florida
and Oklahoma, the total area burned as measured by McCarty (2010) was greater than the area estimated for that
crop, year, and state by Gonzalez (2004-2008) and Anderson (2007) for Florida and Oklahoma, respectively, leading
to a percent area burned estimate of greater than 100 percent. In such cases, it was assumed that the percent crop
area burned for that state was 100 percent.
For the current Inventory, the crop production data for 2010 and 2011 were updated relative to the previous report
using data from USDA (2012). Rice cultivation data for Florida and Oklahoma, which are not reported by USD A,
were updated for 2011 through communications with state experts. These small updates in crop production values
resulted in a negligible (less than 0.0 percent) decrease in sector emissions in 2010, and an average decrease in
emissions of 0.5 percent from 1990 to 2011. An error was identified and corrected in the formula for cotton area
burned. This error affected the percentage of cotton crop area burned for all years, with an average decrease of 7
percent. Overall, the correction had a small effect on 1990 through 2007 emissions, which mostly stayed the same
with the exception of a 1 percent decrease in 2007.
Attempts will be made to incorporate state-level estimates of percentage of crop area burned into the uncertainty
analysis for future inventories, to make the uncertainty analysis more robust. Further investigation will be also
conducted into inconsistent data from Florida and Oklahoma as mentioned in the QA/QC and verification section,
and attempts will be made to revise or further justify the assumption of 100 percent of area burned for those crops
and years where the estimated percent area burned exceeded 100 percent. The availability of useable area harvested
6-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
and other data for bluegrass and the "other crops" category in McCarty (2010) will also be investigated, in order to
try to incorporate these emissions into the estimate. More crop area burned data are becoming available and will be
analyzed for incorporation into the next Inventory report.
Agriculture 6-41
-------
-------
This chapter provides an assessment of the net greenhouse gas flux resulting from the uses and changes in land types
and forests in the United States. 204 The Intergovernmental Panel on Climate Change 2006 Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) recommends reporting fluxes according to changes within and
conversions between certain land-use types termed forest land, cropland, grassland, and settlements (as well as
wetlands). The greenhouse gas flux from Forest Land Remaining Forest Land is reported using estimates of
changes in forest carbon (C) stocks, non-carbon dioxide (CCh) emissions from forest fires, and the application of
synthetic fertilizers to forest soils. The greenhouse gas flux from agricultural lands (i.e., cropland and grassland)
that is reported in this chapter includes changes in organic C stocks in mineral and organic soils due to land use and
management, and emissions of CCh 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 CCh
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. Carbon dioxide fluxes from forest C stocks
(except the wood product components) and from agricultural soils (except the liming component) are calculated on
an average annual basis from data collected in intervals ranging from 1 to 10 years. The resulting annual averages
are applied to years between surveys. Calculations of non-CCh emissions from forest fires are based on forest CCh
flux data. For the landfilled yard trimmings and food scraps source, periodic solid waste survey data were
interpolated so that annual storage estimates could be derived. This flux has been applied to the entire time series,
and periodic U.S. census data on changes in urban area have been used to develop annual estimates of CCh flux.
Land use, land-use change, and forestry activities in 2011 resulted in a net C sequestration of 905.0 Tg CO2 Eq.
(246.8 Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 13.5 percent of total U.S. CO2
emissions. Total land use, land-use change, and forestry net C sequestration increased by approximately 13.9
percent between 1990 and 2011. 205 This increase was primarily due to an increase in the rate of net C accumulation
in forest C stocks. Net C accumulation in Forest Land Remaining Forest Land, Land Converted to Grassland, and
Settlements Remaining Settlements increased, while net C accumulation in Cropland Remaining Cropland,
Grassland Remaining Grassland, and landfilled yard trimmings and food scraps slowed over this period. Emissions
from Land Converted to Cropland decreased between 1990 and 2011.
204 jjjg 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."
205 Carbon sequestration estimates are net figures. The C stock in a given pool fluctuates due to both gains and losses. When
losses exceed gains, the C stock decreases, and the pool acts as a source. When gains exceed losses, the C stock increases, and
the pool acts as a sink; also referred to as net C sequestration.
Land Use, Land-Use Change, and Forestry 7-1
-------
Table 7-1: Net COz Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry
(Tg C02 Eq.)
Sink Category 1990 2005 2007 2008 2009 2010 2011
Forest Land Remaining Forest Landa
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements15
Other (Landfilled Yard Trimmings and
Food Scraps)
(696.8)
(34.1) /
21.0 •'•*<
(5.3) —
(7.7) ;;
(47.5) -
(24.2) .
, (905.0)
4 (2(I3)
m 13.5 .'J
(1.0) ~
(10.2) ;
(63.2)
(11.6)
, (859.3)
'4 (6'6)
• 14.5
7.1
(9.0)
(65.0)
(10.9)
(833.3)
(5.2)
14.5
7.2
(9.0)
(66.0)
(10.9)
(811.3)
(4.6)
14.5
7.3
(8.9)
(66.9)
(12.7)
(817.6)
(3.0)
14.5
7.3
(8.8)
(67.9)
(13.3)
(833.5)
(2.9)
14.5
7.4
(8.8)
(68.8)
(13.0)
Total
(794.5)
(997.8)
(929.2) (902.6) (882.6) (888.8) (905.0)
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
a Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land.
b Estimates include C stock changes on both Settlements Remaining Settlements and Land Converted to Settlements.
Table 7-2: Net COz Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry
(TgC)
Sink Category
Forest Land Remaining Forest Landa
Cropland Remaining Cropland
Land Converted to Cropland
Grassland Remaining Grassland
Land Converted to Grassland
Settlements Remaining Settlements'3
Other (Landfilled Yard Trimmings and
Food Scraps)
1990
(190.0)
(9.3) .
5.7 '•
(1.4) ..
(2.1) '
(13.0)
(6.6)
2005
.. (246.8)
* * rs s^
ji 3/7 •.
(0.3) ..
(2.8) '
(17.2)
(3.2)
2007
, (234.4)
* * C\ 8^
jit 4Q
1.9
(2.5)
(17.7)
(3.0)
2008
(227.3)
(1.4)
4.0
2.0
(2.4)
(18.0)
(3.0)
2009
(221.3)
(1.2)
4.0
2.0
(2.4)
(18.3)
(3.5)
2010
(223.0)
(0.8)
4.0
2.0
(2.4)
(18.5)
(3.6)
2011
(227.3)
(0.8)
4.0
2.0
(2.4)
(18.8)
(3.6)
Total
(216.7)
(272.1)
(253.4) (246.2) (240.7) (242.4) (246.8)
Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to
independent rounding.
a Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land.
b Estimates include C stock changes 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 2011 resulted in CO2 emissions of 8.1 Tg CO2 Eq. (8,117 Gg). Lands undergoing peat
extraction (i.e., Peatlands Remaining Peatlands) resulted in CO2 emissions of .9 Tg CO2 Eq. (918 Gg), and nitrous oxide
(N2O) emissions of less than 0.05 Tg CO2 Eq. The application of synthetic fertilizers to forest soils in 2011 resulted in direct
N2O emissions of 0.4 Tg CO2 Eq. (1 Gg). Direct N2O emissions from fertilizer application to forest soils have increased by
455 percent since 1990, but still account for a relatively small portion of overall emissions. Additionally, direct N2O
emissions from fertilizer application to settlement soils in 2011 accounted for 1.5 Tg CO2 Eq. (4 Gg). This represents an
increase of 50 percent since 1990. Forest fires in 2011 resulted in methane (CH4) emissions of 14.2 Tg CO2 Eq. (675 Gg),
and in N2O emissions of 11.6 Tg CO2 Eq. (37 Gg).
Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg COz Eq.)
Source Category
CO2
Cropland Remaining Cropland:
Liming of Agricultural Soils
Cropland Remaining Cropland
Urea Fertilization
Wetlands Remaining Wetlands:
Peatlands Remaining Peatlands
CH4
Forest Land Remaining Forest
1990
8.1
j
4.7
_
2.4 ,«,
1.0 ..
2.5 ;
2.5 ^
2005
8.9
I ,J
4.3
'
3.5 „ *
1.1 ..
8.0 ;
i 8.0 j
2007
9.2
4.5
3.8
1.0
14.4
14.4
2008
9.6
5.0
3.6
1.0
8.7
8.7
2009
8.3
3.7
3.6
1.1
5.7
5.7
2010
9.4
4.7
3.7
1.0
4.7
4.7
2011
9.0
4.5
3.7
0.9
14.2
14.2
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Land: Forest Fires
N20
Forest Land Remaining Forest
Land: Forest Fires
Forest Land Remaining Forest
Land: Forest Soils3
Settlements Remaining
Settlements: Settlement Soilsb
Wetlands Remaining Wetlands:
Peatlands Remaining Peatlands
Total
3.1
2.0
0.1
1.0 '
+
13.7
,«sl 8.4 ,<
2,417 •' - •
/-•'
1,033 ;
118
•' «ll
118
10
7
o _
3 -
0 ' "~
2005
; 8,933 ^
! il
: 4,349
3,504 -
•
1,079 *
383
I ' j|
383
27 '
—
21
1 ,-,«.«.,
5 -
0
2007
9,233
4,464
3,757
1,012
684
684
44
38
1
5
0
2008
9,630
5,025
3,613
992
413
413
29
23
1
5
0
2009
8,325
3,669
3,567
1,089
271
271
21
15
1
5
0
2010
9,361
4,688
3,663
1,010
222
222
18
12
1
5
0
2011
9,034
4,454
3,663
918
675
675
43
37
1
5
0
+ Emissions are less than 0.5 Tg CCh Eq.
Note: These estimates include direct emissions only. Indirect N2O emissions are reported in the Agriculture chapter. Totals may not
sum due to independent rounding.
a Estimates include emissions from N fertilizer additions on both Forest Land Remaining Forest Land, and Land Converted to Forest
Land, but not from land-use conversion.
b Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to
Settlements, but not from land-use conversion.
In following the UNFCCC requirement under Article 4.1 to develop and submit national greenhouse gas emissions
inventories, the emissions and sinks presented in this report are organized by source and sink categories and
calculated using internationally-accepted methods provided by the Intergovernmental Panel on Climate Change
(IPCC).206 Additionally, the calculated emissions and sinks in a given year for the United States are presented in a
206
See .
Land Use, Land-Use Change, and Forestry 7-3
-------
common manner in line with the UNFCCC reporting guidelines for the reporting of inventories under this
international agreement.207 The use of consistent methods to calculate emissions and sinks by all nations providing
their inventories to the UNFCCC ensures that these reports are comparable. In this regard, U.S. emissions and sinks
reported in this inventory report are comparable to emissions and sinks reported by other countries. Emissions and
sinks provided in this inventory do not preclude alternative examinations, but rather this inventory report presents
emissions and sinks in a common format consistent with how countries are to report inventories under the
UNFCCC. The report itself follows this standardized format, and provides an explanation of the IPCC methods
used to calculate emissions and sinks, and the manner in which those calculations are conducted.
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 (i.e., such that increases in the land areas within particular land-use
categories are balanced by decreases in the land areas of other categories unless the national land base is changing),
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 Inventory has been
developed in order to comply with this guidance.
Multiple databases are used to track land management in the United States, which are also used as the basis to
classify U.S. land area into the six IPCC land-use categories (i.e., Forest Land Remaining Forest Land, Cropland
Remaining Cropland, Grassland Remaining Grassland, Wetlands Remaining Wetlands, Settlements Remaining
Settlements and Other Land Remaining Other Land) and the thirty land-use change categories (e.g., Cropland
Converted to Forest Land, Grassland Converted to Forest Land, Wetlands Converted to Forest Land, Settlements
Converted to Forest Land, Other Land Converted to Forest Lands)2m (IPCC 2006). The primary databases are the
U.S. Department of Agriculture (USDA) National Resources Inventory (NRI)209 and the USDA Forest Service
(USFS) Forest Inventory and Analysis (FIA)210 Database. The U.S. Geological Survey (USGS) National Land
Cover Dataset (NLCD)211 is also used to identify land uses in regions that were not included in the NRI or FIA.
The total land area included in the U.S. Inventory is 936 million hectares. Approximately 867 million hectares of
this land base is considered managed, which has basically not changed over the time series of the Inventory (Table
7-5).212 In 2011, the United States had a total of 301 million hectares of managed Forest Land (4 percent increase
since 1990), 159 million hectares of Cropland (6.6 percent decrease since 1990), 294 million hectares of managed
Grassland (3.4 percent decrease since 1990), 43 million hectares of managed Wetlands (3.4 percent decrease since
1990), 51 million hectares of Settlements (31 percent increase since 1990), and 19 million hectares of managed
Other Land (Table 7-6). Wetlands are not differentiated between managed and unmanaged and are reported as
managed, although some wetlands would be unmanaged according to the U.S. definition (see definition later in this
section). Future improvements will include a differentiation between managed and unmanaged wetlands. In
addition, C stock changes are not currently estimated for the entire land base, which leads to discrepancies between
207 See.
208 Land-use category definitions are provided in the Methodology section.
209 NRI data is available at .
21° FIA data is available at .
211 NLCD data is available at .
The current land representation does not include areas from U.S. territories, but there are planned improvements to include
these regions in future reports
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
the area data presented here and in the subsequent sections of the NRI. Planned improvements are underway or in
development phases to conduct an inventory of C stock changes on all managed land (e.g., federal grasslands).
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.
Table 7-5: Managed and Unmanaged Land Area by Land Use Categories (thousands of
hectares)
Land Use
Categories
Managed Lands
Forest
Croplands
Grasslands
Settlements
Wetlands
Other
Unmanaged Lands
Forest
Croplands
Grasslands
Settlements
Wetlands
Other
Total
1990
866,933
290,080 /
170,309
304,636
38,675
44,409 /
18,824
69,498
14,565 /
0 /
39,675
0
0
15,258 /
936,431
2005
866,932
297,543
159,946
297,122
.. 49,660
43,816
18,844
69,499
14,565
0
39,676
0
0
15,259
936,431
2007
; 866,932
298,783
. 159,101
295,930
50,620
43,498
19,000
69,499
14,565
0
' 39,676
0
0
15,259
936,431
2008
866,932
299,355
159,096
295,528
50,617
43,351
18,985
69,499
14,565
0
39,676
0
0
15,259
936,431
2009
866,932
299,928
159,091
295,126
50,614
43,203
18,970
69,499
14,565
0
39,676
0
0
15,259
936,431
2010
866,932
300,500
159,087
294,722
50,611
43,056
18,955
69,499
14,565
0
39,676
0
0
15,259
936,431
2011
866,932
301,073
159,083
294,319
50,608
42,909
18,941
69,499
14,565
0
39,676
0
0
15,259
936,431
Table 7-6: Land Use and Land-Use Change for the U.S. Managed Land Base (thousands of
hectares)
Land Use & Land-
Use Change
Categories3
1990
2005
2007
2008
2009
2010
2011
Total Forest Land
FF
CF
GF
WF
SF
OF
Total Cropland
CC
FC
GC
we
SC
oc
Total Grassland
GG
FG
CG
290,080
284,970
1,118
3,425
66
103
398
170,309
154,842
1,118
13,583
156
431
180
304,636
294,417
1,611
7,909
297,543
285,250
2,651
7,821
255
371
1,194
159,946
143,069
675
15,067
193
688
253
297,122
277,981
2,990
14,625
298,783
287,311
2,444
7,297
262
386
1,084
159,101
143,879
568
13,581
174
669
231
295,930
278,134
2,725
13,643
299,355
287,877
2,444
7,298
262
386
1,087
159,096
143,874
568
13,580
174
669
231
295,528
277,803
2,723
13,575
299,928
288,444
2,444
7,300
263
387
1,089
159,091
143,870
568
13,580
174
669
231
295,126
277,471
2,721
13,507
300,500
289,010
2,445
7,302
264
388
1,092
159,087
143,866
568
13,580
174
669
231
294,722
277,138
2,719
13,439
301,073
289,577
2,445
7,303
265
389
1,094
159,083
143,863
568
13,580
174
669
231
294,319
276,805
2,717
13,370
Land Use, Land-Use Change, and Forestry 7-5
-------
WG
SG
OG
Total Wetlands
WW
FW
CW
GW
SW
OW
Total Settlements
SS
FS
CS
GS
WS
OS
Total Other Land
OO
FO
CO
GO
WO
SO
Grand Total
238
111
349
44,409
43,760
140
132
343
0
33
38,675
34,134
1,787
1,343
1,353
3
55
18,824
17,791
182
331
454
63
2
866,933
408
274
844
43,816
42,309
393
365
696
10
43
49,660
35,265
6,111
3,625
4,430
31
198
18,844
16,625
538
645
896
119
21
866,932
329
267
832
43,498
42,061
382
345
662
10
39
50,620
36,345
6,089
3,518
4,436
30
201
19,000
16,710
570
703
895
102
20
866,932
329
267
832
43,351
41,917
380
345
661
10
38
50,617
36,342
6,089
3,518
4,436
30
201
18,985
16,695
569
703
895
102
20
866,932
328
267
831
43,203
41,772
378
345
661
10
38
50,614
36,339
6,089
3,518
4,436
30
201
18,970
16,681
569
703
895
102
20
866,932
328
267
831
43,056
41,628
376
344
661
10
38
50,611
36,336
6,089
3,518
4,436
30
201
18,955
16,666
569
703
894
102
20
866,932
328
267
831
42,909
41,483
374
344
661
10
37
50,608
36,333
6,089
3,518
4,436
30
201
18,941
16,652
569
703
894
102
20
866,932
aThe abbreviations are "F" for Forest Land, "C" for Cropland, "G" for Grassland, "W" for Wetlands, "S" for
Settlements, and "O" for Other Lands. Lands remaining in the same land use category are identified with the
land use abbreviation given twice (e.g., "FF" is Forest Land Remaining Forest Land), and land use change
categories are identified with the previous land use abbreviation followed by the new land use abbreviation
(e.g., "CF" is Cropland Converted to Forest Land).
Notes: All land areas reported in this table are considered managed. A planned improvement is underway to
deal with an exception for wetlands which includes both managed and unmanaged lands based on the
definitions for the current U.S. Land Representation Assessment. In addition, U.S. Territories have not been
classified into land uses and are not included in the U.S. Land Representation Assessment. See Planned
Improvements for discussion on plans to include territories in future Inventories.
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 7-1. Percent of Total Land Area in the General Land-Use Categories for 2011
Percent ol Total Land Area in the General Land Use Categories for 2009
Croplands
Grasslands
Wetlands
Forest
Settlements
Other Lands
D<10% " i1l%-3050%
Note: Land use/land-yse change categories were aggregated into the 6 general land-use categories based on the current use in 2009.
Land Use, Land-Use Change, and Forestry 7-7
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IPCC Approaches for Representing Land Areas
IPCC (2006) describes three approaches for representing land areas. Approach 1 provides data on the total area for
each individual land-use category, but does not provide detailed information on changes of area between categories
and is not spatially explicit other than at the national or regional level. With Approach 1, total net conversions
between categories can be detected, but not the individual changes between the land-use categories that led to those
net changes. Approach 2 introduces tracking of individual land-use changes between the categories (e.g., Forest
Land to Cropland, Cropland to Forest Land, Grassland to Cropland, etc.), using surveys or other forms of data that
do not provide location data on specific parcels of land. Approach 3 extends Approach 2 by providing location data
on specific parcels of land, such as maps, along with the land-use history. The three approaches are not presented as
hierarchical tiers and are not mutually exclusive.
According to IPCC (2006), the approach or mix of approaches selected by an inventory agency should reflect
calculation needs and national circumstances. For this analysis, the NRI, FIA, and the NLCD have been combined
to provide a complete representation of land use for managed lands. These data sources are described in more detail
later in this section. All of these datasets have a spatially-explicit time series of land-use data, and therefore
Approach 3 is used to provide a full representation of land use in the U. S. Inventory. Lands are treated as remaining
in the same category (e.g., Cropland Remaining Cropland) if a land-use change has not occurred in the last 20 years.
Otherwise, the land is classified in a land-use-change category based on the current use and most recent use before
conversion to the current use (e.g., Cropland Converted to Forest Land).
Definitions of Land Use in the United States
Managed and Unmanaged Land
The U.S. definitions of managed and unmanaged lands are similar to the basic IPCC (2006) definition of managed
land, but with some additional elaboration to reflect national circumstances. Based on the following definitions,
most lands in the United States are classified as managed:
• Managed Land: Land is considered managed if direct human intervention has influenced its condition.
Direct intervention occurs mostly in areas accessible to human activity and 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 where these areas are readily accessible to
society.213
• Unmanaged Land: All other land is considered unmanaged. Unmanaged land is largely comprised of areas
inaccessible to society due to the remoteness of the locations. Though these lands may be influenced
indirectly by human actions such as atmospheric deposition of chemical species produced in industry or
CO2 fertilization, they are not influenced by a direct human intervention.214
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 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. As a result, all wetlands are
reported as managed. See the Planned Improvements section of the Inventory for work being done to refine the Wetland area
estimates.
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.
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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In addition, managed land that is converted to unmanaged remains in the managed land base for 20 years to account
for legacy effects of management on C stocks.
Land-Use Categories
As with the definition of managed lands, IPCC (2006) provides general non-prescriptive definitions for the six main
land-use categories: Forest Land, Cropland, Grassland, Wetlands, Settlements and Other Land. In order to reflect
U.S. circumstances, country-specific definitions have been developed, based predominantly on criteria used in the
land-use surveys for the United States. Specifically, the definition of Forest Land is based on the FIA definition of
forest,215 while definitions of Cropland, Grassland, and Settlements are based on the NRI.216 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 areas at least 36.6m wide and 0.4 ha in size with at least 10
percent cover (or equivalent stocking) by live trees of any size, including land that formerly had such tree
cover and that will be naturally or artificially regenerated. Forest land includes transition zones, such as
areas between forest and non-forest lands that have at least 10 percent cover (or equivalent stocking) with
live trees and forest areas adjacent to urban and built-up lands. Roadside, streamside, and shelterbelt strips
of trees must have a crown width of at least 36.6m and continuous length of at least 110.6 m to qualify as
forest land. Unimproved roads and trails, streams, and clearings in forest areas are classified as forest if
they are less than 36.6 m wide or 0.4 ha in size; otherwise they are excluded from Forest Land and
classified as Settlements. Tree-covered areas in agricultural production settings, such as fruit orchards, or
tree-covered areas in urban settings, such as city parks, are not considered forest land (Smith et al. 2009).
• 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.217 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,218 as well as lands in temporary fallow or enrolled in conservation
reserve programs (i.e., set-asides219). Roads through Cropland, including interstate highways, state
highways, other paved roads, gravel roads, dirt roads, and railroads are excluded from Cropland area
estimates and are, instead, classified as Settlements.
• Grassland: A land-use category on which the plant cover is composed principally of grasses, grass-like
plants (i.e., sedges and rushes), forbs, or shrubs suitable for grazing and browsing, and includes both
pastures and native rangelands.220 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.221 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,
215 See.
216 See < http://www.nrcs.usda.gov/wps/portal/nrcs/site/national/home>.
217 A minor portion of Cropland occurs on federal lands, and is not currently included in the C stock change inventory. A
planned improvement is underway to include these areas in future C inventories.
218 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.
219 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.
220 Grasslands on federal lands are included in the managed land base, but C stock changes are not estimated on these lands.
Federal grassland areas have been assumed to have negligible changes in C due to limited land use and management change, but
planned improvements are underway to further investigate this issue and include these areas in future C inventories.
221 IPCC (2006) guidelines do not include provisions to separate desert and tundra as land categories.
Land Use, Land-Use Change, and Forestry 7-9
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dirt roads, and railroads are excluded from Grassland area estimates and are, instead, classified as
Settlements.
• 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. Certain areas that fall under the managed Wetlands definition are covered in other areas of the
IPCC guidance and/or the inventory, including Cropland (e.g., rice cultivation), Grassland, and Forest Land
(including drained or undrained forested wetlands).
• Settlements: A land-use category representing developed areas consisting of units of 0.25 acres (0.1 ha) or
more that includes residential, industrial, commercial, and institutional land; construction sites; public
administrative sites; railroad yards; cemeteries; airports; golf courses; sanitary landfills; sewage treatment
plants; water control structures and spillways; parks within urban and built-up areas; and highways,
railroads, and other transportation facilities. Also included are tracts of less than 10 acres (4.05 ha) that may
meet the definitions for Forest Land, Cropland, Grassland, or Other Land but are completely surrounded by
urban or built-up land, and so are included in the settlement category. Rural transportation corridors
located within other land uses (e.g., Forest Land, Cropland, and Grassland) are also included in
Settlements.
• Other Land: A land-use category that includes bare soil, rock, ice, and all land areas that do not fall into
any of the other five land-use categories, which allows the total of identified land areas to match the
managed land base.
to
U.S. Land-Use Data Sources
The three main data sources for land area and use data in the United States are the NRI, FIA, and the NLCD. For
the Inventory, the NRI is the official source of data on all land uses on non-federal lands (except forest land), and is
also used as the resource to determine the total land base for the conterminous United States and Hawaii. The NRI is
conducted by the USD A Natural Resources Conservation Service and is designed to assess soil, water, and related
environmental resources on non-federal lands. The NRI has a stratified multi-stage sampling design, where primary
sample units are stratified on the basis of county and township boundaries defined by the U. S. Public Land Survey
(Nusser and Goebel 1997). Within a primary sample unit (typically a 160-acre [64.75 ha] square quarter-section),
three sample points are selected according to a restricted randomization procedure. Each point in the survey is
assigned an area weight (expansion factor) based on other known areas and land-use information (Nusser and
Goebel 1997). The NRI survey utilizes data derived from remote sensing imagery and site visits in order to provide
detailed information on land use and management, particularly for croplands and grasslands, and is used as the basis
to account for C stock changes in agricultural lands (except federal Grasslands). The NRI survey was conducted
every 5 years between 1982 and 1997, but shifted to annualized data collection in 1998. This Inventory incorporates
data through 2007 from the NRI.
The FIA program, conducted by the USFS, is the official source of data on Forest Land area and management data
for the Inventory. FIA engages in a hierarchical system of sampling, with sampling categorized as Phases 1 through
3, in which sample points for phases are subsets of the previous phase. Phase 1 refers to collection of remotely -
sensed data (either aerial photographs or satellite imagery) primarily to classify land into forest or non-forest and to
identify landscape patterns like fragmentation and urbanization. Phase 2 is the collection of field data on a network
of ground plots that enable classification and summarization of area, tree, and other attributes associated with forest
land uses. Phase 3 plots are a subset of Phase 2 plots where data on indicators of forest health are measured. Data
from all three phases are also used to estimate C stock changes for forest land. Historically, FIA inventory surveys
had been conducted periodically, with all plots in a state being measured at a frequency of every 5 to 14 years. A
new national plot design and annual sampling design was introduced by FIA about ten years ago. Most states,
though, have only recently been brought into this system. Annualized sampling means that a portion of plots
throughout each state is sampled each year, with the goal of measuring all plots once every 5 years. See Annex 3.12
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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to see the specific survey data available by state. The most recent year of available data varies state by state (range
of most recent data is from 2002 through 2012).
Though NRI provides land-area data for both federal and non-federal lands, it only includes land-use data on non-
federal lands, and FIA only records data for forest land.222 Consequently, 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 Alaska.223 The NLCD is used as a supplementary database to account for land use
on federal lands that are not included in the NRI and FIA databases. The NLCD land-cover classification scheme,
available for 1992, 2001, and 2006, has been applied over the conterminous United States (Homer et al. 2007), and
also for Alaska and Hawaii in 2001. For the conterminous United States, the NLCD Land Cover Change Products
for 2001 and 2006 were used in order to represent both land use and land-use change for federal lands (Fry et al.
2011, Homer et al. 2007). The NLCD products are based primarily on Landsat Thematic Mapper imagery. The
NLCD contains 21 categories of land-cover information, which have been aggregated into the IPCC land-use
categories, and the data are available at a spatial resolution of 30 meters. The federal land portion of the NLCD was
extracted from the dataset using the federal land area boundary map from the National Atlas (U.S. Department of
Interior 2005). This map represents federal land boundaries in 2005, so as part of the analysis, the federal land area
was adjusted annually based on the NRI federal land area estimates (i.e., land is periodically transferred between
federal and non-federal ownership). Consequently, the portion of the land base categorized with NLCD data varied
from year to year, corresponding to an increase or decrease in the federal land base. The NLCD is strictly a source of
land-cover information, however, and does not provide the necessary site conditions, crop types, and management
information from which to estimate C stock changes on those lands.
Another step in the analysis is to address gaps as well as overlaps in the representation of the U.S. land base between
the Agricultural Carbon Stock Inventory (Cropland Remaining Cropland, Land Converted to Cropland, Grassland
Remaining Grassland, Land Converted to Grassland) and Forest Land Carbon Stock Inventory (Forest Land
Remaining Forest Land and Land Converted to Forest Land), which are based on the NRI and FIA databases,
respectively. NRI and FIA have different criteria for classifying forest land and sampling designs, leading to
discrepancies in the resulting estimates of Forest Land area on non-federal land. Similarly, there are discrepancies
between the NLCD and FIA data for defining and classifying Forest Land on federal lands. Moreover, dependence
exists between the Forest Land area and the amount of land designated as other land uses in both the NRI and the
NLCD, such as the amount of Grassland, Cropland, and Wetlands, relative to the Forest Land area. This results in
inconsistencies among the three databases for estimated Forest Land area, as well as for the area estimates for other
land-use categories. FIA is the main database for forest statistics, and consequently, the NRI and NLCD were
adjusted to achieve consistency with FIA estimates of Forest Land. The adjustments were made at a state-scale, and
it was assumed that the majority of the discrepancy in forest area was associated with an under- or over-prediction of
Grassland and Wetland area in the NRI and NLCD due to differences in Forest Land definitions. Specifically, the
Forest Land area for a given state according to the NRI and NLCD was adjusted to match the FIA estimates of
Forest Land for non-federal and federal land, respectively. In a second step, corresponding increases or decreases
were made in the area estimates of Grassland and Wetland from the NRI and NLCD, in order to balance the change
in forest area, and therefore not change the overall amount of managed land within an individual state. The
adjustments were based on the proportion of land within each of these land-use categories at the state-level, (i.e., a
higher proportion of Grassland led to a larger adjustment in Grassland area).
As part of Quality Assurance /Quality Control (QA/QC), the land base derived from the NRI, FIA and NLCD was
compared to the Topologically Integrated Geographic Encoding and Referencing (TIGER) survey (U.S. Census
Bureau 2010). The U.S. Census Bureau gathers data on the U.S. population and economy, and has a database of
land areas for the country. The land area estimates from the U.S. Census Bureau differ from those provided by the
land-use surveys used in the Inventory because of discrepancies in the reporting approach for the census and the
methods used in the NRI, FIA, and NLCD. The area estimates of land-use categories, based on NRI, FIA, and
NLCD, are derived from remote sensing data instead of the land survey approach used by the U.S. Census Survey.
More importantly, the U.S. Census Survey does not provide a time series of land-use change data or land
222 pjA does collect some data on non-forest land use, but these are held in regional databases versus the national database. The
status of these data is being investigated.
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.
Land Use, Land-Use Change, and Forestry 7-11
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management information, which is critical for conducting emission inventories and is provided from the NRI and
FIA surveys. Consequently, the U.S. Census Survey was not adopted as the official land area estimate for the
Inventory. Rather, the NRI data were adopted because this database provides full coverage of land area and land use
for the conterminous United States and Hawaii. Regardless, the total difference between the U.S. Census Survey
and the NRI data is about 25 million hectares for the total conterminous U.S. land base of about 786 million hectares
currently included in the Inventory, or a 3.1 percent difference. Much of this difference is associated with open
waters in coastal regions and the Great Lakes. NRI does not include as much of the area of open waters in these
regions as the U.S. Census Survey.
Managed Land Designation
Lands are designated as managed in the United States based on the definitions provided earlier in this section. In
order to apply the definitions in an analysis of managed land, the following criteria are used:
• All croplands and settlements are designated as managed so only grassland, forest land or other lands may
be designated as unmanaged land;224
• All forest lands with active fire protection are considered managed;
• All grasslands are considered managed at a county scale if there are livestock in the county;
• Other areas are considered managed if accessible based on the proximity to roads and other transportation
corridors, and/or infrastructure; and
• Lands that were previously managed remain in the managed land base for 20 years following the
conversion to account for legacy effects of management on C stocks.
These criteria will be expanded in the future as other data sources become available, such as national datasets on
mining and resource extraction.
The analysis of managed lands is conducted using a geographic information system. Lands that are used for crop
production or settlements are determined from the NLCD (Fry et al. 2011, Homer et al. 2007). Active fire
management is determined from maps of federal and state management plans from the National Atlas (U.S.
Department of Interior 2005) and Alaska Interagency Fire Management Council (1998). It is noteworthy that all
federal lands in the conterminous U.S. have active fire protection, and are therefore designated as managed. The
designation of grasslands as managed is determined based on USDA-NASS livestock population data at the county
scale (U. S. Department of Agriculture 2011). Accessibility is evaluated based on a 10km buffer surrounding road
and train transportation networks using the ESRI Data and Maps product (ESRI 2008), and a 10km buffer
surrounding settlements using NLCD. The resulting managed land area is overlaid on the NLCD to estimate the area
of managed land by land use for both federal and non-federal lands. The remaining land represents the unmanaged
land base.
Approach for Combining Data Sources
The managed land base in the United States has been classified into the six IPCC land-use categories using
definitions developed to meet national circumstances, while adhering to IPCC (2006). 225 In practice, the land was
initially classified into a variety of land-use categories using the NRI, FIA and NLCD, and then aggregated into the
thirty-six broad land use and land-use-change categories identified in IPCC (2006). Details on the approach used to
combine data sources for each land use are described below as are the gaps that will be reconciled as part of ongoing
planned improvements:
• Forest Land: Both non-federal and federal forest lands in 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 so forest land in Alaska
is evaluated with 2001 NLCD. Forest Lands in U.S. territories are currently excluded from the analysis,
but FIA surveys are currently being conducted on U.S. territories and will become available in the future.
224 A planned improvement is underway to deal with an exception for wetlands which includes both managed and unmanaged
lands based on the definitions for the current U.S. Land Representation Assessment.
225 Definitions are provided in the previous section.
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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NRI is being used in the current report to provide Forest Land areas on non-federal lands in Hawaii.
Currently, federal forest land in Hawaii is evaluated with the 2001 NLCD, but FIA data will be collected in
Hawaii in the future.
• Cropland: Cropland is classified using the NRI, which covers all non-federal lands within 49 states
(excluding Alaska), including state and local government-owned land as well as tribal lands. NRI is used
as the basis for both Cropland area data as well as to estimate C stocks and fluxes on Cropland. NLCD
2001 is used to determine Cropland area in Alaska. Croplands in U.S. territories are excluded from both
NRI data collection and the NLCD.
• Grassland: Grassland on non-federal lands is classified using the NRI within 49 states (excluding Alaska),
including state and local government-owned land as well as tribal lands. NRI is used as the basis for both
Grassland area data as well as to estimate C stocks and fluxes on Grassland. U.S. territories are excluded
from both NRI data collection and the current release of the NLCD product. Grassland on federal Bureau
of Land Management lands, Department of Defense lands, National Parks and within USFS lands are
covered by the NLCD. In addition, federal and non-federal grasslands in Alaska are currently excluded
from the analysis, but NLCD has a new product for Alaska that will be incorporated into the assessment for
future reports.
• Wetlands: NRI captures wetlands on non-federal lands within 49 states (excluding Alaska), while federal
wetlands and wetlands in Alaska are covered by the NLCD. U.S. territories are excluded. This currently
includes both managed and unmanaged wetlands as no database has yet been applied to make this
distinction. See Planned Improvements for details.
• Settlements: The NRI captures non-federal settlement area in 49 states (excluding Alaska). If areas of
Forest Land or Grassland under 10 acres (4.05 ha) are contained within settlements or urban areas, they are
classified as Settlements (urban) in the NRI database. If these parcels exceed the 10 acre (4.05 ha)
threshold and are Grassland, they will be classified as such by NRI. Regardless of size, a forested area is
classified as non-forest by FIA if it is located within an urban area. Settlements on federal lands and in
Alaska are covered by NLCD. Settlements in 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 for non-federal areas in the 49 states (excluding Alaska) and NLCD for the
federal lands and Alaska. Other land in U.S. territories is 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
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 are considered Croplands if they are used for crop production, such as rice or
cranberries. 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.
The assignment priority does not reflect the level of importance for reporting greenhouse gas emissions and
removals on managed land, but is intended to classify all areas into a single land use. Currently, the IPCC does not
make provisions in the guidelines for assigning land to multiple uses. For example, a Wetland is classified as Forest
Land Use, Land-Use Change, and Forestry 7-13
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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 for crop production, such as rice or cranberries. 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).
Alaska was added to the latest inventory and a formal analysis was conducted for managed and unmanaged lands.
Both improvements led to significant changes in the reporting of the managed land base. Overall more land area is
incorporated into this Inventory, but a large portion of this land is designated as unmanaged due to the remoteness of
some areas in Alaska.
In addition, new data were incorporated from FIA on forestland areas, which was used to make minor adjustments to
the time series. FIA conducts a survey of plots annually so that each plot is visited every 5 years (Note: some states
have not initiated the annual sampling regime, as discussed previously). Consequently, the time series is updated
each year as new data are collected over the 5 year cycles.
Area data by land-use category are not estimated for the U.S. territories. A key planned improvement is to
incorporate land-use data from these areas into the Inventory. Fortunately, most of the managed land in the United
States is included in the current land-use statistics, but a complete accounting is a key goal for the near future. Data
sources will also be evaluated for representing land use on federal and non-federal lands in U.S. territories.
Additional work will be conducted 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, and an analysis
is planned to develop region-specific adjustments.
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.
The implementation criteria will also be expanded in the future, particularly in regard to inclusion of areas managed
for mining and petroleum extraction. This criteria will have an impact on the managed land base in Alaska although
there will still be large tracts of unmanaged land in this region with virtually no direct influence on GHG emissions
from human activity.
In
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.
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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• 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 (HWP) in use.
• HWP in solid waste disposal sites (SWDS).
Carbon is continuously cycled among these storage pools and between forest ecosystems and the atmosphere as a
result of biological processes in forests (e.g., photosynthesis, respiration, growth, mortality, decomposition, and
disturbances such as fires or pest outbreaks) and anthropogenic activities (e.g., harvesting, thinning, clearing, and
replanting). As trees photosynthesize and grow, C is removed from the atmosphere and stored in living tree
biomass. As trees die and otherwise deposit litter and debris on the forest floor, C is released to the atmosphere and
also is 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 of all vegetation C to the atmosphere. Instead, harvesting transfers a
portion of the C stored in wood to a "product pool." Once in a product pool, the C is emitted over time as €62 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. Changes in C stocks
from disturbances, such as forest fires, are implicitly included in the net changes. For instance, an inventory
conducted after fire counts only the trees that are 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.
Similarly, changes in C stocks from natural disturbances, such as wildfires, pest outbreaks, and storms, are implicitly
accounted for in the forest inventory approach; however, they are highly variable from year to year. Wildfire events
are typically the most severe but other natural disturbance events can result in large C stock losses that are time- and
location- specific. 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 just becoming available for the conterminous United States to allow forest land conversions
and forest land remaining forest land to be identified, and research is ongoing to properly use that information based
on research results. Thus, net changes in all forest-related land, including non-forest land converted to forest and
forests converted to non-forest, are reported here.
Forest C storage pools, and the flows between them via emissions, sequestration, and transfers, are shown in Figure
7-2. In the figure, boxes represent forest C storage pools and arrows represent flows between storage pools or
between storage pools and the atmosphere. Note that the boxes are not identical to the storage pools identified in
this chapter. The storage pools identified in this chapter have been refined in this graphic to better illustrate the
processes that result in transfers of C from one pool to another, and emissions to as well as uptake from the
atmosphere.
Land Use, Land-Use Change, and Forestry 7-15
-------
Figure 7-2: Forest Sector Carbon Pools and Flows
Forest Sector Carbon Pools and Flows
AtrnDephsrs
Combustion from forest fires
{carbon dioxide, mothans)
Growth
-%: -
DecompOftliQn;,
Combustion f
WOM!
UHa=
Hawwts
Live,
Vspetition
/ / Processing/
/ / /*~-\_Consump!lon
HwvwtX
Residus \ UBerW
\MaHMy
Mortalto
^P0881/ IndmndoVi-, \
I ^-* , \ '
\ D®c«npo««on MMhanii\ /
\ Bartng \ ^
\ and j /
\ UBlizalion / /
r
Combustion
legend
[3 CsrtwnPool
—> Carbon transfer or Hut
Swires Heath el •!. 2003
Approximately 33 percent (304 million hectares) of the U.S. land area is forested (Smith et al. 2009). The current
forest C inventory includes 275 million hectares in the conterminous 48 states (USDA Forest Service 2012a, 2012b)
that are considered managed and are included in this inventory. An additional 6 million hectares of southeast and
south central Alaskan forest are inventoried and are included here. Some differences exist in forest land defined in
Smith et al. (2009) and the forest land included in this report, which is based on USDA Forest Service (2012b).
Survey data are not yet available from Hawaii and a large portion of interior Alaska, but estimates of these areas are
included in Smith et al. (2009). Alternately, updated survey data for central and western forest land in both
Oklahoma and Texas have only recently become available, and these forests contribute to overall C stock reported
below. While Hawaii and U.S. territories have relatively small areas of forest land and will thus probably not
influence the overall C budget substantially, these regions will be added to the C budget as sufficient data become
available. Agroforestry systems are also not currently accounted for in the inventory, since they are not explicitly
inventoried by either the FIA program of USDA Forest Service or the NRI of the USDA Natural Resources
Conservation Service (Perry et al. 2005).
Sixty-eight percent (208 million hectares) of U.S. forests in Alaska and the conterminous U.S. are classified as
timberland, meaning they meet minimum levels of productivity and have not been removed from production. Nine
percent of Alaskan forests and 81 percent of forests in the conterminous United States are classified as timberlands.
Of the remaining nontimberland forests, 30 million hectares are reserved forest lands (withdrawn by law from
management for production of wood products) and 66 million hectares are lower productivity forest lands (Smith et
al. 2009). Historically, the timberlands in the conterminous 48 states have been more frequently or intensively
surveyed than other forest lands.
Forest land area 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 12 million hectares (Smith et al. 2009). Current trends in
forest area represent an average annual increase of 0.2 percent. In addition to the increase in forest 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
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
biomass density of the forest, thereby increasing the uptake of C.226 Though harvesting forests removes much of the
aboveground C, on average the volume of annual net growth nationwide is about 72 percent higher than the volume
of annual removals on timberlands (Smith et al. 2009). 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, and
timber harvesting and use have resulted in net uptake (i.e., net sequestration) of C each year from 1990 through
2011. 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 influence C
fluxes from these forest lands. More recently, the 1970s and 1980s saw a resurgence of federally-sponsored forest
management programs (e.g., the Forestry Incentive Program) and soil conservation programs (e.g., the Conservation
Reserve Program), which have focused on tree planting, improving timber management activities, combating soil
erosion, and converting marginal cropland to forests. In addition to forest regeneration and management, forest
harvests have also affected net C fluxes. Because most of the timber harvested from U.S. forests is used in wood
products, and many discarded wood products are disposed of in SWDS rather than by incineration, significant
quantities of C in harvested wood are transferred to long-term storage pools rather than being released rapidly to the
atmosphere (Skog and Nicholson 1998, Skog 2008). The size of these long-term C storage pools has increased
during the last century.
Changes in C stocks in U.S. forests and harvested wood were estimated to account for net sequestration of 834 Tg
CO2Eq. (227 Tg C) in 2011 (Table 7-7, Table 7-8, and Table 7-9). 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 54 to 62 Mg C/ha
between 1990 and 2012 (see Annex 3-12 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
2011 are the result of the sequences of new inventories for each state. C in forest ecosystem biomass had the
greatest effect on total change through increases in 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.
Annual net additions to HWP carbon stock were estimated to continue to increase during 2011 from a low in 2009
as inputs to products in use for both solid wood and paper products increased with continued recovery from the
recession. Gross inputs to products in use in 2011 were well above the discard rate but net additions to products in
use were still about 25 percent below the rate for 2008. The primary reason for overall net additions in recent years
is a near stable rate of net additions to products in landfills. Estimates of C additions for 2008, 2009 and 2010 were
adjusted downward due to revision in data on softwood pulpwood production, hardwood lumber production,
hardwood plywood production, and imports of particleboard and medium density fiberboard. Due to the change in
import data, estimates of C storage were reduced more for the Stock Change Accounting approach (Annex Table A-
228) than the Production Approach (Table 7-7, Annex Table A-228).
Table 7-7: Net Annual Changes in C Stocks (Tg COz/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground
Biomass
Belowground
Biomass
Dead Wood
Litter
1990
(565.1)
(359.8)
(70.3)
(32.6)
(25.0)
2005
(799.6)
(436.4)
(86.0)
(47.1) -
(49.6) ,
; 2007
(757.0)
(404.0)
(80.1)
: (52.3)
(54.5)
2008
(757.1)
(403.9)
(80.1)
(52.3)
(54.5)
2009
(757.1)
(403.9)
(80.1)
(52.3)
(54.5)
2010
(758.2)
(403.9)
(80.1)
(53.4)
(54.5)
2011
(761.8)
(403.9)
(80.1)
(57.1)
(54.5)
226 jjjg 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.
Land Use, Land-Use Change, and Forestry 7-17
-------
Soil Organic
Carbon
Harvested Wood
Products in Use
SWDS
Total Net Flux
(77.4) -
(131.8)
(64.8)
(67.0)
(696.8)
(180.5)
(105.4)
(45.4)
(59.9)
(905.0)
(166.2)
(102.3)
(38.5)
(63.8)
(859.3)
(166.3)
(76.3)
(13.6)
(62.7)
(833.3)
(166.3)
(54.3)
6.8
(61.0)
(811.3)
(166.3)
(59.4)
1.2
(60.7)
(817.6)
(166.3)
(71.7)
(10.0)
(61.7)
(833.5)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a portion of managed forests in 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 7-8: 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
(154.1)
(98.1)
(19.2) •: ,
(8.9) .-
(6.8)
(2i.i) ;•
(35.9)
(17.7)
(18.3) ,,
(190.0)
2005
(218.1) «
(119.0)
,*•
(23.4)
(12.9)
(13.5) „
(49.2)
(28.7)
(12.4)
(16.3)
(246.8)
2007
! (206.5)
(110.2)
(21.8)
(14.3)
(14.9)
(45.3)
(28.1)
(10.5)
(17.4)
(234.4)
2008
(206.5)
(110.2)
(21.8)
(14.3)
(14.9)
(45.4)
(20.8)
(3.7)
(17.1)
(227.3)
2009
(206.5)
(110.2)
(21.8)
(14.3)
(14.9)
(45.4)
(14.8)
1.8
(16.6)
(221.3)
2010
(206.8)
(110.2)
(21.8)
(14.6)
(14.9)
(45.4)
(16.2)
0.3
(16.5)
(223.0)
2011
(207.8)
(110.2)
(21.8)
(15.6)
(14.9)
(45.4)
(19.5)
(2.7)
(16.8)
(227.3)
Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a portion of managed lands in 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 7-9. Together, the
aboveground live and forest soil pools account for a large proportion of total forest C stocks. C stocks summed for
non-soil pools increased over time Figure 7-3. 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 7-9: Forest area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools
Forest Area
(1000 ha)
Carbon Pools
(TgC)
Forest
Aboveground
Biomass
Belowground
Biomass
Dead Wood
Litter
Soil Organic C
Harvested
Wood
1990
271,794
38,777
12,284 •
2,432 •.
2,161
4,816
17,084
1,859
2005
279,781 „
41,192
„
13,912 -
2>752 J
2,342
4,880
17,306 "
2,325
2007
4 281,090
41,618
14,146
1 2=798
2,368
4,908
17,399
2,383
2008
281,694
41,825
14,256
2,820
2,383
4,923
17,444
2,411
2009
282,300
42,031
14,366
2,842
2,397
4,937
17,489
2,432
2010
282,905
42,238
14,476
2,863
2,411
4,952
17,535
2,447
2011
283,510
42,444
14,586
2,885
2,426
4,967
17,580
2,463
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Products in Use
SWDS
1,231
628
1,436
890
1,460
923
1,471
941
1,474
958
1,472
974
1,472
991
Total C Stock
40,637
43,517
44,002 44,236 44,463 44,684 44,907
Note: Forest area estimates include portions of managed forests in Alaska for which survey data are available.
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. (2010) 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
25 i
3
IS
-25 -
-75 -
-125
8 -175 -
I
£
-225 -
-275 J
Harvested Wood
- Soil
.-• Forest, Nonsoil
Total Net Change
OOOOOO
G*o
O-rH
Land Use, Land-Use Change, and Forestry 7-19
-------
Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States,
2010
Average C Density in the Forest Tree Pool in the Conterminous United States, 2011
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 forest fire 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 CCh emissions from fire disturbance, these estimates are 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 and IPCC (2006) default combustion factor for wildfire were employed to estimate
CO2 emissions from forest fires. €62 emissions for wildfires and prescribed fires in the lower 48 states and
wildfires in Alaska in 2011 were estimated to be 225.3 TgCO2/yr. This amount is masked in the estimate of net
annual forest C stock change for 2011 because this net estimate accounts for the amount sequestered minus any
emissions.
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 7-10: Estimates of COz (Tg/yr) Emissions for the Lower 48 States and Alaska3
Year
CCh emitted from
Wildfires in
Lower 48 States
(Tg/yr)
COi emitted from
Prescribed Fires
in Lower 48 States
(Tg/yr)
COi emitted from
Wildfires in
Alaska (Tg/yr)
Total CO2 emitted
(Tg/yr)
1990
32.4
7.1
39.5
2005
107.0
20.7
127.7
2007
2008
2009
2010
2011
203.5
122.5
70.6
54.9
208.0
24.8
15.3
20.1
19.3
17.3
+ 228.3
+ 137.8
+ 90.6
+ 74.2
+ 225.3
+ Does not exceed 0.05 Tg CCh Eq.
a Note that these emissions have already been accounted for in the estimates of net annual changes in C
stocks, which account for the amount sequestered minus any emissions.
Methodology and Data Sources
The methodology described herein is consistent with IPCC (2003, 2006) and IPCC/UNEP/OECD/IEA (1997).
Forest ecosystem C stocks and net annual C stock change were determined according to stock-difference methods,
which involved applying C estimation factors to forest inventory data and interpolating between successive
inventory-based estimates of C stocks. Harvested wood C estimates were 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 the amount placed in use
will have been discarded from use) and expected disposition (e.g., product pool, SWDS, combustion). An overview
of the different methodologies and data sources used to estimate the C in forest ecosystems or harvested wood
products is provided here. See Annex 3.12 for details and additional information related to the methods and data.
Forest Ecosystem Carbon from Forest Inventory
Forest ecosystem stock and flux estimates are based on the stock-difference method and calculations for all
estimates are in units of C. Separate estimates were made for the five IPCC C storage pools described above. All
estimates were based on data collected from the extensive array of permanent forest inventory plots in the United
States as well as models employed to fill gaps in field data (USDA Forest Service 2012b, 2012c). Carbon
conversion factors were applied at the disaggregated level of each inventory plot and then appropriately expanded to
population estimates. A combination of tiers as outlined by IPCC (2006) was used. The Tier 3 biomass C values
were calculated from forest inventory tree-level data. The Tier 2 dead organic and soil C pools were based on
empirical or process models from the inventory data. All C conversion factors are specific to regions or individual
states within the United States, which were further classified according to characteristic forest types within each
region.
The first step in developing forest ecosystem estimates is to identify useful inventory data and resolve any
inconsistencies among datasets. Forest inventory data were obtained from the FIA program (Prayer and Furnival
1999, USDA Forest Service 2012b). Inventories include data collected on permanent inventory plots on forest lands
and were organized as a number of separate datasets, each representing a complete inventory, or survey, of an
individual state at a specified time. 227 Many of the more recent annual inventories reported for states were
represented as "moving window" averages, which means that a portion—but not all—of the previous year's
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 7-21
-------
inventory is updated each year (USDA Forest Service 2012d). Forest C calculations were organized according to
these state surveys, and the frequency of surveys varies by state. All available data sets were identified for each
state starting with pre-1990 data, and all unique surveys were identified for stock and change calculations. Since C
stock change is based on differences between successive surveys within each state, accurate estimates of net C flux
thus depend on consistent representation of forest land between these successive inventories. In order to achieve
this consistency from 1990 to the present, states were sometimes subdivided into sub-state areas where the sum of
sub-state inventories produces the best whole-state representation of C change as discussed in Smith et al. (2010).
The principal FIA datasets employed are freely available for download at USDA Forest Service (2012b) as the
Forest Inventory and Analysis Database (FIADB) Version 5.1 (USDA Forest Service 2012, Woudenberg et al.
2010). However, to achieve consistent representation (spatial and temporal), three other general sources of past FIA
data were included as necessary. First, older FIA plot- and tree-level data—not in the current FIADB format—were
used if available. Second, Resources Planning Act Assessment (RPA) databases, which are periodic, plot-level
only, summaries of state inventories, were used to provide the data at or before 1990. Finally, an additional forest
inventory data source used was the Integrated Database (IDE), which is a compilation of periodic forest inventory
data from the 1990s for California, Oregon, and Washington (Waddell and Hiserote 2005). These IDE data were
identified by Heath et al. (2011) as the most appropriate non-FIADB sources for these states and were included in
this inventory. See USDA Forest Service (2012a) for information on current and older data as well as additional
FIA Program features. A detailed list of the specific forest inventory data used in this inventory is in Annex 3.12.
Forest C stocks were estimated from inventory data by a collection of conversion factors and models (Birdsey and
Heath 1995, Birdsey and Heath 2001, Heath et al. 2003, Smith et al. 2004, Smith et al. 2006), which have been
formalized in an FIADB-to-C calculator (Smith et al. 2010). The conversion factors and model coefficients were
categorized by region and forest type, and forest C stock estimates were calculated from application of these factors
at the scale of FIA inventory plots. The results were estimates of C density (Mg C per hectare) for six forest
ecosystem pools: live trees, standing dead trees, understory vegetation, down dead wood, forest floor, and soil
organic matter. The six C pools used in the FIADB-to-C calculator were aggregated to the 5 C pools defined by
IPCC (2006): aboveground biomass, belowground biomass, dead wood, litter, and soil organic matter. The live-tree
and understory C were pooled as biomass, and standing dead trees and down dead wood were pooled as dead wood,
in accordance with IPCC (2006).
Once plot-level C stocks were calculated as C densities on Forest Land Remaining Forest Land for the five IPCC
(2006) reporting pools, the stocks were expanded to population estimates according to methods appropriate to the
respective inventory data (for example, see Bechtold and Patterson (2005)). These expanded C stock estimates were
summed to state or sub-state total C stocks. Annualized estimates of C stocks were developed by using available
FIA inventory data and interpolating or extrapolating to assign a C stock to each year in the 1990 through 2012 time
series. Flux, or net annual stock change, was estimated by calculating the difference in stocks between two
successive years and applying the appropriate sign convention; net increases in ecosystem C were identified as
negative flux. By convention, inventories were assigned to represent stocks as of January 1 of the inventory year; an
estimate of flux for 1996 required estimates of C stocks for 1996 and 1997, for example. Additional discussion of
the use of FIA inventory data and the C conversion process is in Annex 3.12.
Carbon in Biomass
Live tree C pools include aboveground and belowground (coarse root) biomass of live trees with diameter at
diameter breast height (dbh) of at least 2.54 cm at 1.37 m above the forest floor. Separate estimates were made for
above- and below-ground biomass components. If inventory plots included data on individual trees, tree C was
based on Woodall et al. (201 la), which is also known as the component ratio method (CRM), and is a function of
volume, species, and diameter. An additional component of foliage, which was not explicitly included in Woodall et
al. (201 la), was added to each tree following the same CRM method. Some of the older forest inventory data in use
for these estimates did not provide measurements of individual trees. Examples of these data include plots with
incomplete or missing tree data or the RPA plot-level summaries. The C estimates for these plots were based on
average densities (metric tons C per hectare) obtained from plots of more recent surveys with similar stand
characteristics and location. This applies to 5 percent of the forest land inventory-plot-to-C conversions within the
183 state-level surveys utilized here.
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 dbh. In the current inventory, it was assumed that 10
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
percent of total understory C mass is belowground. Estimates of C density were based on information in Birdsey
(1996) and biomass estimates from Jenkins et al. (2003). Understory frequently represented over 1 percent of C in
biomass, but its contribution rarely exceeded 2 percent of the total.
Carbon in Dead Organic Matter
Dead organic matter was initially calculated as three separate pools—standing dead trees, down dead wood, and
litter—with C stocks estimated from sample data or modeled. The standing dead tree C pools include aboveground
and belowground (coarse root) mass and include trees of at least 12.7 cm dbh. Calculations followed the basic
method applied to live trees (Woodall et al. 201 la) with additional modifications to account for decay and structural
loss (Domke et al. 2011, Harmon et al. 2011). Similar to the situation with live tree data, some of the older forest
inventory data did not provide sufficient data on standing dead trees to make accurate population-level estimates.
The C estimates for these plots were based on average densities (metric tons C per hectare) obtained from plots of
more recent surveys with similar stand characteristics and location. This applied to 25 percent of the forest land
inventory-plot-to-C conversions within the 183 state-level surveys utilized here. Down dead wood estimates are
based on measurement of a subset of FIA plots for downed dead wood(Domke et al., Woodall and Monleon 2008,
Woodall et al. In Review). 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. This includes stumps and roots of harvested
trees. To facilitate the downscaling of downed dead wood C estimates from state to individual plots, downed dead
wood models specific to regions and forest types within each region are used. Litter C is the pool of organic C (also
known as duff, humus, and fine woody debris) above the mineral soil and includes woody fragments with diameters
of up to 7.5 cm. Estimates are based on equations of Smith and Heath (2002).
Carbon in Forest Soil
Soil organic C includes all organic material in soil to a depth of 1 meter but excludes the coarse roots of the biomass
or dead wood pools. Estimates of SOC were based on the national STATSGO spatial database (USDA 1991),
which includes region and soil type information. SOC determination was based on the general approach described
by Amichev and Galbraith (2004). Links to FIA inventory data were developed with the assistance of the USDA
Forest Service FIA Geospatial Service Center by overlaying FIA forest inventory plots on the soil C map. This
method produced mean SOC densities stratified by region and forest type group. It did not provide separate
estimates for mineral or organic soils but instead weighted their contribution to the overall average based on the
relative amount of each within forest land. Thus, forest SOC is a function of species and location, and net change
also depends on these two factors as total forest area changes. In this respect, SOC provides a country-specific
reference stock for 1990-present, but it does not reflect effects of past land use.
Harvested Wood Carbon
Estimates of the HWP contribution to forest C sinks and emissions (hereafter called "HWP Contribution") were
based on methods described in Skog (2008) 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 used the production accounting approach to report HWP Contribution. Under
the production approach, C in exported wood was estimated as if it remains in the United States, and C in imported
wood was 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 were 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 were tracked beginning in 1900, with the
exception that additions of softwood lumber to housing began in 1800. Solidwood and paper product production
and trade data were taken from USDA Forest Service and other sources (Hair and Ulrich 1963; Hair 1958; USDC
Bureau of Census; 1976; Ulrich, 1985, 1989; Steer 1948; AF&PA 2006a 2006b; Howard 2003, 2007). Estimates for
Land Use, Land-Use Change, and Forestry 7-23
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disposal of products reflected the change over time in the fraction of products discarded to SWDS (as opposed to
burning or recycling) and the fraction of SWDS that were in sanitary landfills versus dumps.
There are five annual HWP variables that were 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,
(2 A) annual change of C in wood and paper products in use in the United States and other countries where
the wood came from trees harvested in the United States,
(2B) annual change of C in wood and paper products in SWDS in the United States and other countries
where the wood came from trees harvested in the United States,
(3) C in imports of wood, pulp, and paper to the United States,
(4) C in exports of wood, pulp and paper from the United States, and
(5) C in annual harvest of wood from forests in the United States.
The sum of variables 2 A and 2B yielded the estimate for HWP Contribution under the production accounting
approach. A key assumption for estimating these variables was that products exported from the United States and
held in pools in other countries have the same half-lives for products in use, the same percentage of discarded
products going to SWDS, and the same decay rates in SWDS as they would in the United States.
Uncertainty and Time Series Consistency
A quantitative uncertainty analysis placed bounds on current flux for forest ecosystems as well as C in harvested
wood products through Monte Carlo Stochastic Simulation of the Methods described above and probabilistic
sampling of C conversion factors and inventory data. See Annex 3.12 for additional information. The 2011 net
annual change for forest C stocks was estimated to be between -957 and -712 Tg CCh Eq. at a 95 percent confidence
level. This includes a range of -883.7 to -641.1 Tg CO2 Eq. in forest ecosystems and -90.9 to -54.8 Tg CO2 Eq. for
HWP.
Table 7-11: Tier 2 Quantitative Uncertainty Estimates for Net COz Flux from Forest Land
Remaining Forest Land: Changes in Forest C Stocks (Tg COz Eq. and Percent)
Source
Forest Ecosystem
Harvested Wood
Products
Total Forest
Gas
C02
C02
COz
2011 Flux
Estimate
(Tg C02 Eq.)
(761.8)
(71.7)
(833.5)
Uncertainty Range Relative to Flux Estimate a
(Tg COz Eq.) (%)
Lower Bound
(883.7)
(90.9)
(956.5)
Upper
Bound
(641.1)
(54.8)
(712.1)
Lower
Bound
-16.0
-26.8
-14.8
Upper
Bound
+15.8
+23.6
+14.6
Note: Parentheses indicate negative values or net sequestration.
a Range of flux estimates predicted by Monte Carlo stochastic simulation for a 95 percent confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
QA/QC and Verification
As discussed above, the FIA program has conducted consistent forest surveys based on extensive statistically-based
sampling of most of the forest land in the conterminous United States, dating back to 1952. The FIA program
includes numerous quality assurance and quality control (QA/QC) procedures, including calibration among field
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
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 2012d).
Many key calculations for estimating current forest C stocks based on FIA data were developed to fill data gaps in
assessing forest C and have been in use for many years to produce national assessments of forest C stocks and stock
changes (see additional discussion and citations in the Methodology section above and in Annex 3.12). 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 to
standard inventory summaries such as the forest resource statistics of Smith et al. (2009) or selected population
estimates generated from FIADB 5.1, which are available at an FIA internet site (USDA Forest Service 2012b).
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 to units
C 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 solid wood and paper products in
use were calibrated to meet two independent criteria. The first criterion 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 criterion 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
criterion is that the WOODCARB II model estimate of wood and paper being discarded to SWDS needs to match
EPA estimates of discards each year over the period 1990 to 2000 (EPA 2006). 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, reduce
uncertainty in estimates of annual change in C in products made from wood harvested in the United States. In
addition, WOODCARB II landfill decay rates have been validated by ensuring that estimates of CH4 emissions from
landfills based on EPA (2006) data are reasonable in comparison with CH4 estimates based on WOODCARB II
landfill decay rates.
Recalculations Discussion
In addition to annual updates to most-recent inventories for many states, four additional changes in method or data
reduction for the current Inventory affected the national stock and change estimates for forest ecosystems. Of these,
the modification of the down dead wood estimates to incorporate plot level sampling of down woody material
(Woodall et al. 2010, Woodall et al. In Review) resulted in the greatest impact on total forest C stocks. Nationally,
estimates for C in down dead wood stocks decreased by about 8 percent. A second change was a modification in the
approach to determining the necessary volumes as inputs to the tree biomass equations, which only affected a few of
the periodic (i.e., older) inventories. Next, we identified that the older forest inventories classified as woodlands on
National Forests in Colorado included a spatial extent substantially lower than current inventories of that
classification. The older inventories were dropped from our calculations because of the inconsistency (see annex
3.12 for specifics of inventories in use). Finally, the current FIADB 5.1 data do not include the periodic survey for
Alaska as was included in the previous Inventory (EPA 2012). Therefore we retained the estimates based on FIADB
4.0after making appropriate adjustments consistent with this year's Inventory (e.g., the modified down dead wood
estimates). This represents a change in method—that is, including older FIADB data—that does not affect the
estimates, because it maintains consistency between successive Inventories.
Estimates for C additions to harvested wood products pools were adjusted due to revision to data for softwood
pulpwood production (2006 to 2010), hardwood lumber production (2007 to 2010), hardwood plywood production
(2008 to 2010), and imports of particleboard and medium density fiberboard (1998 to 2010). Revisions are
contained in Howard (forthcoming). Estimates of the total C stock have been adjusted to represent the stock at the
beginning of the year rather than the end of the year to match the beginning year estimates for forest stocks.
Previously the estimates had been for the end of the year. This reduced the total stock level estimate for years
through 2010 by 20 to 30 Tg C.
Land Use, Land-Use Change, and Forestry 7-25
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Planned Improvements
The ongoing annual surveys by the FIA Program will improve the precision of forest C estimates as new state
surveys become available (USDA Forest Service 2012b), particularly in western states. The annual surveys will
eventually include all states. To date, three states are not yet reporting any data from the annualized sampling
design of FIA: Hawaii, 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 fine woody debris, litter, and SOC 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 as this information becomes
available (Woodall et al. 201 Ib). Improved resolution, incorporating more of Alaska's forests, and using annualized
sampling data as it becomes available for those states currently not reporting are planned for future reporting.
As more information becomes available about historical land use, the ongoing effects of changes in land use and
forest management will be better accounted for in estimates of soil C (Birdsey and Lewis 2003, Woodbury et al.
2006, Woodbury et al. 2007). Currently, soil C estimates are based on the assumption that soil C density depends
only on broad forest type group, not on land-use history, but long-term residual effects on soil and forest floor C
stocks are likely after land-use change. Estimates of such effects depend on identifying past land use changes
associated with forest lands.
Similarly, agroforestry practices, such as windbreaks or riparian forest buffers along waterways, are not currently
accounted for in the inventory. In order to properly account for the C stocks and fluxes associated with agroforestry,
research will be needed that provides the basis and tools for including these plantings in a nation-wide inventory, as
well as the means for entity-level reporting.
Emissions of non-CO2 gases from forest fires were estimated using the default IPCC (2003) methodology
incorporating default IPCC (2006) emissions factors and combustion factor for wildfires. Emissions from this
source in 2011 were estimated to be 14.2 Tg CO2 Eq. of CH4 and 11.6 Tg CO2 Eq. of N2O, as shown in Table 7-12
and Table 7-13. The estimates of non-CO2 emissions from forest fires account for wildfires in the lower 48 states
and Alaska as well as prescribed fires in the lower 48 states.
Table 7-12: Estimated Non-COz Emissions from Forest Fires (Tg COz Eq.) for U.S. Forests3
Gas
CH4
N2O
Total
1990
2.5
2.0
4.5
2005
8.0
6.6 j|
14.6
2007
14.4
1 11.7
26.1
2008
8.7
7.1
15.7
2009
5.7
4.7
10.4
2010
4.7
3.8
8.5
2011
14.2
11.6
25.7
1 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default
factors in IPCC (2003,2006).
Table 7-13: Estimated Non-COz Emissions from Forest Fires (Gg Gas) for U.S. Forests3
Gas 1990 2005 2007 2008 2009 2010 2011
CH4 118 ' 383 , 684 413 271 222 675
N2Q 7 21 J 38 23 15 12 37_
a Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default
factors in IPCC (2003, 2006).
Methodology
The IPCC (2003) Tier 2 default methodology was used to calculate non-CO2 emissions from forest fires. However,
more up-to-date default emission factors from IPCC (2006) were converted into gas-specific emission ratios and
incorporated into the methodology. Estimates of CH4 and N2O emissions were calculated by multiplying the total
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
estimated CO2 emitted from forest burned by the gas-specific emissions ratios. CO2 emissions were estimated by
multiplying total C emitted (Table 7-14) by the C to CO2 conversion factor of 44/12 and by 92.8 percent, which is
the estimated proportion of C emitted as CO2 (Smith 2008a). The equations used were:
CH4 Emissions = (C released) x 92.8% x (44/12) x (CH4 to CO2 emission ratio)
N2O Emissions = (C released) x 92.8% x (44/12) x (N2O to CO2 emission ratio)
Estimates for C emitted from forest fires are the same estimates used to generate estimates of CO2 presented earlier
in Box 7-1. Estimates for C emitted include emissions from wildfires in both Alaska and the lower 48 states as well
as emissions from prescribed fires in the lower 48 states only (based on expert judgment that prescribed fires only
occur in the lower 48 states) (Smith 2008a). The IPCC (2006) default combustion factor of 0.45 for "all 'other'
temperate forests" was applied in estimating C emitted from both wildfires and prescribed fires. See the explanation
in Annex 3.12 for more details on the methodology used to estimate C emitted from forest fires.
Table 7-14: Estimated Carbon Released from Forest Fires for U.S. Forests
Year C Emitted (Tg/yr)
1990
11.6
2005
37.5
2007
2008
2009
2010
2011
67.1
40.5
26.6
21.8
66.2
Uncertainty and Time-Series Consistency
Non-CO2 gases emitted from forest fires depend on several variables, including: forest area for Alaska and the lower
48 states; average C densities for wildfires in Alaska, wildfires in the lower 48 states, and prescribed fires in 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. The results of the Tier 2 quantitative
uncertainty analysis are summarized in Table 7-15.
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of Non-COz Emissions from Forest
Fires in Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent)
2011 Emission
Source Gas Estimate
(Tg C02 Eq.)
Non-CCh Emissions from
Forest Fires CH4 14.2
Non-CCh Emissions from
Forest Fires N2O 11.6
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower
Bound
2.6
2.2
Upper
Bound
37.6
31.0
Lower
Bound
-82%
-81%
Upper
Bound
+165%
+169%
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Land Use, Land-Use Change, and Forestry 7-27
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QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted consistent with the U.S. QA/QC plan. Source-specific quality
control measures for forest fires included checking input data, documentation, and calculations to ensure data were
properly handled through the inventory process. Errors that were found during this process were corrected as
necessary.
Recalculations Discussion
For the current Inventory, non-CO2 emissions were calculated using the 2006 IPCC default emission factors for CH4
and N2O instead of the 2003 IPCC default emission factors. These default emission factors were converted to CH4
to COa and N2O to CO2 emission ratios and then multiplied by CO2 emissions to estimate CH4 and N2O emissions.
The previous 2003 IPCC methodology provides emission ratios that are multiplied by total C emitted.
The National Association of State Foresters (NASF) releases data on land under wildland protection every several
years. In 2011, NASF released these data for the year 2008, which affected the ratio of forest land to land under
wildland protection for the years 2007 through 2009. For each of these three years, the updated ratio decreased the
forest area burned estimates for the lower forty-eight states by around 15 percent. See the explanation in Annex
3.12 for more details on how the forestland to land under wildland protection ratio is used to calculate forest fire
emissions.
In previous Inventory reports, the methodology has assumed that the C density of forest areas burned in wild and
prescribed fires does not vary between years. This assumption has been in contrast to the forest C stock estimates,
which are updated annually for all years based on data from the USDA Forest Service. The methodology adopted
for the current and previous Inventory improves the C density factors by incorporating dynamic C density values
based on the annual C pool data provided by the USDA Forest Service for the years 1990 to 2011. As a result of
this update, estimates of CO2 and non-CO2 emissions from wild and prescribed fires decreased by between 1 and 4
percent as compared to the estimates included in the previous Inventory. This decrease occurred because the
dynamic C density values calculated were on average 1% lower (depending on the year) than the C density values
previously used for the methodology. For more information on how C density contributes to estimates of emissions
from forest fires, see Annex 3.12.
Planned Improvements
The default combustion factor of 0.45 from IPCC (2006) was applied in estimating C emitted from both wildfires
and prescribed fires. Additional research into the availability of a combustion factor specific to prescribed fires is
being conducted.
Of the synthetic nitrogen (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,
while the rate of N fertilizer application for the area of forests that receives N fertilizer in any given year is relatively
high, the average annual application is quite low as 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. Direct N2O emissions from forest soils in 2011 were 0.4 Tg CO2 Eq. (1 Gg). Emissions have increased by
455 percent from 1990 to 201 las a result of an increase in the area of N fertilized pine plantations in the
southeastern United States and Douglas-fir timberland in western Washington and Oregon. Total forest soil N2O
emissions are summarized in Table 7-16.
Table 7-16: Direct NzO Fluxes from Soils in ForestLandRemaining Forest Land'(Tg COz Eq.
and Gg NzO)
Year Tg CCh Eq. Gg
1990 0.1 0.2
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
2005 0.4 1.2
2007
2008
2009
2010
2011
0.4
0.4
0.4
0.4
0.4
1.2
1.2
1.2
1.2
1.2
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 Forest
Land Remaining Forest Land and from Land
Converted to Forest Land.
Methodology
The IPCC Tier 1 approach was used to estimate N2O from soils within Forest Land Remaining Forest Land.
According to U.S. Forest Service statistics for 1996 (USDA Forest Service 2001), approximately 75 percent of trees
planted were for timber, and about 60 percent of national total harvested forest area is in the southeastern United
States. Although southeastern pine plantations represent the majority of fertilized forests in the United States, this
Inventory also accounted for N fertilizer application to commercial Douglas-fir stands in western Oregon and
Washington. For the Southeast, estimates of direct N2O emissions from fertilizer applications to forests were based
on the area of pine plantations receiving fertilizer in the southeastern United States and estimated application rates
(Albaugh et al. 2007; Fox et al. 2007). Not accounting for fertilizer applied to non-pine plantations is justified
because fertilization is routine for pine forests but rare for hardwoods (Binkley et al. 1995). For each year, the area
of pine receiving N fertilizer was multiplied by the weighted average of the reported range of N fertilization rates
(121 Ibs. N per acre). Area data for pine plantations receiving fertilizer in the Southeast were not available for 2005,
2006, 2007 and 2008, so data from 2004 were used for these years. For commercial forests in Oregon and
Washington, only fertilizer applied to Douglas-fir was accounted for, because the vast majority (~95 percent) of the
total fertilizer applied to forests in this region is applied to Douglas-fir (Briggs 2007). Estimates of total Douglas-fir
area and the portion of fertilized area were multiplied to obtain annual area estimates of fertilized Douglas-fir stands.
The annual area estimates were multiplied by the typical rate used in this region (200 Ibs. N per acre) to estimate
total N applied (Briggs 2007), and the total 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 N fractions for forest
land, calculated according to the IPCC default factors of 10 percent and 30 percent, respectively, were included with
the indirect emissions in the Agricultural Soil Management source category (consistent with reporting guidance that
all indirect emissions are included in the Agricultural Soil Management source category).
Uncertainty and Time-Series Consistency
The amount of N2O emitted from forests depends not only on N inputs and fertilized area, but also on a large
number of variables, including organic C availability, oxygen gas partial pressure, soil moisture content, pH,
temperature, and tree planting/harvesting cycles. The effect of the combined interaction of these variables on N2O
flux is complex and highly uncertain. IPCC (2006) does not incorporate any of these variables into the default
methodology, except variation 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.
Land Use, Land-Use Change, and Forestry 7-29
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Uncertainties exist in the fertilization rates, annual area of forest lands receiving fertilizer, and the emission factors.
Fertilization rates were assigned a default level228 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 2011 emissions estimates. The results of the quantitative uncertainty analysis are summarized
in Table 7-17. 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 2011 emission estimate of
0.4 Tg CO2 Eq.
Table 7-17: Quantitative Uncertainty Estimates of NzO Fluxes from Soils in Forest Land
Remaining Forest Land'(Tg COz Eq. and Percent)
2011 Emission Uncertainty Range Relative to Emission
Source Gas Estimate Estimate
(Tg C02 Eq.) (Tg COz Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Forest Land Remaining Forest Land: N2O
Fluxes from Soils N2O 0_4 0.1 LI -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.
Planned Improvements
State-level area data will be obtained for southeastern pine plantations and northwestern Douglas-fir forests to
estimate soil N2O emission by state and provide information about regional variation in emission patterns.
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.
228 Uncertainty is unknown for the fertilization rates so a conservative value of ±50% was used in the analysi
sis.
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Mineral and Organic Soil Carbon Stock Changes
Soils contain both organic and inorganic forms of C, but SOC stocks are the main source and sink for atmospheric
CO2 in most soils. Changes in inorganic C stocks are typically minor. In addition, SOC is the dominant organic C
pool in cropland ecosystems, because biomass and dead organic matter have considerably less C and those pools are
relatively ephemeral. IPCC (2006) recommends reporting changes in SOC stocks due to agricultural land-use and
management activities on mineral and organic soils.229
Typical well-drained mineral soils contain from 1 to 6 percent organic C by weight, although mineral soils that are
saturated with water for substantial periods during the year may contain significantly more C (NRCS 1999).
Conversion of mineral soils from their native state to agricultural uses can cause as much as half of the SOC to be
decomposed and the C 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 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). Carbon losses are estimated from drained organic soils under both grassland and
cropland management in this Inventory.
Cropland Remaining Cropland includes all cropland in an inventory year that had been cropland for the last 20
years according to the USDA NPJ land-use survey (USDA-NRCS 2009).230 The inventory includes all privately-
owned croplands in the conterminous United States and Hawaii, but there is a minor amount of cropland on federal
lands that is not currently included in the estimation of C stock changes, leading to a discrepancy between the total
amount of managed area in Cropland Remaining Cropland (see Section 7.1) and the cropland area included in the
Inventory. It is important to note that plans are being made to include federal croplands in future C inventories.
The area of Cropland Remaining Cropland changes through time as land is converted to or from cropland
management. CO2 emissions and removals231 due to changes in mineral soil C stocks are estimated using a Tier 3
229 CO2 emissions associated with liming are also estimated but are included in a separate section of the report.
230 jvjj^j pOmts were classified according to land-use history records starting in 1982 when the NRI survey began, and
consequently the classifications were based on less than 20 years from 1990 to 2001.
231 Note that removals occur through crop and forage uptake of CO2 into biomass C that is later incorporated into soil pools.
Land Use, Land-Use Change, and Forestry 7-31
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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 3 approach (i.e., change in C stocks after 2003 due to Conservation Reserve Program
enrollment). Emissions from organic soils are estimated using a Tier 2 IPCC method.
Of the two sub-source categories, land-use and land management of mineral soils was the most important
component of total net C stock change in the early part of the time series, but emissions from organic soils nearly
exceeded mineral soils in the latter part of the time series (see Table 7-18 and Table 7-19). In 2011, mineral soils
were estimated to remove 29.7 Tg CC>2 Eq. (8.1 Tg C). This rate of C storage in mineral soils represented about a 51
percent decrease in the rate since the initial reporting year of 1990. Emissions from organic soils were 26.8 Tg COa
Eq. (7.3 Tg C) in 2011, which was similar to the emissions in 1990. In total, U.S. agricultural soils in Cropland
Remaining Cropland sequestered approximately 2.9 Tg CO2 Eq. (0.8 Tg C) in 2011.
Table 7-18: Net COz Flux from Soil C Stock Changes in Cropland Remaining Cropland (Jq COz
Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990
(60.4)
26.3 '
(34.1)
2005
(47.1)
26.8
(20.3)
2007
(33.4)
26.8
(6.6)
2008
(32.0)
26.8
(5.2)
2009
(31.4)
26.8
(4.6)
2010
(29.8)
26.8
(3.0)
2011
(29.7)
26.8
(2.9)
Table 7-19: Net COz Flux from Soil C Stock Changes in Cropland Remaining Cropland(Tg C)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990
(16.5)
7.2
(9.3)
2005
(12.9) -
7.3
(5.5)
2007
• (9.1)
7.3
(1.8)
2008
(8.7)
7.3
(1.4)
2009
(8.6)
7.3
(1.2)
2010
(8.1)
7.3
(0.8)
2011
(8.1)
7.3
(0.8)
The net reduction in soil C accumulation over the time series (51 percent lower for 2011, relative to 1990) was
largely due to the declining influence of annual cropland enrolled in the Conservation Reserve Program, which
began in the late 1980s. However, there were still positive increases in C stocks from land enrolled in the reserve
program, as well as intensification of crop production by limiting the use of bare-summer fallow in semi-arid
regions, increased hay production, and adoption of conservation tillage (i.e., reduced- and no-till practices).
The spatial variability in 2011 annual CCh flux associated with C stock changes in mineral and organic soils is
displayed in Figure 7-5 and Figure 7-6. The highest rates of net C accumulation in mineral soils occurred in the
Midwest, which is the area with the largest amounts of cropland managed with conservation tillage, and the south-
central and northwest regions. Emissions from organic soils were highest in Southeastern Coastal Region
(particularly Florida), upper Midwest and Northeast surrounding the Great Lakes, and the Pacific Coast (particularly
California), coinciding with largest concentrations of organic soils in the United States that are used for agricultural
production.
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 7-5: Total Net Annual COz Flux for Mineral Soils under Agricultural Management
within States, 2011, Cropland Remaining Cropland
Mai Net Annual CO, Flux (or Mineral Soils under Agriculiurai Management within States,
Tg C02 EqJyear
D>o
n-0.1 too
.o ••/ A D-0.5 to-0.1
II-1 to-0.5
Note: Values greater than zero represent emissions, and yalues less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 inventory computations. See Methodology for additional details.
Land Use, Land-Use Change, and Forestry 7-33
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Figure 7-6: Total Net Annual COz Flux for Organic Soils under Agricultural Management
within States, 2011, Cropland Remaining Cropland
Total Net Annual C02 Flux for Organic Soils under Agricultural Management within States,
2011, ;ft@f
,o
<^
Tg CO, Eq /year
>2
ito2
ifiOStol
1^0 Ho05
pOtoOl
Li No organic soils
Note: Values greater than zero represent emissions.
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 USD A National Resources Inventory (NRI) survey (USD A-NRCS
2009). The NRI is a statistically-based sample of all non-federal land, and includes approximately 529,558 points in
agricultural land for the conterminous United States and Hawaii.232 Each point is associated with an "expansion
factor" that allows scaling of C stock changes from NRI points to the entire country (i.e., each expansion factor
represents the amount of area with the same land-use/management history as the sample point). Land-use and some
management information (e.g., crop type, soil attributes, and irrigation) were originally collected for each NRI point
on a 5-year cycle beginning in 1982. For cropland, data were collected for 4 out of 5 years in the cycle (i.e., 1979-
1982, 1984-1987, 1989-1992, and 1994-1997). However, the NRI program began collecting annual data in 1998,
and data are currently available through 2007. NRI points were classified as Cropland Remaining Cropland in a
given year between 1990 and 2007 if the land use had been cropland for 20 years.233 Cropland includes all land
used to produce food and fiber, or forage that is harvested and used as feed (e.g., hay and silage).
Mineral Soil Carbon Stock Changes
232 NRI points were classified as agricultural if under grassland or cropland management between 1990 and 2007.
NRI points were classified according to land-use history records starting in 1982 when the NRI survey began. Therefore, the
classification prior to 2002 was based on less than 20 years of recorded land-use history for the time series.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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An IPCC Tier 3 model-based approach was applied to estimate C stock changes for mineral soils used to produce a
majority of annual crops in the United States (Ogle et al. 2010), including alfalfa hay, barley, corn, cotton, dry
beans, grass hay, grass-clover hay, oats, onions, peanuts, potatoes, rice, sorghum, soybeans, sugar beets, sunflowers,
tomatoes, and wheat. The model-based approach uses the DAYCENT biogeochemical model (Parton et al. 1998;
Del Grosso et al. 2001, 2011) to estimate soil C stock changes and soil nitrous oxide emissions from agricultural soil
management. Carbon and N dynamics are linked in plant-soil systems through biogeochemical processes of
microbial decomposition and plant production (McGill and Cole 1981). Coupling the two source categories (i.e.,
agricultural soil C and N2O) in a single inventory analysis ensures that there is a consistent treatment of the
processes and interactions are taken into account between C and N cycling in soils.
The remaining crops on mineral soils were estimated using an IPCC Tier 2 method (Ogle et al. 2003), including
some vegetables, tobacco, perennial/horticultural crops, and crops that are 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 DAYCENT model, which is 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 2007, which was not addressed by the Tier 3 method.
Further elaboration on the methodology and data used to estimate stock changes from mineral soils are described
below and in Annex 3.11.
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated using the DAYCENT biogeochemical model (Parton et al.
1998; Del Grosso et al. 2001, 2011), which simulates the dynamics of C and other elements in cropland, grassland,
forest, and savanna ecosystems. The DAYCENT model utilizes the soil C modeling framework developed in
Century model (Parton et al. 1987, 1988, 1994; Metherell et al. 1993), but has been refined to simulate dynamics at a
daily time-step. Crop production is simulated with NASA-CASA production algorithm (Potter et al. 1993, Potter et
al. 2007) using the MODIS Enhanced Vegetation Index (EVI) products, MOD13Q1 and MYD13Q1, with a pixel
resolution of 250m. A prediction algorithm was developed to estimate EVI (Gurung et al. 2009) for gap-filling
during years over the inventory time series when EVI data were not available (e.g., data from the MODIS sensor
were only available 2000 following the launch of the Aqua and Terra Satellites). The modeling approach uses daily
weather data as an input, along with information about soil physical properties. Input data on land use and
management are specified at a daily 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, P, 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 7-3 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.
A Tier 3 model-based approach is used to estimate soil C stock changes on the majority of agricultural land with
mineral soils. This approach entails several fundamental differences compared to the IPCC Tier 1 or 2 methods,
which classify land areas into a number of discrete classes based on a highly aggregated classification of climate,
soil, and management (i.e., only six climate regions, seven soil types and eleven management systems occur in U.S.
agricultural land under the IPCC classification). Input variables to the Tier 3 model, including climate, soils, and
management activities (e.g., fertilization, crop species, tillage, etc.), are represented in considerably more detail both
temporally and spatially, and exhibit multi-dimensional interactions through the more complex model structure
compared with the IPCC Tier 1 or 2 approach. The spatial resolution of the analysis is also finer in the Tier 3
method compared to the lower tier methods as implemented in the United States for previous Inventories (e.g., 3,037
counties versus 181 Major Land Resource Areas (MLRAs), respectively).
Land Use, Land-Use Change, and Forestry 7-35
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The Tier 3 model simulates a continuous time period rather than the equilibrium step change used in the IPCC
methodology (Tier 1 and 2). More specifically, the DAYCENT model (i.e., daily time-step version of the Century
model) simulates soil C dynamics (and CCh emissions and uptake) on a daily time step based on C emissions and
removals resulting from plant production and decomposition processes. The changes in soil C stocks are influenced
by not only changes in land use and management but also weather 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.
Consequently, delayed responses can occur due to variable weather patterns and other environmental constraints that
interact with land use and management and affect the time frame over which stock changes occur in response to
management decisions.
Additional sources of activity data were used to supplement the land-use information from NRI. The Conservation
Technology Information Center (CTIC 2004) 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 (USDA-ERS 1997, 2011) with additional data from other sources, including the
National Agricultural Statistics Service (NASS 1992, 1999, 2004). Frequency and rates of manure application to
cropland during 1997 were estimated from data compiled by the USDA Natural Resources Conservation Service
(Edmonds et al. 2003), and then adjusted using county-level estimates of manure available for application in other
years. Specifically, county-scale ratios of manure available for application to soils in other years relative to 1997
were used to adjust the area amended with manure (see Annex 3.11 for further details). Greater availability of
managed manure N relative to 1997 was, thus, assumed to increase the area amended with manure, while reduced
availability of manure N relative to 1997 was assumed to reduce the amended area. 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 during storage and transport, and including the addition of N from bedding materials. Nitrogen
losses include direct N2O emissions, volatilization of ammonia and NOX, runoff and leaching, and poultry manure
used as a feed supplement. For unmanaged systems, it is assumed that no N losses or additions occur prior to the
application of manure to the soil. More information on livestock manure production is available in the Manure
Management, Section 6.2, and Annex 3.10.
Daily weather data were used as an input in the model simulations, based on gridded weather data at a 32 km scale
from the North America Regional Reanalysis Product (NARR) (Mesinger et al. 2006). Soil attributes were obtained
from the Soil Survey Geographic Database (SSURGO) (Soil Survey Staff 2011). The carbon dynamics at each NRI
point was simulated 100 times as part of the uncertainty assessment, yielding a total of over 18 million simulation
runs for the analysis. Carbon stock estimates from DAYCENT were adjusted using a structural uncertainty
estimator accounting for uncertainty in model algorithms and parameter values (Ogle et al. 2007, 2010). Carbon
stocks and 95 percent confidence intervals were estimated for each year between 1990 and 2007, but C stock
changes from 2008 to 2011 were assumed to be similar to 2007 because no additional activity data are currently
available from the NRI for the latter years.
Tier 2 Approach
In the IPCC Tier 2 method, data on climate, soil types, land-use, and land management activity were used to classify
land area to apply appropriate stock change factors. MLRAs formed the base spatial unit for mapping climate
regions in the United States; each MLRA represents a geographic unit with relatively similar soils, climate, water
resources, and land uses (NRCS 1981). MLRAs were classified into climate regions according to the IPCC
categories using the PRISM climate database of Daly et al. (1994).
Reference C stocks were estimated using the National Soil Survey Characterization Database (NRCS 1997) with
cultivated cropland as the reference condition, rather than native vegetation as used in IPCC (2003, 2006).
Changing the reference condition was necessary because soil measurements under agricultural management are
much more common and easily identified in the National Soil Survey Characterization Database (NRCS 1997) than
native reference conditions.
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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U.S.-specific stock change factors were derived from published literature to determine the impact of management
practices on SOC storage, including changes in tillage, cropping rotations and intensification, and land-use change
between cultivated and uncultivated conditions (Ogle et al. 2003, Ogle et al. 2006). U.S. factors associated with
organic matter amendments were not estimated because there were an insufficient number of studies to analyze
those impacts. Instead, factors from IPCC (2003) were used to estimate the effect of those activities.
Activity data were primarily based on the historical land-use/management patterns recorded in the NRI. Each NRI
point was classified by land use, soil type, climate region (using PRISM data, Daly et al. 1994) and management
condition. Classification of cropland area by tillage practice was based on data from the Conservation Technology
Information Center (CTIC 2004, 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, 1997, 2002 and 2007, using a Monte Carlo stochastic simulation approach and 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, Ogle et al. 2006). 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 1997 was determined by
calculating the average annual change in stocks between 1992 and 1997; annual C flux for 1998 through 2002 was
determined by calculating the average annual change in stocks between 1998 and 2002; and annual C flux from
2003 through 2011 was determined by calculating the average annual change in stocks between 2003 and 2007.
Additional Mineral C Stock Change
Annual C flux estimates for mineral soils between 2008 and 2011 were adjusted to account for additional C stock
changes associated with gains or losses in soil C after 2007 due to changes in Conservation Reserve Program
enrollment. The change in enrollment acreage relative to 2007 was based on data from USDA-FSA (2012) for 2008
through 2011, 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 country-specific factors and the IPCC
default method (see Annex 3.11 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. The final estimates included a measure of uncertainty as determined from the Monte Carlo Stochastic
Simulation with 50,000 iterations. Emissions were based on the 1992, 1997, 2002 and 2007 Cropland Remaining
Cropland areas from the 2007 National Resources Inventory (USDA-NRCS 2009). The annual emissions estimated
for 1992 was applied to 1990 through 1992; annual emissions estimated for 1997 was applied to 1993 through 1997;
annual emissions estimated for 2002 was applied to 1998 through 2002; and annual emissions estimated for 2007
was applied to 2003 through 2011.
Uncertainty and Time-Series Consistency
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
7-20 for each subsource (mineral soil C stocks and organic soil C stocks) and method that was used in the inventory
analysis (i.e., Tier 2 and Tier 3). Uncertainty for the portions of the Inventory estimated with Tier 2 and 3
approaches was derived using a Monte Carlo approach (see Annex 3.11 for further discussion). Uncertainty
estimates from each approach were combined using the error propagation equation in accordance with IPCC (2006).
The combined uncertainty was calculated by taking the square root of the sum of the squares of the standard
deviations of the uncertain quantities. More details on how the individual uncertainties were developed are in
Annex 3.11. The combined uncertainty for soil C stocks in Cropland Remaining Cropland ranged from 1160
percent below to 596 percent above the 2011 stock change estimate of 2.9 Tg CO2 Eq. The large relative
uncertainty is due to the small net flux estimate in 2011.
Land Use, Land-Use Change, and Forestry 7-37
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Table 7-20: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring
within CroplandRemaining Cropland(Tg COz Eq. and Percent)
Source
2011 Flux
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Flux
Estimate
(Tg C02 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 2003)
Organic Soil C Stocks: Cropland Remaining
Cropland, Tier 2 Inventory Methodology
(30.6)
(2.8)
3.7
26.8
(62.3)
(5.1)
1.9
17.7
(19.0)
(0.9)
5.6
39.0
-104%
-80%
-50%
-34%
38%
68%
50%
46%
Combined Uncertainty for Flux associated with
Agricultural Soil Carbon Stock Change in
Cropland Remaining Cropland
(2.9)
(36.0)
14.2 -1160% 596%
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Recalculations Discussion
Methodological recalculations in this year's inventory were associated with the following improvements: 1) use of
the D AYCENT biogeochemical model to estimate SOC stock changes for the Tier 3 method; 2) incorporation of
MODIS Enhanced Vegetation Index to estimate crop production and subsequent C input to the soil; 3) incorporation
of new activity data from the National Resources Inventory (NRI), extending the time series through 2007 (USDA-
NRCS 2009); 4) recalculation of the Tier 2 portion of the inventory with the new NRI activity data; 5) extension of
the tillage activity dataset with statistics from Conservation Technology and Information Center (CTIC 2004); 6)
including more crops in the Tier 3 method application that had been part of the Tier 2 method in the previous
Inventory (i.e., dry beans, onions, peanuts, potatoes, rice, sugar beets, sunflowers, and tomatoes); and 7) extension
of the N fertilizer activity data with new USD A statistics on fertilizer use through 2009 (USD A-ERS 2011). SOC
stock changes declined by 2.1 Tg CCh eq. on average over the time series as a result of these improvements in the
Inventory. The largest changes in SOC trends tended to occur after 2002, and are attributed to the new NRI and
tillage data (the previous Inventory was based on a time series of activity data that ended in 2003). However,
improved estimation of C dynamics associated with the new DAYCENT model also had a significant effect on the
recalculation for Cropland Remaining Cropland.
QA/QC and Verification
Quality control measures included checking input data, model scripts, and results to ensure data were properly
handled throughout the inventory process. DAYCENT simulations had errors in crop harvest indices that were
corrected. Inventory reporting forms and text were reviewed and revised as needed to correct transcription errors.
One of the key quality control issues was an under-estimation of C stocks in the DAYCENT model due to higher
than expected decomposition rates. The model was re-parameterized to correct this error and accurately represent
soil C dynamics. As discussed in the uncertainty section, results were compared to field measurements, and a
statistical relationship was developed to assess uncertainties in the model's predictive capability. The comparisons
included over 45 long-term experiments, representing about 800 combinations of management treatments across all
of the sites (Ogle et al. 2007) (See Annex 3.11 for more information).
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Planned Improvements
An automated quality assurance/quality control system is currently under development for the Tier 3 method that is
used to estimate the majority of emissions associated with this source category. Currently, quality control is
conducted by manual graphing and queries to determine if values are outside of an expected range. The new system
will automatically create graphs, maps and conduct range checking to improve efficiency in this important step for
the inventory analysis. This development will ensure a more thorough review of the inventory results.
IPCC (2006) recommends reporting COa emissions from lime additions (in the form of crushed limestone (CaCOs)
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 CCh. 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 nineteen
years, ranging from 3.7 Tg CCh Eq. to 5.0 Tg CCh Eq. In 2011, liming of agricultural soils in the United States
resulted in emissions of 4.5 Tg CC>2 Eq. (1.2 Tg C), representing about a 5 percent decrease in emissions since 1990
(see Table 7-21 and Table 7-22). The trend is driven entirely by the amount of lime and dolomite estimated to have
been applied to soils over the time period.
Table 7-21: Emissions from Liming of Agricultural Soils (Tg COz Eq.)
Source 1990 2005 2007 2008 2009 2010 20lF
Liming of Soils8 4.7 ' 4.3 . 4.5 5.0 3.7 4.7 4.5
a Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining
Grassland, Land Converted to Grassland, and Settlements Remaining Settlements.
Table 7-22: Emissions from Liming of Agricultural Soils (Tg C)
Source 1990 2005 2007 2008 2009 2010 20TF
Liming of Soils8 L3 1.2 1.2 1.4 1.0 1.3 1.2
a Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining
Grassland, Land Converted to Grassland, and Settlements Remaining Settlements.
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
7-23) were multiplied by CO2 emission factors from West and McBride (2005). These emission factors (0.059
metric ton C/metric ton limestone, 0.064 metric ton C/metric ton dolomite) are lower than the IPCC default emission
factors because they account for the portion of agricultural lime that may leach through the soil and travel by rivers
to the ocean (West and McBride 2005). This analysis of lime dissolution is based on liming occurring in the
Mississippi River basin, where the vast majority of all U.S. liming takes place (West 2008). U.S. liming that does
not occur in the Mississippi River basin tends to occur under similar soil and rainfall regimes, and, thus, the
emission factor is appropriate for use across the United States (West 2008). The annual application rates of
limestone and dolomite were derived from estimates and industry statistics provided in the Minerals Yearbook and
Mineral Industry Surveys (Tepordei 1993 through 2006; Willett 2007a, b, 2009 through 201 Ib; USGS 2008 through
2012). 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"
Land Use, Land-Use Change, and Forestry 7-39
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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 2011 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 2011 data, 2010 fractions were applied to a 2011 estimate of total
crushed stone presented in the USGS Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First
Quarter of 2012 (USGS 2012); thus, the 2011 data in Table 7-21 through Table 7-23 are shaded to indicate that they
are based on a combination of data and projections.
The primary source for limestone and dolomite activity data is the Minerals Yearbook, published by the Bureau of
Mines through 1994 and by the USGS from 1995 to the present. In 1994, the "Crushed Stone" chapter in the
Minerals Yearbook began rounding (to the nearest thousand metric tons) quantities for total crushed stone produced
or used. It then reported revised (rounded) quantities for each of the years from 1990 to 1993. In order to minimize
the inconsistencies in the activity data, these revised production numbers have been used in all of the subsequent
calculations. Since limestone and dolomite activity data are also available at the state level, the national-level
estimates reported here were broken out by state, although state-level estimates are not reported here.
Table 7-23: Applied Minerals (Million Metric Tons)
Mineral 1990 2005 2007 2008 2009 2010 2011
Limestone 19.01 18.09 17.46 20.46 15.66 20.05 19.05
Dolomite 2.36 1.85 2.92 2.55 L20 1.50 1.42
Note: Data represent amounts applied to Cropland Remaining Cropland, Land Converted to Cropland, Grassland
Remaining Grassland, Land Converted to Grassland, and Settlements Remaining Settlements.
Uncertainty and Time-Series Consistency
Uncertainty regarding limestone and dolomite activity data inputs was estimated at ±15 percent and assumed to be
uniformly distributed around the inventory estimate (Tepordei 2003b). Analysis of the uncertainty associated with
the emission factors included the following: the fraction of agricultural lime dissolved by nitric acid versus the
fraction that reacts with carbonic acid, and the portion of bicarbonate that leaches through the soil and is transported
to the ocean. Uncertainty regarding the time associated with leaching and transport was not accounted for, but
should not change the uncertainty associated with CC>2 emissions (West 2005). The uncertainties 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 zero 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 CC>2 emissions from liming.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 7-24. Carbon dioxide emissions
from Liming of Agricultural Soils in 2011 were estimated to be between 0.25 and 9.24 Tg CCh Eq. at the 95 percent
confidence level. This indicates a range of 94 percent below to 112 percent above the 2011 emission estimate of 4.5
Tg CO2 Eq.
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Table 7-24: Tier 2 Quantitative Uncertainty Estimates for COz Emissions from Liming of
Agricultural Soils (Tg COz Eq. and Percent)
2011 Emission
Estimate Uncertainty Range Relative to Emissions Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower
Bound
Liming of Agricultural Soils1 CCh 4.5 0.3
Upper
Bound
9.2
Lower
Bound
-94%
Upper
Bound
+112%
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, Land Converted
to Grassland, and Settlements Remaining Settlements.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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 2009 has been revised; the updated activity data for 2009 for limestone are
approximately 76 thousand metric tons greater and the 2009 data for dolomite are approximately 110 thousand
metric tons less than the data used for the previous Inventory. Consequently, the reported emissions resulting from
liming in 2009 decreased by about 0.8 percent. In the previous Inventory, to estimate 2010 data, 2009 fractions were
applied to a 2010 estimate of total crushed stone presented in the USGS Mineral Industry Surveys: Crushed Stone
and Sand and Gravel in the First Quarter of 2011 (USGS 2011). 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
2010. These values have replaced those used in the previous Inventory to calculate the quantity of minerals applied
to soil and the emissions from liming. The updated activity data for 2011 are approximately 3,605 thousand metric
tons greater than the data used in the previous Inventory. As a result, the reported emissions from liming in 2010
increased by about 20 percent.
CO2
The use of urea (CO(NH2)2) as fertilizer leads to emissions of CC>2 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 (HCOs")- The bicarbonate then evolves into CC>2 and water. Emissions from urea fertilization in the
United States totaled 3.7 Tg CO2 Eq. (1.0 Tg C) in 2011 (Table 7-25 and Table 7-26). Emissions from urea
fertilization have grown 52 percent between 1990 and 2011, due to an increase in the use of urea as fertilizer.
Table 7-25: COz Emissions from Urea Fertilization in Cropland Remaining Cropland'(Tg COz
Eq.)
Source
1990
2005
2007
2008
2009
2010
2011
Urea Fertilization8
2.4
3.5
3.8
3.6
3.6
3.7
3.7
Land Use, Land-Use Change, and Forestry 7-41
-------
a Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland,
Land Converted to Grassland, Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
Table 7-26: COz Emissions from Urea Fertilization in Cropland Remaining Croplandr(Tg C)
Source 1990 2005 2007 2008 2009 2010 2011
Urea Fertilization8 0/7 1.0 ." 1_0 1_0 1_0 1_0 L0_
a Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland,
Land Converted to Grassland, Settlements Remaining Settlements, and Forest Land Remaining Forest Land.
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 7-27) were derived from state-level
fertilizer sales data provided in Commercial Fertilizers (TVA 1991, 1992, 1993, 1994; AAPFCO 1995 through
201 Ib) 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 and June of that calendar year, and 3 5 percent of total fertilizer used in any fertilizer year is applied betwe en
July and December of the previous calendar year. Fertilizer sales data for the 2011 fertilizer year were not available
in time for publication. Accordingly, urea application in the 2011 fertilizer year was assumed to be equal to that of
the 2010 fertilizer year. Since 2012 fertilizer year data were not available, July through December 2011 fertilizer
consumption was estimated by calculating the percent change in urea use from January through June 2010 to
January through June 2011. For this Inventory, because fertilizer year 2011 activity data were set equal to 2010
activity data, this percent change was zero. This percent change was then multiplied by the July through December
2010 data to estimate July through December 2011 fertilizer use; thus, the 2011 data in Table 7-25 through Table
7-27 are shaded to indicate that they are based on a combination of data and projections. 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 7-27: Applied Urea (Million Metric Tons)
1990 2005 2007 2008 2009 2010 2011
Urea Fertilizer1 3.30 4.78 5.12 4.93 4.86 4.99 4.99
'These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland
Remaining Grassland, Land Converted to Grassland, Settlements Remaining Settlements, and Forest Land Remaining
Forest Land.
Uncertainty and Time-Series Consistency
Uncertainty estimates are presented in Table 7-28 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, therefore, likely to be high. In addition,
each urea consumption data point has an associated uncertainty. Urea for non-fertilizer use, such as aircraft deicing,
may be included in consumption totals; it was determined through personal communication with Fertilizer
Regulatory Program Coordinator David L. Terry (2007), however, that this amount is most likely very small.
Research into aircraft deicing practices also confirmed that urea is used minimally in the industry; a 1992 survey
found a known annual usage of approximately 2,000 tons of urea for deicing; this would constitute 0.06 percent of
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
the 1992 consumption of urea (EPA 2000). Similarly, surveys conducted from 2002 to 2005 indicate that total urea
use for deicing at U.S. airports is estimated to be 3,740 MT per year, or less than 0.07 percent of the fertilizer total
for 2007 (Itle 2009). Lastly, there is uncertainty surrounding the assumptions behind the calculation that converts
fertilizer years to calendar years. Carbon dioxide emissions from urea fertilization of agricultural soils in 2011 were
estimated to be between 2.1 and 3.8 TgCChEq. at the 95 percent confidence level. This indicates a range of 42
percent below to 4 percent above the 2011 emission estimate of 3.7 Tg CC>2 Eq.
Table 7-28: Quantitative Uncertainty Estimates for COz Emissions from Urea Fertilization (Tg
COz Eq. and Percent)
2011 Emission
Estimate Uncertainty Range Relative to Emissions Estimate3
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower
Bound
Urea Fertilization CCh 3.7 2.1
Upper
Bound
3.8
Lower
Bound
-42%
Upper
Bound
+4%
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, Land Converted to Grassland, Settlements Remaining Settlements, and Forest Land
Remaining Forest Land.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
QA/QC and Verification
A QA/QC analysis was performed for data gathering and input, documentation, and calculation. Inventory reporting
forms and text were reviewed. No errors were found.
Recalculations Discussion
In the current Inventory, July to December 2010 urea application data were updated with assumptions for fertilizer
year 2011, and the 2010 emission estimate was revised accordingly. The activity data decreased by about 655,000
metric tons for 2010 and this change resulted in an approximately 11.6 percent decrease in emissions in 2010
relative to the previous Inventory.
Planned Improvements
The primary planned improvement is to investigate using a Tier 2 or Tier 3 approach, which would utilize country-
specific information to estimate a more precise emission factor.
Land Use, Land-Use Change, and Forestry 7-43
-------
Land Converted to Cropland includes all cropland in an inventory year that had been another land use at any point
during the previous 20 years according to the USDA NRI land-use survey (USDA-NRCS 2009).234 Consequently,
lands are retained in this category for 20 years as recommended by the IPCC guidelines (IPCC 2006) unless there is
another land-use change. The inventory includes all privately-owned croplands in the conterminous United States
and Hawaii, but there is a minor amount of cropland on federal lands that is not currently included in the estimation
of C stock changes, leading to a discrepancy between the total amount of managed area in Land Converted to
Cropland (see Section 7.1) and the cropland area included in the inventory.
Background on agricultural C stock changes is provided in Cropland Remaining Cropland and will only be
summarized here for Land Converted to Cropland. Soils are the largest pool of C in agricultural land, and also have
the greatest potential for storage or release of C, because biomass and dead organic matter C pools are relatively
small and ephemeral compared with soils. The IPCC (2006) recommends reporting changes in SOC stocks due to
(1) agricultural land-use and management activities on mineral soils, and (2) agricultural land-use and management
activities on organic soils.235
Land-use and management of mineral soils in Land Converted to Cropland led to losses of C throughout the time
series (Table 7-29 and Table 7-30). The total rate of change in soil C stocks was 14.5 Tg COa Eq. (4.0 Tg C) in
2011. Mineral soils were estimated to lose 13.4 Tg CC>2 Eq. (3.6 Tg C) in 2011, while drainage and cultivation of
organic soils led to an annual loss of 1.1 Tg COa Eq. (0.3 Tg C) in 2011.
Table 7-29: Net COz Flux from Soil C Stock Changes in Land Converted to Cropland(Jq COz
EqO
Soil Type 1990 2005 2007 2008 2009 2010 2011
Mineral Soils 18.9 12.4 13.4 13.4 13.4 13.4 13.4
Organic Soils 2.2 1.1 1.1 1.1 1.1 1.1 1.1
Total Net Flux 21.0 13.5 14.5 14.5 14.5 14.5 14.5
Table 7-30: Net COz Flux from Soil C Stock Changes in Land Converted to Cropland(^g C)
Soil Type 1990 2005 2007 2008 2009 2010 2011 '
Mineral Soils 5.1 3.4 3.6 3.6 3.6 3.6 3.6
Organic Soils 0.6 0.3 0.3 0.3 0.3 0.3 0.3
Total Net Flux 5.7 3.7 4.0 4.0 4.0 4.0 4.0
The spatial variability in 2011 annual CCh 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. The largest losses occurred in the
southwestern and Northeastern US. Conversion of grassland to cropland in these regions led to enhanced
decomposition of soil organic matter with cultivation and a net loss of carbon from the soil. Emissions from organic
soils were largest in the Southeastern Coastal Region (particularly Florida), the upper Midwest and Northeast
surrounding the Great Lakes, in addition to the Pacific Coastal Region, which coincides with areas that have a large
concentration of cultivated organic soils in the United States.
234 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began, and
consequently the classifications were based on less than 20 years from 1990 to 2001.
235 CO2 emissions associated with liming are also estimated but included in 7.4 Cropland Remaining Cropland.
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 7-7: Total Net Annual COz Flux for Mineral Soils under Agricultural Management
within States, 2011, Land Converted to Cropland
Total Net Annual C02 F!ux (or Mineral Soils under Agricultural Management within States.
!0!f.1,rt»t •
rO
Tg C0? Eq /year
>0
-0,1 to 0
03 -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.
Land Use, Land-Use Change, and Forestry 7-45
-------
Figure 7-8: Total Net Annual COz Flux for Organic Soils under Agricultural Management
within States, 2011, Land Converted to Cropland
till:.
Tg CO? Eq./year
• O5to1
El 0.1 to 0,5
DO to 0.1
CD No organic soils
Note: Values greater than zero represent emissions.
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.
Biomass C stock changes are not explicitly included in this category but biomass C losses associated with
conversion of forest to grassland are included in the Forest Land Remaining Forest Land section. 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 3.11.
Soil C stock changes were estimated for Land Converted to Cropland according to land-use histories recorded in the
USDA NRI survey (USDA-NRCS 2009). Land-use and some management information (e.g., crop type, soil
attributes, and irrigation) were originally collected for each NRI point on a 5-year cycle beginning in 1982.
However, the NRI program initiated annual data collection in 1998, and the annual data are currently available
through 2007. NRI points were classified as Land Converted to Cropland in a given year between 1990 and 2007 if
the land use was cropland but had been another use during the previous 20 years. Cropland includes all land used to
produce food or fiber, or forage that is harvested and used as feed (e.g., hay and silage).
Mineral Soil Carbon Stock Changes
A Tier 3 model-based approach was applied to estimate C stock changes for soils on Land Converted to Cropland
that are used to produce a majority of all crops (Ogle et al. 2010), including alfalfa hay, barley, corn, cotton, dry
beans, grass hay, grass-clover hay, oats, onions, peanuts, potatoes, rice, sorghum, soybeans, sugar beets, sunflowers,
tomatoes, and wheat.. 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 some vegetables, tobacco, perennial/horticultural crops and crops
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
rotated with these crops; land on very gravelly, cobbly, or shaley soils (greater than 35 percent by volume); and land
converted from forest or federal ownership.236
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated using the DAYCENT biogeochemical model for the Tier 3
method (Parton et al. 1998; Del Grosso et al. 2001, 2011). The DAYCENT model utilizes the soil C modeling
framework developed in Century model (Parton et al. 1987, 1988, 1994; Metherell et al. 1993), but has been refined
to simulate dynamics at a daily time-step. 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 2009). C stocks
and 95 percent confidence intervals were estimated for each year between 1990 and 2007, but C stock changes from
2008 to 2011 were assumed to be similar to 2007 because no additional activity data are currently available from the
NRI for the latter years. The methods used for Land Converted to Cropland are the same as those described in the
Tier 3 portion of Cropland Remaining Cropland section for mineral soils (see Cropland Remaining Cropland Tier 3
methods section and Annex 3.11 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) as described in the
Cropland Remaining Cropland section for organic soils (see Cropland Remaining Cropland Organic Soils methods
section and Annex 3.11 for additional information).
and
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. 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 7-31 for each subsource (i.e., mineral soil C stocks and organic soil C
stocks) and method that was used in the Inventory analysis (i.e., Tier 2 and Tier 3). Uncertainty for the portions of
the Inventory estimated with Tier 2 and 3 approaches was derived using a Monte Carlo approach (see Annex 3.11
for further discussion). Uncertainty estimates from each approach 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. More detail on how the individual uncertainties were estimated is in Annex
3.11. The combined uncertainty for soil C stocks in Land Converted to Cropland ranged from -70 percent below to
70 percent above the 2011 stock change estimate of 14.5 Tg COa Eq.
Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring
within Land Converted to Cropland'(Tg COz Eq. and Percent)
2011 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source (Tg CCh Eq.) (Tg CCh Eq.) (%)
236 pgderal jancj js not a ^d US6j 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 2009).
Land Use, Land-Use Change, and Forestry 7-47
-------
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
11.8
1.5
1.1
Lower
Bound
1.8
0.8
0.3
Upper
Bound
21.9
2.4
2.2
Lower
Bound
-85%
-49%
-71%
Upper
Bound
85%
54%
94%
Combined Uncertainty for Flux associated with
Soil Carbon Stock Change in Land Converted
to Cropland
14.5
4.4
24.7
-70%
70%
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Methodological recalculations in the current Inventory were associated with the following improvements: 1) use of
the D AYCENT biogeochemical model to estimate SOC stock changes for the Tier 3 method; 2) incorporation of
new activity data from the National Resources Inventory (NRI), extending the time series through 2007 (USDA-
NRCS 2009); 3) recalculation of the Tier 2 portion of the inventory with the new NRI activity data; 4) extension of
the tillage activity dataset with statistics from Conservation Technology and Information Center (CTIC 2004); 5)
including more crops in the Tier 3 method application that had been part of the Tier 2 method in the previous
Inventory (i.e., dry beans, onions, peanuts, potatoes, rice, sugar beets, sunflowers, and tomatoes); and 6) extension
of the N fertilizer activity data with new USD A statistics on fertilizer use through 2009 (USDA-ERS 2009). SOC
change rates declined by 13.7 Tg CCh eq. on average over the time series as a result of these improvements to the
Inventory. Improved estimation of C dynamics associated with the new DAYCENT model had the largest influence
on the recalculation for Land Converted to Cropland.
See QA/QC and Verification section under Cropland Remaining Cropland.
Soil C stock changes with land use conversion from forest land to cropland are undergoing further evaluation to
ensure consistency in the time series. Different methods are used to estimate soil C stock changes in forest land and
croplands, and while the areas have been reconciled between these land uses, there has been limited evaluation of
the consistency in C stock changes with conversion from forest land to cropland. See Planned Improvements section
under Cropland Remaining CroplandTor additional planned improvements.
7-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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7.6
Grassland Remaining Grassland includes all grassland in an inventory year that had been grassland for the previous
20 years237 according to the USDA NRI land use survey (USDA-NRCS 2009). The inventory includes all
privately-owned grasslands in the conterminous United States and Hawaii, but does not address changes in C stocks
for grasslands on federal lands, leading to a discrepancy between the total amount of managed area in Grassland
Remaining Grassland (see Section 7.1) and the grassland area included in the Inventory. While federal grasslands
probably have minimal changes in land management and C stocks, plans are being made to further evaluate and
potentially include these areas in future C inventories.
Background on agricultural C stock changes is provided in the Cropland Remaining Cropland section and will only
be summarized here for Grassland Remaining Grassland. Soils are the largest pool of C in agricultural land, and
also have the greatest potential for storage or release of C, because biomass and dead organic matter C pools are
relatively small and ephemeral compared to soils. IPCC (2006) recommends reporting changes in SOC stocks due
to (1) agricultural land-use and management activities on mineral soils, and (2) agricultural land-use and
management activities on organic soils.238
Land-use and management increased soil C in mineral soils of Grassland Remaining Grassland until 2007 when the
trend was reversed to small decreases in soil C. Organic soils lost relatively small amounts of C in each year 1990
through 2011. Due to the pattern for mineral soils, the overall trend was a gain in soil C through most of the time
series, except for the last few years of the time series where there were small losses. The rates varied from year to
year but there was a net emission of 7.4 Tg CC>2 Eq. (2.0 Tg C) in 2011. There was considerable variation over the
time series driven by variability in weather patterns and associated interaction with land management activity. The
change rates on per hectare basis were small, however, even in the years with larger total changes in stocks.
Overall, flux rates declined by 12.7 Tg CO2 Eq. (3.5 Tg C) when comparing the net change in soil C from 1990 and
2011.
Table 7-32: Net COi Flux from Soil C Stock Changes in Grassland Remaining Grassland'(Tg
CO2 Eq.)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990
(8.7)
3.4
(5.3)
2005
(3.8)
2.8
(1.0)
2007
4.4
2.8
7.1
2008
4.4
2.8
7.2
2009
4.5
2.8
7.3
2010
4.6
2.8
7.3
2011
4.6
2.8
7.4
Note: Totals may not sum due to independent rounding.
Table 7-33: Net COz Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg
C)
Soil Type
Mineral Soils
Organic Soils
Total Net Flux
1990
(2.4)
0.9
(1.4)
2005
(1.0)
0.8 /
(0.3)
, 2007
.4 1.2
0.8
J 1.9
2008
1.2
0.8
2.0
2009
1.2
0.8
2.0
2010
1.2
0.8
2.0
2011
1.3
0.8
2.0
Note: Totals may not sum due to independent rounding.
The spatial variability in the 2011 annual CO2 flux associated with C stock changes in mineral and organic soils is
displayed in Figure 7-9 and Figure 7-10. Grassland gained soil organic C in several regions during 2011, including
the Northeast, Southwest, Midwest, Southwest and far western states; although the gains were relatively small on a
per-hectare basis in most of these regions. Emission rates from drained organic soils were highest from organic soils
237 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began, and
consequently the classifications were based on less than 20 years from 1990 to 2001.
238 CO2 emissions associated with liming are also estimated but included in 7.4 Cropland Remaining Cropland.
Land Use, Land-Use Change, and Forestry 7-49
-------
were largest in the Southeastern Coastal Region (particularly Florida), upper Midwest and Northeastern regions, in
addition the Pacific Coastal Region, coinciding with largest concentrations of organic soils in the United States that
are used for agricultural production.
Figure 7-9: Total Net Annual COz Flux for Mineral Soils under Agricultural Management
within States, 2011, Grassland Remaining Grassland
Total Net Annual CO, Flux ior Mineral Soiis under Agricultural Management within States,
1S11, '
Tg CO Eq 'year
g>o
"J-01 toO
71-05 to-0 1
-Ito-
-2to-
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.
7-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Figure 7-10: Total Net Annual COz Flux for Organic Soils under Agricultural Management
within States, 2011, Grassland Remaining Grassland
Total Net Annual CO, Flux (or Organic Soils under Agricultural Management within States,
f011v&asMa«f Jfeiiafcwf
Tg CO? Eq./year
• lio2
H 0-5 to 1
D0.1to0.5
DO to 0,1
Q No organic soils
Note: Values greater than aero represent emissions.
The following section includes a brief description of the methodology used to estimate changes in soil C stocks due
to agricultural land-use and management activities on mineral and organic soils for Grassland Remaining
Grassland. Further elaboration on the methodologies and data used to estimate stock changes from mineral and
organic soils are provided in the Cropland Remaining Cropland section and Annex 3.11.
Soil C stock changes were estimated for Grassland Remaining Grassland according to land-use histories recorded in
the USDA NRI survey (USDA-NRCS 2009). Land-use and some management information (e.g., crop type, soil
attributes, and irrigation) were originally collected for each NRI point on a 5-year cycle beginning in 1982.
However, the NRI program initiated annual data collection in 1998, and the annual data are currently available
through 2007. NRI points were classified as Grassland Remaining Grassland in a given year between 1990 and
2007 if the land use had been grassland for 20 years. Grassland includes pasture and rangeland used for grass forage
production, where the primary use is livestock grazing. Rangelands are typically extensive areas of native grassland
that are not intensively managed, while pastures are often seeded grassland, possibly following tree removal, that
may or may not be improved with practices such as irrigation and interseeding legumes.
Mineral Soil Carbon Stock Changes
An IPCC Tier 3 model-based approach was applied 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.
Land Use, Land-Use Change, and Forestry 7-51
-------
Tier 3 Approach
Mineral SOC stocks and stock changes for Grassland Remaining Grassland were estimated using the DAY CENT
biogeochemical model (Parton et al. 1998; Del Grosso et al. 2001, 2011), as described in Cropland Remaining
Cropland. The DAYCENT model utilizes the soil C modeling framework developed in Century model (Parton et al.
1987, 1988, 1994; Metherell et al. 1993), but has been refined to simulate dynamics at a daily time-step. Historical
land-use and management patterns were used in the DAYCENT 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 (USDA-ERS 1997, 2011) 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. Specifically,
county-scale ratios of manure available for application to soils in other years relative to 1997 were used to adjust the
area amended with manure (see Annex 3.11 for further details). Greater availability of managed manure N relative
to 1997 was, thus, assumed to increase the area amended with manure, while reduced availability of manure N
relative to 1997 was assumed to reduce the amended area.
The amount of manure produced by each livestock type was calculated for managed and unmanaged waste
management systems based on methods described in the Manure Management, Section 6.2, and Annex 3.10.
Manure N deposition from grazing animals (i.e., PRP manure) was an input to the DAYCENT model (see Annex
3.10), and included approximately 91 percent of total PRP manure (the remainder is deposited on federal lands,
which are currently not included in this inventory). C stocks and 95 percent confidence intervals were estimated for
each year between 1990 and 2007, but C stock changes from 2008 to 2011 were assumed to be similar to 2007
because no additional activity data are currently available from the NRI for the latter years. See the Tier 3 methods
in Cropland Remaining Cropland section for additional discussion on the Tier 3 methodology for mineral soils.
Tier 2 Approach
The Tier 2 approach is based on the same methods described in the Tier 2 portion of Cropland Remaining Cropland
section for mineral soils (see Cropland Remaining Cropland Tier 2 methods section and Annex 3.11 for additional
information).
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between 1990 and 2011 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
N 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, and linearly
extrapolated to estimate values for years since 2004. 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 3.11 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, 1997, 2002 and 2007 Grassland Remaining Grassland areas
from the 2007 National Resources Inventory (USDA-NRCS 2009). The annual emissions estimated for 1992 was
applied to 1990 through 1992; annual emissions estimated for 1997 was applied to 1993 through 1997; annual
emissions estimated for 2002 was applied to 1998 through 2002; and annual emissions estimated for 2007 was
applied to 2003 through 2011.
7-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Uncertainty estimates are presented in Table 7-34 for each subsource (i.e., mineral soil C stocks and organic soil C
stocks) disaggregated to the level of the inventory methodology employed (i.e., Tier 2 and Tier 3). Uncertainty for
the portions of the Inventory estimated with Tier 2 and 3 approaches was derived using a Monte Carlo approach (see
Annex 3.11 for further discussion). Uncertainty estimates from each approach 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. More details on how the individual uncertainties were developed are
in Annex 3.11. The combined uncertainty for soil C stocks in Grassland Remaining Grassland ranged from 497
percent below to 497 percent above the 2011 stock change estimate of 7.4 Tg CC>2 Eq. The large relative
uncertainty is due to the small net flux estimate in 2011.
Table 7-34: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes Occurring Within
GrasslandRemaining Grassland'(Tg COz Eq. and Percent)
Source
2011 Flux Estimate
(Tg CQ2 Eq.)
Uncertainty Range Relative to Flux
Estimate
(Tg C02 Eq.)
Mineral Soil C Stocks Grassland Remaining
Grassland, Tier 3 Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Methodology (Change in Soil C
due to Sewage Sludge Amendments)
Organic Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Methodology
5.8
0.1
(1.2)
2.8
Lower
Bound
(31.1)
0.0
(1.9)
1.4
Upper
Bound
42.7
0.2
(0.6)
4.6
Lower
Bound
-636%
-86%
-50%
-48%
Upper
Bound
636%
110%
50%
65%
Combined Uncertainty for Flux Associated with
Agricultural Soil Carbon Stock Change in
Grassland Remaining Grassland
7.4
(29.5)
44.4
-497% 497%
Note: Parentheses indicate negative values.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Methodological recalculations in the current Inventory were associated with the following improvements: 1) use of
the D AYCENT biogeochemical model to estimate SOC stock changes for the Tier 3 method; 2) incorporation of
new activity data from the National Resources Inventory (NRI), extending the time series through 2007 (USDA-
NRCS 2009); 3) recalculation of the Tier 2 portion of the inventory with the new NRI activity data; and 4) extension
of the N fertilizer activity data with new USD A statistics on fertilizer use through 2009 (USDA-ERS 2009). SOC
stock change declined by 11.75 Tg COa eq. on average over the time series as a result of these improvements in the
Inventory. Improved estimation of C dynamics associated with the new DAYCENT model had the largest influence
on the recalculation for Grassland Remaining Grassland.
and
Quality control measures included checking input data, model scripts, and results to ensure data were properly
handled through the inventory process. DAYCENT simulations had errors in the PRP manure N application during
an initial set of simulations that were later corrected. Crop harvest indices also had errors that were corrected.
Land Use, Land-Use Change, and Forestry 7-53
-------
Inventory reporting forms and text were reviewed and revised as needed to correct transcription errors. Modeled
results were compared to measurements from several long-term grazing experiments (See Annex 3.11 for more
information). One of the key quality control issues was an under-estimation of C stocks in the DAYCENT model
due to higher than expected decomposition rates. The model was re-parameterized to correct this error and
accurately represent soil C dynamics.
One of the key planned improvements for the Grassland Remaining Grassland is to develop and inventory of carobn
stock changes on federal grasslands in the western U.S. This is a significant improvement and will take several years
to implement. See Planned Improvements section under Cropland Remaining Cropland for information about other
upcoming improvements.
Land Converted to Grassland includes all grassland in an inventory year that had been in another land use at any
point during the previous 20 years239 according to the USDA NRI land-use survey (USDA-NRCS 2009).
Consequently, lands are retained in this category for 20 years as recommended by IPCC (2006) unless there is
another land use change. The Inventory includes all privately-owned grasslands in the conterminous United States
and Hawaii, but does not address changes in C stocks for grasslands on federal lands, leading to a discrepancy
between the total amount of managed area for Land Converted to Grassland (see Section 7.1) and the grassland area
included in the Inventory. It is important to note that plans are being made to include these areas in future C
inventories.
Background on agricultural C stock changes is provided in Cropland Remaining Cropland and will only be
summarized here for Land Converted to Grassland. Soils are the largest pool of C in agricultural land, and also
have the greatest potential for storage or release of C, because biomass and dead organic matter C pools are
relatively small and ephemeral compared with soils. IPCC (2006) recommend reporting changes in SOC stocks due
to (1) agricultural land-use and management activities on mineral soils, and (2) agricultural land-use and
management activities on organic soils.240
Land-use and management of mineral soils in Land Converted to Grassland led to an increase in soil C stocks from
1990 through 2011 (see Table 7-35 and Table 7-36). For example, the stock change rates were estimated to remove
7.7 Tg CO2 Eq. (2.1 Tg C) and 8.8 Tg CO2 Eq. (2.4 Tg C) from mineral soils in 1990 and 2011, respectively.
Drainage of organic soils for grazing management led to losses varying from 0.4 to 0.8 Tg CO2 Eq. yr1 (0.1 to 0.2
TgC).
Table 7-35: Net COz Flux from Soil C Stock Changes for Land Converted to Grassland(Tg COz
Eq.)
Soil Type
Mineral Soils3
Organic Soils
Total Net Flux
1990
(8.1)
0.4
(7.7)
2005
: (11.0)
0.8 J
(10.2)
2007
(9.8)
0.8
(9.0)
2008
(9.8)
0.8
(9.0)
2009
(9.7)
0.8
(8.9)
2010
(9.6)
0.8
(8.8)
2011
(9.6)
0.8
(8.8)
239 NRI points were classified according to land-use history records starting in 1982 when the NRI survey began, and
consequently the classifications were based on less than 20 years from 1990 to 2001.
240 CO2 emissions associated with liming are also estimated but included in 7.4 Cropland Remaining Cropland.
7-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 7-36: Net COz Flux from Soil C Stock Changes for Land Converted to Grassland(Tg C)
Soil Type
Mineral Soils3
Organic Soils
Total Net Flux
1990s
(2.2)
0.1
(2.1)
2005
(3.0) '
0.2
(2.8) ;
2007
(2.7)
0.2
(2.5)
2008
(2.7)
0.2
(2.4)
2009
(2.6)
0.2
(2.4)
2010
(2.6)
0.2
(2.4)
2011
(2.6)
0.2
(2.4)
The spatial variability in annual CCh flux associated with C stock changes in mineral soils is displayed in Figure 7-
1 land Figure 7-12. Soil C stock increased in most states for Land Converted to Grassland. The largest gains were
in the Southeastern region, Northeast, South-Central, Midwest, and northern Great Plains. The patterns were driven
by conversion of annual cropland into continuous pasture. Emissions from organic soils were highest in the Pacific
Coastal Region, Gulf Coast Region (particularly Florida), and the upper Midwest and Northeast surrounding the
Great Lakes, coinciding with the largest concentrations of organic soils in the United States that are used for
agricultural production.
Figure 7-11: Total Net Annual COz Flux for Mineral Soils under Agricultural Management
within States, 2011, Land Converted to Grassland
Total Net Annuai CO, Flux (or Mineral Sails under Agrieutturai Management witliin States,
1011, :6 ft
TgC02Eqv'year
n>o
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 inventory computations. See Methodology for additional details.
Land Use, Land-Use Change, and Forestry 7-55
-------
Figure 7-12: Total Net Annual COz Flux for Organic Soils under Agricultural Management
within States, 2011, Land Converted to Grassland
Total Net Annual CO2 Flux far Orga nic So ils under Agric ulturaI Ma nage me nt within States,
Tg CQ2Eq,/year
to 1
to 0.5
Do to 0.1
CH No organic soils
Note: Values greater than aro represent emissions.
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. Biomass C
stock changes are not explicitly included in this category but losses associated with conversion of forest to grassland
are included in the Forest Land Remaining Forest Land section. 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 3.11.
Soil C stock changes were estimated for Land Converted to Grassland according to land-use histories recorded in
the USDA NRI survey (USDA-NRCS 2009). Land-use and some management information (e.g., crop type, soil
attributes, and irrigation) were originally collected for each NRI point on a 5-year cycle beginning in 1982.
However, the NRI program initiated annual data collection in 1998, and the annual data are currently available
through 2007. NRI points were classified as Land Converted to Grassland in a given year between 1990 and 2009 if
the land use was grassland, but had been another use in the previous 20 years. Grassland includes pasture and
rangeland used for grass forage production, where the primary use is livestock grazing. Rangeland typically
includes extensive areas of native grassland that are not intensively managed, while pastures are often seeded
grassland, possibly following tree removal, that may or may not be improved with practices such as irrigation and
interseeding legumes.
Mineral Soil Carbon Stock Changes
An IPCC Tier 3 model-based approach was applied to estimate C stock changes for Land Converted to Grassland
on most mineral soils. C stock changes on the remaining soils were estimated with an IPCC Tier 2 approach (Ogle
et al. 2003), including prior cropland used to produce vegetables, tobacco, perennial/horticultural crops, and rice;
land areas with very gravelly, cobbly, or shaley soils (greater than 35 percent by volume); and land converted from
7-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
forest or federal ownership.241 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 DAYCENT biogeochemical model (Parton et al.
1998; Del Grosso et al. 2001, 2011) as described for Grassland Remaining Grassland. The DAYCENT model
utilizes the soil C modeling framework developed in Century model (Parton et al. 1987, 1988, 1994; Metherell et al.
1993), but has been refined to simulate dynamics at a daily time-step. Historical land-use and management patterns
were used in the DAYCENT simulations as recorded in the NRI survey, with supplemental information on fertilizer
use and rates from the USDA Economic Research Service Cropping Practices Survey (USDA-ERS 1997, 2011) and
the National Agricultural Statistics Service (NASS 1992, 1999, 2004) (see Grassland Remaining Grassland Tier 3
methods section and Annex 3.11 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 and Annex 3.11 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), with U.S. -specific C loss rates (Ogle et al. 2003) as described in the
Grassland Remaining Grassland section for organic soils (see Cropland Remaining Cropland Organic Soils
methods section and Annex 3.11 for additional information).
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. 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 7-37 for each subsource (i.e., mineral soil C stocks and organic soil C
stocks), disaggregated to the level of the inventory methodology employed (i.e., Tier 2 and Tier 3). Uncertainty for
the portions of the Inventory estimated with Tier 2 and 3 approaches was derived using a Monte Carlo approach (see
Annex 3.11 for further discussion). Uncertainty estimates from each approach 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). More detail on how the individual uncertainties were estimated is
in Annex 3.11. The combined uncertainty for soil C stocks in Land Converted to Grassland ranged from -105
percent below to 105 percent above the 2011 stock change estimate of 8.8 Tg CO2 Eq. The large relative
uncertainty is due to the small net flux estimate in 2011.
Table 7-37: Tier 2 Quantitative Uncertainty Estimates for Soil C Stock Changes occurring
within Land Converted to Grassland(Tg COz Eq. and Percent)
2011 Flux Uncertainty Range Relative to Flux
Estimate Estimate
Source (Tg CCh Eq.) (Tg CCh Eq.) (%)
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 2009).
Land Use, Land-Use Change, and Forestry 7-57
-------
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
(7.1)
(2.5)
0.8
Lower
Bound
(16.2)
(3.7)
0.4
Upper
Bound
2.0
(1.4)
1.4
Lower
Bound
-129%
-48%
-51%
Upper
Bound
129%
44%
72%
Combined Uncertainty for Flux associated with
Agricultural Soil Carbon Stocks in Land Converted
to Grassland
(8.8)
(18.0)
0.4
-105%
105%
Note: Parentheses indicate negative values.
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Methodological recalculations in the current Inventory were associated with the following improvements: 1) use of
the D AYCENT biogeochemical model to estimate SOC stock changes for the Tier 3 method; 2) incorporation of
new activity data from the National Resources Inventory (NRI), extending the time series through 2007 (USDA-
NRCS 2009); 3) recalculation of the Tier 2 portion of the inventory with the new NRI activity data; and 4) extension
of the N fertilizer activity data with new USD A statistics on fertilizer use through 2009 (USDA-ERS 2009). SOC
stock changes declined by 13.42 Tg CCh eq. on average over the time series as a result of these improvements in the
Inventory. Improved estimation of C dynamics associated with the new DAYCENT model had the largest influence
on the recalculation for Land Converted to Grassland.
and
See the QA/QC and Verification section under Land Converted to Grassland.
Soil C stock changes with land use conversion from forest land to grassland are undergoing further evaluation to
ensure consistency in the time series. Different methods are used to estimate soil C stock changes in forest land and
grasslands, and while the areas have been reconciled between these land uses, there has been limited evaluation of
the consistency in C stock changes with conversion from forest land to grassland. See Planned Improvements
section under Cropland Remaining Cropland for additional planned improvements.
Emissions from Managed Peatlands
Managed peatlands are peatlands which have been cleared and drained for the production of peat. The production
cycle of a managed peatland has three phases: land conversion in preparation for peat extraction (e.g., clearing
surface biomass, draining), extraction (which results in the emissions reported under Peatlands Remaining
Peatlands), and abandonment, restoration, or conversion of the land to another use.
7-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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CO2 emissions from the removal of biomass and the decay of drained peat constitute the major greenhouse gas flux
from managed peatlands. Managed peatlands may also emit CH4 and N2O. The natural production of CH4 is largely
reduced but not entirely shut down when peatlands are drained in preparation for peat extraction (Strack et al., 2004
as cited in IPCC 2006); however, CH4 emissions are assumed to be insignificant under IPCC Tier 1 methodology
(IPCC, 2006). N2O emissions from managed peatlands depend on site fertility. In addition, abandoned and restored
peatlands continue to release greenhouse gas emissions, and at present no methodology is provided by IPCC (2006)
to estimate greenhouse gas emissions or removals from restored peatlands. This inventory estimates both CO2 and
N2O emissions from Peatlands Remaining Peatlands in accordance with Tier 1 IPCC (2006) guidelines.
COz and N2O Emissions from Peatlands Remaining Peatlands
IPCC (2006) recommends reporting CO2 and N2O emissions from lands undergoing active peat extraction (i.e.,
Peatlands Remaining Peatlands) as part of the estimate for emissions from managed wetlands. Peatlands occur
where plant biomass has sunk to the bottom of water bodies and water-logged areas and exhausted the oxygen
supply below the water surface during the course of decay. Due to these anaerobic conditions, much of the plant
matter does not decompose but instead forms layers of peat over decades and centuries. In the United States, peat is
extracted for horticulture and landscaping growing media, and for a wide variety of industrial, personal care, and
other products. It has not been used for fuel in the United States for many decades. Peat is harvested from two
types of peat deposits in the United States: sphagnum bogs in northern states and wetlands in states further south.
The peat from sphagnum bogs in northern states, which is nutrient poor, is generally corrected for acidity and mixed
with fertilizer. Production from more southerly states is relatively coarse (i.e., fibrous) but nutrient rich.
IPCC (2006) recommends considering both on-site and off-site emissions when estimating CO2 emissions from
Peatlands Remaining Peatlands using the Tier 1 approach. Current methodologies estimate only on-site N2O
emissions, since off-site N2O estimates are complicated by the risk of double-counting emissions from nitrogen
fertilizers added to horticultural peat. On-site emissions from managed peatlands occur as the land is cleared of
vegetation and the underlying peat is exposed to sun and weather. As this occurs, some peat deposit is lost and CO2
is emitted from the oxidation of the peat. Since N2O emissions from saturated ecosystems tend to be low unless
there is an exogenous source of nitrogen, N2O emissions from drained peatlands are dependent on nitrogen
mineralization and therefore on soil fertility. Peatlands located on highly fertile soils contain significant amounts of
organic nitrogen in inactive form. Draining land in preparation for peat extraction allows bacteria to convert the
nitrogen into nitrates which leach to the surface where they are reduced to N2O.
Off-site CO2 emissions from managed peatlands occur from the horticultural and landscaping use of peat. Nutrient-
poor (but fertilizer-enriched) peat tends to be used in bedding plants and in greenhouse and plant nursery production,
whereas nutrient-rich (but relatively coarse) peat is used directly in landscaping, athletic fields, golf courses, and
plant nurseries. Most of the CO2 emissions from peat occur off-site, as the peat is processed and sold to firms
which, in the United States, use it predominantly for horticultural purposes.
Total emissions from Peatlands Remaining Peatlands were estimated to be 0.922 Tg CO2 Eq. in 2011 (see Table
7-38) comprising 0.918 Tg CO2 Eq. (918 Gg) of CO2 and 0.004 Tg CO2 Eq. (0.014 Gg) of N2O. Total emissions in
2011 were about 9 percent smaller than total emissions in 2010, with the decrease due to the decrease in peat
production reported in the lower 48 states in 2011. At the time of writing, peat production in Alaska (reported in
cubic meters) was not yet published, and was therefore assumed to equal the value reported in 2010; although early
indications were that production in 2011 will be slightly higher than in 2010 (Harbo 2012 as cited in USGS 2012).
Total emissions from Peatlands Remaining Peatlands have fluctuated between 0.9 and 1.2 Tg CO2 Eq. across the
time series with a decreasing trend from 1990 until 1994 followed by an increasing trend through 2000. After 2000,
emissions generally decreased until 2006 and then increased until 2009, when the trend reversed. Emissions in 2011
represent a decline from emissions in 2010. CO2 emissions from Peatlands Remaining Peatlands have fluctuated
between 0.9 and 1.2 Tg CO2 across the time series, and these emissions drive the trends in total emissions. N2O
emissions remained close to zero across the time series, with a decreasing trend from 1990 until 1995 followed by
an increasing trend through 2000. N2O emissions decreased between 2000 and 2006, followed by a leveling off
between 2008 and 2010, and a decline in 2011.
Table 7-38: Emissions from Peatlands Remaining Peatlands(Tg COz Eq.)
Gas 1990 2005 2007 2008 2009 2010 2011
Land Use, Land-Use Change, and Forestry 7-59
-------
CO2 1.0 1.1 1.0 1.0 1.1 1.0 0.9
N2O + + + + + + +
Total 1.0 1.1 1.0 1.0 1.1 1.0 0.9~
+ Less than 0.05 Tg CO2 Eq.
Note: These numbers are based on U.S. production data in accordance with Tier 1 guidelines, which does not take into account
imports, exports and stockpiles (i.e., apparent consumption).
Table 7-39: Emissions from Peatlands Remaining Peatlands(Gg)
Gas 1990 2005 2007 2008 2009 2010 20l"T
CO2 1,033 1,079 ' 1,012 992 1,089 1,010 918
N2O + . + •'.. + + + + +
+ Lessthan0.5Gg
Note: These numbers are based on U.S. production data in accordance with Tier 1 guidelines, which does not take into account
imports, exports, and stockpiles (i.e., apparent consumption).
Methodology
Off-Site CO2 Emissions
CO2 emissions from domestic peat production were estimated using a Tier 1 methodology consistent with IPCC
(2006). Off-site CO2 emissions from Peatlands Remaining Peatlands were calculated by apportioning the annual
weight of peat produced in the United States (Table 7-40) into peat extracted from nutrient-rich deposits and peat
extracted from nutrient-poor deposits using annual percentage-by-weight figures. These nutrient-rich and nutrient-
poor production values were then multiplied by the appropriate default C fraction conversion factor taken from
IPCC (2006) in order to obtain off-site emission estimates. For the lower 48 states, both annual percentages of peat
type by weight and domestic peat production data were sourced from estimates and industry statistics provided in
the Minerals Yearbook wAMineral Commodity Summaries from the U.S. Geological Survey (USGS 1991-2012).
To develop these data, the U.S. Geological Survey (USGS; U.S. Bureau of Mines prior to 1997) obtained production
and use information by surveying domestic peat producers. On average, about 75 percent of the peat operations
respond to the survey. USGS estimated data for non-respondents on the basis of prior-year production levels
(Apodaca2011).
The Alaska estimates rely on reported peat production from Alaska's annual Mineral Industry Reports (Szumigala et
al. 2010). Similar to the U.S. Geological Survey, Alaska's Mineral Industry Report methodology solicits voluntary
reporting of peat production from producers. However, the report does not estimate production for the non-reporting
producers, resulting in larger inter-annual variation in reported peat production from Alaska depending on the
number of producers who report in a given year (Szumigala 2011). In addition, in both the lower 48 states and
Alaska, large variations in peat production can also result from variations in precipitation and the subsequent
changes in moisture conditions, since unusually wet years can hamper peat production (USGS 1991-2012). The
methodology estimates Alaska emissions separately from lower 48 emissions because the state conducts its own
mineral survey and reports peat production by volume, rather than by weight (Table 7-41). However, volume
production data were used to calculate off-site CO2 emissions from Alaska applying the same methodology but with
volume-specific C fraction conversion factors from IPCC (2006).242
The apparent consumption of peat, which includes production plus imports minus exports plus the decrease in
stockpiles, in the United States is over two-and-a-half times the amount of domestic peat production. Therefore, off-
site CO2 emissions from the use of all horticultural peat within the United States are not accounted for using the Tier
1 approach. The United States has increasingly imported peat from Canada for horticultural purposes; from 2007 to
2010, imports of sphagnum moss (nutrient-poor) peat from Canada represented 97 percent of total U.S. peat imports
(USGS 2012a). Most peat produced in the United States is reed-sedge peat, generally from southern states, which is
classified as nutrient rich by IPCC (2006). Higher-tier calculations of CO2 emissions from apparent consumption
Peat produced from Alaska was assumed to be nutrient poor; as is the case in Canada, "where deposits of high-quality [but
nutrient poor] sphagnum moss are extensive" (USGS 2008).
7-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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would involve consideration of the percentages of peat types stockpiled (nutrient rich versus nutrient poor) as well
as the percentages of peat types imported and exported.
Table 7-40: Peat Production of Lower 48 States (in thousands of Metric Tons)
Type of Deposit
Nutrient-Rich
Nutrient-Poor
Total Production
1990
595.1 •
55.4
692.0
2005
657.6 • -
27.4
685.0
2007
581.0
54.0
635.0
2008
559.7
55.4
615.0
2009
560.3
48.7
609.0
2010
558.9
69.1
628.0
2011
511.2
56.8
568.0
Sources: United States Geological Survey (USGS) (1991-2012)Minerals Yearbook: Peat (1994-2011); United States
Geological Survey (USGS) (1996-2012) Mineral Commodity Summaries: Peat (1996-2011).
Table 7-41: Peat Production of Alaska (in thousands of Cubic Meters)
1990 2005 2007 2008 2009 2010 2011~
Total Production 49.7 47.8 52.3 64.1 183.9 59.8 59.8
Sources: Division of Geological & Geophysical Surveys (DGGS), Alaska Department of Natural Resources (1997-2011)
Alaska's Mineral Industry Report (1997-2010).
On-site CO2 Emissions
IPCC (2006) suggests basing the calculation of on-site emissions estimates on the area of peatlands managed for
peat extraction differentiated by the nutrient type of the deposit (rich versus poor). Information on the area of land
managed for peat extraction is currently not available for the United States, but in accordance with IPCC (2006), an
average production rate for the industry was applied to derive an area estimate. In a mature industrialized peat
industry, such as exists in the United States and Canada, the vacuum method can extract up to 100 metric tons per
hectare per year (Cleary et al. 2005 as cited in IPCC 2006).243 The area of land managed for peat extraction in the
United States was estimated using nutrient-rich and nutrient-poor production data and the assumption that 100
metric tons of peat are extracted from a single hectare in a single year. The annual land area estimates were then
multiplied by the appropriate nutrient-rich or nutrient-poor IPCC (2006) default emission factor in order to calculate
on-site CCh emission estimates. Production data are not available by weight for Alaska. In order to calculate on-site
emissions resulting from Peatlands Remaining Peatlands in Alaska, the production data by volume were converted
to weight using annual average bulk peat density values, and then converted to land area estimates using the same
assumption that a single hectare yields 100 metric tons. The IPCC (2006) on-site emissions equation also includes a
term which accounts for emissions resulting from the change in C stocks that occurs during the clearing of
vegetation prior to peat extraction. Area data on land undergoing conversion to peatlands for peat extraction is also
unavailable for the United States. However, USGS records show that the number of active operations in the United
States has been declining since 1990; therefore it seems reasonable to assume that no new areas are being cleared of
vegetation for managed peat extraction. Other changes in C stocks in living biomass on managed peatlands are also
assumed to be zero under the Tier 1 methodology (IPCC 2006).
On-site N2O Emissions
IPCC (2006) suggests basing the calculation of on-site N2O emissions estimates on the area of nutrient-rich
peatlands managed for peat extraction. These area data are not available directly for the United States, but the on-
site CO2 emissions methodology above details the calculation of area data from production data. In order to
estimate N2O emissions, the area of nutrient rich Peatlands Remaining Peatlands was multiplied by the appropriate
default emission factor taken from IPCC (2006).
243 The vacuum method is one type of extraction that annually "mills" or breaks up the surface of the peat into particles, which
then dry during the summer months. The air-dried peat particles are then collected by vacuum harvesters and transported from
the area to stockpiles (IPCC 2006).
Land Use, Land-Use Change, and Forestry 7-61
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Uncertainty
The uncertainty associated with peat production data was estimated to be ± 25 percent (Apodaca 2008) and assumed
to be normally distributed. The uncertainty associated with peat production data stems from the fact that the USGS
receives data from the smaller peat producers but estimates production from some larger peat distributors. The peat
type production percentages were assumed to have the same uncertainty values and distribution as the peat
production data (i.e., ± 25 percent with a normal distribution). The uncertainty associated with the Alaskan reported
production data was assumed to be the same as the lower 48 states, or ± 25 percent with a normal distribution. It
should be noted that the Alaska Department of Natural Resources estimates that around half of producers do not
respond to their survey with peat production data; therefore, the production numbers reported are likely to
underestimate Alaska peat production (Szumigala 2008). The uncertainty associated with the average bulk density
values was estimated to be ± 25 percent with a normal distribution (Apodaca 2008). IPCC (2006) gives uncertainty
values for the emissions factors for the area of peat deposits managed for peat extraction based on the range of
underlying data used to determine the emission factors. The uncertainty associated with the emission factors was
assumed to be triangularly distributed. The uncertainty values surrounding the C fractions were based on IPCC
(2006) and the uncertainty was assumed to be uniformly distributed. Based on these values and distributions, a
Monte Carlo (Tier 2) uncertainty analysis was applied to estimate the uncertainty of CC>2 and N2O emissions from
Peatlands Remaining Peatlands. The results of the Tier 2 quantitative uncertainty analysis are summarized in Table
7-42. CO2 emissions from Peatlands Remaining Peatlands in 2011 were estimated to be between 0.6 and 1.2 Tg
CO2 Eq. at the 95 percent confidence level. This indicates a range of 33 percent below to 35 percent above the 2011
emission estimate of 0.9 Tg CChEq. N2O emissions from Peatlands Remaining Peatlands in 2011 were estimated
to be between 0.001 and 0.006 Tg CO2 Eq. at the 95 percent confidence level. This indicates a range of 74 percent
below to 39 percent above the 2011 emission estimate of 0.004 TgCC^Eq.
Table 7-42: Tier-2 Quantitative Uncertainty Estimates for COz Emissions from Peatlands
Remaining Peatlands
Source
Peatlands Remaining
Peatlands
2011 Emissions
Estimate Uncertainty Range Relative to Emissions Estimate3
Gas (TgCChEq.) (Tg CCh Eq.) (%)
Lower
Bound
C02 0.9 0.6
N20 + +
Upper
Bound
1.2
Lower
Bound
-33%
-74%
Upper
Bound
35%
39%
+ Does not exceed 0.01 Tg CO2 Eq. or 0.5 Gg.
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. The QA/QC
analysis did not reveal any inaccuracies or incorrect input values.
Recalculations Discussion
The current Inventory represents the fifth Inventory report in which emissions from Peatlands Remaining Peatlands
are included. The Inventory estimates for 2010 have been updated to incorporate new information on the proportion
of rich and poor peat soil, and the bulk density of peat types in 2010. These data are from the advance release of the
2010 Mineral Yearbook: Peat (USGS 2012b), which was released too late to be fully incorporated into the previous
Inventory estimates. Updating these 2010 input values resulted in an 8 percent decrease compared to the previous
Inventory report's 2010 emission estimate.
7-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Planned Improvements
In order to further improve estimates of COa and N2O emissions from Peatlands Remaining Peatlands, future efforts
will consider options for obtaining better data on the quantity of peat harvested per hectare and the total area
undergoing peat extraction.
in in
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 3 percent of the United States (U.S. Census Bureau 2012).
With an average tree canopy cover of 35 percent, urban areas account for approximately 5 percent of total tree cover
in the continental United States (Nowak and Greenfield 2012). Trees in urban areas of the United States were
estimated to account for an average annual net sequestration of 58.5 Tg CCh Eq. (16.0 Tg C) over the period from
1990 through 2011. Net C flux from urban trees in 2011 was estimated to be -68.8 TgCO2Eq. (-18.8 TgC).
Annual estimates of CO2 flux (Table 7-43) were developed based on periodic (1990, 2000, and 2010) U.S. Census
data on urbanized area. The estimate of urbanized area is smaller than the area categorized as Settlements in the
Representation of the U.S. Land Base developed for this report, by an average of 47 percent over the 1990 through
2011 time series—i.e., the Census urban area is a subset of the Settlements area.
In 2011, urban area was about 44 percent smaller than the total area defined as Settlements. Census area data are
preferentially used to develop C flux estimates for this source category since these data are more applicable for use
with the available peer-reviewed data on urban tree canopy cover and urban tree C sequestration. Annual
sequestration increased by 45 percent between 1990 and 2011 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. As a result, the estimates presented in this chapter are not truly representative of changes in C stocks in
urban trees for Settlements areas, but are representative of changes in C stocks in urban trees for Census urban area.
The method used in this report does not attempt to scale these estimates to the Settlements area. Therefore, the
estimates presented in this chapter are likely an underestimate of the true changes in C stocks in urban trees in all
Settlements areas—i.e., the changes in C stocks in urban trees presented in this chapter are a subset of the changes in
C stocks in urban trees in all Settlements areas.
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). However, 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 basis of C sequestered
per unit area of tree cover, rather than C sequestered per total land area. Expressed per unit of tree cover, areas
covered by urban trees have a greater C density than do forested areas (Nowak and Crane 2002). Expressed per unit
of land area, however, the situation is the opposite: urban areas have a smaller C density than forest areas.
Table 7-43: Net C Flux from Urban Trees (Tg CCh Eq. and Tg C)
Year Tg CCh Eq. Tg C
1990 (47.5) (13.0)
2005 (63.2) (17.2)
2007 (65.0) (17.7)
2008 (66.0) (18.0)
2009 (66.9) (18.3)
2010 (67.9) (18.5)
Land Use, Land-Use Change, and Forestry 7-63
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2011 (68.8) (18.8)
Note: Parentheses indicate net
sequestration.
Methodology
Methods for quantifying urban tree biomass, C sequestration, and C emissions from tree mortality and
decomposition were taken directly from Nowak et al. (2013, in review), Nowak and Crane (2002), and Nowak
(1994). In general, the methodology used by Nowak et al. (2013, in review) to estimate net C sequestration in urban
trees followed three steps. First, field data from 28 cities were used to generate allometric estimates of biomass
from measured tree dimensions. Second, estimates of tree growth and biomass increment were generated from
published literature and adjusted for tree condition and land-use class to generate estimates of gross C sequestration
in urban trees. Third, estimates of C emissions due to mortality and decomposition were subtracted from gross C
sequestration values to derive estimates of net C sequestration. Finally, sequestration estimates for these cities, in
units of C sequestered per unit area of tree cover, were used to estimate urban forest C sequestration in the U.S. by
using urban area estimates from U.S. Census data and urban tree cover estimates from remote sensing data, an
approach consistent with Nowak et al. (2013, in review).
This approach is also consistent with the default IPCC methodology in IPCC (2006), although sufficient data are not
yet available to separately 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.
In order to generate the allometric relationships between tree dimensions and tree biomass, Nowak et al. (2013, in
review) and previously published information (Nowak and Crane 2002; and Nowak 1994, 2007c, and 2009)
collected field measurements in a number of U.S. cities between 1989 and 2012. For a sample of trees in each of the
cities in Table 7-44, data including tree measurements of stem diameter, tree height, crown height and crown width,
and information on location, species, and canopy condition were collected. The data for each tree were converted
into C storage by applying allometric equations to estimate aboveground biomass, a root-to-shoot ratio to convert
aboveground biomass estimates to whole tree biomass, moisture content, a C content of 50 percent (dry weight
basis), and an adjustment factor of 0.8 to account for urban trees having less aboveground biomass for a given stem
diameter than predicted by allometric equations based on forest trees (Nowak 1994). C storage estimates for
deciduous trees include only C stored in wood. These calculations were then used to develop an allometric equation
relating tree dimensions to C storage for each species of tree, encompassing a range of diameters.
Tree growth was estimated using annual height growth and diameter growth rates for specific land uses and diameter
classes. Growth calculations were adjusted by a factor to account for tree condition (fair to excellent, poor, critical,
dying, or dead). For each tree, the difference in C storage estimates between year 1 and year (x + 1) represents the
gross amount of C sequestered. These annual gross C sequestration rates for each species (or genus), diameter class,
and land-use condition (e.g., parks, transportation, vacant, golf courses) were then scaled up to city estimates using
tree population information. The area of assessment for each city was defined by its political boundaries; parks and
other forested urban areas were thus included in sequestration estimates (Nowak 2011).
Most of the field data used to develop the methodology of Nowak et al. (2013, in review) were analyzed using the
U.S. Forest Service's Urban Forest Effects (UFORE) model. UFORE is a computer model that uses standardized
field data from random plots in each city and local air pollution and meteorological data to quantify urban forest
structure, values of the urban forest, and environmental effects, including total C stored and annual C sequestration.
UFORE was used with field data from a stratified random sample of plots in each city to quantify the characteristics
of the urban forest. (Nowak et al. 2007a).
Gross C emissions result from tree death and removals. Estimates of gross C emissions from urban trees were
derived by applying estimates of annual mortality and condition, and assumptions about whether dead trees were
removed from the site to the total C stock estimate for each city. Estimates of annual mortality rates by diameter
class and condition class were derived from a study of street-tree mortality (Nowak 1986). Different decomposition
rates were applied to dead trees left standing compared with those removed from the site. For removed trees,
different rates were applied to the removed/aboveground biomass in contrast to the belowground biomass. The
estimated annual gross C emission rates for each species (or genus), diameter class, and condition class were then
scaled up to city estimates using tree population information.
7-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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The field data for the 28 cities are described in Nowaketal. (2013, in review), which builds upon previous research,
including: Nowak and Crane (2002), Nowak et al. (2007a), and references cited therein. The allometric equations
applied to the field data for each tree were taken from the scientific literature (see Nowak 1994, Nowak et al. 2002),
but if no allometric equation could be found for the particular species, the average result for the genus was used.
The adjustment (0.8) to account for less live tree biomass in urban trees was based on information in Nowak (1994).
Measured tree growth rates for street (Frelich 1992; Fleming 1988; Nowak 1994), park (deVries 1987), and forest
(Smith and Shifley 1984) trees were standardized to an average length of growing season (153 frost free days) and
adjusted for site competition and tree condition. Standardized growth rates of trees of the same species or genus
were then compared to determine the average difference between standardized street tree growth and standardized
park and forest growth rates. Crown light exposure (CLE) measurements (number of sides and/or top of tree
exposed to sunlight) were used to represent forest, park, and open (street) tree growth conditions. Local tree base
growth rates (BG) were then calculated as the average standardized growth rate for open-grown trees multiplied by
the number of frost free days divided by 153. Growth rates were then adjusted for CLE. The CLE adjusted growth
rate was then adjusted based on tree health and tree condition to determine the final growth rate. Assumptions for
which dead trees would be removed versus left standing were developed specific to each land use and were based on
expert judgment of the authors. Decomposition rates were based on literature estimates (Nowak et al. 2013, in
review).
Estimates of gross and net sequestration rates for each of the 28 cities (Table 7-44) were compiled in units of C
sequestration per unit area of tree canopy cover. These rates were used in conjunction with estimates of national
urban area and urban tree cover data to calculate national annual net C sequestration by urban trees for the United
States. This method was described inNowak et al. (2013, in review) and has been modified to incorporate U.S.
Census data.
Specifically, urban area estimates were based on 1990, 2000, and 2010 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. In 2010, the
Census updated its definitions to have "urban areas" encompassing Census tract delineated cities with 50,000 or
more people, and "urban clusters" containing Census tract delineated locations with between 2,500 and 50,000
people. Urban land area increased by approximately 23 percent from 1990 to 2000 and 16 percent from 2000 to
2010; Nowak et al. (2005) estimate that the changes in the definition of urban land are responsible for approximately
20 percent of the total reported increase in urban land area from 1990 to 2000. Under all Census (i.e., 1990, 2000,
and 2010) definitions, the urban category encompasses most cities, towns, and villages (i.e., it includes both urban
and suburban areas). Settlements area, as assessed in the Representation of the U.S. Land Base developed for this
report, encompassed all developed parcels greater than 0.1 hectares in size, including rural transportation corridors,
and as previously mentioned represents a larger area than the Census-derived urban area estimates. However, the
smaller, Census-derived urban area estimates were deemed to be more suitable for estimating national urban tree
cover given the data available in the peer-reviewed literature (i.e., the data set available is consistent with Census
urban rather than Settlements areas), and the recognized overlap in the changes in C stocks between urban forest and
non-urban forest (see Planned Improvements below). Specifically, tree canopy cover of U.S. urban areas was
estimated by Nowak and Greenfield (2012) to be 35 percent, assessed across Census-delineated urbanized areas and
urban clusters. This canopy cover percentage is multiplied by the urban area estimated for each year to produce an
estimate of national urban tree cover area.
Net annual C sequestration estimates were derived for the 28 cities by subtracting the gross annual emission
estimates from the gross annual sequestration estimates. The gross and net annual 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 per unit area of tree cover (0.26 kg C/m2-yr) was
then multiplied by the estimate of national urban tree cover area to estimate national annual gross sequestration, per
the methods of Nowak et al. (2013, in review). 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 (0.72)
for those cities that had both estimates. The urban tree cover estimates for each of the 28 cities and the United States
were obtained from Nowak et al. (2013, in review) which compiled ten years of research including Dwyer et al.
(2000), Nowak et al. (2002), Nowak (2007a), and Nowak (2009). The urban area estimates were taken from the
2010 U.S. Census (2012).
Land Use, Land-Use Change, and Forestry 7-65
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Table 7-44: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover
(Percent), and Annual C Sequestration per Area of Tree Cover (kg C/m2-yr) for 28 U.S. Cities
City
Arlington, TX
Atlanta, GA
Baltimore, MD
Boston, MA
Casper, WY
Chicago, IL
Freehold, NJ
Gainesville, FL
Golden, CO
Jersey City, NJ
Hartford, CT
Lincoln, NE
Los Angeles, CA
Milwaukee, WI
Minneapolis, MN
Moorestown, NJ
Morgantown, WV
New York, NY
Omaha, NE
Philadelphia, PA
Roanoke, VI
Sacramento, CA
San Francisco, CA
Scranton, PA
Syracuse, NY
Washington, DC
Woodbridge, NJ
Carbon Gross Annual Net Annual
Stocks Sequestration Sequestration
1,682,599
2,263,366
1,832,289
1,002,364
380,972
3,606,103
58,074
770,597
143,880
496,573
167,630
2,021,556
5,589,259
1,819,099
666,381
378,291
212,767
5,858,668
4,223,950
2,312,040
1,019,062
10,219,814
1,100,474
384,930
558,424
1,355,928
491,062
15,528
38,227
15,251
8,648
975
20,703
449
12,294
577
3,566
732
10,152
40,052
12,766
7,339
3,090
2,385
34,856
20,576
13,275
12,710
59,001
4,194
3,317
4,521
13,290
4,573
14,126
29,213
9,086
6,289
525
14,551
287
8,941
458
2,016
528
8,712
24,350
8,740
3,786
2,327
1,855
18,792
16,084
9,731
8,537
51,176
3,846
2,461
3,205
10,561
3,338
Tree
Cover
22.5
53.9
28.5
28.9
8.9
18.0
31.2
50.6
11.4
26.2
11.5
14.4
20.6
21.6
34.1
28.0
39.6
20.9
14.8
20.8
31.7
13.2
16.0
22.0
26.9
35.0
29.5
Gross Annual Net Annual
Sequestration Sequestration
per Area of per Area of
Tree Cover Tree Cover
0.288
0.229
0.282
0.231
0.221
0.212
0.314
0.220
0.228
0.329
0.183
0.409
0.176
0.260
0.157
0.320
0.297
0.230
0.513
0.206
0.399
0.377
0.241
0.399
0.285
0.263
0.285
Median: 0.26
0.262
0.175
0.168
0.168
0.119
0.149
0.201
0.160
0.181
0.186
0.132
0.351
0.107
0.178
0.081
0.241
0.231
0.124
0.401
0.151
0.268
0.327
0.221
0.296
0.202
0.209
0.208
Net: Gross
Annual
Sequestration
Ratio
0.91
0.76
0.60
0.73
0.54
0.70
0.64
0.73
0.79
0.57
0.72
0.86
0.61
0.68
0.52
0.75
0.78
0.54
0.78
0.73
0.67
0.87
0.92
0.74
0.71
0.79
0.73
Mean: 0.72
NA = not analyzed.
Sources: Nowak et al. (2013, in review)
Uncertainty and Time-Series Consistency
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 each of the 28 U.S. cities. A 10
percent uncertainty was associated with urban area estimates based on expert judgment, while a 1.4 percent
uncertainty is reported for the percent urban tree coverage value (Nowak and Greenfield 2012). Uncertainty
associated with estimates of gross and net C sequestration for each of the 28 U.S. cities was based on standard error
estimates for each of the city-level sequestration estimates reported by Nowak et al (2013, in review). These
estimates are based on field data collected in each of the 28 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 in the Planned
Improvements section of this chapter.
7-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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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 7-45. The net C flux
from changes in C stocks in urban trees in 2011 was estimated to be between -81.9 and -59.9 Tg CCh Eq. at a 95
percent confidence level. This indicates a range of 19 percent more sequestration to 13 percent less sequestration
than the 2011 flux estimate of -68.8 Tg CO2 Eq.
Table 7-45: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C
Stocks in Urban Trees (Tg COz Eq. and Percent)
2011 Flux Estimate Uncertainty Range Relative to Flux Estimate
Source Gas (Tg CCh Eq.) (Tg CCh Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Changes in C Stocks in
Urban Trees CO2 (68.8) (81.9) (59.9) 19% -13%
Note: Parentheses indicate negative values or net sequestration.
Details on the emission trends through time are described in more detail in the Methodology section, above.
QA/QC and Verification
The net C flux resulting from urban trees was predominately calculated using city-specific estimates of gross and net
C sequestration estimates for urban trees and urban tree coverage area published in the literature. The validity of
these data for their use in this section of the inventory was evaluated through correspondence established with Dr.
David J. Nowak, 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, 2011, and Nowak et al. 2013 in review).
Recalculations
The 1990 to 2010 net C flux estimates were recalculated relative to the previous Inventory based on three changes in
activity data; (1) 2010 U.S. Census data were released in March 2012, along with updated definitions of urban area
and urban cluster, resulting in revisions to the annual urban area estimated for 1990 to 2010; (2) a revised average
urban tree canopy cover (35.0 percent) was published by Nowak and Greenfield (2012); and (3) C sequestration data
was available for 28 rather than 14 cities from Nowak et al. (2013, in review). The combination of the
methodological and historical data changes resulted in an average annual net sequestration decrease of 19.5 Tg CCh
Eq. (24.5 percent) in urban trees compared to the previous report across the entire time-series.
Planned Improvements
A consistent representation of the managed land base in the United States is discussed at the beginning of the Land
Use, Land-Use Change, and Forestry chapter, and discusses a planned improvement by the USD A Forest Service to
reconcile the overlap between urban forest and non-urban forest greenhouse gas inventories. Urban forest
inventories are including areas also defined as forest land under the Forest Inventory and Analysis (FIA) program of
the USD A Forest Service, resulting in "double-counting" of these land areas in estimates of C stocks and fluxes for
this report. For example, Nowak et al. (2013, in review) estimates that 13.7 percent of urban land is measured by
the forest inventory plots, and could be responsible for up to 87 Tg C of overlap.
Urban tree cover data specific to all 50 states has been developed (Nowak 2013, in review). It may be possible to
develop and use a set of state-specific sequestration rates for estimating regional C flux estimates.
Future research may also enable more complete coverage of changes in the C stock in urban trees for all Settlements
land. To provide estimates for all Settlements, research would need to establish the extent of overlap between
Settlements and Census-defined urban areas, and would have to characterize sequestration on non-urban Settlements
land.
Land Use, Land-Use Change, and Forestry 7-67
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N2O
5E1)
Of the synthetic N fertilizers applied to soils in the United States, approximately 2.4 percent are currently applied to
lawns, golf courses, and other landscaping occurring within settlement areas. Application rates are lower than those
occurring on cropped soils, and, therefore, account for a smaller proportion of total U.S. soil N2O emissions per unit
area. In addition to synthetic N fertilizers, a portion of surface applied sewage sludge is applied to settlement areas.
In 2011, N2O emissions from settlement soils were 1.5 Tg CO2 Eq. (4.8 Gg). There was an overall increase of 51
percent over the period from 1990 through 2011 due to a general increase in the application of synthetic N fertilizers
to an expanding settlement area. Interannual variability in these emissions is directly attributable to interannual
variability in total synthetic fertilizer consumption and sewage sludge applications in the United States. Emissions
from this source are summarized in Table 7-46.
Table 7-46: Direct NzO Fluxes from Soils in Settlements Remaining Settlements(Tg COz Eq.
and Gg N2O)
Year Tg CCh Eq. Gg
1990 1.0 3.2
2005 1.5 4.7
2007
2008
2009
2010
2011
1.6
1.5
1.4
1.5
1.5
5.1
4.7
4.5
4.7
4.8
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 surface disposal of sewage sludge (see Annex
3.11 for a detailed discussion of the methodology for estimating sewage sludge application).
Nitrogen applications to settlement soils are estimated using data compiled by the USGS (Ruddy et al. 2006). The
USGS estimated on-farm and non-farm fertilizer use is 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 forest lands; values
for 2002 through 2008 were based on 2001 values adjusted for annual total N fertilizer sales in the United States
because there is no new activity data on application after 2001. 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 N fractions for settlements,
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 indirect emissions, as reported
in the N2O Emissions from Agricultural Soil Management source category of the Agriculture chapter (consistent
7-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
with reporting guidance that all indirect emissions are included in the Agricultural Soil Management source
category).
Uncertainty and Time-Series Consistency
The amount of N2O emitted from settlements depends not only on N inputs and fertilized area, but also on a large
number of variables, including organic C availability, oxygen gas partial pressure, soil moisture content, pH,
temperature, and irrigation/watering practices. The effect of the combined interaction of these variables on N2O flux
is complex and highly uncertain. The IPCC default methodology does not explicitly incorporate any of these
variables, except variations in fertilizer N and sewage sludge application rates. All settlement soils are treated
equivalently under this methodology.
Uncertainties exist in both the fertilizer N and sewage sludge application rates in addition to the emission factors.
Uncertainty in fertilizer N application was assigned a default level of ±50 percent.244 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 2011 emission estimates. The results of the quantitative uncertainty analysis are
summarized in Table 7-47. N2O emissions from soils in Settlements Remaining Settlements in 2011 were estimated
to be between 0.8 and 3.9 TgCO2Eq. at a 95 percent confidence level. This indicates a range of 49 percent below
to 163 percent above the 2011 emission estimate of 1.5 Tg CO2 Eq.
Table 7-47: Quantitative Uncertainty Estimates of NzO Emissions from Soils in Settlements
Remaining Settlements (Tg COz Eq. and Percent)
Source Gas 2011 Emissions Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Settlements Remaining
Settlements: N2O Fluxes from
Soils N2Q 1.5 08 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.
Planned Improvements
A minor improvement is planned to update the uncertainty analysis for direct emissions from settlements to be
consistent with the most recent activity data for this source.
Land-use change is constantly occurring, and land under a number of uses undergoes urbanization in the United
States each year. However, data on the amount of land converted to settlements is currently lacking. Given the lack
No uncertainty is provided with the USGS fertilizer consumption data (Ruddy et al. 2006) so a conservative ±50% was used
in the analysis.
Land Use, Land-Use Change, and Forestry 7-69
-------
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.
in in
In the United States, yard trimmings (i.e., grass clippings, leaves, and branches) and food scraps account for a
significant portion of the municipal waste stream, and a large fraction of the collected yard trimmings and food
scraps are discarded in landfills. Carbon contained in landfilled yard trimmings and food scraps can be stored for
very long periods.
Carbon storage estimates are associated with particular land uses. For example, harvested wood products are
accounted for under Forest Land Remaining Forest Land because these wood products are considered a component
of the forest ecosystem. The wood products serve as reservoirs to which C resulting from photosynthesis in trees is
transferred, but the removals in this case occur in the forest. Carbon stock changes in yard trimmings and food
scraps are associated with settlements, but removals in this case do not occur within settlements. To address this
complexity, yard trimming and food scrap C storage is reported under the "Other" source category.
Both the amount of yard trimmings collected annually and the fraction that is landfilled have declined over the last
decade. In 1990, over 53 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 2011; Schneider 2007,
2008). Since then, programs banning or discouraging yard trimmings disposal have led to an increase in backyard
composting and the use of mulching mowers, and a consequent 5 percent decrease in the tonnage generated (i.e.,
collected for composting or disposal). At the same time, an increase in the number of municipal composting
facilities has reduced the proportion of collected yard trimmings that are discarded in landfills—from 72 percent in
1990 to 35 percent in 2011. The net effect of the reduction in generation and the increase in composting is a 54
percent decrease in the quantity of yard trimmings disposed of in landfills since 1990.
Food scrap generation has grown by 46 percent since 1990, and though the proportion of food scraps discarded in
landfills has decreased slightly from 82 percent in 1990 to 80 percent in 2011, the tonnage disposed of in landfills
has increased considerably (by 42 percent). Overall, the decrease in the landfill disposal rate of yard trimmings 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 24.2 Tg CO2 Eq. in 1990 to 13.0 Tg CO2 Eq. in 2011 (Table 7-48 and Table 7-49).
Table 7-48: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg COz Eq.)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
1990
(21.0)
(1.8)
(9.0)
(10.2)
(3.2)
(24.2)
2005
(7.3)
(0.6) J
(3.3)
(3.4)
(4.3)
(11.6)
2007
(7.0)
• (0.6)
(3.2)
(3.2)
(3.9)
(10.9)
2008
(7.0)
(0.6)
(3.2)
(3.1)
(3.9)
(10.9)
2009
(8.5)
(0.8)
(3.9)
(3.8)
(4.2)
(12.7)
2010
(9.3)
(0.9)
(4.2)
(4.1)
(4.1)
(13.3)
2011
(9.2)
(0.9)
(4.2)
(4.1)
(3.8)
(13.0)
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values
Table 7-49: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
1990
(5.7)
(0.5) -
(2.5)
(2.8)
2005
(2.0)
• (0.2) /
(0.9)
(0.9)
2007
(1.9)
(0.2)
(0.9)
(0.9)
2008
(1.9)
(0.2)
(0.9)
(0.9)
2009
(2.3)
(0.2)
(1.1)
(1.0)
2010
(2.5)
(0.3)
(1.1)
(1.1)
2011
(2.5)
(0.2)
(1.1)
(1.1)
7-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Food Scraps (0.9) (1.2) ! (1.1) (1.1) (1.1) (1.1) (1.0)
Total Net Flux (6.6) (3.2) ,-* (3.0) (3.0) (3.5) (3.6) (3.6)
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values
Methodology
When wastes of biogenic origin (such as yard trimmings and food scraps) are landfilled and do not completely
decompose, the C that remains is effectively removed from the global C cycle. Empirical evidence indicates that
yard trimmings and food scraps do not completely decompose in landfills (Barlaz 1998, 2005, 2008; De la Cruz and
Barlaz 2010), and thus the stock of C in landfills can increase, with the net effect being a net atmospheric removal of
C. Estimates of net C flux resulting from landfilled yard trimmings and food scraps were developed by estimating
the change in landfilled C stocks between inventory years, based on methodologies presented for the Land Use,
Land-Use Change, and Forestry sector in IPCC (2003). Carbon stock estimates were calculated by determining the
mass of landfilled C resulting from yard trimmings or food scraps discarded in a given year; adding the accumulated
landfilled C from previous years; and subtracting the mass of C that was 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; 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 (i.e., moisture content and C content) 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: Tables
and Figures for 2010 (EPA 2011), which provides data for 1960, 1970, 1980, 1990, 2000, 2005, and 2007 through
2010. Data were not yet published for 2011, consequently, 2011 data on discards for yard trimmings and food
scraps were assumed to be equal to 2010 data from EPA (2011). To provide data for some of the missing years,
detailed backup data were obtained from Schneider (2007, 2008). Remaining years in the time series for which data
were not provided were estimated using linear interpolation. The EPA (2011) 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 landfills245 and combustors with energy recovery (i.e., ranging from 100
percent and 0 percent, respectively, in 1960 to 81 percent and 19 percent in 2000); it is assumed that the proportion
of each individual material (food scraps, grass, leaves, branches) that is landfilled is the same as the proportion
across the overall waste stream.
The amount of C disposed of in landfills each year, starting in 1960, was estimated by converting the discarded
landfilled yard trimmings and food scraps from a wet weight to a dry weight basis, and then multiplying by the
initial (i.e., pre-decomposition) C content (as a fraction of dry weight). The dry weight of landfilled material was
calculated using dry weight to wet weight ratios (Tchobanoglous et al. 1993, cited by Barlaz 1998) and the initial C
contents and the C storage factors were determined by Barlaz (1998, 2005, 2008) (Table 7-50).
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 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
245 EPA (2011) reports discards in two categories: "combustion with energy recovery" and "landfill, other disposal," which
includes combustion without energy recovery. For years in which there is data from previous EPA reports on combustion without
energy recovery, EPA assumes these estimates are still applicable. For 2000 to present, EPA assumes that any combustion of
MSW that occurs includes energy recovery, so all discards to "landfill, other disposal" are assumed to go to landfills.
Land Use, Land-Use Change, and Forestry 7-71
-------
can be expressed as a proportion of initial C (shown in the row labeled "CS, proportion of initial C stored (%)" in
Table 7-50).
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
over time, resulting in emissions of CH4 and CCh (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. The decay rates for each of the materials are shown in Table 7-50.
The first-order decay rates, k, for each component were derived from De la Cruz and Barlaz (2010). De la Cruz and
Barlaz (2010) calculate first-order decay rates using laboratory data published in Eleazer et al. (1997), and a
correction factor,/ is found so that the weighted average decay rate for all components is equal to the AP-42 default
decay rate (0.04) for mixed MSW for regions that receive more than 25 inches of rain annually. Because AP-42
values were developed using landfill data from approximately 1990, 1990 waste composition for the United States
fromEPA's Characterization of Municipal Solid Waste in the United States: 1990 Update was used to calculate/
This correction factor is then multiplied by the Eleazer et al. (1997) decay rates of each waste component to develop
field-scale first-order decay rates.
De la Cruz and Barlaz (2010) also use other assumed initial decay rates for mixed MSW in place of the AP-42
default value based on different types of environments in which landfills in the United States are found, including
dry conditions (less than 25 inches of rain annually, &=0.02) and bioreactor landfill conditions (moisture is
controlled for rapid decomposition, &=0.12). The Landfills section of the Inventory (which estimates CH4
emissions) estimates the overall MSW decay rate by partitioning the U.S. landfill population into three categories,
based on annual precipitation ranges of: (1) less than 20 inches of rain per year, (2) 20 to 40 inches of rain per year,
and (3) greater than 40 inches of rain per year. These correspond to overall MSW decay rates of 0.020, 0.038, and
0.057 year"1, respectively.
De la Cruz and Barlaz (2010) calculate component-specific decay rates corresponding to the first value (0.020
year1), but not for the other two overall MSW decay rates. To maintain consistency between landfill methodologies
across the Inventory, the correction factors (/) were developed for decay rates of 0.038 and 0.057 year1 through
linear interpolation. A weighted national average component-specific decay rate was calculated by assuming that
waste generation is proportional to population (the same assumption used in the landfill methane emission estimate),
based on population data from the 2000 U.S. Census. The component-specific decay rates are shown in Table 7-50.
For each of the four materials (grass, leaves, branches, food scraps), the stock of C in landfills for any given year is
calculated according to the following formula:
LFC,,t = E Wi,n x (1 -Md) x ICC, x {[CSt x ICC,] + [(1 - (CS, x ICC,)) x e^-"']}
n
where,
/ = Year for which C stocks are being estimated (year),
/' = Waste type for which C stocks are being estimated (grass, leaves, branches, food scraps),
LFdj = Stock of C in landfills in year /, for waste /' (metric tons),
Wi,n = Mass of waste /' disposed of in landfills in year n (metric tons, wet weight),
n = Year in which the waste was disposed of (year, where 1960 <«
-------
Thus, the C placed in a landfill in year n is tracked for each year / through the end of the inventory period (2011).
For example, disposal of food scraps in 1960 resulted in depositing about 1,135,000 metric tons of C. Of this
amount, 16 percent (179,000 metric tons) is persistent; the remaining 84 percent (956,000 metric tons) is degradable.
By 1965, more than half of the degradable portion (518,000 metric tons) decomposes, leaving a total of 617,000
metric tons (the persistent portion, plus the remainder of the degradable portion).
Continuing the example, by 2011, the total food scraps C originally disposed of in 1960 had declined to 179,000
metric tons (i.e., virtually all degradable C had decomposed). By summing the C remaining from 1960 with the C
remaining from food scraps disposed of in subsequent years (1961 through 2011), the total landfill C from food
scraps in 2011 was 38.1 million metric tons. This value is then added to the C stock from grass, leaves, and
branches to calculate the total landfill C stock in 2011, yielding a value of 254.2 million metric tons (as shown in
Table 7-51). In exactly the same way total net flux is calculated for forest C and harvested wood products, the total
net flux of landfill C for yard trimmings and food scraps for a given year (Table 7-49) is the difference in the landfill
C stock for that year and the stock in the preceding year. For example, the net change in 2011 shown in Table 7-49
(3.6 Tg C) is equal to the stock in 2011 (254.2 Tg C) minus the stock in 2010 (250.7 Tg C).
The C stocks calculated through this procedure are shown in Table 7-51.
Table 7-50: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered
(%), Initial C Content (%), and Decay Rate (year'1) for Landfilled Yard Trimmings and Food
Scraps in Landfills
Yard Trimmings
Variable
Moisture Content (% H2O)
CS, proportion of initial C stored (%)
Initial C Content (%)
Decay Rate (year"1)
Grass
70
53
45
0.323
Leaves
30
85
46
0.185
Branches
10
77
49
0.016
70
16
51
0.156
Table 7-51: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Branches
Leaves
Grass
Food Scraps
Total Carbon Stocks
1990
155.8
74.6
66.7
14.5
21.3
177.2
2005
202.9
97.5
87.3
18.1 /
31.7
234.7
2007
206.9
99.3
89.2
18.4
33.7
240.6
2008
208.8
100.2
90.0
18.6
34.8
243.6
2009
211.1
101.2
91.1
18.8
35.9
247.0
2010
213.6
102.3
92.2
19.0
37.0
250.7
2011
216.2
103.5
93.4
19.3
38.1
254.2
Note: Totals may not sum due to independent rounding.
Uncertainty and Time-Series Consistency
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, decay rate, 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 7-52. Total yard
trimmings and food scraps CC>2 flux in 2011 was estimated to be between -19.6 and -5.3 TgCChEq. at a 95
percent confidence level (or 19 of 20 Monte Carlo stochastic simulations). This indicates a range of 50 percent
Land Use, Land-Use Change, and Forestry 7-73
-------
below to 5 9 percent above the 2011 flux estimate of -13.0 Tg CCh Eq. More information on the uncertainty
estimates for Yard Trimmings and Food Scraps in Landfills is contained within the Uncertainty Annex.
Table 7-52: Tier 2 Quantitative Uncertainty Estimates for COz Flux from Yard Trimmings and
Food Scraps in Landfills (Tg COz Eq. and Percent)
Source
2011 Flux
Estimate
Gas (Tg CO2 Eq.)
Uncertainty Range Relative to Flux Estimate3
(Tg COz Eq.) (%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Yard Trimmings and Food
Scraps CCh (13.0) (19.6) (5.3) -50% +59%
a Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate negative values or net C sequestration.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
Recalculations Discussion
The current Inventory has been revised relative to the previous report. Input data were not yet published for 2011 at
the time of writing, so Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Tables and
Figures for 2010 (EPA 2011) input data were used for 2011. Although the input data were the same from 2010 to
2011, the final C stock and C flux estimates changed because of the decomposition model (see Methodology for
more information regarding the decomposition model), which calculates the C that remains from yard trimmings and
food scraps that were landfilled in past years.
Planned Improvements
Future work is planned to evaluate the consistency between the estimates of C storage described in this chapter and
the estimates of landfill CH4 emissions described in the Waste chapter. For example, the Waste chapter does not
distinguish landfill CH4 emissions from yard trimmings and food scraps separately from landfill CH4 emissions from
total bulk (i.e., municipal solid) waste, which includes yard trimmings and food scraps.
7-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 8-1). Landfills
accounted for approximately 17.5 percent of total U.S. anthropogenic methane (CH4) emissions in 2011, the third
largest contribution of any CH4 source in the United States. Additionally, wastewater treatment and composting of
organic waste accounted for approximately 2.8 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 2 percent of total U.S. N2O emissions. Nitrogen
oxides (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: 2011 Waste Chapter Greenhouse Gas Sources
Landfills
Wastewater Treatment
Composting
Waste as a Portion of all
Emissions
1,9%
I
25
50 75
Tg C02 Eq,
100
125
In following the UNFCCC requirement under Article 4.1 to develop and submit national greenhouse gas emission
inventories, the emissions and sinks presented in this report and this chapter, are organized by source and sink
categories and calculated using internationally-accepted methods provided by the Intergovernmental Panel on
Waste 8-1
-------
Climate Change (IPCC).246 Additionally, the calculated emissions and sinks in a given year for the United States
are presented in a common manner in line with the UNFCCC reporting guidelines for the reporting of inventories
under this international agreement.247 The use of consistent methods to calculate emissions and sinks by all nations
providing their inventories to the UNFCCC ensures that these reports are comparable. In this regard, U.S. emissions
and sinks reported in this inventory report are comparable to emissions and sinks reported by other countries.
Emissions and sinks provided in this inventory do not preclude alternative examinations,248 but rather this inventory
presents emissions and sinks in a common format consistent with how countries are to report inventories under the
UNFCCC. The report itself, and this chapter, follows this standardized format, and provides an explanation of the
IPCC methods used to calculate emissions and sinks, and the manner in which those calculations are conducted.
Overall, in 2011, waste activities generated emissions of 127.7 Tg CCh Eq., or just under 2 percent of total U.S.
greenhouse gas emissions.
Table 8-1: Emissions from Waste (Tg COz Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
Composting
N2O
Domestic Wastewater
Treatment
Composting
Total
1990
164.0
147.8
15.9
0.3
3.8
3.5
0.4
167.8
2005
130.5
112.5
16.5
1.6 -
6.4
4.7 .
1.7
136.9
2007
129.8
111.6
16.6
1.7
6.7
4.8
1.8
136.5
2008
131.9
113.6
16.6
1.7
6.8
4.9
1.9
138.6
2009
131.4
113.3
16.5
1.6
6.7
5.0
1.8
138.1
2010
124.7
106.8
16.4
1.5
6.8
5.1
1.7
131.4
2011
120.8
103.0
16.2
1.5
6.9
5.2
1.7
127.7
Note: Totals may not sum due to independent rounding.
Table 8-2: Emissions from Waste (Gg)
Gas/Source
CH4
Landfills
Wastewater Treatment
Composting
N2O
Domestic Wastewater
Treatment
Composting
1990
7,810
7,037 •
758
15
12
11
1
, 2005
.•* 6,217
5,357
785
75
21
15
6 ,
! 2007
6,183
5,314
791
79
21
16
6
2008
6,280
5,409
791
80
22
16
6
2009
6,258
5,397
786
75
22
16
6
2010
5,936
5,083
779
73
22
16
5
2011
5,751
4,907
770
74
22
17
6
Note: Totals may not sum due to independent rounding.
Carbon dioxide, CH4, and N2O emissions from the incineration of waste are accounted for in the Energy sector
rather than in the Waste sector because almost all incineration of municipal solid waste (MSW) in the United States
occurs at waste-to-energy facilities where useful energy is recovered. Similarly, the Energy sector also includes an
estimate of emissions from burning waste tires and hazardous industrial waste, because virtually all of the
combustion occurs in industrial and utility boilers that recover energy. The incineration of waste in the United States
See http://www.ipcc-nggip.iges.or.jp/public/index.html.
247 Seehttp://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/5270.php.
248 For example, see http://www.epa.gov/aboutepa/oswer.html.
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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in 2011 resulted in 12.4 Tg CCh Eq. emissions, nearly half of which is attributable to the combustion of plastics. For
more details on emissions from the incineration of waste, see Section 3.3.
It is additionally noted that in this chapter methodological guidance was taken from the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories. This latest guidance from the IPCC best represents the understanding of
emissions profiles from activities in the waste sector. The use of the most recently published calculation
methodologies by the IPCC, as contained in the 2006 IPCC Guidelines for waste source categories is fully in line
with the IPCC good practice guidance for methodological choice to improve rigor and accuracy. In addition, the
improvements in using the latest methodological guidance from the IPCC has been recognized by the UNFCCC's
Subsidiary Body for Scientific and Technological Advice in the conclusions of its 30th Session249, Numerous U.S.
inventory experts were involved in the development of the 2006 IPCC Guidelines, and their expertise has provided
this latest guidance from the IPCC with the most appropriate calculation methods that are then used in this chapter.
On October 30, 2009, the U.S. EPA published a rule for the mandatory reporting of greenhouse gases from large
GHG emissions sources in the United States. Implementation of 40 CFR Part 98 is referred to as EPA's
Greenhouse Gas Reporting Program (GHGRP). 40 CFR part 98 applies to direct greenhouse gas emitters, fossil
fuel suppliers, industrial gas suppliers, and facilities that inject CO2 underground for sequestration or other
reasons and requires reporting by 41 industrial categories. Reporting is at the facility level, except for certain
suppliers of fossil fuels and industrial greenhouse gases. In general, the threshold for reporting is 25,000 metric
tons or more of CO2 Eq. per year.
EPA's GHGRP dataset and the data presented in this inventory report are complementary and, as indicated in the
respective planned improvements sections for source categories in this chapter, EPA is analyzing how to use
facility-level GHGRP data to improve the national estimates presented in this inventory. Most methodologies
used in EPA's GHGRP are consistent with IPCC, though for EPA's GHGRP, facilities collect detailed
information specific to their operations according to detailed measurement standards. This may differ with the
more aggregated data collected for the inventory to estimate total, national U.S. emissions. It should be noted that
the definitions for source categories in the GHGRP may differ from those used in this inventory in meeting the
UNFCCC reporting guidelines. In line with the UNFCCC reporting guidelines, the inventory report is a
comprehensive accounting of all emissions from source categories identified in the IPCC guidelines. Further
information on the reporting categorizations in EPA's GHGRP and specific data caveats associated with
monitoring methods in EPA's GHGRP has been provided on the EPA's GHGRP website.250
EPA presents the data collected by EPA's GHGRP through a data publication tool251 that allows data to be
viewed in several formats including maps, tables, charts and graphs for individual facilities or groups of facilities.
249 These Subsidiary Body for Scientific and Technological Advice (SBSTA) conclusions state, "The SBSTA acknowledged
that the 2006 IPCC Guidelines contain the most recent scientific methodologies available to estimate emissions by sources and
removals by sinks of greenhouse gases (GHGs) not controlled by the Montreal Protocol, and recognized that Parties have gained
experience with the 2006 IPCC Guidelines. The SBSTA also acknowledged that the information contained in the 2006 IPCC
Guidelines enables Parties to further improve the quality of their GHG inventories." See
250 See
.
251 See .
Waste 8^
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In the United States, solid waste is managed by landfilling, recovery through recycling or composting, and
combustion through waste-to-energy facilities. Disposing of solid waste in modern, managed landfills is the most
commonly used waste management technique in the United States. More information on how solid waste data are
collected and managed in the United States is provided in Box 8-3 and Box 8-4. The municipal solid waste (MSW)
and industrial waste landfills referred to in this section are all modern landfills that must comply with a variety of
regulations as discussed in Box 8-5. Disposing of waste in illegal dumping sites is not considered to have occurred
in years later than 1980 and these sites are not considered to contribute to net emissions in this section for the
inventory time frame of 1990 to 2011. MSW landfills, or sanitary landfills, are sites where MSW is managed to
prevent or minimize health, safety, and environmental impacts. Waste is deposited in different cells and covered
daily with soil; many have environmental monitoring systems to track performance, collect leachate, and collect
landfill gas. Industrial waste landfills are constructed in a similar way as MSW landfills, but accept waste produced
by industrial activity, such as factories, mills, and mines.
After being placed in a landfill, organic 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 methane- (CH4) producing
anaerobic bacteria convert the fermentation products into stabilized organic materials and biogas consisting of
approximately 50 percent biogenic carbon dioxide (CO2) and 50 percent CH4, by volume. Landfill biogas also
contains trace amounts of non-methane organic compounds (NMOC) and volatile organic compounds (VOC) that
either result from decomposition by-products or volatilization of biodegradable wastes (EPA 2008).
Methane and CO2 are the primary constituents of landfill gas generation and emissions. However, the 2006
Intergovernmental Panel on Climate Change (IPCC) Guidelines set an international convention to not report
biogenic CO2 released due to landfill decomposition in the Waste sector (IPCC 2006). Carbon dioxide emissions
are estimated and reported for under the Land Use/Land Use Change and Forestry (LULUCF) sector (see Box 8-6).
Additionally, emissions of NMOC and VOC are not estimated because they are considered to be emitted in trace
amounts. Nitrous oxide (N2O) emissions from the disposal and application of sewage sludge on landfills are also not
explicitly modeled as part of greenhouse gas emissions from landfills. N2O emissions from sewage sludge applied
to landfills as a daily cover or for disposal are expected to be relatively small because the microbial environment in
an anaerobic landfill 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, only CH4 generation and
emissions are estimated for landfills under the Waste sector.
Methane generation and emissions from landfills are a function of several factors, including: (1) the total amount of
waste-in-place, which is the total waste landfilled annually over the operational lifetime of a landfill; (2) the
characteristics of the landfill receiving waste (e.g., composition of waste-in-place, size, climate, cover material); (3)
the amount of CH4 that is recovered and either flared or used for energy purposes; and (4) the amount of CH4
oxidized as the landfill gas passes through the cover material into the atmosphere. Each landfill has unique
characteristics, but all managed landfills practice similar operating practices, including the application of a daily and
intermediate cover material over the waste being disposed of in the landfill to prevent odor and reduce risks to
public health. Based on recent literature, the specific type of cover material used can affect the rate of oxidation of
landfill gas (RTI2011). The most commonly used cover materials are soil, clay, and sand. Some states also permit
the use of green waste, tarps, waste derived materials, sewage sludge or biosolids, and contaminated soil as a daily
cover. Methane production typically begins one or two years after waste is disposed of in a landfill and will continue
for 10 to 60 years or longer as the degradable waste decomposes over time.
In 2011, landfill CH4 emissions were approximately 103.0 Tg CO2 Eq. (4,907 Gg of CH4), representing the third
largest source of CH4 emissions in the United States, behind natural gas systems and enteric fermentation.
Emissions from MSW landfills, which received about 69 percent of the total solid waste generated in the United
States, accounted for about 94 percent of total landfill emissions, while industrial landfills accounted for the
remainder. Approximately 1,900 to 2,000 operational MSW landfills exist in the United States, with the largest
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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landfills receiving most of the waste and generating the majority of the CH4 emitted (EPA 2010; BioCycle 2010;
WBJ 2010). Conversely, there are approximately 3,200 MSW landfills in the United States that have been closed
since 1980 (for which a closure data is known, WBJ 2010). While the number of active MSW landfills has
decreased significantly over the past 20 years, from approximately 6,326 in 1990 to approximately 2,000 in 2010,
the average landfill size has increased (EPA 2010; BioCycle 2010; WBJ 2010). The exact number of active and
closed dedicated industrial waste landfills is not known at this time, but the Waste Business Journal total of landfills
that accept industrial and construction and demolition debris for 2010 is 1,305.
The estimated annual quantity of waste placed in MSW landfills increased 26 percent from about 205 Tg in 1990 to
258 Tg in 2011 (see Annex 3.13). Net CH4 emissions have fluctuated from year to year, but a slowly decreasing
trend has been observed over the past decade despite increased waste disposal amounts. For example, from 1990 to
2011, net CH4 emissions from landfills decreased by approximately 30 percent (see Table 8-3 and Table 8-4). This
decreasing trend can be attributed to a 21 percent reduction in the amount of decomposable materials (i.e., paper and
paperboard, food scraps, and yard trimmings) discarded in MSW landfills over the time series (EPA 2010) and an
increase in the amount of landfill gas collected and combusted (i.e., used for energy or flared), resulting in lower net
CH4 emissions from MSW landfills.252 For instance, in 1990, approximately 954 Gg of CH4 were recovered and
combusted from landfills, while in 2011, approximately 8,177 Ggof CH4 were combusted, representing an average
annual increase in the quantity of CH4 recovered and combusted from 1990 to 2011 of 11 percent (see Annex 3.13).
In 2011, an estimated 71 new landfill gas-to-energy (LFGTE) projects and 29 new flares began operation (EPA
2012). While the amount of landfill gas collected and combusted continues to increase every year, the rate of
increase in collection and combustion no longer exceeds the rate of additional CH4 generation from the amount of
organic MSW landfilled as the U.S. population grows.
The total amount of MSW 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.
Additionally, the quantity of recovered CH4 that is either flared or used for energy purposes is expected to
continually increase as a result of 1996 federal regulations that require large MSW landfills to collect and combust
landfill gas (see 40 CFR Part 60, Subpart Cc 2005 and 40 CFR Part 60, Subpart WWW 2005), as well as voluntary
programs that encourage 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).
252 Due to a lack of data specific to industrial waste landfills, landfill gas recovery is only estimated for MSW landfills.
Waste
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Table 8-3: CH4 Emissions from Landfills (Tg COz Eq.)
Activity
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
1990
172.6
11.6
(13.3)
(6.7)
(16.4)
147.8
2005
< 241.2
15.4 ^
(55.9) -.
- (75.7) /*,
, (12.5) :
: 112.5
2007
254.2
15.5
(62.6)
(83.2)
(12.4)
111.6
2008
259.2
15.7
(67.2)
(81.5)
(12.6)
113.6
2009
262.9
15.8
(74.2)
(78.6)
(12.6)
113.3
2010
266.6
15.9
(82.5)
(81.4)
(11.9)
106.8
2011
270.2
16.0
(88.0)
(83.7)
(11.4)
103.0
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at both municipal and industrial landfills. Oxidation at MSW landfills is accounted for after
CELi recovery.
Table 8-4: ChU Emissions from Landfills (Gg)
Activity
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
Total
1990
8,219
554
(634)
(321)
(782)
7,037
; 2005
11,486
732
(2,660)
(3,606)
. (595)
,4 5,357
2007
! 12,106
740
(2,980)
(3,961)
(590)
5,314
2008
12,343
746
(3,198)
(3,880)
(601)
5,409
2009
12,519
752
(3,532)
(3,743)
(600)
5,397
2010
12,694
758
(3,927)
(3,876)
(565)
5,083
2011
12,868
761
(4,190)
(3,986)
(545)
4,907
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes CH4 oxidation at municipal and industrial landfills. Oxidation at MSW landfills is accounted for after CELi
recovery.
CH4 emissions from landfills were estimated as the CH4 produced from MSW landfills, plus the CH4 produced by
industrial waste landfills, minus the CH4 recovered and combusted from MSW landfills, minus the CH4 oxidized
before being released into the atmosphere:
CH4jSolid Waste = [CH4jMSW + CH4jInd ~ R] ~ Ox
where,
CH4, Soiid waste = CH4 emissions from solid waste
CH4,Msw = CH4 generation from MSW landfills,
CH4jnd = CH4 generation from industrial landfills,
R = CH4 recovered and combusted (only for MSW landfills), and
Ox = CH4 oxidized from MSW and industrial waste landfills before release to the atmosphere.
The methodology for estimating CH4 emissions from landfills is based on the first order decay model described by
the IPCC (IPCC 2006). Methane generation is based on nationwide waste disposal data; it is not landfill-specific.
The amount of CH4 recovered, however, is landfill-specific, but only for MSW landfills due to a lack of data
specific to industrial waste landfills. Values for the CH4 generation potential (L0) and decay rate constant (k) used in
the first order decay model were obtained from an analysis of CH4 recovery rates for a database of 52 landfills and
from published studies of other landfills (RTI2004; EPA 1998; SWANA 1998; Peer, Thorneloe, and Epperson
1993). The decay rate constant was found to increase with average annual rainfall; consequently, values of k were
developed for 3 ranges of rainfall, or climate types (wet, arid, and temperate). 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. Historical census data were used to account for the shift in population to more arid areas over time. An
overview of the data sources and methodology used to calculate CH4 generation and recovery is provided below,
while a more detailed description of the methodology used to estimate CH4 emissions from landfills can be found in
Annex 3.13.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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National MSW landfill waste generation and disposal data are obtained from the BioCycle State of Garbage surveys,
published approximately every two years. The State of Garbage (SOG) survey is the only continually updated
nationwide survey of waste disposed in landfills in the United States. The SOG surveys use the principles of mass
balance where all MSW generated is equal to the amount of MSW landfilled, combusted in waste-to-energy plants,
composted, and/or recycled (BioCycle 2010). This approach assumes that all waste management methods are
tracked and reported to state agencies. Survey respondents are asked to provide a breakdown of MSW generated
and managed by landfilling, recycling, composting, and combustion (in waste-to-energy facilities) in actual
tonnages. The survey reported data are adjusted to exclude non-MSW materials (e.g., industrial and agricultural
wastes, construction and demolition debris, automobile scrap, and sludge from wastewater treatment plants) that
may be included in survey responses. All state disposal data are adjusted for import/export; imported waste is
included in a particular state and exported waste is not. Where no waste generation data are provided by a state in
the SOG survey, the amount generated is estimated using the average nationwide waste per capita rate multiplied by
that particular state's population.
National landfill waste generation data for 1989 through 2008 were obtained from the SOG survey for every two
years (BioCycle 2006, 2008, and 2010). National landfill waste generation data for the years in-between the
BioCycle State of Garbage surveys (e.g., 2001, 2003, 2005, 2007, 2009, 2010, and 2011) were extrapolated based on
BioCycle data and the U.S. Census population The most recent SOG survey was published in 2010 for the 2008
year. Waste generation data will be updated as new reports are published. Because the SOG survey 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 (2009, 2012) and national per capita solid waste generation from the
survey (2010).
Estimates of the quantity of waste landfilled from 1989 to the current inventory year are determined by applying a
waste disposal factor to the total amount of waste generated (i.e., the SOG data). A waste disposal factor is
determined for each year an SOG survey is published and equals the ratio of the total amount of waste landfilled to
the total amount of waste generated. The waste disposal factor is interpolated for the years in-between the BioCycle
surveys, as is done for the amount of waste generated for a given survey year.
Estimates of the annual quantity of waste landfilled for 1960 through 1988 were obtained fromEPA's
Anthropogenic Methane Emissions in the United States, Estimates for 1990: Report to Congress (EPA 1993) and an
extensive landfill survey by the EPA's Office of Solid Waste in 1986 (EPA 1988). Although waste placed in
landfills in the 1940s and 1950s contributes very little to current CH4 generation, estimates for those years were
included in the first order decay model for completeness in accounting for CH4 generation rates and are based on the
population in those years and the per capita rate for land disposal for the 1960s. For calculations in this inventory,
wastes landfilled prior to 1980 were broken into two groups: wastes disposed in landfills (Methane Conversion
Factor, MCF, of 1) and those disposed in dumps (MCF of 0.6). All calculations after 1980 assume waste is disposed
in managed, modern landfills. Please see Annex 3.13 for more details.
Methane recovery is currently only accounted for at MSW landfills since no comprehensive data regarding gas
collection systems have been published for industrial waste landfills. The estimated landfill gas recovered per year at
MSW landfills was based on a combination of three databases: the flare vendor database (contains updated sales
data collected from vendors of flaring equipment), a database of landfill gas-to-energy (LFGTE) projects compiled
by LMOP (EPA 2012), and a database developed by the Energy Information Administration (EIA) for the voluntary
reporting of greenhouse gases (EIA 2007). Based on the information provided by the EIA and flare vendor
databases, the CH4 combusted by flares in operation from 1990 to the current inventory year was estimated.
Information provided by the EIA and LMOP databases were used to estimate CH4 combusted in LFGTE projects
over the time series. The three databases were carefully compared to identify landfills that were in two or all three
of the databases to avoid double or triple counting CH4 reductions.
The flare vendor database estimates CH4 combusted by flares using the midpoint of a flare's reported capacity while
the EIA database uses landfill-specific measured gas flow. As the EIA database only includes data through 2006;
2007 to 2011 recovery for projects included in the EIA database were assumed to be the same as in 2006. This
quantity likely underestimates flaring because these databases do not have information on all flares in operation.
The EIA database is no longer being updated and it is expected that data obtained from the EPA's Greenhouse Gas
Reporting Program (GHGPJ3) will serve as a supplemental data source for facility-reported recovery data.
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
Waste 8-7
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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 provide 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 emission reductions associated with LFGTE projects for which a flare had not been identified from the
emission reductions associated with flares (referred to as the flare correction factor). A further explanation of the
methodology used to estimate the landfill gas recovered can be found in Annex 3.13.
A destruction efficiency of 99 percent was applied to CH4 recovered to estimate CH4 emissions avoided due to the
combusting of CH4 in destruction devices, i.e., flares. The destruction efficiency value was selected based on the
range of efficiencies (86 to 99 percent) recommended for flares in EPA's AP-42 Compilation of Air Pollutant
Emission Factors, Chapter 2.4 (EPA 2008), efficiencies used to establish new source performance standards (NSPS)
for landfills, and in recommendations for shutdown flares used in LMOP.
Emissions from industrial waste landfills were estimated from industrial production data (ERG 2012), waste
disposal factors, and the first order decay model. As over 99 percent of the organic waste placed in industrial waste
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). There are currently no data sources that track
and report the amount and type of waste disposed of in industrial waste landfills in the United States. Therefore, the
amount of waste landfilled is assumed to be a fraction of production that is held constant over the time series as
explained in Annex 3.13. The composition of waste disposed of in industrial waste landfills is expected to be more
consistent in terms of composition and quantity than that disposed of in MSW landfills.
The amount of CH4 oxidized by the landfill cover at both municipal and industrial waste 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 waste landfills.
Several types of uncertainty are associated with the estimates of CH4 emissions from MSW and industrial waste
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 MSW and
industrial waste landfill for each year of its operation. The SOG survey is the only nationwide data source that
compiles the amount of MSW disposed at the state-level. The surveys do not include information on waste
composition and there are no comprehensive data sets that compile quantities of waste disposed or waste
composition by landfill. Some MSW landfills have conducted detailed waste composition studies, but landfills in
the United States are not required to perform these types of studies. 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
MSW landfills, are representative of conditions at U. S. landfills. When this top-down approach is applied at the
nationwide level, the uncertainties are assumed to be less than when applying this approach to individual landfills
and then aggregating the results to the national level. In other words, this approach may over- and under-estimate
CH4 generation at some landfills if used at the facility-level, but the end result is expected to balance out because it
is being applied nationwide. There is also a high degree of uncertainty and variability associated with the first order
decay model, particularly when a homogeneous waste composition and hypothetical decomposition rates are applied
to heterogeneous landfills (IPCC 2006).
Additionally, there is a lack of landfill-specific information regarding the number and type of industrial waste
landfills in the United States. The approach used here assumes that the majority (99 percent) of industrial waste
disposed of in industrial waste landfills consists of waste from the pulp and paper and food and beverage industries.
However, because waste generation and disposal data are not available in an existing data source for all U.S.
industrial waste landfills, we apply a straight disposal factor over the entire time series to the amount of waste
generated to determine the amounts disposed.
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
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Aside from the uncertainty in estimating CH4 generation potential, uncertainty exists in the estimates of the landfill
gas oxidized. A constant oxidation factor of 10 percent as recommended by the Intergovernmental Panel on Climate
Change (IPCC) for managed landfills is used for both MSW and industrial waste landfills regardless of climate, the
type of cover material, and/or presence of a gas collection system. The number of field studies measuring the rate of
oxidation has increased substantially since the IPCC 2006 Guidelines were published and, as discussed in the
Potential Improvements section, efforts are being made to review the literature and revise this value based on recent,
peer-reviewed studies.
Another significant source of uncertainty lies with the estimates of CH4 that are recovered by flaring and gas-to-
energy projects at MSW landfills. Three separate databases containing recovery information are used to determine
the total amount of CH4 recovered and there are uncertainties associated with each. The LMOP database and the
flare vendor databases are updated annually, while the EIA database has not been updated since 2005 and will
essentially be replaced by the GHGRP data for a portion of landfills (i.e., those meeting the GHGPJ3 thresholds). To
avoid double counting and to use the most relevant estimate of CH4 recovery for a given landfill, a hierarchical
approach is used among the three databases. The EIA data are given precedence because CH4 recovery was directly
reported by landfills, the LMOP data are given second priority because CH4 recovery is estimated from facility-
reported LFGTE system characteristics, and the flare data are given third priority because this database contains
minimal information about the flare and no site-specific operating characteristics (Bronstein et al., 2012). The IPCC
default value of 10 percent for uncertainty in recovery estimates was used in the uncertainty analysis when metering
of landfill gas was in place (for about 64 percent of the CH4 estimated to be recovered). This 10 percent uncertainty
factor applies to 2 of the 3 databases (EIA and LMOP). For flaring without metered recovery data (approximately 34
percent of the CH4 estimated to be recovered), a much higher uncertainty of approximately 50 percent was used
(e.g., when recovery was estimated as 50 percent of the flare's design capacity). The compounding uncertainties
associated with the 3 databases leads to the large upper and lower bounds for MSW landfills presented in Table 8-5.
The results of the IPCC Good Practice Guidance Tier 2 quantitative uncertainty analysis are summarized in Table
8-5. In 2011, landfill CH4 emissions were estimated to be between 47.0 and 150.2 Tg COa Eq., which indicates a
range of 54 percent below to 46 percent above the 2011 emission estimate of 103.0 Tg CO2 Eq.
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Landfills (Tg COz
Eq. and Percent)
Source
Landfills
MSW
Industrial
Gas
CH4
CH4
CH4
2011 Emission
Estimate
(Tg C02 Eq.)
103.0
88.7
14.4
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower
Bound
47.0
33.5
10.5
Upper
Bound
150.2
136.0
17.4
Lower
Bound
-54%
-62%
-27%
Upper
Bound
+46%
+53%
+21%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
A QA/QC analysis was performed for data gathering and input, documentation, and calculation. QA/QC checks are
not performed on the published data used to populate the inventory data set, including the SOG survey data and the
published LMOP database. A primary focus of the QA/QC checks was to ensure that CH4 recovery estimates were
not double-counted and that all LFGTE projects and flares were included in the respective project databases. Both
manual and electronic checks were made to ensure that emission avoidance from each landfill was calculated in only
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.
When conducted, methodological recalculations are applied to the entire time-series to ensure time-series
consistency from 1990 through the current inventory year. No methodological changes were made for this
Waste 8-9
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inventory, but the national landfill waste generation data for 2007, 2008, 2009, and 2010 were recalculated for states
that did not report an amount of waste generated in the SOG 2010 survey. This recalculation was warranted after
reviewing the waste generation and disposal trends over the time series, particularly for years after 2004 where a
noticeable decrease in the amount of waste generated was calculated. For states that did not report an amount of
waste generated in the 2010 survey (BioCycle 2010), the recalculations used the most recent SOG waste per capita
data in the 2010 survey and state-specific generation rates from the previous SOG survey (BioCycle 2008). These
recalculations resulted in a slight increase in the waste generated for 2007 through 2010.
Improvements to the inventory being examined include incorporating data from the EPA's GHGRP and recent peer-
reviewed literature, modifying the default oxidation factor applied to MSW and industrial waste landfills, and either
modifying the bulk waste degradable organic carbon (DOC) value or estimating emissions using a waste-specific
approach in the first order decay model.
Beginning in 2011, all MSW landfills that accepted waste on or after January 1, 1980 and generate CH4 in amounts
equivalent to 25,000 metric tons or more of carbon dioxide equivalent (CO2 Eq.) were required to calculate and
report their greenhouse gas emissions to EPA through its GHGRP. The MSW landfill source category of the
GHGRP consists of the landfill, landfill gas collection systems, and landfill gas destruction devices, including flares.
Potential improvements to the inventory methodology may be made using the GHGRP data, specifically for inputs
to the first order decay equation. The approach used by the inventory to estimate CH4 generation assumes a bulk
waste-specific DOC value that may not accurately capture the changing waste composition over the time series (e.g.,
the reduction of organics entering the landfill environment due to increased composting, see Box 8-4). Using data
obtained from the GHGRP and any publicly available landfill-specific waste characterization studies in the United
States, the methodology may be modified to incorporate a waste composition approach or revisions may be made to
the bulk waste DOC value currently used. Additionally, GHGRP data could be analyzed and a weighted average for
the methane correction factor (MCF), fraction of CH4 (F) in the landfill gas, the destruction efficiency of flares, and
the decay rate constant (k) could replace the values currently used in the inventory.
The most significant contribution of the GHGRP data to the inventory is expected to be the amount of recovered
landfill gas and other information related to the gas collection system (Bronstein et al., 2012). Information for
landfills with gas collection systems reporting under the GHGRP will be incorporated into the inventory data set and
the measured CH4 recovery data will be used for the reporting landfills in lieu of the El A, LMOP, and flare vendor
data. The GHGRP data undergo an extensive series of verification steps, are more reliable and accurate than the
data currently used, and will reduce uncertainties surrounding CH4 recovery when applied to the landfills in the
inventory data set (Bronstein et al., 2012).
In addition to MSW landfills, industrial waste landfills at facilities generating CH4 in amounts equivalent to 25,000
metric tons or more of CO2 Eq. were required to report their GHG emissions beginning in September 2012 through
EPA's GHGRP. Similar data for industrial waste landfills as is required for the MSW landfills will be reported. Any
additions or improvements to the inventory using reported GHGRP data will be made for the industrial waste
landfill portion of the inventory. One possible improvement is the addition of industrial sectors other than pulp and
paper, and food and beverage (e.g., metal foundries, petroleum refineries, and chemical manufacturing facilities).
Of particular interest in the GHGRP data set for industrial waste landfills will be the presence of gas collection
systems since recovery is not currently associated with industrial waste landfills in the inventory methodology. It is
unlikely that data reported through the GHGRP for industrial waste landfills will yield improved estimates for k and
Lo for the industrial sectors. However, EPA is considering an update to the L0 and k values for the pulp and paper
sector and are currently gathering feedback from stakeholders.
The addition of this higher tier data will improve the emission calculations to provide a more accurate representation
of greenhouse gas emissions from MSW and industrial waste landfills, but potential improvements to the inventory
will not occur until after the deferral of GHGRP equation inputs expires in March 2013 for both MSW and industrial
waste landfills, or as early as the 1990 to 2013 inventory report. Facility-level reporting data from the GHGRP are
not available for all inventory years as reported in this inventory; therefore, particular attention will be made to
ensure time series consistency while incorporating data from EPA's GHGRP that would be useful to improve the
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
emissions estimates for MSW landfills. In implementing improvements and integration of data from the GHGRP,
the latest guidance from the IPCC on the use of facility-level data in national inventories will be relied upon.253
As a first step toward revising the oxidation factor used in the inventory, a literature review was conducted in 2011
(RTI2011). A standard CH4 oxidation factor of 10 percent has been used for both industrial and MSW landfills for
all inventory reports and is currently recommended as the default for well-managed landfills in the latest IPCC
guidelines (2006). Recent comments on the inventory methodology indicated that a default oxidation factor of 10
percent may be less than oxidation rates achieved at well-managed landfills with gas collection and control. The
impact of different landfill cover types on the rate of oxidation warrants further investigation as well.
Currently, one oxidation factor (10 percent) is applied to the total amount of waste generated nationwide. Changing
the oxidation factor and calculating the amount of CH4 oxidized from landfills with gas collection and control
requires the estimation of waste disposed of in these types of landfills. The inventory methodology uses waste
generation data from the SOG surveys, which report the total amount of waste generated and disposed nationwide
by state. In 2010, the State of Garbage survey requested data on the presence of landfill gas collection systems for
the first time. Twenty-eight states reported that 260 out of 1,414 (18 percent) operational landfills recovered landfill
gas (BioCycle 2010). However, the survey did not include closed landfills with gas collection and control systems.
In the future, the amount of states collecting and reporting this information is expected to increase. The EPA's
GHGRP data set for MSW landfills could be used to fill in the gaps related to the amount of waste disposed in
landfills with gas collection systems. Although the EPA's GHGRP does not capture every landfill in the United
States, larger landfills are expected to meet the reporting thresholds and will be reporting waste disposal information
by year beginning in March 2013. After incorporating the EPA's GHGRP data, it may be possible to calculate the
amount of waste disposed of at landfills with and without gas collection systems in the United States, which will
allow the inventory waste model to apply different oxidation factors depending on the presence of a gas collection
system.
While research findings indicate some evidence that landfills with gas collection and control achieve a 20 percent or
higher oxidation rate, there is not sufficient certainty to adopt a higher oxidation rate at this time. It is expected that
with increased reporting by states in the State of Garbage survey, as well as the data collected through EPA's
GHGRP, the oxidation rate for at least a subset of landfills may be increased in a future inventory. A continued
effort will be made to review peer-reviewed field studies that focus on oxidation specifically to determine how
oxidation is affected by the presence of a gas collection system and landfill cover type and whether increasing the
oxidation factor is warranted for all or only a portion of landfills (e.g., open versus closed, or only those with gas
collection systems).
Municipal solid waste generated in the United States can be managed through landfilling, recycling, composting,
and combustion with energy recovery. There are two main sources for nationwide solid waste management data in
the United States,
• The BioCycle and Earth Engineering Center of Columbia University's State of Garbage (SOG) in America
surveys and
• The EPA's Municipal Solid Waste in The United States: Facts and Figures reports.
The SOG surveys collect state-reported data on the amount of waste generated and the waste managed via different
management options: landfilling, recycling, composting, and combustion. The survey asks for actual tonnages
instead of percentages in each waste category (e.g., residential, commercial, industrial, construction and demolition,
organics, tires) for each waste management option. If such a breakdown is not available, the survey asks for total
tons landfilled. The data are adjusted for imports and exports so that the principles of mass balance are adhered to,
whereby the amount of waste managed does not exceed the amount of waste generated. The SOG reports present
survey data aggregated to the state level.
253 See: http://www.ipcc-nggip.iges.or.jp/meeting/pdfiles/1008_Model_and_Facility_Level_Data_Report.pdf
Waste 8-11
-------
The EPA Facts and Figures reports use a materials flow methodology, which relies heavily on a mass balance
approach. Data are gathered from industry associations, key businesses, similar industry sources, and government
agencies (e.g., the Department of Commerce and the U.S. Census Bureau) and are used to estimate tons of materials
and products generated, recycled, or discarded nationwide. The amount of MSW generated is estimated by
adjusting the imports and exports of produced materials. MSW that is not recycled, composted, or combusted is
assumed to be landfilled. The data presented in the report are nationwide totals.
The State of Garbage surveys are the preferred data source for estimating waste generation and disposal amounts in
the inventory because they are considered a more objective, numbers-based analysis of solid waste management in
the United States. However, the EPA Facts and Figures reports are useful when investigating waste management
trends at the nationwide level and for typical waste composition data, which the State of Garbage surveys do not ask
for.
In this inventory, emissions from solid waste management are presented separately by waste management option,
except for recycling of waste materials. Emissions from recycling are attributed to the stationary combustion of
fossil fuels, and are presented in the stationary combustion chapter in the Energy sector, although the emissions
estimates are not called out separately. Emissions from solid waste disposal in landfills and the composting of solid
waste materials are presented in the Landfills and Composting chapters in the Waste sector of this report. In the
United States, almost all incineration of MSW occurs at waste-to-energy facilities or industrial facilities where
useful energy is recovered, and thus emissions from waste incineration are accounted for in the Incineration chapter
of the Energy sector of this report.
As shown in Figure 8-2 and Figure 8-3, landfilling of MSW is currently and has been the most common waste
management practice. A large portion of materials in the waste stream are recovered for recycling and composting,
which is becoming an increasingly prevalent trend throughout the country. Materials that are composted would have
normally been disposed of in a landfill.
Figure 8-2: Management of Municipal Solid Waste in the United States, 2010 (BioCycle
2010)
Management of MSW in the United States (BioCycle
2010J
Composted
6%
',(!r,;,A^T«s^,lvr^/.y}ws«fi'A-:'.^'i-li'.sr;x,- ;-
MSW to WTE
7%
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Figure 8-3: MSW Management Trends from 1990 to 2010 (EPA 2011)
160
140 -V
120
100
80
60
40
-Landfilling
Combustion with Energy
Recovery
"Recycling
"Composting
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
Table 8-6 presents a typical composition of waste disposed of at a typical MSW landfill in the United States over
time. It is important to note that the actual composition of waste entering each landfill will vary from that presented
in Table 8-6. Understanding how the waste composition changes over time, specifically for the degradable waste
types, is important for estimating greenhouse gas emissions. For certain degradable waste types (i.e., paper and
paperboard), the amounts discarded have decreased over time due to an increase in recovery (see Table 8-6 and
Figure 8-4). Landfill ban legislation affecting yard trimmings resulted in an increase of composting from 1990 to
2008. Table 8-6 and Figure 8-4 do not reflect the impact of backyard composting on yard trimming generation and
recovery estimates. The recovery of food trimmings has been consistently low. Increased recovery of degradable
materials reduces the CH4 generation potential and CH4 emissions from landfills.
Waste 8-13
-------
Table 8-6: Materials Discarded in the Municipal Waste Stream by Waste Type, percent (EPA
2011)
Waste Type
Paper and Paperboard
Glass
Metals
Plastics
Rubber and Leather
Textiles
Wood
Othera
Food Scrapsb
Yard Trimmings0
Miscellaneous
Inorganic Wastes
1990
24.5%
5.7%
7.7%
15.7%
3.5%
5.5% •'
7.4%
1.8%
17.9%
7.0%
2.1%
; 2005
.« 24.5%
5.7%
7.7%
„ 15.7%
3.5%
5.5%
7.4%
1.8%
17.9%
7.0%
2.1%
2007
- 21.7%
5.5%
7.9%
16.4%
3.6%
5.9%
'• 7.5%
1.9%
18.2%
6.7%
2.1%
2008
19.7%
5.3%
8.0%
16.0%
3.7%
6.2%
7.6%
1.9%
18.6%
6.6%
2.2%
2009
14.8%
5.0%
8.0%
15.8%
3.7%
6.3%
7.7%
1.9%
19.1%
7.6%
2.2%
2010
15.3%
4.8%
8.3%
16.3%
3.8%
6.4%
7.8%
1.9%
19.3%
8.1%
2.2%
"Includes electrolytes in batteries and fluff pulp, feces, and urine in disposable diapers. Details may
not add to totals due to rounding. Source: EPA 2011.
b Data for food scraps were estimated using sampling studies in various parts of the country in
combination with demographic data on population, grocery store sales, restaurant sales, number of
employees, and number of prisoners, students, and patients in institutions. Source: EPA 2010.
0 Data for yard trimmings were estimated using sampling studies, population data, and published
sources documenting legislation affecting yard trimmings disposal in landfills. Source: EPA 2010.
Figure 8-4: Percent of Recovered Degradable Materials from 1990 to 2010, percent (EPA 2011)
70% ,
60%
40%
30%
0%
j1'
— * -
o o m r-« co en o
-------
• Leachate collection and removal systems
• Operating practices (e.g., daily and intermediate cover, receipt of regulated hazardous wastes, use of
landfill cover material, access options to prevent illegal dumping, use of a collection system to prevent
stormwater run-on/run-off, record-keeping)
• Air monitoring requirements (explosive gases)
• Groundwater monitoring requirements
• Closure and post-closure care requirements (e.g., final cover construction), and
• Corrective action provisions.
Specific federal regulations that affected MSW landfills must comply with include the 40 CFR Part 258 (Subtitle D
of RCRA), or equivalent state regulations and the New Source Performance Standards (NSPS) 40 CFR Part 60
Subpart WW. Additionally, state and tribal requirements may exist. For more information regarding federal MSW
landfill regulations, see http://www.epa.gov/osw/nonhaz/municipal/landfill/msw_regs.htm.
Regarding the depositing of wastes of biogenic origin in landfills (i.e., all degradable waste), empirical evidence
shows that some of these wastes degrade very slowly in landfills, and the C they contain is effectively sequestered in
landfills over a period of time (Barlaz 1998, 2006). Estimates of C 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).
Wastewater treatment processes can produce anthropogenic CH4 and N2O emissions. Wastewater from domestic254
and industrial sources is treated to remove soluble organic matter, suspended solids, pathogenic organisms, and
chemical contaminants. Treatment may either occur on site, most commonly through septic systems or package
plants, or off site at centralized treatment systems. Centralized wastewater treatment systems may include a variety
of processes, ranging from lagooning to advanced tertiary treatment technology for removing nutrients. In the
United States, approximately 20 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 2011).
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 N present, usually in the form of
urea, ammonia, and proteins. These compounds are converted to nitrate (NOs) 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 has
typically been associated with denitrification. Recent research suggests that higher emissions of N2O may in fact
originate from nitrification (Ahn et al. 2010).
Throughout the inventory, emissions from domestic wastewater also include any commercial and industrial wastewater collected and co-
treated with domestic wastewater.
Waste
-------
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 CH4 than wastewater with lower
COD (or BOD) concentrations. BOD represents the amount of oxygen that would be required to completely
consume the organic matter contained in the wastewater through aerobic decomposition processes, while COD
measures the total material available for chemical oxidation (both biodegradable and non-biodegradable). Because
BOD is an aerobic parameter, it is preferable to use COD to estimate CH4 production. The principal factor in
determining the N2O generation potential of wastewater is the amount of N in the wastewater. The variability of N
in the influent to the treatment system, as well as the operating conditions of the treatment system itself, also impact
the N2O generation potential.
In 2011, CH4 emissions from domestic wastewater treatment were 0.36 Tg CO2 Eq. (360 Gg). Emissions remained
fairly steady from 1990 through 1997, but have decreased since that time due to decreasing percentages of
wastewater being treated in anaerobic systems, including reduced use of on-site septic systems and central anaerobic
treatment systems. In 2011, CH4 emissions from industrial wastewater treatment were estimated to be 8.6 Tg CO2
Eq. (409 Gg). Industrial emission sources have increased across the time series through 1999 and then fluctuated up
and down with production changes associated with the treatment of wastewater from the pulp and paper
manufacturing, meat and poultry processing, fruit and vegetable processing, starch-based ethanol production, and
petroleum refining industries. Table 8-7 and Table 8-8 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 2011 emissions of N2O from centralized
wastewater treatment processes and from effluent were estimated to be 0.3 Tg CO2 Eq. (1 Gg) and 4.9 Tg CO2 Eq.
(15.7 Gg), respectively. Total N2O emissions from domestic wastewater were estimated to be 5.2 Tg CO2 Eq. (16.7
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 8-7: ChU and NzO Emissions from Domestic and Industrial Wastewater Treatment (Tg
COz Eq.)
Activity
CH4
Domestic
Industrial*
N2O
Domestic
Total
1990
15.9
8.8
7.1 .
3.5
3.5
19.4
2005
16.5
8.3
8.2
4.7
4.7 ~
21.2
2007
16.6
i 8.1
8.5
4.8
4.8
21.4
2008
16.6
8.0
8.6
4.9
4.9
21.5
2009
16.5
8.0
8.5
5.0
5.0
21.5
2010
16.4
7.8
8.6
5.1
5.1
21.5
2011
16.2
7.6
8.6
5.2
5.2
21.4
* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing,
fruit and vegetable processing, starch-based ethanol production, and petroleum refining
industries.
Note: Totals may not sum due to independent rounding.
Table 8-8: ChU and NzO Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
CH4
Domestic
Industrial*
N2O
Domestic
1990
758
421
338 ;.
11
11
2005
785
396 J
389
15
15
2007
791
1 385
405
16
16
2008
791
383
409
16
16
2009
786
380
406
16
16
2010 2011
779 770
370 360
409 409
16 17
16 17
* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit
and vegetable processing, starch-based ethanol production, and petroleum refining industries.
8-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Note: Totals may not sum due to independent rounding.
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 or that are designed to have periods of anaerobic activity (e.g.,
constructed wetlands), anaerobic systems (anaerobic lagoons and facultative lagoons), and from anaerobic digesters
when the captured biogas is not completely combusted. CH4 emissions from septic systems were estimated by
multiplying the United States population by the percent of wastewater treated in septic systems (20 percent), an
emission factor (10.7 g CHVcapita/day) and converting that to Gg/year. Methane emissions from POTWs were
estimated by multiplying the total BOD5 produced in the United States by the percent of wastewater treated centrally
(80 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 with all aerobic systems assumed to be well-managed. Methane 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 CH4/m3
CH4), and the destruction efficiency associated with burning the biogas in an energy/thermal device (0.99). The
methodological equations are:
Emissions from Septic Systems = A
= USpop x (% onsite) x (EFSEpTic) x 1/10A9 x Days
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
= [(POTW_flow_AD)
Emissions from Anaerobic Digesters = D
(digester gas)/ (per capita flow)] x conversion to m3 x (FRAC_CH4)
ofCH4) x(l-DE)x l/lOA9
Total CH4 Emissions (Gg) = A + B + C + D
(365.25) x (density
where,
USpop
% onsite
% collected
% 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
= U.S. population
= Flow to septic systems / total flow
= Flow to POTWs / total flow
= 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
Waste 8-17
-------
= Methane emission factor (10.7 g CH4/capita/day) - septic systems
Days = days per year (365.25)
Total BOD5 produced = kg BOD/capita/day x U.S. population x 365.25 days/yr
Bo = Maximum CH4-producing capacity for domestic wastewater (0.60 kg
CHVkgBOD)
1/10A6 = Conversion factor, kg to Gg
MCF-aerobic_not_well_man. = CH4 correction factor for aerobic systems that are not well managed
(0.3)
MCF-anaerobic = CH4 correction factor for anaerobic systems (0.8)
DE = CH4 destruction efficiency from flaring or burning in engine (0.99 for
enclosed flares)
POTW_flow_AD = Wastewater influent flow to POTWs that have anaerobic digesters (gal)
digester gas = Cubic feet of digester gas produced per person per day (1.0
ft3/person/day) (Metcalf and Eddy 2003)
per capita flow = Wastewater flow to POTW per person per day (100 gal/person/day)
conversion to m3 = Conversion factor, ft3 to m3 (0.0283)
FRAC_CH4 = Proportion CH4 in biogas (0.65)
density of CH4 = 662 (g CH4/m3 CH4)
1/10A9 = Conversion factor, g to Gg
U.S. population data were taken from the U.S. Census Bureau International Database (U.S. Census 2012) and
include the populations of the United States, American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and
the Virgin Islands. Table 8-9 presents U.S. population and total BOD5 produced for 1990 through 2011, while Table
8-10 presents domestic wastewater CH4 emissions for both septic and centralized systems in 2011. 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, 2005, 2007, 2009, 2011 American Housing Surveys conducted by the U.S.
Census Bureau (U.S. Census 2011), with data for intervening years obtained by linear interpolation. The percent of
wastewater flow to aerobic and anaerobic systems, the percent of aerobic and anaerobic systems that do and do not
employ primary treatment, 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 2004). Data for
intervening years were obtained by linear interpolation and the years 2004 through 2011 were forecasted from the
rest of the time series. The BOD5 production rate (0.09 kg/capita/day) and the percent BOD5 removed by primary
treatment for domestic wastewater were obtained from Metcalf and Eddy (2003). The CH4 emission factor (0.6 kg
CHVkg BOD5) and the MCF used for centralized treatment systems were taken from IPCC (2006), while the CH4
emission factor (10.7 g CHVcapita/day) used for septic systems were taken from Leverenz et al. (2010). The CH4
destruction efficiency for methane recovered from sludge digestion operations, 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 the Landfill Methane Outreach Program (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 (2003). 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).
Table 8-9: U.S. Population (Millions) and Domestic Wastewater BODs Produced (Gg)
Year Population BODs
1990 253 8,333
2005 300 9,853
2007
2008
2009
2010
2011
305
308
311
314
316
10,039
10,132
10,220
10,303
10,377
8-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Source: U.S. Census Bureau (2012);
Metcalffc Eddy 2003.
Table 8-10: Domestic Wastewater Cm Emissions from Septic and Centralized Systems
(2011)
CH4 emissions (Tg CCh Eq.) % of Domestic Wastewater CH4
Septic Systems
Centralized Systems
5.0
2.5
66.4%
33.6%
Total
7.6
100%
Note: Totals may not sum due to independent rounding.
Industrial Wastewater CH4 Emission Estimates
Methane emission estimates from industrial wastewater were developed according to the methodology described in
IPCC (2006). Industry categories that are likely to produce significant CH4 emissions from wastewater treatment
were identified. High volumes of wastewater generated and a high organic wastewater load were the main criteria.
The top five industries that meet these criteria are pulp and paper manufacturing; meat and poultry processing;
vegetables, fruits, and juices processing; starch-based ethanol production; and petroleum refining. Wastewater
treatment emissions for these sectors for 2011 are displayed in Table 8-11 below. Table 8-12 contains production
data for these industries.
Table 8-11: Industrial Wastewater Cm Emissions by Sector (2011)
CH4 emissions (Tg CCh Eq.) % of Industrial Wastewater CH4
Pulp & Paper
Meat & Poultry
Petroleum Refineries
Fruit & Vegetables
Ethanol Refineries
4.1
3.7
0.6
0.1
0.1
48%
43%
7%
1%
1%
Total
8.6
100%
Note: Totals may not sum due to independent rounding.
Table 8-12: U.S. Pulp and Paper, Meat, Poultry/ Vegetables, Fruits and Juices, Ethanol, and
Petroleum Refining Production (Tg)
Year
1990
2005
2007
2008
2009
2010
2011
Meat Poultry Vegetables,
Pulp and (Live Weight (Live Weight Fruits and
Paper3 Killed) Killed) Juices
128.9
131.4
135.9
134.5
137.0
137.0
137.0
27.3
31.4
33.4
34.4
33.8
33.7
33.8
14.6
25.1
26.0
26.6
25.2
25.9
26.2
38.7
42.9
44.7
45.1
46.5
43.2
42.9
Ethanol
2.7
11.7
19.4
26.9
31.7
39.5
41.5
Petroleum
Refining
702.4
818.6
827.6
836.8
822.4
848.6
858.8
aPulp and paper production is the sum of woodpulp production plus paper and paperboard production.
Methane 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 maximum CH4 producing potential of industrial wastewater (B0). Ratios of BOD:COD in
Waste 8-19
-------
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).
For each industry, the percent of plants in the industry that treat wastewater on site, the percent of plants that have a
primary treatment step prior to biological treatment, and the percent of plants that treat wastewater anaerobically
were defined. The percent of wastewater treated anaerobically onsite (TA) was estimated for both primary treatment
(%TAP) and secondary treatment (%TAS). For plants that have primary treatment in place, an estimate of COD that
is removed prior to wastewater treatment in the anaerobic treatment units was incorporated.
The methodological equations are:
CH4 (industrial wastewater) = [P x W
COD x %TAP x Bo x MCF] + [P x W x COD x %TAS x B0 x MCF]
where,
%TAP = [%Plants0 x %WWa,p x %CODP]
%TAs = [%Plantsa x %WWa,s x %CODS] + [%Plantst x %WWa,t x %CODS
CH4 (industrial wastewater) = Total CH4 emissions from industrial wastewater (kg/year)
P
W
COD
%TAP
%Plants0
%WWap
%CODP
%Plantsa
%Plantst
%WWa,s
%wwat
%CODS
Bo
MCF
= 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 in primary treatment
= Percent of wastewater treated anaerobically on site in secondary treatment
= Percent of plants with onsite treatment
= Percent of wastewater treated anaerobically in primary treatment
= Percent of COD entering primary treatment
= Percent of plants with anaerobic secondary treatment
= Percent of plants with other secondary treatment
= Percent of wastewater treated anaerobically in anaerobic secondary treatment
= percent of wastewater treated anaerobically in other secondary treatment
= percent of COD entering secondary treatment
= Maximum CH4 producing potential of industrial wastewater (default value of
0.25 kg CHVkg COD)
= CH4 correction factor, indicating the extent to which the organic content
(measured as COD) degrades anaerobically
As described below, the values presented in Table 8-13 were used in the emission calculations and are described in
detail in Aguiar and Bartram (2008).
Table 8-13: Variables Used to Calculate Percent Wastewater Treated Anaerobically by
Industry (%)
Variable
%TAP
%TAS
%Plants0
%Plantsa
%Plantst
%WWa,p
%WWa,s
%WWa,t
%CODP
%CODS
Pulp
and
Paper
0
10.5
60
25
35
0
100
0
100
42
Meat
Processing
0
33
100
33
67
0
100
0
100
100
Poultry
Processing
0
25
100
25
75
0
100
0
100
100
Industry
Fruit/
Vegetable
Processing
0
4.2
11
5.5
5.5
0
100
0
100
77
Ethanol
Production
- Wet Mill
0
33.3
100
33.3
66.7
0
100
0
100
100
Ethanol
Production
- Dry Mill
0
75
100
75
25
0
100
0
100
100
Petroleum
Refining
0
100
100
100
0
0
100
0
100
100
Source: Aguiar and Bartram (2008) Planned Revisions of the Industrial Wastewater Inventory Emission Estimates for the
1990-2007 Inventory. August 10,2008.
8-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Pulp and Paper. Wastewater treatment for the pulp and paper industry typically includes neutralization, screening,
sedimentation, and flotation/hydrocycloning to remove solids (World Bank 1999, Nemerow and Dasgupta 1991).
Secondary treatment (storage, settling, and biological treatment) mainly consists of lagooning. In determining the
percent that degrades anaerobically, both primary and secondary treatment were considered. In the United States,
primary treatment is focused on solids removal, equalization, neutralization, and color reduction (EPA 1993). The
vast majority of pulp and paper mills with on-site treatment systems use mechanical clarifiers to remove suspended
solids from the wastewater. About 10 percent of pulp and paper mills with treatment systems use settling ponds for
primary treatment and these are more likely to be located at mills that do not perform secondary treatment (EPA
1993). However, because the vast majority of primary treatment operations at U.S. pulp and paper mills use
mechanical clarifiers, and less than 10 percent of pulp and paper wastewater is managed in primary settling ponds
that are not expected to have anaerobic conditions, negligible emissions are assumed to occur during primary
treatment.
Approximately 42 percent of the BOD passes on to secondary treatment, which consists of activated sludge, aerated
stabilization basins, or non-aerated stabilization basins. No anaerobic activity is assumed to occur in activated
sludge systems or aerated stabilization basins (note: although IPCC recognizes that some CH4 can be emitted from
anaerobic pockets, they recommend an MCF of zero). However, about 25 percent of the wastewater treatment
systems used in the United States are non-aerated stabilization basins. These basins are typically 10 to 25 feet deep.
These systems are classified as anaerobic deep lagoons (MCF = 0.8).
A time series of CH4 emissions for 1990 through 2001 was developed based on production figures reported in the
Lockwood-Post Directory (Lockwood-Post 2002). Published data from the American Forest and Paper Association,
data published by Paper Loop, and other published statistics were used to estimate production for 2002 through 2011
(Pulp and Paper 2005, 2006, and monthly reports from 2003 through 2008; Paper 360° 2007). The overall
wastewater outflow was estimated to be 85 m3/metric ton, and the average BOD concentrations in raw wastewater
was estimated to be 0.4 gram BOD/liter (EPA 1997b, EPA 1993, World Bank 1999). The COD:BOD ratio used to
convert the organic loading to COD for pulp and paper facilities was 2 (EPA 1997a).
Meat and Poultry Processing. The meat and poultry processing industry makes extensive use of anaerobic lagoons
in sequence with screening, fat traps and dissolved air flotation when treating wastewater on site. About 33 percent
of meat processing operations (EPA 2002) and 25 percent of poultry processing operations (U.S. Poultry 2006)
perform on-site treatment in anaerobic lagoons. The IPCC default B0 of 0.25 kg CHVkg 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 (USDA 2012). Data collected by
EPA's Office of Water provided estimates for wastewater flows into anaerobic lagoons: 5.3 and 12.5 m3/metric ton
for meat and poultry production (live weight killed), respectively (EPA 2002). The loadings are 2.8 and 1.5 g
BOD/liter for meat and poultry, respectively. The COD:BOD ratio used to convert the organic loading to COD for
both meat and poultry facilities was 3 (EPA 1997a).
Vegetables, Fruits, and Juices Processing. Treatment of wastewater from fruits, vegetables, and juices processing
includes screening, coagulation/settling, and biological treatment (lagooning). The flows are frequently seasonal,
and robust treatment systems are preferred for on-site treatment. Effluent is suitable for discharge to the sewer.
This industry is likely to use lagoons intended for aerobic operation, but the large seasonal loadings may develop
limited anaerobic zones. In addition, some anaerobic lagoons may also be used (Nemerow and Dasgupta 1991).
Consequently, 4.2 percent of these wastewater organics are assumed to degrade anaerobically. The IPCC default B0
of 0.25 kg 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 USDA National Agricultural Statistics Service (USDA 2012) provided
production data for potatoes, other vegetables, citrus fruit, non-citrus fruit, and grapes processed for wine. Outflow
and BOD data, presented in Table 8-14, were obtained from EPA (1974) for potato, citrus fruit, and apple
processing, and from EPA (1975) for all other sectors. The COD:BOD ratio used to convert the organic loading to
COD for all fruit, vegetable, and juice facilities was 1.5 (EPA 1997a).
Table 8-14: Wastewater Flow (m3/ton) and BOD Production (g/L) for U.S. Vegetables, Fruits,
and Juices Production
Commodity Wastewater Outflow (mVton) BOD (g/L)
Waste 8^2?
-------
Vegetables
Potatoes 10.27 1.765
Other Vegetables 8.69 0.794
Fruit
Apples 3.66 1.371
Citrus 10.11 0.317
Non-citrus 12.42 1.204
Grapes (for wine) 2.78 1.831
Ethanol Production. Ethanol, or ethyl alcohol, is produced primarily for use as a fuel component, but is also used in
industrial applications and in the manufacture of beverage alcohol. Ethanol can be produced from the fermentation
of sugar-based feedstocks (e.g., molasses and beets), starch- or grain-based feedstocks (e.g., corn, sorghum, and
beverage waste), and cellulosic biomass feedstocks (e.g., agricultural wastes, wood, and bagasse). Ethanol can also
be produced synthetically from ethylene or hydrogen and carbon monoxide. However, synthetic ethanol comprises
only about 2 percent of ethanol production, and 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 through 2012, 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
gallons per gallon ethanol produced (for dry milling) to 10 gallons per gallon ethanol produced (for wet milling)
(Ruocco 2006a,b; Merrick 1998; Donovan 1996; 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 CH4 is recovered through the use of biomethanators (ERG
2006). Methane emissions were then estimated as follows:
Methane = [Production x Flow x COD x 3.785 x ([%Plants0 x %WWa,P x %CODP] + [%Plantsa x %WWa,s x %CODS] +
[%Plantst x %WWa,t x %CODS]) x B0 x MCF x % Not Recovered] + [Production x Flow x 3.785 x COD x ([%Plants0 x
%WWa,P x %CODP] + [%PlantSa x %WWa,s x %CODS] + [%Plantst x %WWa,t x %CODJ) x B0 x MCF x (% Recovered) x (1-
DE)] x 1/1QA9
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
%Plants0 = percent of plants with onsite treatment (100%)
%WWa,p = percent of wastewater treated anaerobically in primary treatment (0%)
%CODP = percent of COD entering primary treatment (100%)
%Plantsa = percent of plants with anaerobic secondary treatment (33.3% wet, 75% dry)
%Plantst = percent of plants with other secondary treatment (66.7% wet, 25% dry)
%WWa,s = percent of wastewater treated anaerobically in anaerobic secondary treatment (100%)
8-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
%WWa,t = percent of wastewater treated anaerobically in other secondary treatment (0%)
%CODS = percent of COD entering secondary treatment (100%)
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 2011 was developed based on production data from the Renewable
Fuels Association (RFA 2012).
Petroleum Refining. Petroleum refining wastewater treatment operations produce CH4 emissions from anaerobic
wastewater treatment. The wastewater inventory section includes CH4 emissions from petroleum refining
wastewater treated on site under intended or unintended anaerobic conditions. Most facilities use aerated biological
systems, such as trickling filters or rotating biological contactors; these systems can also exhibit anaerobic
conditions that can result in the production of CH4. Oil/water separators are used as a primary treatment method;
however, it is unlikely that any COD is removed in this step.
Available information from the industry was compiled. The wastewater generation rate, from CARB (2007) and
Timm (1985), was determined to be 35 gallons per barrel of finished product. An average COD value in the
wastewater was estimated at 0.45 kg/m3 (Benyahia et al. 2006).
The equation used to calculate CH4 generation at petroleum refining wastewater treatment systems is presented
below:
Methane = Flow x COD x B0 x MCF
where,
Flow = Annual flow treated through anaerobic treatment system (m3/year)
COD = COD loading in wastewater entering anaerobic treatment system (kg/m3)
Bo = maximum methane producing potential of industrial wastewater (default value of 0.25
kg CH4 /kg COD)
MCF = methane conversion factor (0.3)
A time series of CH4 emissions for 1990 through 2011 was developed based on production data from the Energy
Information Association (EIA 2012).
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/commercial 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.
• The IPCC methodology uses annual, per capita protein consumption (kg protein/[person-year]). For this
inventory, the amount of protein available to be consumed is estimated based on per capita annual food
availability data and its protein content, and then adjusts that data using a factor to account for the fraction of
protein actually consumed.
• Small amounts of gaseous nitrogen oxides are formed as byproducts in the conversion of nitrate to N gas in
anoxic biological treatment systems. Approximately 7 g N2O is generated per capita per year if wastewater
treatment includes intentional nitrification and denitrification (Scheehle and Doom 2001). Analysis of the 2004
CWNS shows that plants with denitrification as one of their unit operations serve a population of 2.4 million
people. Based on an emission factor of 7 g per capita per year, approximately 21.2 metric tons of additional N2O
may have been emitted via denitrification in 2004. Similar analyses were completed for each year in the
Waste 8-23
-------
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 g N2O per capita per
year.
N2O emissions from domestic wastewater were estimated using the following methodology:
N2OpLANT + N2OEFFLUENT
= N2ONIT/DENIT + N2OwOUT MT/DENIT
N2ONIT/DENIT= [(USpQPND) x EF2 X FlND-COM] x 1/10A9
N2OwOUTNIT/DENIT = {[(USpOP X WWTP) - USpOPNo] x FlND-COM X EFl } X 1/1QA9
N2OEFFLUENT = {[(((USpop x WWTP) - (0.9 x USpopND)) x Protein x FM>R x FNON-CON x FIND-COM) - NSLUDGE] x EF3 x
44/28} x 1/10A6
where,
N2OTOTAL = Annual emissions of N2O (Gg)
N2OpLANi = N2O emissions from centralized wastewater treatment plants (Gg)
N2ONiT/DENiT = N2O emissions from centralized wastewater treatment plants with
nitrification/denitrification (Gg)
N2Owour NIT/DENIT = N2O emissions from centralized wastewater treatment plants without
nitrification/denitrification (Gg)
N2OEFFLUENT = N2O emissions from wastewater effluent discharged to aquatic environments (Gg)
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) - plant with no intentional denitrification
EF2 = Emission factor (7 g N2O/person-year) - plant with intentional denitrification
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) - from effluent
0.9 = Amount of nitrogen removed by denitrification systems (EPA 2008)
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 2012) 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, 2005, 2007, 2009, and 2011 American Housing Survey (U.S.
Census 201 1). Data for intervening years were obtained by linear interpolation. The emission factor (EFi) used to
estimate emissions from wastewater treatment for plants without intentional denitrification was taken from IPCC
(2006), while the emission factor (EF2) used to estimate emissions from wastewater treatment for plants with
intentional denitrification was taken from Scheehle and Doom (2001). Data on annual per capita protein intake were
provided by U.S. Department of Agriculture Economic Research Service (USD A 2009). Protein consumption data
for 2005 through 201 1 were extrapolated from data for 1990 through 2004. 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). The factor for non-consumed protein and the factor for industrial and commercial co-
discharged protein were 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 through 201 1 were forecasted from the rest of the time series. An estimate for the N removed as sludge
(NSLUDGE) was obtained by determining the amount of sludge disposed by incineration, by land application
(agriculture or other), through surface disposal, in landfills, or through ocean dumping. In 201 1, 277 Gg N was
removed with sludge. Table 8-15 presents the data for U.S. population, population served by biological
8-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
denitrification, population served by wastewater treatment plants, available protein, protein consumed, and nitrogen
removed with sludge.
Table 8-15: U.S. Population (Millions), Population Served by Biological Denitrification
(Millions), Fraction of Population Served by Wastewater Treatment (%), Available Protein
(kg/person-year), Protein Consumed (kg/person-year), and Nitrogen Removed with Sludge
(Gg-N/year)
Year Population Populations WWTP Population Available Protein Protein Consumed N Removed
1990
2005
253
300
2.0
2.4
75.6
78.8
38.7
41.7
29.6
32.0
215.6
260.3
2007
2008
2009
2010
2011
305
308
311
313
316
2.3
2.2
2.2
2.1
2.1
79.4
79.4
79.3
80.0
80.6
42.1
42.2
42.4
42.6
42.8
32.3
32.4
32.5
32.7
32.8
265.9
268.7
271.4
274.2
277.0
Table 8-16: Fate of Sludge Removed by Domestic Wastewater Treatment
Disposal Practices
Distribution (1000 kg N)
Incineration
Land Application
Ag
Other
Surface Disposal
Landfill
Ocean Dumping
Other
1990
35,027.35
77,378.34
52,198.15
25,180.19
20,325.19
72,962.21
8,294.65
1,645.76
1995
37,806.16
97,230.98
69,001.16
28,229.81
16,142.13
75,945.15
6,353.98
2000
38,399.04
113,311.73
83, 522. 63
29,789.11
10,243.93
74,158.54
11,312.32
2005
38,595.85
129,196.74
98,080.96
31,115.78
4,586.01
71,407.98
16,478.76
2010
38,301.05
144,113.04
112,014.99
32,098.05
2,558.71
67,609.40
21,661.26
2011
38,215.54
147,054.99
114,778.24
32,276.75
2,275.43
66,790.83
22,702.30
The overall uncertainty associated with both the 2011 CH4 and N2O emission 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, ethanol production, and petroleum refining. Uncertainty associated with
the parameters used to estimate N2O emissions include that of sewage sludge disposal, total U.S. population,
average protein consumed per person, fraction of N in protein, non-consumption nitrogen factor, emission factors
per capita and per mass of sewage-N, and for the percentage of total population using centralized wastewater
treatment plants.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 8-17. Methane emissions from
wastewater treatment were estimated to be between 11.5 and 20.7 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 29 percent below to
28 percent above the 2011 emissions estimate of 16.2 Tg CO2 Eq. N2O emissions from wastewater treatment were
estimated to be between 1.2 and 10.2 Tg CO2 Eq., which indicates a range of approximately 77 percent below to 97
percent above the 2011 emissions estimate of 5.2 Tg CO2 Eq.
Table 8-17: Tier 2 Quantitative Uncertainty Estimates for ChU Emissions from Wastewater
Treatment (Tg COz Eq. and Percent)
2011 Emission Uncertainty Range Relative to Emission
Source Gas Estimate Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Waste 8-25
-------
Wastewater Treatment
Domestic
Industrial
Wastewater Treatment
CH4
CH4
CH4
N20
16.2
7.6
8.6
5.2
Lower
Bound
11.5
5.6
4.6
1.2
Upper
Bound
20.7
9.6
12.7
10.2
Lower
Bound
-29%
-26%
-47%
-77%
Upper
Bound
+28%
+27%
+48%
+97%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent
confidence interval.
Methodological recalculations were applied to the entire time-series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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.
Production data were updated to reflect updated USDA NASS datasets. This resulted in minor changes to the
emission estimates from the previous inventory. In addition, population updates from the U.S. Census resulted in
minor changes to domestic wastewater treatment emission estimates from 2000 through 2010.
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 question of whether activity data for wastewater treatment
systems are sufficient across the time series to further 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,
continues to be explored. The CWNS data for 2008 were evaluated for incorporation into the inventory, but due to
significant changes in format, this dataset is not sufficiently detailed for inventory calculations. However, additional
information and other data continue to be evaluated to update future years of the inventory.
For industrial wastewater emissions, data recently collected by EPA's Office of Air for pulp and paper mills and
petroleum refineries is being evaluated to determine if sufficient information is available to update the estimates of
wastewater generated per unit of production and the percent of industry wastewater treated anaerobically in these
industries (%TA). Initial evaluations of EPA's Office of Air data for pulp and paper manufacturing indicate there is
sufficient information to update emission estimates in the next inventory year. Data collected in 2012 under the
EPA's GHGRP will also be investigated for updating this variable. In examining data from EPA's GHGPJ3 for use
in improving the emission estimates for the industrial wastewater category, particular attention will be made to
8-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
ensure time series consistency, as the facility-level reporting data from EPA's GHGRP are not available for all
inventory years as reported in this inventory. In implementing improvements and integration of data from EPA's
GHGRP, the latest guidance from the IPCC on the use of facility-level data in national inventories will be relied
upon.255 For all industries, EPA will continue to review new research on industrial wastewater characteristics,
utilization of treatment systems, and associated greenhouse gas emissions as it becomes available. Before the
incorporation of any new data, EPA will ensure it is representative of industry conditions.
Currently, it is assumed that all aerobic wastewater treatment 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.
With respect to estimating N2O emissions, the default emission factors for indirect N2O from wastewater effluent
and direct N2O from centralized wastewater treatment facilities have a high uncertainty. Research is being
conducted by WERF to measure N2O emissions from municipal treatment systems. In addition, a literature review
has been conducted focused on N2O emissions from wastewater treatment to determine the state of such research
and identify data to develop a country-specific N2O emission factor or alternate emission factor or method. Such
data will continue to be reviewed as they are available to determine if a country-specific N2O emission factor can or
should be developed, or if alternate emission factors should be used.
Previously, new measurement data from WERF were used to develop U.S.-specific emission factors for CH4
emissions from septic systems and incorporated it into the inventory emissions calculation. Due to the high
uncertainty of the measurements forN2O from septic systems, estimates of N2O emissions were not included.
Appropriate emission factors for septic system N2O emissions will continue to be investigated as the data collected
by WERF indicate that septic soil systems are a source of N2O emissions.
In addition, the estimate of N entering municipal treatment systems is under review. The factor that accounts for
non-sewage N in wastewater (bath, laundry, kitchen, industrial components) also has a high uncertainty. Obtaining
data on the changes in average influent N 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. The dataset previously provided by the National Association of Clean
Water Agencies (NACWA) was reviewed to determine if it was representative of the larger population of
centralized treatment plants for potential inclusion into the inventory. However, this limited dataset was not
representative of the number of systems by state or the service populations served in the United States, and therefore
could not be incorporated into the inventory methodology. Additional data sources will continue to be researched
with the goal of improving the uncertainty of the estimate of N entering municipal treatment systems.
The value used for N content of sludge continues to be investigated. This value is driving the N2O emissions for
wastewater treatment and is static over the time series. To date, new data has not been identified that would be able
to establish a time series for this value. The amount of sludge produced and sludge disposal practices will also be
investigated. In addition, based on UNFCCC review comments, improving the transparency of the fate of sludge
produced in wastewater treatment will also be investigated.
A review of other industrial wastewater treatment sources for those industries believed to discharge significant loads
of BOD and COD has been ongoing. Food processing industries have the highest potential for CH4 generation due
to the waste characteristics generated, and the greater likelihood to treat the wastes anaerobically. However, in all
cases there is dated information available on U.S. treatment operations for these industries. Previously, organic
chemicals, the seafood processing industry and coffee processing were investigated to estimate their potential to
generate CH4. Due to the insignificant amount of CH4 estimated to be emitted and the lack of reliable, up-to-date
data, these industries were not selected for inclusion in the industry. Preliminary analyses of the beer and malt and
dairy products industries has been performed. These industries will continue to be investigated for incorporation.
Other industries will be reviewed as necessary for inclusion in future years of the inventory using EPA's Permit
Compliance System and Toxics Release inventory.
In addition, available datasets will be reviewed to provide further information on the fates of sludge removed by
domestic wastewater treatment in the next inventory report.
255 See: http://www.ipcc-nggip.iges.or.Jp/meeting/pdfiles/l008_Model_and_Facility_Level_Data_Report.pdf.
Waste 8^27
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As stated earlier in this chapter, CO2, N2O, and CH4 emissions from the incineration of waste are accounted for in
the Energy sector rather than in the Waste sector because almost all incineration of municipal solid waste (MSW) in
the United States occurs at waste-to-energy facilities where useful energy is recovered. Similarly, the Energy sector
also includes an estimate of emissions from burning waste tires and hazardous industrial waste, because virtually all
of the combustion occurs in industrial and utility boilers that recover energy. The incineration of waste in the United
States in 2011 resulted in 12.4 Tg CO2 Eq. emissions, nearly half of which is attributable to the combustion of
plastics. For more details on emissions from the incineration of waste, see Section 3.3 of the Energy chapter.
Additional sources of emissions from waste incineration include non-hazardous industrial waste incineration and
medical waste incineration. As described in Annex 5 of this report, data are not readily available for these sources
and emissions estimates are not provided. Further investigations will be made, including assessing the applicability
of state-level data collected for EPA's National Emission Inventory (NEI)256.
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. Approximately 400 composting facilities
operate in the United States (WBJ 2010).
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 percent of the initial C content in the material
(IPCC 2006). Depending on the N content of the feedstock and how well the compost pile is managed, nitrous
oxide (N2O) emissions can be produced. The formation of N2O is complicated, but is mainly associated with
anaerobic conditions. Emissions vary and range from less than 0.5 percent to 5 percent of the initial content of the
material (IPCC 2006).
From 1990 to 2011, the amount of material composted in the United States has increased from 3,810 Gg to 18,449
Gg, an increase of approximately 3 84 percent. From 2000 to 2011, the amount of material composted in the United
States has increased by approximately 24 percent. Emissions of CH4 and N2O from composting have increased by
the same percentage. In 2011, CH4 emissions from composting (see Table 8-18 and Table 8-19) were 1.5 Tg CO2
Eq. (74 Gg), and N2O emissions from composting were 1.7 Tg CO2 Eq. (5.5 Gg). The wastes composted primarily
include 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 composted
waste quantities reported here do not include backyard composting. The growth in composting since the 1990s is
attributable to primarily two factors: (1) steady growth in population and residential housing, and (2) the enactment
of legislation by state and local governments 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. Currently, 23 states and the District of Columbia, representing about 50 percent of the
256 See < http://www.epa.gov/ttn/chief/eiinformation.html>
8-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
nation's population, have enacted such legislation (EPA 2010). The total amount of waste composted has decreased
slightly since 2008, by approximately 8 percent.
Table 8-18: Cm and NzO Emissions from Composting (Tg COz Eq.)
Activity
CH4
N2O
Total
1990
0.3
0.4
0.7
2005 ,
1.6 A
1.7 /
3.3 ,-*
2007
1.7
1.8
3.5
2008
1.7
1.9
3.5
2009
1.6
1.8
3.3
2010
1.5
1.7
3.2
2011
1.5
1.7
3.3
Table 8-19: Cm and NzO Emissions from Composting (Gg)
Activity
CH4
N20
1990
15
1
2005
75 •*
6
2007
79
6
2008
80
6
2009
75
6
2010
73
5
2011
74
6
Methane 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 8-18 and Table 8-19 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):
El = MxEFt
where,
Ei = CH4 or N2O emissions from composting, Gg CH4 or N2O,
M = mass of organic waste composted in Gg,
EFi = emission factor for composting, 4 g CHVkg of waste treated (wet basis) and 0.3 g
N2O/kg of waste treated (wet basis) (IPCC 2006), and
i = designates either CH4 or N2O.
Estimates of the quantity of waste composted (M) are presented in Table 8-20. Estimates of the quantity composted
for 1990 and 1995 were taken from the Characterization of Municipal Solid Waste in the United States: 1996
Update (Franklin Associates 1997); estimates of the quantity composted for 2000, 2005, 2006, 2007, 2008, and 2009
were taken from EPA's Municipal Solid Waste In The United States: 2009 Facts and Figures (EPA 2010);
estimates of the quantity composted for 2010 were taken from EPA's Municipal Solid Waste In The United States:
2010 Facts and Figures (EPA 2011); estimates of the quantity composted for 2011 were calculated using the 2010
quantity composted and a ratio of the U.S. population in 2010 and 2011 (U.S. Census Bureau 2012). The estimated
quantity of waste composted in 2010 was revised based on updated information (EPA 2011).
Table 8-20: U.S. Waste Composted (Gg)
Activity 1990 2005 1 2007 2008 2009 2010 2011
Waste 4
Composted 3,810 18,643 / 19,695 20,049 18,824 18,298 18,449
Source: EPA 2008 and EPA 2011.
Waste 8-29
-------
Little is known about the site-specific operating conditions at the composting facilities in the United States. The
generation of CH4 and N2O emissions is highly dependent on the characteristics of the feedstock material (e.g.,
moisture content, C to N ratio, size), on the climate, and on the operating and maintenance practices (e.g., use of a
shredder/grinder to maintain consistency in size of the feedstock material, frequency of pile rotation, addition of
moisture, application of finished compost on the pile). The estimated uncertainty from the 2006 IPCC Guidelines is
±50 percent for the Tier 1 methodology. Emissions from composting in 2011 were estimated to be between 1.6 and
4.9 Tg CO2 Eq., which indicates a range of 50 percent below to 50 percent above the actual 2011 emission estimate
of 3.3 Tg CO2 Eq. (see Table 8-21).
Table 8-21: Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg
COz Eq. and Percent)
Source
Gas
2011 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Composting
CH4, N20
3.3
1.6 4.9 -50% +50%
Methodological recalculations were applied to the entire time series to ensure time-series consistency from 1990
through 2011. Details on the emission trends through time are described in more detail in the Methodology section,
above.
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 the amount of waste composted annually was correct according to the latest
EPA Municipal Solid Waste In The United States: Facts and Figures report.
The estimated amount of waste composted in 2010 was updated based on new data contained in EPA's Municipal
Solid Waste In The United States: 2010 Facts and Figures (EPA 2011). The amounts of CEU andNaO emissions
estimates presented in Table 8-18and Table 8-19 were revised accordingly.
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. Further cooperation with estimating emissions in
cooperation with the LULUCF Other section will be made.
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 2011 are provided in Table 8-22.
8-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Table 8-22: Emissions of NOX, CO, and NMVOC from Waste (Gg)
Gas/Source
NOx
Landfills
Wastewater Treatment
Miscellaneous*
CO
Landfills
Wastewater Treatment
Miscellaneous3
NMVOCs
Wastewater Treatment
Miscellaneous8
Landfills
1990
+
+
+ /
+ /
1
1 ..
+ /
+
673 .
57 /
557
58 /
: 2005
2
2
+
+
7
6
+
+
114
49
43
22
, 2007
< 2
2
+
+
7
6
+
+
111
48
42
21
2008
2
2
+
+
7
6
+
+
109
47
41
21
2009
2
2
+
+
7
6
+
+
76
33
29
14
2010
2
2
+
+
7
6
+
+
76
33
29
14
2011
2
2
+
+
7
6
+
+
76
33
29
14
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.
Due to the lack of data available at the time of publication, emission estimates for 2010 and 2011 rely on 2009 data
as a proxy. Emission estimates for 2009 were obtained from preliminary data (EPA 2010, EPA 2009), and
disaggregated based on EPA (2003), which, in its final iteration, will be published on the National Emission
Inventory (NEI) Air Pollutant Emission Trends web site. Due to redevelopment of the information technology
systems for the NEI, publication of the most recent emissions for these pollutants (i.e., indirect greenhouse gases)
was not available for this report257. 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.
No quantitative estimates of uncertainty were calculated for this source category. Methodological recalculations
were applied to the entire time-series to ensure time-series consistency from 1990 through 2011.
For an overview of the activities and the schedule for developing the 2011 National Emissions Inventory, with the goal of
producing Version 1 in the summer of 2013, see < http://www.epa.gov/ttn/chief/eis/201 lnei/201 lplan.pdf>
Waste 8^
-------
-------
The United States does not report any greenhouse gas emissions under the Intergovernmental Panel on Climate
Change (IPCC) "Other" sector.
Other 9-1
-------
-------
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 both the IPCC
Good Practice Guidance (IPCC, 2000) and the 2006 IPCC Guidelines (IPCC 2006), which states, "Both
methodological changes and refinements over time are an essential part of improving inventory quality. It is good
practice to change or refine methods" when: available data have changed; the previously used method is not
consistent with the IPCC guidelines for that category; a category has become key; the previously used method is
insufficient to reflect mitigation activities in a transparent manner; the capacity for inventory preparation has
increased; new inventory methods become available; and for correction of errors."
The results of all methodological changes and historical data updates are presented in this section; detailed
descriptions of each recalculation are contained within each source's description found in this report, if applicable.
Table 10-1 summarizes the quantitative effect of these changes on U.S. greenhouse gas emissions and sinks and
Table 10-2 summarizes the quantitative effect on annual net CCh fluxes, both relative to the previously published
U.S. Inventory (i.e., the 1990 through 2010 report). These tables present the magnitude of these changes in units of
teragrams of carbon dioxide equivalent (Tg CCh Eq.).
The Recalculations Discussion section of each source's chapter presents the details of each recalculation. In general,
when methodological changes have been implemented, the entire time series (i.e., 1990 through 2010) has been
recalculated to reflect the change, per IPCC (2006). Changes in historical data are generally the result of changes in
statistical data supplied by other agencies.
The following ten emission sources and sinks, which are listed in descending order of annual change in emissions or
sequestration between 1990 and 2010, underwent some of the most significant methodological and historical data
changes. A brief summary of the recalculations and/or improvements undertaken is provided for each of the ten
sources.
• Natural Gas Systems (CH4). Information and data related to the emission estimates was received through the
Inventory preparation process, the formal public notice and comment process of the proposed oil and gas NSPS
for VOCs, and through a stakeholder workshop on the natural gas sector emissions estimates. All relevant
information provided was carefully evaluated, and updates were made to two key sources in the expert review
draft: liquids unloading, and completions with hydraulic fracturing and workovers with hydraulic fracturing
(refracturing). Additional updates were made to well counts (activity data), which impact multiple sources.
Emission estimates will continue to be refined to reflect the most robust data and information available. In
particular, data from EPA's GHGRP will be reviewed and potentially incorporated; GHGRP data will be
published for the first year of emissions data from the oil and gas sector in 2013. Overall, these changes
resulted in an average annual decrease of 41.6 Tg CC>2 Eq. (20.2 percent) in CH4 emissions from Natural Gas
Systems for the period 1990 through 2010.
• Agricultural Soil Management (N2O). Methodological recalculations in the current Inventory were associated
with the following improvements: 1) incorporation of MODIS Enhanced Vegetation Index to reduce
uncertainties in the estimation of crop production and subsequent carbon input to the soil; 2) using the National
Resources Inventory (NRI) as the basis for crop histories and land use change (USDA-NRCS 2009); 3)
addition of specific tillage practices with statistics from Conservation Technology and Information Center
(CTIC 2004); 4) extension of the N fertilizer activity data with new USDA statistics on fertilizer use through
Recalculations and Improvements 10-1
-------
2009 (USDA-ERS 2011); and 5) expansion of the number of crops simulated by D AYCENT (i.e., dry beans,
onions, peanuts, potatoes, rice, sugar beets, sunflowers, and tomatoes). These changes resulted in an increase in
emissions of approximately 16 per cent on average relative to the previous Inventory. The differences are partly
due to the broader scope of the current Inventory that includes the influence of land use change and tillage on
mineral N availability in soils, which is a key driver of nitrification and denitrification. Synthetic fertilizer rates
are also higher for crops based on the updated USDA statistics. In addition, the dataset was expanded for
evaluating the error in model structure, improving the ability to assess uncertainty in the emission estimates.
These changes resulted in an average annual increase in N2O emissions from Agricultural Soil Management of
34.8 Tg CO2 Eq. (16.4 percent) relative to the previous report.
Settlements Remaining Settlements (C Sink). The 1990 to 2010 net C flux estimates were recalculated relative
to the previous Inventory based on three changes in activity data; (1) 2010 U.S. Census data were released in
March 2012, along with updated definitions of urban area and urban cluster, resulting in revisions to the annual
urban area estimated for 1990 to 2010; (2) a revised average urban tree canopy cover (35.0 percent) was
published by Nowak and Greenfield (2012); and (3) C sequestration data was available for 28 rather than 14
cities from Nowak et al. (2013, in review). The combination of the methodological and historical data changes
resulted in an average annual net sequestration decrease of 19.5 Tg CC>2 Eq. (24.5 percent) in urban trees
compared to the previous report across the entire time-series.
Land Converted to Cropland (C Sink). Methodological recalculations in the current Inventory were associated
with the following improvements: 1) use of the D AYCENT biogeochemical model to estimate SOC stock
changes for the Tier 3 method; 2) incorporation of new activity data from the National Resources Inventory
(NRI), extending the time series through 2007 (USDA-NRCS 2009); 3) recalculation of the Tier 2 portion of the
inventory with the new NRI activity data; 4) extension of the tillage activity dataset with statistics from
Conservation Technology and Information Center (CTIC 2004); 5) including more crops in the Tier 3 method
application that had been part of the Tier 2 method in the previous Inventory (i.e., dry beans, onions, peanuts,
potatoes, rice, sugar beets, sunflowers, and tomatoes); and 6) extension of the N fertilizer activity data with new
USDA statistics on fertilizer use through 2009 (USDA-ERS 2009). Improved estimation of C dynamics
associated with the new D AYCENT model had the largest influence on the recalculation for Land Converted to
Cropland. These changes resulted in an average annual net sequestration decrease of 13.7 Tg CC>2 Eq. (443.1
percent).
Land Converted to Grassland (C Sink). Methodological recalculations in the current Inventory were associated
with the following improvements: 1) use of the D AYCENT biogeochemical model to estimate Soil organic C
(SOC) stock changes for the Tier 3 method; 2) incorporation of new activity data from the National Resources
Inventory (NRI), extending the time series through 2007 (USDA-NRCS 2009); 3) recalculation of the Tier 2
portion of the inventory with the new NRI activity data; and 4) extension of the N fertilizer activity data with
new USDA statistics on fertilizer use through 2009 (USDA-ERS 2009). Improved estimation of C dynamics
associated with the new DAYCENT model had the largest influence on the recalculation for Land Converted to
Grassland. These changes resulted in an average annual net sequestration decrease of 13.4 Tg CCh Eq. (57.6
percent).
Grassland Remaining Grassland (C Sink). Methodological recalculations in the current Inventory were
associated with the following improvements: 1) use of the DAYCENT biogeochemical model to estimate SOC
stock changes for the Tier 3 method; 2) incorporation of new activity data from the National Resources
Inventory (NRI), extending the time series through 2007 (USDA-NRCS 2009); 3) recalculation of the Tier 2
portion of the inventory with the new NRI activity data; and 4) extension of the N fertilizer activity data with
new USDA statistics on fertilizer use through 2009 (USDA-ERS 2009 Improved estimation of C dynamics
associated with the new DAYCENT model had the largest influence on the recalculation for Grassland
Remaining Grassland. These changes resulted in an average annual net sequestration decrease of 12.1 Tg CO2
Eq. (17.1 percent).
Fossil Fuel Combustion (CO2). The Energy Information Administration (EIA 2013) updated energy
consumption statistics across the time series relative to the previous Inventory. These revisions primarily
impacted the emission estimates from 2007 to 2010; however, revisions to industrial and transportation
petroleum consumption as well as industrial natural gas and coal consumption impacted emission estimates
across the time series. Overall, these changes resulted in an average annual increase of 8.8 Tg CO2 Eq. (0.2
percent) in CO2 emissions from fossil fuel combustion for the period 1990 through 2010. Additionally, for
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
domestic aviation, a Tier 3B method from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories
was implemented. The data was developed by the FAA using radar-informed data from the ETMS for 1990, and
1995 through 2011 as modeled with the AEDT258, with domestic defined as the 50 U.S. states and U.S.
Territories. These historical data changes resulted in changes to the emission estimates for the entire time-series
to the previous Inventory, which averaged to an annual decrease in emissions from commercial aviation jet fuel
combustion of 6.5 Tg CCh Eq. (10.1 percent) in CCh emissions.
• International Bunker Fuels (CO2). Changes to emission estimates are due to revisions made to historical activity
data for marine residual and distillate fuel oil consumption and a methodology change for collecting U.S. and
Foreign Carrier Aviation Jet Fuel Consumption. The 2011 data formats, developed by the FAA using radar-
informed data from the ETMS for 1990, and 2000 through 2011 as modeled with the AEDT, was used to
recalculate prior inventories. This bottom-up approach is in accordance with the Tier 3B method from the 2006
IPCC Guidelines for National Greenhouse Gas Inventories. The activity data covers the time series 1990, and
2000 through 2011 with domestic defined as the 50 states and U.S. Territories. These historical data changes
resulted in changes to the emission estimates for the entire time-series to the previous Inventory, which
averaged to an annual decrease in emissions from international bunker fuels of 6.5 Tg CO2 Eq. (5.4 percent) in
CO2 emissions.
• Forest Land Remaining Forest (C Sink). In addition to annual updates to most-recent inventories for many
states, additional changes in methods or data reduction for the current Inventory affected the national stock and
change estimates for forest ecosystems. Of these, the modification of the down dead wood estimates to
incorporate plot level sampling of down woody material (Woodall et al. 2010, Woodall et al. In Review)
resulted in the greatest impact on total forest C stocks. Nationally, estimates for C in down dead wood stocks
decreased by about 8 percent. A second change was a modification in the approach to determining the
necessary volumes as inputs to the tree biomass equations, which only affected a few of the periodic (i.e., older)
inventories. Next, we identified that the older forest inventories classified as woodlands on National Forests in
Colorado included a spatial extent substantially lower than current inventories of that classification. The older
inventories were dropped from our calculations because of the inconsistency (see annex 3.12 for specifics of
inventories in use). Finally, the current FIADB 5.1 data do not include the periodic survey for Alaska as was
included in the previous Inventory (EPA 2012). Therefore we retained the estimates based on FIADB 4.0after
making appropriate adjustments consistent with this year's Inventory (e.g., the modified down dead wood
estimates). This represents a change in method—that is, including older FIADB data—that does not affect the
estimates, because it maintains consistency between successive Inventories.
Estimates for C additions to harvested wood products pools were adjusted due to revision to data for softwood
pulpwood production (2006 to 2010), hardwood lumber production (2007 to 2010), hardwood plywood
production (2008 to 2010), and imports of particleboard and medium density fiberboard (1998 to 2010).
Revisions are contained in Howard (forthcoming). Estimates of the total C stock have been adjusted to
represent the stock at the beginning of the year rather than the end of the year to match the beginning year
estimates for forest stocks. Previously, the estimates had been for the end of the year. This reduced the total
stock level estimate for years through 2010 by 20 to 30 Tg C. These changes resulted in an average annual net
sequestration decrease of 3.4 Tg COa Eq. (1.1 percent).
• Cropland Remaining Cropland - Mineral and Organic Soil Carbon Stock Changes (C Sink). Methodological
recalculations in this year's inventory were associated with the following improvements: 1) use of the
DAYCENT biogeochemical model to estimate SOC stock changes for the Tier 3 method; 2) incorporation of
MODIS Enhanced Vegetation Index to estimate crop production and subsequent C input to the soil; 3)
incorporation of new activity data from the National Resources Inventory (NRI), extending the time series
through 2007 (USDA-NRCS 2009); 4) recalculation of the Tier 2 portion of the inventory with the new NRI
activity data; 5) extension of the tillage activity dataset with statistics from Conservation Technology and
Information Center (CTIC 2004); 6) including more crops in the Tier 3 method application that had been part of
the Tier 2 method in the previous Inventory (i.e., dry beans, onions, peanuts, potatoes, rice, sugar beets,
sunflowers, and tomatoes); and 7) extension of the N fertilizer activity data with new USD A statistics on
Additional information on the AEDT modeling process is available at:
http://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/
Recalculations and Improvements 10-3
-------
fertilizer use through 2009 (USDA-ERS 2011). The largest changes in SOC trends tended to occur after 2002,
and are attributed to the new NRI and tillage data (the previous Inventory was based on a time series of activity
data that ended in 2003). However, improved estimation of C dynamics associated with the new DAYCENT
model also had a significant effect on the recalculation for Cropland Remaining Cropland. These changes
resulted in an average annual net sequestration decrease of 2.1 Tg CCh Eq. (0.1 percent).
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg COz Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Electricity Generation
Transportation
Industrial
Residential
Commercial
U.S. Territories
Non-Energy Use of Fuels
Natural Gas Systems
Cement Production
Lime Production
Other Processes of Carbonates
Glass Production
Soda Ash Production and Consumption
Carbon Dioxide Consumption
Incineration of Waste
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production & Metallurgical Coke
Production
Ferroalloy Production
Ammonia Production
Urea Consumption for Non-Agricultural Purposes
Phosphoric Acid Production
Petrochemical Production
Silicon Carbide Production and Consumption
Lead Production
Zinc Production
Cropland Remaining Cropland
Wetlands Remaining Wetlands
Petroleum Systems
Land Use, Land-Use Change, and Forestry (Sink)"
Biomass - Woodb
International Bunker Fuelsb
Biomass - Ethanof
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 & Metallurgical Coke
Production
Ferroalloy Production
1990
8.3
10.2
+
8.0
2.2
+
+ -
+
(2.2)
0.1
NC
+
(0.2)
NC
(1.3)
NC
+
NC
NC
0.2
NC
+
+
NC
0.1
NC
NC
NC
NC
NC
NC
87.3
NC
(8.4)
NC
(28.3)
+
(0.1)
NC
NC
(28.4)
NC
1.4
NC
NC
NC
: 2005
1.7
2.2/
+
' (4.9)
7.1 /
+
+
+.•'
' (1.4)
+ .•
NC'
(0.1)
(0.4) /
NC
(1.3)
NC/
'; +
NC
NC /
0.7
NC
+ /
+
+
0.1
NC/
NC
NC
NC .
NC'
+
88.1
+ •
3.4
NC
(32.1)
+ .•'
(0.2)
0.1
NC
(31.5)
+
2.1
NC .•
NC
NC
, 2007
1 10.0
9.9
+
10.8
+
+
+
(0.9)
+
(0.2)
NC
+
(0.3)
NC
' (1-2)
NC
+
NC
NC
0.1
NC
+
+
+
0.1
NC
NC
NC
NC
NC
+
/ 179.0
(2.8)
(12.3)
NC
(37.6)
(0.1)
(0.1)
+
NC
(36.9)
+
2.2
NC
NC
NC
2008
20.6
19.1
+
26.2
(4.5)
(2.4)
(1.3)
1.1
0.9
(0.2)
NC
+
(0.4)
NC
(1.1)
NC
+
NC
NC
0.7
NC
+
+
(0.1)
0.1
NC
NC
NC
NC
NC
+
184.8
(0.4)
(19.4)
NC
(49.1)
+
(0.1)
0.2
NC
(49.2)
0.1
2.0
NC
NC
NC
2009
17.4
16.3
+
21.3
(4.0)
(2.0)
(1.2)
2.2
0.3
+
NC
(0.1)
(0.1)
NC
(1.0)
NC
+
NC
NC
0.9
NC
+
+
+
0.1
NC
NC
NC
+
NC
+
179.9
1.0
(15.9)
NC
(68.4)
+
(0.1)
0.2
NC
(70.2)
(0.1)
2.1
NC
NC
NC
2010
30.0
20.3
0.8
18.4
2.4
(5.6)
(3.6)
8.0
7.7
+
0.4
+
(0.5)
NC
(1.0)
NC
+
(0.1)
(0.3)
1.5
NC
+
+
0.1
0.1
NC
NC
+
0.3
+
+
185.9
0.2
(10.8)
(1.9)
(73.8)
+
(0.1)
(0.2)
NC
(71.8)
(0.2)
2.2
NC
NC
NC
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
Forest Land Remaining Forest Land
Landfills
Wastewater Treatment
Composting
Incineration of Waste
International Bunker Fuelsb
N20
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
Incineration of Waste
Settlements Remaining Settlements
Forest Land Remaining Forest Land
Composting
Wetlands Remaining Wetlands
International Bunker Fuels'1
HFCs
Substitution of Ozone Depleting Substances
HCFC-22 Production
Semiconductor Manufacture
PFCs
Aluminum Production
Semiconductor Manufacture
SF6
Electrical Transmission and Distribution
Semiconductor Manufacture
Magnesium Production and Processing
Net Change in Total Emissions'"
Percent Change
(1.1)
(0.3)
NC
+
+
0.1
+
NC
NC
+
28.1
+
0.1
+
0.5
(0.4)
27.9
+
NC
NC
NC
NC
+
NC
NC
(0.2)
NC
NC
NC
NC
NC
NC
NC
+
+
NC
NC
8.1
0.1%
: (2.0)
(0.3) ..
NC'
+
(0.1)
(0.2)/
+
NC
NC/
+
24.2
+
(0.1)
NC
0.5
(0.5) ..
24.4
+
+
NC/
NC'
NC
(0.1)
NC/
NC
+
NC
NCy
NC
NC
NC /
NC'
NC
(2.8)
(2.8)/
NC
NC
(9.0)
(0.1%)
. (2.1)
(0.3)
NC
+
/" (0.2)
(0.1)
+
NC
NC
+
41.1
+
0.1
NC
0.6
(0.5)
41.2
+
+
NC
NC
NC
/' (0.2)
NC
NC
(0-1)
+
NC
NC
+
0.1
NC
0.1
(3.3)
(3.3)
+
NC
1 10.4
0.1%
(2.0)
(0.3)
NC
+
(0.1)
0.5
+
NC
NC
+
32.6
+
0.2
NC
0.5
(0.5)
32.5
+
+
NC
NC
+
(0.1)
NC
NC
(0.2)
+
+
NC
+
(0.1)
NC
(0.1)
(3.6)
(3.6)
+
NC
0.4
+
(2.0)
(0.3)
NC
+
(0.1)
2.1
+
+
NC
+
34.7
+
0.2
NC
(0.5)
(0.5)
35.6
+
+
NC
NC
+
(0.1)
+
NC
(0.1)
(0.1)
+
NC
(0.1)
(1.2)
NC
(1.2)
(4.0)
(3.8)
(0.3)
+
(21.6)
(0.3%)
(2.0)
(0.3)
NC
+
(0.2)
(1.1)
+
+
NC
+
37.7
+
0.1
1.6
+
(0.6)
36.7
+
+
NC
NC
0.1
(0.1)
+
+
(0.1)
(1.7)
+
(1.7)
+
0.3
+
0.3
(4.0)
(4.1)
0.1
+
(11.5)
(0.2%)
+ Absolute value does not exceed 0.05 Tg CCh Eq. or 0.05 percent.
Parentheses indicate negative values
NC (No Change)
a Not included in emissions total.
b Excludes net CCh flux from Land Use, Land-Use Change, and Forestry, and emissions from International
Bunker Fuels.
Note: Totals may not sum due to independent rounding.
Recalculations and Improvements 10-5
-------
Table 10-2: Revisions to Annual Net COz Fluxes from Land Use, Land-Use Change, and
Forestry (Tg COz Eq.)
Component: Net COi Flux From
Land Use, Land-Use Change,
and Forestry 1990 2005
2007 2008 2009 2010
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
4.5
(4.7)
18.9
46.9 '
12.1
9.6
NC
87.3
9.9%
35.9
' (2.1)
7.6
7.9
* 14.2
24.6
NC
88.1
8.1%
„ 99.9
13.1
8.6
15.8
15.0
26.8
NC
179.0
16.2%
105.0
12.9
8.6
15.7
14.8
27.9
NC
184.8
17.0%
99.3
12.8
8.6
15.6
14.7
29.0
NC
179.9
16.9%
104.2
12.6
8.6
15.7
14.7
30.1
NC
185.9
17.3%
NC (No Change)
Note: Numbers in parentheses indicate a decrease in estimated net flux of CCh to the atmosphere, or
an increase in net sequestration.
Note: Totals may not sum due to independent rounding.
+ Absolute value does not exceed 0.05 Tg CCh Eq. or 0.05 percent
10-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2011
-------
BEA (2012 ) 2012 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and
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EIA (2012) International Energy Annual 2011. Energy Information Administration (EIA), U.S. Department of
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EPA (2010) "2009 Average annual emissions, all criteria pollutants in MS Excel." National Emissions Inventory
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